Investigating the Mechanism of Courtship Acceptance in Drosophila

INVESTIGATING THE MECHANISM OF COURTSHIP ACCEPTANCE IN DROSOPHILA

JOSEPH SCHINAMAN

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy

Department of Biology

CASE WESTERN RESERVE UNIVERSITY

August, 2015

CASE WESTERN RESERVE UNIVERSITY

SCHOOL OF GRADUATE STUDIES

We hereby approve the thesis/dissertation of

Joseph Schinaman

candidate for the degree of Doctor of Philosophy*.

Committee Chair Michael Bernard

Committee Member Rui Sousa-Neves

Committee Member Claudia Mieko Mizutani

Committee Member Peter Harte

Committee Member Mark Willis

Date of Defense June 29th, 2015

*We also certify that written approval has been obtained

for any proprietary material contained therein.

DEDICATION

To my grandfather Joe, who always insisted on providing his children with the sort of education he could never have, and to my parents, who have provided me with a better education than I could have ever hoped for.

TABLE OF CONTENTS

Abstract ...... 1

Chapter 1: Background and Significance ...... 3 1.1- The Genetic Basis of Behavior ...... 4 1.2- The Drosophila Courtship Display ...... 5 1.3- The Sensory Inputs of Drosophila Courtship ...... 7 1.3.1- The Role of Olfaction in Courtship Stimulation ...... 9 1.3.2- The Role of Audition in Courtship Stimulation ...... 20 1.4- Regions of the Central Brain Controlling Receptivity ...... 25 1.5- Genes Influencing Courtship and Receptivity ...... 27 1.6- Hypothesis of Integration of Courtship Signals ...... 34 1.7- Summary ...... 37

Chapter 2: A Novel Genetic Tool for Clonal Analysis of Fourth Chromosome Mutations ...... 46 2.1- Abstract ...... 47 2.2- Introduction ...... 49 2.3- Results ...... 50 2.3.1- Genotypes and Chromosomes ...... 50 2.3.2- Clone Induction and Marking ...... 51 2.3.3- Frequency of Clone Recovery ...... 53

2.4- Discussion ...... 54 2.5- Materials and Methods...... 57 2.5.1- Fly Culture Conditions and Genotypes Used to Generate Haplo-4 Clones ...... 57 2.5.2- Heat Shock Regimens ...... 58 2.5.3- Brain Dissection, Multiplex in situ, and Confocal Microscopy ...... 58 2.5.4- Fluorescence Signal Normalization...... 60

Chapter 3: The KRÜPPEL-Like Transcription Factor DATILÓGRAFO Is Required in Specific Cholinergic Neurons for Sexual Receptivity in Drosophila Females ...... 67 3.1- Abstract ...... 68 3.2- Introduction ...... 69 3.3- Materials and Methods...... 71 3.3.1- Mutants, Transgenes, Genotypes, and Stocks...... 71 3.3.2- Recording of Mating Behavior ...... 73 3.3.3- Quantification of Discrete Female Behaviors ...... 73 3.3.4- Analysis of Locomotor Behavior ...... 74 3.3.5- Antibodies and Immunostaining ...... 74 3.3.6- Automated Image Analysis and Cell Counting ...... 75 3.3.7- Clonal Analyses ...... 76 3.3.8- Olfactory Behavioral Assays ...... 76 3.3.9- Mushroom Body and Antennal Lobe Image Analysis ...... 77 3.3.10- Statistical Analysis ...... 77 3.4- Results ...... 78 3.4.1- Identification of dati on the Drosophila Fourth Chromosome ...... 78 3.4.2- dati Mutant Females Are Courted Normally But Fail to Accept Male Courtship ...... 79 3.4.3- dati is Required In Neurons for Normal Acceptance and Locomotion ...... 80 3.4.4- The Removal of dati in Cholinergic Neurons Impairs Normal Female Acceptance But Not Locomotion ...... 81 3.4.5- dati Mutants Exhibit Abnormal γ-Lobes of the Mushroom Bodies, But These Defects Do Not Cause Female Rejection ...... 83 3.4.6- dati Is Expressed in a Large Set of Neurons But in a Small Subset of the Cholinergic Neurons...... 83 3.4.7- Mapping Brain Regions Where dati Is Required to Generate Acceptance Reveals Discrete Brain Foci ...... 84 3.4.8- Rejection Foci Contain Few dati-Positive, Cholinergic Neurons ...... 85 3.4.9- dati Is Required to Generate a Subtype of Cholinergic Neurons ...... 86 3.4.10- Nuclear Bar Coding Reveals That DATI CHA Neurons Mediate Short- and Long-Range Connections ...... 87 3.5- Discussion ...... 89

3.5.1- dati Encodes a Conserved ZNF Transcription Factor Related to Rotund/Squeeze and ZNF384 Required for Female Decision Making and Locomotion ...... 89 3.5.2- Locomotor Defects Are Separable From the Inability to Make Decisions ...... 91 3.5.3- dati Adds an Additional Layer to the Identity of Cholinergic Neurons That Is Shared by Noncholinergic Neurons ...... 91 3.5.4- The Regions Where dati Is Required Agree with Previous Mapping and Suggest the Existence of a Core Circuit for Female Decision Making ...... 92 3.5.5- dati 's Requirement in Few Excitatory Neurons in Three Discrete Brain Foci Reveals a Simple, Yet Fundamental, Mechanism of Female Decision Making in Drosophila ...... 94

Chapter 4: Conclusions and Future Directions ...... 114 4.1- dati and the Neural Circuitry of Courtship Acceptance ...... 115 4.2- Revisiting the Summation Hypothesis ...... 117 4.3- Future Directions for Investigating the Neural Circuitry of Receptivity ...... 119 4.4- Further Analysis of Receptivity ...... 122 4.5- The Molecular Mechanism of the dati Gene in Cell Specification ...... 128

References ...... 136

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LIST OF FIGURES

Chapter 1 Figure 1.1- The steps of Drosophila courtship ...... 40 Figure 1.2- Flow of olfactory information through the Drosophila brain ...... 41 Figure 1.3- Atlas of the Drosophila brain ...... 42 Figure 1.4- Flow of auditory information through the Drosophila brain ...... 43 Figure 1.5- Location of neurons of the central brain influencing the acceptance of courtship ...... 44

Chapter 2 Figure 2.1- Schematic overview of the system ...... 61 Figure 2.2- FYT-generated clones in developing and adult tissues ...... 63 Figure 2.3- FYT-induced clones of pan-ciD on the wing ...... 64 Figure 2.4- FYT-induced clones in the adult brain and measurement of RNA levels by multiplex in situ hybridization ...... 65

Chapter 3 Figure 3.1- Molecular mapping of dati1 and conservation of dati across species ...... 96 Figure 3.2- Embryonic and larval expression of dati ...... 98 Figure 3.3- Quantification of discrete responses to male courtship displayed by dati mutant females versus wild-type females ...... 99 Figure 3.4- Results of pair mating and locomotor experiments using dati1 and UAS- dati-RNAi ...... 100 Figure 3.5- dati1 homozygote females exhibit mushroom body defects, whereas Cha-Gal4/ UAS-dati-RNAi females do not ...... 102 Figure 3.6- Cell counts of neurons expressing DATI and both DATI and CHA ... 103 Figure 3.7- The FYT system ...... 104 Figure 3.8- Mapping regions of the brain where dati is required for normal acceptance using the GAF/FYT system ...... 105 Figure 3.9- Detailed view of DATI/CHA double-positive cells in the three foci implicated in female acceptance as revealed by clonal analysis ...... 106 Figure 3.10- Homozygosity for dati1 causes loss of cholinergic projection neurons in the antennal lobe ...... 107 Figure 3.11- Homozygosity for dati1 causes abnormal distribution of cholinergic neurons and improper innervation of the lateral horn ...... 109 Figure 3.12- dati mutants exhibit defects in the trajectory of projection neurons ...... 110 Figure 3.13- Nuclear GFP and nuclear RFP have comparable rates of degradation ...... 111 Figure 3.14- dati is expressed in neurons that have small and large volumes .. 112

Chapter 4 Figure 4.1- Schematic representation of the putative receptivity circuit in Drosophila ...... 134 Figure 4.2- Proposed cellular mechanism by which dati establishes neural cell fates ...... 135

ACKNOWLEDGEMENTS

I would like to extend my heartfelt thanks to Dr. Rui Sousa-Neves and Dr. Claudia Mizutani, my thesis advisors, for their unwavering mentorship, support, and patience over the years. I would also like to thank Dr. Peter Harte and Dr. Mark Willis for serving on my committee and for professional advice over the years as well. I would like to thank Julia Brown, whose assistance has proved invaluable time and again. I would like to thank Rachel Giesey, who provided tremendous help during her time in the lab as an undergraduate. I would also like to thank my fellow lab mates Mirela Belu, Youngmin Chu, Emma Yang, and Sebastian Chadha for providing scientific and moral support over the different stages of my career in the lab. This work was funded by a GAANN fellowship by the Department of Education, as well as the National Institute of Health.

LIST OF ABBREVIATIONS

adPN, anterior–dorsal projection neuron; ALL, acute lymphoblastic leukemia; AMMC, Antennal Mechanosensory and Motor Center; ANOVA, analysis of variance; BI, Behavioral Index; C, degrees Celsius; CA, Corpora Allata; Cha, Choline acetyltransferase; CI, Courtship Index; CS, Canton-S; cVA, cis-vaccenyl acetate; dati, datilógrafo; dcr, dicer; ddc, dopa decarboxylase; elav, embryonic lethal abnormal vision; eLNs, excitatory Lateral Neurons; ePN, excitatory dorsal–lateral Projection Neurons; FLP, Flippase; FRT, Flippase Recognition Target; FYT, FRT-yellow-translocation; Gad, Glutamic acid decarboxylase 1; GFA, GFP-FRT-ActinGal4 GFP, green fluorescent protein; h, hour; IPI, Inter-pulse Interval; iPN, inhibitory Projection Neurons; JO, Johnston’s Organ; koj, kojak; LH, Lateral Horn; Lo, lobula; MARCM Mosaic Analysis by Repressible Cell Marker MB, mushroom body; Me, medulla; min, minute; MYA, million years ago; NBC, nuclear bar coding;

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LIST OF ABBREVIATIONS

NLS, nuclear localization sequence; OR, Odorant receptor; ORN, Odorant Receptor Neuron; pan-ciD, pangolin cubitus interruptus Dominant; PBT, Phosphate Buffered Tris; pilpr, posterior inferior lateral protocerebrum; ple, pale; plpr, posterior lateral protocerebrum; pslpr, posterior superior lateral protocerebrum; repo, reversed polarity; RFP, red fluorescent protein; rn, rotund; RT-PCR, reverse transcriptase polymerase chain reaction; s, second; SEM, standard error of the mean; SMP, Superior Medial Protocerebrum; SOG, Sub-oesophageal Ganglion; spin, spinster; sqz, squeeze; UAS, Upstream Activating Sequence; VLP, ventrolateral protocerebrum; wg, wingless; WT, wild-type

