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2014 The Maintenance of Polymorphism by Behavioral and Genomic Plasticity in Mate Preference Ilana L. Janowitz

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COLLEGE OF ARTS AND SCIENCES

THE MAINTENANCE OF POLYMORPHISM BY BEHAVIORAL

AND GENOMIC PLASTICITY IN MATE PREFERENCE

By

ILANA L. JANOWITZ

A Dissertation submitted to the Department of Biological Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy

Degree Awarded: Spring Semester, 2014 Ilana L. Janowitz defended this dissertation on March 24, 2014. The members of the supervisory committee were:

Kimberly A. Hughes Professor Directing Dissertation

James F. Johnson University Representative

Emily DuVal Committee Member

Emily Lemmon Committee Member

Joseph Travis Committee Member

The Graduate School has verified and approved the above-named committee members, and certifies that the dissertation has been approved in accordance with university requirements.

ii

Dedicated to my parents, Harlan Janowitz and Sherry Janowitz.

iii ACKNOWLEDGMENTS

Graduate school has provided me with the confidence and skills to move forward in life. Without the help of the following people, I would not have accomplished my graduate degree.

- I would first and foremost like to thank God. Without His grace, forgiveness, and gentle guidance, I would not have the perseverance to accomplish my goals. I can only hope that the occupation that he has provided for me will, somehow, serve Him. - My parents, Harlan and Sherry Janowitz. Education was overly emphasized throughout my life. Everything that I am and everything that I need, I have received from my parents. They have never fallen short and I know they never will. - My advisor, Dr. Kimberly Hughes. She has pushed me to be the best scholastic version of myself. She took a leap of faith when she accepted me as a graduate student and I am very grateful for the chance to follow in her footsteps. - My partner, Robby- my favorite person. He has taught me a new way of existing in this world. With the love and the joy that he brings to my life, I can never have a bad day. - Jason, my best friend since childhood. He is my rock and the only one that really knows me. I am truly blessed to have someone in my life that never turns away. - Brittany, my best lady friend. She has been my sister throughout my time in graduate school. I am honored to know her and proud to call her a friend. - My Committee: o Joe Travis: He is an inspirational man. Although he is not my advisor, I have always strived to make him proud. He is not only extremely sharp, intelligent, and levelheaded; he is simply a nice person. o Frank Johnson: He is the reason why I am in graduate school. He believed in me before I believed in myself. o Emily DuVal: She has inspired me to stay true to my roots as an animal behaviorist. Her suggestions are always so crisp and clear. Whenever I leave her office, I know that I’ll spend the next few hours in deep thought.

iv o Emily Lemmon: Her dual role as a fruitful scientist and mother is extremely inspirational. While we have had many work-related discussions, I have always been most excited to chat with her about family. - Dr. James C. Smith: I worked as a lab tech for him before beginning graduate school. He is not only my academic grandfather; he is also a true mentor and inspirational teacher. I am honored to know him. - Judy Bowers: She has always been extremely helpful and insightful. She is the anchor of the department. - Sandy Heath: I am so grateful to have had the chance to meet and know Sandy. Without his constant technical support, the lab would not be standing today. - Finally, I would like to thank NSF for my funding and the Department of Biological Science.

v TABLE OF CONTENTS

List of Tables ...... x

List of Figures ...... xii

Abstract ...... xiv

1 INTRODUCTION...... 1

1.1 Background ...... 1

1.2 Study System ...... 2

1.3 Dissertation Goals & Summary of Chapters ...... 5

1.3.1 Dissertation Goals ...... 5

1.3.2 Summary of Chapters ...... 6

1.3.2.1 Chapter 2 ...... 6

1.3.2.2 Chapter 3 ...... 7

1.3.2.3 Chapter 4 ...... 7

2 MOLECULAR MECHANISMS UNDERLYING NOVEL MALE PREFERENCE IN THE FEMALE GUPPY ...... 8

2.1 Introduction ...... 8

2.2 Methods ...... 10

2.2.1 Ethics Statement ...... 10

2.2.2 Behavioral Methods ...... 10

2.2.2.1 Overview ...... 10

2.2.2.2 Experimental Fish ...... 11

2.2.2.3 Behavioral Paradigm ...... 11

2.2.2.4 Data Analyses ...... 13

2.2.3 Brain Gene Expression Methods ...... 13

vi 2.2.3.1 Brain Dissections ...... 13

2.2.3.2 RNA Sequencing Library Preparation ...... 14

2.2.3.3 Transcriptome Assembly and Annotation ...... 15

2.2.3.4 RNA Sequence Analysis ...... 16

2.2.3.5 Statistical Analyses ...... 16

2.2.3.6 Functional Enrichment Analyses ...... 17

2.2.3.7 qPCR Gene Validation ...... 18

2.3 Results ...... 19

2.3.1 Behavioral Results ...... 19

2.3.2 Gene Expression Results ...... 22

2.4 Discussion & Conclusions ...... 26

3 THE BEHAVIORAL MECHANISMS DRIVING FEMALE GUPPY MATE PREFERENCE ...... 31

3.1 Introduction ...... 31

3.2 Methods ...... 32

3.2.1 Ethics Statement ...... 32

3.2.2 Behavioral Methods ...... 33

3.2.2.1 Overview ...... 33

3.2.2.2 Experimental Fish ...... 33

3.2.2.3 Object Preference Trials ...... 34

3.2.2.4 Food Preference Trials ...... 35

3.2.3 Data Analyses ...... 36

3.2.3.1 Male Object Experiment ...... 36

3.2.3.2 Female Object Experiment ...... 37

3.2.3.3 Male Food Experiment ...... 37

3.2.3.4 Female Food Experiment ...... 37

vii 3.3 Results ...... 38

3.3.1 Male Object Experiment ...... 38

3.3.2 Female Object Experiment ...... 38

3.3.3 Male Food Experiment ...... 39

3.3.4 Female Food Experiment ...... 39

3.4 Discussion & Conclusions ...... 44

4 FEMALE PREFERENCE IN POECILIA PICTA ...... 47

4.1 Introduction ...... 47

4.2 Methods ...... 48

4.2.1 Ethics Statement ...... 48

4.2.2 Behavioral Methods ...... 49

4.2.2.1 Overview ...... 49

4.2.2.2 Experimental Fish ...... 49

4.2.2.3 Behavioral Paradigm: Mate Color Preference Experiment ...... 50

4.2.2.4 Behavioral Paradigm: Novel Morph Preference Experiment ...... 51

4.2.2.5 Behavioral Characterization ...... 52

4.2.3 Data Analyses ...... 54

4.2.3.1. Mate Color Preference Experiment ...... 55

4.2.3.2. Novel Morph Preference Experiment ...... 55

4.3 Results ...... 55

4.3.1 Mate Color Preference Experiment ...... 55

4.3.2 Novel Morph Preference Experiment ...... 56

4.4 Discussion & Conclusions ...... 61

5 CONCLUSION ...... 64

viii APPENDICES ...... 66

A. ANIMAL CARE LETTER OF APPROVAL ...... 66

B. EXAMPLES OF FAMILIAR AND NOVEL MALE PAIRS ...... 67

C. A PRIORI LIST OF NOVELTY-SEEKING GENES ...... 69

D. RESULTS OF TREATMENT (NOVEL / FAMILIAR) AND PREFERENCE ANALYSES ...... 70

References ...... 81

Biographical Sketch ...... 94

ix LIST OF TABLES

Table 2.1 List of primer sequences used in the qPCR validation assays ...... 19

Table 2.2 Results of general linear model of the proportion of positive responses towards male displays for each female during 30 minutes ...... 20

Table 2.3 Results of general linear model of the average response score towards male displays for each female during 30 minutes ...... 20

Table 2.4 Results of general linear model of the raw count data and fold changes for each gene in each treatment group in the RNA-seq data analysis...... 24

Table 2.5 Gene Ontology (GO) table for Novel vs. Familiar analysis ...... 25

Table. 2.6 GO table for preference analysis ...... 25

Table 2.7 qPCR results of general linear model of the relative quantification (RQ) for each gene in each treatment group ...... 26

Table 3.1 Summary of 4 behavioral experiments ...... 36

Table 3.2 Results of general linear model showing the effects of novel object preference (measured by total time In Zone) in male guppies ...... 39

Table 3.3 Results of general linear model showing the effects of novel object preference in female guppies ...... 40

Table 3.4 Results of general linear model showing the effects of novel food preference in male guppies ...... 40

Table 3.5 Results of general linear model showing the effects of novel food preference in female guppies ...... 40

Table 4.1. Behavioral characterization of P. picta female behavioral states ...... 53

Table 4.2 Behavioral characterization of P. picta female behavioral events ...... 54

Table 4.3 Results of general linear model in the mate color preference experiment showing the effects of focal male color and observer on the log-transformed number of female approaches ...... 56

Table 4.4 Results of general linear model in the mate color preference experiment showing the effects of focal male color and observer on the total time ‘In Zone’ < 3 body lengths (seconds) ...... 57

x Table 4.5 Results of general linear model in the mate color preference experiment showing the effects of focal male color and observer on the total time swimming (seconds) ...... 57

Table 4.6 Results of general linear model in the mate color preference experiment showing the effects of focal male color and observer on the total time frozen (seconds) ...... 57

Table 4.7 Results of general linear model in the novel morph preference experiment showing the effects of treatment and pair color on the log-transformed number of female approaches...... 58

Table 4.8 Results of general linear model in the novel morph preference experiment showing the effects of treatment and pair color on the total time ‘In Zone’ < 3 body lengths (seconds) ...... 58

Table 4.9 Results of general linear model in the novel morph preference experiment showing the effects of treatment and pair color on the total time swimming (seconds) ...... 58

Table 4.10 Results of general linear model in the novel morph preference experiment showing the effects of treatment and pair color on the total time frozen (seconds) ...... 59

Table C.1 List of genes related to novelty-seeking or exploratory behavior generated from other behavioral genomic studies...... 69

Table D.1 List of 165 genes differentially expressed in females exposed to males with novel versus familiar color patterns ...... 70

Table D.2 List of 99 genes that showed a significant relationship with gene expression ...... 78

xi LIST OF FIGURES

Figure 1.1 Guppy males from a single population ...... 4

Figure 1.2 Example of male guppies from each Iso-male line used for behavioral experiments ...... 4

Figure 1.3 Example of male P. picta ...... 5

Figure 2.1 Female preference for males with novel and familiar color patterns ...... 21

Figure 2.2 Number of genes significantly upregulated in the novel and familiar treatment groups ...... 23

Figure 2.3 Number of genes that show a significant positive or negative relationship with average preference score, as measured using the average response variable from behavior analyses...... 24

Figure 3.1 Representation of experimental tank set-up ...... 36

Figure 3.2 Response to individual objects in male guppies ...... 41

Figure 3.3 Response to each object varied by treatment group in male guppies ...... 41

Figure 3.4 Response to each object varied by treatment group in female guppies...... 42

Figure 3.5 Assessment of objects for each female reproductive state...... 42

Figure 3.6 Response to each food source varied by treatment group in male guppies...... 43

Figure 3.7 Response to each food source varied by treatment group in female guppies...... 43

Figure 4.1 LS Mean + SE Number of female approaches towards each focal male color in the mate color preference experiment ...... 59

Figure 4.2 LS Mean + SE Number of female approaches towards novel or familiar male pairs in the novel morph preference experiment ...... 60

Figure 4.3 LS Mean + SE Total time swimming for females presented with each pair color in each treatment group in the novel morph preference experiment ...... 60

Figure 4.4 LS Mean + SE Total time frozen for females presented with each pair color in each treatment group in the novel morph preference experiment ...... 61

Figure B.1 Example of ‘Familiar’ male pairs ...... 67

xii Figure B.2 Example of ‘Novel’ male pairs ...... 68

xiii ABSTRACT

The maintenance of genetic variation in traits that are closely tied to fitness, despite evolutionary forces expected to reduce variation, is a long-standing paradox in evolutionary biology. Under simple population genetic models, genetic variation will be determined by a balance between the input of new variation through mutation and the elimination of variation by selection and genetic drift; however, the ability of these forces to generate and maintain the high variation found in natural populations is a continuing debate. Frequency-dependent selection can maintain extensive variation in natural populations well above the levels predicted by simple population genetic models. In the Trinidad guppy, Poecilia reticulata, negative frequency-dependent selection through a female preference for rare or novel mates is one proposed mechanism maintaining the extreme color polymorphism seen in wild populations. Despite the apparent generality of a female mating preference for novel color patterns in this species, the evolutionary origin of the novel mate preference remains unknown. One hypothesis for the origin of the novel mate preference is that guppies have been selected for increased responsiveness to novel stimuli for reasons unrelated to mating. If response to novel stimuli leads to a selective advantage, such as a competitive foraging advantage, then the novel mate preference could be a pleiotropic side- effect of selection for increased efficiency in foraging. To determine whether the novel mate preference is due to a generalized preference for novel stimuli, I conducted two experiments. In the first experiment, I examined the molecular changes occurring in female brains when exposed to a male with a novel versus a familiar color pattern. If mate preference for novel coloration is a byproduct of a general preference for novelty, I predicted that genes previously implicated in novelty-seeking would be differentially expressed in females exposed to males with novel compared to familiar color patterns. While I did find genes specifically related to novelty-seeking, I found over 150 other genes that were differentially expressed between the novel and familiar behavior treatments, suggesting that female perception of novel mates is physiologically complex and is correlated with a series of transcriptional changes. In the second experiment, I examined the preference for novel environmental stimuli. I compared the behavioral responses of guppies exposed to novel versus familiar objects and novel versus familiar food sources. Overall, neither male nor female guppies demonstrated a strong preference for environmental novelty.

xiv In a third experiment, I examined the mating patterns in a species closely-related to the guppy, Poecilia picta. I conducted a series of experiments to determine whether P. picta show a preference for rare males or males with novel color patterns. While I did not find a female preference for males that exhibited the locally rare color pattern found in natural populations, I did determine that female P. picta show a preference for males with novel color patterns. Results of this study suggest that negative frequency-dependent selection is operating in P. picta, and potentially plays a role in the maintenance of color polymorphism in this species. In conclusion, my results do not provide consistent, strong support that the female guppy novel mate preference originated from a bias for generalized novelty. I do, however, identify neurogenomic changes associated with novel mate preference and provide the first demonstration of the mating patterns in a polymorphic P. picta population. Overall, the work outlined in this dissertation provides unique insight into the behavioral and genomic mechanisms driving genetic variation across Poeciliid species.

xv CHAPTER ONE

INTRODUCTION

1.1 Background

The maintenance of genetic variation despite evolutionary processes, such as natural selection, which are expected to reduce variation, is a long-standing paradox in evolutionary biology (Lewontin 1974). Several processes can account for the maintenance of genetic variation in ecologically important traits within a population, including mutation-selection balance, antagonistic pleiotropy, genotype by environment interaction, and balancing selection. Nevertheless, the relative importance of these different phenomena is often debated and, in general, is not known (Ayala & Campbell 1974; Barton & Turelli 1989; Charlesworth & Hughes 2000; Hughes & Sawby 2004; Mitchell Olds et al. 2007). Negative frequency-dependent selection, where the fitness of a genotype increases as its abundance within a population decreases, is one form of balancing selection capable of maintaining extensive genetic variation (Ayala & Campbell 1974; Barton & Turelli 1989). To date, the maintenance of genetic variation through negative frequency-dependent selection has been supported in a limited number of species, including the land snail, Cepaea nemoralis (Cain & Sheppard 1954), the ruff, Philomachus pugnax (Lank et al. 1995; Hugie & Lank 1996), the side-blotched lizard, Uta stansburiana (Alonzo & Sinervo 2001; Bleay et al. 2007), and in some angiosperm plant species (Antonovics & Ellstrand 1984; Gigord et al. 2001; Joly & Schoen 2011). In the Trinidad guppy, Poecilia reticulata, negative frequency-dependent selection has received strong support as the primary driver of the extreme male color polymorphism found in natural populations (Olendorf et al. 2006; Hughes et al. 2013). Guppies provide one of the best examples of mating patterns promoting genetic variation through a well-documented female preference for males with rare or novel color patterns (i.e. negative frequency-dependent mate choice) (Farr 1977; Hughes et al. 1999; Eakley & Houde 2004; Zajitschek et al. 2006; Zajitschek & Brooks 2008; Hampton et al. 2009; Hughes et al. 2013). Despite the apparent generality of the female mating preference for novel color patterns in this species, the evolutionary origin of the novel mate preference remains unknown. One

1 hypothesis for the evolutionary origin of the novel mate preference is that guppies may have been selected for increased responsiveness to novel stimuli for reasons unrelated to mating per se. If increased response to novel stimuli leads to a selective advantage, such as a competitive foraging advantage for example, then the novel mate preference could be a byproduct of selection for increased efficiency in foraging (Hughes et al. 1999; Hughes et al. 2013). Evidence of a novelty bias in a natural selection context could be consistent with pleiotropic models used to explain the evolution of female preference (Kirkpatrick & Ryan 1991). To determine the behavioral mechanisms leading to the evolution of negative frequency- dependent mate preference in guppies and the generality of this mating preference across closely-related species, I tested two hypotheses. First, I tested the hypothesis that the frequency- dependent mate preference in guppies evolved from a preference for general novelty. Second, I tested the hypothesis that a frequency-dependent mate preference is operating in a closely-related Poecillid that displays discrete male color polymorphism.

1.2 Study System

Poeciliid fishes are a well-characterized and widely distributed group that ranges from North to South America. Poeciliids are popular models in the study of sexual selection, as many species exhibit male color polymorphism, elaborate courtship displays, and extreme sexual dimorphism (Bisazza 1993). In natural populations of the Trinidad guppy, Poecilia reticulata, male guppies exhibit extreme, genetically-based color polymorphism (Haskins et al. 1961; Endler 1980; Endler 1983; Houde & Endler, 1990; Houde 1997; Brooks & Endler 2001). This sex-limited color polymorphism is one of the most genetically variable phenotypes reported in the literature, with levels of segregating variation far in excess of that expected under mutation-selection balance (Hughes et al. 2005). Male color patterns consist of highly reflective structural colors (blue, green, purple, and silver iridescence) and pigment-based colors (yellow, orange, red, and black) that can appear on the body, caudal fin, and dorsal fin and vary in size, position, and shape (Fig. 1.1). Maintenance of this extreme polymorphism has been attributed, in part, to a female mating preference for males bearing rare or unfamiliar color patterns (Farr 1977; Hughes et al. 1999; Eakley & Houde 2004; Zajitschek et al. 2006; Zajitschek & Brooks 2008; Hampton et al. 2009). In addition, experiments conducted in natural populations have indicated that males with

2 rare color patterns experience both a survival advantage and a reproductive advantage (Olendorf et al. 2006; Hughes et al. 2013). The guppies I used in my experiments originated from offspring of wild-caught guppies from the Paria River of Trinidad supplied by A.E. Houde, Lake Forest College. Experimental males used in mate choice experiments were derived from two separate Y-linked color pattern lines (“Iso-male” lines) that showed consistency in color pattern within a line but predictable differences between lines (Fig. 1.2). Furthermore, males within a line were used as ‘matched pairs’ if the colors, shapes, and locations of all of their spots and other body markings were approximately 90% identical. This procedure of choosing ‘matched pairs’ is a common method used in other guppy mate-choice studies (Eakley & Houde 2004; Hampton et al. 2009). Since guppy females show directional preferences for orange coloration in this population (Houde 1997), each line had approximately 12% total orange coloration along the combined area of their body, tail, and dorsal fin. See chapters 2 & 3 for a complete description of experimental fish. Poecilia picta, more commonly referred to as the ‘swamp guppy’ is a species within the sister taxon to the guppy, Micropoecilia. (Breden et al. 1999; Hrbek et al. 2007; Meredith et al. 2010; Meredith et al. 2011). P. picta occurs both in sympatry in freshwater conditions and allopatry with the guppy in a wide range of salinity conditions in northeast South America (Torres-Dowdall et al. 2013), with life history traits that closely mirror those of the guppy (Reznick et al. 1992). Male color patterns vary between populations of P. picta, but are either monomorphic or exhibit discrete polymorphism within populations (pers. comm. F. Breden, Simon Fraser University). Males of the polymorphic population that I studied exhibit either a yellow/gold body color or an orange/blush body color with both morphs demonstrating orange, yellow, and black markings on their body, tail, and dorsal fin (Fig. 1.3). The ratio of gold- colored morphs to blush-colored morphs is approximately 4 to 1 in natural polymorphic populations (pers. comm. F. Breden). Similar to guppies, P. picta females lack conspicuous coloration. P. picta used in my experiments originated from offspring of wild-caught fish from Georgetown, Guyana, supplied by F. Breden (Simon Fraser University). Fish were collected from canalized sewerage outlets that have low light, high sediment levels, and low vegetation. Fish used for experiments were descended from four field sites that were bred together in the lab for approximately 3-4 generations (GPS coordinates: 06 31.643’N, 058 15.062’W; 06 49.520’N,

3 058 08.637’W; 06 48.332’N, 058 08.720’W; 06 48.045’N, 058 09.086’W). In general, field collection sites consisted of brackish water conditions composed of high fish densities. Salinity specific gravity (d 20/20) ranged from 1.000-1.003, 0-4 parts per thousand (0/00), and pH ranged from 6.5-7.0.

