INVESTIGATION OF EPISTATIC INTERACTIONS AMONG FORAGING LOCI IN DROSOPHILA MELANOGASTER

by

Christie Elizabeth DesRoches

A thesis submitted in conformity with the requirements

for the degree of Master of Science

Graduate Department of Cell and Systems Biology

University of Toronto

© Copyright by Christie Elizabeth DesRoches 2008 Library and Bibliotheque et 1*1 Archives Canada Archives Canada Published Heritage Direction du Branch Patrimoine de I'edition

395 Wellington Street 395, rue Wellington Ottawa ON K1A0N4 Ottawa ON K1A0N4 Canada Canada

Your file Votre reference ISBN: 978-0-494-38883-9 Our file Notre reference ISBN: 978-0-494-38883-9

NOTICE: AVIS: The author has granted a non­ L'auteur a accorde une licence non exclusive exclusive license allowing Library permettant a la Bibliotheque et Archives and Archives Canada to reproduce, Canada de reproduire, publier, archiver, publish, archive, preserve, conserve, sauvegarder, conserver, transmettre au public communicate to the public by par telecommunication ou par Plntemet, prefer, telecommunication or on the Internet, distribuer et vendre des theses partout dans loan, distribute and sell theses le monde, a des fins commerciales ou autres, worldwide, for commercial or non­ sur support microforme, papier, electronique commercial purposes, in microform, et/ou autres formats. paper, electronic and/or any other formats.

The author retains copyright L'auteur conserve la propriete du droit d'auteur ownership and moral rights in et des droits moraux qui protege cette these. this thesis. Neither the thesis Ni la these ni des extraits substantiels de nor substantial extracts from it celle-ci ne doivent etre imprimes ou autrement may be printed or otherwise reproduits sans son autorisation. reproduced without the author's permission.

In compliance with the Canadian Conformement a la loi canadienne Privacy Act some supporting sur la protection de la vie privee, forms may have been removed quelques formulaires secondaires from this thesis. ont ete enleves de cette these.

While these forms may be included Bien que ces formulaires in the document page count, aient inclus dans la pagination, their removal does not represent il n'y aura aucun contenu manquant. any loss of content from the thesis. Canada Investigation of epistatic interactions among foraging loci in Drosophila melanogaster.

Christie Elizabeth DesRoches

Master of Science Degree

Graduate Department of Cell and Systems Biology

University of Toronto

2008

Abstract

All organisms exhibit a wide array of intricate behavioural phenotypes throughout their lifetime. Understanding the genetic underpinnings of these behaviours will ultimately help to elucidate the cellular and molecular mechanisms that drive these behaviours. In this thesis, I explore genetic contributions to feeding behaviour, using Drosophila melanogaster as a model organism. The foraging gene (for) is a very well known genetic regulator of feeding behaviour in Drosophila melanogaster. While for underlies much of the natural variation in foraging behaviour, I am interested in other genes that may contribute to this complex phenotype. I show that a group of previously isolated mutations influencing larval foraging behaviour also influence food intake in Drosophila. In addition, I demonstrate that many of these functionally related mutations interact with one another in a genetic network to influence foraging behaviour. This thesis employs genetic and behavioural analyses to investigate the pleiotropic nature of complex food-related behaviours.

n Acknowledgments

First and foremost, I owe a great debt of gratitude to Dr. Maria Sokolowski for giving me the opportunity to study in her lab. Maria, thank you for taking me under your wing as an undergraduate, and for letting me stay on for graduate work when I realized how much I loved what I was doing. I have grown both as a researcher and as a person throughout my time in the lab, and for that I am truly grateful.

Thanks also to the two other members of my supervisory committee, Dr. Tim Westwood and

Dr. Joel Levine, for their encouragement, support and advice throughout my thesis.

I also owe a special thanks to the past and present members of the Sokolowski Lab, and the

Levine lab, who have made my tenure so memorable. Thanks for the advice, both about science and about life. The SokoLab is a great environment in which to work and study, and I could not have made it this far without the support of my fellow lab members.

Last, but certainly not least, I am forever indebted to my parents and my brother, for things that would fill a larger volume than this. Mom, Dad and Will, thank you for putting up with me in good times and in bad. Your support has meant more to me than you know, and I couldn't have done it without you.

in Table of Contents

Abstract ii Acknowledgments iii Table of Contents iv List of Tables v List of Figures vi List of Key Terms and Abbreviations vii

Introduction 1 Behaviour Genetics 2 Drosophila melanogaster as a Model Organism 6 The foraging Gene 8 Mutagenesis 11 Epistasis 12 Mapping of Mutations 15

Materials and Methods 17 Fly Stocks 17 Aging of Larvae 18 Larval Foraging Related Locomotion Assay 19 Larval Food Intake Assay 20 Generation of Transheterozygotes 21 Statistical Analysis 22 Complementation Analysis 24 Sequencing Analysis 25 Genomic DNA extraction 26 Amplification, Purification and Sequencing 27

Results 28 Larval Foraging Related Locomotion 28 Food Intake 29 Epistasis 30 Complementation Analysis 33 Sequencing Analysis 34

Discussion 45 Larval Foraging Related Locomotion 45 Food Intake 50 Epistasis 52 Mapping of Mutations 56

References 58

iv List of Tables

Table 1 | Transheterozygote pathlength scores and estimates of general combining abilities

of parental lines 40

Table 2 | Estimates of specific combining abilities of transheterozygote lines 41

Table 3 | List of mutant lines for complementation testing 43

Table 4 | Candidate genes of interest sequenced in homozygous third-instar control and

mutant larvae 44

v List of Figures

Figure 1 | Larval foraging pathlength of control and mutant larvae 36

Figure 2 | Larval food intake of control and mutant larvae 38

Figure 3 | Diallel crossing scheme 39

Figure 4 | Interaction diagram 42

VI List of Key Terms and Abbreviations

for foraging gene

QTL Quantitative trait locus r R Rover allele of foraging for for5 Sitter allele offoraging

PKG cGMP dependent protein kinase

EMS Ethyl methane sulfonate

GFP Green fluorescent protein

SNK Student-Newman-Keuls

GCA General combining ability

SCA Specific combining ability

Vll 1

Introduction

All organisms exhibit a multitude of behavioural phenotypes throughout their lifetime, and these behaviours vary between species, and even among individuals within a species. Some of these behaviours may be used only at certain times, such as courtship, copulation, aggression and oviposition, while others may be employed on a more regular basis, such as learning, memory, olfaction, gustation, mechanosensation, and foraging behaviour. Such behaviours are extraordinarily complex phenotypes integrating a great number and wide array of biological processes. An organism's behavioural response to a stimulus involves the processing of information by the nervous system, the appropriate expression of genes that affect the behaviour, and communication to other cells in the organism to elicit the ultimate behavioural response. Behavioural phenotypes are typically plastic in nature, and can adapt to environmental conditions and to the needs of the organism.

There is considerable evidence, from studies of a number of model organisms, to support a significant genetic contribution to variation in many complex behavioural phenotypes (Sokolowski, 2001; Rankin, 2002; Bucan and Abel, 2002). This relationship between genes and behaviour is complicated, and can provide us with powerful insights into how organisms interact with their environments. Due to the intricate nature of behavioural phenotypes, single behaviours are likely polygenic, or under the influence of many different genes (Pflugfelder, 1998; Heisenberg, 1997). At the same time, single genes may show pleiotropic effects, where one gene influences multiple phenotypes (Pflugfelder, 1998).

Feeding behaviour in Drosophila melanogaster, while influenced mainly by natural allelic variation in the foraging gene, is thought to be a complex, polygenic behaviour, foraging also 2 exhibits pleiotropy, as it is known to influence a variety of additional phenotypes in

Drosophila. This thesis explores the polygenic nature of feeding behaviour, and investigates possible pleiotropic effects of genes involved in this phenotype.

The investigation of the genetic basis of feeding behaviour is a well-known example of the study of the relationship between genes and behaviour. Foraging, encompassing food- search activities and food-intake, or consumption, is one such behaviour. Foraging has established genetic influences, as has been observed in animals as disparate as worms (de

Bono and Bargmann, 1998), bees (Ben Shahar et al, 2002), ants (Ingram, et al, 2005) and fruit flies (Sokolowski, 1980). To understand the mechanisms driving these differences in foraging behaviour, we must first understand the genes underlying individual differences in food-related behaviours. This thesis explores the genetic underpinnings of foraging and feeding using Drosophila melanogaster as a model organism.

Behaviour Genetics

The idea that genes influence behaviour effectively originated over a century ago, through the work of Gregor Mendel and Francis Galton. Mendel, through his work with simple pea plants, proposed that traits are inherited by means of discrete units, which are now known as genes (Plomin et al., 1990). Some of Galton's earliest work sought to demonstrate a hereditary nature for "genius" (Galton, 1865). He was also the first individual to study identical twins to compare the influences of inheritance and environment (nature versus nurture) on behavioural traits (Plomin et al., 1990). Taken together, the work of Mendel and 3

Galton paved the way for the notion that genes can influence behaviour in a variety of organisms.

Since the pioneering work of Mendel and Galton, studies of behaviour genetics have become increasingly prevalent and complex. There are currently two main approaches when it comes to studying the genetic contributions to behavioural variation: quantitative genetics and the single-gene mutant approach (Greenspan, 2004a; Kendler and Greenspan, 2006).

While the two approaches both strive to elucidate the genetic foundations of behaviour, they show stark contrasts in methodology.

The quantitative genetic approach typically focuses on natural genetic variation that influences behaviour (Greenspan, 2004a). Complex, continuously varying traits are known as quantitative traits, and are typically polygenic in nature. Behavioural phenotypes are classic quantitative traits (Mackay 2001a; Mackay 2001b; Mackay, 2004).

The investigation of natural variation in geotaxis behaviour in Drosophila melanogaster is a classic quantitative genetics experiment (Hirsch and Erlenmeyer-Kimling,

1962). This experiment began with bi-directional artificial selection for positive (high) versus negative (low) geotaxis behaviour. Natural lines were collected in the New York area and the flies were assessed by measuring their preference to go up or down in a geotaxis choice maze. High and low lines were selected for over multiple generations (Hirsch and

Erlenmeyer-Kimling, 1962; Greenspan, 2004b). A number of strains were then generated carrying different combinations of chromosomes from one of the originally selected lines.

These chromosome combinations were inserted into the genetic background of an unselected line (Hirsch and Erlenmeyer-Kimling, 1962; Greenspan, 2004b). The geotaxis phenotype of these lines was tested in a choice maze. The geotaxis behaviour of the combined 4 chromosome lines was compared to that of a neutral, unselected line. Chromosomal analysis of geotaxis behaviour revealed genetic contributions from all chromosomes, as well as interactions among all chromosomes (Hirsch and Erlenmeyer-Kimling, 1962; McGuire,

1992; Greenspan, 2004a; Greenspan, 2004b).

Currently, the most common practice of quantitative genetics is quantitative trait locus (QTL) analysis. A quantitative trait locus is a region of the genome that influences natural variation in a complex phenotype (Anholt and Mackay, 2004; Falconer and Mackay,

1996; Mackay, 2004). In effect, QTL analysis makes use of natural allelic variation to isolate genes that influence behaviour (Anholt and Mackay, 2004; Falconer and Mackay, 1996;

Mackay, 2004). The process starts with two naturally varying lines that differ at a number of molecular markers, and that exhibit opposite extremes of a particular quantitative trait (i.e. high and low geotaxis). These extreme lines are crossed to one another, and serially inbred, to create a population of recombinant inbred lines where each line contains different combinations of the molecular markers present in the parental strains. The phenotype of interest is then measured in these lines, and significant associations between the phenotype and a given molecular marker indicate a role for that QTL in the trait of interest (Falconer and Makcay, 1996; Mackay, 2001a; Mackay, 2001b; Mackay, 2004; Greenspan, 2004a).

While identification of the QTL only reveals the genomic region influencing the phenotype, quantitative complementation analysis and deficiency mapping can narrow the region and hopefully identify a single gene that underlies the phenotype in question.

