Molecular Evolution and Functional Characterization of the Visual Pigment Proteins of the Great Bowerbird (Chlamydera nuchalis) and Other Vertebrates

by

Ilke van Hazel

A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Department of Ecology and Evolutionary Biology University of Toronto

© Copyright by Ilke van Hazel 2012 Molecular Evolution and Functional Characterization of the Visual Pigment Proteins of the Great Bowerbird (Chlamydera nuchalis) and Other Vertebrates

Ilke van Hazel

Doctor of Philosophy

Department of Ecology and Evolutionary Biology University of Toronto

2012 Abstract

Visual pigments are light sensitive receptors in the eye that form the basis of sensory visual transduction. This thesis presents three studies that explore visual pigment proteins in vertebrates using a number of computational and experimental methods in an evolutionary framework. The objective is not only to identify, but also to experimentally investigate the functional consequences of genetic variation in vertebrate visual pigments. The focus is on great bowerbirds

(Chlamydera nuchalis), which are a model system in visual ecology due to their spectacular behaviour of building and decorating courtship bowers. There are 4 chapters: Chapter 1 introduces background information on visual pigments and vision in birds. Among visual pigment types, the short-wavelength-sensitive (SWS1) pigments have garnered particular interest due to the broad spectral range among vertebrates and the importance of UV signals in communication. Chapter 2 investigates the evolutionary history of SWS1 in vertebrates with a view toward its utility as a phylogenetic marker. Chapter 3 investigates SWS1 evolution and short-wavelength vision in birds, with particular focus on C. nuchalis and its SWS1. The evolution of spectral tuning mechanisms mediating UV/violet vision in passerines and parrots is elucidated in this chapter using site-directed mutagenesis, protein expression, and phylogenetic recreation of ancestral opsins. While cone opsins mediate colour vision in bright light, the rod

ii visual pigment (RH1) contained in rod photoreceptors is critical for dim light vision. Detailed characterization of RH1 function has only been conducted on a few model systems. Chapter 4 examines C. nuchalis RH1 using a number of functional assays in addition to absorbance spectra, including hydroxylamine sensitivity and the rate of retinal release. This chapter includes an investigation into the role of amino acid mutations typical of dim-light adapted vertebrates,

D83N and A292S, in regulating functional properties of bovine and avian RH1s using site- directed mutagenesis. Together these chapters describe naturally occurring mutations in visual pigments and explore the way they can influence visual perception. These represent one of the few investigations of visual pigments from a species that is not a model lab organism and form a significant contribution to the field of visual pigment biochemistry and evolution.

iii Dedication

This thesis is dedicated to

My family.

Thank you all for the love, support, encouragement and dedication.

I have often had cause to feel that my hands are cleverer than my head. That is a crude way of characterizing the dialectics of experimentation. When it is going well, it is like a quiet conversation with Nature. One asks a question and gets an answer; then one asks the next question, and gets the next answer. An experiment is a device to make Nature speak intelligibly. After that one has only to listen. ~ George Wald 1968

iv Acknowledgments

Throughout my studies I have received support and encouragement from a great number of individuals. It would not have been possible to write this thesis without the help of the kind people around me, to only some of whom it is possible to give mention here.

Above all, I would like to thank Aaron. He has given unequivocal support, help and love for which I am forever grateful. My entire family has been a foundation through all the ups and downs of graduate school. I could not have done it without them.

This thesis would not have been possible with out my principal supervisor, Belinda Chang. I would not be the academic I am today if it weren’t for her guidance. I’d also like to thank my dissertation committee of Drs. Allan Baker and David Guttman, for their advice, support and enthusiasm as I moved from an idea to a completed study. My thesis would also not be possible without the tissue samples provided by Drs. Lainy Day and John Endler. I am thankful for their generous donation.

I would like to acknowledge the financial, academic and technical support of the University of Toronto, the Department of Ecology and Evolutionary Biology, the Ramsay Wright building and associated staff, for their support and assistance since the start of my graduate studies, especially head of the department, Dr. Nick Collins. The good advice, support and friendship of Drs. Helen Rodd and Steve Tobe have also been invaluable on both an academic and a personal level, for which I am extremely grateful.

Amongst my fellow graduate students, I would especially like to thank Ekaterina Hult, Elisabeth Marchal, and Jenny Huang. Their support, help and friendship throughout the last stages of my thesis were most important. Also, I would be remiss to not acknowledge the friendship of Anna Price, Laura Timms, Jessica Ward, and Bonnie Fraser who made academic study, and especially coffee breaks, fun and friendly.

I am most grateful to Cam Weadick for listening to my questions and digressions, as well as for providing patient guidance in molecular evolution. I am glad to have shared my PhD years with such a wonderfully intelligent and funny individual. In a similar vein, I am thankful to other members of the Chang lab, old and new, for their companionship and for opsin and science

v discussions and I am especially thankful to those who helped me in the lab and reviewed my thesis chapters: James Morrow, David Yu, Shannon Refvik, Frances Hauser, Ryan Schott, Gianni Castiglione, Amir Sabouhanian, Benedict Darren, Jess Skillman, Natalie Chan, Jingjing Du, Clement Yang, Hermina Genu, Gloria Lin, Mengshu Xu, Savo Lazic, Francesco Santini, Conni Bickelmann, and Johannes Muller. Also, I extend thanks to Robert Pengelly, whose computer skills saved me many, many hours of work.

I cannot find words to express my gratitude to Carmen Lia Murall, Amie Sergas, and Drs. Anne Kohler and Tara Moriarty whose friendship and faith in me as a fellow scientist and professional imparted the necessary confidence to succeed.

Last, but by no means least, I thank my friends Monica Lavers, Meghan Whitfield, Andrea Marlowe, and Erin Eadie for their lasting friendship. I also thank the Dolls, current and former teammates- the most remarkable, supportive, and inspiring group of women anyone could ever meet. I would like to specifically mention; Kat Attack, Lucky, Iko, Santilly, Scarcasm, Dawson, Hoser, Bomber, Dolly Parts’em, Bonky, Lucid Lou, Sista, and Audrey, whose presence in my life has been particularly important.

vi Table of Contents

DEDICATION ...... IV

ACKNOWLEDGMENTS ...... V

TABLE OF CONTENTS ...... VII

LIST OF TABLES ...... XI

LIST OF FIGURES ...... XII

LIST OF APPENDICES ...... XIV

LIST OF ABBREVIATIONS ...... XV

CHAPTER 1 INTRODUCTION: VISUAL SYSTEM AS A MODEL FOR STUDYING ADAPTATION AND PROTEIN FUNCTION ...... 1

1 ...... 1 1.1 INTRODUCTION: THE DIVERSITY IN VISUAL PIGMENT PROTEINS ...... 1 1.2 VISUAL PIGMENT STRUCTURE AND FUNCTION ...... 2 1.2.1 Rod photopigment structure ...... 3 1.2.2 Retinal chromophore ...... 4 1.2.3 Phototransduction and the visual cycle ...... 5 1.2.4 Duplex vision ...... 7 1.2.5 Spectral tuning...... 8 1.2.6 Short-wavelength sensitive vision ...... 9 1.3 MOLECULAR METHODS TO STUDY VISUAL PIGMENTS ...... 11

1.4 COMPUTATIONAL METHODS TO STUDY PROTEIN CODING GENES ...... 12 1.5 AVIAN VISION ...... 15 1.6 BOWERBIRDS ...... 17 1.7 THESIS OBJECTIVES ...... 18 1.8 THESIS OVERVIEW ...... 19

1.9 TABLES ...... 21 1.10 FIGURES ...... 22

REFERENCES ...... 30

CHAPTER 2 SHORT-WAVELENGTH SENSITIVE OPSIN (SWS1) AS A NEW MARKER FOR VERTEBRATE PHYLOGENETICS ...... 41

vii 2 ABSTRACT ...... 41 2.1 AUTHORS' CONTRIBUTIONS ...... 41 2.2 INTRODUCTION ...... 42

2.3 METHODS ...... 43 2.4 SEQUENCE ALIGNMENT ...... 43 2.4.1 Phylogenetic analyses ...... 44 2.4.2 Nucleotide composition and substitution frequencies ...... 45 2.5 RESULTS ...... 45 2.5.1 Phylogenetic analyses ...... 45 2.5.2 Patterns of sequence variation in the SWS1 data set ...... 47 2.6 DISCUSSION ...... 51 2.7 CONCLUSION ...... 55 2.8 TABLES ...... 56

2.9 FIGURES ...... 60 2.10 SUPPLEMENTARY DATA ...... 62 2.10.1 Supplementary figures...... 62

REFERENCES ...... 70

CHAPTER 3 BOWERBIRD OPSINS, SPECTRAL TUNING MECHANISMS IN SHORT- WAVELENGTH-SENSITIVE (SWS1) VISUAL PIGMENTS, AND THE EVOLUTION OF UV/VIOLET VISION IN PASSERINES AND PARROTS...... 79

3 ABSTRACT ...... 79 3.1 INTRODUCTION ...... 80 3.2 EXPERIMENTAL PROCEDURES ...... 82 3.2.1 Opsin sequences and mutagenesis ...... 82 3.2.2 Expression & purification of wild type and mutant pigments...... 82 3.2.3 Ancestral sequence reconstruction of Helix 2 in Landbirds ...... 83 3.2.4 Tests of selection and BEB sites in avian SWS1 whole gene dataset ...... 85 3.3 RESULTS ...... 85 3.3.1 Mechanisms of wavelength regulation in C. nuchalis SWS1 ...... 86 3.3.2 Other visual pigment characteristics ...... 87

3.3.3 Evolution of λmax in passerine birds ...... 87 3.3.4 Detecting selection in avian SWS1 visual pigments ...... 88 3.4 DISCUSSION ...... 89

viii 3.4.1 Evolution of SWS1 λmax in passerine birds ...... 90 3.4.2 Spectral tuning in C. nuchalis SWS1 ...... 91 3.4.3 Function of UV vs. violet sensitivity ...... 94 3.5 CONCLUSIONS ...... 95 3.6 TABLES ...... 97 3.7 FIGURES ...... 100

3.8 SUPPLEMENTARY DATA ...... 109 3.8.1 Supplementary tables ...... 109 3.8.2 Supplementary figures ...... 117

REFERENCES ...... 126

CHAPTER 4 CHARACTERIZATION OF RHODOPSIN IN THE GREAT BOWERBIRD (CHLAMYDERA NUCHALIS): THE ROLES OF D83N AND A292S IN RETINAL RELEASE ...... 135

4 ABSTRACT ...... 135 4.1 INTRODUCTION ...... 136 4.2 EXPERIMENTAL PROCEDURES ...... 138 4.2.1 PCR, cloning, and sequencing...... 138 4.2.2 Generation of RH1 opsin expression constructs and site-directed mutagenesis ...... 138 4.2.3 Expression of wild type and mutant pigments...... 138 4.2.4 Functional assays ...... 139 4.2.5 Modeling of residues onto the RH1 structure...... 139 4.3 RESULTS ...... 139 4.3.1 Sequence analysis of C. nuchalis RH1 ...... 139 4.3.2 Protein expression and spectroscopic assays...... 140 4.3.3 Functional characteristics of site 83 and 292 mutants ...... 141 4.4 DISCUSSION ...... 141 4.4.1 C. nuchalis RH1 amino acid sequence and functional characteristics ...... 142 4.4.2 Effects of site 83 on RH1 function ...... 143 4.4.3 Effects of site 292 on RH1 function ...... 143 4.4.4 D83N in RH1 structure and function ...... 145 4.4.5 Evolution of RH1 D83N in vertebrates & bowerbirds ...... 148 4.5 CONCLUSIONS ...... 149

4.6 TABLES ...... 151 4.7 FIGURES ...... 153

ix 4.8 SUPPLEMENTARY DATA ...... 162

REFERENCES ...... 166

CHAPTER 5 CONCLUSIONS AND FUTURE DIRECTIONS ...... 174

5 ABSTRACT ...... 174 5.1 CHAPTER 2: SWS1 AS MOLECULAR MARKER IN PHYLOGENETICS ...... 175 5.1.1 Future directions in molecular studies of vertebrate SWS1 genes ...... 176 5.2 CHAPTER 3: FUNCTION AND EVOLUTION OF PASSERINE SWS1 PIGMENTS ...... 176 5.2.1 The anomaly of consistent SWS1 spectral tuning in passerines ...... 177 5.2.2 Further implications on studies in behaviour and ecology ...... 178 5.2.3 Future directions in SWS1 spectral tuning studies ...... 180 5.2.4 Role of UV signals in bowerbird mate choice? ...... 182 5.2.5 Future directions in the ecology of UV/violet vision in birds ...... 183 5.3 CHAPTER 4: BOWERBIRD RH1 AND THE EFFECTS OF SITE 83 AND 292 ON RETINAL RELEASE...... 185 5.3.1 Future directions in understanding the roles of sites 83 and 292 ...... 187 5.4 SUMMARY ...... 187

REFERENCES ...... 189

6 APPENDICES ...... 194 6.1 APPENDIX 1: SECONDARY ABSORBANCE PEAKS IN SHORT WAVE ABSORBING VISUAL PIGMENTS EXPRESSED

IN VITRO ...... 194

REFERENCES ...... 196

6.2 APPENDIX 2: FACTORS AFFECTING SWS1 λMAX ESTIMATES ...... 197

REFERENCES ...... 199

x List of Tables

Chapter 1 Table 1. Parameters in Site models: to detect positive selection that affects individual sites. .. 21 Table 2. Parameters in Branch-Site Model A: to detect positive selection that affects only a few sites on pre-specified lineages...... 21 Table 3. Parameters in Clade models: to detect positive selection that affects entire clades. ... 21

Chapter 2 Table 1. Substitution frequencies and rate heterogeneity parameters ...... 56 Table 2. Base composition and χ2 tests of homogeneity ...... 57 Table 3. Accession numbers and species identification for taxa in SWS1 data set ...... 58

Chapter 3 Table 1. Degenerate oligonucleotides for PCR ...... 97 Table 2. Spectral absorbance characteristics measured for wild type C. nuchalis SWS1 pigments and site-directed mutants expressed in HEK293T cells, with the corresponding putative ancestral states in Passeriformes and Psittaciformes according to reconstruction of sites 86, 90 & 93 indicated...... 98 Table 3. Likelihood ratio tests (LRTs) from Branch-Site analyses of the avian SWS1 dataset with different 'foreground' lineages...... 99 Table S1. Species names & accession numbers corresponding to sequence data used in both datasets for molecular evolution analyses: Aves SWS1 gene (AvS1) and Landbird Helix 2 (LB) ...... 109 Table S2. Likelihood scores, parameter estimates, likelihood ratio test P values from Branch-Site model analyses of the avian SWS1 dataset with different 'foreground' lineages...... 114 Table S3. Likelihood scores, parameter estimates, and likelihood ratio test P values from Clade model analyses of the avian SWS1 dataset with different 'foreground' lineages...... 115 Table S4. Likelihood scores, parameter estimates, and likelihood ratio test P values from Random Sites model analyses of the avian SWS1 dataset...... 116

Chapter 4 Table 1. Spectroscopic and kinetic parameters of wild type and mutant bowerbird and bovine RH1s...... 151 Table 2. Comparison of λmax values of select avian RH1 pigments measured using microspectrophotometry and by in vitro expression ...... 152 Table S1. Vertebrates with RH1s that express N83 and/or S292 ...... 162

xi List of Figures

Chapter 1 Figure 1. Crystal structure model of dark state bovine rod photopigment...... 22 Figure 2. Two isoforms of retinal: 11-cis, and all-trans...... 23 Figure 3. Hydrolysis of the Schiff base linkage generates opsin and free all-trans retinal...... 24 Figure 4. Vertebrate visual pigments respond to light and recover through a number of intermediate steps...... 25 Figure 5. The photoreaction of rhodopsin...... 26 Figure 6. Photoreceptor activation and deactivation occurs through a cascade of molecular events...... 27 Figure 7. Range of SWS1 λmax values in vertebrates...... 29

Chapter 2 Figure 1. Summary of vertebrate evolutionary relationships, based on morphological and molecular data...... 60 Figure 2. Maximum parsimony phylogeny. Strict consensus of 432 equally most parsimonious trees...... 61 Figure S1. Amino acid alignment of vertebrate SWS1 opsin sequences ...... 62

Chapter 3 Figure 1. Alignment of visual pigment sequences in C. nuchalis...... 100 Figure 2. Evolutionary relationships of the C. nuchalis opsins with other vertebrate opsins created using Maximum likelihood and Bayesian methods...... 102 Figure 3. UV-visible absorption spectra of in the C. nuchalis SWS1 after in vitro expression and purification...... 104 Figure 4. UV-visible absorption spectra of purified mutants created in C. nuchalis SWS1 visual pigment expressed in HEK293T cells...... 105 Figure 5. Hydroxylamine sensitivity of the expressed C. nuchalis SWS1 pigment...... 106 Figure 6. Ancestral reconstruction and substitution patterns of sites 86, 90 & 93 in Helix 2 of SWS1 genes in Landbirds...... 107 Figure S1. Alignment of opsin gene fragments from Landbirds used in ancestral reconstruction indicating sites 86, 90 & 93...... 117 Figure S2. Amino acid alignment of avian SWS1 opsin sequences for molecular evolution analyses (AvS1)...... 118 Figure S3. Avian phylogeny used for molecular evolution analyses with foreground branches for Branch-Site and Codon model analyses indicated...... 120 Figure S4. Location of putative positively selected sites in avian SWS1 in snake plot (LHS) and 3D model (RHS)...... 122 Figure S5. Alternate Landbird topologies used to confirm ancestral sequence reconstruction. . 124

xii Chapter 4 Figure 1. Sequence of C. nuchalis RH1 displayed in a snake plot based on the crystal structure of bovine RH1...... 153 Figure 2. UV-visible spectroscopy assays of the expressed C. nuchalis and Bovine RH1 wild- type and mutant pigments at pH 6.5...... 155 Figure 3. Hydroxylamine assay on the expressed C. nuchalis RH1 pigment...... 156 Figure 4. Retinal release rates of expressed C. nuchalis and bovine RH1 wild type and 83 mutant pigments...... 157 Figure 5. Properties of G. gallus wild type RH1...... 158 Figure 6. Properties of C. nuchalis RH1 carrying the A292S mutation...... 159 Figure 7. Bovine RH1 crystal structure highlighting sites 83, 113, 292, 296, & 302...... 160

xiii List of Appendices

Appendix 1: Secondary absorbance peaks in short wave absorbing visual pigments expressed in vitro ...... 194 Appendix 2: Factors affecting SWS1 λmax estimates ...... 197

xiv List of Abbreviations

-lnL ln likelihood 1D4 antibody for C-terminal epitope of bovine rhodopsin A alanine

A280/Amax ratio of absorption at 280 nm and λmax AIC Akaike information criterion

Aλmax absorbance at the wavelength of maximal absorbance Arr arrestin ASR ancestral sequence reconstruction AvS1 avian SWS1 dataset BEB Bayes empirical Bayes bp base pair C cysteine Ca2+ calcium ion cCMP cyclic guanine monophosphate cDNA complementary DNA cGMP/CG cyclic GMP 3-((3-Cholamidopropyl) dimethylammonium)-1-propanesulfonate detergent with CHAPS PC phosphatidylcholine CMV cytomegalovirus D aspartic acid df degrees of freedom DM N-dodecyl-β-D-maltopyranoside dN/dS ratio of synonymous to non-synonymous substitutions DNA deoxyribonucleic acid E glutamic acid ERG electroretinography F phenylalanine G G protein (transducin) G glycine G* activated G-protein (transducin) alpha subunit bound to GTP (Gα-GTP) GC guanylate cyclase GDP guanine 5’-diphosphate GHB glycerol based harvesting buffer GMP guanine 5’ -monophosphate GPCR G protein-coupled receptor GSB glycerol based solubilization buffer GTP guanine 5’-triphosphate Gα G protein (transducin) α subunit

xv H histidine H# alpha (α) helix motif HB harvesting buffer HCl hydrochloric acid Human embryonic kidney cells that stably express SV40 large T-antigen which permits the HEK293T amplification of plasmids containing the SV40 origin of replication HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid I isoleucine Ile isoleucine k transition to transversion ratio K lysine K+ potassium ion L leucine LB Landbird α Helix 2 dataset Leu leucine LG Le and Gascuel (2008) amino acid substitution matrix LHS left hand side LRT likelihood ratio test LWS long-wavelength sensitive visual pigment Lys lysine M methionine MEGA5 molecular evolution genetic analyses version 5 Met methionine

MgCl2 magnesium chloride MI metarhodopsin I MII metarhodopsin II MIII metarhodopsin III min minute ML maximum likelihood MP maximum parsimony MSP microspectrophotometry MWS medium-wavelength-sensitive visual pigment N asparagine Na+ sodium ion NaCl sodium chloride

NH2OH hydroxylamine nm nanometer np number of parameters p proportion P proline PAML phylogenetic analysis by maximum likelihood PCR polymerase chain reaction PDB protein data base

xvi PDE phosphodiesterase PDEϒ inhibitory gamma subunit of phosphodiesterase Phe phenylalanine pIRES- mammalian expression vector with humanized renilla green fluorescent protein hrGFP II pJET1.2 plasmid cloning vector PMSF phenylmethylsulfonyl fluoride PP posterior probability PSB protonated N-retinylidene Schiff base Q glutamine R arginine R rhodopsin R* activated rhodopsin RACE rapid amplification of cDNA ends RGS9 regulator of G-protein signaling type 9 RHS right hand side RH1 rod visual pigment RH2 rod-like visual pigment RK rhodopsin kinase RNA ribonucleic acid S serine SB N-retinylidene Schiff base SbB solubilization buffer SWS1 short-wavelength-sensitive 1 visual pigment SWS2 short-wavelength-sensitive 2 visual pigment T threonine t1/2 length of half-life TMD transmembrane domain Tris Tris (hydroxymethyl) aminomethane UV ultraviolet UVS ultraviolet sensitive V valine Val valine VS violet sensitive W tryptophan Y tyrosine Δ2ι difference in likelihood values

λmax wavelength of maximal absorption ω ratio of synonymous to non-synonymous substitutions

xvii Chapter 1 Introduction: Visual system as a model for studying adaptation and protein function

1 .

1.1 Introduction: The diversity in visual pigment proteins

Visual pigments form the first step in the biochemical cascade that converts light into visual information. It is well known that variation in the spectral properties and subtypes of the visual pigments that mediate colour and dim-light vision are a prevalent mechanism for the molecular adaptation to diverse light environments (Davies et al., 2012). Rod (RH1) photopigments are typically expressed in rod photoreceptors and mediate vision in dim light. Given their sensitivity to light, rod photoreceptors are bleached and thus non-functional in bright light. Instead, cone photoreceptors mediate vision in bright light. There are four cone pigment classes: long-, middle- , and two short-wavelength-sensitive (LWS, RH2, SWS2, & SWS1) (Bowmaker, 2008). Colour vision is achieved by the integration of signals from multiple cone photoreceptors (Baccus, 2007; Mustafi et al., 2009). To achieve vision in dim vs. bright light conditions, rod and cone photoreceptors have different properties (Lamb & Pugh, 2004; Lamb & Pugh, 2006; Lamb, 2009). These differences are determined by the expression of alternate isoforms of proteins of the phototransduction cascade in rods as compared to cones (Ebrey and Koutalos, 2001; Hisatomi and Tokunaga, 2002), and include important differences between rod and cone visual pigments (Kefalov et al., 2003; Fu et al., 2002; Fu and Yau, 2007).

The movement of vertebrates to differing photic niches throughout evolutionary history has led to an enormous diversity of spectral sensitivity shifts in vertebrate visual pigments, and so variation in spectral sensitivity is one of the most highly characterized properties of visual pigments (Yokoyama, 2000a; Hunt et al., 2009; Davies et al., 2012). Among visual pigment types, the Short Wavelength Sensitive 1 (SWS1) visual pigments are unique as they demonstrate the greatest variation in wavelength sensitivity across vertebrates, and can extend sensitivity into the ultraviolet (UV) range (Hunt et al., 2009). There is, however, an increasing awareness that visual pigments can adapt in other ways; for example, in their activation kinetics (Sugawara et

1 al., 2010), and these changes might also play important roles in sensory perception in an ecological context.

Methods in comparative biology have played an important part in advancing our understanding of visual pigment biochemistry. For example, characterizing the diversity in spectral tuning mechanisms across vertebrates has improved the understanding of protein ligand interactions. The finding that visual pigments can adapt in other ways is exciting because it opens new doors to study visual pigment function. There is great potential for diversity in visual pigment function in the natural world. This diversity has a proven capacity to improve our understanding of visual pigment biochemistry.

This thesis focuses on the study of visual pigment proteins and the usefulness of doing so within an evolutionary framework. The following chapter provides background on visual pigments and illustrates their relevance to a variety of research fields. Rhodopsin structure and function is described, with the introduction of examples of variation in the photoactivation cycle and of rod and cone visual pigments. This is followed by a description of methods to characterize functional differences in visual pigments and evolutionary change in protein coding genes. This chapter ends with an introduction to a group of vertebrates that show promising potential in the comparative biology of vision: the birds. The purpose of this chapter is to describe some of the many complexities of the visual system and the potential for a diverse number and range of functional adaptations.

1.2 Visual pigment structure and function Visual pigments consist of an opsin protein covalently bound to a light sensitive chromophore ligand. The energy contained in a photon of light causes isomerization of the chromophore that induces a conformational change in the opsin protein, thereby initiating a biochemical cascade that leads to an electrical response in the photoreceptor cell (Menon et al., 2001). Opsin proteins belong to the superfamily of G-protein coupled receptor (GPCR) proteins. GPCRs are responsible for cellular signaling as a response to a wide spectrum of agonists including hormones, chemical odorants, neurotransmitters, and photons of light. The opsins are unique among this group as their ligand, the chromophore, is covalently bound (Wald, 1968). The visual rod photopigment (RH1), a member of the largest subfamily of GPCRs, has become a model for GPCR structure/function studies (Karnik et al., 2003; Smith, 2010; Zhou et al., 2012). The first

2 portion of this section summarizes what is known of the structure and function of RH1, the most well studied visual pigment. The latter portion introduces important functional differences between rod and cone opsin function that are linked to the disparate roles of their respective photoreceptors in mediating vision in dim vs. bright light. The final section also describes the varied spectral tuning mechanisms in SWS1 pigments.

1.2.1 Rod photopigment structure

The structure of RH1 has been described in detail in original literature and reviews in its inactive, dark state (Palczewski, 2000; Menon et al., 2001; Sakmar et al., 2002; Okada et al., 2004; Smith, 2010), as well as in related photobleaching conformations (Park et al., 2008; Choe et al., 2011; Scheerer et al., 2008; Zhou et al., 2012). It is a membrane-spanning molecule with seven alpha helices, characteristic of GPCRs (Fig. 1). The helices are arranged somewhat parallel to one other in a barrel fashion, creating a binding pocket for the chromophore ligand. The seven transmembrane helices (H1-H7) vary in length from 20 to 33 amino acids. The extracellular, or intradiscal, side includes three loops and the N terminus. The intracellular, or cytoplasmic, side comprises three loops and the C terminus. The C terminus contains a short amphipathic eighth helix that lies on the cytoplasmic surface of the membrane, and is anchored by palmitoylation of cysteine residues in this region. All regions of the opsin structure: extracellular loops, intracellular loops, transmembrane spanning helices, as well as N and C termini contain sites and/or motifs that are highly conserved and have essential functional roles. The chromophore is covalently bound to a lysine residue (K) at site 296 via a Schiff base link. This residue is conserved among all opsins. The Schiff base counter-ion, glutamic acid (E) at site 113, is another. Both sites have important roles in the activation and inactivation of opsin (Cohen et al., 1992).

An important physical property of visual pigments is the non-covalent bonds formed among residue side chains and internal water molecules (Smith, 2010). These molecules form important functional networks throughout the protein and include; disulfide bonds, salt bridges, as well as both direct and water mediated hydrogen bonds. They are not only essential to stabilize the dark state structure, but are also necessary for proper opsin function (e.g. Sakmar et al., 2002; Breikers et al., 2001; Janz and Farrens, 2004; Weitz and Nathans, 1993). Upon isomerization of the chromophore, however, some non-covalent bonds are broken and new bonds must be formed.

3 This rearranges the internal bonding network and dramatically alters the orientation of helices H5 and H6 in the activated RH1 (Choe et al., 2011).

1.2.2 Retinal chromophore

The light sensitive component in a visual pigment is the chromophore. The visual pigments of most vertebrates utilize vitamin A1-derived chromophore, 11-cis-retinaldehyde (retinal). Some instead utilize vitamin A2-derived chromophore, 3,4-dehydroretinaldehyde (3,4-dehydroretinal) (Bowmaker, 2008). This alternate chromophore results in a slight long wave shift and may be an alternate mechanism to adjust spectral sensitivity (Whitmore and Bowmaker, 1989). In some cases RH1 pigments are referred to as ‘rhodopsins’, but this term includes all pigments with an A1 derived chromophore, whereas those with an A2 derived chromophore are referred to as ‘porphyropsins’.

The structure and isomerization of the retinal chromophore is shown in Figure 2. The retinal ligand is covalently bound to a lysine residue at site 296 of the opsin protein by a Schiff base (SB) link that is protonated in the dark state (Hargrave et al., 1983). The exception is in UV absorbing pigments, where this link is stabilized as unprotonated (Babu et al., 2001). In the dark state, the retinal is in a cis conformation at the C11-C12 bond. Energy contained in light generates isomerization of this bond to convert 11-cis-retinal to all-trans-retinal. The protonated SB eases cis to trans isomerization by facilitating electron delocalization. Thus, the lack of protonation in UV absorbing pigments is probably associated with their sensitivity to high- energy light. After isomerization, the retinal-opsin bond is hydrolyzed (Fig. 3). During this process the counterion, glutamate at amino acid site 113 of the opsin protein (E113), plays an important role. It catalyzes hydrolysis of the SB link, and its acidic nature facilitates the production of an unstable intermediate that easily breaks the retinal-opsin bond (Chen et al., 2012; Cooper et al., 1987).

Once released, all-trans-retinal is converted back to 11-cis-retinal in a process called the retinoid cycle. The details of this process are beyond the scope of this study but reviewed in the literature (Wang and Kefalov, 2011). Briefly, the reconversion is carried out by complicated and energy consuming cellular machinery, in retinal pigment cells for rods and in Müller cells for cones. Once reformed, the 11-cis-retinal is transported back to the photoreceptor cells, where it can recombine with free opsin to form the inactive rhodopsin in its ground state. 4 1.2.3 Phototransduction and the visual cycle

Absorption of a photon of light by the visual pigment initiates a cascade of molecular events in the cell that activate and subsequently deactivate the photoreceptor signal (Fig. 4). Transduction of a light signal, activation, occurs through a series of changes in the visual pigment, followed by a cascade of events in the photoreceptor cell. In the dark (inactive) state, rhodopsin (R) contains retinal in the 11-cis conformation. The absorption of energy in the form of light or heat induces chromophore isomerization (Wald 1950). This creates steric strain and subsequent thermal relaxation of both chromophore and protein through a series of spectrally defined intermediates

(Fig 5). These reactions lead to the formation of three photoproducts: Metarhodopsin I (MI) (λmax

~480 nm), MII (λmax ~380 nm), and MIII (λmax ~ 465 nm). MI, II and III exist in equilibrium (Kibelbek et al., 1991; Vogel et al., 2004; Heck et al., 2003; Parkes and Gibson, 1999), yet MII is the active signaling species (also known R*). The molecular details of the biochemical processes of the phototransduction cascade have been thoroughly reviewed (e.g. Arshavsky et al., 2002; Lamb and Pugh, 2006; C. Chen, 2005; Burns and Baylor, 2001). The process is summarized in Figure 6. Activated rhodopsin (R*) catalyzes GDP -> GTP exchange on the α-subunit of many copies of the heterotrimeric G protein, transducin, producing the active form Gα-GTP (G*). Two G* molecules bind the inhibitory subunits of phosphodiesterase (PDEγ) allowing its remaining subunits to catalyze the hydrolysis of massive amounts of cyclic GMP (c-GMP) (Wensel & Stryer 1986). The consequent fall in the cytoplasmic c-GMP concentration causes nucleotide gated ion channels in the plasma membrane to close (Cobbs & Pugh 1987; Karpen et al., 1988). This blocks the inward flux of sodium (Na+) and calcium (Ca2+), leading to membrane hyperpolarization of the photoreceptor cell that causes a reduction in the rate of glutamate release onto second-order retinal neurons. In this cascade, there are three stages that enable signal amplification in the photoreceptor cell response: (1) each R* activates multiple transducin molecules; (2) each activated PDE hydrolyzes many c-GMP molecules, and (3) many gated channels respond to the drop in c-GMP.

Timely recovery of the photoresponse is critical for maintaining sensitivity in steady light and for signaling changes in light intensity. The signal is actively shut down in response to decreasing cellular Ca2+ levels. Recovery requires deactivation of active enzyme intermediates and restoration of cGMP levels (Figure 6). Deactivation of rhodopsin occurs through two stages:

5 phosphorylation and binding of arrestin. First, R* is phosphorylated (at serine and threonine residues in the C-terminal domain) by rhodopsin kinase (RK) (Arshavsky 2002). The activity of RK is normally inhibited in a calcium dependent manner by an RK regulating protein (recoverin in bovine rods (Dizhoor et al., 1991; Kawamura & Yokoyama 1993), S-modulin in frog (Kawamura and Murakami 1991; Kawamura 1993), or visinin in cones (Kawamura et al., 1996)). The drop in Ca2+ releases RK from inhibition. Phosphorylated rhodopsin is then targeted for subsequent binding by arrestin (Arr), which prevents transducin binding on rhodopsin cytoplasmic loops (Wilden et al., 1986). The specific role of arrestin is somewhat unclear. Its interaction with rhodopsin prevents the ability of rhodopsin to activate G-proteins, but also prevents the release of retinal in vitro (Sommer and Farrens, 2006). The R* MII conformation decays by hydrolysis of the retinal SB and dissociation of the rhodopsin into free all-trans retinal and the apoprotein opsin (Fig. 5). An potential alternative decay pathway is via formation of MIII (Bartl and Vogel, 2007; Heck et al., 2003), but this occurs on a timescale of hours in vitro, so its contribution to decay in the photoreceptor cell is likely limited. Complete deactivation occurs once free opsin binds 11-cis retinal to reform the dark state visual pigment (Wald, 1968). The SB link forms through the same but reverse process as hydrolysis (Cooper et al., 1987). Also essential for photoreceptor recovery is the deactivation of the active transducin subunit (G∗), whose activity persists until the bound GTP is hydrolyzed to GDP. This reaction is accelerated by regulator of G-protein signaling protein (RGS9) (He et al., 1998), which preferentially targets G∗ when complexed with PDEγ (Chen et al., 2000). Last, the restoration of intracellular cGMP levels occurs by activation of guanylate cyclase (GC), by Ca2+ regulated guanylate cyclase activating proteins (GCAP) (Dizhoor et al., 1995; Palczewski et al., 1994; Haeseleer et al., 1999). Deactivation of the photoresponse is an essential part of the recovery phase of visual transduction, as the system resets to respond to further light input. Delays in this process alter the ability of the photoreceptors to adapt to changing light conditions. Hypotheses regarding the rate- limiting step include the rate at which free 11-cis- retinal is transported into the photoreceptor (Lamb and Pugh, 2006), and the ability of the protein to uptake and bind with free retinal, which is determined by properties of the opsin binding pocket (Chen et al., 2012; Ala-Laurila et al., 2004).

6 1.2.4 Duplex vision

Most vertebrates have retinae that are considered functionally duplex because they contain one single type of rod photoreceptor cell for vision in dim light and multiple cone types for colour vision in bright light. To perform these disparate roles, rods and cones differ in sensitivity, spectral tuning, and in rates of activation and recovery (see Lamb and Pugh, 2004; Lamb and Pugh, 2006). These alternate properties are achieved by functional differences in the components of the phototransduction cascade (Ebrey and Koutalos 2001; Hisatomi and Tokunaga 2002). In cones, the phototransduction proteins tend to have increased activity and/or are expressed in increased concentrations. For example, RK activity is higher in cones than in rods (Tachibanaki et al., 200). Also, the cone-type RK regulating protein has much higher expression levels than that of the rod isoform, leading to increased RK inhibition in cones compared to rods (Arinobu et al., 2010). As well, RGS9, that which regulates G-protein activity, has higher levels of expression in cones than in rods, and therefore is another potentially important determinant of the faster response kinetics and lower sensitivity of cones, as compared with rods (Cowan et al., 1998). Furthermore, the cone subtypes of guanylate cyclase, responsible for cGMP synthesis and therefore recovery of a light response, have both higher activity and higher expression (Takemoto et al., 2009). Last, even the metabolism of retinal is also more efficient in cones due to a greater concentration of retinol dehydrogenases (Miyazono et al., 2008). Overall, while the steps of the phototransduction cascade are largely similar between rods and cones, the molecular properties of the different isoforms of the phototransduction proteins are responsible for the functional differences between these photoreceptor types.

Among phototransduction proteins, the alternate visual pigments expressed in rods and cones also regulate their disparate response kinetics and sensitivities. This has been demonstrated in transgenic studies in Xenopus and mouse (Kefalov et al., 2003; Fu et al., 2002; Fu and Yau, 2007). There are a number of well-characterized differences between rod and cone visual pigments that explain the altered photoreceptor functions. First, the relative stability of the dark- adapted pigment determines the rate of thermal isomerization, and thus the activation of the phototransduction cascade in the absence of light (Luo et al., 2011). Rod opsins are more stable and exhibit virtually no dark noise, and thus have a more reliable signal (Kefalov et al., 2003). The second property is the lifetime of the light activated conformation (R*, or MII). This determines the number of transducin molecules that can be activated, and might determine the

7 difference in amplitude of the photoresponse in rods vs. cones (Tachibanaki et al., 2007). The third property of visual pigments that likely contributes to differing photoresponses of rods and cones is the rate at which new visual pigment is regenerated. This process is associated with the rate at which a photoreceptor can recover from exposure to light and occurs more quickly in cones than in rods (Imai et al., 2005). The fourth characteristic of visual pigments that contributes varied responses among photoreceptors is the wavelength of light to which the visual pigment is maximally sensitive. This particular trait actually varies considerably among cone types. Each visual pigment has a characteristic range of spectral sensitivity and wavelength of maximal absorption (λmax), ranging from the far red into the UV (Davies et al., 2012). These biochemical characteristics are the primary differences between visual pigment proteins of rods and cones. They are consistent with hypotheses that the visual pigments themselves also contribute to the observed differences in photoresponse and kinetics of rod and cone photoreceptors.

1.2.5 Spectral tuning

Among the primary functional properties known to vary among rod and cone visual pigments, wavelength sensitivity has received the most attention. The spectral sensitivity of a given visual pigment is determined by interactions between the opsin protein and its chromophore, a mechanism referred to as spectral tuning (Kochendoerfer et al., 1999). Specifically, residues in the binding pocket influence the ground and excited electrochemical states of the chromophore, altering the energy required for isomerization (Lin and Sakmar, 1999). Ways in which an opsin protein can interact with the retinal chromophore to alter λmax include: 1) steric strain by large side chains near the chromophore; 2) altered electron delocalization across the chromophore by charged or polarized groups near the polyene chain; 3) stabilization of the protonated or deprotonated state of SB link (Kochendoerfer et al., 1999). Variation in amino acid sequence of a given opsin can, therefore, directly influence the spectral wavelengths an organism can detect. For this reason considerable research has focused on identifying the molecular mechanisms regulating variation in spectral sensitivity among and within the different visual pigment types (see Hunt et al., 2004; Bowmaker and Hunt, 2006; Yokoyama, 2008; Hunt et al., 2009; Davies et al., 2012, and references therein).

8 RH1s tend to have λmax values near ~500 nm. The λmax constraint in RH1s is likely associated with the requirement of minimizing noise in sensitive rod photoreceptors since thermal activation is greater in cone, vs. rod pigments (Luo et al., 2011). However, a number of vertebrate species do express RH1s with blue shifted λmax including whales, bats, and deep-water dwelling fish (McFarland, 1971; Hunt et al., 1996; Fasick et al., 1998; Yokoyama et al., 1999; Fasick and Robinson, 2000; Sugawara et al., 2005; Davies et al., 2007; Yokoyama and Tada, 2008; Sugawara et al., 2010). These species tend to live in very dim, or blue light conditions. As such, their blue shifted λmax values are believed to be adaptive. Cone opsins, on the other hand, have dramatically different λmax values, ranging from the far red into the UV (570- 533 nm Yokoyama, 2000a; Bowmaker, 2008). The four types of cone visual pigments: long (LWS), Rod- like (RH2), and two short (SWS1 & 2), are defined by molecular phylogeny and their relative

λmax values. The variation in sensitivity and mechanisms regulating sensitivity within and among the visual pigment types have been thoroughly reviewed (e.g. Yokoyama, 2000a; Bowmaker, 2008; Hunt et al., 2009; Davies et al., 2012).

1.2.6 Short-wavelength sensitive vision

SWS1 pigments are particularly interesting because across vertebrates they exhibit the broadest naturally occurring variations in λmax; ranging from the violet to UV (Fig. 7). Accordingly, they have been divided into two sub-types on the basis of spectral sensitivity: violet sensitive (VS:

λmax 388-455 nm) and UV sensitive (UVS: λmax 355-380 nm) (Davies et al., 2012; Hunt et al.,

2009). Also interesting, is that sensitivity in the UV range (λmax values < 385 nm) is achieved by deprotonation of the SB link, a unique mechanism among visual pigments. Both VS and UVS pigments have been identified in all major vertebrate groups and the distribution of the two sub- types is highly variable. Phylogenetic studies have shown that the spectral shifts between UVS and VS occurred a number of times throughout vertebrate evolution (Yokoyama and Shi, 2000; Carvalho et al., 2012; 2006; Cowing et al., 2002; Parry et al., 2004; Shi et al., 2001; Takahashi and Ebrey, 2003). The vertebrate ancestral state is thought to be UVS with VS pigments evolving independently in various lineages (Yokoyama and Shi, 2000). The exception is in birds, where it is believed the ancestral avian pigment was VS, and some descendants subsequently regained UVS (Shi et al., 2001).

9 Due to the dramatic spectral variation found among SWS1 type opsins, recent research on vertebrate vision has focused on determining the molecular mechanisms regulating this broad spectral difference (Hunt et al., 2009; Carvalho et al., 2012; 2011; Takahashi and Yokoyama, 2005). Many important spectral tuning residues have been identified, and it is clear that they vary considerably among vertebrates. For example, in some cases the shift from UVS to VS requires many amino acid substitutions (Takahashi and Yokoyama, 2005; Yokoyama and Shi, 2000; Fasick et al., 1999; Carvalho et al., 2012; Yokoyama et al., 2006) whereas in others it can be a point mutation, which can vary in amino acid character and location (Parry et al., 2004; Wilkie et al., 2000; Fasick et al., 2002; Cowing et al., 2002; Yokoyama et al., 2005; 2000). Generally, it is believed that some of the most important residues include those at sites 86, 90 and 93 (numbering according to bovine RH1). In birds, the change in sensitivity from violet to UV is believed to be the result of a single amino acid substitution of serine (S) to cysteine (C) at site 90 (Wilkie et al., 2000; Yokoyama et al., 2000). In mammals more than one mechanism has been identified. For instance, in primates the loss of UVS is determined by a handful of sites (Fasick et al., 1999; Carvalho et al., 2012) whereas, in non-primate mammals the loss of UVS is primarily determined by substitutions replacing Phenylalanine (F) at site 86 (Fasick et al., 2002; Cowing et al., 2002; Parry et al., 2004). F86 is important in other vertebrate groups as well, in that it determines UVS in fish (Fasick et al., 2002) and has been implicated in the loss of UVS in the avian ancestor (Shi et al., 2001). Interestingly, this residue has also been identified in some extant birds (Ödeen and Håstad, 2003). This suggests they too may have re-evolved UVS and thus, as has been observed in mammals, spectral shifts in birds may also have occurred through a variety of molecular mechanisms. However, although the microenvironment within avian SWS1 pigments retains the ability to UV shift via F86 (See Chapter 3 and Carvalho et al., 2007), mutations at site 90 in mammals and fish have negligible effects on sensitivity (Fasick et al., 2002). This indicates that important changes have occurred during the evolution of avian SWS1 pigments that facilitated the evolution of C90 as a residue that can shift sensitivity into the UV.

Overall, it appears that the majority of variation in spectral tuning mechanisms is within mammals. But this may be due to the lack of mutagenesis studies in avian SWS1 pigments. Like mammals, birds are a large and diverse group, where visual cues are important. Given the presence of what seems to be a more complex visual system with four cone types and oil droplets (discussed below), it would seem that the ability to discriminate wavelengths is of particular

10 importance. Therefore, it would not be surprising that the divergence in sensitivity and spectral tuning mechanisms in mammalian SWS1 pigments will extend throughout birds.

1.3 Molecular methods to study visual pigments

To characterize the molecular determinants of the properties of visual pigments, it is necessary to establish associations between amino acid residues and their functional effects (Yokoyama, 2000b). Often, evolutionarily conserved amino acid residues are targeted. As an alternative potentially important sites can be identified using comparative methods, which is commonly used in spectral tuning studies. Generally the process is as follows: First, one identifies differences in protein function between two opsin types (such as wavelength sensitivity). Then, one locates potential residues responsible by identifying those that differ in functionally important areas between pigments with differing function. In this step, the protein crystal structures of the bovine RH1 photopigment are useful (Palczewski, 2000; Okada et al., 2004; Park et al., 2008; Choe et al., 2011; Scheerer et al., 2008;). Using these structures, one can predict how a substitution would perturb known interactions within the complex. Last, one can experimentally test the effects of these substitutions using site-directed mutagenesis and the expression of mutant proteins in tissue culture.