Figure 1.1 Guppy males from a single population.

Figure 1.2 Example of male guppies from each Iso-male line used for behavioral experiments. Top: males from line 1; Bottom: males from line 2.

4

Figure 1.3 Example of male P. picta. Blush morph (top) and gold morph (bottom) that occur in polymorphic populations.

1.3 Dissertation Goals & Summary of Chapters

1.3.1 Dissertation Goals

Overall, the goals for my dissertation research were twofold: 1) to determine the behavioral and genomic mechanisms that lead to negative frequency-dependent mating preference in guppies;

5 and 2) to determine whether females from a closely-related species, P. picta, that display discrete polymorphism, exhibit negative frequency-dependent mating preferences. . 1.3.2 Summary Of Chapters

1.3.2.1 Chapter 2 To determine whether the novel mate preference evolved as a correlated response to a preference for generalized novelty, I conducted a behavioral genomics experiment in which female guppies were presented either with a male that had a novel color pattern or a male that had a familiar color pattern. After mating trials, all females were sacrificed and the brain genomic response was compared between females in the two treatment groups. If a negative frequency-dependent mate preference arose out of a natural selection context, i.e. a bias in the sensory system for novelty, I predicted I would see upregulation of genes related to novelty-seeking found in other studies in those females exposed to males with novel color patterns compared to familiar patterns. On the other hand, expression of genes specifically related to mating behavior would suggest alternative explanations for the evolution and maintenance of the novel mate preference. Results showed that females exposed to males with novel versus familiar color patterns exhibited differential brain gene expression patterns with 165 genes differentially expressed between the two treatment groups. Of those genes that were differentially expressed, five genes have been implicated in novelty-seeking or social behavior in other behavioral genomic studies, including drd4 (Dopamine receptor D4), mhc-II (MHC class II beta antigen), eaat-2 (Excitatory amino acid transporter 2), tph-2 (Tryptophan 5- hydroxylase 2), and mc4r (melanocortin 4 receptor). Therefore, my results provide evidence that neurological responses to novel males involve similar gene activation as do responses to novelty in other contexts across taxa, suggesting that it is the novelty of these preferred males that is triggering a female response. While I did find genes specifically related to novelty-seeking, I found over 150 other genes that were differentially expressed between the novel and familiar behavior treatments, suggesting that female perception of novel mates is physiologically complex and is correlated with a series of transcriptional events.

6 1.3.2.2 Chapter 3 To test the hypothesis that the novel mate preference evolved as a correlated response to a generalized novelty preference in a natural selection context, I examined the behavioral mechanisms that are driving the negative frequency-dependent mate preference in guppies. Specifically, I compared the behavioral responses of both male and female guppies exposed to novel versus familiar environmental stimuli. I tested both inanimate objects and objects that are presumably more ecologically relevant (food items that were identical except for color). Overall, while I found suggestive evidence that males preferred some objects when they were novel, neither males nor females exhibited a strong, consistent preference for environmental novelty. Therefore, I could not support the hypothesis that the novel mate preference arose out of a natural selection context. I propose alternative explanations for the evolution of the novel male preference, such as inbreeding avoidance.

1.3.2.3 Chapter 4 To determine whether a frequency-dependent mate preference is operating in P. picta, and potentially maintaining the discrete polymorphism, I examined the mating preferences for males with color patterns that occur at a low frequency in the wild (i.e. rare males) and the preferences for males exhibiting novel color patterns, irrespective of morph type. While I did not find a female preference for males with the rare color pattern, I did show a female preference for males with novel color patterns. My results suggest that a negative frequency-dependent mate preference is operating in discretely polymorphic populations of P. picta, and could be driving the polymorphism in male color.

7 CHAPTER TWO

MOLECULAR MECHANISMS UNDERLYING NOVEL MALE PREFERENCE IN THE FEMALE GUPPY

2.1 Introduction

The maintenance of genetic variation in the face of both natural selection and genetic drift is an intriguing paradox in evolutionary biology (Lewontin 1974). While directional natural selection is expected to erode variation, extensive variation persists within natural populations. Several evolutionary processes have been proposed to maintain genetic variation in ecologically important traits within a population, including mutation-selection balance, antagonistic pleiotropy, genotype by environment interaction, sexual antagonism, and balancing selection (Ayala & Campbell 1974; Barton & Turelli 1989; Charlesworth & Hughes 2001; Hughes & Sawby 2004; Mitchell Olds et al. 2007). Negative frequency-dependent selection, where the fitness of a genotype increases as its abundance within a population decreases, is one form of balancing selection capable of maintaining extensive genetic variation (Ayala & Campbell 1974; Barton & Turelli 1989). To date, the maintenance of genetic variation through negative frequency-dependent selection has been strongly supported in a limited number of species, including the land snail, Cepaea nemoralis (Cain & Sheppard 1954), the ruff, Philomachus pugnax (Lank et al. 1995; Hugie & Lank 1996), the side-blotched lizard, Uta stansburiana (Alonzo & Sinervo 2001; Bleay et al. 2007), and in some angiosperm plant species (Antonovics & Ellstrand 1984; Gigord et al. 2001; Joly & Schoen 2011). Other studies have suggested that negative frequency-dependent selection is maintaining within-population variation, but have not explicitly measured selection. These studies have been conducted in species such as the Lake Victoria cichlid fish, Neochromis omnicaeruleus (Pierotti et al. 2009), and the penta fish, Poecilia parae (Lindholm et al. 2004). In the Trinidad guppy, Poecilia reticulata, negative frequency-dependent selection is one proposed mechanism maintaining genetic variation in wild populations (Farr 1977; Hughes et al. 1999; Eakley & Houde 2004; Zajitschek et al. 2006; Olendorf et al. 2006; Zajitschek & Brooks 2008; Hampton et al. 2009; Fraser et al. 2013; Hughes et al. 2013). In natural populations, male guppies exhibit extreme, genetically-based color polymorphism (Haskins et al. 1961; Endler

8 1980; Houde 1997). The array of male color patterns consists of both highly reflective structural colors (blue, green, purple, and silver iridescence) and pigment-based colors (yellow, orange, red, and black) that appear on the body, caudal fin, and dorsal fin and vary in size, position, and shape (Fig. 1.1). Guppies provide one of the best-documented examples of mating patterns promoting genetic variation, as females prefer males with rare or novel color patterns (i.e. negative frequency-dependent mate choice) (Farr 1977; Hughes et al. 1999; Eakley & Houde 2004; Zajitschek et al. 2006; Zajitschek & Brooks 2008; Hampton et al. 2009). Despite the apparent generality of a female mating preference for novel color patterns in this species, the evolutionary origin of the novel mate preference remains unknown. One hypothesis is that females prefer novel males because they have been selected for increased responsiveness to novel stimuli in a natural selection context. If response to novel stimuli leads to a selective advantage, such as a competitive foraging advantage for example, then the novel mate preference could be a byproduct of selection for increased efficiency in foraging (Hughes et al. 1999). Rodd et al. (2002) found evidence that the female guppy mate preference for males with greater orange coloration evolved as a result of a bias for orange-colored objects, such as the rare, but highly nutritious, orange-colored fruit that occur in Trinidadian streams. While past experiments measuring sensory system biases have tested for a behavioral attraction or ‘bias’ towards particular stimuli, such as the behavioral tests conducted in guppies (Rodd et al. 2002), no study has yet quantified the neurogenomic changes that are occurring during such behavioral encounters in this species. In studies specifically measuring novelty perception and response, exposure to novel stimuli leaves a distinct brain genomic and physiological signature (Dellu et al. 1996; Kabbaj et al. 2000; Kosten & Ambrosio 2002; De Leonibus et al. 2006; Marquez et al. 2006; Liang et al. 2012). In rodents exposed to novel stimuli, for example, a change in the expression of the dopamine receptor D4 gene (drd4) has been seen in areas of the prefrontal cortex (Paredes et al. 2011). Likewise, variants or polymorphisms of drd4 have also been implicated in novelty- seeking and processing in other animals including the vervet monkey, Cercopithecus aethiop (Bailey et al. 2007), the great tit, Parus major (Fidler et al. 2007), and in humans (Marco- Pallares et al. 2010). Additionally, novelty-seeking and risk taking across vertebrates has been linked to a decrease in serotonin (Blanchard et at. 2009), an increase in norepinephrine (Bell et al. 2007), an increase in glutamate transporter expression (Liang et al. 2012), and an increase in

9 the expression of several immediate early genes (Montag-Sallaz et al. 1999; Sockman et al. 2005; Struthers et al. 2005). Motivated by the evidence from studies in other organisms that demonstrate a repeatable list of genes that are activated in response to novel stimuli, here I test a key prediction of the hypothesis that that the preference for novel mates evolved through a behavioral attraction for novelty: that females presented with males bearing a novel color pattern demonstrate a neurogenomic profile that is similar to those profiles of animals presented with novel stimuli. To test this prediction, I conducted an experiment in which female guppies were either presented with a male that had a novel color pattern or a male that had a familiar color pattern. After behavioral trials, all females were sacrificed and the brain transcriptional response was compared between females in the two treatment groups. If the female mate preference for novel coloration evolved as a pleiotropic byproduct of a general preference for novelty, I predicted that genes implicated in novelty-seeking would be present and differentially expressed in females exposed to males bearing novel color patterns compared to familiar color patterns.

2.2 Methods

2.2.1 Ethics Statement

All experimental procedures were approved by the Animal Care and Use Committee at Florida State University (protocol #0901 & #1142).

2.2.2 Behavioral Methods

2.2.2.1 Overview I compared behavioral responses between female guppies exposed to males with novel versus familiar color patterns. Briefly, female guppies were familiarized to a male with a particular color pattern. Females were then presented with a male bearing either a novel color pattern or a color pattern similar to that of the first male. Behavior was recorded for 30 minutes. Individuals were randomly assigned to each treatment group. All experiments were conducted between August and November of 2011.

10 2.2.2.2 Experimental Fish All fish originated from offspring of wild-caught guppies from the Paria River of Trinidad. Experimental males were derived from two separate Y- linked color pattern lines that showed consistency in color pattern within a line but predictable differences between lines (Fig. 1.2). Each Iso-male line was originally founded by a male with a distinct color pattern. Since guppy females show directional preferences for orange coloration in this population (Houde 1997), each line had approximately 12% total orange coloration along the combined area of their body, tail, and dorsal fin. To minimize inbreeding within a line, a new generation was initiated every 4-6 months with approximately 20 males from that line mated to unrelated virgin females. Upon maturity, all experimental males were transferred to 2.5 gallon (9.5-liter) or 10-gallon (38-liter) tanks and housed with unrelated mature females at approximately 1-2 fish per gallon to ensure that they had sexual experience prior to experimental trials. Experimental females were obtained from a stock population of approximately 300 breeding adults. All fish stocks were maintained in groups of approximately 30 adults plus offspring, with inbreeding controlled for by transferring adults between stock tanks every 1-2 generations. Upon maturity, experimental females were transferred to female- only tanks with a density of two females per gallon. Females that were reared in female- only tanks were visually and sexually naïve and were, therefore, considered virgins. Female guppies show peak receptivity towards male displays when they are non-mated (i.e. virgin) and shortly after giving birth (Houde 1997). Thus, I aimed to simulate the virgin receptivity state. All fish used in the experiment were between 120 and 180 days old. Fish were maintained on a 12:12 h light:dark cycle using full spectrum lights, at 25º Celsius, and were provided a commercial flake food and brine shrimp diet, fed ad lib twice per day. All experimental tanks were separated by opaque plastic dividers and kept on a recirculating system; therefore, all aspects of water quality were identical for experimental tanks.

2.2.2.3 Behavioral Paradigm Mate choice in guppies has been assessed using a wide variety of behavioral paradigms (Houde 1997). For my study, I chose a sequential choice test in which individual females were familiarized to a male with a particular color pattern and then later presented with a male that had a novel color pattern or one that had

11 the same color pattern as the first male. Approximately four days before the familiarization period began, I visually selected matched pairs of males from the same Iso-male line. Pairs were deemed to be matched if the size, color, and location of their spots and other body markings were approximately 90% identical. Additionally, I chose males that were of the same body size and approximate age. In practice, matched pairs differed in the presence, color, or position of one spot, at the most, along the length of the body, or showed minor variation in fin markings (Eakley & Houde 2004; Hampton et al. 2009). I then isolated each matched pair and held them in separate 2.5 gallon (9.5 liter) tanks. One male from a matched pair was used as a ‘familiar’ male on experiment day three, as matched pairs were nearly identical in all color pattern markings (See Appendix Fig. B.1 for examples of matched ‘familiar’ pairs). I also isolated non-matched pairs (one male from each line) following the same procedure and used the second male from a pair as a ‘novel’ male on experiment day three (Appendix Fig. B.2). Novel male pairs were matched in size and approximate age. At the same time, one virgin female along with two smaller, non-focal females were moved into 10-gallon (38-liter) experimental aquaria to allow for acclimation. Non-focal females were used to reduce stress levels of focal experimental females. All non-focals were not sexually mature; therefore, males did not direct courtship attempts towards them and their behavior was not measured. At 9:00 AM on day one of the experiment, a male from a pair was placed into the experimental aquaria containing one virgin female, along with two, smaller non-focal females. Males were allowed to freely interact with females for 48 hours. On day three, the male was gently netted out of the tank and a male with either the same color pattern (familiar male) or one with a different color pattern (novel male) was added to the tank. After introduction of the second male, I recorded behavior for 30 minutes using JWatcher V1.0 event recording (Blumstein et al. 2006). Male courtship displays (sigmoid displays) in the guppy consist of the male bending his body into an ‘S’ shape and quivering (Houde 1997). The strength of the female’s response to each male display was then scored using characteristic levels of female response (Houde 1997). These response levels included: no response, orient towards male, approach male, glide response, and copulate. As in Mariette et al. (2010), I categorized displays as "successful" if the female oriented towards the male, approached, glided, or copulated with the male

12 (i.e. ‘positive responses’), and "unsuccessful" otherwise. The response to displays was scored in the rank order of increasing interest ranging from 0 (no response) to 5 (copulation). Following behavioral trials, females were sacrificed, and brains were partially dissected and stored in RNAlater® (Qiagen, Valenica, California). After experiments, males were placed back into tanks with unrelated mature females. Individual males were re-used. Non-focal females were re-used until they approached sexual maturity.

2.2.2.4 Data Analyses I used two separate measures to determine the strength of a female’s attraction towards a particular male: proportion of positive responses and average response score. The proportion of positive responses was calculated by summing the total number of positive female responses towards a male display (responses > 2) and dividing by the total number of displays within the 30-minute trial period. Proportion of positive responses was analyzed using a general linear model (normal distribution) with treatment (novel vs familiar) and Iso-male line (either line 1 or line 2) as fixed effects in the analysis. Proportion of positive responses was arc-sine square-root transformed to improve normality and homoscedasticity of the residuals. In addition, I calculated the average response (with a range of 0-5 in rank order of increasing interest) towards all male displays over the 30-minute trial period. The average response score was analyzed using a general linear model with treatment (novel vs familiar) and Iso-male line as fixed effects in the analysis. The average response score was non-transformed and met the assumptions of normality and homoscedasticity of residuals. The treatment-by-Iso-male line interaction was also included in both full models. I conducted 72 replicates total (35 with novel males and 37 with familiar males). All behavioral trials were scored by the same experimenter using the non-objective criteria described above to ensure consistency and reliability in behavioral scoring.

2.2.3 Brain Gene Expression Methods

2.2.3.1 Brain Dissections Following completion of behavioral trials, all females were euthanized in an ice-slurry bath. I partially dissected 50 whole heads and stored them in

13 RNAlater® (Qiagen, Valenica, California) at - 80 °C. In total, I used 26 brains from the “novel” treatment and 24 from the “familiar” treatment. Only brains that were representative of their treatment group, as measured by the females’ average response score, were chosen for the gene expression experiment. Brains of females that fell within the highest 60% of average response scores were chosen for the “novel” treatment and brains of females that fell within the lowest 60% (but > 0) of average response scores were chosen for the “familiar” treatment. Using females in the “novel” treatment that showed a heightened sexual response and females in the “familiar” treatment that showed a reduced sexual response, as expected, ensured that I maximized genomic variation between treatment groups. Partial dissections consisted of decapitation, removal of tissue surrounding the head, and puncturing the bony plate around the brain to allow full RNAlater saturation. Care was taken to ensure that all brains were partially dissected in less than 2 minutes. Within 6 months from the completion of behavioral trials, all brains were fully dissected out of the skull.

2.2.3.2 RNA Sequencing Library Preparation From the 50 female brains, I constructed 17 RNA-sequencing (RNA-seq) libraries from whole brain extractions (9 from females in the “novel” treatment and 8 from females in the “familiar” treatment). Each library was constructed from brains of 3 females (with one exception of a 2-brain pool) with similar average response scores. For example, if six females had average response scores of 3, 3, 3.1, 3.5, 3.5, & 3.6, their brains would be pooled into two groups: pool 1 with scores of 3, 3, & 3.1 and pool 2 with scores of 3.5, 3.5, & 3.6, respectively. This method of pooling allowed me to measure the differential brain genomic response of females in each treatment group along with the relationship between gene expression and the strength of the female preference scores. To ensure that female preference was not confounded with general activity levels, I ran a preliminary analysis and did not find a significant Pearson’s product-moment correlation between preference and activity levels (r = 0.09; p = 0.73). I then extracted RNA from each pooled sample using an RNeasy mini kit (Qiagen, Valencia, California) according to the manufacturer’s instructions, including an on-column DNase treatment to remove genomic DNA. An equal amount of RNA per sample was used for RNA-seq library construction. cDNAlibraries were prepared with 2

14 ug of starting total RNA following the protocols of the Illumina TruSeq RNA Sample Preparation Kit (Illumina, San Diego, Ca). The libraries were amplified with 15 cycles of PCR (run parameters: 98°C for 30 seconds, 15 cycles: 98°C for 10 seconds, 60°C for 30 seconds, 72°C for 30 seconds, followed by one cycle of 72°C for 5 minutes) and contained 12 unique TruSeq indexes within the adapters, specifically indexes 1, 3, 8, 9, 10, 11, 20, 21, 22, 23, 25 & 27. The final libraries had an average fragment size of 260 bp and mean final yields of 32 ng/ul. The libraries were then multiplexed 6, 6, & 5 per lane and sequenced on an Illumina HiSeq 2000 instrument with 100 bp paired end reads.