Most complex phenotypes are thought to be influenced by a number of QTLs that interact with one another in an intricate network (Anholt and Mackay, 2004; Mackay, 2004;

Flint, 2003). Typically, a few QTLs have large effects and account for the majority of 5 variation, while a greater number of QTLs have smaller effects that account for the remainder of variation (Mackay, 2001a; Mackay, 2001b; Mackay, 2004; Flint, 2003; Plomin et al, 2001). For example, it is thought that most behavioural phenotypes in rodents are influenced by between six and 24 QTLs (Kendler and Greespan, 2006).

In contrast to the quantitative genetic approach of investigating genes exhibiting natural variation in behaviour, the single-gene mutant approach induces mutations in the genome to identify genes that influence complex behaviours, and therefore the molecular components involved in that behaviour (Greenspan, 2004a). This approach, instead of focusing on natural variation, aims simply to identify genes that influence behaviour

(Greenspan, 1997; Greenspan, 2004a). The single-gene mutant approach was first employed by Seymour Benzer (1967) to explore phototaxis behaviour in Drosophila melanogaster. One of the advantages of the single-gene mutant approach is that induced mutations typically cause more severe effects on a phenotype than natural allelic variants (Greenspan, 2004a).

Therefore, genes that may otherwise have a very small, and perhaps undetectable, effect on natural variation in a phenotype can be uncovered as contributors to the phenotype using this approach.

One of the best examples of the single-gene mutant approach is the identification of the period gene in Drosophila melanogaster (Konopka and Benzer, 1971). Flies were treated with ethyl methane sulfonate to induce mutations in the genome. Three circadian rhythm mutants (short, long and arrhythmic) were identified in the screen, all of which turned out to be alleles of the period gene (Konopka and Benzer, 1971). The period gene and its function are conserved throughout a number of organisms (Greenspan, 2004a). In addition, although period was originally isolated through a single-gene mutant analysis, the gene shows natural 6 polymorphic variation depending on geographical location (Costa et al., 1991; Costa et ai,

1992). The presence of natural variation in a gene isolated through a mutagenesis experiment bridges the gap between quantitative genetics and the single-gene mutant approach.

Despite their differences, the quantitative genetics and single-gene mutant approaches do share some similarities. Both acknowledge that behavioural phenotypes are complex and likely under the influence of a number of genes. The two methods are therefore both interested in interactions among multiple genes influencing a particular behaviour. While the quantitative genetics approach is more concerned with genetic interactions, the single-gene mutant approach is more focused on the molecular and cellular interactions that underlie the mechanisms influencing behavioural phenotypes.

It is clear that both the quantitative genetics approach and the single-gene mutant approach are dedicated to identifying the genes and networks that influence behaviour. While each approach on its own could achieve this goal, even more knowledge about behaviour genetics could be obtained by combining the two methodologies. This thesis combines both quantitative genetics and single-gene mutant analysis to ask how induced mutations in single genes may interact in a network to influence foraging behaviour, a complex phenotype known to be influenced by natural allelic variation at the foraging locus.

Drosophila melanogaster as a Model Organism

Drosophila melanogaster, the common fruit fly, has been used for many years to model the genetic processes underlying development, physiology and behaviour. Fruit flies 7 exhibit a multitude of complex behaviours such as courtship and foraging, which are amenable to genetic analysis (Sokolowski, 2001). The entire genome has been sequenced

(Adams et al., 2000) and the organism is easy to manipulate genetically using a large number of available genetic tools.

Transposable elements such as P-elements can be inserted in the genome to create mutations in genes (Bellen et al., 2004). Conversely, transposable elements can be excised from the genome to generate genomic deletions (Venken and Bellen, 2005). The GAL4-UAS system of Brand and Perrimon (1993) permits the expression of a gene of interest in particular cells or at particular stages in development. Transgenic fruit flies can be created by inserting exogenous DNA sequences into the Drosophila genome (Rubin and Spradling,

1982). Balancer chromosomes contain multiple genomic inversions and prevent recombination, allowing a chromosome to be passed on to the next generation unchanged

(Hentges and Justice, 2004). Balancer chromosomes are particularly useful for maintaining recessive lethal mutations in a heterozygous state. Genetic mosaics can also be generated in

Drosophila. These are organisms that have the mutant allele of a given gene present in only certain cells of the body, and not others (Hotta and Benzer, 1970). This type of individual can indicate the specific cells or regions of the body involved in a particular phenotype. There are also a number of databases containing a wealth of information about the genetics, development and physiology of Drosophila, the most notable of which is FlyBase (see http://flybase.bio.indiana.edu).

A number of genes in the Drosophila melanogaster genome also have structural and functional homologues in other organisms, including mammals (Adams et al, 2000). The foraging gene is one such example, as it has known homologues in organisms such as bees 8

(Ben Shahar, et al, 2002) and ants (Ingram et al, 2005). In addition, 197 of 287 known human disease genes have homologues in Drosophila (Fortini et al, 2000). This characteristic makes the fruit fly an ideal model organism for genetic studies. The identification and characterization of genes that influence behaviour in fruit flies may provide information regarding related behaviours in many other organisms, including ourselves.

The foraging Gene

The foraging gene (for) is a very well known genetic regulator of feeding behaviour in Drosophila melanogaster. Natural variation in for underlies two behavioural types, called rover (forR) and sitter (for5), with rover being dominant to sitter (Sokolowski, 1980; de Belle and Sokolowski, 1987). Rover and sitter larvae differ in both their pathlength behaviour

(distance travelled on a food substrate) and their food intake. Rovers move more and eat less than sitters in the presence of food, but the two variants do not differ in locomotion on a non- nutritive substrate (Sokolowski, 1980; Kaun et al, 2007a). Rover larvae also tend to move more between food patches than sitter larvae (Sokolowski, 2001). for also influences adult behaviour, with rovers moving farther from a food source after feeding than sitters (Pereira and Sokolowski, 1993).

for encodes a cGMP-dependent protein kinase (PKG), and rovers show higher PKG activity levels than sitters (Osborne et al, 1997). The expression of this protein kinase is plastic in Drosophila. Sitters ubiquitously overexpressing PKG show rover-like behaviour, indicating that this kinase influences feeding behaviour in Drosophila (Osborne et al, 1997). 9

A phylogeny compiled by Fitzpatrick and Sokolowski (2004) suggests a similar and conserved association between PKG and food-related behaviours in a number of organisms.

for was localized to the second chromosome using a "lethal tagging" approach. In this approach, gamma radiation mutagenesis created a change in foraging behaviour from rover to sitter, and caused coincident pupal lethality (de Belle et al., 1989). The lethal mutation acted as a genetic "tag", linking the complex behavioural phenotype with the discrete pupal- lethal one. This permitted the localization of the gene by first mapping the discrete pupal- lethal phenotype, and later confirming the behaviour mapped to the same locus.

The identification and localization of the foraging gene was influenced by both the quantitative genetic and the single-gene mutant approaches to behavioural studies. Natural allelic variation in for underlies foraging behaviour in Drosophila, and for is therefore considered to be a quantitative trait locus. While the foraging gene seems to fit neatly into the quantitative genetics domain, it is also closely tied to the single-gene mutant field. The

"lethal tagging" approach used mutagenesis to induce mutations mfor, and these mutations were ultimately used to map for. The discovery of the foraging gene is an excellent example of how both approaches to behavioural studies can be used to gain a better understanding of the genetic underpinnings of behaviour.

The two foraging variants exist at stable frequencies in natural populations, with an approximate ratio of 70% rovers to 30% sitters (Sokolowski et al., 1980). Experiments have suggested the existence of both density-dependent (Sokolowski et al, 1997) and negative frequency-dependent selection (Fitzpatrick et al, 2007) to maintain the polymorphism. When rover and sitter larvae are reared together in crowded conditions (high density), there is a selective advantage of the rover phenotype. Conversely, low density rearing conditions select 10 for the sitter phenotype (Sokolowski et al, 1997). Negative frequency-dependent selection is evident when rover and sitter larvae are reared together in low nutrient conditions. In this situation, the forR allele and the for* allele both show their highest fitness when rare

(Fitzpatrick et al., 2007).

The molecular and behavioural components of the foraging phenotype are plastic, and can respond to changes in environment. For example, when larvae are food deprived, PKG activity decreases in both rovers and sitters (Kaun et al., 2007a). Corresponding to this molecular response is a behavioural response in which both rovers and sitters increase their food intake and decrease their pathlength (Kaun et al, 2007a; Graf and Sokolowski, 1989).

The foraging gene influences a host of behavioural phenotypes in addition to foraging and feeding, for also plays a role in thermal stress tolerance (Dawson-Scully et al., 2007), learning and memory (Kaun et al., 2007b; Mery et al., 2007) and sucrose responsiveness

(Belay et al., 2007; Scheiner et ah, 2004). Furthermore, for has an effect on fat body morphology in Drosophila melanogaster larvae, with rovers showing larger lipid droplets than sitters (Belay, unpublished data), foraging is therefore a classic example of a pleiotropic gene - a single gene influencing many phenotypes.

While the foraging gene is clearly pleiotropic, the possible polygenic nature of foraging behaviour is not so apparent. Genes that might interact with for and affect not only foraging behaviour, but other food-related phenotypes, remain largely unexplored. The seven mutations that are the focus of this thesis are known to play a role in foraging behaviour. The present study attempts to identify the genes underlying these mutations, and explores a possible role for these mutations in food intake, as well as possible interactions among these mutations to influence foraging behaviour in Drosophila. 11

Mutagenesis

Mutagenesis is a process by which mutations are induced in the genome. It is a very popular technique used to create new mutations in Drosophila melanogaster in the hopes of identifying genes underlying specific phenotypes. There are a variety of different types, although the most common are insertional and chemical mutagenesis (St. Johnston, 2002). In insertional mutagenesis, mutations are induced by the insertion of transposable P-elements into the genome. Insertional mutagenesis is not the most efficient mutagenesis method, as there are many insertion biases to P-elements. For example, P-elements will often preferentially insert into certain sequences, into the 5' end of genes, or near other P-elements

(Ryder and Russell, 2003; Pflugfelder, 1998). In addition, some genes are hit at a very high frequency relative to other genes (Ryder and Russell, 2003). Despite these biases, 25% of the vital genes in Drosophila already contain insertions, making P-element induced mutations very useful tools (Spradling et al, 1999).

Chemical mutagenesis is by far the most commonly used mutagenesis method in

Drosophila genetics, and ethyl methane sulfonate, or EMS, is the most commonly used chemical mutagen (Ashburner, 2005; St. Johnston, 2002). The mutagen has a low toxicity to flies, and it is the mutagen that causes the highest frequency of mutations (St. Johnston,

2002). The administration of the mutagen is straightforward, as it is simply fed to adult flies

(Lewis and Bacher, 1968). EMS causes point mutations, or single base changes, which can alter gene function by changing the structure of the protein. Since EMS is an alkylating agent, GC to AT transitions are expected following the mutagenesis (Snow et al., 1984). The number of mutations induced per chromosome is based on the dose of EMS used in the 12 mutagenesis (Ohnishi, 1977). The focus of this thesis is a group of recessive, pupal-lethal, sitter-like foraging mutants created from the EMS mutagenesis of a viable, rover-like control strain.

Epistasis

Complex phenotypes such as behaviours are often under the influence of a number of different genes. It is likely that some or all of the genes affecting a given trait interact with one another in a network or pathway to produce the ultimate phenotype. These types of non- additive genetic interactions among non-allelic genes are known as epistasis. Such interactions occur at both the genetic and the molecular level (Falconer and Mackay, 1996).

Historically, the term epistasis was first used by geneticist William Bateson (1909) in a very broad sense to describe interactions that caused departures from expected Mendelian ratios. Specifically, this use of the term described situations where the effect of one locus masked the effect of another locus (Bateson, 1909; Phillips, 1998). Ronald Fisher, a mathematician, proposed a more detailed definition of epistasis. Fisher defined epistasis as a situation in which the phenotype of a multi-locus genotype could not simply be predicted by summing the individual effects of each gene (Fisher, 1918). In other words, when epistasis is occurring between two genes, the resulting phenotype is not simply equal to the sum of the individual effects of those genes (Fisher, 1918; Phillips, 1998).