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Courtship Acceptance and the dati Gene

Abstract

JOSEPH SCHINAMAN

Courtship is a behavior common to many species in which members of one gender advertise to the other their species identity and overall fitness. In many species, the male courts the female, and the male’s courtship display provides a complex array of auditory, visual and olfactory information to the courted female, which must be decoded to generate the decision to accept or reject the potential mate. However, despite the centrality of courtship behavior to the evolution and maintenance of species, relatively little is known about the genetic and neural circuitry underlying female mate choice. To investigate this process in detail, we have analyzed the courtship acceptance behavior of Drosophila melanogaster, a species in which females are presented with multimodal sensory information during courtship. In this work, we show that Drosophila females mutant for the Krüppel-like transcription factor datilógrafo (dati) are incapable of accepting males, despite eliciting normal courtship from them. To facilitate further study of this gene’s role in patterning the brain for acceptance behavior, we used a novel system to perform clonal analyses of genes on the fourth chromosome, the genomic location of dati. The analysis of

Drosophila females bearing labelled patches of dati mutant tissue throughout the brain revealed three regions where this transcription factor is required for normal acceptance behavior: the antennal lobe of the anterior brain, and two regions flanking the lateral

horn in the posterior brain. These regions encompass areas of olfactory signal processing and sensory integration, respectively. In addition to the experiments above, we carried out an RNA interference screen to determine the neurotransmitter profile of dati neurons required for female acceptance behavior. This screen revealed that dati is required in cholinergic neurons. Finally, to determine precisely the position and number of individual neurons that mediate female acceptance behavior in the regions identified, we determined which dati neurons were cholinergic. Ultimately we found around 60 neuron spread across three regions. In whole, this work highlights indispensable and tractably-sized areas of the overall courtship acceptance circuit, and supports a stimuli- summation mechanism of courtship acceptance.

Chapter 1:

Background and Significance

1.1- The Genetic Basis of Behavior

Many behaviors exhibited by animals are instinctual, i.e., they are innate responses to stimuli that require no prior exposure or training, evidently inherited from parents. For behavior to be heritable, the blueprints of behavior must be encoded genetically, and for behavior to be set without instruction, behavioral paradigms must be patterned somehow during development, much in the same manner as a limb or organ. Genetic analyses of the fruit fly Drosophila melanogaster have shown that behavioral phenotypes indeed can be as readily associated to genetic alleles as anatomical, developmental or biochemical phenotypes. Pioneering work on the fruit fly showed that individual genes could exert influence on behaviors as complex as the female choice of mate (Bastock, 1956), the sensation of the passage of time (Konopka &

Benzer, 1971), the ability to form and recall memories (Dudai et al., 1976), and the orientation of sexual behavior in males (Hall, 1978).

Each of these landmark papers founded subfields of behavioral study that continue today, however, while female mate choice was amongst the first behaviors shown to have a genetic influence (Bastock, 1956), it has been the most neglected behavior of the four in the intervening years, with the dissection of male courtship dominating research into sexual behavior in flies (Ferveur, 2010; Villella & Hall, 2008).

While the study of male courtship has provided important insights into execution of complex behavioral steps and the role of learning and memory on complex behavior

(Kamyshev et al., 2004), the study of female courtship acceptance allows for unique insights into neural mechanisms such as decision-making based on the integration of

multiple sensory inputs (Chu et al., 2013). When females are courted by males, they are presented with an array of sensory stimuli of different modalities, all of which must be integrated in the central brain to reach the decision to accept or reject the male

(Bastock, 1956; Ferveur, 2010). To determine the neural circuitry that performs this operation would be a rare view into how neurons perform a calculation that executes a higher order brain function, something of interest not only to Drosophila geneticists but to the neuroscience community at large. This project set out to probe the genetic and neural determinants of female decision-making behavior, with an eye towards using this as a model for the neural basis of decision-making itself. The following sections of this chapter will thus highlight the current state of the literature on courtship and acceptance behavior in Drosophila to properly frame the contribution of this thesis to the field.

1.2- The Drosophila Courtship Display

As courtship is an interplay between two behaving animals, courtship acceptance behavior cannot be studied in isolation from courtship itself. The stimuli that generate acceptance behavior are generated by the courting males, with genetically encoded behavioral information flowing from one animal, to another with a genetically encoded system of interpreting this information. Therefore, the study of the integration of courtship signals in the female brain must begin with an understanding of the stimuli generated by males. This courtship display provided by males for the evaluation of females is a well-studied and highly stereotyped process (Figure 1.1, reviewed in (Chu et

al., 2013; Greenspan, 1995; Hall, 1994; Krstic et al., 2009)). To initiate courtship, the male begins by tracking or scanning a territory with sweeping movements to visually scan for suitable mates (Cook, 1979). Upon finding a potential mate, the male will then orient towards it, and begin following its movements closely. The male will tap the courted fly’s abdomen with its front tarsi, which bear an array of taste receptors

(Stocker, 1994). This tapping senses the pheromone profile of the courted fly, ensuring it is the right gender (Miyamoto & Amrein, 2008; Moon et al., 2009), the right species

(Billeter et al., 2009; Savarit et al., 1999), and that it has not recently mated (Kurtovic et al., 2007; Scott & Richmond, 1987; Yew et al., 2009). If the courted fly is a conspecific virgin female, the male will proceed with courtship and engage in a series of behaviors to provide information to the female. In this display, the male will vibrate his wing to generate a courtship song (Bennet-Clark & Ewing, 1967), arc back and forth in front of the female in a courtship dance, providing visual input (Ewing, 1983) and generate substrate borne vibrations (Fabre et al., 2012). The male also disperses pheromones

(Jallon, 1984). The courted female will respond to the display initially by fleeing, but if it is stimulated by the display, it will slow to halt as the male continues to perform (Spieth,

1974; Tompkins et al., 1982). The male will proceed from these behaviors to lick the female and attempt to mount. If the female accepts the courtship, it will open its vaginal plates and allow the male to mount and proceed with copulation (Spieth, 1974). If the female rejects the male’s display, the female will execute a behavioral repertoire that includes hindleg kicks, wing flicks, and rapid fleeing (Bastock & Manning, 1955;

Manning, 1967; Paillette et al., 1991). Timing is also a key factor to receptivity, for

instance, developmentally immature females normally reject males and are “switched- on” to a receptive state by the activity of juvenile hormone around two days post eclosion (Manning, 1967; Ringo et al., 1991). Furthermore, recently mated females are also temporarily unreceptive, a behavioral change mediated by the deposition of neuropeptides such as Sex Peptide by the male, which adds ovipositor extrusion to their repertoire of rejection behaviors (Manning, 1967; Wolfner, 1997). Therefore females have a window of receptivity starting a few days after eclosion, lasting until they mate

(Manning, 1967). For conspecific pairs with receptive females, the entire process from tracking to copulation takes on average less than 15 minutes, and rarely exceeds 30 minutes (Manning, 1967). However, males can court unreceptive females vigorously for well over an hour (Bastock & Manning, 1955). From these observations of the courtship ritual in Drosophila, it is clear that the female is subjected to a host of sensory inputs on which to base its decision to accept or reject (Youngmin Chu et al., 2013; Ferveur, 2010).

An early priority of researchers interested in the courtship process was to parse out which of these modalities provided critical information to the female, and which modalities were dispensable.

1.3- The Sensory Inputs of Drosophila Courtship

Mutational analysis and studies using surgical manipulations have revealed what aspects of the male’s courtship display are being assessed by the female. An early study investigated the relative importance of audition, olfaction, and vision, by removal of the courting males’ wings, the courted females’ antennae, and the light from the mating

chambers, respectively (Bastock, 1956). It was found that either surgical manipulation cut the rate of courtship acceptance in half, while the removal of light had no effect on otherwise intact mating pairs (Bastock, 1956). Strikingly, they reported that females could mate when all three sensory modalities were modified, although at a rate about a tenth of the controls (Bastock, 1956). These results showed a clear role for the courtship song and pheromones in receptivity, with possible minor roles for other modalities. A more recent study using genetic manipulations minimized the role for sensory inputs other than olfaction and audition in courtship acceptance, reporting that loss of both modalities abolishes acceptance completely (Rybak et al., 2002). This study also found feminizing the courting male’s pheromone profile caused only a modest reduction in female acceptance compared to ablation of wings, suggesting that olfaction’s role in courtship stimulation is the lesser of the two relevant modalities (Rybak et al., 2002).

However, there is evidence that other cues, such as male eye color, play a role in female choice when discerning between otherwise normal males, as opposed to the no-choice assays of the other experiments (Ewing, 1983). Furthermore, an experiment which paired females mutant for the olfactory defective gene, which have a reduced sense of smell, with wingless males in light and dark conditions revealed the females to be much more receptive in light conditions (Gailey et al., 1986). Together these results suggest that vision may also become more important when olfactory and auditory information is of poor quality (Gailey et al., 1986). Finally, a recent study has shown that a subset of central brain neurons required for receptivity in females fire in response to both courtship song and fly pheromones in intact preparations, suggesting again that both

modalities influence the acceptance of courtship (Zhou et al., 2014). Other signals, such as mechanosensation, appear to reduce the time to acceptance, without influencing the actual overall rate of acceptance (Fabre et al., 2012), but are otherwise poorly understood. In sum, the integration of olfactory and auditory cues is clearly of primary importance, and the study of both modalities has led to important insights into how courtship information is processed in the brain. Furthermore, in Chapter 3 of this work, I will present evidence that the dati gene, the focus of this thesis, is required in three foci of the brain, one of which lies within the antennal lobe, the second order processing center of odors in the brain. The other two lie within an area of known olfactory sensory convergence, which may receive auditory inputs as well. To frame the significance of this thesis, I will review the prior literature on both of these modalities.

