Colour Vision and Mate Choice in the Family Poeciliidae

Home , Amazon molly, Poecilia parae, Poecilia wingei

Beauty in the Eyes of the Beholders: Colour Vision and Mate Choice in the Family Poeciliidae

by Benjamin Alexander Sandkam B.Sc. (Integrative Biology), University of Illinois at Urbana-Champaign, 2009

Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

in the Department of Biological Sciences Faculty of Science

Approval

Name: Benjamin Alexander Sandkam Degree: Doctor of Philosophy (Biological Sciences) Title: Beauty in the Eyes of the Beholders: Colour Vision and Mate Choice in the Family Poeciliidae Examining Committee: Chair: Gerhard Gries Professor

Felix Breden Senior Supervisor Professor

Wendy Palen Supervisor Associate Professor

Kimberly Hughes Supervisor Professor Department of Biological Science Florida State University

Michael Hart Internal Examiner Professor Department of Biological Sciences

Karen Carleton External Examiner Associate Professor Department of Biology University of Maryland, College Park

Date Defended/Approved: September 21, 2015

Ethics Statement

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Abstract

Sexual selection plays a major role in numerous aspects of evolution. Many models have attempted to explain how mate preferences evolve both across populations within a species and across species. ‘Sensory bias’ predicts that the traits involved in mate choice will co-evolve with the tuning of the sensory systems responsible for detecting such traits. The family Poeciliidae is a classic system for studies of mate choice and provides an excellent opportunity to examine the co-evolution of preference for colour traits and the sensory system detecting such traits: colour vision. In this dissertation, I present a body of work investigating how colour vision differs across species and populations, thus exploring the potential role sensory systems have in shaping mate preferences. To do this, I focus on the opsin genes, which play a predominant role in tuning the wavelength sensitivity of cone cells – the detectors for colour vision. I found the Long Wavelength Sensitive opsins (detecting red/orange colours) experience high rates of gene conversion due to their genomic architecture. The effects of conversion may be influenced by the importance of red/orange in mate choice decisions. While traditional models of duplication and divergence suggest sensory repertoire expansion occurs slowly, I found hybridization can expand sensory repertoires in one generation. I have termed this process: Hybrid Sensory Expansion. I then focus on one species to show that differences in visual tuning (gene expression and allele frequency) co-vary with mate preferences across populations in a manner that is consistent with the Sensory Exploitation (SE) model for the evolution of female mate preferences. However, I go on to find that closely related, highly sympatric species differ in colour vision more across populations than across species within populations on mainland South America. This suggests that while SE could explain differences in mate preference across populations, it may not scale up to explain species level differences as generally assumed. Taken together, these results show that the evolution of visual tuning may not always evolve through traditional mutation-selection models and that visual systems are far more variable across populations within species than generally assumed.

Keywords: Opsin; Sensory System; Ecological Genetics; Sensory Bias; Sensory Exploitation; Sexual Selection

Dedication

For family, friends, fish and fun

Acknowledgements

As this thesis is a result of lifelong learning both in the classroom and out, I owe a great deal to a great many people that have touched my life over the years. Specifically, I am tremendously thankful for the wonderful guidance and support of my advisor Dr. Felix Breden who always went along with my crazy plans for projects in both the lab and field- even when it meant exhausting fieldwork. Felix has been not only an excellent mentor but also a great friend and role model.

It is impossible to express my gratitude to my wife, Dr. Nora Prior, for her boundless support, insightful intellectual contributions and her uncanny ability to keep us moving forward. I thank our daughter, Ardea Sandkam, for keeping me active and sharing a love of the outdoors. I am also incredibly thankful for the amazing support of my in-laws, Dr. Julie Hengst and Dr. Paul Prior for their amazing patience, support and guidance into the world of academia. Thank you also to my close friend Matt Taves, for excellent scientific discussions while exploring nature on and under the water. I thank my parents, Tracy and Jeff Sandkam, for their support and kindling a lifelong love of the natural world.

I owe a great deal to all members of the Breden and FAB* labs past and present, specifically: Drs. Mike Hart, Arne Mooers, Bernie Crespi, Corey Watson, Jeff Joy, Will Stein, Mika Mokkonen, Kristen Gorman, and Iva Popovic, for insightful feedback, training, and excellent camaraderie. Megan Young and Kristina Pohl were invaluable to my ability to work off campus and I am very grateful for their patience and assistance.

A big thank you to my committee members, Drs. Kim Hughes and Wendy Palen, for the great feedback and understanding while my thesis morphed into what it has become. Thank you also to Dr. Karen Carleton for graciously taking the time to provide outside perspective as my external examiner.

While not directly involved with the work of this thesis, I am incredibly grateful to Dr. Isabelle Côté for training in scientific SCUBA diving, and inspirational enthusiasm for all things aquatic. Thank you also, to my undergraduate advisor, Dr. Becky Fuller, for the opportunities, advice and support that has continued even long after leaving her lab.

Table of Contents

Approval ...... ii Ethics Statement ...... iii Abstract ...... iv Dedication ...... v Acknowledgements ...... vi Table of Contents ...... vii List of Tables ...... x List of Figures ...... xii Introductory Image ...... xiv

Chapter 1. Introduction ...... 1 The Family Poeciliidae ...... 2 Mate Choice Evolution ...... 3 Colour Vision ...... 5 Objectives ...... 7 References ...... 9

Chapter 2. The impact of genomic environment on the evolution of colour vision in the family Poeciliidae, a model for visually based sexual selection ...... 16 Publication and Contributions ...... 16 2.1. Abstract ...... 16 2.2. Introduction ...... 17 2.3. Materials and Methods ...... 19 2.3.1. Sequencing ...... 19 2.3.2. Tree Building ...... 20 2.3.3. Gene Conversion Analyses in LWS Opsins ...... 21 2.3.4. Identifying Sites Under Selection in Non-LWS Genes ...... 22 2.4. Results ...... 22 2.4.1. Data Set and Alignment ...... 22 2.4.2. Phylogenetic Analyses ...... 23 2.4.3. Gene Conversion Analyses ...... 23 2.4.4. Identifying Sites Under Selection in Non-LWS Genes ...... 23 2.5. Discussion ...... 24 2.5.1. Gene Conversion, Not Independent Duplications ...... 25 2.5.2. Why is Gene Conversion so Prevalent Between LWS-1 and LWS- 3? ...... 25 2.5.3. Implications of Gene Conversion to Colour Vision ...... 26 2.5.4. Selection in Non-LWS Genes ...... 28 2.6. Conclusion ...... 28 Acknowledgements ...... 29 Data Accessibility ...... 29 References ...... 30 Tables and Figures ...... 35

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Chapter 3. Hybridization leads to sensory repertoire expansion in a gynogenetic fish, the Amazon molly (Poecilia formosa): a test of the hybrid-sensory expansion hypothesis ...... 55 Publication and Contributions ...... 55 3.1. Abstract ...... 55 3.2. Introduction ...... 56 3.3. Materials and Methods ...... 58 3.3.1. Sample Preparation, PCR, Cloning and Sequencing ...... 58 3.3.2. Phylogenetic Analyses ...... 59 3.3.3. Determination of Alleles Expressed in a Hybrid Species ...... 60 3.3.4. Behavioural Response to Coloured Disks ...... 61 3.4. Results ...... 62 3.4.1. Dataset ...... 62 3.4.2. Phylogenetic Analysis ...... 63 3.4.3. Determination of Alleles Expressed in a Hybrid Species ...... 63 3.4.4. Behavioural Response to Coloured Disks ...... 64 3.5. Discussion ...... 64 3.5.1. Strong Evidence of HSE in Poecilia formosa ...... 64 3.5.2. What Does HSE Mean For P. formosa Vision? ...... 66 3.5.3. Unanticipated Pecking Behaviour ...... 67 3.5.4. Fitness Implications of HSE ...... 68 3.6. Conclusion ...... 68 Acknowledgements ...... 69 Data Accessibility ...... 69 References ...... 70 Boxes, Figures and Tables ...... 75 Supplementary Tables ...... 81

Chapter 4. Beauty in the eyes of the beholders: Colour vision is tuned to mate preference in the Trinidadian guppy (Poecilia reticulata) ...... 84 Publication and Contributions ...... 84 4.1. Abstract ...... 84 4.2. Introduction ...... 85 4.3. Materials and Methods ...... 88 4.3.1. Sample Collection and Environmental Parameters ...... 88 4.3.2. qPCR Assay Design ...... 89 4.3.3. Sample Processing and Analyses ...... 91 4.3.4. LWS-1 A/S Allele Frequency ...... 93 4.3.5. Statistical Analyses of Opsin Expression ...... 93 4.4. Results ...... 94 4.4.1. Guppy Opsin Expression Differs Across Populations ...... 94 4.4.2. Low Predation Populations Express Higher Levels of LWS Opsins ...... 95 4.4.3. Gene Frequencies of the 180 Ala Versus Ser Allele of LWS-1 ...... 96 4.4.4. Environmental Parameters ...... 96 4.5. Discussion ...... 97 4.5.1. Guppy Colour Vision Differs Across Populations ...... 97 4.5.2. Low Predation Populations Express Higher Levels of LWS Opsins ...... 99 4.5.3. Implications for Evolutionary Theory ...... 101

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4.6. Conclusion ...... 103 Acknowledgements ...... 103 Data Accessibility ...... 103 References ...... 104 Tables and Figures ...... 110 Supplementary Tables and Figures ...... 116

Chapter 5. Colour vision varies more among populations than species of live-bearing fish from South America ...... 127 Publication and Contributions ...... 127 5.1. Abstract ...... 127 5.2. Introduction ...... 128 5.3. Materials and Methods ...... 130 5.3.1. Sample Collection ...... 130 5.3.2. qPCR Assay Design ...... 131 5.3.3. Sample Processing and Analyses for Opsin Expression ...... 133 5.3.4. LWS-1 A/S Allele Frequency ...... 135 5.3.5. Statistical Analyses of Opsin Expression ...... 136 Do species and/or populations differ in colour vision? ...... 136 Does opsin expression differ more by species or locations? ...... 136 How do species differ in colour vision? ...... 137 5.4. Results ...... 137 5.4.1. Do species and/or populations differ in color vision? ...... 137 5.4.2. Does opsin expression differ more by species or location? ...... 137 5.4.3. How do species differ in color vision? ...... 138 5.4.4. Gene Frequencies of the 180 Ala vs. Ser Allele Vary Across Species ...... 138 5.5. Discussion ...... 138 5.5.1. Colour Vision Differs Across Populations Within Species ...... 139 5.5.2. Sensory variation and mate choice divergence ...... 141 5.6. Conclusion ...... 143 Acknowledgements ...... 143 References ...... 143 Tables and Figures ...... 149 Supplementary Tables ...... 155

Chapter 6. Concluding remarks and syntheses: Can beauty be found in the eyes of the beholder? ...... 159 6.1. Colour Vision Can Vary Considerably Within Species ...... 160 6.2. The Value of Sensory Exploitation as a Theoretical Framework for Understanding Mate Preferences ...... 162 6.3. Conclusions...... 164 References ...... 165

List of Tables

Table 2.1. The five key-site haplotype of the four LWS opsin loci with λmax predicted following Yokoyama and Raddlewimmer (1998). The number of different LWS λmax within species is summarized as ‘# LWS’...... 35 Table 2.2. Selection tests on non-LWS opsins using models M0, M1, M2, M7 and M8 of the codeml program in PAML. Likelihood ratio tests (LRTs) were performed between models with selection and models with neural evolution to identify genes under positive selection...... 36 Table 2.3. Sites identified as under positive selection using the M2 and M8 models in codeml of PAML, and the REL, FUBAR, and FEL programs of HYPHY. Grey highlight indicates the site is in the transmembrane domain. / indicates site was not identified to be under selection using that method. NA indicates run was not available. Numbers given for M2, M8, REL, and FUBAR are posterior probabilities while numbers for FEL are P values...... 37 Table 3.1. Comparison of the two P. formosa alleles and parental species for each LWS locus and RH2-1. Percent similarity is given above the diagonal. Number of gaps is given below the diagonal. Dark grey boxes show the most similar parental sequence for each allele from P. formosa...... 78 Table 3.2. Amino acid differences in LWS loci across species. Amino acid numbering follows that of Yokoyama (2000). Transmembrane designations indicate whether the amino acid site is located in the transmembrane domain (Y-yes; N-no), where changes in amino acids are more likely to shift spectral absorbances. ‘-’ indicates there was no variation in amino acids at that site for that locus. The amount of within species variation is unknown. Shading is provided to facilitate visual comparison...... 79 Table 3.3. Tukey’s HSD comparing the hybrid P. formosa and parental species, P. mexicana and P. latipinna, in the number of pecks and approaches made toward coloured disks. Bold values indicate significance at p < 0.05...... 80 Table 4.1. Results of MANOVA on opsin expression profiles. W- Watershed, T- Time, P(W)- Predation nested in watershed...... 110 Table 4.2. Results of MANOVA on opsin expression profiles by watershed...... 110 Table 4.3. Results of LWS ANOVA. W- Watershed, T- Time, P(W)- Predation nested in watershed...... 111

Table 5.1. Results of MANOVA on opsin expression profiles as proportional and relative(hk) measures. Loc, Location; Sp(Loc), Species nested in Location; Sx(Sp(Loc)), Sex nested in Species, nested in Location. Bold indicates P < 0.05...... 149 Table 5.2. AIC values for the ability of models based on Location, Species, or Location*Species to explain variation in proportional measures of opsin expression for each opsin gene. Bold indicates P < 0.05...... 149 Table 5.3. Results of opsin expression ANOVAs using proportional and relative(hk) measures by location. Bold indicates P < 0.05...... 150

List of Figures

Figure 1.1. Male guppies (Poecilia reticulata) are highly variable in colour and number of spots...... 14 Figure 1.2. Males of the subgenus Lebistes are very colourful. While Poecilia reticulata males are highly variable in colouration, there are only two male morphs of Poecilia picta and five discrete male morphs of Poecilia parae...... 15 Figure 2.7. ND2 mitochondrial bayesian consensus tree with posterior probabilities. Outgroup is Oryzias latipes...... 45 Figure 2.8. Bayesian consensus tree with posterior probabilities of SWS1. Outgroup is Oryzias latipes...... 46 Figure 2.9. Bayesian consensus tree with posterior probabilities of SWS2A and SWS2B. Outgroup is Oryzias latipes...... 47 Figure 2.10. Bayesian consensus tree with posterior probabilities of RH1. Outgroup is Oryzias latipes...... 48 Figure 2.11. Bayesian consensus tree with posterior probabilities of RH2-1. Outgroup is Oryzias latipes...... 49 Figure 2.12. Bayesian consensus trees with posterior probabilities of (A) LWS UTR sequence, and (B) LWS full sequences. Outgroup is Oryzias latipes. Note the expected duplication history recovered in UTR sequence and general species relationships (based on ND2 tree) recovered within clades except for LWS-1 and LWS-3 of the full LWS tree...... 50 Figure 2.13. (A) The genomic organization of the LWS opsin loci in P. wingei (adopted from Watson et al. (2011)). (B) The proposed conformation leading to high rates of gene conversion between LWS-1 and LWS-3 in the event of a double strand break. Arrows denote directionality. Coloured boxes denote exons while spaces between boxes denote introns...... 51 Figure 3.1. Bayesian consensus phylogenies of (A) long wavelength sensitive (LWS) opsin loci, and (B) RH2-1 opsin locus in Poecilia mexicana, P. latipinna, and the two P. formosa alleles. Maximum likelihood bootstraps and Bayesian posterior probability values (respectively) are reported for each node...... 76

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Figure 3.2. Violin plots (Hintze and Nelson 1998) showing the proportion of pecks and approaches made toward each coloured disk for the hybrid P. formosa and the parental species P. mexicana, and P. latipinna. Violin plots contain a box plot (white circles denote mean) surrounded by a grey kernel density plot which shows the distribution of the data followed by smoothing to facilitate visual comparison across plots. Letters denote groups that differ significantly (Tukey’s HSD, p<0.05)...... 77 Figure 4.1. Long wavelength-sensitive (LWS) opsin expression by population for proportional measures. Stars denote significant differences between high and low predation within the same watershed (*P < 0.05, **P <0.01, ***P < 0.001); error bars are ±1 SE (see Table S8, Supporting information). Aripo low predation at 13:30 had N = 17; all other population time points had N = 18...... 112 Figure 4.2. Long wavelength-sensitive (LWS) opsin expression by population for relative(hk) measures. Stars denote significant differences between high and low predation within the same watershed (*P < 0.05, **P < 0.01); error bars are ±1 SE (see Table S9, Supporting information). Aripo low predation at 13:30 had N = 17; all other population time points had N = 18...... 113 Figure 4.3. Proportional expression at time point 2. Stars denote significant differences within watershed between high- and low-predation populations (*P < 0.05, **P < 0.01, ***P < 0.001) (see Table S8, Supporting information). Letters denote significant differences between watersheds (see Table S6, Supporting information)...... 114 Figure 4.4. Genotype and gene frequencies of the 180 Ala (A) vs. 180 Ser (S) allele of LWS-1. LWS, long wavelength-sensitive...... 115 Figure 5.1. Proportional measures of opsin expression across species and locations. Letters denote significant differences in expression of individual opsins across species within a location. Note: West Watuka has only P. bifurca and was not used in statistical analyses...... 152

Figure 5.2. Relative(hk) measures of opsin expression across species and locations. Letters denote significant differences in expression of individual opsins across species within a location. Note: West Watuka has only P. bifurca and was not used in statistical analyses...... 153 Figure 5.3. Genotype and gene frequencies of the 180 Ala (A) versus 180 Ser (S) allele of LWS-1. LWS, long-wavelength sensitive...... 154

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Introductory Image

“Hooray for eyes! Hooray, hooray, hooray… for eyes!”

The Eye Book by Dr. Seuss

Image created by Todd Adamson, Integrated DNA Technologies, for a story featuring the published version of Chapter 5.

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Chapter 1.

Introduction

Sexual selection is capable of playing a key role in the evolution and divergence of populations (Carleton et al. 2005; Seehausen et al. 2008), maintaining genetic polymorphisms within populations (Sinervo and Lively 1996; Hughes et al. 2013), and can even lead to speciation (Panhuis et al. 2001; Coyne and Orr 2004). A great many models have been put forth to explain the role of sexual selection on the evolution of a species (reviewed in Kuijper et al. 2012). The genes underlying differences in sexual selection are largely assumed to follow traditional ‘mutation-selection’ models of evolution (Jennions and Petrie 1997; Kirkpatrick and Hall 2004). However, even relatively small deviations from such models could result in significant effects on the direction, strength and role of sexual selection. When sexual selection takes the form of inter-sexual mate choice, both the characters preferred and the corresponding preferences are expected to co-evolve (Pomiankowski and Sheridan 1994; Breden et al. 1994; Andersson and Simmons 2006). As such, one can use differences in sexual characters across species as a proxy for corresponding differences in mate choice. For traits to play a role in mate choice they first must be detected by the assessor’s relevant sensory system (Endler 1990; Horth 2007). Since sensory systems play multiple roles as organisms interact with their environment (such as foraging, navigating, predator avoidance, circadian regulation, etc.) they frequently adapt to local conditions through either evolution or plasticity (Loew and Lythgoe 1978; Fuller et al. 2004; Endler et al. 2005). Such variation in a crucial aspect of mate choice could offer a key factor influencing the strength, direction and role that sexual selection plays in the evolution of a species. It is therefore important to know the extent to which variation in peripheral sensory systems can explain differences in sexually selected traits.

In this thesis I use phylogenetic, laboratory and field based methods to investigate the variation and evolution of colour vision in the extensively studied family of freshwater, live-bearing fishes, the Poeciliidae. This family is one of the premier models for sexual selection as it includes such species as guppies (Poecilia reticulata), swordtails (Xiphophorous helleri), and sailfin mollies (Poecilia latipinna); since 1949, more than 1000 papers have been published on this group solely in the area of intersexual mate choice. Nearly all of the sexually selected traits described in this diverse group are transmitted visually and occur as either differences in morphology or colouration (Pollux et al. 2014). Poeciliid fishes have excellent colour vision, which plays a major role when making mating decisions based on colouration.

The Family Poeciliidae

The family Poeciliidae is comprised of over 250 species spanning 22-28 genera of live-bearing freshwater fishes (Stockwell and Henkanaththegedara 2011). Poeciliid fishes are native to areas from lower North America to the Amazon basin in South America but are now found world wide as a result of human introductions, frequently as pest control or aquarium releases (Stockwell and Henkanaththegedara 2011).

Sexual dimorphism is common across the family such that males are more ornamented than females, demonstrating the strong role that sexual selection has played in the evolution of such a diverse family (Farr 1989; Bisazza 1993). In several species males have exaggerated fins, and females base mating decisions on the size of the males’ fin. This includes species of the genus Xiphophorus where females prefer to mate with males with elongated caudal fins (Basolo 1990a,b; Robinson et al. 2011) and Poecilia latipinna where females prefer males with enlarged dorsal fins (Ptacek and Travis 1997).

In other species sexual dimorphism occurs where males have bright colouration while females remain relatively drab grey or silver, in these species females make mating decisions based on male colouration. This pattern includes classic species such as guppies (Poecilia reticulata) where males vary substantially in the size and colour of spots (Figure 1.1) and females generally prefer more colourful males (Haskins and Haskins 1949; Haskins et al. 1961; Endler 1978; Breden and Stoner 1987; Magurran

2005). Several species that are closely related to guppies also make mating decisions based on male colouration; including P. parae where males occur in five discrete morphs (one large bodied with low colouration, three medium sized bodied with colour variation, and one small bodied female mimic) (Lindholm et al. 2004) (Figure 1.2). Poecilia picta is a sister species to P. reticulata and P. parae, which shows some male colouration but the role of colouration in mate choice is unknown (Breden and Bertrand 1999) (Figure 1.2). Surprisingly, P. reticulata, P. parae, and P. picta occur in extreme sympatry on mainland South America such that they are frequently found schooling together in small drainage ditches. Despite the close proximity and similar morphology they do not hybridize and cross species mating is rare (Liley 1965; Magurran and Ramnarine 2004; 2005). Such strong prezygotic isolation relies on correctly identifying and evaluating potential mates.

Mate Choice Evolution

Many models have been put forth in an effort to explain the evolution of mate preferences. Such models fall into the general categories of: direct benefits, indirect benefits, and sensory by-product (reviewed in Kuijper et al. 2012). Direct benefit models can be used to explain the evolution of female preferences in systems where males contribute more than just sperm - such as access to territory, protection from predators or parental investment (Kuijper et al. 2012). Direct benefit models are unlikely to explain the evolution of female preferences in the Poeciliidae family, as males are not known to make any direct contributions to females or offspring.

Indirect models can be further divided into three categories: ‘Fisherian processes’, ‘good genes’ and ‘compatible genes’. ‘Fisherian processes’ (frequently referred to as ‘sexy sons’) follow the logic originally put forth by RA Fisher (Fisher 1915). This line of reason posits that by choosing attractive mates, females will have more attractive sons, which other females are more likely to choose as mates and thereby securing more grand-offspring. However, some researchers have questioned the ability of ‘Fisherian processes’ to act alone in driving the evolution of sexual selection as they are expected to break down when preferences are costly (Hall et al. 2000). Furthermore, while ‘Fisherian processes’ can explain increases in the strength of pre-existing female preference, they do little to explain the forces that led to the origin of such preferences.

‘Good genes’ and ‘compatible genes’ models of indirect benefits suggest that female preferences arise for traits that signal the genetic quality of a male. There has been some support for ‘good genes’ models to explain female preferences for male colour in Poeciliid fishes, particularly when the colours preferred by females cannot be synthesized by the male and must be obtained by foraging, such as with carotenoids (Grether 2000; Grether et al. 2005). However, ‘good genes’ models are generally thought to lead to a decrease in genetic diversity of a population or species (commonly referred to as the Lek paradox) (reviewed in Kotiaho et al. 2008) yet there is substantial genetic diversity in most Poeciliid species that have been examined (reviewed in Breden and Lindholm 2011) (although high diversity may be the result of genic capture at work (Rowe and Houle 1996)). The loss of genetic diversity is overcome in ‘compatible genes’ models, which suggest mate preferences could be the result of epistatic interactions, leading to variation in female mate preferences (Kuijper et al. 2012). However, neither of these models predict why specific traits arise.

‘Sensory by-product’ models suggest female preferences arise as a by-product of detection by the sensory system. For male signals to play a role in mate choice they must be displayed by an individual, transmitted through the environment, and detected by a female’s sensory system (Endler and Basolo 1998; Endler et al. 2005). While changes to male display traits and environmental transmission processes are both likely to impact female mating decisions, it is detection by the female’s sensory system that is the first stage of the process that is genetically inherited and is thereby capable of impacting the evolution of female mate preferences. There are many ‘sensory by- product’ models (primarily varying in the order or strength of selection), including: sensory traps, sensory drive, pre-existing bias, and sensory exploitation (reviewed in Basolo and Endler 1995; Endler and Basolo 1998). While many of these models were originally brought forth to explain the evolution of male display traits, the implications can be extended to explain the evolution of female mate preferences as well. The ‘sensory bias’ model has previously been implicated in the evolution of female preference for orange colouration in guppies (Rodd et al. 2002). ‘Sensory bias’ predicts that females have evolved a preference toward specific sensory stimuli outside the context of mate choice, and then males evolve to display matching stimuli (Basolo and Endler 1995; Endler and Basolo 1998). This model predicts that all populations should evolve the

same female mate preferences, yet there is considerable variation in mate preference for colouration across populations of guppies (Houde 1997; Brooks and Endler 2001). One alternative model that may better explain differences in mate preferences across populations is that of ‘sensory exploitation’. Sensory exploitation predicts that males evolve sexual signals to maximize stimulation of females’ sensory systems (Endler and Basolo 1998). Environments can vary considerably across populations of freshwater fishes in both quantity and quality of the available light spectrum (Lythgoe 1966; Loew and Lythgoe 1978; Levine and MacNichol 1979; Bowmaker 1995; Palen and Schindler 2010). Such variation would be expected to result in variation of the visual system across populations as organisms adapt to local conditions. Therefore the ‘sensory exploitation’ model is a prime candidate to explain the evolution of female mate preferences when there is variation both across species and across populations within species, such as seen in the family Poeciliidae. Many Poeciliid species base female mate preferences on male colouration, making variation in colour vision a prime candidate to test for the role of ‘sensory exploitation’ in the evolution of female mate preferences. Identifying variation in colour vision requires a detailed understanding of the mechanisms underlying colour vision.

Colour Vision

Colour vision is the discrimination of different wavelengths of light and is accomplished by the brain comparing signals from differentially tuned cone cells in the retina (Conway 2009). Cone cells detect light using transmembrane G protein-coupled receptors called opsins, which when bound to a chromophore are called visual pigments. In vertebrates opsins are either bound to an 11-cis-retinal (A1) or 11-cis-3,4- didehydroretinal (A2) chromophore (Terakita 2005). When a photon is absorbed there is a change in the conformation of the chromophore from 11-cis to all-trans, causing the visual pigment to couple with a G-protein and start a signal transduction cascade resulting in the perception of light. The wavelength of the photon to which a visual pigment is most sensitive is called its λmax. Generally, each cone cell has only one visual pigment type, and it is the comparison of signals from cone cells with visual pigments that have different λmax that allows colour vision. The λmax of visual pigments are tuned by several methods across taxa including: selectively using either A1 or A2 chromophores

(e.g. crayfish (Zeiger and Goldsmith 1989)), differences in the amino acid sequence of the opsin protein (Yokoyama 2000; 2002), or differences in the expression of the opsin proteins (Hofmann and Carleton 2009). Of these methods for tuning visual receptors, differences in opsin sequence are by far the most common (Terakita 2005).

Opsin amino acid sequences are directly coded in the DNA and do not require post-translational modification (Yokoyama and Yokoyama 1996). This means the λmax of a visual pigment made with a particular opsin can be directly estimated from the amino acid sequence of that opsin (hereafter referred to as the opsin’s λmax) (Yokoyama and Radlwimmer 1998). Therefore studies of opsin DNA sequence can be highly informative to investigations on the colour vision of a particular organism. This also means the evolution of colour vision is subject to genomic processes and constraints underlying the evolution of a multi-locus gene family.

Opsin genes are highly similar across taxa and are broken in classes depending on the range of light, and thereby colours, they detect: short wavelength sensitive 1 (SWS1) detect ultraviolet; short wavelength sensitive 2 (SWS2) detect blues and purples; rhodopsin like (RH2) detect greens; and long wavelength sensitive (LWS) detect reds and oranges. While humans with normal colour vision have only three different opsin proteins, Poeciliid fishes have an astounding nine cone opsin proteins: one SWS1, two SWS2 (SWS2A and SWS2B), two RH2 (RH2-1 and RH2-2), and four LWS (LWS-1, LWS-2, LWS-3, and LWS-R). Previously the LWS opsins have been named for the amino acid they possess at the location that corresponds to the 180th amino acid in humans (A180, S180, P180, and S180r) (Ward et al. 2008) but Chapter 3 proposes a new naming scheme for these genes, which has been taken up by the field (Tezuka et al. 2014). The LWS opsins are now named for the genomic location of their locus in the tandem array in which they are situated (for LWS-1, LWS-2 and LWS-3), while LWS-R is a retrotransposed gene (Sandkam et al. 2013). The expansion of the LWS opsin gene family in Poeciliid fishes, variation in sequence, and the role of red/orange in mate choice (detected by LWS opsins) make opsins a likely candidate in which to test for ‘sensory exploitation’ in the evolution of female mate preferences.

Objectives

My thesis is comprised of a series of studies examining the evolution of colour vision and mate choice in Poeciliid fishes. These studies used a combination of laboratory and field techniques to assess variation in opsin gene sequence and expression across species and populations. The goals of this body of work has been to examine: (1) the patterns underlying opsin evolution, (2) the relationship between opsin evolution and sexual selection, (3) the propensity for variation in the visual system to lead to differences in mate preferences across populations of the same species, and (4) whether visual systems vary more across species in the same location or across populations within species. Finally, whether phenotypic adaptation is primarily driven by changes in coding region or regulation of such sequences remains an ongoing controversy in evolutionary biology (King and Wilson 1975; Carroll 2005; Hoekstra and Coyne 2007). The experiments in this thesis directly estimate the relative contributions of these factors to variation in colour vision within and between species.

Chapter 2 explores the evolution of the opsin genes across the family Poeciliidae by sequencing and building phylogenies of fifteen species. Phylogenies built on LWS opsins revealed a high incidence of gene conversion – a phenomenon resulting in one locus overwriting another. Gene conversion of the LWS opsins is likely the result of their genomic architecture, which may be impacting the rate at which these genes are evolving. The potential role of gene conversion in shaping sexually selected characters is explored using phylogenetic techniques.

The evolution of colour vision is generally thought to rely on traditional models of mutation and selection where small, functional, changes occur by chance and accumulate gradually over many generations (Terakita 2005). In time, species are expected to evolve opsin genes that are both functional, and tuned to their local conditions. This pattern results in species having unique, functional opsin genes. Expanding the number of sensory genes is thought to rely on gene duplication, which then must go through the traditional slow process of divergence. Hybridization is a process that brings together genetic material from two species. Chapter 3 proposes and tests the Hybrid Sensory Expansion hypothesis. This hypothesis predicts that when two

species with distinct sensory repertoires hybridize, the resulting offspring will have a functional sensory repertoire that is larger than either of the parent species.

While wavelength sensitivity is largely tuned by opsin gene sequence, colour vision can also be modulated through differential expression of the opsin genes (Hofmann and Carleton 2009). Chapter 4 explores how colour vision differs across populations of guppies in independently colonized watersheds of Trinidad through opsin gene expression and allele frequency variation. Populations known to have stronger female preferences for more red/orange males were found to express higher levels of LWS opsins (responsible for detecting those colours) and differ in the frequency of an allele known to affect tuning of the LWS-1 opsin. These results support the sensory exploitation model for the evolution of female mate preferences and demonstrate how dramatically populations can differ in colour vision.

Populations divergence in mate preference through sensory bias models that results in speciation relies on variation in sensory systems within and across species. Chapter 5 evaluates whether there is more variation within or across closely related sympatric species on mainland South America. Surprisingly, opsin expression and allele frequencies of P. reticulata, P. picta, and P. parae differed as much or more across populations within species as they did between species within populations. These results suggest sensory exploitation may explain differences in mate choice across populations.

In general, this body of work furthers our understanding of how sensory system evolution can be promoted or constrained by the genomic architecture- a process frequently assumed to only follow traditional mutation selection models. This work also highlights how highly variable sensory systems can be across populations within species- a phenomenon largely unconsidered when exploring the visual ecology of an organism.

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Figure 1.1. Male guppies (Poecilia reticulata) are highly variable in colour and number of spots.

Figure 1.2. Males of the subgenus Lebistes are very colourful. While Poecilia reticulata males are highly variable in colouration, there are only two male morphs of Poecilia picta and five discrete male morphs of Poecilia parae.

Chapter 2.

The impact of genomic environment on the evolution of colour vision in the family Poeciliidae, a model for visually based sexual selection

Publication and Contributions

A version of this chapter is currently being prepared for submission: Sandkam, BA, JB Joy, CT Watson, and F Breden. The impact of genomic environment on the evolution of colour vision in the family Poeciliidae, a model for visually based sexual selection.

Contributions: BAS and CTW designed primers. BAS performed sequencing and ran site selection analyses. BAS and JBJ made alignments and generated phylogenies.

BAS, JBJ, CTW and FB designed the project and wrote the manuscript.

2.1. Abstract

Sexual selection is predicted to lead to a co-evolution of sensory systems and mate preferences, but sensory system evolution can be constrained by genomic architecture. Here we examine the evolutionary interplay between sexual selection and the opsin genes (responsible for tuning colour vision) of 15 species across the family Poeciliidae, which includes such classic systems for studies of sexual selection as guppies, swordtails and mollies. Male colouration patterns vary widely within and among genera, yet only one of the known amino acid sites that tune Long Wavelength Opsins was found to be variable in this specious family that is characterized by colour-mediated sexual selection. While most opsin genes appear to evolve without genomic constraint, we identified high rates of gene conversion between two of the LWS loci (LWS-1 and

LWS-3), likely due to the genomic architecture of the LWS genes. The LWS opsins are responsible for detecting and discriminating red and orange colouration- a key sexually selected trait in members of the subgenus Lebistes. This is the only subgenus with differences in wavelength sensitivity between LWS-1 and LWS-3. Taken together these results suggest selection is acting against the homogenizing effects of gene conversion to maintain LWS diversity. Additionally, while we found mixed results for selection acting on opsin tuning, across the family there was strong selection acting on the rhodopsin gene, which acts in scotopic rather than photopic vision.

2.2. Introduction

Behaviours and decision-making processes are understood to be partially determined by the genomic repertoire available to an organism (Robinson et al. 2008; Renn et al. 2008). However, gene repertoire evolution is subject to its own set of processes and constraints (Lynch 2007). Therefore it is of great importance for studies investigating the evolution of behaviours to explore the associated changes in the genomic repertoire impacting the behaviours in question (Wilkinson et al. 2015).

Sexual selection is a suite of behaviours that has received a great deal of attention with respect to evolution in terms of both origins and changes (Andersson 1994; Panhuis et al. 2001; Andersson and Simmons 2006). Sexual selection is capable of driving large-scale evolutionary changes through mechanisms such as behavioural isolation (Ryan and Rand 1993) and the elaboration of sexually selected traits (Andersson 1994). Several evolutionary models predict sensory systems responsible for detecting traits under sexual selection and mate preferences are tightly linked, including Sensory Bias (Basolo and Endler 1995; Endler and Basolo 1998; Boughman 2002). Indeed, the genes underlying relevant sensory systems have been shown to strongly influence the strength and direction of trait evolution (reviewed in Horth 2007). It is well known that gene duplication is the driving force underlying the expansion of sensory repertoires, specifically those repertoires that are then co-opted for use in mate choice (Horth 2007). Gene duplication can occur through multiple mechanisms, resulting in differences in the genomic architecture, which can impose constraints and selection upon gene evolution (Zhang 2003).

The family Poeciliidae is a group of freshwater fishes that provides an excellent model for studies of sexual selection as it includes such classic model systems in sexual selection as; guppies (Poecilia reticulata), swordtails (Xiphophorous helleri), and sailfin mollies (Poecilia latipinna). Whereas sexual selection via female mate choice is common within this family, the dominant criteria females are selecting differ across species, for example: guppies base mating decisions on male colouration (Houde 1997; Magurran 2005), swordtails base mating decisions on the length of the male caudal fin (Basolo 1990; Robinson et al. 2011), and sailfin mollies base mating decisions on the size of the male dorsal fin (Ptacek and Travis 1997).

While nearly all of the sexually selected traits described in this diverse group are transmitted visually, the role of colouration differs strikingly across species. Colour vision (the discrimination of different wavelengths of light) is accomplished by having cone cells in the retina that are maximally sensitive to different wavelengths of light. The brain interprets the strength of signals from the different types of cone cells as colour (Conway 2009), thereby having a greater repertoire of cone cells facilitates better colour discrimination (Gegenfurtner & Sharpe 1999). The most influential factor determining the wavelength to which a cone cell is maximally sensitive (λmax) is the transmembrane protein expressed by that cell, called an opsin (Yokoyama 2002). The λmax of an opsin protein is directly determined by its amino acid sequence, hence the number of functionally different opsins possessed by an organism can be directly determined by the genomic repertoire and selection analyses on opsin genes can reveal insights to visual tuning (Yokoyama and Yokoyama 1996). Guppies and swordtails have recently been shown to have an expanded repertoire of opsin genes compared to other fish families resulting in a total of nine cone opsin genes, among the largest known opsin repertoire of any vertebrate (Ward et al. 2008; Watson et al. 2010; 2011). This expanded repertoire is especially pronounced in the long wavelength-sensitive (LWS) class of opsins, which detect wavelengths in the red, yellow, and orange end of the visible light spectrum (Yokoyama et al. 2008). This expanded LWS opsin repertoire has been proposed to be involved in the origin and prevalence of sexual selection in this group (Hoffmann et al. 2007; Ward et al. 2008; Watson et al. 2011), but has not been tested in a phylogenetic framework. A phylogenetic approach requires a detailed understanding of the evolution of colour vision in this family.

To investigate the evolution of colour vision in the family Poeciliidae we sequenced eight of the nine cone opsins as well as the rod opsin (rhodopsin) and built gene phylogenies for 15 species across the family. We proposed a targeted hypotheses regarding LWS opsin evolution and mate choice. Specifically, if differences across species in mate preference are driven by differences in the sensory system, then we would expect to see differences in the tuning of LWS opsins in the species for which red/orange plays a predominant role in mate choice. Additionally, we describe patterns of evolution in four of the five non-LWS cone opsins (SWS1, SWS2A, SWS2B, RH2-1) as well as rhodopsin (RH1). Since the lighting environment varies considerably across these species we tested for sites under selection that could describe differences in visual tuning. While most opsin genes appear to be under neutral evolution, we identified high rates of gene conversion between two of the LWS loci (LWS-1 and LWS-3) that occurs throughout the family Poeciliidae. We propose that the evolution of the LWS opsin genes may be influenced by an interplay between gene conversion due to genomic architecture and the role of red/orange colouration in sexual selection.

2.3. Materials and Methods

2.3.1. Sequencing

Using DNeasy blood and tissue kits (QIAGEN), DNA was extracted from tissue samples of single specimens of the following species: Heterandria formosa, Xiphophorus helleri, Poecilia caymanensis, P. vittata, P. nigrofasciata, P. latipinna, P. velifera, P. petenensis, P. mexicana, P. minor, P. reticulata, P. wingei, P. bifurca, P. picta, and P. parae. Primers specific to 5’ and 3’ UTR regions of each of the four LWS loci and the two SWS2 loci were designed using genomic data from Poecilia wingei (Watson et al. 2011) and Xiphophorous helleri (Watson et al. 2010). Primers specific to 5’ and 3’ UTR of RH2- 1 were taken from Sandkam et al. (2013). SWS1 and RH1 UTR primers were designed using genomic data from whole genome shotgun sequence of Xiphophorus maculatus (GenBank accessions: AGAJ01036758.1 and AGAJ01019341.1 respectively). PCR primers were designed to be specific to the UTR regions upstream and downstream of each locus due to high exon sequence similarity in the LWS opsins; in such cases it has

been shown that UTR primers are critical to ensure locus specificity of the PCR products (Watson et al. 2011) (for primer sequences see Supplementary Table 2.1). We follow Sandkam et al. (2013) and refer to LWS loci by their location in the genome relative to one another. Due to the length of LWS-2, PCR products for this locus were generated in two overlapping segments. Locus specificity was maintained for each of these segments by PCR amplifying with one UTR primer and one internal primer.

All sequencing was performed by Molecular Cloning Laboratories (MCLAB; San Francisco, CA, USA). Sequence chromatograms were viewed and analyzed using SeqMan Pro (Lasergene 8.0; DNASTAR). All sequences are available on GenBank (accession numbers pending submission_).

A firm understanding of the phylogenetic relationships of the species used in this study was obtained from ND2 mitochondrial sequences retrieved from GenBank (see Supplementary Table 2.2 for accession numbers). LWS and SWS2 sequences for P. wingei were taken from Watson et al. (2011) (GenBank Accession: HM540108 and HM540107) and X. helleri from Watson et al. (2010) (GenBank Accession: GQ999832 and GQ999833). The LWS and RH2-1 sequences of P. mexicana and P. latipinna were taken from Sandkam et al. (2013) (GenBank Accessions: JF823552 – JF823560). PCR products could not be reliably made for the RH2-2 locus in the majority of the species so this opsin was left out of all analyses.

2.3.2. Tree Building

The divergence of the opsin classes occurred before the rise of the family Poeciliidae (Rennison et al. 2012), making alignment of introns and UTRs difficult, however, opsins are highly conserved structurally, allowing alignments of coding sequence to be made across classes. To best explore the evolutionary history of the opsins in the family Poeciliidae we built a series of trees based on several sets of sequences: (1) mitochondrial ND2, (2) all opsins: exon sequence only, (3) SWS1: full sequences (UTR, introns and exons), (4) SWS2: full sequences, (5) RH1: full sequences, (6) RH2-1: full sequences, and (7) LWS: full sequences. Upon seeing high

rates of gene conversion in the LWS opsins we built one additional tree: (8) LWS: UTR- only sequence.