2.2.3.3 Transcriptome Assembly and Annotation The reference brain transcriptome was constructed from an initial data set containing > 450 million overlapping 100-bp paired end reads. Overlapping reads were merged using a custom Python script provided by Dr. Alan Lemmon (Florida State University) and filtered for high quality sequence using Trimmomatic v. 0.22 (Lohse 2012). Trimmomatic was used to cut adapter sequences and any low-quality sequence from each read. I used a threshold quality of 3 which trims bases below the specified level at the start or the end of a read, a minimum read length after trimming of 36 bp, and a sliding window option of 4:15 in which reads are scanned at the 5’ end and trimmed once the average quality within the window falls below the threshold. Reads were then normalized in-silico using Trinity v. 2013-02-25 (Grabherr et al. 2011) to compress the range in kmer abundance. The Trinity algorithm compares the ratio of the desired coverage to the median coverage to a random number between 0 & 1. If the random number is less than the ratio of the desired:median coverage, the read is kept. I used a desired coverage parameter of 20. I used SeqMan NGEN 4.1.2 from the Lasergene DNAStar software package (Madison, WI; Kumar and Blaxter 2010; Feldmeyer et al. 2011) to perform the assembly. The assembly contained 41,347 contigs with N50 = 2,548 and it recovered 63% of Tilapia (Oreochromis niloticus) Ensembl proteins (Release 70). Contigs from the assembly were annotated by blastx (Altschul et al. 1990) queries against three different databases: SwissProt (database downloaded Oct 6, 2012), UniProt/Trembl (Nov 28, 2012), and nr (Dec 11, 2012). Default parameters were used in the blastx queries, with an

15 e-value cutoff of 10-4. The assembly will be deposited in a publically-available archive before publication.

2.2.3.4 RNA Sequence Analysis RNA sequencing reads were mapped to the reference transcriptome. Sequencing reads from the 17 brain samples were aligned to the reference transcriptome using Bowtie2 v. 2.0.0 (Langmead & Salzberg 2012) on a 64-bit computing cluster running Red Hat Enterprise Linux 6.3. I used a seed size of 20 bp, with no mismatches allowed in the seed (run options: -D 15 -R 2 -N 0 -L 20 -i S,1,0.75). I retained mappings with quality scores > 20 (<0.01 probability that the read maps elsewhere in the reference). I then applied an abundance filter to retain only transcripts represented by more than 1 count per million reads in at least three samples, resulting in 38,812 transcripts remaining in the data set. I used the number of reads mapping to each of those transcripts, along with TMM-normalized library sizes (Robinson and Oshlak 2010) to analyze differential expression (see below).

2.2.3.5 Statistical Analyses To test the hypothesis that females exposed to novel and familiar males show differential brain gene expression patterns, I compared novel and familiar female brain expression profiles using general linear models. I assessed differences in expression between the novel and familiar treatment groups by applying a univariate general linear model to each transcript with treatment as a fixed effect. The dependent variable in the model was the log transformed and normalized number of sequencing reads that mapped to each transcript, where the normalization resulted in mapped reads expressed as the count per million reads. To assess differential expression associated with female behavior, I used a linear model with the average response score of the females used in each sample as a continuous predictor variable. Mean activity scores were used as a covariate in the model to account for any overall differences in activity. General linear models were fit using Proc GLM from SAS 9.3 (SAS Institute Inc. 2011) running on the computing cluster described above. Statistical significance of model effects was evaluated using permutation tests because these tests allowed me to correct for multiple testing and to take into account the potential correlation among transcripts within samples (traditional methods of correcting for multiple testing assume

16 independence among tests). Permuted data sets were generated by randomly reassigning entire RNA-seq samples between treatments (or response scores) so that the correlation structure among different transcripts in the same sample was retained. I then compared the test statistic derived from the real data to the distribution of test statistic values produced in 250 permuted data sets. In the evaluation of treatment effects, the test statistic was a t value, while in the preference analysis (using the average response score), the statistic was an F value. If the statistic computed from the real data fell within the upper and lower 0.25% of the permuted values, I called that transcript differentially expressed. I then compared the number of transcripts that were called differentially expressed to the distribution of that number in all 250 permuted data sets to determine if there were more transcripts called differentially expressed than expected across all 38,812 tests.

2.2.3.6 Functional Enrichment Analyses I evaluated enrichment of functional classes in the transcripts that were differentially expressed in each analysis using Gene Ontology (GO) classification (The Gene Ontology Consortium 2000). GO is a set of hierarchal gene associations designed to cluster genes into broad categories, including the ‘cellular component’ of a gene, the ‘molecular function’, and the primary ‘biological process’ of a gene. GO IDs for transcripts in the reference database were derived from GI-to-GO mappings provided by UniProt, a tool used to find all of the GO annotations corresponding to a list of gene identifiers; these mappings were downloaded on 3/10/2013. I evaluated over-representation of biological process, molecular function, and cellular component ontologies using the topGo R package version: Release (2.13) (Alexa and Rahnenfuhrer 2010) running on R 2.15.2 in Mac OS 10.8.2. To account for correlation in the GO graph topology, I used the weight01 algorithm in the topGo package, which applies the elim and weight algorithms of Alexa et al. (2006). For gene lists, I report categories that were significant at p <0.05 and that contained three or more transcripts from the list. I did not apply formal correction for multiple testing in these analyses because when one accounts for the GO graph topology, the p-values of a GO term are conditioned on the occurrence of neighboring terms. The tests are thus not independent and the theory of multiple testing does not directly apply.

17 2.2.3.7 qPCR Gene Validation qPCR validation was conducted on all 17 samples, including one reference sample that was not part of the experiment. Total RNA from each sample was reverse transcribed using the SuperScript ® III First-Strand Synthesis System (Invitrogen, Carlsbad, CA). Quantitative real-time PCR (qPCR) reactions were performed on an Applied Biosystems 7500 Fast cycler (Applied Biosystems, Grand Island, NY) using SYBR Green PCR Master Mix (Applied Biosystems) following the manufacturer’s recommendations. Beta-actin was chosen as an endogenous control because the expression values were assumed to be the same across all samples. Genes selected for validation were genes that showed a relationship to novelty-seeking behavior a priori and genes related to other behaviors found in gene expression studies (See Appendix Table C.1 for a priori list of genes related to novelty-seeking behavior). Selected genes and their primers are shown in Table 2.1. Each reaction was run twice and a dissociation curve was used to assess each amplicon. Amplicon length for all target genes was approximately 100 bp. A No-template control (NTC) and a No-reverse transcriptase control (No-RT) were included on each plate. Relative gene expression levels were determined by the comparative Ct method (Ct). To measure differential expression between treatment groups, I used a general linear model with treatment as a fixed effect in the analysis and relative quantification (RQ), a measure used to analyze changes in gene expression in a given sample relative to a reference sample, as the dependent variable. To evaluate the overall concordance between RNA-Seq and qPCR assays of gene expression, I calculated the Pearson Product-Moment Correlation between RQ from the qPCR data and the raw count data from the RNA-seq analysis. As a separate analysis, I examined the correlation between the qPCR RQ data and the normalized, transformed count data from the RNA- seq analysis. This measure allowed me to determine whether there was a positive relationship between the qPCR data and the RNA-seq data, as predicted. To verify genes in the preference regression analysis, I used a linear model that included the mean preference score of the females used in each sample as the independent variable and general activity levels as a covariate. RQ was again used as the dependent variable.

18 Table 2.1 List of primer sequences used in the qPCR validation assays.

Gene Forward sequence Reverse sequence

b-actin TTCGAGCAGGAGATGGGTACC GCAACGGAACCTCTCATTGC mhc-II GGCTGAGAGACGGACAGGAAG CAGCGTGGAGTGGATCTGGTA

eaat-2 CATTTATCGAGGGCCGAACTG CGACCAGGTCCATTTCTGTGA

drd4 CTGGGAGGAACCTGGACTCTG CGATGTACCGGTCTACGCTGA

tph-2 GGACGTCTCCCGTTTTCTCAG ACACCCTGTAGGCCAAACCAG

mc4r GCGGTACCACAACATCGTCAC GATGAAGAGGATGCCGGAGAC

Reference gene for normalization of qPCR data: b-actin =Beta Actin control; Target genes: drd4=Dopamine receptor D4; mhc-II=MHC class II beta antigen; eaat- 2=Excitatory amino acid transporter 2; tph-2=Tryptophan 5-hydroxylase 2; mc4r=melanocortin 4 receptor.

2.3 Results

2.3.1 Behavioral Results

I conducted 72 replicates of the behavioral experiment (35 with novel males and 37 with familiar males). As expected, females were more likely to exhibit a positive response to courtship displays of males with novel, compared to familiar, color patterns (p < 0.0001; Table 2.2, Fig. 2.1 top). There was no significant main effect of Iso-male line from which the test male was derived nor a significant treatment-by-Iso-male line interaction (Table 2.2). Females also displayed significantly more intense responses to males with novel compared to familiar color patterns (p < 0.0001; Table 2.3, Fig. 2.1 bottom). Again, there was no significant main effect of Iso-male line or a significant treatment-by-Iso-male line interaction (Table 2.3). All graphs are depicted using non-transformed data; statistics for data representing proportion of positive responses are arc-sine square root transformed.

19 Table 2.2 Results of general linear model of the proportion of positive responses towards male displays for each female during 30 minutes.

Source of Variation Df SS F p

Treatment 1,68 2.99 25.22 <.0001 Iso-male line 1,68 0.01 0.05 0.83 Line*Treat 1,68 0.02 0.13 0.72

Table 2.3 Results of general linear model of the average response score towards male displays for each female during 30 minutes.

Source of Variation Df SS F p

Treatment 1,68 9.21 18.58 <.0001 Iso-male line 1,68 0.19 0.37 0.54 Line*Treat 1,68 0.33 0.66 0.42

20

1 0.9 0.8 0.7 0.6 0.5 0.4 Responses Responses 0.3 0.2 Proportion of Positive of Positive Proportion 0.1 0 Familiar Novel Treatment Group

3

2.5

2

1.5

1

Average Response Score Score Response Average 0.5

0 Familiar Novel Treatment Group

Figure. 2.1 Female preference for males with novel and familiar color patterns. Top: LS Mean + SE Proportion of positive responses. Proportion of positive responses represents the mean of the number of positive responses for each male display over the total number of responses for each male display of each female over 30 minutes; bottom: LS Mean + SE Average response score. Average response score represents the mean of the average response towards male displays for each female over 30 minutes; N = 35 Novel and 37 Familiar.

21 2.3.2 Gene Expression Results

I obtained 1,289,497,622 100-bp paired-end reads that passed the machine quality filter with a range of 29,768,694 to 49,504,152 reads per one end of each sample. The percent of reads with an average quality score > 30 was 90.3%. Of reads passing filter, 1,186,604,160 (92%) mapped with high stringency (map quality >20) to the 41,347 unique transcripts in the guppy reference brain transcriptome. After removing low abundance transcripts, 38,812 remained in the data set to which 1,185,322,003 of the high quality reads were mapped. In total, 165 transcripts were differentially expressed between the novel and familiar treatment groups, based on permutation tests (See Appendix Table D.1 for complete list of genes; least squares means were generated from log-transformed/normalized gene counts). No genes were differentially expressed in the permuted data sets at the cut-off p-value. Seventy-four transcripts were upregulated in the familiar treatment group while 91 were upregulated in the novel treatment group (Fig. 2.2). Of those that were upregulated in females exposed to novel males, I found eaat-2 (excitatory amino acid transporter-2; Table 2.4). Of those genes that were upregulated in females exposed to familiar males, I found drd4, tph-2 (trypophan hydroxylase 2), and mc4r (melanocortin 4 receptor; Table 2.4). In addition, 99 transcripts were significantly associated with female preference (See Appendix Table D.2 for complete list). Sixty transcripts showed a positive relationship between preference score and gene expression while 39 transcripts showed a negative relationship between preference and gene expression (Fig. 2.3). Of those genes that showed a positive relationship with preference, I found mhc-II (major histocompatibility complex class II). Sixteen genes overlapped between the treatment and preference list; none were behavior-related. Of the 165 genes differentially expressed between novel and familiar treatment groups, 114 had GO annotations (Biological Process=74, Molecular Function=81, Cellular Location=71). Integrin-mediated signalling pathway & purine ribonucleoside catabolic process (Biological Process), nucleic acid binding, hydrolase activity, transcription corepressor activity, & peptidase activity (Molecular Function), and cilium (Cellular Location) were over-represented according to the GO analysis following my apriori cut-off of p < 0.05 (Table 2.5). Of the 99 genes associated with mean preference score of females, 55 had GO annotations (Biological

22 Process=39, Molecular Function=35, Cellular Location=37). Only one of these categories met my a priori cut-off of p < 0.05: intracellular protein transport (Biological Process) (Table 2.6). I examined the correlation between the RQ values of the qPCR data and the raw counts and normalized/transformed counts of the RNA-seq data. I found a significant positive Pearson’s product-moment correlation between the RQ and the RNA-seq count data (r = 0.57; p < 0.0001) and a significant positive correlation between the RQ and normalized/transformed RNA-seq count data (r = 0.50; p < 0.0001). Data met the assumptions of the Pearson’s product-moment correlation test. All five of my target genes, as well as my control gene, were amplified by qPCR. All of the five target genes that were included in the qPCR validation were regulated in the same direction as the RNA-seq data, except drd4, which was slightly higher in the novelty treatment based on the qPCR results (Table 2.7). Eatt-2 showed upregulation in the novelty treatment as expected while tph-2 and mc4r showed upregulation in the familiar treatment as expected (Table 2.7). For the analysis in which I fit a linear model with preference score as a predictor, one example of a gene that showed a positive relationship with gene expression was mhc-II, although the p-value was non-significant (R2 = 0.21; p = 0.12). Overall, although most of the genes from the qPCR analysis were in the predicted direction as the RNA-seq data, none were significantly differentially expressed. Therefore, I was unable to validate any of the chosen genes.

Figure 2.2 Number of genes significantly upregulated in the novel and familiar treatment groups. Numbers depicted in center of bar represent exact count of genes upregulated in each treatment group. Genes above bar represent examples of genes significantly upregulated in each treatment group.

23

Figure 2.3 Number of genes that show a significant positive or negative relationship with average preference score, as measured using the average response variable from behavior analyses. Numbers depicted in center of bar represent exact count of genes. Gene above bar represents an example of a

gene that showed a significant positive relationship with preference score.

Table 2.4 Results of general linear model of the raw count data and fold changes for each gene in each treatment group in the RNA-seq data analysis.

Target Familiar Novel Fold 95% (+/-) 95% (+/-)

Gene Least Least Change Confidence Confidence Squares Squares Limits of Limits of Novel Mean Mean Familiar means means eaat-2 0.61 1.38 0.44 0.73/0.50 1.65/1.15

drd4 2.67 2.14 1.25 2.83/2.51 2.25/2.03

tph-2 7.24 6.11 1.19 7.54/6.96 6.36/5.87 mc4r 5.70 4.53 1.26 5.99/5.42 4.76/4.31

24

Table 2.5 Gene Ontology (GO) table for Novel vs. Familiar analysis. GO Term Reference1 DE2 P

Biological Process

GO:0007229 Integrin-mediated signaling pathway 111 3 0.015

GO:0046130 Purine ribonucleoside catabolic process 496 5 0.022

Molecular Function

GO:0003676 Nucleic acid binding 4411 27 0.011

GO:0016818 Hydrolase activity, acting on acid anhydrides 1134 4 0.015

GO:0003714 Transcription corepressor activity 127 3 0.023

GO:0008233 Peptidase activity 720 4 0.025

Cellular Location

GO:0005929 Cilium 220 4 0.02

Table 2.6 GO table for preference analysis. GO Term Reference1 DE2 P

Biological Process

GO:0006886 Intracellular protein transport 562 4 0.033

1 Number of transcripts annotated to this category in the entire data set. 2 Number of transcripts that were differentially expressed.

25 Table 2.7 qPCR results of general linear model of the relative quantification (RQ) for each gene in each treatment group. Target Gene RQ Familiar LS RQ Novel LS P value Mean + SE Mean + SE

eaat-2 0.61 + 0.20 1.05 + 0.19 0.13

drd4 0.96 + 0.10 0.10 + 0.10 0.82

tph-2 1.53 + 0.10 1.45 + 0.09 0.54

mc4r 0.99 + 0.07 0.80 + 0.07 0.06

Target genes: drd4=Dopamine receptor D4; mhc-II=MHC class II beta antigen; eaat- 2=Excitatory amino acid transporter 2; tph-2=Tryptophan 5-hydroxylase 2; mc4r=melanocortin 4 receptor.

2.4 Discussion & Conclusions

Overall, my behavioral results were consistent with previous studies that demonstrate a strong female preference for males with novel color patterns. I used RNA-seq analyses to measure the brain gene response in females exposed to males with novel versus familiar color patterns. I found 74 genes upregulated in females exposed to males with familiar color patterns and 91 genes upregulated in females exposed to males with novel color patterns. In addition, 99 genes showed a quantitative relationship with the average preference score towards male displays. Among these genes, I identified three that have been specifically implicated in novelty-seeking and two genes that have been linked to other forms of behavior (i.e. social behavior and mating- related behavior) in other behavioral genomic studies. Therefore, my results provide evidence that neurological responses to novel males involve similar gene activation as do responses to novelty in other contexts across taxa, suggesting that it is the novelty of these preferred males that is triggering a female response.

26 Differential gene expression in females exposed to males with familiar color patterns

From the 74 genes that were upregulated in females exposed to familiar males, I found drd4, tph- 2, and mc4r. Polymorphisms in drd4 have been directly implicated in novelty-seeking across taxa (Benjamin et al. 1996; Ebstein 1996; Bailey et al. 2007; Fidler et al. 2007; Marco-Pallares et al. 2010) and knockout studies in mice show that D4R knockout mice display reduced exploratory and novelty-seeking behaviors (Dulawa 1999). Expression of other dopamine receptors besides the D4 receptor has also been implicated in novelty-seeking across taxa (Viggiano et al. 2003; Holmes et al. 2004; Liang et al. 2012). Tph-2, on the other hand, is indirectly implicated in novelty-seeking through its relationship to serotonin, because tph-2 catalyzes the rate limiting step in serotonin synthesis. Overall, the brain serotonin system is a key player in the regulation of reward and aversion behaviors (Hayes & Greenshaw 2011) and has been directly related to increased novelty-seeking across taxa (Blanchard et al. 2009). While both drd4 and tph-2 have been associated with novelty-seeking behavior specifically, mc4r has been associated with sexual and grooming behaviors, energy balance, and food intake across species from various taxa (Metz et al. 2006; Ducrest et al. 2008; Lampert et al. 2010). The differential expression of drd4, tph-2, and mc4r in this study suggest that these genes are not only involved in novelty-seeking and other behaviors, but also that they are involved in the mate preference for novel male color patterns in female guppies.