This process of identifying and mutating sites is often used if the functional difference between two visual pigments is already known. Alternatively, given the importance of the visual system to survival, changes in the environment can impart strong selective pressure on the visual system, which can lead to changes in opsin function. Therefore, some researchers instead investigate the molecular characteristics of organisms with unusual visual ecologies (Sugawara et al., 2010; Bowmaker et al., 1994; Spady, 2005; Hunt et al., 1996; Carleton et al., 2005; Weadick, 2007; Fasick and Robsinson, 1998). For example, species of fish living at different depths within the water column in Lake Baikal have evolved rod opsins with λmax values corresponding to the predominant wavelengths of light present in their photic environments (Bowmaker et al., 1994).

Blue λmax shifts in RH1s are, in fact, a common functional difference among deep-water dwelling and nocturnal mammals and fish (Sugawara et al., 2010; Hunt et al., 1996; Sugawara et al., 2005;

Davies et al., 2007; Dartnall and Lythgoe, 1965). However, these examples relate to λmax. Changes that alter visual pigment activation and deactivation kinetics in ways that affect perceptual sensitivity are likely also relevant, and possible. Indeed, it was recently demonstrated 11 that the opsins of deep-water African cichlid species form the active MII state more quickly than those of shallow water species (Sugawara et al., 2010). This change would likely have the effect of increasing the efficiency of the photoactivation response. As this study suggests, the visual systems of these fish may have adapted to the dim light conditions of their environment not only by shifting λmax but also by increasing their sensitivity to light. In summary, comparative biology methods can lead to the identification of interesting visual adaptations, with respect to wavelength sensitivity as well as photoactivation kinetics.

Other methods to assay visual pigment function are microspectrophotometry (MSP) (Bowmaker 1984), and electroretinography (ERG) (Weymouth and Vingrys 2008). MSP measures the absorption of specific wavelengths of light by a photoreceptor cell. ERG measures the electrical responses of various cell types in the retina. These methods measure opsin function within the context of the visual system, which is a more accurate way to determine the effects of a particular functional difference on the photoresponse of a photoreceptor cell. However, they have their limitations. Primarily these methods require sacrificing the organism of study, which can be expensive and unreasonable for rare or unusual species. Furthermore, these methods only allow the measurement of certain aspects of photoreceptor function: MSP methods measure wavelength sensitivity; ERG methods measure the rate and amplitude of the photoresponse. The primary limitation of both MSP and ERG methods is the difficulty in assaying the molecular mechanisms underlying differences in function. The use of transgenic organisms has been implemented to answer such questions and has proven very useful (e.g. Dryja, 2000; Fu et al., 2008; Whitcomb et al., 2010; Sakurai et al., 2011; Hao et al., 2002), however researching transgenic organisms is often costly and restricted to particular model lab species.

1.4 Computational methods to study protein coding genes In addition to the primary advantages of being able to express opsins in the lab, opsin sequence data can also be used to study visual pigment function from a phylogenetic perspective. These methods utilize genetic information and apply our understanding of how DNA and protein sequences can evolve in order to 1) evaluate substitution rates in a gene, and identify specific residues that are likely experiencing evolutionary change, and 2) infer ancestral gene sequences (Yang 2006; Yang and Bielawski, 2000; Harms and Thornton, 2010). One powerful and commonly used method for analyses of DNA and protein sequences that employs

12 phylogenetically based maximum likelihood methods is the PAML package (Yang, 2007). While typical nucleotide and amino acid models can be used, the strength of PAML is in its implementation of codon substitution models.

The most common application for phylogenetically based maximum likelihood methods is to use codon models to identify changes in evolutionary rates within an alignment of protein-coding DNA sequences (reviewed in Yang, 2006). Because most amino acids are specified by more than one codon, there exists redundancy in the genetic code that allows for two types of nucleotide substitutions: those that do not change the encoded amino acid (synonymous), and those do (non- synonymous). Codon models estimate the ratio of non-synonymous and synonymous substitution rates (dN/dS = ω) in different partitions of the data, where ω < 1, ω = 1, and ω > 1 indicate purifying selection, neutral evolution, and positive selection, respectively1. The ML algorithm determines the fit of the specified model to the extant sequence data, given a phylogenetic tree. The fit of different models can be explicitly evaluated by comparing likelihood scores of nested models using a likelihood ratio test (LRT).

Different types of codon models have been developed that are useful to detect positive selection that affects specific sites or lineages. The fit of random sites models are compared to test for positive selection that affects individual sites in a dataset (Table 1; Nielsen and Yang, 1998; Yang et al., 2000; 2005). These models estimate ω in a way that allows for variation in selection pressure across codons, where codons with high rate ratios (ω> 1) are defined as positively selected. This is compared to a null model that does not allow for any codons with ω > 1 using a

1 Since amino acid changes can have considerable effects on the function of a protein, these substitutions are not subject to the same evolutionary pressures. Equal rates of non-synonymous and synonymous substitutions this indicates a gene is experiencing no selection pressure and thus evolving under neutral evolution (Yang and Bielawski, 2000; Kimura, 1977). A higher rate of non-synonymous substitutions means those substitutions provide a fitness advantage and are being fixed more quickly than silent mutations, which is indicative of positive selection (Yang, 1998). A lower rate of non-synonymous substitutions indicates such changes are deleterious, and is termed stabilizing, or purifying selection. The estimation of non-synonymous and synonymous substitution rates can thus provide insight into the form and strength of selection shaping a protein-coding gene.

13 LRT. Branch site models are used to identify sites likely involved in gene divergence associated with particular lineages in a phylogeny (Table 2; Yang and Nielsen, 2002; Yang et al., 2005; Zhang et al., 2005). Specified (foreground) branches are compared to all other branches, and a proportion of sites in the foreground branch are allowed to fall into the positively selected site class (ω ≥ 1). Separate analyses can be run with different branches set as the foreground, and these are compared, individually, to a null model where no positively selected site class is permitted in the foreground branch. Clade models can be used to identify site-specific divergence among different clades (Table 3; Bielawski and Yang, 2004). In these models, a proportion of sites are allowed to evolve under divergent selection pressure in each selected clade (ω2, ω3 > 1;

ω2 ≠ ω3 ). To test for divergence among the specified clades, this analysis is compared against the null models M2a_rel or M1a (which do not allow for divergence among clades) (Weadick and Chang, 2012). Branch models are designed to detect positive selection acting on particular lineages (Yang 1998, Yang and Nielsen 1998). These models allow ω to vary among branches, where ω can be independent for each branch or partitioned into a user specified number of discreet values. Overall, different types of codon substitution models; random site, branch site, codon and branch, allow us to detect adaptive or divergent molecular evolution that influences specific lineages or individual sites.

Another common application of codon substitution models is to identify specific sites that are evolving with different evolutionary signatures. This is an extension of the site and branch-site models. When the LRT suggests positive selection, an empirical Bayes method can be applied to calculate the posterior probability (PP) of sites belonging to a particular site class (i.e., to divergently or positively selected classes) (Yang et al., 2005). Positively selected sites are those with high posterior probabilities of ω > 1. These sites can be targeted for further study in light of the particular protein’s structure and function. In the visual system these methods have been used to characterize the evolutionary history of opsins (Shen et al., 2010; Spady, 2005; Yokoyama and Tada, 2008) and other proteins such as lens crystallins (Weadick and Chang, 2009).

One of the most interesting ways phylogenetically based maximum likelihood methods can be used is for ancestral sequence reconstruction (ASR) (Thornton, 2004; Liberles, 2007). From the alignment, phylogeny, and substitution model, the most likely gene sequence is estimated at each node in the phylogeny, along with posterior probability estimates for each alternate state at each

14 site (Yang et al., 1995). The ML algorithm infers most likely reconstruction as that which has the highest probability of giving rise to the extant sequence data, given the phylogeny and the model of sequence evolution (which can be nucleotide, codon or amino acid). From the reconstructed nodes, relevant substitutions can also be mapped onto the phylogeny to explore the potential evolutionary history of a gene. Moreover, the ancestral protein sequence can be synthesized in the lab, allowing the ancestral protein to be expressed and characterized experimentally. ASR methods have been used to predict the evolution of protein function (e.g. Kuang et al., 2006; Ugalde et al., 2004). Given the links between vision, ecology, and behaviour, ASR of opsins can even be used to make predictions regarding the ecology and behaviour of extinct animals (Chang et al., 2002).

1.5 Avian vision

Birds are clearly highly visual organisms. First, they have some of the most stunning visual displays among animals demonstrating visual signals are an important component of communication in this group (Waldvogel, 1990). Second, birds exhibit a number of visual adaptations (Martin, 2011; Waldvogel, 1990; Walsh and Milner, 2011); for example, the avian eye is the largest relative to head size of all terrestrial vertebrates, typically occupying at least 50% of the cranial volume, compared with 5% in humans (Waldvogel, 1990). The structure of the avian eye is similar to that of mammals, but is not spherical in shape and has a sclerotic ring, which allows the lens and cornea to protrude out of the skull (Hall, 2008).

There are a number of characteristics in the avian retina that demonstrate how vision in birds is different from that of mammals, particularly humans (Hart and Hunt, 2007; Hart, 2001). Unlike mammals, birds can have multiple foveae, which are dense concentrations of cones that enhance perception at various angles (Tucker, 2000). This contributes high visual acuity in some birds, which are able to detect prey from far beyond 1 km away (Tucker et al., 2000). Like mammals, the photoreceptors in the avian retina include both rod and cone cell types, but birds express four types of cone cells, each expressing one of the four cone opsin types found in vertebrates (Bowmaker 1980). Therefore birds have tetrachromatic colour vision. As well, within the inner segment of avian cones are oil droplets containing carotenoids (Bowmaker, 1980). These structures act as filters, cutting out low wavelengths of light before they reach the photoreceptor, and probably enhance the ability of birds to discriminate colours (Vorobyev et al., 1998). The

15 avian retina also contains a class of double cone photoreceptors. The principle and accessory member joined by gap junctions, and usually express the LWS pigment. Although double cones dominate the retinae of diurnal species, they are not involved in colour detection, but instead are thought to play a role in detecting movement (Campenhausen and Kirschfeld, 1998). In summary, there are a number of retinal characteristics typical of birds that allow them to perceive their world in a considerably different way than humans do.

With four cone opsins and oil droplets, birds have a visual system well suited for detecting colour. Given the complexity of visual displays, it is clear that visual signals and plumage colouration form an important component of avian communication. Many studies have examined the ecological and evolutionary significance of avian body colouration, demonstrating avian plumage colours have the potential to reliably indicate male quality, health, and the ability to provide parental care (Hubbard et al., 2010; Mundy, 2005; Roulin, 1999; Protas and Patel, 2008). UV plumage signals in particular can play important roles in avian communication (Andersson and Amundsen, 1997; Alonso-Alvarez, 2004; Siitari et al., 2002; Berg and Bennett, 2010). Aside from its use in intraspecific signaling, birds also use UV signals in foraging (Bennett and Cuthill, 1994; Probst et al., 2002; Honkavaara et al., 2002; Hausmann et al., 2003). As well, UV vision has been suggested to play a role in orientation (Bennett and Cuthill, 1994).

The expression of UV-type SWS1s is thought to be an adaptation because it expands the visual range, and presumably increases the viewer’s ability to perceive UV signals. However, although only some birds express SWS1 pigments that are maximally sensitive in the UV range, most birds are sensitive to UV light. For instance, despite the presence of a VS-type SWS1 (Kawamura et al., 1999), behavioural and ERG experiments have shown that pigeons perceive UV light as low as 320 nm (reviewed in Kawamura et al., 1999). As well, some pigeon feathers show peak reflectance in the UV range (McGraw 2004). The ability to perceive UV light by birds lacking UVS type pigments is because UV light is not entirely filtered out by the ocular media in all birds and the sensitivities of VS-type pigments usually extend into the UV range (Hart and Hunt 2007).

Species with known UVS-type pigments are individuals within Psittaciformes (parrots) and Passeriformes (passerines), which include some of the most well studied birds in avian science (Wilkie et al., 1998; Bowmaker et al., 1997; Yokoyama et al., 2000; Carvalho et al., 2011; Hart,

16 2004; Maier, 1994; Hart et al., 1998; Das et al., 1999; Hart et al., 2000; Hart, et al., 2000). Other birds that have been investigated express VS-type pigments, with λmax values ranging from 420- 388 nm. Sequence studies focusing on the region coding for Helix 2 of the SWS1 gene have identified considerable variation, particularly at sites 86 and 90 (Ödeen and Håstad, 2003; Ödeen et al., 2009; Ödeen and Håstad, 2009; Håstad et al., 2005; Ödeen et al., 2011). Given this and the abilities of C90 and F86 to significantly shift λmax in avian as well as in mammalian pigments (reviewed in Hunt et al., 2009), it is quite possible that UVS evolved in a number of other avian orders as well.

1.6 Bowerbirds

While all passerines and parrots show superior cognitive attributes relative to other birds (Emery, 2006), the Corvida are especially well known for their cognitive skills that include advanced problem solving, tool use, and the assembly of complex constructions (Grodzinski and Clayton, 2010; Emery and Clayton, 2009; Hansell and Ruxton, 2008). The bowerbirds are a family of birds of this infraorder that show particularly interesting visual behaviours: bower building. Male bowerbirds build elaborate display grounds, ‘bowers’, that are decorated with various coloured objects as part of their courtship display (Diamond, 1986a; Marshall, 1954). This is done in a highly organized manner, often using tools. Different species build different types of bowers - ‘avenues’, ‘huts’, or ‘maypoles’- and the structure, location, and orientation can be very specific (Diamond, 1986b; Marshall, 1954). The types of objects found in bowers include items such as berries, flowers, plastic, stones, and shells. There also exists considerable variation in colour preference among, and within species (Endler and Day, 2006; Diamond, 1986a), and in many species, the ornaments selected tend to contrast with plumage and visual background colours (Endler et al., 2005). Bowerbirds also exhibit complex song behaviour (Westcott and Kroon, 2002; Kroon and Westcott, 2006; Kelley and Healy, 2010), demonstrating their use of multiple signal communication modes.

When choosing a mate, female bowerbirds assess the quality of a male’s bower and its decorations, vocalizations, and ritualized displays (Madden, 2003; Robson et al., 2005). Colourful plumage displays are common examples of sexually selected traits in birds, thus the presence of UV reflectance in male plumage and bower decorations has raised the question of whether bowerbirds have UV or violet type SWS1 pigments. As well the degree of UV

17 reflectance varies across species, therefore their SWS1 sensitivity might equally vary (Endler et al., 2005).

The great bowerbird (Chlamydera nuchalis) occupies the northern open ‘scrub-lands' that are dry for months on end and then subjected to torrential monsoon rains. These birds are nearly sexually monomorphic; the males possess a nuchal crest that, to humans, has violet, pink and orange colouration (Marshall, 1954) and some UV reflectance (Endler et al., 2005). Males build a long avenue bower within which females view the male displaying over his bower court. The bower is built on a specific north-south axis (Marshall, 1954), and arranged in a way that creates forced perspective that yields a false perception of size and distance (Endler et al., 2010). There is also reason to believe these bowers are built in specific areas to avoid brush fires (Mikami et al., 2010). Due to their unusual and complex behaviour, bowerbird visual ecology has been extensively studied (e.g. Endler et al., 2005; Endler and Day, 2006; Borgia et al., 2007). Consequently, these birds provide an intriguing system with which to study the function and evolution of visual pigments as well as vision in birds.

1.7 Thesis objectives

The primary objective of this thesis is to identify functionally important genetic variation in vertebrate visual pigments, and experimentally investigate the potential consequences for visual perception using in vitro expression methods. The particular goals of this research are as follows: 1. To describe the molecular evolution of SWS1 opsin genes in vertebrates. 2. To isolate the visual pigments of the great bowerbird (C. nuchalis) and to determine whether it has a UV or violet type SWS1 using in vitro expression. 3. To explore the mechanisms of wavelength regulation in passerine SWS1 genes by replacing residues at known spectral tuning sites in C. nuchalis SWS1 and measuring

their effects on λmax. 4. To improve our understanding of avian vision by investigating the distribution of UV/violet vision across birds, and to infer the evolutionary history of UV vision in passerines using ancestral sequence reconstruction. 5. To experimentally characterize the properties of the bowerbird RH1, in order to better understand its function in comparison with well-characterized model systems: bovine (Bos taurus) and chicken (Gallus gallus).

18 6. To use site-directed mutagenesis methods to determine the mechanistic bases underlying functional differences between C. nuchalis and bovine RH1s. 7. To demonstrate the utility of exploring naturally occurring differences in visual pigment function in order to better understand the diversity of molecular mechanisms involved in visual pigment function.

1.8 Thesis overview

To contribute to the developing knowledge of visual pigment protein function and visual adaptations, this thesis investigates the evolution of visual pigment structure and function and is composed of the following 3 studies:

1. Short wavelength sensitive opsin (SWS1) as a new marker for vertebrate phylogenetics. Most genetic studies must begin with an evolutionary perspective. In chapter 2 I present an investigation into the molecular evolution of the SWS1 gene across vertebrates, which addresses the correspondence between the SWS1 gene phylogeny and the consensus of major vertebrate lineages.

This chapter has been published: van Hazel, I., Santini, F., Müller, J., Chang, B.S.W. (2006) Short-wavelength sensitive opsin (SWS1) as a new marker for vertebrate phylogenetics. BMC Evol Biol. 6, 97. This was co-written by Chang and myself with text from Santini & Müller

2. Bowerbird opsins and the evolution of spectral sensitivity in short-wavelength-sensitive (SWS1) visual pigments in passerines and their ancestors. The short wavelength sensitive type pigments (SWS1) are of particular interest due to the broad spectral range among vertebrates and the existence of UV signals in animal communication. Avian orders with known UV sensitivity are passerines and parrots, but sequence data suggests a complex evolutionary pattern. Chapter 3 describes an investigation into the evolution of wavelength sensitivity in passerine birds, with particular emphasis on characterizing the SWS1 pigments of C. nuchalis. To explore the evolutionary origins of UV vision in passerines and parrots ancestral character states are inferred using ancestral sequence reconstruction and site directed mutagenesis. Spectral tuning mutants are created in the C. nuchalis SWS1 to explore mechanisms of wavelength regulation in passerine SWS1 pigments. Also, a smaller dataset of full-length avian genes is used to investigate the pattern of evolution in avian SWS1 genes.

19 3. Characterization of the RH1 of the great bowerbird (Chlamydera nuchalis): effects of D83N and A292S on retinal release. In RH1 photopigments, amino acid substitutions D83N and A292S are thought to be adaptations to living in dim light as they change wavelength sensitivity and photointermediate kinetics in ways that could significantly alter the photoresponse. Chapter 4 describes the detailed characterization of the C. nuchalis RH1 that

was found to contain the D83N substitution. This RH1 showed a slightly blue shifted λmax and a slow retinal release compared to chicken and bovine RH1. Site directed mutagenesis methods are used to investigate N83 as the molecular mechanism responsible for the slow retinal release. Results are discussed in context of previous biochemical studies on site 83, well known to be important to RH1 function.

It is intended that the studies presented in this thesis will illustrate methods to study the structure, function, and evolution of visual pigments. Also, a description of some of the naturally occurring mutations in the opsins of birds shows how they influence visual pigment properties in ways that can alter visual perception. In doing so, this thesis highlights the benefit of characterizing the natural variation in vertebrates to reveal and explain the intricacy of visual pigment function. Overall, this thesis represents a significant contribution to the disciplines of visual pigment function and visual ecology.

20 1.9 Tables

Table 1. Parameters in Site models: to detect positive selection that affects individual sites. Model p Parameters LRT Citations M0 (One ratio) 1 One ω ratio for all sites Nielsen and Yang, 1998; Yang et al., 2000; 2005 M1a (Neutral) 2 p0 (p1 =1–p0), ω0 < 1, ω1 =1

M2a (Selection) 4 p0, p1 (p2 =1–p0 –p1), ω0 < 1, ω1 =1, ω2 > 1 M1a*

M3 (Discrete) 5 p0, p1 (p2 =1–p0 –p1), ω0 , ω1, ω2 M0* M7 (Beta) 2 p, q

M8 (Beta&ω) 4 p0, (p1 =1–p0), p, q, ω1 >1 M8* NOTE – p; number of free parameters in the ω distribution; p, proportion of sites; ω, non- synonymous/synonymous substitution rate ratio (dN/dS). * Can calculate posterior probabilities for site classes if the LRT suggests presence of codons under positive selection.

Table 2. Parameters in Branch-Site Model A: to detect positive selection that affects only a few sites on pre-specified lineages.

Site class Proportion Background Foreground Citations 0: Purifying p0 0< ω0 < 1 0< ω0 < 1 Yang et al., 2005; Zhang et al., 2005 1: Neutral p1 ω1 = 1 ω1 = 1 2a: Divergent A (1-p0-p1)- p0/(p0+p1) 0< ω0 < 1 ω2 ≥ 1 2b: Divergent B (1-p0-p1)- p1/(p0+p1) ω1 = 1 ω2 ≥ 1

NOTE –This model is compared to a null where ω2 is constrained (ω2 = 1) on the foreground branch; p, proportion of sites; ω, non-synonymous/synonymous substitution rate ratio (dN/dS). * Can calculate posterior probabilities for site classes if the LRT suggests presence of codons under positive selection on the foreground branch.

Table 3. Parameters in Clade models: to detect positive selection that affects entire clades.

0: Purifying 1: Neutral 2: Divergent ω p ω p ω p LRT Citations CmC 0< ω0 < 1 p0 ω1 = 1 p1 ω2, ω3 > 0 1 - p0 - p1 M1a/ M2a_rel Bielawski and M1a 0< ω0 < 1 p0 ω1 = 1 1-p0 – – Yang 2004

M2a_rel 0< ω0 < 1 p0 ω1 = 1 p1 ω2 (ω3) > 0 1 - p0 - p1 Weadick and Chang 2011 NOTE – p, proportion of sites; ω, non-synonymous/synonymous substitution rate ratio (dN/dS).

21 1.10 Figures

Figure 1. Crystal structure model of dark state bovine rod photopigment. The rod photopigment is a 7 helical transmembrane molecule. The two figures are related by a 90º rotation along the vertical axis. Water molecules found inside the protein are visualized as blue spheres. In both figures, two amphipathic molecules shown are to indicate the approximate range of the transmembrane domain. The 11-cis-retinal chromophore is covalently attached to K293 on H6, and is within the transmembrane helix bundle (PDB IUI9; Okada et al., 2004).

22 Figure 2. Two isoforms of retinal: 11-cis, and all-trans. Isomerization of the retinal chromophore is facilitated by electron delocalization aided by the proton of the Schiff base formed between

Lys296 of the opsin and the retinal chromophore. The exception is in pigments with λmax values <385 nm, where Schiff base link is deprotonated.

11 12

11 hυ 12 NH+

K296 + NH 11-cis retinal K296 11 K N 296 12 H+

11 K N 296 12 H+

all-trans retinal

23 Figure 3. Hydrolysis of the Schiff base linkage generates opsin and free all-trans retinal. After isomerization the retinal is attached to K296 in all-trans conformation (1). The unprotonated Schiff base is attacked by water catalyzed by the primary counterion (E113) to form a protonated carbinolamine intermediate (2). Removal of a proton by the acidic counterion produces an unstable intermediate (3) that decays to release all-trans-retinal (4), which can then dissociate from the protein (adapted from Chen et al., 2012; Cooper et al., 1987).

E113 E113

COOH COO- 1 K296 K All-trans N All-trans N 296 H+

2 H2O E E113 113

- COOH COO O- OH 3 K K296 All-trans N 296 All-trans N H + H H + H2 2

E113 4 Opsin E 113 COO- K Release + 296 COO- H3N + K296 All-trans O H3N +

All-trans O

24 Figure 4. Vertebrate visual pigments respond to light and recover through a number of intermediate steps. In visual pigments (R), the chromophore isomerizes, which activates the rhodopsin (R*), leading to activation of the G-protein (G*) and the transduction cascade. The R* is deactivated by phosphorylation (P) by rhodopsin kinase (RK) and arrestin binding (Arr). The all-trans chromophore dissociates from the opsin and is enzymatically reconverted to its 11-cis conformation in retinal pigment cells (RPC) or Müller cells (MC) for rods and cones, respectively. The 11-cis chromophore is then transported back to the photoreceptor cell where it is incorporated into a free opsin molecule forming the inactive dark state visual pigment. The rate-limiting step in this process is unclear. Some suggest it is associated with the properties of the binding pocket in the opsin, which is loose in cone photopigments (Ala-Laruila et al., 2004). Others suggest it is restricted by the rate at which free 11-cis retinal is transported back into the photoreceptor cell (Lamb & Pugh, 2004).

25 Figure 5. The photoreaction of rhodopsin. Upon absorption of light, 11-cis retinal chromophore isomerizes to the all-trans state and the visual pigment relaxes thermally through a series of spectrally defined intermediates to the active metarhodopsin II (MII) state, which binds and activates the G-protein, transducin. The three photointermediates Metarhodopsin I, MII, and MIII exist in equilibrium where isomerization occurs thermally or induced by specific wavelengths of light. Both MII and MIII can decay to opsin + retinal. In vitro, the former photointermediate decays in minutes, while the latter decays in hours. Neither has similar rates as those measured in vivo, demonstrating the important role of the molecular shut-off mechanism in the cell (adapted from Smith, 2010; Bartl et al., 2007).

26 Figure 6. (Following page) Photoreceptor activation and deactivation occurs through a cascade of molecular events. A) Activation occurs after absorption of a photon of light by the visual pigment chromophore. Activated rhodopsin (R*) catalyzes GDP -> GTP exchange on transducin. Activated transducins (G*) bind inhibitory γ subunits of phosphodiesterase (PDE), allowing it to catalyze cGMP hydrolysis. The reduction of cytoplasmic cGMP leads to closing of cyclic nucleotide gated channels, which blocks the influx of Na+ and Ca2+ and reduces the circulating electrical current causing hyperpolarization of the cell. Recovery of the photoreceptor cell is induced by low intracellular Ca2+ concentration. B) Low Ca2+ levels induce the binding of rhodopsin kinase (RK) to rhodopsin, catalyzing phosphorylation of serine (S) and threonine (T) residues on the C terminus of the photopigment. Phosphorylated rhodopsin is then bound by arrestin (Arr) blocking the G-protein binding site. The complex then loses its all-trans retinal. C) G*PDE is shut down by RGS9, which is normally inhibited by Ca2+. Finally Restoration of cGMP is restored by guanylyl cyclase (GC), also inhibited by Ca2+. cGMP leads to the opening of ion channels that restores cytoplasmic Ca2+, thereby turning off GC, RGS9 and RK (Lamb and Pugh, 2006; Chen, 2005; Burns and Baylor, 2001).

27

28 Figure 7. Range of SWS1 λmax values in vertebrates. The diversity of vertebrate SWS1 λmax values displayed within the UV/visible spectrum. λmax values reviewed in Davies et al., (2012) and Hunt et al., (2009).

29 References

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40 Chapter 2 Short-wavelength sensitive opsin (SWS1) as a new marker for vertebrate phylogenetics

2 Abstract

Vertebrate SWS1 visual pigments mediate visual transduction in response to light at short wavelengths. Due to their importance in vision, SWS1 genes have been isolated from a surprisingly wide range of vertebrates, including lampreys, teleosts, amphibians, reptiles, birds, and mammals. The SWS1 genes exhibit many of the characteristics of genes typically targeted for phylogenetic analyses. This study investigates both the utility of SWS1 as a marker for inferring vertebrate phylogenetic relationships, and the characteristics of the gene that contribute to its phylogenetic utility. Phylogenetic analyses of vertebrate SWS1 genes produced topologies that were remarkably congruent with generally accepted hypotheses of vertebrate evolution at both higher and lower taxonomic levels. The few exceptions were generally associated with areas of poor taxonomic sampling, or relationships that have been difficult to resolve using other molecular markers. The SWS1 data set was characterized by a substantial amount of among-site rate variation, and a relatively unskewed substitution rate matrix, even when the data were partitioned into different codon sites and individual taxonomic groups. Although there were nucleotide biases in some groups at third positions, these biases were not convergent across different taxonomic groups. Our results suggest that SWS1 may be a good marker for vertebrate phylogenetics due to the variable yet consistent patterns of sequence evolution exhibited across fairly wide taxonomic groups. This may result from constraints imposed by the functional role of SWS1 pigments in visual transduction.

2.1 Authors' contributions

IVH, JM and BC conceived of the study, assembled and refined the data set. IVH and FS carried out phylogenetic analyses. IVH carried out statistical analyses of sequence data. BC and IVH drafted the manuscript, with help from JM and FS. BC guided the analyses, and was involved in all aspects of the work. All authors were responsible for interpretation of results in an evolutionary context as well as read and approved the final version of the manuscript.

41 2.2 Introduction

Opsins, or visual pigments, form the first step in the visual transduction cascade in the photoreceptor cells of the retina. By means of a covalently-bound retinal chromophore, opsins are able to respond to light by changing conformation, which activates a second messenger G- protein, and triggers a biochemical cascade that eventually results in a neural signal to the brain that light has been perceived (Menon et al., 2001). Opsins are a member of the extremely large superfamily of integral membrane G-protein coupled receptors (GPCRs), with thousands of genes present in the human genome alone (Filipek et al., 2003). This family is involved in a diverse array of physiological functions in vertebrates, including neurotransmission, learning, memory, and various endocrine and hormonal pathways. All of its members are thought to share the same tertiary structure, mechanisms of activation, and activation of G proteins, even if the downstream effectors of the G proteins may differ. Despite the vast array of functions mediated by this family of receptors, the highly conserved seven helical transmembrane structure of GPCRs as a whole (particularly the Class A type, of which opsins are a member) has ensured that insertions and deletions remain rare, particularly in transmembrane regions.

Visual pigments can vary widely in their wavelength of maximal absorption, ranging from the ultraviolet to the red. The molecular basis of spectral sensitivity depends on interactions between amino acids within the binding pocket of an opsin protein and its associated light-sensitive chromophore. Any variation in the amino acid sequence of a given opsin can, therefore, directly influence the spectral wavelengths an organism can detect. Phylogenetically, visual pigments are divided into 5 groups, roughly reflecting their function in vision, such as whether they are active during the day (cone opsins) or at night (rod opsins), and the spectral tuning of the wavelengths at which they are maximally sensitive (Chang et al., 1995; Okano et al., 1992; Yokoyama and Yokoyama, 1996): red/green or long-wavelength sensitive cone opsins (LWS; approx. 500–570 nm), rod-like or medium-wavelength sensitive cone opsins (RH2; approx. 465–520 nm), ultraviolet/violet or short-wavelength sensitive type 1 cone opsins (SWS1; approx. 360–430 nm), blue or short-wavelength sensitive type 2 cone opsins (SWS2; approx. 430–460 nm), and the rod opsins active at low light levels (RH1; approx. 500 nm). The SWS1 opsins are the shortest wavelength sensitive opsins, and are generally expressed in a particular type of cone photoreceptor found throughout vertebrates that is characterized by an extremely short outer segment (Walls, 1942), though exceptions do exist (Lukats et al., 2002). Only a few types of

42 vertebrates, such as those living in extreme low light environments (subterranean or deep sea habitats) are thought to lack this type of cone. For example, pseudogenes have been identified in the blind Ehrenberg's mole rat (David-Gray et al., 2002), as well in the bottle-nosed dolphin (Fasick et al., 1998) and a number of whales (Levenson and Dizon, 2002). Similarly, organisms with primarily nocturnal behaviours may also lack the SWS1 opsin; such as the owl monkey and the bushbaby (Jacobs et al., 1996).

Perhaps due to the highly conserved nature of its role in vertebrate vision, the SWS1 opsin (hereafter SWS1) occurs as a single copy nuclear gene in almost all animals investigated thus far. However, despite the fundamental importance of this gene for vision at short wavelengths, SWS1 exhibits considerable sequence variation across the diversity of vertebrates that have been investigated. This variation may be a product of SWS1 functional diversity, as measured by absorption sensitivities (Hunt et al., 2004; Vorobyev et al., 1998; Yokoyama, 2000), which in visual pigments have often been found to be optimized to specific visual environments (Bowmaker et al., 1994; Spady et al., 2005; Yokoyama and Yokoyama, 1996). To investigate the molecular evolution of SWS1, we conducted phylogenetic analyses of the gene using available vertebrate sequences. SWS1 genes have been cloned from a considerable variety of vertebrates, ranging from the lamprey to mammals. Surprisingly, we found that this single gene appears to reconstruct many of the commonly accepted relationships among vertebrates (Figure 1), for both deeper and more recent divergences. Indeed, SWS1 results were comparable to those obtained from more exhaustive analyses using multi-gene data sets (e.g. Hedges, 1994). Here, we present a comprehensive phylogenetic analysis of vertebrate SWS1 sequences. We then investigate the characteristics of this gene that contribute to its evident success as a phylogenetic marker across a broad taxonomic range.

2.3 Methods 2.4 Sequence alignment

Sixty-two vertebrate SWS1 opsin nucleotide and amino acid sequences were retrieved from GenBank, with accession numbers for all sequences used in the analyses presented here provided in Table 3. SWS1 coding sequences range in length from 1005 (salmonids) to 1056 (pig) nucleotides, with very few indels (only 6 indels in complete coding sequences in the entire alignment; see Table 3 and Additional file 1). All SWS1 opsin genes identified so far have four

43 introns at highly conserved homologous positions (located at amino acid positions 120, 176, 231, and 311 in the macaque sequence (Onishi et al., 2002)). The first two introns are generally short, ranging in length from 70–76 bp in fish (Dimidiochromis compressiceps), to 283–324 bp in mammals (Macaca fascicularis); whereas the second two introns tend to be longer (120–143 bp in D. compressiceps, 627–979 bp in M. fascicularis) (Carleton et al., 2000; Onishi et al., 2002). Only one copy of SWS1 has been found in all taxa investigated so far, with the exception of the smelt (Plecoglossus altivelis), which may be due to a unique duplication specific to this lineage of fish (Minamoto and Shimizu, 2005). Only one smelt sequence was included in our analyses, as investigations including the second sequence showed it to be strongly monophyletic with the first, and had no other effect on the phylogeny (results not shown).

Sampling within the vertebrate groups was as follows: one lamprey (Geotria australis), 17 actinopterygians (all of which were teleosts); four lissamphibians (referred to in the text as amphibians); 13 birds; three squamates; and 23 mammals (Table 3). The amino acid sequences were aligned using Clustal X (Thompson et al., 1997), Additional file 1). This amino acid alignment was then used to produce an equivalently aligned nucleotide sequence alignment.

2.4.1 Phylogenetic analyses

Phylogenetic analyses were performed using PAUP*v4b10 (Swofford, 1993) for the maximum parsimony (MP) and likelihood (ML) methods, and MrBayes version 3.1 (Huelsenbeck and Ronquist, 2001) for the Bayesian analyses. For the MP analysis all characters were assigned equal weight. Heuristic searches, with random addition of taxa and TBR branch swapping, were performed with 10000 random-addition sequences. A strict consensus tree was calculated from the equally most parsimonious trees found. To assess support for internal branches, bootstrap analyses (Felsenstein, 1985) of 1000 replicates with 10 random-addition sequences for each replicate, were performed.

ModelTest (Posada and Crandall, 1998) was used to perform a series of nested likelihood ratio tests in order to determine which nucleotide model of those tested best fit the data. This model was then used in subsequent model-based phylogenetic analyses such as likelihood and Bayesian analyses. Heuristic ML analyses were conducted with TBR branch swapping (10 random addition replicates), as well as bootstrap analyses with 100 replicates in order to assess the robustness of the clades recovered (Felsenstein, 1985). The Bayesian analyses were run for two

44 million generations with default priors, sampling the chains every 100 generations. To ensure that our analyses were not trapped in local optima, four independent Markov Chain Monte Carlo (MCMC) runs were performed (with default heating values). Stationarity was assumed when the cumulative posterior probabilities of all clades stabilized. The first 5000 trees were considered 'burn-in' and discarded, and the remaining trees were saved. The associated Bayesian posterior probabilities were calculated from the sample points after the MCMC algorithm started to converge.

2.4.2 Nucleotide composition and substitution frequencies

Parameters such as base frequencies, substitution rate frequencies, among site rate variation (α), and invariant sites (I) were all estimated on the ML phylogeny using maximum likelihood methods under the GTR+I+Γ model (Rodriguez et al., 1990; Yang, 1994a; Yang, 1994b) as implemented in PAUP*. Chi-squared tests of base compositional homogeneity were also implemented in PAUP* (Swofford, 1993). Since estimates of invariant sites (I) can be problematic, particularly in reduced data partitions due to insufficient data (Sullivan et al., 1999), the number of invariant sites was therefore also calculated by simple counts of the observed number of constant sites in our data set, as implemented in MEGA3 (Kumar et al., 2004).

2.5 Results 2.5.1 Phylogenetic analyses

Sixty-two vertebrate SWS1 opsin nucleotide coding sequences were obtained from GenBank, aligned using Clustal X (Thompson et al., 1997), and analyzed using a variety of phylogenetic methods including maximum parsimony (Fitch, 1971; Lake, 1987), maximum likelihood (Felsenstein, 1981; Kishino et al., 1990), and Bayesian methods (Yang and Rannala, 1997). A series of nested likelihood ratio tests were performed using ModelTest (Posada and Crandall, 1998) in order to determine which nucleotide model of those tested best fit the data. Of the nucleotide models commonly implemented for phylogenetic analysis, the general time-reversible model incorporating parameters for invariant sites, as well as among-site rate heterogeneity (GTR+I+Γ) (Rodriguez et al., 1990; Yang, 1994a; Yang, 1994b)was found to fit the data significantly better than any simpler model. This model was therefore used in subsequent likelihood and Bayesian phylogenetic analyses. Assessing confidence in nodes of the phylogeny was accomplished by bootstrap analysis (Felsenstein, 1985) or Bayesian posterior probabilities 45 (Yang and Rannala, 1997). The results of the phylogenetic analyses are shown in Figure 2, with the bootstrap values of the maximum parsimony (MP), maximum likelihood (ML) and posterior probabilities of the Bayesian analyses mapped onto the MP tree.

In all analyses, the reconstructed clades were remarkably similar to currently accepted vertebrate relationships based on morphological and molecular analyses (Figure 1). Among the available sequences, however, there are quite a few groups not represented in our dataset, such as cartilaginous fish, monotremes, turtles, crocodiles and snakes. The lack of adequate sampling is particularly evident in the non-tetrapod vertebrates, with the only sequences available being some of the more recently derived ray-finned fish lineages. However, on the basis of the taxa available, the vertebrate clade is divided into two major groups: actinopterygians (ray-finned fishes), and tetrapods. The latter clade is further divided into modern amphibians (frogs and salamanders), mammals, and reptiles (birds+squamates). This is in surprisingly good agreement with the generally accepted relationships among the major vertebrate lineages according to molecular and morphological data as summarized in Figure 1 (Cloutier and Arratia, 2004; Ericson and Johansson, 2003; Garcia-Moreno et al., 2002; Inoue et al., 2003; Meyer and Zardoya, 2003; Muller and Reisz, 2005; Murphy et al., 2001; Phillips and Penny, 2003; Takezaki et al., 2004).

Within the ray-finned fishes, our trees support the basal position of ostariophysans (carp, goldfish, and zebrafish), followed by the neoteleosts, salmonids, and smelt, a situation congruent with morphological (Lauder, 1983), mitochondrial (Inoue et al., 2003) and nuclear data (Zaragueta-Bagils et al., 2002). Between the latter three clades, however, the relationships remain debated: in some morphological studies salmonids and smelts form a clade (Johnson et al., 1996), whereas in other investigations salmonids group with the neoteleosts (Lauder, 1983). A monophyly of smelts and neoteleosts has also been proposed (Begle, 1991; 1992), and has since received support from molecular analyses (Inoue et al., 2003; Miya et al., 2003). Our analyses are in agreement with the foremost hypothesis, having salmonids and smelts as a monophyletic sister group to neoteleosts.

In our analyses, there is only weak support for the monophyletic grouping of modern amphibians (30% MP bootstrap, 24% ML bootstrap, 0.66 Bayesian posterior probability). The paraphyly of amphibians has been suggested by Carroll (1995) using morphological and paleontological data;

46 by contrast, most research, including the remaining paleontological studies and all molecular analyses, disagree with this hypothesis and maintain the monophyly of modern amphibians (Zhang et al., 2005; Soch et al., 2004). It should be mentioned, however, that only four amphibian sequences were available for this study, which might be the reason for the lack of resolution in our results.

Within birds, our results confirm the chicken as basal and sister to the Neoaves (all other birds), with the passerines (Passerida) as monophyletic and most derived, a result congruent with recent molecular studies (Garcia-Moreno et al., 2002; Sibley and Ahlquist, 1990). Previous studies by Sibley and Ahlquist (1990) using DNA-DNA hybridization, which since has been supported by nuclear and mitochondrial sequence data (Alstrom et al., 2006; Ericson and Johansson, 2003), divided Passerida into three major clades: Muscicapoidea (represented in our phylogeny by the bluethroat and Siberian rubythroat), Sylvoidea (tits), and Passeroidea (finch and bishops); patterns of these relationships were identified in all our reconstructed phylogenies.

Among mammals, marsupials are found to be the basal lineage within Mammalia, followed by the monophyletic groupings of rodents (minus the guinea pig), laurasiatherians, afrotherians, and higher primates; these relationships are all well supported by recent research [see (Springer et al., 2004) for review]. Moreover, the more recent divergences within these mammalian clades also resemble the results found by other investigations. For example, all three phylogenies show apes and Old World monkeys to be monophyletic, forming the catarrhines, with the New World monkeys, or platyrrhines, as a sister group, which together form the higher primates. Although their positions are unresolved in the MP consensus tree, there is some support for the prosimians (the lemur and tarsier) as the most basally positioned primates in the bootstrap (57% ML, 48% MP) and Bayesian analyses (0.9 posterior probability). Our results correspond not only with molecular phylogenies constructed using nuclear (Goodman et al., 1998) as well as mitochondrial (Raaum et al., 2005) datasets, but also with morphological data (Benton, 2005).

2.5.2 Patterns of sequence variation in the SWS1 data set

Given the utility of SWS1 for elucidating vertebrate evolutionary relationships across a range of divergences, we explored patterns of sequence variation in our data set by estimating parameters such as base composition, among-site rate heterogeneity, and informative sites using parsimony

47 and likelihood phylogenetic methods, and then compared them to those published for other molecular phylogenetic data sets.

The aligned SWS1 nucleotide dataset consisted of 1083 characters, of which 686 (63%) were parsimony informative. The proportion of invariant sites in our data set was estimated in two ways: (1) by calculating the observed number of invariant sites in our alignment, and (2) by estimating the number of sites likely to be invariant under a particular model of evolution (Table 1). Within vertebrates, there were a relatively small proportion of sites estimated as invariant (I = 0.17). Within the data partitions corresponding to the major vertebrate groups, ML estimates do not exceed 0.34. SWS1 tended to have similar proportions of invariant sites as other nuclear markers commonly used for phylogenetic purposes, as estimated using ML methods, for example RAG1 (0.34, squamates (Townsend et al., 2004), 0.36, amphibians (van der Meijden et al., 2005), 0.40, rodents (Steppan et al., 2004)) or RAG2 (0.24, frogs (van der Meijden et al., 2005)). While it is generally assumed that a lower proportion of invariable sites might be indicative of greater phylogenetic information in the data set, this parameter is often difficult to estimate accurately (Steel and Penny, 2000; Sullivan et al., 1999).

The parameter (α) describing the shape of the Γ-distribution used to account for among-site rate heterogeneity was estimated for the SWS1 data set using likelihood methods to be approximately 1.0 (Table 1). This suggests a fairly even distribution of different substitution rates across sites. Other nuclear genes widely used in phylogenetic analyses tend to have α estimates of at least 1. For example, RAG1 ranges from 1.0 in amphibians (van der Meijden et al., 2005) to 1.7 in squamates (Townsend et al., 2004). When α is equal to 1, substitution rates are exponentially distributed, which is intermediate between the bell-shaped curves at higher values (α > 1) and 'L' shaped functions at lower values (α < 1). This exponential shape suggests that there is a more evenly distributed range of substitution rates across sites than would be the case for higher or lower α values. It has been suggested that higher values of α might be better in aiding phylogenetic resolution (Yang, 1998). But, a more even range of slow to fast evolving sites may be best for phylogenetic analyses because it incorporates both slow sites to carry a signal from deeper divergences, as well as fast sites for more recent divergences. Past studies, based on both empirical data (Sullivan et al., 1995) and simulations (Bininda-Emonds and Sanderson, 2001; Yang, 1998) have suggested that large amounts of among-site rate variation (as indicated by low

48 values of α) such as those often found in some mitochondrial data sets, might tend to adversely affect phylogenetic signal.

Furthermore, the variability observed in SWS1 does not appear to be concentrated on third base positions only, as is often the case in many genes; relative to other molecular markers a great deal of variation is found at first and second positions as well. First, although about 92% of third codon positions were parsimony informative, the proportion of informative sites present in first and second codon positions was 55% and 41%, respectively. Second, estimates of invariant sites (I) were generally low across all three codon positions (Table 1), though the proportion of invariant sites was lowest at third positions, as expected. Third, relatively high α values were also found for first (0.84) and second codon positions (0.65), though highest at third positions (4.7).