For each set, sequences were aligned using Mafft v6.833b (Katoh et al. 2009) and edited manually using Se-Al v2.0a11 (Rambaut 1996) to ensure that intron-exon boundaries (where applicable) were consistent across all species. Best-fit models of molecular evolution were determined using MrModelTest 3.04 (Nylander 2004). Phylogenetic trees were reconstructed under Maximum Likelihood (ML) using PAUP* 4.0b10 (Swofford 2003) and Bayesian methods as implemented in MrBayes 3.1.2 (Ronquist and Huelsenbeck 2003). Two runs utilizing four Markov chains (three heated and one cold) were run for 107 generations, with trees sampled every 1000 generations. Convergence was assessed using the standard deviation of the split frequencies between runs, and graphically using the program Tracer (Rambaut and Drummond 2007) and AWTY (Nylander et al. 2008). ML bootstrap values and Bayesian posterior probabilities were employed to assess support.

2.3.3. Gene Conversion Analyses in LWS Opsins

The LWS duplication history is known to precede the emergence of the family Poeciliidae (Rennison et al. 2012). Yet when building a phylogeny of the LWS loci, LWS- 1 and LWS-3 cluster within species and clades, indicative of high frequencies of gene conversion between these loci (see discussion for further justification) (Chen et al. 2007). To understand how gene conversion differed across the family Poeciliidae we identified gene conversion breakpoints using GARD (Kosakovsky Pond et al. 2006), a part of the HyPhy software package (Kosakovsky Pond et al. 2005), on the DataMonkey Server (Kosakovsky Pond and Frost 2005a). We ran GARD by subgenus: Lebistes (Poecilia reticulata, P. parae, P. picta, and P. bifurca), Poecilia (P. latipinna, P. velifera, P. mexicana, and P. pentenensis), and Limia (P. caymenensis, P. vittata, and P. nigrofasciata). Running GARD on subgenus rather than our full set of species allowed us to focus on how gene conversion has acted within these clades. The high incidence of gene conversion in the LWS opsins invalidates the assumptions required for traditional selection level analyses.

2.3.4. Identifying Sites Under Selection in Non-LWS Genes

GARD analyses found no evidence of recombination in any of the non-LWS gene classes, thereby meeting the assumption of no recombination required for selection analyses. To explore selection in the SWS1, SWS2A, SWS2B, RH2-1, and RH1 opsin classes; positively selected sites were identified using the random sites models (M0, M1, M2, M7, M8) in the codeml program from the PAML 4.0 software package (Yang 2007) run by the pamlX GUI (Xu and Yang 2013). The ND2 mitochondrial tree was used without branch lengths as the known species relationships for each of the opsin classes run through codeml. The highly robust Bayes’ Empirical Bayes (BEB) analysis was used to identify sites under positive selection in the M2 and M8 models. Due to unknown reasons, we were unable to get the PAML analyses to run on the RH2-1 data set.

To increase confidence in the sites found using PAML, we also identified sites under selection using the REL, FEL, and FUBAR models (Kosakovsky Pond et al. 2006; Murrell et al. 2013) in the HYPHY software package on the Datamonkey server (Kosakovsky Pond and Frost 2005a).

2.4. Results

2.4.1. Data Set and Alignment

All sequences were generated and aligned successfully. Within each locus the size of the opsin genes did not differ more than 50 base pairs (bp) across species with the exception of intron 1 in LWS-2; this intron varied between 1808 bp in P. minor to 2410 bp in P. reticulata. The differences in length of intron 1 of LWS-2 are caused by expansions of micro-satellites in some species (Watson et al. 2011). For each opsin class, amino acid alignments are presented in Figures 2.1-2.6 following the style of (Hofmann et al. 2012), such that annotations are provided denoting the sites that correspond to known tuning sites, the transmembrane region, and the retinal binding pocket of bovine rhodopsin.

2.4.2. Phylogenetic Analyses

Phylogenetic trees inferred using ML (PAUP*) and Bayesian (MrBayes) methods converged upon similar topologies for all eight datasets. Support for recovered nodes was robust for all topologies inferred under both ML and Bayesian methods with no well- supported nodes (posteriori value > 0.8) differing among analyses. The ND2 mitochondrial tree provides expected species relationships within each opsin and is presented in Figure 2.7. Due to the large size of the phylogeny built on the exons of all opsins, it is presented as Supplementary Figure 2.1. The phylogenies of SWS1, SWS2, RH1, and RH2-1 are presented in Figures 2.8, 2.9, 2.10, and 2.11 respectively. The full LWS and the LWS UTR only trees are presented in Figure 2.12. In the phylogeny built on LWS-UTR sequences, each opsin locus (LWS-1, LWS-2, LWS-3 and LWS-R) formed a clear clade and generally followed the phylogenetic relationships between species in the ND2 mitochondrial tree. In the LWS-full sequences tree, LWS-2 and LWS-R formed clades with relationships between species generally matching those identified in the ND2 and LWS-UTR phylogenies. However, LWS-1 and LWS-3 clustered together (within species and clades) more frequently than expected based on the ND2 and LWS-UTR phylogenies. The frequent clustering of LWS-1 and LWS-3 is indicative of high rates of gene conversion between these two loci throughout the family Poeciliidae.

2.4.3. Gene Conversion Analyses

In the subgenus Lebistes, GARD identified 5 significant breakpoints (p<0.05) and 1 possible breakpoint (p<0.10). In the subgenus Limia, GARD identified 2 significant breakpoints (p<0.05). In the subgenus Poecilia, GARD identified 2 significant breakpoints (p<0.05) and 2 possible breakpoints (p<0.10). The number of breakpoints identified in the different subgenera could indicate that the sections of LWS-1 and LWS- 3 loci undergoing gene conversion in Lebistes are shorter than the sections of LWS-1 and LWS-3 loci undergoing gene conversion in Limia or Poecilia.

2.4.4. Identifying Sites Under Selection in Non-LWS Genes

The different analyses (M2, M8, REL, FUBAR, and FEL) identified some of the same and some different sites under selection. Likelihood ratio tests between models

M2-M1 and M8-M7 in codeml of PAML revealed only RH1 to be under strong positive selection (Table 2.2) yet several sites identified to be under selection by M2 or M8 were also found to be under selection using either REL, FUBAR or FEL programs in the HyPhy package (Table 3). Sites identified using Bayes Empirical Bayes (BEB) analysis of M8 in PAML (P > 95%) revealed: 2 sites in SWS1, 1 site in SWS2B, and 5 sites in RH1 with an additional 9 sites at P > 0.99%. All of these sites concurred with at least one other analysis (M2, REL, FUBAR or FEL) and have been marked on the presented amino acid alignments (Figures 2.1–2.6). The REL, FUBAR and FEL analyses found no positively selected sites in either SWS1 or SWS2B.

2.5. Discussion

We sequenced and built phylogenies of rhodopsin and eight of the nine cone- opsin genes across 15 species in the family Poeciliidae. The lighting environments of the species examined here vary considerably both across and within species. Therefore we expected to see divergent visual systems but conserved species relationships. While expected species relationships were recovered for most of the opsins, we found the LWS-1 and LWS-3 loci cluster within species and clade, which would not be expected from their known duplication history. The unanticipated clustering of LWS-1 and LWS-3 is likely due to the process of gene conversion. Gene conversion is expected to homogenize gene sequence between genes, which would be expected in opsins to produce products with the same predicted tuning optimum. This has occurred for all species in this group except those in the subgenus Lebistes. Gene conversion is a process that results in one region of DNA “overwriting” another region of DNA; this makes the two regions identical and can look like independent duplications on a phylogeny (Chen et al. 2007). The maintenance of LWS-1 / LWS-3 diversity in the species in the subgenus Lebistes may be selected for because this facilitates the role of red/orange male colouration in mate choice throughout this clade. Below we outline our rationale for our conclusion of gene conversion between LWS-1 and LWS-3, discuss how the genomic architecture is likely promoting such gene conversion, and hypothesize how such patterns of conversion and life history could impact the evolution of these

genes. We go on to identify sites under selection in the non-LWS genes and hypothesize on the interplay between these changes and life history.

2.5.1. Gene Conversion, Not Independent Duplications

The genomic organization of the LWS opsin genes is shared between Xiphophorus helleri and Poecilia reticulata (Watson et al. 2010; 2011), suggesting that the duplication history of the opsin genes precedes the divergence of Poeciliidae. Rennison et al. (2012) also supported this with a wide range of species in the family. The work presented here further supports a shared duplication history across the family Poeciliidae, because primers were designed in the untranslated regions (UTR) upstream and downstream of the opsin genes to generate sequencing products. Having primers anneal in the UTR makes them specific to a location in the genome. Had there been independent duplications throughout the family Poeciliidae, we would expect the LWS loci to occur in different locations in the genome. The fact that UTR primers worked across all species suggests that all LWS loci occur at the same place and therefore share a duplication history that is older than the family Poeciliidae. Furthermore, the LWS phylogeny built on only UTR sequence recovered clear LWS-1, LWS-2, LWS-3, and LWS-R clades. Had the conserved UTR sequence been a result of independent duplications that included the UTR regions, we would expect to see LWS-1 and LWS-3 clustering within species (as observed in the phylogeny built on full LWS-1 and LWS-3 sequences).

The recovered full sequence LWS opsin gene phylogeny (Figure 2.12) revealed LWS-1 and LWS-3 cluster within species and clades more frequently than expected from the true duplication history, indicative of gene conversion.

2.5.2. Why is Gene Conversion so Prevalent Between LWS-1 and LWS-3?

Gene conversion frequently occurs following a double strand break (DSB). To repair the DNA the broken ends find a template strand that matches intact sequence adjacent to the break, and the ends are extended as complementary base-pairs to the template strand. The likelihood of using an incorrect template strand is a function of

proximity and similarity (Chen et al. 2007). LWS-1, LWS-2, and LWS-3 occur in a tandem array with less than 6 kb between LWS-1 and LWS-2, while there is less than 4 kb between LWS-2 and LWS-3 (Watson et al. 2010; 2011). The close proximity of LWS- 1, LWS-2, and LWS-3 greatly increases the likelihood of gene conversion occurring between these loci, yet gene conversion only seems to occur between LWS-1 and LWS- 3. The sequence length of LWS-2 is likely what decreases the chances of gene conversion involving this locus. While the introns and exons of LWS-1 and LWS-3 are nearly identical in length, LWS-2 has a greatly expanded intron 1 in all species throughout the family Poeciliidae. The difference in size of intron 1 between LWS-2 and LWS-1 / LWS-3 makes it less likely that LWS-1 or LWS-3 will use LWS-2 as a template in the event of a DSB due to the dramatic size differences that make alignment difficult. However, the close proximity of LWS-1 and LWS-3 in addition to the fact that all of their introns and exons match in length make it likely they will experience gene conversion with one another in the event of a DSB.

The orientation of LWS-1 and LWS-3 make it even more likely these two genes will experience gene conversion because they are inverted to one another. When a DSB occurs and the DNA doubles back on itself LWS-1 and LWS-3 are in the same orientation (Figure 2.13). The close proximity, identical sequence length and inverted orientation of LWS-1 relative to LWS-3 make these genes prime candidates for gene conversion and explain the high prevalence of such a process across the family Poeciliidae.

2.5.3. Implications of Gene Conversion to Colour Vision

The λmax of the LWS opsins in vertebrates is predominantly determined by the amino acids at five key sites (Yokoyama and Radlwimmer 1998; Yokoyama et al. 2008). We found low allelic diversity across the family Poeciliidae at the key sites tuning the LWS loci (Table 2.1). Across the 15 species sequenced: LWS-1 has two alleles, LWS-2 has three alleles, LWS-3 has only one allele, and LWS-R has two alleles. The five key tuning sites correspond to the 180, 197, 277, 285 and 308 amino acid in the human opsin sequence (Yokoyama and Radlwimmer 1998) and were SHYTA for both LWS-1 and LWS-3 for all species except P. wingei, P. bifurca, and P. picta (which were all

AHYTA at LWS-1 and SHYTA at LWS-3). These three species, together with P. reticulata and P. parae, make up the subgenus Lebistes- a group well known to possess high levels of red/orange male colouration that are involved in female mate decisions (Liley 1965; Houde 1997; Lindholm et al. 2004). Interestingly, while the P. reticulata and P. parae individuals sequenced for this study had an S at the 180 site, both of these species have recently been shown to possess an allele with an A at the 180 site and vary in the frequency of this allele across populations (P. reticulata- (Tezuka et al. 2014; Sandkam et al. 2015); P. parae- Sandkam et al. in review). In guppies, the frequency of the A and the S has been observed to vary in a predictable manner between upstream and downstream populations (Sandkam et al. 2015). The most highly expressed LWS in these three species is LWS-1 (Sandkam et al. 2015 and Sandkam et al. in review), therefore the change from an S to an A at the 180 amino acid likely has important tuning implications in these species.

The presence of an A at the 180 site in LWS-1 relative to the fixed S at LWS-3 has previously been postulated to play a role in mate choice in the subgenus to which these species belong; Lebistes (P. bifurca, P. parae, P. picta, P. reticulata, and P. wingei) (Ward et al. 2008). Our data may offer some support to this hypothesis. When looking for breakpoints of conversion events between LWS-1 and LWS-3 within clades, GARD analyses reveal more breakpoints in the subgenus Lebistes than either the subgenus Poecilia (P. latipinna, P. mexicana, P. petenensis, and P. velifera) or the subgenus Limia (P. caymanensis, P. nigrofasciata, and P. vittata). The increased number of breakpoints in Lebistes shows that effective gene conversion is occurring in shorter segments compared to conversion events in Poecilia or Limia species. By occurring in smaller segments, gene conversion does not completely homogenize LWS- 1 and LWS-3 in Lebistes species. The smaller segments of conversion in Lebistes may be the result of selection acting against the homogenizing effects of large gene conversion events in these species where red/orange discrimination plays a large role in mate choice. Normally differential selection in LWS-1 and LWS-3 of Lebistes versus non-Lebistes would be tested using methods such as dN/dS. However, the presence of gene conversion makes this impossible because it violates the assumptions of molecular evolution models underlying methods such as dN/dS (Kosakovsky Pond and Frost 2005b).

The presence of multiple alleles at LWS-1 in P. parae, P. picta and P. reticulata (Tezuka et al. 2014; Sandkam et al. 2015 and Sandkam et al. in review) raises the possibility that other species may also possess multiple alleles at opsin loci. The sequences presented here provide an excellent tool for future studies to investigate variation in colour vision across populations or individuals by examining the sequence and/or expression of the opsin genes.

2.5.4. Selection in Non-LWS Genes

Using dN/dS tests we identified sites under selection in several of the non-LWS genes. We found RH1 has many sites under positive selection, all of which occur either in the transmembrane domain or the retinal-binding pocket. Changes in both of these regions can be responsible for changing the tuning of the rod cells (Hargrave et al. 1983). RH1 has recently been shown to experience positive selection in cichlids that is driven by both ecology and phylogeny (Nagai et al. 2010; Schott et al. 2014; Torres- Dowdall et al. 2015). The positive selection we identified in RH1 is likely also indicative of differences in life history and presents an exciting system in which to test how differences in ecology can drive differences in visual tuning. It is noteworthy that in two colourful families of freshwater fishes (Cichlidae and now Poeciliidae) the RH1 gene appears to be so strongly under selection despite its use in non-colour based vision.

Surprisingly, most of the sites identified to be under selection by PAML and HyPhy were not located in the retinal binding pocket, which is thought to be the important sites influencing the tuning of the opsin λmax. Therefore care should be taken when interpreting these selection level results until protein expression studies can be performed to show whether or not changes to these sites are indeed altering the phenotype.

2.6. Conclusion

We identified the phylogenetic relationships for nine of the ten colour opsin genes in 15 species throughout the family Poeciliidae. The LWS-1 and LWS-3 loci have undergone gene conversion at several points across this family, acting to homogenize

LWS sequence at these loci within species. Members of the subgenus Lebistes experience gene conversion in smaller segments leading to greater LWS allelic diversity compared to non-Lebistes species. The LWS opsins are responsible for detecting the reds, oranges, and yellows upon which Lebistes base mating decisions. It is possible that the LWS-1 / LWS-3 diversity observed in Lebistes species is a result of selection pressure on the sensory system for its role in sexual selection. We also found RH1 is under strong positive selection in the family Poeciliidae.

Acknowledgements

We wish to thank members of the Breden lab: Laura Chow, Ian McNeil, and Luke Rawle for assistance in the lab.

Data Accessibility

All sequences will be available on GenBank. Accession numbers pending submission.

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Tables and Figures

LWS-1 LWS-2 LWS-3 LWS-R # L Amino Acid 180 197 277 285 308 λmax 180 197 277 285 308 λmax 180 197 277 285 308 λmax 180 197 277 285 308 λmax W S X. helleri S H Y T A 560 P H F A A 545 S H Y T A 560 S H Y T A 560 2 H. formosa S H Y T A 560 P H F A A 545 S H Y T A 560 S H Y T A 560 2 P. minor S H Y T A 560 S H F A A 534 S H Y T A 560 S H Y T A 560 2 P. S H Y T A 560 P H F A A 545 S H Y T A 560 S H F A A 534 3 caymanensis P. S H Y T A 560 P H F A A 545 S H Y T A 560 S H F A A 534 3 nigrofasciatus P. vittata S H Y T A 560 P H F A A 545 S H Y T A 560 S H F A A 534 3 P. latipinna S H Y T A 560 P H F A A 545 S H Y T A 560 S H F A A 534 3 P. mexicana S H Y T A 560 P H F A A 545 S H Y T A 560 S H F A A 534 3 P. velifera S H Y T A 560 P H F A A 545 S H Y T A 560 S H F A A 534 3 P. petenensis S H Y T A 560 P H F A A 545 S H Y T A 560 S H F A A 534 3 P. bifurca A H Y T A 553 P H F A A 545 S H Y T A 560 S H Y T A 560 3 P. picta A H Y T A 553 P H F A A 545 S H Y T A 560 S H Y T A 560 3 P. wingei A H Y T A 553 P H F A A 545 S H Y T A 560 S H Y T A 560 3 P. parae S H Y T A 560 P H F A A 545 S H Y T A 560 S H Y T A 560 2 P. reticulata S H Y T A 560 P H F A A 545 S H Y T A 560 S H Y T A 560 2

Table 2.2. Selection tests on non-LWS opsins using models M0, M1, M2, M7 and M8 of the codeml program in PAML. Likelihood ratio tests (LRTs) were performed between models with selection and models with neural evolution to identify genes under positive selection.

Gene Model np lnL K w0/p w1/q w2/wp Null LRT P M0 30 -2212.50 2.09 0.08 n/a

M1 31 -2185.55 2.03 0.00 1.00 n/a

SWS1 M2 33 -2183.62 2.10 0.02 1.00 2.39 M1 3.86 > 0.05 M7 31 -2186.57 2.07 0.01 0.05 n/a

M8 33 -2184.79 2.10 1.98 99.00 2.38 M7 3.55 > 0.05 M0 30 -2617.56 4.87 0.19 n/a

M1 31 -2599.21 4.77 0.05 1.00 n/a

SWS2A M2 33 -2597.28 4.88 0.10 1.00 2.27 M1 3.86 > 0.05 M7 31 -2599.92 4.80 0.06 0.27 n/a

M8 33 -2597.26 4.88 1.18 9.56 2.45 M7 5.32 > 0.05 M0 30 -2365.32 2.74 0.10 n/a

M1 31 -2348.02 2.73 0.00 1.00 n/a

SWS2B M2 33 -2347.33 2.77 0.01 1.00 5.53 M1 1.36 > 0.05 M7 31 -2348.02 2.73 0.01 0.07 n/a

M8 33 -2347.24 2.76 0.03 0.30 5.20 M7 1.54 > 0.05 M0 30 -2385.05 3.30 0.34 n/a

M1 31 -2321.15 2.77 0.00 1.00 n/a

RH1 M2 33 -2291.25 3.32 0.01 1.00 5.41 M1 59.80 <0.0001 M7 31 -2321.82 2.72 0.01 0.05 n/a

M8 33 -2291.25 3.31 1.50 99.00 5.46 M7 61.14 <0.0001

Table 2.3. Sites identified as under positive selection using the M2 and M8 models in codeml of PAML, and the REL, FUBAR, and FEL programs of HYPHY. Grey highlight indicates the site is in the transmembrane domain. / indicates site was not identified to be under selection using that method. NA indicates run was not available. Numbers given for M2, M8, REL, and FUBAR are posterior probabilities while numbers for FEL are P values.

Gene Site M2 (Pr) M8 (Pr) Rel (Pr) FUBAR (Pr) FEL (P) 62 / / 0.712 / / 129 / 0.640 / / / 144 0.780 0.912 0.718 / / SWS1 155 0.757 0.903 0.679 / / 163 0.541 0.682 0.761 / / 193 0.910 0.976 0.707 / / 274 0.908 0.975 / / / 5 0.721 0.908 0.989 0.939 0.036 7 / 0.580 0.734 / / 31 / 0.682 0.825 / / 66 / 0.589 / / / 100 / 0.598 / / / 160 0.747 0.936 0.981 18.427 / SWS2A 161 / 0.617 0.713 / / 164 0.766 0.944 0.905 / / 234 0.750 0.938 0.990 24.249 / 288 / 0.595 0.738 / / 324 0.637 0.830 0.928 / / 325 / 0.589 0.760 / / 11 0.896 0.972 / / / 54 0.549 0.666 / / / 64 0.772 0.898 / / / SWS2B 126 0.585 0.698 / / / 170 0.653 0.777 / / / 171 0.539 0.656 / / / 274 / 0.576 / / / 32 NA NA 0.793 / / 166 NA NA 0.998 / 0.027 RH2-1 187 NA NA 0.975 / / 217 NA NA 0.961 / / 274 NA NA 0.827 / /

327 NA NA 0.998 0.990 0.044 343 NA NA 0.966 / / 11 / / 0.963 / / 19 0.627 0.759 0.986 / / 38 0.689 0.807 0.847 / / 63 / / 0.952 / / 95 / / 0.952 / / 112 / / 0.980 / / 133 0.990 0.998 0.987 0.934 0.072 149 0.657 0.782 0.974 / / 166 0.993 0.999 0.975 0.919 / 173 0.719 0.829 0.964 / / 189 0.937 0.980 / / / RH1 205 0.934 0.979 / / / 213 0.990 0.998 0.968 0.908 / 217 0.948 0.984 / / / 218 0.936 0.980 0.987 / / 255 0.991 0.998 0.883 / / 263 0.991 0.998 0.877 / / 266 0.998 1.000 / / / 290 0.932 0.979 0.971 / / 297 0.999 1.000 0.832 / / 298 / / 0.962 / / 304 0.984 0.997 / / / 309 0.977 0.995 0.943 / /

according to to according Key: Known SWS2 tuning site region Transmembrane Retinal binding pocket site rhodopsin in bovine selection under positive Site P>95% at (BEB) Empirical Bayes Bayes of model 8 in PAML analysis * C C C C C N C C C C N C N C N C N C C N N C N N N N N N N N S S S S S A S S S S A S A S A S A S S A A A A S A A A A A A C C C C C C Y C C C C Y C Y C Y C C Y C Y Y Y Y Y Y Y Y Y Y G G G VFVA G VFVA G G VFVA G VFVA VFVA VFVA G VFVA G VFMA VFVA VFVA G VFVA G VFVA VFVA VFVA G VFVA G G G L L L L L LW L L L L LW L LW L LW L LW L L LW LW LW LW L LW LW LW LW LW LW G G G SQ G SQ G G G SQ G SQ SQ SQ G SQ G G SQ SQ SQ G G SQ G G SQ SQ SQ G G SQ G G G G G G G G G G G G G E E E V E V E E V E T V V V E V E V V V E T V E T V V V E T V E E T T T E T T T T T T T T P P P S P S P P S P S S S P S P S S S P S P S S S P S P P P I I I F I F I AL I F I F F F I F I AL F F F I AL F I AL F F F AL F I AL AL AL AL I AL AL AL AL AL AL Y Y Y Y T Y T Y Y Y T Y T T T Y T Y Y T T T Y Y T Y CI Y T T T CI Y T Y Y Y Y Y Y Y Y Y Y Y 81 261 171 R R R R R R P R R R R P R P R R P R P R P P P P P P P P P P S S S S S S G S S S S G S G S S G S G S G G G G G G G G G G W W W W W W Y W W W W Y W Y W W Y W Y W Y Y Y Y Y Y Y Y Y Y G G G G FIFV G FIFV G C G FIFV G FIFV FIFV FIFV G FIFV G C FIFV FIFV FIFV G C FIFV G G C FIFV FIFV FIFV G C FIFV G C C C C C C C C C C G G T G G G G G T G G G T G T G G G S G T T T T T T T T T T FF FF FF FF FF FF FF FF FF FF FF FF FF FF FF P FA FA FV P FA FA FA FA FA FV FA FA FA FV FA FV FA FA FA FV FA FV FV FV FV FV FV FV FV FV FV PP PP PP S PP PP S S PP S PP S PP S S S PP S S PP S S PP S S PP S S PP S S S S S S S S S S S S S S S S S SS I S S I G S SS I S I S I I I S G I S I I S G I S G I S I I G I G G G G G G G G G G N N V N N N N N V N N N V N V N N N V N V V V V V V V V V V 71 251 161 CA CA CA CA CA CA CA CA CA CA CA CA CA CA CA G G G G G G G G G G G G G G G V V V ILV V V ILV V ILV V V ILV ILV ILV V ILV V ILV ILV ILV V ILV V V ILV ILV ILV V ILV V G G Y G G Y G G Y G Y G Y Y Y G Y G Y Y Y G Y G Y Y G Y G G N N MIIVM N N N N N MIIVM N N N MIIVM N MIIVM N N N MIIVM N MIIVM MIIVM MIIVM MIIVM MIIVM MIIVM MIIVM MIIVM MIIVM MIIVM L L R L L L L L R L L L R L R L L L S S S S S R L S S S S S S S S S S R R R R R R R R R R WFM WCM WFM P WFM WFM P WCM S P WFM WFM P P P WFM P WFM S P P P WCM S P WFM WCM S P P P WCM S P WFM A A A A A S S S S A A A A A A A A A A S S S S S S T T T A T T A T V A T T A A A T A T V A A A T V A T T V A A A S V A T V V V V V V V V V V R Q E R R R R R E R R R E R E R R R ST ST ST ST ST E R ST ST ST ST ST ST ST ST ST ST E E E E E E E E E E VF VF VF VF L VF VF L K VF VF L VF L VF L L L VF K L VF L L VF K L VF K L VF L L V V V V V K L V V V V V V V V V V K K K K K K K K K K 61 241 151 331 E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E KK KK A KK KK KK KK KK A KK KK KK A KK A KK KK KK T T T T T A KK T T T T T T T T T T A A A A A A A A A A Y Y K Y Y Y Y Y AAV K Y Y Y AAV K Y AAV K Y Y Y K K K K K K Y K K K K K K K K K K K K K K K K K K K K K K K K K K K G K K K G K G K K K K AAAAV AAAAV AAAAV AAAAV A AAAAV AAAAV A AAAAV AAAAV A AAAAV A AAAAV A A A A A AAAAV A A A A A A AAAAV A A SS SS SS SS SS A SS SS SS SS SS SS SS SS SS SS H H H T H H T H STQ T H H T T T H T H STQ T T T H STQ T H H STQ T T T V V V V V H STQ T H V V V V V V V V V V STQ STQ STQ STQ STQ STQ STQ STQ STQ STQ A A A A E E E E E A E E E E E E E E E E A A A A A A A A A A ST ST SS ST SS ST S ST ST ST SS S SS S ST SS S S S S S S S SS S ST S S S S S S S S S S S S S S S S S S S G G G G G G E G G G G E G E G G E A A A A A A G E G A A A A A A A A A E E E E E E E E E E F F F VLLA F F VLLA F A VLLA F F VLLA VLLA VLLA F VLLA F A VLLA VLLA VLLA F A VLLA F F A VLLA VLLA VLLA F A VLLA F A A A A A A A A A A 51 231 141 321 K K K K K K K K K K K K EE EE EE EE EE K EE K EE EE EE EE EE EE EE EE EE K LL LL QQ LL LL LL LL LL QQ LL LL LL QQ LL M M M M M M QQ LL LL LL M M M M M M M M M QQ LL QQ QQ QQ QQ QQ QQ QQ QQ QQ QQ AF AF AF N AF AF N AF N AF AF N N N AF N AF N N N AF N AF AF N N N AF N AF G G G L G G L G L G G L L L G L G L L L G L G KK KK KK KK G KK KK L L L G KK KK KK KK KK KK KK KK KK L G F F F F P F F P F P F F P P P F P F P P P F P F G G G G F G G P P P F G G G G G G G G G P P P P P T P P T P AVAA T P P T T T P AVAA T P AVAA T T T P AVAA T P P AVAA T T T P AVAA AVAA T AVAA AVAA AVAA AVAA AVAA AVAA AVAA AVAA K K K K G K K G K R G K K G G G K R G K R G G G K R G K K R G G G K R R G R R R R R R R R MVF MVF MVF MVF MVF MVF MVF MVF MVF MVF MVF MVF MVF MVF MVF AL AL AL AL AL E E E E E E AL AL AL AL E E E E E E E E E AL AL AL AL AL AL VIC VIC VIC VIC FFA VIC VIC FFV VIC G FFA VIC VIC FFA FFA FFA VIC G FFA VIC G FFA FFA FFA VIC G FFA VIC VIC G FFA FFA FFA M M M M M M VIC G G FFA G G M M M M M M M M M G G G G G G 41 221 131 311 L L L L L L L L L Y Y Y Y FV Y Y FV Y LL FV FL FL FV FV FV FL LL FV Y LL FV FV FV FL LL FV Y FL LL FV FV FV FL LL LL FV LL LL LL LL LL LL LL LL R R R R G R R G R G R R G G G R G R G G G R G R R G G G ACI ACI ACI ACI ACI ACI R G ACI ACI ACI ACI ACI ACI ACI ACI ACI E E E E E E E SQ E E E SQ E SQ E SQ E E SQ N N N N N N E SQ SQ SQ SQ N N N N N N N N N SQ SQ SQ SQ SQ SQ F F F F F F F Y F F F Y Y F Y F Y F F Y F F F F F F F Y Y Y F F F F F F F F F Y Y Y Y Y Y S S S S S S S S S S S S S S S S S S S S Q Q Q Q Q Q S S S S Q Q Q Q Q Q Q Q Q S S S S S S ALFM ALFM ALFM ALFM ALFM ALFM ALFM ALFM ALFM ALFM ALFM ALFM ALFM ALFM K K K K K K ALFM K K K K K K K K K Q Q Q Q Q Q Q Q Q Q Q Q Q Q N N N N N N Q N N N N N N N N N L L L L L L L L L L L L L L M M M M M M L M M M M M M M M M LAVL LAVL LAVL LAVL LAVL H LAVL LAVL IIIF H LAVL LAVL H LAVL IIIF IIIF H LAVL H H IIIF H LAVL IIIF H LAVL H H LAVL IIIF H LAVL IIIF IIIF H H H IIIF IIIF IIIF IIIF IIIF IIIF IIIF H 31 211 121 301 S S S S S S S S S S S S S S S S S S S S AF AF AF AF AF AF S S S F S AF AF AF AF AF AF AF AF AF S S S S S S W W W W W W W L W W W L L W L W L W W L Y Y Y Y Y Y W L L T L Y Y Y Y Y Y Y Y Y L L L L L L P P P P P P P P P P P P P P P TS TS TS TS TS AWAF TS TS AWAF TS TS AWAF TS AWAF TS AWAF AWAF AWAF TS AWAF TS AWAF AWAF TS AWAF LI LI LI LI LI LI TS AWAF AW AWAF LI LI LI LI LI LI LI LI LI AWAF P P P P P P P P P P P P P P P P P P P P P P P P P P P P P P LV LV LV LV LV LV LV LV LV LV LV LV LV LV N N N N N LV N N N N N N N N N N G G G G G LA G G CFCM LA G G LA LA G CFCM CFCM LA G LA LA CFCM LA G CFCM LA G LA LA G CFCM LA Y Y Y Y Y Y G CFCM CFCM LA LA LA CFCM Y Y Y Y Y Y Y Y Y CFCM CFCM CFCM CFCM CFCM CFCM T T T T T T T T T T T T T T HY HY HY HY HY HY HY HY HY HY HY TT HY CV CV CV CV CV CV HY HY HY CV CV CV CV CV CV CV CV CV AVA AVA AVA AVA AVA AVA AVA LI AVA AVA AVA LI LI AVA LI AVA LI AVA AVA L AVA LI LI LI LI LI LI LI LI LI 21 201 111 291 G G G G G SQ G G SQ G SQ G SQ SQ G SQ G SQ SQ SQ G SQ G SQ SQ G SQ SS SS SS SS SS SS G SQ SQ SS SS SS SS SS SS SS SS SS G FL G G G G FL FL G G G FL G FL G G G FL G K K K K K K FL FL G G FL K K K K K K K K K FL FL FL FL FL FL E Y E E E E Y Y E E E Y E Y E E E Y E S S S S S S Y Y E E Y S S S S S S S S S Y Y Y Y Y Y AAM AAM AAM AAM AAM F AAM AAM M F AAM F AAM F F AAM M M F AAM F F M F AAM M F AAM F F AAM M F AAM M M F F M M M M M M M E E E E E P E E Y P E P E P P E Y Y P E P P Y P E Y P E P P E Y P E Y Y P P Y Y Y Y Y Y Y D D D D D D D D D D D D D AFF AFF AFF AFF AFF AFF D D AFF AFF AFF AFF AFF AFF AFF AFF AFF V TS V V V V TS V V V V V V V V P P P P P P TS TS V V TS P P P P P P P P P TS TS TS TS TS TS K C K K K K C K K K TTS K TTS K K K TTS K I I I I I I C TTS K K C I I I I I I I I I C C C C C C C * LCAL LCAL LCAL LCAL S LCAL G LCAL S LCAL S S LCAL S LCAL G S S S LCAL G S LCAL G S S S LCAL G S LCAL T T T T LCAL T T G G S S G LCAL T T T T T T T T T G G G G G G G T T T T I T Y T I T I I T I T Y I I I T Y I T Y I I I T Y I T T Y Y I I Y T Y Y Y Y Y Y Y 11 191 101 281 Y Y Y Y N Y Y N Y N N Y N Y N N N Y N Y N N N Y N Y LV LV LV LV Y LV LV N N Y LV LV LV LV LV LV LV LV LV G G G G E G EE G E G E E G E G EE E E E G EE E G EE E E E G EE E G R R R R G R R EE EE E E EE G R R R R R R R R R EE EE EE EE EE EE EE Y N Y Y Y Y N Y Y Y N Y N Y Y Y N Y Y Y Y Y Y Y N N Y Y N Y Y Y Y Y Y Y Y Y N N N N N N N FL FL FL FL L FL H FL L FL L L FL L FL H L L L FL H L FL H L L L FL H L FL D D D D FL D D H H L L FL H D D D D D D D D D H H H H H H H H T H H H H T H H H T H T H H H T H K K K K K K T T H H T K K K K K K K K K T T T T T T T YY YY YY YY F YY Y YY F YY F F YY F YY Y F F F YY Y F YY Y F F F YY Y F YY N N N YY N N N Y Y F F YY Y N N N N N N N N N Y Y Y Y Y Y Y G G G H G H G W G H G H H G H G W H H H G W H G W H H H G W H G A A A G A A V W W H G W V V A A A A A V V W W W W W W W * R R R K R K R D R K R K K R K R D K K K R D K R D K K K R D K R R D D K R D D D D D D D D L L L G L G L P P L G L G G L G L P G G G L P G L P G G G L P G L EE EE EE L EE EE EE P P G L P EE EE EE EE EE EE EE EE EE P P P P P P S S S M S M S G G S M S M M S M S G M M M S G M S G M M M S G M S S S S S S S S G G 1 M S G S S S S S S S S S G G G G G G 91 181 271 SWS1 P.vittata|SWS1 P.caymanensis|SWS1 P.minor|SWS1 P.petenensis|SWS1 P.latipinna|SWS1 P.mexicana|SWS1 H.formosa|SWS1 X.helleri|SWS1 H.formosa|SWS1 P.velifera|SWS1 P.nigrofasciatis|SWS1 X.helleri|SWS1 P.picta|SWS1 P.vittata|SWS1 P.wingei|SWS1 P.parae|SWS1 P.petenensis|SWS1 P.reticulata|SWS1 P.bifurca|SWS1 P.caymanensis|SWS1 P.wingei|SWS1 P.reticulata|SWS1 P.picta|SWS1 P.minor|SWS1 P.mexicana|SWS1 P.parae|SWS1 P.latipinna|SWS1 H.formosa|SWS1 P.reticulata|SWS1 P.picta|SWS1 P.bifurca|SWS1 P.velifera|SWS1 P.nigrofasciatis|SWS1 P.mexicana|SWS1 P.nigrofasciatis|SWS1 P.vittata|SWS1 P.caymanensis|SWS1 H.formosa|SWS1 P.parae|SWS1 X.helleri|SWS1 P.latipinna|SWS1 P.minor|SWS1 X.helleri|SWS1 P.wingei|SWS1 P.bifurca|SWS1 P.reticulata|SWS1 P.picta|SWS1 P.parae|SWS1 P.bifurca|SWS1 P.minor|SWS1 P.latipinna|SWS1 P.velifera|SWS1 P.petenensis|SWS1 P.wingei P.caymanensis|SWS1 P.vittata|SWS1 P.nigrofasciatis|SWS1 P.mexicana|SWS1 P.petenensis|SWS1 P.velifera|SWS1

Figure 2.1. Amino acid alignment of SWS1.