Degrees of epistasis can vary depending on genomic complexity. Smaller, simpler genomes (such as viruses) tend to exhibit antagonistic epistasis (where mutations in 13 combination have a smaller effect than expected), while larger, more complex genomes (such as eukaryotes) tend to exhibit synergistic epistasis (where mutations in combination have a larger effect than expected) (Sanjuan and Elena, 2006).

Epistatic interactions are thought to be archetypal features of complex traits in

Drosophila melanogaster (Mackay, 2004). A number of studies have investigated epistatic networks underlying behavioural phenotypes in Drosophila melanogaster. Interactions among a group of co-isogenic smell-impaired loci were investigated by testing the olfactory behaviour of all possible transheterozygote combinations of the loci. Many of the loci showed epistatic interactions with one another to influence olfactory behaviour in Drosophila

(Fedorowicz et al, 1998). The majority of these interactions showed greater phenotypic effects than expected, a result which corresponds to the predicted synergistic epistasis of complex genomes (Fedorowicz et al., 1998; Sanjuan and Elena, 2006). The investigation of epistatic interactions among foraging loci presented within this thesis is based on this study of smell-impaired loci. In another example, biometrical genetic analyses of geotaxis data in

Drosophila suggested the presence of extensive epistatic interactions among genes on all three major chromosomes (McGuire, 1992).

A study by van Swinderen and Greenspan (2005) identified 16 genes that interact with SyntaxinlA to affect loss of coordination in Drosophila. These genes were identified based on their modification of the coordination phenotype when paired with a mutation in

SyntaxinlA as a double heterozygote. Having demonstrated genetic interactions between each of these genes and SyntaxinlA, the authors went on to investigate epistatic interactions among these 16 functionally related genes. To do this, strains were generated that were heterozygous at 2 of the 16 loci either in the presence or absence of the original SyntaxinlA 14 mutation. All possible combinations were made, and the coordination phenotype of these lines was measured (van Swinderen and Greenspan, 2005). The relationships among these 16 genes were shown to be plastic depending on the presence or absence of the starting mutation, indicating flexibility within an epistatic network (van Swinderen and Greenspan,

2005). Interactions among genes can also vary depending on environmental conditions. A recent study of olfactory mutants in Drosophila melanogaster not only revealed epistatic interactions among the mutations, but also demonstrated that these interactions changed depending on the concentration of the olfactory stimulus presented (Sambandan et ah, 2006).

The ability of interactions to influence behavioural plasticity is extremely important.

If multiple genes influence a given phenotype, there are many possible ways for these genes to interact and modulate that phenotype in response to environmental conditions and/or the needs of the organism. This ability to adapt to various conditions is crucial to survival. If genes within a network are involved in a number of different cell types, as is likely the case in complex eukaryotes like Drosophila, the number of possible modifications that can be made increase exponentially (Greenspan, 2001).

Evolutionary processes are also influenced by epistatic interactions. Epistasis is thought to affect elements like fitness, adaptive evolution and canalization (Brodie, 2000;

Templeton, 2000; Rice, 2000). It is clear that epistatic interactions have important implications in the genetics, evolution and plasticity of complex traits, such as behaviour.

Identifying epistatic interactions at the genetic level can help to elucidate the intricate cellular and molecular mechanisms that generate phenotypic variation. This thesis explores epistatic interactions among loci involved in foraging behaviour in Drosophila melanogaster. 15

Mapping of Mutations

Deficiency mapping and complementation analysis are common methods used to identify genes influencing a phenotype of interest. A deficiency chromosome is a chromosome in which a known genomic region has been deleted (Anholt and Mackay,

2004). For mapping qualitative traits, when a recessive mutation of interest is crossed to a deficiency, observation of the mutant phenotype in the offspring (failure to complement) indicates that the gene of interest is contained within that deficiency (Pasyukova et al., 2000).

This approach can also be used by crossing the mutation of interest to mutations (such as P- element insertions) in candidate genes, instead of deficiencies that may encompass multiple genes, to look for complementation. The method is slightly different when mapping quantitative traits, such as behaviour. In this case, the mutant chromosome is paired with either a deficiency chromosome or a balancer chromosome (Pasyukova et al., 2000). This is called quantitative complementation analysis. If the phenotype of the mutant paired with the deficiency is significantly different from the mutant paired with the balancer (but not significantly different from the homozygous mutant), the gene of interest is contained within the deficiency (Pasyukova et al., 2000).

As previously mentioned, chemical mutagenesis (specifically EMS mutagenesis) of a control strain can create single base change mutations that produce phenotypic changes.

These types of mutations can also be mapped by sequencing candidate genes of interest in both the mutant and control strains to look for sequence polymorphisms between the two.

The mapping of mutations to single genes can often reveal the molecular function of that gene. If a network of genetic interactions is already known, mapping the loci involved 16 down to single genes will provide vast insight into the cellular and molecular mechanisms that bring about variation within a phenotype.

This thesis investigates the role of 7 EMS induced mutations in foraging behaviour and food intake, two complex behavioural phenotypes, using Drosophila melanogaster as a model organism. These mutations are shown to influence both foraging and food intake, although they do not exhibit the same inverse relationship between these phenotypes that is seen in rover and sitter alleles of the foraging gene. In addition, epistatic interactions among these mutations were investigated, and we show that at least 5 of the 7 mutations interact with one another in a genetic network to influence foraging behaviour. This network of genes may contribute to the plasticity of the foraging phenotype in Drosophila. Efforts to map the genes underlying these mutations using complementation analysis and sequencing methods are ongoing, although none of the genes have yet been conclusively identified.

While the majority of natural phenotypic variation in larval foraging behaviour can be attributed to foraging, the work in this thesis identifies an interacting network of additional genes that influence foraging behaviour in Drosophila melanogaster. While these genes may not exhibit natural allelic variation in foraging behaviour, the results presented here suggest smaller roles for a number of additional genes in this complex phenotype. Since the genetic interactions among these mutants are now known, the eventual identification of the genes underlying these mutations, and their corresponding functions, will help to elucidate the mechanisms that shape phenotypic variation in foraging behaviour both in Drosophila melanogaster, and in other, more complex, organisms. 17

Materials and Methods

Fly Stocks

Seven previously isolated Drosophila ethyl methane sulfonate (EMS) induced recessive foraging mutants were used: pokey, homebody, lingerer, loiterer, lackadaisical, caboose and lazybones (Shaver et al., 2000). These mutants were all isolated from the EMS mutagenesis of ry+5, an isogenic control strain that is homozygous for the rover allele at the foraging locus and is rover-like in foraging related locomotion (Shaver et ah, 2000). Based on the "lethal tagging" approach used to localize foraging (de Belle et al, 1989), Susan

Shaver tested the foraging pathlength behaviour of over 100 pupal-lethal lines generated from this EMS mutagenesis, looking for a behavioural change coincident with the pupal- lethal phenotype. Following the mutagenesis, each of these 7 mutant lines exhibited sitter­ like foraging related locomotion and coincident pupal lethality. This behavioural change is food specific, as the control strain does not significantly differ from the mutant lines in locomotion behaviour on agar, a non-nutritive substrate.

The mutations have all been localized to regions on the second chromosome, and none co-localize with foraging. These lines share a common isogenic background because they were isolated from the mutagenesis of a single ry+5 strain, and because the balancer strain used in the crossing scheme to isolate the mutants was also on a ry+5 background

(Humphreys et al. 1996). 18

The dose of EMS used in the mutagenesis of ry+5 was low (12mM), and was expected to induce, on average, a single base change per chromosome, which will likely affect only a single gene (Shaver et al, 2000; Humphreys et ah, 1996; Ohnishi, 1977). For each mutant strain, the lethality and the behaviour independently mapped to the same chromosomal region, suggesting co-localization of these phenotypes to a single gene. These recessive, pupal-lethal foraging mutants are all balanced over the second chromosome balancer CyO.

ry+5 was used as a control strain with the mutant lines in all behavioural assays. All strains were maintained at 22°C ± 1°C in a 12L:12D cycle with lights on at 0800 hours, in

170mL culture bottles containing 40mL of a standard yeast-sucrose-agar medium.

Aging of Larvae

Strains and crosses were maintained at standard conditions (25°C ± 1°C in a 12L:12D cycle with lights on at 0800 hours) in a 170mL plastic culture bottle with a small Petri dish lid containing a grape juice-agar medium for oviposition. The 7 mutants are all balanced over the second chromosome balancer CyO with a green fluorescent protein (GFP) marker. Larvae carrying the GFP balancer will fluoresce green when viewed under a fluorescent microscope.

Homozygous mutant larvae from the mutant lines of interest will not carry the CyO-GFP balancer and therefore will not fluoresce (non-GFP). Similarly, when two mutant lines of interest are crossed to one another, the transheterozygote individuals will not carry the balancer and will not express GFP. 19

Fifty non-GFP (homozygous parental strains or transheterozygotes) newly hatched first instar larvae from each strain or cross were placed in a small Petri dish containing 15mL of a standard yeast-sucrose-agar medium. These larvae were kept at 25°C ± 1°C until they reached the third instar stage (96±2 hours post-hatch). This developmental stage was chosen for the testing of all larval behaviours because when the mutant strains were originally isolated this is the developmental stage at which the foraging behaviour was tested.

The mutant lines were originally isolated as pupal-lethal foraging mutants. They have been maintained in the lab for 7 years. Over this period, the stage of lethality changed in some of the mutant lines (Ashburner, 2005). Three of our 7 foraging mutants (lingerer, loiterer and caboose) are now lethal earlier than the pupal stage as homozygotes. The larvae begin to wander as second instars, and die before they reach third instar stage. The foraging and food intake behaviours of these lines were not able to be tested since larval behaviours are tested at the third instar stage. The remaining 4 foraging mutants (homebody, lackadaisical, pokey and lazybones) maintained their pupal lethality and thus were tested for behaviour. All 7 mutants could be investigated as heterozygotes.

Larval Foraging Related Locomotion Assay

To confirm the phenotype found by Shaver and colleagues (2000), the foraging related locomotion of the viable third instar EMS induced foraging mutants was tested, along with the natural rover and sitter strains, and ry+5, the unmutagenized control for the mutant lines. Thirty homozygous third instar larvae were tested for each strain in 3 replicate 20 experiments. Foraging related locomotion, or pathlength, was quantified as described in

Pereira et al. (1995). Briefly, shallow circular wells (8.5cm in diameter) carved into black plexiglass plates were coated in a thin layer of aqueous yeast (distilled water and Baker's yeast in a 2:1 ratio). Individual third instar larvae were placed in the centre of each of these wells. All of the wells were covered with a standard Petri dish lid, and the larvae were allowed to forage on the food substrate for 5 minutes. After 5 minutes, the distance traveled by each larva (pathlength) was traced onto the Petri dish lid that covered the well.

Pathlengths were then traced onto a sheet of paper, scanned, and quantified using ImageJ.

Larval Food Intake Assay

Food intake was measured for our 4 viable mutant lines of interest, along with ry+5 and the natural rover and sitter strains, in 2 replicate experiments. To measure food intake, the bottom surface of a medium Petri dish (60x15mm) was coated in a layer of aqueous yeast

(distilled water and Baker's yeast in a 2:1 ratio) containing 1/200 fluorescein by volume.

Forty-eight homozygous third instar larvae (96±2 hours post-hatch) of a single strain were placed together in a single dish and allowed to feed on the yeast-fluoroscein substrate for fifteen minutes. After fifteen minutes, the forty-eight larvae were washed in distilled water, and divided into six 1.5mL microtubes, with 8 larvae suspended in 150ul 0.1M Tris (pH 9) per microtube. This made a total of six replicates per strain, with 8 larvae per replicate.

Larvae were homogenized in the Tris solution, and the homogenates were transferred into 21 individual wells in a 96-well plate. The amount of fluorescein ingested was quantified using a fluorometer. The quantity of fluorescein ingested served as a measure of food intake.

Generation of transheterozygotes

Epistatic interactions among the EMS induced foraging mutants were investigated by creating transheterozygote lines, using a previous study which explored epistatic interactions among olfactory loci in Drosophila melanogaster (Fedorowicz et ah, 1998) as a model.

Twenty-one transheterozgote lines were generated from crosses among the 7 parental foraging mutant lines: pokey, homebody, lingerer, loiterer, lackadaisical, caboose and lazybones. These lines were crossed to one another in a half-diallel design to create all possible transheterozygote combinations (according to Griffing, 1956). Males of parental line i were crossed to virgin females of parental line j (where i and j are two of the seven aforementioned parental lines, and i ±j). This half-diallel design excludes reciprocal crosses.

