PATTERNS OF GENOME SIZE DIVERSITY IN INVERTEBRATES:

CASE STUDIES ON BUTTERFLIES AND MOLLUSCS

A Thesis

Presented to

The Faculty of Graduate Studies

of

The University of Guelph

by

PAOLA DIAS PORTO PIEROSSI

In partial fulfilment of requirements

For the degree of

Master of Science

April, 2011

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1+1 Canada ABSTRACT

PATTERNS OF GENOME SIZE DIVERSITY IN INVERTEBRATES: CASE STUDIES ON BUTTERFLIES AND MOLLUSCS

Paola Dias Porto Pierossi Advisor: University of Guelph T. Ryan Gregory

This thesis investigates genome size relationships with organismal and ecological traits in butterflies and molluscs. Relationships between genome size and organismal-level traits were analyzed for 84 species of butterflies. All estimates were found to be within the hypothetical

2pg threshold for holometabolous insects, and positive correlations were observed with sperm length, habitat choices, and food preferences. In addition, correlations between genome size and ecological traits, such as habitat shifts and latitude were examined in 259 species of molluscs (gastropods and bivalves). While variation in DNA content was not associated with environmental shifts, within gastropods it was positively correlated with latitude. Conversely, in bivalves both environmental shifts and latitude were marginally correlated to DNA content.

These results suggest that before a complete understanding of the evolution of the genome can be achieved, multiple levels of biological organization will need to be explored in different taxa. ACKNOWLEDGEMENTS

First and foremost I would like to thank Dr. T Ryan Gregory, my advisor, for making all of this possible. When we met 6 years ago, I could never have imagined how this experience would shape my life. Your invaluable mentoring has inspired me to always dream bigger and aim higher. Thank you for all your advice and guidance. I would also like to express my sincere gratitude to my committee members, Dr. Sarah Adamowicz and Dr. Paul Hebert for their unfailing assistance throughout the creation and development of this thesis.

Thanks are due to all members of the Gregory, Lynn, Crease, Hebert and Adamowicz labs, past and present. In particular, I would like to thank Tyler Elliott and Nick Jeffery for sharing this experience with me every step of the way and for putting up with my endless questions and requests.

The completion of this thesis would not have been possible without many collaborations and partnerships. For that, I would like to thank Adrienne Brewster and the entire staff of the

Cambridge Butterfly Conservatory, and Cheryl Tyndall and the staff of Niagara Butterfly

Conservatory for supplying so many of the specimens used in this study; Michael Mucci and

Tannis Slimmon for providing the adequate conditions for me to raise my butterflies; Dr. John

Wilson, Dr. Vazrick Nazari, Jayme Sones and the staff at the Canadian Center for DNA Barcoding for their vital assistance in making sure my samples were properly barcode; Dr. Andre Martel,

Dr. Eva Pip, Dr. Gerry Mackie, and Robert Forsyth for identifying all my molluscan specimens; and the staff at the Churchill Northern Study Center for their excellent hospitality and accommodations. You have all been instrumental in allowing me to conduct my research. Most importantly, I would like to thank all my friends and family for all of their love and support. I am especially indebted to my parents, Joceli Pierossi and Deborah Porto Pierossi for all the sacrifice you have made to provide the best opportunities for me. I am forever grateful to your continuous encouragement for me to pursue a higher level of education, and for believing I could do it when I didn't believe it myself. To my sister, Juliana Pierossi, thank you for your wisdom and guidance. You are much more than my big sister, you are the example I try to follow. Thank you for all the lessons you taught me along the way. Lastly, thanks to Callie

Sanderson for keeping me sane and making this experience a little more enjoyable. I dedicate this thesis to all of you.

"Ofuturo sefaz agora E cada erro e uma vitoria Pois a derrota nao existe Nao ha conquista sem labuta A vida e uma infinita luta Onde so perde quern desiste." - Douglas Rafael

ii TABLE OF CONTENTS LIST OF FIGURES viii

LIST OF TABLES xi

CHAPTER ONE: AN OVERVIEW OF GENOME SIZE RESEARCH 1

INTRODUCTION 2

Defining Genome Size 2

A Historical Account of Genome Size 2

The C-value Enigma 3

Genome Size Evolution in Animals 4

Genome Size Evolution in Invertebrates 5

A Hierarchical Approach to Genome Size Correlations 6

OBJECTIVES 8

CHAPTER TWO: CASE STUDY ONE: INVESTIGATING ORGANISMAL LEVEL PATTERNS OF GENOME SIZE DIVERSTIY IN BUTTERFLIES 12

INTRODUCTION 13

Genome Size Diversity in the Lepidoptera and Other Insects 13

Genome Size and Development in Insects 14

Genome Size Diversity within Butterflies 16

Genome Size and Phenotypic Properties 17

QUESTIONS AND PREDICTIONS 20

METHODS 22

Source of Specimens 22

Specimen Identification 24

Acquiring Genome Size Data 24

Feulgen Image Analysis Densitometry 25

Flow Cytometry 26

iii Other Parameters 27

Cellular Parameters 27

Morphological Parameters 28

Developmental Parameters 28

Ecological Preference Parameters 29

Data Analysis 30

RESULTS 31

Feulgen Image Analysis Densitometry and Flow Cytometry 31

Butterfly versus "Moths" 32

Within Butterfly Comparisons 33

Cellular Parameters 33

Morphological Parameters 33

Developmental Parameters 34

Ecological Preference Parameters 34

DISCUSSION 35

Feulgen Image Analysis and Flow Cytometry 35

Sperm and Haemolymph 35

FIA and FCM 37

"Moths" and Butterflies 37

Temperate "Moths" and Tropical Butterflies 38

Diurnal and Nocturnal Lifestyles 39

Within-Butterfly Comparisons 40

Cellular Parameters 40

Morphological Parameters 41

Developmental Parameters 41

iv Ecological Preference Parameters 42

QUESTIONS AND PREDICTIONS REVISITED 43

FUTURE DIRECTIONS 45

CHAPTER THREE: CASE STUDY TWO: AN EXAMINATION OF ECOLOGICAL PATTERNS IN GENOME SIZE DIVERSITY IN GASTROPOD AND BIVALVE MOLLUSCS 76

INTRODUCTION 77

Molluscs and Genome Size 79

Big Genomes for Land Pioneers? 80

QUESTIONS AND PREDICTIONS 82

METHODS 83

Source of Specimens 83

Collection Protocol 84

Genome Size Estimation 85

Compiled Data 86

Ecological Parameters 86

Phylogenetic Trees 88

Statistical Analysis 90

RESULTS 91

Overview of Genome Sizes in Bivalves and Gastropods 91

Bivalves 91

Gastropods 91

Genome Size and Shifts into Terrestrial Habitats in Gastropods 92

Genome Size and Shifts into Freshwater Habitats in Gastropods 94

Genome Size and Shifts into Freshwater Habitats in Bivalves 95

Genome Size and Thermal Regimes in Marine Gastropods and

Bivalves 96

v DISCUSSION 97

Genome Size and Shifts into Terrestrial Habitats in Gastropods 97

Genome Size and Shifts into Freshwater Habitats in Gastropods 97

Genome Size and Shifts into Freshwater Habitats in Bivalves 98

Genome Size and Thermal Regimes in Marine Gastropods and

Bivalves 99

QUESTIONS AND ANSWERS REVISITED 101

FUTURE DIRECTIONS 102

SUMMARY 128

CONCLUSION 129

REFERENCES 131

APPENDICES 146

Appendix 2.1 Flow Cytometry Histograms 147

Appendix 2.2 Images of wing scales 151

Appendix 2.3 Biological and ecological parameters analysed in the butterflies 155

Appendix 3.1 All genome size estimates obtained from the Animal Genome Size

Database 171

Appendix 3.2 Mean genome size estimates for the species measured in multiple

studies 185

Appendix 3.3 Genome size comparisons between estimates measured in this

study and those compiled from the Animal Genome Size Database 187

Appendix 3.4 Ecological parameters used in the analysis of the molluscs 188

Appendix 3.5 Supplementary material in the construction of the phylogenetic trees 200

VI Appendix 3.6 Summary of all the data analysed by the three-way ANOVA 207

Appendix 3.7 Barcoding tree of gastropods 209

VII LIST OF FIGURES

CHAPTER ONE

Figure 1.1 Distribution of genome sizes across the major groups of animals 10

Figure 1.2 Conceptual framework of the different levels of biological organization .... 11

CHAPTER TWO

Figure 2.1 Distribution of genome sizes across major insect orders 47

Figure 2.2 Phylogeny of all major superfamilies within Lepidoptera 48

Figure 2.3 Types of cells measured through Feulgen Image Analysis Densitometry .... 49

Figure 2.4 Types of Feulgen-stained haemocytes found in the same individual 50

Figure 2.5 Relationship between measurements from Feulgen Image Analysis

Densitometry using sperm and haemolymph 51

Figure 2.6 Relationship between estimates obtained by Fuelgen Image Analysis and

estimated obtained by Flow Cytometry 52

Figure 2.7 Distribution of genome sizes among the different butterfly families 53

Figure 2.8 Distribution of genome sizes of butterflies and "moths" 54

Figure 2.9 Mean genome size for 13 Lepidoptera superfamilies 55

Figure 2.10 Relationship between genome size and sperm length 56

Figure 2.11 Relationship between genome size and mean thorax length and mean

forewing length 57

Figure 2.12 Relationship between genome size and wing scale size 58

Figure 2.13 Relationship between genome size and the developmental parameters:

duration in the egg, duration as a larva, and duration as a chrysalis 59

Figure 2.14 Relationship between genome size and longevity 61

Figure 2.15 Distribution of genome sizes across the four habitat type categories 62

viii Figure 2.16 Distribution of genome sizes across the three food type categories 63

CHAPTER THREE

Figure 3.1 Relative distribution of genomic publications for mammals, birds, insects,

gastropods, and bivalves 104

Figure 3.2 Distribution of genome sizes across four molluscan classes 105

Figure 3.3 Map of the oceanic water temperatures in February of 2011 106

Figure 3.4 Phylogenetic tree of pulmonate gastropods derived from Salvini-Plawen

and Steiner (1996) 107

Figure 3.5 Phylogenetic tree of pulmonate gastropods derived from Dayrat and Tillier

(2002) 109

Figure 3.6 Phylogenetic tree of pulmonate gastropods derived from Klussanam-Kolb

etal. (2008) Ill

Figure 3.7 Phylogenetic tree of pulmonate gastropods derived from Holznagel et al.

(2010) 113

Figure 3.8 Phylogenetic hypothesis for several families within the class

Gastropoda 115

Figure 3.9 Phylogenetic hypothesis for several families within the class Bivalvia 116

Figure 3.10 Distribution of genome sizes across 101 species of bivalves divided into

four subclasses 118

Figure 3.11 Distribution of genome sizes within each bivalve subclass 119

Figure 3.12 Distribution of genome sizes across 158 species of gastropods divided

into four subclasses 120

Figure 3.13 Distribution of genome sizes within each gastropod subclass 121

Figure 3.14 Relationship between genome size and latitudinal ranges in bivalves 122

ix Figure 3.15 Relationship between genome size and latitudinal range in gastropods 123

x LIST OF TABLES

CHAPTER TWO

Table 2.1 Genome size estimates derived from Feulgen Image Analysis

Densitometry using spermatozoa and haemocytes, and estimates derived from

Flow Cytometry using neural tissue 64

Table 2.2 Mean genome size estimates for the 84 species examined in this

study 71

CHAPTER THREE

Table 3.1 Mean genome size estimates for all species collected in this study .... 124

Table 3.2 Calculated average genome size estimate for rainbow trout based on

comparisons with several standards of known C-value 127

XI CHAPTER ONE:

AN OVERVIEW OF GENOME SIZE RESEARCH IN INVERTEBRATES

1 Introduction

Defining Genome Size

Genome size (GS) is described as the total amount of deoxyribonucleic acid (DNA) contained in a single copy of the genome (Bennett, 1972). In current practice, measurements of genome size are given in terms of mass in picograms (pg) or number of nucleotide base pairs

(bp), where lpg of DNA corresponds to 978Mbp (Dolezel et al., 2003).

The importance of genome size extends far into the practical realm of research, as access to accurate C-values is necessary for evaluating the feasibility of proposed projects in large-scale genomics (Pryer et al., 2002; Gregory 2005a). For example, the quantity of DNA in a genome is generally proportional to both the financial and labour costs involved in genome sequencing

(Gregory, 2005b). Genome size also provides an estimate of the amount of non-coding DNA, most of which is repetitive and difficult to sequence. Nevertheless, the most important reasons to study genome size are not so pragmatic, and instead involve understanding major biological and evolutionary relationships. It would be impossible to create a comprehensive framework of genome evolution without information on the amount of DNA contained within genomes

(Gregory 2005b).

A Historical Account of Genome Size Study

Interest in genome size was first sparked in the late 1940's, when studies on DNA content revealed a "remarkable constancy in the nuclear DNA amount of all the cells in all the individuals within a given animal species" (Vendrely and Vendrely, 1948; translated by Gregory 2005b). This key finding provided support to the theory that perhaps DNA and not protein was the material of genetic inheritance (Vendrely, 1955; Gregory 2005a), which was thereafter revealed to be the case in the famous blender experiment by Hershey and Chase (1952). As the process of

2 inheritance became better understood and the role of DNA established, interest in genome size proliferated and a new field quickly arose.

Pioneering genome size studies quickly recognized that the low intraspecific variation was coupled with large interspecific differences in genome size (e.g., Mirsky and Ris, 1951). In fact, it is now recognized that within animals alone there is a 7,000-fold difference between the largest and smallest genomes (Gregory et al., 2007).

It was initially thought that most of the DNA in the genome functioned in coding proteins, and therefore the amount of DNA contained in the nucleus should correspond to the levels of phenotypic complexity (Thomas, 1971). Yet, genome size bears no relation to organismal complexity and most organisms contain far more DNA in their nuclei than is necessary for protein-coding and regulatory functions (Cavalier-Smith and Beaton, 1999). This baffling observation was termed "the C-value paradox" in the early 1970's (Thomas, 1971).

The discovery of numerous types of non-coding DNA resolved the paradox, by decoupling the size of the genome and the number of genes (Gregory, 2005a). In other words, GS does not have to parallel organismal complexity because not all of the genome is composed of protein- coding genes and most of the variation in the amount of DNA is caused by non-coding structures.

The C-value enigma

With the C-value paradox resolved, numerous new questions have arisen, but the answers remain elusive. In particular, what are the origins of non-coding DNA, how is it formed and how is it lost or gained? What effects or functions do these sequences have on cellular and organismal phenotypes? Why are genome sizes so varied in certain taxa while in others they appear constrained? What, if any are the distribution patterns of genome size among taxa? These questions represent key elements of a complex puzzle known as the "C-value enigma" (Gregory

3 2001; 2005a). It has been proposed that only multi-dimensional explanations, supported by large genome size surveys on many taxonomic groups, will be capable of answering these questions

(Gregory, 2001)

One key observation that has been made in animals, plants, and protists is that a larger genome is associated with larger cells and slower cell division (reviewed by Gregory, 2001;

2005b; Bennett and Leitch, 2005). For multicellular organisms such as animals, this has the potential to create links between genome size, body size, metabolic rate, and developmental parameters. The particular impact of these relationships will depend on the biology of the group in question, which again indicates the importance of taking broad taxonomic perspectives.

A positive correlation between GS and nuclear and cellular volumes has been documented in a variety of organisms and cell types (Olmo 1983, Gregory, 2001, 2005b), but the reason behind this relationship has been the subject of significant debate over the past several decades (Bennett, 1972; Cavalier-Smith, 1978; Pagel and Johnstone, 1992; Gregory 2001). Today the most widely accepted view is that a larger amount of DNA is causally associated with larger nuclei and cells, though the exact mechanism remains a subject of research. Whatever the mechanistic basis, the strong link between genome size and cellular parameters plays an important role in the efforts to answer several of the questions in the C-value enigma.

Genome size evolution in animals

There are approximately 5000 animal genome size species estimates currently recorded

in the Animal Genome Size Database (AGSD) available online at www.genomesize.com (Gregory,

2011). The objective of this and similar databases on plants and fungi is to catalogue and make

available a compilation of all the estimates currently known - so far, that represents a total of

more than 10,000 species across these taxa (Gregory et al, 2007).

4 With thousands of species analysed, the present state of knowledge on animal DNA

contents may seem impressive however, it only represents a very small percentage of the total

biodiversity described: a remarkable 1.25 million species (IUCN, 2011). More importantly, the

AGSD is severely biased towards vertebrates. Despite their unparalleled abundance and

diversity, data on invertebrate genome sizes are comparatively scarce. Only 1/3 of the available

C-values are from invertebrate species (Gregory, 2011). Moreover, several invertebrate groups

are represented by less than 1% of their total species diversity; others have never been

investigated at all (Figure 1.1).

Genome size evolution in invertebrates

It is clear that there is an overwhelming need to expand the coverage on invertebrate genome sizes and investigate the patterns and relationships that may be found in non-vertebrate animals. Because genome size implications at the organism level vary according to the biology of a group in question - in such that one group may demonstrate a strong positive correlation with a trait while another group may show no relationship to the same trait at all (Gregory, 2005b) - assumptions regarding general patterns of variation found in vertebrates can only be taken as preliminary. Nevertheless, interesting GS trends are already evident in a few invertebrate groups.

For example, positive body size correlations have been reported in a variety of species, including turbellarian flatworms (Gregory et al., 2000), copepod crustaceans (McLaren et al., 1988; Gregory et al., 2000), polychaetes (Soldi et al., 1994) and aphids (Finston et al., 1995); while in mosquitoes and fruit flies it was wing size, which revealed a positive correlation to genome size (Ferrari and

Rai, 1989; Craddock et al., 2000).

In addition, developmental rate was shown to negatively correlate with genome size in many species of the genus Drosophila (Greg ory and Johnston, 2008) and duration of pupal

5 development in ladybird beetles (Gregory et al. 2003). Furthermore, polychaetes inhabiting harsh

interstitial habitats have been shown to exhibit smaller DNA contents than macrobenthics, which

could be explained by selection for fast development and small body sizes (Soldi et al., 1994;

Gambi et al., 1997). Similarly, it has been suggested in leaf beetles that species with more than

one generation per year have genomes smaller than 0.5pg while single generation species

possess C-values greater than 0.6pg (reviewed in Gregory, 2005b [Chapter 1]).

Developmental complexity provides another example of a negative correlation with

genome size; species that undergo rapid, intensive morphological changes appear to have

smaller genomes compared to species that experience steady growth when development time is

constant. Insects are the ideal example to illustrate this pattern; as Gregory (2002) observed,

orders with complete metamorphosis are constrained to DNA contents of 2pg or less, whereas

non-metamorphosing orders often surpass this threshold.

Higher levels of biological organization have also been investigated with regard to

genome size in select groups of invertebrates. For instance, parasitism and eusociality were

examined in the insect order Hymenoptera, where results indicated genome size was significantly

smaller in parasitoid compared with non-parasite groups, but no relationship was observed

between eusocial and solitary species (Ardila-Garcia et al., 2010). Nevertheless, studies exploring these and other behavioural and ecological features are fundamental to construct a complete

picture of the evolutionary implications of genome size.

A hierarchical approach to genome size correlations

Genome size can have important consequences for organismal fitness from its link with cell size and division rate (Gregory 2005b). However the implications of genome size may extend well beyond its effects on cellular properties. In fact several levels of biological organization may

6 be involved in determining patterns of genome size variation. These include relationships at subgenomic, cellular, physiological, developmental, behavioural, and ecological scales (Figure

1.2).

In order to understand the hierarchy of possible GS relationships, a brief highlight of the multiple levels of interactions involving DNA content is warranted. In short, both bottom-up and top-down interactions may be occurring simultaneously. From a bottom-up perspective, intragenomic selection acting on autonomous elements (selfish DNA) may influence cellular parameters, such as cell size and division rate. These parameters, in turn, have the potential of affecting organismal-level traits, including body size, metabolic rate, and developmental rate.

Finally, the behaviour as well as the ecological lifestyle of a species may be strongly influence by the physiological, morphological, and developmental characteristics it possesses (Gregory,

2005c). On the other hand, from a top-down standpoint several ecological and behavioural parameters, such as habitat selection, ability to compete for resources and food preferences, impose selective pressures by affecting the evolution of morphological, metabolic and developmental traits. In turn, these organismal features play a role at the cellular level, by constraining cell size and division rate. As a consequence, changes in genome size may follow, as large genomes cannot be sustained by small, fast-dividing cells (Gregory, 2005c)

Although complicated, the schematic framework described above illustrates how genome size may indirectly correlate to organismal and ecological level parameters, therefore highlighting the need to further examine such relationships in many different eukaryotic groups.

In animals, most studies performed to date have investigated GS relationships at the organismal scale, concentrating on interactions involving metabolism, morphology, and development.

However it is becoming increasingly apparent that the effects of genome size extend well beyond the level of the organism (Gregory, 2005c). In fact, recent years have seen a surge of projects

7 focused on behavioural parameters (Ardila-Garcia et al., 2010; Andrews and Gregory, 2009; and

Gregory and Witt, 2008). Yet true ecological interactions remain largely ignored in animals.

Plants, on the other hand, provide some examples of the relationship between DNA content and ecological features. For example, it appears large-genomed plants are fairly uncommon in harsh environments with short growth seasons, despite being more tolerant of

droughts, frosts and high C02 (Knight and Ackerly, 2002; Knight et al., 2005). This is because large- genomed plants tend to have slower developmental rates which limit their ability to establish and perpetuate in these environments (Knight et al., 2005; Bennett and Leitch, 2005).

Objectives

To answer major questions regarding genome evolution it is necessary to incorporate patterns observed at various levels of biological organization. This thesis aims to explore DNA content relationships at both the organismal and ecological scales by presenting separate case studies on two understudied groups of invertebrates.

In the first case study, several physiological and morphological traits, together with preliminary behavioural parameters, are examined in butterflies with regards to their relationship with genome size. Butterflies were the target group for this study because of the relatively minor ecological variation seen between species; all butterflies are terrestrial, they are in direct contact with vegetation in at least one stage of their life cycle, and they all rely on flying as their adult mode of transportation. In particular, the samples used in this project consisted solely of tropical species, further constraining the ecological variation of this group.

Additionally, despite their abundance, butterflies constitute a fairly small phylogenetic clade. Within the Papillionoidea superfamily, although the field of butterfly systematics is in a

8 constant state of change, there are only five well-supported families to which all species belong

(Ehrlich, 1958; DeVries, 1987, Lamas, 2008). Finally, it is also important to note that butterflies have scarcely been explored in terms of their genome sizes. Prior to this study, only 6 estimates were available for this group, accounting for less than 0.0005% of their total diversity. In 2003,

Gregory and Hebert suggested C-value surveys of butterflies were well warranted, but this call had yet to be taken up.

The second case study concentrates on exploring ecological correlations with genome size in molluscs. To date, few have attempted to examine ecological relationships in animals, especially at a large scale. Molluscs were an excellent model group for a project of this type because they occur in a wide array of habitat niches. There is an abundance of marine, freshwater and terrestrial species well distributed around the world, on every continent (Aktipis et a I, 2008) and in environments ranging from deep sea hydrothermal vents to deserts (Schmidt-

Nielsen et al., 1971). Moreover, there is a major need for improved coverage of mollusc genome sizes, as a mere 0.12% of their total diversity is currently known in terms of DNA content.

9 Nematoda (54/28,000) + + •****»«» «** O Mollusca (236/130,000) «w >*»# Insects (706/1,000,000) <^( Platyhelminthes (64/25,000) <3K Echmodermata (47/7,000) 4MMM& <#«M»-> Crustecea (278/50,000) #•<.

Annelida (136/17,000) •# •]:•>»!

Reptiha (320/8,200)

Mammalia (485/5,500)

Actinopterygn (1,372/23,000) •W Sarcopterygn (7/2,700) o ••#»• #• Cephalaspidomorphi (17/100)

Chondnchtyes (130/940)

Aves (358/10,000) Amphibia (504/6,500) <*« !•»•

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2.5 Log Genome size (pg)

Figure 1.1. A distribution of log transformed genome size estimates between the major groups of invertebrates and vertebrates. Darker shades within the distribution indicate ranges where estimates are most abundant. The numbers of genome size estimates, as well as total species count for each group are given in parentheses.

10 Physiological Properties

Cellular Properties

GENOME SIZE

Subgenomic Properties

Figure 1.2. A simplified schematic representation of how genome size may directly or indirectly interact with different levels of biological organization. Arrows indicate direct relationships between two parameters, with black arrows illustrating bottom-up interactions and gray arrows indicating top-down.

11 CHAPTER TWO

CASE STUDY ONE: INVESTIGATING ORGANISMAL LEVEL PATTERNS OF GENOME SIZE IN BUTTERFLIES

12 Introduction

Genome size diversity in the Lepidoptera and other Insects

With more than 1,000,000 species described to date (Adler and Foottit, 2009), insects are the most diverse group of eukaryotic animals. It should therefore not be surprising that of all invertebrate groups, insects have the largest number of available genome size estimates

(Gregory, 2011). These animals are often crucial components of ecosystems and it is very important to fully understand their biology, including genomic properties.

Several genome size relationships have been investigated among different groups of insects, including positive correlations with body size (Ardila-Garcia and Gregory, 2009; Gregory and

Johnston, 2008; Finston et al, 1995), negative correlations with developmental rate (Gregory and

Johnston, 2008; Gregory et al, 2003; Finston et al 1995), and developmental complexity (Gregory

2002), as well as relationships with parasitism, eusociality (Ardila-Garcia et al 2010) and flight

(Ardila-Garcia and Gregory, 2009). Nevertheless, the more than 700 estimates recorded account for less than 0.09% of their total described species diversity and more than 90% of these estimates come from only five of the 32 insect orders (Gregory, 2011).

The order Lepidoptera (moths and butterflies) is one of the few that has been studied, although only in a preliminary way. Lepidoptera is considered the second most diverse order of insects behind only the Coleoptera (beetles) and currently includes 155,000 described species worldwide (Pogue, 2009). Moths and butterflies have been collected and studied extensively for centuries. Most recently, they have been the subject of a major global project in DNA barcoding

(Janzen et al., 2009 and Hebert et al., 2009). However, to date only one published study has provided a dataset of genome sizes for these animals, with a focus on about 50 species (almost all moths) from southern Ontario (Gregory and Hebert, 2003). A more recent project examined

13 about 300 species from the same region, but again they were all nocturnal moths collected at light traps (Laforest and Gregory, in preparation), leaving a great deal unknown about lepidopteran diversity both in terms of geographic variability and patterns among diurnal species, especially butterflies. Clearly, there is much to be explored on the variation of genome size in these animals.

Prior to this study, only 59 genome size estimates had been recorded in Lepidoptera

(Gage, 1974; Rasch, 1974; Efstratiadis et al, 1976; Rasch, 1985; Petipierre, 1996; Gregory and

Hebert, 2003; Jiggins, 2005; Tobler et al, 2005; Taylor et al, 2005). The current published dataset ranges from estimates of 0.29 pg in the Monarch Butterfly Danaus plexippus to 1.94 pg in the

Least-marked Euchlaena Euchlaena irraria, with the mean genome size for all Lepidoptera at 0.65 pg ± 0.04 (Gregory, 2011).

Relative to other insects, the Lepidoptera appear to have a moderate level of variability in genome size across species. Genome sizes in moths appear less constrained than in some other orders (e.g. Diptera), but are nowhere near as large as the largest value seen in orders such as the Orthoptera (grasshoppers), with more than 10-fold range and estimates well above 15 pg, and the Hemiptera (true bugs) with more than 25-fold range and estimates above 4 pg (Gregory,

2011) (Figure 2.1). It has been hypothesized that this apparent constraint on genome size in

Lepidoptera and some other insect orders is linked to their mode of development (Gregory,

2005b).

Genome size and Development in Insects

Developmental parameters have been examined in relation to genome size in various groups of animals and plants, since these parameters are directly affected by variation in cell size

14 and division rate (Gregory, 2002). In the simplest sense, developmental rate is determined by the amount time necessary for the growth and differentiation of an organism. This particular parameter has been examined in several groups of insects, where an inverse correlation between genome size and developmental rate has been reported (Gregory and Johnston, 2008; Gregory,

2003; Gregory et al, 2003; Finston et al 1995). That is, species with large genome sizes exhibit slower overall development from egg to adult.

Conversely, as stated by Gregory (2002): "The flip-side of rate in the developmental coin is complexity". In other words, how quickly an animal transforms into an adult is only one parameter that may relate to genome size; the other is how much transformation it needs to complete when developmental time is held constant.

Developmental complexity and genome size relationships have been best studied in amphibians with regard to metamorphosis (or lack thereof), which represents a time-limited period of intense development. In fact, metamorphosis appears to be one of the main factors determining patterns of genome size diversity in amphibians (Gregory, 2002). Frog metamorphosis is much more intense than that of salamanders, in which juveniles are more similar to adults, and there is almost no overlap between genome sizes in the two groups, with frogs having smaller genomes (Gregory, 2002). Within frogs, rapidly metamorphosing species

(especially those living in short-term bodies of water) have the smallest genomes, followed by direct developers and biphasic (normally metamorphosing) species (Gregory, 2002). Species with a biphasic lifestyle have the smallest genomes among salamanders (but still larger than frogs), followed by direct developers, facultative neotenes, and obligate neotenes, the latter of which never undergo metamorphosis (Gregory, 2005b).

Evidence suggests a similar relationship between genome size and developmental complexity in insects (Gregory, 2002). However in these organisms, development can be

15 holometabolous (complete metamorphosis), including complete larval, pupal and adult phases or, hemimetabolous (incomplete metamorphosis), in which growth is via a series of moults rather than metamorphosis through distinct lifestages (Gregory, 2005b). In keeping with the pattern observed in amphibians, the holometabolous insects examined to date appear to have genome sizes constrained to values below 2 pg (Figure 2.1). Based on these results, Gregory (2002) proposed that a "genome size of about 2 pg represents the threshold for metamorphosis in insects". Non-metamorphosing insects, by comparison, may have genome sizes of 15 pg or more.