Key: Known SWS2 tuning site region Transmembrane Retinal binding pocket site rhodopsin in bovine with Key tuning site variable AA V L L G L L G G L L L L L L G G L L G L G G L G L G G G G G G N N N N N N N N N N N N N N N LL LL LL LL LV LL LL LL LL LL LL LL LL LL LL FLVC FLVC FLVC FLVC FLVC FLVC FLVC FLVC FLVC FLVC FLVC FLVC FLVC FLVC FLVC G G G G G G G G G G G G G G PP PP PP PP PP PP PP PP PP PP PP PP G PP PP PP LAVA LAVA V LAVA LAVA V V LAVA LAVA LALA LAVA LAVA LALA V V LAVA LAVA V LAVA V V LAVA V LAVA V V V V V V N N S N N S S N N N N N N S S N N S N S S N S N S S S S S S A A A A A A A A A A A A A A A T T T T T T T T I T T T T T T A A A A A A VVMVL VVMVL A A VVMVL VVMVL VVMVL VVMVL A A VVMVL A VVMVL VVMVL VVMVL A VVMVL A A A VVMVL VVMVL IVMVL ILV L ILV ILV ILV L L ILV ILV ILV ILV L L ILV ILV ILV L ILV L L ILV L ILV ILV L L L L L VVMVL L 81 351 171 261 P P P P P P P P P P P P P P P Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y G G G G G G MV MV G G MV MV MV MV G G MV G MV MV MV G MV G G G MV MV MV N N N N N N N N N N N N N N N MV V V V V V V R R V V R R R R V V R V R R R V V R V V R R R L L L L L L L L L L L L L L L R K K K K K K T T K K T T T T K K T K T T T K K T K K T T T H WIFA H H WIFA WIFA H H H H WIFA WIFA H H H WIFA H WIFA WIFA H WIFA H H WIFA WIFA H WIFA WIFA WIFA T WIFA S S S S S S V V S S V V V V S S V S V V V S V S S S V V V S S T T S S S S T T S S S T S T T S T S S T T S T S T T V T T V V V V V V E E V V E E E E V V E I E E E V V E I V E E E R R R H R R R R R R R R R R R E E E E E E E K K E E K K K K E E K E K K K E K E E E K K K L L L L L L L L L L L L L L L K T T T T T T E E T T E E E E T T E T E E E T T E T T E E E E V V V V V V A A V V A A A A V V A V A A A V V A V V A A A KK KK KK KK KK KK KK KK KK KK CCAI KK CCMF KK KK KK KK A S S S S S S K K S S K K K K S S K S K K K S S K S S K K K Y Y ACCAI ACCAI Y Y Y Y ACCAI ACCAI Y Y Y ACCVF Y S ACCAI Y S Y Y ACCVI ACCAI Y ACCAI Y ACCVI ACCAI K ACCVI ACCVI 71 341 161 251 K K K R R S T R R R R T T R R R M R M T R M R R T M Q S R T M T T M M A A M M M V A A M M M A M A A M A M M A A M A M A A A A STQ STQ STQ STQ STQ ST STQ ST STQ ST STQ STQ STQ STQ T T H H T T T T H H T T T H T H H T H T T H H T H T H H STQ H H STTQ STTQ STTQ STTQ STTQ STTQ A A STTQ STTQ A A A A STTQ STTQ A STTQ A A A STTQ STTQ A STTQ STTQ A A A E E E E E E E E E E E E E A E E V V V V V V S S V V S S S S F V S V S S S V V S V V S S S P P P P P P P P P P P P P S P P E E E E E E E E E E E E E E IVC IVC K K IVC IAC IVC IAC K K IVC IVC IVC K IMC K K IVC K IVC IVC K K IVC K IVC K K E K K A A A A A V A A A A A A A A T T T T T T T T T T T T T T T A EEE EEE EEE EEE EEE EEE Q Q Q EEE EEE Q Q Q Q EEE EEE Q EED Q Q Q EEE EEE Q EED EEE Q Q L L L L L L L L L L L L L L L Q G G G G G G A A A G G A A A A G A G G A A A G A G G G A A VAF VAF VAF VAF VAF VAF VAF VAF VAF VAF I VAF VAF VAF A VAF VAF D D D D D D K K K D D K K K K D D K D K K K D K D D D K K NT NT N N NT NT NT NT N N NT NT NT N NT N N NT N NT NT N N N N NT N N K N N 61 331 151 241 G G G G G G G G G G G G G G G I I G G I I I I G G I I I G I G G I G I I G G I G I G G G G M M M M M M M M M M M M M M M L L L L L L L L L L L L L L L G G G G G G MVA G G MAA MVA MAA MVA G G MAA G MVA MAA MVA G G MAA G G MVA VVA MVA MVA P P TS TS TS TS TS P P SS TS TS P TS P P TS P TS TS P P TS P TS TS P P MVA P P K K K K K K K K K K K K K K K K G G G G G K K G G G K G K K G K G G K K G K G G K K K K K ML ML ML ML ML ML L ML ML L L L L ML ML L ML L L L ML ML L ML ML L L L L L N N N N N N T N N T T T T S N T N T T T S N T N T T T T T SN CML CML CML CMI CML CML LLV CML CML LLV LLV LLI LLV CML CML LLV CML LLI LLV LLI CML CML LLI CML CM LLI LLV LLI LLV WLVIC WLVIC WLVIC WLVIC WLVIC WLVIC WLVIC WLVIC WLVIC WLVIC WLVIC WLVIC WLVIC LLI WLVIC WLVIC T T T T T T T T T T T T T T T R R FFLFVV FFLFVV FFLFVV FFLFVV FFLFVV R R FFLFVV FFLFVV FFLFVV R FFLFVV R R FFLFVV R FFLFVV FFLFVV R R FFLFVV R FFLFVV FFLFVV R R R R 51 321 141 231 R R R R R R SQ R R SQ SQ SQ SQ R R SQ R SQ SQ SQ R R SQ R R SQ SQ SQ SQ E E T T T T T E E T T T E T E E T E T T E E T E T T E E SQ E E F F F F F F Y F F Y Y Y Y F F Y F Y Y Y F F Y F F Y Y Y Y F F F F F F F F F F F F F F F Y Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q G G G G G G G G G G G G G G G K K K K K K K K K K K K K K K N N N N N N N N N N N N N N N IIFC IIFC IIFC IIFC IIFC IIFC IIFC IIFC IIFC IIFC IIFC IIFC IIFC IIFC AMA AMA AMA AMA AMA AMA AMA AMA AMA AMA AMA AMA AMA AMA AMA IIFC LAVVAF LAVVAF Y Y Y Y Y LAVVAF LAVVAF Y Y Y LAVVAF Y LAVVAF LAVVAF Y LAVVAF Y Y LAVVAF LAVVAF Y LAVVAF Y Y LAVVAF LAVVAF LAVVAF LAVVAF VFL VVL VFL VVL VFL VFL TT TT TT VFL VFL TT TT TT TT VFL VFL TT VVL TT TT TT VFL VFL TT VVL IVL TT TT S S F F F F F S S F F F S F S S F S F F S S F S F F S S TT S S Y Y Y Y Y Y F F F Y Y F F F F Y Y F Y F F F Y Y F Y Y F F T T T M T M T T T T T T T T T F P P P P P P P P P P P P P P LW LW G G LW LW G G G G LW G G LW LW G LW G G LW LW G LW G G LW LW G LW P LW 41 311 131 221 VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI S S L S S S S S S S S S S S S S P P P P P P P P P P P P P P P N NS NS NS NS NS NS NS NS NS NS NS NS NS NS N N N N N N N N N N N N N N N MV MV G G MV MV G G G G MV G G MV MV G MV G G MV MV G MV G G MV MV G MV MV Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y L L L L L L L L L L L L L L L V V V V V V V V V V V V V V GG GG H H GG GG H H H H GG H H GG GG H GG H H GG GG H GG H H GG GG H GG GG AV L L D D L L D D D D L D D L L D L D D L L D L D D L L D L L ST ST ST ST ST ST ST ST ST S ST ST ST ST ST T T Q Q T T Q Q Q Q T Q Q T T Q T Q Q T T Q T Q Q T T Q T T A A A A A A A A A A A A A A A P P P P P P P P P P P P P P P K K K K K K K K K K K K K K K V V V V V V V V V V V V V V V S S S S S S S MFLFCFCFAA S S MFLFCFCFAA MFLFCFCFAA MFLFCFCFAA MFLFCFCFAA S S MFLFCFCFAA S MFLFCFCFAA MFLFCFCFAA MFLFCFCFAA S S MFLFCFCFAA S MFLFCFCFAA MFLFCFCFAA MFLFCFCFAV MFLFCFCFAA FVA FVA S FVA FVA S FVA FVA FVA FVA FVA FVA FVA FVA FVA FVA MFLFCFCFAV FVA 31 301 121 211 V V V V V V V V V V V V V V G FL G FL FL F FL G G F FL FF G FL G G FL G FL FL G G FL G FL FL G G G V G CL CL CL CL CL CL CL Y Y Y CL CL Y Y Y Y CL CL Y CL Y Y Y CL CL Y CL Y E P E P P P P E E P P P E P E E P E P P E E P E P P E E Y E Y E S S S S S S S S S S S S S S S S S S S S S S S S S S S S I I S S S S S I I S S S I S I I S I S S I I S I S S I I S I S I P P P P P P P E E E P P E E E E P P E P E E E P P E P E K L K L L L L K K L L L K L K K L K L L K K F K L L K K E K E K L L L L L L L L L L L L L L L F T T T T T NN T T NN NN NN NN T T NN NN NN NN T T NN T NN NN T T NN T SS SS SS SS SS SS S SS SS SS SS SS SS SS SS NN NN G Y Y Y Y Y Y Y Y Y Y Y Y Y I I LAC LAC I I I LAC LAC I I I I LAC I LAC LAC I LAC I I LAC LAC I LAC I LAC LAC Y Y LAC LAC LA LA LA LA L K K K LA LA K K K K LA LA K K K K LA K LA LA K LA N N LA LA P P N N N P S N N N N P N P P N P N N P P N P N P P K K P P R R R R R R R R R R R R R D D R R G G D D D G G D D D D G D G G D G D D G G D G D G G G G L L L L L NN NN NN L L NN NN NN NN L NN L NN NN NN L NN L L NN L T T L L F F T T T F F T T T T F T F F T F T T F F T F T F F NN NN F F 21 291 111 201 D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D F F F F F TT F F TT TT TT TT F F TT TT TT TT F TT F F TT TT F L L TT F F FI FI L L L L L L FI FI L L FI L FI FI L FI L L FI FF L FI FI FF TT TT FI FI K R R K R Y K K Y Y Y Y K K Y Y Y Y T K Y K Y Y T P P Y K K Y Y P P P P P P Y Y P P Y P Y Y P Y P P Y Y P Y Y Y Y Y Y Y Q Q Q Q Q W Q Q W W W W Q Q W W W W Q W Q Q W W Q I I W Q Q R R I V I I V I R R I I R I R R I R I I R R I R R R W W R R G G G G G D G G D D D D G D G D D D G D G G D D G P P D G G F F P P P P P P F F P P F P F F P F P P F F P F F F D D F F R R R R R P R R P P P P R R P P P P R P R R P P R P R R T T T T T T T T T T T T T P P T T G G G G G G G G G G G G G F F F F F F F F F F F F F G G F F NN NN NN NN NN C NN NN C C C C NN NN C C C C NN NN C NN C C NN FWI FWI C NN NN S S FWI FWI FWI FWI FWI FWI S S FWI FWI S FWI S S FWI S FWI FWI S S FWI S S S C C S S S S S S S S S S S S S S S S S VV VV VI VV VV C VV VV C C C C VV VV C C C C VV VV C VV C C VV ED ED C VV VV CF CF ED ED ED ED ED ED CF CF ED ED CC ED CF CF ED CC ED ED CF CF ED CF CF CF C C CF CF 11 281 101 191 Q Q Q Q Q Q Q Q Q Q Q Q P P Q P P P P P P P P A P P A P P P Q Q I V LW L L L L L L L L L L L L F F L TT TT F F F TT TT F F F F F T TT TT F F T F TT TT F TT F TT TT L TT L T G G G G G G G G G G G G G E E G F F E E E F F E E E E E F F F E E F E F F E F E F F G F G F F FALW FALW FALW FALW E FALW FALW E E E E FALW FALW E E E E FALW E FALW FALW E E FALW E FALW FALW S S S S S S S S S S S S S E S E S S S S S S P S S P P P P S S P P P P S P S S P P S VV VI P S S G VV VV VV G G VV VV VV VV VL G G G VV VI G VV G G VI G VV G G G P G P G A A A A A I A A I I I I A A I I I I A A I A I I A R R I A A R R R R S R R R R R R R I I Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y VV N VV VV N VV VV VV VV VV VV VV VV VV VV Y VV Y VV P P P P P P R R P P R R R R P P R R R R P P R P R R P SN SN P S SN F SN S S SN F SN SNQ SN S S S SN SN S SN S S SN S SN S S S R S R S S S S S S S S S S S S S S R R R R R R R R R R R R R R R S S WM WM WM WM WM WM W W WM WM W W W W WM WM W W W W WM W WM WM W W WM M 1 M WM LV M M M LV LV M M M M M LV LV LV M M LV M LV LV M LV M LV LV LV W LV W LV 91 271 181 SWS2A | P.petenensis|SWS2A P.picta|SWS2A P.mexicana|SWS2A P.parae|SWS2A P.nigrofasciatis|SWS2A P.bifurca|SWS2A P.latipinna|SWS2A P.velifera|SWS2A P.vittata|SWS2A P.minor|SWS2A P.wingei|SWS2A P.petenensis|SWS2A P.reticulata|SWS2A P.mexicana|SWS2A P.caymanensis|SWS2A P.latipinna|SWS2A P.picta|SWS2A P.wingei P.nigrofasciatis|SWS2A P.parae|SWS2A P.vittata|SWS2A H.formosa|SWS2A P.velifera|SWS2A P.bifurca|SWS2A P.reticulata|SWS2A P.caymanensis|SWS2A P.minor|SWS2A X.helleri|SWS2A P.petenensis|SWS2A P.picta|SWS2A P.bifurca|SWS2A P.velifera|SWS2A X.helleri|SWS2A P.reticulata|SWS2A P.nigrofasciatis|SWS2A P.parae|SWS2A P.latipinna|SWS2A H.formosa|SWS2A P.wingei|SWS2A P.caymanensis|SWS2A P.minor|SWS2A X.helleri|SWS2A P.mexicana|SWS2A P.picta|SWS2A P.vittata|SWS2A P.bifurca|SWS2A H.formosa|SWS2A P.nigrofasciatis|SWS2A P.petenensis|SWS2A P.reticulata|SWS2A P.parae|SWS2A P.caymanensis|SWS2A P.mexicana|SWS2A P.velifera|SWS2A P.wingei|SWS2A P.vittata|SWS2A H.formosa|SWS2A P.latipinna|SWS2A X.helleri|SWS2A P.minor|SWS2A

Figure 2.2. Amino acid alignment of SWS2A.

according to to according Key: Known SWS2 tuning site region Transmembrane Retinal binding pocket site rhodopsin in bovine with Key tuning site variable AA selection under positive Site P>95% at (BEB) Empirical Bayes Bayes of model 8 in PAML analysis V * L L L L L L L L L L L L L L L FL FL FL FL FL FL FL FL FL FL FL FL FL FL FL G PP PP G PP PP G PP PP G PP PP G PP PP G PP G G PP G G G G PP G G PP G PP MAVA MAVA MAVA MAVA MAVA MAVA MAIA MAVA MAVA MAVA MAVA MAVA MAVA MAVA MAVA N N N N N N N N N N N N N N N S S S S S S S S S S S S S S S P P P P P P P P P P P P P P ILV P ILV ILV ILV ILV ILV ILV ILV ILV ILV ILV ILV ILV ILV ILV G G G G G G G G G G G G G G Y G Y Y Y Y Y Y Y Y Y Y Y Y Y Y V V V V V V V V V V V V V V N V CALCAAV FALCAAV MVVVMVL CALCAAV N FALCAAV N MVVVMVL CALCAAV N FALCAAV MVVVMVL FALCAAV FALCAAV MVVVMVL CALCAAV N FALCAAV N MVVVMVL CALCAAV N MVVVMVL MVVVMVL CALCAAV N N MVVVMVL N MVVVMVL MVVVMVL MVVVMVL FALCAAV MVVVMVL N MVVVMVL N FALCAAV MVVVMVL CALCAAV MVVVMVL N N N 81 351 261 171 K K K K K K K K K K K K K K K R L L R L R R L L R L R R L L R L R R R R L R L R R L L L L S S S S S S S S S S S S S S S WF WF T WF H WF H T WL H WF T WF WF T WF H WF H T WF H T T WV H H T H T T T WF T H T H WF T WF T H H H H V V V V V V V V V V V V V V V V T S T S V T S T V T T V T S T S V T S T V T V T S S V S V V V V S V S T V T V T S S S S E E E E E E E E E E E E E E E E R R E R E E R R E R E E L R R E R E E E E R E R E E R R R R T T T T T T T T T T T T T T T K L L K L K K L L K L K K G L L K L K K K K L K L K K L L L L V V V V V V V V V V V V V V V E E E E E E E E E E E E E E E A KK KK A KK A A KK KK A KK A A KK KK A KK A A A A KK A KK A A KK KK KK KK K Y Y K Y K K Y Y K Y K K Y Y K Y K K K K Y K Y K K Y Y Y Y SQS SQS SQS SQS SQS SQS SQS SQS SQS SQS SQS SQS SQS SQS SQS Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q A A A A A A A A A A A A A A ALFFCAL A ALFFCAL ALFFCAL I ALFFCAL I ALFFCAL I ALFFCAL ALFFCAL ALFFCAL ALLFCAL I ALFFCAL I ALLFCAL I ALFFC I I I ALFFCAL I I ALFFCAL ALFFCAL I I I I 71 341 251 161 S H H ST H T H T ST H T H ST H H ST H T H T ST H T ST ST H T T ST T ST ST ST H ST T ST T H ST H ST T T T T SS SS SS SS SS SS SS SS SS SS SS SS SS A E E A E SS E A E E A E E A E E A E A A E A A A A E A A E A E A S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S K K E K K E K IAC K IAC E K IAC K E K K E K IAC IAC E IAC E K E IAC E IAC E IAC E K E E K IAC E IAC K E IAC IAC IAC IAC A A T T A T A A T T A T A A T A T A T A A A T A T A T T T T DEEE DEEE DEEE DEEE DEEE DEEE DEEE DEEE DEEE DEEE DEEE DEEE DEEE DEEE Q DEEE Q Q Q Q Q Q Q Q Q Q Q Q Q Q G FAF FAF FAF FAF A FAF VL FAF VL A FAF VL FAF A FAF FAF A FAF VL IL A IL A FAF A VL A IL A IL A FAF A A FAF IL A VL FAF A A IL VL IL VL GG GG GG GG GG GG GG GG GG GG GG GG GG A N N N GG N K N N N N K N N N K N N K N N N K N K N K N K N K N K N K K N N K N N K K N N N N S S S S S S S S S S S S S S G G G S G G G G G G G G G G G G M M M M M M M M M M M M M M L AA L AI M L AI AA L AI L AA L L AA L AI L AI AA L AI AA AA L AI AA AI AA L AI AA AA AA L AI AA AI L AA L AA AI AI AI AI 61 331 241 151 G G G G G G G G G G G G P G G S P T P T S P T G P S P P S P T P T S P T S S P T S T S P T S S S P T S T P S P S T T T T K K K G K G K K G K K K K K K G K G K K G K K K G K G K K G K K K K G K G K K K K G G G G ML ML ML ML ML ML ML ML ML ML ML ML ML ML L L ML L L L L L L L L L L L L L T T T T T T T T T T T T T T T RK RK RK RK RK RK RK RK RK RK RK RK RK RK RK CM CM CM CM CM CM CM CM CM CM CM CM WLVIC CM CM LLF WLVIC WLVIC LLF WLVIC CM WLVIC LLF WLVIC WLVIC LLF WLVIC WLVIC LLF WLVIC LLF LLF WLVIC LLF LLF WLVIC LLF LLF LLF WLVIC LLF WLVIC LLF WLVIC LLF V S S S S S S S S S S S S R S S R R R S R R R R R R R R R R R R R R R R R R R R R R R E R R SQ E E SQ E R E SQ E E SQ E E SQ E SQ SQ E SQ SQ E SQ SQ SQ E SQ E SQ E SQ F F F F F F F F F F F F F F F Y F LMFVLFVA F LMFFLFAA Y F LMFFLFVA F F Y F F Y F LMFFLFVA F LMFVLFAA Y F LMFFLFVA Y Y F LMFFLFVA Y LMFFLFVA Y F LMFFLFVA Y Y Y F LMFFLFVA Y LMFFLFVA F Y F Y LMFFLFVA LMFVLFVA LMFFLFVA LMFVLFVA 51 321 231 141 Q Q Q Q Q Q Q Q Q Q Q Q Q Q A A A Q A A A A A A A A A A A A K K K K K K K K K K K K K K S S S K S S S S S S S S S S S S N N N N N N N N N N N N N N M M M N M M M M M M M M M M M M S S S S S S S S S S S S S S S LAVIA CIVFC LAVIA LAVIA CIVFC LAVIA Y LAVIA Y CIVFC LAVIA Y LAVIA CIVFC LAVIA LAVIA CIVFC LAVIA Y Y CIVFC Y CIVFC LAVIA CIVFC CIVFC LAVIA Y Y CIVFC Y CIVFC CIVFC LAVIA CIVFC LAVIA Y CIVFC Y LAVIA CIVFC Y Y Y Y VLL VLL VLL VLL VLL VLL VLL VLL VLL VLL VLL VLL S VLL VLL T S S T S VLL S T S S S S S T S S T S T S S T T T S T S T S T Y Y Y Y Y Y Y Y Y Y Y Y Y Y F F LF Y LF F LF F F LF LF F LF F F F LF LF F LF F F F LF F LF F LF LF LF LF LW P LW LW P LW G LW G P LW G LW P LW LW P LW G G P G P LW P P LW G G P G P P LW P LW G P W LW P G G G G VI VI VI VI VI VI VI VI VI VI VI VI S VI VI V S S V S L VI S L V S L S V S S V S L L V L V S V V S L L V L V V S V S L V L S V L L L L P P P P P P P P P P P P P P S S S P S S S S S S S S S S S S S S S S S S S S S S S S S S S 41 311 221 131 N N N N N N N N N N N N MV N N MV MV MV G N MV G MV G MV MV MV MV G G G MV MV G G G MV MV G G MV G G G G Y Y Y Y Y Y Y Y Y Y Y Y Y Y L Y L L L L L L L L L L L L L L V V V V V V V V V V V V V GG V GG GG GG H V GG H GG H GG GG GG GG H H H GG GG H H H GG GG H H GG H H H H L L L L D L D L D L L L V D D D L D D D L L D D L D D D D ST ST ST ST ST ST ST ST ST ST ST ST ST S ST S S S Q ST S Q S Q S S S T Q Q Q S Q Q Q S S Q Q S Q Q Q Q V A A A A A A A A A A A A A A A P A P A P A A A A A P A P A P AAL P P A P A P P A A A P P P P K K K K K K K K K K K K K K T T T K T T T T T T T T T T T T S S S S S S S S S S S S S S F LV F LV F LV S F F F F LV F LV F LV F LV LV F LV F LV LV F F F LV LV LV LV G Y G Y G Y G G G G Y G Y G Y G Y Y G Y G Y Y G G G Y Y Y Y CV CV CV CV CV CV CV CV CV CV CV CV CV CV FVLFLFCFCF E P E P FVLFLFCFCF E P CV E FVLFLFCFCF E E FVLFLFCFCF E P E P FVLFLFCFCF E P FVLFLFCFCF E FVLFLFCFCF FVLFLFCFCF P P FVLFLFCFCF E P FVLFLFCFCF FVLFLFCFCF FVLFLFCFCF E FVLFLFCFCF P FVLFLFCFCF P E FVLFLFCFCF E E P P P P 31 301 211 121 S S S S S S S S S S S S S S S I S I S S I S S I S I I S I S I S S I S S I S S S S S I S S S T I S S S S I S I I S S S S P P P P P P P P P P P P P P K K E K P K E K K E K K E K L E K E E E K E E E K E K E E K E K I I I I I I I I I I I I I I C AL C AL C AL I C C C C AL C C AL C AL AL C AL C AL AL C C C AL AL AL AL T T T T T T T T T T T T T T NT G T G T NT G T T G NT G G NT G T G TT NT G T NT G NT NT T T NT G T NT NT NT G NT T NT T G NT G G T T T T Y L I L I Y L I L Y L L Y L I L I Y L I Y L Y Y I I Y L I Y Y Y L Y I Y I L Y L L I I I I LA LA LA LA LA LA LA LA LA LA LA LA LA LA K P N P N K P N LA P K P P K P N P N K P N K P K K N N K P N K K K P K N K N P K P P N N N N R R R R R R R R R R R R R R N G D G D N G D R G N G G N G D G D N G D N G N N D D N G D T N N G N D N D G N G G D D D D L L L L L L L L L L L L L L G T T G T L G G T T G T G G G T T G T G G G G T G T G T T T T D D D D D D D D D D D D D D E E E D E E E E E E E E E E E E F F F F F F F F F F F F F F TT MAL L MAL L TT MAL L F MAL TT MAL MAL TT MAL L MAL L TT MAL L TT MAL TT TT L L TT MAL L TT TT TT MAL TT L TT L MAL TT MAL MAL L L L L 21 291 201 111 Y Y P Y P Y Y P Y Y Y Y Y Y P Y P Y Y P Y Y Y Y P P Y Y P Y Y Y Y Y P Y P Y Y Y Y P P P P QT QT QT QT QT QT QT QT QT QT QT QT W QT R I QT R I W R I R W R QT R W R I R I W R I W R W W I I W R I W W W R W I W I R W R R I I I I G G G G G G G G G G G G D G P G P D P D G D P P D P D D D P P D P D D D D P D P D P P P P R R R R R R R R R R R R P R R P P R P P P P P P P P P P P P H H H H H H H H H H H H G H H G G H G G G G G G G G G G G G N N N N N N N N N N N N C N CFAF FWI N CFAF FWI C CFAF FWI CFAF C CFAF N CFAF C CFAF FWI CFAF FWI C CFAF FWI C CFAF C C FWI FWI C CFAF FWI C C C CFAF C FWI C FWI CFAF C CFAF CFAF FWI FWI FWI FWI S S Y Y S Y Y S Y Y S Y Y S Y S S Y S S S Y S S S Y S Y Y Y C DD DD C DD C C DD ED C DD C C C DD DD C DD C C C C DD C DD C DD DD DD DD Q CF P CF P Q CF P CF Q CF CF Q CF P CF P Q CF P Q CF Q Q P P Q CF P Q Q Q CF Q P Q P CF Q CF CF P P P P LWVV LWVV LWVV LWVV LWVV LWVV LWVV LWVV LWVV LWVV LWIV LWVV M LWVV T T LWVV T T M T T T M T LWVV T M T T T V M T M M T M M T M M T M M M M T M M M T T M T T M T M T * 11 281 191 101 G F F G F F G F F G F F G F G F G G G F G G G F G G F G F F FA FA FA FA FA FA FA FA FA FA FA FA FA EE FA EE E S EE S E S FA S E S EE S EE E S EE S E S E S EE E EE E EE E S E E EE E EE S E E S E S EE EE S EE EE S S S S S S S S S S S S S Q S Q P G Q G P G S G P G Q G Q P G Q G P G P G Q P Q P Q P G P P Q P Q G P P G P G Q Q G Q Q A A A A A A A A A A A A A R A R I V R V I V A V I V R V R I V R V I V I A R I R I R I V I I R I R V I I V I V R R V R R Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y P P P P P P P P P P P P P TS P TS R SS TS SS R SS P SS R SS TS SS TS R SS TS SS R SS R SS TS R TS R TS R SS R R TS R TS SS R R SS R SS TS TS SS TS TS V V M V M V M M M M M M M R M R S R S M S R R S R S S R S R S R S S S R S R S S S R R R R Y Y Y Y Y Y Y Y Y Y Y Y Y M Y M W M W Y W M M W M W W M W M W M W W W M W M W W W M M M M K K G LIV K LIV G LIV LIV G LIV K LIV K G LIV K LIV G LIV G LIV K G K G K G LIV G G K G K LIV G G LIV G LIV K K LIV K K VC VC VC VC VC VC VC VC VC VC VC VC VC M VC M 1 V N M N V N VC N V N M N M V N M N V N V N M V M V M V N V V M V M N V V N V N M M N M M 91 271 181 SWS2B P.picta|SWS2B P.parae|SWS2B P.petenensis|SWS2B P.bifurca|SWS2B P.mexicana|SWS2B P.minor|SWS2B P.nigrofasciatis|SWS2B P.latipinna|SWS2B P.wingei P.vittata|SWS2B P.velifera|SWS2B P.reticulata|SWS2B P.caymanensis|SWS2B P.picta|SWS2B H.formosa|SWS2B X.helleri|SWS2B P.minor|SWS2B P.nigrofasciatis|SWS2B P.petenensis|SWS2B P.parae|SWS2B P.vittata|SWS2B P.mexicana|SWS2B X.helleri|SWS2B P.picta|SWS2B P.bifurca|SWS2B P.petenensis|SWS2B P.reticulata|SWS2B P.reticulata|SWS2B H.formosa|SWS2B P.nigrofasciatis|SWS2B P.velifera|SWS2B P.velifera|SWS2B P.wingei|SWS2B P.parae|SWS2B P.latipinna|SWS2B P.mexicana|SWS2B P.minor|SWS2B P.wingei|SWS2B X.helleri|SWS2B P.caymanensis|SWS2B P.picta|SWS2B P.latipinna|SWS2B P.petenensis|SWS2B P.bifurca|SWS2B H.formosa|SWS2B P.reticulata|SWS2B P.vittata|SWS2B P.velifera|SWS2B P.minor|SWS2B X.helleri|SWS2B P.caymanensis|SWS2B P.wingei|SWS2B H.formosa|SWS2B P.latipinna|SWS2B P.caymanensis|SWS2B P.nigrofasciatis|SWS2B P.bifurca|SWS2B P.vittata|SWS2B P.mexicana|SWS2B P.parae|SWS2B

Figure 2.3. Amino acid alignment of SWS2B.

** Key: Known RH1 tuning site region Transmembrane Retinal binding pocket site rhodopsin in bovine under positive Site selection P>95% (*) and at to P>99% ( ) according (BEB) Empirical Bayes Bayes of model 8 in PAML analysis

**/ * P P P P P P P P P P P P P P P S S S S S S S S S S S S S S S I I I I I GG GG I GG GG I GG GG GG I GG GG I GG GG GG I I I I I I GG A A A A A A A A GG GG A A A A A A A Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y R R R R R R R R R R R R R R R P P P P P P P P P P P P P P P S S S S S S S S S S S S S S S I I T I T T T L I I T I T T I W W W W W W W W W W W W W W W G G G

** A A G LFMVF LFMVF G A A LFMVF LFMVF A A G LFMVF LFMVF G LFMVF A A LFMVF LFMVF LFMVF A A A G LFMVF LFMVF G LFMVF A A LFMVF LFMVF G G G G G G A A P P D D P P D D P P D D D P P D D D P P P D D D P P D D P P LL LL LV S S LV LL S S S S LV LL S S S S S LL LL S S LV LV LV LV LV LV S ** S V V VA VA V V VA VA V V VA VA VA V V VA VA VA V V V VA VA VA V V VA VA FLVCW FLVCW FLVCW FLICW FLICW FLICW FLICW FLVCW V FLVCW FLVCW FLVCW FLICW FLICW FLVCW FLICW V 81 351 171 261 PP PP PP PP PP PP PP PP PP PP PP PP PP PP PP G G G G G G G G G G G G G G G LA LA LA LA LA LA LA LA LA LA LA LA LA LA LA N N N N N N N N N N N N N N N CAA CAA CAA SSSS SSSS CAA CAA SSSS SSSS SSSS SSSS CAA CAA SSSS SSSS SSSS SSSS SSSS CAA CAA SSSS SSSS CAA CAA CAA CAA CAA CAA SSSS SSSS T T A V V A S V V V V A S V V V V V S T V V A A A A A G V V N N N N ILL ILL N ILL ILL N ILL ILL N ILL ILL ILL ILL N ILL ILL N ILL ILL ILL N N N N N ** N SS SS SS SS Y Y SS SS Y Y SS SS Y Y Y SS SS SS Y Y Y SS SS Y Y Y SS Y Y SS A A A A N N A A N N A A N N N A A A N N N A A N N N MVVIMVI MVIIMVI MVVIMVI MVIIMVI MVIIMVI MVIIMVI MVVIMVI A N N MVVIMVI MVVIMVI MVIIMVI MVIIMVI MVVIMVI MVVIMVI MVVIMVI MVVIMVI ** A E E E E L L E E L L E E L L L E E E L L L E E L L L R R R R R R R R E L L R R R R R R R E WIMA WIMA T WIMA T T T WIMA P P WIMA T T P P T T WIMA P P WIMA P T T T P P P T T WIMA P P WIMA P T T T T T T T T T P P T T T T T T T WIMA WIMA WIMA WIMA WIMA WIMA T 71 161 251 341 T T K K T K K T T K K T T T T K K T T T K K K T T T T T K K T T T V V V V V V V V K T T T V V V V V V V T T T T T T T K S S S S R R S S R R S S R R R S S S R R R S S R R R E E E E E E E E S R R E E E E E E E S A A L L A A L L A A L L L A A L L L A A A L L L R R R R R R R R A A L L R R R R R R R A A LVF LVF LVF LVF LVF LVF LVF LVF LVF LVF LVF LVF LVF LVF LVF E E E E E E E E E E E E E E E G G G KK KK G KK KK G KK KK KK G KK KK G KK KK KK KK G KK KK G G G G G G G A A A A A A A A A A A A A A A STT STT STT STT H H STT STT H H STT STT H H H STT STT STT H H H STT STT H H H STT H H R R R R R R R R STT R R R R R R R A A A A E E A A E E A A E E E A A A E E E A A E E E A E E A AIM AIM G G AIM G G I I G G AIM I I AIM G G I I I G G G AIM I I AIM I G G I I I G AIM M I AIM AIM AIM AIM AIM AIM AIM G H H H T T H T T H T T T H T T H T T T T TTQ TTQ TTQ TTQ TTQ TTQ TTQ TTQ H T T TTQ TTQ TTQ TTQ TTQ TTQ TTQ H H H H H H H N N EE EE N EE EE V V EE EE N V V N EE EE V V V EE EE EE N V V N V EE EE V V V E E E E E E E E EE N V V E E E E E E E N N N N N N N EE 61 241 331 151 E E E Y Y E Y Y E Y Y Y E Y Y E Y Y Y Y S S S S S S S S E Y Y S S S S S S S E E E E E E E S S EE EE G EE EE L L EE EE G L L S EE EE L L L EE EE EE G L L S L EE EE L L L E E E E E E E E EE S L L E E E E E E E G G G G S G G EE F F F F F F F T T F F F T T F F F T T T F F F F T T F T F F T T T F F T T F F F F F F F F R R P P R P P P P R R P P P P P R R P P QQ QQ QQ QQ QQ QQ QQ QQ P R QQ QQ QQ QQ QQ QQ QQ R R R R R R R P F F N N F N N FL FL N N F FL FL F N N FL FL FL N N N F FL FL F FL N N FL FL FL N F FL FL F F F F F F F N K K K K N N K K N N K K N N N K K K N N N K K N N N K N N K SN SN G G SN G G I I G G SN I I SN G G I I I G G G SN I I SN I G G I I I G SN I I SN SN SN SN SN SN SN G I I I P P I P P I P P P I P P I P P P P I P P I I I I I I I AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA AAAA P P P F F P F F P F F F P F F P F F F F P F F P P P P P P P E E E E E E E E E E E E E E E K K LCC LCC K LCC LCC G G LCC LCC K G G K LCC LCC G G G LCC LCC LCC K G G K G LCC LCC G G G LCC K G G K K K K K K K K K K K K K K K LCC K K K K K K K 51 321 141 231 TT TT TT TT TT TT TT TT TT TT TT TT TT TT TT WLVVC WLVVC WLVVC CMI CMI WLVVC CMI CMI CMI CMI WLVVC WLVVC CMI CMI CMI CMI CMI WLVVC WLVVC CMI CMI CMI WLVVC WLVVC WLVVC WLVVC WLVVC WLVVC WLVVC LLCAV LLCAV LLCAV LLCAV LLCAV LLCAV LLCAV LLCAV CMI LLCAV LLCAV LLCAV LLCAV LLCAV LLCAV LLCAV R R R H H R H H H H R R H H H H H R R H H H R R R R R R R R R R R R R R R H R R R R R R R E E E R R E R R MFFLILV MFFLILV R R E MFFLILV MFFLILV E R R MFFLILV MFFLILV MFFLILV R R R E MFFLILV MFFLILV E MFFLILV R R MFFLILV MFFLILV MFFLILV R E MFFLILV MFFLILV E E E E E E G G G G G G G G R G G G G G G G F F F F Y Y F F Y Y F F Y Y Y F F F Y Y Y F F Y Y Y F Y Y Y Y Y Y Y Y Y Y F Y Y Y Y Y Y Y Q Q Q Q A A Q Q A A Q Q A A A Q Q Q A A A Q Q A A A Q A A Q LAV LAV LAV K K LAI K K G G K K LAV G G LAV K K G G ** G K K K LAV G G LAV G K K G G G K LAV G G LAI LAI LAI LAI LAV LAI FC FC FC FC FC FC FC FC K FC FC FC FC FC FC FC 41 311 131 221 N N N N N N N N N N N N N N N * LVV LVV LVV LVV ACL ACL LVV ACL ACL LVV ACL ACL ACL LVV ACL FCL LVV ACL ACL FCL ACL LVV ACL ACL LVV LVV LVV LVV LVV LVV ** S S S ICM ICL S ICM ICL Y Y ICL ICM S Y Y S ICL ICM Y Y Y ICM ICM ICL S Y Y S Y ICL ICM Y Y Y ICM S Y Y S S S S S S ICM * Y Y Y Y Y Y Y Y Y Y Y Y Y LIVVF LVVVF LVIVF LVIVF LVIVF LVIVF LAVVF LVIVF Y Y LVVVF LVVVF LAVVF LVVVF LVIVF LVIVF LVIVF LW LW LW LW AA AA LW AA AA LW AA AA AA LW AA AA LW AA AA AA AA LW AA AA LW LW LW LW LW LW P P P P P P P P P P P P P P P G G LI G MI MI G MI MI P P LI MI G P P G LI LI P P P MI LI MI G P P G P MI LI P P P MI G P P G G G G G G I I P I P P I P P S S P P I S S I P P S S S P P P I S S I S P P S S S P I S S I I I I I I ** E E N E N N E N N N N E E N N N N N E E N N FCI FLI FCI FCI FCI FCI FCI FCI N E FCI FII FCI FCI FCI FCI FCI E E E E E E ** Y Y Y Y Y LV LV Y Y LV LV Y Y LV LV LV Y Y Y LV LV LV Y Y LV LV LV H H H H H H H H Y LV LV H H H H H H H 31 121 211 301 GG GG I GG I I GG I I I I GG GG L I I I I GG GG I I I GG GG GG GG GG GG GG L L S L S S L S S YY YY S S L YY YY L S YY YY YY S S S L YY YY L YY S S YY YY YY S L YY YY L L L L L L T T A T A A T A A Q Q A A T Q Q T A Q Q Q A A A T Q Q T Q A A Q Q Q A T Q Q T T T T T T S S T T T P P T T P P SSS S P P P S S T P P P T T P P P MFIC MFIC MFIC MFIC MFIC MFIC MFIC MFIC T P P MFIC MFIC MFIC MFIC MFIC MFIC MFIC FA FA FA K K FA K Y Y K K FA Y Y FA K K Y Y Y K K FA Y Y FA Y K K K Y Y Y Y Y Y Y Y Y Y Y K K FA Y Y Y Y Y Y Y Y Y FA FA FA FA FA FA ** K Y Y Y Y E E Y E E Y E E E Y E E Y E E E E Y E E Y Y Y Y Y Y * G G G G Y Y G Y Y G Y Y Y G Y Y G Y Y Y Y G Y Y G G G G G G E E E E P P E P P E P P P E P P E P P P P FVI FVI FVI FVI FVI FVI FVI FVI E P P FVV FVV FVI FVV FVI FVI FVI E E E E E E L L AFFA L AFFA AFFA L AFFA AFFA S S AFFA AFFA V S S L AFFA AFFA S S S AFFA AFFA AFFA V S S L S AFFA AFFA S S S S S S S S S S S AFFA L S S S S S S S S S L L L L L L N N P N P P N P P R R P P N R R N P P R R R P P P N R R N R P P R R R E E E E E E E E P N R R E E E E E E E N N N N N N * 21 111 201 291 C C V C I I C I I I I C C I V V I I C C V I I C C C C C C C G G T G T T G T T IV IV T T G IV IV G T T IV VV IV T T T G IV IV G IV T T IV IV VV NN NN NN NN NN NN NN NN T G IV IV NN NN NN NN NN NN NN G G G G G G L L L L G G L G G L G G G L G G L G G G G F F F F F F F F L G G F F F F F F F L L L L L L R R R R R R R R G G G G G G G G G G G G G G G R R R R R R R G G LFM G LFM LFM G LFM LFM LFM LFM G G LFM LFM LFM LLM LFM G G LFM LFM E E E E E E E E LFM E E E E E E E G G G G G G G P P P P P P P NTT NTT P P NTT NTT P P P NTT NTT NTT P P NTT NTT NTT A A A A A A A A P NTT NTT A A A A A A A NTT NTT NTT G G G G G G G G G G G G G G R R R R R R R R G R R R R R R R FVL FVL F FVL F F FVL F F MV MV F F FVL MV MV FVL F F MV MV MV F F F FVL MV MV FVL MV F F MV MV FVL FVL FVL FVL FVL FVL FVL MV T T T T T T T T F MV MV T T T T T T T Y Y E Y E E Y E E P P E E Y P P Y E E P P P E E E Y P P Y P E E P P Y Y Y Y Y Y Y P E P P G G S G S S G S S V V S S G V V G S S V V V S S S G V V G V S S I V G G G G G G G V YY YY YY YY YY YY YY YY S V V YY YY YY YY YY YY YY 11 191 281 101 H H G H G G H Y G G Y Y G G H Y Y H G G Y Y Y G G G H Y Y H Y G G Y Y H H H H H H H D D D D D D D D G Y Y D D D D D D D M M Q M Q Q M F Q Q F F Q Q M F F M Q Q F F F Q Q Q M F F M F Q Q F F M M M M M M M V V I I I I I V Q F F V V V V I I I * H H H Y H H Y Y H H Y Y H H Y Y Y H H H Y Y Y H H Y Y G G G G G G G G H Y Y G G G G G G G TS TS TS T T TS P T P P T T TS P P TS T T P P P T T TS P P TS P T T T P P TS TS TS TS TS TS TS C C C C C C C C T T P P C C C C C C C T Y Y Y Y G G G Y G G Y G G G Y G G Y G G G Y Y Y Y Y Y Y S S S S S S S S G G S S S S S S S I I I IF IF I E IF E E IF IF I E E I IF IF E E E IF IF I E E I E IF IF IF E E I I I I I I M C C C C C C C C IF IF E E C C C C C C C IF Y Y T Y T T Y Y T T Y Y T T T Y Y T T T Y Y Y T T Q Q Q Q Q Q Q Q Y Y T T Q Q Q Q Q Q Q Y G G G G G G G G G G G G G M M M M M M M M G G M M M M M M M TTT TTT TTT TTT N N N TTT N N TTT N N N TTT N N TTT N N N TTT TTT TTT TTT TTT TTT TTT G G G G G G G G N N G G G G G G G F F F VAW VAW F M VAW M M VAW VAW F M M F VAW VAW M M M VAW VAW F M M F M VAW VAW VAW M M F F F F F F F E E E E E E E E VAW VAW 1 M M E E E E E E E VAW 91 181 271 RH1 P.picta|RH1 P.parae|RH1 P.bifurca|RH1 P.petenensis|RH1 P.mexicana|RH1 P.minor|RH1 P.petenensis|RH1 P.picta|RH1 P.nigrofasciatis|RH1 P.mexicana|RH1 P.parae|RH1 P.picta|RH1 P.vittata|RH1 P.latipinna|RH1 P.nigrofasciatis|RH1 P.bifurca|RH1 P.wingei|RH1 P.parae|RH1 P.caymanensis|RH1 P.vittata|RH1 P.minor|RH1 P.wingei|RH1 H.formosa|RH1 P.bifurca|RH1 P.velifera|RH1 P.caymanensis|RH1 P.latipinna|RH1 P.reticulata|RH1 P.reticulata|RH1 P.wingei X.helleri|RH1 P.minor|RH1 H.formosa|RH1 P.velifera|RH1 P.petenensis|RH1 P.mexicana|RH1 P.nigrofasciatis|RH1 P.vittata|RH1 P.caymanensis|RH1 H.formosa|RH1 X.helleri|RH1 P.wingei|RH1 P.petenensis|RH1 P.mexicana|RH1 P.nigrofasciatis|RH1 P.vittata|RH1 P.caymanensis|RH1 H.formosa|RH1 X.helleri|RH1 P.reticulata|RH1 P.latipinna|RH1 X.helleri|RH1 P.reticulata|RH1 P.picta|RH1 P.parae|RH1 P.bifurca|RH1 P.minor|RH1 P.latipinna|RH1 P.velifera|RH1 P.velifera|RH1

Figure 2.4. Amino acid alignment of RH1.