Most protein-coding data sets show higher α values (and lower I values) at third codon positions compared to first and second positions (Page and Holmes 1998). However, the values of α at first and second codon positions in the SWS1 data set were comparatively high. For example, under a similar model of evolution (GTR+I+Γ), Dettai and Lecointre (Dettai and Lecointre, 2005) estimated α values of 0.29 for both codon positions in a portion of the MLL gene in fish, as compared with 0.42 and 0.41 for first and second positions in fish SWS1 genes. This would suggest that variation in substitution rates tends to be more evenly distributed across codon positions in the SWS1 data set, and that more sites in the gene are phylogenetically informative.

Maximum likelihood estimates of substitution rate parameters in the SWS1 data set under the GTR+I+Γ model did not exhibit substantial skew when estimated across vertebrates, with values ranging only from about 1.0 to 3.3 (Table 1). This range of values is smaller than many other data sets, including cyt b in birds (0.5 to 8.8 (Garcia-Moreno et al., 2002)), RAG1 in squamates (1.0 to 7.6 (Vidal and Hedges, 2005)), and RAG1 in amphibians (1.0 to 5.7 (van der Meijden et al., 2005)). A skewed rate matrix may decrease the number of states a given site can have, resulting in increased homoplasy and potential loss of phylogenetic information. Although this has yet to be investigated in detail in many data sets, a recent comparison of mitochondrial and nuclear genes in insects (Lin and Danforth, 2004) found that nuclear genes tended to have more homogeneous patterns of among-site rate variation (i.e., larger α values), as well as more symmetrical transformation rate matrices, and that these patterns appeared to be associated with phylogenetic utility in their data sets.

49 Furthermore, substitution rate matrices were estimated in different data partitions of the SWS1 data set corresponding to the different vertebrate groups and/or codon position (Table 1). Overall, the rate matrices remain relatively homogeneous and unskewed across different partitions of the data set, although there were certain partitions exhibiting differences in particular rate parameters. For example, there is some variation in substitution rates between C and G in reptiles, as compared with fish and mammals (3.3, 0.1, and 0.73 respectively), and across vertebrates at second codon positions, as compared with first and third positions (7.3, 0.7, and 0.6 respectively). Also, fish generally tend to have higher substitution rates relative to other vertebrate groups at second codon positions (Table 1).

Base composition was estimated using likelihood methods under the GTR+I+Γ model for the complete data set, as well as within partitions of the data corresponding to individual codon positions, and the major vertebrate groups (Table 2). Base compositional biases can be problematic in phylogenetic analyses, particularly if there is convergence in bias across unrelated groups (Chang and Campbell, 2000; Mooers and Holmes, 2000; Steel et al., 1993). The SWS1 data set does not appear to be affected in this manner. Despite a significantly heterogeneous base compositional bias overall (chi-square test of homogeneity p < 0.001, df = 183; Table 2), in the different data partitions, corresponding to the major vertebrate groups and/or codon position, the base frequencies are generally found to be homogeneously distributed throughout the data set, except in tetrapods and in third positions of many vertebrate groups (Table 2). Second positions showed a slightly increased frequency of T, but this was also found to be homogeneous across the data set (Table 2). The high frequency of T at second codon positions is also seen in genes such as rod opsin and cyt b, and presumably reflects a strong functional constraint in genes coding for transmembrane proteins, which contain many hydrophobic amino acids such as Ile (ATY), Phe (TYY) and, Leu (YTR) (Chen et al., 2003; Naylor et al., 1995).

In summary, molecular patterns in the vertebrate SWS1 data suggest a substantial amount of variation across the three codon positions, as well as high among-site rate variation throughout the gene. As well, the substitution rates tend to be fairly homogeneous among the different classes. Although there is some bias in nucleotide composition across different codon positions, this bias appears to be non-convergent.

50 2.6 Discussion

Despite the ever-increasing number of gene sequences available in the databases, it remains surprisingly difficult to select genes that will be useful for phylogenetic analyses, particularly across a variety of taxonomic ranges. Known issues in molecular phylogenetics such as model mis-specification, gene paralogs and alignment ambiguities often contribute to misleading results (Sanderson and Shaffer, 2002), and accounting for effects such as among-site rate heterogeneity can substantially alter results. For example, early analyses of mtDNA data tended to place the root of the avian phylogeny within passerines (Haring et al., 2001; Harlid and Arnason, 1999; Harlid et al., 1998; Mindell et al., 1999), a result in strong conflict with prior phylogenetic studies (Sibley and Ahlquist, 1990). Further analysis of mitochondrial data that accounted for unequal evolutionary rates among sites, however, recovered the traditional division of birds between palaeognathans and neognathans, with passerines being a phylogenetically derived neognath lineage (Paton et al., 2002). Similarly, correcting for base compositional bias in a mammalian data set of full mitochondrial genomes increased support for marsupials as the sister group of placentals (Phillips and Penny, 2003), as opposed to the original analysis, which supported a marsupial - monotreme grouping (Janke et al., 2002). Many characteristics have been identified as problematic; however, we know little about exactly what characteristics make a strong molecular marker. For example, in insects, comparisons of nucleotide substitution patterns and phylogenetic utility between nuclear ribosomal and protein coding genes (Danforth et al., 2005) as well as between nuclear and mitochondrial genes (Lin and Danforth, 2004) identified a number of features as useful for phylogenetic analyses, including larger values of α (parameter for among-site rate heterogeneity), and relatively unskewed substitution rate parameters. However, such studies remain relatively rare in the literature.

Mitochondrial genes have been widely used in molecular systematics due to the relative ease with which mitochondrial genes, or even whole genomes can be amplified and sequenced, as well as the absence of problematic features often associated with nuclear markers such as introns, heterozygosity, and paralogy. Mitochondrial genes can, however, suffer from some marked disadvantages. In most cases mitochondrial genes are thought to evolve much faster than nuclear genes (Brown et al., 1979, but see Monteiro and Pierce, 2001), and they may be subject to significant rate accelerations and decelerations in evolutionary history (Vawter and Brown, 1986), possibly due to changes in factors such as metabolic rate (Martin and Palumbi, 1993).

51 Such rate differences can easily lead to positively misleading topological effects (Felsenstein, 1978), and may be particularly problematic in resolving deeper relationships or rapid radiations such as those found within mammals (Springer et al., 2001). Furthermore, mitochondrial data sets can often be biased in terms of base composition, which has been found to contribute to misleading signal in a number of data sets including basal vertebrates (Chang and Campbell, 2000; Naylor and Brown, 1998), birds (Paton et al., 2002) and mammals (Lin et al., 2002; Phillips and Penny, 2003; Schmitz et al., 2002). However, their faster rate of evolution in comparison to nuclear genes can be useful for resolving more recent relationships (Lin and Danforth, 2004).

Recent years have shown a dramatic increase in the number of nuclear genes that have been developed for vertebrate phylogenetics in order to complement and expand the set of useful phylogenetic markers (Cotton and Page, 2002; Takezaki and Gojobori, 1999; Zardoya and Meyer, 2001). Some nuclear genes have been used with success in multiple vertebrate groups ranging from fish to mammals, for example RAG1 and 2 (Brinkmann et al., 2004; Groth and Barrowclough, 1999; Lovejoy and Collette, 2001), c-mos (Garcia-Moreno et al., 2002; Vidal and Hedges, 2005), c-myc (Ericson and Johansson, 2003; Steppan et al., 2004), MLL (Dettai and Lecointre, 2005; Zaragueta-Bagils et al., 2002), and 18S (Hedges et al., 1990; Xia et al., 2003). A host of other nuclear genes have been used primarily in particular vertebrate groups, such as rod opsin in ray-finned fish (Chen et al., 2003; Dettai and Lecointre, 2005), and more recently amphibians (Hoegg et al., 2004; van der Meijden et al., 2005); β-fibrinogen introns in birds (Edwards et al., 2005), and a variety of genes aimed at resolving higher level mammalian phylogenetics: IRBP, α2B adrenergic receptor, aquaporin, β-basein, γ-fibrinogen, κ-casein, protamine, and von Willebrand Factor (Springer et al., 2001).

Despite the success of nuclear markers in resolving some of the longstanding problems in vertebrate phylogenetics (Meyer and Zardoya, 2003; Springer et al., 2004), several issues continue to plague many molecular data sets. First, alignment issues, though long recognized as problematic, often tend to be overlooked in many data sets. Some sequences, particularly ribosomal genes such as 18S, are known to be difficult to align properly (Hickson et al., 2000), and these alignment ambiguities can significantly affect phylogeny reconstruction (Lee, 2001; Xia et al., 2003). However, these problems can easily be avoided by careful selection of molecular markers that are unambiguously alignable. Second, and even more importantly, some 52 of the important assumptions currently incorporated into commonly used phylogenetic methods may not be reasonable for many molecular data sets. For instance, most molecular models of evolution assume that state frequencies, and even more importantly, substitution rate frequencies do not change over evolutionary time, assumptions incorporated in likelihood/Bayesian methods which tend to model molecular evolution as stationary, homogeneous Markov processes (Felsenstein 2004).

Even though nuclear data sets tend to suffer fewer problems than mitochondrial genes with respect to base compositional changes across a phylogeny, there are examples of nuclear data sets for which nonstationarity can yield positively misleading results, if there is convergence in base compositional bias (Phillips et al., 2004; Tarrio et al., 2001), or worse yet, codon bias (Chang and Campbell, 2000; Harris, 2003) among lineages. The use of phylogenetic methods that have been developed to take into account nonstationarity in base frequencies using either distance (Lake, 1994; Steel et al., 1993) or likelihood approaches (Galtier and Gouy, 1995) can at least somewhat ameliorate these effects, though not for codon bias issues (Chang and Campbell, 2000; Harris, 2003).

More recently, the use of genome-based approaches has enabled more extensive investigations of sources of systematic bias, or inconsistency in phylogenetic analyses [(Delsuc et al., 2005; Jeffroy et al., 2006; Philippe et al., 2005a; Phillips et al., 2004) and identified new effects difficult to detect in smaller data sets, such as site-specific changes in evolutionary rates among lineages, or heterotachy (Baele et al., 2006; Lopez et al., 2002; Misof et al., 2002). However, these issues are only just being addressed, and the robustness of current phylogenetic models to such violations explored (Kolaczkowski and Thornton, 2004; Lockhart et al., 2006; Philippe et al., 2005b; Steel, 2005; Thornton and Kolaczkowski, 2005). Similarly, the issue of changes in substitution rate frequencies across a phylogeny, or nonhomogeneity, has received relatively little attention, though it has been recognized as a potential problem [(Galtier and Gouy, 1998; Herbeck et al., 2005; Lake, 1994; Steel et al., 1993). Accounting for such effects in more complex models of evolution may be useful for genomic scale analyses, but it is not clear how much power such parameter-rich models may have for relatively small data sets. Selecting genes less susceptible to these effects would tend to obviate the necessity of implementing more complex models, and therefore tend to increase the statistical power of likelihood and Bayesian phylogenetic methods. 53 With regard to some of the issues plaguing many molecular data sets, SWS1 visual pigment genes offer several clear advantages. First, this gene has very few indels in its evolution across vertebrates, making for a largely unambiguous alignment, and it is a single copy nuclear gene with no paralogs of high sequence similarity. Second, for the vertebrate SWS1 data set, base frequencies were found to be fairly constant across the phylogeny. There was little evidence of base compositional heterogeneity; aside from third codon positions in fish, reptiles, and tetrapods. Third, the SWS1 data set exhibits a relatively unskewed distribution of substitution rate frequencies among the different types of substitutions, and a substantial amount of among site rate variation, both of which are characteristics that previous studies suggest might be important for phylogenetic utility (Danforth et al., 2005; Lin and Danforth, 2004; Yang, 1998). Fourth, the substitution rate frequencies are not only unskewed, they are also relatively constant across the phylogeny, indicative of a homogeneous substitution process, which may be important in not attenuating phylogenetic signal across fairly large divergences.

Why does the SWS1 visual pigment gene exhibit useful phylogenetic characteristics across such a wide range of divergences in vertebrates? Factors important in contributing to its utility as a phylogenetic marker may be due, at least in part, to the highly conserved, yet somewhat variable nature of its functional role in visual transduction. The fundamental role of SWS1 genes in mediating visual sensitivities at the shortest wavelengths of the spectrum is highly conserved throughout vertebrates, along with its expression in a specific photoreceptor cell in the retina characterized by extremely short outer segments (Hisatomi et al., 1998; Loew and Lythgoe, 1978; Sillman et al., 1997). Unlike many other genes used for systematic purposes, which are often housekeeping genes which tend to be expressed ubiquitously in many different cell types, or developmental genes that may be expressed in a different tissues mediating a variety of functions, SWS1 genes are generally only expressed in a particular photoreceptor cell type, though they have been found in rare instances to be co-expressed in other types of photoreceptors with longer wavelength-sensitive opsin genes, for example in the mouse (Rohlich et al., 1994), guinea pig (Lukats et al., 2002), and tiger salamander (Makino and Dodd, 1996). Its overall tertiary 3D structure has remained unchanged, most likely due to constraints imposed by its role as an integral membrane protein, and the mechanisms of activation which require specific structural rotations of the helices which are thought to be conserved in many G-protein coupled receptors (Strader et al., 1994). This conserved role in evolution may be important for

54 maintaining homogeneous molecular evolutionary processes such as substitution rate frequencies across vertebrate evolution.

Along with its highly conserved role as the first step in visual transduction, vertebrate SWS1 visual pigments are well-understood examples of functional variation in spectral sensitivity: SWS1 pigments can range in maximal absorption from the ultraviolet to violet (see Hunt et al., 2004; Hunt et al., 2001, for reviews. However, these shifts in function are thought to be mediated via a few specific residues in the protein (see Hunt et al., 2004). Despite the obvious constraints on protein structure, and adaptive changes in function such as spectral sensitivities, these factors may have only limited influence in restricting protein sequence evolution, as SWS1 clearly shows a substantial amount of evolutionary variation capable of carrying phylogenetic information. In fact, the constraints imposed by SWS1 structure and function may provide a framework in which the protein can vary in a more homogeneous fashion that allows for the retention of a strong phylogenetic signal.

2.7 Conclusion

The various phylogenetic methods used to analyze SWS1 produced strongly supported topologies showing remarkable congruence with most traditionally accepted hypotheses of vertebrate evolution from the consensus of morphological and molecular studies. This nuclear, protein coding gene recovers not only deep relationships, usually requiring combinations of genes, but also recent relationships that typically require markers with high rates of evolution, such as mitochondrial DNA. The few exceptions include the monophyly of the primates, the relationships among the major groups of placental mammals, and the position of the guinea pig, which remain inconclusive in many data sets.

The phylogenetic utility of the SWS1 gene may result from a number of features of the SWS1 gene found to be important in previous studies, including substantial among site rate variation. Its ability to carry a phylogenetic signal across a broad range of divergences in vertebrates may also be due to a number of features, such as fairly homogeneous substitution rate matrix parameters, which are potentially important but largely unexplored for other phylogenetic markers. Future studies will explore these characteristics in data sets of other nuclear markers, in order to assess how well they correlate with phylogenetic utility.

55 2.8 Tables

Table 1. Substitution frequencies and rate heterogeneity parameters

A↔C A↔G A↔T C↔G C↔Ta αb I (ML)c Id All sites Fish 0.778 2.419 1.328 0.984 3.192 1.203 0.262 0.412 Reptiles 1.081 4.598 0.907 3.330 2.516 0.392 0.000 0.611 Mammals 1.322 4.876 0.838 0.727 4.672 1.473 0.345 0.530 Tetrapods 1.091 4.120 0.969 1.431 3.341 1.029 0.244 0.367 Vertebrates 0.987 3.326 1.084 1.298 3.115 1.014 0.166 0.263

Codon #1 Fish 2.338 2.645 1.434 0.793 2.877 0.422 0.000 0.334 Reptiles 2.383 2.148 0.777 0.579 1.313 0.312 0.000 0.629 Mammals 2.504 4.097 0.739 0.828 3.515 1.445 0.447 0.646 Tetrapods 2.051 2.781 0.935 0.602 1.891 0.780 0.212 0.457 Vertebrates 2.188 2.473 1.008 0.741 2.256 0.837 0.122 0.319

Codon #2 Fish 5.561 9.417 3.878 23.904 10.450 0.411 0.000 0.629 Reptiles 0.411 7.219 0.549 5.696 3.547 1.936 0.666 0.806 Mammals 1.654 11.198 2.489 6.140 7.073 0.364 0.298 0.747 Tetrapods 1.727 8.563 1.226 6.564 4.313 0.403 0.119 0.593 Vertebrates 2.435 7.089 1.480 7.343 4.679 0.647 0.108 0.435

Codon #3 Fish 0.454 2.419 1.878 0.286 3.282 3.877 0.013 0.103 Reptiles 0.377 4.589 0.000 0.431 4.089 1.002 0.000 0.343 Mammals 0.985 5.023 0.810 0.194 4.248 2.907 0.000 0.197 Tetrapods 0.623 4.283 0.973 0.679 3.599 3.058 0.028 0.050 Vertebrates 0.521 3.386 1.169 0.622 3.027 4.665 0.032 0.036 a Parameters are reversible and measured against the G↔T parameter with a value of 1 b Shape parameter for the gamma distribution. c Proportion of invariant sites estimated using maximum likelihood methods d Proportion of invariant sites calculated from raw alignment data using MEGA3 (Kumar et al., 2004)

56 Table 2. Base composition and χ2 tests of homogeneity

A C G T Avg # bps χ2 df p All sites Fish 0.214 0.290 0.249 0.247 1008 40.53 48 0.770 Reptiles 0.165 0.344 0.263 0.228 932.7 18.77 45 1.000 Mammals 0.191 0.293 0.246 0.271 1029 36.98 69 0.999 Tetrapods 0.197 0.315 0.242 0.246 995.4 419.3 129 <<0.001 Vertebrates 0.210 0.306 0.239 0.245 999.6 613.4 183 <<0.001

Codon #1 Fish 0.266 0.160 0.289 0.286 336.0 7.590 48 1.000 Reptiles 0.235 0.198 0.295 0.271 310.9 8.498 45 1.000 Mammals 0.242 0.205 0.282 0.272 342.9 12.94 69 1.000 Tetrapods 0.260 0.198 0.279 0.263 331.8 37.29 129 1.000 Vertebrates 0.281 0.171 0.279 0.269 333.2 97.57 183 1.000

Codon #2 Fish 0.230 0.262 0.163 0.345 336.0 3.147 48 1.000 Reptiles 0.220 0.244 0.184 0.352 310.9 10.32 45 1.000 Mammals 0.221 0.235 0.184 0.359 342.9 5.601 69 1.000 Tetrapods 0.222 0.244 0.179 0.356 331.8 18.94 129 1.000 Vertebrates 0.224 0.250 0.176 0.349 333.2 76.50 183 1.000

Codon #3 Fish 0.143 0.392 0.280 0.186 336.6 84.81 48 0.001 Reptiles 0.050 0.588 0.311 0.051 310.8 92.56 45 <<0.001 Mammals 0.118 0.416 0.266 0.200 342.9 66.27 69 0.571 Tetrapods 0.129 0.454 0.253 0.164 331.7 1363.3 129 <<0.001 Vertebrates 0.143 0.432 0.245 0.179 333.1 1678.6 183 <<0.001

57 Table 3. Accession numbers and species identification for taxa in SWS1 data set Class (order) Common Name Scientific name Accession # Actinopterygii Cyprinodontiformes killifish Lucania goodei AY296735 Perciformes Malawi eye-biter Dimidiochromis compressiceps AF191220 Fuelleborn’s cichlid Labeotropheus fuelleborni AF191223 zebra mbuna Metriaclima zebra AF191219 Nile tilapia Oreochromis niloticus AF191221 Pleuronectiformes Atlantic halibut Hippoglossus hippoglossus AF156264 Cypriniformes goldfish Carassius auratus D85863 carp Cyprinus carpio AB113669 zebrafish Danio rerio AB087810 Osmeriformes smelt Plecoglossus altivelis AB098706 Salmoniformes pink salmon Oncorhynchus gorbuscha AY214153 chum salmon Oncorhynchus keta AY214143 coho salmon Oncorhynchus kisutch AY214148 rainbow trout Oncorhynchus mykiss AF425074 sockeye salmon Oncorhynchus nerka AY214158 chinook salmon Oncorhynchus tshawytscha AY214138 Atlantic salmon Salmo salar AY214133 Amphibia Anura African clawed frog Xenopus laevis BC084882 American bullfrog Rana catesbeiana AB001983 Caudata tiger salamander Ambystoma tigrinum AF038948 firebelly newt Cynops pyrrhogaster AB052889 Aves Galliformes chicken Gallus gallus NM_205438 Ciconiiformes Humboldts penguin Spheniscus humboldti AJ277991 Columbiformes pigeon Columba livia AJ238856 Psittaciformes budgerigar Melopsittacus undulatus Y11787 Passeriformes common canary Serinus canaria AJ277922 Siberian rubythroat Luscinia calliope AY274226 bluethroat Luscinia svecica AY274225 blue tit Parus caeruleus AY274220 great tit Parus major AY274221 marsh tit Parus palustris AY274222 yellow crowned bishop Euplectes afer AY274223 red bishop Euplectes orix AY274224 zebra finch Taenopygia guttata AF222331 Mammalia Artiodactyla cow Bos taurus U92557 pig Sus scrofa NM_214090 Carnivora dog Canis familiaris XM_539386 Primates white-tufted-ear marmoset Callithrix jacchus L76201 mantled howler monkey Alouatta palliata AH005790 weeping capuchin monkey Cebus olivaceus AH005810 Bolivian squirrel monkey Saimiri boliviensis U53875 crab-eating macaque Macaca fascicularis AF158977 talapoin Miopithecus talapoin L76226 gorilla Gorilla gorilla AH005811 human Homo sapiens AH003620 chimpanzee Pan troglodytes AH005813 brown lemur Eulemur fulvus AB111464 western tarsier Tarsius bancanus AB111463 Proboscidea African elephant Loxodonta africana AY686753

58 Rodentia guinea pig Cavia porcellus AY552608 Djungarian hamster Phodopus sungorus AY029604 house mouse Mus musculus AH005191 Norway rat Rattus norvegicus AF051163 Sirenia Caribbean manatee Trichechus manatus AY228443 Dasyuromorpha dunnart Sminthopsis crassicaudata AY442173 Peramelemorpha short nosed bandicoot Isoodon obesulus AY726544 Diprotodontia tammar wallaby Macropus eugenii AY286017 quokka Setonix brachyurus AY726545 Squamata tokay gecko Gekko gecko AY024356 day gecko Phelsuma madagascariensis AF074045 green anole Anolis carolinensis AH007736 Cephalaspidomorphi Petromyzontiformes pouched lamprey Geotria australis AY366495

59 2.9 Figures

Figure 1. Summary of vertebrate evolutionary relationships, based on morphological and molecular data. Colours indicate taxonomic groups represented in the SWS1 data set.

60 Figure 2. Maximum parsimony phylogeny. Strict consensus of 432 equally most parsimonious trees. (Length = 3965, CI = 0.35, RI = 0.75) found in a heuristic search with 10,000 replicates. Bootstrap percentages above 50% for MP analyses (1000 replicates), followed by those for ML analyses under the GTR+I+Γ model (100 replicates) are indicated above the nodes. Dashes represent less than 50% bootstrap support. An asterix denotes a posterior probability of ε0.95 in the Bayesian analysis. Colours correspond to vertebrate groups as indicated in Figure 1.

61

2.10 Supplementary data 2.10.1 Supplementary figures

Figure S1. Amino acid alignment of vertebrate SWS1 opsin sequences

#NEXUS [Title: Vert SWS1 protein] begin characters; dimensions nchar= 361; format missing=? gap=- matchchar=. datatype=protein interleave; matrix

[!Domain=Data;]

AY366495Gaus -----MSGDE EFYLFKNISK VGPWDGPQF- HIAPKWAFYL QAAFMGFVFI CGTPLNAIVL VVTIKYKKLR QPLNYILVNI L._chalumnae -----MLREE DFYLFSKISS VGLWDGLQY- HIAPIWAFYL QAVFMGFMFF VGTLLNAIVL IVTLKYNKL* QPLNYILLNI L._menadoensis ------FSKNSS VGLWDGLQY- HIAPIWAFYL QAVFMGFMFF VGTLLNAIVL IVTLKYNKL* QPLNYILLNI D85863Caurat ------MDA WTYQFGNLSK ISPFEGPQY- HLAPKWAFYL QAAFMGFVFF VGTPLNAIVL FVTMKYKKLR QPLNYILVNI AB113669Ccar ------MDA WTYQFGNLSK VSPFEGPQY- HLAPKWAFYL QAAFMGFVFL VGTPMNAIVL FVTMKYKKLR QPLNYILVNI AF191220Dcom ------GK HFHLYENISK ISPFEGPQY- YLAPVWAFYL QAAFMGFVFF AGTPLNFIVL VATMKYKKLR VPLNFILVNI AB087810Drer ------MDA WAVQFGNASK VSPFEGEQY- HIAPKWAFYL QAAFMGFVFI VGTPMNGIVL FVTMKYKKLR QPLNYILVNI BC067683Drer ------MDA WAVQFGNASK VSPFEGEQY- HIAPKWAFYL QAAFMGFVFI VGTPMNGIVL FVTMKYKKLR QPLNYILVNI BC060894Drer ------MDA WAVQFGNASK VSPFEGEQY- HIAPKWAFYL QAAFMGFVFI VGTPMNGIVL FVTMKYKKLR QPLNYILVNI NM131319Drer ------MDA WAVQFGNASK VSPFEGEQY- HIAPKWAFYL QAAFMGFVFI VGTPMNGIVL FVTMKYKKLR QPLNYILVNI AF156264Hhip ------MMGK HFHLYENVSN VSPFDGPQY- YLAPQWAFHL QTIFMGSVLF AGTPLNFIVL LVTLKYKKLR VPLNYILVNI AF191223Lfue ------MGK HFHLYENISK ISPFEGPQY- YLAPVWAFYL QAAFMGFVFF AGTPLNFIVL VATMKYKKLR VPLNFILVNI AY296735Lgoo ------MGK HFHLYENISK VDPFEGPQY- YLAPSWAFHL QALFMGFVFF TGTPLNFLVL LATAKYKKLR APLNYILVNI AF191219Mzeb ------MGK HFHLYENISK ISPFEGPQY- YLAPVWAFYL QAAFMGFVFF AGTPLNFIVL VATMKYKKLR VPLNFILVNI AY214153Ogor ------MGK DFHLYENISK VSPFEGPQY- HLAPKWAFYL QTAFMGFVFF AGTPLNFIIL LVTVKYKKLR QPLNYILVDV AY214143Oket ------MGK DFHLYENISK VSPFEGPQY- HLAPIWAFYL QTAFMGFVFF AGTPLNFIIL VVTVKYKKLR QPLNYILVNV AY214148Okis ------MGK NFHLYENISK VSPFEGPQY- HLAPIWAFYL QTAFMGFVFF AGTPLNLIIL VVTVKYKKLR QPLNYILVNV AF425074Omyk ------MGK DFHLYENISK VSPFEGPQY- HLAPIWAFYL QTAFMGFVFF AGTPLNFIIL VVTVKYKKLR QPLNYILVNV AY214158Oner ------MGK DFHLYENISK VSPFEGPQY- HLAPIWAFYL QTAFMGFVFF AGTPLNFIIL VVTVKYKKLR QPLNYILVNV AF191221Onil ------MGK YFHLYENISK VSPFEGPQY- YLAPTWAFYL QAAFMGFVLF AGTPLNFVVL VATMKYKKLR VPLNFILVNI AY214138Otsh ------MGK DFHLYENISK VSPFGGPQY- HLAPIWAFYL QTAFMGFVFF AGTPLNFIIL VETVKYKKLR QPLNYILVNV AB098706Palt ------MGK QFHLYENVSK IGPFEGPQY- YLAPVWVFYL QAAFMGFVFF VGTPLNFVIL MVTIKYKKLR QPLNYILVNI AB098705Palt ------MGK VFYLYENISK ISPFEGPQY- HLAPLWAFYL QAAFMGTVFF VGTPLNFVVL LVTVKYKKLR QPLNYILVNI AY214133Ssal ------MGK DFHLYENISK ISPFEGPQY- HLASMWAFYL QAAFMGFVFF AGTPLNFIIL VVTVKYKKLR QPLNFILVNI AH005790Apal --MSKMSEEE EFYLFKNISS VGPWDGPQY- HIAPVWAFYL QAAFMGIVFL AGLPLNAMVL VATVRYRKLR HPLNYVLVNV U92557Btau --MSKMSEEE EFLLFKNISL VGPWDGPQY- HLAPVWAFHL QAVFMGFVFF VGTPLNATVL VATLRYRKLR QPLNYILVNV XM539386Cfam --MSKMSGEE EFYLFKNISL VGPWDGPQY- HIAPVWAFHL QAVFMGFVFF AGTPLNGTVL VATLRYKKLR QPLNYILVNV L76201Cjac --MSKMSEEE EFYLFKNISS VGPWDGPQYP HIAPSWAYYL QAAFMGIVFL IGLPLNTMVL VATVRYKKLR HPLNYVLVNV AH005810Coli --MSKMSEEE EFYLFKNISS VGPWDGPQY- HIAPVWAFYL QAAFMGIVFL VGLPLNAMVL VATVRYKKLR HPLNYVLVNV AY552608Cpor -----MSEEE EFYLFKNASS VGPWDGPQY- HVAPVWAFRL QAAFMGIVFC IGTPLNGIVL VATLLYKKLR QPLNYILVNV AB111464Eful --MCKMSGEE EFYLFKNLSP VGPWDGPQY- HIAPVWAFYL QAAFMGLVFF AGAPLNVMVL VATLRYKKLR QPLNYILVNL 62

AH005811Ggor ---MRKMSEE EFYLFKNISP VGPWDGPQY- HIAPVWAFYL QAAFMGTVFL IGFPLNAMVL VATLRYKKLR QPLNYILVNV AF545497Hamp --MSKMSEEE EFLLFKNISL VGPWDGPQY- HLAPVWAFHL QAAFMGFVFF AGTPLNATVL VATLRYRKLR QPLNYILVNV AH003620Hsap ---MRKMSEE EFYLFKNISS VGPWDGPQY- HIAPVWAFYL QAAFMGTVFL IGFPLNAMVL VATLRYKKLR QPLNYILVNV AY726544Iobe -----MSGDE EFYLFKNISS VGPWDGPQY- HIAPAWAFHC QTVFMGFVFF AGTPLNAVVL IATLRYKKLR QPLNYILVNI AY686753Lafr -MIKMSGEEE EFYLFKNISS VGPWGGPQY- HIGPVWAFHL QAAFMAFVFF VGTPLNALVL VATLRYRKLR QPLNYILVNI AY286017Meug -----MSGDE EFYLFKNISS VGPWDGPQY- HIAPAWAFHC QTVFMGFVFF AGTPLNAVVL IATFRYKKLR QPLNYILVNI AF158977Mfas --MRKMSEEE EFYLFKNLSS VKPWDGPQY- HIAPVWAFYL QAAFMGTVFL AGFPLNAMVL VATVRYKKLR QPLNYILVNV AH005191Mmus -----MSGED DFYLFQNISS VGPWDGPQY- HLAPVWAFRL QAAFMGFVFF VGTPLNAIVL VATLHYKKLR QPLNYILVNV L76226Mtal --MRKMSEEE EFYLFKNISS VKPWDGPQY- HIPPVWAYYL QAAFMGTVFL AGFPLNAMVL VATVRYKKLR QPLNYILVNV AY092006Ppyg ------AY029604Psun ------VFF AGVPLNATVL VATLRYKKLR QPLNYILVNI AH005813Ptro ---MRKMSEE EFYLFKNISS VGPWDGPQY- HIAPVWAFYL QAAFMGTVFL IGFPLNAMVL VATLRYKKLR QPLNYILVNV U36972Rnor -----MSGE? EFYLFQNISS VGPWDGPQY- HIAPVWAFHL QAAFMGFVFF AGTPLNATVL VATLHYKKLR QPLNYILVNV U53875Sboliv --MSKMPEEE EFYLFKNISS VGPWDGPQY- HIAPVWAFQL QAAFMGIVFL AGLPLNSMVL VATVRYKKLR HPLNYVLVNV AY726545Sbra -----MSGDE EFYLFKNISS VGPWDGPQY- HIAPAWAFHC QTVFMGFVFF AGTPLN?VVL IATFRYKKLR QPLNYILVNI AY442173Scra -----MSGDE EFYLFKNISL VGPWDGPQY- HLAPAWAFHF QTAFMGFVFF AGTSLNGVVL IATLRYKKLR QPLNYILVNI NM214090Sscr MSKMPEEEEE EFLLFKNISL VGPWDGPQY- HLAPVWVFHL QAAFMGFVFL VGTPLNATVL VATLRYRKLR QPLNYILVNV AB111463Tban -----MSEEE EFYLFKNISS VGPWDGPQH- HLAPVWVFHL QAAFMGVVFS VGIPLNTMVL VATLRYRKLR QPLNYILVNV AH007736Acar -----MSGQE DFYLFENISS VGPWDGPQY- HIAPMWAFYF QTAFMGFVFF AGTPLNAIIL IVTVKYKKLR QPLNYILVNI AY024356Ggec -----MSGEE DFYLYANISS VGPFDGPQY- HIAPMWAFYF QTAFMGFVFF VGTPLNAIIL FAIVKYKKLR QPLNYILVNI AF074045Pmad -----MSGEE DFYLFTNISS VGPFDGPQY- HIAPMWAFYI QTAFMGFVFF AGTPLNGIIL IAIVKYKKLR QPLNYILVNI AH007798Cliv -----MSGDE EFYLFKNGSS VGPWDGPQY- HIAPPWAFYL QTAFMGFVFL VGTPFNAIVL VVTIKYKKLR QPLNYILVNI AJ238856Cliv -----MSGDE EFYLFKNGSS VGPWDGPQY- HIAPPWAFYL QTAFMGFVFL VGTPFNAIVL VVTIKYKKLR QPLNYILVNI AY274223Eafe ------AFYL QTIFMGLVFV AGTPLNAIVL IVTIKYKKLR QPLNYILVNI AY274224Eori ------AFYL QTIFMGLVFV AGTPLNAIVL IVTIKYKKLR QPLNYILVNI NM205438Ggal -----MSSDD DFYLFTNGSV PGPWDGPQY- HIAPPWAFYL QTAFMGIVFA VGTPLNAVVL WVTVRYKRLR QPLNYILVNI AY274226Lcal ------FYL QTIFMGLVLV AGTPLNAIVL IVTVKYKKLR QPLNYILVNI AY274225Lsve ------?FYL QTIFMGLVLV AGTPLNAIVL IVTVKYKKLR QPLNYILVNI Y11787Mundul -----MSGEE EFYLFKNGSI GGPWDGPQY- HIAPPWAFYL QTAFMGFVFM VGTPLNAIVL VVTIKYKKLR QPLNYILVNI AY274220Pcae ------WAFYL QTIFMGLVFV AGTPLNAIVL IVTIKYKKLR QPLNYILVNI AY274221Pmaj ------AFYL QTIFMGLVFV AGTPLNAIVL IVTIKYKKLR QPLNYILVNI AY274222Ppal ------AFYL QTIFMGLVFV AGTPLNAIVL IVTIKYKKLR QPLNYILVNI AJ277991Shum ------PWDGPQY- HIAPPWAFYL QTAFMGFVFL VGTPFNAVVL VVTVKYKKLR QPLNYILVNI AJ277922Scan ------MDEE EFYLFKNQSS VGPWDGPQY- HIAPMWAFYL QTIFMGLVFV AGTPLNAIVL IVTVKYKKLR QPLNYILVNI AF222331Tgut ------MDEE EFYLFKNQSS VGPWDGPQY- HIAPMWAFYL QTIFMGLVFV AGTPLNAIVL IVTIKYKKLR QPLNYILVNI AF038948Atig -----MLEEE EFYLYKNISK VGPWDGPQY- HIAPAWTFYF QTAFMGFVFF VGTPLNAIVL IVTVKYKKLR QPLNYILVNV AB052889Cpyr -----MVGDD DFYLFKNISK VGPWDGPQY- HIAPAWTFYF QTAFMGFVFF VGTPLNAIVL IVTVKYKKLR QPLNYILVNV AB001983Rcat -----MLGDE DFYLFKNVSD IRPWDGPQY- HIAPRWAFTL QAIFMGVVFI IGTPLNAVVL LVTVKYKKLR QPLNYILVNI BC084882Xlae -----MLEEE DFYLFKNVSN VSPFDGPQY- HIAPKWAFTL QAIFMGMVFL IGTPLNFIVL LVTIKYKKLR QPLNYILVNI AY228443Tman --MSKMSEEE EFYLFKNISS VGPWDGPQY- HIAPVWAFRL QAAFMGFVFF AGTPLNAMVL VATLRYRKLR QPLNYILVNI AY099455Maur -----MSGEE EFYLFRNISS VGPWDGPQY- HIAPAWAFRL QAAFMGFVFF AGTPLNATVL VATLHYKKLR QPLNYILVNV AY099455Nehr -----MSGEE DFYLFQNASS VGPWDGPQY- LIAPVWALHL QAAFIGFVFF AGTPLNATVL VATLHYKKLR QPLNYILVNV AF055458Ttru --MRKMSEEE EF?LFKNI-L VGPWDGPQY- RLAPVWGFHL HAAFTGFVFL VWRALDATVL VATLRYRKLR QPLNYILVNV AF545491Bmys --MSKMSEEE EFFLFKNISL VGPWDGPQY- HLTPVWVFHL QAAFTGFVFF VGTPLSATVL VARLRYRKLQ QPLNYILVNV AY366495Gaus SAAGLVFCLF SISTVFVASM QGYFFLGPTI CALEAFFGSL AGLVTG-WSL AFLAAERYIV ICKPFGNFRF GSKHALVAVG

L._chalumnae SLAGFIVCLF ?IFTVFIFSS RGYFIFGRAV CAIESFLGSM ----TG?SSL ATLAFERDIV ICKPFSNFCF GSKQSLLAVG L._menadoensis SLAGFIVCLF ?IFTVFIFSS RGYFIFGRAV CAIE?------SSL ATLAFERDIV ICKPFSNFCF GSKQSRLAVG 63

D85863Caurat SLGGFIFDTF SVSQVFFSAL RGYYFFGYTL CAMEAAMGSI AGLVTG-WSL AVLAFERYVV ICKPFGSFKF GQSQALGAVA AB113669Ccar SLGGFIFDTF SVSQVFFSAL RGYFFFGHTM CAMESAMGSI AGLVTG-WSL AVLAFERYVV ICKPFGSFKF GQGQAMGAVA AF191220Dcom SFSGFIFVTF SVSQVFLASM RGYYFLGHTL CALESAVGSV AGLVTA-WSL AVLSFERYLV ICKPFGAFKF GSNHALAAVA AB087810Drer SLAGFIFDTF SVSQVFVCAA RGYYFLGYTL CAMEAAMGSI AGLVTG-WSL AVLAFERYVV ICKPFGSFKF GQGQAVGAVV BC067683Drer SLAGFIFDTF SVSQVFVCAA RGYYFLGYTL CAMEAAMGSI AGLVTG-WSL AVLAFERYVV ICKPFGSFKF GQGQAVGAVV BC060894Drer SLAGFIFDTF SVSQVFVCAA RGYYFLGYTL CAMEAAMGSI AGLVTG-WSL AVLAFERYVV ICKPFGSFKF GQGQAVGAVV NM131319Drer SLAGFIFDTF SVSQVSVCAA RGYYSLGYTL CSMEAAMGSI AGLVTG-WSL AVLAFERYVV ICKPFGSFKF GQGQAVGAVV AF156264Hhip CFAGLIFVVF SVSQVFVSTM RGYFFLGPTL CALESAMGSI AGLVTS-WSL AVLSLERYLV ICKPFGAFRF GSNHAAGAVA AF191223Lfue SFSGFIFVTF SVSQVFLASM RGYYFLGHTL CALESAVGSV AGLVTA-WSL AVLSFERYLV ICKPFGAFKF GSNHALAAVA AY296735Lgoo SFAGFIFVTF SVSQVFVSSA RGYYFLGYTL CALEAAMGAV AGLVTS-WSL AVLSFERYLV ICKPFGAFKF GSSHAAGAVV AF191219Mzeb SFSGFIFVTF SVSQVFLASM RGYYFLGHTL CALESAVGSV AGLVTA-WSL AVLSFERYLV ICKPFGAFKF GSNHALAAVA AY214153Ogor SLAGFIFVTF SVSQVFVSSA RGYYFLGYTL CAMEACMGSI AGLVSA-WSL AVLAFERYVV ICKPFGTFKF DNNQALAAVG AY214143Oket SLAGFIFVTF SVSQVFVSSA RGYYFLGYTL CAMEACMGSI AGLVSA-WSL AVLAFERYVV ICKPFGTFKF DNNQALAAVG AY214148Okis SLAGFIFVTF SVSQVFVSSA GGYYFLGYTL CAMEACMGSI AGLVSA-WSL AVLAFERYVV ICKPFGTFKF DNNQALAAVG AF425074Omyk SLAGFIFVTF SVSQVFVSSA RGYYFLGYTL CAMEACMGSI AGLVSA-WSL AVLAFERYVV ICKPFGTFKF DNNQALAAVG AY214158Oner SLAGFIFVTF SVSQVFVSSA RGYYFLGYTL CAMEACMGSI AGLVSA-WSL AVLAFERYLV ICKPFGTFKF DNNQALAAVG AF191221Onil SFSGFIFVTF SVSQVFLASM RGYYFLGHTL CALEAAVGAI AGLVTA-WSL AVLSFERYLV ICKPFGAFKF GSNHALAAVA AY214138Otsh SLAGFIFVTF SVSQVFVSSA RGYYFLGYTL CAMEACMGSI AGLVSA-WSL AVLAFERYVV ICKPFGTFKF DNNQALAAVG AB098706Palt SVGGFIFAVF SVSQVFVASL RGYYFLGYTL CAMEACMGSI AGLVTG-WSL AVLAFERYVV ICKPFGQFKF GNTQALMAVG AB098705Palt SFAGFLALIF SVFQVFLAST RGFFFMGHMA CSIETWIGSV AGLVTG-WSL AVLAFERYVV ICKPFGQFKF GSSQAASAVA AY214133Ssal SLAGFIFVTF SVSQVFVSSA RGYYFLGYTL CAMEACMGSI AGLVSA-WSL AVLAFERYVV ICKPFGTFKF DNNQALAAVA AH005790Apal SVGGFLLCIF SVFPVFVASC HGYFVFGRHV CALEGFLGTV AGLVTG-WSL AFLAFERYIV ICKPFGNFRF SSKHALMVVL U92557Btau SLGGFIYCIF SVFIVFITSC YGYFVFGRHV CALEAFLGCT AGLVTG-WSL AFLAFERYII ICKPFGNFRF SSKHALMVVV XM539386Cfam SLGGFLYCIS VS-TVFIASC QGYFVFGRHV CALEAFLGST AGLVTG-WSL AFLAFERYIV ICKPFGNFRF SSKHALMVVL L76201Cjac SVGGFLLCIF SVFPVFVASC HGYFVFGRHV CALEGFLGTV AGLVTG-WSL AFLAFERYIV ICKPFGNFRF SSKHALMVVL AH005810Coli SVGGFLLCIF SVFPVFVASC HGYFVFGRHV CALEAFLGTV AGLVTG-WSL AFLAFERYIV ICKPFGNFRF SSKHALMVVL AY552608Cpor SLGGFLVCIF SVLAVFIASC YGYFIFGRHV CALEGFLGSV AGMVTG-WSL AFLAFERYLV ICKPFGNFRF SSKHALIVVL AB111464Eful SFGGFLCCIF SVLPVFIASC RGYFLFGRHV CALEGFLGSA AGLVIG-WSL AFLAFERYVI ICKPFGNFRF SSKHALMVVL AH005811Ggor SFGGFLLCIF SVFPVFVASC NGYFVFGRHV CALEGFLGTV AGLVTG-WSL AFLAFERYIV ICKPFGNFRF SSKHALTVVL AF545497Hamp SLGGFIYCIF SVFVVFITSC HGYFVFGRHV CALEAFLGCT AGLVTG-WSL AFLA------AH003620Hsap SFGGFLLCIF SVFPVFVASC NGYFVFGRHV CALEGFLGTV AGLVTG-WSL AFLAFERYIV ICKPFGNFRF SSKHALTVVL AY726544Iobe SLAGFIFCIF SVFTVFISSS QGYFIFGRHV CAMEAFLGSV AGLVTG-WSL AFLAFERFIV ICKPFGNFRF HSKHAMMVVL AY686753Lafr SLGGFLSCIF SVFIVFISSC KGYFIFGRYV CALEAFVGSV AGLVTG-WSL AFLAFERYIV ICKPFGNIRF SSKHALMVVL AY286017Meug SLAGFIYCIF SVFTVFISSS QGYFIFGRHV CAMEGFLGSV AGLVTG-WSL AFLAFERFIV ICKPFGNFRF NSKHSMMVVL AF158977Mfas SFGGFLLCIF SVFPVFVNSC KGYFVFGRHV CAFEAFLGTV AGLVTG-WSL AFLAFERYIV ICKPFGNFRF SSKHALTVVL AH005191Mmus SLGGFLFCIF SVFTVFIASC HGYFLFGRHV CALEAFLGSV AGLVTG-WSL AFLAFERYVV ICKPFGSIRF NSKHALMVVL L76226Mtal SFGGFLLCIF SVFPVFVNSC KGYFVFGRHV CGFEAFLGTV AGLVTG-WSL AFLAFERYIV ICKPFGNFRF SSKHALTVVL AY092006Ppyg ------AY029604Psun SLGGFLFCSF SVFTVFIASC HGYFLFGRHV CALEAFLGSV AGLVTG-WSL AFLAFERYIV ICKPFGNVRF SSKHALIVVL AH005813Ptro SFGGFLLCIF SVFPVFVASC NGYFVFGRHV CALEGFLGTV AGLVTG-WSL AFLAFERYIV ICKPFGNFRF SSKHALTVVL U36972Rnor SLGGFLFCIF SVFTVFIASC HGYFLFGRHV CALEAFLGSV AGLVTG-WSL AFLAFERYLV ICKPFGNIRF NSKHALTVVL U53875Sboliv SVGGFLLCIF SVLPVFVNSC NGYFVFGRHV CALEGFLGTV AGLVTG-WSL AFLAFERYIV ICKPFGNFRF SSKHALMVVL AY726545Sbra SLAGFIYCII SVFTVFISSS QGYFIFGRHV CAMEGFLGSV AGLVTG-WSL AFLAFERFIV ICKPFGNFRF NSKHSMMVVL AY442173Scra SLAGFIFCVF SVFTVFVSSS QGYFVFGRHV CAMEGFLGSV AGLVTG-WSL AFLAFERFIV ICKPFGNFRF NSKHAMMVVL NM214090Sscr SLGGFIYCIF SVFSVFIASC HGYFVFGRRV CAMEAFLGSA AGLVTG-WSL AFLAFERYII ICKPFGNFRF SSKHALIAVL AB111463Tban SLGGFLLCIF SVLPVFIASC RGYFVFGRHV CALEGFLGSV AGLVTG-WSL AFLAFERYMV ICKPFGNFRF SPKHALMVVL AH007736Acar SFAGFLFCTF SVFTVFMASS QGYFFFGRHV CAMEAFLGSV AGLVTG-WSL AFLAFERYIV ICKPFGNFRF NSKHALLVVA AY024356Ggec SAAGFLFCVV AVFTVFISSS QGYFIFGKHI CALEAFLGSL AGLVTG-WSL AFLALERYIV ICKPFGNFRF SAKHASLVVA 64