Therefore, the limited range in genome size seen so far among moths and butterflies may be linked to the fact that they undergo complete metamorphosis, and it is predicted that the maximum genome size in this order will not exceed 2 pg. Testing this prediction is one of the goals in the present study.

Genome Size Diversity within Butterflies

The current genome size estimates for the Lepidoptera in the Animal Genome Size

Database are strongly biased toward moths, including only six species of butterflies. Even the major study of Lepidoptera recently conducted by Laforest and Gregory (unpublished) included several species of nocturnal, temperate moths but no butterflies. Despite being a very charismatic group, no previous study has aimed to survey their genome size diversity to date.

Butterflies (superfamily Papilionoidea) have a worldwide distribution, but are most common in tropical regions. They are often used in environmental monitoring, since they are both conspicuous and sensitive to change (The Scottish Government, 2007 and Feltwell, 1986).

Economically, butterflies are both allies and enemies to humans, providing a source of income in ecotourism and merchandises, and an expense as pests to many agriculture crops (Carter, 2002).

16 For these reasons, they have been well studied from a variety of perspectives other than genome size.

Phylogenetically, butterflies represent a monophyletic clade nested within the paraphyletic "moths" (Figure 2.2). Thus, from a strictly phylogenetic perspective, comparisons between "butterflies" and "moths" are problematic. However, from the perspective of their general biology, such comparisons can be quite informative so long as the phylogenetic issues are not ignored. No single trait can distinguish butterflies from other moths groups, but overall they differ from most other Lepidoptera by being mostly diurnal, largely tropical, feeding as adults and not producing protective cocoons during metamorphosis (Brewer and Winter, 1986).

It is interesting to note that the smallest genome size estimate so far reported for the

Lepidoptera comes from a butterfly, but based on current data it is not possible to determine whether butterflies exhibit smaller genomes in general relative to other lepidopteran groups. It is plausible their unique combination of traits may be indirectly linked with genome size. For example, the diurnal lifestyle (experienced by most butterflies) may be associated with different metabolic demands than those experienced by species with nocturnal lifestyles. Exploring the relationship between butterflies and "moths" and some of the possible explanations for this relationship represents another goal of the present study.

Genome Size and Phenotvoic Properties

As discussed in chapter 1, cell size and cell division rate can lead to associations with other biological features, such as body size, metabolic rate, developmental rate and ecological lifestyles. This applies not only to the much better-studied vertebrates, but also to several groups of insects (Ardila-Garcia and Gregory, 2009; Gregory and Johnston, 2008; Gregory et al, 2003).

17 Nevertheless, little is known on the causes and consequences of the genome size diversity that

occurs within Lepidoptera and especially within butterflies. This case study explores relationships

between genome size and organismal-level parameters in butterflies, which represent a

phylogenetically and geographically restricted test group. Several parameters were investigated

as described below.

Cell size. The most universal implication of genome size variation is a positive correlation

with cell size (Gregory, 2005b), since DNA content and cell size are believed to be causally

related. This means that an increase in DNA content is accompanied by an increase in the size of

the cell (Gregory, 2001). In animals this relationship has been well examined in vertebrates,

where genome size has been shown to correlate with the sizes of various cells (especially red

blood cells, reviewed in Gregory 2001, 2005b).

Relationships between genome size and cell size have not been studied in detail in any

group of insects. In part, this reflects the lack of an easily-studied cell type such as the

erythrocytes of vertebrates. There is, however, some indication that sperm size may be

correlated with genome size in the genus Drosophila (Gregory and Johnston, 2008). Butterflies

possess two types of sperm, eupyrene (fertilizing) and apyrene (non-fertile). Their formation is

identical until maturation when apyrene sperm shed their nuclei; despite that, the lengths of

both sperm types have been reported to correlate positively to body size in these organisms

(Gage, 1994), just as in Drosophila (Gregory and Johnston, 2008). Sperm length was therefore

included as a possible correlate to genome size in the present study.

Wing scale size. Each scale on the wing of moths and butterflies is formed from a single

trichogen cell, the sizes (and therefore adjacent spacing) of which may relate to genome size. For this reason, Simonsen and Kristensen (2003) proposed that the sizes of individual wing scales in

Lepidoptera should correlate positively with genome size. This is worthwhile to consider, as it

18 provides an indirect assessment of genome size-cell size relationship. However, no study has attempted to test this relationship and no evidence to accept or refute this correlation exists in butterflies.

Body size. Body size is correlated positively with genome size in some insects (Ardila-

Garcia and Gregory, 2009; Craddock et al, 2000; Ferrari and Rai, 1989). However, Gregory and

Hebert (2003) suggested that no such correlation was present in Lepidoptera (non-butterflies) but, this was based largely on comparisons of a few species of notably different body sizes. It remains worthwhile to test such relationship statistically.

Developmental rate. A negative relationship between genome size and cell division rate has been observed among many animals and plants (Bennett and Leitch, 2005; Bennet, 1976;

Grosset and Odartchenko, 1975; Van't Hof and Sparrow, 1963). This relationship suggests that developmental parameters may also be linked to genome size at the whole organism level.

Indeed, a relationship has been found in some groups of insects (Ardila-Garcia and Gregory,

2010; Gregory et al., 2003), but remains to be investigated in butterflies. A measure of developmental rate was included in this study as a possible correlate to genome size.

By extension of the potential correlations between genome size and organismal parameters, it is possible that relationships exist at higher levels of biological organization, such as behavioural strategies. For example, Andrews and Gregory (2009) found that parrots that chose to occupy open habitats had smaller genomes than ones who preferred arboreal environments. This may be linked to the correlation observed between genome size and relative brain size and could be related to higher behavioural resourcefulness required in open areas to search for food and buffer climatic fluctuations (Andrews and Gregory, 2009). It is plausible that similar relationships exist in insects and specifically in butterflies. Although comparative

19 physiological data are often unavailable in butterflies, it is possible to draw comparisons based on the large variation in habitat choice and food preferences they exhibit.

Questions and Predictions

There are many questions to be asked regarding the diversity of genome sizes found among butterflies. In order to better understand the evolution of the genomic characteristics of these animals and address a major gap in invertebrate genome size research, this study presents and attempts to answer numerous specific questions:

1. What is the range in genome sizes across the superfamily Papilionoidea, and do these values fall within the 2pg threshold observed for insects with complete metamorphose?

If the Papilioinidea follow similar distribution patterns as observed in other groups of

Lepidoptera, then a comprehensive sampling in this group should reveal genome sizes all below the hypothetical 2pg threshold.

2. Is there a significant difference in the mean DNA content of butterflies relative to other

Lepidoptera?

If variation in genome sizes within Lepidoptera is associated with a combination of distinctive differences between moths and butterflies, such as diurnal versus nocturnal behaviour, adult feeding strategies or the formation of above-ground chrysalides, then the mean DNA content of butterflies will be different from other groups of "moths" within the Lepidoptera.

20 3. Does genome size correlate with sperm size in butterflies?

If genome size has evolved a causative link to cell size as observed in several other animal groups, it may be predicted that these two features will positively correlate across all butterflies independently of a phylogenetic relationship.

4. Is genome size diversity in butterflies associated with variability in body size?

If body size is controlled by cell size as oppose to cell number in butterflies, then genome size will be positively correlated to body size, so species with larger body measurements will have larger genomes.

5. Is there a relationship between genome size and wing scale size?

If variation in scale sizes are directly related to size variation in scale-forming trichogen cells, and these cells are, in turn, directly related to variation in genome size, then butterfly species with larger average scale sizes will have larger genomes.

6. Can developmental parameters explain the observed diversity of genome sizes in butterflies?

Given that holometabolous development plays an important role in constraining genome sizes within 2pg in Lepidoptera, it is expected that development rate will also be a vital determinant of genome size diversity within butterflies.

21 7. Do behavioural parameters such as food and regional habitat preferences influence genome size diversity in Papilionoidea?

If genome size is constrained by morphological parameters, such as body size, development or metabolic rate, then it may be predicted that genome sizes will be related to behavioural features associated to these parameters, such as feeding and habitat preferences.

Methods

Source of Specimens

In total 436 individual specimens were analyzed in this study, consisting of 88 species representing 45 genera, 15 subfamilies, and 3 families. All species were of tropical origin, native to Costa Rica, the Philippines, and Australia and obtained from the Niagara Butterfly

Conservatory in Niagara Falls, Ontario and Wings of Paradise Butterfly Conservatory in

Cambridge, Ontario (now known as the Cambridge Butterfly Conservatory). This study was performed in two phases, which were distinguished from one another based on the methods used to measure genome size.

Phase I was started in the summer of 2005, when 190 specimens consisting of 61 species were analyzed by Feulgen Image Analysis Densitometry (FIA; see below). Whenever possible the butterflies were sexed and males were processed whereas females were released, so that sperm could be used in this study in addition to haemolymph. Specimens for this study were collected as adults, and preparation of the samples was made on site at the butterfly conservatories..

Butterflies to be processed were euthanized in chloroform kill jars and a leg was removed to allow for haemolymph to be extruded onto a microscope slide and air dry. In addition, abdomens of every male were dissected to remove the testis, while the head, thorax and wings

22 were labelled and stored in a pinning box. Although butterfly testes are fused, brightly coloured and easy to detect, sperm are formed in tight bundles that are very difficult to break apart

(Gregory and Hebert, 2003). Tissue grinders, 2ml Kontes dounce (type A pestle) were used in an effort to disperse individual sperm. Each whole testis was placed in a grinder with Ringers

solution (1L distilled H20 + 7.5g NaCI + 0.35g CaCI2 + 0.21g KCI) and mixed vigorously until all large pieces of tissue had been disrupted. The final solution was poured onto a microscope slide and allowed to air dry.

Phase II was carried out from the fall of 2007 to summer of 2008. In this phase, 246 specimens, representing 73 species were examined by Flow Cytometry (FCM; see below), using brain cells. Flow cytometry works best with fresh tissue, but live adult butterflies are not permitted to be transported outside the conservatories. Therefore, chrysalides were imported from suppliers in Costa Rica and the Philippines with the help of the Niagara Butterfly

Conservatory and Wings of Paradise and brought to the University of Guelph for rearing. Rearing took place at the Guelph Phytotron in E15 growth chambers equipped with Conviron Cp5000 controllers able to regulate temperature (37°), humidity (80%), and photoperiod (12 L: 12 D). As most butterflies eclose at sunrise, artificial sunrise conditions were replicated in the chambers.

The chrysalides were pinned upside down in mesh cages to imitate their natural conditions and chambers were checked three times per day, once at "sunrise" and twice more throughout the day. Once a butterfly emerged, it was brought back to the lab for processing. Adult specimens were euthanized immediately after immersion in ethyl acetate killing jars. Specimens that were not analyzed immediately were stored intact in a -80° freezer until analysis could be undertaken.

23 Specimen Identification

Most of the species identifications were conducted by the staff entomologist at the

collaborating conservatories and/or by the suppliers, with vouchers kept in pinning boxes.

However in cases where there were uncertainties with the identifications, DNA barcoding was

used for clarification.

DNA barcoding consists of short standardized regions of the cytochrome oxidase subunit

I (COI) gene in the mtDNA, which are used to genetically differentiate species groups. This

technique has been proven very effective in differentiating between tropical Lepidoptera species

(Hajibabaei et al, 2006). A single leg was removed from each specimen in order to be used in DNA

extraction. The primers LepF (5_-ATTCAACCAATCATAAAGATATTGG-3_) and LepR (5_-

TAAACTTCTGGATGTCCAAAAAATCA-3J were used to amplify the COI gene region. The amplified

DNA was then sequenced using LepFl and LepRl primers. Sequences were edited and assembled

using Sequencher software. Once they were completed, the sequences were aligned and edited.

Species-level identifications were obtained for all specimens barcoded. Less than 1% intraspecific

variation was found between specimens belonging to the same species, while approximately 6%

of sequence variation was observed between species. The final sequences were entered in the

Barcode of Life Data Systems (BOLD) under the Tropical Butterflies Genome Size [TBGS] project,

along with trace files, photographs, and additional information on the specimens.

Acquiring Genome Size Data

Genome size estimates were conducted using modern best practice Feulgen Image Analysis

Densitometry (FIA) and Flow Cytometry (FCM) (Hardie et al., 2002; DeSalle et al., 2005). Both

methods have been widely used in several different groups of animals and plants, and it is clear

there are advantages and disadvanteages to both techniques depending on the study group and

24 research project. For example, FIA is much more time consuming than FCM, however it is ideal in field expeditions as it relies on microscope slide preparations which are easy to store and transport (details on the methods are given below). This study used FIA and FCM in order to investigate which technique is better suited to acquire genome sizes in butterflies. Only original

DNA content estimates were used in the analyses presented in this study.

Feulgen Image Analysis Densitometry

Feulgen image analysis densitometry (FIA) consists of the Feulgen staining protocol coupled with computer imaging technology. Hardie et al. (2002) describe in detail these procedures.

In short, sperm and haemolymph slides prepared in the conservatories were fixed overnight at room temperature in 85 methanol: 10 formalin: 5 glacial acetic acid solution. This was followed by 120 minutes hydrolysis in 5.0N HCI and staining in freshly made Schiff reagent for another 120 minutes. A series of bisulphite and water rinses concluded the staining process.

Optical absorbance of Schiff reagent, measured as integrated optical densities (IOD) were calculated for each nucleus. An average of 20 sperm nuclei and 35 haemolymph nuclei were measured per slide using the Bioquant Life Science version 8.00.20 software package and a Leica

DM LS microscope at 1000X magnification. The amount of Schiff stain that is bound to the nuclei is directly proportional to the amount of DNA present (Hardie et al., 2002). Absolute genome sizes were converted from lODs to picograms, by comparing ratios with standards of known genome sizes: Drosophila melanogaster (0.18pg) and Bombyx mori (0.52pg). These standards were the same tissue type as the samples being investigated, with Drosophila melanogaster being used for sperm and Bombyx mori for haemolymph (Figure 2.3). The ratio between the standard and the unknown species provided the final genome size, as illustrated below. Blood

25 smears of Gallus domesticus and Oncorhynchus mykiss were also included as internal checks of staining.

Unknown IOD x (Standard GS) = (Unknown GS) Standard IOD

Both haemolymph and sperm posed challenges in butterflies. It is evident that some haemocytes were dividing or were endopolyploid, with some nuclei containing twice the diploid quantity of DNA (Figure 2.4). On the other hand, sperm are reliably haploid but very long and string-like in butterflies, which mean they were often broken and did not always fully take up stain.

Flow Cytometry

Flow cytometry involves quantifying the fluorescence emitted by suspended particles dyed with a fluorochrome when these are excited by a laser. In this study, 1mm3 brain tissue was dissected from an adult and nuclei were released by grinding simultaneously with a single head from a specimen of Drosophila melanogaster (0.18pg) in 0.5u.l of Galbraith buffer solution using a

2ml Kontes dounce (type A pestle) tissue grinder. The co-prepared sample was then filtered through a 30 micron mesh and dyed using 0.12u,l of 5% of the non-basepair-specific fluorochrome propidium iodide. Samples were incubated on ice for an hour to allow dye uptake by the DNA, before being run on a Beckman Coulter Cell Lab Quanta SC MPL flow cytometer using a 488nm laser.

Prior to running any samples, the machine was tested for the quality and resolution of its peaks by running blood samples of rainbow trout Oncorhynchus mykiss. A minimum of 1,300 nuclei was measured per peak per sample and peaks with coefficient of variance (CV) higher than

26 10% were omitted from the analysis. On average four individuals were measured per species and absolute DNA contents were calculated from the ratio of mean peak values, as illustrated below.

Mean of Unknown Peak X (Standard GS) = Unknown GS Mean of Standard Peak

In some cases, only one individual was measured per species, but variation between conspecifics was always very low in cases where multiple individuals were available for a species

(Table 2.1).

Other Parameters

All genome size estimates and some morphological parameters (e.g. thorax length and scale areas) included in this study were measured in the laboratory, whereas additional data were assembled from the literature (eg. cellular, developmental, morphological and ecological lifestyle parameters). The sources of the data used in this study are described below.

Cellular Parameters

The following parameters were compiled from the literature (complete list of references available in appendix 2.3).

• (MASL) - Mean apyrene sperm length, derived from averaging the mean sperm length for each male measured in micrometers (u.m). The number of sperm and the number of males analysed varied from 17 to 45 and from 3 to 9, respectively (Gage, 1994).

• (MESL) - Mean eupyrene sperm length, derived from averaging the mean sperm length for each male measured in micrometers (u.m). The number of sperm per individual and the number of males per species analysed varied from 11 to 38 and from 3 to 9 respectively (Gage, 1994).

27 Morphological Parameters

The following parameter was taken from the literature (complete list of references available in appendix 2.3).

• (FWL) - Forewing length, measured from the apex to the insertion on the thorax. In cases where sexual dimorphism was evident, an average value was calculated to the nearest millimeter

(mm). This parameter was taken from the literature instead of measured from the original samples, because wings of the collected butterflies were often too damaged or broken to provide accurate length measurements.

The following parameters were measured in the laboratory.

• (MTL) - Mean thorax length, measured with callipers to the nearest millimeter (mm).

• (MSA) - Mean scale areas, measured by image analysis. Slides were prepared by transferring scales from the wing to a microscope slide. Scale areas were measured in pixels at 5x magnification on a Leica DM LS microscope using the Bioquant Life Science v8.00.20 image analysis software. As butterflies display scales of varying shapes and sizes, only a single type of scale was measured (Appendix 2.2) at approximately 40 scales per individual.

Developmental Parameters

The following parameters were compiled from the literature (complete list of references available in appendix 2.3). It is important to note that the following parameters were compiled from multiple literary sources and external factors which influence development in butterflies, such as temperature and humidity were not controlled the same way in every study.

• (MED) - Mean egg duration, measured from the time the egg is laid until the time of hatching

(days).

28 • (MLD) - Mean larval duration, calculated from the moment of hatching up to the formation of the chrysalis (days); including a prepupal phase, where the caterpillar is considered intermediate between a larva and a fully developed pupa.

• (MCD) - Mean chrysalis duration, measured from time of chrysalis formation until eclosion

(days).

• (LONG) - Longevity, defined as the amount of time an adult butterfly will survive under optimum conditions (days).

Ecological Preference Parameters

The following parameters were compiled from the literature (complete list of references available in appendix 2.3).

• (HABT) - Habitat type; butterflies were divided categorically based on the localities they were

most often found in:

1. Rain forests

2. Deciduous forests

3. Open fields

4. Disturbed fields

• (FEEDP) - Feeding preferences; butterflies were divided categorically by diet:

1. Nectar eaters

2. Rotting fruit eaters

3. Pollen eaters - some butterflies have evolved complex morphological features of the proboscis that allow them to remove amino acids and proteins from pollen (Gilbert, 1972).

29 Data Analysis

Comparisons between estimates derived by FIA and FCM and using different tissue types (ie. sperm and haemolymph) were assessed by paired t-tests and Pearson correlations on log- transformed data, when the assumptions for these paramatic analysis were met. In cases where the data were not normally distributed the non-parametric tests, Wilcoxon Signed Ranks,

Kendall's tau correlation, and Spearmen's rank correlation were used instead. Both parametric and non-parametric correlations as well as least-square regressions were helpful in determining the correspondence of estimates obtained using the FIA and FCM. A detail listing of the tests employed on each analysis in given on Appendix 2.4.

The comparison between moths and butterflies did not meet the assumptions for normality and were evaluated with non-parametric Wilcoxon Signed Rank test on absolute values. Data on moth genome sizes were obtained from Laforest and Gregory, unpublished. The monophyletic butterflies were treated as functionally distinct from the paraphyletic moths, based on a combination of parameters, such as time of activity, production of chrysalides/pupae and feeding behaviour. While all butterflies in this study feed as adults, produce above-ground chrysalides, fly during the day, and are native to the tropics; the majority of moths used in the comparison produce below-ground pupae, fly at night, and have temperate distributions.

Cellular, morphological, and developmental parameters were assessed with Pearson correlations on log-transformed data when normality was assumed, and with Kendall's tau and

Spearmen's rank correlations when the data were non-parametric (Appendix 2.4). The categorical parameters, HABT and FEEDP were not normally distributed and therefore were analyzed with the Kruskal-Wallis test. Significant differences between each category was identified using the Wilcoxon Signed Rank test.

30 Given that a complete phylogenetic tree including all species of butterflies examined in this study does not yet exist, analyses were performed to compare genome sizes and ecological parameters at several taxonomic levels, mainly from species to family, using the Kruskal-Wallis test. These analyses are able to identify if differences in genome size between HABT and FEEDP are largely influenced by taxonomy, if the patterns observed do not hold beyond the species level comparisons. Significant genome size patterns for which sample sizes were low are nonetheless discussed in order to identify groups deserving more thorough analysis in the future.

Results

Feulaen Image Analysis Densitometry and Flow Cytometry

Comparisons between FIA and FCM were performed in order to determine the best technique to measure genome sizes in butterflies. Estimates made from sperm nuclei were significantly different from estimates of haemolymph (paired t-test, p= 0.001) (Table 2.1).

Moreover, despite a strong positive correlation between the two (r= 0.84, p=0.001 and n=58), haemolymph samples gave consistently higher estimated DNA contents than sperm (Figure 2.5).

The comparison between genome size estimates obtained using brain tissue measured by FCM versus those obtained using haemolymph measured by FIA indicate there is a significant difference between the means of the two treatments (Wilcoxon Signed Ransks, p < 0.001), with haemolymph consistently providing larger estimates than brain (Figure 2.6). Nevertheless, both

Kendall's tau and Spearman's correlations still revealed a positive relationship between the two sets of samples (Kendall's, r= 0.54, p < 0.001, n= 50; Spearman's, r=0.70, p < 0.001, n=50) (Table

2.1).

31 Brain estimates performed by FCM were significantly different from sperm estimates performed by FIA (Wilcoxon Signed Ranks, p < 0.001), with sperm values on average higher than brain (Figure 2.6). However, a strong positive correlation between the two estimates was still indicated by Kendall's tau and Spearman's correlations (Kendall's, r= 0.70, p < 0.001, n= 47;

Spearman's, r= 0.86, p < 0.001, n=47) (Table 2.1). Based on these results, and given the significant difficulties associated with measuring genome sizes of butterflies via FIA, only estimates derived from FCM brain samples were used in subsequent analyses (refer to "Feulgen Image Analysis and

Flow Cytometry" section in the discussion).

Butterflies vs. "Moths"

Genome size estimates for 84 species of butterflies are presented in Tables 2.2. These represent 12 subfamilies that were previously unstudied. In fact, of all the species presented, only three overlap with previously reported estimates: Danaus plexippus (0.29 pg by Gregory and

Hebert (2003) using heamocytes and FIA vs. 0.25 pg in the present study); Heliconius erato

(0.41pg by Tobler et al. (2005) using flow cytometry to 0.44 pg in the present study); and

Heliconious melpomene (0.30 pg by Jiggings et al. (2005) using flow cytometry vs. 0.27 pg in the present study). Thus, there is a generally good correspondence between the current FCM estimates and the few examples reported in the literature.

The average genome size among butterflies in this study was 0.42 pg ± 0.01SE, ranging from 0.23 pg in Papilio lowii to 1.04 pg in Graphium agamemnon. However, it should be noted that the estimated genome size of G. agamemnon is much larger than all other species examined; the next highest estimate is 0.64 pg in Caligo memnon.

32 Among the groups sampled in the present study, the family Papilionidae was the most variable in terms of genome size, ranging from 0.23 pg to 1.04 pg (IC = 0.39 pg ± 0.03, n = 23) followed by the Nymphalidae, ranging from 0.24 pg to 0.64 pg, (IC = 0.43 ± 0.02, n = 54) and

Pieridae, ranging from 0.31pg to 0.56pg, (IC = 0.37 ± 0.04, n = 6; but note the smaller sample size of this family) (Figure 2.7). Currently available data reveal the mean genome size of non-butterfly

Lepidoptera ("moths") to be 0.62 pg ± 0.01, which is significantly larger than the mean of 0.42 pg

± 0.01 found in the tropical butterflies examined here (Wilcoxon Signed Ranks, p<0.001) (Figure

2.8). Moreover, the superfamily of butterflies Papilionoidea showed a considerably smaller average genome size as compared to all other Lepidoptera superfamilies examined (Figure 2.9).

Within-Butterflv Comparisons

Cellular Parameters

As shown in figure 2.10, genome size is positively correlated with sperm length both in the apyrene sperm (r= 0.80, p=0.02, n=8) and eupyrene sperm (r=0.71, p=0.05, n=8), even though the latter type lacks nuclei when mature and sample sizes were small.

Morphological Parameters

Body size was measured by thorax length (MTL) and forewing length (MFW) in butterflies. Forewing length has been identified as a good indicator of body mass in this group

(Gage, 1994), but both Kendall's and Spearman's correlations revealed no significant relationships between genome size and MTL (Kendall's, r=0.06, p=0.52, n= 52; Spearman's, r=0.09, p=0.55, n=52) or MFW (Kendall's, r=0.10, p=0.28, n=53; Spearman's, r=0.18, p=0.20, n=53) (Figure 2.11).

33 Likewise, there was no relationship between genome size and scale size (Kendall's, r=0.08, p=0.39, n=51; Spearman's, r=0.10, p=0.49, n=51), contradicting the predictions of

Simonsen and Kristensen (2003) (Figure 2.12). However, thorax length and forewing length were correlated with one another (Pearson, r = 0.62, p < 0.001, n = 53) and both were positively correlated with scale size (Pearson correlations, MTL: r = 0.46, p < 0.001, n = 68; MFW: r = 0.54, p

< 0.001, n = 51)

Developmental Parameters

Developmental time was divided into three distinctive stages in butterflies: egg, larval, and chrysalides (pupal), none of which correlated with genome size in the present study (egg: r=

0.02, p= 0.93, n=25; larval: r= 0.17, p=0.35, n= 33; pupal: r= 0.02, p=0.91, n=40) (Figure 2.13).

However, when combined, egg + larval duration revealed a significant positive correlation with each other (r=0.60, p=0.002, n= 24) as well as egg + pupal duration (r=0.52, p=0.008, n=24).

Larval and pupal duration also showed a positive correlation (r=0.35, p=0.04, n=33). Finally, although data were very limited, a positive correlation was found between genome size and longevity (r=0.91, p=0.002, n= 8) (Figure 2.14).

Ecological Preference Parameters

Habitat choice and food preferences were treated as categorical parameters in this study and were primarily analysed using the non-parametric Kruskal-Wallis and Wilcoxon Signed Rank tests. Genome size was significantly different between habitat types (Kruskal-Wallis, p<0.05), with species living in the rain forest (1C=0.45 pg ± 0.03) having genome sizes significantly larger then species living in open fields (1C=0.35 pg ± 0.01) and deciduous (dry) forests (1C=0.36 pg ±

0.07) (Wilcoxon Signed Ranks, p<0.01 and p<0.05, respectively). Conversely, all other categories

34 were not significantly different from each other (Figure 2.15 and Appendix 2.4). To determine if genome size and habitat choice are indeed related to each other instead of an artefact of phytogeny, non parametric test were conducted at other taxonomic levels and revealed significant relationships at specific, generic and subfamilial levels (all p< 0.05).

Feeding preferences were divided between nectar, rotting fruits, and pollen and significant differences in genome sizes between each category were indetified (Kruskal-Wallis, p<0.001). More specifically, species that feed on rotting fruit (1C=0.49 pg ± 0.03) were found to have significantly larger genome sizes than nectar (1C=0.39 pg ± 0.02) and pollen eaters

(lC=0.35pg ± 0.05) (Wilcoxon Signed Ranks, p<0.05 in both cases (Figure 2.16 and Appendix 2.4).

This relationship was not significant at the generic and subfamilial levels (p>0.06).

Discussion

This study aimed to answer key questions regarding the diversity of genome sizes among butterflies. To this end, best-practice methods were tested for their suitability in measuring genome size in butterflies, major taxonomic/biological differences within the Lepidoptera were investigated, and numerous biological and ecological parameters hypothesized to influence genome size were examined.

Feulgen Image Analysis and Flow Cytometry

Sperm and Haemolymph

Genome size estimates obtained through Feulgen Image Analysis (FIA) with sperm were significantly different from estimates obtained via FIA with haemolymph. However, both tissues

35 were highly correlated with one another. This implies that although the values obtained from spermatozoa and haemocytes are not equal, large-scale patterns derived from them are likely to be similar. However, the most reliable comparisons with other parameters will be ones that use the most consistent genome size data, and in butterflies (but not in various other insect groups),

FIA has significant drawbacks.

Both haemolymph and sperm pose substantial challenges in measuring DNA content through FIA in butterflies. Unlike vertebrate blood (with the exception of mammals), insect haemolymph does not contain a large number of nucleated cells, making smears difficult to prepare and analyse. Also, with four or five different types of haemocytes all classified based on their unique morphology (Lackie, 1988), it is very difficult to consistently measure the same cell group. This is a problem, considering that DNA compaction - and therefore stain uptake and estimated DNA content - appears to vary between haemocyte types. The problem with inconsistent genome size estimates created by different levels of nuclear compaction is a general one in studies using FIA (Hardie et al., 2002). In addition, haemocytes in adult butterflies are known to undergo regular mitosis (Lackie, 1988), resulting in a range of DNA content estimates from 2C to 4C (Hardie et al., 2002).

Spermatozoa are always haploid, thereby alleviating concern with endopolyploidy, but difficulties still exist as a result of the aggregation of sperm in bundles, which under normal circumstances only become separated in the reproductive female tract post-mating (Shepherd,

1974, 1975). The use of tissue grinders can provide suitable numbers of intact sperm nuclei for analysis with FIA, but this is a time-consuming process and results in relatively small sample sizes.