Key: Known RH2 tuning site region Transmembrane Retinal binding pocket site rhodopsin in bovine L L L L L L L L L L L L L L L FL FL FL FL FL FL FL FL FL FL FL FL FL FL FL PP PP PP G PP G PP PP PP PP PP PP G PP G G G PP G G G PP G G G PP G G PP G LAVA LAVA LAVA LAVA LAVA LAVA LAVA LAVA LAVA LAVA LAVA LAVA LAVA LAVA LAVA N N N N N N N N N N N N N N N ILV ILV ILV ILV ILV ILV ILV ILV ILV ILV ILV ILV ILV ILV ILV Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y MALACAA N MALACAA N AA AA MALACAA MCVLMVL N MALACAA MCVLMVL AA AA MALACAA N MALACAA N AA MALACAA AA MALACAA N MALACAA AA AA N N MALACAA AA AA MCVLMVL N MALACAA MCVLMVL N MCVLMVL MCVLMVL N AA MALACAA AA MCVLMVL MCVLMVL MCVLMVL N MALACAA MCVLMVL AA AA AA N MCVLMVL MCVLMVL N MALACAA MCVLMVM MCVLMVL N MALACAA MCVLMVL 81 261 171 351 L L L R L R L L L L L R L R L R R L R R R L R L R R L R R R WI P P WI P ST ST WI T P WI T ST ST WI P WI P ST WI ST WI P WI ST ST P P WI ST ST T P WI T P T T P ST WI ST T T T P WI T ST ST ST P T T P WI T T WI T Q Q Q V V V Q V V V Q Q V V Q V V Q Q V V V V Q V Q V V Q V V V V V Q V V V V Q V V Q V V R R R E E E R E E E R R E E ST R E E R R E E E E R E R E E R E E E E E R E E E E R E E R E E TST STT L L TST L T T TST K L TST K T T TST L TST L T TST T I L TST T T L L TST K T T K L SST K L K K L T TST T K K K L TST K T T T L K K L TST K K V V V K K V E V E K K V V K V K V V K K V E K K E V E E E K V K E E E V E K K K E E V E E G G KK KK G KK S S G A KK G A G KK G KK G G KK G KK KK G A A KK G A KK A A KK G A A A KK G A S S KK A A KK G A A A A K K K K K S K K K K K K A A K K K K QN QN QN S S Q QN Q STS STS QN QN STS STS QN STS STS QN QN Q STS STS Q QN Q Q Q Q QN STS STS Q Q Q QN Q S STS S QN Q Q QN Q Q AAA AAA A A AAA AAA A V V A AAA AAA V V A AAA AAA A V AAA V A AAA V V A A AAA V V A AAA A A V AAA V A AAA V V V A A AAA 71 251 161 341 H H T T H H T ST T H H ST T H H T H T H T T H ST ST T H ST T ST ST T H ST ST ST T H ST T ST ST T H ST ST T T T T TS TS A T T A TS TS T T TS T TS T TS TS T A TS TS A T A A A TS T TS A A A T A TS TS TS A A T A A G G G G S G G S G G G G G S S G S S S G S S S G S S S G S S T T LFV LFV T T LLV D LFV T T D LFV T T LFV T LFV T LFV LFV T D D LFV T D LFV D D LFV T D D LFV D T D LFV D D LFV T D D F F T T F F T EDE EDE T F F EDE EDE T F F T EDE F EDE T F EDE EDE T T F EDE EDE T F T T EDE F EDE T F EDD EDE EDE T T F K K L L K K L L K K L K K L K L K L L K L K L L K L K L L K F F G G F F G QQQ G MV F MV F QQQ G F MV MV F G F MV MV G F G G MV F MV QQQ QQQ G F QQQ MV MV G QQQ QQQ G F QQQ QQQ MV MV QQQ G F QQQ G QQQ QQQ G MV F MV MV QQQ QQQ S S N N S S N N S S N S S N S N S N N S N S N N S N S N N S G G I I G G I GG GG I G G GG GG I G G I GG G GG I G GG GG I I G GG GG I G I I GG G GG I G GG GG GG I I G M M P P M M P AAA M M AAA P M M M M P M M P M M M P M M M P AAA P M AAA AAA M M AAA P M AAA P AAA AAA P M M M AAA AAA P AAA M AAA M M M P AAA AAA P M 61 241 151 331 P P T T P P T A G G A T P P G G T P P T G P G T P G G T A T P A A G G A T P A T A A T G P G A A T A P A G G G T A A T P K K G G K K G K I I K G K K I I G K K G I K I G K I I G K G K K K I I K G K K G K K G I K I K K G K K K I I I G K K G K T T T V V T T T T T T T V T V V V T V T V V T V V T V V T V V T T T ST ST T ST A ST A TT ST T T T TT TT T T T T ST ST T T T T ST ST ST T IVVC IVVC IVVC IVVC IVVC IVVC IVVC IVVC IVVC IVVC IVVC IVVC IVVC IVVC IVVC Y Y Y Y LVM LVM CML Y CML Y LVM Y CML CML Y Y CML CML Y CML Y CML LVM LVM Y LVM CML CML LVM LVM Y LVM LVM CML CML LVM Y LVM LVM LVM CML Y CML CML LVM R R R N R S S N R N R S R N N R R N N R N R N S S R S N N S S R S S N N S R S S S N R N S E E MFFLIC E MFFLIC R E G MFFLIC G R E R E G MFFLIC E R R E MFFLIC E MFFLIC R R E MFFLIC R E R MFFLIC G MFFLIC G E G R R G MFFLIC G E MFFLIC G G MFFLIC R R G E G MFFLIC G G R E R MFFLIC G MFFLIC I I Y I Y F I Y Y Y F I F I Y Y I F F I Y I Y F F I Y F I F Y Y Y Y I Y F F Y Y Y I Y Y Y Y F F Y I Y C Y Y F I F Y Y Y 51 231 141 321 Q T T Q Q T Q Q Q Q Q Q T T T Q Q T T T T Q Q T T T T Q Q T K K K K K K K K K K K K K K K N N N N N N N N N N N N N N N LLAF LLAF LLAF LLAF LLAF LLAF LLAF LLAF LLAF LLAF LLAF LLAF LLAF LLAF LLAF LVVLA LVVLA K LVVLA K LVVLA K LVVLA LVVLA K LVVLA LVVLA K LVVLA K LVVLA K LVVLA K K LVVLA K LVVLA K K LVVLA K LVVLA K K S S S Y S Y S VLM Y S S Y VLM VLM S S Y VLM S VLM Y S VLM VLM Y S Y Y VLM VLM S Y VLM S VLM Y Y S VLM VLM Y Y Y VLM VLM Y VFLIFF VFLIFF Y Y VFLIFF Y Y Y Y Y Y VFLIFF VFLIFF VFLIFF Y Y VFLIFF VFLIFF VFLIFF VFLIFF Y Y VFLIFF VFLIFF VFLIFF VFLIFF Y Y VFLIFF MV MI P MI P MI P MI MI MI MI MI P P MI P MI P P MI P P P MI P MI P P MI P P P VI I P I P VI VI I P VI VI P VI VI P P P VI VI I I P I VI VI P I I P I I VI VI I P I P I I P VI VI I VALW VALW VALW D VALW D VALW P D VALW VALW D P P VALW VALW D P VALW P D VALW P P D VALW D D P P VALW D P VALW P D D VALW P P D D D P P 41 221 131 311 E E E E E N FF E E FF N N FF E E N E N E N N E N N E FF FF FF N E N FF FF FF E FF N N FF FF FF FF N N FF MV MV Y H MV H MV Y Y H MV Y Y MV Y Y MV MV MV Y Y H H MV H Y Y MV H H MV H H Y Y H MV H MV H H MV Y Y H GG GG GG GG GG GG GG GG GG GG GG GG GG GG GG L L YY L YY L AL L YY YY AL L AL L YY L AL AL L YY L AL AL YY L YY YY AL L AL YY L AL AL YY YY L AL AL YY L YY YY AL AL T T Q T Q T T Q Q T T Q T T Q T Q T Q Q T Q T Q Q T Q T Q Q P P SS P MFVV MFVV P SS SS MFIV P SS SS P SS SS P P P SS SS MFVV MFVV P MFVV SS SS P MFVV MFIV P MFVV MFVV SS SS MFVV P MFVV P MFVV MFVV Q SS SS MFVV Y Y K Y Y Y Y K K Y Y K K Y K K Y Y Y K K Y Y Y Y K K Y Y Y Y Y Y K K Y Y Y Y Y Y Y K K Y FMA FMA E FMA E FMA FMA E E FMA FMA E FMA FMA E FMA E FMA E E FMA E FMA E E FMA E FMA E E G G Y G F G VI G F VI VI F G G F G G F G F G F VI F G VI VI VI F G VI F VI VI F G VI VI F VI G VI F VI Y E E P E P E FFA Y E P Y FFA FFA Y P E E FFA FFA P E E P FFA E FFA P E FFA FFA P Y P E Y Y FFA FFA Y P E Y P Y Y P FFA E FFA Y Y P Y E Y FFA FFA P Y P 31 211 121 301 S S A S S S A A S S A A S S A A S A A S S S S S A A S S S S S S S A A S S S S S A A S S S R R P P E R E P P E R P P R R P P R P P R E R E E P P E R E R E E R P P E E R E E P R E R FCAI FCAI IV FCAI IV FCAI NN FCAI IV NN NN IV FCAI FCAI IV FCAI FCAI IV FCAI IV FCAI IV NN IV FCAI NN NN NN IV FCAI NN IV NN NN IV FCAI NN NN NN IV FCAI NN IV NN IV T T G T G AAL T AAL F T G F AAL AAL F G T T AAL AAL G T T G AAL T AAL G T AAL AAL G F G T F F AAL AAL F G T F G F F G AAL T AAL F F G F T F AAL G F G P P T P T T P T G P T G T T G T P P T T T P P T T P T T P T T T G T P G G T T G T P G T G G T T P T G G G T A G T T G T G G K G K G P G K P P K G G K G G K G K G K P K G P P P K G P K P P K G P P K P G P K P K AL AL AL AL AL AL AL AL AL AL AL AL AL AL AL SN T T SN LA T T SN LA LA SN T T SN T T SN T T SN SN LA SN T T LA LA LA SN LA T T SN LA LA SN LA LA T LA SN LA SN LA SN FIL FIL M F F FIL M FIL T F F FIL M T T M F FIL F FIL M FIL F F FIL M FIL F F M FIL L T M F FIL F T T T M FIL T F F L T T M FIL T T F L T FIL T M T M 21 201 111 291 Y Y P Y P Y Y P P Y Y P Y Y P Y P Y P P Y P Y P P Y P Y P P G G I AA AA G I G YY AA AA G I YY YY I AA G AA G I G AA AA G I G AA AA I G I YY I AA G AA YY YY YY I G YY AA AA I YY YY I G YY YY AA I YY G YY I YY I N N Y G G N Y N D G G N Y D D Y G N G N Y N G G N Y N G G Y N Y D Y G N G D D D Y N D G G Y D D Y N D D G D Y N D Y D Y F K K F P K K F P P F K K F K K F K K F F P F K K P P P L P K K F P P F P P K F P P F P F AL AL N N N AL N AL G N N AL N G G N N AL N AL N AL N N AL N AL N N N AL N G N N AL N G G G N AL G N N N G G N AL G G N N G AL G N G N K K C K C C K K K K K C K C C C K C K C C K C C C K C K C K TS TS G TS G TS S TS G S S G TS TS G TS TS G TS G TS G S G TS S S S G TS S G S S G TS S S S G TS S G S G I I E I E I C I E C C E I I E I I E I E I E C E I C C C E I C E C C E I C C E C I C E C E T T T T T WIFL T WIFM Q T T Q WIFM WIFM Q T T T WIFL WIFL T T T T WIFL T WIFL T T WIFL WIFL T Q T T Q Q WIFL WIFL Q T T Q T Q Q T WIFM T WIFL Q Q Q T T Q WIFM T Q T I I G I G G I G M I G M G G M G I I G G G I I G G I G G I G G G M G I M M G G M G I M G M M G G I G M M M G I M G G M G 11 191 101 281 T T N T N T G T N G G N T T N T T N T N T N G N T G G G N T G N G G N T G G N G T G N G N F F P F P FA F FA E F P E FA FA E P F F FA FA P F F P FA F FA P F FA FA P E P F E E FA FA E P F E P E E P FA F FA E E E P F E FA P E P G G E G E T G T P G E P T T P E G G T T E G G E T G T E G T T E P E G P P T T P E G P E P P E T G T P P E P G P S E P E Y Y A A L Y L A A I Y A A Y Y A A Y A A Y L Y L L A A L Y L Y L L Y A A I L Y L L A Y L Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y GG GG P P R GG R P P R GG P P GG GG P P GG P P GG R GG R R P P R GG R GG R R GG P P R R GG R R P GG R GG D D T T S D S T T S D T T D D T T D T T D S D S S T V S D S D S S D T T S S D S S T D S D W W W W W W W W W W W W W W W LIMCAF LIMCAF LIMCAF G LIMCAF G LIMCAF G LIMCAF LIMCAF LIMCAF LIMCAF LIMCAF LIMCAF G G G LIMCAF G G G LIMCAF G G G LIMCAF G G LIMCAF G G G MAW MAW VAW VAW G F G MAW F VAW VAW G F MAW VAW G VAW G MAW G MAW VAW VAW G G MAW VAW VAW MAW G F MAW VAW F F VAW G VAW F MAW F MAW F G F MAW VAW VAW F F G F MAW F 1 MAW F G MAW 91 181 271 RH21 P.bifurca|RH21 P.minor|RH21 P.parae|RH21 P.mexicana|RH21 P.velifera|RH21 P.wingei P.vittata|RH21 P.caymanensis|RH21 P.latipinna|RH21 P.bifurca|RH21 H.formosa|RH21 P.petenensis|RH21 P.reticulata|RH21 P.caymanensis|RH21 X.helleri|RH21 P.nigrofasciatis|RH21 P.mexicana|RH21 P.velifera|RH21 P.picta|RH21 H.formosa|RH21 P.minor|RH21 P.wingei|RH21 P.vittata|RH21 P.nigrofasciatis|RH21 P.parae|RH21 X.helleri|RH21 P.petenensis|RH21 P.latipinna|RH21 P.vittata|RH21 P.bifurca|RH21 P.wingei|RH21 P.reticulata|RH21 P.latipinna|RH21 P.caymanensis|RH21 X.helleri|RH21 P.wingei|RH21 P.velifera|RH21 P.caymanensis|RH21 P.mexicana|RH21 P.minor|RH21 P.reticulata|RH21 P.velifera|RH21 P.petenensis|RH21 P.reticulata|RH21 P.picta|RH21 P.picta|RH21 P.mexicana|RH21 H.formosa|RH21 H.formosa|RH21 P.latipinna|RH21 P.parae|RH21 P.nigrofasciatis|RH21 P.nigrofasciatis|RH21 P.bifurca|RH21 P.petenensis|RH21 P.vittata|RH21 P.picta|RH21 P.minor|RH21 P.parae|RH21 X.helleri|RH21

Figure 2.5. Amino acid alignment of RH2-1.

1 11 21 31 41 51 61 71 81

X.helleri|LWS1 MAEEWGKQVF AAR--HEDTT RGSAFTYTNS NHTKDPFEGP NYHIAP RWVY NLSTFWMFIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV H.formosa|LWS1 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NVSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.caymanensis|LWS1 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NVSTLWMFIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.vittata|LWS1 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NVSTVWMFIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.nigrofasciatus|LWS1 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NVSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.mexicana|LWS1 MAEEWGKQVF AAR--HEDTT RGSAFTYTNS NHTKDPFEGP NYHIAPRWVY NISTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.petenensis|LWS1 MAEEWGKQVF AAR--HEDTT RGSAFTYTNS NHTKDPFEGP NYHIAPRWVY NISTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.velifera|LWS1 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NISTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.latipinna|LWS1 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NISTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.minor|LWS1 MAEEWGRQVF AAR--HEDTT RGSAFTYTNS NHTKDPFEGP NYHIAPRWVY NISTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.bifurca|LWS1 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NLSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.parae|LWS1 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NVSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.picta|LWS1 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NISTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.reticulata|LWS1 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NVSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.wingei|LWS1 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NVSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV X.helleri|LWS2 MADDWRKQTFAARRHNEDTT RGSAFTYTNS NQTRDPFEGP NYHIAPRWVY NIATLWMFIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV H.formosa|LWS2 MADDWKKQMF AARRHNEDTT RGSAFIYTNS NQTRDPFEGP NYHIAPRWVY NVATLWMCIV VVLSIFTNGL VLVATAKFKR LRHPLNWILV P.caymanensis|LWS2 MSDDWRKQPFAARWHNEDTT RGSAFTYTNS NQTRDPFEGP NYHIAPRWVY DVATVWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.vittata|LWS2 MSDDWRKQPFAARWHNEDTT RGSAFTYTNS NQTRDPFEGP NYHIAPRWVY DVATVWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.nigrofasciatus|LWS2 MSDDWRKQPFAARWHNEDTT RGSAFTYTNS NQTRDPFEGP NYHIAPRWVY DVATVWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.mexicana|LWS2 MSDDWRKQPFAARWHNEDTT RGSAFTYTNS NQTRDPFEGP NYHIAPRWVY DAATVWMCIV VILSVFTNGL VLVATAKFKK LRHPLNWILV P.petenensis|LWS2 MSDDWRKQPFAARWHNEDTT RGSAFTYTNS NQTRDPFEGP NYHIAPRWVY DVATVWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.velifera|LWS2 MSDDWRKQPFAARWHNEDTT RGSAFTYTNS NQTRDPFEGP NYHIAPRWVY DVATVWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.latipinna|LWS2 MSDDWRKQPFAARWHNEDTT RGSAFTYTNS NQTRDPFEGP NYHIAPRWVY DVATVWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.minor|LWS2 MSDDWRKQLF AARRHNEDTT RGSAFTYTNS NQTRDPFEGP NYHIAPRWVY NISTLWMCIV VILSVFTNGL VLVATAKFKI LRHPLNWILV P.bifurca|LWS2 MSDDWRKQPFAARRHNEDTT RGSLFTYTNS NQTRDPFEGP NYHIAPRWVY DVATVWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.parae|LWS2 MSDDWRKQPFAARRHNEDTT RGSVFTYTNS NQTRDPFEGP NYHIAPRWVY DVATVWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.picta|LWS2 MSDDWRKQPFAARRHNEDTT RGSVFTYTNS NQTRDPFEGP NYHIAPRWVY DVATVWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.reticulata|LWS2 MSDDWRKQPFAARRHNEDTT RGSVFTYTNS NQTRDPFEGP NYHIAPRWVY DVATVWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.wingei|LWS2 MSDDWRKQPFAARRHNEDTT RGSVFTYTNS NQTRDPFEGP NYHIAPRWVY DVATVWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV X.helleri|LWS3 MAEEWGKQVF AAR--HEDTT RGSAFTYTNS NHTKDPFEGP NYHIAPRWVY NLSTFWMFIV VILSVFTNGL VLVATAKFKK LRHPLNWILV H.formosa|LWS3 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NVSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.caymanensis|LWS3 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NVSTLWMFIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.vittata|LWS3 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NVSTLWMFIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.nigrofasciatus|LWS3 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NVSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.mexicana|LWS3 MAEEWGKQVF AAR--HEDTT RGSAFTYTNT NHTKDPFEGP NYHIAPRWVY NLSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.petenensis|LWS3 MAEEWGKQVF AAR--HEDTT RGSAFTYTNT NHTKDPFEGP NYHIAPRWVY NLSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.velifera|LWS3 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NISTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.latipinna|LWS3 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NISTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.minor|LWS3 MVEEWGKQVF AAR--HEDTT RGSAFTYTNS NHTKDPFEGP NYHIAPRWVY NISTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.bifurca|LWS3 MAEEWGKQVF AAR--HEDTT RGSAFTYTNS NHTKDPFEGP NYHIAPRWVY NLSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.parae|LWS3 MAEEWGKQVF AAR--HEDTT RGSAFTYTNS NHTKDPFEGP NYHIAPRWVY NLSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.picta|LWS3 MAEEWGKQVF AAR--HEDTT RGSAFTYTNS NHTKDPFEGP NYHIAPRWVY NLSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.reticulata|LWS3 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTRDPFEGP NYHIAPRWVY NLSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV P.wingei|LWS3 MAEEWGKQVF AAR--HEDTT RGAAFTYTNS NHTKDPFEGP NYHIAPRWVY NVSTLWMCIV VVLSVFTNGL VLVATAKFKK LRHPLNWILV X.helleri|LWSR MAEDWGKQVL APWKNNEETT RGSAFTYTNS NHTKDPFEGP NYHIAPRWVY NITTVWMCFV VVFSVFTNGL VLAATAKFKK LRHPLNWILV H.formosa|LWSR MAEDWGKQAF APWKNNEETT RGSAFTYTNS NHTKDPFEGP NYHIAPRWVY NITTVWMCFV VVSSVFTNGL VLVATAKFKK LRHPLNWILV P.caymanensis|LWSR MAEDWGKQAF APWKNNEETT RGSAFTYANS NHTRDPFEGP NYHIAPRWVY NITTAWMCFV VVLSVFTNGL VLVATARFKK LRHPLNWILV P.vittata|LWSR MAEDWGKQAF APWKNNEETT RGSAFTYANS NHTRDPFEGP NYHIAPRWVY NITTAWMCFV VVLSVFTNGL VLVATARFKK LRHPLNWILV P.nigrofasciatus|LWSR MAEDWGKQAF APWKNNEETT RGSAFTYTNS NHTRDPFEGP NYHIAPRWVY NITTAWMCFV VVLSVFTNGL VLVATARFKK LRHPLNWILV P.mexicana|LWSR MAEDWGKQAF APWKNNEETT RGFAFTYTNS NHTRDPFEGP NYHIAPRWVY NITTVWMCFV VVLSVFTNGL VLVATARFKK LRHPLNWILV P.petenensis|LWSR MAEDWGKQAF APWKNNEETT RGSTFTYTNS NHTRDPFEGP NYHIAPRWVY NITTVWMCFV VVLSVFTNGL VLVATARFKK LRHPLNWILV P.velifera|LWSR MAEDWGKQAF APWKNNEETT RGSAFTYTNS NHTRDPFEGP NYHIAPRWVY NITTVWMCFV VVLSVFTNGL VLVATARFKK LRHPLNWILV P.latipinna|LWSR MAEDWGKQAF APWKNNEETT RGSAFTYTNS NHTRDPFEGP NYHIAPRWVY NITTVWMCFV VVLSVFTNGL VLVATARFKK LRHPLNWILV P.minor|LWSR MAEDWGKQAF APWKNNEETT RGSAFTYTNS NHTRDPFEGP NYHIAPRWVY NITTVWMCFV VVLSVFTNGL VLVATARFKK LRHPLNWILV P.bifurca|LWSR MAEDWGKQAF APWKNNEETT RGSAFTYTNS NHTRDPFEGP NYHIAPRWVY NITTVWMCFV VVLSVFTNGL VLVATARFKK LRHPLNWILV P.parae|LWSR MAEDWGKQAF APWKNNEETT RGSAFTYTNS NHTRDPFEGP NYHIAPRWVY NITTVWMCFV VVLSVFTNGL VLVATARFKK LRHPLNWILV P.picta|LWSR MAEDWGKQAF APWKNNEETT RGSAFTYTNN NHTRDPFEGP NYHIAPRWVY NISTVWMCFV VVLSVFTNGL VLVATARFKK LRHPLNWILV P.reticulata|LWSR MAEDWGKQAF APWKNNEETT RGSAFTYTNS NHTRDPFEGP NYHIAPRWVY NITTVWMCFV VVLAVFTNGL VLVATARFKK LRHPLNWILV P.wingei|LWSR MAEDWGKQAF APWKNNEETT RGSAFTYTNS NHTRDPFEGP NYHIAPRWVY NITTVWMCFV VVLAVFTNGL VLVATARFKK LRHPLNWILV

91 101 111 121 131 141 151 161 171 V

X.helleri|LWS1 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTIISWERWI VVCKPFGNVK FDAKWATAGIVFSWVWSAAW H.formosa|LWS1 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTIISWERWI VVCKPFGNVK FDAKWATAGIVFSWVWSAVW P.caymanensis|LWS1 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAVW P.vittata|LWS1 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAVW P.nigrofasciatus|LWS1 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAVW P.mexicana|LWS1 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYIV STCGITALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAAW P.petenensis|LWS1 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGFIV STCGITALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAAW P.velifera|LWS1 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGFTV STCGITALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAAW P.latipinna|LWS1 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGFTV STCGITALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAAW P.minor|LWS1 NLAVADLGET VFASTISVCNQFFGYFILGH PMCVFEGFTV STCGIAALWS LTIISWERWV VVCKPFGNVK FDAKWATAGIVFSWVWSAAW P.bifurca|LWS1 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYTV STCGIAALWS LTIISWERWV VVCKPFGNVK FDEKWATAGIVFSWVWAAAW P.parae|LWS1 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYTV STCGIAALWS LTIISWERWV VVCKPFGNVK FDEKWATAGIVFSWVWSAAW P.picta|LWS1 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYTV STCGIAALWS LTIISWERWV IVCKPFGNVK FDEKWATAGIVFSWVWAAAW P.reticulata|LWS1 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAVW P.wingei|LWS1 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTIISWERWI VVCKPFGNVK FDAKWATAGIVFSWVWAAVW X.helleri|LWS2 NLAVADLGET VFASTISVCNQVFGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWERWI VVCKPFGNIK FDAMWATAGIVFSWVWPAVW H.formosa|LWS2 NLAIADLGET VFASTISVCNQIFGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWERWI VVCKPFGNVK FDARWATAGIAFSWVWPAVW P.caymanensis|LWS2 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWPAVW P.vittata|LWS2 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWPAVW P.nigrofasciatus|LWS2 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWDRWI VVCKPFGNVK FDAKWATGGILFSWVWPAVW P.mexicana|LWS2 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWPAVW P.petenensis|LWS2 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWPAVW P.velifera|LWS2 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWPAVW P.latipinna|LWS2 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWPAVW P.minor|LWS2 NLAIADLGET VFASTISVCNQFYGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWERWI VVCKPFGNVK FDAKWATGGILFSWVWSAVW P.bifurca|LWS2 NLAIADLGET VFASTISVCNQVFGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWERWI VVCKPFGNVK FDSKWATAGILFSWVWPAVW P.parae|LWS2 NLAIADLGET VFASTISVCNQVFGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWERWI VVCKPFGNVK FDSKWASAGILFSWVWPAVW P.picta|LWS2 NLAIADLGET VFASTISVCNQVFGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWERWI VVCKPFGNVK FDSKWATAGILFSWVWPAVW P.reticulata|LWS2 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWERWI VVCKPFGNVK FDAKWATAGILFSWVWPAVW P.wingei|LWS2 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV SICGIAGLWS LTIISWERWI VVCKPFGNVK FDAKWATAGILFSWVWPAVW X.helleri|LWS3 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTIISWERWI VVCKPFGNVK FDAKWATAGIVFSWVWSAAW H.formosa|LWS3 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTIISWERWI VVCKPFGNVK FDAKWATAGIVFSWVWSAVW P.caymanensis|LWS3 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAVW P.vittata|LWS3 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAVW P.nigrofasciatus|LWS3 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAVW P.mexicana|LWS3 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGFIV STCGIAALWS LTIISWERWV VVCKPFGNVK FDAKWATGGIVFSWVWSAAW P.petenensis|LWS3 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGFVV STCGIAALWS LTIISWERWV VVCKPFGNVK FDAKWATGGIVFSWVWSAAW P.velifera|LWS3 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGFTV STCGITALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAAW P.latipinna|LWS3 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGFTV STCGITALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAAW P.minor|LWS3 NLAVADLGET VFASTISVCNQFFGYFILGH PMCVFEGFTV STCGIAALWS LTIISWERWV VVCKPFGNVK FDAKWATAGIVFSWVWSAAW P.bifurca|LWS3 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGFTV STCGIAALWS LTIISWERWV VVCKPFGNVK FDEKWATAGIVFSWVWSAAW P.parae|LWS3 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGFTV STCGIAALWS LTIISWERWV VVCKPFGNVK FDEKWATAGIVFSWVWSAAW P.picta|LWS3 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGFTV STCGIAALWS LTIISWERWV VVCKPFGNVK FDEKWATAGIVFSWVWSAAW P.reticulata|LWS3 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGFVV STCGIAALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAAW P.wingei|LWS3 NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGFVV STCGIAALWS LTIISWERWI VVCKPFGNVK FDAKWATGGIVFSWVWSAAW X.helleri|LWSR NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYIV STCGIAALWS LTVISWERWI VVCKPFGNTK FDAKWATAGIMFSWVWSAVW H.formosa|LWSR NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTVISWERWI VVCKPFGNTK FDAKWATAGIMFSWVWSAVW P.caymanensis|LWSR NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTVISWERWI VVCKPFGNTK FDAKWATAGIAFSWVWSAVW P.vittata|LWSR NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTVISWERWI VVCKPFGNTK FDAKWATAGIAFSWVWSAVW P.nigrofasciatus|LWSR NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTVISWERWI VVCKPFGNTK FDAKWATAGIAFSWVWSAVW P.mexicana|LWSR NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTVISWERWI VVCKPFGNTK FDAKWATAGIVFSWVWSAVW P.petenensis|LWSR NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTVISWERWI VVCKPFGNTK FDAKWATAGIVFSWVWSAVW P.velifera|LWSR NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTVISWERWI VVCKPFGNTK FDAKWATAGIVFSWVWSAVW P.latipinna|LWSR NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTVISWERWI VVCKPFGNTK FDAKWATAGIVFSWVWSAVW P.minor|LWSR NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGITALWS LTVISWERWI VVCKPFGNTK FDAKWATAGIVFSWVWSAVW P.bifurca|LWSR NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTVISWERWI VVCKPFGNTK FDAKWATAGIVFSWVWSAVW P.parae|LWSR NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYIV STCGIAALWS LTVISWERWI VVCKPFGNTK FDAKWAAAGIVFSWVWSAVW P.picta|LWSR NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTVISWERWI VVCKPFGNTK FDAKWATGGIVFSWVWSAVW P.reticulata|LWSR NLAIADLGET VFASTISVCNQSFGYFILGH PMCVFEGYVV STCGIAALWS LTVISWERWI VVCKPFGNTK FDAKWAAAGIMFSWVWSAVW P.wingei|LWSR NLAIADLGET VFASTISVCNQFFGYFILGH PMCVFEGYVV STCGIAALWS LTVISWERWI VVCKPFGNTK FDAKWAAAGIMFSWVWSAVW Key:

181 191 201 211 221 231 241 251 261 Known LWS tuning site

X.helleri|LWS1 CAPPIFGWSR YWPHGLKTSC GPDVFSGSED PGVQSYMVVL MITCCIIPLA IIILCYLAVW LAIHAVAMQQ KESESTQKAE KEVSRMVVVM Transmembrane region H.formosa|LWS1 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MVTCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.caymanensis|LWS1 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.vittata|LWS1 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM Retinal binding pocket site P.nigrofasciatus|LWS1 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MSTCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM in bovine rhodopsin P.mexicana|LWS1 CAPPVFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.petenensis|LWS1 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.velifera|LWS1 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM V Key tuning site with P.latipinna|LWS1 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM variable AA P.minor|LWS1 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.bifurca|LWS1 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.parae|LWS1 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.picta|LWS1 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.reticulata|LWS1 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIHAVAMQQ KESESTQKAE REVSRMVVVM P.wingei|LWS1 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM X.helleri|LWS2 CSPPIFGWSR YWPHGLKTSC GPDVFSGSED PGVQSYMIVL IVTCCLIPLS IIILCYLAVW LAIHAVAMQQ LDSETTQKAE REVTRMVVVM H.formosa|LWS2 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVQSYMIVL MVTCCIIPLS IIILCYLAVW LAIRAVAMQQ LDSESTQKAE REVSRMVVVM P.caymanensis|LWS2 CAPPIFGWSR YWPHGLKTSC GPDVFSGNED PGVQSYMIVL MITCCIIPLA IIILCYLAVW LAIRAIAMQQ LDSESTQKAE REVSRMVVVM P.vittata|LWS2 CAPPIFGWSR YWPHGLKTSC GPDVFSGNED PGVQSYMIVL MITCCIIPLA IIILCYLAVW LAIRAIAMQQ LDSESTQKAE REVSRMVVVM P.nigrofasciatus|LWS2 CAPPIFGWSR YWPHGLKTSC GPDVFSGNED PGVQSYMIVL MITCCIIPLA IIILCYLAVW LAIRAIAMQQ LDSESTQKAE REVSRMVVVM P.mexicana|LWS2 CAPPIFGWSR YWPHGLKTSC GPDVFSGNED PGVQSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ LDSESTQKAE REVCRMVVVM P.petenensis|LWS2 CAPPIFGWSR YWPHGLKTSC GPDVFSGNED PGVQSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ LDSESTQKAE REVCRMVVVM P.velifera|LWS2 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ LDSESTQKAE REVCRMVVVM P.latipinna|LWS2 CAPPIFGWSR YWPHGLKTSC GPDVFSGNED PGVQSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ LDSESTQKAE REVCRMVVVM P.minor|LWS2 CAPPIFGWSR YWPHGLKTSC GPDVFSGNED PGIQSYMIVL VITCCIIPLS IIILCYLAVW LAIRSVAMQQ LDSESTQKAE REVSRMVVVM P.bifurca|LWS2 CAPPIFGWSR YWPHGLKTSC GPDVFSGSED PGVQSYMMVL IITCCFIPLA IIILCYLAVW LAIRAVAMQQ LDSESTQKAE REVSRMVVVM P.parae|LWS2 CAPPIFGWSR YWPHGLKTSC GPDVFSGSED PGVQSYMIVL IITCCIIPLA IIILCYLAVW LAIRAVAMQQ LDSESTQKAE REVSRMVVVM P.picta|LWS2 CAPPIFGWSR YWPHGLKTSC GPDVFSGSED PGVQSYMIVL IITCCLIPLA IIILCYLAVW LAIRAVAMQQ LDSESTQKAE REVSRMVVVM P.reticulata|LWS2 CAPPIFGWSR YWPHGLKTSC GPDVFSGSED PGVQSYMIVL MITCCIIPLS IIILCYLAVW LAIRAVAMQQ LDSESTQKAE REVSRMVIVM P.wingei|LWS2 CAPPIFGWSR YWPHGLKTSC GPDVFSGSED PGVQSYMIVL VITCCIIPLS IIILCYLAVW LAIRAVAMQQ LDSESTQKAE REVSRMVIVM X.helleri|LWS3 CAPPIFGWSR YWPHGLKTSC GPDVFSGSED PGVQSYMVVL MITCCIIPLA IIILCYLAVW LAIHAVAMQQ KESESTQKAE KEVSRMVVVM H.formosa|LWS3 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MVTCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.caymanensis|LWS3 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.vittata|LWS3 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.nigrofasciatus|LWS3 CAPPIFGWSR YWPHGLKTSC GPDVFSGNED PGVLSYMIVL MSTCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.mexicana|LWS3 CAPPIFGWSR FWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLG IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.petenensis|LWS3 CAPPIFGWSR FWPHGLKTSC GPDVFSGSED PGVLSYMIVL MITCCIIPLG IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.velifera|LWS3 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.latipinna|LWS3 CAPPIFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.minor|LWS3 CAPPVFGWSR YWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.bifurca|LWS3 CAPPIFGWSR FWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCFIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.parae|LWS3 CAPPIFGWSR FWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCFIPLA IIILCYLAVW LAIRAVAMQQ KESESTQKAE REVSRMVVVM P.picta|LWS3 CAPPIFGWSR FWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW MAIRAVAMQQ KESESTQKAE REVSRMVVVM P.reticulata|LWS3 CAPPIFGWSR FWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLG IIILCYLAVW LAIHAVAMQQ KESESTQKAE REVSRMVVVM P.wingei|LWS3 CAPPIFGWSR FWPHGLKTSC GPDVFSGSDD PGVLSYMIVL MITCCIIPLA IIILCYLAVW LAIHAVAMQQ KESESTQKAE REVSRMVVVM X.helleri|LWSR CAPPVFGWSR YWPHGLKTSC GPDVFSGSED AGVKSYMIVL MITCCIIPLA VIILCYLAVW LAIRDIAMQQ KECESTQNAQ KEVSRMVVVM H.formosa|LWSR CAPPLFGWSR YWPHGLKTSC GPDVFSGSED PGVKSYMIVL MVTCCIIPLA VIILCYLAVW LAIRDIAMQQ KECESTQNAQ KEVSRMVVVM P.caymanensis|LWSR CAPPVFGWSR YWPHGLKTSC GPDVFSGSEE PGVKSYMIVL MITCCITPLA VIVLCYLAVW LAIRDIAMQQ KECESTQNAQ KEVSRMVVVM P.vittata|LWSR CAPPVFGWSR YWPHGLKTSC GPDVFSGSEE PGVKSYMIVL MITCCITPLA VIVLCYLAVW LAIRDIAMQQ KECESTQNAQ KEVSRMVVVM P.nigrofasciatus|LWSR CAPPVFGWSR YWPHGLKTSC GPDVFSGSEE PGVKSYMIVL MITCCITPLA VIVLCYLAVW LAIRDIAMQQ KECESTQNAQ KEVSRMVVVM P.mexicana|LWSR CAPPVFGWSR YWPHGLKTSC GPDVFSGSED PDVKSYMIVL MITCCVTPLA VIVLCYLAVW LAIRDIAMQQ KECESTQNAQ KEVSRMVVVM P.petenensis|LWSR CAPPVFGWSR YWPHGLKTSC GPDVFSGSED PDVKSYMIVL MITCCVTPLA VIVLCYLAVW LAIRDIAMQQ KECESTQNAQ KEVSRMVVVM P.velifera|LWSR CAPPVFGWSR YWPHGLKTSC GPDVFSGSED PDVKSYMIVL MITCCVTPLA VIVLCYLAVW LAIRDIAMQQ KECESTQNAQ KEVSRMVVVM P.latipinna|LWSR CAPPVFGWSR YWPHGLKTSC GPDVFSGSED PDVKSYMIVL MITCCVTPLA VIVLCYLAVW LAIHDIAMQQ KECESTQNAQ KEVSRMVVVM P.minor|LWSR CAPPVFGWSR YWPHGLKTSC GPDVFSGSED PGVKSYMIVL MITCCVAPLA VIVLCYLAVW LAIRDIAMQQ KECESTQNAQ KEVSRMVVVM P.bifurca|LWSR CAPPVFGWSR YWPHGLKTSC GPDVFSGSED PGVKSYMIVL MITCCVIPLA VIVLCYLAVW LAISDIDMQQ KECESTQNAQ KEVSRMVVVM P.parae|LWSR CAPPVFGWSR YWPHGLKTSC GPDVFSGSED PGVKSYMIVL MITCCVIPLA VIVLCYLAVW LAIRDIAMQQ KECESTQNAQ KEVSRMVVVM P.picta|LWSR CAPPVFGWSR YWPHGLKTSC GPDVFSGSED PGVKSYMIVL MITCCIIPLA VIFLCYLAVW LAIRDIAMQQ KECESTQNAQ KEVSRMVVVM P.reticulata|LWSR CAPPVFGWSR YWPHGLKTSC GPDVFSGSED PGVKSYMIVL MITCCITPLA VIILCYLAVW LAIRDIAMQQ KECESTQNAQ KEVSRMVVVM P.wingei|LWSR CAPPVFGWSR YWPHGLKTSC GPDVFSGSED PGVKSYMIVL MITCCITPLA VIILCYLAVW LAIRDIAMQQ KECESTQNAQ KEVSRMVVVM

271 281 291 301 311 321 331 341 351 V

X.helleri|LWS1 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX H.formosa|LWS1 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.caymanensis|LWS1 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.vittata|LWS1 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.nigrofasciatus|LWS1 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.mexicana|LWS1 IVAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.petenensis|LWS1 IVAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.velifera|LWS1 IVAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.latipinna|LWS1 IVAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.minor|LWS1 ILAYCVCWGP YTFFACFAAA NPGYALHPLA AAMPAYFAQS APIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.bifurca|LWS1 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.parae|LWS1 ILAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQGDD GSEVSTSKTE VSSGAPAX P.picta|LWS1 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.reticulata|LWS1 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.wingei|LWS1 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX X.helleri|LWS2 ILAFCLCWGP YATFACFAAA NPGYAFHPLA AAIPAYLAKS ATIYNPVIYVFMNRQFRTCI MKLLGKETDD DSEVSTSKTE VSSVAPEX H.formosa|LWS2 ILAFCLCWGP YASFACFAAA NPGYAFHPLA ASIPAYLAKS ATIYNPVIYVFMNRQFRTCI MKLFGKEMDD DSEVSTSKTE VSSVAPEX P.caymanensis|LWS2 ILAFCLCWGP YATFACFAAA IPGYAFHPLA AAVPAYLAKS ATIYNPVIYVFMNRQFRTCI MKLFGKQMDD DSEVSTSKTE VSSVAPEX P.vittata|LWS2 ILAFCLCWGP YATFACFAAA NPGYAFHPLA AAVPAYLAKS ATIYNPVIYVFMNRQFRTCI MKLFGKQMDD DSEVSTSKTE VSSVAPEX P.nigrofasciatus|LWS2 ILAFCLCWGP YATFACFAAA NPGYAFHPLV AAMPAYLAKS APIYNPVIYVFMNRQFRTCI MKLFGKQMDD DSEVSTSKTE VSSVAPEX P.mexicana|LWS2 ILAFCLCWGP YATFACFAAA NPGYAFHPLA AAMPAYLAKS ATIYNPVIYVFMNRQFRTCI MKLFGKQMDD DSEVSTSKTE VSSVAPEX P.petenensis|LWS2 ILAFCLCWGP YATFACFAAA NPGYGFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MKLFGKQMDD DSEVSTSKTE VSSVAPEX P.velifera|LWS2 ILAFCLCWGP YATFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MKLFGKQMDD DSEVSTSKTE VSSVAPEX P.latipinna|LWS2 ILAFCLCWGP YATFACFAAA NPGYGFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MKLFGKQMDD DSEVSTSKTE VSSVAPEX P.minor|LWS2 ILAFCLCWGP YATFACFAAA NPGYAFHPLA AAIPAYLAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD DSEVSTSRTE VSSVAPEX P.bifurca|LWS2 ILAFCLCWGP YATFACFAAA NPGYAFHPLA AAIPAYLAKS ATIYNPVIYVFMNRQFRTCI MKLFGKQMDD DSEVSTSKTE VSSVAPEX P.parae|LWS2 ILAFCLCWGP YATFACFAAA NPGYAFHPLA AAIPAYLAKS ATIYNPVIYVFMNRQFRTCI MKLFGKQMDD DSEVSTSKTE VSSVAPEX P.picta|LWS2 ILAFCLCWGP YATFACFAAA NPGYAFHPLA AAIPAYLAKS ATIYNPVIYVFMNRQFRTCI MKLFGKQMDD DSEVSTSKTE VSSVAPEX P.reticulata|LWS2 ILAFCLCWGP YATFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MRLFGKQMDD DSEVSTSKTE VSSVAPEX P.wingei|LWS2 ILAFCLCWGP YATFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MRLFGKQMDD DSEVSTSKTE VSSVAPEX X.helleri|LWS3 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX H.formosa|LWS3 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEMSTSKTE VSSVAPAX P.caymanensis|LWS3 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.vittata|LWS3 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.nigrofasciatus|LWS3 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRRCI MQLFGKQVED GSEVSTSKTE VSSVAPAX P.mexicana|LWS3 IVAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.petenensis|LWS3 IVAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.velifera|LWS3 IVAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.latipinna|LWS3 IVAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.minor|LWS3 ILAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQGDD GSEVSTSKTE VSSVAPAX P.bifurca|LWS3 IVAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPIIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.parae|LWS3 IVAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPIIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.picta|LWS3 IVAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPIIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.reticulata|LWS3 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX P.wingei|LWS3 IIAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MQLFGKQVDD GSEVSTSKTE VSSVAPAX X.helleri|LWSR ILAYCICWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATVYNPVIYVFMNRQFRTCI MQLFGKEVDD GSEVSTSKTE VSSIAPEX H.formosa|LWSR ILAYCICWGP YTVFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFCTCI MRLFGREVDD GSEVSTSKTE VSSVAPAX P.caymanensis|LWSR ILAFCVCWGP YAFVACFAAA NPGYAFHPLA AAIPAYFAKS ATIYNPVIYVFMNRQFRTCI MRLFGKEVDD GSEVSTSKTE ISSVAPEX P.vittata|LWSR ILAFCVCWGP YAFVACFAAA NPGYAFHPLA AAIPAYFAKS ATIYNPVIYVFMNRQFRTCI MRLFGKEVDD GSEVSTSKTE ISSVAPEX P.nigrofasciatus|LWSR ILAFCVCWGP YAFVACFAAA NPGYAFHPLA AAIPAYFAKS ATIYNPVIYVFMNRQFRTCI MRLFGKEVDD GSEVSTSKTE ISSVAPEX P.mexicana|LWSR ILAFCVCWGP YAFFACFAAA NPGYAFHPLA AAIPAYFAKS ATIYNPVIYVFMNRQFRTCI MRLFGKEVDD GSEVSTSKTE VSSVAPEX P.petenensis|LWSR ILAFCVCWGP YAFFACFAAA NPGYAFHPLA AAIPAYFAKS ATIYNPVIYVFMNRQFRTCI MRLFGKEVDD GSEVSTSKTE VSSVAPEX P.velifera|LWSR ILAFCVCWGP YAFFACFAAA NPGYAFHPLA AAIPAYFAKS ATIYNPVIYVFMNRQFRTCI MRLFGKEVDD GSEVSTSKTE VSSVAPEX P.latipinna|LWSR ILAFCVCWGP YAFFACFAAA NPGYAFHPLA AAIPAYFAKS ATIYNPVIYVFMNRQFRTCI MRLFGKEVDD GSEVSTSKTE VSSVAPEX P.minor|LWSR ILAYCVCWGP YTLFACFAAA NPGYAFHPLA AALPAYFAKS ATIYNPVIYVFMNRQFRTCI MRLFGKEVDD GSEVSTSKTE VSSVAPEX P.bifurca|LWSR ILAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MRLFGKEVDD SSEVSTSKTE VSSVAPEX P.parae|LWSR ILAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MRLFGKEVDD GSEVSTSKTE VSSVAPEX P.picta|LWSR ILAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MRLFGKEVDD GSEVSTSKTE VSSVAPEX P.reticulata|LWSR ILAYCVCWGP YTFFACFAAA NPGYAFHPLA AAMPAYFAKS ATIYNPVIYVFMNRQFRTCI MRLFGKEVDD GSEVSTSKTE VSSVAPEX FigureP.wingei LWSR 2ILAY.CVCW6GP. YT FFACFAAA AminoNPGYAFHPLA AAMPAYFAKS AacidTIYNPVIYVFMNR QFalignmentRTCI MRLFGKEVDD GSEVSTSKTE VSSVAP EXof LWS.