1.3.1 The Role of Olfaction in Courtship Stimulation

As alluded to above, the exact importance of olfaction is somewhat disputed, with more recent experiments in feminizing male pheromones showing a much smaller role for olfaction than early ablation experiments suggested (Bastock, 1956; Rybak et al.,

2002). However, both methods of probing the role of olfaction come with inherent limitations. The ablation experiments partially removed the third antennal segment, which in addition to housing the sensory units that detect smell, also function to convey the transduction of sound (Bastock, 1956; Eberl et al., 1997; Gopfert & Robert, 2001). As such, these early experiments may have well overestimated the role of olfaction. On the other hand, the feminization experiments relied on the transient expression of

transformer during development, a gene that activates female-specific cell fates (Rybak et al., 2002). This method was shown to reduce the amount of male-specific cuticular hydrocarbons being produced (Rybak et al., 2002). However, the study made the assumption that the hydrocarbons being tracked were the ones responsible for the female response to courtship, an unproven link (Rybak et al., 2002). Therefore, this study would underestimate the role of olfaction if cuticular hydrocarbons were not the major olfactory stimulus of courtship. This method could ostensibly feminize structures other than those involved in pheromone production as well. A more direct method to assay the role of olfaction is to genetically disrupt the female sense of smell, which would leave the antennae physically intact while making no assumptions about what odorants are involved. Such a study was made possible by the discovery of the mutation smellblind, which was originally observed to abolish the male response to the scent of females (Tompkins et al., 1980). A later study of the response of females mutant for smellblind found that in 30 minute pair matings, 63% of mutants unable to smell could be enticed to mate, compared to 92% of controls (Tompkins et al., 1982). This genetic study, unbiased for the odorants tested, show olfaction is not as minor as the Rybak et al (2002) publication would suggest. However, in order to better understand the flow of pheromone-mediated courtship information into the brain, greater understanding of the odorants involved as well as analysis of more targeted genetic mutations would be required.

One such breakthrough came with the development of methods to record the neural firings from individual odor sensing structures, called sensilla (Clyne et al., 1997).

Each sensillum consists of a porous, hair-like, cuticular housing, an aqueous fluid that contains proteins which process and shuttle odorants to and from receptors, and the cilia of 1-4 Odorant Receptor Neurons (ORNs) (Couto et al., 2005) (Figure 1.2A). The ability to make electrophysiological recordings from individual neurons of these structures allowed for the precise association of specific odorant molecules with each sensilla. As a proof of concept, a specific type of sensilla, the “T1” trichoid sensilla was investigated in depth, due to it being one of the most simple sensilla in structure, with only one neuron per sensillum (Clyne et al., 1997) (Figure 1.2A). The T1 sensillum was found to have remarkable specificity, reacting to only the molecule cis-vaccenyl acetate

(cVA), a previously described male pheromone synthesized and stored in the ejaculatory bulb (Brieger & Butterworth, 1970; Butterworth, 1969). This molecule was later shown to be deposited by males to females during mating, presumably to inhibit courtship from subsequent males (Jallon, 1984; Jallon et al., 1981). The responsiveness of T1 sensilla to a male-specific pheromone made them an attractive entry point for studying the flow of courtship information into the brain. however, these early studies relied on morphological identification of T1 sensilla. In order to trace the path genetically, a sensillum-specific marker gene would be required. Such a breakthrough came with the discovery of the odorant receptor (OR) gene family. This family of genes was one of the first major discoveries made through bioinformatics analysis of draft genome information (Clyne et al., 1999). By combing sequence data for genes predicted to encode seven-pass transmembrane domains, Clyne et al (1999) discovered sequences encoding putative transmembrane proteins with no previously ascribed function in the

genomic sequence available at the time (about ~10% of the total draft genome). By designing primers against the sequence of these genes, and attempting to amplify gene products with these primers in cDNA made from antennae via RT-PCR, they were able to amplify two of the predicted sequences. In situ probes made from these genes confirmed they were expressed only in the neurons of sensilla of the third antennal segment and maxillary palp, and refinement of the bioinformatics search algorithm based on the similarities between these two genes (they were found to be 75% identical) uncovered another 14 putative odorant receptors from the early genomic sequences. These genes would later gain functional proof that they encoded proteins capable of changing a membrane potential in response to odors, first by expressing them on patch clamped Xenopus oocytes and exposing the oocytes to fruit odors

(Wetzel et al., 2001). They were soon shown to indeed be Drosophila odorant receptors by showing that ectopic expression of these genes in ORNs could confer novel responses to odors in the modified neurons (Störtkuhl & Kettler, 2001). Upon the completion of the Drosophila Genome Project, a total of 62 odorant receptor genes were isolated

(Robertson, Warr, & Carlson, 2003). Using this genomic data, a host of tools were developed to further study the anatomy and electrophysiology of chemosensory structures. One study set out to map the olfactory system of Drosophila by driving the expression of the marker gene green fluorescent protein (GFP) in the pattern of each odorant receptor gene, showing the location of the cell bodies of each neuron bearing the receptors, as well as their projections (Couto et al., 2005). By doing this, two maps were created: one that assigned odorant receptors to each sensilla, and another that

showed where the neurons of every sensilla projected into the brain. This analysis showed that neurons of T1 sensilla expressed the odorant receptor gene Or67d, allowing for genetic dissection of the function of a sex-specific pheromone. A loss of function experiment found a genetic basis for the observation that cVA on females inhibited male courtship made decades earlier (Jallon, 1984; Jallon et al., 1981; Kurtovic et al., 2007). Or67d knockout males courted females doused with cVA twice as often as wild-type males, and expression of Or67d back in T1 neurons was sufficient to rescue this effect (Kurtovic et al., 2007). The authors also found that Or67d knockout males were three times as likely to court each other compared to controls, suggesting cVA mediated gender recognition as well. However, the authors also investigated the role of

Or67d in the female response to courtship, discovering that only 35% of Or67d knockout females accepted the courtship of wild-type males within thirty minutes, compared to

65% of control females. This was a surprising result, as many previous studies presumed long chain cuticular hydrocarbons to be the stimulatory pheromone produced by males

(Gailey et al., 1986; Jallon, 1984; Rybak et al., 2002). This finding provided new evidence for a large role of olfaction in courtship, by showing such a strong rejection phenotype in females deficient for the ability to sense cVA (Kurtovic et al., 2007). Furthermore, by showing that cVA was the relevant pheromone for receptivity, this result also provided an explanation why previous work on olfaction that focused on manipulating long chain hydrocarbons failed to identify a significant role for olfaction in courtship. The singling out of Or67d in receptivity behavior (Kurtovic et al., 2007), in conjunction with the neuronal map of ORs (Couto et al., 2005), allowed for an unprecedented tracing of

courtship information into the brain: a specific male chemical could be linked to a specific set of sensilla on the female, which in turn yielded a defined innervation pattern in the central brain. Other genetic analyses revealed functions for other odorant receptors in sexually dimorphic behaviors as well.

The correlation of odors to their cognate receptors was facilitated by the discovery of a mutant fly with a specific odorant receptor neuron devoid of any receptors, a so called “empty neuron” (Hallem et al., 2004). Knowing that this neuron had no inherent response to smell, the authors could ectopically express each individual food-sensitive odorant receptor one at a time in this neuron, expose it to specific odorant molecules, and record the neuron’s electrophysiological response. With this system, the authors created a response profile of each odorant receptor to an array of food odors (Hallem et al., 2004). This same technique was later used to investigate the response to odorants extracted from flies (van Naters & Carlson, 2007). This later study reconfirmed that Or67d only responded to extracts from males and recently mated females, and discovered 3 additional odorant receptors tuned specifically to the smell of flies. Two of these, Or88a and Or47b, responded to both male and female odors, while

Or65a reacted specifically to extracts of virgin females. The two odorant receptors responding to general fly odors have recently been assayed for roles in female courtship receptivity (Sakurai et al., 2013). By expressing an inwardly rectifying potassium channel in the expression patterns of Or88a and Or47b, Sakurai et al. (2013) were able to hyperpolarize the neurons bearing these receptors and render them unable to fire, providing a functional knockout. While no effect on receptivity was seen in the Or88a

knockouts, Or47b knockout females took significantly longer to accept courtship than their controls. Thus, females respond to two different types of odorants during courtship: one specific to males, and one that is general to the species. From this one can hypothesize that Or47b mediates species specific courtship information, and that

Or67d mediates information about the quality of the male and his display. However, whether or not Or47b positive neurons fire when exposed to the extracts of other species of flies has never been tested, and its exact ligand is unknown. Furthermore, it is not known if the courtship stimulating effect of cVA is dose dependent, which would suggest a mechanism by which some males would provide more stimulation to females than others, leaving defined functional roles for these genes in courtship a conjecture.

However, the innervations of neurons bearing both types of receptor have been traced into the brain (Couto et al., 2005; Marin et al., 2002), yielding some preliminary insights into the neural circuitry underlying courtship decision-making behavior, both in the existing literature, and in the work that will be presented in Chapter Three of this work

(Schinaman et al., 2014).

All odorant sensory neurons in Drosophila terminate into discrete synaptic regions called glomeruli, an arrangement common not only to all arthropods, but to vertebrates as well (Figure 1.3B) (Hildebrand & Shepherd, 1997; Laissue & Vosshall,

2008; Strausfeld & Hildebrand, 1999). Earlier studies into olfaction in rodents suggested that each odorant sensory neuron expressed only one odorant receptor, and all neurons expressing the same receptor converged to the same glomerulus, leading to a well- defined spatial representation of odors in the brain, the “one receptor-one neuron” and

“one neuron-one glomerulus” rules (Mombaerts et al., 1996; Serizawa et al., 2004). The analysis of the expression patterns of each odorant receptor gene showed that the arrangement of the Drosophila antennal lobe, where glomeruli are arranged, was broadly similar with a few key differences (Couto et al., 2005). Most notably, all odorant sensory neurons expressed more than one odorant receptor; in particular, each ORN expresses Or83b, found to be an obligate cofactor in the detection of smell by the other receptors (Couto et al., 2005; Larsson et al., 2004). Furthermore, certain ORNs could express up to four “standard” odorant receptors in addition to Or83b, a departure from the “one receptor-one neuron-one glomerulus” setup observed in other species (Couto et al., 2005; Serizawa et al., 2004). However, it was found that all neurons of the same class, that is, expressing the same set of ORs, do indeed project to just a singular glomerulus, and as such each of the 62 odorant receptors is associated with just one of the ~51 glomeruli (Couto et al., 2005; Laissue & Vosshall, 2008). Furthermore, the fact that each glomerulus forms an anatomically distinct zone of synaptic connection makes them uniquely amenable to isolating the synaptic partners of each upstream sensory neuron via genetic techniques such as the generation of labelled clones (Marin et al.,

2002). In fact, even before first order neurons of chemosensation were mapped to glomeruli, clonal analysis had already revealed the pathways of second order neurons that connect each glomerulus to higher area orders of the brain (Marin et al., 2002). This work confirmed earlier studies in flies and moths which suggested that neurons innervating the antennal lobe project to two higher brain regions of the mushroom body