Based on the results presented above and difficulties associated with finding and measuring adequate haemocytes, it is recommended that FIA using heamolymph not be

36 employed in future genome size studies of Lepidoptera unless no other technique or tissue types are available.

FIA vs FCM

There was a significant difference between genome size estimates obtained through

Feulgen Image Analysis and estimates derived from Flow Cytometry, independent of tissue type.

Specifically, both haemocyte and sperm measurements using FIA were significantly higher than neural tissue measurements using FCM. However, estimates based on all three tissues were highly correlated, suggesting that both techniques are adequate for identifying very general patterns in genome size diversity in butterflies. For more focused analyses it is preferred to use a single, reliable approach. In the present study, the choice was made to use only FCM estimates in the remaining analyses. However, if access to a flow cytometer is not available or if there are other logistical issues at play, acceptable genome size estimates can be obtained using FIA and sperm nuclei.

Moths and Butterflies

The present study represented the first focused survey of genome size variation among butterflies. It has greatly expanded the available dataset for Lepidoptera, generating 84 new species estimates, all but three of which had been examined before. In agreement with the proposed hypothetical 2 pg threshold for holometabolous insects, all butterfly genome size estimates in this study were well below 2 pg, and all but one were below 0.65 pg.

The only notably larger butterfly genome belonged to Graphium agamemnon (1C =

1.04pg). This is somewhat surprising given that G. agamemnon is an active flyer and fast developer, which might be expected to correspond to a small genome. Why this particular

37 species exhibit a large genome compared with other tropical butterflies remains to be determined. It is possible that chromosome-level mechanisms and repetitive DNA sequences played a significant role in increasing genome size in this species. Further work on this and related species, especially looking into cytogenetics, is necessary before any general conclusions can be drawn.

Overall, the mean genome size of the (monophyletic, tropical) butterflies was significantly different from the mean genome size of the (paraphyletic, temperate) "moths".

Butterflies seem to have a much more constrained genome size both in terms of average and range than moths, despite an overlap in the southern distribution of some families of moths. In addition, when comparing these animals at the superfamily level, the Papillionidea had the smallest average genome, in relation to all other superfamilies of Lepidoptera.

Temperate Moths and Tropical Butterflies

All moth data used for comparisons in this study were from temperate species collected at light traps in southern Ontario, while all the butterflies studied were imported from the tropics. In plants, a correlation between DNA content and latitude has been extensively examined (Bennett, 1976; Grime and Mowforth, 1982; and Bottinni et al., 2000). Bennett (1976) investigated this relationship on numerous crop plants and concluded that temperate species had larger genomes than their tropical counterparts. He suggested that this relationship is not determined by latitude per se, but probably by one or more environmental factors closely associated with changes in latitude, such as temperature, day-length, etc.

Although a similar correlation has not yet been properly tested in butterflies, it is plausible these organisms are also affected by changes in temperature and day-light availability, implying that similar patterns in DNA content may be expected. It bears noting, however, that

38 the comparison performed between butterflies and moths in this study was not controlled for

testing the influences of climate/latitude. It is still possible that differences in DNA content

between moths and butterflies are purely phylogenetic and/or functional. Future studies

focusing on investigating this relationship are warranted.

Diurnal and Nocturnal Lifestyles

In order to fly, Lepidoptera must raise their body temperature sufficiently to allow their

flight muscles to function effectively (Heinrich et al., 1973). Butterflies that are active during the

day use solar radiation to warm up and fly (Brewer and Winter, 1986), whereas nocturnal moths

rely on thicker scales and vibrations of the wing and thorax muscles to achieve body warmth

(Heinrich, 1981). These approaches may involve different energetic demands and could be linked

to metabolic processes at the cellular level and thus genome size.

Metabolism in insects does not directly depend on blood cells as it does in vertebrates.

Instead, oxygen is delivered to tissues by diffusion through the tracheal system (Weis-Fogh, 1964;

Snyder et al, 1995). Therefore, the surface area to volume ratio effects on the red blood cells that

are thought to drive correlations between metabolic rate and genome size in mammals and birds are not applicable in the same way in insects. Nevertheless, the surface area to volume ratio may

play an important role in allowing more oxygen into the cells, as smaller cells with greater surface

area to volume ratio, have a greater contact surface for 02 diffusion. This particular hypothesis

has never been investigated, as no previous study has attempted to test the direct correlation

between genome size and metabolism in invertebrates. Differences identified in this study

between nocturnal and diurnal Lepidoptera, although there were covarying and potentially confounding factors could be used to guide further work along these lines.

39 Within-Butterfly Comparisons

This study also examined patterns in genome size variation within the superfamily

Papilionoidea as related to cellular, morphological, developmental, and behavioural parameters.

Unfortunately, the present analyses could not incorporate phylogenetic information on the species of butterflies examined here due to lack of available phylogenetic information. This means that the degrees of freedom may be inflated in species comparisons and that the analyses conducted are more likely to reveal significant relationships. By contrast, an apparent lack of significant correlations between two parameters would probably be reinforced if phylogenetically comparative methods could be used.

Cellular Parameters

Both eupyrene and apyrene sperm lengths were highly correlated to genome size in butterflies, such that species with large spermatozoa were also found to have large genomes.

Apyrene sperm are formed with a nucleus which is then shed out from the cell close to the end of development (Salama, 1976). The function of these anucleated spermatocytes is still unknown

(Friedlander, 1997). The fact their size correlates with genome size even though they do not contain nuclei parallels the observations made in the enucleated red blood cells of mammals and certain salamanders (Gregory, 2000; Mueller et al., 2008).

Eupyrene sperm are functionally active in fertilization (Garcia-Gonzalez, 2004); therefore these cells may be under selection for various properties, especially since sperm competition plays an important role in selection of sperm number, testis size, and sperm size in many butterflies. In fact, some hypotheses suggest that sperm competition may even be able to predict increases and decreases in spermatocyte size (Garcia-Gonzalez, 2004). If genome size imposes

40 any limits on minimum sperm length, then it is plausible that selection on sperm size has resulted indirectly in changes in genome size among butterflies.

Morphological Parameters

Gregory and Hebert (2003) noted that the largest moths measured in their study did not exhibit the largest genomes, although an explicit relationship between genome size and body size was not tested. Neither forewing nor thorax length correlated with DNA content in butterflies in this study, suggesting that cell number as opposed to cell size may play a more influential role in determining body size in this group. This is unlike the situation observed in other groups of arthropods, such as copepod crustaceans where cell number remains constant and cell growth determines body size (Gregory et al., 2000). Furthermore, contrary to the hypothesis presented in Simonsen and Kristensen (2003), scale size did not correlate with genome size in butterflies.

Developmental Parameters

An investigation of the relationship between genome size and developmental time in butterflies was attempted in the present study. Compiled field data on egg duration, larval duration, and time from start of pupal stage until eclosion were examined. Based on the present analysis, genome size does not correlate with any of these developmental parameters in butterflies. This differs from observations from other insects such as ladybird beetles and flies in the genus Drosophila, in which larger genome sizes are correlated with slower overall development (Gregory et al., 2003; Gregory and Johnston, 2008). On the other hand, longevity does appear to correlate positively with genome size in butterflies, at least across the very limited number of species for which data are available. It is important to note however, the most likely cause for this correlation is a small sample size. Similar correlations have been reported in

41 birds and fishes (Monaghan and Metcalfe, 2000; and Griffith et al., 2003), but these claims have been strongly challenged by subsequent analyses (reviewed in Gregory, 2005b).

Ecological Preference Parameters

Genome size has the potential of being associated with numerous behavioural and ecological parameters, as long as these parameters can be linked back to cytological, morphological, and physiological traits influenced by DNA content. Although uncommon, a few examples of such links have been observed in animals and plants (reviewed by Bennett and

Leitch, 2005; Gregory, 2005b). For example, in insects of the order Hymenoptera, genome size has been linked with parasitism, so that parasitic species have significantly smaller genomes than non-parasitic ones. This relationship is based on the link between genome size and development, since parasitic Hymenoptera have much faster developmental rates than their non-parasitic counterparts (Ardila-Garcia and Gregory, 2009). It is plausible numerous relatioships such as this may exist in regards to genome size in several groups, providing an association exists between

DNA content and organismal-level traits.

In this study, genome sizes were found to correlate with different microhabitats in butterflies. Notably, species that live the rainforest exhibited significantly larger genomes than species from open fields and deciduous forests. A possible explanation for this pattern may be associated with differences in the level of activity of butterflies from the different habitats.

Higher levels of activity would be directly linked with higher metabolic demands, which have been shown to correlate with genome size in other groups of animals (Gregory, 2005b).

In the case of the butterflies, species in rainforests may be less active due to the presence of dense vegetation with lots of places to hide from predators and climatic elements, such as wind and rain. On the other hand, open fields and deciduous (dry) forests have much

42 sparser vegetation with fewer shelter spots for the butterflies to hide (Sparks and Greatorex-

Davies, 1997). It is plausible that in these butterflies have to fly longer distances and more often in order to avoid predators (especially birds) and find adequate perching places. Therefore it could be expected that these butterflies would have higher metabolism than species from the rainforest.

Likewise, butterflies feeding predominantly on rotting fruits were found to have significantly larger average genome sizes than both pollen and nectar feeders. Hall and Willmott

(2000) proposed that choice of food is directly correlated with both flight speed and metabolic rate at least in male butterflies. Few studies have attempted to quantify the amount of energy provided by different food sources, but it is likely differences exist (Gilbert, 1972; O'Brien, 1999; and Romeis and Wackers, 2000). Just as in the case of microhabitats, differences in the amount of energy provided by each food type and their effects on flight activity and metabolic rate could explain the relationship observed here in regards to genome size. A direct correlation between

DNA content and metabolism has been observed among several groups of animals (mainly vertebraters), where fast metabolic rates are associated with small genome sizes.

Questions and Predictions Revisited

The present study was undertaken in order to address a series of specific research questions, which can be revisited in light of the results obtained:

1. What is the range in genome sizes across the superfamily Papilionoidea, and do these

values fall within the observed 2pg threshold?

43 Evidence provided in this study supports the hypothesis that butterfly genomes are constrained well below the 2pg threshold observed for holometabolous insects. In fact, most butterflies had genome sizes smaller than 0.65pg, with the exception of Graphium agamemnon, at 1.04pg.

2. Is there a significant difference in the mean DNA content of butterflies relative to other

Lepidoptera?

Genome sizes of the monophyletic clade known as butterflies were significantly smaller than the rest of the Lepidoptera. Moreover, the superfamily Papilionoidea had a considerably smaller estimate than all other "moth" superfamilies examined to date. This relationship is likely caused by differences between lifestyle and geographic distribution of the two groups examined. While all moths were temperate and nocturnal, all butterflies were tropical and diurnal.

3. Does genome size correlate with sperm size in butterflies?

Both eupyrene (nucleated) and apyrene (enucleated) sperm length and genome size in butterflies are positively correlated.

4. Is genome size diversity in butterflies associated with variability in body size?

Genome size did not correlate with any body size parameters investigated in this study, suggesting that body size is not a major factor in explaining butterfly genome size diversity, and that it may be determined more by cell number than cell size.

5. Is there a relationship between genome size and wing scale size?

Despite previous speculations of a significant relationship between genome size and scale area in butterflies, no correlation was observed in this study.

44 6. Can developmental parameters explain the observed diversity of genome sizes in

butterflies?

All developmental parameters examined in this study were unrelated to genome size in butterflies. However, it is important to note that all developmental data were compiled from multiple sources in the literature, and differences in measuring developmental stages could have greatly affected the results. External factors, such as temperature and humidity, when not controlled will cause major differences in the length of development.

7. Do behavioural parameters such as food and regional habitat preferences influence

genome size diversity in Papilionoidea?

Both food and regional habitat preferences were associated with genome size in butterflies, perhaps due to a link between genome size and metabolism. In this study, rainforest butterflies exhibited larger genomes than species living in open fields, whereas species that feed predominantly on rotting fruit had the largest genomes compared to nectar and pollen eaters.

Future directions

The present study was the first to venture into the unexplored territory of butterfly genome size diversity. With 155,000 described species, the current dataset represents only a small addition to the coverage of the Lepidoptera as a whole, but it nevertheless provides a major increase in the knowledge of this order by addressing a serious gap in prior information. Based on the results of this study, some areas of particular interest can be identified for future research:

1) The results presented in this chapter imply a possible association between genome size

and metabolism in butterflies, which could be investigated through targeted comparative

45 analyses of groups with different ecological and physiological traits. In all cases, the

inclusion of phylogenetic analyses would be desirable once the necessary data become

available.

2) The Papilionoidea forms a phylogenetic clade together with Hedyloidea and

Hesperioidea, therefore it would be interesting to compare the genome size of the true

butterflies with their sister taxa in order to determine if a reduction in genome size is

associated with the larger clade or if it is unique to the Papilionoidea.

3) Preliminary results revealed a considerable constraint in genome size within tropical,

diurnal butterflies in comparison to temperate, nocturnal "moths". It is possible this

relationship is based solely on the differences in geographical distribution and lifestyle

between the two groups. In order to determine if genome sizes are in fact different

between butterflies and all other Lepidoptera, the next step is to examine genome sizes

of tropical and diurnal moths, and temperate butterflies.

46 i Coleoptera mmm (185/400,000) \ Diptera «H» (244/140,000) i Hymenoptera

Hemiptera (54/80,000)

Isoptera <§U^K- (14/2,600)

Mantodea -# (3/2,200)

Odonata (144/6,200)

Orthoptera "Gfe • - ?• #&+ > • <€*' *, (67/20,000) '

Phasmida ^ m (11/3,000)

Phthiraptera (2/3,000)

Strepsiptera " (2/600)

0.00 5.00 10.00 15.00 20.00

Genome Size (pg)

Figure 2.1. Distribution of genome size diversity within major orders of insects available in the

Animal Genome Size Database. Holometabolous insects (complete metamorphosis with distinct egg, larval, pupal, and adult life stages) are represented by Coleoptera, Diptera, Hymenoptera and Lepidoptera and are all below the 2pg hypothetical threshold. The number of individual estimates and the total number of described species are given in parenthesis for each group.

Dark shades illustrate areas of high concentration of estimates.

47 non-Ditrysia (outgroups) Tineoidea Yponomeutoidea (part.) Gracillarioidea Yponomeutoidea Epermeniodea Copromorphoidea Urodoidea Schreckensteinioidea Gracillarioidea (part.) Rerophoroidea Choreutoidea Immoidea Galacticoidea Tortricoidea Hesperioidea Hedyloidea Papilionoidea Hyblacoidea Tnyriodoidea Mimallonoidea Gelechioidea Sesioidea Cossoidea Sesioidea (part.) Zygaenoidea Alucitoidea Calliduloidea Pyraloidea Geometroidea Drepanoidea Lasiocampoidea Geometroidea (part.) Drepanoidea (part.) Axioidea Bombycoidea Noctuoidea

Figure 2.2. Phylogenetic tree assembled from Mutanen, Wahlberg and Kaila, 2010 including all the major superfamilies within the Lepidoptera. The Papilionoidea, representing the true butterflies, is highlighted in red and it is monophyletic though it is nested within the paraphyletic group commonly called "moths".

48 Figure 2.3. Feulgen-stained nuclei from two species of butterflies. A) Spermatozoa from Heliconius melpomene (IC = 0.27pg) B) Haemocytes from Hypolimnas missipus (IC = 0.44pg). Magnification at 1000X.

49 Figure 2.4. Different sizes of Feulgen-stained haemocyte nuclei from the same individual.

Heliconius erato (GS = 0.44pg). Magnification at 1000X.

50 0.2

0.1 y = 0.942x + 0.0123

.£ Q. 0 E > -0.1 E 0o) (0 -0.2 X 1 y -0.3 '5! >- -0.4 (Pg ) Ana l 01 -0.5 bo n> E -0.6 c 01 -0.7 3 01 LL. -0.8 60 q -0.8 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 Log Feulgen Image Analysis - Sperm (pg)

Figure 2.5. Relationship between genome size estimates obtained by Feulgen image analysis densitometry using haemolymph versus sperm. The line of conformity is shown (dashed line) along with the regression line (solid line) (r=0.84, p < 0.001, n= 58).

51 0.2 • C-values from sperm y = o.9194x + 0.0042 0.1 O C-values from haemolymph y = 0.8998x + 0.0361

0

"So 3 -0.1 10 g -0.2 < ai ff -0.3 E I -0-4 3 01 oo -0.5 o

-0.6

-0.7 O O

-0.8 -0.8 -0.6 -0.4 -0.2 0.2 Log Flow Cytometry (pg)

Figure 2.6. Relationship between genome size estimates obtained by Feulgen image analysis densitometry using either haemocytes or sperm and by flow cytometry using brain tissue. (A) regression line for haemolymph vs brain (Spearman's, r=0.70, p < 0.001, n=50) and (B) regression line for sperm vs brain (Spearman's, r= 0.86, p < 0.001, n= 47).

52 1.00-

BO-

54 Q. 23 at o _N .60" "E5 at E o c a» O .40"

"X .20*

.00" Nymphliadae Papilionidae r^ Piei idae

Figure 2.7. Distribution of genome sizes among the 3 butterfly families. Papilionidae had the largest range between the familes (0.23 pg to 1.04 pg), followed by the Nymphalidae (0.24 pg to

0.64 pg) and the Pieridae (0.31 pg tp 0.56 pg).

- represents samples that are within three "box lengths" from the upper quartile value *- represents samples that are further than three "box lengths" from the upper quartile value

53 Butterflies 90 I Moths 80

70

60

.2 50 '0v a. £ 40 o | 30 3 z 20

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 Genome Size (pg)

Figure 2.8. Distribution of genome sizes in butterflies and "moths". The average butterfly genomes size (IC = 0.41pg ± 0.013SE) is significantly smaller than the average "moth" genome size (IC = 0.62pg ± 0.013SE).

54 1.2

0.8 53 62 M 60 I I 131 10 a o.6 45 (/> T V 1 E 83 o | 0-4 c re v 5 0.2

•#? ,jf -^ -^ #* -^ -^ ^ #* ^ ^ ^ ^

3# *

Figure 2.9. Average genome size of all lepidopteran superfamilies examined to date. The smallest genomes belong to the Papilionoidea, the true butterflies.

55 (A) (B) 3.3 y = 0.7662x +3.0391 y=1.1846x +3.4996 2.9 3.2 E 2.85 E to 3.1 c JZ 01 2.8 to c 01 01 Q. 2.75 to 01 01 2.9 c Q. 01 £c 2.8 Q. 0>1 < Q. 60 2.65 3 UJ 2.7 o 00 o 2.6 2.6 -0.6 -0.5 -0.4 -0.3 -0.2 -0.6 -0.5 -0.4 -0.3 -0.2 Log Genome Size (pg) Log Genome Size (pg)

Figure 2.10. Relationships between genome size and sperm size in butterflies, measured as (A) Mean Apyrene Sperm Length (u.m)(r=0.80, p=0.02, n=8) and (B) Mean Eupyrene Sperm Length (u.m) (r=0.71, p=0.05, n=8). A significant positive relationship can be seen in both cases.

56 A)

1.1 y = 0.1247X + 0.8684

1 E u'0. 9 toi c 01 -I I0. 8 X re 0.7 )

0.6 • #

0.5 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0.1 Log Genome Size (pg)

B) 2.05 y = 0.3634X + 1.793 1.95 , . E 1.85 .c to 1.75 2c GO C 1.65 i 1.55 uo. 00 1.45 o _1 1.35

1.25 -0.7 -0.6 -0.5 -0.4 0.3 -0.2 -0.1

Log Genome Size (pg)

Figure 2.11. A) Illustration of the relationship between genome size(pg) and mean thorax length

(mm). Kendall's tau and Spearman's rho correlations revealed no significant relationship between these parameters (Spearman's, r=0.08, p=0.55, n= 52). B) Illustration of the relationship between genome size (pg) and forewing length (mm), no significant correlation was found between the two parameters (Spearman's, r=0.18, p=0.2, n=53).

57 4.4 , y = -0.0577X + 3.7348

4.2

X 'a. ~Z 3-8 N <75 % 0re1 • ' • v> 3.6 , # ** # Q

3.4

3.2

3 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 Log Genome Size (pg)

Figure 2.12. Relationship between genome size (pg) and scale size (pixels) in butterflies. The largest scale type in the wing was consistently chosen for these measurements. No correlation was found between genome size and scale size (Speaman's, r=0.1, p=0.49, n=51).

58 Log Development Inside the Egg -^ Log Duration as a Larva (days) (days)

10 i-> Co Ln ID O O O O O O Ln Ln Ln Ln Ln Ln Ln In cn 00 o P kj ki < -< II II p O LO o b o Ln i-> 00 in cn X • • NJ X + + p o •$• ID p Ln o In l-» Ln Ln

o *» i-o 00 (t>a a 3 m O , 3 p m Lo i° "J (DLO N' J/l n> IM* n> •D p TOO 22. k>

Ln LO C) 2 y = -0.0291x +1.1711 tt) o. 1.8 3 Q. 1.6 m nin "uT 1.4 41 ** c > re 1.2 o •o 4-* *F^—•A rf * • re 1 • 3 Q 0.8 t>0 o 0.6 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1

Log Genome Size (pg)

Figure 2.13. Relationship between genome size and A) Duration in the egg (r= 0.02, p= 0.93, n=23); B) Duration as a larvae (r=0.17, p=0.35, n= 32); C) Duration as a chrysalis (r=0.02, p=0.91, n=39). Pearson correlations did not reveal any relationships between these parameters.

60 1.8 y = 2.6066x + 2.1011 1.6 U) (>0 13 1.4

4->» 01 1.2 00 c 5 1 00 —oI 0.8

0.6 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1

Log Genome Size (pg)

Figure 2.14. Illustration of the relationship between genome size and longevity. A strong positive correlation can be seen between the two parameters (r=0.91, p=0.002, n=8), although the sample size was very limited.

61 1 1 1 i Open Field n=17 Rainforest n= Distut bed fields n=7 Deciduous forests n=14

Figure 2.15. Distribution of genome sizes among the four categories representing habitat types in tropical butterflies. Rain forests species showed significantly different genome sizes than open field and deciduous species (Wiicoxon Signed Ranks, p<0.05). No other habitat was found to be significantly different from one another.

62 1 E ! Nectar n=29 Rotting Fruit n=18 Pollen n=

Figure 2.16. Distribution of genome sizes among the three feeding categories: nectar eaters, rotten fruit eaters, pollen eaters. Species that feed on rotten fruits had significantly larger genomes than species feeding predominantly on nectar or pollen (Wilcoxon Signed Ranks, p<0.05).

63 Table 2.1. Mean genome size estimates (GS, in pg) for all butterfly species, including measurements from Feulgen Image Analysis haemolymph

(FIAh); Feulgen Image Analysis sperm (FIAs) and Flow Cytometry neural tissue (FCMn). Standard errors and number of individuals are given for all estimates. A recommended estimate is included for all species examined. In cases where flow cytometry values were not available, Feulgen image analysis sperm measurements were recommended instead.

SE SE SE Recommended Species FIAh +/- n FIAs +/- n FCMn +/- n estimate Adelpha fessonia 0.60 0.13 2 0.56 0.07 2 0.56

Anartia fatima 0.50 N/A 1 0.48 N/A 0.48

Anteos clorinde 0.37 0.01 2 0.32 N/A 0.30 0.04 6 0.30

Anteos maerula 0.33 0.02 2 0.56 N/A 0.56

Appias drusilla 0.46 N/A 1 0.51 N/A 0.38 0.02 4 0.38

Archaeoprepona demophon 0.49 0.04 2 0.45 N/A 0.31 0.01 4 0.31

Ascia monuste 0.54 N/A 1 0.54

Battus belus 0.66 0.14 2 0.76 0.22 2 0.51 0.06 3 0.51

64 SE SE SE Recommended Species FIAh +/- n FIAs +/- n FCMn +/- [] estimate

Battus polydamus 0.59 N/A 1 0.52 N/A 1 0.45 0.05 5 0.45

Biblis hyperia 0.62 0.11 3 0.62 N/A 1 0.62

Caligo atreus 0.61 0.06 3 0.61

Caligo eurilochus 0.58 0.19 2 0.55 0.09 2 0.56 0.08 6 0.56

Caligo illloneus 0.62 0.07 3 0.62

Caligo memnon 0.77 0.05 3 0.64 0.09 2 0.64 0.03 4 0.64

Catonephele mexicana 0.48 0.00 2 0.48 0.47 0.07 4 Catonephele numilia 0.60 0.06 3 0.46 0.07 2 0.46 0.46 0.17 2 Cethosia biblis 0.44 0.01 2 0.36 0.00 2 0.36 0.48 N/A 1 Chlosyne janais 0.34 0.01 4 0.34 0.43 0.06 2 Colobura dirce 0.31 N/A 1 0.33 0.04 2 0.33

Consul fabius 0.46 0.03 3 0.46 0.58 N/A 1 Danaus affinis 0.50 N/A 1 0.50 0.45 N/A 1 Danaus chrysippus 0.41 N/A 1 0.41 0.04 3 0.41 N/A N/A 0 Danaus plexippus 0.24 N/A 1 0.25 0.02 3 0.25

65 SE SE SE Recommended Species FIAh +/- FIAs +/- n FCMn +/- n estimate Dionejuno 0.28 N/A 1 0.39 N/A 1 0.33 N/A 1 0.33

Dione moneta 0.33 0.03 3 0.33

Doleschallia bisaltide 0.39 0.01 2 0.39

Doxocopa laure 0.42 N/A 1 0.42

Dryadula phaetusa 0.45 0.06 4 0.44 0.02 4 0.44

Dryas iulia 0.55 0.07 6 0.47 0.08 2 0.45 0.00 2 0.45

Elymnias hypermnestra 0.41 0.03 4 0.46 0.02 4 0.46

Eueides Isabella 0.39 0.03 3 0.39

Eurytides phaon 0.46 0.02 3 0.46

Graphium agamemnon 1.34 0.02 2 0.89 0.07 4 1.04 0.04 4 1.04

Greta oto 0.44 N/A 1 0.44

Hamadryas arinome 0.58 0.03 4 0.58

Hamadryas februa 0.36 0.12 5 0.40 0.01 2 0.40

Hebomoia glaucippe 0.37 N/A 1 0.37

Heliconius charitonia 0.40 0.05 4 0.39 0.00 2 0.39 0.04 4 0.39

66 SE SE Recommended FIAs +/- n FCMn +/- n estimate

0.28 0.03 4 0.25 N/A 1 0.25

0.42 0.10 5 0.37 0.04 3 0.37

0.44 0.04 6 0.44

0.43 0.09 3 0.36 N/A 1 0.36

0.31 N/A 1 0.38 0.06 3 0.38

0.38 N/A 1 0.32 0.03 4 0.32

0.23 0.00 2 0.31 0.03 6 0.31

0.48 0.04 2 0.50 0.04 2 0.50

0.41 0.05 4 0.34 N/A 1 0.34

0.34 0.01 2 0.38 0.04 12 0.38

0.50 0.01 2 0.38 0.04 3 0.38

0.30 0.00 2 0.29 0.03 2 0.29

0.41 N/A 1 0.28 N/A 1 0.28

0.31 0.02 3 0.31

0.39 0.02 2 0.39

67 SE SE SE Recommended Species FIAh +/- n FIAs +/- n FCMn +/- n estimate Memphis eurypyle 0.38 0.05 2 0.44 N/A 1 0.44 Morpho granadensis 0.47 0.03 5 0.47 Morpho peleides 0.61 0.07 3 0.47 0.04 2 0.41 N/A 1 0.41 Morpho polyphemus 0.62 0.05 3 0.52 N/A 1 0.45 0.01 3 0.45 Myscelias ethusa 0.50 0.06 2 0.50 Myscelias cyaniris 0.65 0.05 4 0.58 0.05 3 0.54 0.03 5 0.54 Ornithoptera priamus 0.51 N/A 1 0.47 0.04 2 0.35 0.05 4 0.35 Pachliopta kotzebuea 0.43 0.07 6 0.34 0.01 3 0.37 0.02 3 0.37 Papilio anchisiades 0.22 0.01 2 0.27 0.01 2 0.26 0.01 3 0.26 Papilio androgeus 0.39 N/A 1 0.39 Papilio astyalus 0.27 0.02 3 0.27 0.06 3 0.55 N/A 1 0.55 Papilio erostratus 0.28 0.03 2 0.28 Papilio hipponous 0.33 N/A 1 0.23 N/A 1 0.23 Papilio lowi 0.33 0.07 2 0.28 0.05 3 0.23 N/A 1 0.23 Papilio memnon 0.32 N/A 1 0.32

68 SE SE SE Recommended Species FIAh +/- n FIAs +/- n FCMn +/- n estimate 0.83 0.07 2 0.64 0.04 3 0.57 0.07 11 0.57 Papilio palinurus 0.35 0.04 4 0.27 0.02 3 0.27 0.00 3 0.27 Papilio polytes N/A N/A 0 0.31 N/A 1 0.32 0.06 3 0.32 Papilio polyxenes 0.20 0.01 2 0.24 0.00 3 0.27 0.01 9 0.27 Papilio rumanzovia 0.33 N/A 1 0.28 N/A 1 0.25 0.02 5 0.25 Papilio thoas 0.39 0.13 2 0.37 0.04 2 0.32 0.03 5 0.32 Papilio ulysses 0.37 0.08 2 0.32 0.03 4 0.26 0.02 2 0.26 Parides areas N/A 1 0.38 Parides chilasedeous 0.38 N/A 1 0.39 Parides childrenae 0.39 N/A 1 0.05 11 0.33 Parides iphidamas 0.44 N/A 1 0.35 0.33 0.68 0.03 2 0.07 7 0.45 Parthenos sylvia 0.45 0.50 0.10 4 0.46 0.06 4 0.44 0.02 2 0.44 Philaethria dido 1 0.04 0.32 Phoebis philea 0.43 N/A 0.31 N/A 1 0.32 3 2 0.01 4 0.31 Phoebis sennae 0.39 0.03 0.33 0.03 2 0.31

Siproeta epaphus 0.45 0.01 3 0.45

69 SE SE SE Recommended Species FIAh +/- n FIAs +/- n FCMn +/- n estimate 0.03 3 0.40 0.05 0.40 Siproetas stelenes 0.54 0.14 3 0.45 6 0.30 N/A 0.30 Tithorea tarricina 0.35 N/A 1 1 0.02 2 0.34 0.02 0.34 Troides rhadamantus 0.48 0.04 2 0.39 2

70 Table 2.2. New mean genome size estimates (C-value, in pg) for all butterfly species examfned in this study organized taxonomically. Most values were measured via Flow Cytometry (FCM), but

Fuelgen Image Analysis using sperm (FIAs) were also included for species which FCM estimates were not available. Standards used in determining C-values included Drosophila melanogaster

(GS= 0.18pg) and Bombyx mori (GS= 0.52pg). Butterfly tissue was collected from both Niagara

Butterfly Conservatory and Cambridge Butterfly Conservatory.