AF074045Pmad SAAGFLFCTF SVFTVFVSSA QGYFVFGKHI CALEAFLGSL AGLVTG-WSL AFLAMERYIV ICKPFGNFRF NAKHASLVVA AH007798Cliv SFSGFISCIF SVFTVFVSSS QGYFIFGKDM CALEAFVGAT GGLVTG-WSL AFLAFERYIV ICKPFGNFRF NSKHALMAVV AJ238856Cliv SFSGFISCIF SVFTVFVSSS QGYFIFGKDM CALEAFVGAT GGLVTG-WSL AFLAFERYIV ICKPFGNFRF NSKHALMAVV AY274223Eafe SVSGLMCCVF CIFTVFVASS QGYFVFGKHM CAFEGFAGAT GGLVTG-WSL AFLAFERYIV ICKPFGNFRF NSRHALLVVA AY274224Eori SVSGLMCCVF CIFTVFVASS QGYFVFGKHM CAFEGFAGAT GGLVTG-WSL AFLAFERYIV ICKPFGNFRF NSRHALLVVA NM205438Ggal SASGFVSCVL SVFVVFVASA RGYFVFGKRV CELEAFVGTH GGLVTG-WSL AFLAFERYIV ICKPFGNFRF SSRHALLVVV AY274226Lcal SVSGLMCCVF CIFTVFVSSS QGYFVFGKHV CAFEGFSGAT VGLVTG-WSL AFLAFERYIV ICKPFGNFRF NSRHALLVVA AY274225Lsve SVSGLMCCVF CIFTVFVSSS QGYFVFGKHV CAFEGFSGAT VGLVTG-WSL AFLAFERYIV ICKPFGNFRF NSRHALLVVA Y11787Mundul SFCGFLACII CIFTVFVSSS QGYFVFGKHV CAFEGFMGAT AGLVTG-WSL AFLAFERYIV ICKPLGNFRF TAKHALVVVV AY274220Pcae SVSGLMCCVF CIFTVFVSSS QGYFVFGKHM CAFEGFAGAT GGLVTG-WSL AFLAFERYIV ICKPFGNFRF NSRHALLVVA AY274221Pmaj SVSGLMCCVF CIFTVFVSSS QGYFVFGKHM CAFEGFAGAT GGLVTG-WSL AFLAFERYIV ICKPFGNFRF NSRHALLVVA AY274222Ppal SVSGLMCCVF CIFTVFVSSS QGYFVFGKHM CAFEGFAGAT GGLVTG-WSL AFLAFERYIV ICKPFGNFRF NSRHALLVVA AJ277991Shum SFSGFISCIF SVFTVFVSSS QGYFVFGKHM CALEGFVGAT GGLVTG-WSL AFLAFERYIV ICKPFGNFRF SSKHAVMVVV AJ277922Scan SVSGLMCCVF CIFTVFVASS QGYFVFGKHM CRFEGFAGAT GGMVTG-WSL AFLAFERYIV ICKPFGNFRF NSRHALLVVA AF222331Tgut SVSGLMCCVF CIFTVFIASS QGYFVFGKHM CAFEGFAGAT GGLVTG-WSL AFLAFERYIV ICKPFGNFRF NSRHALLVVA AF038948Atig SLAGFTFCIF SVFTVFVSSS QGYFIFGKTI CELEAFLGSV SGLVTG-WSL AFLAIERYIV ICKPMGSFRF SSKHATMVVL AB052889Cpyr SLAGFTFCIF SVFSVFVASS QGYFIFGKFM CEMEAFLGSV SGLVTG-WSL AFLAIERYIV ICKPMGNFRF ASKHALMIVL AB001983Rcat SVGGLLICIF SNFVVFINSW QGYFFFGKAF CAIEAFVGTL AGLVTG-WSL AFLAFERYIV ICKPMGTFTF TSKHALAVVL BC084882Xlae TVGGFLMCIF SIFPVFVSSS QGYFFFGRIA CSIDAFVGTL TGLVTG-WSL AFLAFERYIV ICKPMGNFNF SSSHALAVVI AY228443Tman SLGGFLYCIF SVFIVFITSC HGYFIFGRYV CALEAFLGAT TGLVTG-WSL AFLAFERYIV ICKPFGNIRF SSKHALMVVL AY099455Maur SLGGFLFCSF SVF?VFIASC HGYFLFGRHV CALEAFLGSV A?------AY099455Nehr SLR?FLFCIF SVSTVFIASC HGYFLFGRHV CALEAFLGSV AGLVTG-WSL AFLAFERYIV ICNAFSNFRF SSKHALMVVL AF055458Ttru SLGGFIYCIF SVFVVFITSC HGYFVFGRHV CALGAFLGRT AGLLTG-WSL AFLVFERYII ICKPFGNFRF SSKHALMVVL AF545491Bmys SLGGFIYCIF S?-VVFITSW HEYFVFGCHV CALEAFLGCT AGLVTG-WSL AFLA?------

AY366495Gaus LTWMLGLSVA LPPFFGWSRY IPEGLQCSCG PDWYTVGTKY KSEYYTYFLF VFCFVVPLSI IIFSYGSLLG TLRA--VAAQ L._chalumnae ATWVIGLGAA LPPVFGWSQY IPEGLQCSCG PEWYTVNNKW NNESYVIFLF SFCFGLPLSI IIFSYTKLLM TLHT?*VAKQ L._menadoensis ATWVIGLGAA LPPVFGWSQY IPEGLQCSCG PEWYTVNNKW NNESYVIFLF SFCFGLPLSI IIFSYTKLLM TLHT?*VAKQ D85863Caurat LTWIIGIGCA TPPFWGWSRY IPEGIGTACG PDWYTKNEEY NTESYTYFLL VSCFMMPIMI ITFSYSQLLG ALRA--VAAQ AB113669Ccar LTWVIGIGCA TPPFWGWSRY IPEGLGTSCG PDWYTKNEEY NCESYTYFLM VTCFILPMMI IIFSYSQLLG ALRA--VAAQ AF191220Dcom FTWFMGIGCA CPPFFGWSRY IPEGLGCSCG PDWYTHNEQY NTTSYTHFLM VTCFIIPLSI IIFCYSQLLG ALRA--VAAQ AB087810Drer FTWIIGTACA TPPFFGWSRY IPEGLGTACG PDWYTKSEEY NSESYTYFLL ITCFMMPMTI IIFSYSQLLG ALRA--VAAQ BC067683Drer FTWIIGTACA TPPFFGWSRY IPEGLGTACG PDWYTKSEEY NSESYTYFLL VTCFMMPMTI IIFSYSQLLG ALRA--VASQ BC060894Drer FTWIIGTACA TPPFFGWSRY IPEGLGTACG PDWYTKSEEY NSESYTYFLL VTCFMMPMTI IIFSYSQLLG ALRA--VAAQ NM131319Drer FTWIIGTACA TPPFFGWSRY IPEGLGTACG PDWYTKSEEY NSESYTYFLL ITCFMMPMTI IIFSYSQLLG ALRA--VAAQ AF156264Hhip FTWFMGISCA IPPFFGWSRY IPEGLGCSCG PDWYTHNEEF HCSSYTNFLM VTCFILPLTI IIFSYTQLLS SLRA--VAAQ AF191223Lfue FTWFMGIGCA CPPFFGWSRY IPEGLGCSCG PDWYTHNEQY NTTSYTHFLM VTCFIIPLSI IIFCYSQLLG ALRA--VAAQ AY296735Lgoo FTWFMGVGCS SPPFFGWSRY IPEGLGCSCG PDWYTNDQEL GTTSYMYFLL ITCFCMPLSI IIFSYSQLLG ALRA--VAAQ AF191219Mzeb FTWFMGIGCA CPPFFGWSRY IPEGLGCSCG PDWYTHNEQY NTTSYTHFLM VTCFIIPLSI IIFCYSQLLG ALRA--VAAQ AY214153Ogor FTWVMGIGCA TPPFFGWSRY IPEGLGCSCG PDWYTNNEEY HCASYTKFLI VTCFLMPMSI IFFSYSQLLG ALRA--VAAA AY214143Oket FTWVMGIGCA TPPFFGWSRY IPEGLGCSCG PDWYTNNEEY HCASYTKFLI VTCFLMPMSI IFFSYSQLLG ALRA--VAAA AY214148Okis FTWVMGIGCA TPPFFGWSRY IPEGLGCSCG PDWYTNNEEY HCASYTKFLI VTCFLMPMSI IFFSYSQLLG ALRA--VAAA AF425074Omyk FTWVMGIGCA TPPFFGWSRY IPEGLGCSCG PDWYTNNEEY HCASYTKFLI VTCFLMPMSI IFFSYSQLLG ALRA--VAAA AY214158Oner FTWVMGIGCA TPPFFGWSRY IPEGLGCSCG PDRYTNNEEY HCASYTKFLI VTCFLMPMSI IFFSYSQLLG ALRA--VAAA AF191221Onil FTWFMGVGCA CPPFFGWSRY IPEGLGCSCG PDWYTHNEEY NTTSYIYFLL ITCFIFPLTI IIFCYSQLLG ALRA--VAAQ AY214138Otsh FTWVMGIGCA TPPFFGWSRY IPEGLGCSCG PDWYTNNEEY HCASYTKFLI VTCFLMPMSI IFFSYSQLLG ALRA--VAAA AB098706Palt FTWVMGVGCA TPPFFGWSRY IPEGLGCACG PDWYTHNEEY HCTSYTYFLM VTCFMMPLTI IIFSYSQLLG ALRA--VAAQ AB098705Palt FTWVMGVGCS SPPFFGWSRF IPEGLGCSCG PDWYTHNEEY HCTSYTYFLM ITCFVMPMTV IIFSYAQLLG ALRA--VAAQ 65

AY214133Ssal FTWVMGIGCA TPPFFGWSRY IPEGLGCSCG PDWYTNNEEY HCASYTKFLI VTCFLMPMSI IFFSYSQLLG ALRA--VAAA AH005790Apal TTWTIGIGVS IPPFFGWSRF IAEGLQCSCG PDWYTVGTKY RSEYYTWFLF IFCFIVPLSL ICFSYAQLLR ALKA--VAAQ U92557Btau ATWTIGIGVS IPPFFGWSRF VPEGLQCSCG PDWYTVGTKY YSEYYTWFLF IFCYIVPLSL ICFSYSQLLG ALRA--VAAQ XM539386Cfam ATWTIGIGVS IPPFFGWSRF IPEGLQCSCG PDWYTVGTKY RSEYYTWFLF IFCFIVPLSL ICFSYLQLLR ALRA--VAAQ L76201Cjac TTWTIGIGVS IPPFFGWSRY IAEGLQCSCG PDWYTVGTKY RSEYYTWFLF IFCFIVPLAL ICFSYAQLLR ALKA--VAAQ AH005810Coli TTWTIGIGVS IPPFFGWSRF IAEGLQCSCG PDWYTVGTKY RSEYYTWFLF IFCFIVPLSL ICFSYAQLLR ALKA--VAAH AY552608Cpor ATWVIGIGVS IPPFFGWSRY MPEGLQCSCG PDWYTVGTKY RSEYFAWFLF IFCFIVPLSL ICFSYCQLLR TLRT--VAAQ AB111464Eful ATWTIGVGVS IPPFFGWS-F IPEGLQCSCG PDWYTVGTKY RSEYYTWFLF IFCFIVPLSL ICFSYSQLLR ALRA--VAAQ AH005811Ggor ATWTIGIGVS IPPFFGWSRF IPEGLQCSCG PDWYTVGTKY RSESYTWFLF IFCFIVPLSL ICFSYTQLLR ALKA--VAAQ AF545497Hamp ------AH003620Hsap ATWTIGIGVS IPPFFGWSRF IPEGLQCSCG PDWYTVGTKY RSESYTWFLF IFCFIVPLSL ICFSYTQLLR ALKA--VAAQ AY726544Iobe ATWVIGIGVS IPPFFGWSRF IPEGLQCSCG PDWYTVGTKY RSEYYTWFLF IFCFIIPLSL ICFSYSQLLR ALRT--VAAQ AY686753Lafr ATWTIGIGVS IPPFFGWSRF LPEGLQCSCG PDWYTVGTKY RSEYYTWFLF IFCFIVPLSL ICFSYSQLLG ALRA--VAAQ AY286017Meug ATWVIGIGVS IPPFFGWSRY IPEGLQCSCG PDWYTVGTKY RSEYYTWFLF ILCFIMPLSL ICFSYSQLLG ALRA--VAAQ AF158977Mfas ATWTIGIGVS IPPFFGWSRF IPEGLQCSCG PDWYTVGTKY RSESYTWFLF IFCFIVPLSL ICFSYTQLLR ALKA--VAAQ AH005191Mmus ATWIIGIGVS IPPFFGWSRF IPEGLQCSCG PDWYTVGTKY RSEYYTWFLF IFCFIIPLSL ICFSYSQLLR TLRA--VAAQ L76226Mtal ATWIIGIGVS IPPFFGWSRF IPEGLQCSCG PDWYTVGTKY RSESYTWFLF IFCFIVPLSL ICFSYTQLLR ALKA--VAAQ AY092006Ppyg ------AY029604Psun VTWVIGVGVS IPPFFGWSRF IPEGLQCSCG PDWYTVGTKY RSESYTWFLF LFCFIVPLSL ICFSYSQLLR TLRA--VAAQ AH005813Ptro ATWTIGIGVS IPPFFGWSRF IPEGLQCSCG PDWYTVGTKY RSESYTWFLF IFCFIVPLSL ICFSYTQLLR ALKA--VAAQ U36972Rnor ITWTIGIGVS IPPFFGWSRF IPEGLQCSCG PDWYTVGTKY RSEHYTWFLF IFCFIIPLSL ICFSYFQLLR TLRA--VAAQ U53875Sboliv TTWTIGIGVS IPPFFGWSRY IAEGLQCSCG PDWYTVGTKY RSEYYTWFLF IFCFIVPLSL ICFSYAQLLR ALKA--VAAQ AY726545Sbra ATWVIGIGVS IPPFFGWSRY IPEGLQCSCG PDWYTVGTKY HSEYYTWFLF ILCFIMPLSL ICFSYSQLLG ALRA--VAAQ AY442173Scra ATWIIGIGVS IPPFFGWSRY IPEGLQCSCG PDWYTVGTKY RSEYYTWFLF IFCFIVPLSL ICFSYSQLLG ALRA--VAAQ NM214090Sscr ATWAIGIGVS IPPFFGWSRF LPEGLQCSCG PDWYTVGTKY YSEYYTWFLF IFCYIVPLAL ICFSYSQLLR ALRA--VAAQ AB111463Tban ATWTIGIGVS VPPFFGWSRF IPEGLQCSCG PDWYTVDTKY HSEYYTWFLF IFCFIVPLSL ICFSYAQLLR ALRA--VAAQ AH007736Acar ATWFIGIGVS IPPFFGWSRY IPEGLQCSCG PDWYTVGTKY KSEYYTWFLF IFCFIVPLTL IIFSYSQLLG ALRA--VAAQ AY024356Ggec ATWFIGIGVS IPPYFGWSRF IPEGLQCSCG PDWYTVGTKY YSEYYTWFLF VLCFIVPLSI IVFSYSQLLS ALRA--VAAQ AF074045Pmad ATWVIGIGVS VPPFFGWSRY IPEGLGCSCG PDWYTVGTKY RSEYYTWFLF IFCFMVPLTI IIFSYSQLLS ALRA--VAAQ AH007798Cliv ATWVIGLGVA LPPWFGWSRY VPEGLQCSCG PDWYTVGTKY KSEYYTWFLF IFCFIVPLSL IIFSYSQLLS ALRA--VAAQ AJ238856Cliv ATWVIGLGVA LPPWFGWSRY VPEGLQCSCG PDWYTVGTKY KSEYYTWFLF IFCFIVPLSL IIFSYSQLLS ALRA--VAAQ AY274223Eafe ATWIIGVGVA IPPFFGWSRY IPEGLQCSCG PDWYTVGTKY KSEYYTWFLF IFCFIVPLSL IIFSYSQLLS ALRA--VAAQ AY274224Eori ATWIIGVGVA IPPFFGWSRY IPEGLQCSCG PDWYTVGTKY KSEYYTWFLF IFCFIVPLSL IIFSYSQLLS ALRA--VAAQ NM205438Ggal ATWLIGVGVG LPPFFGWSRY MPEGLQCSCG PDWYTVGTKY RSEYYTWFLF IFCFIVPLSL IIFSYSQLLS ALRA--VAAQ AY274226Lcal ATWIIGVGVA IPPFFGWSRY IPEGLQCSCG PDWYTVGTKY KSEYYTWFLF IFCFIVPLSL IIFSYSQLLS ALRA--VAAQ AY274225Lsve ATWIIGVGVA IPPFFGWSRY IPEGLQCSCG PDWYTVGTKY KSEYYTWFLF IFCFIVPLSL IIFSYSQLLS ALRA--VAAQ Y11787Mundul ATWVIGIGVA IPPFFGWSRY VPEGLQCSCG PDWYTVGTKY RSEYYTWFLF IFCFIVPLSL IIFSYSQLLS ALRA--VAAQ AY274220Pcae ATWIIGVGVA VPPFFGWSRY VPEGLQCSCG PDWYTVGTKY KSEYYTWFLF IFCFIVPLSL IIFSYSQLLS ALRA--VAAQ AY274221Pmaj ATWIIGVGVA VPPFFGWSRY VPEGLQCSCG PDWYTVGTKY KSEYYTWFLF IFCFIVPLSL IIFSYSQLLS ALRA--VAAQ AY274222Ppal ATWIIGVGVA VPPFFGWSRY VPEGLQCSCG PDWYTVGTKY KSEYYTWFLF IFCFIVPLSL IIFSYSQLLS ALRA--VAAQ AJ277991Shum ATWVIGVGVA IPPFFGWSRY IPEGLQCSCG PDWYTVGTKY KSEYYTWLLF IFCFIVPLSL IIFSYSQLLS ALRA--VAAQ AJ277922Scan ATWIIGVGVA IPPFFGWSRY IPEGLQCSCG PDWYTVGTKY KSEYYTWFLF IFCFIIPLSL IIFSYSQLLS PCGA--VAAQ AF222331Tgut ATWIIGVGVA IPPFFGWSRY IPEGLQCSCG PDWYTVGTKY KSEYYTWFLF IFCFIVPLSL IIFSYSQLLS ALRA--VAAQ AF038948Atig ATWAIGFSVS IGPLVGWSRY IPEGLQCSCG PDWYTVGTKY NSETYTWFLF IFCFIIPLSL ICFCYAQLLG ALRA--VAAQ AB052889Cpyr TTWVIGFSVS IGPLVGWSRY IPEGLQCSCG PDWYTVGTKY NSETYTWFLF IFCFIIPLSL ICFCYSQLLG ALRA--VAAQ AB001983Rcat TTWMIGVGVS VPPFFGWSRY IPEGLQCSCG PDWYTVGTKY HSEYYTWFIF VFCFIIPLTL ICYSYARLLG ALRA--VAAQ BC084882Xlae CTWIIGIVVS VPPFLGWSRY MPEGLQCSCG PDWYTVGTKY RSEYYTWFIF IFCFVIPLSL ICFSYGRLLG ALRA--VAAQ AY228443Tman ATWAIGIGVS IPPFFGWSRF MPEGLQCSCG PDWYTVGTKY HSEHYTWFLF IFCFIVPLSL ICLLLLPAAG ALRA--VAAQ 66

AY099455Maur ------AY099455Nehr TTWIIGIGVC IPPFFGWSRF IPEGLQCSCG PGWYTVGTKY RSEYYTRFLF LFCFIMPLLL TCFSYCQLLR TLRD--VAAQ AF055458Ttru ATWTIGIGVS IPPFFGWSRF APEGLQCSC- ----TVGTKY YSEYYTWFLF IFCYTVPLSL ICFSYSQLLG VFRA--VAAQ AF545491Bmys ------AY366495Gaus QQESASTQKA EREVSRMVIM MVASFCTCYV PYAALAVYMV TNRDHNIDLR FVTVPAFFSK ASCVYNPLIY SFMNKQFRAC L._chalumnae QEQSASAQKA EREVTKMVIV MVLGFLMCWL PYASFALWVI THRGEPFDLR MASIPSVFSK ASTVYTPIIY IFMNKQ---- L._menadoensis QEQSASTQKA EREVTKMVIV MVLGFLMCWL PYASFALWVI THRGEPFDLR MASIPSVFPK ASTVYT?------D85863Caurat QAESASTQKA EKEVSRMVVV MVGSFVVCYG PYAITALYFS YAEDSNKDYR LVAIPSLFSK SSCVYNPLIY AFMNKQFNAC AB113669Ccar QAESASTQKA EKEVSRMVVV MVGSYIVCYG PYAIAALYFG YAEDTNKDYR LVAIPALFSK SSCVYNPLIY AFMNKQFNAC AF191220Dcom QAESASTQKA EKEVSRMIIV MVGSFVTCYG PYALAALYFA YSTDENKDYR LVTIPAFFSK SACVYNPLIY VFMNKQFNGC AB087810Drer QAESESTQKA EREVSRMVVV MVGSFVLCYA PYAVTAMYFA NSDEPNKDYR LVAIPAFFSK SSCVYNPLIY AFMNKQFNAC BC067683Drer QAESESTQKA EREVSRMVVV MVGSFVLCYA PYAVTAMYFA NSDEPNKDYR LVAIPAFFSK SSCVYNPLIY AFMNKQFNAC BC060894Drer QAESESTQKA EREVSRMVVV MVGSFVLCYA PYAVTAMYFA NSDEPNKDYR LVAIPAFFSK SSCVYNPLIY AFMNKQFNAC NM131319Drer QAESESTQKA EREVSRMVVV MVGSFVLCYA PYAVTAMYFA NSDEPNKDYR LVAIPAFFSK SSSVYNPLIY AFMNKQFNAC AF156264Hhip QTESVSTQKA EKEVSRMIIV MVGSFVTCYG PYALAALYFA HSSDTNKDYR LVTIPAFFSK SSCVYNPLIY VFMNKQFKAC AF191223Lfue QAESASTQKA EKEVSRMIIV MVGSFVTCYG PYALAALYFA YSTDENKDYR LVTIPAFFSK SACVYNPLIY VFMNKQFNGC AY296735Lgoo QAESASTQKA EKEVSRMIVV MVGSFVTCYA PYALTGLWFA NSPEVNKDYR LVTIPAFFSK SSCVYNPLIY AFMNKQFNAC AF191219Mzeb QAESASTQKA EKEVSRMIIV MVGSFVTCYG PYALAALYFA YSTDENKDYR LVTIPAFFSK SACVYNPLIY VFMNKQFNGC AY214153Ogor QAESASTQKA EKEVSRMVIV MVCSFILCYG PYALAGLYFA YTTSENKDYR LVTIPAFFSK SSCVYNPLIY AFMNKQFNAC AY214143Oket QAESASTQKA EKEVSRMVIV MVCSFILCYG PYALAGLYFA YTTSENKDYR LVTIPAFFSK SSCVYNPLIY AFMNKQFNAC AY214148Okis QAESASTQKA EKEVSRMVIV MVCSFILCYG PYALAGLYFA YTTSENKDYR LVTIPAFFSK SSCVYNPLIY AFMNKQFNAC AF425074Omyk QAESASTQKA EKEVSRMVIV MVCSFILCYG PYALAGLYFA YTTSENKDYR LVTIPAFFPK SSCVYNPLIY AFMNKQFNAC AY214158Oner QAESASTQKA EKEVSRMVIV MVCSFILCYG PYALAGLYFA YTTSENKDYR LVTIPAFFSK SSCVYNPLIY AFMNKQFNAC AF191221Onil QAESASTQKA EKEVSRMIIV MVGSFVTCYG PYALAALYFA YSTDENKDYR LVTIPAFFSK SSCVYNPLIY VFMNKQFNGC AY214138Otsh QAESASTQKA EKEVSRMVIV MVCSFILCYG PYALAGLYFA YTTSEVKDYR LVTIPAFFSK SSCVYNPLIY AFMNKQFNAC AB098706Palt QAESASTQKA EKEVSRMVIV MVGSFVVCYA PYAITALYYG FSTNENKDYR MVTIPAMFSK SSCVYNPLIY AFMNKQFNAC AB098705Palt QAESASTQKA EKEVSRMVIV MVGSFVVCYA PYALAALYFA ISTDENKDYR MVTIPAFFTK SSCVYNPLIY AFMNKQFNAC AY214133Ssal QAESASTQKA EKEVSRMVIV MVCSFILCYG PYALAGLYFA YTTSENKDYR LVTIPAFFSK SSCVYNPLIY AFMNKQFNAC AH005790Apal QQESATTQKA EREVSRMVVV MVGSFCVCYV PYAALAMYMV NNRNHGLDLR LVTIPAFFSK SSCIYNPIIY CFMNKQFRAC U92557Btau QQESASTQKA EREVSHMVVV MVGSFCLCYT PYAALAMYIV NNRNHGVDLR LVTIPAFFSK SACVYNPIIY CFMNKQFRAC XM539386Cfam QQESASTQKA EREVSRMVVV MVGSFCLCYT PYAAMAMYMV NNRNHGLDLR LVTIPAFFSK SACVYNPIIY CFMNKQFRAC L76201Cjac QQESATTQKA EREVSRMVVV MVGSFCVCYV PYAALAMYMV NNRNHGLDLR LVTIPAFFSK SSCIYNPIIY CFMNKQFRAC AH005810Coli QQESATTQKA EREVSRMVVV MVGSFCVCYV PYAALAMYMV NNRNHGLDLR LVTIPSFFSK SSCIYNPIIY SFMNKQFRAC AY552608Cpor QQESATTQKA EREVSRMVVV MVGSFCVCYV PYAALAMYIV NNRNHGLDLR LVTIPAFFSK SSCIYNPIIY CFMNKQFRAC AB111464Eful QQESATTQKA EREVSRMVVV MVGSFCLCYV PYAALAMYIV NNRNHGLDLR LVTIPAFFSK SACVYNPIIY CFMNKQFQAC AH005811Ggor QQESATTQKA EREVSRMVVV MVGSFCVCYV PYAAFAMYMV NNRNHGLDLR LVTIPSFFSK SACIYNPIIY CFMNKQFQAC AF545497Hamp ------AH003620Hsap QQESATTQKA EREVSRMVVV MVGSFCVCYV PYAAFAMYMV NNRNHGLDLR LVTIPSFFSK SACIYNPIIY CFMNKQFQAC AY726544Iobe QQESATTQKA EREVSRMVVV MVGSFCLCYV PYAALAMYMV NNRNHGLDLR LVTIPAFFSK SACVYNPIIY CFMNKQFHAC AY686753Lafr QQESATTQKA EREVSRMVVV MVASFCLCYV PYAALAMYMV NNRNHGLDLR LVTIPAFFSK SACVYNPIIY CFMNKQFRGC AY286017Meug QQESATTQKA EREVSRMVVM MVGSFCLCYV PYAALAMYMV NNRNHGIDLR LVTIPAFFSK SSCVYNPIIY CFMNKQFHAC AF158977Mfas QQESATTQKA EREVSRMVVV MVGSFCVCYV PYAAFAMYMV NNRNHGLDLR LVTIPAFFSK SACIYNPIIY CFMNKQFQAH AH005191Mmus QQESATTQKA EREVSHMVVV MVGSFCLCYV PYAALAMYMV NNRNHGLDLR LVTIPAFFSK SSCVYNPIIY CFMNKQFRAC L76226Mtal QQESATTQKA EREVSRMVVV MVGSFCVCYV PYAAFAMYMV NNRNHGLDLR LVTIPAFFSK SACIYNPIIY CFMNKQFQAH AY092006Ppyg ------SRMVVV MVGSFCVCYV PYAAFAMYMV NNRNHGLDLR LVTIPSLFSK SACIYNPIIY CFMNKQFQA AY029604Psun QQESATTQKA EREVTLMVVV MVASFCVCYV PYAALAMYMV NNRNHGLDLR LVTIPAFFSK SSCVYNPIIY CY?------AH005813Ptro QQESATTQKA EREVSRMVVV MVGSFCVCYV PYAAFAMYMV NNRNHGLDLR LVTIPSFFSK SACIYNPIIY CFMNKQFQAC U36972Rnor QQESATTQKA EREVSHMVVV MVGSFCLCYV PYAALAMYMV NNRNHGLYLR LVTIPAFFSK SSCVYNPIIY CFMNKQFRAC 67

U53875Sboliv QQESATTQKA EREVSRMVVV MVGSFCVCYV PYAALAMYMV NNRNHGLDLR LVSIPAFFSK SSCIYNPIIY CFMNKQFRAC AY726545Sbra QQESATTQKA EREVSRMVVM MVGSFCLCYV PYAALAMYMV NNRNHGIDLR LVTIPAFFSK SACVYNPIIY CFMNKQFHAC AY442173Scra QQESATTQKA EREVSRMVVV MVGSFCLCYV PYAAMAMYMV NNRNHGLDLR LVTIPAFFSK SACVYNPIIY CFMNKQFHAC NM214090Sscr QQESASTQKA EREVSHMVVV MVGSFCVCYT PYAALAMYIV NNRNHGVTLR LVTIPAFFSK SACIYNPIIY CFMNKQFRAC AB111463Tban QQESATTQKA EREVSRMVVV MVGSFCLCYV PYAALAMYMV NNQNHGLDLR LVTIPSFFSK SACVYNPIIY CFMNKQFQAC AH007736Acar QQESATTQKA EREVSRMVVV MVGSFCLCYV PYASLAMYMV NNRDHGLDLR LVTIPAFFSK SSCVYNPIIY CFMNKQFRAC AY024356Ggec QQESATTQKA EREVSRMVVV MVGSFCLCYV PYAALAMYMV NNRNHGIDLR MVTIPAFFSK SSCVYNPIIY CFMNKQFRG AF074045Pmad QQESATTQKA EREVSRMVVV MVGSFCTCYV PYAALAMYMV NYRNHGIDLR MVTIPAFFSK SACVYNPIIY CFMNKQFRGC AH007798Cliv QQESATTQKA EREVSRMVVV MVGSFCLCYV PYAALAMYMV NNRNHGLDLR LVTIPAFFSK SSCVYNPIIY CFMNKQFRAC AJ238856Cliv QQESATTQKA EREVSRMVVV MVGSFCLCYV PYAALAMYMV NNRNHGLDLR LVTIPAFFSK SSCVYNPIIY CFMNKQFRAC AY274223Eafe QQESATTQKA EREVSRMVVV MVGSFCMCYV PYAALAMYMV NNREHGIDLR LVTIPAFFSK SSC?------AY274224Eori QQESATTQKA EREVSRMVVV MVGSLCMCYV PYAALAMY?------NM205438Ggal QQESATTQKA EREVSRMVVV MVGSFCLCYV PYAALAMYMV NNRDHGLDLR LVTIPAFFSK SACVYNPIIY CFMNKQFRAC AY274226Lcal QQESATTQKA EREVSRMVVV MVGSFCLCYV PYAALAMYMV NNREHGIDLR LVTIPAFFS? ------AY274225Lsve QQESATTQKA EREVSRMVVV MVGSLCLCYV PYAALAMYMV NNREHGIDLR LVTIPAFFSK SSCVYNPIIY CF?------Y11787Mundul QQESATTQKA EREVSRMVVV MVGSFCVCYV PYAALAMYMV NNREHGIDLR LVTIPAFFSK SSCVYNPIIY CFMNKQFRGC AY274220Pcae QQESATTQKA EREVSRTVVV MVGSFCLCYV PYAALAMYMV NNREHGIDLR LVTVPAFFSK SSCVYNPIIY CFMNKQFRAC AY274221Pmaj QQESATTQKA EREVSRMVVV MVGSFCLCYV PYAALAMYMV YNR------AY274222Ppal QQESATTQKA EREVSRMVVV MVGSFCLCYV PYAGLAMYMV NNREHGIDLR LVTVPAFFSR APAFHPIIY? ------AJ277991Shum QQESATTQKA EREVSRMVVV MVGSFCLCYV PYAALAMYMV NNRNHGLDLR LVTIPAFFSK SACIYNPIIY CFMNKQFRAC AJ277922Scan QQESATTQKA EREVSRMVVV MVGSFCMCYV PYAALAMYMV NNREHGIDLR LVTIPAFFSK SSCVYNPIIY CFMNKQFRAC AF222331Tgut QQESATTQKA EREVSRMVVV MVGSFCMCYV PYAALAMYMV NNREHGIDLR LVTIPAFFSK SSCVYNPIIY CFMNKQFRA AF038948Atig QQESATTQKA EREVTRMVIV MVVSFCLCYV PYAAMAMYMV NNRNHGLDLR LVTIPAFFSK SACVYNPIIY SFMNKQFRAC AB052889Cpyr QQESATTQKA EREVTRMVIV MVASFCVCYV PYAAMAMYMV NNRNHGLDLR LVTIPAFFSK SACVYNPIIY SFMNKQFRAC AB001983Rcat QQESASTQKA EKEVSRMVVV MVGSFCLCYV PYAAMAMYMI TNRNHGLDLR FVTIPAFFSK SACVYNPIIY TFMNKQFRGC BC084882Xlae QQESASTQKA EREVSRMVIF MVGSFCLCYV PYAAMAMYMV TNRNHGLDLR LVTIPAFFSK SSCVYNPIIY SFMNKQFRGC AY228443Tman QQESATTQKA EREVSRMVIV MVGSFCLCYV PYAALAMYIV NNRNHGLDLR LVTIPAFFSK SACAYNPIIY CFMNKQV--- AY099455Maur ------AY099455Nehr QQESATTQKA EREVSCLVVV MVGAFCLCYV PYAALAMYMV NNRNHGLDLW LVTIPAFFSK SSCVYNPINL LLMNKQFRAC AF055458Ttru QQEAATTQKA GREVSHKVVM MVGSFCLCYT PYAALAMYIV NNHNHGVDLR FVTIPSFFSK SACIYNPIIY CFMNKQFQAC AF545491Bmys ------

AY366495Gaus ILETVCGKPI TDESETSSSR TEVSSVSTTQ MIPG*------L._chalumnae ------L._menadoensis ------D85863Caurat IMETVFGKKI DESSEVSSKT ETSSVSA*------AB113669Ccar IMETVFGKKI DEGSEVSSKT ETSSVSA*------AF191220Dcom IMEMVFGKTM DESSEVSTKT EVSTAS*------AB087810Drer IMETVFGKKI DESSEVSSKT ETSSVSA*------BC067683Drer IMETVFGKKI DESSEVSSKT ETSSVSA*------BC060894Drer IMETVFGKKI DESSEVSSKT ETSSVSA*------NM131319Drer IMETVFGKKI DESSEVSSKT ETSSVSA*------AF156264Hhip IMETVFGKKM DESSEVSSKT EASSVSTVN* ------AF191223Lfue IMEMVFGKTM DESSEVSTKT EVSTAS*------AY296735Lgoo IMEMVFGKKM EEASEVSSKT EVSTAS*------AF191219Mzeb IMEMVFGKTM DESSEVSTKT EVSTAS*------AY214153Ogor IMETVFGKQI EETSVSACKT EVSTA*------AY214143Oket IMETVFGKQI EETSVSASKT EVSTA*------68

AY214148Okis IMETVFGKQI EETSVSASKT EVSTA*------AJ277922Scan IMETVCGRPM SDDSDVSSSA QRTEVSSVSS SQVGPGQPRM * AF425074Omyk IMETVLGKQI EETSVSASKT EVSTA*------AF222331Tgut IMETVCGRPM TDDSEVSSSA QRTEVSSVSS SQVGPS*--- - AY214158Oner IMETVFGKQI EETSVSASKT EVSTA*------AF038948Atig IMETVCGTPM TDESDISSSS NKTEVSSVSS SQVSPS*--- - AF191221Onil IMEMVFGKKM DESSEVSTKT EVSTAS*------AB052889Cpyr IMETVCGTPI TDESDVSTSS NKTEVSSVSS SQVSPN*--- - AY214138Otsh IMETVFGKQI EETSVSASKT EVSTA*------AB001983Rcat IMETVCGRPM TDDSTLSSTS QKTEVSTVSH SQVSPSAS*- - AB098706Palt IMETVFGKKI DESSEVSSKT ETSSVSTA*------BC084882Xlae IMETVCGRPM SDDSSVSSTS QRTEVSTVSS SQVSPA*--- - AB098705Palt IMETVFGKKM EESSEVSSKT ETSSVSSA*------AY228443Tman ------AY214133Ssal IMETVFGKQI EETSVSASKT EVSTA*------AY099455Maur ------AH005790Apal IMEMVCGKAM TDESDLSSSQ KTEVSTVSSS QVGPN------AY099455Nehr ILEMVRRKPM TDEFNMSSSQ KTEVSTVSSS KVGPN*---- - U92557Btau IMEMVCGKPM TDESELSSSQ KTEVSTVSSS QVGPN*---- - AF055458Ttru IMKMVCGKAM TDESDTCSSQ KTEVSTVSST QVGPN*---- - XM539386Cfam IMEMVCGKSM TEDSEMSSSQ KTEVSTVSPS QVGPN*---- - AF545491Bmys ------L76201Cjac IMEMVCGKAM TDESDISSSQ KTEVSTVS?------AH005810Coli IMEMVCGKAM TDESDISSSQ KTEVSTVSTS QVGPN*---- - AY552608Cpor IMELVCRKPM ADESDMSTSQ KTEVSAVSSS KVGPH*---- - AB111464Eful IMEMVCGKAM TDESNTSSSQ KTEVSTFSSS QVGPN*---- - AH005811Ggor IMKMVCGKAM TDESDTCSSQ KTEVSTVSST QVGPN------AF545497Hamp ------AH003620Hsap IMKMVCGKAM TDESDTCSSQ KTEVSTVSST QVGPN*---- - AY726544Iobe IMEMICRKPM TDDSETSSSQ KTEVSTVSSS QVSPS*---- - AY686753Lafr IMEMVCGKSV ADESDMSSSQ KMEVSTVSSS QVGPN*---- - AY286017Meug IMEMVCRKPM TDDSEASSSQ KTEVSTVSSS QVGPS*---- - AF158977Mfas IMKMVCGKAM TDESDISSSQ KTEVSTVSSS QVGPN*---- - AH005191Mmus ILEMVCRKPM ADESDVSGSQ KTEVSTVSSS KVGPH*---- - L76226Mtal IMKMVCGKAM TDESDISSSQ KTEVSTVS?------AY092006Ppyg IMKMVCGKAM TDESDTCSSQ ?------AY029604Psun ------AH005813Ptro IMKMVCGKAM TDESDTCSSQ KTEVSTVSST QVGPN*---- - U36972Rnor ILEMVCRKPM TDESDMSGSQ KTEVSTVSSS KVGPH*---- - U53875Sboliv IMEMVCGKAM TDESDISSSQ KTEVSTVSSS QVGPN*---- - AY726545Sbra IMEMVCRKPM TDDSEASSSQ KTEVSTVSSS QVGPS*---- - AY442173Scra IMEMICKKPM TDDSETTSSQ KTEVSTVSSS QVGPS*---- - NM214090Sscr IMEMVCGKPM TDESDMSSSQ KTEVSTVSST QVGPN*---- - AB111463Tban IMEMVCRKAM ADESDTSSSQ KTEVSALSSS QVSPN*---- - AH007736Acar ILETVCGKPM SDESDVSSSA QKTEVSSVSS SQVSPS*--- - AY024356Ggec ILEMVCGKTM AEESEVSSAS QKTEVSSVSS SQVGPS*--- - AF074045Pmad IMEMVCGKPM SDDS-EASTS QKTEVSSVSS SQVSPS*--- - AH007798Cliv ILELVCGRPM TDDSDVSSSA QRTEVSSVSS SQVSPS*--- - AJ238856Cliv ILELVCGRPM TDDSDVSSSA QRTEVSSVSS SQVSPS*--- - AY274223Eafe ------AY274224Eori ------NM205438Ggal IMETVCGKPL TDDSDASTSA QRTEVSSVSS SQVGPT*--- - AY274226Lcal ------AY274225Lsve ------Y11787Mundul IMEMVCGKPM TDDSDMSSSA QRTEVSSVSS SQVSPS*--- - AY274220Pcae IMETVCGRPM SDDSDVSSSA QRTEVSSVSS S?------AY274221Pmaj ------AY274222Ppal ------AJ277991Shum IMETVCGKPM TDDSDVSSSA QRTEVSSVST S------69

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Chapter 3 Bowerbird opsins, spectral tuning mechanisms in short- wavelength-sensitive (SWS1) visual pigments, and the evolution of UV/violet vision in passerines and parrots

3 Abstract

One of the most striking features of avian vision is the variation in spectral sensitivity of the short wavelength sensitive (SWS1) opsins. Because of their broad spectral range, SWS1 pigments have been sub-divided into 2 sub-types: violet- and UV- sensitive (VS & UVS). In birds, UVS is confirmed in the closely related passerine and parrot orders. But, sequence data suggests some passerine lineages are VS, including basal bowerbirds, which are notable for their colourful courtship displays. Five opsin sequences were identified and cloned from the great bowerbird (Chlamydera nuchalis) RH1, RH2, SWS2, & LWS, indicating C. nuchalis has typical avian tetrachromatic/scotopic vision. The SWS1 opsin was characterized following in vitro heterologous expression, yielding a pigment with a maximal absorbance (λmax) of 403 nm, thus VS and not UV, even though such colours are a component of the male’s courtship display. To investigate the origins of UV/violet vision in passerines, ancestral SWS1 pigments were recreated. The SWS1 visual pigments of the passerine and shared passerine/parrot ancestors were both likely VS, suggesting that UVS evolved independently in passerines and parrots. In fact, the phylogenetic reconstruction suggests UVS evolved multiple times in passerines. To further our understanding of the molecular basis of spectral sensitivity, mutant pigments with alternate residues at sites known to shift λmax were expressed. While mutagenesis of C86F, S90C, and C86S/S90C yielded UV pigments, C86S had no effect, which confirmed sites 90 and 86 are important in SWS1 function, but site 86 is context dependent. Lastly, codon-based likelihood methods applied to complete avian SWS1 pigments identified elevated substitution rates in lineages associated with shifts to UVS where positively selected sites might form a basis to clarify functional differences between UVS and VS SWS1s. This study expands on previous studies suggesting SWS1 spectral tuning in birds are unusually consistent compared to what is known in other systems, but highlights a highly varied distribution of UVS vs. VS in passerines.