O. latipes

X. helleri

P. caymanensis 1 P. vittata 0.99 P. nigrofasciata

0.68 P. petenensis

1 P. velifera 0.47 P. latipinna 0.78 0.99 P. mexicana

P. minor 0.93 P. bifurca 0.98 P. parae 0.9 P. picta 0.4 0.97 P. reticulata 1 P. wingei

H. formosa 0.3 Figure 2.7. ND2 mitochondrial bayesian consensus tree with posterior probabilities. Outgroup is Oryzias latipes.

X. helleri

P. minor

8.0E-4 0.93 P. nigrofasciata

1 P. vittata 1 1 0.98 P. caymanensis

P. latipinna 1 P. velifera 1 P. mexicana 0.90 0.58 H. formosa

P. picta 1 1 P. bifurca 1 P. parae 0.72 P. petenensis

1 P. wingei 1 P. reticulata

O. latipes

Figure 2.8. Bayesian consensus tree with posterior probabilities of SWS1. Outgroup is Oryzias latipes.

Figure 2.9. Bayesian consensus tree with posterior probabilities of SWS2A and SWS2B. Outgroup is Oryzias latipes.

O. latipes

X. helleri 0.50 H. formosa 1 P. bifurca 0.86 P. parae 1

1 P. picta

1 P. petenensis 1 P. wingei 1 P. reticulata

0.86 P. velifera 1 P. latipinna 1 P. mexicana

1 P. nigrofasciata

1 P. vittata 0.65 6.0E-4 1 P. caymanensis

P. minor

Figure 2.10. Bayesian consensus tree with posterior probabilities of RH1. Outgroup is Oryzias latipes.

P. latipinna 1 P. bifurca 1 P. velifera 1 P. mexicana 0.35 P. reticulata 1 P. petenensis 1

0.36 P. wingei P. minor

0.66 P. caymanensis 0.54 1

1 P. vittata P. nigrofasciata

0.0030 1 P. parae 1 P. picta

0.78 X. helleri 1 H. formosa

1 O. latipes A 1 O. latipes B

O. latipes C

Figure 2.11. Bayesian consensus tree with posterior probabilities of RH2-1. Outgroup is Oryzias latipes.

Figure 2.12. Bayesian consensus trees with posterior probabilities of (A) LWS UTR sequence, and (B) LWS full sequences. Outgroup is Oryzias latipes. Note the expected duplication history recovered in UTR sequence and general species relationships (based on ND2 tree) recovered within clades except for LWS-1 and LWS-3 of the full LWS tree.

Figure 2.13. (A) The genomic organization of the LWS opsin loci in P. wingei (adopted from Watson et al. (2011)). (B) The proposed conformation leading to high rates of gene conversion between LWS-1 and LWS-3 in the event of a double strand break. Arrows denote directionality. Coloured boxes denote exons while spaces between boxes denote introns.

Supplementary Figure 2.1. Bayesian consensus tree with posterior probabilities of exon only sequence from all opsins. Outgroup is Oryzias latipes.

Supplementary Table 2.1. PCR primer sequences.

LWS2 LWS2 LWS1 (Piece (Piece LWS3 LWSR SWS1 SWS2A SWS2B RH1 RH2-1 Primer Sequence Species 1) 2) For Rev For Rev For Rev For Rev For Rev For Rev For Rev For Rev For Rev For Rev 1 TGTGAAGTGCAGATCACCTAG

Poecilia nigrofasciatis 1 2 6 7 8 9 11 12 16 17 18 19 20 21 22 23 24 25 28 29 2 CTTCATAAACAGAGAACATGAAGG Poecilia vittata 1 3 6 7 8 9 11 12 16 17 18 19 20 21 22 23 26 27 28 29 3 AGAATTTGTTTTCTCCCAGCC Pamphorichthys minor 1 4 6 7 8 10 13 12 16 17 18 19 20 21 22 23 26 27 28 29 4 GTTACACATTCATGCATGATGC Poecilia caymanensis 1 3 6 7 8 9 14 15 16 17 18 19 20 21 22 23 26 27 28 29 5 ACACATTCATGCATGATGCAG Heterandrai formosa 1 3 6 7 8 9 11 12 16 17 18 19 20 21 22 23 26 27 28 29 6 CCCAGCAAAACTCTCAAGGT Peocilia parae 1 5 6 7 8 9 13 12 16 17 18 19 20 21 22 23 26 27 28 29 7 GCAAAGACTGTCTCTCCAAGATC Poecilia picta 1 3 6 7 8 9 13 12 16 17 18 19 20 21 22 23 26 27 28 29 8 GATCCCTTTGAAGGACCAAACT Poecilia bifurca 1 3 6 7 8 9 13 12 16 17 18 19 20 21 22 23 26 27 28 29 9 CAGTCCCGGCAGTAATAACAAAC Poecilia latipinna 1 3 6 7 8 9 11 12 16 17 18 19 20 21 22 23 26 27 28 29 10 GGTAATACAATGCAAAAGTTCCATC Poecilia reticulata 1 5 6 7 8 9 13 12 16 17 18 19 20 21 22 23 26 27 28 29 11 CCCAGCAAACGCAGAAGGTTATAAG Poecilia petenensis 1 3 6 7 8 9 11 12 16 17 18 19 20 21 22 23 26 27 28 29 12 GTAGCACTCAAAATACTTTCAGTAC

Poecilia mexicana 1 3 6 7 8 10 11 12 16 17 18 19 20 21 22 23 26 27 28 29 13 GATAAGCGTTGGTATATAAGGAG Poecilia velifera 1 3 6 7 8 9 13 12 16 17 18 19 20 21 22 23 26 27 28 29 14 GGTGAAGCACCCAGCAAACG Poecilia wingei ------18 19 - - - - 26 27 28 29 15 CATTTGCCATAAAGTTTCCGTTTATC Xiphophorous helleri ------18 19 - - - - 26 27 28 29 16 CCACAAGGTTACAAGCCAGAG 17 TGCATTGACACATCCATGAGTTC

18 GTCCATCATCATCTTCTCCT 19 AGTTGGCGTACCAGAGG

20 ATGTTTTAGATTTGGACTTGGTG 21 GCAGAATGTTGCTAAGTTGTTC 22 CGTATTTAATCATCCAGTCTAG 23 GCAGATGTGCTACATGCATT

24 CAACCATGAATGGCACAGAG 25 CTCGGTCTTGGAAGCAGTAG 26 CTGTGGCCTAAATCAATTTGTGC

27 AAGCCAGTATCATATAGGATCC 28 GAGTGTAGGATTGGCATTTACCA 29 TTGCACGCGTAACCAGATGA

Supplementary Table 2.2. GenBank accession numbers of ND2 sequences used to identify species relationships.

Species ND2 GeneBank Accession Poecilia nigrofasciatis AF031391.1 Poecilia vittata AF353201.1 Poecilia minor GU179242.1 Poecilia caymanensis AF353192.1 Heterandria formosa AF084973.1 Poecilia parae GU179235.1 Poecilia picta GU179237.1 Poecilia bifurca GU179232.1 Poecilia latipinna AF031389.1 Poecilia reticulata AF031394.1 Poecilia petenensis AF031401.1 Poecilia mexicana AF080488.1 Poecilia velifera AF031402.1 Poecilia wingei AY249318.1 Xiphophorous helleri FJ226476.1 Oryzias latipes AP004421.1

Chapter 3.

Hybridization leads to sensory repertoire expansion in a gynogenetic fish, the Amazon molly (Poecilia formosa): a test of the hybrid-sensory expansion hypothesis

Publication and Contributions

A version of this chapter is published as: Sandkam, B. A., Joy, J. B., Watson, C. T., Gonzalez-Bendiksen, P., Gabor, C. R. and Breden, F. (2013), Hybridization leads to sensory repertoire expansion in a gynogenetic fish, the Amazon Molly (Poecilia formosa): a test of the hybrid sensory expansion hypothesis. Evolution, 67: 120–130. doi: 10.1111/j.1558-5646.2012.01779.x

Contributions: BAS, JBJ, CTW and FB conceived and designed the project. BAS performed all sequencing and analyses. BAS and JBJ built phylogenies and drafted early versions of the manuscript. GBP and CRG ran all behavioural trials.

3.1. Abstract

Expansions in sensory systems usually require processes such as gene duplication and divergence, and thus evolve slowly. We evaluate a novel mechanism leading to rapid sensory repertoire expansion: hybrid-sensory expansion (HSE). HSE occurs when two species with differently tuned sensory systems form a hybrid, bringing together alleles from each of the parental species. In one generation a sensory repertoire is created that is the sum of the variance between parental species. The Amazon molly presents a unique opportunity to test the HSE hypothesis in a “frozen” hybrid. We compared opsin sequences of the Amazon molly, Poecilia formosa, to those of the parental species. Both parental species are homozygous at the RH2-1 locus and

each of the four LWS loci, while P. formosa possess two different alleles at these loci; one matching each parental allele. Gene expression analysis showed P. formosa use the expanded opsin repertoire that was the result of HSE. Additionally, behavioural tests revealed P. formosa respond to coloured stimuli in a manner similar or intermediate to the parental species P. mexicana and P. latipinna. Together these results strongly support the HSE hypothesis. Hybrid sensory repertoire expansion is likely important in other hybrid species and in other sensory systems.

3.2. Introduction

The evolution of sensory systems is generally driven by selection acting upon variation arising through gradual intragenomic processes such as mutation, gene duplication, and recombination (Horth 2007). More rarely, novel variation in sensory systems could also arise through more rapid intergenomic processes such as hybridization, although empirical evidence for such a process has not yet been demonstrated.

We suggest that hybridization, a previously unexplored mechanism behind sensory repertoire expansion, could act to rapidly combine variation accumulated in two different genomes, often from different environments, into a single organism. By bringing together variation from two organisms in one mating event, hybridization expands the sensory repertoire much more quickly than more traditional models of duplication and divergence. We term this process the hybrid-sensory expansion (HSE) hypothesis (outlined in Box 3.1). A diploid F1 hybrid receives one allele of each sensory locus from both parental species (Dowling and Secor 1997; Lampert and Schartl 2008). The HSE hypothesis predicts that if the parental species’ sensory repertoires are differentially tuned, then the sensory repertoire of the hybrid will be different than that of either parental species. When a hybrid species possesses a sensory repertoire which is a combination of the variation present in the two parental species, selection may act on that variation. When a hybrid lives in a similar selective environment to the parental species, selection is likely to maintain the sensory repertoire to be more similar to either or both of the parental species, which could impact hybrid fitness.

The sensory repertoires of species capable of colour vision are often tuned to take advantage of their specific spectral environments (Carleton and Kocher 2001; Fuller et al. 2005; Endler et al. 2005). Colour vision is mediated via cone cells in the retina of the eye (Loew and Lythgoe 1978). The peak spectral sensitivity (λmax) of a cone cell is determined by its visual pigment, consisting of a chromophore coupled with a transmembrane protein called an opsin, which is maximally sensitive to a specific wavelength of light (Yokoyama 2000, 2002). The fishes in the family Poeciliidae possess excellent colour vision (Schwanzara 1967; Houde 1987; Anstis et al. 1998; Grether et al. 2005) and have undergone extensive gene duplication and subsequent differentiation in their long wavelength sensitive (LWS) opsin genes. Thus, some poeciliid species possess the largest known opsin repertoire among vertebrates (Hoffmann et al. 2007; Windsor and Owens 2009; Watson et al. 2011).

The Amazon molly (Poecilia formosa) is a member of the Poeciliidae family and is the result of a hybridization event between a female P. mexicana and male P. latipinna (Hubbs and Hubbs 1932; Avise et al. 1991; Schartl et al. 1995) that likely occurred once about 120,000 years ago (Stöck et al. 2010). Poecilia formosa reproduce through gynogenesis (Kallman 1962; Schlupp 2005), a form of clonal reproduction in which a diploid egg is created through mitosis. During this process the development of the egg is triggered by the presence of sperm from a sexual species. However, the sperm’s genetic material is almost never incorporated into the egg (Beukeboom and Vrijenhoek 1998; Schlupp and Riesch 2011). This unusual form of reproduction has led some people to call P. formosa “frozen F1s” (Vrijenhoek 1979), because they are predicted to still possess full haploid genomes from each parental species. Previous work on the cone cells of the parental species P. mexicana and P. latipinna show that they are tuned to different wavelengths of light in ranges characteristic of the RH2-1/LWS class of opsins, while the cone cells of P. formosa span the range of the parental species (Körner et al. 2006). Both of these classes of opsins function in the cone cells to provide photopic (colour) vision. While RH2-1 typically detects greens and yellows, the LWS opsins detect greens, yellows, reds, and oranges (Yokoyama et al. 2008). The maintenance of the “F1 genotype” together with the potential of an expanded opsin repertoire makes specific predictions about the sensory repertoire of P. formosa allowing a formal evaluation of the HSE hypothesis.

We tested the HSE hypothesis by comparing RH2-1 and LWS opsin sequences of P. formosa to those of its parental species, P. mexicana and P. latipinna. The HSE hypothesis predicts that P. formosa RH2-1 and LWS opsin alleles should be more similar to one of the parental species (P. mexicana or P. latipinna) than they would be to each other, and that this combination of diverged parentally-derived opsins would result in a unique, differentially tuned sensory system. We compared genomic sequence of RH2-1 and the four LWS opsins to evaluate our hypothesis that there is an expanded RH2-1/LWS opsin repertoire in P. formosa due to one chromosome coming from the maternal ancestor, P. mexicana and the other chromosome coming from the paternal ancestor, P. latipinna. To verify that the hybrid species utilizes its expanded opsin repertoire we identified which of the opsin alleles were being expressed in the eyes of P. formosa. In addition, we identified behavioural differences in response to colour stimuli between P. formosa across these three species. We conclude by interpreting our findings of expanded opsin repertoire, expression profiles, and behavioural differences as support for the HSE hypothesis in light of experimental data on spectral tuning of cone cells in P. formosa and its parental species (Körner et al. 2006).

3.3. Materials and Methods

3.3.1. Sample Preparation, PCR, Cloning and Sequencing

DNA was extracted from tissue samples of single specimens of P. mexicana, P. latipinna and P. formosa from natural populations using a DNeasy blood and tissue kit (QIAGEN). Primers specific to 5’ and 3’ UTR regions of each of the four LWS loci were designed using genomic data from Poecilia reticulata (Watson et al. 2011; GenBank Accession: HM540108 and HM540107) and Xiphophorous hellerii (Watson et al. 2010; GenBank Accession: GQ999832 and GQ999833). Primers were also designed in the 5’ and 3’ UTR regions of an RH2-1 transcript from P. reticulata (Hoffmann et al. 2007; GenBank Accession: DQ234859). Given the high exon sequence similarity between LWS loci we designed all primers to be locus specific (for a list of primers used and their sequences see Supplemental Table 3.1). The LWS opsins in the Poeciliidae family have previously been identified by amino acids at position 180 of the protein, because this site

is known to dramatically influence the λmax of LWS opsins (Yokoyama and Radlwimmer 1998), and has been shown to differ between LWS loci in Poecilia reticulata and the sister taxa in the subgenus, Micropoecilia (Ward et al. 2008). However, this nomenclature becomes confusing when describing poeciliids outside of this clade, as several species have multiple loci with the ‘S180’ genotype (Watson et al. 2010; this study; Sandkam unpublished data). To avoid confusion between species, we refer to LWS loci by their location in the genome relative to one another: LWS-1 (previously A180 or S180-1), LWS-2 (previously P180), LWS-3 (previously S180 or S180-2), and LWS-R (because it is the result of a retrotransposition event) (previously S180r) (Ward et al. 2008; Watson et al. 2010, 2011; Laver and Taylor 2011). Due to the length of LWS-2, PCR products for this gene were generated in two overlapping segments. To maintain locus specificity for these segments we amplified each with internal and external primers. LWS-3 and the second segment of LWS-2 each had two primer sets designed for them; one specific to P. latipinna and one specific to P. mexicana.

PCR products generated from P. formosa DNA were cloned prior to sequencing to ensure P. mexicana and P. latipinna derived alleles were sequenced and analyzed separately. PCR products were cloned into One Shot® chemically competent TOP10 E. coli cells using a TOPO TA Cloning® kit with pCR®2.1-TOPO® vector (Invitrogen®). Plasmid DNA was isolated from overnight cultures using the QIAprep® miniprep kit (QIAGEN). All sequencing was performed by Molecular Cloning Laboratories (McLab; San Francisco, CA, USA). Sequence chromatograms were viewed and analyzed using SeqMan Pro (Lasergene 8.0; DNASTAR). All sequences are available on GenBank; accession numbers JF823551 - JF823570.

3.3.2. Phylogenetic Analyses

All phylogenetic analyses were performed separately on the RH2-1 and LWS classes of genes, because the divergence of these opsin subfamilies pre-dates the Poeciliidae; as a result, many gene regions within the RH2 and LWS genes are highly diverged and cannot be aligned (Rennison et al. 2011). Sequences for each group of loci were aligned using Mafft v6.833b (Katoh et al. 2009) and edited using Se-Al v2.0a11 (Rambaut 1996) to ensure intron-exon boundaries were consistent across LWS or RH2-

1 loci for each of the three species. Best-fit models of molecular evolution were determined using MrModelTest 3.04 (Nylander 2004). Phylogenetic trees were reconstructed under Maximum Likelihood (ML) using PAUP* 4.0b10 (Swofford 2003) and Bayesian methods as implemented in MrBayes 3.1.2 (Ronquist and Huelsenbeck 2003). Two runs utilizing four Markov chains (three heated and one cold) were run for 107 generations, with trees sampled every 1000 generations for the LWS loci and RH2- 1. Convergence was assessed using the standard deviation of the split frequencies between runs, and graphically using the program Tracer (Rambaut and Drummond 2007) and AWTY (Nylander et al. 2008). ML bootstrap values and Bayesian posterior probabilities were employed to assess support. Pair-wise nucleotide similarities within and between species were calculated for each locus using BLASTn (Zhang et al. 2000).

3.3.3. Determination of Alleles Expressed in a Hybrid Species

Both eyes from one individual of P. formosa were removed and placed into RNAlater (Life Technologies) immediately after being sacrificed in an overdose of MS- 222. Eyes were ground with a disposable pestle (VWR®) in 600 µL of TRIzol® reagent (Life Technologies) and homogenized in a Homogenizer Cartridge (Life Technologies). RNA was isolated using the TRIzol® Plus Purification System (Life Technologies) and subjected to an on-column PureLink® DNase treatment (Life Technologies) to ensure no DNA was present before generating cDNA. Reverse transcription was carried out using a MultiScribe Reverse Transcriptase™ kit (Life Technologies) with the addition of an RNase inhibitor (Life Technologies).

Using genomic data generated above, one PCR primer set was designed to be specific to each parental species for each locus (Supplemental Table 3.2). The primer sets for LWS-R did not work and so the same primer set used for genomic PCR was used. PCR products of locus RH2-1 and LWS-1 were sequenced directly, resulting in ‘clean’ single consensus sequences, without the presence of multiple peaks per base pair position in the chromatograms. A direct sequencing approach did not generate ‘clean’ sequence for LWS-2, LWS-3, and LWS-R therefore PCR products of these loci were cloned and sequenced following the methods described above. This approach did

yield ‘clean’ single consensus sequences. Sequences were visually compared to genomic sequences generated for each locus to confirm allele type.

3.3.4. Behavioural Response to Coloured Disks

Adult female P. latipinna and P. formosa were collected in 2011 from an introduced population (P. latipinna from Louisiana and Florida, (Brown 1953); and P. formosa from Brownsville, Texas (Hubbs et al. 1991)) in Spring Lake at the headwaters of the San Marcos River in Hays County, Texas (29.89˚N, 97.82˚W) and maintained in the lab for several months before testing. Allopatric adult female P. mexicana were collected in Campeche, Mexico in 2002 (19.14˚N, 90.50˚W). Testing individuals were maintained at 25˚C on a 14:10 h light:dark cycle with full spectrum UV lights (Rayon Lighting Group) and fed daily with Purina AquaMax 200 pellets supplemented with live brine shrimp. The spectrum and intensity of the lighting environment was not measured because all holding tanks were exposed to the same lighting.

To determine level of attraction to different colours, simultaneous choice tests were performed on individual fish by measuring the number of approaches toward and pecks at coloured discs following the methodologies of Rodd et al. (2002). The testing arena used was 61x51cm, filled to a depth of 15cm and lit overhead with full spectrum fluorescent lighting (Rayon Lighting Group). Black plastic covered three sides of the arena, the fourth was covered with one-way glass to minimize disturbance from the observer. Female P. mexicana (n = 17), P. formosa (n = 17), and P. latipinna (n = 15) were tested individually. All behavioural tests were performed at Texas State University.

Four clear plastic petri dishes (diameter 9.7cm) were randomly placed on the bottom of the tank and buried in gravel so that the lip of the dish formed a ring that could be seen by the observer and acted as an association zone with a coloured disk placed in the center. Coloured disks were made by painting pennies using Acrylic Colors (by Liquitex) either orange (Cadmium Orange Hue), yellow (Cadmium Yellow Hue), red (Naphthol Crimson), or green (Light Green). These were the same paints used by Rodd et al. 2002, which include reflectance spectra for each of the coloured disks. Preliminary trials revealed that individuals were reluctant to begin foraging unless food was present;

therefore a brown food pellet (AquaMax 200) was placed on top of each coloured disk to elicit foraging behaviour. The order in which the coloured disks were arranged was randomized for each trial. A focal individual was introduced to the aquarium and allowed 10 min to begin foraging; if they did not begin foraging they were returned to the holding tank to be tested at another time. A trial began when an individual began foraging and lasted 10 min, during which time the number of approaches (snout passes into the association zone) and number of pecks toward each coloured disk were recorded. To compare the raw number of pecks and approaches toward the different coloured disks we ran repeated measures ANOVAs followed by Tukey’s HSD in R 2.14.0 (R Core Development Team).

The presence of food on a disk at the start of a trial could impact the measured 'preference' (pecks at and approaches toward) the coloured disks. However, this is unlikely to be the case because it would be expected to lead to one of two scenarios: (a) an individual could be attracted to the coloured disk only to consume the food pellet- this would result in pecks/approaches toward all colours to be roughly equal, (b) an individual could be attracted to the first colour with food it comes across- this would result in the individual associating with/pecking at the first colour it comes across and would be random across individuals. Neither of these two scenarios was observed; individuals had clear preferences and species were similar in preference across individuals.

3.4. Results

3.4.1. Dataset

At each of the five loci (four LWS and one RH2-1) sequenced in P. formosa, we identified two alleles. For each locus, one allele was more similar to P. mexicana and thus labeled the ‘-M’ allele, and the other was more similar to P. latipinna and labeled the ‘-L’ allele (for RH2-1, ‘-L’ and P. latipinna are 100% identical). At every locus the P. formosa ‘-M’ allele and the P. formosa ‘-L’ allele differ from one another roughly as much as the P. mexicana allele differs from the P. latipinna allele (Table 3.1). Assuming equal rates of molecular change, this suggests that the P. formosa ‘-M’ allele and the P.

formosa ‘-L’ allele diverged at the same time as the P. mexicana allele and the P. latipinna allele, which is supported by our phylogenetic findings described below.

To assess functional opsin diversity we compared amino acid sequences between species for each locus. The RH2-1 amino acid sequences were identical between P. formosa, P. latipinna, and P. mexicana. However, the LWS loci demonstrated considerable amino acid diversity (Table 3.2). As expected, all variable parental opsin haplotypes were observed in the P. formosa LWS repertoire with the exception of novel amino acids at one position in LWS-1, 2 and 3, and two in LWS-R.

The λmax of the RH2/LWS classes of opsins are primarily determined by five specific amino acid changes that occur in the region of the protein spanning the membrane (Yokoyama and Radlwimmer 1998, 2001; Yokoyama et al. 2008). Of the novel amino acids identified in P. formosa, none were located at any of the five sites that determine the λmax of an opsin; therefore, the alleles gained from each of the parental species likely behave identically to the alleles in the parental species.

3.4.2. Phylogenetic Analysis

Phylogenetic trees inferred using ML and Bayesian methods converged upon identical topologies for both the RH2-1 and LWS opsin datasets. Support for recovered nodes was robust for all topologies inferred under both ML and Bayesian methods with no well-supported nodes differing among analyses. The fully resolved phylogenies of RH2-1 and LWS opsins are presented in Figure 3.1. For each locus the ‘-M’ and ‘-L’ alleles of P. formosa group with the respective alleles from P. mexicana and P. latipinna.

3.4.3. Determination of Alleles Expressed in a Hybrid Species

For four of the loci (LWS-1, LWS-3, LWS-R, and RH2-1) alleles from both parental species were expressed in the eyes of P. formosa. We were unable to detect the presence of LWS-2 transcripts in the eyes of P. formosa. This is not surprising given that recent work has shown LWS-2 to be expressed at very low levels in the closely related P. reticulata (Ward et al. 2008; Laver and Taylor 2011; Sandkam and Breden unpublished data). The LWS genomic organization of P. reticulata is identical to P.

formosa, which likely leads to similar patterns of relative LWS expression. If P. formosa relative LWS expression is similar to P. reticulata then it is possible that LWS-2 alleles from both parents are being expressed at such low levels that we were unable to detect either of them. Based on the absence of introns, we were able to verify that each sequence originated from cDNA.

3.4.4. Behavioural Response to Coloured Disks

The proportions of pecks at and approaches toward the different coloured disks are presented in Figure 3.2. The number of pecks made towards the green disks significantly differed between P. mexicana and P. latipinna (p=0.0331), but did not differ between P. formosa and P. latipinna (p=0.1279), or P. mexicana and P. formosa (p=0.8023). These data indicate that P. formosa exhibits a level of attraction to green disks that is intermediate between that observed for the two parental species. The intermediate attraction of P. formosa was also observed in the number of approaches toward green. In contrast, P. formosa had a greater number of pecks toward yellow disks than P. mexicana (p=0.0334) but not P. latipinna (p=0.2595), and the parental species also did not differ (p=0.6310). There were no significant differences between any of the species in approaches or pecks toward orange or red.

3.5. Discussion

3.5.1. Strong Evidence of HSE in Poecilia formosa

The phylogenetic analyses and pairwise sequence comparisons presented here clearly demonstrate that P. formosa possess one allele for every RH2-1 and LWS locus from each parental species, and these alleles differ from one another in amino acid sequence at several sites for the LWS opsins. Our expression analysis revealed that P. formosa simultaneously express alleles from both parental species at four out of the five loci we investigated (with no expression of either parental allele identified for locus LWS- 2).

Microspectrophotometry (MSP), a technique used to identify the peak spectral sensitivities (λmax) of a cone cell, further supports our evidence that P. formosa have experienced HSE in the RH2-1 and LWS opsins. Körner and colleagues used MSP in P. formosa, P. mexicana, and P. latipinna to show that the λmax values of the cone cells were virtually identical across all three species except for cones tuned to long wavelength light (i.e. RH2-1/LWS). The two cone types that differed in λmax absorbance between P. mexicana and P. latipinna fell in the range of the RH2-1 and LWS opsin classes (P. mexicana- 536.6 ± 4.7 nm and 563.0 ± 3.0 nm; P. latipinna 551.2 ± 4.9 and 576.7 ± 5.9 nm) (Körner et al. 2006). Distinct spectral peaks were not able to be determined in this range for P. formosa, although an average peak was reported at 560.3 ± 16.1 nm. MSP is performed by directing a monochromatic light source at an individual cone cell and changing the wavelength while measuring the amount of light absorbed (Loew and Lythgoe 1978). Specific absorbance peaks for cone cells are determined by averaging groups of similar absorbances; this procedure makes assigning cone types to groups difficult when cones have similar λmax values. Given that P. formosa have opsins that closely match the amino acid sequence of each of their parental species’ opsins (Table 3.2), and that our expression data show they are all expressed, the inability to determine a spectral peak in P. formosa is most likely the result of producing all of the parental opsin types in their cone cells. Because the parental species have cones with λmax values at 536.6 ± 4.7 and 563.0 ± 3.0 nm (P. mexicana) and 551.2 ± 5.9 and 576.7 ± 5.9 (P. latipinna) it is possible that the 560.3 ±

16.1 nm range in P. formosa is actually four cone types with λmax values at 536, 551, 563, and 576 nm. If one is to consider all P. mexicana and P. latipinna RH2-1/LWS cone types at once, the distance between the λmax plus the standard deviation of one cone and λmax minus standard deviation of the next highest cone is smaller than the standard deviations themselves; 4.0, 3.1, 4.8 nm between 536.6, 551.2, 563.0, and 576.7 nm respectively. Therefore, if all cone types from the parental species were present in the same eye the resulting λmax values would form a near-continuous distribution, which would be indistinguishable from one cone cell type with a λmax that has a high standard deviation, such as that reported for P. formosa. While it is clear that the additional opsin alleles are being used, it is also possible that P. formosa are expressing two opsin alleles per cone cell (functional implications will be discussed below).

Another possibility is that alleles of either P. latipinna or P. mexicana are acting in a dominant/recessive manner. Having dominant alleles from one parental species would result in P. formosa possessing a sensory system that matches one of the parental species. The data generated from the MSP study by Körner et al. (2006) clearly show that P. latipinna, P. mexicana, and P. formosa have dramatically different visual systems in the range of the LWS opsins, and thus that the LWS opsins are not acting in a dominant/recessive manner. Therefore, the LWS opsin alleles from one locus are either expressed in different cone cells (as discussed above), or in the same cone cell, and are acting in a co-dominant fashion. Either way, the RH2-1/LWS opsin repertoire is clearly expanded in P. formosa as a result of the hybridization of P. mexicana and P. latipinna. Thus, our results provide strong support for the hybrid-sensory expansion (HSE) hypothesis.

3.5.2. What Does HSE Mean For P. formosa Vision?

Vision is the detection of different wavelengths of light, whereas colour vision is the discrimination of different wavelengths of light. Adding photoreceptor pigments can expand the detectable spectral window and/or expand the ability to discriminate wavelengths (i.e. colour discrimination) (Jacobs et al. 1999). Colour discrimination is accomplished by comparing the signals from cone cells with different λmax. In normal colour vision each cone cell expresses only one opsin (Hagstrom et al. 2000), thereby maximally detecting only one wavelength of light. Because P. formosa are expressing two alleles at the same locus, it is possible that their cone cells have two wavelengths that they ‘maximally’ detect. Some New World primates are heterozygous for MWS/LWS opsin alleles but do not have this “problem” because their opsin locus is on the X chromosome, therefore only one allele is expressed per cell due to X-inactivation (Jacobs 1998). Mapping data and synteny comparisons of LWS opsin gene regions between the P. reticulata and Oryzias latipes genomes suggest that P. reticulata LWS opsin genes are not sex-linked (Tripathi et al. 2009; Watson et al. 2011). Given the close similarity between species in Poeciliidae (Breden et al. 1999; Hamilton 2001), it is likely that this is also true for P. formosa. However, it is not known whether multiple opsin genes are expressed in individual cone cells in fish retinas, or if some form of allelic exclusion exists.

Two studies by Jacobs et al. (1999, 2007) highlight possible implications of an expanded opsin repertoire. Jacobs et al. (2007) created a line of transgenic mice in which the cone cells either expressed an MWS opsin or an LWS opsin. The mice had an expanded range of wavelengths they could detect and were able to differentiate additional wavelengths of light. However, Jacobs et al. (1999) also created a line of transgenic mice with MWS and LWS opsins but had to co-express them in individual cone cells. The mice could detect an expanded range of wavelengths but were unable to differentiate wavelengths of light (i.e. see colour). It is unknown if hybrid sensory expansion in P. formosa has resulted in an increased ability to differentiate wavelengths or only an expanded visual range. Our behaviour experiments suggest that P. formosa still have the ability to differentiate wavelengths of light. The extent that P. formosa pecked at/approached painted disks differed by colour in a manner similar to the parental species which are homozygous at opsin loci (Figure 3.2). This pattern held except for attraction to green (P. formosa is intermediate to the parental species) and attraction to yellow (P. formosa is more attracted than either parental species). Thus, the combination of parental opsin loci through hybridization has led to functional differences in the tuning of the sensory system of P. formosa.

3.5.3. Unanticipated Pecking Behaviour

Using MSP, both P. mexicana and P. latipinna have been shown to possess two classes of cone cells that maximally detect light in the range of green, yellow, red, and orange. While P. mexicana cones detect wavelengths around 536 and 563 nm, cones of P. latipinna detect wavelengths around 551 and 576 nm (Körner et al. 2006). Both cone classes in P. mexicana maximally detect shorter wavelengths of light than those of P. latipinna. Because P. mexicana are better tuned to detect shorter wavelengths than P. latipinna, we hypothesized that P. mexicana would peck at coloured disks that reflect shorter wavelengths of light more than P. latipinna. The yellow and green coloured disks used in our behavioural trials reflect shorter wavelengths than the red and orange coloured disks (Rodd et al. 2002). Therefore, we predicted that P. mexicana would peck at green and yellow disks more than P. latipinna, while P. formosa would be intermediate to the two parental species because it has opsins from both. Surprisingly, we found that P. mexicana pecked at the green disks less than P. latipinna, while P. formosa behaved

as predicted (intermediate to the parental species). The unexpected switch in pecking behaviour between P. mexicana and P. latipinna is interesting and may be an outcome of a female preference for the green-blue colouring of large male sailfin mollies but further exploration by the field of behavioural ecology is needed to test this hypothesis. Despite the unanticipated behaviour of the parental species, it should be noted that P. formosa did behave as predicted; pecking the green disk at a proportion that was intermediate to the parental species. Clearly P. formosa has inherited opsin alleles from both P. mexicana and P. latipinna, which has influenced the sensory system and thus behaviour of this hybrid species.

3.5.4. Fitness Implications of HSE

Our data show that P. formosa have received the RH2-1 and LWS opsin repertoire of both parental species. This raises the question of whether or not this expanded repertoire has impacts on P. formosa fitness. There have been at least 840,000 generations since the hybridization event that lead to the formation of P. formosa (Stöck et al. 2010) and yet opsin amino acid sequences remain almost identical to their parental sequences (Table 3.2); this is possibly due to selection for the maintenance of functional opsins with the same λmax as their parental species (although slow neutral evolution is still a possibility (Schartl et al. 1991)). We therefore suggest that tests of the HSE in systems where sensory stimuli influence fitness through foraging or mating decisions may prove useful for understanding the importance of hybridization in expanding sensory system repertoires (such as crickets (Shaw and Herlihy 2000), flies (Schwarz et al. 2005; Mallet 2007), cichlids (Carleton and Kocher 2001), and butterflies (Awata et al. 2009)).

3.6. Conclusion

Taken together our results clearly show that hybrid species can have a different sensory repertoire than either of their parental species, because they share sensory genetic variation with both parents. Bringing together sensory allelic variation from both parental species results in an expanded sensory system in one generation that is much faster than the more traditional models of duplication and divergence. We have termed

this phenomenon ‘hybrid-sensory expansion’ (HSE) and propose that it could help explain many differences between hybrids and their parental species. Providing hybrids with large sensory repertoires made up of alleles that have experienced selection in two different species could result in different outcomes depending upon the selective environment of the hybrid. Given a selective environment that is similar to one or both of the parental species, the hybrid may exhibit the same tuning of the sensory repertoire to either or both parental species. However, it is also possible that divergent selection could act on the allelic diversity within the hybrid to favor differentiation of the sensory system, resulting in different sensory alleles from the parental species.

In some cases, hybridization may thus be an important driver of the diversification of sensory systems via repertoire expansion and this process likely catalyzes sensory diversification among other organisms and in the context of other sensory systems.

Acknowledgements

We thank Dr. Margaret Ptacek for Poecilia mexicana specimens. We also thank Dr. Catherine Peichel, Dr. Ingo Schlupp and one anonymous reviewer for insightful comments. This work was funded by the Natural Sciences and Engineering Research Council (NSERC) of Canada and approved by the UACC of Simon Fraser University (protocol: 982B-06). We declare no conflicts of interest.

Data Accessibility

DNA sequences: GenBank Accessions JF823551 - JF823570

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Boxes, Figures and Tables

Hybrid Sensory Expansion (HSE) Hypothesis We propose that when a hybrid is formed between two parental species (P1 and P2) possessing functionally diverged sensory alleles (1 and 2) at the same autosomal locus; then the hybrid will be heterozygous, possessing the sensory alleles of both P1 and P2. Bringing together sensory alleles from P1 and P2 provides the hybrid with a combined sensory repertoire of both P1 and P2 (tested in this manuscript). While sensory expansion normally depends upon relatively slow evolutionary processes such as gene duplication and divergence, HSE occurs in a single generation. The expanded sensory repertoire may then be shaped by selection.

P1 1,1 x P2 2,2

H1 1,2

Hybrid Sensory Expansion (HSE) Predictions The resulting sensory repertoire of the hybrid can be shaped by selection from various aspects of life history including: sexual selection, prey detection, predator detection, etc. The resultant sensory repertoire could resemble the sensory system of one, both, or neither parental species if the selective regime experienced by the hybrid resembles those experienced by either or both parental species or is entirely or partially novel.

Parental species 1, 1 2, 2

Hybrid, F1 individuals 1, 2

Hybrid species, after selection and mutation 1, 1 2, 2 1, 2 1’, 2 1, 2’ 1’, 2’ 1’, 1’ 2’, 2’

Experienced selection regime similar to one parental species, both parental One Both One and Novel species, or novel pressures: Novel

Sensory systems are the tools by which organisms perceive and interact with their environment. Changes to the sensory system can change the environmental parameters under which an organism can survive. Sensory alleles inherited from parental species P1 and P2 have been tuned to facilitate interaction with the environmental parameters of P1 and P2 respectively. First generation hybrids have sensory alleles from both parental species suggesting they could live in the environments of P1 and P2. Depending upon the direction of selection the set of environmental parameters available to the hybrid species could decrease, or shift to a new set of parameters. Selection working to maintain the full set of P1 and P2 alleles in the hybrid species would be observed as heterozygote advantage and could explain behavioral diferences within populations of hybrid species as some individuals would be homozygous for each of the parental sensory alleles. Similarly, diferent populations of hybrids could experience selection pressures in diferent directions; matching P1 or P2. Hybrid Environmental Zone Environmental Parameters of P1 Parameters of P2

1,2

1,1 2,2 1’,1 2,2’

1’,1’ 1’,2’ 2’,2’

Box 3.1. Hybrid Sensory Expansion (HSE): hypotheses and predictions.

RH2-1 Oryzias latipes RH2-1 RH2-1 RH2-1-L RH2-1-M Poecilia latipinna Poecilia formosa 100/1.00 Poecilia mexicana Poecilia formosa 80/0.79 B LWS-R LWS-R-M LWS-R LWS-R-L LWSB LWS-2 LWS-2-M LWS-2 LWS-2-L Poecilia formosa Poecilia mexicana Poecilia latipinna Poecilia formosa Oryzias latipes 100/1.00 99/0.98 Poecilia mexicana Poecilia formosa LWS-3-M LWS-3 Poecilia formosa Poecilia latipinna 100/1.00 LWS-1 LWS-1-M LWS-1 LWS-1-L LWS-3 99/1.00 LWS-3-L 96/0.99 100/1.00 Poecilia formosa Poecilia mexicana Poecilia mexicana Poecilia formosa Poecilia formosa Poecilia latipinna Poecilia latipinna Poecilia formosa 98/1.00 98/1.00 91/1.00 98/1.00 70/0.97 100/1.00 97/1.00 83/0.94 A

Figure 3.1. Bayesian consensus phylogenies of (A) long wavelength sensitive (LWS) opsin loci, and (B) RH2-1 opsin locus in Poecilia mexicana, P. latipinna, and the two P. formosa alleles. Maximum likelihood bootstraps and Bayesian posterior probability values (respectively) are reported for each node.

Pecks Approaches 1.0 AB B 1.0 AB B .8 .8 A A .6 .6 .4 .4 Proportion Green .2 .2 0 0 P. mexicana P. formosa P. latipinna P. mexicana P. formosa P. latipinna 1.0 1.0 .8 .8

.6 B .6 .4 .4

Proportion Yellow A AB .2 .2 0 0 P. mexicana P. formosa P. latipinna P. mexicana P. formosa P. latipinna 1.0 1.0 .8 .8 .6 .6 .4 .4 Proportion Orange .2 .2 0 0 P. mexicana P. formosa P. latipinna P. mexicana P. formosa P. latipinna 1.0 1.0 .8 .8 .6 .6 .4 .4 Proportion Red .2 .2 0 0 P. mexicana P. formosa P. latipinna P. mexicana P. formosa P. latipinna

Table 3.1. Comparison of the two P. formosa alleles and parental species for each LWS locus and RH2-1. Percent similarity is given above the diagonal. Number of gaps is given below the diagonal. Dark grey boxes show the most similar parental sequence for each allele from P. formosa.