Since the crossing scheme used to generate the mutants ensured that all lines had identical genetic backgrounds and therefore identical X chromosomes, reciprocal crosses were unnecessary (Humphreys et ah, 1996). Homozygous parental lines are not included in the half-diallel design (Griffing, 1956).

It is important that the lines of interest share a common genetic background. A controlled background genotype allows subtle effects to be detected, and ensures that any significant interactions are in fact due to epistasis among the loci, and not due to confounding effects of background genotype (Fedorowicz et ah, 1998). 22

To investigate epistatic interactions among these mutants, third instar larvae of each of the twenty-one transheterozygote strains were tested. Rover and sitter, the two natural foraging variants, as well as ry+5, the unmutagenized control strain, were also tested. Twenty third instar larvae for each of these twenty-four strains were tested for pathlength every day over 5 consecutive days.

Statistical Analysis

Variation in mean pathlength and food intake among the parental mutants and ry+5

(their control) was measured using a two-way ANOVA with strain and replicate as fixed effects. Student-Newman-Keuls (SNK) tests were used a posteriori to determine significant differences between the means.

Variation in pathlength behaviour of transheterozygotes was analyzed using a two way analysis of variance (ANOVA), with genotype and day as fixed effects. Sums of squares were divided into genotype, day, genotype x day interaction and error sources. An F-ratio test statistic was used to measure the overall genotype, day and genotype x day effects. Since a fixed effects model was used, the error mean square was the denominator for all F variance ratio test statistics. Out of the five test days, the three days that minimized strain by day interactions were selected for analysis. Epistatic effects among our 7 loci were investigated by comparing the foraging performance of all transheterozygote lines to one another, as opposed to comparing them to their homozygous parental lines. By comparing transheterozygotes only with one another, we control for the effect of heterozygosity. 23

The statistical analysis involves quantifying the general and specific combining abilities of the mutant lines of interest (GCA and SCA, respectively). The sum of squares for the genotype effect was partitioned into GCA and SCA effects, and the significance of overall GCA and SCA effects was measured using an F-ratio test statistic. Specific GCA values were then calculated for each parental line, and SCA values were calculated for each transheterozygote combination.

The general combining ability is the average score (in this case, pathlength) of a given mutation when in transheterozygote combination with all other mutations, expressed as a deviation from mean of all crosses in the diallel (Falconer and Mackay, 1996; Lynch and

Walsh, 1998). In other words, it estimates the heterozygous effect of a given mutation relative to all other mutations. According to the half-diallel design outlined in Method 4,

Model I by Griffing (1956), GCA effects are calculated as:

GCA, = T, / (n - 2) - XT / n(n - 2) (1) where T,- is the sum of mean pathlength scores for all transheterozygotes containing the rth mutation, n is the number of mutant lines, and XT is twice the sum of mean pathlength scores for all transheterozygotes (each transheterzygote contributes to two totals, one for each parent) (Falconer and Mackay, 1996; Fedorowicz et al, 1998). If additive gene action is at work (i.e. no interaction), the score of a given transheterozygote is expected to be the sum of the GCAs, or heterozygous effects, of each parent (Falconer and Mackay, 1996).

The specific combining ability quantifies the difference between the observed score of a given transheterozygote and the score expected from the sum of the parental GCAs, again expressed as a deviation from the overall mean (Fedorowicz et al., 1998). A significant deviation of the actual transheterozygote score from the sum of the two GCAs is indicative of 24 non-additive genetic interaction (epistasis) between the two genes of interest. Again as per

Griffmg (1956), the SCA effect of each transheterozygote is calculated as:

SCAy = xy - (T,- + T» / (n - 2) + £T / (n - l)(n - 2) (2) where xy is the mean pathlength for the transheterozygote carrying the rth andy'th mutations.

The SCA equation can be simplified as:

SCA(> = x^ - (GCA, + GCAy) - overall mean (3) where the overall mean is £T / (n(n-l)).

GCA and SCA values were calculated as per equations (1) and (2), respectively. A student's t test was used to determine whether each GCA and SCA value is significantly different from zero. A significant difference is indicative of a greater than average heterozygous effect (GCA) or of epistatic interactions between 2 of the loci (SCA). All analyses of variance were carried out using SAS. Sums of squares for GCA and SCA were calculated using DIALL (Schaffer and Usanis, 1969). Analysis of the epistasis data was generously performed by Trudy Mackay at the University of North Carolina.

Complementation Analysis

As previously mentioned, the lethal and the behavioural phenotypes of these mutants both independently mapped to the same chromosomal region. This, in conjunction with the expected single base change caused by the EMS mutagenesis, indicates co-localization of these phenotypes to a single gene. Based on this theory of co-localization, the discrete, pupal- lethal phenotype can be mapped first using complementation analysis. If a gene is identified, 25 subsequent testing can confirm that the behavioural phenotype maps to the same locus. Since the mutants of interest are all balanced over the second chromosome balancer CyO, we can cross these lines to recessive lethal mutations or insertions in known genes (also balanced over CyO) available within their respective chromosomal regions.

If the known lethal mutation selected for the complementation test is in the same gene that is responsible for the mutant pupal-lethal phenotype, then there is no complementation and the viable progeny of a cross between the recessive foraging mutant and this known lethal line will only have curly-wings. This is because flies homozygous for the CyO balancer are lethal, and flies with both the recessive foraging mutation and the known lethal mutation will be lethal, since they are in the same gene. If there is complementation, then the lethal mutation is found in a gene different from that responsible for the pupal-lethal phenotype. In this case, viable progeny will be straight-winged or curly-winged. For each known lethal mutation, complementation crosses were performed in 5 reciprocal sets. These crosses were maintained in plastic culture vials containing lOmL of a standard yeast-sucrose- agar medium in standard conditions. The viable progeny from each cross were scored for the presence of either curly wings, or curly and straight wings.

Sequencing Analysis

Sequencing is another tool that can identify the gene responsible for our phenotypes of interest. As previously mentioned, the dose of EMS used is expected to induce a single base change per chromosome, which will likely affect a single gene. This single base change 26 likely underlies the two observed post-mutagenesis phenotypes (lethality and behaviour), which are expected to co-localize to this single gene. Candidate genes of interest were identified within the known mutant regions and the entire coding region of the gene was sequenced in both the ry+5 control strain and the corresponding mutant line. The two sequences were compared to one another in an attempt to identify the single base change caused by the mutagenesis, and therefore the gene responsible for the observed phenotypes.

If a gene is identified based on a sequence difference between the control strain and the mutant, complementation analysis and behaviour testing can be used to confirm that the lethal and the behavioural phenotypes do indeed map to that gene.

Genomic DNA Extraction

Genomic DNA was extracted from homozygous mutant third instar larvae. The extraction protocol was modified from the DrosDel protocol. In a 1.5mL microtube, fifteen homozygous mutant third instar larvae were homogenized in 300 ul of the following solution: lOOmM Tris-HCl (pH 8), lOOmM EDTA, lOOmM NaCl and 0.5%SDS. The homogenate was then incubated at 65°C for thirty minutes. 172 ul 5M KAc and 428 ul 6M

LCI (1:2.5 ratio) were added, and the solution was incubated on ice for twenty minutes.

Following incubation, the solution was centrifuged for twenty minutes at 12000 rpm. 600 ul of the supernatant was transferred to a new 1.5 mL microtube and DNA was precipitated with 450 ul (approximately 0.6 volumes) ice cold isopropanol. This new solution was centrifuged for 5 minutes at 12000 rpm. The supernatant was discarded and the precipitate 27 was washed in 500 ul 70% EtOH as follows: EtOH was added, the solution was vortexed until the pellet was loose and was centrifuged for 1 minute at 12000 rpm. Following centrifugation, EtOH was discarded and the precipitate was allowed to dry for 5 minutes.

DNA was resuspended in 50 ul sterile dE^O and stored at -20°C.

Amplification, Purification and Sequencing

Candidate genes of interest were amplified using Polymerase Chain Reaction (PCR).

DNA of the gene of interest was purified from the PCR product using the QIAGEN

QIAquick PCR Purification Kit. Sequencing reactions were carried out by the CORE

Molecular Biology Facility at York University. 28

Results

Larval Foraging Related Locomotion

Rover and sitter larvae differ in their foraging related locomotion, with rovers moving more than sitters in the presence of food (Sokolowski, 1980; de Belle and Sokolowski, 1987).

The 7 mutants that are the focus of this thesis were originally isolated as sitter-like foraging mutants derived from the EMS mutagenesis of ry+5, a strain which is homozygous for the rover allele at for and is rover-like in its larval foraging related locomotion (Shaver et ah,

2000).

To confirm the larval foraging related locomotion phenotypes of the rover-like control strain and the sitter-like foraging mutants, the foraging pathlength of homozygous third instar larvae for ry+5 and the viable foraging mutant strains (homebody, lackadaisical, lazybones and pokey) was measured in three replicate experiments.

As expected, the results were consistent with the previously shown phenotypes of these lines. Differences among ry+ , homebody, lackadaisical and lazybones were analyzed using a two-way ANOVA on strain and replicate with a significance value of 0.05. The

ANOVA results showed a significant effect of strain (F(3,338)=180.148, pO.OOl), no significant effect of replicate (F(2,338)=0.994, p=0.371) and no significant strain-by-replicate interaction (F(6,338)=l-917, p=0.077). The lack of significance of both the replicate effect and the strain-by-replicate interaction allowed us to pool the replicates for these lines (Figure 1).

While pokey showed consistent and expected differences with ry+5 within each individual replicate experiment, the pathlength measures of this mutant were not consistent 29 across the three replicate experiments. The data for pokey could therefore not be pooled, and instead a representative value of pokey's performance was selected and is presented in Figure

1. All of the mutants tested showed a significantly lower foraging pathlength than their ry+ control. In addition, the natural and rover strains behaved as expected. Rovers did not significantly differ from ry+5, and showed significantly higher pathlengths than sitters and the

EMS mutants. The pathlength of sitters was significantly lower than that of rovers and ry+5, and was similar to that of the EMS mutants. Overall, it is clear that the third instar homozygous viable mutant lines still show the sitter-like foraging related locomotion phenotype that was present when they were isolated 7 years ago.

Food Intake

Rover and sitter larvae also differ in their food intake, such that well-fed rover larvae have lower food intake than sitter larvae (Kaun et al., 2007a). We asked whether this inverse relationship between foraging related locomotion and food intake was also found in our foraging mutant lines. The food intake of homozygous third instar larvae of the homebody, pokey, lackadaisical and lazybones mutants and the ry+5 control line was measured in two replicate experiments.

Interestingly, we found that foraging related locomotion and food intake were not inversely related in these mutant lines. A two-way ANOVA on strain and replicate using a significance value of 0.05 showed a significant effect of strain (F(4j49) = 41.084, pO.OOl), no significant effect of replicate (F(i)49) = 0.643, p=0.426) and no significant strain-by-replicate 30

interaction (F(4>49) = 1.875, p=0.130). The lack of significance of both the replicate effect and the strain-by-replicate interaction allowed us to pool the replicates (Figure 2).

ry+5, the control strain that is rover-like in its foraging related locomotion, had one of the highest food intake levels, while 3 of its sitter-like foraging mutant derivatives

(homebody, lazybones and lackadaisical) showed significantly lower consumption levels

(Figure 2). These results show a positive relationship between foraging related locomotion and food intake, which differs from that found for the allelic variants of for. The significant differences seen between these 3 mutant lines and ry+5 in both foraging related locomotion and food intake suggests the single mutagenesis affected both of these food-related phenotypes. The exception to this pattern is pokey, whose food intake is significantly higher than that of the other mutants, and does not differ from ry+i'. The natural rover and sitter lines showed expected levels of food intake. Rover food intake did not significantly differ from that of ry+5, and was higher than that of the EMS mutants. Sitters showed a food intake significantly higher than that of rovers, ry+5, and the EMS mutants. While previous work demonstrated that these EMS-induced mutations affect foraging related locomotion, the present study suggests that some of the mutations also influence food intake in Drosophila melanogaster larvae.