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3.1 Introduction

Bowerbirds are a remarkable group of passerine birds where males build elaborate bowers/structures made of plant material and brightly coloured objects to attract females. These colourful displays are among the most striking examples of sexually selected traits. Consequently, bowerbirds have become a model system in visual ecology and evolutionary biology, particularly with respect to the evolution of visual signals (Madden, 2003; Doucet, 2003b; Endler et al., 2005; Doucet et al., 2006; Endler and Day, 2006; Endler et al., 2010). Birds in general are well known for their vibrant displays. They have a visual system well suited for colour detection with four types of cone visual pigments, which likely facilitate tetrachromatic vision. These pigments span a wide range of the electromagnetic spectrum extending into the ultraviolet (UV). UV based signals in particular can play important roles in avian behaviours (Viitala et al., 1995; Siitari et al., 2002; Alonso-Alvarez, 2004), especially in mate choice in passerines (Andersson and Amundsen, 1997; Hunt et al., 1998) and parrots (Pearn et al., 2001).

The first step in vision is the absorption of light by visual pigments in the photoreceptor cells of the retina. Visual pigments consist of an opsin protein covalently bound to a light sensitive chromophore via a Schiff base (SB) link. Opsins are G-protein coupled receptors (GPCRs), and possess a characteristic seven transmembrane helical structure that forms a binding pocket to surround a chromophore ligand (Smith, 2010). Absorption of a photon of light triggers cis-trans isomerization in the chromophore. This induces a conformational change in the opsin that allows it to bind and activate the downstream G-protein, transducin, thus initiating a biochemical cascade that can result in an electrical response in the photoreceptor cell (Menon et al., 2001).

Five opsin types exist in vertebrates. Rod opsins (also known as rhodopsins or RH1) mediate dim light (scotopic) vision, while the four cone opsins mediate colour (photopic) vision. Vertebrates can adapt to diverse light environments by variation in subtypes and spectral properties of their visual pigments (Davies et al., 2012). Spectral properties of the visual pigment are determined by the interactions between the opsin protein and its chromophore, a mechanism known as spectral tuning (Kochendoerfer et al., 1999). Each visual pigment can thus be characterized by its wavelength of maximal absorption (λmax). The four cone opsin types are named by their relative

λmax values: long- (LWS), medium- (RH2) and two short-wavelength-sensitive (SWS1 & 2). SWS1 pigments mediate sensitivity to light in the violet to UV range. This group of pigments 80

exhibits the broadest range in spectral sensitivity across vertebrates, and so are divided into two groups based on λmax: violet-sensitive (VS: λmax 388-435 nm) and UV-sensitive (UVS: λmax 355- 380 nm).

The molecular mechanisms determining wavelength sensitivity among vertebrate SWS1 pigments are not straightforward. To achieve sensitivity in the UV range, the SB link must be stabilized in a deprotonated form (Altun et al., 2009). However, in some cases individual residues are able to explain the majority of λmax difference between UV and violet pigments, which can vary in amino acid character and location (Wilkie et al., 2000; Yokoyama, Radlwimmer, et al., 2000; Cowing et al., 2002; Fasick et al., 2002); whereas in other cases the collective effect of a number of residues are required (Fasick et al., 1999; Shi and Yokoyama, 2003; Takahashi and Ebrey, 2003). In birds, it is generally thought that the most important site is site 90: both passerines and parrots regained UVS from a VS avian ancestor by a single amino acid substitution from a serine (S) to a cysteine (C) at site 90 (Wilkie et al., 2000; Yokoyama, Radlwimmer, et al., 2000; Yokoyama and Shi, 2000; Shi and Yokoyama, 2003). Phenylalanine (F) 86 might be a second mechanism by which birds achieve UVS because it is found in the SWS1 genes of both trogon and paleognaths (Ödeen and Håstad, 2003; Aidala et al., 2012) and is capable of UV shifting VS pigments of pigeon and chicken (Carvalho et al., 2007) and many mammals (Cowing et al., 2002; Fasick et al., 2002; Parry et al., 2004; Yokoyama et al., 2005).

Due to the importance of UV signals and the dramatic spectral variation among SWS1 opsins, recent research has focused on determining whether different species have UVS or VS vision. In birds, orders with known UV sensitivity, determined from microspectrophotometry (MSP) or protein expression data, are Passeriformes (passerines) and Psittaciformes (parrots) (Maier and Bowmaker, 1993; Bowmaker et al., 1997; Hart et al., 1998; Wilkie et al., 1998; Das et al., 1999; Hart, et al., 2000; Hart et al., 2000; Yokoyama, et al., 2000; Carvalho et al., 2010) two groups that are relatively closely related within the larger bird phylogeny (Hackett et al., 2008; Suh et al., 2011; Wang et al., 2012). All parrots share C90, likely retaining this from an ancestral substitution (Carvalho et al., 2010). Among passerines, however, those with known UVS are restricted to higher songbird lineages, and recent sequence data shows some basal lineages have S90 (Ödeen et al., 2011). This brings one to question whether these birds with S90 are VS. Also, if some passerines have S90, did C90, and subsequently UVS, evolve independently in

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passerines and parrots? A number of other avian orders are also thought to have UVS because they contain members with C90 and/or F86: Charadriiformes, Trogoniformes, and Paleognathae (Ödeen and Håstad, 2003; Ödeen et al., 2010; Machovsky Capuska et al., 2011; Aidala et al., 2012). However, it has yet to be established whether these species are, in fact, UVS.

Since the ecological and behavioral aspects of bowerbird vision are so well characterized and given their phylogenetic position as basal passerines, these birds provide an ideal system with which to study the function and evolution of avian vision. In this study, great bowerbird (Chlamydera nuchalis) vision is investigated. Its opsin genes are isolated and the SWS1 visual pigment is further characterized. The evolution of UVS in passerines and parrots is then explored using phylogenetic ancestral reconstruction methods to infer ancestral SWS1 pigments. Additionally, maximum likelihood methods are used to investigate the form and strength of selection acting on avian SWS1 genes. Last, to further expand our understanding of wavelength regulation in avian SWS1 pigments, a series of spectral tuning mutants in C. nuchalis SWS1 are created.

3.2 Experimental procedures 3.2.1 Opsin sequences and mutagenesis

RNA was extracted from a C. nuchalis retina using TRIzol Reagent (Invitrogen) and a cDNA library was prepared with the SMART cDNA Library Construction Kit (BD Biosciences). Degenerate primers were designed to amplify fragments of the opsin coding regions (Table 1). The remaining sequences of the opsin fragments were amplified by RACE PCR. After cloning into the pJET1.2 cloning vector (Fermentas), purified PCR products were sequenced from multiple clones. Mutations were introduced into this construct using the QuikChange site- directed mutagenesis kit (Stratagene). Genomic DNA was extracted from blood samples of two individuals from different geographic locations using the DNeasy Blood and Tissue Kit (QIAGEN). Genome walking methods were used with nested PCR to isolate SWS1 introns and the flanking genomic regions.

3.2.2 Expression & purification of wild type and mutant pigments.

Complete coding sequences of C. nuchalis wild type and mutant pigments were subcloned into

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the p1D4-hrGFP II expression vector for transient expression (Morrow and Chang, 2010). This vector has a C-terminal 1D4 epitope tag that encodes the last nine amino acids of bovine RH1 [TETSQVAPA], and employs the CMV promoter to drive transgene expression. Cultured HEK293T cells were transiently transfected with the opsin-1D4 construct using Lipofectamine 2000 (Invitrogen). Four 175 cm2 flasks were used per expression sample. Methods for purification of C. nuchalis SWS1 opsins were adapted from those of Starace & Knox (1998) for the purification of Xenopus SWS1. Cells were harvested 48 h post transfection, and washed with

Harvesting Buffer (GHB: 50 mM HEPES ph 6.6, 140 mM NaCl, 3 mM MgCl2, 10 ug/ml aprotinin & leupeptin). Pigments were regenerated in 5 µM 11-cis-retinal; solubilized from cell membranes in Solubilization Buffer (GSB: GHB, containing 1% n-dodecyl-β-D-maltoside detergent (DM: Anatrace) and 20% (w/v) glycerol); purified with the 1D4 monoclonal antibody (Molday and MacKenzie, 1983) by immunoaffinity chromatography; eluted with 1D4 peptide; and concentrated using centrifugal filter columns (Amicon Ultra 30K; Millipore). The UV- visible absorption spectra of purified visual pigments were recorded at 21°C using a Cary 4000 dual beam spectrophotometer (Agilent, Santa Clara, CA). For functional assays, absorbance spectra were also measured after exposure to light (either a 366 nm UV light illuminator or a 60- W lamp with 440 nm cutoff filter, for VS and UVS pigments, respectively), to hydrochloric acid

(HCl; 100 mM), or to hydroxylamine (NH2OH; 50 mM). To produce difference spectra, either the light or the acid-denatured spectra were subtracted from the dark absorbance spectra. To estimate λmax, the dark absorbance spectra were baseline corrected and fit to a visual pigment template (Govardovskii et al., 2000). The F86 mutant λmax was estimated by fitting the dark-acid difference spectra (Parry et al., 2004), as a perturbation in the long wave arm produced template curves that clearly did not resemble the data.

3.2.3 Ancestral sequence reconstruction of Helix 2 in Landbirds

To reconstruct ancestral passerine SWS1 states, a dataset of 83 gene fragments coding for Helix 2 of SWS1 genes from passerines, parrots and other ‘Landbirds’ (sensu Hackett et al., 2008) (Table S1) was assembled. For most species, this region comprises all that is known of the SWS1 gene. The dataset was truncated to include only amino acid sites 72-101, which codes for Helix 2 of the SWS1 visual pigment, and comprises most vertebrate SWS1 spectral tuning sites. The sequences were aligned with C. nuchalis using Clustal W (Larkin et al., 2007) and adjusted by

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eye with MEGA5 (Tamura et al., 2011) (Figure S1). The topology of the tree used in the analysis reflects the most recent understanding of Landbird relationships (Barker et al., 2002; 2004; Beresford et al., 2005; Hackett et al., 2008; Irestedt and Ohlson, 2008; Johansson et al., 2008; Wright et al., 2008; Gardner et al., 2010; Driskell et al., 2011; Jønsson et al., 2011; Lee et al., 2011; Suh et al., 2011; Wang et al., 2011). Both codon and amino acid inference maximum likelihood (ML) methods of ancestral sequence reconstruction were performed (Yang et al., 1995), using the codeml program of the PAML software package, version 4.3 (Yang, 2007). For codon inference, random sites and branch sites models were used (Yang et al., 2000; 2005; Zhang et al., 2005). For amino acid inference, the LG substitution matrix was used (Le and Gascuel, 2008), both with and without the addition of a gamma parameter (Yang and Kumar, 1996). Nested models were compared using likelihood ratio tests (LRTs) (Felsenstein, 1981; Yang and Kumar, 1996). For random-site models, a χ2 null distribution was used, with the degrees of freedom equal to the number of extra parameters estimated by the alternative model, 2 whereas for the branch-site LRTs a 50:50 mixture distribution of 0 and χ 1 was used, following Goldman (Goldman and Whelan, 2000) and Yang and dos Reis (Yang and Reis, 2011). Multiple runs were carried out with different starting values to check for convergence in all analyses.

Although ASR is a useful method with which to study the evolution of protein function, this method is not without limitations that, to some extent, compromise its robustness. Primarily, due to the availability of sequence data the ASR results are based on only a short fragment, which can affect the accuracy of the reconstruction by reducing the power to accurately predict parameters of the model of sequence evolution (Yang 2006). Correspondingly, functional inferences are founded on the reconstruction of sites in the background of C. nuchalis. As well, some conclusions rely on predictions of λmax based on amino acid sequences, particularly C90. As discussed below, one cannot reliably assume that certain sites will always be functionally important, nor can one ignore the possibility that there might be other sites and/or residue combinations that have not yet been investigated that are equally important. Our understanding of SWS1 spectral tuning is restricted by a paucity of data in expression and mutagenesis studies in birds. So it may be somewhat tenuous to expect the functional roles of the residues in Helix 2 to be consistent across passerines, although our mutagenesis results would support otherwise (see below). Regardless, the predictions of spectral sensitivity presented here should therefore be interpreted with these considerations in mind. 84

3.2.4 Tests of selection and BEB sites in avian SWS1 whole gene dataset

To test the form and strength of selection acting on avian SWS1 opsin genes ML methods were employed to estimate the non synonymous-to-synonymous substitution rate ratios (dN/dS = ω) among sites. dN/dS relates to the form and strength of selection operating on protein coding genes, with values < 1 indicating purifying selection, values = 1 indicating neutrality, and values > 1 indicating positive selection (Anisimova and Kosiol, 2009). Full-length avian SWS1 sequences available on NCBI were obtained, of which there are 18 (Table S1), and aligned with C. nuchalis SWS1 as described above (Figure S2). The alignment included amino acid sites 46 to 316, as sequence data was missing for some species. The tree was based on the most current studies of phylogenetic relationships among these species (Hackett et al., 2008; Pratt et al., 2009; Suh et al., 2011; Wang et al., 2012) (Figure S3). dN/dS was estimated using a variety of codon substitution models as implemented in the codeml program in the PAML software package, version 4.3 (Yang, 2007). To test for among-site variation in dN/dS throughout the SWS1 dataset a variety of models were implemented, including; random sites models (Yang et al., 2000; 2005), branch-site models (Yang and Nielsen, 2002; Yang et al., 2005; Zhang et al., 2005) and Clade models (Bielawski and Yang, 2004) including M2a_rel, a new null clade model that better accounts for among-site variation in selective constraint (Weadick and Chang, 2012). Models were run multiple times with different starting values to check for convergence in all analyses. Nested models were compared using LRTs. Again; a χ2 null distribution was used for random- 2 site models. For branch-site LRTs, a 50:50 mixture distribution of 0 and χ 1 was used (Yang and Reis, 2011). The Bayes empirical Bayes (BEB) method was used to identify positively selected sites (Yang et al., 2005), and BEB sites with ω > 1 and high posterior probabilities were mapped on the 3D structure of bovine RH1 (PDB: 1U19 Okada et al., 2004) using MacPyMol (Delano Scientific, San Carlos, CA)

3.3 Results

The complete C. nuchalis SWS1 gene was sequenced from both cDNA and genomic DNA. It has 4 introns, ranging in length from 416 to 600 bp. In addition to SWS1, four other opsin genes were isolated: SWS2, RH2, and LWS, and rod opsin (RH1) (Figure 1). All genes contain important structural characteristics typical of functional visual pigments (see Figure legend).

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Phylogenetic analyses show these sequences cluster with expected visual pigment families (Chang et al., 1995) (Figure 2).

The C. nuchalis SWS1 gene codes for residues C86 and S90, a residue combination found in past sequencing-surveys of SWS1 opsins (Ödeen and Håstad, 2009), but which has not previously been considered in mutagenesis experiments. Therefore the C. nuchalis SWS1 opsin was transiently expressed in HEK293T cells, reconstituted with 11-cis-retinal, solubilized in DM detergent, and immunoaffinity purified. The expressed pigment produced a VS-type absorption spectrum with a λmax of 403 nm (Figure 3), similar to the cormorant (405 nm, Carvalho et al., 2007) and Humboldt’s penguin (403 nm, Wilkie et al., 2000), which were also assayed by in vitro expression. These VS pigments are mid-range between the chicken at ~419 nm (Yokoyama et al., 2000; Carvalho et al., 2007) and the pigeon at 388/393 nm (Kawamura et al., 1999; Carvalho et al., 2007). Given this spectral difference and the variation in effects of spectral tuning sites in mammals, the following spectral tuning mutants were created in the background of C. nuchalis SWS1: C86S, S90C, C86S/S90C, and C86F.

3.3.1 Mechanisms of wavelength regulation in C. nuchalis SWS1

Replacement of S90 with C as a single mutation generated a UV shifted pigment (λmax 363 nm), corresponding to a 40 nm shift from the wild type (Figure 4A). The nm shift in C. nuchalis is somewhat similar to what has been reported in S90C mutants in chicken and pigeon with shifts of 29 and 42 nm, respectively, and the reverse mutation, C90S, shifts the UVS pigments of zebra finch and budgerigar into the violet range, 38 and 60 nm (Yokoyama et al., 2000; Hunt et al., 2004; Carvalho et al., 2007). The replacement of C86 with F also created a UV absorbing pigment (λmax 365 nm, Figure 4b), 38 nm shifted from the wild type λmax. This nm shift is consistent with findings of others where the replacement of a S86 with F in pigeon and chicken resulted in large shifts of 31 and 47 nm, respectively (Carvalho et al., 2007). The single mutation

C86S did not affect sensitivity in C. nuchalis (λmax 403, Figure 4c). In other studies, substitutions between S and C at site 86 affect λmax, but to varying extents: -2 nm in the wild type pigeon (Carvalho et al., 2007) to -27 nm in an inferred and synthesized ancestral avian SWS1 pigment (Shi and Yokoyama, 2003). A double mutant C86S/S90C was also created. This pigment had a

λmax at 363 nm, identical to the S90C single mutant (Figure 4d).

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3.3.2 Other visual pigment characteristics

To confirm C. nuchalis SWS1 wild type and mutant opsins were functional, expressed pigments were also characterized by light bleaching, and exposure to acid and hydroxylamine. All pigments were more difficult to express and purify than bovine RH1 but this is expected of cone pigments, which are generally less stable than rod pigments. All expressed opsins bound 11-cis retinal and produced stable photopigments. The absorbencies at λmax ranged from 0.05- 0.15 (Table 2), comparable to other SWS1 pigments expressed in vitro (e.g. Xenopus VS, 0.027

(Starace and Knox, 1998); Mouse UV, 0.05 (Tsutsui et al., 2007)). Spectral ratios (A280/Amax) of the wild type and C86S VS were low (~3.5), while those of the UV absorbing mutants were higher (4.5 – 5.5). All are similar to other in vitro expressed SWS1 pigments (mouse ~4, (Dukkipati et al., 2002; Kusnetzow et al., 2004). When denatured in HCl, absorbance peaks shifted to a 440 nm absorbing species (Figures 3 & 4, Inset), characteristic of denatured opsin bound to chromophore, demonstrating that all of the pigments covalently bound retinal (Kito et al., 1968). All pigments bleached with light to a ~380 nm absorbing species, characteristic of the biologically active MII state of visual pigments (Matthews et al., 1963; Koutalos et al., 1989).

The wild type pigment reacted in the presence of hydroxylamine (Figure 5), with a t1/2 = ~6, typical of cone pigments (Ma et al., 2001; Das et al., 2004). The C86 mutant also reacted (t1/2 = ~10 min, data not shown). These results show the binding pocket is not as tightly packed as in RH1 pigments, which do not react to hydroxylamine. Hydroxylamine sensitivity was not measured for the UVS pigments because the absorbance peaks of the visual pigment and the retinal oxime moiety overlap. All pigments had small secondary absorbance peaks at varying wavelengths. Secondary absorbance peaks, which can have the effect of broadening pigment absorbance curves, have previously been observed in SWS1 pigments. In this study, attempts were made to prevent the formation of a secondary absorbance peak using alternate buffers, but were unsuccessful (Appendix 1).

3.3.3 Evolution of λmax in passerine birds

To better understand the evolution of SWS1 genes in passerines (Passeriformes), maximum likelihood codon and amino acid reconstruction methods were used to infer the sequence of Helix 2 of the SWS1 gene in the ancestors of passerines and parrots (nodes indicated in Figure

6). We focused on sites 86, 90, and 93, because they have a major impact on λmax in vertebrate 87

SWS1 pigments (Wilkie et al., 2000; Yokoyama, et al., 2000; Shi et al., 2001; Carvalho et al., 2007). The passerine ancestor is identical to C. nuchalis, except for A99S in the transmembrane region, which has no known role in wavelength regulation in any opsin. The Passeriformes/Psittaciformes ancestor is also similar, but with the additional change of S86, instead of C86. Because the SWS1 sequence in C. nuchalis is identical to the passerine ancestor, it likely retained the ancestral phenotype. It also means the C. nuchalis SWS1 is a prime candidate for studying the evolution of UV/violet sensitivity. Therefore, the site-directed mutagenesis results can be interpreted in light of these ancestral reconstructions to predict the ancestral states at these nodes. The results strongly suggest both the passerine ancestor and the shared ancestor of passerines and parrots had VS pigments (Fig 5). Reconstructions for basal passerine nodes had high posterior probability values for all sites (all >0.95; Fig. 5), and results were consistent across best fitting codon and amino acid reconstructions. The inclusion of gamma in the amino acid reconstruction significantly improved the fit of the model (P<0.05). Conversely, LRTs of codon M8 and Branch-site models were not significant (P > 0.05 in all cases).

The substitutions at sites 86, 90 and 93 are mapped on the phylogeny. Most occur in leaf lineages, while the backbone lineages are relatively unchanged. Substitutions at site 90 occur multiple times throughout the passerine phylogeny, and it is always the substitution of S for C. Substitutions at sites 86 and 93 are few. Most notably, S86C occurs in the base of the passerine lineage. Other interesting substitutions include: C86M shared among Sylvioidea, one of the three major clades in Passerida; T93L in Acanthisitta chloris; and T93V and C86S in independent lineages within suboscines.

3.3.4 Detecting selection in avian SWS1 visual pigments

To further investigate the evolution of SWS1 in birds, the form and strength of selection was tested in a dataset of complete avian SWS1 opsin genes. Branch site analyses show significant positive selection when either both higher passerine (Passerida) and parrot branches are set as foreground, or only the parrot branch is set as foreground (p < 0.05, Table 2). Both of these lineages correspond to UVS shifts (Figure S3). Other lineages do not show any evidence of positive selection. Parameter estimates for Branch-site models are shown in Table S2. Clade models were also used to detect more subtle changes in selective constraints among clades of 88

passerines and parrots, but these analyses produced no evidence of divergent selection (Table S3). Random site models also did not detect any significant differences in selection (Table S4).

Maximum Likelihood methods can be useful in identifying important functional sites (Yang and dos Reis, 2011). When the parrot lineage is set as the foreground, only sites 199 (P>0.95) and 109 (PP > 0.5) show evidence of positive selection. When both UVS lineages are set as foreground, substantially more positively selected sites are reported. This includes the spectral tuning site 90 (PP > 0.95) as well as sites 112, 199, 283 (PP > 0.95); 149 (PP > 0.90); 91, 280, and 298 (PP > 0.80). The positions of these sites in the visual pigment and their potential roles are illustrated and discussed in Figure S4. Like site 90, sites 91, 112 and 298 are near the chromophore and its SB linkage to the opsin at Lys 293 and therefore might be involved in spectral tuning. Other BEB sites are in extra/intra-cellular regions, which are also crucial for proper opsin function. These residues might contribute to some of the unique properties of UVS pigments (Das et al., 2004; Luo et al., 2011; Chen et al., 2012). The preliminary results presented here support the use of molecular evolution methods to identify functional sites because site 90 is identified in lineages associated with UVS shifts. The data set is, however, fairly small. This topic should be revisited when a greater number of full avian SWS1 opsin sequences are available, as the branch-site test, like all statistical tests, will inevitably produce some false- positive results for some data sets (Yang and dos Reis, 2011). Nevertheless it is a starting point with which to investigate the functional differences between UV and violet type SWS1 pigments.

3.4 Discussion

The present study extends our understanding of SWS1 opsin function and evolution by investigating evolutionary changes that occurred in avian SWS1 genes. The SWS1 of C. nuchalis, a basal passerine bird, was expressed with a series of spectral tuning mutants that correspond to ancestral passerine SWS1 states allowing us to identify the evolution of UV/violet sensitivity in early passerines and parrots. In addition to SWS1, four other visual pigments were isolated: RH1, RH2, LWS and SWS2, demonstrating C. nuchalis possesses a retina capable of tetrachromatic/scotopic vision.

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3.4.1 Evolution of SWS1 λmax in passerine birds

The C. nuchalis SWS1 pigment has a λmax of 403 nm, which is intermediate within the VS range (388–419 nm). This finding is in agreement with a previous MSP study demonstrating C. nuchalis has a λmax of 405 nm (Coyle et al., 2012). Thus we have confirmed the first example of a passerine bird with VS-type vision. Other passerines with known λmax values are UVS and have C90, yet are restricted to higher passerine lineages. Some passerines are highly similar to C. nuchalis within the Helix 2 region of the protein (Ödeen et al., 2011), implying bowerbirds may not be the only passerines with VS-type vision. Also, UV sensitivity in passerines and their sister group, parrots, is achieved by the same amino acid substitution, S90C. This brings to question whether UVS evolved independently in these two groups. Given this, the SWS1 sequences of the ancestral passerine and the shared ancestor to passerines and parrots were inferred and the λmax values of opsins containing the predicted substitutions at spectral tuning sites were measured. The results show the passerine ancestor most likely had a VS type SWS1 as did the passerine/parrot ancestor, indicating UV sensitivity probably evolved independently in these two orders. The phylogenetic reconstruction also indicates multiple independent evolutionary events of S90C occurred in parallel within passerines. This would imply that in passerines shifts to UVS might have been recurrently driven by selection that targeted a common amino acid site within the SWS1 pigment.

Our experimentally determined λmax of the passerine ancestral SWS1 contradicts the predictions of previous studies that suggest the passerine ancestor was UVS (Ödeen et al., 2011). Our analysis included more outgroup species and used maximum likelihood reconstruction methods that employ specific models of codon sequence evolution. Furthermore, the hypotheses were tested experimentally by combining computational and mutagenesis results. But, our phylogeny is based on the current agreement of phylogenetic studies among Landbirds that includes a recent revision of the relationships among higher lineages (Irestedt and Ohlson, 2008; Jønsson et al., 2008; Zuccon and Ericson, 2012), and therefore is somewhat different from that of Ödeen et al., (2011). Therefore, the dataset was re-analyzed on a phylogeny similar to theirs to confirm our findings (Figure S5). The reconstructions at basal nodes were the same, regardless of the slight differences in topology among higher passerine lineages, which is expected when only leaf lineages are rearranged (Hanson-Smith et al., 2010).

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Although not related to the primary focus of this paper, it is worth mentioning that while the original analysis supports independent evolutionary events of S90C in parallel lineages, the analysis on the alternate tree supported the possibility that reversals might have occurred in higher passerines; from S to C to S (Figure S4), similar to the results of Ödeen et al., (2012). These alternate evolutionary hypotheses lead to different interpretations regarding the evolution of UV/violet vision within passerines, and provide different suggestions of how easily λmax shifts may occur. Indeed, more sequence data and phylogenetic information is necessary to resolve these contradictory hypotheses. SWS1 carries a strong phylogenetic signal (van Hazel et al., 2006), and might resolve both the relationships among higher passerines and the alternate hypotheses regarding the evolution of wavelength sensitivity among them.

3.4.2 Spectral tuning in C. nuchalis SWS1

The C. nuchalis VS pigment possesses an unusual residue combination at the two spectral tuning sites known to be most important in specifying UVS or VS: C86/S90. This residue combination has been found in a few passerine SWS1 opsins in past sequence-based surveys (Ödeen and Håstad, 2009; Ödeen et al., 2011), but its spectral relevance has not been examined using mutagenesis experiments, which thus far have only dealt with VS-type pigments with S86/S90, in pigeon and chicken, (Yokoyama et al., 2000; Carvalho et al., 2007) and UVS type with either A86/C90 or C86/C90, in budgerigar and zebra finch, respectively (Wilkie et al., 2000; Yokoyama et al., 2000, Hunt et al., 2004). Past mutagenesis studies on vertebrate SWS1 pigments have shown the magnitude of λmax shift caused by a given amino acid change can differ significantly among pigments due to synergistic interactions within and between transmembrane regions I-VII (Shi et al., 2001; Fasick et al., 2002; Takahashi and Yokoyama, 2005). As such, characterization of great bowerbird SWS1 mutants may provide new insights into mechanisms contributing to naturally occurring variation in SWS1 pigment λmax, and help clarify patterns of evolution between VS and UVS visual systems in birds.

Our results showing S90C shifts the C. nuchalis SWS1 into the UV is consistent with previous studies where similar shifts have been documented in the chicken, pigeon zebra finch and budgerigar (Wilkie et al., 2000; Yokoyama et al., 2000; Carvalho et al., 2007). In C. nuchalis, the effect of the double mutant C86S/S90C was identical to that of the single S90C mutant. Thus, in the presence of C90, C86 has no additional effect on sensitivity. In other avian pigments, 91

substitutions at known spectral tuning sites also do not change λmax if expressed with C90 (Wilkie et al., 2000; Carvalho et al., 2007). Others have suggested that the effect of C90 is so strong it prevents detection of any subtler effects other residues might have (Carvalho et al.,

2007). In birds, all in vitro expressed pigments, whether wild type or mutant, with C90 have λmax

~360 nm. The exception is in chicken where S90C only shifts λmax to 369 nm. This indicates particular changes have occurred in the SWS1 gene since the divergence of chickens that contribute to the strong affect of C90.

The mutation C86F in C. nuchalis also shifts λmax into the UV. The substitution of F86 to S in the ancestral avian SWS1 is believed to have resulted in a loss of UVS in ancient birds (Shi and Yokoyama, 2003). In mammals, substitutions from F86 are also responsible for shifts to VS in many lineages2 (Cowing et al., 2002; Fasick et al., 2002; Takahashi and Ebrey, 2003; Parry et al., 2004; Yokoyama et al., 2005; Carvalho et al., 2012). C86 therefore plays an important role in maintaining VS sensitivity in C. nuchalis, as the replacement of C86F short wave shifts the λmax into the ancestral UV state. The results presented here also support the hypothesis that extant birds with F86 are UVS, and, therefore, the supposition that there are at least two mechanisms determining UVS in birds (Carvalho et al., 2007).

While the mutation C86F significantly affects λmax in C. nuchalis, the mutation C86S did not. A wide spectral range encompasses VS pigments, from 388 nm (pigeon) to 420 nm (chicken) (Carvalho et al., 2007). It has previously been suggested S86C might contribute to this variation as it can shift λmax in other avian pigments (Shi and Yokoyama, 2003; Hunt et al., 2004; 2009). The results presented here show this is not the case, at least in C. nuchalis. Therefore the residues 3 regulating the difference in λmax among these VS pigments remains unknown . Our finding is

2 These sites include: Y86F in the bovine pigment (-71 nm) (Fasick et al., 2002; Cowing et al., 2002) and wallaby (- 59 nm) (Takahashi et al., 2003), V86F in guinea pig (-53 nm) (Parry et al., 2004), S86F in the elephant pigment (-52 nm) (Yokoyama et al., 2005) F86S in lemur (-7 nm) (Carvalho et al., 2012), F86Y in mouse (66 nm), L86Y in human (2 nm) (Fasick et al., 2002). 3 Sites 93, 118, and 298 are promising candidates. The mutations T93V A118T and S298A have no effect on the budgerigar UVS SWS1 pigment, but this is likely due to the strong UV shifting effect of C90. Most birds have T93 and A118, but the chicken has V93 and T118. In other vertebrates, site 93 can affect sensitivity on its own (Carvalho et al., 2012), but also can regulate the effects of other sites, like site 118 (Shi et al., 2001). As for site 298, the pigeon uniquely shares S298 with UVS type pigments, and so might be responsible for the SW shift observed in this bird. 92

similar to others where in the pigeon SWS1 S86C barely shifts λmax (Carvalho et al., 2007), and similarly A86S in budgerigar (Wilkie et al., 2000). In contrast, in a hypothetical ancestral avian SWS1, S86C shifts ~30 nm into the UV (Shi and Yokoyama, 2003). Therefore, in birds the role of site 86 depends not only on the residue expressed, whether F or C, but also on the background in which it is expressed. This has been found to be true of mammal SWS1s where the variation at site 86 is better characterized (Cowing et al., 2002; Fasick et al., 2002; Takahashi and Ebrey, 2003; Parry et al., 2004; Yokoyama et al., 2005; Carvalho et al., 2012).

Juxtaposing our mutagenesis results with those of others suggests that the effects of C90 and F86 might be consistent across birds. In support of this, some gulls have UV-type eye characteristics and SWS1s with C90, implying the presence of UVS (Håstad et al., 2009). In other vertebrate groups, however, C90 and F86 do not always confer UVS. For instance, some primate SWS1s with F86 are VS (Carvalho et al., 2012), and the human, bovine, and goldfish SWS1s are unaffected by C90 (Cowing et al., 2002; Fasick et al., 2002). It is clear these residues do not UV shift in all backgrounds. Thus, it is possible these residues might not UV shift in some avian SWS1s. Also, mutagenesis work in avian orders other than passerines and parrots is limited to the pigeon and chicken. Furthermore, birds express a variety of residues at spectral tuning sites, particularly at site 86, whose spectral tuning effects have not yet been explored (Ödeen and Håstad, 2003; Ödeen et al., 2009; 2011). It is therefore unreliable to assume F86 and C90 will also UV shift λmax in other avian orders until further mutagenesis work is done.

The possibility that known spectral tuning residues might not always confer UVS is of particular interest regarding avian species with F86, as the λmax of a wild type bird with F86 has yet to be determined experimentally. Of particular interest are the paleognathous birds. Physiological measurements indicate the ostrich (Struthio camelus) has a VS-type eye, including ocular media that filters out most UV light (wavelength of 0.5 transmittance is 377 nm) and a VS type SWS1

(λmax 403 nm; Wright and Bowmaker, 2001). While MSP was unsuccessful on the rhea (Rhea americana), other retinal characteristics were identical to that of the ostrich, indicating the rhea likely has a VS-type SWS1 as well (Wright and Bowmaker, 2001). In contrast, a recent sequencing survey identified both F86 and C90 in the SWS1 genes of both species (Aidala et al., 2012) (but see Ödeen and Håstad, 2003). This suggests F86 and C90 might not always be capable of UV shifting λmax in avian SWS1 pigments. One must, therefore consider the 93

possibility that avian wild type pigments with these residues might be VS. Certainly these species present themselves as an interesting system to investigate further.

Here we have shown that known spectral tuning sites affect C. nuchalis SWS1 similarly as they do in other avian species, suggesting SWS1 spectral tuning mechanisms are unusually consistent across birds. The potential spectral tuning roles of many sites remain a mystery. Given the variation in spectral tuning sites in mammals and across vertebrates, and the diversity in avian SWS1 genes that has not yet been examined experimentally, it is not unlikely other spectral tuning sites exist birds. Correspondingly, even more spectral variation in SWS1 λmax might exist. Indeed, dramatic spectral variation exists in closely related groups of fish, which also possess tetrachromatic colour vision (e.g. Carleton et al., 2005). Future studies to investigate uncharacterized spectral tuning sites and to determine λmax of birds in other avian orders are necessary.

3.4.3 Function of UV vs. violet sensitivity

Hypotheses to explain the function of UV type pigments are based on the idea that UVS improves the viewer’s ability to detect UV signals. In C. nuchalis, males display a patch of feathers on their head to the female during courtship (Marshall, 1954). These feathers are pink and orange to the human eye, but also reflect in the UV (Marshall, 1954; Endler et al., 2005). If the UV component of this patch is important, it seems a VS pigment has sufficient sensitivity in the short wave range to fulfill the requirement of perceiving UV signals. Alternatively the UV component of the signal could be irrelevant to these birds. In these circumstances, there would be no selective pressure to improve perception of UV signals in C. nuchalis. In a closely related species, the satin bowerbird (Ptilonorhynchus violaceus), even though UV plumage coloration predicts the intensity of infection from blood parasites, feather growth rate, and body size (Doucet, 2003a), blue colours are important for signaling, not UV (Savard et al., 2011). Both species would, therefore support the hypothesis that bowerbird plumage is less important in mate choice, and instead functions in species recognition (Endler and Day, 2006).

It is generally thought that UVS type pigments offer an advantage as they improve sensitivity in this short wave range (Hausmann et al., 2003). Here we have shown C. nuchalis does not have UVS, despite the presence of UV colours in the courtship display (Endler et al., 2005), and the

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importance of UV signals in a number of passerine species (Andersson and Amundsen, 1997; Hunt et al., 1998; Alonso-Alvarez, 2004). This brings one to question why C. nuchalis does not have a UVS type SWS1. Many birds with VS pigments can still perceive some UV because SWS1 cone oil droplets are effectively transparent to light in this range (Bowmaker 1980) and in all but a few species that have been studied so far, avian ocular media transmits most short wavelength light (Hart et al., 2005, and citations therein). In the C. nuchalis, the oil droplets of VS single cones were transparent and the wavelength of 0.5 normalized transmittance of the ocular media is 349 nm (Coyle et al., 2012). So it seems that the some UV light is reaching the retina, and the VS type SWS1 has sufficient UV sensitivity to perceive light in this range.

Compared to VS pigments, UVS pigments have many unique properties including: a deprotonated SB link (Kusnetzow et al., 2004), slow retinal release (Chen et al., 2012), a tightly packed binding pocket (Das et al., 2004), increased dark state stability (Luo et al., 2011), narrow absorption curve bandwidth (Govardovskii et al., 2000; Tsutsui and Shichida, 2010), but decreased quantum yield (Tsutsui et al., 2007). If birds with VS-type vision can sufficiently perceive UV signals yet there are a number of properties that vary among these two sub-types, the wavelength difference between UVS and VS type pigments might not be the only, or the most important, functional difference between these two opsin subtypes. The consequences these properties might have on visual perception are not yet clear, but functional tradeoffs among them are most certainly involved in the evolution of UVS in birds and other vertebrates. Further biochemical and mutagenesis studies are necessary to refine the functional differences between UVS and VS type SWS1 pigments.

3.5 Conclusions

This study contributes to the current understanding of the evolution of UVS in birds by exploring the function and evolution of SWS1 pigments in passerines: The SWS1 of C. nuchalis is shown to have a VS-type λmax. Experimental evidence indicates that although the passerine and parrot ancestors evolved UVS by the same molecular mechanism, UVS evolved independently in these two groups as the SWS1 of their shared ancestor was VS, as was the ancestral passerine SWS1.

The C. nuchalis SWS1 λmax is affected similarly by C86S, C86F and S90C as other avian SWS1s. Results suggest spectral tuning in avian SWS1 pigments birds is unusually consistent,

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but in doing so highlight the importance of investigating the diversity of avian spectral residues in future mutagenesis studies.

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3.6 Tables

Table 1. Degenerate oligonucleotides for PCR

Direction of Namea Target opsin Sequence 5' - 3' primer AA siteb AvesRH2_1018R RH2 gac gga sga gac ctc rgt ytt gct R 1018 AvesRH2_898R RH2 tca tga gsa crt aga tga ygg ggt t R 898 AvesRH2_179F RH2 tgg tca cct tca arc aca aga agc t F 179 AvesRH2_785R RH2 gcr tag ggy gtc cag gcc agc at R 785 VertS2_103R SWS2 aag tac ats tgg gag aag ctg ta R 103 VertS2_315R SWS2 cga vcg gaa ctg ytk gtt cat R 315 VertS2_95F SWS2 ttc tac agc ttc tcs cag atg tac tt F 95 VertS2_22F SWS2 agc ccn ttc ctg gtv ccs ca F 22 AvesS2_258R SWS2 cac cat cac vay yac cat cyt sgt R 258 VertUV_243F SWS1 acg cag aag gci gag mri gar gt F 243 VertUV_232F SWS1 gcc gtg gcc gci car car car ga F 232 TetUV_187F SWS1 tgc gcc cig act cct aya cn F 187 VertUV_230R SWS1 ctg ctg cgc cgc iac igc nyk nag R 237 TetUV_239R SWS1 tcc tgc tgc tgi gci gcn acn gc R 239 AvesUV_306R SWS1 gaa ctg ctt gtt cat raa rca rta R 313 VertUV_230F SWS1 ctg cgc gcc gtc gci gcn car ca F 230 AvesUV_306R SWS1 gaa ctg ctt gtt cat raa rca rta R 306

Note - Primers have been used to successfully isolate opsins from birds, snakes, turtles, & squamates. aAves; degenerate for birds, Vert; degenerate for vertebrates, Tet; degenerate for all vertebrates except fish. bAmino acid site in bovine RH1 corresponding to the 5’ end of the primer.

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Table 2. Spectral absorbance characteristics measured for wild type C. nuchalis SWS1 pigments and site-directed mutants expressed in HEK293T cells, with the corresponding putative ancestral states in Passeriformes and Psittaciformes according to reconstruction of sites 86, 90 & 93 indicated.

Reconstructed Residue Spectral ancestral Shift ratio a b c d e Mutation node 86 90 93 λmax (nm) n (nm) Amax (A280/Amax) GBS1 wt Passerine C S T 402.97 ± 0.22 3 0.09 3.77 S90C Passerida C C T 363.05 ± 0.05 2 -40 0.04 4.53 Passerine + C86S S S T 403.05 ± 0.12 2 0 0.13 3.42 Parrots C86Ff F C T 365 ± 1 -38 0.09 4.74 C86S/S90C S C T 362.95 ± 0.26 2 -40 0.04 5.45

a Reconstructed sites 86, 90, & 93 created in C. nuchalis background. b Data values are given as c mean ± standard deviation. λmax shifts from C. nuchalis wild type pigment are expressed as d e negative for blue shifts. Amax is the absorbance of a given pigment at its λmax. A280/Amax is the ratio of absorbance of a given pigment at 280 nm and its visible λmax and represents the f proportion of expressed protein that is functional. λmax of single mutant C86F calculated from fitting difference spectra of dark and acid denatured species.

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Table 3. Likelihood ratio tests (LRTs) from Branch-Site analyses of the avian SWS1 dataset with different 'foreground' lineages.

Foreground branch # ∆2ι p-value Passerida & Psittaciformes 2+5 3.21792 0.0364 * Passeriformes & Psittaciformes 1 0.00000 0.5000 Psittaciformes 2 4.50852 0.0169 * Passeriformes 3 1.76714 0.0919 Bowerbird 4 0.00000 0.5000 Passerida 5 0.00000 0.5000 Note- #, branch number in supplementary Fig. S3 ; ∆2ι , likelihood ratio test

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3.7 Figures

Figure 1. (Following page) Alignment of visual pigment sequences in C. nuchalis. Numbering is according to Bovine RH1. The seven transmembrane domains (TMD) (Palczewski, 2000) are indicated by gray shading. Key functional sites are boxed: (1) C110, C185, and C187 involved in disulphide bond formation (Karnik and Khorana, 1990); (2) E113, the counterion to the proton of the Schiff base (SB) (Sakmar et al., 1989); (3) K296, covalently linked to the chromophore via a SB link (Dratz and Hargrave, 1983); (4) palmitoylation sites C322 and C323 in RH1 and RH2 opsins, and C322 in the LWS and SWS opsins (Ovchinnikov et al., 1988; Tachibanaki et al., 2005); (5) multiple S and T residues in the C-terminus that are likely phosphorylation targets (Ohguro, 2000). All site numbers are according to corresponding sites in bovine RH1. The sequence of the SWS2 gene is missing 6 amino acids at 5’ end. The intron locations of SWS1 are at residues G119, R177-Y178, V233 and Q312-F313, underlined and emboldened. Known spectral tuning sites for each visual pigment are as follows: RH1- 83, 292, and 299, (Nathans, 1990; Fasick and Robinson, 2000; Sugawara et al., 2005; 2010); RH2 - 122, 222, and 295 (Sakmar et al., 1989; Zhukovsky and Oprian, 1989; Heath et al., 1997); LWS – 100, 164, 181, 214, 261, 269, 217, 292 (Asenjo et al., 1994; Yokoyama and Raldwimmer, 2001), and Cl- binding sites 181 and 184 (Wang et al., 1993). SWS2 - 46, 49, 52, 91, 93, 94, 207 261, 269 and 292 (Takahashi and Ebrey, 2003; Yokoyama and Tada, 2003). SWS1 – 86, 90, 93, 114, 118 (Wilkie et al., 2000; Yokoyama and Shi, 2000; Fasick et al., 2002; Carvalho et al., 2012)

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C TMD I nCn_SWS1 M------DEDEFYLFKNQSSVGPWDG---PQYHIAPMWAFYLQTIFMGVVFVVGTPLNAIVLIVTVKYK [ 66] CCn_RH1 M------NGTEGQDFYVPMSNKTGVVRSPFEYPQYYLAEPWKFSALAAYMFMLILLGFPINFLTLYVTIQHK [ 66] CCn_RH2 M------NGTEGINFYVPMSNKTGVVRSPFEYPQYYLAEPWKYRLVCCYIFFLISTGFPINFLTLLVTFKHK [ 66] CCn_LWS MATWDGAVFAARRRHDDDDTTRDSVFTYTNSNNTRGPFEGPNYHIAPRWVYNLTSLWMIFVVVASVFTNGLVLVATAKFK [ 66] CCn_SWS2 ------??????RDELP?DFYISAALDAPNLTALSPFLVPQTHLGSPGVFRAMAAFMFLLIALGVPVNALTVVCTAKYK [ 66]

TMD II TMD III CCn_SWS1 KLRQPLNYILVNISFSGFLCCIFSVFTVFVSSAQGYFVFGKHMCALEGFAGATGGLVTGWSLAFLAFERYIVICKPFGNF [146] CCn_RH1 KLRTPLNYILLNLAVANLFMVFGGFTTTMYTSMNGYFVFGVTGCYIEGFFATLGGEIALWSLVVLAIERYVVVCKPMSNF [146] CCn_RH2 KLRQPLNYILVNLAVADLCMACFGFTVTFYTAWNGYFVFGPIGCAVEGFFATLGGQVALWSLVVLAIERYIVICKPMGNF [146] CCn_LWS KLRHPLNWILVNLAVADLGETVIASTISVVNQIFGYFILGHPMCIIEGYTVSACGITALWSLAIISWERWFVVCKPFGNI [146] CCn_SWS2 KLRSHLNYILVNLAVANLLVVCVGSTTAFYSFSQMYFALGPTACKVEGFAATLGGMVSLWSLAVVAFERFLVICKPLGNF [146]

TMD IV TMD V CCn_SWS1 RFSSRHALLVVAATWVIGISVAIPPFLGWSRYVPEGLQCSCGPDWYTVGTKYKSEYYTWFLFIFCFIVPLSLIIFSYSQL [226] CCn_RH1 RFGENHAILGVAFSWIMALACAAPPLFGWSRYIPEGMQCSCGIDYYTLKPEVNNESFVIYMFVVHFMIPLLIIFFCYGNL [226] CCn_RH2 RFSASHAMMGIVFTWVMAISCAAPPLFGWSRYIPEGMQCSCGPDYYTHNPDFHNESYVLYMFVIHFIIPVIIIFFSYGRL [226] CCn_LWS KFDGKLAVAGVLFSWIWSCAWTAPPIFGWSRYWPHGLKTSCGPDVFSGSTDPGVQSYMVVLMVTCCLFPLSVIIFCYLQV [226] CCn_SWS2 TFRGSHAVLGCAITWIFGLIASAPPLFGWSRYIPEGLQCSCGPDWYTTDNKWNNESYVIFLFCFCFGFPLAVIVLSYGRL [226]

TMD VI TMD VII CCn_SWS1 LSALRAVAAQQQESATTQKAEREVSRMVVVMVGSFCLCYVPYAALAMYMVNNRDHGLDLRLVTVPAFFSKSACVYNPIIY [306] CCn_RH1 VCTVKEAAAQQQESATTQKAEKEVTRMVIIMVIAFLICWVPYASVAFYIFTNQGSDFGPIFMTIPAFFAKSSAIYNPVIY [306] CCn_RH2 VCKVREAAAQQQESATTQKAEKEVTRMVILMVLGFMLAWTPYAVVAFWIFTNKGADFTATLMAVPAFFSKSSSLYNPIIY [306] CCn_LWS WLAIRAVAAQQKESESTQKAEKEVSRMVVVMILAYIFCWGPYTFFACFAAANPGYAFHPLTAALPAFFAKSATIYNPIIY [306] CCn_SWS2 LLTLRAVAKQQEQSATTQKAEREVTKMVVVMVLGFLVCWAPYSAFALWVVTHRGRHFDVGLASIPSVFSKASTVYNPVIY [306]

CCn_SWS1 CFMNKQFRACIMETVC-GR-PMTDDSEMSSSAQ-RTEVSSVSSSQVSPS* [356] CCn_RH1 IVMNKQFRNCMITTLCCGKNPLGDEDTSAG----KTETSSVSTSQVSPA* [356] CCn_RH2 VLMNKHFRNCMNTTFCCGKNPFGDEDTSSTVSHNKTEVSSVSSSQVSPA* [356] CCn_LWS VFMNRQFRNCILQLF--GKKV--DDGSEVSTS--RTEVSSVSNSSVSPA* [356]

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Figure 2. (Following page) Evolutionary relationships of the C. nuchalis opsins with other vertebrate opsins created using Maximum likelihood and Bayesian methods. All opsin sequences obtained from the great bowerbird in this study and other vertebrate opsin sequences obtained from NCBI were aligned using Clustal W (Larkin et al., 2007). Large gaps in the alignment were excluded to reduce errors when estimating evolutionary distances. Maximum Likelihood methods were implemented in the program PHYML 3.0 (Guindon and Gascuel, 2003; Guindon et al., 2005), Bayesian inference in MrBayes 3.2.1 (Ronquist and Huelsenbeck, 2003) both under the HKY+I+G model, the best model favoured under the Akaike Information Criterion (AIC) using MrModeltest2.3 (Nylander, 2008). For likelihood analyses, bootstrapping methods were used to assess the degree of confidence in nodes of the phylogeny (Felsenstein, 1985).