Differential gene expression in females exposed to males with novel color patterns

From the list of 91 genes upregulated in females exposed to novel males, I found eaat-2, a gene previously implicated in novelty-seeking. Glutamate transporters are related to behavioral syndromes, including, but not limited to novelty-seeking. Specifically, glutamate transporters play a role in exploratory behavior (Alttoa et al. 2010) and in behavioral disorders, such as drug addiction (Pitychoutis et al. 2011). Recently, eaat-2 was implicated in novelty-seeking behavior in honeybees (Liang et al. 2012). Therefore, differential expression of eaat-2 in females exposed to novel compared to familiar color patterns provides suggestive evidence that females perceive mates as novel.

27 Gene expression directly associated with female preference

Of the 99 genes that showed a direct relationship with preference score, mhc-II was one behavior-related gene that increased in expression level as preference score increased. Recent evidence suggests that MHC genes expressed in the brain, particularly MHC class I genes, play a role in neuronal signaling, neuronal regeneration, synaptic connectivity, and synaptic plasticity in rodents (Corriveau et al. 1998; Oliveira et al. 2004; Goddard et al. 2007; Shatz et al. 2009). In the threespine stickleback, Gasterosteus aculeatus, of the transcripts differentially expressed between fish exposed to cues of a predator and a control group, the majority was related to antigen processing and presentation via MHC class II (Sanogo et al. 2011). Other studies in fish have shown differential expression of MHC genes in those fish that have adopted different life history strategies (Aubin-Horth et al. 2005) and those that are entering into a socially-mediated reproductive change (Renn et al. 2008). While these studies suggest that MHC gene expression plays a role in specific social behaviors, my study is the first to provide a link between mhc-II gene expression and mate preference behavior.

Technical Limitations

While I was able to identify multiple behavior-related genes in the gene lists that were generated from females in the novel and familiar treatment groups, this study had two major limitations. First, I was unable to validate my five chosen genes through qPCR. Four out of the five genes showed expression differences that were in the predicted direction of the RNA-seq data, yet they were not significantly different. Other studies have failed to validate genes through qPCR, in particular those with relatively low fold changes (Mukai et al. 2009; Sanogo et al. 2011). Therefore, I cannot rule out the possibility that the changes in gene expression between treatment groups were too small to be detected by qPCR in this study. To ensure that primer design did not affect qPCR validation, I will be conducting a follow-up qPCR study with distinct primer sets. Second, since my gene lists were relatively small and did not provide an overabundance of clustered categories, the GO analysis was less informative. Of the classes that met my cut-off, however, I found categories that were related to transcription and protein transport, as expected. Cilium, on the other hand, was an unexpected category. Cilia are microtubule-based organelles

28 that project from the surface of cells. Recent evidence has shown that cilia modulate hippocampal neurogenesis, a function that might impact cognitive processes, such as learning and memory (Lee & Gleeson 2010). The role of cilia in behavior is a topic that requires further exploration.

The female novelty preference: sensory biases and future directions

Overall, my results suggest that female preference for novel male color patterns is underlain by a similar neurogenomic response as other forms of novelty-seeking. This is a necessary critical assumption of the hypothesis the preference for novel mates evolved through a behavioral attraction for novelty. In the field of sexual selection, ‘sensory bias’ has been proposed as an explanation for the evolution of female preference by positing that these preferences evolve through natural selection on the sensory system (West-Eberhard 1984; Basolo 1990, 1995, 1998; Proctor 1991, 1992; Ryan 1990, 1998; Ryan et al. 1990; Ryan and Rand 1993a; Ryan and Rand 1993b; Endler and Basolo 1998; Fuller et al. 2005). Sensory biases have been described and reported in a number of species (Basolo 1990; Ryan et al. 1990; Proctor 1991; Rodd et al. 2002; Smith et al. 2004; Kolm et al. 2012). Unlike other studies that have tested for sensory biases, the bias proposed in my study is for novelty- a dynamic and plastic mating response that depends on previous experience. While I found expression of several genes related to novelty-seeking, an explicit test of the sensory bias hypothesis would require behavioral testing of a preference for novel stimuli outside of the mating context. In addition to the five genes discussed above, over 150 other genes were also differentially expressed between females exposed to novel and familiar male color patterns. Investigation into the behavioral basis of these genes could provide new insight into the behavioral genomics field. In addition, a direct comparison of the hormonal signatures of females exposed to novel versus familiar male color patterns could provide further insight into the physiological changes that occur when a female is exposed to a novel mate. For example, Bell et al. (2007) assessed both monoamine neurotransmitters and whole body cortisol stress hormones in stickleback fish presented with predators and unfamiliar conspecifics, providing a full snapshot of the physiological response to particular behavioral stimuli (Bell et al. 2007). Therefore, measuring endocrine changes that occur during female guppy mate choice could

29 elucidate the physiological basis of novel color pattern preference. In conclusion, female guppies show both a behavioral and corresponding genomic change in response to exposure to males with novel versus familiar color patterns. While I did find genes specifically related to novelty-seeking, I found over 150 other genes that were differentially expressed between the novel and familiar behavior treatments, suggesting that female perception of novel mates is physiologically complex and is associated with a series of transcriptional changes. Future studies should be aimed at addressing the behavioral mechanisms driving the female novelty response and the hormonal changes that occur when a female is exposed to a novel, compared to a familiar, mate.

30 CHAPTER THREE

THE BEHAVIORAL MECHANISMS DRIVING FEMALE GUPPY MATE PREFERENCE

3.1 Introduction

The maintenance of genetic variation in traits that are closely tied to fitness, despite evolutionary forces such as selection that are expected to reduce variation, is a long-standing paradox in evolutionary biology (Lewontin 1974). Under directional selection, genetic variation will be determined by a balance between the input of new variation through mutation and the elimination of variation by selection and genetic drift; however, the ability of these forces to generate and maintain the high variation found in natural populations has been debated (Lewontin 1974; Barton & Turelli 1989; Houle 1992; Charlesworth & Hughes 2000; Mitchell- Olds et al. 2007). Various forms of balancing selection, on the other hand, can maintain genetic variation above the levels that are expected through mutation-selection-drift models (Turelli & Barton 2004). In general, however, the contribution of balancing selection to genetic variation in ecologically-important traits is poorly understood (Mitchell-Olds et al. 2007). Recent evidence suggests that sexual selection might be an under-appreciated mechanism for generating balancing selection (Gray & McKinnon 2006). For example, both male-male competition and female preference can generate negative frequency-dependent selection on male secondary sexual traits (Ayala & Campbell 1974; Farr 1977; Hughes et al. 1999; Alonzo & Sinervo 2001; Bleay et al. 2007; Hughes et al. 2013). Negative frequency-dependence is, at least theoretically, capable of maintaining very high levels of genetic variation within populations (Crow & Kimura 1970; Ayala & Campbell 1974). Frequency-dependent sexual selection occurs whenever the departure from random mating is dependent on the frequencies of the genotypes involved (Ayala & Campbell 1974; O’Donald & Majerus 1988). To date, frequency-dependent sexual selection has been implicated in the maintenance of male-limited genetic polymorphism in a few species, including the ruff, Philomachus pugnax (Lank et al. 1995; Hugie & Lank 1996), the side-blotched lizard, Uta stansburiana (Alonzo & Sinervo 2001; Bleay et al. 2007), and guppies, Poecilia reticulata (Farr

31 1977; Hughes et al. 1999; Eakley & Houde 2004; Zajitschek et al. 2006; Olendorf et al. 2006; Zajitschek & Brooks 2008; Hampton et al. 2009; Hughes et al. 2013). The sex-limited color polymorphism in guppies is one of the most genetically variable phenotypes reported in the literature (Brooks and Endler 2001; Hughes et al. 2005). Male color patterns consist of highly reflective structural colors (blue, green, purple, and silver iridescence) and pigment-based colors (yellow, orange, red, and black) that can appear on the body, caudal fin, and dorsal fin and vary in size, position, and shape (Fig. 1.1). Maintenance of this extreme polymorphism has been attributed to female mating preferences for males bearing rare or unfamiliar color patterns (i.e. negative frequency-dependent mate choice, Farr 1977; Hughes et al. 1999; Eakley & Houde 2004; Zajitschek et al. 2006; Zajitschek & Brooks 2008; Hampton et al. 2009; Hughes et al. 2013). Likewise, a male preference for unfamiliar females has also been documented (Kelley et al. 1999). Despite the apparent generality of a female mating preference for novel color patterns in this species, the behavioral mechanisms and evolutionary origin of the novel mate preference remains unknown. One hypothesis for the evolutionary origin of the novel mate preference is that guppies have been selected for increased responsiveness to novel stimuli for reasons unrelated to mating per se. If response to novel stimuli leads to a selective advantage, such as a competitive foraging advantage, then the novel mate preference could be a pleiotropic side-effect of selection for increased efficiency in foraging (Kirkpatrick & Ryan 1991; Hughes et al. 1999). To determine the behavioral mechanisms leading to the negative frequency-dependent mate preference in guppies, here I test the hypothesis that the novel mate preference arose out of a general preference for novelty.

3.2 Methods

3.2.1 Ethics Statement

All experimental procedures were approved by the Animal Care and Use Committee at Florida State University (protocol #0901 & #1142).

32 3.2.2 Behavioral Methods

3.2.2.1 Overview To test the hypothesis that the female preference for males with novel color patterns evolved through a generalized preference for novelty, I compared behavioral responses between male and female guppies exposed to novel inanimate objects in their environment. I tested both non-food and food objects to determine if ecological relevance affected response to inanimate objects. Guppies respond to small, colored, non-food objects in their environment (Rodd et al. 2002). Therefore, I used methods similar to those used in Rodd et al. (2002) to evaluate preference for novel non- food objects. If novelty preference evolved via natural selection (as opposed to sexual) selection, I predicted that both male and female guppies would be attracted to novel objects. Briefly, both male and female guppies were familiarized either to a non-food object or to a food item. Males and females were then presented with a novel object or the same object; individuals presented with a food source were presented with a novel food source or the same food source. Behavior was recorded for 30 minutes. Individuals were randomly assigned to each treatment group. All experiments were conducted between 2010 and 2013.

3.2.2.2 Experimental Fish All fish originated from descendants of wild-caught guppies from a tributary of the Paria River in Trinidad. Experimental males and females were obtained from a stock population of approximately 300 breeding adults. All fish stocks were maintained in groups of approximately 30 adults plus offspring at a density of 1-2 fish per gallon, with inbreeding minimized by transferring adults between stock tanks every 1-2 generations. Males used in the experiment were housed in stock tanks upon maturity and were presumed to have mated. In tests for female novelty preference, I used females from three different reproductive states to account for any behavioral variation that could occur from prior sexual experience. These three reproductive states included virgins, non-virgins immediately post-partum, and non-virgins that were not immediately post-partum. Virgin females were never exposed to mature males. Non-virgin immediately post-partum females (henceforth “non-virgin PP”) had two males placed into their tank approximately 4-8 weeks before experimental trials began. Female tanks

33 were checked every morning for offspring. Upon giving birth, males and offspring were removed from the tank, two small non-focal females were added to reduce stress levels often caused by isolation, and females were immediately provided with the first object. Non-virgin females that were not immediately post-partum were presumed to be non- virgin and pregnant (henceforth “non-virgin”). All virgin and non-virgin PP females were reared in female-only tanks with a density of two females per gallon. Females in the non- virgin treatment were reared in stock tanks. All fish used in the experiment were between 120 and 180 days old and were maintained on a 12:12 h full-spectrum light:dark cycle, at 25º Celsius. Fish were reared and maintained on a commercial flake food and brine shrimp diet, fed ad lib, with the exception of fish used in food preference trials (see description below). All tanks were separated by opaque plastic dividers and kept on a recirculating system; therefore, water quality was identical for experimental tanks.

3.2.2.3 Object Preference Trials Previous work has shown that guppies are attracted to orange and red colored painted disks (Rodd et al. 2002). Therefore, I used objects that had partial orange/red coloration to stimulate female interest, but that differed in other properties. Specifically, the four objects used in this experiment differed in shape, dimensionality (2-D or 3-D), contrasting colors, and amount of orange/red coloration. One object was an American nickel painted half orange and half green (Liquitex Heavy Body acrylic colors: cadmium orange & light emerald green). The other three objects used were various shaped die approximately 8 cm in diameter: triangular red die with white spots, triangular orange die with white spots, and octagon-shaped orange die with white spots. Twenty-four hours before trials began, I placed a focal male or female and two, non-focal fish of the same sex as the focal fish into 30-liter experimental aquaria. Non-virgin PP females were already housed in experimental aquaria, and therefore, did not need tank acclimation time (see description above). At 9:00 AM on trial day one, I dropped the first object into the tank and allowed it to sink to the bottom. Objects were not placed in any particular orientation. Each object was kept in the tank for 48 hours. On test day, the object was removed and replaced with either the same object (‘familiar’ object) or an object that the focal individual had never seen before (‘novel’ object). All

34 objects on test day were placed into the tank in the same orientation and location as the first object. See Fig. 3.1 for a schematic representation of behavioral trials. Behavior during all trials was recorded for thirty minutes using JWatcher V1.0 event recording (Blumstein et al. 2006). Focal individuals were never re-used. Object preference was measured as total time within three body lengths of the object.

3.2.2.4 Food Preference Trials I added virgin females to 19-liter tanks five days before trials began to allow acclimation. Experimental males were added to 30-liter tanks the day of trials and were given a ten-minute acclimation period. At 9:00 AM on trial day one, individuals were randomly given one of two food choices, a green sinking Spirulina Wafer (OSI; Manufacturer Part # 1523) or a tan colored bottom-feeder tablet (Aqueon; Manufacturer Part # 06029). Both items were similar in size and shape, but differed in color. I chose these colors to simulate food sources, such as algae, that occur naturally in Trinidadian streams. Although food sources differed in color, they had identical crude protein, fat, and fiber content. Individuals were allowed 30 minutes to eat the food disk and the disk was then removed from the tank. Additionally, fish were fed a small amount of brine shrimp in the afternoon. This procedure continued for 3 days total and ensured that fish would be hungry the following morning when they received their disk of food. Fish in this experiment were given a slightly longer familiarization period than the previous experiments to ensure they were accustomed to receiving a sinking food source. On test day 4, the same food source was provided to fish as they had been receiving for their familiarization trial period. After 30 minutes, I removed the food and either the same (‘familiar’) or the opposite colored (‘novel’) food source was added to the tank. This procedure ensured that fish only approached food because they recognized it as novel or familiar, rather than approaching food indiscriminately due to hunger. I scored behavior for 30 minutes using the same scoring system as the object trials. Focal individuals were never re-used. See Table 3.1 for a summary of each experiment.

35 Table 3.1 Summary of 4 behavioral experiments. Trial Focal sex Type of fish Non-focal, Length of Length of type used smaller sex acclimation familiarization used to tank period to first object/food Object Male Mated Male 24 hours 48 hours Object Female Virgin, Non- Female 24 hours (or 48 hours virgin post- longer for partum (PP), non-virgin Non-virgin PP) Food Male Mated Male 10 minutes 72 hours Food Female Virgin Female 5 days 72 hours

Figure 3.1 Representation of experimental tank set-up. Focal fish with two, smaller, non-focal fish. One example of an object used in the experiment. Dotted line represents 3 body lengths.

3.2.3 Data Analyses

3.2.3.1 Male Object Experiment I measured the total time an individual spent within a three-body length zone of the object (approximately five centimeters). This measure was

36 referred to as ‘In Zone’, and is a characteristic measure found in behavioral studies assessing interest in objects (Rodd et al. 2002; Bevins & Besheer 2006). Total time In Zone of the object was square-root transformed to improve normality and homoscedasticity of residuals and was analyzed using general linear models with treatment (novel vs familiar) as a fixed effect in the analysis and total time In Zone as a dependent variable in the analysis. Additionally, I used object type (1-4) as a main effect in the model and analyzed the object-by-treatment interaction.

3.2.3.2 Female Object Experiment I measured the total time an individual spent within a three-body length zone around the object (approximately six centimeters). Total time In Zone of the object was square-root transformed to improve normality and homoscedasticity of residuals and was analyzed using general linear models with treatment (novel vs familiar) as a fixed effect in the analysis and total time In Zone as a dependent variable in the analysis. Additionally, I included female reproductive state (virgin, non-virgin PP, and non-virgin) as a main effect in the model, along with all two- way and three-way interactions between female state and other terms in the model (object type, treatment).

3.2.3.3 Male Food Experiment I measured the total time a focal male spent within a three-body length zone around the food (approximately five centimeters). Total time In Zone around the food was square-root transformed to improve normality and homoscedasticity of residuals and was analyzed using general linear models with treatment (novel vs familiar) as a fixed effect in the analysis and total time In Zone as a dependent variable in the analysis. Additionally, I used food type (green or tan) as a main effect in the model and analyzed the food-by-treatment interaction.

3.2.3.4 Female Food Experiment For the female food experiment, I measured the total time a virgin female spent within a three-body length zone around the food (approximately six centimeters). Total time In Zone around the food was square-root transformed to improve normality and homoscedasticity of residuals and was analyzed using general linear models with treatment (novel vs familiar) as a fixed effect in the

37 analysis and total time In Zone as a dependent variable in the analysis. Additionally, I used food type (green or tan) as a main effect in the model and analyzed the food-by- treatment interaction.

To account for observer biases in experiments that had multiple observers, I conducted a preliminary analysis and did not find a significant interaction between observer and familiarization treatment for any experiments. By using total time In Zone as a measure of interest towards objects or food, experiments that were scored by only one observer remained objective. All data met the assumptions of normality and homoscedasticity of residuals. All graphs are depicted using non-transformed data, while all statistics were derived from square-root transformed data.

3.3 Results

3.3.1 Male Object Experiment

I conducted 45 replicates of the male object experiment (21 with familiar objects and 24 with novel objects). Attraction did vary depending on object type with males showing a preference for orange/white octagon shaped die (p = 0.048; Table 3.2; Fig. 3.2), but there was no significant main effect of treatment group (p = 0.88; Table 3.2). There was no significant object*treatment interaction, although males showed a non-significant trend towards a slightly higher preference for some objects when they were novel (p = 0.08; Table 3.2; Fig. 3.3). In particular, males spent more than twice as long near the orange/white octagonal die when it was novel than when it was familiar, and about 50% longer near the orange/white triangular die when it was novel. For the other two objects (half orange/half green American nickel and red/white triangular die), males spent less time near them when they were novel than when they were familiar.

3.3.2 Female Object Experiment

I conducted 64 replicates of the female object experiment (31 with familiar objects and 33 with novel objects). There was no significant main effect of object (p = 0.81; Table 3.3) or treatment

38 (p = 0.84; Table 3.3), and no significant interactions, including object*treatment (p = 0.06; Table 3.3; Fig. 3.4). However, I found a significant main effect of reproductive state (p < 0.0001; Table 3.3; Fig. 3.5) with a post hoc multiple comparisons test using Tukey HSD showing that virgin females respond to objects significantly less overall compared to previously-mated females (p < 0.05), as measured by total time In Zone (approximately 6 centimeters) from object.