Epistasis

The 7 EMS induced mutations investigated in this thesis influence foraging related locomotion in Drosophila melanogaster. These mutants are genetically rovers (like the ry+5 31 control), but the induced mutations make them behave as sitters. Since none of the mutations map to for, we know the behavioural phenotype is not a result of a change at the foraging locus. Since these 7 mutations all influence a common phenotype, we hypothesized that they may be functionally related, and we were therefore interested in possible interactions among them. We were able to investigate these interactions because our mutants were generated on a common genetic background during the mutagenesis of the isogenic strain ry+5.

Twenty-one transheterozygote lines were generated from crosses among the 7 mutant lines in a half-diallel design (Figure 3). The foraging related locomotion of these transheterozygote lines was measured to quantify possible epistatic interactions among the loci.

Assuming a fixed day effect, analysis of variance showed statistically significant genotypic variation among the transheterozygote lines, indicating significant differences in the foraging behaviour of these different genotypes (F(2o,ii7i) = 7.55, pO.OOOl). This genotypic variation was divided into overall general combining ability (GCA) and specific combining ability (SCA) effects, and the significance of these effects was measured using an

F-ratio test statistic. The transheterozygote lines showed significant overall GCA (F^.ini) -

13.997, pO.OOOl) and SCA (F(i4,ii7i) = 4.632, pO.OOOl) effects. The significant variation in overall GCA indicates differences in the heterozygous effects of each parent, while the significant overall SCA effect suggests the presence of epistatic interactions among these loci. General combining abilities were calculated for each of the 7 parental mutations, and the significance of these values was measured using a student's t test. Five of the 7 mutant lines showed significant GCA effects (Table 1). 32

Specific combining abilities were calculated for each transheterozygote genotype, and the significance of these values was measured using a student's t test (Table 2, significant results shown in bold). Significant SCA effects are those in which the performance of the transheterozygote is significantly different from the expected performance based on the sum of the two GCA scores of the parents. When interpreting the SCA values, it is important to note that the sitter-like foraging behaviour found in the mutants is considered to be the mutant phenotype. A negative SCA that is significantly different from the sum of its GCAs means the score of the double heterozygote is worse than would be expected given the average heterozygous effects of the parental mutations (enhancement of mutant phenotype).

A positive SCA that is significantly different from the sum of its GCAs means the score of the double heterozygote is better than expected from the average heterozygous effects of the parental mutations (suppression of mutant phenotype). Since all of the mutant lines share a common genetic background, any interactions detected will be due to epistatis between the mutations of interest.

Seven of the 21 transheterozygote lines show epistatic interactions based on significant specific combining abilities (pokey/lackadaisical, pokey/lingerer, lackadaisical/lazybones, lackadaisical/lingerer, homebody/lingerer, lazybones/loiterer, lingerer/loiterer). Three of these seven significant cases had negative SCA values

{pokey/lingerer, lackadaisical/lazybones and lingerer/loiterer), indicating enhancement of the mutant phenotype (sitter-like behaviour). The remaining four cases had positive SCA values, indicating suppression of the mutant phenotype. The significant interaction between homebody and lingerer is driven by the results of only one of the three pooled days, and 33 therefore may not be a true interaction. Overall, of 7 loci known to influence foraging related locomotion, 5 interact with at least one another in a genetic network (Figure 4).

To correct for multiple comparisons, a sequential Bonferroni test (Rice, 1989) was performed on the SCA data. Adjusting the probability value using this test resulted in significant SCA values for only 3 transheterozygote lines {lackadaisical/lazybones, lingerer/loiterer and lazybones/loiterer), encompassing 4 of our 7 loci.

These results indicate that an intricate network of gene interactions contributes to the complex foraging related locomotion exhibited by Drosophila melanogaster larvae. While much of the natural phenotypic variation seen in foraging related locomotion can be attributed to the foraging gene, it is clear from this work that there are additional genes that can be mutagenized to affect foraging related locomotion.

Complementation Analysis

Lethal complementation testing was used to identify one or more of the genes underlying our mutations of interest. In total, 31 lethal mutations and lethal P-element insertions were tested for complementation throughout the known chromosomal regions

(Table 3). All crosses showed complementation, indicating that none of the lethal mutations selected within the deficiencies for our mutant lines were in the same gene responsible for the observed pupal lethal phenotype. Efforts to identify the gene of interest in each of these regions will continue as additional tools in our regions of interest become available, such as smaller deletions and new lethal mutations. 34

Sequencing Analysis

In addition to complementation testing, sequencing analysis was used to try to identify one or more of the genes underlying our mutations of interest. Candidate genes of interest were selected based on known functions that may relate to foraging behaviour, such as involvement in taste, feeding, or in the cGMP-dependent protein kinase (PKG) pathway which is known to influence foraging related locomotion. The coding regions of candidate genes were sequenced to look for a single base change that may be responsible for the observed lethal and behavioural phenotypes (Table 4). None of the candidates sequenced thus far showed sequence differences between control third-instar larvae (ry+5) and homozygous mutant third-instar larvae from the region of interest. 35

Figure 1: Foraging related locomotion, or pathlength, of homozygous third instar larvae was quantified by measuring the distance traveled by a larva in a 5 minute period. As expected, the rover-like control strain (ry+5) showed a significantly higher pathlength than all of its sitter-like mutant derivatives. Data from three replicate experiments was pooled for ry , homebody, lackadaisical and lazybones. The pathlength value for pokey is a representative mean value from a single replicate. Letters represent SNK groupings.

Levels with the same letter are not significantly different. 36

10

A

E o o» 5 c

Q. B B

C

1 1

ry+5 homebody lackadaisical lazybones pokey Strain 37

Figure 2: Food intake of homozygous third-instar larvae was quantified by measuring the amount of fluoroscein-yeast substrate consumed. Most of the sitter-like foraging mutants showed decreased food intake relative to their rover-like control, the exception being pokey, which did not significantly differ from the ry+5 control. Letters represent

SNK groupings. Levels with the same letter are not significantly different. Intake (Arbitrary Units)

Cd

W

01 cr o (I

•a o

00 -K ) pokey homebody lackadaisical lingerer lazybones caboose loiterer pokey — homebody — — lackadaisical — — — 6 lingerer — — — — lazybones — — — — — caboose — — — — — — loiterer — — — — — — —

Figure 3: Diallel crossing scheme used to generate 21 transheterozygote lines. Table 1: Transheterozygote pathlength scores and estimates of general combining abilities of parental lines.

9 lackadaisical caboose homebody lazybones lingerer loiterer Ti GCA P pokey 6.086 5.637 5.496 5.048 5.984 6.874 35.125 0.0455 0.7291 lackadaisical 5.091 5.255 3.831 6.813 5.66 32.735 -0.4383 0.0009 caboose 4.904 4.991 5.819 6.116 32.558 -0.4690 0.0004 8 homebody 5.572 7.041 6.08 34.349 -0.1197 0.3635 lazybones 6.768 6.866 33.076 -0.3786 0.0039 lingerer 6.396 38.822 0.7687 <.0001 loiterer 37.991 0.5915 <.0001

Parental lines are shown in the first column and across the top row. Mean foraging pathlengths for all possible transheterozygote combinations

(excluding reciprocal crosses) of these parental lines are shown. Mean scores were calculated from testing across three days. The T, of a particular line is the sum of the pathlength scores for all transheterozygote combinations containing that mutation. This value is used to calculate the GCA for a given line, as per equation (1). GCA values and their corresponding significance values are shown in the last two columns.

4^ O 41

Table 2: Estimates of specific combining abilities of transheterozygote lines.

Genotype SCA t Value P pokey/lackadaisical 0.6798 2.61 0.0091 pokey/caboose 0.2637 1.01 0.3110 pokey/homebody -0.2725 -1.05 0.2930 pokey/lazybones -0.4421 -1.72 0.0860 pokey/lingerer -0.6427 -2.48 0.0132 pokey/loiterer 0.4137 1.61 0.1087 lackadaisical/caboose 0.1741 0.67 0.5039 lackadaisical/homebody -0.0502 -0.19 0.8472 lackadaisical/lazybones -1.1752 -4.56 <.0001 lackadaisical/lingerer 0.6591 2.56 0.0107 lackadaisical/loiterer -0.2876 -1.10 0.2726 caboose/homebody -0.3183 -1.22 0.2217 caboose/lazybones 0.0151 0.06 0.9531 caboose/lingerer -0.3045 -1.18 0.2375 caboose/loiterer 0.1699 0.66 0.5100 homebody/lazybones 0.2468 0.96 0.3380 homebody/lingerer 0.6247 2.40 0.0166 homebody/loiterer -0.2305 -0.88 0.3766 lazybones/lingerer 0.2377 0.73 0.4678 lazybones/loiterer 0.8132 3.14 0.0017 lingerer/loiterer -0.8788 -3.32 0.0009

SCA values were calculated as per equation (2). Statistically significant SCAs (indicating genetic interaction between loci) are shown in bold. A probability level of 0.05 was used. 42

lazybones loiterer

lackadaisical

+

pokey lingerer

Figure 4: Interaction diagram of EMS induced foraging mutants. + and - indicate suppression and enhancement of the mutant phenotype, respectively. Table 3: List of mutant lines for complementation testing Right Mutant Full Name Region Gene Function Comp? Gene? l(2)SH2135 P{lacW}l(2)SH2135bH-d1J;' homebody CG15678 Unknown Yes No protein amino acid dephosphorylation; Ras1 enhancer; Ras protein l(2)SH1715 P{lacW}l(2)SH1715SH1715 homebody PTP-ER signal transduction (G-protein coupled receptor pathway) Yes No l(2)SH1834 P{lacW}l(2)SH1834SH1834 homebody CG6393 Unknown Yes No l(2)SH0848 P{lacW}l(2)SH0848SH0848 homebody CG30403 DNA binding Yes No l(2)SH0955 P{lacW}l(2)SH0955SH0955 homebody Clt Carboxylesterase Yes No l(2)SH0978 P{lacW}l(2)SH0978SH0978 homebody CG30404 Unknown Yes No l(2)SH1121 P{lacW}l(2)SH1121SH1121 homebody Sdc cytoskeletal anchoring protein; heparin sulphate proteogylcan Yes No 11341 P{PZ}I(2)0360503605 homebody 1(2)03605 Unknown Yes No 12345 P{PZ}I(2)0783707837 homebody 1(2)07837 Unknown Yes No l(2)SH2293 P{lacW}l(2)SH2293SH2293 pokey CG3409 monocarboxylic acid transporter Yes No l(2)SH0498 P{lacW}l(2)SH0498SHO498 pokey Vha16 hydrogen transporting two sector ATPase Yes No l(2)SH0531 P{lacW}l(2)SH0531SH0531 pokey CG3267 methylmalonyl-CoA carboxylase Yes No l(2)SH1846 P{lacW}l(2)SH1846SH1846 pokey 1.28 Protein-transporting two sector ATPase complex Yes No l(2)SH2001 P{lacW}l(2)SH2001SH2001 pokey Coro actin binding, constituent of cytoskeleton Yes No l(2)SH2060 P{lacW}l(2)SH2060SH2060 pokey 1(2)01289 electron transporter, protein disulfide isomerase Yes No l(2)SH2227 P{lacW}l(2)SH2227SH2227 lazybones/lingerer Mio transcription factor Yes No l(2)SH0354 P{lacW}l(2)SH0354SH0354 lazybones/lingerer E2f2 RNA polymerase II transcription factor Yes No l(2)SH2164 P{lacW}l(2)SH2164SH2164 lazybones/lingerer CG9252 Unknown Yes No l(2)SH0764 P{lacW}l(2)SH0764SH0764 lazybones/lingerer CG8671 Unknown Yes No l(2)SH0471 P{lacW}l(2)SH0471SH0471 lazybones/lingerer CG9253 ATP dependent RNA helicase Yes No l(2)SH0123 P{lacW}l(2)SH0123SH0123 lazybones/lingerer l(2)SH0123 Unknown Yes No l(2)SH2113 P{lacW}l(2)SH2113SH2113 lazybones/lingerer CG9247 Unknown Yes No 10662 P{lacW}l(2)k07215k07215 lazybones/lingerer I(2)k07215 Unknown Yes No l(2)SH1156 P{lacW}l(2)SH1156SH1156 loiterer Cyt-B5-r electron transporter, oxidoreductase Yes No l(2)SH1469 P{lacW}l(2)SH1469SH1469 loiterer Grp Protein serine/threonine kinase - checkpoint DNA damage Yes No l(2)SH1473 P{lacW}l(2)SH1473SH1473 loiterer CG17912 DNA binding, nucleic acid binding, zinc ion binding Yes No 11763 P{PZ}bln1 loiterer Bin Unknown Yes No l(2)SH1819 P{lacW}l(2)SH1819SH1819 caboose CG11604 Unknown Yes No 10377 P{lacW}shgk034°1 lackadaisical Shg calcium ion binding, signal transduction Yes No Table 4: Candidate genes of interest sequenced in homozygous third-instar control and mutant larvae.