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103

Figure 3. UV-visible absorption spectra of in the C. nuchalis SWS1 after in vitro expression and purification. C. nuchalis SWS1 protein was purified from transfected HEK293T cells in detergent solution (pH 6.6) following incubation with 11-cis-retinal. The visible absorption maximum, λmax, is 403 nm. Inset A) Dark-minus-light difference spectrum, B) Dark-minus-acid difference spectrum.

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Figure 4. UV-visible absorption spectra of purified mutants created in C. nuchalis SWS1 visual pigment expressed in HEK293T cells. Dark spectra of (a) single mutant S90C, (b) single mutant C86F, (c) single mutant C86S, (d) double mutant C86S/S90C, all recorded at pH 6.6. Insets show dark-minus-acid difference spectra of the mutants after treatment with 100 mM HCl. All C. nuchalis cone opsin mutants form functional visual pigments with various λmax values (indicated for each mutant).

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Figure 5. Hydroxylamine sensitivity of the expressed C. nuchalis SWS1 pigment. A) Reactivity of the C. nuchalis SWS1 pigment with hydroxylamine at 21°C in the dark. Hydroxylamine was added to the pigment to a final concentration of 50 mM at t = 0 minutes and absorption spectra were recorded at t = 2, 4, 6, 8, 12, 14, 16, 18, 20, 25, 30, 35, 40, 45, 60, 75, 105, and 120 minutes. The 0 (dark blue) and 120 (orange) minute spectra are shown. The 403 nm peak that decreased with time and the 363 nm peak that increased with time was due to formation of retinal oxime. Finally, the sample was exposed to light (hυ, purple broken line). B) The absorbance values at 403 nm and 363 nm were plotted as a function of time after addition of hydroxylamine. Half-life for the formation of the retinal oxime in the presence of hydroxylamine was obtained by fitting the plot to a single exponential function.

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Figure 6. (Following page) Ancestral reconstruction and substitution patterns of sites 86, 90 & 93 in Helix 2 of SWS1 genes in Landbirds. Reconstructions were carried out using codon and amino acid-based likelihood models of substitution as implemented in PAML (Yang, 2007). The tree topology is based on the consensus of previously published phylogenies (Barker et al., 2002; 2004; Beresford et al., 2005; Hackett et al., 2008; Irestedt and Ohlson, 2008; Johansson et al., 2008; Wright et al., 2008; Gardner et al., 2010; Driskell et al., 2011; Jønsson et al., 2011; Lee et al., 2011; Suh et al., 2011; Wang et al., 2011). GenBank Accession numbers and names of species given in Table S1. Higher relationships within certain orders are collapsed and shown as triangles. Black dots mark the reconstructed nodes for Passerine + Parrot and Passerine ancestors. Boxes beside each node display the reconstructed residues at sites 86, 90 and 93, as well as predicted opsin types, whether UV- or Violet-sensitive, as created in the background of C. nuchalis SWS1. The shared ancestor of passerines and parrots and the passerine ancestor are Violet-type. Substitutions at sites 86 and 90 elsewhere in the phylogeny are marked along corresponding lineages showing parallel evolution of C90 in a number of lineages. The posterior probabilities for all reconstructed sites as calculated in PAML, were high across the tree (PP > 0.95).

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3.8 Supplementary data 3.8.1 Supplementary tables

Table S1. Species names & accession numbers corresponding to sequence data used in both datasets for molecular evolution analyses: Aves SWS1 gene (AvS1) and Landbird Helix 2 (LB) AvS1 Order Family Species Common Name Accession # Reference LB name name Galliformes Phasianidae Gallus gallus chicken M92039 Okano et al., 1992 G gallu Bucerotiformes Upupidae Upupa epops Eurasian hoopoe AY227191 Ödeen & Håstad 2003 Upupa Coraciiformes Alcedinidae Alcedo atthis common kingfisher AY227169 Ödeen & Håstad 2003 Alcedo Coraciiformes Coraciidae Coracias garrulus common roller AY227170 Ödeen & Håstad 2003 Coracias great spotted Piciformes Picidae Dendrocopos major AY227184 Ödeen & Håstad 2003 Dendrocop woodpecker blue-crowned Trogoniformes Trogonidae Trogon curucui AY227190 Ödeen & Håstad 2003 Trogon trogon Falconiformes Falconidae Falco peregrinus peregrine falcon AY227157 Ödeen & Håstad 2003 Falco Corvus corone Passeriformes Corvidae hooded crow AY227176 Ödeen & Håstad 2003 CorvusC cornix Passeriformes Corvidae Pica pica Eurasian magpie GQ305970 Ödeen & Håstad 2009 Pica Cyclarhis rufous-browed Passeriformes Vireonidae HE601826 Ödeen et al., 2011b Cyclarhis gujanensis peppershrike Eurasian golden Passeriformes Oriolidae Oriolus oriolus HE601828 Ödeen et al., 2011b Oriolus oriole magnificent Passeriformes Paradisaeidae Ptiloris magnificus HE601835 Ödeen et al., 2011b Ptiloris riflebird Browne et al., Passeriformes Corvidae Corvus frugilegus rook DQ451006 CorvusF (GenBank 2006) Coracina black-faced Passeriformes Campephagidae HE601825 Ödeen et al., 2011b Coracina novaehollandiae cuckooshrike Passeriformes Dicruridae Dicrurus bracteatus spangled drongo HE601829 Ödeen et al., 2011b Dicrurus Cyanocorax Passeriformes Corvidae plush-crested jay HE601832 Ödeen et al., 2011b Cyanocora chrysops Passeriformes Dicruridae Rhipidura New Zealand HM159132 Hauber & Chong Rhipidura 109

fuliginosa fantail (GenBank 2010) Creadion Hauber & Chong Passeriformes Callaetidae saddleback Creadion carunculatus HM159129 (GenBank 2010) Lichenostomus yellow-tinted Passeriformes Meliphagidae GQ305955 Ödeen & Håstad 2010 Lichenost flavescens honeyeater Acanthorhynchus Passeriformes Maluridae eastern spinebill GQ305959 Ödeen & Håstad 2010 Acanthorh tenuirostris broad-billed Passeriformes Maluridae Malurus grayi HE588093 Ödeen et al., 2011a MalurusG fairywren Malurus Passeriformes Maluridae emperor fairywren HE588094 Ödeen et al., 2011a MalarusCy cyanocephalus Passeriformes Maluridae Malurus amabilis lovely fairywren HE588095 Ödeen et al., 2011a MalarusA red-winged Passeriformes Maluridae Malurus elegans HE588099 Ödeen et al., 2011a MalurusE fairywren Malurus Passeriformes Maluridae splendendens turquoise fairywren HE588101 Ödeen et al., 2011a MalurusS musgravi purple-crowned HE588108, Passeriformes Maluridae Malurus coronatus Ödeen et al., 2011a MalurusCo fairywren HE588109 Malurus red-backed HE588111- Passeriformes Maluridae Ödeen et al., 2011a MalurusM melanocephalus fairywren HE588113 Malurus white-winged HE588114- Passeriformes Maluridae leucopterus Ödeen et al., 2011a MalurusL fairywren HE588116 edouradi orange crowned Passeriformes Maluridae Clytomias insignis HE588121 Ödeen et al., 2011a Clytomyia fairywren Passeriformes Maluridae Amytorins barbatus grey grasswren HE588123 Ödeen et al., 2011a Amytornis HM159130, Hauber & Chong Passeriformes Acanthizidae Gerygone igata grey gerygone Gerygone HM159131 (GenBank 2010) Menura Passeriformes Menuridae superb lyrebird HE601819 Ödeen et al., 2011b Menura novaehollandiae Sericulus Passeriformes Ptilonorhynchidae regent catbird HE588091 Ödeen et al., 2011a Sericulus chrysocephalus Pomatostomus grey-crowned Passeriformes Pomatostomidae HE601820 Ödeen et al., 2011b PomatostT temporalis babbler Pomatostomus chestnut-crowned Passeriformes Pomatostomidae HE601821 Ödeen et al., 2011b PomatostR ruficeps babbler Orthonyx Australian Passeriformes Orthonychidae HE601822 Ödeen et al., 2011b Orthonyx temminckii logrunner 110

Passeriformes Cnemophilidae Cnemophilus loriae Loria's satinbird HE601823 Ödeen et al., 2011b Cnemophil Toxorhamphus slaty-headed Passeriformes Melanocharitidae HE601824 Ödeen et al., 2011b Toxorham poliopterus longbill Chlamydera Passeriformes Ptilonorhynchidae great bowerbird This Study C nucha Chlamyder nuchalis HE601851, Passeriformes Sittidae Sitta europaea Eurasian nuthatch Ödeen et al., 2011b Sitta HE601852 Passeriformes Sturnidae Sturnus vulgaris common starling AY227180 Ödeen & Håstad 2003 Sturnus Raman & Andersson Passeriformes Muscicapidae Luscinia svecica bluethroat AY274225 L sveci LusciniaS (GenBank 2003) Raman & Andersson Passeriformes Muscicapidae Luscinia calliope Siberian rubythroat AY274226 L calli LusciniaC (GenBank 2003) chalk-browed Passeriformes Mimidae Mimus saturninus GQ305972 Ödeen & Håstad 2009 Mimus mockingbird Passeriformes Turdidae Turdus iliacus redwing HE601854 Ödeen et al., 2011b Turdus Raman & Andersson Passeriformes Paridae Parus caeruleus blue tit AY274220 P caeru (GenBank 2003) Raman & Andersson Passeriformes Paridae Parus major great tit AY274221 P major Parus (GenBank 2003) Raman & Andersson Passeriformes Paridae Parus palustris marsh tit AY274222 P palus (GenBank 2003) Passeriformes Passeridae Taeniopygia guttata zebra finch AF222331 Yokoyama et al., 2000 T gutta Taeniopyg Passeriformes Fringillidae Serinus canaria common canary AJ277922 Das et al., 1999 S canar Serinus yellow crowned Raman & Andersson Passeriformes Passeridae Euplectes afer AY274223 E aferx Euplectes bishop (GenBank 2003) Passeriformes Estrilidae Amadina fasciata cut-throat finch FJ440639 Ödeen et al., 2009 Amadina white-headed Passeriformes Estrilidae Lonchura maja FJ440641 Ödeen et al., 2009 Lonchura munia Passeriformes Passeridae Neochmia modesta plum-headed finch FJ440642 Ödeen et al., 2009 Neichima Passeriformes Nectariniidae Cinnyris pulchellus beautiful sunbird GQ305964 Ödeen & Håstad 2010 Cinnyris Passeriformes Motacillidae Anthus cervinus red-throated pipit HE601865 Ödeen et al., 2011b Anthus Western Passeriformes Icteridae Sturnella neglecta HE601868 Ödeen et al., 2011b Sturnella meadowlark Phylloscopus Passeriformes Phylloscopidae willow warbler AY227181 Ödeen & Håstad 2003 Phyllosco trochilus Passeriformes Timaliidae Leiothrix lutea red-billed leiothrix FJ440645 Ödeen et al., 2009 Leiothrix Passeriformes Hirundinidae Hirundo rustica barn swallow HE601843 Ödeen et al., 2011b Hirundo

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Donacobius black-capped Passeriformes Donacobiidae HE601848 Ödeen et al., 2011b Donacobiu atricapilla donacobius Hauber & Chong Passeriformes Zosteropidae Zosterops lateralis silver-eye Zosterops HM159125 (GenBank 2010) Passeriformes Petroicidae Petroica rosea rose robin HE601839 Ödeen et al., 2011b PetroicaR Hauber & Chong Passeriformes Acanthisittidae Acanthisitta chloris rifleman Acanthisi HM159126 (GenBank 2010) Passeriformes Pittidae Hydrornis elliotii bar-bellied pitta HE601813 Ödeen et al., 2011b Pitta Myrmeciza southern chestnut- Passeriformes Thamnophilidae GQ924591 Seddon et al., 2010 Myrmeciza hemimelaena tailed antbird Phlegopsis black-spotted bare- Passeriformes Thamnophilidae GQ924592 Seddon et al., 2010 Phlegopsi nigromaculata eye white-bearded Passeriformes Pipridae Manacus manacus AY227182 Ödeen & Håstad 2003 Manacus manakin Onychorhynchus Amazonian royal Passeriformes Tityridae HE601817 Ödeen et al., 2011b Onychorhy coronatus flycatcher Myiarchus brown-crested Passeriformes Tyrannidae AY227183 Ödeen & Håstad 2003 Myiarchus tyrannulus flycatcher Camptostoma southern beardless Passeriformes Tyrannidae HE601814 Ödeen et al., 2011b Camptosto obsoletum tyrannulet Passeriformes Tyrannidae Xolmis irupero white monjita HE601815 Ödeen et al., 2011b Xolmis fork-tailed Passeriformes Tyrannidae Tyrannus savana HE601816 Ödeen et al., 2011b Tyrannus flycatcher Calyptorhynchus Carnaby’s black Psittaciformes Cacatuidae HM150800 Carvalho et al., 2010 C latir Calyptorh latirostris cockatoo Eolophus Psittaciformes Cacatuidae galah HM150801 Carvalho et al., 2010 E rosei Elophus roseicapilla sulphur-crested Psittaciformes Cacatuidae Cacatua galerita HM150802 Carvalho et al., 2010 C galer Cacatua cockatoo Psittaciformes Psittacidae Ara macao scarlet macaw HM150792 Carvalho et al., 2010 AraM Psittaciformes Psittacidae Amazona versicolor St. Lucia amazon HM150793 Carvalho et al., 2010 Amazona blue-and-yellow Psittaciformes Psittacidae Ara ararauna HM150803 Carvalho et al., 2010 AraA macaw Psittaciformes Psittacidae Psittacus erithacus grey parrot HM150804 Carvalho et al., 2010 Psittacus red-and-green Psittaciformes Psittacidae Ara chloropterus HM150805 Carvalho et al., 2010 AraC macaw Anodorhynchus Psittaciformes Psittacidae hyacinth macaw HM150806 Carvalho et al., 2010 Anodorhyn hyacinthinus 112

Psittaciformes Psittacidae Platycercus elegans crimson rosella HM150794 Carvalho et al., 2010 P elega Platycerc Barnardius Psittaciformes Psittacidae zonarius Twenty eight parrot HM150799 Carvalho et al., 2010 B zonar Barnardiu semitorquatus Melopsittacus M Psittaciformes Psittacidae budgerigar Y11787 Wilkie et al., 1998 Melopsitt undulatus undul Psittaciformes Strigopidae Nestor notabilis Kea HM150807 Carvalho et al., 2010 Nestor Spheniscus S Ciconiiformes Spheniscidae Humboldt's penguin AJ277991 Wilkie et al., 2000 humboldti humbo Columbiformes Columbidae Columba livia pigeon AJ238856 Wilkie et al., 2000 C livia Phalacrocorax Pelecaniformes Phalacrocoracidae great cormorant carbo EF568933 Carvalho et al., 2007

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Table S2. Likelihood scores, parameter estimates, likelihood ratio test P values from Branch-Site model analyses of the avian SWS1 dataset with different 'foreground' lineages.

Site class 0 Site class 1 Site class 2 LRT

p0 p2 Foreground # Model -lnL np k ω0 ω1 p1 (%) ω2 P-value (%) (%) branch Passerida & 2+5 BrS_null -3061.02375 39 3.164 0.025 87.2 1 8.8 1.000 9.2 0.0364* Psittaciformes BrS_alt -3059.41479 40 3.188 0.026 90.0 1 6.2 2.614 6.4

Passeriformes & 1 BrS_null -3076.69207 39 3.121 0.031 0.0 1 95.1 1.000 100.0 0.5000 Psittaciformes BrS_alt -3076.69207 40 3.121 0.031 0.0 1 95.1 1.000 100.0

2 BrS_null -3076.57298 39 3.124 0.030 92.9 1 2.5 1.000 2.6 0.0169* Psittaciformes BrS_alt -3074.31872 40 3.174 0.030 94.1 1 1.7 62.09 1.8

3 BrS_null -3075.47731 39 3.110 0.030 93.4 1 1.7 1.000 1.8 0.0919 Passeriformes BrS_alt -3074.59374 40 3.095 0.031 94.4 1 1.0 95.37 1.1

4 BrS_null -3072.13605 39 3.134 0.029 0.0 1 95.1 1.000 100.0 0.5000 Bowerbird BrS_alt -3072.13605 40 3.134 0.029 0.0 1 95.1 1.000 100.0

5 BrS_null -3069.58420 39 3.140 0.027 57.9 1 37.5 1.000 39.3 0.5000 Passerida BrS_alt -3069.58420 40 3.140 0.027 57.9 1 37.5 1.000 39.3

NOTE— #, branch number in supplementary Figure S3; lnL, natural log likelihood score; np, number of parameters, k, transition-to-transversion rate ratio; ω, non synonymous-to-synonymous rate ratio (dN/dS); p, proportion; LRT, likelihood ratio test.

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Table S3. Likelihood scores, parameter estimates, and likelihood ratio test P values from Clade model analyses of the avian SWS1 dataset with different 'foreground' lineages.

Purifying Neutral Divergent selection site pressure selection site class site class class LRT Foreground Tree p p p Model ω np -lnL k ω 0 ω 1 ω , ω 2 Null df P-value branch (#) Length 0 (%) 1 (%) 2 3 (%) M2a_rel 1 2.372 40 -3030.1889 3.283 0.162 22.3 1 0 0.006 77.7 M1a (K)2 2.270 38 -3076.8276 3.114 0.031 95.1 1 4.9 CmC Passerida (2) 0.2 2.427 41 -3028.29773 3.312 0.159 22.5 1 0 0.003 77.5 M2a_rel 1 0.02590* 0.012 M1a 2 0.00000 CmC Psittacidae (5) 0.2 2.367 41 -3030.1485 3.283 0.162 22.3 1 0 0.006 77.7 M2a_rel 1 0.38806 0.005 M1a 2 0.00000 Passerida & CmC Psittaciformes 0 2.445 41 -3028.8539 3.306 0.160 22.3 1 0 0.003 77.7 M2a_rel 1 0.05113* (2,5) 0.009 M1a 2 0.00000 Passerida, CmC Psittaciformes 0.5 2.449 42 -3028.1628 3.316 0.159 22.4 1 0 0.003 77.6 M2a_rel 2 0.06592 (2&5) 0.005 M1a 3 0.00000 NOTE— #, branch number in supplementary Figure S3; np, number of parameters; -lnL, natural log likelihood score; k, transition-to-transversion rate ratio; ω, non synonymous-to-synonymous rate ratio (dN/dS); p, proportion; LRT, likelihood ratio test; df degrees of freedom for likelihood ratio test.

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Table S4. Likelihood scores, parameter estimates, and likelihood ratio test P values from Random Sites model analyses of the avian SWS1 dataset.

# site LRT Model np -lnL class k Parameter Estimates Null df P-value

M0 37 -3088.258 3.145 ω= 0.03643

M1a: neutral 38 -3076.828 3.114 ω= 0.03099 ω1 = 1

p= 0.95105 p1 = 0.04895

M2a: selection 40 -3076.829 3.114 ω0= 0.03099 ω1= 1.000 ω2= 1.000 M1a 2 0.0000 **

p0= 0.95105 p1= 0.03031 p2= 0.01864 ** M3: discrete 41 -3030.139 3.291 ω0= 0.00399 ω1=0.05509 ω2=0.17788 M0 4 0.0000

(K=3) p0= 0.72374 p1= 0.09276 p2=0.18349

M7: beta 38 -3030.541 10 3.309 p= 0.18984 q= 4.03318 ** M8: beta&ω 40 -3030.541 11 3.309 p= 0.18985 q= 4.03333 M0 3 0.0000

p0= 0.99999 p1= 0.00001 M7 2 1.0000 ω= 1 NOTE— np, number of parameters; -lnL, natural log likelihood score; k, transition-to-transversion rate ratio; ω, non synonymous-to-synonymous rate ratio (dN/dS); LRT, likelihood ratio test; p, proportion; K, number of discrete classes; df degrees of freedom for likelihood ratio test.

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3.8.2 Supplementary figures

Figure S1. Alignment of opsin gene fragments from Landbirds used in ancestral reconstruction indicating sites 86, 90 & 93.

7 8 8 9 9 0 CorvusF LNYILVNISFSGFLCCIFSVFTVFISSSQG 234567890123456789012345678901 Pica LNYILVNISFSGFLCCIFSVFTVFISSSQG Alcedo LNYILVNISFSGFISCIFSVFTVFVSSSQG Cyclarhis LNYIL?N?SVSGLMCCVFCIFTVFVASSQ- Coracias LNYILVNISFSGFISCIFSVFTVFVSS--- Coracina LNYILVNVSFSGFLCCIFSVFTVF------Dendrocop LNYILVNISFSGFLSCIFSVFTVFVSSSQG Oriolus LNYILVNVSFSGFLCCIFSVFTVFVSSAQG Trogon LNYILVNISLGGFIFCVFSVFTVFVSS--- Dicrurus LNYILVNISFSGFLCCIFSVFTVFVSSSQG Upupa LNYILVNISFSGFMSCIFSVFTVFVSSSQG Cyanocora --YILVNISFSGFLCCIFSVFTV------Falco --YILVNISFSGFISCIFSVF?VFVS---- Ptiloris LNYILVNISFSGFLCCIFSVFTVFVSSAQG Acanthisi LNYILVNISLSGLLCCILCVFLVFVASTQG PetroicaR ------NISVSGLMCCIFCLFTVFISSSQG Manacus -NYILVNISFSGFISCIFSVFTV------Parus LNYILVNISVSGLMCCVFCIFTVFVSSSQG Myrmeciza LNYILVNISFSGFLCCIFSVFTVF------Sitta LNYILVNISVSGLMCCIFCIFTVFISSSQG Phlegopsi LNYILVNISFSGFLCCIFSVFTVFV----- Turdus LNYILVNISVSGLMCCVFCIFTVFVSSSQG Pitta LNYILVNISFSGFL?CIFSVFTV------Sturnus ------NISVSGLMCCIFCIFTVFVSSSQG Myiarchus LNYILVNISVSGFMCCIFSVFTVFVSSSQG Mimus ----LVNISVSGLMCCIFCIFTVFVS?SQG Camptosto LNYILVNISVSGFMCCIFSVFTV------LusciniaS LNYILVNISVSGLMCCVFCIFTVFVSSSQG Xolmis LNYILVNISVSGFMCCIFSVFTV------LusciniaC LNYILVNISVSGLMCCVFCIFTVFVSSSQG Tyrannus --YILVNISVSGFMCCIFSVFTVFV----- Phyllosco LNYILVNISVSGLMMCIFCIFTVFVSSSQG Onychorhy LNYILVNISVSGFFCCIFSVFVV------Hirundo LNYILVNISVSGLMMCIFCIFTVFVSSSQG Menura ------NISVSGFFCCIFCVFTVFVSS?QG Donacobiu --YILVNISVSGLMMCIFCIFTVFVSSSQG Sericulus LNYILVNISFSGFLCCIFSVFTVFVSSAQG Leiothrix ------NISVSGLMMCVFCIFTVFVSSSQG Chlamyder LNYILVNISFSGFLCCIFSVFTVFVSSAQG Zosterops ------NISVSGLMMCIFCIF?VFVSSSQG PomatostT LNYILVNISFSGFLCCIFSVFTVFVSSAQG Cinnyris LNYILVNISVSGLMCCVFCIFTVFVSSSQG PomatostR LNYILVNISFSGFLCCIFSVFTVFVSSAQG Serinus LNYILVNISVSGLMCCVFCIFTVFVASSQG Orthonyx LNYILVNISVSGFFCCIFCVFTVFVSSAQG Sturnella LNYILVNISVSGLMCCVFCIFTVFVASSQG Cnemophil LNYILVNMSISGLMCCIFSVFTVF------Anthus LNYILVNISVSGLMCCVFCIFTVF------Toxorhamp LNYILVNISVSGLMCCVFCIFTV------Lonchura LNYILVNISVAGLMCCVFCIFTVFIASSQG Lichenost LNYILVNISFAGFMCCIFSVFTVFVSSAQG Amadina -NYILVNISVSGLMCCVFCIFTVFVASSQG Acanthorh LNYILVNISFAGFMCCIFSVFTVFVS---- Taeniopyg LNYILVNISVSGLMCCVFCIFTVFIASSQG MalurusA LNYILVNISFSGFLCCIFCIFTV------Euplectes LNYILVNISVSGLMCCVFCIFTVFVASSQG MalurusE LNYILVNISFSGFLCCIFCIFTVFVSSSQG Neochmia LNYILVNISVSGLMCCVFCIFTVFIASSQG MalurusCy ------NISFSGFLCCIFCIFTVFVSSSQG Cacatua LNYILVNISFCGFLACIFCIFTVFVSSSQG MalurusS LNYILVNISFSGFLCCIFCIFTVFV----- Eolophus LNYILVNISFCGFLACIFCIFTVFVSSSQG MalurusM LNYILVNISFSGFLCCIFSVFTVFVSSSQG Calyptorh LNYILVNISFCGFLACIFCIFTVFVSSSQG MalurusL LNYILVNISFSGFLCCIFSVFTVFVSS--- Psittacus LNYILVNISFCGFLACIFCIFTVFVSSSQG MalurusCo LNYILVNISFSGFLCCIFSVFTV------AraA LNYILVNISFCGFLACIFCIFTVFVSSSQG MalurusG --YILVNISFSGFLCCIFSVFTVFV----- AraM LNYILVNISFCGFLACIFCIFTVFVSSSQG Clytomyia LNYILVNISFSGFLCCIFSVFTV------AraC LNYILVNISFCGFLACIFCIFTVFVSSSQG Amytornis ---ILVNISFSGFLCCIFSVFTVF------Amazona LNYILVNISFCGFLACIFCIFTVFVSSSQG Gerygone ------NISFSGFMCCIFSVFTVFVSSAQG Anodorhyn LNYILVNISFCGFPACIFCIFTVFVSSSQG Creadion ------NISVSGLMCCVFCIFTVFVSSSQG Platycerc LNYILVNISFCGFLACIFCIFTVFVSSSQG Rhipidura LNYILVNISFSGFLCCIFSVFTVFVSSAQG Barnardiu LNYILVNISFCGFLACIFCIFTVFVSSSQG C C NYILVNISFSGFMCCIFSVFTVF?S Melopsitt LNYILVNISFCGFLACIICIFTVFVSSSQG Nestor LNYILVNISFCGFLACIFCIFTVFVSSSQG

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Figure S2. Amino acid alignment of avian SWS1 opsin sequences for molecular evolution analyses (AvS1). GenBank accession numbers and species names are given in Table S1. The alignment included amino acid sites 46 to 316. Regions at 5’ & 3’ ends were excluded, as sequence data was missing for some species.

G_gallu AFYLQTAFMG IVFAVGTPLN AVVLWVTVRY KRLRQPLNYI LVNISASGFV SCVLSVFVVF VASARGYFVF GKRVCELEAF VGTHGGLVTG WSLAFLAFER P_carbo AFYLQTAFMG FVFLLGTPLN AIVLVVTVKY KKLRQPLNYI LVNVSFSGFI CCLFSVFTVF VSSSQGYFVF GKNMCSLEGF VGATGGLVTG WSLAFLAFER S_humbo AFYLQTAFMG FVFLVGTPFN AVVLVVTVKY KKLRQPLNYI LVNISFSGFI SCIFSVFTVF VSSSQGYFVF GKHMCALEGF VGATGGLVTG WSLAFLAFER C_livia AFYLQTAFMG FVFLVGTPFN AIVLVVTIKY KKLRQPLNYI LVNISFSGFI SCIFSVFTVF VSSSQGYFIF GKDMCALEAF VGATGGLVTG WSLAFLAFER M_buger AFYLQTAFMG FVFMVGTPLN AIVLVVTIKY KKLRQPLNYI LVNISFCGFL ACIICIFTVF VSSSQGYFVF GKHVCAFEGF MGATAGLVTG WSLAFLAFER P_elega AFYLQTAFMG VVFLVGTPLN AIVLVVTIKY KKLRQPLNYI LVNISFCGFL ACIFCIFTVF VSSSQGYFVF GKHVCAFEGF MGATAGLVTG WSLAFLAFER C_galer AFYLQTAFMG FVFLVGTPLN AIVLVVTVKY KKLRQPLNYI LVNISFCGFL ACIFCIFTVF VSSSQGYFVF GKHVCAFEGF MGATAGLVTG WSLAFLAFER C_latir AFYLQTAFMG FVFLVGTPLN AIVLVVTVKY KKLRQPLNYI LVNISFCGFL ACIFCIFTVF VSSSQGYFVF GKHVCAFEGF MGATAGLVTG WSLAFLAFER E_rosei AFYLQTAFMG FVFLVGTPLN AIVLVVTVKY KKLRQPLNYI LVNISFCGFL ACIFCIFTVF VSSSQGYFVF GKHVCAFEGF MGATAGLVTG WSLAFLAFER B_zonar AFYLQTAFMG IVFLVGTPLN AIVLVVTIKY KKLRQPLNYI LVNISFCGFL ACIFCIFTVF VSSSQGYFVF GKHVCAFEGF MGATAGLVTG WSLAFLAFER C_nucha AFYLQTIFMG VVFVVGTPLN AIVLIVTVKY KKLRQPLNYI LVNISFSGFL CCIFSVFTVF VSSAQGYFVF GKHMCALEGF AGATGGLVTG WSLAFLAFER L_sveci -FYLQTIFMG LVLVAGTPLN AIVLIVTVKY KKLRQPLNYI LVNISVSGLM CCVFCIFTVF VSSSQGYFVF GKHVCAFEGF SGATVGLVTG WSLAFLAFER L_calli -FYLQTIFMG LVLVAGTPLN AIVLIVTVKY KKLRQPLNYI LVNISVSGLM CCVFCIFTVF VSSSQGYFVF GKHVCAFEGF SGATVGLVTG WSLAFLAFER P_caeru AFYLQTIFMG LVFVAGTPLN AIVLIVTIKY KKLRQPLNYI LVNISVSGLM CCVFCIFTVF VSSSQGYFVF GKHMCAFEGF AGATGGLVTG WSLAFLAFER P_palus AFYLQTIFMG LVFVAGTPLN AIVLIVTIKY KKLRQPLNYI LVNISVSGLM CCVFCIFTVF VSSSQGYFVF GKHMCAFEGF AGATGGLVTG WSLAFLAFER P_major AFYLQTIFMG LVFVAGTPLN AIVLIVTIKY KKLRQPLNYI LVNISVSGLM CCVFCIFTVF VSSSQGYFVF GKHMCAFEGF AGATGGLVTG WSLAFLAFER S_canar AFYLQTIFMG LVFVAGTPLN AIVLIVTVKY KKLRQPLNYI LVNISVSGLM CCVFCIFTVF VASSQGYFVF GKHMCRFEGF AGATGGMVTG WSLAFLAFER T_gutta AFYLQTIFMG LVFVAGTPLN AIVLIVTIKY KKLRQPLNYI LVNISVSGLM CCVFCIFTVF IASSQGYFVF GKHMCAFEGF AGATGGLVTG WSLAFLAFER E_aferx AFYLQTIFMG LVFVAGTPLN AIVLIVTIKY KKLRQPLNYI LVNISVSGLM CCVFCIFTVF VASSQGYFVF GKHMCAFEGF AGATGGLVTG WSLAFLAFER

G_gallu YIVICKPFGN FRFSSRHALL VVVATWLIGV GVGLPPFFGW SRYMPEGLQC SCGPDWYTVG TKYRSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA P_carbo YIVICKPFGN FRFSSRHALL VVVATWAIGV GVAVPPFFGW SRYVPEGLQC SCGPDWYTVG TKYKSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA S_humbo YIVICKPFGN FRFSSKHAVM VVVATWVIGV GVAIPPFFGW SRYIPEGLQC SCGPDWYTVG TKYKSEYYTW LLFIFCFIVP LSLIIFSYSQ LLSALRAVAA C_livia YIVICKPFGN FRFNSKHALM AVVATWVIGL GVALPPWFGW SRYVPEGLQC SCGPDWYTVG TKYKSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA M_buger YIVICKPLGN FRFTAKHALV VVVATWVIGI GVAIPPFFGW SRYVPEGLQC SCGPDWYTVG TKYRSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA P_elega YIVICKPLGN FRFTSKHALV VVVATWVIGI GVAIPPFFGW SRYVPEGLQC SCGPDWYTVG TKYRSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA C_galer YVVICKPLGN FRFTSKHALV VVVATWVIGV GVAVPPFFGW SRYVPEGLQC SCGPDWYTVG TKYRSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA C_latir YVVICKPLGN FRFTSKHALV VVVATWVIGV GVAVPPFFGW SRYVPEGLQC SCGPDWYTVG TKYRSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA E_rosei YVVICKPLGN FRFTSKHALV VVVATWVIGV GVAVPPFFGW SRYVPEGLQC SCGPDWYTVG TKYRSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA B_zonar YIVICKPLGN FRFTSKHALV VVVATWVIGI GVAIPPFFGW SRYVPEGLQC SCGPDWYTVG TKYRSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA C_nucha YIVICKPFGN FRFSSRHALL VVAATWVIGI SVAIPPFLGW SRYVPEGLQC SCGPDWYTVG TKYKSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA L_sveci YIVICKPFGN FRFNSRHALL VVAATWIIGV GVAIPPFFGW SRYIPEGLQC SCGPDWYTVG TKYKSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA L_calli YIVICKPFGN FRFNSRHALL VVAATWIIGV GVAIPPFFGW SRYIPEGLQC SCGPDWYTVG TKYKSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA P_caeru YIVICKPFGN FRFNSRHALL VVAATWIIGV GVAVPPFFGW SRYVPEGLQC SCGPDWYTVG TKYKSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA P_palus YIVICKPFGN FRFNSRHALL VVAATWIIGV GVAVPPFFGW SRYVPEGLQC SCGPDWYTVG TKYKSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA P_major YIVICKPFGN FRFNSRHALL VVAATWIIGV GVAVPPFFGW SRYVPEGLQC SCGPDWYTVG TKYKSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA S_canar YIVICKPFGN FRFNSRHALL VVAATWIIGV GVAIPPFFGW SRYIPEGLQC SCGPDWYTVG TKYKSEYYTW FLFIFCFIIP LSLIIFSYSQ LLSPCGAVAA T_gutta YIVICKPFGN FRFNSRHALL VVAATWIIGV GVAIPPFFGW SRYIPEGLQC SCGPDWYTVG TKYKSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA 118

E_aferx YIVICKPFGN FRFNSRHALL VVAATWIIGV GVAIPPFFGW SRYIPEGLQC SCGPDWYTVG TKYKSEYYTW FLFIFCFIVP LSLIIFSYSQ LLSALRAVAA

G_gallu QQQESATTQK AEREVSRMVV VMVGSFCLCY VPYAALAMYM VNNRDHGLDL RLVTIPAFFS KSACVYNPII Y P_carbo QQQESATTQK AEREVSRMVV VMVGSFCLCY VPYAALAMYM VNNRDHGLDL RLVTIPAFFS KSACIYNPII Y S_humbo QQQESATTQK AEREVSRMVV VMVGSFCLCY VPYAALAMYM VNNRNHGLDL RLVTIPAFFS KSACIYNPII Y C_livia QQQESATTQK AEREVSRMVV VMVGSFCLCY VPYAALAMYM VNNRNHGLDL RLVTIPAFFS KSSCVYNPII Y M_buger QQQESATTQK AEREVSRMVV VMVGSFCVCY VPYAALAMYM VNNREHGIDL RLVTIPAFFS KSSCVYNPII Y P_elega QQQESATTQK AEREVSRMVV VMVGSFCLCY VPYAALAMYM VNNREHGIDL RLVTIPAFFS KSSCIYNPII Y C_galer QQQESATTQK AEREVSRMVV VMVGSFCLCY VPYAALAMYM VNNREHGIDL RLVTIPAFFS KSSCVYNPII Y C_latir QQQESATTQK AEREVSRMVV VMVGSFCLCY VPYAALAMYM VNNREHGIDL RLVTIPAFFS KSSCVYNPII Y E_rosei QQQESATTQK AEREVSRMVV VMVGSFCLCY VPYAALAMYM VNNREHGLDL RLVTVPAFFS KSSCVYNPII Y B_zonar QQQESATTQK AEREVSRMVV VMVGSFCLCY VPYAALAMYM VNNREHGIDL RLVTIPAFFS KSSCIYNPII Y C_nucha QQQESATTQK AEREVSRMVV VMVGSFCLCY VPYAALAMYM VNNRDHGLDL RLVTVPAFFS KSACVYNPII Y L_sveci QQQESATTQK AEREVSRMVV VMVGSLCLCY VPYAALAMYM VNNREHGIDL RLVTIPAFFS KSSCVYNPII Y L_calli QQQESATTQK AEREVSRMVV VMVGSFCLCY VPYAALAMYM VNNREHGIDL RLVTIPAFFS ------P_caeru QQQESATTQK AEREVSRTVV VMVGSFCLCY VPYAALAMYM VNNREHGIDL RLVTVPAFFS KSSCVYNPII Y P_palus QQQESATTQK AEREVSRMVV VMVGSFCLCY VPYAGLAMYM VNNREHGIDL RLVTVPAFFS -SSCV--PII Y P_major QQQESATTQK AEREVSRMVV VMVGSFCLCY VPYAALAMYM VYNR------S_canar QQQESATTQK AEREVSRMVV VMVGSFCMCY VPYAALAMYM VNNREHGIDL RLVTIPAFFS KSSCVYNPII Y T_gutta QQQESATTQK AEREVSRMVV VMVGSFCMCY VPYAALAMYM VNNREHGIDL RLVTIPAFFS KSSCVYNPII Y E_aferx QQQESATTQK AEREVSRMVV VMVGSFCMCY VPYAALAMYM VNNREHGIDL RLVTIPAFFS KSSC------

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Figure S3. (Following page) Avian phylogeny used for molecular evolution analyses with foreground branches for Branch-Site and Codon model analyses indicated. The topology is based on consensus of previous phylogenetic studies (see Methods Section). Species thought to be

UVS are shaded green, and VS are blue. λmax SWS1 pigments taken from the literature are indicated beside the names of the corresponding species, asterices denote λmax measured using MSP. The dataset included 19 sequences: 6 parrot species, 9 passerine species as well as the Humboldt’s penguin (Spheniscus Humboldti), the cormorant (Phalacrocorax carbo), the pigeon (Columba livia) and the chicken (Gallus gallus) (GenBank accession numbers and species names are given in Table S1). Analyses were carried out on random site, branch-site and clade models using the PAML program (see Materials and Methods). For each model, the ratio of non- synonymous (dN) to synonymous (dS) substitution rates was estimated. The thick, numbered branches are those set as foreground lineages in various analyses for detecting positive selection, where a separate ω ratio was estimated. The following lineages were investigated with Branch- Site and Clade models: 5, Passerida; 3, Passeriformes; 2, Psittaciformes; 2&5, Passerida with Psittaciformes. The great bowerbird (4) and Landbirds (1) lineages were investigated only with Branch-Site models. Using Clade models, Passerida and Psittaciformes were investigated where they were allowed independent ω values. Branch-Site models that resulted in a significant improvement compared to the null are marked with the omega (ω) symbol: Passerida with Psittaciformes and only Psittaciformes.

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Figure S4. (Following page) Location of putative positively selected sites in avian SWS1 in snake plot (LHS) and 3D model (RHS). Sites inferred to be evolving under positive selection pressure according to Bayes empirical Bayes analysis with the Branch-Site model and branches 2 & 5 (Psittaciformes & Passerida) set as foreground. Only sites with PP> 0.8 are shown. (LHS) The bowerbird SWS1 sequence is displayed, with protein domains based on that of bovine RH1. The seven transmembrane α-helices (H1-H7), Helix 8 (H8), extracellular (E1-E3) and cytoplasmic (C1-C3) regions, as well the cytoplasmic terminal region (CT) and the N-terminal region (NT) are labeled. Amino acid positions refer to bovine RH1 numbering. Known spectral tuning sites 86, 90 and 93 are shaded. Positively selected sites are marked with thick circles. Note: The region corresponding to Helix 2, that which was used for ancestral reconstruction is boxed (amino acid sites 72-101). (RHS) The 3D crystal structure of bovine RH1 is viewed from the side with the extracellular side on top. The opsin helices are shown as blue cylinders, while the chromophore and positively selected sites are visualized as yellow spheres. Similar to site 90, positively selected sites 91, 112 and 298 are near the chromophore and its SB linkage to the opsin at K 293. Site 298, has also been identified as positively selected in mammalian RH1 pigments, with the same alternate residues: S and A (Zhao et al., 2009). However, introducing the S298A mutation to budgerigar SWS1 pigments does not affect λmax. Therefore, despite its proximity to the SB link, 298 is likely not a spectral tuning site (Wilkie et al., 2000). Though whether this result applies to all SWS1 genetic backgrounds, particularly VS types that lack any strong SB deprotonating residues, is not clear. Other BEB sites are in extra/intra-cellular regions, which are also crucial for proper opsin function. This includes: Cytoplasmic loop 2 (C2), responsible for G-protein binding (König et al., 1989; Franke et al., 1992; Smith, 2010); Extracellular loop 2 (E2), involved in forming a plug over the top of the protein and interacting with the chromophore (Janz et al., 2003; Okada et al., 2004); and Extracellular loop 3 (E3), linked to H6 that shifts considerably upon protein activation (Choe et al., 2011; Zhou et al., 2012; Altenbach et al., 2008). These residues might contribute to some of the unique properties of UVS pigments: such as slow retinal release (Chen et al., 2012), a constrained binding pocket (Das et al., 2004), and dark state stability (Luo et al., 2011), by preventing access within the binding pocket or restricting movement of H6.

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Figure S5. (Following page) Alternate Landbird topologies used to confirm ancestral sequence reconstruction. LHS: original tree based on consensus of current phylogenetics studies. RHS: Secondary tree based on topology of Ödeen et al., (2011). The trees differ in the relationships among higher passerines (Passerida and core-Corvoidea). The reconstructed ancestral nodes are indicated by circles: Passerines (blue), Passerines and Parrots (P + P, green). The corresponding reconstructed fragments are indicated in boxes pointing to their respective nodes. The residue substitutions at sites 86, 90, & 93 are indicated. The reconstructed ancestral nodes are identical in sequence regardless of the topology used. But, the alternate topologies produce slightly dissimilar hypothesis regarding substitutions at site 90 in higher passerines (in red): a single event in the LHS tree, and two events in the RHS tree.