Method Family Subfamily Species C-value Genus used Nymphalidae Apaturinae Doxocopa Doxocopa laure 0.42 FCM

Brassolinae Caligo Caligo Atreus 0.61 FCM

Caligo illoneus 0.62 FCM

Caligo eurilochus 0.56 FCM

Caligo memnon 0.64 FCM

Charaxinae Archeoprepona Archaeprepona demophon 0.38 FCM

Consul Consul fabius 0.46 FCM

Memphis Memphis eurypyle 0.44 FIAs

Danainae Danaus Danuas affinis 0.50 FIAs

Danuas chrysippus 0.41 FCM

Danaus plexippus 0.24 FCM

Idea Idea leuconoe 0.29 FCM

Ideopsis Ideopsis juventa 0.28 FCM

eliconiinae Cethosia Cethosia biblis 0.40 FCM

Dione Dione juno 0.33 FCM

71 Method Family Subfamily Genus Species C-value used Dione moneta 0.33 FCM

Dryadula Dryadula phaetusa 0.44 FIAs

Dryas Dryas iulia 0.45 FCM

Eueides Eueides Isabella 0.39 FCM

Heliconius Heliconius charitonia 0.39 FIAs

Heliconius cydno 0.27 FCM

Heliconius doris 0.39 FCM

Heliconius erato 0.44 FIAs

Heliconius hecale 0.36 FCM

Heliconius hewitsoni 0.34 FCM

Heliconius ismenius 0.35 FCM

Heliconius melpomene 0.27 FCM

Heliconius sapho 0.49 FCM

Heliconius sara 0.37 FCM

Philathria Philathria dido 0.45 FCM

Ithomiinae Mechanitis Mechanitis menapis 0.31 FCM

Mechanitis polymnia 0.39 FIAs

Tithorea Tithorea tarricina 0.30 FCM

Limenitidinae Pathernos Parthenos Sylvia 0.45 FCM

Melitaeinae Chlosyne Chlosynejanais 0.34 FCM

Nymphalidae Morphinae Morpho Morpho granadensis 0.47 FCM

72 Method Family Subfamily Genus Species C-value used Morpho peleides 0.44 FCM

Morpho polyphemus 0.49 FCM

Nymphalinae Adelpha Adelpha fessonia 0.56 FIAs

Anartia Anartia Fatima 0.48 FIAs

Biblis Biblis hyperia 0.62 FIAs

Catonephele Catonephele Mexicana 0.48 FCM

Catonephele numilia 0.53 FCM

Colobura Colobura dirce 0.33 FCM

Doleschallia Doleschallia bisaltide 0.39 FCM

Hamandryas Hamandryas arinome 0.58 FCM

Hamandryas februa 0.40 FCM

Hypolimnas Hypolimnas bolina 0.38 FCM

Hypolimnas missipus 0.38 FCM

Myscelia Myscelia cyaniris 0.54 FCM

Myscelia ethusa 0.50 FCM

Siproeta Siproeta epaphus 0.45 FCM

Siproetas stelenes 0.40 FCM

Satyrinae Elymnias Elymnias hypermnestra 0.46 FIAs

Papilionidae Papilioninae Battus Battus belus 0.51 FCM

• Battus polydamus 0.45 FCM

Eurytides Eurytides phaon 0.46 FCM

73 Method Family Subfamily Species C-value Genus used Graphium Graphium agamemnon 1.04 FCM

Ornithoptera Ornithoptera priamus 0.35 FCM

Papilio °apilio anchisiades 0.26 FCM

aapilio androgenus 0.39 FCM

Papilio astyalas 0.55 FCM

Papilio erostratus 0.28 FCM

Papilio hipponous 0.23 FCM

Papilio lowii 0.23 FCM

Papilio palinurus 0.57 FCM

Papilio polytes 0.27 FCM

Papilio polyxenes 0.31 FCM

°apilio rumanzovia 0.27 FCM

Papilio thoas 0.25 FCM

Papilio Ulysses 0.32 FCM

Parides Parides areas 0.26 FCM

Parides chilasedeous 0.38 FCM

Parides childrenae 0.39 FCM

Parides iphidamas 0.34 FCM

Papilionidae Papilioninae Troides Troides rhadamantus 0.34 FCM

Polyommatinae Pachliopta Pachliopta kotzebuea 0.37 FCM

Pieridae Coliadinae Anteos Anteos clorinde 0.31 FCM

74 Method Family Subfamily Genus Species used Anteos maerula 0.56 FIAs

Phoebis Phoebis philea 0.32 FCM

Phoebis sennae 0.31 FCM

Pierinae Appias Apppias Drusilla 0.38 FCM

Hebomoia Hebomoia glaucippe 0.37 FCM

75 CHAPTER THREE

CASE STUDY TWO: AN EXAMINATION OF ECOLOGICAL PATTERNS IN GENOME SIZE VARIATION IN GASTROPOD AND BIVALVE MOLLUSCS

76 Introduction

The phylum Mollusca is the second largest in animals after the Arthropoda, with

130,000 named species (Haszprunar et al., 2008). They represent the most diverse group of marine animals, with 23% of all species in the world's oceans. Apart from their sheer abundance and worldwide distribution, molluscs are of particular biological interest due to their remarkable variability in morphology and ecology- ranging from a tiny terrestrial snail to the colossal deep- sea squid, and from relatively simple clams to highly intelligent octopi.

Living molluscs are divided into seven or eight classes: Aplacophora (often separated into Solenogastres and Caudofoveata by taxonomists), Bivalvia (mussels and clams),

Cephalopoda (squids and octopi), Gastropoda (snails and slugs), Monoplacophora,

Polyplacophora (chitons) and Scaphopoda (tusk shells) (Ponder and Lindberg, 2008). The classes

Bivalvia and Gastropoda make up more than 90% of the diversity in the phylum (with 20,000 and 100,000 species respectively) (Haszprunar et al., 2008) and are the focus of the present study.

Bivalves are bilaterally compressed and bounded by two symmetrical shells. They are common components of marine and freshwater environments across the world (Giribet, 2008).

Their unique morphology is believed to be directly associated with their suspension feeding habits (Haszprunar et al., 2008). In general, most bivalves are indirect developers with marine species producing planktonic, free-swimming larvae which are released in the water column

(Giribet, 2008). Some freshwater species have evolved a parasitic larval stage, called glochidia, which attaches to fish (or in some cases salamander) hosts and it stays attached until it is ready to metamorphose and settle into the substrate (Cummings and Bogan, 2006).

The class Gastropoda is characterized by having a single shell with an operculum, at least in early development, and by body torsion experienced in the larval stage (Aktipis et al.,

77 2008). As the largest molluscan class and the second most species-rich animal class, gastropods show a great disparity in morphology, physiology, and ecology. They have adapted to a variety of environments and are found in most major habitats (Aktipis et al., 2008). The variety in feeding mechanisms and diets employed by this group is extensive, including: herbivores, predaceous carnivores, scavengers and parasites (Dillon, 2006; Pearce and Orstan, 2006; Geiger,

2006). Unlike bivalves, gastropods exhibit a diverse range of developmental strategies including indirect and direct developers, species that attach their eggs to the vegetation and species that give birth to live young. These developmental modes are generally linked with habitat, since direct developers and live births are most commonly found among freshwater and terrestrial species.

Bivalves and gastropods are of major economic importance to humans (Haszprunar et al., 2008), but they also are among the most vulnerable organisms. In fact, unbeknownst to a broad public, no other group of animals has so many species under threat of extinction by mankind (Lydeard et al., 2004). Despite their importance and abundance, these classes seldom receive the research attention they deserve (Simison and Boore, 2008) including in genome biology. A search in ISI Web of Knowledge bibliographic database for the terms "Mammals",

"Birds", "Insects", "Gastropods" and "Bivalves" all in combination with "Genome" returned

15,654; 6,621; 6,906; 68; 149 publications respectively (Figure 3.1). These searches illustrate, for example, that gastropod papers amount to 0.43% of the number of available papers for mammals. These results reinforce the view that malacology in general and gastropods and bivalves in specific have been poorly studied from many perspectives, especially in the field of genomics (Simison and Boore, 2008).

78 Molluscs and Genome Size

Within the field of molluscan genome biology, genome size remains in need of particular attention. As with many invertebrate taxa, molluscs are vastly underrepresented in terms of

DNA content relative to their diversity. Only estimates for 237 species representing four of the seven extant classes are included in the Animal Genome Size Database, which accounts for less than 0.18% of their total biodiversity. Bivalves and gastropods have the highest number of estimates with 88 and 129 r espectively, but in terms of total coverage they are the most underrepresented at 0.40% and 0.13% of the total number of described species (Figure 3.2).

Nevertheless, based on the limited data available, some interesting preliminary observations can be made. For example, the entire range in mollusc DNA content occurs within the class Gastropoda alone; from 0.43 pg in the Owl limpet, Lottia gigantean, to 7.85 pg in the terrestrial snail, Diplommatina kiiensis (Gregory, 2011). Based on current data, the mean genome size of molluscs in general is 1C=2.13 pg ± 0.09, whereas it is 1C=1.69 pg ± 0.06 for bivalves and 1C=2.32 pg ± 0.12 for gastropods. These values fall within the ranges observed for much better-studied vertebrates; the means are larger than seen in teleost fishes and birds and similar to that of reptiles (Gregory, 2011).

The major patterns of genome size diversity within molluscs have not been well investigated, though there have long been speculations in this regard. In 1951, Mirsky and Ris suggested that the most "primitive" members of the Mollusca had the smallest genome sizes; their idea was based on the notion that cephalopods are more "developed" than other classes within the group, such as gastropods and polyplacophorans. This earlier suggestion has not stood up to further analysis, in part because the concepts of more or less "developed" organisms is problematic and moreover because cephalopods do not have the largest genomes among molluscs (Gregory, 2011).

79 Two decades later, Hinegardner (1974) proposed a pattern within gastropods and bivalves in which genome size are larger in 'generalized' species as compared to 'specialized' species. The rationale behind this proposed pattern came from idea that "evolution of groups such as fishes, insects, and amphibians, all appear to have been accompanied by specializations, loss of parts and loss of DNA" (Hinegardner, 1974). Since then, his results have been widely debated. It is unclear what parameters he used to differentiate a "specialized" from a

"generalized" species. For example, a generalist filter-feeder may nevertheless be very specialized in terms of reproductive biology, as seen in freshwater mussels - it is not clear how such a species would be classified in Hinegardner (1974) scheme.

Big genomes for Land Pioneers?

Aside from the problematic notion of "developed" or "generalized" species having large genomes (Mirsky and Ris, 1951; Hinegardner, 1974), few other large-scale patterns have been proposed in molluscs, perhaps because the data are still too limited for these to be investigated.

More recently, and on a much more focused scale, Vinogradov (2000) suggested a pattern in which genome sizes are related to habitat transitions. In particular, he reported new data indicating that terrestrial pulmonate snails (Stylommatophora) have DNA contents roughly twice as large as their freshwater relatives (Basommatophora). He believed that this represented a causal relationship, and even went so far as to suggest these results paralleled the case of large genome sizes in amphibians and lungfishes, ""indicating that a genome enlargement in the land pioneers is not incidental".

The reason, he argued, is that large genomes provide a cytogenetic buffer against the challenges of harsh terrestrial environments: "terrestrial snails, which should sustain much

80 greater fluctuations in humidity and temperature than watery molluscs, have markedly larger genomes" (Vinogradov, 1998).

Despite the suggested parallelism between vertebrates and molluscs and the proposed adaptive significance of large genomes on land, many questions remain about the validity of this relationship. In amphibians, for example, the groups with the largest genomes are the aquatic

(and neotenic) salamanders, whereas the smallest genomes are found in frogs living in deserts

(Gregory, 2011). Furthermore, there is no evidence that the terrestrial molluscs analyzed by

Vinogradov were actually pioneers on land or that they are phylogenetically related to the aquatic species used in the study for comparison.

Relationships between genome size and habitat have been proposed to exist in other groups of animals and in plants, either because groups with larger genomes have broader ecological tolerances (e.g. Bennett, 1976 and Hardie and Hebert, 2004) or because species with the largest genomes are excluded from harsh environments (Knight et al., 2005). One notable pattern is an apparent relationship between genome size and latitude and/or temperature, with species living in cold climates exhibiting large genomes and more frequent polyploidy (Gregory and Hebert, 1999)

Thus, although the broad interpretation offered by Vinogradov (2000) is problematic, the basic pattern he presents can serve as a useful starting point in investigating patterns of genome size diversity in molluscs, which can be expanded by adding genome size data for underrepresented taxa, incorporating phylogenetic comparisons, investigating patterns related to latitude and temperature, and including additional cases of aquatic/terrestrial shifts as well as examples of marine/freshwater habitat transitions.

81 Questions and Predictions

This study poses and attempts to answer several specific research questions:

1) Are genome sizes larger in terrestrial gastropods than in their aquatic relatives, as proposed by Vinogradov (2000)?

If Vingradov's (2000) predictions are correct and genomes are larger in molluscs that have invaded terrestrial habitats, then this pattern should hold when examined in the face of current phylogenetic information and across a larger number of species.

2) Is there a difference in genome size between marine versus freshwater gastropods and

bivalves?

If larger genome sizes in terrestrial species are associated with physiological and biological changes which allow these animals to have broader ecological tolerances as suggested by

Vinogradov (2000), then molluscs inhabiting more stable marine environments would be expected to have smaller genomes than species living in more variable freshwater habitats.

3) Is diversity in genome size in gastropods and bivalves associated with latitudinal ranges?

If higher latitudes are associated with variable climate and environmental fluctuations and genome size in gastropods and bivalves are influenced by biological adaptations to these climatic changes, then genome sizes within both groups will positively correlate with latitude.

82 Methods

Source of Specimens

In order to conduct large-scale comparisons between genome size and ecological correlates, the available mollusc data from the Animal Genome Size Database were supplemented with original samples collected in the course of this project. 283 individuals representing 44 species and 28 families were collected and analyzed in this study (Table 3.1).

These included mostly subarctic species sampled in July of 2009 from Churchill, Manitoba, and included marine, freshwater and terrestrial species.

The town of Churchill is situated on the shores of Hudson Bay in northern Manitoba (58°

46' 09" N; 094° 10' 09"W) and it stands at the juncture between the boreal forest to the south and the arctic tundra to the north. The landscape also includes freshwater lakes, many temporary tundra ponds, streams, a large river, fens, bogs, and an extensive marine shoreline.

Its unique ecotone and diverse ecoregions make Churchill an ideal location to simultaneously survey ecologically different species of molluscs. The current estimates for freshwater and terrestrial molluscs in this region range anywhere between 18 to 25 species (Clarke, 1973), while estimates for the species-rich oceanic gastropods and bivalves total around 42 species

(Rosenberg, 2009).

Several field sites were surveyed in Churchill, covering the three major bioregions: terrestrial, freshwater, and marine. These included fen and bog fields, burnt forest sites, and grassy tundra fields; lakes, temporary ponds, and rock pools; and intertidal, estuarine and subtidal zones, respectively. In most sampling sites, with the exception of estuarine and subtidal zones, all collections were primarily done by hand and with the aid of dip nets. In estuary and subtidal habitats, dredge runs pulled with the aid of motorized boats were conducted in order to

83 collect benthic species. A description of the habitat and GPS coordinates were recorded from every sampling location.

Collection protocol

All captured specimens were brought back to the research facility at the Churchill

Northern Studies Centre (CNSC) field station, where they were sorted and preserved for later analysis at the University of Guelph. In all possible cases, multiple individuals were collected for a single species; however, in the case of marine subtidal samples this was not always accomplished. In addition to GPS coordinates, all specimen records included a unique identification code, a date of collection, details on the collection protocol, and photographs.

For gastropods and bivalves which hide within their shells, animals were placed in dissolved menthol crystal solution anywhere between 2 and 12 hours, depending on the species. Once the animals appeared relaxed they were removed from the solution and preserved in nitrogen vapour cryoshippers.

Species identifications were performed in partnership with several experts in the field of molluscan taxonomy using morphological shell characteristics and photographs. Dr. Andre

Martel from the Canadian Museum of Nature in Ottawa, Ontario was responsible for the identification of all marine species collected in this study, while Dr. Eva Pip from the University of Winnipeg in Winnipeg, Manitoba identified all freshwater and most terrestrial gastropods. Dr.

Gerry Mackie, professor emeritus from the University of Guelph identified all freshwater bivalves and Robert G. Forsyth identified a few terrestrial gastropod species.

All specimens collected in this study were also DNA barcoded, in collaboration with the ongoing efforts by the Canadian Centre for DNA Barcoding (CCDB) to identify and barcode the flora and fauna from Churchill, Manitoba. The DNA sequences and specimen data can be

84 accessed in the Barcode of Life Data Systems (BOLD) [www.boldsystems.org] under the

Mollusca of Churchill [PPCHU] project. While the barcode data were available to the collaborating taxonomic experts and were congruent with the species identifications, the species names were assigned to the specimens on the basis of direct morphological examination. Further consideration of the barcode results is beyond the scope of the present study.

Genome Size Estimation

Genome size estimates were obtained via flow cytometry (FCM), which has previously shown to provide accurate DNA content estimates in molluscs (Dillon, 1989; Rodriguez-Juiz,

1999; and Bonnivard et al., 2009). FCM has the benefit of being rapid and cost efficient, allowing a large number of estimates to be obtained in a short amount of time. A description of the flow cytometry protocol used in this study is presented in Chapter 2 of this thesis. In brief, molluscan tissue samples were ground in LB01 buffer (pH 7.5) solution (15 mM Tris (hydroxymethyl)

aminomethane, 2 mM Na2EDTA, 0.5 mM spermine, 80 mM KCI, 20 mM NaCI, 15 mM meraptoethanol and 0.1% (v/v) Triton X-100) (Dolezel et al., 1989) to produce a suspension of isolated nuclei. A drop of rainbow trout (Oncorhynchus mykiss; 1C = 2.38 pg as calculated using

Feulgen Image Analysis Densitometry; Table 3.2) blood was used as the standard, and it was added to every sample before grinding.

Prepared molluscan samples were stained with propidium iodide (PI) and run on a Cell

Lab Quanta SC MPL flow cytometer by Beckman Coulter using a 488nm laser. Quality of the peaks was determined by coefficients of variation below 15%. In cases where the unknown and standard peaks overlapped samples were run using blood of domestic chicken (Gallus

85 domesticus; lC=1.25pg) instead. A minimum of 1,300 nuclei was counted and an average of three individuals was measured per species.

Compiled Data

In addition to original field sampling (283 samples comprising 44 species), this study counted on estimates compiled in the Animal Genome Size Database (AGSD) [available online at: www.genomesize.com]. In total, 217 species of molluscs, of which 88 were bivalves and 129 gastropods, from 28 different sources were included in this analysis. A detailed list of all estimates is provided in appendix 3.1. All values published in the database were included in this study without discriminating between tissue types and methods used.

In cases where a species' C-value was measured by more than one author, an average of all estimates was used. These instances served as comparison tools to evaluate the accuracy of genome sizes derived from different studies. Averages and standard errors are also presented in appendix 3.2 for all 19 duplicate cases while appendix 3.3 presents all cases of duplicates between the compiled and collected data.

Ecological Parameters

Both habitat shifts and latitudinal distributions were examined in this study with regards to DNA content. Most of the information was assembled from the literature and is presented in appendix 3.4. For the purpose of this analysis ecoregions were divided categorically into Marine,

Freshwater and, Terrestrial.

Gastropods are found in all three of the ecoregions examined. Gastropods which originate in the sea are thought to have successfully invaded freshwater and terrestrial habitats multiple times independently during their evolutionary history (Mordan and Wade, 2008).

86 By comparison, bivalves are all marine or freshwater, with no known terrestrial species.

Yet, similarly to the gastropods it is believed the ancestral bivalve form was native to the sea and has since invaded freshwater environments in more than one instance (Giribet, 2008).

Phyloginies assembled in the literature were used in this analysis to identify the major habitat shifts (details are given below).

In order to avoid possible confounding variation caused by differences in habitats, only marine species were chosen for the latitudinal distribution investigations performed in this study. Latitudinal ranges were defined according to ocean surface water temperatures. Figure

3.3 illustrates the surface temperature of the oceans in the beginning of 2011 according to the

National Oceanic and Atmospheric Administration (NOAA) fhttp://www.noaa.gov/]. Although ocean temperatures have changed in the last decades, these have not influenced the overall temperature patterns of warmer waters in the tropics and cooler waters at the poles. Therefore the map provides the guidelines for the categorical latitudinal distributions used in this study.

Latitudinal ranges were divided categorically into Tropical, Temperate and Polar. Species whose range spanned more than one category were assigned to all the categories representing their range. Information on the distribution of each species is given in appendix 3.4

o Tropical distribution - This includes all marine species found between 30°S and 20°N,

covering all of Central America, the Caribbean, and the Indo-Pacific islands; as well

as most of the coast of Mexico, South America, Africa and Australia.

o Temperate distribution - This range is divided into two separate segments, from

30°S to 50°S and from 20°N to 40°N. These ranges combined include northern

Mexico and all of the United States; the southern coast of Chile, Argentina, and

Uruguay; northern and southern Africa; southern Europe; and all of New Zealand

and Japan.

87 o Polar distribution - This range is also divided into two and includes all species found

between 50°S and 80°S and 40°N and 80°N. These latitudes cover the entire

Canadian coast; northern Asia and all the coast of Antarctica.

Species native to hydrothermal vents were not included in this analysis, because these habitats do not follow similar water temperature patterns observed in the surface of the sea, and animals tend to be uniquely adapted to life at these distinctive habitats.

Phyloaenetic trees

In order to account for the non-independence of phylogenetically related species, several phylogenies were assembled in this study, though it must be noted that the major molluscan phylogenetic relationship continue to be revised (Ponder and Lindberg, 2008).

The positions of the classes Bivalvia, Scaphophoda, Gastropoda, and Cephalopoda within the Mollusca are uncertain (Haszprunar et al, 2008). In addition, molecular techniques have just recently been implemented in an effort to clarify these relationships. In 2004,

Passamaneck et al. conducted an analysis of all extant classes with the exception of the

Monoplacophora by combining SSU (small subunit, 18S rRNA) and LSU (large subunit, 28S rRNA) sequences. Their study revealed many surprising relationships including the positioning of

Polyplacophora within the Bivalvia and Scaphophoda within the Cephalopoda. Since then, their findings have caused many molluscan systematics to question the capacity of molecular markers to identify deep relationships within molluscs (Haszprunar et al, 2008). More recently, Giribet et al. (2006) applied the first multi-gene analysis with representatives in all molluscan classes. Their results did not support the Scaphophoda-Cephalopoda clade, but it also did not clear up any further interrelationships of molluscan classes and neither Gastropoda nor Bivalvia were shown as monophyletic (Giribet et al, 2006). Therefore the most widely accepted hypothesis for the

88 relationship between all molluscan classes is still the classical view based on morphology where all classes are monophyletic.

The classification within bivalves and gastropods has also been debated for decades. In bivalves, due to the recent progress of systematics, a new stable classification based on the combined analysis of morphology and molecular data has been developed (Giribet, 2008). In this classification, bivalves are separated into 5 major groups, including the newly created

Opponobranchia. The four other major taxa are: Nuculanoida, Pteriomorphia,

Paleoheterodonta, and Heterodonta.

In gastropods, Bouchet et al. (2005) presented the most recent revised classification of the class. The authors combined previous Linnaean taxonomy and molecular work to recognized

611 families (Bouche et al., 2005). While this new classification makes use of unranked clades for all taxonomic organizations above superfamily, for the purpose of this study, the current classification was combined with taxonomy provided in the Integrated Taxonomic Information

System website [www.itis.gov] in order to assign orders and subclasses for the species examined.

For the habitat transition analysis presented here, several phylogenetic trees illustrating the most commonly accepted topologies for the relationships in gastropods and bivalves were assembled from the literature and drawn in Mesquite v2.72. A detailed description of the steps taken in the production of the trees is provided in Appendix 3.5. For the analysis of Vinogradov's

(2000) hypothesis, four phylogenies were constructed from diverse sources in order to include possible relationships currently accepted for Pulmonata in the literature, including strictly morphological and molecular trees (Figure 3.4-3.7). For all other habitat shift analyses, a single tree of each class was assembled representing the most accepted hypothesis on the evolution of the clade (Figure 3.8 and Figure 3.9)

89 Statistical analysis

Data for the analysis on the different habitat shifts in both bivalves and gastropods, did

not meet the assumptions of normality and therefore were examined with non-parametric tests

as preliminary indications of a relationship. Each habitat transitions investigated in this study -

freshwater to terrestrial environments in gastropods, marine to freshwater environments in

gastropods, and marine to freshwater environments in bivalves - were analysed individually

using the Mann-Whitney U test. A detail record of which tests were performed on each

comparison can be found on Appendix 3.6. These tests were subsequently complemented by

phylogenetic comparisons of the habitat shifts at the family level.

Moreover, genome size and latitudinal distributions between TROP, TEMP, and POLAR

marine species were assessed using the non-parametric Kruskal-Wallis test, since normality of

both gastropod and bivalve datasets could not be met (Appendix 3.6). Phylogenetic

relationships among gastropods and bivalves included in this study, at the species level have not

been determined, precluding analysis of phylogenetic non-independence of the data at the fine

scale. In order to control for phylogenetic influences on the data, the parameters were tested at

all taxonomic levels from species to order. Statistical analyses were carried out using Excel

(Microsoft Corporation, 2010), PASW Statistics 18 (SPSS, 2009) and Statgraphics Plus version 5.0

(Manugistics 1999).

90 Results

Overview of genome sizes in bivalves and gastropods

Bivalves

This combined dataset (Animal Genome Size Database; present study) included 101 species of bivalves belonging to 66 genera, 31 families, 10 orders, and 4 subclasses. The four subclasses examined were highly different from one another, with the Paleoheterodonta (1C=

3.40 pg ± 0.30SE, n=3) and the Opponobranchia (1C=3.44 pg ± 0.70SE, n=4) appearing significantly larger than the Heterodonta (1C= 1.89 pg ± 0.12SE, n=46) and the Pteriomorpha

(1C=1.59 pg ± 0.07SE, n=48) (Figure 3.10).

Ranges in genome sizes within the subclasses also varied, but were relatively small, compared to other animals, such as some crusteceans (Gregory, 2011). The largest range was observed in the Heterodonta, at approximately 7-fold from 0.70 pg to 4.91 pg, and the smallest in the Paleoheterodonta with only 1.33-fold from 3.00 pg to 3.99 pg. The range of the

Pteriomorpha genome sizes was close to 5-fold, from 0.69 pg to 3.40 pg, while the

Opponobranchia varied about 3-fold from 2.10 pg to 5.40 pg (Figure 3.11).

Gastropods

A total of 158 species included in 87 genera, 46 families, 12 orders and 4 subclasses were examined in this analysis based on the Animal Genome Size Database and original estimates. All collected species examined in this study produced consistent genome sizes across individuals, with the exception of Promenetus exacuous, a member of the family Planorbidae, which showed two distinct DNA contents derived from two different populations. The genome

91 size in population 1, collected in the weir on the Churchill River, was approximately half the size of population 2, collected from the shores of Landing Lake (1C = 0.49 pg ± 0.01SE, n=3; and 1C =

1.01 pg ± 0.04SE, n=3, respectively). It also appeas other taxa within Gastropoda have experienced quantum jumps in genome size between cogenerics, in some cases representing a triple increase in genome size between closely related species (Appendix 3.7).

Differences in mean genome sizes were observed between the subclasses of gastropods

included in this study, with the Caenogastropoda (1C = 2.94 pg ± 0.18SE, n=88) being significantly larger than the Heterobranchia (1C = 1.84 pg ± 0.14SE, n= 45), the

Patellogastropoda (1C = 0.61 pg ± 0.05SE, n=8), and the Vestigastropoda (1C = 1.69 pg ± 0.26SE,

n=17) (Figure 3.12).

Ranges of genome sizes were fairly consistent among the four subclasses studied, with the exception of the Patellogastropoda, which was much more constrained than the other groups. The Patellogastropoda ranged from 0.43 pg to 0.94 pg, whereas the Caenogastropods varied from 0.61 pg to 7.85 pg, followed by the Vestigastropoda with a range between 0.50 pg and 5.32 pg, and the Heterobranchia with a range between 0.49 pg and 4.40 pg (Figure 3.13).