Strain Region Candidate Gene Location Function Size (bp) homebody 57D8-9; DNA binding, transcription factor binding, RNA polymerase II transcription 58B1-2 Tbp 57F8 factor activity 1441 Transmembrane receptor protein serine/threonine kinase activity, protein CG10307 57F8 kinase activity, transmembrane receptor protein kinase activity 1342 Intracellular cyclic nucleotide activated cation channel - binds cNMP to effect ion flux (Ca) and is a powerful route for modulation of signalling routes by CG17922 57F9 cGMP - cyclic nucleotide gated channel (CNG) 4467 Gr58c 58A4 Gustatory receptor 1295 Gr58a 58B1 Gustatory receptor 1239 Gr58b 58B1 Gustatory receptor 1283 pokey 42A14; 42E3 tomboy40 42A14 Voltage-gated ion selective channel activity 1258 DNA binding, larval locomotion, learning/memory, transcription regulation, Adh Adf1 42C3 transcription factor 5818 Methylmalonyl-CoA carboxylase, fatty acid catabolism/biosynthesis, eclosion CG3267 42C8 regulation 2569 CG15235 42D3 RAP guanyl-nucleotide exchange factor 993 lackadaisical 57B6-14 CG30291 57B5-9 Regulation of cyclin dependent protein kinase activity 1818

-^ -^ 45

Discussion

Natural phenotypic variation in foraging related locomotion is known to be influenced primarily by allelic differences in the single foraging gene in Drosophila melanogaster (Sokolowski, 1980; de Belle and Sokolowski, 1987). While much is known about for and its influence on feeding behaviour, genes that interact with for and affect not only foraging behaviour, but other food-related phenotypes, remain largely unexplored. This thesis explores new genes that affect foraging behaviour and addresses whether these genes interact with one another.

Larval Foraging Related Locomotion

The focus of this thesis is a group of 7 recessive pupal-lethal mutant lines isolated from the EMS mutagenesis of a single strain (ry+3) that is homozygous for the rover allele at for and is rover-like in its foraging related locomotion. Previous work by Shaver and colleagues (2000) demonstrated that these EMS-induced mutations, when present in an individual that is both genetically and phenotypically rover, alter its larval foraging related locomotion behaviour from rover-like to sitter-like. The post-mutagenesis sitter-like behavioural phenotype could not be confirmed in 3 of the 7 mutant lines (lingerer, loiterer and caboose) because changes in the stage of lethality made it impossible to test the behaviour of homozygous third instar larvae. 46

These 3 mutant lines are no longer lethal at the pupal stage of development. They are now lethal prior to the third instar stage, and were therefore unable to be included in any of the behavioural analyses which tested homozygous third instar larvae. However, since the mutations are recessive, these lines were still able to be tested as transheterozygotes for the epistasis experiment.

It is not clear why or how these lines lost their pupal lethality, although this has been known to occur in stocks that have been maintained in the laboratory for a number of years

(Ashburner, 2005). In the future, the mutants could be backcrossed to the ry+5 control strain to try and regain the pupal lethal phenotype. If the lethality could be regained, it would be important to confirm that the mutants are still sitter-like in their foraging related locomotion.

These particular mutants are likely still sitter-like in foraging behaviour, and likely still possess their original EMS induced mutations. If the mutation was lost in a given line, that locus would be like the ry+5 control strain, and interactions would not have been detected in the epistasis screen. Assuming the mutations are still present and the pupal lethality could be regained, it would also be interesting to measure their food intake, to see if it shows a pattern similar to that of the other mutants.

Despite this early lethality in some of the mutant lines, the sitter-like behavioural phenotype was confirmed in the remaining 4 lines that are viable as homozygous third instar larvae (pokey, homebody, lazybones and lackadaisical).

This change in foraging behaviour from rover-like to sitter-like in an individual homozygous for the rover allele suggests that these mutations might somehow interact with for to influence this behaviour, foraging already has a number of known modifiers that alter 47 the foraging behaviour of an individual from what is expected based on the alleles present at the foraging locus.

Chaser is a viable, third chromosome mutation isolated from a gamma mutagenesis screen, and is a dominant suppressor of homozygous for5 individuals. In other words, the presence of at least one copy of the Chaser allele significantly increases the pathlength of sitter larvae to rover-like levels (Pereira et al., 1995).

In 1996, Varnam and colleagues investigated the effect of central complex mutants on

Drosophila larval locomotion on both nutritive and non-nutritive substrates. The central complex is a large neuropil in the insect brain and previous work has implicated the central complex in the regulation of adult locomotory behaviour (Strauss and Heisenberg, 1993).

The study identified 2 food-specific modifiers offoraging, no bridge1 is a recessive mutation, that when present in a genetically rover individual, significantly decreased its foraging pathlength to a sitter-like level (Varnam et al., 1996). Similarly, when present in a rover genetic background, ellipsoid body open significantly decreased foraging pathlength to a sitter-like level (Varnam et al., 1996).

While there are a number of genetic mutations that interact wither, the gene wings up A (wupA) has been identified as a naturally occurring modifier of for (Fitzpatrick et al., in prep). wupA encodes Troponin-I, a regulatory protein that plays a role in muscle contraction

(Perry, 1979). Quantitative trait locus (QTL) mapping identified a region of natural genetic variation on the X chromosome associated with larval foraging behaviour in Drosophila.

This QTL was mapped to the wupA locus on the X chromosome. The presence of a wupA mutation significantly decreased the foraging pathlength of both homozygous rovers and sitters. An independent wupA mutant allele also caused a significant decreased in the 48 pathlength of homozygous rovers. In addition, the presence of a natural wupA allele similarly decreases the foraging pathlength of rovers. wupA therefore appears to be epistatically interacting with for as a dominant suppressor of homozygous for individuals, similar to no bridge and ellipsoid body open .

While the level of Troponin-I protein did not differ between rovers and sitters, the two for variants did show differences in post-translational modification of the protein. The pH distribution of Troponin-I isoforms was greater in sitters than in rovers (Fitzpatrick et al., in prep). Troponin-I is phosphorylated by PKG in mammals, and rovers and sitters are known to differ in their PKG expression. The variation in Troponin-I isoform distribution between rovers and sitters is thought to be due to phosphorylation differences between the for variants

(Fitzpatrick et al., in prep). The association of Troponin-I with the protein encoded by for suggests a possible role for Troponin-I in foraging behaviour. Similarly, the involvement of

Troponin-I in muscle contraction might link this protein to the observed behavioural output of searching and feeding.

Modifiers of for could be either directly or indirectly involved in the PKG pathway

(like wupA), or they may be part of an independent network or pathway that influences foraging behaviour. It would be interesting to measure PKG expression and activity levels in our foraging mutants. If any of the sitter-like mutants, which are on a rover background, showed decreased PKG levels, it would suggest involvement of that gene in the PKG pathway. It would also be interesting to know whether these mutations influence foraging related locomotion when present in a sitter genetic background.

The 7 mutants studied in this thesis show an affect on foraging related locomotion similar to that of wupA, no bridge1 and ellipsoid body open2. This behaviour appears to be a 49

complex phenotype under the influence of multiple genes, and therefore could be associated

with multiple networks and mechanisms.

Our EMS mutants and the known modifiers of for both significantly decrease

pathlength to a sitter-like level when present in a rover genetic background. These EMS

mutants could be acting as additional modifiers of for, although further experiments would

confirm whether or not any of the 7 mutants actually interact with foraging. As more genetic

modifiers of foraging are identified, the networks and mechanisms that underlie foraging

behaviour may become clearer.

Overall, the effect of these mutations on larval foraging related locomotion suggests a

role for these mutants in foraging behaviour and possibly other phenotypes known to be

influenced by foraging, for has a demonstrated role in other behavioural phenotypes

including response to thermal stress (Dawson-Scully et ah, 2007), learning and memory

(Kaun et al., 2007b; Mery et al., 2007), sucrose responsiveness (Belay et al., 2007; Scheiner

et al, 2004) and response to food deprivation (Graf and Sokolowski, 1989; Kaun et al.,

2007a). Following food deprivation, both rovers and sitters decrease their pathlength on a

food substrate (Graf and Sokolowski, 1989), and PKG activity decreases in both rovers and

sitters (Kaun et al., 2007a).

It would be interesting to see if our mutations show pleiotropic effects on these other

/or-related phenotypes. Investigating the role our mutants play in such phenotypes would

help to elucidate the range of phenotypes influenced by these mutations, as well as the gene

interaction networks in which our mutants may be involved. While the effects of our

mutations on these phenotypes remains unexplored, the influence of these mutations on food

intake, a food-related phenotype in which foraging plays a role, is presented in this thesis. 50

Food Intake

Natural variation in foraging not only underlies behavioural differences in foraging related locomotion, but has also been demonstrated to influence food consumption in

Drosophila. When larvae are well-fed, rovers, even though they move more than sitters on a nutritive substrate, actually eat less (Kaun et al., 2007a). In addition, there is no significant difference in size between the two allelic variants of for. We were interested in whether our foraging mutants showed a similar inverse relationship between foraging behaviour and food intake. Based on the foraging related locomotion phenotype of our mutants and the difference between rovers and sitters in their food intake, we expected our sitter-like mutants to consume more than their rover-like control.

Interestingly, none of the sitter-like mutants showed the expected inverse relationship relative to ry+5, their rover-like control, homebody, lazybones and lackadaisical all consumed less food than their rover-like control. This positive relationship between foraging related locomotion and food intake (the more an individual moves the more it eats) is the opposite of what is seen between the rover and sitter allelic variants of for. The exception within this experiment was pokey, which was not significantly different from ry+5. There is no observable difference in size between ry+5 and its mutant derivatives, although quantitative measurements of the size of third instar larvae for these strains would confirm that the food intake difference is not due to larval size. It is not clear at this point why some of these foraging mutations produce the opposite of the expected effect on food intake. The genes underlying these mutations may somehow uncouple the foraging related locomotion and food intake phenotypes, although the mechanism by which this might occur is unknown. 51

It is not known whether the correlation between foraging behaviour and food intake is positive or negative in natural populations. To determine this, a number of natural lines could be collected and the correlation between these two phenotypes could be tested. Regardless of the relationship between these traits in nature, the results presented in this thesis indicate that foraging behaviour and food intake do not need to be inversely related to one another. In other words, there is no apparent physiological requirement or constraint for this inverse relationship.

In fact, an example of a positive correlation between foraging behaviour and food intake is seen in rovers and sitters that have been food deprived. When reared on high quality food prior to testing, rovers consume less food than sitters. Conversely, when reared on low quality food prior to testing, both strains increase their food intake and there was no significant difference in their food intake (Kaun et ah, 2007a). It would be interesting to observe whether our control and mutant strains show a similar pattern following such chronic food deprivation.

Our foraging mutants have yet to be cloned, but the genes underlying these food- related phenotypes may be involved in pathways, or with other genes, already known to influence food intake. For example, the short neuropeptide F (sNPF) gene is known to play a role in adult food intake in Drosophila. Overexpression of sNPF increases food intake, while loss-of-function mutants consume less food (Lee et al, 2004). It would be beneficial to look at genes related to neuropeptide F as candidates for the genes underlying our foraging mutants.

In addition to differing in the amount of food consumed, Kaun and colleagues

(2007a) showed that rovers absorb more glucose than sitters. This increased absorption level 52 in rovers is present in both well-fed and food deprived larvae. Perhaps our mutants also exhibit differences in the acquisition and use of various nutrients. It would be interesting to see if our mutants show the same pattern in this absorption phenotype as is seen in their food intake.