(MB) and the lateral horn (LH) (Figure 1.2B, See Figure 1.3 for atlas of the Drosophila

brain (Homberg et al., 1988; Stocker et al., 1990)). However, the tracing of neural projections with single cell resolution in Drosophila yielded several new insights (Marin et al., 2002). First, they found that neurons contacting most glomeruli projected to both the MB and the LH, with a synaptic projection pattern invariant in the lateral horn, but highly variable in the mushroom body. This was an interesting result as the mushroom body has been implicated in odor-associative memory (Debelle & Heisenberg, 1994), and the variability seen in the synaptic connections in this region is thought to reflect these experience-dependent changes to odor response (Marin et al., 2002). Another interesting result was that two glomeruli were found to have more complex innervation than others: the two glomerular targets of Or67d and Or47b, the known mediators of courtship sensation. The glomerular target of Or47b, assigned the designation VA1lm, was shown to be innervated by two separate classes of neuron that contact the MB and

LH, each innervating different regions of the LH, as opposed to single class innervating most other glomeruli. It is also innervated by a third class that bypasses the MB altogether, directly relaying information from the glomerulus to the LH (Marin et al.,

2002). The target of Or67d, designated DA1, was also found to have a unique innervation, with one canonical class of neuron innervating both the MB and LH, and two classes which bypassed the MB, contacting only the LH (Marin et al., 2002). A caveat to this study is that they were only able to obtain clones for 30 of the ~51 glomeruli, suggesting they were not able to systematically observe all the possible projection neurons, and other glomeruli might well have proven to have similar complexity as the DA1 and VA1lm (Marin et al., 2002). However a more comprehensive

follow-up study confirmed these glomeruli to be unique, finding that projections from these neurons into the LH are spatially segregated from those from glomeruli mediating food odors (Jefferis et al., 2007). Furthermore, projections from them are sexually dimorphic in structure, and while the canonical MB + LH projection neurons are cholinergic and excitatory (Jefferis et al., 2007), the projection neurons that bypass the

MB are GABAergic and inhibitory (Jefferis et al., 2007). It appears then that excitatory courtship information can be modulated by experience via the mushroom body before reaching its target in the LH, but inhibitory information cannot, although this has not been functionally proven. However, some functional insight into the reception of pheromones at the neural level has begun to emerge. A study of the electrophysiological response of Or67d first order neurons and DA1 second order neurons found no difference in the response to cVA between males and females, suggesting the sexually dimorphic response to cVA is mediated solely by how they connect to third order neurons (Datta et al., 2008). However, mapping third order olfactory neurons and beyond has presented several new challenges. While first order neurons proved highly amenable to mapping due to the ability to express GFP in the patterns of OR genes (Couto et al., 2005), and second order neurons were equally mappable due to their connection to glomeruli (Marin et al., 2002), there are no known genes with such an orderly expression or areas of synaptic connection with easily defined boundaries for the analysis of neurons innervating the LH (Tanaka et al., 2004).

One approach has been to screen for the expression of enhancer trap lines that sparsely label neurons in the brain, and to look for overlaps in synaptic regions in the LH and MB.

One such study screened 4000 enhancer trap lines, and found five which revealed various second order projection neurons, and 6 which labeled third order neurons contacting the LH (Tanaka et al., 2004). This study of neuroanatomy showed that second order neurons contacting the DA1 glomerulus innervated a discrete region of the lateral horn, a region innervated by third order neurons of the lateral horn which send projections to the antennal mechanosensory and motor center (AMMC) and ventrolateral protocerebrum (VLP), regions both implicated in the reception of sound, as well as the superior medial protocerebrum (SMP), a high-level region bearing neurons shown to respond to both cVA and to courtship song (Zhou et al., 2014). While these LH neurons are ideal candidates for integrating multiple sensory modalities upstream of the SMP, there has been no experiment to date linking these LH neurons to sensory integration or receptivity behavior. Thus, prior to this work, the tracing of receptivity-stimulating olfactory information through the brain ended at candidate third order neurons of the LH. In Chapter 2 of this work, we will introduce a novel system of mapping tissues in the brain (Sousa-Neves & Schinaman, 2012). Using this technique, we will then show in Chapter 3 the first evidence that these third order lateral horn neurons are indeed necessary for female receptivity, and furthermore, identify the gene that confers to these neurons the ability to properly respond to courtship (Schinaman et al.,

2014).

1.3.2- The role of audition in courtship stimulation

While the exact role of olfaction in courtship has been subject to debate, it is undisputed that auditory cues exert a significant effect on the success or failure of courtship (Rybak et al., 2002; Tompkins et al., 1982). The courtship song produced by the male’s wing vibrations is capable of inducing rapid behavioral responses in flies of both sexes (Bennet-Clark & Ewing, 1968; Tauber & Eberl, 2003). In contrast to olfactory cues, in which male pheromones inhibit male courtship and increase aggression (Wang

& Anderson, 2010), exposure to courtship song stimulates otherwise inactive males to begin courtship, even if they have not yet identified a female (if one male is courting, it appears to indicate to other males that a female must be in the area) (von Schilcher,

1976). Females exposed to the song begin to cease their default fleeing behavior in response to males and slow down, which in turn exposes them to more intense courtship by males (Eberl et al., 1997; Tauber & Eberl, 2003; Tompkins et al., 1982).

These songs follow a simple pattern of two different bouts of vibration: the sine song and the pulse song (Figure 1.4A) (von Schilcher, 1976). Sine song is a high frequency, humming or droning sound that, while varying in frequency between different species, does not seem to encode stimulatory or species-specific information, as playback of the sine song alone has very little effect on female receptivity (Kyriacou & Hall, 1984; Rybak et al., 2002). Pulse song, however, appears to be the crucial aspect of song production that induces behavioral changes in males and females (Bennet & Ewing, 1969; Kyriacou

& Hall, 1984; Rybak et al., 2002). Pulse song consists of short bouts of intense vibration, spaced out by a specific inter-pulse interval (IPI) of about 34 ms in D. melanogaster, in

trains of three or more bouts (Bennet-Clark & Ewing, 1968)(Figure 1.4A). IPI was shown in early experiments to be the first key component of the pulse song, as playback of songs with the correct interval between bouts was able to partially rescue receptivity of females when paired with wingless males, but songs with incorrect IPIs could not

(Bennet & Ewing, 1969). IPI is a species-specific parameter, with D. melanogaster’s sister species Drosophila simulans spacing each pulse out by about 45 ms (Cowling & Burnet,

1981), and with hybrids producing pulse songs with IPIs roughly intermediate of those of their parent species, about 38 ms (Wheeler, Fields, & Hall, 1988).

The length of time between small changes in the IPI produced by males, known as IPI rhythm or KH cycle, has also been described as a spectral component of courtship song unique to each Drosophila species (Kyriacou & Hall, 1982). It was originally reported that these rhythms were a crucial aspect of courtship information provided by the male, as playback of artificial songs with conspecific IPI and IPI rhythm could rescue mating deficits of wingless males, but playback of songs with either parameter alone was insufficient (Kyriacou & Hall, 1982). This discovery led to a number of papers investigating the underlying genetics of IPI rhythm, suggesting that IPI rhythm was linked to the X chromosome (Kyriacou & Hall, 1986), and later showing that IPI rhythm generation was influenced by the circadian rhythm gene, period (Kyriacou & Hall, 1980;

Wheeler et al., 1989). However, several contemporaneous studies could not find evidence for IPI rhythms (Crossley, 1988; Ewing, 1988), and a recent analysis purports that IPI rhythms are merely an artifact of the sampling methods used in the original papers (Stern, 2014). As of this writing, no papers have been published in to either

rebut or support this most recent analysis, and as such, the existence and importance of

IPI rhythm as a mating signal interpreted by females, remains controversial. While it is clear that more research must be done in order to pin down the exact spectral parameters being scrutinized by females, it is undisputed that courtship song has an enormous amount of influence on a female’s decision to mate, and that these signals can be used to probe how auditory signals are received by sensory organs and projected deeper into the brain, much like how cVA was utilized in probing the olfactory system.

The reception of courtship song in flies begins in the same structure by which they receive olfactory information, the third antennal segment (Figure 1.4B), in a form of non-tympanal ear that can only detect sounds close to their source, and as such seems tuned specifically for communication with nearby flies (Tauber & Eberl, 2003;

Yack, 2004). Briefly, such near-field sound waves are initially received by thin filamentous protrusions from the third antennal segment called aristae, which in turn causes the entire third antennal segment to oscillate relative to the stationary second segment, or pedicel (Gopfert & Robert, 2001). Housed within the pedicel is the

Johnston’s Organ (JO) a collection of around 200 individual structures called scolopidia, which are capable of converting vibration into action potentials (1.4B) (Caldwell & Eberl,

2002). Each scolopidium consists of several stretch receptive, mechanosensory neurons alongside support cells which attach them to the hook, a protrusion of the third antennal segment into the second (Eberl & Boekhoff-Falk, 2007; Nadrowski et al., 2011).

As the hook oscillates with vibrations picked up by the arista, the mechanosensory neurons deform sympathetically, firing as they are stretched and ceasing as they

compress, with two opposing populations firing at each apex of the swing of the hook, robustly encoding frequencies of near-field sound (Yorozu et al., 2009). In addition to simply responding to vibration, at certain frequencies, the neurons of the JO are also capable of activating muscles which can in turn vibrate the third antennal segment at the frequency it is being stimulated, effectively providing a simple mechanism of sound amplification (Göpfert & Robert, 2003). This method of feedback based mechanical amplification has been shown to occur in a species-specific manner at different frequencies, and are tuned such that each species amplifies its conspecific song

(Riabinina et al., 2011). Thus, a stimulatory feedback loop, and the discrimination between stimulatory courtship information from that of heterospecifics, begins to occur at the level of the mechanism of the sensor itself. These self-amplifying mechanosensory neurons of the JO project axons into the central brain, to a region called the Antennal Mechanosensory Motor Center (AMMC) (Homberg et al., 1989), a region analogous to the antennal lobe for olfaction. Whereas the antennal lobe consists of many, morphologically distinct regions of synaptic contact, JO neurons have been mapped only to five, broadly spatially separate regions within the Johnston’s Organ and

AMMC, designated A, B, C, D and E (Kamikouchi et al., 2006). Live imaging studies employing forms of GFP that only fluoresce under the high calcium conditions of neuronal firing have begun to ascribe functions to these regions. Region A is responsive to high frequency vibration (up to 400 Hz), and B is responsive to lower frequency (~20

Hz) vibration, and both respond to “playback” of the pulse song on to the arista via electrostatic force (Kamikouchi et al., 2009). Regions C, D and E are responsive to static

deflection, firing tonically as the arista is bent and held back. Consistent with these findings, inactivation of JO neurons which innervate region B was shown to abolish the male behavior of singing when exposed to the song of other males. The behavioral effect of suppressing region B JO neurons on female receptivity however, was not investigated, nor was the role of region A in either sex. A recent work has shown via electrophysiology that region A neurons respond to the playback of courtship song in females, and found that playback of conspecific and heterospecific pulse songs elicit different responses in 2nd order neurons of the AMMC (Tootoonian et al., 2012).