Genome size and shifts into terrestrial habitats in gastropods

Initial analyses of the data revealed a significant difference in genome sizes between the terrestrial species and their aquatic counterparts (Mann-Whitney U test, p<0.005). Indeed, terrestrial species were found to have larger genomes than their freshwater relatives within pulmonates (1C=2.47 pg ± 0.27SE, n=14 and 1C=1.57 pg ± 0.18SE, n=20, respectively). However, these results did not seem to hold when patterns were considered in a phylogenetic context. In

92 total, four phylogenetic trees on the possible relationships currently accepted within pulmonates were assembled for this study and are presented in figures 3.4-3.7.

Foremost in the trees derived from Salvin-Plawen and Steiner (1996) (Figure 3.4),

Klussamann-Kolb et al. (2008) (Figure 3.6) and Holznagel et al. (2010) (Figure 3.7), the terrestrial lineage, Stylommatophra, does not form a sister relationship to the freshwater clade,

Basommatophora, as previously anticipated.

In the phylogeny constructed from Dayrat and Tillier (2002) (Figure 3.5),

Stylommatophora is a sister group to a clade which includes the freshwater species examined.

However this tree does not allude to the idea of terrestrial species transitioned from freshwater habitats. In fact, the freshwater groups included on this and on the original study by Vinogradov

(2000) are more closely related to marine families, than to the terrestrial clade (Figure 3.4-3.7)

Furthermore, an examination of the mean genome size of each pulmonate family indicates that DNA content is not consistently larger in terrestrial groups and in fact only three of the seven terrestrial families examined have genomes larger than 2.00 pg. All other terrestrial pulmonate families possessed estimates ranging from 1.52 pg to 1.78 pg, while freshwater pulmonate families ranged from 1.26 pg to 1.74 pg (Figures 3.4-3.7).

The terrestrial family Diplommatinidae (1C= 4.62 pg ± 0.35SE, n=22) provided an additional example outside of pulmonates for examining the relationship between genome size and movement onto land in gastropods. This family is part of a clade of purely terrestrial species within Caenogastropoda. Based on the phylogeny presented in figure 3.8, the Diplommatinidae clade represents an outgroup to all other members in this subclass and is not shown to possess the largest genome (Figure 3.8). In fact, DNA content of the family Thiaridae was much larger

(lC = 6.65pg,n=l).

93 Genome size and freshwater habitat shifts in gastropods

The non -parametric Mann-Whitney U test did not reveal a significant difference in genome sizes between freshwater and marine gastropods (p=0.27). The mean genome size of the freshwater species (IC = 1.98 pg ± 0.21SE, n=58) was in fact slightly smaller than that of the marine species (1C= 2.19 pg ± 0.14SE, n=85).

By examinig the genome size estimates of all families on the phylogeny, it was possible detect four cases worthy of detailed examination. These encompass all instances where data are available following a transition from marine to freshwater habitats (Figure 3.8).

• Case 1 - Thiaridae (IC = 6.65 pg, n=l). This freshwater family forms a sister relationship with

a large clade that includes both other freshwater and marine species. Its genome size is

larger than all marine species in the sister clade.

• Case 2 - Viviparidae (IC = 2.46 pg ± 0.44SE, n=5). This family, like Thiaridae, forms a sister

branch with a large clade which includes both marine and freshwater families. In this

particular case, the mean genome size of Viviparidae is smaller than that of several marine

relatives: Muricidae (1C=2.58 pg ± 0.08SE, n=ll), Conidae (1C= 3.58 pg ± 0.21SE, n=6),

Buccinidae (1C=4.66 pg ± 0.64SE, n=3) and Cancellariidae (1C=5.73 pg, n=l).

• Case 3- Hydrobiidae (1C= 0.68 pg, n=l) and Bithyniidae (1C= 1.25 pg, n=l) cluster. According

to the phylogenetic tree, the transition into freshwater appears to be associated to at least a

cluster containing Pomatiopsidae, Ammicolidae, Hydrobiidae, and Bithyniidae, of which

estimates are known for the last two families. Due to the absence of genome size data on

the sister branch to this group, analysis were performed on the next closest relatives, a

clade containing Anabathridae, Provannidae (1C= 0.92 pg, n=l), and Littorinidae (IC = 1.08

pg ± 0.1SE, n=9). The mean DNA content for freshwater family Hydrobiidae is smaller than

94 both marine values, whereas the estimate for Bithyniidae is slightly larger, but not

significantly so (Wilcoxon Signed Ranks, p=0.30).

• Case 4 - Valvatidae (1C= 1.50 pg, n=l). This freshwater family was compared to the closest

relatives available including Tergipedidae (1C = 0.91 pg, n=l), Flabellinidae (1C= 0.71 pg,

n=l), Dorididae (1C= 1.66 pg ± 0.34SE, n=2), Aminidae (1C= 1.00 pg, n=l), Aeolidiidae (1C=

1.20 pg, n=l), Limapontiidae (1C= 2.83 pg, n=l), Aplysidae (1C= 1.90 pg ± 0, n=2) and'

Bullidae (1C= 1.60 pg, n=l). Although none of them represent a sister taxa to Valvitidae,

they are members of the clade sister to the Valvatidae clade.

Thus, in 3 of the 4 cases examined, smaller DNA contents were found in freshwater families as compared to marine relatives.

Genome size and freshwater habitat shifts in bivalves

Genome sizes were significantly different between freshwater and marine species of bivalves (Mann-Whitney U test, p<0.001). The mean C-value among freshwater species was 3.71 pg ±0.25SE, n=8; while the mean among marine ones was 1.74 pg ± 0.07SE, n=113.

A careful look at the phylogeny indicated that all shifts into freshwater habitats in bivalves occur within a clade containing the Palaeoheterodonta and the Heterodonta (Figure 3.9). A

Kruskal-Wallis test including only the members of those clades still revealed a significant difference in genome size between freshwater and marine species (p<0.001). Furthermore, the phylogeny underlined 4 cases of transitions into freshwater habitats, which are described in detail below (Figure 3.9):

• Case 1 - Unionidae (1C=3.40 pg ± 0.3SE, n=3). This family is part of the small subclass

Palaeoheterodonta and, together with five other freshwater families, forms a clade sister to

Trigoniidae. This larger clade is sister to all of Heterodonta (Figure 3.9). The mean genome

95 size of Unionidae is substantially larger than most marine families studied within the

Heterodonta clade, with the only exception being Astartidae (4.42 pg).

• Case 2- Dreissenidae (1C= 1.74 pg, n=l). This freshwater taxon is sister to Corbulidae and

close relative to Myidae (1C=1.55 pg ± 0.11SE, n=3), Mactridae (1C=1.24 pg ± 0.18SE, n=5)

and Pholadidae (1C=0.70 pg, n=l), all possessing smaller DNA contents than Dreissenidae.

• Case 3 - Sphaeriidae (1C=4.05 pg ± 0.54SE, n=3). Sphaeriidae is sister to a large clade that

includes another freshwater family (Corbiculidae) as well as several marine taxa:

Vesicomyidae (1C=2.35 pg, n=l), Veneridae (1C=1.76 pg ± 0.12SE, n=8) and Petricolidae

(1C=1.10 pg, n=l). Yet, no other taxa studied have shown genome sizes larger than

Sphaeriidae.

• Case 4 - Corbiculidae (1C=1.93 pg, n=l). Similarly to Sphaeriidae, this family forms a sister

clade to Veneridae (1.76 pg) and Petricolidae (1.10 pg) and is still larger than both taxa.

Thus, freshwater taxa displayed consistently larger genomes in 3 of the 4 cases examined, with the only exception belonging to the unionids, which are known to have a parasitic larval stage.

Genome size and thermal regimes in marine gastropods and bivalves

A strong positive relationship was identified between genome size and latitudinal ranges in gastropods (Kruskal-Wallis, p<0.004) (Figure 3.14). The relationship persisted at the specific and generic levels (all p< 0.05), but not at the familial and ordinal level (p>0.10). Marine gastropod species living in polar regions had larger genomes (1C= 2.85pg ±0.28, n=26) than temperate (lC=1.84pg ± 0.16, n=39) and tropical species (1C= 1.60pg ± 0.20, n=22). On the other hand, genome sizes in marine bivalves were not significantly related latitude in any of the taxonomic scales examined (Kruskal-Wallis, p=0.30) (Figure 3.15).

96 Discussion

The goals of the present study were to investigate general patterns in genome size diversity among bivalves and gastropods and especially to address specific questions regarding possible links between ecological parameters and genome size in these molluscs.

Genome size and shifts into terrestrial habitats in gastropods

Although initially it may have appeared that larger genome sizes were associated with shifts into terrestrial environments among gastropods (Vinogradov, 2000), the more detailed analyses conducted here have thrown considerable doubt on this proposed relationship. In particular, genome size estimates for several terrestrial pulmonate families were not found to be significantly larger compared to their freshwater relatives. Moreover, the freshwater

Basommatophora and the terrestrial Stylommatophora are not sister taxa, and there is no evidence to indicate that the latter has actually stemmed from the former. Rather, movement onto land more likely occurred within an ancestral marine lineage (Salvini-Plawen and Steiner,

1996; Dayrat and Tillier, 2002; Holznagel et al., 2002; Klussamann-Kolb et al., 2008 and Ponder et al., 2008), making the comparison between freshwater and terrestrial groups irrelevant.

Therefore, marine lineages should be the main consideration in the future as they may represent the ancestral lineage to both terrestrial and freshwater groups.

Genome size and habitat shifts into freshwater in gastropods

Based on the present results, genome sizes were not significantly larger in gastropods adapted to life in freshwater habitats than their marine counterparts. These findings differ from previous patterns observed in fishes, in which freshwater/anadromous fishes had larger

97 genomes than marine/catadromous fishes (Hardie and Hebert, 2004), which are consistent with

previous evidence supporting the idea that larger-genome organisms have broader ecological

tolerances (Bennett, 1976; Beaton and Hebert, 1988).

In gastropods, multiple shifts into a freshwater lifestyle have occurred in their

evolutionary history. Yet these shifts do not seem to be directly accompanied by changes in DNA

content. It is likely other ecological parameters which influence development, morphology and

metabolism in this group, instead of habitat, are more prevalent in shaping variation in genome

size - however, these parameters remain to be investigated in future work.

Genome size and freshwater habitat shifts in bivalves

Freshwater bivalves were found to possess significantly larger genome sizes than marine

ones. Although the relationship could not be investigated phylogenetically to a comprehensive

degree (including all suspected sister clades of independent transitions to freshwater), a

comparison between closely related families revealed larger genome sizes associated with freshwater taxa in 3 of the 4 phylogenetically independent comparisons, the only exception

belonging to Unionidae. This group was compared to a large clade containing several marine families, including Astartidae, the sole marine taxa to possess a genome larger than that of

unionids.

Nevertheless, it is possible that the relationship observed in this study between DNA

content and habitat is related to (ancient) polyploidy in the freshwater species analysed. In fact

several examples of polyploids have been suggested in molluscs living in freshwater (Burch,

1960; Burch and Huber, 1966; and Burch and Jung, 1993). In particular, the family Sphaeriidae

represents one of the most abundant naturally occurring polyploidy groups within bivalves

(Gregory, 2005b; Jara-Seguel et al., 2010).

98 In fishes, it is believed that polyploid species tend to better persist and succeed in variable freshwater environments (Ebeling et al., 1971; Hardie and Hebert, 2004). In addition some authors argue that polyploids can actually arise more frequently in these habitats (Hardie and Hebert, 2004). Unlike marine environments, freshwater habitats have a tendency of being highly segregated, providing many barriers to gene flow and enhancing the opportunity for population isolation, both factors that may promote the creation of polyploids when populations come back into contact (Otto and Whitton, 2000). These impacts could influence

DNA content in molluscs as well as in fishes.

In any event, polyploidy cannot be the sole contributor to the genome size pattern observed, since polyploids have also been well documented among marine taxa including several species examined here (Eudeline et al., 2000; Beaumont and Fairbrother, 1991), and none of these groups exhibited larger-than-average genomes. A look at biological features characteristic of freshwater bivalves, such as length of development and parental care, would be a wise progression in unrevealingthe nature of this relationship.

Genome size versus thermal regimes in gastropods and bivalves

The relationship between genome size and thermal regimes has been identified in several taxonomic groups (Bennett, 1976; Grime and Mowforth, 1982, Beaton and Hebert,

1988; Bottini et al., 2000; and Hardie and Hebert, 2004). It involves a dine in DNA content associated with both latitude and altitude, with species inhabiting northern or high altitude climates exhibiting larger genomes and more frequent polyploidy than southern or low altitude ones (Gregory and Hebert, 1999). In gastropods, polar taxa exhibited larger mean genome sizes

99 than their tropical and temperate counterparts, whereas in bivalves no significant relationships were observed between genome size and any latitudinal range.

Although total DNA content was larger in polar regions for gastropods, that is not to say all species in the north had large genomes while all species living close to the equator had small ones, instead, this only means the average DNA content of the two groups were significantly different. It is important to make such a distinction because one explanation for the observed pattern appears to be related to the fact species with larger genomes have broader ecological tolerances (Hardie and Hebert, 2004). This does not imply that small genome species are unable to survive in the north, simply that larger genome taxa are likely to be more common in those environments.

Larval development may also play an important role in explaining the relationship identified in this analysis. A direct correlation between latitude and the presence of pelagic larvae has been widely suggested among marine subtidal invertebrates, in particular within molluscs (Thorson, 1936 - revised in Mileikovsky, 1971; Mileikovsky, 1971 and 1975; Rohde,

1985; Gallardo and Penchaszadeh, 2000). This could explain why a significant correlation was observed within gastropods that can undergo a diversity of developmental strategies, including direct and indirect development (Aktipis et al., 2008), but not within bivalves, which most oftenly develop via pelagic larvae (Giribet, 2008).

Thorson's rule, developed in 1936 on work done on Littorina snails, states that the prevalence of species developing via pelagic larvae decreases from the equator towards the poles and from shallow waters to great oceanic depths (Thorson, 1936; revised by Milekovsky,

1971). Since its development, Thorson's rule has been highly debated (Clark and Goetzfried,

1978; and Pearse et al., 1991). However, it is possible that genome size correlates with indirect versus direct development, and thus to latitude in gastropods. Pelagic larvae need to develop,

100 grow, and settle quickly to avoid predation and succeed in competing for resources (Duda and

Palumbi, 1999), therefore it would not be surprising if species with pelagic larval development had small genomes compared to species where youngs are cared for by the parents.

Investigations on the relationship between genome size and development in molluscs should comprise a next step in molluscan genomic research.

Questions and Answers Revisited

Based on the results presented in this study, it is possible to provide answers to the research questions posed at the outset.

1) Are genome sizes larger in terrestrial gastropods than in their aquatic relatives, as

proposed by Vinogradov (2000)?

Genome size does not appear to correlate with shifts from aquatic to terrestrial habitats,

contrary to Vinogradov's (2000) claim. However, until a direct comparison can be made

between a terrestrial lineage and its sister marine taxa, this relationship will remain

inconclusive. That said, the small genomes observed among many terrestrial families make

it unlikely that such a comparison will reveal strong patterns either.

2) Is there a difference in genome size in marine versus freshwater gastropods and bivalves?

No significant relationship was found between genome size and marine and freshwater

environments in gastropods. Although in fishes, freshwater species were found to have

larger genomes than marine ones (Hardie and Hebert, 2004), gastropods do not appear to

follow a similar pattern. Due to their great diversity in morphology, behaviour, physiology,

and ecology, it is likely no simple answer is going to be able to fully explain the patterns of

genome size variation in gastropods.

101 In bivalves, on the other hand, DNA content was significantly larger in freshwater species as

compared to marine ones. In addition, of the four cases of phylogenetic shifts examined in

this group, three showed enlargements in genome size associated to freshwater habitats.

The reason behind this relationship remains unknown, but polyploidy could be a significant

factor.

3) Is diversity in genome size in gastropods and bivalves associated with latitudinal ranges?

Genome size was significantly larger for polar taxa at the specific and generic in marine

gastropods, but not in bivalves. Large genome species have been suggested to possess

broader ecological tolerances, which may clarify why such species persist in the north, but

not why they have evolved larger genomes in the first place. Larval development may be the

missing link in this explanation however, further research is needed.

Future Directions

The present study was the first to examine the influence of multiple levels of ecological parameters on genome size in both gastropods and bivalves. Besides addressing existing questions, it has opened numerous new questions on genome size variation in molluscs. In addition to much-needed expansions of the overall dataset (including in the major molluscan groups that have never been studied), several specific areas and taxa worth investigating are described below:

1) In order to continue investigating the relationship between genome and habitat

transitions in bivalves, several families need to be added to the dataset, including

Trigoniidae,' Corbulidae, Arcticidae, Etheriidae, Mutelidae, Margaritiferidae,

Mycetopodidae, and Hyriidae. These are all the other freshwater families belonging to

the Paleoheterodonta as well as the closest marine relatives to the freshwater clades. In

102 addition, better coverage of all the families already present in the analysis is also

necessary.

2) Developmental strategies are quite varied in molluscs, yet it appears these parameters

may influence several levels of relationships within this group. A thorough investigation

between genome size and developmental parameters, including larval type and

developmental rate, is likely to reveal many interesting relationships in molluscs. For

example, the parasitic larval stage experienced by freshwater mussels may directly

influence developmental rate in these animals, which could explain why they exhibit

larger than average genome sizes.

3) Given that genome size appears to correlate with latitudinal ranges in gastropods, the

obvious next step is to expand this analysis to include additional latitudinal gradient

sampling, and to examine species at different altitude ranges and depths.

4) It would also be interesting to investigate the real habitat transition from marine to

terrestrial environments in gastropods, as this represents the real evolutionary shift and

could help clarify the prediction that genome sizes have increased following the

establishment on land, as stated by Vinogradov (2000).

In brief, the results presented in this study, highlighting some of the general patterns in genome size diversity in molluscs, will serve as the foundation for new research in this group. Molluscs in general, and gastropods and bivalves in particular, need to receive more attention in terms of genome size research. Undoubtedly, ecological parameters play a role in genome size evolution in gastropods and bivalves, but little is known on the effects of organismal level parameters, such as development, metabolism, and morphology.

Therefore many patterns are still available to be pursed in this exciting field of biology.

103 Gastropods Bivalves 11

Insects

Birds ! •

Figure 3.1. Pie diagram illustrating the relative number of publications found on ISI Web of

Knowledge database for the terms "Mammals", "Birds", "Insects", "Gastropods" and "Bivalves" in combination with "Genome".

104 Polyplacophora ^. ^^ (7/1,000)

Gastropoda

Cephalopoda $> #• •• #• (5/850)

0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 ' Genome size (pg)

Figure 3.2. Graphic illustration of genome size distribution among the four (of seven) best-

studied classes of molluscs available at the Animal Genome Size Database. Monoplacophora,

Aplacophora, and Scaphophoda have not been examined to date and no estimates are available.

Darker shades within the distribution indicate ranges where estimates are most abundant. The

number of genome size estimates as well as total number of recognized species per taxon are given at the end of each distribution.

105 NOAA/NESDIS SST 50KM GLOBAL ANALYSIS

•180-160-140-120-100 -80 -60 -40 -ZO 0 ZO 40 60 BO 100 1Z0 140 160 NOAX-19 OPERATION OAY/NITE 2/19/2011 through 2/22/2011 SST in degrees C (ice is white, brown is unreliable)

•1.7 2.5 6.7 10.9 IS.1 19.4 23.8 27.B 32.0

Figure 3.3. Map of the oceanic water temperature of the world in February of 2011, used as a template to map latitudinal distribution of gastropods and bivalves. Water temperatures between 23.6 and 32 degrees were considered tropical, whereas temperature between 15.1 and 23.6 degrees were temperate and 2.5 and 15 degrees were considered polar.

106 Pyramidulidae Orculidae Strophocheilidae Spelaeodiscidae Strobilupsidae Urocoptidae Cerastidae Argnidae Vertiginidae (1.52pg; n=l) Trochomorphidae Gastrodontidae Ariophantidae Urocyclidae Ariolimacidae Helicanonidae Dyakiidae Euconulidae (1.79pg; n=l) Boettgerillidae r Limacidae Agriolimacidae (1.78pg; n=2) Bradybaenidae Helmmthoglyptidae Camaenidae Polygyridae Sagdidae Chonchlicellidae Humboldttianidae Monadeniidae Hygromiidae (2.49pg; n=l) Halolimnohelicidae Cepolidae Sphincterochilidae Pleurodontidae Thysanophoridae Helicondontidae Trissexodontidae Xanthonychidae Epiphragmophoridae Helicidae (3.54pg; n=5) Ferussaciidae Subulinidae Achatinidae (2.25pg; n=l) Streptaxidae Micractaeonidae Succinidae (178pg; n=3) Athoracophoridae Coeliaxdae Glessulidae Otinidae Trimusculidae Smeagolidae Ellobiidae Veronicellidae Rathouisidae Onchidiidae Chilinidae Latiidae Acroloxidae Lymnaeidae (1.74pg; n=12) Physidae (1.26pg; n=3) Planorbidae (1.36; n=7) Amphibolidae Siphonariidae Opistobranchia Figure 3.4. Pulmonata tree containing all Basommatophora and Stylommatophora families used in the analysis of genome size and terrestrial habitat shift in gastropods. The phylogenetic relationship was based on a maximum parsimony phylogeny derived from Salvini-Plawen and

Steiner (1996) based on morphological characters. Green branches represent terrestrial families, while blue indicates freshwater groups and yellow are marine.

108 Pyramidulidae Orculidae Strophocheilidae " Spelaeodiscidae - Strobilupsidae Urocoptidae Cerastidae Argnidae - Vertiginidae (1.52pg; n=l) • * Trochomorphidae - Gastrodontidae I-" ' Ariophantidae Urocyclidae - Ariolimacidae * Helicarionidae Dyakiidae L - Euconulidae (1.79pg; n=l) - Boettgerillidae Limacidae "- Agrioiimacidae (1.78pg; n=2) Bradybaenidae - Helminthoglyptidae Camaenidae Polygyndae - Sagdidae — Chonchlicellidae — Humboldttianidae Monadeniidae — Hygromitdae (2.49pg; n=l) — Haloiimnohelicidae — Cepolidae — Sphincterochilidae — Pleurodontidae — Thysanophoridae — Heiicondontidae — Trissexodontidae — • Xanthonychidae ~- Epiphragmophoridae — Helicidae (3.54pg; n=5) Ferussaciidae - Subulinidae Achatinidae (2.25pg; n-1) jU>. - Streptaxidae Micractaeonidae Succinidae (1.78pg; n=3) Athoracophoridae L. »- Coeliaxdae Glessulidae Smeagolidae Otinidae Latiidae Ellobiidae Amphibolidae Chiiinidae Lymnaeidae (1.74pg; n=12) Physidae (1.26pg; n=3) Planorbidae (1.36; n=7) Acroloxidae Siphonariidae Opistobranchia Figure 3.5. Pulmonata tree containing all Basommatophora and Stylommatophora families used in the analysis of genome size and terrestrial habitat shifts in gastropods. The tree was assembled from the phylogenetic hypothesis proposed by Dayrat and Tillier (2002) based on cladistic evaluation of 77 morphological characters. Green branches represent terrestrial families, while blue indicates freshwater groups and yellow are marine.

110 Pyramidulidae * Orculidae Strophocheilidae - Spelaeodiscidae » Strobilupsidae f * Urocoptidae »-. - Cerastidae Argnidae L - Vertiginidae (1.52pg; n=l) - Trochomorphidae §,,„ - Gastrodontidae > Ariophantidae * Urocyclidae - Ariolimacidae • Helicarionidae Dyakiidae • Euconulidae (1.79pg; n=l) » Boettgerillidae Limacidae Agriolimacidae (1.78pg; n=2) • Bradybaenidae - Helminthoglyptidae • Camaenidae - Polygyridae - Sagdidae - Chonchlicellidae - Humboidttianidae ~ Monadeniidae - Hygromiidae (2.49pg; n=l) - Halolimnohelicidae - Cepolidae - Sphincterochiiidae «• Pleurodontidae - Thysanophondae - Helicondontidae - Trissexodontidae ~> Xanthonychidae - Epiphragmophoridae - Helicidae (3.54pg; n=5) - Ferussaciidae •» Subulinidae -- Achatinidae (2.25pg; n=l) -< Streptaxidae - Micractaeonidae - Succinidae (1.78pg; n=3) - Athoracophoridae - Coeliaxdae - Glessulidae Otinidae Trimusculidae Smeagolidae •» Ellobiidae Veronicellidae r~" - Rathouisidae Onchidiidae Amphibolidae Chilinidae Latiidae Acroloxidae Lymnaeidae (1.74pg; n=12) Physidae (1.26pg; n=3) Planorbidae (1.36; n=7) Siphonariidae Opistobranchia Figure 3.6. Pulmonata tree containing all Basommatophora and Stylommatophora families used in the analysis of genome size and terrestrial habitat shifts in gastropods. The tree was assembled from the phylogenetic hypothesis proposed by Klussanam-Kolb et al. (2008), based on a Bayesian phylogram of 18SrRNA, 28S rRNA, 16S rRNA and COI DNA. Green branches represent terrestrial families, while blue indicates freshwater groups and yellow are marine.

112 ,» ~ Pyramidulidae r Orculidae j~——- Strophocheihdae - Spelaeodiscidae f Strobilupsidae f - Urocoptidae \ Cerastidae ,' Argnidae ^ Vertiginidae (1.52pg; n=l) r Trochomorphidae J* Gastrodontidae |«._ Ariophantidae k~-~ Urocyclidae f—•- Ariolimacidae j"-—~ Helicarionidae f ~ Dyakiidae Euconulidae (1.79pg; n=l) ~-«.- Boettgerillidae

: Limacidae * Agriolimacidae (1.78pg; n=2) |—-- Bradybaenidae j- ••-" Helminthoglyptidae ** Camaenidae t Polygyridae st~— Sagdidae §•-- Chonchlicellidae -~ Humboldttianidae t-*- Monadeniidae f——~~ Hygromiidae (2.49pg; n=l) ~~-~ - Halolimnohelicidae ff '- Cepolidae I™ - Sphincterochilidae Pieurodontidae i |—~-~ Thysanophoridae f—•'" Helicondontidae j- Trissexodontidae f-~~—• Xanthonychidae Epiphragmophoridae Hehcidae (3.54pg; n=5) ... Ferussaciidae Subulinidae L ™_ Achatinidae (2.25pg; n=l) I - Streptaxidae ' Micractaeonidae f — — Succinidae (1.78pg; n=3) r — Athoracophoridae f Coeliaxdae ' Glessulidae •—-- Ellobiidae Trimusculidae Otinidae Smeagolidae Onchidiidae r——- Rathouisidae w~ Veronicellidae Siphonariidae Acroloxidae Chilinidae Latiidae Physidae (1.26pg; n=3) Lymnaeidae (1.74pg; n=12) Planorbidae (1.36; n=7) Opistobranchia Amphibolidae Figure 3.7. Pulmonata tree containing all Basommatophora and Stylommatophora families used in the analysis of genome size and terrestrial habitat shifts in gastropods. The relationships were based on a 28S rRNA gene sequence, Bayesian 50% majority tree proposed Holznagel et al.

(2010). Green branches represent terrestrial families, while blue indicates freshwater groups and yellow are marine.

114 Cocculinidae Pettospindae Cyatherrmidae Neomphalidae Acmaeidae (0 65pg, n=5) Lottidae(065pg, n=6) Lepetidae Patellidae Neoleptopsidae Naceliidae Pteurotomanidae Stomatelhdae Lepetodnlidae (1 30pg, n=3) Scissurellidae HaliotKtae (1 86pg, n=6) Fissurellidae (1 14pg, n=4) Anatomidae Clypeosectidae Troohidae (1 60pg, n=3) Turbinidae (2 50pg, n=4) Titiscaniidae §** Nerrtopsidae Phenacolepadidae Nentidae **"" Hydrocenidae l*"" Praserpmidae Is** Proserpmellidae | Nentfllidae 3"s Helicinidae **"* Diptommatmidae(469pg, n=23) y»" Cyclophondae J88" Aciculidae jTs^^^^^^^^^s^s^wssss^wsfisa^^-^^ Craspedopomatidae | J®* Marzatmdae I ¥** Megatomastomatidae <08» Neocyclotidae am® Pupinidae Campanitidae Centhmidae

Lrtiopidae Pleurocendae (2 10pg, n=16) Ampullanidae (0 64pg, n=1) Scaliohdae Potamididae Modulidae Symolopsidae Melanopsidae Batillanidae Paludomidae Pachychilidae Tumtellidae Thiandae (6 65pg, n=1) Vivipandae (2 46pg, n=5)

Hipponiadae Cypraeidae(1 60pg, n=1) OvulKJae bttonnidae (1 10pg, n=12) Provamidae (0 92pg, n=2) Ammicolidae Hydrobiidae (0 68pg, n=1) Brthyniidae (1 25pg, n=1) [f Pomatiopsidae Strombidae Xenophondae Tnchotropidae Capulidae Calyptraeidae Cassidae Velutinidae Tnviidae Terebndae

Munodae (2 60pg, n=13) Melogenidae Buccmidae (4 66pg, n=3) Conidae (3 58pg, n=6) Cimidae Aclididae I Valvatidae(1 SOpg n=1)

Pyramidellidae 1 Glacidorboidea Amphibotoidea Tergipedidae (0 91 pg, n=1) Flabellmidae (0 71pg, n=1) Dondidae (1 66pg, n=2) Armmidae (1 OOpg, n=1) Aeolidndae (1 20pg, n=1) Pleurobranchidae Acteonidae Limapontiidae (2 83pg, n=1) Tylodinoidea Aplysiidae (1 90pg, n=3) Bullidae (1 60pg, n=1) I Pulmonata Solemyidae (2 10pg, n=1) Manzanellidae Pnstiglomidae Nucuhdae (3 89pg, n=3) Nuculanidae Malletiidae Lametilidae Yoldndae Sareptidae Tindanidae Siliculidae Bathyspinuhdae Neilonellidae Mytilidae (1 79pg, n=32) Aradae (1 56pg, n=4) Parallelodontidae Philobryidae Noetudae (1 90pg, n=1) Limopsidae Cucullaeidae Glycymendidae Limidae (1 40pg, n=2) Anomndae Pectinidae (1 35pg, n=11) Spondyndae Dimyidae Placunidae Syncyclonemidae Propeamussndae Entolndae Gryphaeidae Isognomonidae Pulvinrbdae Ramonalinidae Malleidae Pinidae (1 10pg, n=1) Ostreidae (1 02pg, n=7) Ptenidae •• Unionidae (3 40pg, n=3) f— Margantrfendae pi Mycetopodidae f— Hynidae J— Mutelidae ••• Ethenidae Tngonudae Astartidae (4 42pg, n=1) Carditiidae Crassatellidae Thyasmdae (2 27pg, n?1) Anomalodesmata Hiatellidae (1 69pg, n=1) Lasalidae Luamdae (1 70pg, n=1) Galeommatidae Teredimdae Gastrochaenidae Semelidae Chamidae (1 50pg, n=1) Cardndae (1 52pg, n=4) Tndacnidae Psammobiidae (1 67pg, n=l) Donacidae (1 60pg, n=1) Solecurtidae (1 30pg, n=1) Tellenidae (2 12pg, n=7) Phanidae (1 50pg, n=1) Solenidae (1 70pg, n=1) Pholalidae (1 15pg, n=2) Mactndae (1 24pg, n=5) Myidae (1 55pg, n=4) Corbulidae •MB Dreissenidae (1 74, n=1) ••• Sphamdae (4 05pg, n=3) Vesicomyidae (2 35pg, n=1) •MM Corbiculidae (1 93pg, n=1) Arcticidae Venendae (1 76pg, n=8) Petncolidae (1 10pg, n=1)

116 Figure 3.9. Representative bivalve tree containing many families for which phylogenetic relationships are known and including all cases for which genome sizes have been measured.