3.3.3 Male Food Experiment

I conducted 40 replicates of the male food experiment (20 with novel food and 20 with familiar food). Attraction did not vary depending on food type (p = 0.83; Table 3.4), and there was no effect of familiarity (p = 0.97; Table 3.4). There was, however, a significant food*treatment interaction (p = 0.03; Table 3.4; Fig. 3.6) with males preferring novel green food more than familiar green food and familiar tan food more than novel tan food.

3.3.4 Female Food Experiment

In 40 female food preference trials (20 with novel and 20 with familiar food), attraction did not vary depending on food type (p = 0.11; Table 3.5), there was no effect of treatment (p = 0.12; Table 3.5), and no food *treatment interaction (p = 0.28; Table 3.5; Fig. 3.7).

Table 3.2 Results of general linear model showing the effects of novel object preference (measured by total time In Zone around the object) in male guppies.

Source of Df SS F p Variation Object 3,37 95561.29 2.88 0.048 Treatment 1,37 241.63 0.022 0.88 Object*Treatment 3,37 80446.78 2.42 0.08

39 Table 3.3 Results of general linear model showing the effects of novel object preference in female guppies. Source of Variation Df SS F p

Object 3,40 21995.28 0.33 0.81 Treatment 1,40 943.73 0.04 0.84 Object*Treatment 3,40 182282.23 2.70 0.06 Female State 2,40 720505.49 16.02 <.0001 Female State*Object 6,40 225644.93 1.67 0.15 Female State*Treatment 2,40 28416.68 0.63 0.54 State*Obj*Treat 6,40 289658.08 2.15 0.07

Table 3.4 Results of general linear model showing the effects of novel food preference in male guppies.

Source of Df SS F p Variation Food 1,36 1822.04 0.05 0.83 Treatment 1,36 48.92 0.01 0.97 Food*Treatment 1,36 194738.64 5.22 0.03

Table 3.5 Results of general linear model showing the effects of novel food preference in female guppies.

Source of Df SS F p Variation Food 1,36 344406.76 2.71 0.11 Treatment 1,36 322385.86 2.54 0.12 Food*Treatment 1,36 155081.48 1.22 0.28

40

A AB

B B

1 2 3 4

Figure 3.2 Response to individual objects in male guppies. LS Mean + SE Total time In Zone around the object within 3 body lengths for each object; Each number represents a different object (1=half orange/half green American nickel; 2= orange/white octagon die; 3=orange/white triangle die; 4=red/white triangle die); N=11, 15, 10, & 9, respectively. Means with different letters are significantly different (Student’s t-test, p<0.05).

100

80

60 40

20 Familiar Novel 0 -20

Total Total Time In Zone (seconds) -40 1 2 3 4 Object

Figure 3.3 Response to each object varied by treatment group in male guppies. LS Mean + SE Total time In Zone for males within 3 body lengths of each object in each treatment group (novel or familiar); Each number represents a different object (1=half orange/half green American nickel; 2= orange/white octagon die; 3=orange/white triangle die; 4=red/white triangle die); Object 1: N=6 familiar, 5 novel, Object 2: N=9 familiar, 6 novel, Object 3: N=2 familiar, 8 novel, Object 4: N=4 familiar, 5 novel.

41

350

300 250

200 150 Familiar 100 Novel 50 0 Total Total Time In Zone (seconds) -50 1 2 3 4 Object

Figure 3.4 Response to each object varied by treatment group in female guppies. LS

Mean + SE Total time In Zone for females within 3 body lengths of each object in

each treatment group (novel or familiar); Each number represents a different object

(1=half orange/half green American nickel; 2=orange/white octagon die;

3=orange/white triangle die; 4=red/white triangle die); Object 1: N=11 familiar, 11

novel, Object 2: N=8 familiar, 10 novel, Object 3: N=7 familiar, 6 novel, Object 4:

N=5 familiar, 6 novel. Data is pooled across all 3 female reproductive states.

Figure 3.5 Assessment of objects for each female reproductive state. LS Mean + SE Total time In Zone within 3 body lengths of object. Data is pooled across treatment groups (novel/familiar) for each female reproductive state; N=18, 26, & 20, respectively. Means with different letters are significantly different (Tukey HSD p<0.05).

42

200

150

100

50

Total Time In Zone (Seconds) 0

Familiar Novel -50 Treatment Group

Figure 3.6 Response to each food source varied by treatment group in

male guppies. LS Mean + SE Total time In Zone within 3 body lengths

for each food disk in each treatment group (novel or familiar); Tan=tan

bottom-feeder disks, Green=spirulina green food disk; N=10 for each

bar.

Figure 3.7 Response to each food source varied by treatment group in female guppies. LS Mean + SE total time In Zone within 3 body lengths of food disk.

43 3.4 Discussion & Conclusions

Overall, my results do not provide consistent strong support of a preference for novel stimuli outside of the mating context. While male guppies showed a significant preference for orange/white octagonal die and a non-significant trend towards a preference for orange/white octagonal die when it was novel, overall, they did not prefer novel objects more than familiar objects. The preference for the orange-colored die, however, could be the result of a previously documented bias for orange color (Rodd et al. 2002). Moreover, male guppies showed a slight preference for the orange/white triangular die, which had an equal amount of orange color as the octagonal die, and a slight preference for that object when it was novel. In addition, male guppies showed a significant preference for novel green food, along with familiar tan food. Female guppies, on the other hand, did not show a significant preference for novel objects or food. Therefore, I did not find a strong preference for environmental novelty, overall. If guppy females do not show a bias for novel stimuli, then the evolution of the mating preference could have evolved for other adaptive reasons, such as inbreeding avoidance. Evidence suggests that both male and female guppies prefer rare or unfamiliar mates (Farr 1977; Hughes et al. 1999; Kelley et al. 1999; Eakley & Houde 2004; Zajitschek et al. 2006; Zajitschek & Brooks 2008; Hampton et al. 2009) and there is inbreeding depression for multiple traits related to fitness (Farr 1983; Sheridan & Pomiankowski 1997; Nakadate et al. 2003; van Oosterhout et al. 2003; Mariette et al. 2006; Pitcher et al. 2008; Zajitschek et al. 2009). Therefore, a preference for unfamiliar mates could have evolved to increase the likelihood of mating with non-kin (Brooks 2002; Johnson et al. 2010), a problem that may be more common during the dry season when pools desiccate and guppies can become isolated (Griffiths & Magurran 1997), and in the upstream portions of river drainages in which effective population sizes can be low (Barson et al. 2009). Evidence of a female preference for less-related mates remains equivocal, however. Two studies conducted in lab populations of guppies found no difference in the mating behavior of virgin females towards unrelated versus full-sibling mates (Viken et al. 2006; Zajitschek & Brooks 2008). In another lab-based study that compared female preference for siblings versus non-siblings, females did not exhibit differential sexual responsiveness and males did not differ in the number of copulatory attempts between treatment groups (Pitcher et al. 2008). A study

44 conducted by Johnson et al. (2010) used polymorphic molecular markers to assess both inbreeding depression and avoidance in a natural population of guppies. Results showed that males more distantly related to females produced a greater number of offspring and females demonstrated a non-significant trend towards a preference for avoiding closely-related mates. Other organisms, such as naked mole rats (Heterocephalus glaber), exhibit preferences for unfamiliar mates, but not necessarily, less related mates (Clark & Faulkes 1999). If males with novel color patterns are, on average, less related to females within a pool, then females might use the color pattern of males to recognize and choose individuals that are unlikely to be kin (i.e. males with unfamiliar color patterns, Brooks 2002). Future studies should be designed to examine the role of unsolicited mating attempts by males, or other behavioral mechanisms, that might prevent females from exercising a preference for less-related mates. In addition to inbreeding avoidance, the possibility remains that by choosing dissimilar mates during each bout of mating, females can maximize the genetic diversity of their offspring (Brooks 2002). Female guppies mate with multiple males and will store sperm of multiple males (Kelley et al. 1999; Evans & Magurran 2000; Pitcher et al. 2003; Johnson et al. 2010; Lopez- Sepulcre 2013). Therefore, in addition to choosing a less-related mate, females that can recognize previous may incur a fitness advantage through multiple mating (Brooks 2002). The fitness benefits of multiple mating remain controversial (Jennions & Petrie 2000), however, and assume that higher heterozygosity corresponds with higher fitness. Likewise, females may gain a selective benefit from choosing rare males through a rarity benefit to their sons (i.e. ‘Sexy Sons’), yet this model assumes that only a small proportion of females within a population demonstrate the rarity preference (Kokko et al. 2007). Both of the proposed hypotheses remain to be tested. While I did not find a strong and consistent preference for novel stimuli in this study, I cannot rule out the possibility that that the objects used in my experiment were not salient to guppies. A study that assessed a bias for orange coloration showed that guppies displayed differential preferences for objects of various colors (Rodd et al. 2002). Since I used objects that were similar in size and shape to those used in Rodd et al. (2002), it is unlikely that the objects used in my study were undetectable or stressful to guppies. Furthermore, both female and male guppies across treatment groups showed slight preferences for particular objects and food types, suggesting that they could distinguish among novel stimuli used in this study. In addition, I

45 cannot rule out the possibility that guppies would show differential exploration of novel versus familiar environments, rather than novel versus familiar objects. While I used object approach and avoidance behavior to measure novelty-seeking, studies conducted in other species, such as rodents, have used novel-environment paradigms to measure exploratory and novelty-seeking behavior (Eilam & Golani 1989). A study that used this paradigm in guppies demonstrated age- dependent changes in exploration level in novel environments (Mikheev & Andrew 1993). However, zebra fish placed in novel environments exhibit anxiety-like behavior (Wright et al. 2003; Maximino et al. 2010). Therefore, fish, such as guppies, could be particularly sensitive to the effects of a novel environment and assessment of preference behavior could be confounded with stress levels when using these paradigms. In summary, while I did find slight color-specific novelty preferences in male guppies, my results do not provide strong, consistent support for the hypothesis that the female guppy novel mate preference evolved out of a behavioral preference for environmental novelty. Future studies should be designed to further elucidate the role of alternative evolutionary forces, such as inbreeding avoidance or increased offspring heterozygosity, that are potentially driving frequency-dependent mating patterns in guppies. Additionally, an alternative measurement of novelty-seeking, such as a novel-environment paradigm, would provide further assessment of novelty preferences in this population of guppies.

46 CHAPTER FOUR

FEMALE PREFERENCE IN POECILIA PICTA

4.1 Introduction

The maintenance of extensive genetic variation in natural populations of animals, in the force of selection expected to erode variation, is a central paradox in evolutionary biology (Lewontin 1974). While several evolutionary forces can account for genetic polymorphism seen in wild populations of animals (Barton & Turelli 1989; Charlesworth & Hughes 2000; Hughes & Sawby 2004), behavioral mechanisms, such as female mate preference, are often overlooked sources of variation. Although there is evidence that in some species, females prefer males with reliable indicators of fitness (Hamilton & Zuk 1982; Iwasa et al. 1991; Folstad & Karter 1992; Rowe & Houle 1996; Houle & Kondrashov 2002; Kokko et al. 2003; Mead & Arnold 2004; Bonduriansky & Rowe 2005; Neff & Pitcher 2005; Andersson 2006), female preference in many species may not be fixed; rather, preference can be quite dynamic and plastic, and be dependent on multiple factors (Gibson & Langen 1996; Jennions & Petrie 1997). One form of plastic female choice that can maintain variation in natural populations is frequency-dependent mate preference. Frequency-dependent sexual selection occurs whenever the departure from random mating is dependent on the frequencies of the genotypes within a population (Ayala & Campbell 1974; O’Donald & Majerus 1988). Unlike stabilizing or directional selection, negative frequency-dependent selection can maintain extensive genetic variation within natural populations (Crow & Kimura 1970; Ayala & Campbell 1974; Barton & Turelli 1989; Hughes & Sawby 2004; Mitchell-Olds et al. 2007). To date, the maintenance of genetic variation through negative frequency-dependent selection has been supported in a limited number of species (Cain & Sheppard 1954; Antonovics & Ellstrand 1984; Hughie & Lank 1996; Mallet & Joron 1999; Alonzo & Sinervo 2001; Lindholm et al. 2004; Pierotti et al. 2009; Joly & Schoen 2011). In the Trinidad guppy, Poecilia reticulata, negative frequency-dependent selection has received strong support as the primary driver of the extreme genetically-based male color polymorphism in wild populations (Farr 1977; Hughes et al. 1999; Eakley & Houde 2004; Olendorf et al. 2006;

47 Zajitschek et al. 2006; Zajitschek & Brooks 2008; Hampton et al. 2009; Hughes et al. 2013). Poeciliid fishes are popular models in the study of sexual selection because many species exhibit male color polymorphism, elaborate courtship displays, and extreme sexual dimorphism (Bisazza 1993; Andersson & Simmons 2006). Poecilia picta, more commonly referred to as the ‘swamp guppy’, is the close relative of the guppy (Breden et al. 1999; Hrbeck et al. 2007; Meredith et al. 2010; Meredith et al. 2011). Male color patterns vary between populations, but are either monomorphic or exhibit two, discrete morphs within populations (pers. comm. F. Breden, Simon Fraser University). While the majority of males within discretely polymorphic populations exhibit the same color pattern, a small percentage of males exhibit a unique color pattern. Similar to guppies, females lack conspicuous coloration in all populations (pers. comm. F. Breden). While guppies provide one of the best-documented examples of mating patterns promoting genetic variation through a well-documented female preference for males with rare or novel color patterns (i.e. negative frequency-dependent mate choice) (Farr 1977; Hughes et al. 1999; Eakley & Houde 2004; Zajitschek et al. 2006; Zajitschek & Brooks 2008; Hampton et al. 2009), the contribution of female preference towards the maintenance of the discrete polymorphism in P. picta populations remains unknown. To determine whether a frequency-dependent mate preference is operating in a discretely polymorphic P. picta population, I first characterized the courtship and mating behavior of P. picta. I then conducted a mate choice color experiment to determine whether P. picta females show an inherent preference for males with a color pattern that occurs at a low frequency in the wild (i.e. rare males). Finally, I used a sequential choice test to determine whether females exhibit a preference for males with novel, compared to familiar, color patterns.

4.2 Methods 4.2.1 Ethics Statement

All experimental procedures were approved by the Animal Care and Use Committee at Florida State University (protocol # 1332).

48 4.2.2 Behavioral Methods

4.2.2.1 Overview To test the hypothesis that females show a preference for locally rare and/or novel color patterns, I completed two experiments. Based on my preliminary observations, females were more responsive to pairs of males than to a single male. Therefore, females were exposed to male pairs in both of the following experiments. The first experiment assessed a female’s overall preference for male color pattern, using simultaneous-choice trials. Briefly, female P. picta were provided with two males that each represented the two color patterns that occur in the natural population from which the experimental fish were derived. The females’ behavior towards one focal male was assayed. This experiment allowed me to determine if females have an inherent preference for either of the two naturally occurring morphs, and, more specifically, to determine if they prefer the locally rare color morph. The second experiment asked whether females show a preference for males with novel color patterns, irrespective of the morph type. Briefly, females were familiarized to a set of ‘matched’ males for 48 hours. After the 48- hour familiarization period, females were either presented with two males that had the same color pattern as the first two males (familiar treatment) or two males that had the alternate pattern (novel treatment). After introduction of the second pair, female behavior was recorded for 30 minutes. Individuals were randomly assigned to each treatment group. All experiments were conducted between April and December of 2013.

4.2.2.2 Experimental Fish All fish originated from offspring of wild-caught fish collected from Georgetown, Guyana, supplied by F. Breden (Simon Fraser University). Fish were collected from canalized sewerage outlets that have low light, high sediment levels, and low vegetation. Fish used for experiments were descended from four, polymorphic-male, field sites that were bred together for approximately 3-4 generations (GPS coordinates: 06 31.643’N, 058 15.062’W; 06 49.520’N, 058 08.637’W; 06 48.332’N, 058 08.720’W; 06 48.045’N, 058 09.086’W). In general, field collection sites consisted of brackish water conditions composed of high fish densities. Salinity specific gravity (d 20/20) ranged from 1.000-1.003, 0-4 parts per thousand (0/00), and pH ranged from 6.5-7.0.

49 Males from polymorphic populations either have a yellow/gold body color or an orange/blush body color with orange, yellow, and black markings on their body, tail, and dorsal fin (Fig. 1.3). The ratio of gold-colored morphs to blush-colored morphs is approximately 4 to 1 in natural polymorphic populations (pers. comm. F. Breden, Simon Fraser University). All experimental fish were obtained from a stock population of approximately 50 breeding adults. Fish stocks were maintained in groups of 3-5, with inbreeding controlled for by collecting all offspring before maturity. Additionally, breeding adults were shuffled between stock tanks every 2-3 months. Upon maturation, experimental males were housed with un-related stock females to ensure they had sexual experience prior to beginning behavioral trials. Experimental females were removed from stock tanks upon maturation and housed with other females. Stock tanks and female- holding tanks were kept in both 2.5- (9.5-liter) and 10-gallon (38-liter) aquaria with a maximum density of 3 fish per gallon. While guppies show peak receptivity when they are virgin (i.e. non-mated) and shortly after giving birth (Houde 1997), evidence for increased receptivity in virgin P. picta is limited. Liley (1966) reported that virgin and non-virgin P. picta females did not show a significantly different number of approaches or copulations with males, yet males did exhibit increased responsiveness and a greater number of thrusts towards virgins. Therefore, to control for previous experience in females and to ensure male’s responsiveness, all females used in the experiment were virgin. Experimental females were between 90 and 180 days old when they were used in preference trials. Males were between 90 days and one year old. Experimental animals were maintained on a 12:12 h light:dark cycle using a full spectrum light source, at 26º Celsius. Fish were reared on a commercial pellet food and brine shrimp diet, fed ad lib twice per day. All tanks were separated by opaque plastic dividers. Both home tanks and experimental tanks were kept on the same recirculating system; therefore, all aspects of water quality were identical across tanks.

4.2.2.3 Behavioral Paradigm: Mate Color Preference Experiment At 2:00 PM on experiment day one, a virgin female was removed from her home tank and placed into a 5-gallon (19-liter) experimental tank to allow acclimation. At 9:00 AM on experiment

50 day two, a pair of males from stock tanks was added to the experimental tank. Male pairs consisted of one gold and one blush male. I visually inspected male pairs to match them for size and age. Males were never from the same stock tanks as females, and were therefore unrelated to females. I recorded female behavior towards one focal male, chosen randomly, for 30 minutes using JWatcher V1.0 event recording (Blumstein et al. 2006). Females were never re-used but approximately 50% of male pairs were used twice. To account for any differences in pair behavior, I conducted a preliminary analysis using all dependent variables described below and did not find a significant main effect of male pair in any general linear model. Behavior was scored by multiple observers; therefore, observer was included as a main effect in data analyses.

4.2.2.4 Behavioral Paradigm: Novel Morph Preference Experiment At least 24 hours before trials began, I visually matched pairs of males based on similarity in color pattern and size. Pairs were deemed to be matched if the size, color, and location of theirs spots and other body markings were closely matched (approximately 90%). Male pairs were housed with two stock females prior to being used for experiments. At 9:00 AM on day one of the experiment, a male pair was placed into the experimental aquaria along with one virgin female. Males were allowed to freely interact with the female for 48 hours. On day three, the male pair was gently netted out of the tank and the second male pair (‘familiar’ or ‘novel’) was added to the tank. Novel male pairs were closely matched using the criteria described above, but were opposite in color from the first pair. Familiar male pairs were matched to the first pair of males in size, color, and most body markings. Behavior was recorded for 30 minutes using JWatcher. Since males within a pair were nearly identical and I could not distinguish them from one another, I scored female behavior towards both males (i.e. a pair was considered one male for scoring and data analysis). Focal females were not re-used; 12 out of 16 male pairs were re-used between 2 & 4 times. To account for any differences in pair behavior, I conducted a preliminary analysis using all dependent variables described below and did not find a significant main effect of male pair in any general linear model. All data was scored by the same experimenter using the non-objective behavioral criteria described below.