Epistasis

Thus far we have demonstrated roles for the 7 foraging mutants in foraging related locomotion and food intake. Since these mutants all seem to have similar influences on specific phenotypes, we were curious as to whether any or all of these mutations showed epistatic interactions with one another.

Epistasis is a form of non-additive gene interaction. In the absence of epistasis, additive gene action predicts that the effect of two mutations when present together (i.e. in a transheterozygote) will equal the sum of the individual effects of each mutation. If the observed phenotype significantly deviates from the expectation under additive gene action, epistasis is likely occurring (Falconer and Mackay, 1996).

These possible interactions were investigated by crossing our mutants to one another to create all possible transheterozygote individuals, and measuring the foraging related locomotion of these individuals. This study was modeled after a previous experiment investigating epistatic interactions among olfactory loci in Drosophila melanogaster

(Fedorowicz et ai, 1998). This particular type of experiment is ideal for this thesis, since all 53 the mutants share a common genetic background, and it is not necessary to know the identity of the genes underlying the mutations of interest.

This investigation demonstrated that at least 5 of our 7 mutants interact epistatically with one another in a genetic network. It is not clear whether these mutations are all members of the same cellular network, or whether they belong to independent, interacting networks.

These results suggest a number of additional genes can influence foraging related locomotion in Drosophila melanogaster, and that these genes can interact with one another to modulate the phenotype. Behavioural phenotypes involve the integration of a number of processes and actions at the level of both the cell and the whole organism. This intricate combination suggests a complex group of genes acting together to produce a phenotype. In fact, quantitative phenotypes such as behaviour are thought to be influenced by a few major genes, and a number of additional genes, each with smaller effects (Mackay, 2001a; Mackay,

2001b; Mackay 2004; Flint, 2003).

Such complex interactions among genes contribute to the ability of an organism to adapt to different environments and conditions. Recently, genetic interactions among olfactory mutations in Drosophila melanogaster were shown to vary depending on the concentration of the olfactory stimulus presented (Sambandan et ah, 2006). It would be exciting to investigate whether the interactions among our foraging loci show a similar plasticity in response to environmental conditions. For example, it would be interesting to see if the interactions among these loci changed depending on food substrate quality. Plasticity within this genetic network would be further evidence of the complexity of the foraging phenotype in Drosophila melanogaster. 54

While we have demonstrated epistatic interaction at the genetic level, it would also be interesting to show such interactions at the level of the transcriptome. A correlation between genetic and transcriptional epistasis was demonstrated using the aforementioned olfactory mutants, on which the study presented herein was based (Anholt et al, 2003). Five interacting olfactory mutants were investigated using whole-genome expression analysis.

Specifically, whole-genome microarray experiments were performed on each of the 5 strains, and their control. 530 genes showed altered transcription levels in the presence of one or more of the olfactory mutations (Anholt et al., 2003). In other words, these 530 genes appear to be transcriptionally co-regulated in the presence of the olfactory mutations.

The authors then performed quantitative complementation experiments using candidates of interest from the group of co-regulated genes to demonstrate genetic epistasis.

Mutations in these candidate genes were crossed to the olfactory mutants and to the control, and olfactory behaviour was compared in these lines. 67% of the candidate mutations tested showed genetic epistasis with the olfactory mutations, correlating with the previously demonstrated transcriptional epistasis (Anholt et al., 2003). Not only would such an experiment provide insight into interactions at the transcriptional level, it would also propose candidate genes for our mutations of interest based on gene expression data.

In addition, while we know that at least 5 of our mutants interact with one another, it is not yet clear how foraging fits into this interacting network. There are already a number of genes that appear to interact with for to influence foraging related locomotion. While foraging has a major effect on the behaviour, these other genes appear to have smaller, yet significant, effects on foraging related locomotion. These 7 foraging mutants might interact with for to produce similar minor effects on this behaviour. 55

Possible epistatic interactions between our 7 mutants and for could be investigated using quantitative complementation. As a preliminary test, transheterozygotes could be created that carry a given mutant allele (i.e. pokey) along with either the for* ox for allele.

The foraging related locomotion of these transheterozygotes would then be compared to the performance of each foraging allele paired with a balancer chromosome. Differences among these genotypes would indicate epistatic interactions.

A more accurate and extensive assessment offor's role in our epistatic network could be achieved by making transheterozygotes that pair one of the for alleles with one of the mutants and with the unmutagenized ry+5 strain. For example, individuals would be created which carry either the^o^ or the for* second chromosome paired with a mutant chromosome

(i.e. pokey). Before the for chromosome was paired with the mutant chromosome, it would first have to be crossed into a ry+5 genetic background so that it carried the ry+5 X and third chromosomes, just like the mutant. This would control the genetic background so that we are only concerned with the second chromosome. The foraging related locomotion of these transheterozygotes would be compared to the performance of each for chromosome paired with ry+5. Since the mutant and ry+5 only differ at the mutant locus on the second chromosome, the only difference between, for example, forRlpokey and forR/ry+5 would be the mutant locus. If the for chromosomes show a different effect when paired with the mutant chromosome as compared to ry+5, this is indicative of epistatic interactions between for and the mutant.

Finally, it would be very interesting to investigate similar epistatic effects in other phenotypes, such as food intake. While the results of the food intake experiment presented in 56 this thesis were not expected, it would be exciting to see whether these mutant lines showed the same interactions for a different phenotype.

When the genes underlying these mutations are identified, the nature of these interactions could be explored in more depth. The identity of these genes may reveal the mechanisms by which they interact, and how they influence foraging behaviour.

Mapping of Mutations

In addition to exploring the role of these mutants in food-related behavioural phenotypes, work throughout this thesis also aimed to identify the genes underlying these mutations. Both complementation analysis and sequencing were used to try and identify these genes of interest. Unfortunately, none of the genes have been successfully identified thus far.

Additional techniques that were not explored in this thesis could be used to identify the genes. P-elements and meiotic recombination can be used to map a mutation to within

50kb (Zhai et al., 2003). Briefly, the mutant strain of interest (on a white" background) is crossed to a number of viable P-element insertions containing w+. The percentage of white- eyed flies in the F2 generation represents the recombination distance. Using this recombination distance, along with the physical distance between two P-element insertions of interest, an approximate location of the gene of interest can be calculated. This process, if it could not specifically identify the gene, would at least narrow down the potential candidates. 57

While all current lethal P-elements in the regions of interest have been used for complementation analysis, the Berkley Drosophila Genome Project Gene Disruption Project predicted that eventually at least 85% of vital genes in Drosophila melanogaster will be mutated with P-elements (Spradling et al, 1999). This indicates promise for the future availability of additional P-element mutations in our regions of interest, which could be used to identify the genes responsible for these mutations. In addition, more genes could be sequenced, even if their functions are unknown.

Identifying these genes would be beneficial not only to the Drosophila research community, but also to the research of a number of other organisms, for has known functional orthologs in worms (Fujiwara, et al., 2002; L'Etoile et al., 2002), ants (Ingram et al., 2005; Lucas et al., in prep) and honeybees (Ben-Shahar et al., 2002), and there may be unidentified for orthologs in a number of other organisms. Identifying these genes in fruit flies could mean identifying genes with similar functions in other organisms, which would contribute to the elucidation of genetic networks in a variety of model organisms.

When these genes are eventually identified, the nature of their genetic interactions will already be known, allowing more in depth investigations of the mechanisms by which these genes influence food-related phenotypes in Drosophila melanogaster. With the identity of the genes known, further research could be done to elucidate the nature of interactions at the cellular and molecular levels. We know that the genes interact with one another to influence foraging related locomotion, but it would be beneficial to know how the proteins interact to produce the behavioural response. This research is a stepping stone towards the goal of a greater understanding of feeding behaviour not only in fruit flies, but in other more complex organisms. 58

References

Adams, M.D. et al. 2000. The genome sequence of Drosophila melanogaster. Science 287:

2185-2195.

Anholt, R.R., C.L. Dilda, S. Chang, J.J. Fanara, N.H. Kulkarni, I. Ganguly, S.M. Rollmann,

K.P. Kamdar and T.F.C. Mackay. 2003. The genetic architecture of odor-guided

behavior in Drosophila: epistasis and the transcriptome. Nature Genetics 35: 180-184.

Anholt, R.R. and T.F.C. Mackay. 2004. Quantitative genetic analyses of complex behaviours

in Drosophila. Nature Reviews Genetics 5: 838-849.

Ashburner, M. 2005. Drosophila: A Laboratory Handbook. Cold Spring Harbor Laboratory

Press, New York.

Bateson, W. 1909. Mendel's Principles of Heredity. Cambridge University Press, Cambridge.

Belay, A.T., R. Scheiner, A.K. So, S.J. Douglas, M. Chakaborty-Chatterjee, J.D. Levine, and

M.B. Sokolowski. 2007. The foraging gene of Drosophila melanogaster: spatial-

expression analysis and sucrose responsiveness. Journal of Comparative Neurology

504: 570-582.

Bellen, H.J., R.W. Levis, G. Liao, Y. He, J.W. Carlson, G. Tsang, M. Evans-Holm, P.R.

Hiesinger, K.L. Schulze, G.M. Rubin, R.A. Hoskins, and A.C. Spradling. 2004. The

BDGP gene disruption project: single transposon insertions associated with 40% of

Drosophila genes. Genetics 167: 761-781.

Ben-Shahar, Y., A. Robichon, M.B. Sokolowski, and G.E. Robinson. 2002. Influence of gene

action across different time scales on behavior. Science 296: 741-744. 59

Benzer, S. 1967. Behavioral mutants of Drosophila isolated by countercurrent distribution.

Proceedings of the National Academy of Sciences (USA) 58: 1112-1119.

Brand, A.H. and N. Perrimon. 1993. Targeted gene expression as a means of altering cell

fates and generating dominant phenotypes. Development 118: 401-415.

Brodie, E.D. III. 2000. Why evolutionary genetics does not always add up. In: Epistasis and

the Evolutionary Process, J.B. Wolf, E.D. Brodie III and M.J. Wade eds. Oxford

University Press. 2000. pp 3-19.

Bucan, M. and T. Abel. 2002. The mouse: genetics meets behaviour. Nature Reviews

Genetics 3: 114-123.

Costa R., A.A. Peixoto, J.R. Thackeray, R. Dalgleish, and C.P. Kyriacou. 1991. Length

polymorphism in the threonine-glycine-encoding repeat region of the period gene in

Drosophila. Journal of Molecular Evolution 32: 238-246.

Costa R., A.A. Peixoto, G. Barbujani, and C.P. Kyriacou. 1992. A latitudinal cline in a

Drosophila clock gene. Proceedings of the Royal Society of London 250: 43-49.

Dawson-Scully, K., G.A. Armstrong, C. Kent, R.M. Robertson and M.B. Sokolowski. 2007.

Natural variation in the thermotolerance of neural function and behavior due to a

cGMP-dependent protein kinase. PLoS One 2: e773. de Belle, J.S. and M.B. Sokolowski. 1987. Heredity of rover/sitter alternative foraging

strategies of Drosophila melanogaster. Heredity 59: 73-83. de Belle, J.S., A.J. Hilliker, and M.B. Sokolowski. 1989. Genetic localization offoraging

(for): a major gene for larval behavior in Drosophila melanogaster. Genetics 123:

157-163. de Bono, M. and C.I. Bargmann. 1998. Natural variation in a neuropeptide Y receptor

homolog modifies social behavior and food response in C. elegans. Cell 94: 679-

689.

Falconer, D.S. and Mackay, T.F.C. 1996. Introduction to Quantitative Genetics. Ed. 4,

Longman Group Limited, Harlow, England.

Fedorowicz, G.M., J.D. Fry, R.R. Anholt, and T.F.C. Mackay. 1998. Epistatic interactions

between smell-impaired loci in Drosophila melanogaster. Genetics 148: 1885-1891.

Fisher, R.A. 1918. The correlations between relatives on the supposition of Mendelian

inheritance. Transactions of the Royal Society of Edinburgh 52: 399-433.