However, no functional test establishing necessity or sufficiency of region A JO neurons was performed, leaving much to be learned about exactly how auditory courtship information is transmitted and processed in the female brain. Some generalizations can be made from photoactivation studies looking at higher order brain circuitry of the

AMMC, which reveal a network of projection neurons which connect both the left and right AMMC regions to one another, and another which sends projections into the inferior VLP (Lai et al., 2012)( Figure 1.4B). Third order neurons have also been identified which connect these iVLP synaptic regions to areas higher in the VLP, adjacent to the lateral horn. This suggests olfactory and auditory information may be integrated somewhere within the VLP/LH, although a role for these regions in receptivity to the auditory and chemical cues has not previously been shown. In Chapter 3 of this work, I show evidence that two such regions of the brain are indeed required for courtship acceptance: one located directly above the lateral horn, and another below the lateral

border of the VLP. In addition I show that neurons in these regions require the gene dati for proper development and function in acceptance behavior (Schinaman et al., 2014).

1.4- Regions of the Central Brain Controlling Receptivity

In conjunction with efforts to map the flow of sensory information of courtship into the brain from its source, there have also been attempts to isolate higher order brain centers involved in reproductive behavior directly. One such early work utilized gynandromorphs to find what regions of the fly’s brain need be female in order for the fly’s behavior to be female, i.e., to be receptive to courtship (Tompkins & Hall, 1983). In their experimental design, the authors exploited the fact that in Drosophila, sex is determined by the ratio of sex chromosomes to autosomes, normally males having one sex chromosome, and females having two (Bridges, 1921). Thus, during development, dividing female cells that spontaneously lose a sex chromosome merely become male, and continue to give rise to male tissues. By designing a cross in which the parental males carried the mutation paternal loss (which induces the loss of the paternal X chromosome during cell divisions at a rate of 0.6-0.8%), Tompkins and Hall (1983) could generate gynanders at a rate feasible for replicable study (Tompkins & Hall, 1983).

Furthermore, knowing that the paternal X would be lost, the authors designed the paternal X chromosome such that it carried markers to distinguish male from female tissue, both externally by cuticle color, and internally by presence of absence of an acid phosphatase, differentially staining male and female tissue during slide preparation.

Then, by generating a large number of externally female gynanders, testing them

behaviorally for receptivity, and analyzing them individually for patches of phosphatase- negative male tissue, Tompkins and Hall (1983) were able to correlate masculinized brain regions to ‘male-like’ rejection of courtship (Tompkins & Hall, 1983). By this method the authors came to find that the focus of female receptivity was the central brain, as opposed to ventral ganglia or reproductive structures. In fact, they could localize this focus to just a subset of the brain, an area in an around the antennal lobes

(Tompkins & Hall, 1983). However, while groundbreaking, this study by design could not give greater resolution than a broad patch of tissue in the brain, and could say nothing of the types of cells involved. Also, the use of gynanders raises the question of whether the behavioral change is truly due to the loss of female-specific behavior, as opposed to the gain of function of male behavior, as males exhibit rejection behaviors such as wing flicks towards courting males much like females. This hurdle, of making neural tissue null for the behavior being studied, rather than changing it to a separate behavioral paradigm, would only come after the isolation of specific mutants affecting the brain’s ability to interpret courtship information, as highlighted in the next section. In Chapter 2 of this work, we will present a novel genetic technique to create clonal tissue in the brain. As we will show, this technique is capable of cellular resolution, as opposed to the patch level resolution used in Tompkin’s and Hall’s earlier work. Furthermore, we are able to circumvent the issues of changing the gender identity within these cells, keeping the cells developmentally female and influencing behavior by changing the expression of only a single gene. In Chapter 3, we then use this technique to reveal three regions of the brain which require the gene dati for proper female acceptance, one of which

confirms the original work of Tompkins and Hall, along with two novel regions in the posterior of the brain. Chapter 3 will also contain a characterization of the phenotypes caused by the dati mutation, both cellular and behavioral. To frame the significance of the discovery of this gene to the literature, a brief review of the previously described genes influencing receptivity will follow.

1.5- Genes Influencing Courtship and Receptivity

In addition to the mutational analyses performed for genes strictly tied to various sensory modalities, a number of genes have been isolated by their behavioral phenotype first, and later probed for their expression and effect on the nervous system.

The first such gene discovered for reproductive behavior is fruitless, an x-ray induced mutation that causes inappropriate courtship between males (Gill, 1963). Later, an entire series of alleles of fruitless were generated, in which each step of the male courtship process is interrupted (Villella et al., 1997; Villella & Hall, 2008). fruitless was found to be expressed in an entire circuit of male behavior, from sensory neurons of the antennae responsive to pheromones, the motoneurons that generate courtship song, and the interneurons that connect them all, an indispensable map to tracing courtship information through the male brain (Yu et al, 2010). However, this gene would provide only limited insights into female behavior. While some transcripts of fruitless are common to both males and females and are required for proper embryonic development and viability (Song et al., 2002), the transcripts of fruitless associated with sexual behavior are only translated into protein in males (Usui-Aoki et al., 2000). Despite

lacking sex-specific protein translation, shutting off synaptic transmission in fruitless- expressing cells in females impairs their courtship acceptance (Kvitsiani & Dickson,

2006), suggesting that either the transcript itself has a function independent of the translated protein, that the proteins common to both males and females encode a default female program that can be overridden by the male specific transcripts, or even that another gene upstream of fruitless controls sexual behavior in both genders, but uses differential translation of fruitless to execute male vs. female programs. As most of the interest has focused on the male specific transcripts to the exclusion of those common to both sexes, the function of fruitless in females remains an open question.

However, another gene as central to sexual differentiation was discovered to also have a role in neural patterning: doublesex (dsx). In contrast to fruitless, doublesex has a role in sexual patterning in both males and females, mediated by expression of gender specific isoforms (Baker & Wolfner, 1988). Doublesex appears to have a broader role in sexual differentiation than fruitless as well, being expressed in oenocytes (pheromone producing cells), genitalia, and other gender specific tissues, as well as sparse populations of neurons in both sexes (Rideout et al., 2010). Initial work on doublesex- positive neurons suggested they played a role in modulating courtship behavior in both sexes (Rideout et al., 2010). This study found that shutting down doublesex neurons in females using tetanus toxin slowed their response to courtship, but ultimately did not impair their ability to accept . This suggested that doublesex neurons influenced courtship acceptance in females but were not indispensable (Rideout et al., 2010).

However, a later paper using a different set of genetic tools showed a much more

central role for doublesex neurons in courtship acceptance (Zhou et al., 2014). In this paper, the authors knocked down or activated neurons in the pattern of the doublesex gene, as well as in the patterns of expression of individual enhancer fragments of doublesex. They found that blocking synaptic transmission in neurons labelled by one such enhancer fragment led to a near total loss of acceptance, in pair matings measured out to thirty minutes. Furthermore, ectopic stimulation of these neural subsets was able to prime females to mate with less courtship than controls. As doublesex is expressed in only around 60 neurons in the central brain, this enhancer fragment approach was able to provide enough specificity to successfully identify these subsets of doublesex neurons as necessary and sufficient for influencing receptivity (Zhou et al., 2014). As alluded to before, this approach was also able to reveal that a high order subset of doublesex neurons known as pC1 was responsive to both courtship song and pheromones, and thus ostensibly involved in the integration of multimodal cues during courtship. While this is an important result in the establishment of a circuit underlying multisensory integration, it is evident from its sparse expression that doublesex does not form a complete circuit in the same manner as fruitless does in males (Rideout et al., 2010; Yu et al., 2010). The neurons which connect pC1 neurons to those conveying sensory information are not known, nor are those downstream of pC1 or other doublesex neurons (Zhou et al., 2014), so much of the circuitry remains to be revealed.

Compared to doublesex, other genes which delay female acceptance have garnered significantly less attention. One gene, dissatisfaction, causes a failure of females to lay eggs properly and also affects female courtship acceptance (Finley et al.,

1997). However, while dissatisfaction females significantly delay their time to mate, their overall receptivity does not appear to be affected. Antibody stainings revealed dissatisfaction to be expressed in neurons of the uterus, far from any potential sensory integration point, but also in and around the anterior dorsal brain, in broad agreement with the findings of Hall 1983 (Finley et al., 1998). However, fine resolution mapping of dissatisfaction-positive neurons is not available. Another mutation, retained, exhibits a similar phenotype of delayed acceptance (Ditch et al., 2005). As with doublesex and dissatisfaction, retained mutant females delay acceptance but ultimately accept male courtship at wild–type levels (Ditch et al., 2005). Retained was found to be expressed in the mushroom bodies, an area of synaptic connection between the antennal lobe and the lateral horn, as well as the sub-oesophageal ganglion (SOG), an area where gustatory information converges. Unfortunately this gene was not analyzed beyond the initial publication, so its exact role in these regions is unknown.

Several genes have been isolated with the opposite effect, causing females to be hyperreceptive to courtship. One gene, painless, is an ion channel previously implicated in nociception (Tracey et al., 2003). Knockout females of painless not only mate more quickly with males once they are past the normal “switch-on” time for receptivity, they also switch on much earlier, suggesting that painless neurons mediate a state of unreceptiveness responsive to both juvenile hormone and male seminal peptides (Sakai et al., 2009). Interestingly, this gene was found to be expressed in odorant receptor neurons, as well as neurons of the Johnston’s Organ (Sakai et al., 2009). This means that females actively express ion channels used to conduct pain signals in the major organs

of courtship stimulation, initially raising the question of whether courtship stimulation is painful prior to the switching on of receptivity, and as such elicits such violent responses as kicking. However a follow up paper showed that a small cluster of painless-positive neurons expressing insulin-like peptide of the pars intercerebralis were responsible for the switch-on of receptivity (Takaomi Sakai et al., 2014). This is an exciting discovery as another gene causing hyperacceptance, SIFamide, encodes a peptide neurotransmitter expressed in only four neurons, also within the pars intercerebralis (Terhzaz et al.,

2007). Knockout males for SIFamide court males and females indiscriminately, and knockout females mate with males in 1/3 of the time of controls. Despite being expressed in only four neurons, these neurons send projections to every part of the central brain and ventral nerve cord (Terhzaz et al., 2007), limiting how much it can tell us about what brain regions are necessary for acceptance. Unfortunately, no test was done as to whether or not females become receptive sooner than their wild-type counterparts, which would suggest a role for SIFamide in global shutdown of sexual behavior. Also, whether these are the same neurons remains to be proven.