51 4.2.2.5 Behavioral Characterization All behaviors were characterized from approximately two months of observing fish in different social environments for a total of 40 hours of observation. Behaviors were observed from fish in approximately ten mixed- sex stock tanks with a 1:1 sex ratio, ten two-male/one-female groups, ten one-male/two- female groups, and ten single pair groups. In addition, male color was controlled for, with each social environment composed of either all blush, all gold, or mixed males. Density was held constant at approximately one to two fish per gallon for all behavioral observations. Both virgin and non-virgin females were used in all social environments described above. All behaviors that occurred during observations were recorded and compared to a previous ethogram developed for P. picta (Liley 1966). While there was overlap between the list of behaviors generated from my observations and the list generated previously, Liley (1966) listed a small subset of behaviors that I did not observe, including tilting, vigorous swimming, and evading. These behaviors could be population-specific, as Liley (1966) did not account for population in his analyses. Similarly, Liley collected fish from several field sites, but did not account for level of male color polymorphism (monomorphic vs. discretely polymorphic). In addition, behaviors characterized from Liley (1966) were collected from female-biased, mixed-sex tanks. While I did conduct behavioral observations from female-biased, along with male- biased groups, I did not use female-biased, mixed-sex tanks. All behaviors that were naturally longer in duration were characterized as ‘states’ (Table 4.1), while behaviors that were temporally shorter, or occurred in bouts, were characterized as ‘events’ (Table 4.2; Altmann 1974). ‘In Zone’ and ‘Out of Zone’ were mutually exclusive but were non- mutually exclusive with the other states. All other states and events were mutually exclusive with each other.

52

Table 4.1. Behavioral characterization of P. picta female behavioral states.

Non-Sexual States

Behavior Description In Zone Female is within 3 body lengths of male. Can be initiated and maintained by either the male or the female.

Out of Zone Female is not within 3 body lengths of male. Can be initiated and maintained by either the male or the female.

Swimming Female is actively moving through the water column with fins moving.

Frozen Female is not moving through water column for more than 3 seconds; motionless.

Glass-running Female is swimming along the surface of the glass with her rostrum touching the glass; can be either horizontal or vertical.

Sexual-Related States

Behavior Description Chasing Female swims briskly behind male with fins back.

Tail Flicking Female swings her caudal peduncle towards male briskly.

Pecking Female nips at the male.

53 Table 4.2. Behavioral characterization of P. picta female behavioral events.

Behavior Description In response to a male display? No Response Female ignores male display. Y

Positive Response Female orients her body towards or moves Y towards displaying male.

Glide Response Female bends her body, ceases movement Y of fins, and glides her body towards displaying male.

Copulation Attempt Female circles around in unison with the Both male; presumed to be an attempt to mate. Approach Female ceases activity and moves briskly N from out of zone ( > 3 body lengths) towards the male’s zone (< 3 body lengths); once In Zone (< 3 body lengths), female briefly stops in the male’s zone; Alternatively, approach can be scored more than once if the female remains in the male’s zone for more than 3 seconds (i.e. continued approach). Glide Female bends her body, ceases movement N of fins, and glides her body towards male.

4.2.3 Data Analyses

For both experiments, I did not analyze any dependent variables that did not occur in at least 25% of the behavioral trials (i.e. columns with mostly zeros) including glass running, chasing, tail flicking, pecking, glide (not in response to a display), and all three sexual events that occur in response to a display. In addition, ‘Out of Zone’ was not analyzed because it was the inverse of ‘In Zone’; therefore, it provided no additional information. Remaining behaviors (approach, frozen, swimming, and In Zone) were objective behaviors that ensured consistency and reliability in scoring.

54 4.2.3.1. Mate Color Preference Experiment I measured the number of female approaches towards the focal male morph and the total time a female spent swimming, frozen, and ‘In Zone (< 3 body lengths)’ of the male throughout the 30-minute trial. Swimming, frozen, and ‘In Zone’ met the assumptions of normality and homoscedasticity of residuals. The number of approaches, however, was log transformed to improve normality and homoscedasticity of residuals. All dependent variables were analyzed using a general linear model with focal male color as a main effect in the analysis. Observer and the observer-by-focal male color interaction were also included in all general linear models.

4.2.3.2 Novel Morph Preference Experiment I measured the number of female approaches towards either male of a pair, and the total time a female spent swimming, frozen, and ‘In Zone’ (< 3 body lengths) of either male throughout the 30-minute trial. Swimming, frozen, and ‘In Zone’ met the assumptions of normality and homoscedasticity of residuals. The number of approaches, however, was log transformed to improve normality and homoscedasticity of residuals. All dependent variables were analyzed using a general linear model with treatment (novel vs. familiar male pair) and male pair color as fixed effects in the analysis. Pair color and the treatment-by-pair color interaction term were also included in all general linear models.

4.3 Results

4.3.1 Mate Color Preference Experiment

I conducted 40 replicates of the mate color preference experiment (20 females scored for their behavior towards gold males and 20 females scored for their behavior towards blush males). Three separate observers scored behavior: observer one scored 12 blush and 14 gold trials, observer two scored 3 blush and 1 gold trial, and observer three scored 5 blush and 5 gold trials). Overall, there was no significant main effect of male color pattern on the number of female approaches (p=0.33; Table 4.3; Fig. 4.1), the total time a female spent ‘In Zone’ of the male (p=0.88; Table 4.4), the total time a female spent swimming (p=0.46; Table 4.5), or the total

55 time a female spent frozen (p=0.72; Table 4.6) within the 30-minute trial periods. I did not find a significant main effect of observer in any models, nor an observer*treatment interaction.

4.3.2 Novel Morph Preference Experiment

I conducted 32 replicates of the novel morph preference experiment (9 with females exposed familiar blush pairs, 8 with females exposed to familiar gold pairs, 7 with females exposed to novel blush pairs, and 8 with females exposed to novel gold pairs). Overall, there was a significant main effect of the novel versus familiar treatment, with females showing a greater number of approaches towards novel compared to familiar male pairs (p=0.03; Table 4.7; Fig. 4.2). There was no significant main effect of treatment for the total time a female spent ‘In Zone’ of the male (p=0.15; Table 4.8), the total time a female spent swimming (p=0.58; Table 4.9), or the total time a female spent frozen (p=0.84; Table 4.10). In addition, there was no main effect of pair color in any of the models. However, while the treatment*pair color interaction was not significant for the total time a female spent swimming (p=0.07; Table 4.9) or the total time a female spent frozen (p=0.07; Table 4.10), I found a trend towards an increase in female activity (i.e. swimming) when presented with familiar gold pairs (Fig. 4.3) and an increase in freezing when gold pairs were novel (Fig. 4.4). All graphs are depicted using non-transformed data.

Table 4.3 Results of general linear model in the mate color preference experiment showing the effects of focal male color and observer on the log-transformed number of female approaches. Df SS F p Source of Variation Focal Male Color 1,34 2.09 0.99 0.33 Observer 2,34 0.18 0.04 0.96 Observer*Focal 2,34 8.69 2.07 0.14 Male Color

56

Table 4.4 Results of general linear model in the mate color preference experiment showing the effects of focal male color and observer on the total time ‘In Zone’ < 3 body lengths (seconds).

Df SS F p Source of Variation Focal Male Color 1,34 4323904 0.02 0.88 Observer 2,34 55853000 0.14 0.87

Observer*Focal 2,34 771770000 1.93 0.16 Male Color

Table 4.5 Results of general linear model in the mate color preference experiment showing the effects of focal male color and observer on the total time swimming (seconds). Df SS F p Source of Variation Focal Male Color 1,34 127100000 0.55 0.46 Observer 2,34 134340000 0.29 0.75 Observer*Focal 2,34 82177000 0.18 0.84 Male Color

Table 4.6 Results of general linear model in the mate color preference experiment showing the effects of focal male color and observer on the total time frozen (seconds). Df SS F p Source of Variation Focal Male Color 1,34 26227000 0.13 0.72 Observer 2,34 304080000 0.78 0.47 Observer*Focal 2,34 21647000 0.06 0.95 Male Color

57 Table 4.7 Results of general linear model in the novel morph preference experiment showing the effects of treatment and pair color on the log-transformed number of female approaches. Df SS F p Source of Variation Treatment 1,28 13.76 0.29 0.03 Pair Color 1,28 1.83 0.70 0.41 Treatment*Pair 1,28 0 0 0.98 Color

Table 4.8 Results of general linear model in the novel morph preference experiment showing the effects of treatment and pair color on the total time ‘In Zone’ < 3 body lengths (seconds).

Df SS F p Source of Variation Treatment 1,28 292100000 2.21 0.15 Pair Color 1,28 47438000 0.36 0.55 Treatment*Pair 1,28 681447.76 00.01 0.94 Color

Table 4.9 Results of general linear model in the novel morph preference experiment showing the effects of treatment and pair color on the total time swimming (seconds).

Df SS F p Source of Variation Treatment 1,28 57853000 0.31 0.58 Pair Color 1,28 11506000 0.06 0.81 Treatment*Pair 1,28 665580000 3.52 0.07 Color

58

Table 4.10 Results of general linear model in the novel morph preference experiment showing the effects of treatment and pair color on the total time frozen (seconds).

Df SS F p Source of Variation Treatment 1,28 8246344.53 0.04 0.84 Pair Color 1,28 4609062.42 0.02 0.88 Treatment*Pair 1,28 704050000 3.66 0.07 Color

6

5

4

3

2 Number Number of Approaches 1

0 Gold Blush Focal Male Color

Figure 4.1 LS Mean + SE Number of female approaches towards each focal male color in the mate color preference experiment. N = 20 gold; N = 20 blush.

59

7

6

5

4

3

2

Number Number of Approaches 1

0 Familiar Novel Treatment

Figure 4.2 LS Mean + SE Number of female approaches towards novel or familiar male pairs in the novel morph preference experiment. Familiar N = 17; Novel N = 15.

2000 1800 1600 1400 1200 1000 Familiar 800 Novel 600 400

Total Total Time Swimming (seconds) 200 0 Blush Gold Pair Color

Figure 4.3 LS Mean + SE Total time swimming for females presented with each pair color in each treatment group in the novel morph preference experiment. Familiar blush N=9, Novel blush N=7, Familiar gold N=8, Novel gold N=8.

60

700

600

500 400

300 Familiar 200 Novel 100

Total Total Time Frozen (seconds) 0 -100 Blush Gold

Pair Color

Figure 4.4 LS Mean + SE Total time frozen for females presented with each pair color in each treatment group in the novel morph preference experiment. Familiar blush N=9, Novel

blush N=7, Familiar gold N=8, Novel gold N=8.

4.4 Discussion & Conclusions

Overall, my results suggest that negative frequency-dependent mate preferences are operating in P. picta females. While I did not see a significant difference in female behavior towards gold or blush males in the mate color preference experiment, I found a significantly greater number of approaches towards males with novel color patterns in the novel morph preference experiment. These results are consistent with other studies in closely-related species demonstrating a female preference for rare or novel male color patterns (Farr 1977; Hughes et al. 1999; Bourne et al. 2003; Eakley & Houde 2004; Zajitschek et al. 2006; Zajitschek & Brooks 2008; Hampton et al. 2009; Hurtado-Gonzales et al. 2010). If females in natural populations of P. picta express novel morph preferences similar to the females used in my experiment, then frequency-dependent selection could be promoting genetic variation in male color patterns within polymorphic populations of this species.

61 Sexual selection through male competition

In addition to a female preference for novel male pairs, I found a non-significant trend towards an increase in female activity (i.e. swimming) when presented with familiar gold pairs and an increase in freezing when gold pairs were novel. I therefore cannot rule out the possibility that male-male competitive interactions or male-specific behavior is driving female mating preferences or directly influencing variation. Based on my results, it is possible that gold pairs were differentially affecting female behavior and may be behaving differently than blush males, overall. While I did not measure male-specific competitive interactions or male behavior in my experiment, other studies have shown that male competition can affect both female choice and the maintenance of polymorphism (Lank 1995; Alonzo & Sinervo 2001; Kingston et al. 2003; Hurtado-Gonzales & Uy 2009; Hurtado-Gonzales & Uy 2010) and a recent study found a high number of aggressive encounters between males of a monomorphic P. picta population (Bierbach et al. 2013). Therefore, a detailed analysis of male behavior in polymorphic populations of this species might uncover alternative reproductive or behavioral strategies between the two morphs that are potentially affecting the maintenance of color pattern variation.

Alternative evolutionary drivers of color pattern variation

The role of alternative evolutionary forces thought to drive genetic variation in other, closely- related species, requires further exploration in natural populations of P. picta. In the guppy, both frequency-dependent mating preferences and frequency-dependent survival have been shown to occur simultaneously and possibly drive genetic variation (Farr 1977; Hughes et al. 1999; Eakley & Houde 2004; Olendorf et al. 2006; Zajitschek et al. 2006; Zajitschek & Brooks 2008; Hampton et al. 2009; Fraser et al. 2013; Hughes et al. 2013). Likewise, in the pentamorphic fish, P. parae, both females and predators prefer the locally rare morph (Hurtado-Gonzales & Uy 2009; Hurtado-Gonzales & Uy 2010; Hurtado-Gonzales et al. 2010). Therefore, future studies in P. picta should be aimed at addressing the predation regime and predator preferences to determine if predation is affecting color pattern variation both within and across populations. In addition to predator behavior, other environmental factors, such as signaling environment, could potentially explain the varying levels of polymorphism across P. picta populations. For example,

62 both male traits and female preferences can be ‘driven’ by the evolution of the signaling environment through differences in light transmission, perceptual tuning, and signal matching (Endler 1992, 1993; Endler & Basolo 1998; Boughman 2001, 2002; Smith et al. 2012). It is therefore possible that females’ perception of male morphs in different light environments has influenced the evolution and persistence of male color pattern within and across P. picta populations. In summary, my results indicate that P. picta females demonstrate a preference for males with novel color patterns in a laboratory setting, as measured by the number of approaches. While I did not find a significant correlation between approach and copulation attempt in this study, it is possible that females in my study would have mated over a period of hours or days. Future studies should evaluate the usefulness of the approach variable as a measure of female preference. If negative frequency-dependent mate preferences do, in fact, operate in natural populations, it could maintain the discrete polymorphism in male color patterns observed in polymorphic populations. While this study provided unique insight into the behavioral mechanisms potentially driving variation in this species, multiple hypotheses for the maintenance of polymorphism remain to be tested. Likewise, the mode of inheritance of the two color morphs in P. picta remains unknown. Future studies should be designed to test the influence of sexual selection through male-male competitive interactions and the influence of other evolutionary forces, such as frequency-dependent natural selection, that can potentially drive color pattern variation within and across populations of P. picta. In addition, field tests of novel color pattern preferences are needed to determine whether frequency-dependent selection is driving male color pattern variation.

63 CHAPTER FIVE

CONCLUSION

Poecillids are an invaluable resource for understanding the causes and consequences of genetic variation. While many species within the Poecillid family exhibit sexual dimorphism and polymorphism in color pattern, guppies represent a unique case of extreme genetically-based polymorphism in an ecologically-important trait. A role for behavior, through both predator and mate preference, in shaping the polymorphism in guppies has been extensively demonstrated; however, the evolutionary origin of the mating preference was not known. The first goal of my dissertation was to determine the behavioral and genomic mechanisms underlying negative-frequency dependent mating preferences in guppies. Overall, my results provide suggestive evidence that the female guppy preference for novel mates did not originate from a novelty bias in a natural selection context. Results from Chapter 2 show that female guppies exhibit both a behavioral and corresponding genomic change in response to presentation of males with novel versus familiar color patterns. Based on my gene lists, females seem to perceive males as both mates and as novel at the level of the sensory system. While I did detect the up-regulation of genes specifically related to novelty-seeking when females encountered novel males, I found over 150 other genes that were differentially expressed between the novel and familiar behaviour treatments, suggesting that female perception of novel mates is physiologically complex and is correlated with a series of transcriptional events. To determine the behavioral mechanisms that are driving negative frequency-dependent mate preference in guppies, I compared the behavioral responses of both male and female guppies exposed to novel versus familiar environmental stimuli in Chapter 3. Overall, I found that neither males nor females show a strong, consistent preference for environmental novelty (objects/food), providing support that the novel mate preference did not originate from a bias for novelty. Future studies in the guppy should be aimed at testing alternative hypotheses for the evolution of the novel male preference, such as inbreeding avoidance. Unlike guppies, polymorphic Poecilia picta populations are composed of males with two distinct color morphs. While the maintenance of variation in guppies has been attributed to negative frequency-dependent section, the ubiquity of frequency-dependent selection across this

64 taxonomic group requires further exploration. The second goal of my dissertation was to determine whether P. picta from a discretely polymorphic population exhibits negative frequency-dependent mate preferences. In Chapter 4, I tested the hypothesis that a frequency- dependent mate preference is operating in natural populations of P. picta, and is potentially maintaining the discrete polymorphism in male coloration. To test this hypothesis, I first examined the mating preferences for males with color patterns that occur at a low frequency in the wild (i.e. rare males). My results showed that females do not have an inherent preference for blush males, the locally rare color pattern. I then asked whether females exhibit a preference for males with novel compared to familiar color patterns. Females exhibited stronger preference behavior (i.e. greater number of approaches) to males with novel compared to familiar color patterns. Overall, my results suggest that a negative frequency-dependent mate preference is operating in discretely polymorphic populations of P. picta and is potentially maintaining the polymorphism in male coloration. Future studies in P. picta should be designed to determine the influence of other selective forces, such as sexual selection through male-male competitive interactions, potentially driving the maintenance of color polymorphism. In addition to polymorphic populations of P. picta, female preference in monomorphic populations warrants further investigation. Using an integrative approach, spanning the fields of neuroscience and evolutionary biology, I have presented unique insight into the proximate mechanisms driving genetic variation. In addition, I provided the first demonstration of the mating patterns in a polymorphic Poecilia picta population. In conclusion, this dissertation has provided critical tests for the role of behavioral and genomic mechanisms shaping genetic variation of ecologically-important traits across Poeciliid species.

65 APPENDIX A

ANIMAL CARE LETTER OF APPROVAL

66 APPENDIX B

EXAMPLES OF FAMILIAR AND NOVEL MALE PAIRS

1a 1b

2a 2b

3a 3b

4a 4b

Figure B.1 Example of ‘Familiar’ male pairs. Males in the left column represent the first male presented to females. Males in the second column represent the corresponding male presented to females on test day.

67

1a 1b

2a 2b

3a 3b

4a 4b

Figure B.2 Example of ‘Novel’ male pairs. Males in the left column represent the first male presented to females. Males in the second column represent the corresponding male presented to females on test day.