Formosa-M Formosa-L Mexicana Latipinna

Formosa-M - 98.647 99.621 98.701

LWS-1 Formosa-L 3 - 98.593 99.837 Mexicana 0 3 - 98.647

Latipinna 3 0 3 -

Formosa-M - 97.772 98.859 97.799

LWS-2 Formosa-L 25 - 98.138 99.532 Mexicana 27 4 - 96.905

Latipinna 25 12 50 -

Formosa-M - 96.346 97.310 96.346

LWS-3 Formosa-L 21 - 97.676 99.783 Mexicana 16 5 - 97.676

Latipinna 21 0 5 -

Formosa-M - 98.685 99.862 98.616

LWS-R Formosa-L 2 - 98.824 99.931 Mexicana 0 2 - 98.754

Latipinna 2 0 2 -

Formosa-M - 99.057 99.730 99.057

RH2-1 Formosa-L 3 - 99.125 100.000 Mexicana 1 4 - 99.125

Latipinna 3 0 4 -

Table 3.2. Amino acid differences in LWS loci across species. Amino acid numbering follows that of Yokoyama (2000). Transmembrane designations indicate whether the amino acid site is located in the transmembrane domain (Y-yes; N-no), where changes in amino acids are more likely to shift spectral absorbances. ‘-’ indicates there was no variation in amino acids at that site for that locus. The amount of within species variation is unknown. Shading is provided to facilitate visual comparison.

Human amino acid number

Locus 11 20 26 33 55 65 131 132 139 153 188 194 233 247 298 310

P. mexicana 1 - - S - - - Y I - - V - - - - - P. formosa-M 1 - - S - - - F I - - V - - - - - P. formosa-L 1 - - A - - - F T - - I - - - - - P. latipinna 1 - - A - - - F T - - I - - - - - P. mexicana 2 - - - - A I ------A L P. formosa-M 2 - - - - A I ------G L P. formosa-L 2 - - - - V V ------G F P. latipinna 2 - - - - V V ------A F P. mexicana 3 Q - S T L - - I A V - F G - - - P. formosa-M 3 P - S T L - - I A V - F G - - - P. formosa-L 3 Q - A S I - - T T I - Y A - - - P. latipinna 3 Q - A S I - - T T I - Y A - - - P. mexicana R - E F ------R A - P. formosa-M R - K F ------R T - P. formosa-L R - E S ------H A - P. latipinna R - E S ------H A - Transmembrane N N N N Y Y Y Y Y N Y N Y N N Y

Table 3.3. Tukey’s HSD comparing the hybrid P. formosa and parental species, P. mexicana and P. latipinna, in the number of pecks and approaches made toward coloured disks. Bold values indicate significance at p < 0.05.

Pecks Approaches

P-value F-value df P-value F-value df

P. latipinna x P. formosa 0.1279 3.625 2 0.8792 3.920 2 Green P. mexicana x P. formosa 0.8023 3.625 2 0.0856 3.920 2 P. mexicana x P. latipinna 0.0331 3.625 2 0.0334 3.920 2 P. latipinna x P. formosa 0.2595 3.436 2 0.4062 1.860 2 Yellow P. mexicana x P. formosa 0.0334 3.436 2 0.1565 1.860 2 P. mexicana x P. latipinna 0.6310 3.436 2 0.8594 1.860 2 P. latipinna x P. formosa 0.9969 1.323 2 0.5459 1.815 2 Orange P. mexicana x P. formosa 0.3567 1.323 2 0.6578 1.815 2 P. mexicana x P. latipinna 0.3411 1.323 2 0.1488 1.815 2 P. latipinna x P. formosa 0.4646 0.757 2 0.9766 0.521 2 Red P. mexicana x P. formosa 0.6756 0.757 2 0.7205 0.521 2 P. mexicana x P. latipinna 0.9274 0.757 2 0.6075 0.521 2

Supplementary Tables

Supplementary Table 3.1. Primers used for creating PCR products and sequencing

Species PCR Product PCR Primers Sequencing Primers Poecilia formosa-L LWS-1 01, 06 22, 19, 33, 35 Poecilia formosa-L LWS-2A 26, 13 12, 16, 33, 35 Poecilia formosa-L LWS-2B 13, 40 02, 03, 33, 35 Poecilia formosa-L LWS-3 35, 01 17, 18, 33, 35 Poecilia formosa-L LWS-R 37, 36 22, 33, 35 Poecilia formosa-L RH2-1 31, 32 33, 34 Poecilia formosa-M LWS-1 01, 06 22, 19, 33, 35 Poecilia formosa-M LWS-2A 26, 13 12, 16, 33, 35 Poecilia formosa-M LWS-2B 27, 28 02, 03, 33, 35 Poecilia formosa-M LWS-3 29, 30 17, 18, 33, 35 Poecilia formosa-M LWS-R 37, 36 22, 33, 35 Poecilia formosa-M RH2-1 31, 32 33, 34 Poecilia latipinna LWS-1 01, 06 09, 10, 13, 18, 19, 20, 22 Poecilia latipinna LWS-2A 13, 26 05, 12, 13, 15, 26 Poecilia latipinna LWS-2B 13, 40 02, 03, 08, 13, 20 Poecilia latipinna LWS-3 01, 35 04, 07, 13, 17, 18, 20 Poecilia latipinna LWS-R 36, 37 21, 22, 24, 25 Poecilia latipinna RH2-1 31, 32 31, 32 Poecilia mexicana LWS-1 01, 06 07, 09, 10, 11, 13, 20, 22 Poecilia mexicana LWS-2A 13, 26 05, 10, 12, 13, 14, 15, 23, 26 Poecilia mexicana LWS-2B 13, 32 02, 03, 08, 13, 20 Poecilia mexicana LWS-3 01, 35 07, 10, 17, 18, 20 Poecilia mexicana LWS-R 36, 37 21, 22, 24, 25 Poecilia mexicana RH2-1 31, 32 31, 32

Primer # Primer Sequence 01 TGTGAAGTGCAGATCACCTAG 02 GTGAAGACCCTGGAGTCCAG 03 TGGGTTGATTCACTATCTAGC 04 ACATCCAGAGTGTGGAGACG

05 AGGAAGATGACTCTGGCATTG 06 AGAATTTGTTTTCTCCCAGCC 07 TTATGCAGGAGCCACAGAGG 08 TCTTATCAGTCTTCACCAACGG 09 TTACTGTGTCTGCTGGGGACCCTAC 10 ATGTGGTAGTTTGGTCCTTC 11 AGGACGTTTTCAGTCCATGAGGC 12 ATACAGCTTGTCAGCAGAAG 13 GCAAAGACTGTCTCTCCAAGATC 14 AGATGTCCAGAAGACAGTCATG 15 GTCTCTATGCTATGCCACA 16 GGAACAACAGCCTTGAGAGGATTGTC 17 GACCCAGGAGAAAACTATTCCAGC 18 CATGACTACAACCATCCTGG 19 GCCCACCTGTCGGTTCATGAAG 20 CTTCATGAACCGACAGGTGGGC 21 CCCAGAAGGAAGTATCTAGGATG 22 ATCGCTCCTCGATGGGTTTAC 23 GTAAACCCATCGAGGAGCGAT 24 GGCAAGGTTGACTAAGATCCAGT 25 GGACACTTCAGAGCCGTCAT 26 CCCAGCAAAACTCTCAAGGT 27 CCTCGATGGGTTTATGATGC 28 CTAACAAGTTACAGTTACAGTCCC 29 CAGTTTCTGTACAGGTCACAGA 30 GAAGGTTATAAGCCAGAGGAAG 31 GAGTGTAGGATTGGCATTTACCA 32 TTGCACGCGTAACCAGATGA 33 TAATACGACTCACTATAGGG 34 CGCTGATTGTTTATTCAGGTGC 35 ATTAACCCTCACTAAAGGGA 36 TGCATTGACACATCCATGAGTTC 37 CCACAAGGTTACAAGCCAGAG

Supplementary Table 3.2. Primers used for creating cDNA products

Species Allele Primers Primer # Primer Sequence Poecilia formosa LWS-1-M 38, 39 38 GGACAATCATGTAGGACAGGACA Poecilia formosa LWS-2-M 40, 41 39 CTGAGGAACATTATTTCTAG Poecilia formosa LWS-3-M 42, 43 40 CCAAAACCGAGAACACTGACA Poecilia formosa LWS-R-M 44, 45 41 CCTCGATGGGTTTATGATGC Poecilia formosa RH2-1-M 46, 47 42 GTTTCCTCCTAAACAGAACATGAAGG Poecilia formosa LWS-1-L 48, 49 43 CGAAGACACAACAAGAGGTT Poecilia formosa LWS-2-L 50, 51 44 TTCCCAAAAAGCCGCATGATG Poecilia formosa LWS-3-L 52, 53 45 GAAGATCAAGCAGCTCAGATC Poecilia formosa LWS-R-L 54, 55 46 GCAGTTACGGAACTGTTTA Poecilia formosa RH2-1-L 56, 57 47 CTCCGCAGCTTTTGGCACTTT 48 GGACAATCATGTAGGACAGGACC 49 CTGAGGAACATTATTTCCAG 50 CCAAAACCGAGAACATTGACT 51 CCTCGATGGGTTTATGATGT 52 GTTTCTTCCTAAACAGAATATGAAGG 53 CGAAGATACAACAAGAGGCG 54 TTCCCAAAAAGCCGCATGATA 55 GAAGATCAAGCAGCTCAGATT 56 GCAGTTACGGAACTGTTTG 57 CTCCGCAGCTTTTGGCACTTC

Chapter 4.

Beauty in the eyes of the beholders: Colour vision is tuned to mate preference in the Trinidadian guppy (Poecilia reticulata)

Publication and Contributions

A version of this chapter is published as: Sandkam, B., Young, C. M. and Breden, F. (2015), Beauty in the eyes of the beholders: colour vision is tuned to mate preference in the Trinidadian guppy (Poecilia reticulata). Molecular Ecology, 24: 596– 609. doi: 10.1111/mec.13058

Contributions: BAS and FB conceived and designed the project, conducted fieldwork, and wrote the manuscript; BAS designed assays and conducted all qPCR work; BAS and MY sequenced LWS-1 loci.

4.1. Abstract

A broad range of animals use visual signals to assess potential mates, and the theory of sensory exploitation suggests variation in visual systems drives mate preference variation due to sensory bias. Trinidadian guppies (Poecilia reticulata), a classic system for studies of the evolution of female mate choice, provide a unique opportunity to test this theory by looking for co-variation in visual tuning, light environment, and mate preferences. Female preference co-evolves with male colouration, such that guppy females from 'low predation' environments have stronger preferences for males with more orange/red colouration than do females from 'high predation' environments. Here we show that colour vision also varies across populations, with 'low' predation guppies investing more of their colour vision to detect red/orange

colouration. In independently colonized watersheds, guppies expressed higher levels of both LWS-1 and LWS-3 (the most abundant LWS opsins) in ‘low predation’ populations than ‘high predation’ populations at a time that corresponds to differences in cone cell abundance. We also observed that the frequency of a coding polymorphism differed between high and low predation populations. Together this shows that the variation underlying preference could be explained by simple changes in expression and coding of opsins, providing important candidate genes to investigate the genetic basis of variation in this model system.

4.2. Introduction

Understanding the forces driving population divergence is critical to understanding phenotypic evolution and ultimately speciation (Coyne & Orr 2004). Population divergence via sexual selection can occur rapidly when variation in mate preferences change across populations (Panhuis et al. 2001). Many hypotheses have been brought forth to explain the rapid evolution of female preference and male traits, including indirect models (such as Fisher’s runaway and Good Genes), and direct models (such as sensory bias) (reviewed in Kuijper et al. 2012). Female preferences for male colouration occurs in a broad range of taxa from insects to mammals making the question of what shapes evolution of mating preferences fundamental to a wide range of fields including evolution, ecology and animal behaviour. One problem with evaluating the models for the evolution of female preference is that there are few systems in which variation in female preference exists across populations in a consistent replicated manner.

In the Trinidadian guppy (Poecilia reticulata), female mate preferences vary both within and between populations in response to environmental factors, making this system a premier model for evaluating the relative importance of the above models (Haskins et al. 1961; Endler 1980; Houde & Endler 1990; Brooks & Endler 2001; Hughes et al. 2013). High predation populations undergo strong forces of natural selection, which favor the evolution of males with drab colouration and weak (to non-existent) female preferences for colourful males. Alternatively, females from low predation populations have strong preferences for colourful males (usually reds/oranges) resulting in more

colourful males (Haskins et al. 1961; Endler 1978; Breden & Stoner 1987; Houde & Endler 1990; Endler & Houde 1995; Houde 1997; Magurran 2005). The watersheds of Trinidad were colonized independently, in each case from high to low predation regimes, thereby acting as naturally occurring experimental replicates (Reznick et al. 1996).

It has been strongly argued that female preferences for orange and red have evolved as a pleiotropic effect due to a pre-existing bias in guppies (following the Sensory Bias model of sexual selection) (Rodd et al. 2002). As highlighted by Endler and Basolo (1998) there are two models included in sensory bias that differ in their focus: in the sensory exploitation (SE) model, variation in the peripheral sensory system leads to variation in mate preferences; while in the sensory trap (ST) model mate preferences are due to neural responses that have evolved in a context outside of sexual selection. According to the SE model, variation in the tuning of peripheral sensory systems alone should be capable of driving changes in preferences for mate characteristics (Endler & Basolo 1998).

Mating decisions based on colour requires colour vision, which is largely accomplished by comparing the signals from cone cells in the retina, which are sensitive to different wavelengths of light (Gegenfurtner & Sharpe 1999). The wavelengths at which photopigments absorb light is largely determined by the transmembrane opsin protein expressed by the cone cell (Yokoyama 2000; 2002). While humans have 3 cone opsin proteins (and thus 3 cone cell types) guppies have an astounding 9 cone opsin proteins (Hoffmann et al. 2007; Ward et al. 2008; Watson et al. 2011). Each cone opsin protein is coded by a single gene which are grouped and named for the range of light they detect: short-wavelength sensitive (SWS1) detects ultraviolet; short-wavelength sensitive 2 (SWS2A and SWS2B) detect blues and purples; rhodopsin-like (RH2-1 and RH2-2) detect greens; and long-wavelength sensitive (LWS-1, LWS-2, LWS-3 and LWS- R) detect reds and oranges (Ward et al. 2008; Watson et al. 2011; Sandkam et al. 2012).

Differences in sensory tuning are traditionally assumed to occur via changes in gene sequences. However, differences in gene expression can also alter the tuning of sensory systems both across species (Cichlids- Carleton & Kocher 2001) and even

across populations within a species (Bluefin killifish- Fuller et al. 2004) (Reviewed in Horth 2007). Therefore both factors may be variable at the level that female preference changes in guppies. A large population genetics study of guppy opsin sequences in Trinidad by Tezuka et al. (2014) found variation in the frequency of polymorphisms known to impact colour vision only in LWS-1, where there are two alleles named for the amino acid at the position that corresponds to residue 180 in human M/LWS opsins: 180 Ala and 180 Ser. This same polymorphism occurs multiple times in the evolution of vertebrate opsins, and can result in a significant change in the tuning of an opsin pigment up to 15nm (Ward et al. 2008). Cone cell proportions in the retina are frequently estimated using opsin expression profiles, thereby opsin expression provides an excellent measure of the allocation of an individual’s colour vision repertoire to a certain region of the spectrum (Fuller et al. 2003; 2004; Cheng & Flamarique 2004; 2007; Parry et al. 2005; Shand et al. 2008).

Here we assess the potential for the sensory exploitation model to explain female preferences in this model system by examining whether variation in visual tuning is associated with variation in mate choice at the population level. The parallel colonizations of watersheds each with high and low predation populations (with known differences in mate choice for reds and oranges) allows us to directly test if variation in the peripheral nervous system exhibits parallel variation in mate preferences by assessing the differences in allele frequency and expression of LWS opsins (responsible for detecting red/orange colouration). Using this framework we asked ‘Do guppy populations vary in colour vision?’ and pose the following hypothesis: If there is a causal relationship between visual tuning and mate choice, then low predation populations in independently colonized watersheds should show higher LWS expression and consistent changes in the frequency of genetic polymorphisms known to affect opsin sensitivity compared to high predation populations.

4.3. Materials and Methods

4.3.1. Sample Collection and Environmental Parameters

Poecilia reticulata were sampled from one high and one low predation population in the Aripo watershed, as well as one high and one low predation population in the Marianne watershed. These are all populations in the Northern Range Mountains of Trinidad where the Marianne watershed lies on the north slope while the Aripo watershed lies on the south slope. These watersheds were colonized independently and are thus a prime example of parallel evolution (Reznick & Bryga 1996). High and low predation populations were chosen from previously established study sites (see Supplementary Table 4.1 for GPS coordinates of each population)(Crispo et al. 2006). Previous work has shown female preference for males with more red/orange colouration in low predation populations of both the Aripo (Kemp et al. 2009) and Marianne (Endler & Houde 1995) watersheds. Each population was sampled at four time points: 07:30, 10:30, 13:30, and 16:30 (here-after referred to as “Time”) on three days between July 3- 14, 2011. Sampling consisted of catching 3 males and 3 females, which were rapidly sacrificed in an overdose of MS-222, measured, and photographed (totaling 288 individuals). Eyes were immediately removed and a small puncture was made to facilitate complete penetration of RNAlater® Stabilization Solution (Life Technologies™). Both eyes from an individual were placed into a vial of RNAlater® and kept at 10°C for 24 hours, to allow tissue to be saturated per manufacturer’s recommendation. After 24 hours, the vial was transferred to liquid nitrogen. The vials were removed from liquid nitrogen just prior to being placed in checked baggage and flown to Simon Fraser University where they were placed in a -20°C freezer until RNA extraction. Time spent at room temperature totaled less than 24 hours and fell well under the 1-week maximum suggested by manufacturer. The bodies of individuals sampled were placed in tubes of 95% EtOH buffered with EDTA and kept at -20ºC until DNA extraction.

During the 10:30 collection the absolute irradiance of the light environment was measured using a Jaz Spectrophotometer fitted with a 600 um fiber cable and cosine corrector running the JazIrrad Program (Ocean Optics). This configuration measured the intensity of light arriving at the detector over a 180º field of view at 0.33 nm intervals

from 250-800 nm. The detector was placed 15cm below the surface and faced up to measure the absolute irradiance of the down-welling light. Guppies are usually found less than 15cm deep and therefore these measures of light environment are representative of the light experienced by guppies. To compare light environments across populations the λp50 was determined for each measure taken. The λp50 is the median wavelength of photons between 300-800 nm (McFarland & Munz 1975; Hortado- Gonzales et al. 2014). A larger λp50 is indicative of a light environment that is shifted toward longer wavelengths. Absolute irradiance measures are subject to variation in environmental parameters across days, such as cloud cover, therefore measures from the identical spot were taken on all 3 days of sampling at the same time to incorporate natural variation. On each day of sampling, environmental parameters were measured of the population using a DO700 Waterproof Dissolved Oxygen kit (ExTech®). Parameters measured included dissolved oxygen (DO), water temperature, conductivity, pH, Total Dissolved Solids (TDS), and salinity. Measures of λp50, DO, water temperature, conductivity, pH, TDS and salinity were compared between high and low predation populations within watersheds using independent Welch Two Sample t-tests in R v3.0.2 (R Core Team 2014) with the 3 days acting as replicates for each population.

4.3.2. qPCR Assay Design

Opsin expression profiles are a well established methodology by which to measure an organism's visual system, as differences in opsin expression profiles in the mid-morning correlate with differences in the ratio of cone cells expressing those opsins in fish and humans (Hagstrom et al. 2000; Fuller et al. 2004; Cheng & Flamarique 2004). Probe based PrimeTime® qPCR assays (IDT® Technologies) were designed to be specific for each of the 9 opsins, 1 rhodopsin (RH1), and 3 housekeeping genes (beta actin (B-actin); cytochrome c oxidase subunit I (COI); myosin heavy chain (Myosin HC)) such that a primer or probe spanned intron-exon boundaries whenever possible. Assays consisted of a forward primer, reverse primer and 5’ FAM labeled probe with both 3’ Iowa Black® and internal ZEN™ quenchers (IDT® Technologies). Assay specificity was verified by the presence of a single band when running PCR products on an agarose gel. LWS-1 and LWS-R assays resulted in products of the same size, while LWS-1 and LWS-3 loci are similar in sequence. To ensure LWS-1, LWS-3, and LWS-R were truly

locus specific assays, we measured the pairwise covariance of these 3 assays on the final relative(hk) data set (described below) using R v3.0.2 (R Core Team 2014). If assays were binding to non-specific targets we would expect to see positive covariance between assays. We found no positive covariance between either LWS-1 and LWS-R (-0.0284) or LWS-1 and LWS-3 (-6.5021), demonstrating locus specificity of the LWS assays.

Three gBlocks® Gene Fragments (synthetic double stranded, sequence-verified ® genomic blocks made by IDT Technologies) were built to determine PCR efficiency (Ei) for each assay. The gene fragments contained sequence for each of the genes being assayed from 10 bp upstream of the forward primer to 10 bp downstream of the reverse primer. The order of genes was randomized such that gBlock® 1 contained LWS-1, RH2- 1, SWS2A; gBlock® 2 contained SWS1, LWS-2, RH2-2, SWS2B; and gBlock® 3 contained RH1, LWS-3, LWS-R. The 3 gBlocks® were mixed in equal proportions and brought to a concentration of 0.001 ng/µl resulting in a control with equal ratios of all the opsin and housekeeping genes. Six replicates of each assay were run using 4.5 µl of the control. The relative primer efficiencies (Ei) were then calculated following Carleton and Kocher (2001) using the equation:

Ct (1+1) High = 1 Cti (1+ Ei )

The critical threshold for the opsin with the highest expression (lowest Ct value) is CtHigh and Cti is the critical threshold for opsin i. Running six replicates resulted in a mean relative efficiency and standard error for each of the assays (Supplementary Table 4.2).

As COI had the highest relative efficiency it was used to measure absolute efficiency. A ten fold serial dilution was made of a randomly chosen fish from those sampled in Trinidad. qPCR was performed on five replicates of each concentration using the COI assay. The absolute efficiency of COI was found using the slope of

−slope ln(concentration) plotted on Ct such that absolute ECOI = e −1 . The absolute efficiencies of the other primer/probes were determined following Fuller et al. (2004) using the equation:

absolute Ei = (relative Ei x absolute ECOI ) relative ECOI

4.3.3. Sample Processing and Analyses

Both eyes from one individual were placed in 600 uL of TRIzol® reagent (Life Technologies™) and ground in a 1.5 mL RNase-free Kontes® Pellet Pestle Grinder (Kimble Chase). Solution was then run through an Ambion® Homogenizer (Life Technologies™) on a Beckman Coulter Microfuge® 18 microcentrifuge for 8 minutes at 12,000 rpm to reduce viscosity. RNA was extracted following the manufacturer’s instructions using PureLink® RNA Mini Kit with the addition of an on column treatment with PureLink® DNase (Life Technologies™) to eliminate any potential genomic contamination during qPCR.

RNA yields were quantified by measuring each sample 3 times using a NanoDrop 2000c spectrophotometer and averaging across the 3 measures. Concentrations of RNA were adjusted to 50 ng/uL using UltraPure™ DNase/RNase-Free Distilled Water (Life Technologies™). For each sample 500 ng RNA was reverse transcribed using a High Capacity cDNA Reverse Transcription Kit with RNase Inhibitor (Life Technologies™) following the manufacturer’s instructions. cDNA yields were quantified by measuring each sample 3 times using a NanoDrop 2000c spectrophotometer and averaging across the 3 measures. Concentrations of cDNA were adjusted to 11 ng/uL using UltraPure™ DNase/RNase-Free Distilled Water (Life Technologies™) for use in qPCR reactions.

For each individual the 9 opsins, 1 rhodopsin, and 3 housekeeping genes were quantified using the qPCR probe based assays described above, each reaction was run in triplicate. All 39 reactions for each individual were run simultaneously on the same 384 well plate in addition to negative controls (UltraPure™ water) for each assay. Each 10 uL reaction consisted of: 5 uL Brilliant III Ultra-Fast qPCR Master Mix (Agilent Technologies), 0.5 uL FAM labeled assay (described above) and 4.5 uL sample. All reactions were set up on ice and the plates were briefly spun down before being run on an Applied Biosystems® 7900HT qPCR machine (Life Technologies™). PCR conditions were as follows: 95°C for 3:00 followed by 40 cycles of 95°C for 0:05, 60°C for 0:15.

Since each assay was done in triplicate, the standard deviation was taken and when >2, outliers were removed. One of the 288 individuals had all poor data and was removed from further analyses. To assess differences in colour vision, the proportion of total opsin expression (Tall) made up of each opsin (Ti) was calculated following Fuller et al. (2004) and Carleton and Kocher (2001) with the following equation:

Cti 1 (1+ Ei ) Ti ( ) = ( ) Cti Tall 1 1+ E ∑( (( i ) ))

Ei is the mean primer/probe efficiency for assay i (described above) and Cti is the critical cycle number for gene i (such that expression of the 9 opsins add to 1 for each individual).

Each of the 9 opsins as well as the 1 rhodopsin were also compared to the average of the 3 housekeeping genes (THouse) to determine differential regulation of the genes. Using the mean of 3 housekeeping genes decreases the potential for random variation in housekeeping gene expression to lead to errors (Vandesompele et al. 2002).

The level of expression for each opsin and rhodopsin (Ti) was calculated based on the following equation modified from Fuller and Claricoates (2011):

Cti T 1 (1+ Ei ) i = ( ) CtHouse THouse 1 1+ E 3 ((∑( ( House ) )) )

EHouse is the primer/probe efficiency for a housekeeping gene and CtHouse is the critical cycle number for that gene.

The above two methods resulted in each individual having two measures for each opsin: proportional opsin expression (proportional), and relative to housekeeping genes (relative(hk)). Proportional measures of opsin expression provide a measure of colour vision, as colour vision is accomplished by comparing the signal from different cone cell types and opsins are the major differentiating character of cone cell types. Proportional opsin expression acts as a measure of the ratio of the different cone cell

types in the back of the retina (Fuller et al. 2004; Fuller & Claricoates 2011). Meanwhile relative(hk) measures of opsin expression reveal which opsins are differentially regulated (Fuller & Claricoates 2011), compared to a measure of overall gene activity, as evidenced by the mean of 3 housekeeping genes.

4.3.4. LWS-1 A/S Allele Frequency

A DNeasy blood and tissue kit (Qiagen) was used to extract genomic DNA from tail tissue of the same individuals used for expression analyses. Primers specific to the 5’ and 3’ UTR region of LWS-1 were used to generate PCR products of the LWS-1 locus. A 438 bp region including part of exon 2 and all of exon 3 was directly sequenced using internal sequencing primers by Molecular Cloning Laboratories (McLab, San Francisco, CA) (Supplemental Table 4.3). Sequence chromatograms were viewed and analyzed using SeqMan Pro (Lasergene 8.0; DNASTAR, Madison, WI). Individuals were identified to have either a Serine, Alanine or to be heterozygous at the 180 amino acid residue (no other variable sites were identified that would change wavelength sensitivity of LWS-1 (Tezuka et al. 2014)). The frequency of the three genotypes was determined in each population (sample sizes: Aripo watershed- high predation N= 54, low predation

N=48; Marianne watershed- high predation N=49, low predation N= 46). FST based on the frequency of alleles with a Serine at amino acid position 180 were calculated between high and low predation for each watershed using:

var(S) F = ST S *(1− S )

Where var(S) is the variance of the frequency of the Serine allele across high and low predation populations within the same watershed and S is the frequency of the Serine allele in the watershed.

4.3.5. Statistical Analyses of Opsin Expression

All expression data were analyzed using R v3.0.2 (R Core Team 2014). Time, sex, predation, and watershed were treated as fixed effects in all models with predation

nested in watershed. In all analyses time was treated as a categorical rather than continuous variable.

Do populations differ in colour vision? -

The overall effects of time, predation, watershed and sex on both proportional and relative(hk) opsin expression profiles was assessed using MANOVAs, with the levels for each of the 9 cone opsins log transformed and treated as dependent variables. Sex had no effect and was not involved in any significant interactions so was removed from the model. Significant interactions were followed up on individual watersheds where we examined the effects of time and predation.

Do low predation populations express higher levels of LWS opsins? -

Individual ANOVAs were conducted for each LWS opsin (both proportional and relative(hk) measures) to describe the effects of time, predation, sex, and watershed, because of the known importance of male orange and red colour patterns in these populations. Sex again had no effect nor was it involved in any significant interactions for any opsin and was removed from the models. Significant interactions were followed up with ANOVAs on data subsets by time, examining the effects of watershed and predation. Any significant watershed*predation interaction was further examined on subset data by watershed to examine the effects of predation.

4.4. Results

4.4.1. Guppy Opsin Expression Differs Across Populations

Across all populations SWS2A, LWS-2 and LWS-R showed lower levels of expression compared to other opsin genes (Figures 4.1, 4.2, and Supplementary Figures 4.1, 4.2). The most abundant opsin expressed varied across populations with RH2-1 being most highly expressed in Marianne low predation and Aripo high predation while SWS2B was the highest expressed in Marianne high predation and RH2-2 was highest expressed in Aripo low predation. MANOVAs of full opsin expression profiles

showed significant effects of predation (nested in watershed), watershed, time and every interaction therein for both proportional and relative(hk) measures (Table 4.1). Sex did not impact either proportional (F1,271 = 0.7565, P = 0.6568) or relative(hk) (F1,271 = 0.6815, P = 0.7255) measures of opsin expression profiles, nor was sex involved in any significant interactions with predation (nested in watershed), watershed or time. There were highly significant differences in opsin expression by predation, time and predation*time within both the Aripo and Marianne watersheds (Table 4.2). This shows that guppy colour vision, as measured by differences in opsin expression, does vary across populations.

4.4.2. Low Predation Populations Express Higher Levels of LWS Opsins

The ANOVAs of proportional and relative(hk) measures for LWS opsin expression revealed significant interactions between predation nested in watershed and time (Table 4.3; all other opsins presented in Supplementary Tables 4.4 and 4.5). To tease apart the effects of predation at each time point both datasets were subset by time point, and ANOVAs revealed significant effect of predation nested within watershed for many time points (Supplementary Tables 4.6 and 4.7). To tease apart the effect of predation in each watershed at the four time points, the time point data were subset by watershed and ANOVAs were run by predation; results for LWS are shown in Figures 4.1 and 4.2 (ANOVA results for all opsins are in presented in Supplementary Tables 4.8 and 4.9). When proportional LWS opsin expression differed within watershed by predation (Figure 4.1 and Supplementary Table 4.8), expression levels were higher in the low predation population, except for LWS-1 and LWS-2 at the end of the day in the Marianne watershed (Figure 4.1). This is likely due to the dramatic increase in LWS-3 expression experienced by this population at this timepoint (as can be seen in relative(hk) measures, Figure 4.2) which would result in relative expression of other opsins making up a smaller proportion of total opsin expression. When relative(hk) LWS opsin expression differed by predation within the Marianne watershed the low predation population had higher expression except for LWS-2 at time point 1 (Figure 4.2 and Supplementary Table 4.9); however the low level of LWS-2 expression in the low predation population at this time point may not be biologically relevant as it is indicative of very few cone cells expressing this gene and could have very minor contributions to colour detection. The higher

expression in both proportional and relative(hk) measures of LWS-1 and LWS-3 expression of low predation populations was accompanied by a decrease in expression of SWS2B (Figures 4.1, 4.2, 4.3; Supplementary Figure 4.2). The relative opsin expression of all opsins at time point 2 is shown in Figure 4.3.

4.4.3. Gene Frequencies of the 180 Ala Versus Ser Allele of LWS-1

Gene frequencies differed between high and low predation populations in both watersheds but all populations were found to follow Hardy Weinberg Equilibrium following independent chi-squared tests. The allele frequencies of the high predation populations were S- 62.37% A- 36.73% in the Marianne and S- 66.67% A- 33.33% in the Aripo, while low predation populations were S- 100% A- 0% in the Marianne and S-

97.92% A- 2.08% in the Aripo (Figure 4.4). FST between high and low predation populations was 0.3221 in the Aripo and 0.4393 in the Marianne watersheds. Sequences are available on GenBank under accession numbers: KP218062 – KP218254.

4.4.4. Environmental Parameters

We did not detect any differences in environmental parameters that likely drove differences in LWS opsin expression between high and low predation populations within watersheds (for raw data see Supplementary Table 4.10). The λp50 did not significantly differ between high and low predation populations in either the Marianne (t = 1.1373, P = 0.3542) or the Aripo (t = -2.6963, P = 0.0767) watersheds. Since increases to the λp50 is a measure of how far the available light is shifted toward longer wavelengths (Hurtado- Gonzales et al. 2014) we would expect to see significant within watershed differences between high and low predation populations if differences in LWS opsin expression were being driven by plastic responses to environmental differences in available light. Dissolved oxygen has been used as a proxy for differences in lighting environment elsewhere (Tezuka et al. 2014) yet for this environmental variable we still found no differences between high and low predation populations in either the Aripo (t = -0.0354, P = 0.9736) or the Marianne (t = -1.7165, P = 0.1954) watersheds. We also found no significant differences between high and low predation populations within watershed for temperature (Aripo – t = -1.2522, P = 0.2817 ; Marianne – t = 0.3288, P = 0.7629),

conductivity (Aripo – t = 4.0328, P = 0.0529 ; Marianne – t = 1.4242, P = 0.2332), pH (Aripo – t = -0.5048, P = 0.6593 ; Marianne – t = 1.8954, P = 0.1311), or total dissolved solids (Aripo – t = -0.3474, P = 0.7602 ; Marianne – t = 1.4661, P = 0.2218). However, there was a significant difference in salinity between the high and low predation populations of the Aripo watershed (t = 3.8891, P = 0.0399) but not in the Marianne watershed (t = 1.4444, P = 0.2302). As such no environmental parameters corresponded with differences in LWS opsin expression observed between high and low predation populations within both watersheds.

4.5. Discussion

Using guppies, a classic model system for studies of evolution by sexual selection, we found support for the sensory exploitation model to explain population divergence in mate preferences. This is the first study of opsin expression in natural populations of guppies and coupled with the allele frequency data we demonstrate that guppy vision differs across populations in a consistent manner. Proportionally, guppies in low predation populations express more long wavelength sensitive (LWS) opsins than do guppies from high predation populations, and low predation populations are almost fixed for an alternative amino acid known to affect retinal tuning. This suggests that much of the variation in female preferences in guppies could be explained by variation in the visual system, supporting the sensory exploitation model. This model for the evolution of mate preference posits that variation in the peripheral sensory systems can lead to variation in mate preferences (Endler and Basolo 1998). Thus, more broadly, support of the sensory exploitation model furthers our understanding of the mechanisms of mate choice that have the potential to lead to speciation (Panhuis et al. 2001; Coyne & Orr 2004).

4.5.1. Guppy Colour Vision Differs Across Populations

Variation in colour vision can be due to differences in the amino acid sequences of the opsin proteins, ratio of cone cells expressing different opsins, or neural processing of signals from the eyes. Here we show guppy populations differ both in opsin expression profiles and the frequency of alleles at the LWS-1 locus. Importantly, both

relative(hk) (measuring gene regulation) and proportional (measuring colour vision) guppy opsin expression profiles differ across watersheds but also by predation within each watershed (Table 4.2). Differences in relative(hk) expression suggest the regulation of opsin genes differ across populations, whereas differences in proportional expression suggest colour vision in guppies is not a fixed phenotype as has been assumed when modeling population differences in mate choice and colouration (such as Endler 1991 and Kemp et al. 2009). Specifically, the differences we found in proportional expression profiles at midmorning demonstrate that the ratio of cone cell types in the retina differ across populations. While implications of the diurnal variation in opsin expression across populations are less clear, it supports the conclusion that visual tuning differs dramatically across populations.

Further evidence of differences in guppy visual systems comes from the variation in allele frequencies seen across populations. The wavelength of light to which an opsin is maximally tuned, λmax, provides a good estimate for how sequence level changes in the opsin genes do or do not impact the visual system (Yokoyama 2008). Determination of λmax for the LWS opsins in guppies using protein expression systems has proven difficult (B. Chang (University of Toronto, Canada) personal communication). However, Tezuka et al. (2014) used the ‘five site rule’ (Yokoyama & Radlwimmer 2001) to identify two alleles of LWS-1 that differ in λmax by 7nm (LWS-1 (180 Ala) ~553nm, LWS-1 (180

Ser) ~560nm), and estimated the following λmax values for the other loci: LWS-2 ~518nm, LWS-3 ~560nm, and LWS-R ~560nm.

Tezuka et al. showed differences in frequency of the 180 Ala and 180 Ser alleles of LWS-1 across populations, such that most of the geographic variation occurred between streams in northern and southern parts of the island. However, Tezuka et al. also measured one Upper Aripo (equivalent to low predation Aripo in this study) and one Lower Aripo (equivalent to high predation Aripo in this study) population and the frequencies of the LWS-1 180 Ala/Ser alleles were very similar to those presented here. The frequency of the 180 Ser allele in the Lower Aripo (Tezuka) - 0.82 (N=45) compared to high predation (this study) - 0.73 (N=54), while the Upper Aripo (Tezuka) - 1.00 (N=33) compared to low predation (this study) - 0.96 (N=48). This demonstrates that low predation populations have a higher frequency of the longer wavelength LWS allele. The

FST based on LWS-1 between high and low predation populations in the Aripo was similar between Tezuka et al. (0.492) and this study (0.3221). Both these values are greater than the average FST estimate based on 7 non-opsin genes by Tezuka et al. for upstream/downstream pairs in the Aripo (0.070) and Guanapo (0.101) watersheds. The discrepancy in estimates of population divergence between those based on LWS-1 and those based on non-opsin genes is in line with the high levels of selection acting on LWS-1 reported by Tezuka et al. which corresponded with DO levels in their study. We found no differences in either DO or λp50, however this could be a seasonal effect of wet season driving high levels of DO across populations. It would be interesting to see if the other differences in allele frequency detected across watersheds by Tezuka et al. correspond with differences in predation level and/or mate preferences.

Classically, visual systems are assumed to be the same across different populations of the same species. However, our work adds guppies to the growing number of species that have recently been shown to vary in visual systems across populations due to differences in either opsin expression (e.g. Bluefin killifish (Fuller et al. 2004), cichlids (Smith et al. 2010), stickleback (Flamarique et al. 2013)) or sequence variation (e.g. Sand goby (Larmuseau et al. 2009), pied flycatchers (Lehtonen et al. 2012)). In consideration of this growing body of work we suggest care be taken when making assumptions that dismiss intra-species sensory system variation, such as when modeling quantum catch of available light.

4.5.2. Low Predation Populations Express Higher Levels of LWS Opsins

In most guppy populations, there is a trade off between natural selection against colourful males and sexual selection for colourful males, especially with respect to red/orange colouration (Endler 1980; Breden & Stoner 1987; Endler & Houde 1995; Lindholm et al. 2014). Guppy populations under low predation regimes evolve to invest more in female choice with increased male displays and stronger female preferences (Breden & Stoner 1987; Houde & Endler 1990; Endler & Houde 1995; Reznick et al. 2001; Lindholm et al. 2014). The increase in female preference for colourful males and decrease in predation pressure results in greater red/orange male colouration in low

than high predation populations (Haskins et al. 1961; Endler 1980). Furthermore transplant experiments have shown the evolution of female choice and male colouration can occur rapidly with changes to predation environments (Endler 1980; Reznick & Bryga 1987; O'Steen et al. 2002).

LWS opsins are the proteins responsible for detecting and discriminating red/orange colouration. We found greater LWS expression in low compared to high predation populations for both Aripo and Marianne watersheds. These watersheds were colonized independently and are thus a prime example of parallel evolution (Reznick & Bryga 1996). Therefore the greater expression of LWS opsins by low predation populations likely plays a major role in determining level of female preferences for the red/orange colouration of potential mates.

The differences in opsin expression profiles across populations could be due to either plastic response to differences in environmental conditions or heritable differences in opsin regulation. If expression differences in guppies between low and high predation are indeed due to plastic responses to lighting environment one would expect to see differences in the λp50 of the populations since the λp50 is a measure of whether a light environment is shifted to shorter or longer wavelengths. However, we did not find any differences in this parameter. The lack of lighting differences is not unprecedented as Smith et al. (2010) found significant differences in opsin expression across intra-specific populations of cichlids with no differences in lighting environment. Additionally Endler et al. (2001) found visual sensitivity to be heritable in guppies in response to artificial selection, and many other species have a strong heritable component to opsin expression (e.g. Bluefin killifish (Fuller et al. 2005), three spined stickleback (Flamarique et al. 2013), cichlids (Carleton & Kocher 2001; Hofmann & Carleton 2009)). This emphasizes the possibility that visual systems are far more genetically variable across populations within species than is commonly assumed. Since colour vision is constrained by the number of cone cells in the retina, even minor differences in selection pressures for the various roles vision plays (e.g. detecting and evaluating potential mates, competitors, predators, food, etc.) across populations could lead to differences in visual systems and may help explain population divergence in vision across a wide range of taxa.

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Interestingly, we saw no difference in colour vision between males and females. The lack of sexual dimorphism in guppy opsin expression is not surprising since sexual dimorphism in opsin expression is rarely observed in other species for which it has been tested (such as killifish (Johnson et al. 2013), some cichlid species (Sabbah et al. 2010), or three-spined stickleback (Boulcott & Braithwaite 2006)), nor was there any sexual dimorphism found in Trinidadian guppy visual systems using microspectrophotometry to measure cone cell absorbencies (Archer & Lythgoe 1990). It should be noted that Laver and Taylor (2011) did report a sexual dimorphism in opsin expression in a laboratory population of guppies from mainland South America. We measured opsin expression profiles on individuals, with a large sample size (287 individuals), using highly specific probe based qPCR assays; therefore we feel it extremely unlikely that we failed to detect a true sexual dimorphism in guppy opsin expression for these Trinidadian populations. Further work is needed on opsin expression in guppies from mainland South America and laboratory populations of guppies before we can completely rule out sex differences in guppy opsin expression.