In contrast to these genes which appear to relax the “switch-on” component of receptivity, another controls the “switch-off” of receptivity upon mating. This gene, sex peptide receptor (SPR), mediates the response to signaling peptides transferred from the male to the female during mating (Wolfner, 1997; Yapici et al., 2008). Exposure to these peptides was shown to be the cause of the reduced receptivity and increases in egg laying associated with the mating (Chen et al., 1988). Knockdown of SPR via RNA interference abolishes these postmating responses to the presence of sperm,

phenocopying the response of females mated to males devoid of sex peptide (Yapici et al., 2008). Interestingly, SPR is found not only in neurons of the reproductive tract, but of the ventral nerve cord and subeosophageal ganglion as well, suggesting it mediates the response to courtship on multiple neural levels, including acting on the central brain itself (Haesemeyer et al., 2009; Yapici et al., 2008).

Finally, a few other genes have strong negative receptivity phenotypes, fully blocking rather than delaying acceptance. One is Abdominal-B, a transcription factor that, when knocked down in neurons via RNAi, reduces the rate of acceptance to about

25%, compared to about 80% for control females (Bussell et al., 2014). However, as the name suggests, Abdominal B is expressed only in the terminal segment of the ventral nerve cord, as well as the reproductive tract, indicating that Abdominal B neurons are probably the motoneurons that execute decision-making commands from higher brain centers. This is evidenced further by the fact that artificially stimulating Abdominal-B neurons to fire caused spontaneous stopping and opening of the vaginal plates (Bussell et al., 2014), the downstream behaviors of courtship receptivity. Another gene definitively lowering receptivity, chaste, appears to effect courtship acceptance by perpetuating the unreceptive virgin state indefinitely (Suzuki et al., 1997). Chaste mutant females were found to ultimately accept courting males in only 11% of 1 hr pair matings, compared to 70% of control females, a much stronger phenotype than those affecting individual sensory modalities discussed earlier (Bastock, 1956; Kurtovic et al.,

2007; Rybak et al., 2002), suggesting it exerts an effect in a region more central to sensory integration or decision-making. Chaste was found to be an allele of muscleblind

(Juni & Yamamoto, 2009), a gene involved in a host of processes, including photoreceptor differentiation (Begemann et al., 1997), synaptic targeting (Artero et al.,

1998), muscle development (Machuca-Tzili et al., 2006), and targeted cell death

(Vicente-Crespo et al., 2008). Despite this apparent pleiotropy, no gross behavioral or locomotor defects were reported for the chaste allele. This lack of pleiotropic effects, alongside its strong phenotype, makes chaste a seemingly ideal candidate to probe how courtship acceptance can be interrupted. However, to date, further analyses of this allele’s effect on the central brain have not been carried out. One final gene merits attention, spinster. Spinster mutant females also show a very strong rejection phenotype, with around 6% accepting males (Suzuki et al., 1997). Early work on spinster localized its expression to the central brain, further suggesting the rejection was not a result of a deficit of sensory stimulation, but of central processing of stimuli (Suzuki et al., 1997). Spinster has also been found to have a number of pleiotropic effects, with roles in starvation response (Rong et al., 2011), egg development (Nakano et al., 2001) and cell migration (Yuva-Aydemir et al., 2011), obscuring its exact role in receptivity.

However, the discoverers of spinster combined mutation analysis with mosaic analysis, seen in the early paper on gynanders (Tompkins & Hall, 1983). Through the analysis of labelled mosaic clones of spinster, they showed the gene to be necessary for courtship acceptance in small subsets of neurons in the central brain (Sakurai et al., 2013), namely the antennal lobe and the sub-oseophageal ganglion (Fig 1.5B). This method allowed a gene with a behavioral phenotype, but broad expression in the brain, to be used to pinpoint specific neural circuits, an incredibly powerful tool to analyze behaviors at

circuit level. In Chapter 2 of this work, we will present a new and independently developed method of generating labelled clones designed for the analysis of genes on the Drosophila 4th chromosome, a genomic region previously unamenable to such technique. In Chapter 3, this technique will be used to perform a mosaic analysis of a newly identified gene required for female acceptance, datilografo (dati). This 4th chromosome gene shows a strong receptivity phenotype, with females completely rejecting males. We show that like spinster, dati is required in the antennal lobe, in addition to two other regions in the posterior brain not identified in the spinster screen.

1.6- Hypothesis of Integration of Courtship Signals

With the experiments performed thus far to probe into and disrupt female courtship, what hypotheses have been put forth as to how these reproductive decisions are being made? The major hypothesis put forth to explain the female reaction to male courtship is the “summation hypothesis,” the idea that the summation of stimulatory inputs by the male past an excitation threshold causes a receptive female to accept

(Ewing, 1964). As this brief review will show, this hypothesis garnered early support, but fell out of favor for several decades in light of conflicting evidence. However, recent advances, including the work of this thesis, have renewed interest in the hypothesis.

This hypothesis has its original basis in the finding that surgical reduction of the courting male’s wings increased the amount of courtship required to stimulate a female to mate, with the increase in courtship proportional to the severity of the wing reduction (Ewing,

1964). The interpretation of this result was that males with smaller wings provided less

stimulation per unit time, and thus more bouts of display were required to reach the same excitation threshold (Ewing, 1964; Manning, 1967). This experiment was repeated with the wings of males removed entirely and even without wings, males could still use other means of stimulation to entice females to mate, although wingless males took far longer to do so (Manning, 1967). These results led Manning to first refer to a “courtship summation mechanism” within females which controlled acceptance of courtship

(Manning, 1967). This attractive idea would gain support from early work on the artificial playback of courtship song (Bennet-Clark & Ewing, 1967). It was found that artificial playback of the sound and air pressure generated by courtship could rescue the delay in acceptance exhibited by wingless males; indeed, wingless males courting these artificially stimulated females mated even more frequently than intact males with unstimulated females (Bennet-Clark & Ewing, 1967). Work on hearing defective flies also supported Manning’s hypothesis, as it was shown that females with defective arista required more stimulation and took longer to mate than normal females (Burnet et al.,

1971).

The first setback to the summation hypothesis would come with the publication of a study of the ‘constancy’ of female courtship requirements (Cook, 1973). In this study, the author made the assumption that if courtship is summed and the threshold of this excitation is an intrinsic set value in a given female fly’s brain, a female fly should require a constant set amount of courtship to stimulate her to mate over several repeat pairings with males (Cook, 1973). To test this idea, the amount of time a male courted a particular female was recorded, and at the onset of courtship, the pairs were

anesthetized and separated prior to insemination to prevent the transfer of seminal factors that shut down female receptivity (Cook, 1973). The female would then be re- mated the next day with a new male, and so on, for four days, and the amount of courtship the female required each day was calculated (Robert M. Cook, 1973). Cook found that females did require significantly similar amounts of various parameters of courtship, in two of three replicates of this experiment. However, this experiment was called in to question several years later, with the initial finding that the Cook paper had made several statistical errors, casting doubt about the validity of the research

(Robertson, 1982). In the intervening years another troublesome paper emerged, which sought to determine the specific functions of sine vs. pulse song (von Schilcher, 1976).

This paper found that when females were played an artificial version of the sine component of courtship song before exposure to a male, they would be “pre- stimulated” and copulate more quickly than females exposed to either pulse song or white noise (von Schilcher, 1976). This result was not consistent with earlier results which suggested pulse song to be the stimulatory component of courtship song, and conflicts with later results which would also show pulse song, but not sine song, to influence courtship (Kyriacou & Hall, 1984; Rybak et al., 2002). In any case, sine song was erroneously thought to be the summed stimuli of courtship when Robertson attempted to replicate Cook’s successive mating experiment (Cook, 1973; Robertson,

1982). In light of this, Robertson repeated the experiment but subdivided the time males spent courting females into time spent in sine song vs. pulse song. Since no correlation was found between the amount of sine song performed and the time to

acceptance, it was concluded that the theory of “Female Courtship Summation” was unsupported by sufficient evidence (Robertson, 1982). However, it is worth noting that the amount of pulse song needed to stimulate a female was significantly similar in two of his four replicates, the only statistically significant results in his repeat experiment, consistent with our current view of pulse song as stimulatory (Kyriacou & Hall, 1984;

Robertson, 1982; Rybak et al., 2002). Nonetheless, after Robertson’s revisiting of Cook’s experiment, the summation hypothesis appears to have fallen out of favor (Gailey et al.,

1986; Kyriacou & Hall, 1984).

However, the recent, renewed interest and work on female behavior, including the work of this thesis, has led to a resurgence in support for the hypothesis. Work on doublesex which revealed a neural population that responded to both song and pheromones, and responded most strongly in the presence of both stimuli, led the authors to reference the original work and hypotheses of Ewing (Zhou et al., 2014).

Furthermore, the work presented in Chapter 3 of this thesis shows evidence that multiple populations of stimulatory neurons form an area of sensory convergence and are necessary for females to accept males (Schinaman et al., 2014), highlighting neuronal circuitry consistent with what the summation hypothesis would predict.

1.7- Summary

In many species, the choice to accept or reject a courting male by a female is critical both to fitness of the female (Chapman et al., 1995), and to the viability of its offspring (Sturtevant, 1920). Despite this, relatively little is known about how these

decisions are made, especially on the neural level. One of the best models we have to ask such questions is the fruit fly, whose females are subjected to a multisensory courtship ritual, are free to accept or reject mates and are amenable to a wide range of genetic techniques and analyses.

In this dissertation, I will introduce a novel courtship receptivity mutant gene, called datilógrafo (dati) identified in the lab. dati is located on the Drosophila fourth chromosome and females mutant for this gene exhibit strong rejection behaviors. For clarity, the aims for my thesis work on this gene, and what I have done to accomplish them, are outlined as follows:

Aim 1- Employ a new method to create labelled clones of fourth chromosome genes, such as dati

In Chapter 2, I will present the FYT system, a novel technique developed in the lab to create clones of cells mutant for genes on the fourth chromosome, a task which could not be accomplished using previously existing technology.

Aim 2- Characterize the behavioral and cellular phenotypes of the dati mutation

In Chapter 3, I will present the results of behavioral analysis of dati mutants, finding that they are courted normally by males, and that their lack of mating is due to rejection of male courtship. I present evidence that this phenotype is due to loss of dati in neurons, and in cholinergic neurons specifically. I conclude that dati does not specify developing neurons to become cholinergic, and show evidence it does not define a specific

neuronal morphology. I show that loss of dati is associated with abnormal growth and loss of cells in the brain.

Aim 3- Use mosaic clones of dati to discover brain regions required for female acceptance

In Chapter 3, I will also present the results of a gene-specific, cellular resolution mosaic analysis of receptivity in the brain, using the technique described in Chapter 2, and the gene characterized in Chapter 3. This mosaic analysis will reveal three brain foci where wild-type dati expression is needed for proper receptivity. One focus lies in the anterior brain, around the antennal lobes, in a region corroborated by gynander mosaic analysis and mosaic analysis of the gene spinster (Sakurai et al., 2013; Tompkins & Hall, 1983).