Yellow branches represent marine while blue represent freshwater families. Tree was assembled from several sources from the literature; references are available in appendix 3.5.

117 * *

o o 48 46

T

Hetei odonta Palaeoheterodonta Opponobranchia Pteiiomorpha

Figure 3.10. Distribution in genome size diversity among 101 species of bivalves divided into 4 subclasses. Palaeoheterodonta and Opponobranchia were significantly different from

Heterodonta and Pteriomorpha. o - represents samples that are within three "box lengths" from the upper quartile value *- represents samples that are further than three "box lengths" from the upper quartile value

118 b) 25 a) 25

2 2 •

1.5 • 1.5 -

1 • | | 'Vs, ; 05 05 • i

0 - n • L..J •*"***** M *J '(J 0) Ul UT Ul a.

. 0) c) IS d) 20 16 • E 14 3 IS 12 10 • 10 • r— 8 • 6 • 5 • 4 - i 2 0 • o J . ..— :-•.» UJ UJ t-* h-* M M U) UJ in UJ i/i *-• m NJ m UJ '-'i W Ul UJ UT Ul Ul in w ui UJ in J> Ul Ul

Genome size range (pg)

Figure 3.11. Distribution of genome sizes of among bivalves represented by the four subclasses, a) Palaeoheterodonta (3 species); b) Opponobranchia (4 species); c) Heterodonta (46 species); and d) Pteriomorphia (42 species).

119 88

6.00-

a. 41 _N 45 'vt o o | 4.00- c C O

17 2.00" I

.00" Caenogastropoda Heterodonta Patellogastropoela /estigastropoda

Figure 3.12. Distribution in genome size diversity among 158 species separated into 4 subclasses of Gastropoda. Caenogastropoda was significantly different from Heterobranchia,

Patellogastropoda, and Vestigastropoda.

- represents samples that are within three "box lengths" from the upper quartile value *- represents samples that are further than three "box lengths" from the upper quartile value

120 a)

u m a. «T N v" •>, V -S ^ 4. ^ «,' «. *T (D^ A -\ ' 0 3S1 115 IS! i!S 253 J5S ,Si -S ,S5

01 si £ c) 3

! 10 C 23 0 33 C 43 C 50 16C C 70 3 81? 3 93

Genome size range (pg)

Figure 3.13. Distribution of genome sizes of gastropods included in this study divided into 4 subclasses: a) Vestigastropoda (17 species); b) Heterobranchia (45 species); c) Caenogastropoda

(88 species); and d) Patellogastropoda (8 species).

121 3-

a.

£ c * at 0

1 Polar n=26 Temperate n=39 Tropical n=22

Figure 3.14. Relationships between genome size and thermal regimes associated with latitudinal ranges in gastropods. Polar species were significantly different from both temperate and tropical groups (Kruskal-Wallis, p<0.004).

122 2.5Q-

2.25-

3 11 a. 4) 2.00" N in a Genom e il II

1.50-

* 1.25-

Polar n=2Q Temperate n=59 Tropical n=32

Figure 3.15. Comparison between genome size and thermal regimes associated to latitudinal ranges in marine bivalves. Polar species were significantly different from temperate and tropical species (Kruskal-Wallis, p=0.30).

123 Table 3.1. New mean genome size estimates (GS, in pg) for moiluscan species, including standard error for estimates obtained from more than one individual. Genome sizes were measured by Flow Cytometry with at least 1,300 nuclei and CVs below 10%. Two estimates for the species

Promenetus exacuous are included in the table, as the two values may represent evidence for polyploidy.

Class Order Family Genus Species Name Mean C-value S.E. of Mean

Bivalve Carditoida Astartidae Astarte Astarte cf. montagui 4.42 7 0.09 Euheterodonta Hiatellidae Hiatella Hiatella arctica 1.69 2 0.005 Lucinoida Thyasiridae Axinopsida Axinopsida orbiculata 2.27 2 0.24 Myoida Myidae Mya Mya truncata 1.79 2 0.06 Mytiloida Mytilidae Crenella Crenella faba 1.84 6 0.07 Mytilus Mytilus edulis 1.72 8 0.03 Nuculida Nuculidae Ennucula Ennucula tenuis 3.17 1 Unionoida Unionidae Lasmigona Lasmigona compressa 3.99 6 0.08 Veneroida Dreissenidae Dreissena Dreissena polymorpha 1.78 9 0.02 Sphaeriidae Pisidium Pisidium nitidum 3.06 1 Pisidium rotundatum 4.19 5 0.17 Pisidium ventricosum 4.91 4 0.17 Tellinidae Macoma Macoma balthica 1.58 2 0.04 Gastropoda Architaenioglossa Vivaparidae Cipangopaludina Cipangopaludina chinensis 4.12 4 0.07 Lymnaeidae Fossaria Fossaria exigua 1.14 2 0.03 Fossaria modicella 4.4 1 Fossaria parva 2.47 6 0.08

124 Class Order Family Genus Species Name Mean C-value n S.E. of Mean

Lymnaea Lymnaea stagnalis 1.04 5 0.06 Stagnicola Stagnicola elodes 1.2 20 0.02 Physidae Aplexa Aplexa elongata 1.6 13 0.07 Physa Physa jenessi 0.98 8 0.06 Planorbidae Gyraulus Gyraulus circumstriatus 1.76 4 0.03 Helisoma Helisoma campanulatum 2.53 5 0.09 Promenetus Promenetus exacuous 0.49 2 0.02 Promenetus Promenetus exacuous 1.06 3 0.04 Heterostropha Valvatidae Valvata Valvata sincera helicoidea 1.5 . 2 0.02 Littorinimorpha Littorinidae Littorina Littorina saxatilis 1.42 3 0.04 Neogastropoda Cancellariidae Admete Admete viridula 5.73 2 0.07 Conidae Oenopota Oenopota bicarinata 3.91 2 0.08 Oenopota Oenopota spl 3.49 2 0.33 Propebela Propebela turricula 3.96 2 0.09 Neotaenioglossa . Thiaridae Melanoides Melanoides tuberculatus 6.65 10 0.01 Nudibranchia Dorididae Dorididae sp 1.31 1 Stylommatophora Euconulidae Euconulus Euconulus fulvus 1.79 7 0.04 Helicidae Cepaea Cepaea nemoralis 4.22 12 0.1 Limacidae Deroceras Deroceras laeve 1.87 1 Succineidae Succinea Succinea spl 1.46 8 0.08 Succinea sp2 0.95 3 0.1 Vertiginidae Vertigo Vertigo sp. 1.52 2 0.05 Lottiidae Testudinalia Testudinalia testudinalis 0.6 7 0.03 Turbinidae Margarites Margarites costalis 5.32 1

125 Class Order Family Genus Species Name Mean C-value n S.E. of Mean

Margarites helicinus 1.68 2 0.08 Polyplacophora Chitonida Ischnochitonidae Stenosenus Stenosenus albus 1.86 1 Tonicella Tonicella marmorea 2.82 2 0.03 Table 3.2. Calculated average genome size estimate for rainbow trout, Oncorhynchus mykiss, based on the comparisons with several standards of known C-value. Genome sizes were measured by Flow Cytometry and Feulgen Image Analysis and standard error and number of runs are included in the table.

0.mykiss Standard used Common name S.E. of Mean Number of Runs Method Employed C-value Efestia elutella Cacao Moth 2.37 0.01 5.00 FCM Tenebrio molitor Mealworm Beetle 2.38 0.03 5.00 FCM Mytilus edulis Blue Mussel 2.38 0.02 6.00 FCM Gallus domesticus Chicken 2.39 0.06 9.00 FIA Average O. mykiss C-value 2.38

127 SUMMARY

Genome size correlations were investigated at both the organismal and ecological scale for two understudied groups of invertebrates. The first case study presented in chapter 2

examined primarily organismal-level patterns in butterflies. A total of 84 species were analysed

and all but three represent novel estimates. General results revealed butterflies have

significantly smaller genome sizes than their "moth" relatives and, in agreement with the

previously proposed hypothetical threshold for holometabolous insects, all butterflies had genome sizes smaller than 2pg. In addition, sperm length was positively correlated with genome size among butterflies, whereas thorax length and forewing length did not correlate with DNA

content. Wing scale area also did not correlate with genome size, despite a previous hypothesis

suggesting it would. None of the developmental parameters examined in this case study

correlated with genome size with the exception of longevity. However this result was based on

only 8 species. Finally, habitat choice and food preference both correlated with genome size. To

be specific, species living in rainforest had larger genomes on average than species living in open fields, and species feeding on rotting fruits had the largest genomes compared to nectar and

pollen feeders.

The second case study presented in chapter 3 examined ecological patterns in genome

size diversity in two groups of molluscs, gastropods and bivalves. In this case study, 259 species were included in the analysis, these were divided into 44 species collected and analysed in this

study and 215 species compiled from the Animal Genome Size Database. General results

revealed that genome sizes for both bivalves and gastropods are intermediate compared with those of better-studied vertebrate groups. In gastropods, genome size did not correlate with

habitat transitions, neither from freshwater to terrestrial, nor from marine to freshwater

128 habitats. However, genome size was associated with latitudinal range categories, with species living in polar regions having on average larger genomes than temperate and tropical groups. In bivalves on the other hand, shifts from marine to freshwater habitats appear to correlate to genome size. However, this correlation may be strongly driven by freshwater polyploids. In addition, similarly to gastropods, broad latitudinal ranges correlated with genome size; and polar species revealed significantly larger genomes than species living in temperate and tropical seas.

CONCLUSION

One of the main goals of genome size research is to answer the question of why some species have accumulated so much DNA in their nuclei, while other species have lost most of it.

In this study, this question was addressed by investigating two invertebrate groups from organismal and ecological perspectives. Both pathways of investigation were very informative in revealing significant relationships with genome size, substantiating the claim that DNA content influences an organism's biology well beyond the cytogenetic level.

It is noteworthy to mention that most studies on animals have concentrated on genome size interactions at the organismal level. This is understandable since the number of external factors that may influence a genome size correlation increases with higher levels of biological organization (e.g. organismal versus ecological). For example, genome size does not directly correlate with habitat, instead it correlates with cell size and division rate, which in turn correlates with an organismal parameter (most likely metabolism), which then correlates with habitat; yet most analyses will not reveal all these steps, instead only indicating that the relationship between genome size and habitat is significant.

129 Nevertheless, for many animal groups and especially in invertebrates, data on

organismal-level parameters such as body size, developmental rate, and metabolism may not be

available for a large number of species. On the other hand, data on latitudinal distribution,

habitat choice, and food products may be easily accessible. Even though genome size

correlations at the ecological level may not reveal all underlying relationships, they are still very

informative in elucidating general patterns of variation.

This study was the first to emphasize the importance of examining genome size diversity from different levels of biological organization. Ultimately, this should propel genome size

research of rare and under-studied taxa, by encouraging the use of ecological data to define

preliminary patterns, when other sources of biological information are not available. In contrast, for taxa which have been well studied biologically, investigating a combination of organismal

and ecological parameters in association with genome size may still prove useful in answering the fundamental question of why genome sizes have evolved the way they have. Therefore, the

use of several levels of biological parameters represents an important step in the future of genome size research.

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145 APPENDICES

146 Appendix 2.1. Flow cytometry histograms from a variety of species of butterflies. A) Heliconius charitona (IC = 0.39pg) B) Heliconius ismenius

(IC = 0.35pg) C) Siproeta steneles (IC = 0.42pg) D) Parides iphidamas (IC = 0.34pg) E) Dryas iulia (IC = 0.46pg) F) Morpho peleides (IC = 0.44pg).

Charts as displayed in the BioQuant software. A head of a Drosophila melanogaster (Standard 2C) was used as a standard on all samples.

Standard 2C peaks represent the diploid DM peak and Unknown 2C represents the butterfly diploid peak. At least 1,300 nuclei were counted per sample.

147 A) B) All Data Points All Data Points 800- 400- • Standard 2C • Standard 2C I I .Unknown 2C I IUnknown 2C

•S ; J*. *¥H *~?L

400- 200-

ImT Ptlwiir [ iliiiiiiiiiiiiJUMijAiii i ^a^w^*. •j.MfcMISiT*|!^iMfcfc- 'I'M 1^1 • I ' 1—I—r 200 400 600 800 1000 0 n 20i0 ' r •40 i 0 600 800 1000 FL3 (PI) FL3 (PI)

148 C) D)

All Data Points All Data Points 1600-TT 400-j • Standard 2C I I .Unknown 2C l__f Untnew if

800- 200-

T^lL 1 l ' Pi ' I ' I ' "i—I—r 200 400 600 800 1000 400 600 FL3 (PI) FL3 (PI)

149 F) E) All Data Points All Data Points 200- 400-r •Standard 2C • Standard 2C I I .Unknown 2C I I .Unknown 2C

100- 200-

•d • MII i^dMMMw>T^~W«iii< n 400 600 800 1000 400 600 800 1000 FL3 (Pi) FL3 (PI)

150 Appendix 2.2. Images of wing scales from several species measured in pixels using image analysis. Different shapes and sizes of scales can be found in a single wing; efforts were made to ensure similar scales types were consistently analyzed. (A) Anteos chloride; (B) Caligo memnon; (C)

Philathria dido; (D) Dryas iulia; (E) Heliconius doris; (F) Idea leuconoe.

151 IT) CO in

#1?^ m^ ^1- Appendix 2.3. A list of all biological and ecological parameters analyzed in this study and their corresponding source reference (REF). Cellular parameters include Mean Apyrene Sperm Length (MASL) and Mean Eupyrene Sperm Length (MESL); morphological parameters include Forewing

Length (FWL), Mean Thorax Length (MTL), and Mean Scale Area (MSA), developmental parameters include Mean Egg Duration (MED), Mean

Larval Duration (MLD), Mean Chrysalis Duration (MCD) and Longevity (LONG), and behavioural parameters including habitat type (HABT) and feeding preferences (FEEDP).

155 Family Subfamily Species MED MLD MCD MSA MTL FWL MASL MESL LONG HABT FEEDP um um days Doxocopa Deciduous fores Nymphalidae Apaturinae laure 18(1) 19(1) 34 (2) Mectar (2) Brassolinae Caligo atreus 25(1) 20(1) 79 35(2) Rain forest (2) totting fruits (2) Caligo illoneus 6(3) 46(3) 14(3) 71 35(2) Rain forest (2) totting fruits (2) Caligo eurilochus 9(4) 50(4) 18(4) 7095.29 11.75 84 756 (5) 1411 (5) 54(6) Rain forest (2) totting fruits (2) Caligo memnon 20(7) 8038.43 10 73 35(2) Disturbed (2) totting fruits (2) Archaeprepona Charaxinae demophon 6(8) 60(8) 19(8) 7352.08 11 57 Rain forest (2) Deciduous Consul fabius 5(9) 32(9) 11(9) 38 forest (2) totting fruits (2) Memphis eurypyle 5(10) 31 (10) 10 (10) 5468.34 6.5 29 Danainae Danuas affinis 6464.71 5 • Danuas chrysippus 7(11) 12 (il) 8(11) 6330.9 5 38 Open field (ii) Nectar (2) Danaus plexippus 4(12) 14 (12) 14 (12) 48 Open field (13) Mectar (13) Idea leuconoe 10885.19 6.67 Ideopsis juventa 6529.24 6 Heliconiinae Cethosia biblis 6425.67 6.5 31.5 Rain forest (14) Nectar (15) Dionejuno 6(16) 13 (16) 30 (16) 5425.41 6.5 37.5 Open field (2) Nectar (2) Dione moneta 6(16) 13 (16) 30 (16) 36.5 Open field (2) Nectar (2) Dryadula phaetusa 4(17) 19(1) 14(1) 5530.93 4.6 40.5 Mectar (2) Dryas iulia 4(17) 16(1) 12(1) 5126.78 5.07 43 464 (5) 1545 (5) All habitats (2) Mectar (is) Deciduous Eurides Isabella 4(18) 17 (18) 8(18) 45 forest (2) Nectar (is) Family Subfamily Species MED MLD MCD MSA MTL FWL MASL MESL LONG HABT FEEDP Heliconius charitonia 12(1) 10(1) 4782.15 4.7 43 352 (5) 547 (5) 3ollen (2) Heliconius Deciduous 3 cydno 11(1) 3455.07 4.6 40.5 forest (2) ollen (2) Heliconius Deciduous doris 4(17) 13 (17) 10 (17) 5125.4 4.42 40 Forest (14) 3ollen (2) Heliconius erato 4(17) 21(6) 3934.16 4.35 34 534 (5) 914 (5) 'ollen (2) Heliconius hecale 5(19) 21 (19) 9 (1,19) 4617.66 4.75 46 All habitats (2) 'ollen (2) Heliconius hewitsoni 2905.33 5 37.5 Rain forest (14) 'ollen (2) Heliconius ismenius 19(1) 4372.33 5.67 43 Rain forest (14) 'ollen (2) Heliconius melpomene 4(17) 13 (17) 10 (17) 4.75 37 474 (5) 700 (5) Heliconius sapho 3987.66 4.5 40 Rain forest (14) 'ollen (2) Heliconius sara 4(17) 13 (17) 10 (17) 4079.54 3.75 32.5 Rain forest (14) 'ollen (2) Philathria dido 4(17) 4454.52 5.1 Mechanitis Ithomiinae menapis 39.5 Rain forest (14) Nectar (15) Mechanitis polymnia 10(1) 1715.67 4 36 Tithorea tarricina 15(1) 3819.96 5 41 Mectar (15) Parthenos Limenitidinae sylvia 5571.38 8 Melitaeinae Chlosyne janais 9(20) 5366.17 4 25.5 Open field (2) Mectar (2) Morpho Morphinae granadensis 81(1) 25(1) 69.5 Rain forest (21) Rotting fruit (21) Morpho 11 (21) 53 (21) 14 (21) 11932.7 9 71 653 (5) 1164 (5) Rain forest (21) Rotting fruit (21) Family Subfamily Species MED MLD MCD MSA MTL FWL MASL MESL LONG HABT FEEDP peleides Morpho polyphemus 12601.0 7 77.5 Rain forest (22) totting fruit (23) Adelpha Nymphalinae fessonia 6(24) 23(24 9(24) 5351 5 29.5 totting fruit (2) Anartia fatima 5(25) 23 (25) 7(25) 5698.65 6 28.5 11 (26) Open field (14) Mectar (14) Biblis hyperia 3(26) 19 (26) 10 (26) 5785.55 5.5 32.5 550 (5) 1326 (5) Open field (2) totting fruit (2) Catonephele mexicana 24(1) 11(1) 29.5 Rain forest (2) totting fruit (2) Catonephele numilia 5(27) 26 (27) 11 (27) 4145.76 5.6 35 Rain forest (2) totting fruit (2) Colobura dirce 4(28) 23 (28) 13 (28) 4835.12 6.17 36 422 (5) 1195 (5) totting fruit (2) Doleschallia bisaltide Rain forest (12) Hamandryas arinome 36.5 Rain forest (2) totting fruits (29) Hamandryas februa 5(29) 21 (29) 8(29) 6524.32 5.9 36 Disturbed (2) totting fruits (29) Hypolimnas Deciduous bolina 11183.5 5.83 42 forest (2) Hypolimnas Deciduous missipus 8435.96 6.17 36.5 forest (2)

Myscelia cyaniris 6100.99 5.25 31 Rain forest (23) totting fruits (23) Myscelia ethusa totting fruits (23)

Siproeta Mectar/ epaphus 47(1) 16(1) 5575.56 6.5 49 Rain forest (21) totting fruits (23) Siproetas Mectar/ stelenes 14(1) 7760.07 7.5 46.5 Open field (21) totting fruits (20) Satyrinae Elymnias 6(30) 24 (30) 20 (30) 1103.37 4.6

158 Family Subfamily Species MED MLD MCD MSA MTL FWL MASL MESL LONG HABT FEEDP hypermnestra

Papilionidae Papilioninae Battus belus 16(1) 22(1) 6217.30 7 48 Rain forest (2) Mectar (2) Battus polydamus 21(1) 21(1) 5282 7 45 597 (5) 1061 (5) Open field (22) Mectar (31) Eurytides phaon 41 Nectar (2) Graphium agamemnon 4(32) 18 (32) 14 (32) 2386.64 7.5 Rain forest (22) Nectar (20) Ornithoptera priamus 9362.51 11.75 Papilio anchisiades 7(33) 45 (33) 72 (33) 5994.07 8.5 52.5 Disturbed (22) Mectar (20) Papilio androgenus 65 Open field (2) Nectar (20) Papilio Deciduous astyalas 7753.95 9.33 60 forest (20) Nectar (15,20) Papilio erostratus Papilio hipponous 1508.11 5 Papilio lowii 9387.38 7.5 Papilio palinurus 7256.35 7 Papilio polytes 6014.18 6.5 Papilio polyxenes 26(1) 6958.41 10 37.5 488 (5) 980 (5) Open field (2) Nectar (15) Papilio rumanzovia 1993.12 10.7 Papilio thoas 7203.54 7 59 Rain forest (2) Nectar (15) Papilio ulysses 14404.2 7 Deciduous Parides areas 6(34) 33 (34) 14 (34) 3888.05 5.75 41 6(35) Forest (2) Mectar (15) Family Subfamily Species MED MLD MCD MSA MTL FWL MASL MESL LONG HABT FEEDP Parides chilasedeous Parides childrenae , 34(1) 2KD 50 6 Rain forest (20) Mectar (2) Parides Deciduous iphidamas 7(36) 26 (36) 30 (36) 4921.55 6 40 6 forest (20) Nectar (15) Troides rhadamantus 8236.15 10.75 Pachliopta Polyommatin kotzebuea 1416.87 6.92 Pieridae Coliadinae Anteos clorinde 4(23) 20 (23) 9(23) 7248.14 6 42.5 Open field (2) Mectar (2) Anteos - maerula 7466.2 8.25 49 Open field (2) Nectar (2) Phoebis philea 14(1) 12(1) 4144.5 8 42.5 Open field (2) Nectar (2) Phoebis sennae 26(1) 4843.92 6.5 32.5 428 (5) 503 (5) Open field (20) Mectar (15) Apppias Pierinae drusilla 3(37) 19 (37) 6(37) 5927.98 4 31.5 Open field (2) Mectar (15) Hebomoia glaucippe References for the Appendix 2.3

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165 Appendix 2.4. Details on all the statistical analysis performed on each comparison presented in case study one. Data for the individual parameters were tested using the Shapiro-Wilk test and normality was assumed when p-values were larger than 0.01 (Park, 2008). In cases where normality could be assumed, parametric tests including t-tests and Pearson correlations were performed. However, when assumptions for normality were not met based on Shapiro-Wilk test, non-parametric tests were chosen automatically by SPSS based on the most suitable analysis for the data. Each comparison and a detail record of the statistical analysis used are presented below.

Genome sizes derived by FIAhaem0iymph versus FIAsperm

Shapiro-Wilk normality Paired t-test Pearson's correlation test

F'AHaemolymph P=0.08 p-value p=0.001 p<0.001 FIAsperm P=0.67

correlation 0.84 coefficient t-value 3.42

n 58 58

Genome sizes derived by FIAhaemoiymph versus FCM Shapiro-Wilk Wilcoxon Kendall's Spearman's normality test Signed Ranks correlation correlation

FIA p=0.21 p-value haemo p<0.001 p<0.001 p<0.001 FCM p=0.009

correlation 0.54 0.70 coefficient

n 50 50 50

166 Genome sizes devired by FIAsperm versus FCM

Shapiro-Wilk Wilcoxon Kendall's Spearman's normality test Signed Ranks correlation correlation

FIA perm P=0.62 p-value S p<0.001 p<0.001 p<0.001 FCM p=0.006

correlation 0.70 0.86 coefficient

n 47 47 47

Genome sizes in butterflies versus "moths"

Shapiro-Wilk normality test Wilcoxon Signed Ranks

butterflies p<0.001 p-value p<0.001 moths p<0.001

84

Genome size and eupyre sperm length

Shapiro-Wilk normality test Pearson's correlation

GS p=0.12 p-value p=0.05 Eupyrene Sperm p=0.41

correlation coefficient 0.71

n 8 8

167 Genome size and apyrene sperm length

Shapiro-Wilk normality test Pearson's correlation

GS p=0.12 p-value p<0.05 Apyrene Sperm p=0.24

correlation coefficient 0.8

n 8 8

Genome size and MTL

Shapiro-Wilk Kendall's Spearman's normality test correlation correlation

GS p=0.008 p-value p>0.05 p>0.05 MTL p=0.255

correlation coefficient 0.63 0.86

n 52 52 52

Genome size and FWL

Shapiro-Wilk Kendall's Spearman's normality test correlation correlation

GS p=0.347 p-value p>0.05 p>0.05 FWL p=0.006

correlation coefficient 0.103 0.18

n 53 53 53 Genome size and wing scale area

Shapiro-Wilk Kendall's Spearman's normality test correlation correlation

GS p=0.01 p-value p>0.05 p>0.05 Scale area p=0.167

correlation coefficient 0.08 0.10

n 51 51 51

Genome size and development inside the egg

Shapiro-Wilk normality test Pearson's correlation

GS p=0.02 p-value p>0.05 Egg development p=0.02

correlation coefficient 0.02

n 25 25

Genome size and larval development

Shapiro-Wilk normality test Pearson's correlation

GS p=0.06 p-value p>0.05 Larval development p=0.02

correlation coefficient 0.17

n 33 33

169 Genome size and pupae development

Shapiro-Wilk normality test Pearson's correlation

GS p=0.02 p-value p>0.05 Pupae development p=0.14

correlation coefficient 0.02

n 42 33

Genome size and longevity

Shapiro-Wilk normality test Pearson's correlation

GS p=0.25 p-value p<0.005 Longevity p=0.04

correlation coefficient 0.91

n 8 8

Genome size and habitat choice

Shapiro-Wilk „ , ...... Wilcoxon Signed Kruskal-Walhs „ , normality test Ranks

1 Rainforest p-cO.OOl 2 p-value K p<0.05 p<0.05

I • ,l- —•••"•••• • p-values for all other habitats were larger than 0.01, indicating all but rainforest estimates had normal distributions 2 Differences between each habitat were examined with Wilcoxon Signed Ranks revealing both open field and deciduous forest were significantly different from rainforest

Genome size and diet preferences

Shapiro-Wilk Wilcoxon Signed Kruskal-Wallis normality test Ranks

Nectar p^.0011 p-value p<0.001 p<0.052

p-values for all other food types were larger than 0.01, indicating that all but nectar eaters had normal distributions 2 Differences between each diet were examined with Wilcoxon Signed Ranks revealing both nectar and pollen eaters significantly different from rotting fruit eaters

170 Appendix 3.1. List of all species estimates obtained from the Animal Genome Size Database [www.genomesize.com] and included in the analysis in this study. A total of 217 species are presented, comprising 88 bivalves and 129 gastropods. All values published in the database were included in this study without discriminating between tissue types and methods used. Methods and standards used in measuring the genome sizes are included and a taxonomic organization of each species is also presented. Methods used included: (BCA) Biochemical Analysis, (BFA)Bulk

Fluorometric Assay, (FCM) Flow Cytometry, (FD) Feulgen Densitometry, (FFA) Fluorescence Fading Analysis, and (FIA) Feulgen Image Analysis.

Standard species included: (AAR) Artemisia arborescens, (CA) Carassius auratus, (CG) Crassostrea gigas*, (DT) Donax trunculus*, (GD) Gallus domesticus, (HS) Homo sapiens, (LS) Lymnaea stagnalis*, (ME) Mytilus edulis*, (OM) Oncorhynchus mykiss, (PSV) Pisum sativum, (RT) Rana temporaria, (SP) Strongylocentrotus purpuratus, (SS)Susscrofa. * indicates molluscan standards.