Differences in LWS opsin expression need not be the result of selection specifically for its role in mate choice for it to impact mate choice decisions. The sensory drive hypothesis states that sensory systems adapt to local environments and predicts that divergence in signals (such as the colours involved in mate choice) occurs with differences in those environments (Endler 1992, 1993; Endler & Basolo 1998; Boughman 2002). While this study found no significant differences in lighting environments it is possible that differences do occur at other times of the year (as potentially seen in DO levels by Tezuka et al. 2014) or measured in ways other than λp50. Further experiments are needed to test how much variation in opsin expression profiles are due to genetic versus environmental factors, and to what extent these differences in expression and allele frequency can affect female preferences.

4.5.3. Implications for Evolutionary Theory

According to the sensory bias model of sexual selection, variation in peripheral sensory systems can lead to differences in female mate preferences (Basolo & Endler 1995; Endler & Basolo 1998; Boughman 2002). Indeed changes to sensory systems

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responsible for detecting the signals involved in mate choice are well known to influence both the direction and strength of preference for those signals (reviewed in Horth 2007 and Ryan & Cummings 2013). Traditional models of sensory system evolution through protein changes rely on the slow accumulation of sequence level changes due to mutation, gene duplication, and recombination that alter the tuning of sensory proteins (Horth 2007; Sandkam et al. 2012). These relatively slow models of sequence change do little to explain what happens to the sensory systems of populations that are capable of rapidly diverging with respect to mate choice, such as guppies. Meanwhile, regulatory differences are thought to be able to evolve more quickly since changes to regulatory regions are often less deleterious (Carroll 2005); these differences in opsin regulation could then persist in a population and be amenable to selection. As seen in Endler et al. (2001) artificial selection on guppies can result in different visual sensitivities in less than 9 generations. Clearly visual sensitivities have the capacity to keep pace with the rapidly evolving male colouration and female preferences seen in transplant experiments.

In 2002 Rodd et al. demonstrated that both male and female guppies prefer red and orange coloured objects outside of a mating context. Their data provided compelling support for their hypothesis that female mate choice has evolved following the sensory bias model of the evolution of sexual selection (Rodd et al. 2002). There are two models underlying Sensory Bias (Endler & Basolo 1998): the Sensory Trap (ST) model posits that female mate preferences toward a specific trait are due to selection historically leading to a preference for that trait outside of a mating context, allowing males to exploit that preference by displaying traits that resemble that preference (Christy 1995). The Sensory Exploitation (SE) model posits that female preferences for male traits are a result of male traits tuned to maximize detection by a female’s sensory system (Ryan 1990; Ryan & Rand 1990, 1993; Ryan et al. 1990). The ST and SE models largely vary in the emphasis placed on what physiological changes occur to drive changes to female preference; the ST predicts changes at the level of higher order processing, while the SE model predicts changes at the peripheral sensory system should be capable of driving differences in female preferences. However, we saw no differences in opsin expression between males and females; this raises the possibility that red/orange attractions in both mating and non-mating contexts are the result of differences in visual tuning, and sexual selection in guppies is actually following the SE model.

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4.6. Conclusion

Here we present support for the sensory exploitation model of the evolution of sexual selection. We found well-established differences in female mating preferences in guppies are associated with variation in the visual system. Populations with stronger female preferences for red/orange colouration invest a strikingly greater proportion of their colour vision in detecting those colours and are strongly differentiated for sequence variants at LWS-1 known to change spectral sensitivity. Furthermore, this pattern holds for two independently colonized watersheds. The intra-species differences in sensory systems across populations presented here and in other taxa suggest care should be taken when modeling sensory input based on measures of sensory systems taken from a different population.

Acknowledgements

We wish to thank Dr. Nadia Aubin-Horth, Dr. Becky Fuller and 2 anonymous reviewers with Axios Review for insightful comments and critiques of the manuscript; Frances Margaret Walker Breden for assistance in the field; Dr. Andrew Hendry and Kiyoko Gotanda for identifying field sites; Dr. Nora Hengst Prior, Dr. Kim Hughes, and Dr. Natasha Bloch for comments on early versions of the manuscript; and Dr. William Davidson and Dr. Krzysztof Lubieniecki for assistance and use of their qPCR machine at Simon Fraser University. Animals were collected under SFU animal protocol 982B-06 and permit # 001453 from The Trinidad Ministry of Housing and the Environment. This work was supported by NSERC discovery grant #138178 to FB, a Graduate International Research Award from Simon Fraser University to BS and an Undergraduate Student Research Award from NSERC to MY.

Data Accessibility

LWS-1 DNA sequences: GenBank Accessions KP218062-KP218254. All qPCR data, LWS-1 alignment, LWS-1 frequency, environmental parameter data, and commented R code used for statistical analyses are available on the Dryad Digital Repository at http://dx.doi.org/10.5061/dryad.sk6d5

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Tables and Figures

Table 4.1. Results of MANOVA on opsin expression profiles. W- Watershed, T- Time, P(W)- Predation nested in watershed.

Proportional Expression Relative(hk) Expression

df F P F P

W 1, 279 6.82 7.75E-09 7.16 2.53E-09

T 1, 279 20.56 < 2.2e-16 20.51 < 2.2e-16

P(W) 2, 279 9.33 < 2.2e-16 9.81 < 2.2e-16

W*T 1, 279 22.74 < 2.2e-16 22.68 < 2.2e-16

P(W)*T 2, 279 10.20 < 2.2e-16 11.67 < 2.2e-16

Table 4.2. Results of MANOVA on opsin expression profiles by watershed.

Aripo Watershed Marianne Watershed

Proportional Relative Proportional Relative (hk) (hk) Expression Expression Expression Expression

F (1,139) P F (1,139) P F (1,140) P F (1,140) P

Predation < < 7.56 < 0.0001 7.78 16.06 < 0.0001 15.84 (P) 0.0001 0.0001 < < Time (T) 31.01 < 0.0001 27.33 17.38 < 0.0001 17.79 0.0001 0.0001 < < P*T 10.05 < 0.0001 9.12 13.36 < 0.0001 14.78 0.0001 0.0001

110

Table 4.3. Results of LWS ANOVA. W- Watershed, T- Time, P(W)- Predation nested in watershed.

Proportional Opsin Relative(hk)

LWS-1 LWS-2 LWS-3 LWS-R LWS-1 LWS-2 LWS-3 LWS-R

F(1,279) 3.70 5.02 0.16 1.34 9.21 5.48 1.41 7.74 W P 0.0553 0.0258 0.6836 0.2469 0.0026 0.0198 0.2347 0.0057

F(1,279) 0.14 2.82 15.87 16.53 0.19 5.83 0.08 3.87 T 0.0940 <0.000 <0.000 0.7009 0.6605 0.0164 0.7720 0.0500 P 1 1 1

F(1,279) 9.81 7.90 7.44 11.74 8.33 1.14 0.21 9.21 P(W) <0.000 <0.000 0.0004 0.0007 0.0003 0.3205 0.8065 0.0001 P 1 1

F(1,279) 0.94 28.16 2.53 9.82 0.50 7.65 0.22 5.20 W*T <0.000 0.3324 0.1127 0.0019 0.4777 0.0060 0.6328 0.0232 P 1

F(1,279) 13.00 5.69 8.20 22.82 0.19 2.52 4.28 5.00 P(W)* T <0.000 <0.000 0.0037 0.0003 0.8270 0.08217 0.0147 0.0073 P 1 1

111

LWS-1 LWS-2 LWS-3 LWS-R

0.4 *** 0.020 0.20 0.008 0.3 0.015 0.15 ** 0.006 ** ** 0.2 0.010 0.10 0.004

0.1 0.005 0.05 0.002 Aripo 0.0 0.000 0.00 0.000 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 Proportional Expression

*** 0.4 *** 0.08 0.25 *** 0.020 ** * 0.3 * 0.06 0.20 0.015 ** 0.15 0.2 0.04 *** 0.010 0.10 0.1 0.02 0.05 0.005 0.0 0.00 0.00 0.000 Marianne 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 Proportional Expression Timepoint Timepoint Timepoint Timepoint

Low Predation High Predation Figure 4.1. Long wavelength-sensitive (LWS) opsin expression by population for proportional measures. Stars denote significant differences between high and low predation within the same watershed (*P < 0.05, **P <0.01, ***P < 0.001); error bars are ±1 SE (see Table S8, Supporting information). Aripo low predation at 13:30 had N = 17; all other population time points had N = 18.

112

LWS-1 LWS-2 LWS-3 LWS-R

25 * 0.08 ** 100 0.3 20 ** 0.06 80 15 60 0.2 Expression * 0.04 10 (hk) 40 * * 0.1 5 0.02 20 Aripo 0 0.00 0 0.0

Relative 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30

2.0 2.0 20 0.05 * * * 1.5 1.5 15 0.04 0.03 Expression 1.0 1.0 10 *

(hk) 0.02 0.5 * 0.5 5 0.01 0.0 0.0 0 0.00 Marianne Relative 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 Timepoint Timepoint Timepoint Timepoint Low Predation High Predation Figure 4.2. Long wavelength-sensitive (LWS) opsin expression by population for relative(hk) measures. Stars denote significant differences between high and low predation within the same watershed (*P < 0.05, **P < 0.01); error bars are ±1 SE (see Table S9, Supporting information). Aripo low predation at 13:30 had N = 17; all other population time points had N = 18.

113

Proportional Expression at Timepoint 2 (10:30)

Aripo Marianne High Predation High Predation Aripo Marianne Low Predation Low Predation 0.6 D D

* ** 0.4 C C * *** **

0.2 ** ** *** ** A A B B 0.0 Proportional Expression

RH2-1 RH2-2 SWS1 LWS-1 LWS-2 LWS-3 LWS-R SWS2A SWS2B

Figure 4.3. Proportional expression at time point 2. Stars denote significant differences within watershed between high- and low-predation populations (*P < 0.05, **P < 0.01, ***P < 0.001) (see Table S8, Supporting information). Letters denote significant differences between watersheds (see Table S6, Supporting information).

114

Marianne High Predation Marianne Low Predation

S/S - 36.7% S/S - 100% S/A - 53.1% S/A - 0% A/A - 10.2% A/A - 0%

N = 49 N = 46

Aripo High Predation Aripo Low Predation

S/S - 40.7% S/S - 95.8% S/A - 51.9% S/A - 4.2% A/A - 7.4% A/A - 0%

N = 54 N = 48

180 Ala allele 180 Ser allele

Figure 4.4. Genotype and gene frequencies of the 180 Ala (A) vs. 180 Ser (S) allele of LWS-1. LWS, long wavelength-sensitive.

115

Supplementary Tables and Figures Supplementary Table 4.1. Coordinates of populations sampled.

Latitude - N Longitude - W

Aripo High Predation 10° 39.036 061° 13.387

Aripo Low Predation 10° 40.955 061° 13.846

Marianne High Predation 10° 45.894 061° 18.279

Marianne Low Predation 10° 45.015 061° 17.130

116

Supplementary Table 4.2. Primer/probe sequence, length of product (bp), GenBank accession number for sequence on which assay was designed, relative (+ SE) and absolute qPCR efficiencies of each gene assay.

0.8258 0.0457 0.7858 0.8267 0.7751 0.7856 0.7856 0.7781 0.7844 0.7780 0.7795 0.7609 0.7823 0.8313 Absolute efficiency

0.0287 0.0314 0.0340 0.0299 0.0276 0.0271 0.0282 0.0277 0.0271 0.0284 0.0265 0.0245 0.0284

Relative efficiency 0.9623 0.9686 0.9156 0.9633 0.9031 0.9142 0.9154 0.9066 0.9140 0.9065 0.9083 0.8866 0.9115

GenBank EU143772 HQ391989 HQ260688 DQ912023 DQ234859 DQ234858 DQ912025 HM540108 HM540108 HM540108 HM540107 HM540108 HM540108 Accession

80 137 108 136 128 145 132 128 148 120 127 137 100 Length Product

) ’ 3 - ’ (5

T G G G AG Primer

Reverse CACTCATCCCCAGCATCTTC AGCCGTACTCTTCATTGTGG GAATCCGGCTTTGCACATAC CACATCCAGACTGTCGTGAT TGTTCAGGTGCTGTGTAGTG CCACGATACACATCCAGAGT GAACAACCAGAGACCAGAGA GACCAACTTTGGAGATTTCAG TTGTAGATGGAGGCTGACTTG CGAGGTTACAGTCAAGGATCT CACGATACACATCCAGAGAGT GACCACGATACACATCCAGAC GCTAAGACCACAAGAGACCAT

with )

’

3 - ’

Probe

GG AAG GAGG AAACC GTTGC TACGC TCCGC AACTACCAT AACATGCAT ACTACCACA AACTACCAC ACTACCACA labeled

quencher FAM CTGGAGCAGGTACATCCCGG TTCCTGGTTTGCTGGATACCT ACGTTCTCCTCAATAAGCAGT AGTCCTCAATAAGCAGTTTCG ATAGGAGCCGTCTTTGCCATT AAGATCCCTTTGAAGGACCAA AAGATCCCTTTGAAGGACCAA CCAGTTCTCGGACCCTCTGCT AGAGATCCTTTTGAGGGACCA AGGGATTCATGGCAACACTTG AGAGATCCCTTTGAAGGACCA CATGGCTGAACTTTGGGTGTG TGACCTCCAACCGTAGCAAAG

) ’ 3 - ’ (5

C CT Primer

Forward ATACAACAAGAGGCGCCG TCCTGTGTCTCAAAAGCCTC CACCGTCTACAATCCTGTCA GTCTTCACCTGGTTCATGGG GCGGCACAATGAAGATACAA AAGATACAACAAGAGGCGCT AATGAAGAAACTACAAGGGG TCTCTGCTCACCTTCAACTTC GCCCACTTCCACTATGTTCTC TCACCATCACCATCACATCTG TGGTCGTTATCATGGTCATCG GCTTGTGCGGGATATCATTTG GGACCCTTAGGCTGTGATATG

1 2 3 R

1 2

------actin HC COI - RH1 Gene SWS1 RH2 RH2 LWS LWS LWS LWS B Myosin SWS2B SWS2A

117

Supplementary Table 4.3. PCR and sequencing primers used for LWS-1 180 Ala/Ser allele identification.

Forward Reverse PCR TGTGAAGTGCAGATCACCTAG ACACATTCATGCATGATGCAG Sequencing GATCCCTTTGAAGGACCAAACT GGACAATCATGTAGGACAGGACC

Supplementary Table 4.4. Results of ANOVAs for proportional measures of expression for each opsin (bold denotes P < 0.05). W- Watershed, T- Time, P(W)- Predation nested in watershed.

LWS-1 LWS-2 LWS-3 LWS-R SWS1 SWS2A SWS2B RH21 RH22

F(1,279) 3.71 5.02 0.17 1.35 5.41 2.73 1.32 0.34 21.17 W P 0.0553 0.0258 0.6836 0.2469 0.0207 0.0997 0.2520 0.5600 <0.0001

F(1,279) 0.15 2.82 15.88 16.53 3.32 11.59 0.28 0.17 3.10 T P 0.7009 0.0940 <0.0001 <0.0001 0.0695 0.0008 0.6010 0.6840 0.0794

F(1,279) 9.81 7.90 7.44 11.75 1.88 5.30 1.89 1.03 13.03 P(W) P <0.0001 0.0004 0.0007 <0.0001 0.1541 0.0055 0.1540 0.3600 <0.0001

F(1,279) 0.94 28.17 2.53 9.82 31.44 16.92 0.09 19.41 2.72 W*T P 0.3324 <0.0001 0.1128 0.0019 <0.0001 <0.0001 0.762 <0.0001 0.1006

F(1,279) 13.00 5.70 8.21 22.82 3.29 14.23 13.66 0.07 19.75 P(W)*T P <0.0001 0.0038 0.0003 <0.0001 0.0385 <0.0001 <0.0001 0.931 <0.0001

Supplementary Table 4.5. Results of ANOVAs for relativehk measures of expression for each opsin (bold denotes P < 0.05). W- Watershed, T- Time, P(W)- Predation nested in watershed.

LWS-1 LWS-2 LWS-3 LWS-R SWS1 SWS2A SWS2B RH2-1 RH2-2 RH1

F(1,279) 9.22 5.49 1.42 7.74 0.35 0.16 0.64 0.56 28.49 17.14 W P 0.0026 0.0199 0.2347 0.0058 0.5546 0.6926 0.4249 0.4543 <0.0001 <0.0001

F(1,279) 0.19 5.83 0.08 3.87 2.95 6.41 5.05 2.30 7.52 3.93 T P 0.6605 0.0164 0.7720 0.0500 0.0870 0.0119 0.0254 0.1308 0.0065 0.0483

F(1,279) 8.33 1.14 0.22 9.22 8.33 0.37 1.62 4.74 5.00 6.05 P(W) P 0.0003 0.3206 0.8065 0.0001 0.0003 0.6914 0.1999 0.0095 0.0074 0.0027

F(1,279) 0.51 7.66 0.23 5.21 6.09 3.48 0.46 2.19 3.68 4.36 W*T P 0.4777 0.0060 0.6328 0.0232 0.01420 0.0631 0.4993 0.1400 0.0560 0.0377

F(1,279) 0.19 2.52 4.28 5.00 6.55 1.84 4.27 2.30 27.76 14.45 P(W)*T P 0.8270 0.0822 0.0147 0.0073 0.0017 0.16100 0.0149 0.1019 <0.0001 <0.0001

118

Supplementary Table 4.6. Results of ANOVAs for proportional measures of expression for each opsin by time (bold denotes P < 0.05). T1- 07:30, T2- 10:30, T3- 13:30, T4- 16:30, W- Watershed, T- Time, P(W)- Predation nested in watershed.

LWS-1 LWS-2 LWS-3 LWS-R SWS1 SWS2A SWS2B RH21 RH22

F(1,68) 3.67 9.00 1.37 6.34 2.12 9.33 0.60 7.22 15.13 W P 0.0593 0.0037 0.2450 0.0142 0.1500 0.0032 0.4410 0.0091 0.0002 T1

F(2,68) 9.48 0.44 1.35 12.88 3.35 7.63 1.90 2.83 4.05 P(W) P 0.0002 0.6427 0.2640 <0.0001 0.0410 0.0010 0.1570 0.0661 0.0217

F(2,67) 3.17 5.71 3.39 0.07 3.77 0.22 0.37 4.51 5.58 W P 0.0792 0.0196 0.0697 0.7906 0.0565 0.6381 0.5480 0.0373 0.0211 T2 F(2,67) 12.43 1.238 12.42 4.74 1.39 2.78 9.32 3.06 6.31 P(W) P <0.0001 0.2964 <0.0001 0.0118 0.2565 0.0694 0.0003 0.0533 0.0031

F(1,68) 0.12 2.61 0.17 9.93 35.31 0.11 1.27 9.27 1.37 W P 0.7241 0.1106 0.6765 0.0024 <0.0001 0.7470 0.2645 0.0033 0.246 T3 F(2,68) 8.34 2.57 4.88 0.36 6.74 1.52 4.07 6.07 19.92 P(W) P 0.0005 0.0833 0.0104 0.6927 0.0021 0.2270 0.0214 0.0038 <0.0001

F(1,68) 0.22 11.33 0.30 0.00 20.41 1.95 0.01 5.24 4.83 W P 0.6343 0.0012 0.5816 0.9798 <0.0001 0.1674 0.9108 0.0252 0.0314 T4 F(2,68) 5.63 4.81 6.25 2.98 0.331 3.62 12.62 1.24 16.53 P(W) P 0.0054 0.0110 0.0032 0.0574 0.7200 0.0321 <0.0001 0.2974 <0.0001

119

Supplementary Table 4.7. Results of ANOVAs for relative(hk) measures of expression for each opsin by time (bold denotes P < 0.05). T1- 07:30, T2- 10:30, T3- 13:30, T4- 16:30, W- Watershed, T- Time, P(W)- Predation nested in watershed.

2.01 2.96 RH1 6.04 5.71 6.58 5.89 6.39 11.10 0.1606 0.0587 0.0165 0.0051 0.0014 0.0025 0.0179 0.0029

3.83 7.11 9.61 RH22 18.50 11.37 15.03 11.42 12.49 0.0002 0.0007 0.0264 0.0096 0.0002 <0.0001 <0.0001 <0.0001

3.12 0.02 0.57 1.96 4.57 4.01 RH21 15.37 29.85 0.0505 0.8836 0.4520 0.1480 0.0002 0.0362 0.0226 <0.0001

2.07 0.34 0.13 0.46 2.03 4.75 5.25 4.14 0.1550 0.5606 0.7170 0.5020 0.1390 0.0117 0.0076 0.0200 SWS2B

1.51 2.16 0.08 2.44 0.46 0.74 8.15 3.18 0.2240 0.1230 0.7730 0.0948 0.4990 0.4820 0.0057 0.0479 SWS2A

0.01 1.59 6.24 6.65 5.86 12.93 21.94 11.88 SWS1 0.9416 0.2119 0.0033 0.0121 0.0045 0.0006 0.0009 <0.0001

R - 1.19 0.16 2.84 1.57 2.26 5.01 9.75 8.02 0.2801 0.6919 0.0655 0.2140 0.1120 LWS 0.0093 0.0026 0.0007

- 1.02 1.02 0.00 1.61 0.67 1.58 5.43 4.80 0.3160 0.3650 0.9847 0.2089 0.4170 0.2140 LWS 0.0065 0.0112

- 0.03 1.70 2.49 0.17 3.91 1.17 5.52 6.83 0.8566 0.1963 0.0905 0.8450 0.0522 0.3175 LWS 0.0060 0.0110

- 0.00 2.68 2.36 4.24 6.80 5.89 6.75 4.84 0.9649 0.0759 0.1017 LWS 0.0433 0.0020 0.0178 0.0021 0.0313

P P P P P P P P 1,68) (1,68) (2,68) (2,67) (2,67) ( (2,68) (1,68) (2,68) F F F F F F F F

W W W W P(W) P(W) P(W) P(W)

T1 T2 T3 T4

120

Supplementary Table 4.8. ANOVA table of proportional measures of opsin expression subset by watershed and run by predation for gene-time point combinations that had a significant watershed*predation interaction (bold denotes P < 0.05). Note: Aripo watershed had an F1,33 at timepoint 2 due to one sample being discarded.

Timepoint 1 Timepoint 2 Timepoint 3 Timepoint 4

(7:30) (10:30) (13:30) (13:30)

F(1,34) P F(1,34) P F(1,34) P F(1,34) P 8.82 Aripo 3.25 0.0801 0.0055 25.78 <0.0001 1.49 0.2300 (F1,33) LWS-1 Marianne 10.87 0.0023 13.67 0.0007 0.92 0.3450 6.69 0.0142

Aripo ------0.00 0.9650 LWS-2 Marianne ------4.82 0.0351

10.93 Aripo - - 0.0023 10.16 0.0031 2.55 0.1190 (F ) LWS-3 1,33 Marianne - - 20.55 <0.0001 3.85 0.0579 18.31 0.0001

1.23 Aripo 3.43 0.0728 0.2750 - - - - (F1,33) LWS-R Marianne 16.37 0.0003 8.03 0.0077 - - - -

Aripo 3.72 0.0620 - - 1.80 0.1880 - - SWS1 Marianne 2.41 0.1300 - - 6.96 0.0125 - -

Aripo 10.11 0.0031 - - - - 3.65 0.0645 SWS2A Marianne 7.47 0.0099 - - - - 2.692 0.1100

6.56 Aripo - - 0.0152 5.11 0.0303 3.059 0.0893 (F1,33) SWS2B Marianne - - 10.50 0.0027 3.24 0.0805 32.47 <0.0001

Aripo - - - - 14.34 0.0006 - - RH2-1 Marianne - - - - 0.263 0.6110 - -

4.85 Aripo 5.68 0.0229 0.0348 19.14 0.0001 17.13 0.0002 (F1,33) RH2-2 Marianne 0.10 0.7510 8.65 0.0059 20.27 <0.0001 14.8 0.0005

121

Supplementary Table 4.9. ANOVA table of relative(hk) measures of opsin expression subset by watershed and run by predation for gene-time point combinations that had a significant watershed*predation interaction (bold denotes P < 0.05). Note: Aripo watershed had an F1,33 at timepoint 2 due to one sample being discarded.

Timepoint 1 Timepoint 2 Timepoint 3 Timepoint 4

(7:30) (10:30) (13:30) (13:30)

F(1,34) P F(1,34) P F(1,34) P F(1,34) P

Aripo 7.01 0.0122 - - 6.75 0.0137 - - LWS-1 Marianne 0.79 0.3810 - - 4.32 0.0454 - -

Aripo 10.99 0.0022 ------LWS-2 Marianne 4.95 0.0329 ------4.23 Aripo - - 0.0477 7.38 0.0103 - - (F ) LWS-3 1,33 Marianne - - 7.17 0.0113 4.59 0.0394 - -

Aripo 1.04 0.3160 - - 8.02 0.0077 - - LWS-R Marianne 6.75 0.0138 - - 3.64 0.0648 - - 5.93 Aripo 3.24 0.0808 0.0205 2.64 0.1140 - - (F ) SWS1 1,33 Marianne 13.62 0.0008 0.94 0.3400 26.61 <0.0001 - -

Aripo - - - - 3.15 0.0847 - - SWS2A Marianne - - - - 4.01 0.0534 - - 9.26 Aripo 1.02 0.3210 0.0046 6.71 0.0140 - - (F ) SWS2B 1,33 Marianne 9.23 0.0046 3.10 0.0872 3.52 0.0693 - -

Aripo 6.29 0.0171 - - 4.72 0.0370 - - RH2-1 Marianne 33.78 <0.0001 - - 3.71 0.0624 - - 11.86 Aripo 11.38 0.0019 0.0016 3.83 0.0584 9.93 0.0034 (F ) RH2-2 1,33 Marianne 4.00 0.0535 0.27 0.6070 0.64 0.4300 2.88 0.0988 6.49 Aripo 5.70 0.0226 0.0157 6.33 0.0167 - - (F ) RH1 1,33 Marianne 59.58 <0.0001 4.36 0.0443 9.57 0.0039 - -

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Supplementary Table 4.10. Raw measures of environmental parameters.

Total Temperature Conductivity Watershed Predation Day λp50 DO (ppm) pH Dissolved Salinity (ppt) (ºC) (μS/m) Solids (mg/L) 1 611 6.62 25.4 272 7.87 192 0.14 High 2 571 7.52 24.9 330 8.08 221 0.16

3 573 6.74 25.7 338 7.84 233 0.17 1 Aripo 614 6.9 24.8 403 8.03 273 0.2 Low 2 704 7.01 24.4 393 7.14 264 0.19 3 677 7.25 25.4 398 8.13 22.6 0.19 1 651 8.03 24.4 115.8 7.63 77.9 0.05

High 2 567 7.29 24.1 217 7.84 144 0.1 3 585 7.62 24.4 247 7.82 164 0.12 1 555 7.3 24.7 306 8.04 205 0.15

Marianne Low 2 585 7.41 24.3 207 7.81 139 0.1 3 571 7.34 24.1 278 7.99 185 0.13

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Relative (hk) Low Predation Aripo Marianne High Predation

250 * 15 ** 200 *** 10 * 150 * ) Expression ) Expression k 100 * k 5 Proportion

RH1 50

0 0 Relative (h 07:30 10:30 13:30 16:30 Relative (h 07:30 10:30 13:30 16:30 Aripo Marianne

0.6 40 * 40 0.6 *** 30 30 *** 0.4 0.4

) Expression 20 ) Expression 20 k k 0.2 0.2 10 * 10

RH2-1 0.0 0 0 0.0 Proportional Expression 07:30 10:30 13:30 16:30 Proportional Expression Relative (h 07:30 10:30 13:30 16:30 Relative (h 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30

*** 0.5 * 0.5 60 ** 10 * *** 8 0.4 *** 0.4 ** *** 40 ** 6 0.3 0.3 ) Expression ) Expression k ** k 4 0.2 0.2 20 0.1 0.1 RH2-2 2

0 0 0.0 0.0 Proportional Expression Proportional Expression Relative (h 07:30 10:30 13:30 16:30 Relative (h 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 Timepoint Timepoint Timepoint Timepoint Supplementary Figure 4.1. RH opsin expression by population. Stars denote significant differences between high and low predation within the same watershed (see Supplementary Tables S7 and S8).

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Relative (hk) Proportion

Aripo Marianne Aripo Marianne

15 8 0.4 0.4 * *** 6 0.3 0.3 * 10 ) Expression ) Expression 4 *** 0.2 0.2 k k 5 2 0.1 0.1 SWS1

0 0 0.0 0.0 Relative (h Relative (h 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 Proportional Expression 07:30 10:30 13:30 16:30 Proportional Expression 07:30 10:30 13:30 16:30

0.15 0.3 0.04 0.08 **

0.03 0.06 0.10 0.2 ** ) Expression ) Expression 0.02 k k 0.04 0.05 0.1 0.01 0.02 SWS2A 0.00 0.0 0.00 0.00 Relative (h Relative (h Proportional Expression 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 Proportional Expression 07:30 10:30 13:30 16:30

150 50 0.5 0.5 *** 40 0.4 * 0.4 ** 100 * 30 0.3 0.3 ) Expression ) Expression k * k 20 0.2 0.2 50 ** ** 10 0.1 0.1 SWS2B

0 0 0.0 0.0 Relative (h Relative (h 07:30 10:30 13:30 16:30 07:30 10:30 13:30 16:30 Proportional Expression 07:30 10:30 13:30 16:30 Proportional Expression 07:30 10:30 13:30 16:30 Timepoint Timepoint Timepoint Timepoint

Low Predation High Predation

Supplementary Figure 4.2. SWS opsin expression by population. Stars denote significant differences between high and low predation within the same watershed (see Supplementary tables S7 and S8).

125 mec_24_3_oc_Layout 1 16-01-2015 19:14 Page 1

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MOLECULAR ECOLOGY MOLECULAR VOLUME 24 NUMBER 3 ECOLOGY VOLUME 24, NUMBER 3, FEBRUARY 2015 FEBRUARY MOLECULAR 2015

NEWS AND VIEWS Ecological Genomics Perspectives 610 RNA-seq reveals regional differences in 523 Why are marine adaptive radiations rare in Hawai’i? transcriptome response to heat stress in the marine P. C. Wainwright snail Chlorostoma funebralis ECOLOGY L. U. Gleason & R. S. Burton INVITED REVIEWS AND SYNTHESES 628 Secondary successional trajectories of structural and 525 Species are hypotheses: avoid connectivity catabolic bacterial communities in oil-polluted soil FEBRUARYpp.523–698 3, 2015, NUMBER 24, VOLUME assessments based on pillars of sand planted with hybrid poplar E. Pante, N. Puillandre, A. Viricel, S. Arnaud-Haond, S. Mukherjee, T. Sipilä, P. Pulkkinen & K. Yrjälä D. Aurelle, M. Castelin, A. Chenuil, C. Destombe, Speciation and Hybridization D. Forcioli, M. Valero, F. Viard & S. Samadi 643 Characterizing a hybrid zone between a cryptic species pair of freshwater snails ORIGINAL ARTICLES S. Patel, T. Schell, C. Eifert, B. Feldmeyer & Population and Conservation Genetics M. Pfenninger 545 Local adaptation despite high gene flow in the Phylogeography waterfall-climbing Hawaiian goby, Sicyopterus 656 Diet strongly influences the gut microbiota of stimpsoni surgeonfishes K. N. Moody, S. N. Hunter, M. J. Childress, S. Miyake, D. K. Ngugi & U. Stingl R. W. Blob, H. L. Schoenfuss, M. J. Blum & 673 Evolutionary and biogeographical patterns of M. B. Ptacek barnacles from deep-sea hydrothermal vents 564 Establishing the evolutionary compatibility of S. Herrera, H. Watanabe & T. M. Shank potential sources of colonizers for overfished stocks: Ecological Interactions a population genomics approach A. Gonçalves Da Silva, S. A. Appleyard & J. Upston 690 Stability of the gorilla microbiome despite simian immunodeficiency virus infection 580 Mechanistic insights into landscape genetic structure A. H. Moeller, M. Peeters, A. Ayouba, E. M. Ngole, of two tropical amphibians using field-derived A. Esteban, B. H. Hahn & H. Ochman resistance surfaces A. J. Nowakowski, J. A. Dewoody, M. E. Fagan, 698 Corrigendum J. R. Willoughby & M. A. Donnelly 596 Beauty in the eyes of the beholders: colour vision is tuned to mate preference in the Trinidadian guppy (Poecilia reticulata) B. Sandkam, C. M. Young & F. Breden

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Supplementary Figure 4.3. Cover of Molecular Ecology featuring the published version of chapter 5.

Caption: Barrier waterfalls in Trinidadian streams (bottom photo) restrict movement of predators upstream. Upstream guppies are typically very colorful, with high amounts of red and orange male coloration, and strong female preferences to mate with more red and orange males. Sandkam et al. show upstream guppies also express high levels of LWS opsins. The two photos show the dramatic effect of the presence (top left) or absence (top right) of such LWS opsins on the ability to perceive red and orange coloration. Photos by Ben Sandkam, Dr. Felix Breden and Frances Breden. Color blind (protanopia) simulation performed by Etre Limited.

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Chapter 5.

Colour vision varies more among populations than species of live-bearing fish from South America

Publication and Contributions

A version of this chapter is in review at BMC Evolutionary Biology: Sandkam, BA, CM Young, FMW Breden, GR Bourne, and F Breden. Colour vision varies more among populations than species of live-bearing fishes from South America.

Contributions: BAS and FB conceived and designed the project and wrote the manuscript. BAS, GRB, FMWB and FB conducted fieldwork. BAS designed assays and conducted all qPCR work. CMY sequenced all LWS-1 loci.

5.1. Abstract

Sensory Bias models for the evolution of mate preference place a great emphasis on the role of sensory system variation in mate preferences. However, the extent to which sensory systems vary across- versus within-species remains largely unknown. Here we assessed whether color vision varies in natural locations where guppies and their two closest relatives, Poecilia parae and Poecilia picta, occur in extreme sympatry and school together. All three species base mate preferences on male coloration but differ in the colors preferred. Measuring opsin gene expression, we found that within sympatric locations these species have similar color vision and that color vision differed more across populations of conspecifics. In addition, all three species differ across populations in the frequency of the same opsin coding polymorphism that influences visual tuning. Together, this shows sensory systems vary considerably across populations and supports the possibility that sensory system variation is involved in population divergence of mate preference.

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5.2. Introduction

Population divergence is widely accepted as a precursor to speciation (Coyne and Orr 2004), and can occur rapidly due to sexual selection via changes in mate preference (Panhuis et al. 2001). Many hypotheses have attempted to explain the drivers behind changes in mate preference, which fall into two general categories— indirect models, such as Fisher’s runaway and good genes, or direct models such as Sensory Bias (reviewed in Andersson and Simmons 2006; Kuijper et al. 2012). Sensory Bias models emphasize the role of sensory system variation in driving divergence in mate preferences (Ryan and Rand 1993; Basolo and Endler 1995; Endler and Basolo 1998; Boughman 2002; Ryan and Cummings 2013). However, the extent to which sensory systems vary across- versus within-species remains largely unknown. Describing where the variation in sensory systems is partitioned is important for research aimed at directly testing such models of population divergence in mate choice.

Guppies (Poecilia reticulata) have been a valuable model for studies of the evolution of female mate preferences based on visual signals for nearly 100 years (reviewed in Houde 1997; Magurran 2005). Recently, P. reticulata has been shown to vary in the tuning of color vision across populations in a manner that correlates with female mate preferences on the island of Trinidad (Sandkam et al. 2015). In contrast to Trinidad, populations of guppies from mainland South America frequently occur in extreme sympatry and commonly school with two of their closest relatives, Poecilia picta and P. parae (Liley 1965; Breden et al. 1999). These species occupy similar ecological niches and have highly similar morphometrics, with the largest differences between species being male coloration (Liley 1965; Lindholm et al. 2004; Magurran and Ramnarine 2005; Lindholm et al. in review). In all three species, female mate preferences largely rely on male visual cues, yet the male traits preferred by females differ across species (Haskins and Haskins 1949; Liley 1965; Lindholm et al. 2004; Hurtado-Gonzales et al. 2014). Males of P. reticulata have highly variable numbers and colors of spots on their body (Haskins et al. 1961; Liley 1965; Luyten and Liley 1985). In P. parae, males occur in one of five discreet Y-linked morphs: three uni-color morphs (with color pattern dominated by a horizontal stripe that is either: red, yellow, or blue), one female mimic morph (colored like the female and engaging in sneak copulations),

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and one large, aggressive morph (with vertical dark bars and most of its coloration on the caudal fin; Lindholm et al. 2004; Hurtado-Gonzales and Uy 2009). Males of P. picta all have an orange stripe on their caudal fin and yellow bands on their dorsal fin (Liley 1965). While most males of P. picta have no additional color, some males occur as a morph with red running diffusely throughout the entire body, although this red coloration doesn’t strongly influence mating (Lindholm et al. in review) (see Supplementary Figure 5.1 for pictures of the male morphs for all three species). While males occasionally perform courtship displays for heterospecific females, female P. picta do not accept heterospecific males as mates (Liley 1965; Magurran and Ramnarine 2004; 2005). The variable role of color in female mate choice (Rodd et al. 2002; Bourne and Watson 2009), high similarity in niche and morphology, and occurrence in sympatry make these species, P. reticulata, P. picta, P. parae, an excellent system with which to examine whether color vision varies more across species or populations.

Color vision is accomplished by comparing the signals from different cone cells in the retina, which are maximally tuned to different wavelengths of light (Gegenfurtner and Sharpe 1999). The wavelength at which a cone cell maximally detects light is primarily determined by the transmembrane protein expressed, called an opsin (Yokoyama 2000; 2002). P. reticulata, P. picta, and P. parae have an astounding nine cone opsin proteins, among the highest for vertebrates (Hoffmann et al. 2007; Ward et al. 2008; Watson et al. 2011). Each cone opsin is coded by a single gene which is grouped and named for the range of light they detect: SWS1 (SWS1, short wavelength-sensitive) detects ultra-violet; SWS2A and SWS2B (SWS2, short wavelength sensitive 2) detect blues and purples; RH2-1 and RH2-2 (RH2, rhodopsin-like) detect greens; and LWS-1, LWS-2, LWS-3, and LWS-R (LWS, long wavelength-sensitive) detect reds and oranges (Ward et al. 2008; Watson et al. 2011; Sandkam et al. 2012; Tezuka et al. 2014).

Differences in tuning of color vision can occur through changes in either gene sequence or expression (reviewed in Horth 2007). Guppies have been shown to vary in tuning of color vision across populations through both differences in the frequency of an allele known to affect tuning of LWS-1 (Tezuka et al. 2014; Sandkam et al. 2015) and also differences in opsin expression profiles (Sandkam et al. 2015). Opsin expression profiles provide an estimate of cone cell proportions in the retina and thereby offer an

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excellent measure of the allocation of an individual’s color vision repertoire to different cone cell types (Fuller et al. 2003; Fuller and Travis 2004; Cheng and Flamarique 2004; 2007; Parry et al. 2005; Shand et al. 2008; Sandkam et al. 2015). Guppy populations with stronger female preferences for males with more red/orange coloration have higher expression of LWS opsins (Sandkam et al. 2015).

Here, we examined whether there is more variation in visual tuning within species or across species. The occurrence of multiple sympatric locations of the three closely related species P. parae, P. picta, and P. reticulata on mainland South America allows us to examine differences in visual tuning of all three species from the same environment in a replicated manner across populations. By examining visual tuning of each species across multiple locations we are able to assess the variability of opsin expression across populations and compare this to species differences.

5.3. Materials and Methods

5.3.1. Sample Collection

We sampled Poecilia parae, P. picta, and P. reticulata from four sympatric locations within Guyana between 10:00 and 16:00 in June-July 2010 (see Supplementary Table 5.1 for GPS coordinates and Supplementary Figure 5.2 for map). One sympatric location (Seawall Trench) was sampled on two days. Efforts were made to collect five adult males and five adult females of each species at every location; however not all species were present at the same density within locations resulting in smaller sample sizes for some collections (see Supplementary Table 5.1 for sample sizes of each species and population). P. bifurca is a close relative of P. reticulata, P. picta, and P. parae but does not occur sympatrically. Opsin expression for one population of P. bifurca (~79 km from closest sympatric location sampled) is reported here only as a qualitative comparison and is not included in statistical analyses. All four species occur in similar environments; small drainage ditches of Guyana that are usually only a few meters wide and less than a meter deep (Liley 1965). Adult males show pronounced species specific coloration, while females are all grey with minor differences in black patterning around the urogenital opening; these traits allow us to rapidly perform

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visual identification of species and sex (Rosen and Bailey 1963). Sampling followed the protocols of Sandkam et al. (2015). Briefly, adult fish were caught with dip nets— individuals were rapidly sacrificed in an overdose of MS-222, measured and photographed. We immediately removed eyes and made a small puncture to facilitate complete penetration of RNAlater® Stabilization Solution (Life Technologies™). Both eyes from an individual were placed into a vial of RNAlater® and kept on ice for 24 hours, to allow tissue to be saturated per manufacturer’s recommendation. After 24 hours, we transferred the vials to liquid nitrogen. The vials were removed from liquid nitrogen just prior to being placed in checked baggage and flown to Simon Fraser University where we placed them in a -20°C freezer until RNA extraction. Time spent at room temperature totalled less than 24 hours and fell well under the one-week maximum suggested by manufacturer. The bodies of individuals sampled were placed in tubes of 95% EtOH buffered with EDTA and kept at -20ºC until DNA extraction.

5.3.2. qPCR Assay Design

To measure opsin expression, we designed qPCR assays following the methods of Sandkam et al. (2015). We modified the primers reported in Sandkam et al. for P. reticulata, such that one set of qPCR assays could be used across all four species. Sequences from P. reticulata, P. picta, P. parae, and P. bifurca were aligned and viewed using SeqMan Pro (Lasergene 8.0; DNASTAR, Madison, WI). We designed probe based PrimeTime® qPCR assays (IDT® Technologies) in regions of conserved sequence such that there were no SNPs between any of the four species or primer/probe combinations. Assays were designed to be specific for each of the nine opsins, one rhodopsin (RH1), and three housekeeping genes (beta actin (B-actin); cytochrome c oxidase subunit I (COI); myosin heavy chain (Myosin HC)). Whenever possible, primers spanned intron- exon boundaries. Each assay consisted of a forward primer, reverse primer and 5’ FAM labeled probe with both 3’ Iowa Black® and internal ZEN™ quenchers (IDT® Technologies) (for primer/probe sequences and product length see Supplementary Table 5.2). Assay specificity for each species was verified by the presence of a single band when running PCR products on an agarose gel. Within each species, LWS-1 and LWS-R assays resulted in products of the same size, while LWS-1 and LWS-3 loci are similar in sequence. To ensure that LWS-1, LWS-3, and LWS-R were truly locus specific

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assays, we measured the pairwise covariance of these three assays on the final relative(hk) data set (described below) using R v3.0.2 (R Development Core Team 2014). If assays were binding to non-specific targets we would expect to see large positive covariances between assays. We found no substantial covariance in any of the four species between either LWS-1 and LWS-R (covariance: P. reticulata, -9*10-6; P. parae, 0.0011; P. picta, -0.001; P. bifurca, -0.0028) or LWS-1 and LWS-3 (covariance: P. reticulata, -1*10-6; P. parae, 0.0066; P. picta, 0.0004; P. bifurca, 0.0059), demonstrating locus specificity of the LWS assays.