The other two foci lie in the posterior brain, flanking the lateral horn, an area of olfactory sensory convergence hypothesized to integrate other senses as well. This is the first evidence that this region of sensory convergence is involved in courtship decision-making, and coupled with finding that these neurons are cholinergic, lends support to the summation hypothesis that acceptance is a summed convergence of stimulatory inputs.

Figure 1.1- The Steps of Drosophila Courtship

The steps of the display performed by male flies upon discovering a potential mate. The male begins by orienting himself to the female, aligning himself at an angle to her posterior (center). He then taps the female with his front legs, and proceeds to follow and chase her as she flees (top). The male will then extend his wing 90o relative to his body and vibrate it to generate a courtship song (left). The female, if receptive to the song, will begin to slow her movement, which will allow the male to sing more closely to her, and sweep back and forth in front of her. If then female slows completely to a halt, the male will lick her abdomen, and while continuing his song and sweeping movements (bottom). Finally, the male will mount the female in an attempt to copulate (right). If the female is receptive, she will allow the male to proceed. If the female is not, she will kick the male with her hind legs, flick her wings and flee (not shown).

Used with permission from Chu 2013.

Figure 1.2- Flow of Olfactory Information through the Drosophila Brain

(A) Schematic representation of olfactory sensilla. The three types of trichoid sensilla are depicted, T1, T2, and T3, named for the number of neurons innervating each sensillum. Below each neuron is the identity of each odorant receptor expressed in each neuron. Note each canonical odorant receptor neuron expresses Or83b, a necessary cofactor for the reception of smell, and at least one other receptor. (B) Schematic representation of information flow from sensillae to the central brain. The three types of trichoid sensilla, T1, T2, and T3, (red, blue, and yellow, respectively) and their relative position and abundance on the third antennal segment of the adult fly. All are tuned specifically to fly odors, with T1 sensilla being shown to mediate the female response to pheromones in courtship. The left side of the schematic shows the axonal projection of a first order, T1 neuron into the glomeruli of the antennal lobe, which specifically targets the sexually dimorphic glomerulus DA1 (red projection). The right side of the brain shows this same neuron, as well as a second order projection neuron of the antennal lobe (PN, green), as well as their site of synaptic contact in the DA1 glomerulus (yellow). The projection neuron receives inputs from the T1 neuron at DA1, and sends this signal to higher brain centers at the mushroom body calyx (Ca) and the lateral horn (LH).

Adapted from Couto 2005 and Van der Naters 2007.

Figure 1.3- Atlas of the Drosophila Brain

3D projection of the anterior (A) and posterior (B) Drosophila central brain, as revealed by nc82 staining, with major brain regions labelled. (A) Anterior brain. Optic lobes (OL), Superior Lateral Protocerebrum (SLP), Superior Medial Protocerebrum (SMP), Pars intercerebralis (PI), Optic Tubercle (OT), Ventro-lateral Protocerebrum (VLP), Antennal Lobe (AL), Antennal Motor and Mechanosensory Complex (AMMC), Sub-oesophageal Ganglion (SOG), alpha-, beta-, and gamma-lobes of the mushroom body (α, β, γ).

(B) Posterior brain. ), Superior Lateral Protocerebrum (SLP), Superior Medial Protocerebrum (SMP), Lateral Horn (LH), Calyx of Mushroom Bodies (Ca), Ventro-lateral Protocerebrum (VLP), Protocerebral Bridge (PB), Posterior Slope (PS), Sub-oesophageal Ganglion (SOG), Lamina (La), Medulla (Me), Lobula Plate (LP), Lobula (Lo).

Adapted from Milyaev 2012.

Figure 1.4- Flow of Auditory Information through the Drosophila Brain

(A) The structure of the Drosophila courtship song. The courtship song of Drosophila consists of two patterns, the humming sine song, and the pulse song, which consists of short, intense bursts of sound separated by a period of rest, called the interpulse interval. The IPI is unique to each species and is a major conveyor of species specific auditory information.

(B) The structure and neuroanatomy of the Drosophila auditory system. Near-field sound causes the vibration of the featherlike arista, which in turn causes sympathetic twisting of the third antennal segment (a3). This movement is conveyed from the third antennal segment into the stationary second antennal segment (a2), via a protrusion called the hook (h). The second antennal segment houses the Johnston’s Organ, a ring of stretch receptive neurons attached to the hook (green circles). These first order sensory neurons project out through the first antennal segment (a1) and form synapses into discrete regions of the central brain called the antennal motor and mechanosensory center (AMMC, yellow field). Second order neurons from the Ventro-Lateral Protocerebrum (red) contact these neurons and send projections higher into the VLP (purple fields). This information is carried further up to the most anterior portion of the VLP by third order neurons, whose synaptic partners are unknown (blue, blue fields).

Adapted from Murthy 2010 and Kamikouchi 2013.

Figure 1.5- Location of Neurons of the Central Brain Influencing the Acceptance of Courtship

(A) Location of doublesex-positive neurons of the central brain. Inactivation of doublesex neurons leads to a delayed receptivity phenotype. Doublesex is expressed in four bilateral clusters in the female brain, one cluster in the anterior brain (light blue circles) and three in the posterior brain (dark blue circles). Adapted from Sakurai 2013 and Goodwin 2010.

(B) Location of spinster-positive neurons required for proper receptivity. Mosaic analyses revealed 2 bilateral clusters of neurons which require expression of the gene spinster for females to have wild-type levels of acceptance (green circles), a set above the antennal lobes which project into the glomeruli and into the mushroom body calyx as well as the lateral horn, and a set is located and project locally within the Sub- oesophageal Ganglion. Both sets are located on the anterior side of the brain.

Adapted from Rideout 2010 and Sakurai 2013.

Chapter 2:

A novel genetic tool for clonal analysis of fourth chromosome mutations

In this chapter, we describe the technique developed in the laboratory to generate GFP-labelled clones of any allele on the Drosophila fourth chromosome. Here we show this technique is amenable to making clones in the eye, the developing wing disc and adult wing, the cuticle, and the brain. In addition, we show that labelled dati clones disrupt the expression of dati mRNA, which will be used to map brain regions in Chapter 3.

This material was published previously in the journal Fly: Sousa-Neves, R and Schinaman, J (2012)

2.1- Abstract

The fourth chromosome of Drosophila remains one of the most intractable regions of the fly genome to genetic analysis. The main difficulty posed to the genetic analyses of mutations on this chromosome arises from the fact that it does not undergo meiotic recombination, which makes recombination mapping impossible, and also prevents clonal analysis of mutations, a technique which relies on recombination to introduce the prerequisite recessive markers and FLP-recombinase recognition targets

(FRT). Here we introduce a method that overcomes these limitations and allows for the generation of single Minute haplo-4 clones of any fourth chromosome mutant gene in tissues of developing and adult flies.

2.2- Introduction

The success of Drosophila as a model organism relies on the ability to manipulate its genome. These manipulations include reverse and forward genetics approaches to study the functions of individual genes. Forward genetics approaches are feasible because mutations that cause a phenotype of interest can be readily mapped and the responsible gene identified, and somatic clones of loss-of-function alleles can be induced in a spatially and temporally controlled manner to allow analysis of their effects in any tissue and cell type. However, not all regions of the Drosophila genome are equally amenable to these types of approaches. A particularly troublesome region is the fourth chromosome, which has been resistant to forward genetic technologies for almost a century, primarily due to the lack of meiotic crossover that prevents meiotic mapping, but also due to the poor availability of deletions with defined molecular limits.

The barrier to routine mapping of genes on the fourth chromosome has been partly overcome by the generation and characterization of deletions with molecularly mapped breakpoints (Podemski et al., 2004; Ryder et al., 2004; Sousa-Neves et al., 2005).

However, a general method for systematically analyzing the loss-of-function phenotypes of fourth chromosome genes in somatic mosaics has remained elusive for a number of reasons. Lack of recombination prevents the introduction of necessary markers onto fourth chromosomes carrying FLP-recombinase recognition target sites (FRT). The older

way of inducing mitotic recombination, by ionizing radiation, results in haploidy or aneuploidy of the fourth chromosome at a very low frequency (Albornoz & Dominguez,

1994). Other strategies employed to generate somatic clones of mutants on the fourth chromosome rely on the use of mutations that cause chromosomal loss and allow the generation of clones of haplo-4 cells. Although haplo-4 cells and tissues are viable and develop normally, the frequency of these events is low, on the order of 1–2% (Sousa-

Neves, unpublished observation) (Gelbart, 1974). Another difficulty posed by chromosomal loss strategies is the inability to control the time of clone induction and the size of somatic clones.

So far, the most efficient technology currently available to generate somatic clones of fourth chromosome mutations relies on cloning and transferring wild-type copies of genes from this chromosome to other regions of the genome, where they can then be lost by standard FLP/FRT-based mitotic recombination methods to form a clone of cells in which a constitutionally homozygous fourth chromosome mutation has been uncovered (Schweizer et al., 2003). The high efficiency of this method stems from the use of the yeast FLP-FRT system (Golic & Lindquist, 1989). However, this strategy requires generation of the appropriate transgenic material for each individual gene of interest, which is time consuming and can be challenging for large and complex genes.

Here we report a new tool that allows the efficient generation of somatic mosaics of mutations in virtually any fourth chromosome gene. Our method enables the generation of somatic clones using the FLP-FRT system. Clones can be visualized with

green fluorescent protein, by utilizing components of the previously reported mosaic analysis by repressible cell marker (MARCM) system (Lee & Luo, 2001). We believe that this method should greatly simplify the functional analyses of fourth chromosome mutations.

2.3 Results

2.3.1- Genotypes and chromosomes

The genetic system to generate somatic mosaics of fourth chromosome mutants involves several genetic components (outlined visually in Fig. 2.1A). On the X chromosome there is a heat-inducible FLP-recombinase transgene (FLP) on a yellow white background (Golic & Lindquist, 1989). One of the second chromosomes bears a

FLP-recombinase recognition target site (FRT42D) located close to the centromere of chromosome 2R, a yellow+ transgene, a ubiquitous source of Gal80, and terminally, a reciprocal translocation that links all genes of the fourth chromosome to the right arm of the second chromosome (2R) (Cryderman et al., 1999; T. Lee & Luo, 1999; Xu &

Rubin, 1993). This chromosome is referred to as FRT Yellow Translocation (FYT). The other second chromosome bears a UAS-GFP transgene on the left arm, and FRT42D and a ubiquitous source of Gal4 on the right (Brand & Perrimon, 1993; Ito et al., 1997). This chromosome is referred to as GFP-FRT-ActinGal4 (GFA). The fourth chromosomes are modified as well. One is the complementary half of the FYT reciprocal translocation. The other fourth chromosome bears the mutation of interest.