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Chapter 4 Characterization of rhodopsin in the great bowerbird (Chlamydera nuchalis): The roles of D83N and A292S in retinal release 4 Abstract

Rod opsin (RH1) is a photoreceptive protein found in vertebrate rod photoreceptors cells, responsible for dim light vision. Bowerbirds are highly visual diurnal birds that exhibit one of the most striking examples of sexually selected traits among birds: bower-building. Previously, we isolated the visual pigments of the great bowerbird (Chlamydera nuchalis), and the presence of an RH1 with N83, a mutation thought to be an adaptation to dim light, prompted further experimental investigation. The expressed, purified bowerbird RH1 has a λmax at 500 nm, denatures in acid, bleaches in light, but does not react in the presence of hydroxylamine, all of which indicate it is a functional RH1 with a tight binding pocket, typical of mammalian rod pigments. The retinal release rate of C. nuchalis RH1 (t1/2 = 29 min) as measured by fluorescence spectroscopy was found to be much slower than bovine RH1 (t1/2= 14 min) and chicken RH1 (t1/2

=17 min). In C. nuchalis RH1, the mutation N83D increases the rate of retinal release (t1/2 = 18 min), indicating N83 is responsible for the decreased rate in the wild type pigment. The reverse mutation, D83N in bovine RH1 decreases retinal release (t1/2 = 25 min), similar to C. nuchalis wild type, indicating N83 is sufficient to induce the same phenotype in another RH1. The mutation A292S in C. nuchalis also increases retinal release (t1/2 = 17 min), suggesting it might be a compensatory mutation in organisms naturally expressing both N83/S292. Overall our results demonstrate both sites 83 and 292 mediate retinal release. In C. nuchalis RH1, the discovery of N83 is unexpected, as it has not been previously identified in a bird, or in any vertebrate that is primarily diurnal. This study is the first characterization of a neoavian RH1 and indicates there is considerable variation in RH1 retinal release across vertebrates.

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4.1 Introduction

Rod opsin (RH1) is a widely studied G-protein coupled receptor (GPCR) expressed in the outer segments of rod photoreceptor cells in the retina that is responsible for generating visual signals in dim-light settings. RH1 comprises seven transmembrane helices that form a binding pocket for the light sensitive ligand 11-cis- retinal (Okada et al., 2004), which is bound to the opsin via a protonated Schiff base (SB) link (Menon et al., 2001). Absorption of a photon generates cis-trans isomerization of the chromophore (Wald, 1968). This triggers conformational changes in the protein producing a series of photo-intermediates, resulting in the formation of the active form of the protein, Metarhodopsin II (MII), which is able to bind and activate the G-protein transducin (Smith, 2010). Transducin binds the inhibitory units of phosphodiesterase, which then hydrolyzes cGMP, thereby closing nucleotide gated ion channels and resulting in hyperpolarization of the cell (Chen, 2005). MII is one of three photoproducts, the others being MI and MIII, which all exist in dynamic equilibrium with each other (Matthews et al., 1963; Kibelbek et al., 1991; Kolesnikov et al., 2003; Vogel et al., 2004), yet MI and MIII are either inactive or marginally active toward transducin. Both MII and MIII forms degrade by hydrolysis of the SB link and release of all-trans-retinal. In the photoreceptor cell, two important steps are involved in the deactivation of RH1; C-terminal phosphorylation and arrestin binding, which can influence the stability of meta intermediate states and thus also alter the photoresponse (Xu et al., 1997; Kefalov et al., 2003; Sommer, 2005; Sommer and Farrens, 2006).

The crystal structure of RH1 has been found to contain intra-molecular networks of non-covalent interactions involving water molecules necessary for proper folding and function (reviewed in Smith, 2010). Altering the chemical character of certain sites can alter receptor properties because it disrupts these interactions. Using mutagenesis studies, a number of key sites and motifs have been identified. For example, at site 83 most vertebrate RH1s have aspartic acid (D), a charged molecule. Replacing this residue with uncharged asparagine (N) alters the wavelength of maximal absorption (λmax) (Janssen et al., 1990; Nathans, 1990; Fahmy et al., 1993; Fasick and Robinson, 2000; Breikers et al., 2001; Sugawara et al., 2005; 2010), the energetics of the MI-MII transition (Weitz and Nathans, 1993; DeCaluwé et al., 1995; Breikers et al., 2001; Sugawara et al., 2010), and opsin-transducin interactions (Nakayama and Khorana, 1991; Fahmy et al., 1993; Weitz and Nathans, 1993; Breikers et al., 2001). N83 is found in a number of dim-

136 light adapted vertebrates (Hunt et al., 1996; Hope et al., 1997; Fasick et al., 1998; Fasick and Robinson, 2000; Sugawara et al., 2005; 2010; Bischoff et al., 2012), and might be an adaptation to the photic conditions in which they live. Many dim light adapted vertebrates also express a substitution of alanine (A) for serine (S) at site 292, which significantly blue shifts λmax in fish and mammalian RH1s (Sun et al., 1997; Fasick and Robsinson, 1998; Lin et al., 1998; Yokoyama et al., 1999; Janz and Farrens, 2001; Sugawara et al., 2005; Yokoyama et al., 2007; Yokoyama and Tada, 2008), and is therefore also believed to be an adaptation to dim and/or blue light photic conditions.

Most functional RH1 research has focused on those of mammals and fish. In birds, research on the visual pigments of the chicken (Gallus gallus) is extensive, and λmax estimates of the cone opsins of many species have been measured (Hart and Hunt, 2007), but few avian opsins have been functionally characterized. This is surprising since the dramatic visual displays in birds clearly indicate they are highly visual organisms. Also, there are many examples of avian species whose eye morphologies show adaptations to the visual environments in which they exist (Martin, 2011 and references therein). Great bowerbirds (Chlamydera nuchalis) are diurnal birds found in the savannah woodland of Australia (Marshall, 1954). They are well-studied because of the males’ unusual courtship behaviour which includes the building and maintenance of a display area, called a bower (Diamond, 1986). The bower is decorated with objects of various colours (Endler and Day, 2006), involves complex cognitive skills (Endler et al., 2010) and its quality is associated with male mating success (Madden, 2003).

In this study we use spectrophotometric assays on expressed visual pigments, to investigate a number of opsin functions known to differ among visual pigments including; λmax (Davies et al., 2012), hydroxylamine stability (Kawamura and Yokoyama, 1998; Starace and Knox, 1998), and the rate of retinal release upon photoactivation (Farrens and Khorana, 1995; Chen et al., 2012). We show retinal release is twice as slow in C. nuchalis RH1 compared to bovine and chicken RH1, indicating this property varies across vertebrate RH1 pigments. We then demonstrate N83 is not only responsible for this decreased rate, but is also sufficient to produce an equivalently reduced rate in bovine RH1. We also investigate the A292S substitution in C. nuchalis RH1. It blue shifts λmax by -12 nm, similar to fish and mammalian RH1s, and increases retinal release to a rate similar to bovine RH1, suggesting it might be a compensatory mutation in organisms with both D83N and A292S substitutions. 137

4.2 Experimental procedures 4.2.1 PCR, cloning, and sequencing.

C. nuchalis RH1 was isolated from genomic DNA and cDNA as discussed previously (Chapter 3). All amplified fragments were cloned into the pJET1.2 cloning vector (Fermentas) and fully sequenced. In all cases, sequences from several reactions were compared to eliminate PCR incorporation errors. To confirm the presence of the N83 mutation, fragments of RH1 were isolated from genomic DNA of blood samples of two other individuals.

4.2.2 Generation of RH1 opsin expression constructs and site-directed mutagenesis

The complete coding sequence RH1 from C. nuchalis was amplified from retinal cDNA and inserted into the p1D4-hrGFP II expression vector, a derivative of the pIRES mammalian expression vector that encodes the 9 C-terminal amino acids from bovine rod opsin (the 1D4 epitope), and employing the CMV promoter to drive transgene expression (Morrow and Chang, 2010). Site-directed mutagenesis, performed using the QuikChange mutagenesis kit (Stratagene), was used to generate the mutants N83D and A292S in C. nuchalis RH1 and D83N in bovine RH1.

4.2.3 Expression of wild type and mutant pigments.

Expression techniques are similar to those described previously to express vertebrate RH1 genes (Morrow and Chang, 2010; Morrow et al., 2011). HEK293T cells were transiently transfected with the expression vector containing target opsin genes using Lipofectamine 2000 (Invitrogen). Three 175 cm2 flasks were used per experiment. Cells were harvested 48 h post transfection and washed three times with Harvesting Buffer (HB: PBS containing 10ug/ml of aprotinin and leupeptin, pH 7.0); regenerated with 5 µM 11-cis-retinal; solubilized from cell membranes using Solubilization Buffer (SbB: 1% n-dodecyl-β-D-maltoside detergent, 50 mM Tris, 100 mM NaCl,

1mM CaCl2, 0.1 mM PMSF, pH 6.8); and purified with the 1D4 monoclonal antibody (Molday and MacKenzie, 1983). Absorbance spectra of purified pigments were recorded using a Cary

4000 dual-beam spectrophotometer (Agilent, Santa Clara, CA). To estimate λmax, the dark absorbance spectra were baseline corrected and fit to a visual pigment template (Govardovskii et al., 2000).

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4.2.4 Functional assays

Absorbance spectra were again measured after either photoexcitation with light from a fiber optic lamp with a 495 nm cutoff filter, or after addition of hydrochloric acid (HCl) to 100 mM to create the acid-denatured pigment. The light and acid treatment spectra were subtracted from the dark absorbance spectra to produce difference spectra. Reactivity to hydroxylamine (NH2OH) was measured in the wild type RH1 by exposing the sample to 50 mM NH2OH at 25°C. After one minute, the absorption spectra was re-recorded and again at intervals up to 60 min. The rate of all-trans-retinal release from photoactivated opsin was measured as the increase in the intrinsic tryptophan fluorescence of the opsin following retinal release from the opsin binding pocket (Farrens and Khorana, 1995; Chen et al., 2012). The intrinsic fluorescence signal was measured using a Cary Eclipse fluorometer (Varian Inc.) with excitation/emission wavelengths at 295/330 nm and excitation/emission slit widths of 1.5 and 10 nm, respectively. First, the signal from a solution of RH1 was measured at 20°C for 5 min. Then the RH1 sample was bleached with light at a wavelength of > 495 nm for 60 s. The illuminated sample was kept in the fluorometer at 20°C to allow hydrolysis of the SB and release of all-trans-retinal to yield free opsin and the increase in fluorescence was measured. Data for retinal release assays were fit to a -bx first-order exponential curve (y = y0 + a(1-e )), with half-life values calculated based on the rate constant “b” (t1/2 – ln2/b)

4.2.5 Modeling of residues onto the RH1 structure.

Site 83 and other nearby residues were visualized in the 3D structure of bovine RH1 (PDB 1U19; Okada et al., 2004) using MacPyMol (Delano Scientific, San Carlos, CA).

4.3 Results 4.3.1 Sequence analysis of C. nuchalis RH1

The full-length coding sequence of the C. nuchalis RH1 was isolated as described previously (Chapter 3). It is displayed in 2 dimensional form superimposed on the known crystal structure of bovine RH1, where amino acid sites are noted as similar or different from bovine RH1 (Fig. 1). The translated amino acid sequence contains many conserved residues and motifs known to be important for visual pigment function (reviewed in Smith, 2010).

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Unlike bovine RH1, the C. nuchalis RH1 contains additional serine (S) and threonine (T) residues at the C terminus, typical of birds and other vertebrates but not eutherian mammals (pers. obs.). There are three residues unique to C. nuchalis RH1: V218I, M155L, and D83N. As far as we know, sites 218 and 155 have no known role in opsin function. Conversely, as previously introduced, D83N is well known to influence a number of opsin functions. Furthermore, the avian RH1 sequence data available indicates N83 is not present in any other avian species studied to date except for other bowerbirds (Coyle et al., 2012).

4.3.2 Protein expression and spectroscopic assays

The C. nuchalis RH1 was cloned into the p1D4-hrGFP II expression vector and expressed in mammalian cell culture, regenerated with 11-cis- retinal, solubilized with dodecyl maltoside, and purified with the 1D4 monoclonal antibody, as previously described (Morrow and Chang, 2010). It was expressed and purified with relative ease, bound 11-cis-retinal and produced a stable photopigment (Fig. 2A). The C. nuchalis RH1 expressed in vitro had a λmax of 500 nm (Table 1).

When denatured by HCl, a new absorption peak was observed at 440 nm (Fig. 2A Inset), the characteristic λmax of a protonated SB 11-cis-retinal in solution (Kito et al., 1968). This indicates the chromophore is covalently bound to the opsin via a SB link. When bleached with light, the absorption peak of each pigment shifts to 380 nm (Fig. 2A Inset), characteristic of MII (Matthews et al., 1963), demonstrating the conversion of RH1 to the active state. Immediately after photobleaching samples were also exposed to HCl. The new absorption peaks at 440 nm indicate the chromophore remains covalently bound in the MII state. The expression level and absorbance ratio (A280/Amax) of wild type C. nuchalis RH1 was similar to bovine RH1, suggesting it is as stable and as likely to fold. In addition, the C. nuchalis RH1 is stable in the presence of hydroxylamine (Fig. 3), indicating an inaccessible binding pocket typical of mammalian RH1s.

The rate of retinal release of light-activated RH1 was investigated by measuring the increase in intrinsic tryptophan fluorescence of the opsin as the retinal exits the binding pocket (Farrens and Khorana, 1995; Chen et al., 2012). We measured retinal release for C. nuchalis RH1 as well as bovine and chicken RH1 (Table 1). As expected, all displayed a monoexponential decay reaction. The halftime of retinal release for C. nuchalis RH1 was 29.1 ± 3.1 min, twice as slow as bovine RH1 (t1/2= 14.2 ± 1.0 min, Fig.4B , Table 1), which is comparable with previously 140 reported values (Farrens and Khorana, 1995; Janz and Farrens, 2001; Janz et al., 2003; Sommer and Farrens, 2006). The rate of retinal release in chicken RH1 was almost identical to that observed in bovine RH1 (t1/2= 16.4, Fig. 5)

4.3.3 Functional characteristics of site 83 and 292 mutants

Bowerbird N83D λmax is 503 nm (Fig. 2C), a +3 nm shift compared to wild type (Table 1). As expected, bovine D83N had a -3 nm shift in λmax, similar to previous studies (Nathans, 1990;

Fasick and Robinson, 2000; Breikers et al., 2001). The A292S λmax is 486 nm, -13 nm from the wild type (Fig. 6, Table 1). Similar to the C. nuchalis RH1 wild type pigment, the N83D mutant, A292S mutant, bovine wild type, and bovine D83N mutant all react to acid and light, forming appropriate light absorbing species (Figs. 2B-D & 5 Inset).

The half-life of the retinal release in the C. nuchalis RH1 N83D mutant was 17.5 ± 0.6 min (Fig. 4D, Table 1), faster than the wild type, and similar to that of bovine RH1 wild type. Conversely, the half-life in the bovine RH1 D83N mutant was 24.4 ± 2 min (Fig. 4C, Table 1) , slower than wild type and similar to the C. nuchalis wild type RH1. In C. nuchalis, the A292S mutant also had a retinal release rate similar to chicken and bovine wild type RH1 (t1/2 = 17 min Fig. 6).

4.4 Discussion

In the present study we characterize the RH1 pigment of C. nuchalis. While λmax values have been determined for the RH1 pigments of >20 avian species (reviewed in Hart 2001), the only other avian RH1 pigment for which properties aside from λmax have been measured is that of the chicken (e.g. Imai et al., 2005; Kuwayama et al., 2005; Imai et al., 2007). We identified N83 in the RH1 sequence of C. nuchalis RH1, which appears to be unique among birds, yet is naturally occurring in the RH1 pigments of many fish and mammals with dim-light behaviours (Supplementary Table 1, references therein).

The C. nuchalis RH1 functions similarly to previously characterized RH1s when exposed to light, acid and hydroxylamine. As well, the nm shifts in λmax caused by RH1 spectral tuning sites N83D and A292S, common in dim-light adapted vertebrates, are similar to those observed in mammalian and fish RH1 pigments. The exceptional characteristic of the C. nuchalis RH1 is a slow retinal release rate (t1/2 = 29 min) compared to bovine and chicken RH1 (t1/2= 14 min & 17

141 min, respectively). Mutagenesis experiments demonstrate N83 is responsible for this difference as the mutation N83D results in an increased rate (t1/2 = 18 min) and the reverse mutation, D83N in bovine decreases retinal release (t1/2 = 25 min). Like N83D, A292S in C. nuchalis produces a pigment with a faster retinal release (t1/2 = 17 min), indicating the effects of N83 and S292 on retinal release are opposed; suggesting S292 might be a compensatory mutation in species expressing both mutations.

4.4.1 C. nuchalis RH1 amino acid sequence and functional characteristics

Our results show the C. nuchalis RH1 λmax = 500 nm, atypical among bird RH1s, which tend to have slightly red-shifted λmax values, ranging from 501-509 nm (Hart and Hunt, 2007). Our λmax measurement is 3 nm different from a previously published value measured from rod photoreceptors using microspectrophotometry (MSP), 503 nm (Coyle et al., 2012). Few avian

RH1 pigments have been expressed in vitro, but the λmax values are also blue shifted relative to values obtained using MSP: chicken, zebra finch, and pigeon have respective reported λmax values of 503, 501, and 502 nm from in vitro expression studies but 507, 507, and 506 from MSP studies (Table 2, references therein). Therefore the difference in λmax values of C. nuchalis RH1 obtained by in vitro expression vs. MSP is likely due to methodical differences.

Our assays also show the C. nuchalis RH1 functions similarly to mammalian rod opsins: It is responsive to light and denatures in acid with a protonated SB link. The non-reactivity of C. nuchalis RH1 in the presence of hydroxylamine demonstrates a less accessible binding pocket, typical of mammalian RH1 opsins. Unbleached cone pigments have more open binding pockets and so react in the presence of hydroxylamine as it can access and bind to retinal (Fager and Fager, 1981). Some RH1 pigments have also been found to react to hydroxylamine, for example that of the anolis (Anolis carolinensis) (Kawamura and Yokoyama, 1998), and the echidna (Tachyglossus aculeatus) (Bickelmann et al., 2012).

The rates of retinal release varied among the different vertebrate RH1s examined in this study. The bovine and chicken RH1s have similar retinal release rates, whereas that of C. nuchalis RH1 is at least twice as slow. Unlike C. nuchalis, the echidna RH1 retinal release is faster than bovine

(t1/2 = 9.5 min; Bickelmann et al., 2012), it too has the N83 substitution. These findings indicate retinal release rates vary considerably across vertebrates, but imply that the rate of bovine and 142

chicken (t1/2 ~15 min) might be typical for RH1 pigments, and thus would be expected across most vertebrates. In cone visual pigments, retinal release rates are ~250 fold faster than rods (Chen et al., 2012).

4.4.2 Effects of site 83 on RH1 function

In C. nuchalis RH1, the N83D mutation resulted in a 3 nm red shift (λmax 503 nm). This shift is comparable to that observed in other RH1 pigments. For example, D83N shifts 2-6 nm in bovine RH1 (Janssen et al., 1990; Nathans, 1990; Fahmy et al., 1993; Fasick and Robinson, 2000; Breikers et al., 2001), and up to 8 nm in different cichlid species (Sugawara et al., 2005). Also, a

3 nm shift would explain the somewhat atypical λmax in this bird compared to other avian RH1s that tend to have λmax values slightly red shifted from 500 nm (Hart and Hunt, 2007).

Our results show N83 contributes to a slow retinal release rate in C. nuchalis. The N83D mutation increased retinal release to a rate similar to that of the RH1 pigments of bovine and chicken. Conversely, the reverse D83N mutation in bovine RH1 produces the opposite effect, decreasing retinal release to a rate almost identical to that of the bowerbird wild type. Therefore, N83 is not only responsible for the slow retinal release in C. nuchalis RH1, but also sufficient to induce an equal phenotype in other RH1s. In the echidna, even though the wild type RH1 had a retinal release rate faster than bovine RH1, the similar mutation in the echidna (N83D) also increases retinal release (Bickelmann et al., 2012). Juxtaposing our results with those of others shows N83 consistently slows retinal release despite the background in which it is expressed. Therefore, it is likely other vertebrates N83 will also demonstrate a slow retinal release, barring the possibility of compensatory mutations like A292S, discussed below.

4.4.3 Effects of site 292 on RH1 function

Many RH1 pigments that naturally express N83 also express S292, particularly those of vertebrates that are primarily nocturnal and/or live in very dim photic conditions (i.e. very deep water). Since the C. nuchalis RH1 only carries N83, we also created an A292S mutant. A292S significantly altered λmax, blue shifting sensitivity -13 nm. Unlike site 83, 292 is in close proximity to the chromophore binding site at K296, ~1 helical turn away (Fig. 7). Therefore it is not unexpected that substitutions at this site alter wavelength sensitivity. Site 292 regulates wavelength sensitivity in the RH1s of many other vertebrates. Like in C. nuchalis RH1, A292S

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blue shifts the RH1 λmax in bovine (-10 nm; Sun et al., 1997; Fasick and Robsinson, 1998; Lin et al., 1998; Janz and Farrens, 2001; Yokoyama et al., 2007), and cichlids (-14 nm; Sugawara et al., 2005). The reverse mutation, S292A, red shifts the naturally blue shifted RH1s of many fish (Yokoyama et al., 1999; Yokoyama and Tada, 2008; Sugawara et al., 2005). Thus, S292 is thought to be responsible for blue shifted λmax in other fish and mammals as well (McFarland, 1971; Hunt et al., 1996; Fasick and Robinson, 2000; Sugawara et al., 2005; Davies et al., 2007; Sugawara et al., 2010). Likewise, any RH1 carrying S292 is predicted to be blue shifted (Archer et al., 1995; Hope et al., 1997; Fasick and Robinson, 2000; Zhang et al., 2000; Zhao et al., 2009; Bischoff et al., 2012). These species expressing S292 live in deep water or are nocturnal. Due to the blue shifting effects of A292S, and the ecotypes of the vertebrates in which it is found, it is believed to be an adaptation to dim and/or blue shifted light conditions. Our results demonstrate the spectral tuning potential of site 292 is conserved within bird RH1s as well. However, to our knowledge S292 is not in any avian pigment studied so far, although most sequence data available does not include this site.

The effect of A292S on retinal release in C. nuchalis was also examined. S292 increased retinal release to a rate similar to bovine wild type, which is opposite to the effect of N83. A previous study showed A292S increased the rate of retinal release in bovine RH1 as well (t1/2= 10.5 min,

Janz and Farrens, 2001). Therefore, as S292 blue shifts λmax it also regulates the strength of the link between the chromophore and opsin. In fact, S292 might be a compensatory mutation to counteract the effects of N83 on retinal release in organisms that naturally express both substitutions. Like site 83, it is clear site 292 affects more than one property in RH1s; both λmax and retinal release.

Site 292 is an important site in other visual pigment types as well. Regulating wavelength sensitivity in SWS2 (Takahashi and Ebrey 2003), RH2 (Yokoyama et al., 1999) and LWS pigments (Sun et al., 1997; Fasick and Robinson 1998; Davies et al., 2009). In LWS pigments, site 292 influences the binding of chloride ions at H180 (Davies et al., 2009; Davies et al., 2012), responsible for their red shift in λmax relative to RH1 pigments (Kleinschmidt and Harosi 1992; Wang et al., 1993). RH1 pigments are insensitive to anions (Kleinschmidt and Harosi 1992), but the addition of an extra hydroxyl group by A292S probably stabilizes protonation of the SB, resulting in a blue shift in λmax. In LWS pigments, the extra hydroxyl group also results in a

144 smaller pocket surrounding the SB (Davies et al., 2012). In RH1 pigments, S292 could therefore decrease retinal release by preventing access of water necessary for SB hydrolysis (Jastrzebska et al., 2011).

4.4.4 D83N in RH1 structure and function

Even before the substitution D83N was identified in the dim light adapted RH1s of mammals, it has been the focus of many biochemical studies to identify the role of D83 in RH1 function. D83 was identified as a key site because it is highly conserved among GPCRs and possesses an acidic side chain, and thus likely involved in important non-covalent bonding networks within the protein (Breikers et al., 2001; Okada et al., 2004). In bovine RH1, many functional changes accompany the D83N substitution including: λmax, MI - MII energetics, the efficiency of transducin activation, and pH sensitivity (Janssen et al., 1990; Nathans, 1990; Nakayama and Khorana, 1991; Fahmy et al., 1993; Weitz and Nathans, 1993; DeCaluwé et al., 1995; Breikers et al., 2001). A recent mutagenesis study on the RH1s of vertebrates that naturally carry the N83 substitution has since shown N83 also increases MII formation in dim light adapted cichlids, and therefore believed to increase photoactivation efficiency (Sugawara et al., 2010). Sugawara et al., (2010) confirmed N83 as a dim light adaptation, but also highlighted the possibility that visual pigments can adapt in other ways aside from wavelength sensitivity. Correspondingly the D83N substitution warrants further discussion in context of previous structural and biochemical studies of RH1.

4.4.4.1 Molecular mechanisms underlying differences in retinal release

Changes in the photoactivation process caused by the mutation D83N are believed to be due to a dislocation of this site from H-bond networks as this mutation involves a switch from a charged to an uncharged molecule (Breikers et al., 2001). In wild type bovine RH1, the MII state is characterized by large changes in the orientation of Helix 6 (H6) during photoactivation (Zhou et al., 2012). The proposed rearrangement of H-bonds during photoactivation is as follows: In the ground state, conserved residues N302 and W265, on H7 and H6, respectively, are connected via water molecules. Following chromophore isomerization, W265 rotates causing N302 to lose existing H bond contacts. N302 then forms new H bonds, likely with D83, causing outward rotation of the cytoplasmic end of H6 (Fig. 7) (Smith, 2010). Therefore, without a carboxylic side chain at site 83, N302 will have to form bonds with other residues. This might produce an

145 alternate orientation of H6 in the MII state, perhaps by reducing the outward rotation of H6, which could explain the altered rate of retinal release.

The change in chemical character of site 83 is also important to explain the mechanism by which this mutation alters retinal release rates because, similar to spectral tuning and RH1 activation, the molecular and chemical mechanisms involved in retinal release also rely on non-covalent interactions (Liu et al., 2009; Chen et al., 2012; Piechnick et al., 2012), and therefore are susceptible to rearrangement. Retinal release occurs in two steps: hydrolysis of the SB link, and dissociation of all-trans retinal through the exit pore. Under the current proposal for SB hydrolysis in a visual pigment (Cooper et al., 1987), the counterion (E113) stabilizes the attack of water and reaction intermediates, which require hydrophilic conditions. For this process to occur, unbound water molecules must also move into the binding pocket (Jastrzebska et al., 2011). While residues near then SB link can directly alter hydrolysis (Chen et al., 2012), distant mutations can also slow hydrolysis by changing global protein dynamics (Piechnick et al., 2012). Therefore, although site 83 is somewhat distant from the SB counterion, a rearrangement of non- covalent bonds by D83N could slow hydrolysis by producing hydrophobic conditions that prevent the access of water or the ability of the counterion to stabilize reaction intermediates. After hydrolysis, the retinal exits the opsin through retinal entry/exit pores (Hildebrand et al., 2009). Electrochemical changes in the binding pocket due to substitutions at site 83 could alter residue interactions with the chromophore as it is transported to the pore(s) or in the accessibility of the chromophore to pass through the pore(s).

It is unknown which step, whether hydrolysis or retinal dissociation, plays a more important role in retinal release. Mutagenesis studies in RH1s propose SB hydrolysis as the rate limiting step (Piechnick et al., 2012). However, between rods and cones the energetics of SB hydrolysis are the same, therefore the mechanism slowing retinal release in rods compared to cone opsins instead resides in different dissociation rates of all-trans-retinal (Chen et al., 2012). Whether N83 affects retinal release by altering hydrolysis or retinal dissociation, or both, is unknown but the hydrophobic conditions produced by N83 certainly play an important role.

4.4.4.2 The role of site 83 on photointermediate kinetics

Since MII is the active photointermediate, perturbation of the equilibrium reactions among MI, MII, and MIII can affect the photoactivation response (Imai et al., 2007). Photoactivation

146 kinetics are altered by stabilization or destabilization of certain RH1 states by residues within the protein (e.g. Weitz and Nathans, 1993; Imai et al., 1997; Kuwayama et al., 2002; 2005) or through the interactions of photoactivated opsin with other molecules (Sommer and Farrens, 2006; Lee et al., 2010). Previous biochemical studies show D83N alters the pKa of the MI-MII equilibrium, favouring the MII state (Weitz and Nathans, 1993; DeCaluwé et al., 1995; Breikers et al., 2001). Since N83 increases the rate of MII formation, but does not alter the MII – MIII equilibrium, Sugawara and others (2010) suggest this residue acts by destabilizing MI, rather than by stabilizing MII. Here, we show that bovine and C. nuchalis RH1s containing D83 have faster retinal release rates, whereas those with N83 have slower retinal release rates. Since MII is known to decay to opsin + retinal, prompting retinal release, one possible explanation of our results is that N83 does, in fact, stabilize the MII state.

This hypothesis, however, is speculation as no study has investigated the link between the retinal release assay and MII decay rates. Thus, the particular process that is affected by these substitutions is unknown. Measuring the rates of formation and decay of MII and MIII might identify what state is altered by these substitutions in these species4. Regardless, retinal release is an important assay as all-trans-retinal must be released for the pigment to be regenerated, and this is an important step in photoreceptor recovery (Lamb and Pugh, 2006). In this study we clearly demonstrate sites 83 and 292 are important in this process because residue substitutions at these sites alter the rates, and thus the ease at which all-trans-retinal is freed from the activated pigment.

4.4.4.3 Possible implications of slow retinal release on photoresponse and the visual cycle

It is believed that N83 improves light sensitivity because by favouring the active MII form, and thus will hasten the initiation of the photoresponse (Sugawara et al., 2010). Our results support a hypothesis where the MII is favoured by N83 because retinal release is slow once the pigment is activated. However, an extended active lifetime will not increase signal amplification as the photoresponse reaches its peak at ~0.2 s. Conversely, since retinal release rates determine the

4 Measuring the rate of decrease in MII λmax (460 nm) post photoactivation compared with the formation of free opsin would confirm the relative contribution of MII and MIII to our measurements. 147 rate at which free opsin becomes available post photoactivation, a slowed rate could reduce the timing of photoresponse recovery, which is crucial for maintaining sensitivity in steady light and for changes in light intensity (Lamb and Pugh, 2004). In the vertebrate eye, however, the activated pigment is attenuated by a complex shut-off mechanism, which includes phosphorylation of C-terminal residues and binding of arrestin (Chen, 2005). In this case the shut-off mechanism may render a slow retinal release irrelevant, or could even adapt to compensate5. As such, the kinetic effect we have measured could be a by-product of another adaptive change, perhaps to improve signaling by increasing the rate of MII formation, as previously observed (Sugawara 2010). Similarly, a slow retinal release might be advantageous if it represents an improved MIII stability. Storing light activated opsin in a form that does not activate transducin might contribute to both light and dark adaptation (Heck et al., 2003), and, since the MIII-MII conversion is regulated by light (λmax ~470 nm) (Arnis and Hofmann, 1995), MIII might provide a more immediately available photoreceptor (Zimmerman et al., 2004; Ritter et al., 2008). This could be especially useful in organisms living in deeper water where light is attenuated to a narrow range around 477 nm with increasing depth. Regardless of the potential consequences of a slow retinal release suggested here, opsin photointermediates interact with a number of molecules that, as previously mentioned, can also mediate photoactivation kinetics (Zimmermann, 2004; Sommer and Farrens, 2006; Lee et al., 2010). Here we measure a RH1 property in a system devoid of regulatory proteins, therefore predictions regarding the functional role of an altered retinal release rate on the photoresponse must be subject to experimental testing.

4.4.5 Evolution of RH1 D83N in vertebrates & bowerbirds

The identification of N83 and a decreased retinal release in the C. nuchalis is unexpected because this bird is not thought to be dim-light adapted. Having an efficient RH1 might,

5 To this point, the extra phosphorylation sites found in C. nuchalis and other birds might increase attenuation. Phosphorylated sites are necessary to quickly attenuate the photoresponse (Kefalov, 2003), and the number of which can affect the arrestin-opsin complex where hyperphosphorylated rhodopsin releases retinal more quickly (Vishnivetskiy, 2007). Accordingly, perhaps the additional S and T sites in C. nuchalis improve deactivation, thus eliminating or reducing any issues associated with a slow retinal release. Further investigation into phosphorylation in non-mammalian visual systems is necessary to determine whether these sites are phosphorylated and their role in the attenuation process.

148 therefore, be unnecessary. Phylogenetic studies indicate N83D occurred several times throughout vertebrates, including parallel evolutionary events and reversals within some groups like cichlids, bats, and whales (Sugawara et al., 2005; 2010). These shifts are all linked to ecological changes in dim light environments. In fact, eels show differential expression of an RH1 opsin type with both N83 and S292 when switching to deep water life stages (Archer et al., 1995; Zhang et al., 2000), revealing a strong link between these residues and living in dim light. On the other hand, like C. nuchalis, some species express only N83 including, albeit not exclusively; African elephant (Loxodonta Africana; Yokoyama et al., 2005), California sea lion (Zalophus californianus), walrus (Odobenus rosmarus; Levenson et al., 2006), guinea pig (Cavia porcellus; Simpanya et al., 2008), platypus (Ornithorhynchus anatinus; Davies et al., 2007), and echidna (Tachyglossus aculeatus; Bickelmann et al., 2012). These species are not specifically dark adapted, but demonstrate behaviours that might benefit from increased light sensitivity. For example, elephants must feed continuously during night and day to meet their metabolic needs; guinea pigs are semi-fossorial; sea lions dive to great depths in search of food, and predominantly in the nighttime. Correspondingly, these dim light behaviours might be the ecological link to explain the shared N83 mutation. If N83 is an adaptation to dim-light, this suggests C. nuchalis might benefit from an increased sensitivity to light. For male bowerbirds, maintaining a bower requires a significant investment of resources. There is a strong advantage for a well-maintained bower and decorations with colours that contrast with the male’s predominantly brown plumage (Endler and Day, 2006). Theft of bower decorations among males is common, and is also associated with mating success (Doerr, 2009; 2010a; 2010b; 2010a). Perhaps males must continually protect their bower and search for ornaments, during the day and at night? A thorough investigation into the diel habits of bowerbirds is necessary to confirm the potential role of what might be a dim-light adapted RH1 in this bird. Alternatively, the role of N83 might be different in this system compared to others.

4.5 Conclusions

Here, the functional characteristics of C. nuchalis RH1 are investigated. It exhibits a slow retinal release rate relative to bovine and chicken RH1, a property explained by a single amino acid substitution, N83, which is common to dim-light adapted vertebrates. Another substitution common to dim-light adapted vertebrates, S292, increases retinal release in the RH1 of this bird, suggesting a potential compensatory role. While the functional purpose and interactions between

149 sites 83 and 292 remain unclear, we have shown that N83 and S292 both affect retinal release, but in opposite ways. Conversely, both mutations blue shift λmax and increase MII formation (Sugawara et al., 2010). So it seems these sites can have either complimentary or opposing roles. Regardless, both 83 and 292 affect a variety of RH1 properties. Also, their effects on similar properties suggest they might be linked. The particular combination of residues at sites 83 and 292 in a given organism is likely an optimization of their functional effects to adapt to the photic conditions in which the animal uses its vision. Future experiments should include single and double mutants in bovine RH1, additional functional assays on these pigments and corresponding mutants, as well as characterizing RH1 pigments in species naturally carrying the N83 and S292 substitutions to clarify their roles in photoactivation.

150

4.6 Tables

Table 1. Spectroscopic and kinetic parameters of wild type and mutant bowerbird and bovine RH1s.

Residue Shift Retinal release Species 83 292 λmax (nm) (nm) (t1/2) (min) bowerbird wt N A 500 ± 1.1 29.1 ± 3.1 (3) Chlamydera nuchalis D A 503 ± 1.5 3 17.5 ± 0.6 (3) A292S N S 487 ± 0.4 -13 17.1 (1)

bovine wt D A 499 14.2 ± 1 (3) Bos Taurus D83N N A 496 -3 24.4 ± 2 (5) A292S* N S 489.5 9.5 10.5 chicken wt D A 503 16.4 (1) Gallus gallus

*Janz & Farrens 2001. Measured bovine wild type λmax 500 nm

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Table 2. Comparison of λmax values of select avian RH1 pigments measured using microspectrophotometry and by in vitro expression

MSP In vitro expression Species λmax Citation λmax Citation Chicken 506 (Bowmaker et al., 1997) 503 (Okano et al., 1992) Gallus gallus 507 (Heath et al., 1997) Zebrafinch 507 (Bowmaker et al., 1997) 501 (Yokoyama et al., 2000) Taeniopygia guttata Pigeon 506 (Bowmaker et al., 1997) 502 (Kawamura et al., 1999) Columba livia 515 Bowmaker 1977 Bowerbird 503 (Coyle et al., 2012) 500 This Study Chlamydera nuchalis

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4.7 Figures

Figure 1. (Following page) Sequence of C. nuchalis RH1 displayed in a snake plot based on the crystal structure of bovine RH1. Residues shared with bovine RH1 are in light grey, those differing from bovine RH1, but common to birds are in green and emboldened. Note the additional S and T residues at the C terminus, typical of birds and other vertebrates but not eutherian mammals. Sites with unique residues in C. nuchalis are in white font: V218I, M155L, and D83N. Pink filled circles denote important functional residues including: K296, the chromophore binding site (Dratz and Hargrave, 1983), its counterion E113 (Sakmar et al., 1989); C110 and C187 form a disulphide bridge (Karnik and Khorana, 1990) and R177 and D190 form a salt bridge to maintain the tertiary structure (Davidson et al., 1994; Hwa et al., 1999); an H- bonded network that includes E181, Y192, Y268, S186, E113, & C187 to maintain high pKa for the protonated Schiff base for the dark state RH1 (Okada et al., 2004) and another centered on H211/G124, which rearranges upon retinal isomerization and receptor activation (Smith, 2010); the structural motifs (E/D)RY and NPxxY on H8 involved in creating and breaking an ionic lock necessary for receptor activation (Park et al., 2008; Scheerer et al., 2008); glycosylation sites N2 and N15 (Kaushal et al., 1994; Murray et al., 2009); palmitoylation sites C322 and C323 in Helix 8 (Ovchinnikov et al., 1988), used to stabilize the C-terminal end (Park et al., 2009); S and T residues in the C-terminus that are phosphorylation targets in the deactivation of MII (Ohguro et al., 1996); as well as residues I189 and E122 that maintain the slow photoisomerization kinetics characteristic of rod opsins (Imai et al., 1997; Kuwayama et al., 2002)

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Figure 2. UV-visible spectroscopy assays of the expressed C. nuchalis and Bovine RH1 wild- type and mutant pigments at pH 6.5. (A) C. nuchalis RH1 (black), λmax 500 nm; (B) bovine RH1

(green), λmax 499 nm; (C) C. nuchalis N83D (blue), λmax 503 nm; (D) bovine D83N (red), λmax 497 nm. Inset are the difference spectra where the change in absorbance is plotted as a function of wavelength: LHS- Light bleach (60 s), RHS- Acid bleach (100 mM HCl).

155

Figure 3. Hydroxylamine assay on the expressed C. nuchalis RH1 pigment. (A) Reactivity of C. nuchalis RH1 with hydroxylamine at 25° C in the dark. The dark absorption spectra is at t = 0 min. Hydroxylamine was added to the pigment to a final concentration of 50 mM, after t = 1 min the absorption spectra was re-recorded and again at intervals up to 60 min. The 0, 1 and 60 min spectra are marked. (B) The absorbance values at 500 nm (black) and 363 nm (grey) were plotted as a function of time after addition of hydroxylamine. 363 nm is the absorbance of a released retinal oxime. The absorbance peaks do not change with time indicating hydroxylamine does not successfully compete with the opsin for retinal binding.

156

Figure 4. Retinal release rates of expressed C. nuchalis and bovine RH1 wild type and 83 mutant pigments. Data displayed with single exponential curve fit as follows: A) Bovine RH1 wild type (green); B) C. nuchalis RH1 (black) shown in comparison to curve fit of bovine RH1 wild type data; C) bovine RH1 D83N mutant (red) in comparison to bovine and C. nuchalis wild type; D) C. nuchalis N83D mutant (blue) in comparison bovine and C. nuchalis wild type. Purified RH1 was incubated at 20°C for 5 min and then bleached for 60 s to photoconvert the pigment to MII. The release of retinal was monitored as the increase in tryptophan fluorescence intensity as a function of time after illumination. Fluorescence was recorded immediately following photolysis.

Half-life (t1/2) values are presented in Table 1. Data points were normalized, plotted, and fit to single-exponential curves.

157

Figure 5. Properties of G. gallus wild type RH1. Retinal release rate of expressed wild type G. gallus RH1 (purple) at 20°C is nearly identical that of bovine RH1 (grey). Half-life (t1/2) is 16.4 min. Inset: G. gallus RH1 absorbance spectra with λmax at 503 nm.

158

Figure 6. Properties of C. nuchalis RH1 carrying the A292S mutation. (A) UV−visible spectroscopy assays of the expressed C. nuchalis A292S pigment (orange) at pH 6.5. Inset are the difference spectra where the change in absorbance is plotted as a function of wavelength: LHS- light bleach (60 s), RHS- acid bleach (100 mM HCl). The absorption maximum of the mutated RH1 pigment is 486 nm. (B) Retinal release rate of the expressed A292S mutant RH1

(orange) at 20°C is similar that of bovine RH1 (grey). Half-life (t1/2) of the rate of release is 17.1 min

159

Figure 7. (Following page) Bovine RH1 crystal structure highlighting sites 83, 113, 292, 296, & 302. The bovine RH1 protein in the centre is in semi-transparent cartoon format (light grey), with water molecules visualized as blue balls, retinal in green is shown attached to K296 (dark grey). Sites D83, A292 & E113 are also visualized, in purple. (LHS) Image expanded around Schiff base link. Site 292 is in closer proximity to the retinal Schiff base compared to site 83. (RHS) Image expanded on sites 83 and 302, separated by three water molecules. Replacement of D83 with a more hydrophobic residue would likely alter the local environment and consequently alter the non-covalent bonds among these molecules.