We determined the relative PCR efficiency (Ei) for each assay as in Sandkam et al. (2015), using four gBlocks® Gene Fragments (synthetic double stranded, sequence- verified genomic blocks made by IDT® Technologies). gBlocks® were designed on sequence from P. reticulata and contained sequence for each of the genes being assayed from 20 bp upstream of the forward primer to 20 bp downstream of the reverse primer. To ensure equal proportions of each gene when calculating relative efficiency, we adjusted the length of each opsin gBlocks® to 728 bp by adding upstream and downstream sequence from the first and last opsin. There were less than seven SNPs per gene across the four species in regions spanned by the assays and none of these differences occurred in primer/probes sites. Relative primer efficiencies calculated using these constructs were used for all four species. Gene order in the gBlocks® was randomized: gBlock® 1 contained LWS-1, RH1, SWS1, LWS-R; gBlock® 2 contained SWS2B, LWS-3, RH2-2; gBlock® 3 contained LWS-2, SWS2A, RH2-1; and gBlock® 4 contained B-actin, COI, Myosin-HC. The 4 gBlocks® were mixed in equal proportions and brought to a concentration of 0.001 ng/µl resulting in a control with equal ratios of all the opsin and housekeeping genes. We ran six replicates of each assay using 4.5 µl of the control. The relative primer efficiencies (Ei) were then calculated following Carleton and Kocher (2001) using the equation:

Ct (1+1) High = 1 Cti (1+ Ei )

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such that CtHigh is the critical threshold of the opsin with the highest expression

(lowest Ct value) and Cti is the critical threshold for opsin i. The mean relative efficiency and standard error was calculated across the six replicates (Supplementary Table 5.2).

The SWS2A assay had the highest relative efficiency and was used to measure absolute efficiency. A thousand fold serial dilution was made of a random sample of P. picta. Three replicates of qPCR were performed on each concentration using the SWS2A assay. The absolute efficiency of COI was found using the slope of

−slope ln(concentration) plotted on Ct such that ESWS2 A = e −1 . The absolute efficiencies of the other primer/probes were determined following Fuller et al. (2004) using the equation:

absolute Ei = (relative Ei × absolute ESWS2 A ) relative ESWS2 A

5.3.3. Sample Processing and Analyses for Opsin Expression

Sample processing followed Sandkam et al. (2015). We placed both eyes from one individual in 600 uL of TRIzol® reagent (Life Technologies™) and ground them with a 1.5 mL RNase-free Kontes® Pellet Pestle Grinder (Kimble Chase). Solution was then run through an Ambion® Homogenizer (Life Technologies™) to reduce viscosity. We extracted RNA following the manufacturer’s instructions using PureLink® RNA Mini Kits with the addition of on column treatments with PureLink® DNase (Life Technologies™) to eliminate any potential genomic contamination during qPCR. To verify quality of extracted RNA we ran a subset of samples on an Experion Bioanalyzer. RNA concentrations were adjusted to 50 ng/uL using UltraPure™ DNase/RNase-Free Distilled Water (Life Technologies™). For each sample 500 ng RNA was reverse transcribed using a High Capacity cDNA Reverse Transcription Kit with RNase Inhibitor (Life Technologies™) following manufacturer’s instructions. cDNA samples were diluted roughly 20-fold using UltraPure™ DNase/RNase-Free Distilled Water (Life Technologies™) for use in qPCR reactions. Triplicate qPCR reactions were run on each individual for the nine opsins, one rhodopsin, and three housekeeping genes using the qPCR probe based assays described above. We ran all 39 reactions for each individual

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simultaneously on the same 384 well plate in addition to negative controls (UltraPure™ water) for each assay. Each 10 uL reaction consisted of: 5 uL Brilliant III Ultra-Fast qPCR Master Mix (Agilent Technologies), 0.5 uL FAM labeled assay (described above) and 4.5 uL sample. We set up all reactions on ice and the plates were briefly spun down before being run on an Applied Biosystems® 7900HT qPCR machine (Life Technologies™). PCR conditions were as follows: 95°C for 3:00 followed by 40 cycles of 95°C for 0:05, 60°C for 0:15. The standard deviation of the triplicate reactions was taken and when >2, outliers were removed (comprising only 5% of the 5538 reactions for this study).

We assessed differences in color vision by calculating the proportion of total opsin expression (Tall) made up of each opsin (Ti) following Fuller et al. (2004) and Carleton and Kocher (2001) with the following equation:

Cti 1 (1+ Ei ) Ti ( ) = ( ) Cti Tall 1 1+ E ∑( (( i ) ))

where Ei is the mean primer/probe efficiency of assay i and Cti is the mean critical cycle number for gene i (expression of the nine opsins adds to one for each individual).

We assessed differences in regulation of the nine opsin and one rhodopsin genes by comparing expression relative to housekeeping genes (THouse). To control for random variation in housekeeping gene expression, we took the average of three housekeeping genes (Vandesompele et al. 2002). We calculated measures following Sandkam et al. (2015) using the equation:

Cti T 1 (1+ Ei ) i = ( ) CtHouse THouse 1 1+ E 3 ((∑( ( House ) )) )

where EHouse is the primer/probe efficiency for a housekeeping gene and CtHouse is the critical cycle number for that gene.

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This resulted in each individual having two measures for each opsin: the proportion of total opsin expression made up by that opsin (proportional), and relative to housekeeping genes (relative(hk)). As opsins are the major differentiating character of cone cell types, and color vision is accomplished by comparing the signal from different cone cell types, proportional measures of opsin expression provide a measure of color vision (Fuller et al. 2004; Fuller and Claricoates 2011). Differences in regulation of individual opsins compared to overall gene transcription are revealed by relative(hk) measures of opsin expression, whereas overall gene activity is measured as the mean of the three housekeeping genes (Fuller and Claricoates 2011; Sandkam et al. 2015).

5.3.4. LWS-1 A/S Allele Frequency

Variation in visual systems across species or populations can also occur through differences in the frequency of polymorphisms known to alter tuning of the visual pigments. Only LWS-1 is known to possess a polymorphism that alters spectral tuning in P. parae, P. picta, or P. reticulata (Ward et al. 2008; Tezuka et al. 2014; Sandkam et al. 2015). The key difference between these alleles is the presence of either a serine or alanine as the amino acid at the position that corresponds to residue 180 in human M/LWS opsins (termed ‘LWS-1 (180 Ser)’ and ‘LWS-1 (180 Ala)’ respectively). This polymorphism can result in a change of tuning of the LWS-1 opsin protein by up to 15nm (Ward et al. 2008). To determine species and population frequencies of the LWS-1 (180 Ala) and LWS-1 (180 Ser) polymorphism we extracted genomic DNA from tail tissue of the same individuals we used for expression analyses using a DNeasy blood and tissue kit (Qiagen). We generated PCR products using 5’ and 3’ UTR-specific primers of the LWS-1 locus. Internal sequencing primers were used directly on PCR products to generate chromatograms, spanning part of exon 2 and all of exon 3, at Molecular Cloning Laboratories (McLab, San Francisco, CA) (for primer sequences see Supplementary Table 5.3). We viewed and analyzed the sequencing chromatograms using SeqMan Pro (LASERGENE 8.0; DNASTAR, Madison, WI). For each individual, we determined if the 180 amino acid residue was either a serine, alanine or heterozygous.

We calculated genotype and allele frequencies for each species in each location. FST values based on the frequency of alleles with a serine at amino acid position 180 were

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calculated two ways; between species within the same location, and within species across populations. FST values were calculated as in Sandkam et al. (2015), using:

var(S) F = ST S × (1− S ) where var(S) is the variance of the frequency of the serine allele, either across species

(within locations) or across populations (within species), and S is the frequency of the serine allele in either the location or species (respectively).

5.3.5. Statistical Analyses of Opsin Expression

Do species and/or populations differ in colour vision?

To test whether closely related sympatric species differ in either proportional or relative(hk) measures of opsin expression profiles, we ran MANOVAs with the levels for each of the nine cone opsins log transformed and treated as dependent variables. Sex was nested within Species and since Locations were sampled at different times of the day, which can impact opsin expression (Sandkam et al. 2015), we further nested Species within Location. All expression data were analyzed using R v3.0.2 (R Development Core Team 2014).

Sex had no main or interaction effect (Table 1). There are no differences between sexes in opsin expression of natural guppy populations on Trinidad (Sandkam et al. 2015), nor for opsin expression in most other species in which it has been examined (such as stickleback (Gasterosteus aculeatus)- Boulcott and Braithwaite 2006; and killifish (Lucania goodei)- Johnson et al. 2013). Therefore we pooled sexes for all of the following analyses.

Does opsin expression differ more by species or locations?

Akaike Information Criterion (AIC) scores were calculated by Species, Location, or a Species*Location interaction to determine the ability of models built on these factors to explain variation in proportional expression for each of the opsin genes.

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How do species differ in colour vision?

To better understand differences in colour vision across species within the same population, independent ANOVAs on data subset by population were run by Species. Opsins that significantly differed in ANOVAs were followed up with a Tukey test to determine which of the species contributed to the significant effects.

5.4. Results

5.4.1. Do species and/or populations differ in color vision?

Across all populations and species SWS2A, RH2-2, LWS-2, LWS-3, and LWS-R showed rather low levels of expression compared to other opsin genes (Figures 5.1, 5.2). The most abundant opsin expressed was either SWS1 or LWS-1 but varied across populations and species (Figure 5.1). MANOVAs revealed that colour vision, as measured by differences in opsin expression, varied significantly within species across populations and within populations across species (Table 5.1). However, expression profiles did not vary by sex (nested in species-in populations) for either proportional

(F12,109 = 1.1275, P = 0.1872) or relative(hk) (F12,109 = 0.977, P = 0.5490) measures.

5.4.2. Does opsin expression differ more by species or location?

We found opsin expression to vary significantly by Location and Species nested within Location. To determine if Species, Location or a Location*Species interaction best explained variation in proportional expression we calculated AIC scores. Location alone best explained variation in SWS1, SWS2B, RH2-1, RH2-2, and LWS-1 (Table 5.2). Location and Location*Species explained the variation equally well for SWS2A and LWS-3, as seen by AIC scores differing by less than 2 for these two models in both genes. Location and Species explained variation of LWS-R equally well with AIC scores within 1 for these two models. Only for LWS-2 did Species best explain variation in opsin expression (Table 5.2). Overall, we found that variation in color vision, as measured by opsin expression, was better explained by Location than by Species.

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5.4.3. How do species differ in color vision?

When relative(hk) measures of opsin expression differed by species, P. parae generally had highest expression (Figure 5.2). Despite differences in the abundance of opsin expression, colour vision was highly similar across species, as indicated by few occurrences in which locations differed in proportional measures of opsin expression across species (10 of 45 possible opsin by location combinations tested) (Table 5.3).

5.4.4. Gene Frequencies of the 180 Ala vs. Ser Allele Vary Across Species

We found within-species gene frequencies were similar across locations, but across-species gene frequencies differed within locations such that P. reticulata showed higher frequencies of alleles with LWS-1 (180 Ala) than either P. parae or P. picta

(Figure 5.3). The FST scores we observed confirmed low differences within species in the frequency of the serine allele across locations, with the most variation occurring in P. parae (FST = 0.1304) (Table 5.4). The within location differences in frequency of the serine allele observed across species were moderate, as demonstrated by FST scores between 0.336 – 0.608 (Table 5.4). This is a result of the high frequency of LWS-1 (180 Ala) in P. reticulata while it is nearly absent in P. parae and P. picta. However, while qualitative differences in frequency and FST scores are clear, one should take care when interpreting the results quantitatively as the samples sizes were low (ranging from 2-20 individuals) (Figure 5.3).

5.5. Discussion

Intersexual mate choice was first proposed as a mechanism for speciation through divergence in the traits preferred (Darwin 1871). Over time, divergence of populations has widely been accepted as the first step toward speciation (Coyne and Orr 2004). Therefore, understanding the factors involved in population divergence of mate choice has far reaching implications to many fields including animal behaviour and evolutionary biology. Sensory Bias models for the evolution of mate preference place a strong emphasis on the role of sensory system variation in mate preferences (Ryan and

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Rand 1993; Basolo and Endler 1995; Endler and Basolo 1998; Boughman 2002; Ryan and Cummings 2013). However, the extent to which sensory systems vary across, versus within, species remains largely unknown. Here we describe variation in color vision across three closely related sympatrically occurring species. We found that color vision varies across populations but does not vary consistently between species across locations. Below we describe the variation we found and discuss our findings in the framework of mate choice evolution.

5.5.1. Colour Vision Differs Across Populations Within Species

Visual systems are classically thought to show low to no variation across individuals within a species, especially when color vision is modeled in the context of mate choice (such as Endler 1991; Kemp et al. 2009; Hurtado-Gonzales et al. 2014; Cole and Endler 2015). Yet color vision can vary through differences in the abundance of different cone cell types, amino acid sequences of the opsin proteins, or neural processing of signals from the eyes (Horth 2007). Opsin expression profiles provide an estimate of the ratio of cone cells expressing different opsins in the eyes, which can impact color vision (Carleton and Kocher 2001; Fuller et al. 2004; Horth 2007; Sandkam et al. 2015). We present the first study of opsin expression in P. bifurca, P. parae and P. picta, and one of the few to carefully compare within versus between species color vision in similar environments. We demonstrate that color vision in these species, and sympatric P. reticulata, likely differs across populations through differences in opsin expression, and could differ through frequency of an alternative amino acid sequence.

Color vision of P. parae from nearby Guyanan populations has recently been explored using microspectrophotometry (MSP) to identify the peak wavelength sensitivity

(λmax) of the cone cells (Hurtado-Gonzales et al. 2014). While P. parae possess nine opsin genes, Hurtado-Gonzales and colleagues only found seven cone cell types across individuals. This can be explained by the low-to-no expression of both SWS2A and LWS-2 we found, emphasizing the important role of expression in tuning the visual system. While our measures of opsin gene expression provide insight to differences in color vision, it is possible that the exact cone cell proportions could differ from measures

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of proportional RNA expression through differences in non-transcriptional control such as translation rates.

The long wavelength-sensitive-1 (LWS-1) opsin is the only opsin in Poeciliidae known to vary in tuning due to differences in amino acid sequence. The LWS-1 opsin can either have an Alanine or Serine at the site corresponding to the 180th amino acid in the human opsin sequence and is therefore termed: LWS-1 (180 Ala) and LWS-1 (180 Ser) respectively. The frequency of these two alleles varies across populations in P. reticulata (Tezuka et al. 2014; Sandkam et al. 2015). This same variation is also thought to be the only sequence difference in important tuning sites across the species P. reticulata, P. parae, P. picta, and P. bifurca where as the later three have, until now, been thought to be fixed for either LWS-1 (180 Ala) or (180 Ser) (Ward et al. 2008). Using the ‘five site rule’ (Yokoyama and Radlwimmer 1998), Tezuka et al. (2014) estimated the λmax of the LWS-1 (180 Ala) to be ~553 nm and LWS-1 (180 Ser) to be ~560nm. Previously P. parae was thought to possess only one LWS-1 allele (180 Ser), however we show that P. parae also possesses the alternate LWS-1 (180 Ala), albeit at a low frequency. Interestingly, only 5 out of the 17 individuals (29.4%) examined by

Hurtado-Gonzales et al. (2014) possessed cone cells with a λmax of 553 ± 1.9 nm, this matches the predicted λmax of LWS-1 (180 Ala) (Tezuka et al. 2014). The closest location to the populations sampled by Hurtado-Gonzales et al. we sampled for this study was West Patentia, where 22.2% of individuals had at least one copy of LWS-1 (180 Ala). The close proximity and lack of geographic barrier between these two populations makes it likely that allele frequencies are similar in these populations. The close frequencies of individuals with λmax of 553 (Hurtado-Gonzales et al. 2014) and those with the LWS-1 (180 Ala) (this study) suggest variation in allele frequency across populations likely explains the presence/absence of cone cell types across individuals and further demonstrates that color vision varies across individuals in P. parae. We found differences across populations in the frequency of LWS-1 (180 Ala) in all three species (except for the allopatric species, P. bifurca which appears fixed for LWS-1 (180 Ala)) and demonstrate that color vision differs across populations not only in opsin expression, but also through differences in tuning of the opsins.

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The frequency of the LWS-1 (180 Ala) allele varies across P. reticulata populations in Trinidad such that low predation populations are nearly fixed for the LWS- 1 (180 Ser) allele while high predation populations had a greater frequency of the LWS-1 (180 Ala) allele. All the populations we use in this study are in the lowland region of Guyana where predation is extremely high (predators include birds, snakes, caiman and many fishes). Interestingly, for all of our populations of P. reticulata, the frequency of the LWS-1 (Ala) allele was as high or higher than the high predation populations of Trinidad (Sandkam et al. 2015) highlighting the potential role of predation in determining LWS-1 allele frequencies.

We also found the closely related but not sympatric species, P. bifurca, has a similar color vision system to P. picta, P. parae and P. reticulata. P. bifurca lives in environments that are generally tannin stained and occur further inland, thereby further demonstrating the surprisingly conserved nature of color vision across species in this group.

It should be noted that sites were not all sampled at the same time of day, therefore differences across populations could be confounded with diurnal variation in opsin expression, which has been shown to occur in Trinidadian guppy populations (Sandkam et al. 2015). However, the diurnal differences across locations are expected to occur in all three of the sympatric species; therefore we feel our cross- versus within- species comparisons are justified.

5.5.2. Sensory variation and mate choice divergence

For sensory systems to play a role in mate choice divergence there needs to be variation in sensory systems (Ryan 1990; Ryan and Cummings 2013). We recently found support for the Sensory Exploitation model to explain population divergence in female mate preferences of Trinidadian guppies (Poecilia reticulata) (Sandkam et al. 2015) such that populations with stronger female preferences for orange male coloration expressed higher levels of LWS opsins. These results raised two important questions regarding the feasibility of sensory variation to explain mate choice differences: (1) was population variation in sensory systems present before the split of the guppy from the

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clade of P. picta and P. parae, and (2) if there is variation in other species, do visual systems vary more across species or populations?

We found visual systems do vary in both opsin gene expression and LWS-1 allele frequency across populations of P. parae, P. picta, and P. reticulata on mainland South America. Although these three species occur in such extreme sympatry that they frequently school together, they exhibit female preferences for males with different color traits (Haskins and Haskins 1949; Liley 1965; Bourne et al. 2003). All three of these species are known to vary in the frequency of their respective different male morphs across populations (P. parae- Hurtado-Gonzales et al. 2014; P. picta- Lindholm et al. in review; P. reticulata- Alexander et al. 2004). It will be especially interesting for future work to determine if the variation we found in visual systems across populations correlates with differences in mate choice.

As more species are shown to vary in sensory systems across populations [e.g. Bluefin killifish (Fuller et al. 2004), cichlids (Smith et al. 2010), stickleback (Flamarique et al. 2013), sand goby (Larmuseau et al. 2009), pied flycatchers (Lehtonen et al. 2011), guppies (Sandkam et al. 2015)], Sensory Bias models become a more likely candidate to explain divergence in mate preferences across species. This raises the question of whether differences in mate preference across species are maintained through consistent differences in their peripheral sensory systems. We found variation in color vision, as measured by opsin expression, is better explained by location than by species for most of the opsins, showing no consistent differences across species. Our data suggest mate preferences are likely maintained at another level of preference (such as higher order processing). However, we did find that the frequency of the LWS-1 (180 Ala) allele not only differs across populations, but also across species. This raises the possibility that the minor tuning differences between the LWS-1 (180 Ala) and LWS-1 (180 Ser) alleles could also play a role in mate choice differences across species. It will be interesting for future work in these species to investigate the correlation between color preference and genotype to further our understanding of visual tuning and mate preference.

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5.6. Conclusion

We show that color vision, as measured by opsin expression, differs more across populations of the same species than across species in the same location. These differences provide support for Sensory Bias models to explain population divergence in mate preference since these models rely on sensory system differences across populations. Opsin expression did not differ consistently between species across locations, suggesting species level differences in mate preference are likely maintained at levels of higher order processing.

Acknowledgements

We wish to thank Orrin Clarke, Selwin France, and Joyce Wade for assistance in the field; Dr. William Davidson and Dr. Krzysztof Lubieniecki for use of their qPCR machine at Simon Fraser University; and CEIBA Biological Center for hosting us during fieldwork. We acknowledge the Guyana EPA for issuing research permit # 120710 BR 135.

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Tables and Figures

Proportional Relative(hk)

F(3,109) 7.13 5.87 Population P <0.0001 <0.0001

F(8,109) 1.61 2.04 Species(Population) P 0.0014 <0.0001

F(12,109) 1.13 0.98 Sex(Species(Population)) P 0.1872 0.5490

Table 5.2. AIC values for the ability of models based on Location, Species, or Location*Species to explain variation in proportional measures of opsin expression for each opsin gene. Bold indicates P < 0.05.

df SWS1 SWS2A SWS2B RH2-1 RH2-2 LWS-1 LWS-2 LWS-3 LWS-R

Location*Species 13 -156.12 -2015.89 -147.09 -244.66 -847.86 -71.63 -1022.10 -678.85 -626.69 Location 5 -160.52 -2014.14 -154.32 -255.37 -855.18 -78.62 -1024.31 -677.00 -630.76 Species 4 -152.08 -2008.59 -134.21 -250.90 -839.24 -70.27 -1027.32 -669.96 -631.74

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Table 5.3. Results of opsin expression ANOVAs using proportional and relative(hk) measures by location. Bold indicates P < 0.05.

Seawall Trench Seawall Trench Princess Cemetery Turkeyen West Patentia Day 1 Day 2

F(2,27) P F(2,21) P F(2,28) P F(2,23) P F(2,19) P

SWS1 1.97 0.1590 10.11 0.0008 2.15 0.1350 0.21 0.8100 3.03 0.0722 SWS2A 3.22 0.0556 2.64 0.0951 0.25 0.7810 0.83 0.4500 23.86 <0.0001 SWS2B 0.06 0.9460 1.37 0.2750 1.24 0.3060 0.98 0.3911 2.40 0.1170

Measures RH2-1 0.02 0.9840 9.94 0.0009 2.85 0.0747 2.09 0.1470 0.28 0.7590 RH2-2 0.94 0.4030 4.44 0.0247 0.79 0.4660 1.89 0.1730 8.56 0.0022 LWS-1 3.45 0.0464 10.03 0.0009 5.17 0.0123 1.26 0.3020 0.62 0.5470

Proportional Proportional LWS-2 1.71 0.1990 4.88 0.0182 0.86 0.4350 1.20 0.3200 4.01 0.0354 LWS-3 0.38 0.6880 2.58 0.0999 2.41 0.1090 0.12 0.8880 0.57 0.5740 LWS-R 0.60 0.5580 1.65 0.2160 0.96 0.3960 1.03 0.3730 1.59 0.2290

SWS1 8.84 0.0011 19.99 <0.0001 4.35 0.0227 1.14 0.3370 5.30 0.0149 SWS2A 4.22 0.0253 0.90 0.4220 0.76 0.4790 0.75 0.4820 4.47 0.0256

SWS2B 2.71 0.0847 9.98 0.0009 3.85 0.0332 0.73 0.4920 5.55 0.0126 RH2-1 3.46 0.0429 18.74 <0.0001 0.76 0.4760 2.65 0.0922 7.49 0.0040 RH2-2 4.19 0.0259 2.04 0.1550 1.52 0.2370 0.80 0.4630 0.82 0.4550 Measures

(hk) LWS-1 15.04 <0.0001 2.94 0.0747 2.91 0.0711 3.99 0.0323 13.52 0.0002 LWS-2 10.05 0.0005 5.67 0.0108 0.16 0.8560 0.56 0.5800 1.32 0.2030 Relative LWS-3 1.75 0.1930 11.42 0.0004 1.65 0.2110 0.68 0.5160 0.44 0.6520 LWS-R 1.22 0.3110 2.34 0.1210 1.15 0.3310 1.00 0.3820 0.72 0.5000 RH1 5.55 0.0096 5.73 0.0103 2.66 0.0876 6.19 0.0045 12.64 0.0003

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Table 5.4. FST based on the frequency of the 180 Ser allele of LWS-1. Calculated across populations of the same species or across species in the same population.

Within Species – Across Populations P. parae P. picta P. reticulata

Fst 0.130 0.077 0.033 Within Locations – Across Species Princess Seawall West Turkeyen Cemetery Trench Patentia

Fst 0.609 0.353 0.385 0.336

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Princess Cemetary Turkeyen West Patentia 0.6 0.6 0.6

0.4 0.4 0.4

A A B B 0.2 0.2 0.2

B B A B A A A

Proportional Expression 0.0 0.0 0.0 SWS1 SWS1 SWS1 RH2-1 RH2-2 RH2-1 RH2-2 RH2-1 RH2-2 LWS-1 LWS-2 LWS-3 LWS-1 LWS-2 LWS-3 LWS-1 LWS-2 LWS-3 LWS-R LWS-R LWS-R SWS2A SWS2B SWS2A SWS2B SWS2A SWS2B

Seawall Trench-Day 1 Seawall Trench-Day 2 West Watuka 0.6 0.6 0.6 A A B A A B

0.4 0.4 0.4

B A A B B 0.2 A A 0.2 0.2

B B B A A A A

Proportional Expression 0.0 0.0 0.0 SWS1 SWS1 SWS1 RH2-1 RH2-2 RH2-1 RH2-2 RH2-1 RH2-2 LWS-1 LWS-2 LWS-3 LWS-1 LWS-2 LWS-3 LWS-1 LWS-2 LWS-3 LWS-R LWS-R LWS-R SWS2A SWS2B SWS2A SWS2B SWS2A SWS2B

Parae Picta Reticulata Bifurca

Figure 5.1. Proportional measures of opsin expression across species and locations. Letters denote significant differences in expression of individual opsins across species within a location. Note: West Watuka has only P. bifurca and was not used in statistical analyses.

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Princess Cemetary Turkeyen West Patentia 0.20 0.5 0.8 A A A A A A B B 0.4 B B 0.15 0.6

0.3

Expression 0.10 A A 0.4 B B 0.2 (hk) A B A A A 0.05 B C 0.2 0.1 B B A A B B A A A A B B A A B B B B A BA B B Relative 0.00 0.0 0.0 SWS1 SWS1 SWS1 RH2-1 RH2-2 RH2-1 RH2-2 RH2-1 RH2-2 LWS-1 LWS-2 LWS-3 LWS-1 LWS-2 LWS-3 LWS-1 LWS-2 LWS-3 LWS-R LWS-R LWS-R SWS2A SWS2B SWS2A SWS2B SWS2A SWS2B

Seawall Trench-Day 1 Seawall Trench-Day 2 West Watuka 0.6 A 0.8 5

4 0.6 0.4 A A B B 3

Expression 0.4 A

(hk) BB 2 0.2 A B B 0.2 B B 1 B A A A B B

Relative 0.0 0.0 0 SWS1 SWS1 SWS1 RH2-1 RH2-2 RH2-1 RH2-2 RH2-1 RH2-2 LWS-1 LWS-2 LWS-3 LWS-1 LWS-2 LWS-3 LWS-1 LWS-2 LWS-3 LWS-R LWS-R LWS-R SWS2A SWS2B SWS2A SWS2B SWS2A SWS2B

Parae Picta Reticulata Bifurca

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P. parae P. picta P. reticulata

S/S - 100% S/S - 100% S/S - 0% A/S - 0% A/S - 0% A/S - 60% A/A - 0% A/A - 0% A/A - 40% Princess Cemetery N = 9 N = 10 N = 10

S/S - 100% S/S - 100% S/S - 45% A/S - 0% A/S - 0% A/S - 20% A/A - 0% A/A - 0% A/A - 35% Trench Seawall N = 11 N = 17 N = 20

S/S - 100% S/S - 90% S/S - 40% A/S - 0% A/S - 0% A/S - 0% A/A - 0% A/A - 10% A/A - 60%

Turkeyen N = 10 N = 10 N = 5

S/S - 77.8% S/S - 100% S/S - 30% A/S - 11.1% A/S - 0% A/S - 20% A/A - 11.1% A/A - 0% A/A - 50% West

Patentia N = 9 N = 2 N = 10

180 Ala allele 180 Ser allele

Figure 5.3. Genotype and gene frequencies of the 180 Ala (A) versus 180 Ser (S) allele of LWS-1. LWS, long-wavelength sensitive.

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Supplementary Tables

Supplementary Table 5.1. GPS location and sample size for each location. Note: West Watuka has only P. bifurca and was not used in statistical analyses.

Time Salinity P. parae P. picta P. reticulata P. bifurca GPS-N GPS-W Date Sampled (d20/20) M F M F M F M F Princess Cemetary 06º 48.045’ 058º 09.086’ 7/14/10 10:00 1.002 5 5 5 5 5 5 - - Seawall Trench – Day1 06º 49.520’ 058º 08.637’ 7/12/10 15:30 1.003 5 3 5 1 5 5 - - Seawall Trench – Day2 06º 49.520’ 058º 08.637’ 7/13/10 10:00 1.002 5 5 6 5 5 5 - - Turkeyen 06º 49.067’ 058º 06.764’ 7/8/10 13:00 1.000 5 5 5 5 4 2 - - West Patentia 06º 41.752’ 058º 12.066’ 7/11/10 12:00 1.003 5 5 1 1 4 6 - - West Watuka 05º 59.509’ 058º 18.282’ 7/9/10 12:30 1.000 ------4 5

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Supplementary Table 5.2. Relative and absolute efficiency (% efficiency) of qPCR assays.

Product Relative Standard Absolute Forward Primer Probe Reverse Primer Length Efficiency Error Efficiency GCTTGTGCGGG CCCACACCCAAAGTTCA GTATGTGCAAAGC B-actin 137 0.7593 0.0114 1.3258 ATATCATTTG GCCATG CGGATTC GCCCACTTCCA ATAGGAGCCGTCTTTGC CACTACACAGCAC COI 108 0.5462 0.0126 0.9537 CTATGTTCTC CATTGTTGC CTGAACA GAGCTGAGAAA ATGGCAGAGGAATGGG GCTGTTTGTGTAT LWS1 116 0.7056 0.0173 1.2322 CCTTCTTT GAAAACA GTGAATGC CAATGTGTGTC GTTGTCTCAATTTGTGG CAAACTTGACATT LWS2 123 0.8685 0.0144 1.5165 TTTGAAGGCTA AATTGCTGGGC TCCAAAGGG CAGAGGAAGGT ATGGCAGAGGAATGGG GCTGTTTGTGTAT LWS3 131 0.9694 0.0146 1.6927 GTGACAG GAAAACA GTGAATGC GGGCTCTGCTT CATACAAGAGATCCTTT CCAAGACCAGAC LWSR 155 0.6412 0.0117 1.1196 TCACATAC TGAGGGACCAAACTAC CATTTGTG Myosin TCTCTGCTCAC CCAGTTCTCGGACCCTC CAGATCCTTGACT 136 0.5303 0.0136 0.9260 HC CTTCAACTTC TGCT GTAACCTCG CTGGTTTGCTG CCAGTGTGGCCTGGTA GCTTGTTCATGCA RH1 151 0.6168 0.0131 1.0770 GATACCTTAC CATCTTCAC GATGTAGATC ACCATCACATC GCTATTGAGGGATTCAT AACAACCAGAGAC RH2-1 111 0.6637 0.0139 1.1589 TGCTCTTAA GGCAACACT CAGAGAG TAGGCTGTGAT GGAGGTCAAGTATCACT CCACTATGTATCT RH2-2 93 0.8852 0.0258 1.5457 ATGGAAGGT ATGGTCTCTTGT CTCAATAGCTAAG GCGTTCTTCTC ACAAACAGTTCAATGCC GTGGACACCTCA SWS1 146 0.6268 0.0164 1.0945 CAAGAGC TGCATCATGG GTCTTTGA SWS2 CCATCCTGCCT AGTCCTCAATAAGCAGT GTCACTGACTGAG 140 0.9737 0.0263 1.7003 A GTCGAAG TTCGAACATGCATG TTGTAGAGAC SWS2 TCCTGTGTCTC ACGTTCTCCTCAATAAG CACTCATCCCCAG 100 0.7110 0.0167 1.2414 B AAAAGCCTC CAGTTCCGC CATCTTC

Supplementary Table 5.3. PCR and sequencing primers used for LWS-1 180 Ala/Ser allele identification.

Forward Reverse

PCR TGTGAAGTGCAGATCACCTAG ACACATTCATGCATGATGCAG Sequencing GATCCCTTTGAAGGACCAAACT GGACAATCATGTAGGACAGGACC

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Supplementary Figure 5.1. Male morphs of the three sympatric species.

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Field Sites

Supplementary Figure 5.2. Map of field sites in Guyana.

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Chapter 6.

Concluding remarks and syntheses: Can beauty be found in the eyes of the beholder?

Sexual selection has been a focus of evolutionary biology since being proposed by Darwin (Darwin 1871). While at first controversial, in time we have come to truly appreciate the far-reaching effects of sexual selection on the evolution of species, and many models have been put forth to explain the evolution of sexual selection (reviewed in Kuijper et al. 2012). One form of sexual selection is intersexual mate choice, which is expected to result in a coevolution of characters preferred and preferences for those characters (Pomiankowski & Sheridan 1994; Breden et al. 1994; Andersson & Simmons 2006). Making mating decisions based on the characters of a conspecific requires a sensory system capable of detecting and discriminating such traits (Endler et al. 2005). The Sensory Exploitation model predicts that variation in the sensory systems involved in evaluating potential mates will lead to differences in mate preferences (Basolo & Endler 1995; Endler & Basolo 1998). The family Poeciliidae provides an astounding model system for studies of the evolution of mate preference as intersexual selection is rampant. Many of the species in this family make mating decisions based on male colouration, which requires colour vision, but there is variation in the colours preferred. If Sensory Exploitation plays a role in mate preference evolution in this family then we expect to also see variation in colour vision.

In this dissertation I have presented a series of studies examining the co- variation in colour vision and mate choice in Poeciliid fishes. These studies used a combination of laboratory and field techniques to assess variation in opsin gene sequence and expression across species and populations. In brief, I report that, (a) the LWS-1 and LWS-3 opsins experience a high incidence of gene conversion in the family Poeciliidae but diversity is maintained in the subgenus Lebistes (Chapter 2), (b) the evolution of sensory repertoires does not need to rely on the slow processes of

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duplication and divergence (Chapter 3), (c) differences in colour vision correlate with differences in mate preference across natural guppy populations (Chapter 4), and (d) colour vision differs more across populations than across species in the same location (Chapter 5). More broadly, these findings demonstrate; (1) colour vision can vary considerably within species and (2) the value of sensory exploitation as a theoretical framework for understanding mate preferences. Below I discuss how my work has supported these conclusions and suggest further lines of work that could build off the results of this dissertation.

6.1. Colour Vision Can Vary Considerably Within Species

Sensory systems are classically assumed to be constant within species, especially when modeling visual reception (eg. Endler 1991; Kemp et al. 2009; Hurtado- Gonzales et al. 2014). The work presented here clearly shows there can be high variability in sensory systems across populations within species, arising from differences in both allele frequencies and gene expression (Chapters 4 and 5). Such differences could be the result of adaptations to local light environments or differences in the selection pressures from the various roles of such sensory systems. Differences in selection pressures experienced by the visual system are likely as the visual system plays a key role in an organism’s ability to both detect and evaluate: potential mates, conspecific and heterospecific competitors, predators, food location and quality, as well as obstacles in their environment. The relative importance of each of these functions can vary dramatically across time and space depending on the strength of selection pressures. Since colour vision is constrained by the number of cone cells in the back of the retina it is a trade off to find a visual system that is best suited to the relative selection pressures of the current environment. Thereby even minor differences in selection pressures across populations could lead to differences in visual systems.

Chapter 4 found natural populations of guppies (Poecilia reticulata) in Trinidad differ in colour vision through differences in the frequency of the LWS-1 (180 Ala) allele (Sandkam et al. 2015). The LWS-1 (180 Ala) is the only known allele variant of the LWS opsins that is thought to alter the tuning of cone cells in guppies (Tezuka et al. 2014) and is thought to decrease λmax by 7nm relative to the LWS-1 (180 Ser) allele. The frequency

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of the LWS-1 (180 Ala) allele differed between high and low predation populations in a very similar manner across two independently colonized watersheds (Aripo watershed: high predation- 0.33, low predation- 0.02; Marianne watershed: high predation- 0.36, low predation- 0.00). Such replicated allele frequency differences suggest populations with similar predation regimes experience similar selective pressures, which is in line with a large body of previous work on guppies and strengthens the conclusion that the colour vision of populations adapt to local conditions (Reznick et al. 2001; Tezuka et al. 2014).

Differences in the frequency of the LWS-1 (180 Ala) allele across populations were not restricted to guppies (as previously thought); Chapter 5 found two closely related species (Poecilia picta and Poecilia parae) also possess the LWS-1 (180 Ala) allele at a varying frequency across populations. This highlights the possibility that possessing multiple sensory alleles at a given locus may be much more widespread than is frequently assumed. Classically, studies that examine variation in the sequence of sensory genes examine only one or a few individuals per species, which is then assumed to be the same across all individuals of that species (reviewed in Rennison et al. 2012). However, more and more recent studies are finding allelic variation in sensory systems within species (eg. Smith & Carleton 2010; Tezuka et al. 2014; Sandkam et al. 2015). Such variation has important implications to sensory ecology and may help explain individual variation in behaviour, as these individuals would be expected to differ slightly in the information detected or discriminated in their environment. Future work is needed to assess how differences in sensory alleles influence how an organism interacts with their environment.

The process of Hybrid Sensory Expansion (HSE), proposed in Chapter 3, also supports variation in sensory alleles within species. HSE posits that when two species with differentially tuned sensory repertories form a hybrid, that hybrid will have an expanded sensory repertoire by being a heterozygote for the loci that differ in the parental species. Chapter 3 uses a unique system to test this part of the process, the species Poecilia formosa, which reproduces gynogenetically and is thereby a ‘frozen F1’ (Vrijenhoek 1979; Rogers & Vamosi 2010). However, when most hybrid species are formed they reproduce sexually, and according to traditional mendelian genetics, when two heterozygotes reproduce they are expected to form offspring of three genotypes at

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each locus with different alleles. Clearly HSE results in differentially tuned sensory systems within species through allelic variation.

While changes to the wavelength at which an opsin absorbs light largely occurs at the sequence level, differences in the expression of the different opsin genes can also dramatically alter colour vision (reviewed in Horth 2007). Variation in colour vision due to differences in expression has been observed across species (cichlids- Carleton & Kocher 2001) and even across populations within species (Bluefin killifish- Fuller et al. 2004; Cichlids- Smith et al. 2010; Stickleback- Flamarique et al. 2013). Chapter 4 shows opsin gene expression varies across natural populations of guppies. As with the allele frequency differences the differences in opsin expression between high and low predation populations are similar in two independently colonized watersheds. Similarly, in Chapter 5 I showed opsin gene expression differs across populations in Guyana, not only in guppies, but also in the closely related P. picta and P. parae. Despite variation in opsin expression across populations of these three species, there was little to no difference in opsin gene expression across species from the same location.

The high variation in colour vision across populations due to allelic and expression level differences demonstrated in this body of work brings up an important but frequently overlooked aspect of visual ecology- that sensory systems vary within species. Models of visual ecology generally use one set of sensory receptors and assume equal proportions of all receptors then ask how changes in the light environment drive differences in life history (eg. Endler 1991; Kemp et al. 2009; Hurtado-Gonzales et al. 2014). As more and more technology and resources are available for field measures of sensory systems, it is becoming more feasible to measure sensory systems of many individuals in both sequence and expression to get a much higher resolution understanding of how sensory systems can drive differences in life history traits.

6.2. The Value of Sensory Exploitation as a Theoretical Framework for Understanding Mate Preferences

The Sensory Exploitation (SE) model for the evolution of mate preferences predicts that variation in peripheral sensory systems can lead to variation in the traits

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preferred (Basolo & Endler 1995; Endler & Basolo 1998). Support for the SE model has largely come from comparison of preferences and sensory systems across species (reviewed in Ryan & Cummings 2013). Chapter 2 adds qualitative support to this pattern, such that a group of fishes with mate preferences based on red/orange colouration (the subgenus Lebistes) possess a unique allele of LWS-1 (responsible for detecting and discriminating those colours). Chapters 4 and 5 show sensory systems can vary dramatically across populations within species, raising the possibility that SE may be able to explain variation in mate preferences, not only across, but also within species. Indeed, Chapter 4 found that sensory systems co-vary with mate preferences across populations in guppies, supporting the idea that SE may play a role in population differences in mate preference. Chapter 5 further demonstrated colour vision varies across populations within species. Unfortunately we did not have measures of mate preference for these populations, it would be interesting to go back and measure the mate preferences for these populations to determine if the differences in colour vision could predict differences in mate preference.

The work of this dissertation offers qualitative support for SE and paves the way for future work to develop a more nuanced sense of the role that SE plays in leading to mate preferences. Particularly, directly determining colour preferences of individuals and populations, then measuring their opsin expression and allele frequencies could provide a stronger sense of how variation in sensory systems can lead to differences across populations in mate preferences. Additionally, manipulating colour vision and looking for differences in colour preferences would provide a key examination of whether changing sensory systems can in fact drive changes to mate preference, as is predicted from SE. New tools for genomic editing, such as the CRIPR/cas9 system, may provide a way to directly test how changes in opsin tuning influence mate preferences. Additionally, modification of the putative Locus Control Region (LCR) upstream of the LWS opsin array in guppies (Tam et al. 2011) may help us understand how changes in gene expression can influence colour preferences.

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6.3. Conclusions

In this body of work I have examined variation in colour vision throughout the family Poeciliidae. I have found opsin amino acid sequence varies relatively little across species, which may be due to the genomic environment resulting in gene conversion homogenizing loci. However, I found there to be relatively high diversity within species in colour vision across populations in nature. The Sensory Exploitation hypothesis for the evolution of female preferences posits that variation in peripheral sensory systems can lead to differences in mate preference. As such, this work highlights a potential driver to population divergence and opens an interesting line of inquiry for future work to explore.

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