171 Class Order Family Species C-value Method Std. Species

Bivalvia Arcoida Arcidae Anadara broughtoni 1.45 FIA CG Arcoida Arcidae Area boucardi 1.66 FIA CG Arcoida Neotiidae Noetia ponderosa 1.90 BFA SP Limoida Limidae Lima hemphillii 1.20 BFA SP Limoida Limidae Lima scabra 1.60 BFA SP Myoida Myidae Mya arenaria 1.40 FIA/ BFA CG/SP Myoida Myidae Platyodon cancellatus 1.60 BFA SP Myoida Pholadidae Barnea costata 0.70 BFA SP Bivalvia Myoida Pholadidae Pholadidea sp. 1.80 BFA SP Mytiloida Mytilidae Aulacomya ater maoriana 2.24 FCM ME Mytiloida Mytilidae Bathymodiolus azoricus 1.70 FCM/ FD PSV/ NS Mytiloida Mytilidae Bathymodiolus thermophilus 1.27 FCM AAR Mytiloida Mytilidae Botula falcata 1.80 BFA SP Mytiloida Mytilidae Hormomya mutabilis 1.79 FIA CA Mytiloida Mytilidae Lithophaga bisulcata 2.50 BFA SP Mytiloida Mytilidae Lithophaga curta 2.12 FIA CA Mytiloida Mytilidae Lithophaga plumula 2.30 BFA SP Mytiloida Mytilidae Modiolus auriculatus 1.68 FIA CA Mytiloida Mytilidae Modiolus kurilensis 3.40 FIA CG Mytiloida Mytilidae Modiolus sp. 1.90 BFA SP Mytiloida Mytilidae Musculista senhousia 1.16 FIA CA Mytiloida Mytilidae Mytilaster solidus 1.54 FCM ME Mytiloida Mytilidae Mytilus californianus 1.75 FIA/ BFA DT/SP Mytiloida Mytilidae Mytilus coruscus 1.90 FIA CA Class Order Family Species C-value Method Std. Species

Mytiloida Mytilidae Mytilus edulis 1.66 FD/BFA/ FCM IMS/ SP/ GD Mytiloida Mytilidae Mytilus galloprovincialis 1.66 FIA/ FCM CA/GD Mytiloida Mytilidae Mytilus gray an us 2.11 FIA CG Mytiloida Mytilidae Mytilus trossulus 1.40 FIA CG/DT Mytiloida Mytilidae Perna canaliculus 1.11 FCM ME Mytiloida Mytilidae Septifer keenae 1.06 FIA CA Mytiloida Mytilidae Septifer virgatus 1.08 FIA CA Mytiloida Mytilidae Volsella modiolus 2.80 BFA SP Mytiloida Mytilidae Volsella plicatulus 1.90 BFA SP Mytiloida Pinnidae Atrina rigida 1.10 BFA SP Bivalvia Nuculoida Nuculidae Acila castrensis 5.40 BFA SP Nuculoida Nuculidae Nucula proximo 3.10 BFA SP Ostreoida Ostreidae Crassostrea gigas 0.91 FIA DT Ostreoida Ostreidae Crassostrea virginica 0.69 BFA SP Ostreoida Ostreidae Cryptostrea permollis 1.10 BFA SP Ostreoida Ostreidae Ostrea edulis 1.17 FCM GD Ostreoida Ostreidae Ostrea lurida 1.30 BFA SP Ostreoida Ostreidae Unknown sp.l 1.30 BFA SP Ostreoida Ostreidae Unknown sp.2 0.65 BFA SP Ostreoida Pectinidae Argopecten irradians 1.20 BFA SP Ostreoida Pectinidae Argopecten purpuratus 1.10 FFA V Ostreoida Pectinidae Chlamys hastata 1.64 FIA DT Ostreoida Pectinidae Chlamys hericus 0.95 BFA SP Ostreoida Pectinidae Chlamys hindsii 1.00 BFA SP

173 Class C-value Method Std. Species

Ostreoida Pectinidae Chlamys opercularis 1.12 FCM GD Ostreoida Pectinidae Hinnites giganteus 1.29 FIA DT Ostreoida Pectinidae Hinnites multirugosus 1.30 BFA SP Ostreoida Pectinidae Pecten maximus 1.42 FCM GD Ostreoida Pectinidae Placopecten magellanicus 2.10 BFA SP Pectinoida Pectinidae Mizuhopecten yessoensis 1.69 FIA CG Solemyacea Solemyidae Solemya velum 2.10 BFA SP Unionoida Unionidae Elliptio sp. 3.20 BFA SP Unionoida Unionidae Uniomerus sp. 3.00 BFA SP Veneroida Cardiidae Cerastoderma edule 1.37 FCM GD Veneroida Cardiidae Cerastoderma pinnulatum 1.40 BFA SP Veneroida Cardiidae Laevicardium mortoni 1.30 BFA SP Veneroida Cardiidae Trachycardium quadragenarium 2.00 BFA SP Veneroida Chamidae Chama pellucida 1.50 BFA SP Veneroida Corbiculidae Corbicula japonica 1.93 FIA CG Veneroida Donacidae Donax variabilis 1.60 BFA SP Veneroida Dreissenidae Dreissena polymorpha 1.70 FIA GD, HS Veneroida Lucinidae Phacoides pectinata 1.70 BFA SP Veneroida Mactidae Spisula sachalinensis 1.41 FIA CG Veneroida Mactridae Spisula solidissima 1.18 BFA/ FCM SP/GD Veneroida Mactridae Tresus capax 1.64 FIA DT Veneroida Mactridae Tresus nuttalli 0.77 BFA SP Veneroida Petricolidae Petricola pholadiformis 1.10 BFA SP Veneroida Pharidae Ensis directus 1.50 BFA SP Class Order Family Species C-value Method Std. Species .

Veneroida Psammobiidae Nuttallia nuttallii 1.67 FIA/ BFA DT/SP Veneroida Solecurtidae Tagelus californianus 1.30 BFA SP Veneroida Solenidae Solen viridis 1.70 BFA SP Veneroida Tellinidae Apolymetis biangulata 2.30 BFA SP Veneroida Tellinidae Macoma balthica 2.30 BFA SP Veneroida Tellinidae Macoma nasuta 2.28 FIA/ BFA DT/SP Veneroida Tellinidae Macoma secta 2.40 BFA SP Veneroida Tellinidae Macoma tenta 1.70 BFA SP Veneroida Veneridae Callithaca adamsi 1.97 FIA CG Veneroida Veneridae Chione undatella 2.00 BFA SP Veneroida Veneridae Dosinia japonica 2.02 FIA CG Veneroida Veneridae Mercenaria campechiensis 2.30 BFA SP Veneroida Veneridae Mercenaria mercenaria 2.00 BFA SP Veneroida Veneridae Protothaca staminea 1.68 FIA/ BFA DT/SP Bivalvia Veneroida Veneridae Saxidomus nuttalli 1.10 BFA SP Veneroida Veneridae Tapes decussata 1.81 FCM GD Veneroida Veneridae Tapes philippinarum 1.97 FIA DT Veneroida Veneridae Tapes pullastra 1.78 FCM GD Veneroida Veneridae Tapes rhomboideus 1.62 FCM GD Veneroida Veneridae Tivela stultorum 0.96 BFA SP Veneroida Vesicomyidae Calyptogena magnifica 2.35 FCM AAR

Gastropoda Anaspidea Aplysiidae Aplysia californica 1.90 BFA SP/SS Anaspidea Aplysiidae Aplysia dactylomela 1.90 BFA SP Class Order Family Species C-value Method Std. Species

Gastropoda Archaeogastropoda Fissurellidae Diodora aspera 1.50 BFA SP Archaeogastropoda Fissurellidae Fissurella barbadensis 0.50 FD GD Archaeogastropoda Fissurellidae Fissurella volcano 0.65 BFA SP Archaeogastropoda Fissurellidae Megathura crenulata 1.90 BFA SP Archaeogastropoda Haliotidae Haliotis corrugata 2.07 FFA/ BFA NS/SP Archaeogastropoda Haliotidae Haliotis fulgens 1.70 FFA/ BFA NS/SP Archaeogastropoda Haliotidae Haliotis rufescens 1.81 FFA/ BFA NS/SP Archaeogastropoda Lepetodrilidae Lepetodrilus sp. 1.80 FD NS Archaeogastropoda Trochidae Norrisia norrisi 1.60 BFA SP Archaeogastropoda Trochidae Tegula brunnea 1.70 BFA SP Archaeogastropoda Trochidae Teg u la funebralis 1.50 BFA SP Archaeogastropoda Turbiniidae Astraea undosa 2.30 BFA SP Archaeogastropoda Vermetidae Aletes squamigerus 1.50 BFA SP Architaenioglossa Ampullariidae Pomacea cuprina 0.67 BFA SP Architaenioglossa Ampullariidae Pomacea paludosa 0.61 FCM LS Architaenioglossa Viviparidae Campeloma geniculum 1.73 FCM GD, OM Architaenioglossa Viviparidae Campeloma limum 1.85 FCM GD, OM Architaenioglossa Viviparidae Campeloma parthenum 2.54 FCM GD, OM Architaenioglossa Viviparidae Viviparus contectus 2.04 FCM LS Basommatophora Lymnaeidae Lymnaea auricularia 1.51 FCM LS Basommatophora Lymnaeidae Lymnaea calamphala 1.22 FCM LS Basommatophora Lymnaeidae Lymnaea fontinalis 1.32 FCM RT Basommatophora Lymnaeidae Lymnaea fulva 1.30 FCM LS Basommatophora Lymnaeidae Lymnaea sp. 2.00 BFA SP Class Order Family Species C-value Method Std. Species

Gastropoda Basommatophora Lymnaeidae Lymnaea stagnalis 1.22 FCM LS Basommatophora Physidae Physarubra 1.20 FCM RT Basommatophora Planorbidae Biomphalaria glabrata 0.95 FIA GD Basommatophora Planorbidae Planorbella tenuis 1.48 FCM LS Basommatophora Planorbidae Planorbis corneus 1.25 BFA/ FCM SP/LS Basommatophora Planorbidae Planorbis planorbis 1.43 FCM RT Caenogastropoda Provannidae Alviniconcha hessleri 0.94 FCM AAR Caenogastropoda Provannidae Ifremeria nautilei 0.90 FCM AAR Cephalaspidea Bullidae Bulla gouldiana 1.60 BFA SP Mesogastropoda Diplommatinidae Arinia japonica 2.60 FIA CA Mesogastropoda Diplommatinidae Diplommatina cassa 2.80 FIA CA Mesogastropoda Diplommatinidae Diplommatina circumstomata 4.38 FIA CA Mesogastropoda Diplommatinidae Diplommatina collarifera collarifera 6.34 FIA CA Mesogastropoda Diplommatinidae Diplommatina collarifera okiensis 7.72 FIA CA Mesogastropoda Diplommatinidae Diplommatina collarifera tenuiplica 6.19 FIA CA Mesogastropoda Diplommatinidae Diplommatina gibbera 4.45 FIA CA Mesogastropoda Diplommatinidae Diplommatina hidaensis 3.26 FIA CA Mesogastropoda Diplommatinidae Diplommatina kiiensis kiiensis 7.85 FIA CA Mesogastropoda Diplommatinidae Diplommatina kiiensis ssp. 6.17 FIA CA Mesogastropoda Diplommatinidae Diplommatina kobelti 4.73 FIA CA Mesogastropoda Diplommatinidae Diplommatina nipponensis 5.23 FIA CA Mesogastropoda Diplommatinidae Diplommatina shikokuensis 5.56 FIA CA Mesogastropoda Diplommatinidae Diplommatina sp. 3.93 FIA CA Mesogastropoda Diplommatinidae Diplommatina tanegashimae kyushuensis 3.13 FIA CA Class Order Family Species C-value Method Std. Species

Gastropoda Mesogastropoda Diplommatinidae Diplommatina tosana goniobasis 3.93 FIA CA Mesogastropoda Diplommatinidae Diplommatina tosana kureana 4.12 FIA CA Mesogastropoda Diplommatinidae Diplommatina tosana onoensis 4.34 FIA CA Mesogastropoda Diplommatinidae Diplommatina tosana tosana 6.09 FIA CA Mesogastropoda Diplommatinidae Diplommatina tosanella abei 2.73 FIA CA Mesogastropoda Diplommatinidae Diplommatina tosanella tosanella 4.08 FIA CA Mesogastropoda Diplommatinidae Palaina pusilla 1.94 FIA CA Mesogastropoda Littorinidae Littorina obtusata 1.21 FCM GD Neogastropoda Buccinidae Buscyon canaliculatum 4.40 BFA SP Neogastropoda Buccinidae Kelletia kelleti 3.70 BFA SP Neogastropoda Buccinidae Neobuccinum eatoni 5.88 FCM ME Neogastropoda Conidae Conus californicus 2.60 BFA SP Neogastropoda Conidae Conus lividus 3.90 BFA SP Neogastropoda Conidae Conus pennaceus 3.60 BFA SP Neogastropoda Mitridae Mitra idae 2.70 BFA SP Neogastropoda Muricidae Bolinus brandaris 2.83 FD ME,V Neogastropoda Muricidae Ceratostoma nuttalli 2.40 BFA SP Neogastropoda Muricidae Hexaplex trunculus 2.26 FD ME,V Neogastropoda Muricidae Nucella canaliculata 2.54 FD ME,V Neogastropoda Muricidae Nucella emarginata 2.75 FD ME, V Neogastropoda Muricidae Nucella lamellosa 2.43 FD ME,V Neogastropoda Muricidae Nucella lapillus 2.73 FD/ BFA NS/SP/ME/V Neogastropoda Muricidae Ocenebra erinaceus 2.61 FD ME,V Neogastropoda Muricidae Ocenebra poulsoni 2.60 BFA SP

178 Class Order Family Species C-value Method Std. Species

Gastropoda Neogastropoda Muricidae Thais haemastoma 2.09 FD ME,V Neogastropoda Muricidae Urosalpinx cinerea 3.10 BFA SP Neogastropoda Nassariidae Nassarius fossatus 4.40 BFA SP Neogastropoda Nassariidae Nassarius obsoletus 3.20 BCA NS Neogastropoda Nassariidae Nassarius tegula 3.90 BFA SP Neogastropoda Olividae Olivella biplicata 2.00 BFA SP Neotaenioglossa Bithyniidae Bithynia sp. 1.25 FCM LS Neotaenioglossa Cypraeidae Cypraea spadicea 1.60 BFA SP Neotaenioglossa Hydrobiidae Hydrobia ulvae 0.68 FCM LS Neotaenioglossa Littorinidae Littorina irrorata 0.82 BFA SP Neotaenioglossa Littorinidae Littorina keenae 0.90 FCM GD Neotaenioglossa Littorinidae Littorina littorea 1.06 FD/ BFA/ FCM NS/ SP/ LS Neotaenioglossa Littorinidae Littorina neritoides 1.42 FCM GD/ME Neotaenioglossa Littorinidae Littorina punctata 0.81 FCM ME Neotaenioglossa Littorinidae Littorina saxatilis 1.35 FCM ME Neotaenioglossa Littorinidae Tectarius muricatus 0.67 FD GD Neotaenioglossa Naticidae Polinices duplicatus 1.50 BFA SP Neotaenioglossa Naticidae Polinices heros 2.40 BFA SP Neotaenioglossa Pleuroceridae Goniobasis alabamensis 2.10 FCM HS,V Neotaenioglossa Pleuroceridae Goniobasis catenaria dislocata 2.10 FCM HS,V Neotaenioglossa Pleuroceridae Goniobasis floridensis 2.10 FCM HS,V Neotaenioglossa Pleuroceridae Goniobasis livescens 2.10 FCM HS,V Neotaenioglossa Pleuroceridae Goniobasis proximo 2.10 FCM HS,V Neotaenioglossa Pleuroceridae Goniobasis simplex 2.10 FCM HS,V

179 Class Order Family Species C-value Method Std. Species

Gastropoda Neotaenioglossa Pleuroceridae lofluvialis 2.10 FCM HS,V Neotaenioglossa Pleuroceridae Juga hemphilli 2.10 FCM HS,V Neotaenioglossa Pleuroceridae Leptoxis (Mudalia) carinata 2.10 FCM HS,V Neotaenioglossa Pleuroceridae Leptoxis praerosa 2.10 FCM HS,V Neotaenioglossa Pleuroceridae Lithasia duttoniana 2.10 FCM HS,V Neotaenioglossa Pleuroceridae Lithasia verrucosa 2.10 FCM HS,V Neotaenioglossa Pleuroceridae Pleurocera acuta 2.10 FCM HS,V Neotaenioglossa Pleuroceridae Pleurocera canaliculatum 2.10 FCM HS,V Neotaenioglossa Pleuroceridae Pleurocera unciale 2.10 FCM HS,V Nudibranchia Aeolidiidae Aeolidia papulosa 1.20 BFA SP Nudibranchia Arminidae Armina californica 1.00 BFA SP Nudibranchia Dorididae Archidoris montereyensis 2.00 BFA SP Nudibranchia Flabellinidae Flabellina iodinea 0.71 BFA SP Nudibranchia Tergipedidae Phestilla sp. 0.91 FIA GD Patellogastropoda Acmaeidae Acmaea mitra 0.94 BFA SP Patellogastropoda Acmaeidae Collisella digitalis 0.61 BFA SP Patellogastropoda Acmaeidae Collisella limatula 0.56 BFA SP Patellogastropoda Acmaeidae Collisella paradigitalis 0.58 BFA SP Patellogastropoda Acmaeidae Collisella scabra 0.57 BFA SP Patellogastropoda Lottiidae Lottia gigantea 0.43 BFA SP Patellogastropoda Lottiidae Tectura testudinalis 0.57 BFA SP Patellogastropoda Lottiidae Unknown sp.l 0.94 FD NS Patellogastropoda Lottiidae Unknown sp.2 0.79 FD NS Patellogastropoda Lottiidae Unknown sp.3 0.55 FD NS

180 Class Order Family Species C-value Method Std. Species

Sacoglossa Stiligeridae Stiligerfelinus 2.83 FCM ME Stylommatophora Achatinidae Achatina fulica 2.25 FCM LS Stylommatophora Helicidae Arianta arbustorum 2.84 FCM LS Stylommatophora Helicidae Cantareus aspersus 3.58 FCM GD Stylommatophora Helicidae Cantareus mazzullii 3.08 FCM GD Stylommatophora Helicidae Helix vulgaris 4.00 FCM RT Stylommatophora Hygromiidae Trichia hispida 2.49 FCM LS Stylommatophora Limacidae Deroceras reticulatum 1.68 FCM RT Stylommatophora Succineidae Succinea putris 2.92 FCM LS Vetigastropoda Lepetodrilidae Leptodrilus atlanticus 1.04 FCM PSV Vetigastropoda Lepetodrilidae Pseudorimula midatlantica 1.05 FCM PSV Vetigastropoda Turbinidae Potrolira sp. 0.70 FCM LE

181 References for Appendix 3.1

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184 Appendix 3.2. Mean genome size estimates and standard error for all 20 species in the database that were measured by multiple studies. The largest number of estimates for a single species is 4, and most standard errors of the mean are relatively small. All these cases of multiple measurements serve as a tool to test the accuracy and consistency of estimates derived from different studies.

S.E. of Class Order Family Species Mean C-value Mean Bivalvia Myoida Myidae Mya arenaha 1.4 2 0 Mytiloida Mytilidae Bathymodiolus azoricus 1.7 2 0.2 Mytiloida Mytilidae Mytilus californianus 1.75 2 0.14 Mytiloida Mytilidae Mytilus edulis 1.66 4 0.03 Mytiloida Mytilidae Mytilus galloprovincialis 1.66 2 0.25 Mytiloida Mytilidae Mytilus trossulus 1.4 2 0.11 Veneroida Mactridae Spisula solidissima 1.18 2 0.02 Veneroida Psammobiidae Nuttallia nuttallii 1.67 2 0.07 Veneroida Tellinidae Macoma nasuta 2.28 2 0.33 Veneroida Veneridae Protothaca staminea 1.68 2 0.07

Gastropoda Anaspidea Aplysiidae Aplysia californica 1.9 0.1 Archaeogastropoda Haliotidae Haliotis corrugata 2.07 0.07 Archaeogastropoda Haliotidae Haliotis fulgens 1.7 0.005 Archaeogastropoda Haliotidae Haliotis rufescens 1.81 0.01 Basommatophora Planorbidae Planorbis corneus 1.25 0.15 Mesogastropoda Diplommatinidae Diplommatina collarifera collarifera 6.34 0.36

185 S.E. of Class Order Family Species Mean Neogastropoda Muricidae Nucella lapillus 2.73 3 0.07 Neogastropoda Nassariidae Nassarius obsoletus 3.2 3 0.06 Neotaenioglossa Littorinidae Littorina littorea 1.06 3 0.06 Neotaenioglossa Littorinidae Littorina neritoides 1.42 2 0.04

186 Appendix 3.3.Mean genome size and standard error for the 6 comparisons between collected and database species. All cases presented low standard error of the mean, indicating both measured and compiled estimates were similar to one another.

S.E. of Class Order Family Species Mean C-vaiue n Mean Bivalve Mytiloida Mytilidae Mytilus edulis 1.66 4 0.03 Veneroida Dreissenidae Dreissena polymorpha 1.74 2 0.04 Veneroida Tellinidae Macoma balthica 1.94 2 0.36

Gastropoda Basommatophora Lymnaeidae Lymnaea stagnalis 1.13 2 0.09 Neotaenioglossa Littorinidae Littorina saxatilis 1.38 2 0.03 Patellogastropoda Lottiidae Tectura testudinalis 0.58 2 0.01

187 Appendix 3.4. Summary of the ecological parameters used in the analysis. Habitats were divided into marine, freshwater and terrestrial and each species was assigned to one of the categories. Latitude, on the other hand was divided into POLAR (polar), TEMP (temperate) and TROP

(Tropical) ranges and species were assigned to one or more categories depending on their distributions. Cosmopolitan species were assigned to all three categories.

Class Subclass Family Species C-value Habitat Latitude Bivalve Heterodonta Hiatellidae Hiatella arctica 1.69 Marine POLAR/TEMP/TROP Bivalvia Heterodonta Myidae Mya arenaria 1.40 Marine POLAR/TEMP Bivalve Heterodonta Myidae Mya truncata 1.79 Marine POLAR Bivavlia Heterodonta Myidae Platyodon cancellatus 1.60 Marine TEMP Bivavlia Heterodonta Pholadidae Barnea costata 0.70 Marine TEMP/TROP Bivalve Heterodonta Astartidae Astarte cf. montagui 4.42 Marine POLAR Bivavlia Heterodonta Cardiidae Cerastoderma edule 1.37 Marine TEMP/TROP Bivavlia Heterodonta Cardiidae Cerastoderma pinnulatum 1.40 Marine TEMP Bivavlia Heterodonta Cardiidae Laevicardium mortoni 1.30 Marine TROP Bivavlia Heterodonta Cardiidae Trachycardium quadragenarium 2.00 Marine TEMP Bivavlia Heterodonta Chamidae Chama pellucida 1.50 Marine TROP Bivalvia Heterodonta Corbiculidae Corbicula japonica 2.90 Freshwater Bivavlia Heterodonta Donacidae Donax variabilis 1.60 Marine TROP Bivalve Heterodonta Dreissenidae Dreissena polymorpha 1.74 Freshwater Bivavlia Heterodonta Lucinidae Phacoides pectinata 1.70 Marine TROP

188 | Bivaivia Heterodonta Mactidae Spisula sachalinensis 1.41 Marine [ TEMP Bivavlia Heterodonta Mactridae Spisula solidissima 1.18 Marine | TEMP Bivavlia Heterodonta Mactridae Tresus capax 1.64 Marine | POLAR Bivavlia Heterodonta Mactridae Tresus nuttalli 0.77 Marine TEMP Bivavlia Heterodonta Petricolidae Petricola pholadiformis 1.10 Marine POLAR/TEMP/TROP Bivavlia Heterodonta Pharidae Ensis directus 1.50 Marine I TEMP Bivavlia Heterodonta Psammobiidae Nuttallia nuttallii 1.67 Marine 1 POLAR Bivavlia Heterodonta Solecurtidae Tagelus califomianus 1.30 Marine TEMP/TROP Bivavlia Heterodonta j Solenidae Solen viridis 1.70 Marine I TROP Bivalve Heterodonta | Sphaeriidae Pisidium nitidum 3.06 Freshwater | POLAR/TEMP Bivalve Heterodonta | Sphaeriidae Pisidium rotundatum 4.19 Freshwater POLAR/TEMP Bivalve Heterodonta | Sphaeriidae Pisidium ventricosum 4.91 Freshwater POLAR/TEMP Bivavlia Heterodonta Tellinidae Apolymetis biangulata 2.30 Marine TEMP Bivalve Heterodonta Tellinidae Macoma balthica 1.94 Marine POLAR/TEMP Bivavlia Heterodonta Tellinidae Macoma nasuta 2.28 Marine TROP Bivavlia Heterodonta Tellinidae Macoma secta 2.40 Marine TEMP Bivavlia Heterodonta Tellinidae Macoma tenta 1.70 Marine Bivalve Heterodonta Thyasiridae Axinopsida orbiculata 2.27 Marine POLAR Bivaivia Heterodonta Veneridae Callithaca adamsi 1.97 Marine TEMP Bivavlia Heterodonta Veneridae Chione undatella 2.00 Marine TEMP Bivaivia Heterodonta Veneridae Dosinia japonica 2.02 Marine TEMP/TROP | Bivavlia Heterodonta Veneridae Mercenaria campechiensis 2.30 Marine TROP Bivavlia f Heterodonta Veneridae Mercenaria mercenaria 2.00 Marine TEMP/TROP

189 Bivavlia Heterodonta Veneridae Protothaca staminea 1.68 Marine TEMP Bivavlia Heterodonta Veneridae Saxidomus nuttalli 1.10 Marine TEMP Bivavlia Heterodonta Veneridae Tapes decussata 1.81 Marine TEMP Bivavlia Heterodonta Veneridae Tapes philippinarum 1.97 1 Marine POLAR/TEMP II Bivavlia Heterodonta Veneridae Tapes pullastra 1.78 | Marine TEMP Bivavlia Heterodonta Veneridae Tapes rhomboideus 1.62 I Marine Bivavlia Heterodonta Veneridae Tivela stultorum 0.96 | Marine TEMP Bivalvia Heterodonta Vesicomyidae Calyptogena magnifica 2.35 J Marine Bivavlia Palaeoheterodonta Unionidae Elliptio sp. 3.20 Freshwater Bivalve Palaeoheterodonta Unionidae Lasmigona compressa 3.99 Freshwater TEMP Bivavlia Palaeoheterodonta Unionidae Uniomerus sp. 3.00 Freshwater | Bivavlia Protobranchia Nuculidae Acila castrensis 5.40 Marine POLAR Bivalve I Protobranchia Nuculidae Ennucula tenuis 3.17 Marine POLAR Bivavlia Protobranchia Nuculidae Nucula proximo 3.10 Marine Bivavlia Protobranchia Solemyidae Solemya velum 2.10 Marine TEMP Bivalvia Pteriomorpha Arcidae Anadara broughtoni 1.45 Marine TEMP Bivalvia Pteriomorpha Arcidae Area boucardi 1.66 Marine TROP Bivavlia Pteriomorpha Noetiidae Noetia ponderosa 1.90 Marine TROP Bivavlia J Pteriomorpha Limidae Lima hemphillii 1.20 Marine TROP Bivavlia Pteriomorpha Limidae Lima scabra 1.60 Marine TROP Bivavlia Pteriomorpha Mytilidae Aulacomya ater maoriana 2.24 Marine TEMP Bivalvia Pteriomorpha Mytilidae Bathymodiolus azoricus 1.70 Marine Bivalvia | Pteriomorpha Mytilidae Bathymodiolus thermophilus 1.27 Marine

190 Bivavlia Pteriomorpha Mytilidae Botula falcata 1.80 Marine TEMP Bivalve Pteriomorpha Mytilidae Crenella faba 1.84 Marine POLAR Bivavlia Pteriomorpha Mytilidae Hormomya mutabilis 1.79 Marine TEMP Bivavlia Pteriomorpha Mytilidae | Lithophaga bisulcata 2.50 Marine TROP Bivavlia Pteriomorpha Mytilidae Lithophaga curta 2.12 Marine TEMP Bivavlia Pteriomorpha Mytilidae Lithophaga plumula 2.30 Marine TEMP Bivavlia Pteriomorpha Mytilidae Modiolus auriculatus 1.68 Marine TROP Bivalvia Pteriomorpha Mytilidae Modiolus kurilensis 3.40 Marine POLAR/TEMP 1 Bivavlia Pteriomorpha Mytilidae Modiolus sp. 1.90 Marine Bivavlia Pteriomorpha Mytilidae Musculista senhousia 1.16 Marine TEMP/TROP Bivavlia Pteriomorpha Mytilidae Mytilaster solidus 1.54 Marine TROP Bivavlia Pteriomorpha | Mytilidae Mytilus californianus 1.76 Marine TEMP/TROP Bivavlia J Pteriomorpha J Mytilidae Mytilus coruscus 1.90 Marine TEMP Bivalve | Pteriomorpha | Mytilidae Mytilus edulis 1.66 Marine POLAR/TEMP/TROP Bivavlia j Pteriomorpha Mytilidae Mytilus galloprovincialis 1.66 Marine TEMP Bivalvia J Pteriomorpha Mytilidae Mytilus gray anus 2.11 Marine TEMP Bivalvia I Pteriomorpha -Mytilidae Mytilus trossulus 1.40 Marine TEMP Bivavlia | Pteriomorpha Mytilidae Perna canaliculus 1.11 Marine TEMP Bivavlia Pteriomorpha Mytilidae Septifer keenae 1.06 Marine TEMP/TROP Bivavlia Pteriomorpha Mytilidae Septifer virgatus 1.08 Marine TROP Bivavlia Pteriomorpha Mytilidae Volsella modiolus 2.80 Marine POLAR/TEMP Bivavlia Pteriomorpha Mytilidae Volsella plicatulus 1.90 Marine TEMP Bivavlia Pteriomorpha Ostreidae | Crassostrea gigas 0.91 Marine POLAR/TEMP/TROP