160

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4.8 Supplementary data

Table S1. Vertebrates with RH1s that express N83 and/or S292

Common name Scientific name λmax 83 292 Accession # DNA Citation λmax Citation Mammalia walrus Odobenus rosmarus *499 N A AY883925 Levenson et al., 2006 California sea lion Zalophus californianus 501 N A AY883924 Levenson et al., 2006 Levenson et al., 2006 northern elephant seal Mirounga angustirostris 491/483 D S AY883928 Levenson et al., 2006 Southall et al., 2002 Eurasian river otter Lutra lutra N ? AB455182 Sugawara et al., 2010 bowhead whale Balaena mysticetus *493 N A Bischoff et al., 2012 fin whale Balaenoptera physalus *484 N S Bischoff et al., 2012 common minke Balaenoptera acutorostrata *484 N S Bischoff et al., 2012 Antarctic minke whale Balaenoptera bonaerensis N ? AB455162 Sugawara et al., 2010 sei whale Balaenoptera borealis *484 N S Bischoff et al., 2012 Bryde’s whale Balaenoptera brydei *484 N S Bischoff et al., 2012 blue whale Balaenoptera musculus *484 N S Bischoff et al., 2012 pygmy right whale Caperea marginata *479 N S Bischoff et al., 2012 common dolphin Delphinus delphis 489 N S AF055314 Fasick & Robinson, 2000 Fasick & Robinson, 2000 gray whale Eschrichtius robustus 497 N A Bischoff et al., 2012 McFarland, 1971 north Atlantic right whale Eubalaena glacialis 493 N A Bischoff et al., 2012 pacific right Eubalaena australis *493 N A Bischoff et al., 2012 long-finned pilot whale Globicephala melas 488 N S AF055315 Fasick & Robinson, 2000 Fasick & Robinson, 2000 boutu Inia geoffrensis N ? AB455180 Sugawara et al., 2010 Yangtze River dolphin Lipotes vexillifer N ? AB455181 Sugawara et al., 2010 humpback whale Megaptera novaeangliae 492 D S AB455184 Sugawara et al., 2010 McFarland, 1971 Sowerby's beaked whale Mesoplodon bidens 484 N S AF055316 Fasick & Robinson, 2000 Fasick & Robinson, 2000 sperm whale Phyester macrocephalus 483 N S Bischoff et al., 2012 Southall et al., 2002 Ganges River dolphin Platanista gangetica N ? AB455193 Sugawara et al., 2010 bottlenose dolphin Tursiops truncatus 488 N S AF055456 Fasick et al., 1998 Fasick & Robinson, 2000 greater false vampire Megaderma Lyra 496 N A Sugawara et al., 2010 Sugawara et al., 2010

162

bat little brown bat Myotis lucifugus 497 N A GQ241248 Feller et al., 2009 Feller et al., 2009 Rickett's big-footed bat Myotis ricketti *497 N A GQ290312 Zhao et al., 2009 Japanese pipistrellus Pipistrellus abramus N ? AB455192 Sugawara et al., 2010 brown big-eared bat Plecotus auritus N ? AB455194 Sugawara et al., 2010 greater horseshoe bat Rhinolophus ferrumequinum 498 D S GQ290314 Zhao et al., 2009 Sugawara et al., 2010 lesser horseshoe bat Rhinolophus pussillus *499 D S GQ290315 Zhao et al., 2009 lesser bamboo bat Tylonycteris pachypus N ? AB455207 Sugawara et al., 2010 damaraland mole rat Cryptomys damarensis *496 N A GQ290302 Zhao et al., 2009 Heliophobius silky mole rat argenteocinereus *496 N S GQ290306 Zhao et al., 2009 guinea pig Cavia porcellus N A EF457995 Simpanya et al., 2008 African elephant Loxodonta africana 496 N A AY686752 Yokoyama et al., 2005 Yokoyama et al., 2005 Asiatic elephant Elephas maximus N ? AB455174 Sugawara et al., 2010 cape rock hyrax Procavia capensis N ? AB455196 Sugawara et al., 2010 platypus Ornithorhynchus anatinus 498 N A EF050076 Davies et al., 2007 Davies et al., 2007 echidna Tachyglossus aculeatus 498 N A AY894355 Bickelmann et al., 2012 Bickelmann et al., 2012 Squamata Kawamura & Kawamura & Yokoyama, chameleon Anolis carolinensis 491 N A L31503 Yokoyama, 1998 1998 Amphibia leopard frog Rana pipiens 502 N A S49004 Fyhrquist et al., 1998 Liebman & Entine, 1968 bullfrog Rana catesbeiana 502 N A Fyhrquist et al., 1998 Donner et al., 1990 common frog Rana temporaria 501 N A U59920 Fyhrquist et al., 1998 Koskelainen et al., 1994 European toad Bufo bufo 502 N A U59921 Fyhrquist et al., 1998 Fyhrquist et al., 1998 cane toad Bufo marinus 502 N A U59922 Fyhrquist et al., 1998 Harosi, 1975 NM_00108 African clawed frog Xenopus laevis 500 N A 7048 Batni et al., 1996 Batni et al., 1996 tiger salamander Ambystoma tigrinum 506 N A U36574. Chen et al., 1996 Chen et al., 1996 Fish longfin baikal sculpin Cottocomephorus inermis 495 N A U97266 Hunt et al., 1996 Hunt et al., 1996 short-headed sculpin Cotinella boulengeri 484 N S U97273 Hunt et al., 1996 Hunt et al., 1996 Batrachocottus Sculpin sp. multiradiatus 490 D S U97267 Hunt et al., 1996 Hunt et al., 1996

163

Sculpin sp. Batrachocottus nicolskii 490 D S U97268 Hunt et al., 1996 Hunt et al., 1996 Sculpin sp. Limnocottus bergianus 490 D S U97270 Hunt et al., 1996 Hunt et al., 1996 Sculpin sp. Limnocottus pallidus 490 D S U97271 Hunt et al., 1996 Hunt et al., 1996 Sculpin sp. Abyssocottus korotneffi 484 N S U97272 Hunt et al., 1996 Hunt et al., 1996 Baileychromis African cichlid Sp. centropomoides 492 N A AB185217 Sugawara et al., 2005 Sugawara et al., 2005 African cichlid Sp. Diplotaxodon macrops 500 N A AB185220 Sugawara et al., 2005 Sugawara et al., 2005 African cichlid Sp. Pallidochromis tokolosh 500 N A AB185229 Sugawara et al., 2005 Sugawara et al., 2005 African cichlid Sp. Xenotilapia caudafasciata 491 D S AB185239 Sugawara et al., 2005 Sugawara et al., 2005 African cichlid Sp. Perissodus elaviae 490 D S AB185230 Sugawara et al., 2005 Sugawara et al., 2005 Greenwoodochromis African cichlid Sp. bellcrossi 488 D S AB185221 Sugawara et al., 2005 Sugawara et al., 2005 African cichlid Sp. Benthochromis tricoti 488 D S AB084927 Sugawara et al., 2005 Sugawara et al., 2005 African cichlid Sp. Trematocara macrostoma 488 D S AB084945 Sugawara et al., 2005 Sugawara et al., 2005 African cichlid Sp. Xenotilapia nigrolabiata 488 D S AB185241 Sugawara et al., 2005 Sugawara et al., 2005 humphead cichlid Cyphotilapia frontosa 487 D S AB084929 Sugawara et al., 2005 Sugawara et al., 2005 African cichlid Sp. Trematocara unimaculatum 484 D S AB185238 Sugawara et al., 2005 Sugawara et al., 2005 common sawbelly Hoplostethus mediterraneus 483 N S JN412583 Hope et al., 1997 Partridge, 1989 abyssal halosaur Halosauropsis macrochir 479 N S JN544541 Hunt et al., 2001 Douglas & Partridge, 1995 shortfin spiny eel Notacanthus bonapartei 483 N S JN544543 Hunt et al., 2001 Partridge et al., 1989 flathaus Cataetyx laticeps 468 N S JN412580 Hope et al., 1997 Douglas et al., 1995 long-tooth anglemouth Gonostoma elongatum 483 N S JN412561 Hope et al., 1997 Partridge 1989 deepwater arrowtooth eel Histiobranchus bathybius 477 N S JN544542 Hope et al., 1997 Partridge et al., 1992 Baird's smooth-head Alepocephalus bairdii 476 D S JN412584 Hunt et al., 2001 Douglas et al., 1995 Agassiz' slickhead Alepocephalus agassizii 477 N S JN544545 Hunt et al., 2001 Douglas et al., 1995 Salmon smooth-head Conocara salmonea 480 D S JN412577 Hunt et al., 2001 Douglas et al., 1995 deepsea lizardfish Bathysaurus ferox 481 N S JN412585 Hunt et al., 2001 Douglas et al., 1995 highfin lizardfish Bathysaurus mollis 479 N S JN412586 Hunt et al., 2001 Partridge et al., 1992 Coryphaenoides deepwater grenadier profundicolus 482 D S JN544538 Hunt et al., 2001 Partridge et al., 1992 ghostly grenadier Coryphaenoides leptolepis 482 D S JN544537 Hunt et al., 2001 Douglas et al., 1995 Noren et al., 2008 roundnose grenadier Coryphaenoides rupestris 480 ? S EU492249 GenBank Douglas et al., 1995 European eel Anguilla anguilla 482 Nǂ Sǂ L78007 Wood et al., 1992 164

501 D A L78008 Japanese eel Anguilla japonica *482 Nǂ Sǂ AJ249202 Zhang et al., 2000 Zhang et al., 2000 *501 D A AJ249203 pouch lamprey Geotria australis 497 N A AY366493 Collin et al., 2003 Davies et al., 2007 492 D A AY366494 Zhang & Yokoyama sea lamprey Petromyzon marinus *500 N A U67123 1997 river lamprey Lethenteron japonicum *500 N A M63632 Hisatomi et al., 1991 Hisatomi et al., 1991 John Dory Zeus faber 492 N A Y14484 Archer & Hirano, 1998 Dartnall & Lythgoe 1965 dogfish Galeus melastomus 481 N S Y17586 Bozzano et al., 2001 Bozzano et al., 2001 Note -- *Predicted value based on amino acid residues. ǂ Differential expression of RH1s: variant with D83N & A292S occurs during transition from freshwater to deep marine life stages.

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Chapter 5 Conclusions and Future Directions

5 Abstract

A central issue in evolutionary biology is to identify the molecular mechanisms involved in the adaptation of organisms to different environments. The visual system plays an important role in the recognition of the external world and is essential for the survival of many species. As such, it provides an excellent model for evaluating adaptation of vertebrates to the divergent environments in which they live. One of the most important components of this system are visual pigment proteins; the light sensitive complexes that convert light to biochemical signals. Characterizing molecular differences in the visual pigments of vertebrates offers new approaches to improve our understanding of the visual system.

This thesis presents studies that add to the growing body of knowledge of visual pigment function and evolution. The majority of this work focuses on the visual pigments of the great bowerbird (C. nuchalis), a passerine bird well known for its splendid bower-building behaviour. Each chapter illustrates the investigation of visual pigments in a different context. First a phylogenetic analysis that describes relatively unbiased sequence evolution in vertebrate SWS1 gene. Next is an exploration of the function and evolution of UV/violet vision in passerine birds by expressing the C. nuchalis SWS1, creating mutant pigments and reconstructing ancestral passerine states. Finally, the RH1 of C. nuchalis is characterized and the roles of N83 and S292 in regulating retinal release are explored. These studies demonstrate how investigating and explaining the natural variation in vertebrate visual pigments can provide a greater understanding of the molecular mechanisms of visual pigment function. This conclusion reviews the main findings of the studies in this thesis in light of their relevance to different fields, and some directions for future research are suggested.

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5.1 Chapter 2: SWS1 as molecular marker in phylogenetics

Chapter Two compares SWS1 gene phylogenies with vertebrate phylogenies. As a protein coding gene it is expected that sequence evolution in SWS1 will be restricted by constraints on protein structure and function. Despite this, it was found that the SWS1 gene is informative in resolving ancient, as well as more recent vertebrate relationships, even though it is under functional constraint and a relatively low evolutionary rate to maintain short wavelength sensitive vision across vertebrates.

These results were unexpected for a number of reasons. First, considering the link between opsin nucleotide sequences and function, one might expect sequences to group by spectral sensitivity (i.e. UVS vs. VS). This is clearly not the case with the SWS1 opsins, where the phylogenetic relationships mirror species relationships and not spectral sensitivity. Second, the ability of a single gene to recover the evolutionary relationships among vertebrates is also unusual. Although paleontological, morphological and molecular methods have, to some extent, agreed upon a basic topology of vertebrates, reconstructing the evolutionary history of vertebrates has proven difficult (Meyer and Zardoya, 2003). Last, these results are also unexpected, given that previous research using opsin genes to infer vertebrate phylogenies has determined they can perform poorly, due to biases in base composition and convergent evolution (Chang and Campbell, 2000).

Though single gene phylogenetic studies are rare, previous studies have investigated the use of opsin genes in predicting phylogenetic relationships finding that some perform well but only in certain vertebrate groups. For this reason, opsin sequence data, particularly RH1 and LWS are often included in multi-gene datasets6 (e.g. Hackett et al., 2008), although, SWS1 data has yet to be used in a multi-gene dataset yet.

6 Of note, however, I have discovered that many previous studies claiming to have isolated RH1 have instead, accidentally isolated RH2. The high sequence similarity among these genes is certainly the cause, but it does prompt concern. 175

5.1.1 Future directions in molecular studies of vertebrate SWS1 genes

There are a number of unresolved areas in the vertebrate phylogeny that could, potentially, benefit from the inclusion of SWS1 opsin sequence data. A relevant example would be in the higher passerine lineages: Passerida, ‘core-Corvoidea’ (sensu Barker et al., 2004), Callaeatidae, Cnemophilidae and Melanocharitidae. Even within the last year, alternate topologies have been published (Barker et al., 2004; Irestedt and Ohlson, 2008; Jønsson et al., 2011; Zuccon and Ericson, 2012). This group of birds is composed of two of the largest avian radiations (Core- corvoidea and Passerida), as well as unique lineages (Callaeidae contains one species). The genetic information contained in SWS1 genes could be used to reconstruct the evolutionary relationships among these birds7.

Since the publication of this chapter, more SWS1 opsin sequence data has become available: within mammals, species between mammals and ray-finned fish (including coelacanth & lungfish), and also within squamates. These sequences would be interesting to include as they are situated in areas where phylogenetic relationships remain difficult to resolve. Furthermore, a number of gaps correspond to lineages that appear to have lost functionality in their SWS1 genes, although their SWS1 genes remain somewhat intact and can be isolated from genetic sources (Fasick et al., 1998; Spady, 2005; Carvalho et al., 2006; Newman and Robinson, 2005). It would be interesting to investigate the loss of function in a phylogenetic context.

5.2 Chapter 3: Function and evolution of passerine SWS1 pigments

Among vertebrate visual pigments, the SWS1 opsins are unique because they exhibit the broadest naturally occurring variation in λmax. They are thought to achieve sensitivity in the UV range by deprotonation of the normally protonated Schiff base link with the retinal chromophore.

The wide variation in λmax suggests the visual system of different vertebrates might be able to evolve to fine tune SWS1 λmax in order to optimize sensitivity under certain ecological

7 These birds are also note-worthy from the perspective of vision biology: They demonstrate a diversity of S vs. C residues at site 90 in their SWS1 genes and, as mentioned in Chapter 3, different phylogenetic trees lead to opposing hypotheses regarding the evolution of UV vision: either multiple parallel evolutionary events of S90C, or reversals from S to C to S again. To pinpoint where UVS evolved in these lineages and whether it occurred more than once is most compelling. 176 conditions. Also, UVS might allow some organisms to perceive a range of light that is imperceptible by others.

Chapter 3 demonstrates that the λmax of the SWS1 pigment of the great bowerbird expressed in vitro is VS, while all other passerines previously studied have UVS-type pigments (Maier and Bowmaker, 1993; Bowmaker et al., 1997; Hart et al., 1998; Das et al., 1999; Hart, Partridge, Bennett, et al., 2000; Hart, Partridge, Cuthill, et al., 2000; Yokoyama et al., 2000). Our results are consistent with recent MSP studies of bowerbirds (Coyle et al., 2012); thus we have confirmed the presence of VS in passerine birds. Chapter 3 also shows that the ancestral passerine SWS1 was most likely VS, a result that contrasts with earlier studies suggesting that basal passerines may have been UVS (Ödeen et al., 2011). In hand with this, our study presents experimental evidence to indicate that the shared ancestor of passerines and parrots was also VS. Therefore, despite the fact that both passerines and parrots evolved UVS by the same mechanism (S90C), it evolved independently in these orders. In fact, the phylogenetic reconstruction suggests UVS evolved a number of times in passerines, a characteristic of passerines that is not shared with parrots, which are all UVS (Carvalho et al., 2010).

5.2.1 The anomaly of consistent SWS1 spectral tuning in passerines

The study presented here also contributes by presenting the first experimental investigation of SWS1 spectral tuning mechanisms in basal passerines that have a unique residue complement at sites 86 and 90 (C86/S90). It is known that across vertebrates there is a great deal of variation in SWS1 spectral tuning mechanisms (Shi et al., 2001; Takahashi and Ebrey, 2003; Hunt et al., 2004; Parry et al., 2004; Takahashi and Yokoyama, 2005; Hunt et al., 2009; Carvalho et al., 2012). The variation within mammals is particularly interesting because it demonstrates that significant change can occur even over short evolutionary distances (Carvalho et al., 2012). What these prior studies emphasize in particular is the important role of background residues in regulating spectral tuning sites. In this chapter, however, the mutagenesis results demonstrate that spectral tuning mutations in C. nuchalis SWS1 have similar effects on λmax as they do in other extant avian SWS1 genes. Specifically, C90 and F86 in the bowerbird shift λmax into the

UV, and other residues at site 86, C86S in this case, does not affect λmax, nor does it regulate the effects of C90. These findings are similar to those of almost all other avian mutagenesis experiments (Wilkie et al., 2000; Yokoyama et al., 2000; Shi and Yokoyama, 2003; Carvalho et

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al., 2007), except where S86C in an inferred ancestral pigment shifts λmax 30nm into the UV (Shi and Yokoyama, 2003). Therefore, despite the large body of biochemical evidence regarding variation in SWS1 spectral tuning mechanisms across vertebrates that would suggest otherwise, the current consensus of mutagenesis studies in birds suggest it is primarily the presence of C90, and perhaps F86, that determines UVS in avian SWS1 pigments. Therefore it seems that spectral tuning mechanisms are unusually less varied in birds than in other vertebrates. Since the current research in birds is narrow compared to studies in mammals, future work to determine wavelength estimates and spectral tuning mechanisms in birds outside passerines and parrots is necessary to determine whether these traits are consistent across the entire avian lineage.

5.2.2 Further implications on studies in behaviour and ecology

Once it was known that birds perceive colours differently than humans, new approaches were developed to investigate their vision, including models to quantify how colour signals are perceived by an observer (Vorobyev et al., 1998; Endler et al., 2005). The parameters for these models are ideally based on physiological data for the species of interest, but, since spectral absorbance data are available for a small proportion of bird species (Hart, 2001; Hart and Vorobyev, 2005), researchers then must rely on data from related species. This method is not without its risks, as the distribution of UVS and VS might be highly varied across species indicating that assumptions of phylogenetic inertia are unwarranted (Ödeen et al., 2011); the results in Chapter 3 confirm this claim. In order to avoid such problems, it has been proposed that one can instead accurately calculate λmax based on the residues present at sites 86, 90 and 93 (Ödeen and Håstad, 2003; Ödeen et al., 2009). This method has been used in a number of studies (e.g. Håstad et al., 2005; Ödeen and Håstad, 2009; Ödeen and Håstad, 2010; Ödeen et al., 2010; Machovsky Capuska et al., 2011; Ödeen et al., 2011; Aidala et al., 2012; Ödeen et al., 2012). This is a continuing trend in visual ecology but it has not been well supported with experimental testing.

Using spectral tuning residues to calculate λmax is a cost and time efficient method and produces useful genetic information. However, this method implies that SWS1 wavelength sensitivity is primarily bimodal; either UVS or VS, and that SWS1 spectral tuning is a simple mechanism, which misrepresents what is known of SWS1 spectral tuning and could have important consequences. First, discretely categorizing SWS1 λmax as ‘either’ UVS or VS is misleading

178 because it ignores the dramatic wavelength difference among VS type pigments, which can vary from 419 nm to ~390 nm in birds (Yokoyama, et al., 2000; Carvalho et al., 2007), but even more so in across mammals, from 485-445 nm (Hunt et al., 2009). The prevalence and importance of smaller wavelength differences are unclear in birds, but are very important in other systems, such as in fish (Seehausen et al., 2008). Second, by presenting spectral tuning as simple, this suggests that the mechanisms are well known, and, therefore, λmax predictions are reliable and thus can be used to support broader conclusions regarding visual ecology. Contrary to what is suggested however, while most mutagenesis work in SWS1 spectral tuning in birds seems to agree on S90C as an important substitution, the studies are quite limited compared to the number of studies in mammals, where a wide variety of spectral tuning mechanisms have been identified (Hunt et al., 2004; 2009; Carvalho et al., 2012 and references therein).

As discussed in Chapter 3, wavelength regulation in vertebrate SWS1 pigments can be quite complex, whereas in birds it appears it might be less so. Accordingly predicting λmax based on residues at certain amino acid sites might be reasonable in this vertebrate group. But this method has not been well supported by experimental testing. Since avian mutagenesis studies are lacking, many questions remain unanswered. In particular, there is no experimental evidence to support these residues are the cause of UVS in birds outside passerines and parrots. As well, the mechanisms regulating λmax among VS-type pigments remain unidentified. Therefore these methods may be premature. Furthermore, the calculation is based on early mutagenesis studies where C90S wavelength shifts the budgerigar UVS pigment 30 nm (Wilkie et al., 2000; Yokoyama et al., 2000), but this has since been refined to +60 nm (Hunt et al., 2004). Altering the calculation accordingly would dramatically alter the outcome of many λmax estimates.

Certainly, it might be the case that C90 and F86 have a disproportionate effect on λmax in all avian SWS1 pigments, and therefore one might be able to speculate on a broad range whether a pigment is UVS or violet. But, given the diversity in spectral tuning mechanisms that has been observed in other vertebrate groups, and the few expression studies across the diversity of birds, it would seem unreliable to estimate specific λmax values until further expression work is done.

If prediction methods are unavoidable, careful selection of the model species is necessary. Typical models for VS type eyes are the pigeon and chicken. However their SWS1 pigments have extremely low and high λmax values, 388 and 429 nm, respectively (Fager and Fager, 1981;

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Carvalho et al., 2007). It is unknown how a VS pigment with λmax at 388 nm compared to one at 419 nm might influence an animal's visual ability. Given that the difference between them (~30 nm) is as broad as that between pigeon VS and zebra finch UVS (~28 nm), it seems plausible that the difference among VS-type SWS1 pigments imparts marked differences in colour perception. In other vertebrates, even very small differences in λmax can be functionally important (Seehausen et al., 2008). Also, mid-range λmax values are more common: e.g. bowerbird (403), penguin (405 nm) (Wilkie et al., 2000), cormorant (403 nm) (Carvalho et al., 2007), and ostrich (405 nm) (Wright and Bowmaker, 2001). Therefore, since the functional relevance of the wavelength differences among VS-type pigments is not well understood, and the residues responsible for differences among VS pigments are unknown, models based on pigeon and chicken might be even more inappropriate estimations of visual characteristics in other birds, like passerines. Instead, it would seem that when neither in vitro expression nor MSP of the SWS1 are possible, a mid range VS-type pigment, like that of C. nuchalis, might be a more reasonable estimation and thus a better model to use.

5.2.3 Future directions in SWS1 spectral tuning studies

The issue of identifying new spectral tuning sites remains. With this goal in mind, targeted selection of species with unusual residues is necessary. The bowerbird was not selected based on its spectral tuning residues. C86 was a promising possibility as most VS type pigments have S86/S90 whereas UVS type pigments have C86/C90. However, this site had no effect on bowerbird SWS1 λmax. Also, the C86 substitution occurred in the ancestral passerine lineage and is retained among most extant lineages8. Regardless, it might still be important to spectral tuning in other birds as it can alter λmax in other pigments. At the beginning of this study, no other sequence data to identify potentially relevant residues were available. Today, there are a number of examples of individuals with unusual residues at known spectral tuning sites, including a number of passerine lineages which include T93L, T93V, & C86M. T93L is particularly interesting because it occurs with S90C in Acanthisitta chloris. The presence of C90 would

8 Of note, C86 is conserved across most passerine lineages, suggesting it might have an important functional role.

Given it is not involved in λmax regulation, it might have some alternate function relevant to understanding the function and evolution of SWS1 pigments in passerines. As discussed, functional differences among SWS1 pigments are relatively unknown, and correspondingly C86 warrants further consideration. 180 suggest UVS, however site 93 is known to regulate the roles of other spectral tuning sites in mammals (Shi et al., 2001), possibly preventing F86 from having UV shifting effects in some primates (Carvalho et al., 2012). Thus whether A. chloris is UVS or VS would be an interesting question to answer. C86M is interesting because while C86 is shared among most passerines, M86 is conserved within the Sylvioidea, one of the major groups within higher passerines

(Johansson et al., 2008). Mutagenesis studies to clarify the effects of these residues on λmax are needed to clarify the roles of these sites on avian SWS1 wavelength regulation.

Another potentially interesting group would be the paleognaths. Although they include fewer than 1% of extant avian species, paleognaths have long been viewed as central to understanding the early evolution of birds. This group is noteworthy because there is some contradiction among studies of their visual characteristics as to whether they have UV or violet type vision. First, there is conflicting data regarding the residues at the spectral tuning sites in these birds. The most recently published sequence data shows all paleognaths have F86/C90 (Aidala et al., 2012), whereas a previous study indicated S86/S90 in the ostrich (Struthio camelus) and F86/C90 in the rhea (Rhea Americana) (Ödeen and Håstad, 2003). Similarly, with Oliver Haddrath and Allan Baker, colleagues at the Royal Ontario Museum, we isolated SWS1 opsin fragments from the elegant crested tinamou (Eudromia elegans) indicating it has C86/S90. Aside from the clear contradictory sequence data, a physiological study by Wright & Bowmaker (2001) shows the ostrich pigment has a λmax at 405 nm and the ocular media of both ostrich and rhea transmits little light at wavelengths below 377 nm. Since hardly any UV light reaches the retina, the presence of a UV-type SWS1 would be highly unlikely. Therefore, a most pressing question is to confirm the SWS1 sequence data for these species and determine whether these birds have VS type SWS1 pigments, as suggested by physiological characteristics, or UVS-type pigments, as suggested by amino acid characteristics of their SWS1 opsins. In fact, in the SWS1 pigments of these birds F86 and C90 might not confer UVS, which would be particularly interesting given the strong role of these residues in regulating wavelength sensitivity in so many other vertebrate SWS1 pigments.

From the perspective of the evolution of UV vision in vertebrates, these questions are also interesting because it is currently thought that the avian ancestor lost UVS due to a F86S substitution (Shi and Yokoyama, 2003). If the paleognaths are VS, despite the presence of F86, it is possible that other ancestral vertebrates with F86 might also be VS, which could dramatically 181 alter our understanding of the evolution of UV vision in vertebrates. Isolating and expressing paleognath SWS1 pigments followed by mutagenesis experiments would help to clarify the roles of F86 and C90 in these avian SWS1 pigments, and also refine our understanding of the shift to VS in the avian ancestor, particularly when and how it occurred.

The last and most interesting possibility of this project would be to investigate visual ecology of the extinct moas (Diornithiformes), a group of flightless birds endemic to New Zealand. The ostrich sequence could be mutated to resemble those of the moas. This would allow us to explore visual characteristics of an extinct organism, which has never been done before. Identifying the characteristics of their visual pigments could be used to better understand the ecology and behaviour of this highly unusual group of birds.

5.2.4 Role of UV signals in bowerbird mate choice?

In birds, colourful plumage displays are common examples of sexually selected traits. Specific colors are important for mate choice in many species (e.g. Stein and Uy, 2006; Siitari et al., 2007). Ultraviolet (UV) reflectance is widespread in birds (Eaton and Lanyon, 2003). This has led to many studies that have investigated the role of UV in avian mate choice, some demonstrating UV colouration can affect mating success (Andersson and Amundsen, 1997; Hunt et al., 1998; Pearn et al., 2001). These findings have led to suggestions that high UV reflectance has an important role in mate choice (Hausmann et al., 2003), but its importance has also been questioned (Stevens and Cuthill, 2007).

Equally so, the identification of UV reflectance in male plumage and bower ornaments provided motivation for the work presented in Chapter 3: To determine whether bowerbirds have UV or violet type SWS1 pigments. Most bowerbirds have UV reflectance in their plumage and/or choice of bower ornaments, although the proportion of plumage that has UV reflectance varies among species (Endler et al., 2005). Specifically the goal was to identify a link between SWS1 absorption spectra and UV reflectance in the courtship display. But, even though UVS is important for observing UV signals in other passerines (Andersson and Amundsen, 1997; Hunt et al., 1998), C. nuchalis is VS. Similarly, the satin bowerbird (Ptilonorhynchus violaceus) is also VS (Coyle et al., 2012). In this species, the presence of UVS is particularly unusual because the males’ entire plumage shows UV reflectance, and is one of a few avian species with black plumage that also demonstrates a distinct UV reflectance peak (Mullen and Pohland 2008).

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These results suggest the UV component of plumage colouration might not be linked to spectral sensitivity, and UV colouration might not function in bowerbird mate choice.

Further studies on bowerbird behaviour and mate choice in the last few years support the idea that plumage signals, and specifically UV signals, are less important in mate choice in bowerbirds. For example, in spotted bowerbirds (Chlamydera maculata), although crest feathers increase in size relative to status (bower owner vs. non-owner, male vs. female), it is not linked to mating success (Madden et al., 2004). Similarly, in satin bowerbirds the peak reflectance of male plumage is in the UV and UV plumage coloration predicts the intensity of infection from blood parasites, feather growth rate, and body size (Doucet, 2003), yet blue plumage colouration is more important than UV in mate choice (Savard et al., 2011). In fact, considering the varied components of bowerbird visual signals (non-display and display-plumage as well as bower), and their function in sexual selection and mate choice, it has been suggested that bowerbird plumage functions simply in species recognition whereas bower ornaments affect mate choice (Endler et al., 2005; Endler and Day, 2006). In this case, these signals may be evolutionary artifacts from ancestral lineages. For example, in spotted bowerbirds, ancestral females might have selected for male crest size in the past, but over time the focus of female mate choice has shifted to emphasize bower characteristics. Similarly in the satin bowerbird, the mismatch between the peak reflectance of male plumage and both SWS1 λmax and the chroma that is correlated with mating success shows that a peak in plumage reflectance does not necessarily indicate the importance of that color in sexual signaling or spectral sensitivity in that range. Certainly these results would indicate that it is not safe to infer a UVS type SWS1, nor a role for UV colouration in mate choice simply because of a relatively high UV reflectance. Overall, the role of UV signals in bowerbird communication, specifically in mate choice, remains unanswered. The mounting evidence increasingly points to the possibility that UV plumage colouration is not as important to these birds as previously thought. It is possible however that they are sensitive to UV for the purposes of perceiving other types of UV signals or UV light.

5.2.5 Future directions in the ecology of UV/violet vision in birds

There are many avenues for further research on SWS1 visual pigments that can build on my work and that of other researchers. It is clear there is a variable distribution of UV and violet type SWS1 visual pigments across passerines, and whether this extends across birds is yet to be

183 determined. As mentioned, it is necessary to determine the spectral absorbance characteristics of other birds. Interesting species for further investigation include those with interesting sequence characteristics, such as, gulls (Laridae), (with C90 and UV-type ocular characteristics); Paleognaths (with F86/C90 and VS-type ocular characteristics); trogons (with F86). In mammals, nocturnal species have UVS type SWS1 pigments, whereas fossorial and deep-water dwelling species lose SWS1 function altogether. Following suit, other interesting avian species include those that live in unusual photic conditions. Dim-light adapted birds show many morphological adaptations, such as large rod dominated retinae in nocturnal owls (Lisney et al., 2012) and cave- dwelling oil-birds (Martin et al., 2004), and therefore are likely to have molecular adaptations as well.

Aside from investigating the functional characteristics of SWS1 pigments in certain organisms, there are a number of interesting questions regarding the function and evolution of SWS1 pigments and UV vision. While the distribution of UV and violet type SWS1 pigments extends across all vertebrates, it is not yet firmly established 1) exactly how UVS/VS opsins differ at the biochemical level 2) how they are used (i.e. what the role of UV vision is) and 3) whether the

λmax differences observed are adaptive, particularly those across passerines. Answering the first two points will be useful to address the third.

Efforts to describe the functional characteristics of SWS1 pigments are ongoing (e.g. (Kusnetzow et al., 2004; Ramos et al., 2007; Tsutsui et al., 2007; Mooney et al., 2012) and a number of functional differences exist between UVS and VS type SWS1 pigments, highlighted in Chapter 3. These studies, however, focus on model lab species, and could be expanded to encompass SWS1 pigments of a variety of different vertebrates. Also mentioned in Chapter 3 are potential amino acid substitutions in birds (BEB sites or sites derived from comparative sequence analysis) that might affect λmax and/or other properties of avian SWS1 visual pigments. Spectrophotometric and kinetic analyses of these pigments and their mutants in vitro will be needed to reliably link sequence to biochemical variation in this system.

Identifying the variation in λmax would certainly be beneficial, but functional assays of UVS and VS pigments are more interesting. Studies so far suggest remarkable differences between these two opsin sub-types (Altun et al., 2009; Chen et al., 2012). Also, sensitivity in the violet or UV range is determined by the protonation state of the Schiff Base link (Altun et al., 2009), a trait

184 that is regulated by an H-bond network around the retinal chromophore (Altun et al., 2011). As discussed in Chapter 4, non-covalent bond networks are essential to opsin protein function. Correspondingly, changes in the hydrophobic conditions that stabilize deprotonation of the Schiff base link will undoubtedly have further functional consequences. Therefore, there must be functional tradeoffs associated with evolutionary shifts between UV and violet sensitivity. Accordingly, given the increasing evidence that UV signals are not important in all systems, and the dramatic functional differences between UVS vs. VS type pigments, it might be that λmax is not the most important property in some circumstances.

The role that UVS pigments play in any visual behaviour will depend on the expression pattern of the S1 cones in the retina. Mapping UV/violet wavelength sensitivity with retinal characteristics might help to identify how the S1 cones are used. A detailed investigation of expression patterns via in situ hybridization of opsin mRNA sequences or immunohistochemistry labeling of opsin proteins would be necessary. Correlating retinal photoreceptor patterns with UV/violet sensitivity as well as ecology might help to better explain how the different SWS1 types are used.

By incorporating aspects of visual ecology, including mate choice and plumage colouration, one could explore associations under the context of the sensory drive model of evolution. Indeed, a divergence in colour sensitivity associated with changes in male colouration and female preference led to speciation in African cichlids (Seehausen et al., 2008). A potential groups of passerines that might demonstrate this evolutionary trait might be the fairy wrens (genus:

Malurus). A recent sequence survey across the genus suggests λmax shifts between UVS and VS are associated with changes in plumage colouration (Ödeen et al., 2012). These birds are a promising system that seems to demonstrate a link between SWS1 λmax and plumage colouration, and might even be an example of sensory drive in birds.

5.3 Chapter 4: Bowerbird RH1 and the effects of site 83 and 292 on retinal release.

Until very recently, the majority of functional work on RH1s on non-model lab species has focused on differences in λmax. This is somewhat unusual given the primary role of RH1 in mediating dim light vision, where mutations that alter sensitivity would seem most likely. Only recently was N83 suggested to be an adaptation to improve sensitivity, where dim-light adapted 185 cichlids with N83 have increased MII formation rates, which likely increases photoactivation efficiency. My work in Chapter 4 reveals another functional consequence of the N83 substitution, which is a slow retinal release. This suggests that the MII photointermediate may be stabilized by the N83 mutation. Many organisms with N83 express the substitution A292S as well, which also alters retinal release, but increases the rate, suggesting it might be a compensatory mutation.

There are a number of unusual and new findings in this study that make this an exciting project. It is interesting from the perspective of RH1 biochemistry and also from an ecological point of view, with regard to dim light adaptations and bowerbird visual behaviour. From a biochemical perspective, one of the most fascinating aspects of this study is identification of a functional property that has never been observed in any RH1 pigment – an unusually slow retinal release rate. Also interesting is the identification of the particular residue responsible, N83, which has been implicated in a number of studies of RH1 function. This paper is also intriguing from an ecological perspective because this is the first instance N83 has been identified in a bird that is not considered to have dim-light behaviour. Therefore, sharing a substitution with dim-light adapted vertebrates is certainly unexpected. The results regarding A292S also have ecological implications, especially if S292 can compensate for the effects of N83 on retinal release. This means that although organisms with either one or both substitutions are classified similarly, as ‘dim-light adapted’, their RH1s might not share the same functional properties.

Characterizing the functional differences in visual pigment proteins can help us understand how proteins evolve, how the environment can influence the evolution of the visual system, and how ecology and molecular biology are linked. Differences in visual pigment function apart from wavelength sensitivity are also interesting because such adaptations are relatively new to visual pigment research, and so are largely understudied. Furthermore, substitutions that alter visual pigment processing have been the topic of many biochemical studies because such mutations can result in visual disease (Mendes et al., 2005). As well, a number of functional properties of visual pigments are shared among members of the GPCR family of proteins (Smith, 2010). Therefore, comparative functional studies on adaptive characteristics of visual pigment function that alter photoactivation kinetics will not only provide new avenues to study molecular adaptation in the visual system of vertebrates, but will also contribute to characterizing visual diseases and understanding function in similar signaling molecules. 186

5.3.1 Future directions in understanding the roles of sites 83 and 292

There are two obvious directions for building on this work. First, the double mutant in C. nuchalis was not created, neither was the A292S mutation nor a double mutant in the bovine RH1. Measuring retinal release in RH1s carrying all possible combinations of residues at sites 83 & 292, in both bovine and C. nuchalis would make for a more complete story. Second, as mentioned in Chapter 4, it is difficult to predict how these sites are changing photoisomerization kinetics because only retinal release is measured. A more accurate measurement of how these residues alter the relative stabilities of the different photoproducts is necessary to explain the molecular mechanisms involved. This requires a more complete set of functional assays. Primarily, a measurement of how each mutation influences the equilibrium among the MI/MII/MIII photointermediates is required. Along with these studies it would be useful to include RH1s that naturally express both N83 and S292. Lastly, as mentioned in Chapter 4, the effects of N83 have been measured in vitro, thus devoid of regulatory proteins. To determine the consequences of this mutation on greater aspects of the vision process, it must be examined in a complete visual system. All amphibians studied to date contain the N83 mutation (Fyhrquist et al., 1998), and therefore provide a useful system with which to investigate the role of site 83 in RH1 function. Of particular interest are some early electrophysiological experiments in frog rods noting rapid dark adaptation and hypersensitivity after photoactivation (Donner and Reuter, 1965; Sillman et al., 1973; Azuma and Azuma, 1979). A comparison of functional characteristics of frog rods with the rods of species lacking N83, such as mouse, might highlight interesting differences that could be used to direct future studies. Additionally, the implementation of transgenic methods might be useful to determine the effects of the alternate residues at site 83 in the visual systems of both organisms.

5.4 Summary

Presented here is an investigation of the visual pigment proteins of the great bowerbird (C. nuchalis) and other vertebrates. The findings bear primarily on two major fields: in visual ecology and visual pigment function. These studies present examples that illustrate the different ways in which visual pigments can evolve altered properties, and the varied methods that can be used to study them. Also addressed are questions regarding how and why some organisms perceive their world differently than humans do. By identifying the molecular basis for functional differences, these results present a relevant compilation of work on function in visual 187 pigments. In doing so, this thesis highlights the benefit of characterizing the natural variation in vertebrates to reveal and explain the intricacy of visual pigment function. These studies contribute to a greater understanding of visual pigment properties and the evolutionary forces that affect the visual system.

Many birds demonstrate dramatic morphological and behavioural visual adaptations (Waldvogel 1990; Martin, 2011); it is therefore not surprising they have equally unusual molecular adaptations associated with their vision. These molecular differences offer exciting new opportunities to improve our understanding of the visual system, which has been based on studies primarily of humans and model lab species. By characterizing these adaptations we can expand our abilities to answer complex questions associated with the function and evolution of the visual system.

One of nature’s values is in its ability to answer our questions and to teach us things we could never imagine or previously thought impossible. Through this thesis I have emphasized the capacity of natural adaptations to expand our understanding of complex molecular systems. I believe it is through the study of nature, our conversations with it, that we can truly understand the mechanisms, functions, histories, and mysteries of life. This thesis is a documentation of my conversations, and I hope that they may inspire many more.

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6 Appendices 6.1 Appendix 1: Secondary absorbance peaks in short wave absorbing visual pigments expressed in vitro

We observed the wild type and mutant absorption spectra had broad absorbance curves, particularly in the VS pigments. It has been previously noted that SWS1 wild type and mutant pigments expressed in solution can have somewhat abnormal absorption spectra; described as ‘broad’, or as having an ‘additional minor peak’ (Fasick et al., 1999; Wilkie et al., 2000; Yokoyama, et al., 2000; Yokoyama and Shi, 2000; Dukkipati et al., 2001; Shi et al., 2001; Tsutsui and Shichida, 2010). This has also been observed in blue shifted RH1 mutants with the mutations G90C and G90S, which can have unusual bleaching properties (Rao et al., 1994; Janz and Farrens, 2001; Tsutsui and Shichida, 2010).

Hypotheses to explain this phenomenon include: a portion of pigments with altered Schiff base protonation generated by a lowering or raising of the Schiff base pKa, a β band with increased intensity, an impurity that has a relatively strong contribution because of the generally low expression level of SWS1 pigments, or some alternate form of the visual pigment. In VS pigments the peak, or ‘ridge’ is at about 410-420 nm. Given this λmax, it is likely not MII (λmax 380 nm), or MIII (470 nm). It could be explained as contamination of free retinal (the release of retinal from the binding pocket can form adducts with phospholipid head-groups (λmax 440-450 nm) (Sommer and Farrens, 2006). But it is likely not retinal, however, because acid denaturation causes the absorbance spectrum to shift to that characteristic of a protonated retinylidene Schiff base (λmax ~440 nm; Chapter 3 Figures 3 & 4; (Dukkipati et al., 2001)). In the UV absorbing pigments, the peak is about 380 nm, so could be MII.

Others have attempted to narrow the absorption spectrum experimentally, for example by altering pH conditions, but were unsuccessful (Yokoyama, et al., 2000; Shi et al., 2001; Tsutsui and Shichida, 2010). Although commonly expressed in HEPES/glycerol buffers, some researchers have successfully expressed short wave absorbing pigments in Tris-phosphate buffers (e.g. Lin et al., 1998). Therefore, we attempted to narrow the width of the absorption spectrum by purifying the pigments using Tris phosphate buffers, both types of buffers with and without 20% glycerol, as well as by decreasing purification time and by minimizing light and

194 temperature exposure. Our hypothesis was that if the additional LW shifted peak is, in fact, absorbance due to some degraded opsin product, therefore associated with the stability of the opsin, the spectra would be narrower with an improved yield. Alternatively, if the additional peak is due to a modified form of the pigment that forms due to the solution in which it is expressed, the amplitude of the secondary peak might change in different buffers. Samples expressed in Tris phosphate buffers with, and without, glycerol still had secondary absorption peaks. Samples with better yield do have smoother curves and narrower absorption spectra, but retain the secondary peak. Including glycerol in the expression buffer glycerol and fast purification (<12 hrs from harvesting) could increase yield, but the quality of cells used for expression would offer a greater improvement.

It remains unclear why the absorption spectra of some SWS1 pigments are broader than others. In contrast, to our knowledge broad bandwidth spectra have never been observed in MSP data, where absorbance is measured of proteins in the outer segments of photoreceptor cells, in fact UVS type pigments have characteristically narrow absorbance spectra (e.g. Govardovskii et al., 2000). This suggests that the additional peak is likely due to some structural change in the pigment when it is not in its native membrane. In RH1 pigments, the transition through each intermediate is affected by the detergent used (DM vs. CHAPS PC vs. Rod outer segments) (Lewis et al., 1997; Heck et al., 2003; Kuwayama et al., 2005). Accordingly it is quite possible the detergent used is the cause of the secondary light absorbing species, if it is due to the formation of a photointermediate. For this reason, it would be useful to express these pigments in different detergents to prevent the secondary peaks from forming.

195

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6.2 Appendix 2: Factors affecting SWS1 λmax estimates

In this study, we compare both the λmax values of expressed pigments and the nm shifts caused by mutations to λmax estimates from other studies. Such comparisons should be done with caution for a variety of reasons, primarily associated with the variety of methods used to determine λmax and the problems associated with different methods, which are exacerbated in SWS1 pigments due to their short wave absorbencies. These issues are not often discussed in the literature. Some issues are, in fact, unique to SWS1 opsins but it is for this reason, and the lack of SWS1 opsin expression data, that I believe that they have not previously been addressed.

Relating to curve fitting methods: different methods to estimate, whether by fitting an opsin template to a dark spectrum or a difference spectrum, are known give different λmax estimates (Fasick et al., 2002). Additionally, estimates measured from MSP vs. in vitro expressed data can give somewhat different values. For example the λmax of chicken SWS1 measured in vitro is λmax determined from dark spectrum is 415 nm (Yokoyama et al., 2000), or determined from difference spectrum is 419 nm (Carvalho et al., 2007), whereas that purified from eye is 417 nm (Fager and Fager, 1981), and determined using MSP is 418 (Bowmaker et al., 1997).

Other problems are due to the methods used to obtain the data: MSP data is unreliable particularly when λmax is in the Beta curve range, but also because the cones are very small and typically hard to find, so it is difficult to get repeated measurements (E. Lowe pers. commun. ; Govardovskii et al., 2000).

Equally, λmax estimates taken from in vitro data can be questionable for a number of reasons.

First, lower yields affect λmax estimates, and SWS1 proteins are generally less stable, thus more susceptible to such problems. For example, the first expressions of the budgerigar C90S mutant had a 30 nm shift from wild type (Wilkie et al., 2000), whereas a later expression with increased yield demonstrated this shift was, in fact, 60 nm (Hunt et al., 2004). Furthermore, data collected from proteins in solution are affected by the underlying absorbance of the buffer, which increases dramatically towards shorter wavelengths. Finally, proteins expressed in vitro, particularly mutant pigments can have extra absorbance peaks that broaden the absorbance spectra, and therefore it does not reflect the standard template shape (Appendix 1). In addition, the commonly used template is designed to narrow towards shorter wavelengths to accommodate observations

197 made of absorbance curves obtained by MSP (Govardovskii et al., 2000). Correspondingly the effects of an artificially broadened peak will be exacerbated. However, estimating λmax from the difference spectra might account for this (Fasick et al., 1999; Wilkie et al., 2000). While low yields can affect λmax estimates from all types of pigments, the absorbance by the buffer and presence of secondary absorbance peaks are more problematic for SWS1 pigments because they absorb in the SW range and therefore are more susceptible to distortion.

In considering the above discussion points and my observations from my data and of others, it is possible that the 'observed variation' in λmax among vertebrate SWS1 pigments, particularly the

UVS type, might not be real but instead due to the variety of methods used to estimate λmax and the inherent issues associated with these different methods, many of which are particular to or exacerbated in SWS1 pigments due to their relative instability and short wave absorbance.

Methods to address these issues are necessary. Particularly to compare the differences in estimation methods on a variety of data and to determine the degree by which poor data affects

λmax estimates. Chicken SWS1 has been measured a number of times using a variety of methods and therefore would be an appropriate model to use.

Accordingly I acknowledge the potential inaccuracies of the comparisons of my λmax estimates to those of others, knowing that different λmax estimation methods were used. Because of the limited data available, it is unavoidable. Regardless, it is clear that the S90C, C86S/S90C, and C86F mutants are UVS, and that the S90C and double mutant C86S/S90C are very similar, if not identical, in λmax.

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