68 APPENDIX C

A PRIORI LIST OF NOVELTY-SEEKING GENES

Table C.1 List of genes related to novelty-seeking or exploratory behavior generated from other behavioral genomic studies. Gene Name Direction/Description Reference D4-type dopamine DRD4 exon III polymorphism; D4 Kluger et al. 2002 receptor knockout mice show decreased novelty Holmes et al. 2004 seeking. De Leonibus et al. 2006 Bailey et al. 2007 Blanchard et al. 2009 Liang et al. 2012

D1-type dopamine Related to decreased scouting behavior Liang et al. 2012 receptor in honeybees. Glutamate Related to increased novelty seeking. Liang et al. 2012 transporters Eaat-2 Glutamate Related to increased scouting behavior Liang et al. 2012 transporters Vglut in honeybees. AMPA-type Related to increased scouting behavior Liang et al. 2012 glutamate receptor in honeybees. Glu-RI Glutamate receptor, Related to a decrease in exploratory Alttoa et al. 2010 ionotropic, AMPA3 behavior. Glutamate receptor, Related to a decrease in exploratory Alttoa et al. 2010 ionotropic, N-methyl behavior. D-aspartate 2A. Gamma-aminobutyric Related to an increase in exploratory Alttoa et al. 2010 acid A receptor behavior.

69 APPENDIX D

RESULTS OF TREATMENT (NOVEL / FAMILIAR) AND PREFERENCE ANALYSES

Table D.1 List of 165 genes differentially expressed in females exposed to males with novel versus familiar color patterns. Contigs in bold overlap with those in Table D.2.

Contig Sequence ID Treatment LSMean StdErr Contig10081 Q5RAT4|ENOF1_PONAB Familiar 2.20506166 0.03305464 Contig10081 Q5RAT4|ENOF1_PONAB Novel 2.32275433 0.03116421 Contig10229 Q4V8V1|BM1LA_DANRE Familiar 1.14616041 0.07105025 Contig10229 Q4V8V1|BM1LA_DANRE Novel 1.43588 0.06698682 Contig10318 Q8CDU6|HECD2_MOUSE Familiar 2.44311641 0.13158049 Contig10318 Q8CDU6|HECD2_MOUSE Novel 1.86598288 0.12405528 Contig10718 None available Familiar 0.98511578 0.03962126 Contig10718 None available Novel 1.14099222 0.03735528 Contig10889 Q0Z8I9|MC4R_VULVU Familiar 1.739952 0.05157499 Contig10889 Q0Z8I9|MC4R_VULVU Novel 1.50807082 0.04862536 Contig1144 None available Familiar 0.66956758 0.0505282 Contig1144 None available Novel 0.8986575 0.04763844 Contig11447 Q5R6F2|ARHG3_PONAB Familiar 0.08341565 0.058235 Contig11447 Q5R6F2|ARHG3_PONAB Novel 0.16773288 0.05490449 Contig11557 Q5R680|OAZ2_PONAB Familiar 2.80382262 0.04309512 Contig11557 Q5R680|OAZ2_PONAB Novel 2.92563555 0.04063047 Contig11608 None available Familiar 0.12492504 0.25292069 Contig11608 None available Novel 0.90837947 0.23845591 Contig12595 Q6NT16|S18B1_HUMAN Familiar 1.26577445 0.05138175 Contig12595 Q6NT16|S18B1_HUMAN Novel 1.54838078 0.04844318 Contig13011 None available Familiar 1.78206698 0.03359954 Contig13011 None available Novel 1.88975067 0.03167795 Contig13217 P00367|DHE3_HUMAN Familiar 1.86494372 0.03094374 Contig13217 P00367|DHE3_HUMAN Novel 1.68787027 0.02917403 Contig13444 Q5XH09|CMBL_XENLA Familiar 2.50901581 0.03490447 Contig13444 Q5XH09|CMBL_XENLA Novel 2.66371525 0.03290825 Contig13459 Q8WTP8|AEN_HUMAN Familiar 1.47443737 0.03639715 Contig13459 Q8WTP8|AEN_HUMAN Novel 1.59655597 0.03431556 Contig13924 O55175|CNCG_SPETR Familiar 0.57177287 0.37212014 Contig13924 O55175|CNCG_SPETR Novel 1.65904778 0.35083823 Contig14322 Q5U5R9|HECD2_HUMAN Familiar 2.71048452 0.07613929 Contig14322 Q5U5R9|HECD2_HUMAN Novel 2.38990558 0.07178481 Contig14684 None available Familiar 0.93910131 0.02797262 Contig14684 None available Novel 1.10915926 0.02637284 Contig15967 Q8CDU6|HECD2_MOUSE Familiar 0.60516736 0.05569342 Contig15967 Q8CDU6|HECD2_MOUSE Novel 0.39886864 0.05250826

70 Table D.1-continued

Contig Sequence ID Treatment LSMean StdErr Contig16320 None available Familiar 0.82319132 0.0469458 Contig16320 None available Novel 1.12395034 0.04426092 Contig16357 Q4G148|GXLT1_HUMAN Familiar 2.41521624 0.02348756 Contig16357 Q4G148|GXLT1_HUMAN Novel 2.29821586 0.02214429 Contig16629 None available Familiar 0.34114602 0.09017613 Contig16629 None available Novel 0.02909201 0.08501888 Contig1680 Q5VZL5|ZMYM4_HUMAN Familiar 3.35885334 0.04012739 Contig1680 Q5VZL5|ZMYM4_HUMAN Novel 3.24225618 0.03783247 Contig16937 Q08462|ADCY2_HUMAN Familiar 3.53241097 0.01908654 Contig16937 Q08462|ADCY2_HUMAN Novel 3.45250571 0.01799496 Contig17062 P18729|ZG57_XENLA Familiar 0.0042539 0.05991907 Contig17062 P18729|ZG57_XENLA Novel 0.23711563 0.05649224 Contig17586 None available Familiar 0.97291062 0.07641874 Contig17586 None available Novel 0.61092317 0.07204828 Contig17875 P16960|RYR1_PIG Familiar 4.60876969 0.01646614 Contig17875 P16960|RYR1_PIG Novel 4.55220897 0.01552443 Contig17976 None available Familiar 0.68595124 0.10418626 Contig17976 None available Novel 1.20391461 0.09822775 Contig18032 None available Familiar 4.26737927 0.05194098 Contig18032 None available Novel 4.10689427 0.04897042 Contig18187 A1L2T6|ZCHC7_XENLA Familiar 0.32621137 0.05021687 Contig18187 A1L2T6|ZCHC7_XENLA Novel 0.09277793 0.04734492 Contig18279 Q9NQM4|PIHD3_HUMAN Familiar 1.17209837 0.03845366 Contig18279 Q9NQM4|PIHD3_HUMAN Novel 1.30224199 0.03625446 Contig18379 None available Familiar 2.27333407 0.02914464 Contig18379 None available Novel 2.37449771 0.02747783 Contig18517 Q62470|ITA3_MOUSE Familiar 1.26925358 0.04206557 Contig18517 Q62470|ITA3_MOUSE Novel 1.4576913 0.0396598 Contig18927 Q1LZ89|CC106_BOVIN Familiar 2.49221221 0.02277963 Contig18927 Q1LZ89|CC106_BOVIN Novel 2.58325195 0.02147684 Contig19303 Q5MD89|VGFR3_DANRE Familiar 1.13976731 0.04613572 Contig19303 Q5MD89|VGFR3_DANRE Novel 1.31906308 0.04349717 Contig19380 None available Familiar 1.67982285 0.04292063 Contig19380 None available Novel 1.79609883 0.04046596 Contig19907 Q9ULD9|ZN608_HUMAN Familiar 2.60975487 0.05787034 Contig19907 Q9ULD9|ZN608_HUMAN Novel 2.42654257 0.05456068 Contig19920 Q8TAM1|BBS10_HUMAN Familiar 0.87408733 0.02571263 Contig19920 Q8TAM1|BBS10_HUMAN Novel 1.05320514 0.0242421 Contig20234 Q0VG62|CH059_MOUSE Familiar 2.41689461 0.01496343 Contig20234 Q0VG62|CH059_MOUSE Novel 2.50368528 0.01410766 Contig20800 None available Familiar 0.82425806 0.04742854 Contig20800 None available Novel 0.64380307 0.04471606

71 Table D.1-continued

Contig Sequence ID Treatment LSMean StdErr Contig21095 Q8R316|HBP1_MOUSE Familiar 1.79754915 0.02814963 Contig21095 Q8R316|HBP1_MOUSE Novel 1.89633569 0.02653972 Contig2165 Q9WTS6|TEN3_MOUSE Familiar 4.68970169 0.02453783 Contig2165 Q9WTS6|TEN3_MOUSE Novel 4.61744065 0.02313449 Contig21742 None available Familiar 0.11212343 0.06515944 Contig21742 None available Novel 0.15122008 0.06143291 Contig21932 P20959|IBP3_BOVIN Familiar 0.77183382 0.0484143 Contig21932 P20959|IBP3_BOVIN Novel 0.95000572 0.04564544 Contig22219 A8E7I5|TTC36_DANRE Familiar 0.26862984 0.08611689 Contig22219 A8E7I5|TTC36_DANRE Novel 0.10717425 0.08119178 Contig22277 Q96K62|ZBT45_HUMAN Familiar 1.79569632 0.10360072 Contig22277 Q96K62|ZBT45_HUMAN Novel 1.46749809 0.0976757 Contig22479 Q6DBV4|PHOP1_DANRE Familiar 0.95802648 0.07015969 Contig22479 Q6DBV4|PHOP1_DANRE Novel 0.69257009 0.06614719 Contig22485 Q8TBP0|TBC16_HUMAN Familiar 0.71894898 0.04209606 Contig22485 Q8TBP0|TBC16_HUMAN Novel 0.52911363 0.03968854 Contig2250 P36512|UDB13_RABIT Familiar 1.60058114 0.05845295 Contig2250 P36512|UDB13_RABIT Novel 1.87248032 0.05510997 Contig22503 None available Familiar 1.43292128 0.03655683 Contig22503 None available Novel 1.58198914 0.03446611 Contig22739 P25050|STP_SHV24 Familiar 3.0096604 0.04510854 Contig22739 P25050|STP_SHV24 Novel 2.83677962 0.04252874 Contig23003 Q6DG32|S2536_DANRE Familiar 2.0196908 0.05732235 Contig23003 Q6DG32|S2536_DANRE Novel 1.84616899 0.05404403 Contig23124 D3ZN43|NDUF6_RAT Familiar 1.8005933 0.0332327 Contig23124 D3ZN43|NDUF6_RAT Novel 1.96552713 0.03133209 Contig23248 None available Familiar 1.23763719 0.07661543 Contig23248 None available Novel 1.49142304 0.07223372 Contig23429 Q2PFW9|NOVA1_MACFA Familiar 1.55370332 0.05927894 Contig23429 Q2PFW9|NOVA1_MACFA Novel 1.36270307 0.05588872 Contig23800 Q5EA46|CREL1_BOVIN Familiar -0.1723401 0.0889582 Contig23800 Q5EA46|CREL1_BOVIN Novel 0.20975551 0.08387059 Contig23896 E7FDE0|TM138_DANRE Familiar 0.45949756 0.06965206 Contig23896 E7FDE0|TM138_DANRE Novel 0.70979147 0.06566859 Contig23999 Q08DN7|VAV_BOVIN Familiar 0.62390412 0.06993222 Contig23999 Q08DN7|VAV_BOVIN Novel 0.90562913 0.06593273 Contig24156 Q90WI4|MXRA8_CHICK Familiar 1.08582688 0.0668018 Contig24156 Q90WI4|MXRA8_CHICK Novel 1.35923192 0.06298134 Contig24258 None available Familiar 0.46776797 0.06655314 Contig24258 None available Novel 0.22644623 0.0627469 Contig24472 None available Familiar 0.72686202 0.1042906

72 Table D.1-continued

Contig Sequence ID Treatment LSMean StdErr Contig24472 None available Novel 1.2079307 0.09832612 Contig24476 P21917|DRD4_HUMAN Familiar 0.97673576 0.05735224 Contig24476 P21917|DRD4_HUMAN Novel 0.76250942 0.05407221 Contig24500 Q1LWL8|MCL1B_DANRE Familiar 1.51689586 0.04986715 Contig24500 Q1LWL8|MCL1B_DANRE Novel 1.34999011 0.0470152 Contig24648 Q80ZQ5|JAZF1_MOUSE Familiar 1.70200544 0.03656561 Contig24648 Q80ZQ5|JAZF1_MOUSE Novel 1.56679989 0.03447439 Contig25091 None available Familiar 1.89205463 0.0209457 Contig25091 None available Novel 1.97532812 0.0197478 Contig25167 Q08CL8|CNOTA_DANRE Familiar 1.15557401 0.04424475 Contig25167 Q08CL8|CNOTA_DANRE Novel 0.96471848 0.04171435 Contig25390 None available Familiar 0.28849705 0.0523782 Contig25390 None available Novel 0.64824774 0.04938264 Contig25778 None available Familiar 0.21490751 0.25776213 Contig25778 None available Novel 0.90742762 0.24302047 Contig26163 None available Familiar 0.26583219 0.04945585 Contig26163 None available Novel 0.01799116 0.04662742 Contig26325 O75460|ERN1_HUMAN Familiar 0.30597384 0.06665296 Contig26325 O75460|ERN1_HUMAN Novel 0.01489815 0.06284101 Contig26517 None available Familiar 1.45622559 0.05432959 Contig26517 None available Novel 1.69514239 0.05122243 Contig2673 None available Familiar 4.24191942 0.02568989 Contig2673 None available Novel 4.35261802 0.02422066 Contig26795 P61765|STXB1_RAT Familiar 1.68292169 0.12075256 Contig26795 P61765|STXB1_RAT Novel 1.96005056 0.11384661 Contig26952 Q86VQ1|GLCI1_HUMAN Familiar 1.10310164 0.05417816 Contig26952 Q86VQ1|GLCI1_HUMAN Novel 0.88620868 0.05107966 Contig26987 Q5RDW1|GTPB5_PONAB Familiar 0.90443355 0.01836606 Contig26987 Q5RDW1|GTPB5_PONAB Novel 0.99934819 0.01731568 Contig27321 None available Familiar 0.68312695 0.08410537 Contig27321 None available Novel 0.36158388 0.0792953 Contig27408 Q6NYV9|LEO1_DANRE Familiar 0.66596753 0.04856548 Contig27408 Q6NYV9|LEO1_DANRE Novel 0.93102995 0.04578798 Contig27487 None available Familiar 0.77937217 0.0314432 Contig27487 None available Novel 0.63705635 0.02964493 Contig27509 None available Familiar 1.19818836 0.27420905 Contig27509 None available Novel 0.07432202 0.25852678 Contig27557 None available Familiar 2.74462808 0.03700798 Contig27557 None available Novel 2.89564785 0.03489145 Contig28072 O75153|CLU_HUMAN Familiar 1.58946987 0.04661033 Contig28072 O75153|CLU_HUMAN Novel 1.25585797 0.04394464 Contig28162 Q9WUM7|HIPK2_MESAU Familiar 1.39352934 0.0474345

73 Table D.1-continued

Contig Sequence ID Treatment LSMean StdErr Contig28162 Q9WUM7|HIPK2_MESAU Novel 1.22289042 0.04472168 Contig28187 Q99P63|EFHA1_RAT Familiar 0.1507135 0.04529167 Contig28187 Q99P63|EFHA1_RAT Novel 0.38200175 0.0427014 Contig28532 Q6NV74|K121L_HUMAN Familiar 1.31739951 0.04943707 Contig28532 Q6NV74|K121L_HUMAN Novel 1.51590783 0.04660972 Contig28607 Q9UHC6|CNTP2_HUMAN Familiar 1.4607095 0.0464592 Contig28607 Q9UHC6|CNTP2_HUMAN Novel 1.3070909 0.04380215 Contig28713 Q2KIE2|HAX1_BOVIN Familiar 1.78329755 0.04257381 Contig28713 Q2KIE2|HAX1_BOVIN Novel 1.91525973 0.04013898 Contig2892 Q9Y2E4|DIP2C_HUMAN Familiar 2.47281338 0.02138035 Contig2892 Q9Y2E4|DIP2C_HUMAN Novel 2.56193986 0.02015759 Contig28940 Q7Z5H3|RHG22_HUMAN Familiar 1.3216533 0.04887802 Contig28940 Q7Z5H3|RHG22_HUMAN Novel 1.10352972 0.04608264 Contig29060 Q66I67|IFT20_DANRE Familiar 1.06573217 0.028406 Contig29060 Q66I67|IFT20_DANRE Novel 1.19586731 0.02678144 Contig29162 O55012|PICA_RAT Familiar 0.88286606 0.07156413 Contig29162 O55012|PICA_RAT Novel 0.65187764 0.06747131 Contig29698 Q62245|SOS1_MOUSE Familiar 0.8014716 0.04574539 Contig29698 Q62245|SOS1_MOUSE Novel 0.62557732 0.04312916 Contig29792 None available Familiar 0.4173449 0.0675192 Contig29792 None available Novel 0.65291865 0.06365772 Contig29931 None available Familiar 0.81059809 0.09415698 Contig29931 None available Novel 0.44569562 0.08877206 Contig30035 O19112|CILP1_PIG Familiar 1.71839077 0.03531849 Contig30035 O19112|CILP1_PIG Novel 1.52004981 0.03329859 Contig30176 None available Familiar 0.48077459 0.0389982 Contig30176 None available Novel 0.67159124 0.03676785 Contig30588 None available Familiar 0.16085248 0.05677403 Contig30588 None available Novel 0.36883664 0.05352707 Contig31032 Q5DRE4|PCDA8_PANTR Familiar 1.05239074 0.11274541 Contig31032 Q5DRE4|PCDA8_PANTR Novel 0.77442981 0.1062974 Contig31202 None available Familiar 0.46291379 0.04349132 Contig31202 None available Novel 0.65749444 0.04100401 Contig31478 Q6GM82|ALAT2_XENLA Familiar 0.06517816 0.06609011 Contig31478 Q6GM82|ALAT2_XENLA Novel 0.17856283 0.06231035 Contig31766 None available Familiar 0.79487734 0.03777814 Contig31766 None available Novel 0.9489176 0.03561757 Contig31862 P41586|PACR_HUMAN Familiar 2.86194609 0.13098765 Contig31862 P41586|PACR_HUMAN Novel 2.37846305 0.12349634 Contig31867 Q9CUB6|OTUD1_MOUSE Familiar 1.21313225 0.03189181 Contig31867 Q9CUB6|OTUD1_MOUSE Novel 1.34371925 0.03006788