Fitzpatrick, M.J. and M.B. Sokolowski. 2004. In search of food: exploring the evolutionary

link between cGMP-dependent protein kinase (PKG) and behaviour. Integrative and

Comparative Biology 44: 28-36.

Fitzpatrick, M.J., E. Feder, L. Rowe, and M.B. Sokolowski. 2007. Maintaining a behaviour

polymorphism by frequency-dependent selection on a single gene. Nature 447: 210-

212.

Flint, J. 2003. Analysis of quantitative trait loci that influence animal behaviour. Journal of

Neurobiology. 54: 46-77.

Fortini, M.E., M.P. Skupski, M.S. Boguski, and I.K. Hariharan. 2000. A survey of human

disease gene counterparts in the Drosophila genome. Journal of Cell Biology 150:

F23-F30.

Fujiwara, M., P. Sengupta, and S.L. Mclntire. 2002. Regulation of body size and behavioral

state of C. elegans by sensory perception and the EGL-4 cGMP-dependent protein

kinase. Neuron 36: 1091-1102. 61

Galton, F. 1865. Hereditary talent and character. Macmillan's Magazine. 12: 157-166.

Graf, S.A. and M.B. Sokolowski. 1989. The rover/sitter Drosophila foraging polymorphism

as a function of larval development, food patch quality and starvation. Journal of

Insect Behavior 2: 301-313.

Greenspan, R.J. 1997. A kinder, gentler genetic analysis of behavior: dissection gives way to

modulation. Current Opinion in Neurobiology 7: 805-811.

Greenspan, R.J. 2001. The flexible genome. Nature Reviews Genetics 2: 383-387.

Greenspan, R.J. 2004a. E pluribus unum, ex uno plura: quantitative and single-gene

perspectives on the study of behavior. Annual Review of Neuroscience 27: 79-105.

Greenspan, R.J. 2004b. The varieties of selectional experience in behavioural genetics.

Journal of Neurogenetics 17: 241-270.

Griffing, B. 1956. Concept of general and specific combining ability in relation to diallel

crossing systems. Australian Journal of Biological Sciences 9: 463-493.

Heisenberg, M. 1997. Genetic approaches to neuroethology. BioEssays 19: 1065-1073.

Hentges, K.E. and M.J. Justice. 2004. Checks and balancers: balancer chromosomes to

facilitate genome annotation. Trends in Genetics 20: 252-259.

Hirsch, J. and L. Erlenmeyer-Kimling. 1962. Studies in experimental behavior genetics: iv.

chromosome analyses for geotaxis. Journal of Comparative Physiological Psychology

55: 732-739.

Hotta, Y. and S. Benzer. 1970. Genetic dissection of the Drosophila nervous system by

means of mosaics. Proceedings of the National Academy of Sciences (USA) 67:

1156-1163. 62

Humphreys, J.M., B. Duyf, M.L. Joiner, J.P. Phillips and A J. Hilliker. 1996. Genetic

analysis of oxygen defense mechanisms in Drosophila melanogaster and

identification of a novel behavioural mutant with a Shaker phenotype. Genome 39:

749-757.

Ingram, K.K., P. Oefher, and D.M. Gordon. 2005. Task-specific expression of the foraging

gene in harvester ants. Molecular Ecology 14: 813-818.

Kaun, K.R., C.A. Riedl, M. Chakaborty-Chatterjee, A.T. Belay, S.J. Douglas, A.G. Gibbs

and M.B. Sokolowski. 2007a. Natural variation in food acquisition mediated via a

Drosophila cGMP-dependent protein kinase. Journal of Experimental Biology 210:

3547-3558.

Kaun, K.R., T. Hendel, B. Gerber and M.B. Sokolowski. 2007b. Natural variation in

Drosophila larval reward learning and memory due to a cGMP-dependent protein

kinase. Learning and Memory 14: 342-349.

Kendler, K.S. and R.J. Greenspan. 2006. The nature of genetic influences on behavior:

lessons from "simpler" organisms. The American Journal of Psychiatry 163: 1683-

1694.

Konopka, R.J. and S. Benzer. 1971. Clock mutants of Drosophila melanogaster. Proceedings

of the National Academy of Sciences (USA) 68: 2112-2116.

L'Etoile, N.D., CM. Coburn, J. Eastham, A. Kistler, G. Gallegos, and C.I. Bargmann. 2002.

The cyclic GMP-dependent protein kinase EGL-4 regulates olfactory adaptation in C.

elegans. Neuron 36: 1079-1089. 63

Lee, K.S., K.H. You, J.K. Choo, Y.M. Han and K. Yu. 2004. Drosophila short neuropeptide

F regulates food intake and body size. Journal of Biological Chemistry 279: 50781-

50789.

Lewis, E.B. and F. Bacher. 1968. Methods of feeding ethyl methane sulfonate (EMS) to

Drosophila males. Drosophila Information Service 43:193.

Lynch, M. and B. Walsh. 1998. Genetics and analysis of quantitative traits. Massachusetts:

Sinauer Associates Inc.

Mackay, T.F.C. 2001a. Quantitative trait loci in Drosophila. Nature Reviews Genetics 2: 11-

20.

Mackay, T.F.C. 2001b. The genetic architecture of quantitative traits. Annual Review of

Genetics 35: 303-339.

Mackay, T.F.C. 2004. The genetic architecture of quantitative traits: lessons from

Drosophila. Current Opinion in Genetics and Development 14: 253-257.

McGuire, T.R. 1992. A biometrical genetic approach to chromosome analysis in Drosophila:

detection of epistatic interactions in geotaxis. Behavior Genetics 22: 453-467.

Mery, F., A.T. Belay, A.K. So, M.B. Sokolowski and T.J. Kawecki. 2007. Natural

polymorphism affecting learning and memory in Drosophila. Proceedings of the

National Academy of Sciences (USA) 104: 13051-13055.

Ohnishi, O. 1977. Spontaneous and ethyl methanesulfonate-induced mutations controlling

viability in Drosophila melanogaster. I. Recessive lethal mutations. Genetics 87: 519-

527. Osborne, K.A., A. Robichon, E. Burgess, S. Butland, R.A. Shaw, A. Coulthard, H.S. Pereira,

R.J. Greenspan, and M.B. Sokolowski. 1997. Natural behavior polymorphism due to

a cGMP-dependent protein kinase of Drosophila. Science 277: 834-836.

Pasyukova, E.G., C. Vieira, and T.F.C. Mackay. 2000. Deficiency mapping of quantitative

trait loci affecting longevity in Drosophila melanogaster. Genetics 156: 1129-1146.

Pereira, H.S. and M.B. Sokolowski. 1993. Mutations in the larval foraging gene affect adult

locomotory behavior after feeding in Drosophila melanogaster. Proceedings of the

National Academy of Sciences (USA) 90: 5044-5046.

Pereira, H.S., D.E. MacDonald, A.J. Hilliker and M.B. Sokolowski. 1995. Chaser (Csr), a

new gene affecting larval foraging behavior in Drosophila melanogaster. Genetics

141:263-270.

Perry, S.V. 1979. The regulation of contractile activity in muscle. Biochemical Society

Transactions 7: 593-617.

Pflugfelder, G.O. 1998. Genetic lesions in Drosophila behavioural mutants. Behavioural

Brain Research 95: 3-15.

Phillips, P.C. 1998. The language of gene interaction. Genetics 149: 1167-1171.

Plomin, R., J.C. DeFries, and G.E. McClearn. 1990. Behavioral Genetics: A Primer. Ed. 2,

W.H. Freeman and Company, New York.

Plomin, R., J.C. DeFries, G.E. McClearn and P.McGuffin. 2001. Behavioral Genetics. Ed. 4,

Worth Publishers, New York.

Rankin, C.H. 2002. From gene to identified neuron to behaviour in Caenorhabditis elegans.

Nature Reviews Genetics 3: 622-630. 65

Rice, W.R. 1989. Analyzing tables of statistical tests. Evolution 43: 223-225.

Rice, S.H. 2000. The evolution of developmental interactions: epistasis, canalization, and

integration. In: Epistasis and the Evolutionary Process, J.B. Wolf, E.D. Brodie III and

M.J. Wade, eds. Oxford University Press. 2000. pp 82-98.

Rubin, G.M. and A.C. Spradling. 1982. Genetic transformation of Drosophila with

transposable element vectors. Science 218: 348-353.

Ryder, E. and S. Russell. 2003. Transposable elements as tools for genomics and genetics in

Drosophila. Briefings in Functional Genomics and Proteomics 2: 57-71.

Sambandan, D., A. Yamamoto, JJ. Fanara, T.F.C. Mackay, and R.R. Anholt. 2006. Dynamic

genetic interactions determine odor-guided behavior in Drosophila melanogaster.

Genetics 174: 1349-1363.

Sanjuan, R. and S.F. Elena. 2006. Epistasis correlates to genomic complexity. Proceedings of

the National Academy of Sciences (USA) 103: 14402-14405.

Schaffer, H.E. and R.A. Usanis. 1969. General least squares analysis of diallel experiments: a

computer program - DIALL. Genetics Department, North Carolina State University.

Scheiner, R., M.B. Sokolowski, and J.Erber. 2004. Activity of cGMP-dependent protein

kinase (PKG) affects sucrose responsiveness and habituation in Drosophila

melanogaster. Learning and Memory 11: 303-311.

Shaver, S.A., C.A.L. Riedl, T.L. Parkes, M.B. Sokolowski and A.J. Hilliker. 2000. Isolation

of larval behavioral mutants in Drosophila melanogaster. Journal of Neurogenetics

14: 193-205. 66

Snow, E.T., R.S. Foote, and S. Mitra. 1984. Base-pairing properties of 06-methylguanine in

template DNA during in vitro DNA replication. Journal of Biological Chemistry 259:

8095-8100.

Sokolowski, M.B. 1980. Foraging strategies of Drosophila melanogaster. a chromosomal

analysis. Behavior Genetics 10: 291-302.

Sokolowski, M.B., H.S. Pereira, and K. Hughes. 1997. Evolution of foraging behavior in

Drosophila by density-dependent selection. Proceedings of the National Academy of

Sciences (USA) 94: 7373-7377.

Sokolowski, M.B. 2001. Drosophila: genetics meets behaviour. Nature Reviews Genetics 2:

879-890.

Spradling, A.C., D. Stern, A. Beaton, E.J. Rhem, T. Laverty, N. Mozden, S. Misra, and G.M.

Rubin. 1999. The Berkeley Drosophila Genome Project gene disruption project:

Single P-element insertions mutating 25% of vital Drosophila genes. Genetics 153:

135-177.

St. Johnston, D. 2002. The art and design of genetic screens: Drosophila melanogaster.

Nature Reviews Genetics 3: 176-188.

Strauss, R. and M. Heisenberg. 1993. A higher control center of locomotor behavior in the

Drosophila brain. Journal of Neuroscience 13: 1852-1861.

Templeton, A.R. 2000. Epistasis and complex traits. In: Epistasis and the Evolutionary

Process, J.B. Wolf, E.D. Brodie III and M.J. Wade eds. Oxford Unversity Press.

2000. pp 41-57. van Swinderen, B. and R.J. Greenspan. 2005. Flexibility in a gene network affecting a simple

behavior in Drosophila melanogaster. Genetics 169: 2151-2163. 67

Vamam, C.J., R. Strauss, J.S. de Belle and M.B. Sokolowski. 1996. Larval behavior of

Drosophila central complex mutants: interactions between no bridge, foraging and

Chaser. Journal of Neurogenetics 11: 99-115.

Venken, K.J. and H.J. Bellen. 2005. Emerging technologies for gene manipulation in

Drosophila melanogaster. Nature Reviews Genetics 6: 167-178.

Wolf, J.B., E.D. Brodie III and M.J. Wade eds. Epistasis and the Evolutionary Process.

Oxford University Press, Oxford. 2000.

Zhai, R.G., P.R. Hiesinger, T.W. Koh, P. Verstreken, K.L. Schulze, Y. Cao, H. Jafar-Nejad,

K.K. Norga, H. Pan, V. Bayat, M.P. Greenbaum and H.J. Bellen. 2003. Mapping

Drosophila mutations with molecularly defined P element insertions. Proceedings of

the National Academy of Sciences (USA) 100: 10860-10865.