191 Bivavlia Pteriomorpha Ostreidae Crassostrea virginica 0.69 Marine TEMP/TROP Bivavlia Pteriomorpha Ostreidae Cryptostrea permollis 1.10 Marine TROP Bivavlia Pteriomorpha Ostreidae Ostrea edulis 1.17 Marine TEMP Bivavlia Pteriomorpha Ostreidae Ostrea lurida 1.30 Marine TEMP Bivavlia Pteriomorpha Pectinidae Argopecten irradians 1.20 Marine TEMP Bivavlia Pteriomorpha Pectinidae Argopecten purpuratus 1.10 Marine TEMP Bivavlia Pteriomorpha Pectinidae Chlamys hastata 1.64 Marine POLAR/TEMP/TROP Bivavlia Pteriomorpha Pectinidae Chlamys hericus 0.95 Marine Bivavlia Pteriomorpha Pectinidae Chlamys hindsii 1.00 Marine POLAR/TEMP Bivavlia Pteriomorpha Pectinidae Chlamys opercularis 1.12 Marine TEMP Bivavlia Pteriomorpha Pectinidae Hinnites giganteus 1.29 Marine POLAR/TEMP/TROP Bivavlia Pteriomorpha Pectinidae Hinnites multirugosus 1.30 Marine Bivavlia Pteriomorpha Pectinidae Pecten maximus 1.42 Marine TEMP Bivavlia Pteriomorpha Pectinidae Placopecten magellanicus 2.10 Marine TEMP Bivalvia Pteriomorpha Pectinidae Mizuhopecten yessoensis 1.69 Marine TEMP/TROP Bivavlia Pteriomorpha Pinnidae Atrina rigida 1.10 Marine TEMP/TROP Gastropoda Caenogastropoda Ampullariidae Pomacea cuprina 0.67 Freshwater TROP Gastropoda Caenogastropoda Ampullariidae Pomacea paludosa 0.61 Freshwater TROP Gastropoda Caenogastropoda Diplommatinidae Arinia japonica 2.60 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina cassa 2.80 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina circumstomata 4.38 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina collarifera collarifera 6.34 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina collarifera okiensis 7.72 Terrestrial TEMP

192 ————— Caenogastropoda Diplommatinidae Diplommatina collarifera tenuiplica 6.19 Terrestrial TEMP Gastropoda Gastropoda Caenogastropoda Diplommatinidae Diplommatina gibbera 4.45 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina hidaensis 3.26 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae | Diplommatina kiiensis kiiensis 7.85 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae | Diplommatina kiiensis ssp. 6.17 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina kobelti 4.73 J Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina nipponensis 5.23 J Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina shikokuensis 5.56 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina sp. 3.93 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina tanegashimae kyushuensis 3.13 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina tosana goniobasis 3.93 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina tosana kureana 4.12 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina tosana onoensis 4.34 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina tosana tosana 6.09 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina tosanella abei 2.73 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Diplommatina tosanella tosanella 4.08 Terrestrial TEMP Gastropoda Caenogastropoda Diplommatinidae Palaina pusilla 1.94 Terrestrial TEMP Gastropoda Caenogastropoda Vivaparidae Cipangopaludina chinensis 4.12 Freshwater POLAR/TEMP Gastropoda Caenogastropoda Viviparidae Campeloma geniculum 1.73 Freshwater TEMP Gastropoda Caenogastropoda Viviparidae Campeloma limum 1.85 Freshwater TEMP Gastropoda Caenogastropoda Viviparidae Campeloma parthenum '* 2.54 Freshwater TEMP Gastropoda Caenogastropoda Viviparidae Viviparus contectus 2.04 Freshwater POLAR/TEMP Gastropoda Caenogastropoda Bithyniidae Bithynia sp. 1.25 Freshwater

193 Gastropoda | Caenogastropoda Cypraeidae Cypraea spadicea 1.60 Marine TROP Gastropoda J Caenogastropoda Hydrobiidae Hydrobia ulvae 0.68 Freshwater TEMP Gastropoda f Caenogastropoda Littorinidae Littorina irrorata 0.82 Marine TEMP Gastropoda Caenogastropoda Littorinidae Littorina keenae 0.90 Marine TEMP Gastropoda Caenogastropoda Littorinidae Littorina littorea 1.06 Marine POLAR Gastropoda Caenogastropoda Littorinidae Littorina neritoides 1.47 Marine POLAR Gastropoda Caenogastropoda Littorinidae Littorina neritoides 1.38 Marine Gastropoda Caenogastropoda Littorinidae Littorina obtusata 1.21 Marine TEMP | | Gastropoda Caenogastropoda Littorinidae Littorina punctata 0.81 Marine TROP Gastropoda Caenogastropoda Littorinidae Littorina saxatilis 1.38 Marine POLAR Gastropoda Caenogastropoda Littorinidae Tectarius muricatus 0.67 Marine TROP 1 Gastropoda Caenogastropoda Naticidae Polinices duplicatus 1.50 Marine TEMP 1 Gastropoda Caenogastropoda Naticidae Polinices heros 2.40 Marine TEMP | Gastropoda Caenogastropoda Vermetidae Aletes squamigerus 1.50 Marine TEMP/TROP Gastropoda Caenogastropoda Buccinidae Buscyon canaliculatum 4.40 Marine TROP Gastropoda Caenogastropoda Buccinidae Kelletia kelleti 3.70 Marine TEMP Gastropoda Caenogastropoda Buccinidae Neobuccinum eatoni 5.88 Marine POLAR Gastropoda Caenogastropoda Cancellariidae Admete viridula 5.73 Marine POLAR Gastropoda Caenogastropoda Conidae Conus californicus 2.60 Marine TEMP Gastropoda Caenogastropoda Conidae Con us livid us 3.90 Marine TROP Gastropoda Caenogastropoda Conidae Conus pennaceus 3.60 Marine TROP Gastropoda Caenogastropoda Conidae Oenopota bicarinata 3.91 Marine POLAR Gastropoda Caenogastropoda Conidae Oenopota spl 3.49 Marine POLAR

194 Gastropoda Caenogastropoda Conidae Propebela turricula | 3.96 Marine POLAR Gastropoda Caenogastropoda Mitridae Mitra idae [ 2.70 Marine TEMP Gastropoda Caenogastropoda Muricidae Bolinus brandaris 2.83 Marine TROP Gastropoda Caenogastropoda Muricidae Ceratostoma nuttalli 2.40 Marine TEMP Gastropoda Caenogastropoda Muricidae Hexaplex trunculus 2.26 Marine TROP Gastropoda Caenogastropoda Muricidae Nucella canaliculate! 2.54 Marine POLAR Gastropoda Caenogastropoda Muricidae Nucella emarginata 2.75 Marine POLAR/TEMP Gastropoda Caenogastropoda Muricidae Nucella lamellosa 2.43 Marine POLAR/TEMP Gastropoda Caenogastropoda Muricidae Nucella lapillus 2.73 Marine TEMP Gastropoda Caenogastropoda Muricidae Ocenebra erinaceus 2.61 Marine POLAR/TEMP Gastropoda Caenogastropoda Muricidae Ocenebra poulsoni 2.60 Marine TEMP/TROP Gastropoda Caenogastropoda Muricidae Thais haemastoma 2.09 Marine TROP Gastropoda Caenogastropoda Muricidae Urosalpinx cinerea 3.10 Marine POLAR/TEMP Gastropoda Caenogastropoda Nassariidae Nassarius fossatus 4.40 Marine POLAR/TEMP Gastropoda Caenogastropoda | Nassariidae Nassarius obsoletus 3.20 Marine POLAR/TEMP Gastropoda Caenogastropoda Nassariidae Nassarius tegula 3.90 Marine TEMP Gastropoda Caenogastropoda Olividae Olivella biplicata 2.00 Marine POLAR/TEMP Gastropoda Caenogastropoda Pleuroceridae Goniobasis alabamensis 2.10 Freshwater Gastropoda Caenogastropoda Pleuroceridae Goniobasis catenaria dislocata 2.10 Freshwater TEMP Gastropoda Caenogastropoda Pleuroceridae Goniobasis floridensis 2.10 Freshwater TEMP Gastropoda Caenogastropoda Pleuroceridae Goniobasis livescens 2.10 Freshwater POLAR/TEMP Gastropoda Caenogastropoda Pleuroceridae Goniobasis proximo 2.10 Freshwater TEMP Gastropoda Caenogastropoda Pleuroceridae Goniobasis simplex 2.10 | Freshwater | POLAR/TEMP

195 Gastropoda Caenogastropoda Pleuroceridae lofluvialis 2.10 Freshwater POLAR/TEMP Gastropoda Caenogastropoda Pleuroceridae Juga hemphilli 2.10 Freshwater TEMP Gastropoda Caenogastropoda Pleuroceridae Leptoxis (Mudalia) carinata 2.10 Freshwater POLAR/TEMP Gastropoda Caenogastropoda Pleuroceridae Leptoxis praerosa 2.10 Freshwater POLAR/TEMP Gastropoda Caenogastropoda Pleuroceridae Lithasia duttoniana 2.10 Freshwater TEMP Gastropoda Caenogastropoda Pleuroceridae Lithasia verrucosa 2.10 Freshwater TEMP Gastropoda Caenogastropoda | Pleuroceridae Pleurocera acuta 2.10 Freshwater TEMP Gastropoda Caenogastropoda Pleuroceridae Pleurocera canaliculatum 2.10 Freshwater TEMP/TROP Gastropoda Caenogastropoda Pleuroceridae Pleurocera unciale 2.10 Freshwater TEMP Gastropoda Caenogastropoda Thiaridae Melanoides tuberculatus 6.65 Freshwater TEMP Gastropoda Provannidae Alviniconcha hessleri 0.94 Marine Gastropoda 1 Provannidae Ifremeria nautilei 0.90 Marine Gastropoda Heterobranchia Aplysiidae Aplysia californica 1.90 Marine TROP Gastropoda Heterobranchia Aplysiidae Aplysia dactylomela 1.90 Marine TROP Gastropoda Heterobranchia Lymnaeidae Fossaria exigua 1.14 Freshwater POLAR/TEMP Gastropoda Heterobranchia Lymnaeidae Fossaria modicella 4.4 Freshwater POLAR/TEMP Gastropoda Heterobranchia Lymnaeidae Fossaria parva 2.47 Freshwater POLAR/TEMP Gastropoda Heterobranchia Lymnaeidae Lymnaea auricularia 1.51 Freshwater TEMP Gastropoda Heterobranchia Lymnaeidae Lymnaea calamphala 1.22 Freshwater Gastropoda Heterobranchia Lymnaeidae Lymnaea fontinalis 1.32 Freshwater TEMP Gastropoda Heterobranchia Lymnaeidae Lymnaea fulva 1.30 Freshwater TEMP Gastropoda Heterobranchia Lymnaeidae Lymnaea sp. 2.00 Freshwater Gastropoda Heterobranchia Lymnaeidae Lymnaea stagnalis 1.13 Freshwater POLAR/TEMP | Gastropoda Heterobranchia Lymnaeidae Stagnicola elodes 1.2 Freshwater POLAR/TEMP Gastropoda Heterobranchia Physidae Aplexa elongata 1.6 Freshwater POLAR/TEMP Gastropoda Heterobranchia Physidae Physa jennessi 0.98 Freshwater POLAR/TEMP Gastropoda Heterobranchia Physidae Physa rubra 1.20 Freshwater POLAR Gastropoda j Heterobranchia Planorbidae Biomphalaria glabrata 0.95 Freshwater TROP Gastropoda | Heterobranchia Planorbidae Gyraulus circumstriatus 1.76 Freshwater POLAR/TEMP Gastropoda Heterobranchia Planorbidae Helisoma campanulatum 2.53 Freshwater POLAR Gastropoda Heterobranchia Planorbidae Planorbella tenuis 1.48 Freshwater TEMP/TROP Gastropoda Heterobranchia Planorbidae Planorbis corneus 1.25 Freshwater TEMP Gastropoda Heterobranchia Planorbidae Planorbis planorbis 1.43 Freshwater TEMP Gastropoda Heterobranchia Planorbidae Promenetus exacuous 0.49 Freshwater POLAR/TEMP Gastropoda Heterobranchia Bullidae Bulla gouldiana 1.60 Marine POLAR/TEMP/TROP Gastropoda | Heterobranchia Valvatidae Valvata sincera helicoidea 1.5 Freshwater POLAR Gastropoda j Heterobranchia Aeolidiidae Aeolidia papillosa 1.20 Marine TEMP Gastropoda | Heterobranchia Arminidae Armina californica 1.00 Marine POLAR/TEMP/TROP Gastropoda | Heterobranchia Dorididae Archidoris montereyensis 2.00 Marine POLAR/TEMP Gastropoda I Heterobranchia Dorididae Dorididae sp 1.31 Marine Gastropoda j Heterobranchia Flabellinidae Flabellina iodinea 0.71 Marine TEMP/TROP Gastropoda j Heterobranchia Tergipedidae Phestilla sp. 0.91 Marine Gastropoda | Heterobranchia Stiligeridae Stiliger felinus 2.83 Marine TROP Gastropoda | Heterobranchia Achatinidae Achatina fulica 2.25 Terrestrial TROP Gastropoda I Heterobranchia Euconulidae Euconulus fulvus 1.79 Terrestrial POLAR/TEMP Gastropoda | Heterobranchia | Helicidae Arianta arbustorum 2.84 Terrestrial TEMP . ,

197 Gastropoda Heterobranchia Helicidae Cantareus aspersus 3.58 Terrestrial TEMP/TROP Gastropoda Heterobranchia Helicidae Cantareus mazzullii 3.08 Terrestrial TEMP | Gastropoda Heterobranchia Helicidae Cepaea nemoralis 4.22 Terrestrial POLAR/TEMP/TROP 1 Gastropoda Heterobranchia Helicidae Helix vulgaris 4.00 Terrestrial TEMP 1 Gastropoda Heterobranchia Hygromiidae Trichia hispida 2.49 Terrestrial TEMP Gastropoda Heterobranchia Limacidae Deroceras laeve 1.87 Terrestrial POLAR/TEMP/TROP Gastropoda Heterobranchia Limacidae Deroceras reticulatum 1.68 Terrestrial TEMP/TROP Gastropoda Heterobranchia Succineidae Succinea putris 2.92 Terrestrial TEMP Gastropoda Heterobranchia Succineidae Succinea spl 1.46 Terrestrial Gastropoda Heterobranchia Succineidae Succinea sp2 0.95 Terrestrial 1 Gastropoda Heterobranchia Vertiginidae Vertigo sp. 1.52 Terrestrial 1 Gastropoda Patellogastropoda Acmaeidae Acmaea mitra 0.94 Marine POLAR/TEMP 1 Gastropoda Patellogastropoda Acmaeidae Collisella digitalis 0.61 Marine TEMP Gastropoda Patellogastropoda | Acmaeidae Collisella limatula 0.56 Marine TEMP Gastropoda Patellogastropoda Acmaeidae Collisella paradigitalis 0.58 Marine TROP Gastropoda Patellogastropoda | Acmaeidae Collisella scabra 0.57 Marine TEMP Gastropoda Patellogastropoda Lottiidae Lottia gigantea 0.43 Marine TEMP Gastropoda Patellogastropoda Lottiidae Tectura testudinalis 0.57 Marine TEMP Gastropoda Lottiidae Testudinalia testudinalis 0.6 Marine TEMP Gastropoda Vestigastropoda Fissurellidae Diodora aspera 1.50 Marine POLAR/TEMP Gastropoda Vestigastropoda Fissurellidae Fissurella barbadensis 0.50 Marine TROP Gastropoda Vestigastropoda Fissurellidae Fissurella volcano 0.65 Marine TEMP Gastropoda Vestigastropoda Fissurellidae Megathura crenulata 1.90 Marine TEMP

198 1 Gastropoda Vestigastropoda Haliotidae Haliotis corrugata 2.07 Marine TROP | Gastropoda Vestigastropoda Haliotidae Haliotisfulgens 1.70 Marine TEMP Gastropoda Vestigastropoda Haliotidae Haliotis rufescens 1.81 Marine TEMP | Gastropoda Vestigastropoda Lepetodrilidae Lepetodrilus sp. 1.80 Marine | 1 Gastropoda Vestigastropoda Lepetodrilidae Leptodrilus atlanticus 1.04 Marine 1 Gastropoda Vestigastropoda Lepetodrilidae Pseudorimula midatlantica 1.05 Marine 1 Gastropoda Vestigastropoda Trochidae Margarites costalis 5.32 Marine POLAR 1 Gastropoda Vestigastropoda Trochidae Margarites helicinus 1.68 Marine POLAR Gastropoda Vestigastropoda Trochidae Norrisia norrisi 1.60 Marine TEMP | Gastropoda Vestigastropoda Trochidae Tegula brunnea 1.70 Marine TROP | Gastropoda Vestigastropoda Trochidae Tegula funebralis 1.50 Marine TROP | 1 Gastropoda Vestigastropoda Turbinidae Potrolira sp. 0.70 Marine 1 Gastropoda Vestigastropoda Turbiniidae Astraea undosa 2.30 Marine TEMP

*Data derived from WoRMS - World Registry of Marine Species [www.marinespecies.org]; IUCN - International Unit for Conservation of Nature

[www.iucn.org]; Gbif - Global Biodiversity Information Facility [data.gbif.org/species/]; Marine Species Identification Portal [species-

indentification.org]; and EOL- Encyclopedia of Life [www.eol.org] Appendix 3.5. Supplementary material on the construction qf the phylogenetic trees. A detailed description of each phylogenetic hypothesis used is given below.

Contents:

1. General procedures on the assemblage of the phylogenies 2. Heterobranchia: Pulmonata trees 3. Gastropoda tree 4. Bivalvia tree 5. References

1. General procedures on the assemblage of the phytogenies

Molluscs represent the second largest and most species-rich animal phylum. As such,' no single phylogenetic tree containing all the species analyzed in this study was available. In order to accommodate all groups examined, phylogenies were built at the familial level from several published sources. The results presented hereafter should be interpreted with caution as they represent current hypotheses of the relationships between families, which are not yet all fully resolved and well supported. A few general procedures were considered in the construction of all trees presented in this chapter:

1) Families were placed in polytomies in cases where phylogenetic relationships were

uncertain or where incongruence existed between studies.

2) Recent molecular phylogenetic studies containing large taxonomic and genetic sampling

were preferred in the assemblage of most trees, with the exception of the

Heterobranchia: Pulmonata where phylogenetic trees based on morphological

characters were also used.

' 3) Taxonomic relationships unsupported by the phylogenies were still included in the trees

and phylogeny was taken as overriding taxonomy in those cases.

200 2. Heterobranchia: Pulmonata trees

• Relationships among the major groups within Stylommatophora (terrestrial species) were

taken from Wade et alv (2001, 2006). These relationships closely support the current

taxonomy at the familial and super-familial levels within the group. The original tree was

based on a Bayesian hypothesis of 823 unambiguous aligned nucleotide sites from the LSU;

28S rRNA gene. It included 160 species belonging to 60 families.

• In order to provide a complete representation of the Stylommatophora, additional families

were added to the phylogeny based on the taxonomy of Bouchet et al. (2005). Since direct

evidence for these families' placement within the phylogeny was not available, they were

added as polytomies based on taxonomic relationships.

• This assembled relationship was used in conjunction with several hypothetic phylogenies for

the Pulmonata, in order to determine the nature of the relationship between freshwater

and terrestrial gastropods.

Tree #1 - Salvin-Plawen, J. and Steiner, G. 1996.

• The first hypothetical relationship among the Pulmonata included in this study was derived

from Salvini-Plawen and Steiner (1996). This relationship was based on the cladistics analysis

of several morphological characters. This study was preferred over other morphological

analysis of pulmonates for their broad taxon sampling, large number of characters

inspected, and for being the first to provide a cladistics analysis for the Pulmonata (Dayrat

and Tillier, 2002).

201 Tree #2 - Dayrat, B. and Tillier, S. 2002

• The morphological phylogeny derived from Dayrat and Tillier (2002) was the second

hypothesis included in this study. Their final topology consisted of a strict consensus tree of

3446 equally parsimonious trees. The phylogeny was preferred over other morphological

studies, due to greater taxon coverage. In total, 75 taxon and 77 morphological characters

were included in the data matrix.

Tree #3 - Klussmann-Kolb, A., Dinapoli, A., Kuhn, K., Streit, B., Albrecht. C. 2008.

• The first molecular phylogeny included in this study to examine the Pulmonata relationship

was derived from Klussmann et al., 2008. The authors used sequences of nuclear 18S rRNA

and 28S rRNA as well as mitochondrial 16S rRNA and COI DNA to construct two phylogenies

using Maximum Likelihood and Bayesian inference methods. Both analyses supported a

similar topography; therefore the phylogeny presented here was assembled from a Bayesian

analysis phylogram. In total 56 taxa were included in the original study.

Tree #4 - Holznagel, W.E., Colgan, D.J. and Lvdeard, C. 2010

• The last tree selected for the analysis of freshwater and terrestrial pulmonates was derived

from Holznagel et al., 2010. This molecular topology was based on Bayesian inference

method on 28S rRNA gene sequences. This study was preferred over other phylogenetic

hypotheses because of their great taxonomic coverage of both freshwater and terrestrial

species.

202 3- Gastropoda tree

• The class Gastropoda is often divided into 6 major groups: the Patellogastropoda, the

Cocculiniformia, the Vestigastropoda, the Neritimorpha, the Caenogastropoda, and the

Heterobranchia (Aktipis et al, 2008). Large phylogenies incorporating robust sampling of all

groups are lacking; therefore, this study relied on multiple sources in order to construct the

Gastropoda topology presented.

• Relationships among the major taxon groups and relationships within Cocculiniformia and

Patellogastropoda represented in this study were taken from Aktipis et al. (2008). This

phylogeny was based on a combination of morphological and molecular data and included

all major families within Cocculiniformia and Patellogastropoda examined in this study.

• Relationships within the Vestigastropoda were taken from Geiger and Thacker (2005). This

phylogeny was based on a combination of molecular sequences including COI, H3, and 18S

rRNA. In total 38 species in 15 families were included in the original phylogeny, accounting

for all families analyzed in this study.

• Since no genome size records exist for the Neritimorphians, this clade was not investigated

phylogenetically. Representatives of this clade were included in the final tree as a large

polytomy. This is because the relationship within Neritimorphia was not essential in the

current analysis; however, its position within the Gastropoda tree was important in

determining the overall topology of the tree.

• Relationships within Caenogastropoda included in this study, were taken from Colgan et al.

(2007). This study was preferred as it represents the only comprehensive multi-gene

phylogenetic analysis in the group. Molecular sequences were collected from 18S rRNA, 28S

rRNA, 12S rRNA, COI, and H3 for 29 Caenogastropoda families.

203 • All families examined in this study were included in the final Gastropoda tree, despite

caenogastropods remaining poorly represented. This clade is considered the most diverse

among gastropods, with more than 190 families described. Most of these families have

never been investigated phylogenetically, and including them in the tree would result in a

very large polytomy.

• Major relationships between the Heterodonta were derived from Holznagel et al (2010).

Their study used large sample sizes including most of the taxa examined here with the

exception of the Nudibranchia. Relationships in the Nudibranchia group were taken from

Wollscheid-Lengeling et al (2001). This phylogenetic hypothesis contained all the families

examined in this study and therefore was the preferred topology.

• Similarly to the caenograstropods, many families for which phylogenetic relationships were

not available were left out of the final tree to avoid large polytomies. In addition the

Pulmonata clade was not included in this phylogeny, since it was constructed separately for

the analysis between freshwater and terrestrial snails.

4 - Bivalvia tree

• The topology for the major groups within bivalves was derived from Giribet and Wheeler

(2002). This phylogenetic hypothesis was based on a combination of morphological

characters and molecular sequences, consisting of 183 characters and 3 genes, respectively.

A total 42 families were included in the phylogeny, covering all families examined in this

study.

• Some families were added as polytomies to the tree based on taxonomic relationships in

order to complement the topology.

204 5-References

Aktipis SW, Giribet G, Lindberg DR, Ponder WF. 2008. Gastropoda: an overview and analysis. In:

W. F. Ponder, D. R. Lindberg, eds. Phylogeny and Evolution of the Mollusca. Berkely:

University of California Press, 201-238.

Colgan DJ, Ponder WF, Beacham E, Macaranas J. 2007. Molecular phylogenetics of

Caenogastropoda (Gastropoda: Mollusca). Molecular Phylogenetics and Evolution 42:

717-37.

Dayrat B, Tillier S. 2002. Evolutionary relationships of euthyneuran gastropods (Mollusca): a

cladistic re-evaluation of morphological characters. Zoological Journal of the Linnean

Society 135: 403-470.

Geiger DL, Thacker CE. 2003. Molecular phylogeny of Vetigastropoda reveals non-monophyletic

Scissurellidae, Trochoidea, and Fissurelloidea. Molluscan Reseach 25: 47-55.

Giribet G, Wheeler W, Wheeler W. 2011. Morphology and DNA sequence data on bivalve

phylogeny : a high-level analysis of the Bivalvia ( Mollusca ) data. Society 121: 271-324.

Holznagel WE, Colgan DJ, Lydeard C. 2010. Molecular phylogenetics and evolution Pulmonate

phylogeny based on 28S rRNA gene sequences: A framework for discussing habitat

transitions and character transformation. Molecular Phylogenetics and Evolution 57:

1017-1025.

205 Klussmann-Kolb A, Dinapoli A, Kuhn K, Streit B, Albrecht C. 2008. From sea to land and beyond-

new insights into the evolution of euthyneuran Gastropoda (Mollusca). BMC

Evolutionary Biology 8: 57.

Salvini-Plawen L, Steiner G. 1996. Synapomorphies and pleisiomorphies in higher classification

of Mollusca. In: JD Taylor, ed. Origin and Evolutionary Radiation of the Mollusca. Oxford:

Oxford University Press, 29-51.

Wade GM, Mordan PB, Naggs F. 2006. Evolutionary relationships among the Pulmonate land

snails and slugs (Pulmonata, Stylommatophora). Biological Journal of the Linnean Society

87: 593-610.

Wollscheid-Lengeling E, Boore JL, Brown W, Wagele H. 2001. The phylogeny of Nudibranchia

(Opisthobranchia, Gastropoda, Mollusca) reconstructed by three molecular markers.

Organisms Diversity & Evolution 1: 241-256.

206 Appendix 3.6. Detail listings on the statistical analysis used in case study two. Data for the individual parameters were tested using the Shapiro-Wilk test and normality was assumed when p-values were larger than 0.01 (Park, 2008). In cases where normality could be assumed, parametric tests were performed while non-parametric tests when assumptions for normality were not met based on Shapiro-Wilk test. These tests were then chosen automatically by SPSS based on the most suitable analysis for the data. Each comparison and a detail record of the statistical analysis used are presented below.

Genome size and shifts from freshwater to terrestrial habitats

Shapiro-Wilk normality test Mann-Whitney U test

Freshwater p=0.65 p-value T . , „ ™, p<0.05 Terrestna p<0.001 K

Genome size and shits from marine to freshwater habitats (gastropods)

Shapiro-Wilk normality test Mann-Whitney U test

Freshwater pO.OOl _ „_ p-value .. . „„„„ p>0.10 Marine p<0.001 ^

Genome size and shifts from marine to freshwater habitats (bivalves)

Shapiro-Wilk normality test Mann-Whitney U test

Freshwater p=0.78 p-value ... „„„„ p<0.001 Marine p<0.001

207 Genome size and latitudinal ranges in gastropods \AT\\t Friedman's two- Kruskal-Wallis test way analysis of normality test variance

1 . Tropical pO.Ol . rt.r „ , p-value K y p<0.005 p<0.05

p-values for all other latitudinal ranges were larger than 0.01, indicating that all but tropical species had a normal distribution 2 Differences between polar, temperate and tropical species were examined with Friedman's two-way analysis of varience, revealing polar species were significantly different from temperate and tropical species

Genome size and latitud inal ranges in bivalves

Shapiro-Wilk normality test Kruskal-Wallis test

Polar p^.011 p-value p>0.05

p-values for temperate and tropical species were larger than 0.01, indicating that only polar estimates did not exhibit a normal distribution

208 Appendix 3.7. Barcode tree of most gastropod species collected and analysed in this study. All barcodes can be found in the Barcode of Life Data Systems (BOLD) websites: www.boldsystems.org, under the project Mollusca of Churchill [PPCHU]. The tree illustrated two cases (Margarites and Fossaria), where genomes appear to have duplicated (and triplicated) between species of the same genus. Note that within Margarites the two species in question are still most closely related, however within Fossaria, it appear quantum shifts in genome size are accompanied by large evolutionary distances. A more detail analysis on these findings is beyond the scope of this study.

209 2%

Margarites costalis (lC=5.32pg)

Margarites helicinus (lC=1.68pg)

Oenopta sp.l (lC=3.49pg)

Littorina saxatilis (lC=1.42pg)

Oenopta bicarinata (lC=3.91pg)

Propebela turricula (lC=3.96pg)

Valvata sincera (lC=1.5pg)

Physajennesi (lC=0.98pg)

Fossaria parva (1C= 2.47pg)

Lymnaea stagnalis (lC=1.04pg) Fossaria exigua (lC=1.14pg) Stagnicola elodes (lC=1.2pg)

Aplexa elongata (lC=1.6pg)

Deroceras laeve (lC=1.87pg)

Euconulusfulvus (lC=1.79pg)

Fossaria modicella (lC=4.4pg)

Vertigo sp. (lC=1.52pg)

Gyraulus circumstriatus (lC=1.76pg)

Promenetus exacuous (lC=0.49pg)

Promenetus exacuous (lC=1.06pg)