74 Table D.1-continued

Contig Sequence ID Treatment LSMean StdErr Contig3194 Q8CGU9|TPH2_RAT Familiar 1.9789836 0.04187761 Contig3194 Q8CGU9|TPH2_RAT Novel 1.81451049 0.03948259 Contig31974 None available Familiar 0.93121978 0.04603589 Contig31974 None available Novel 0.76295348 0.04340305 Contig32045 None available Familiar 0.32259869 0.08237762 Contig32045 None available Novel 0.07519548 0.07766637 Contig32166 Q99L88|SNTB1_MOUSE Familiar 2.30304182 0.0374899 Contig32166 Q99L88|SNTB1_MOUSE Novel 2.43605319 0.03534582 Contig32215 None available Familiar 1.02375565 0.02581259 Contig32215 None available Novel 0.92127274 0.02433635 Contig32226 None available Familiar 0.86919231 0.11607929 Contig32226 None available Novel 1.3526984 0.1094406 Contig32345 Q8K352|SASH3_MOUSE Familiar 0.81646668 0.07748899 Contig32345 Q8K352|SASH3_MOUSE Novel 1.11962973 0.07305732 Contig32589 Q9P2E7|PCD10_HUMAN Familiar 0.32414831 0.07952398 Contig32589 Q9P2E7|PCD10_HUMAN Novel 0.55161832 0.07497593 Contig32647 None available Familiar 0.92237429 0.05206299 Contig32647 None available Novel 0.7090582 0.04908546 Contig32886 Q6V0L0|CP26C_HUMAN Familiar 0.82615384 0.06446349 Contig32886 Q6V0L0|CP26C_HUMAN Novel 0.98130783 0.06077676 Contig33050 None available Familiar 0.36963736 0.06970363 Contig33050 None available Novel 0.15841293 0.06571722 Contig33486 Q4W5Z4|DNM3A_CHICK Familiar 0.50294839 0.04881097 Contig33486 Q4W5Z4|DNM3A_CHICK Novel 0.28774178 0.04601942 Contig33609 Q86V71|ZN429_HUMAN Familiar 0.52465448 0.04707554 Contig33609 Q86V71|ZN429_HUMAN Novel 0.68404761 0.04438324 Contig34278 Q5RDX1|Z585A_PONAB Familiar 0.93746221 0.06363995 Contig34278 Q5RDX1|Z585A_PONAB Novel 0.74320899 0.06000032 Contig3445 Q4JQI6|NU2M_TETNG Familiar 7.86405285 0.03204679 Contig3445 Q4JQI6|NU2M_TETNG Novel 7.98865404 0.030214 Contig34573 Q9FHN8|KCBP_ARATH Familiar 0.35290923 0.06664451 Contig34573 Q9FHN8|KCBP_ARATH Novel 0.65587524 0.06283305 Contig34693 None available Familiar 0.16352227 0.07017171 Contig34693 None available Novel 0.08483286 0.06615852 Contig34719 O14593|RFXK_HUMAN Familiar 2.04405475 0.03590305 Contig34719 O14593|RFXK_HUMAN Novel 2.2112426 0.03384972 Contig34738 None available Familiar 0.21764002 0.06131994 Contig34738 None available Novel 0.43177991 0.057813 Contig34751 None available Familiar 0.05947739 0.06846869 Contig34751 None available Novel -0.1674977 0.0645529 Contig34817 P43004|EAA2_HUMAN Familiar 0.49583871 0.19065976

75 Table D.1-continued

Contig Sequence ID Treatment LSMean StdErr Contig34817 P43004|EAA2_HUMAN Novel 0.32449061 0.17975575 Contig34873 None available Familiar 0.12729107 0.0867066 Contig34873 None available Novel 0.57694048 0.08174777 Contig34961 Q3V1L6|MTMRB_MOUSE Familiar 0.74747918 0.07360508 Contig34961 Q3V1L6|MTMRB_MOUSE Novel 0.48636616 0.06939553 Contig35386 O43278|SPIT1_HUMAN Familiar 0.21492301 0.14937784 Contig35386 O43278|SPIT1_HUMAN Novel 0.37945654 0.14083478 Contig35491 Q9D572|UBX11_MOUSE Familiar 0.21663256 0.04018023 Contig35491 Q9D572|UBX11_MOUSE Novel 0.40946018 0.03788228 Contig35527 Q66H98|SDPR_RAT Familiar 0.08590748 0.09636057 Contig35527 Q66H98|SDPR_RAT Novel 0.41926776 0.09084962 Contig35671 Q90674|LSHR_CHICK Familiar 0.67621303 0.05470939 Contig35671 Q90674|LSHR_CHICK Novel 0.89493294 0.05158051 Contig35987 Q0VCA2|ARRD3_BOVIN Familiar 0.05221953 0.07124604 Contig35987 Q0VCA2|ARRD3_BOVIN Novel 0.27708555 0.06717141 Contig36538 None available Familiar 0.03474046 0.09124384 Contig36538 None available Novel 0.3864166 0.08602552 Contig36739 None available Familiar 0.49889137 0.05527591 Contig36739 None available Novel 0.32484994 0.05211463 Contig36980 Q307W7|KNCN_MOUSE Familiar 0.41064472 0.2007615 Contig36980 Q307W7|KNCN_MOUSE Novel 0.05000303 0.18927976 Contig37137 None available Familiar 0.03017992 0.06863854 Contig37137 None available Novel 0.32709861 0.06471304 Contig37605 O54890|ITB3_MOUSE Familiar 0.97486975 0.05162382 Contig37605 O54890|ITB3_MOUSE Novel 0.74760306 0.0486714 Contig37633 None available Familiar 0.09898602 0.07834495 Contig37633 None available Novel 0.49475077 0.07386433 Contig37691 O62664|PGH1_BOVIN Familiar 0.16604189 0.07288065 Contig37691 O62664|PGH1_BOVIN Novel 0.14982498 0.06871253 Contig37832 None available Familiar 0.11093934 0.06772345 Contig37832 None available Novel 0.16521602 0.06385028 Contig38386 None available Familiar 0.20732392 0.06543874 Contig38386 None available Novel 0.17323469 0.06169624 Contig38670 None available Familiar 0.59165974 0.04970591 Contig38670 None available Novel 0.38408258 0.04686318 Contig38692 Q8TEW8|PAR3L_HUMAN Familiar 0.3467853 0.03624942 Contig38692 Q8TEW8|PAR3L_HUMAN Novel 0.14332387 0.03417629 Contig38750 Q8MJW8|CCR4_CANFA Familiar 0.22185099 0.09323856 Contig38750 Q8MJW8|CCR4_CANFA Novel 0.20861331 0.08790616 Contig39297 P37889|FBLN2_MOUSE Familiar 0.34370586 0.07260254 Contig39297 P37889|FBLN2_MOUSE Novel 0.09877887 0.06845033 Contig39572 Q8BLR2|CPNE4_MOUSE Familiar 1.24184119 0.07061926

76 Table D.1-continued

Contig Sequence ID Treatment LSMean StdErr Contig39572 Q8BLR2|CPNE4_MOUSE Novel 1.02709941 0.06658048 Contig39766 None available Familiar 0.10962568 0.10805569 Contig39766 None available Novel 0.52247226 0.10187588 Contig40473 None available Familiar 0.04298762 0.04886118 Contig40473 None available Novel 0.24545702 0.04606676 Contig40492 O15353|FOXN1_HUMAN Familiar 0.40317919 0.0373146 Contig40492 O15353|FOXN1_HUMAN Novel 0.58364142 0.03518054 Contig4086 None available Familiar 1.11095727 0.05199616 Contig4086 None available Novel 0.90430834 0.04902245 Contig41074 P14381|YTX2_XENLA Familiar 0.07101887 0.06853332 Contig41074 P14381|YTX2_XENLA Novel 0.32986699 0.06461383 Contig41149 None available Familiar 0.56233176 0.06112475 Contig41149 None available Novel 0.32412551 0.05762897 Contig4215 Q99PP2|ZN318_MOUSE Familiar 6.01716045 0.01630956 Contig4215 Q99PP2|ZN318_MOUSE Novel 5.95048642 0.0153768 Contig4595 A0JMD0|CLU_DANRE Familiar 2.78678149 0.03109115 Contig4595 A0JMD0|CLU_DANRE Novel 2.61949559 0.02931302 Contig498 None available Familiar 3.12093301 0.09798392 Contig498 None available Novel 2.79339411 0.09238013 Contig5348 Q7ZVZ6|PREP_DANRE Familiar 2.40518965 0.0371215 Contig5348 Q7ZVZ6|PREP_DANRE Novel 2.2791931 0.03499848 Contig5512 Q6DBX1|MED20_DANRE Familiar 1.86801077 0.0563741 Contig5512 Q6DBX1|MED20_DANRE Novel 2.04407282 0.05315001 Contig5555 Q9Y5Z4|HEBP2_HUMAN Familiar 3.1784608 0.02766964 Contig5555 Q9Y5Z4|HEBP2_HUMAN Novel 3.2930926 0.02608718 Contig5787 Q53G44|IF44L_HUMAN Familiar 2.13698851 0.03537971 Contig5787 Q53G44|IF44L_HUMAN Novel 2.25312019 0.03335631 Contig6052 Q6DJ71|CO038_XENTR Familiar 2.15105146 0.01765429 Contig6052 Q6DJ71|CO038_XENTR Novel 2.21894017 0.01664463 Contig6794 P0C024|NUDT7_HUMAN Familiar 1.2801076 0.02708952 Contig6794 P0C024|NUDT7_HUMAN Novel 1.38289295 0.02554024 Contig7153 P46937|YAP1_HUMAN Familiar 3.47916084 0.02015124 Contig7153 P46937|YAP1_HUMAN Novel 3.56378436 0.01899877 Contig7470 Q8JHF0|PEN2_DANRE Familiar 3.24223814 0.03367752 Contig7470 Q8JHF0|PEN2_DANRE Novel 3.3625248 0.03175147 Contig7807 Q8UVQ4|KAISO_XENLA Familiar 2.89826219 0.02215525 Contig7807 Q8UVQ4|KAISO_XENLA Novel 2.83158208 0.02088817 Contig8472 Q498M4|WDR5_RAT Familiar 3.90878813 0.01535742 Contig8472 Q498M4|WDR5_RAT Novel 3.84602294 0.01447912 Contig8556 Q9Z248|AEBP2_MOUSE Familiar 0.68978017 0.03993755 Contig8556 Q9Z248|AEBP2_MOUSE Novel 0.53052592 0.03765349 Contig8577 Q9UBN1|CCG4_HUMAN Familiar 3.13993224 0.02460652

77 Table D.1-continued

Contig Sequence ID Treatment LSMean StdErr Contig8577 Q9UBN1|CCG4_HUMAN Novel 3.0297133 0.02319925 Contig8582 Q6DGQ1|KBRS1_DANRE Familiar 2.61629725 0.01996469 Contig8582 Q6DGQ1|KBRS1_DANRE Novel 2.53957636 0.01882289

Table D.2 List of 99 genes that showed a significant relationship with gene expression. Contigs in bold overlap with those in Table D.1.

Partial Regression Contig Sequence ID Coefficient StdErr Contig10229 Q4V8V1|BM1LA_DANRE 0.2376 0.0434 Contig10446 Q5SWW4|MED13_MOUSE -0.04224 0.0173 Contig1045 P98165|VLDLR_CHICK -0.04251 0.0132 Contig13321 Q91ZW6|TMLH_RAT -0.09899 0.0288 Contig13418 Q8TEX9|IPO4_HUMAN -0.10595 0.0300 Contig14149 Q6P5Z2|PKN3_HUMAN -0.12649 0.0420 Contig14281 Q08DG8|ZN135_BOVIN -0.06666 0.0216 Contig14292 Q3MHW0|SRGEF_BOVIN 0.06122 0.0202 Contig14383 None Available 0.06607 0.0201 Contig15057 P56700|RGS16_RAT 0.04002 0.0109 Contig15395 Q86YH6|DLP1_HUMAN -0.10424 0.0289 Contig17010 None Available 0.08103 0.0221 Contig17223 P48676|PERI_XENLA 0.16474 0.0533 Contig17277 None Available 0.15092 0.0508 Contig17651 None Available 0.12934 0.0463 Contig18279 Q9NQM4|PIHD3_HUMAN 0.09438 0.0246 Contig18564 None Available 0.10961 0.0356 Contig19011 Q9D4P0|ARL5B_MOUSE 0.04595 0.0197 Contig19086 Q9XSC3|WDR44_BOVIN -0.0467 0.0126 Contig198 P26369|U2AF2_MOUSE -0.12757 0.0450 Contig19842 Q9JJR6|CK016_MOUSE -0.14237 0.0509 Contig19920 Q8TAM1|BBS10_HUMAN 0.10414 0.0252 Contig21138 None Available 0.22445 0.0932 Contig21233 Q5R8Z4|PAK6_PONAB -0.09316 0.0293 Contig21742 None Available 0.21045 0.0398 Contig21954 None Available 0.20989 0.0744 Contig22276 None Available 0.28575 0.0688

78

Table D.2-continued Partial Regression Contig Sequence ID Coefficient StdErr Contig22503 None Available 0.11228 0.0249 Contig22515 Q9QZZ4|MYO15_MOUSE -0.15611 0.0419 Contig22603 None Available 0.07124 0.0233 Contig22617 None Available 0.14342 0.0394 Contig22714 None Available 0.13612 0.0385 Contig22732 None Available 0.13703 0.0387 Contig22975 Q9NPJ8|NXT2_HUMAN -0.07579 0.0260 Contig23328 None Available 0.13992 0.0474 Contig23340 O70255|MPZL2_MOUSE 0.08245 0.0286 Contig23881 None Available 0.15889 0.0465 Contig23999 Q08DN7|VAV_BOVIN 0.17986 0.0578 Contig24030 Q3T1G7|COG7_RAT 0.3721 0.1032 Contig24114 None Available 0.18514 0.0464 Contig24825 None Available 0.14278 0.0447 Contig24893 None Available 0.10469 0.0254 Contig25390 None Available 0.19602 0.0461 Contig26325 O75460|ERN1_HUMAN 0.20956 0.0565 Contig26435 None Available 0.3508 0.1242 Contig26804 None Available -0.12147 0.0356 Contig26987 Q5RDW1|GTPB5_PONAB 0.05668 0.0169 Contig27487 None Available -0.08795 0.0254 Contig27509 None Available 0.85575 0.2255 Contig27715 None Available 0.13678 0.0360 Contig27878 Q8I7P9|POL5_DROME -0.7589 0.2298 Contig27883 Q6DK99|CNFNB_XENLA 0.31188 0.0975 Contig28009 Q60780|GAS7_MOUSE -0.09318 0.0361 Contig29866 None Available 0.26143 0.0799 Contig30017 P15464|HB21_SPAEH 0.16524 0.0568 Contig30128 Q07973|CP24A_HUMAN -0.17172 0.0552 Contig30176 None Available 0.12177 0.0325 Contig30191 None Available 0.29405 0.0742 Contig30453 None Available -0.08319 0.0370 Contig30902 Q28BP2|T150A_XENTR -0.13845 0.0321 Contig31202 None Available 0.12806 0.0369 Contig31281 None Available 0.16125 0.0456 Contig31343 O96028|NSD2_HUMAN -0.09693 0.0314 Contig31460 None Available -0.0901 0.0300 Contig31850 P83851|IUNH_LEIMA 0.18926 0.0591 Contig31983 None Available 0.13379 0.0376

79

Table D.2-continued Partial Regression Contig Sequence ID Coefficient StdErr Contig32093 P47804|RGR_HUMAN 0.11224 0.0330 Contig3235 Q91Z79|LIPA3_RAT -0.05582 0.0182 Contig32881 None Available -0.19064 0.0605 Contig33283 None Available 0.15283 0.0439 Contig34187 None Available 0.15212 0.0542 Contig34240 None Available -0.1583 0.0369 Contig34325 Q32LP0|URP2_BOVIN 0.17261 0.0507 Contig34573 Q9FHN8|KCBP_ARATH 0.21277 0.0514 Contig34695 None Available 0.07498 0.0209 Contig34938 None Available 0.15956 0.0533 Contig35840 Q8IYF3|TEX11_HUMAN -0.1406 0.0403 Contig36599 P82951|HEPC_MORCS 0.19525 0.0611 Contig3731 None Available -0.06616 0.0249 Contig37633 None Available 0.2627 0.0639 Contig38301 None Available -0.17958 0.0561 Contig38616 None Available -0.11114 0.0352 Contig38888 Q5ZLK4|GBGT1_CHICK 0.1456 0.0398 Contig39275 None Available -0.24121 0.0578 Contig4504 None Available -0.09025 0.0321 Contig4515 None Available 0.03697 0.0131 Contig4595 A0JMD0|CLU_DANRE -0.11433 0.0227 Contig465 O00214|LEG8_HUMAN -0.07217 0.0247 Contig4729 Q66K64|DCA15_HUMAN -0.05733 0.0203 Contig5262 P36372|TAP2_RAT 0.10425 0.0319 Contig541 Q6EEF3|TTLL5_CHLAE -0.12765 0.0329 Contig6162 O95486|SC24A_HUMAN 0.08699 0.0256 Contig7648 P27615|SCRB2_RAT -0.07607 0.0256 Contig7663 Q6DGQ1|KBRS1_DANRE 0.03298 0.0094 Contig8582 None Available -0.05009 0.0172 Contig876 None Available 0.14431 0.0488 Contig8812 P21658|FGF6_MOUSE -0.06188 0.0189 Contig9314 Q13349|ITAD_HUMAN 0.13286 0.0368 Contig9522 Q9EQ20|MMSA_MOUSE -0.06613 0.0199

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93 BIOGRAPHICAL SKETCH

ILANA L. JANOWITZ

EDUCATION:

Ph.D. Candidate, Biological Science, Florida State University (Entered Spring of 2009; Anticipated Completion Spring of 2014)

B.S. Psychology, Florida State University (2006)

POSITIONS HELD:

Research Assistant, Current Position Department of Biology Florida State University

Teaching Assistant, 2009-2010 Experimental Biology Lab Department of Biology Florida State University

Teaching Assistant, 2008-2009 Conditioning and Learning Lab Department of Psychology Florida State University

Departmental Assistant, 2007-2008 Department of Psychology Florida State University

Research Assistant, 2006-2007 Department of Psychology Florida State University

94 PUBLICATIONS:

Fraser, B.A., Janowitz, I., Travis, J. & Hughes, K.A. 2014. Phenotypic and genomic plasticity of alternative male reproductive tactics in sailfin mollies. Proceedings of the Royal Society of London. Series B: Biological Sciences, 281, 20132310.

Fraser, B.A., Weadick, C.J., Janowitz, I., Rodd, F.H. & Hughes, K.A. 2011. Sequencing and characterization of the guppy (Poecilia reticulata) transcriptome. BMC Genomics, 12, 202.

Houpt, T.A., Carella, L., Gonzalez, G. Janowitz, I., Mueller, A. Mueller, K. Neth, B. & Smith, J.C. 2011. Behavioral effects of rats in motion within a high static magnetic field. Physiology & Behavior, 102, 338-346.

Houpt, T.A., Cassell, J.A., Hood, A., DenBleyker, M., Janowitz, I., Mueller, K., Ortega, B. & Smith, J.C. 2010. Repeated exposure attenuates the behavioral response of rats to high static magnetic fields. Physiology & Behavior, 99, 500-508.

PRESENTATIONS:

Janowitz, I. The Role of Sensory Bias in the Evolution of Choosy Females & Variable Males. Ecology & Evolution Seminar. October 25, 2013. Tallahassee, Fl. (Departmental Seminar, oral presentation).

Janowitz, I. & Hughes, K.A. Mate Preference in the Female Guppy: Patterns in Behavior and Brain Genomics. Animal Behavior Society Conference. July 30, 2013. Boulder, Co. (oral presentation).

Janowitz, I. Behavioral and Genomic Plasticity In Mate Preference. FSU Illumina User Group. June 27, 2013. Tallahassee, Fl. (oral presentation).

Janowitz, I. & Hughes, K.A. Novelty Preference in the Female Guppy (Poecilia reticulata): From Molecules to Behavior. Annual SEPEEG (Southeast Population Ecology & Evolutionary Genetics) Conference. October 13, 2012. Pendleton, SC. (oral presentation).

Janowitz, I. & Hughes, K.A. Novelty Preference in the Female Guppy (Poecilia reticulata): From Molecules to Behavior. Neuroethology Fowler Symposium. April 8, 2011. Tallahassee, Fl. (poster presentation).

95