2.3.2- Clone induction and marking

Heterozygous FYT/GFA animals do not express GFP, as Gal80 represses Gal4.

However, induction of FLP-recombinase in dividing cells produces randomly distributed clones of cells in which the chromosome arm carrying y+, Gal80 and the linked fourth chromosome gene complement has been lost, and thus, are also hemizygous for the structurally normal fourth chromosome containing the mutation of interest (Figs. 2.1B and 2.2)). In any living tissue, the descendants of these cells can be directly visualized by their GFP expression and in the sclerotized adult cuticle are marked by y- (Fig. 2.1C).

Haplo-4 tissues and even entire haplo-4 individuals develop into normal adults, except for their dominant Minute phenotype due to the haploinsufficiency of the RpS3 ribosomal protein gene, which slows the rate of cell growth and proliferation, causing slowed development, late emergence of adult flies and thinning of the bristles (Bridges,

1925; van Beest et al, 1998).

To test the efficacy of this method in uncovering recessive mutations on the fourth chromosome, we induced clones in larvae heterozygous for the recessive mutation sparklingpol (spapol), a recessive viable mutation that causes eye roughening. As expected, the somatic clones of this mutation in the adult eye exhibited disorganized ommatidia and eye roughening (compare the wild-type eye of Fig. 2.2A with the eye of the same animal with a spapol clone in Fig. 2.2B), while the heterozygous tissue appears wild-type.

Wild-type haplo-4 clones labeled with GFP were also obtained in imaginal discs

(Fig. 2.2C) and in adult wings using the marker kojak (koj) (Fig. 2.2D, see Materials and

Methods for the genotype used).

Due to the growth retardation (Minute) phenotype of haplo-4 cells, haplo-4 clones compete with neighboring faster growing euploid cells, resulting in smaller clones. To minimize the growth competition that favors the wild-type tissue, we made a variant of FYT that contains a mutation in a Minute gene on the right arm of the second chromosome [M(2)531]. Under these conditions, the growth of all cells in the entire body is slowed due to the heterozygosity for M(2)531. However, when FYT– clones are generated they gain two wild-type copies of M(2)531 and lose one copy of RpS3, and thus, have a growth advantage relative to their euploid neighbors, enabling them to become substantially larger (Fig. 2.2E).

We also generated pangolin-cubitus interruptus Dominant (pan-ciD) clones marked with kojak in wings (Fig. 2.3). Pan acts downstream of Wingless (wg), which is normally required along the wing margin. pan-ciD is an inversion between pan and ci in which the promoter of pan directs the expression of ci in both the anterior and posterior compartments of imaginal discs. The visible phenotype of heterozygotes ciD /+ is the interruption of the posterior vein 4, but no defects in the anterior compartment. pan-ciD is also mutant for pan and embryonic lethal. Here, we show a clone pan-ciD in the anterior compartment. Like previously reported (Schweizer et al., 2003), we note that

the loss of pan does not affect the pattern of the wing blade, but removes the sensilla along the margin that requires wg signaling.

Haplo-4 tissues can be obtained in larval and adult tissues including the brain

(Fig. 2.4A-H). In this case, we generated clones of the semi-lethal mutant dati1 that impairs locomotion and female behavior, and compared the mRNA levels within a clone, the neighboring diploid wild-type tissue and adjacent neuropile. Direct fluorescence intensity levels measurements show the reduction of dati mRNA in these clones (Fig.

2.4G and H).

2.3.3- Frequency of Clone Recovery

To estimate the frequency of clone recovery, we generated clones in which both parents were balanced for the second chromosome and one of them (i.e., the carrier of

GFA) was heterozygous for ciD spa or dati. In this setting, 1/3 of the larval progeny is heterozygous for FYT and GFA, and carries either ciD spa or dati. We next screened larvae for GFP and found that 13% exhibited clearly distinguishable clones (n = 138). By these counts, we note that nearly half of the expected number of clones could be recovered. However, when we analyzed the non-ciD adults capable of generating clones

(i.e., FYT/GFA), without pre-selecting for GFP, we observed that 21/24 (87%) had clones in the brain. This data suggests that ciD spa are more difficult to recover than dati clones and that the frequency of clone generation is equal or greater than 87% in individuals that carry FYT and GFA.

In summary, the fourth chromosome contains several important genes predicted to be involved in nervous system development and behavior. The FYT technique reported here will enable researchers to test these predictions and systematically investigate any role these genes play in neurodevelopment, physiology and behavior.

2.4- Discussion

The strategy of generating somatic clones has been crucial to the study of the biological functions of individual genes in Drosophila, but a generally applicable method of doing so for any fourth chromosome mutation has not been available. Application of the most advanced and efficient methods for producing somatic clones of fourth chromosome mutations requires prior knowledge of what gene is affected and laborious introduction of wild-type transgenes onto one of the other autosomes. While the number of genes on the fourth chromosomes are few and the challenges to studying them have been great, many fourth chromosome genes are of vital importance to several fields of study. In the field of development, the examples are numerous. Pan has been identified as a member of the Wg/Wnt signaling pathway (Brunner et al., 1997). ci is a well-known downstream effector in the Hedgehog signaling cascade (AzaBlanc,

RamirezWeber, Laget, Schwartz, & Kornberg, 1997; Methot & Basler, 2001; Ohlmeyer &

Kalderon, 1998). In visual system development specifically, the fourth chromosome hosts spa, ey and toy, the first being a homolog of Pax2, and the latter two homologs of

Pax6 (Czerny et al., 1999; Fu & Noll, 1997; Quiring et al., 1994). Also well represented on the fourth chromosome are genes related to neuronal patterning and function. The

semaphorins plexA and plexB have roles in axon guidance in the developing brain (Hu et al, 2001; Winberg et al., 1998). The fourth chromosome also contains both Ephrin and its associated receptor tyrosine kinase, which have roles in patterning the mushroom bodies and the visual ganglia (Boyle et al., 2006; Dearborn et al., 2002). Unc-13 encodes a synaptic vesicle fusion protein essential for neurotransmission in all neurons

(Aravamudan et al., 1999). DmGluRA encodes a metabotropic receptor for the excitatory neurotransmitter glutamate (Parmentier et al., 1996).

As such, the genes of the fourth chromosome are indispensable to our understanding of development and neural functioning of Drosophila. However, prior to the development of this system, the methods available to clonally study these genes were time-intensive, inefficient or both. The generation of haplo-4 clones using mitotic loss inducer is reported to occur at a frequency of only 0.013 (Gelbart, 1974). Clones of fourth chromosome genes have also been performed by translocating the gene of interest to the second chromosome, but this is relatively labor intensive and must be repeated for every gene of interest (Schweizer et al., 2003). This system, however, readily incorporates any allele of any gene generated on the fourth chromosome. The advent of RNAi technology has led to much greater access to knock-downs of many genes, but can be prone to disruption of off-target genes, insertion effects, incomplete knockouts, and is incapable of investigating an allele of interest. Our method, on the other hand, generates the most extreme knockout of an allele short of deletion: the haploid condition of a recessive allele.

The generation of clones is quite simple and only two stocks are required: (1) the clone inducer FYT stock (y w FLP; SM/FRT42D y+ Gal80 T(4;2)X-4; T(2;4)X-4/spa) and (2) the mutation receiver GFA ciD (y w FLP; SM/ UAS-GFP FRT42D Actin > Gal4; ciD spa/Df(4)BH). The mutations of interest are received by the GFA stock and the male offspring ciD mated to FYT. Clones are analyzed in heterozygotes FYT/GFA.

There are several considerations worthy of note for those interested in using this system to generate haplo-4 clones. The first consideration is that the loss of a fourth chromosome leads to the loss of one copy of the RpS3 ribosomal protein, a Minute gene, and as such clones will be predicted to grow more slowly than surrounding tissues. As alluded to in the results section, this effect can be mitigated by a variant of

FYT in which the right arm of the second chromosome contains a mutation in M(2)531.

In this case overall development is slowed, and clone tissues should grow faster than surrounding tissues. In either case, a deviation from the normal rate of growth should be recognized and accounted for. The FLP-recombinase-induced mitotic recombination event in the FYT/GFA heterozygotes, which is the crux of the system, will, upon segregation, yield one daughter cell that will be haplo-4 (and triplo for a number of genes on the 2R that are linked to the fourth chromosome centromere of the complementary half of the FYT reciprocal translocation). We have not observed any adverse effect in terms of clone recovery and survival with the triplo condition for this segment. The other daughter cell will be haploid for the part of the right arm of chromosome 2, which is cell lethal. Thus, the haplo-4 clone will not have a counterpart twin clone. This is a consideration in the design of certain experiments, such as those

involving asymmetric cell division or lineage tracing. With these considerations in mind, this system provides a much-needed general tool for efficient clonal analysis of any fourth chromosome mutation. It incorporates all of the most advanced capabilities currently available for efficient production and analysis of genetic mosaics and should readily allow incorporation of any further improvements.

2.5- Materials and Methods

2.5.1- Fly Culture Conditions and Genotypes Used to Generate Haplo-4 Clones

Flies were reared at 18 and 25°C depending on the experimental setting. Unless otherwise stated, the stocks and genotypes can be found in Flybase and references elsewhere dati1 was previously described. All constructs were introduced to FYT and

GFA chromosomes by meiotic recombination in multiple steps. A detailed description of these steps can be obtained upon request. Wild-type haplo-4 clones marked with y- were obtained from the genotype y w FLP; FRT42D w+/FRT42D y+ T(4;2)X-4; T(2;4)X-4/+.

The translocation used is a reciprocal translocation in which region 102A-F of the fourth chromosome is translocated to position 56 D-F of the 2R. Wild-type haplo-4 clones in the wing surface were induced and marked with kojakVAI51 (AKA shavenoid), a marker that eliminates trichomes (FBal0099828). These clones were induced in the genotype y w FLP; FRT42D kojVAI51 w+/ FRT42D y+ T(4;2)X-4 ; T(2;4)X-4/+. Clones in wing discs were generated in y w FLP; UAS-GFP FRT42D Actin > Gal4/ FRT42D y+ Gal80 T(4;2)X-4 ;

T(2;4)X-4/+. Clones corrected for size were generated in the y w FLP; FRT42D w+/FRT42D y+ Gal80 M(2)531 T(4;2)X-4; T(2;4)X-4/+ genotype. sparkling clones were generated in y

w FLP; FRT42D w+/FRT42D y+ Gal80 T(4;2)X-4; T(2;4)X-4/spapol (FBal0015991). Finally, dati clones in the brain were generated in y w FLP; UAS-GFP FRT42D w+ Actin >

Gal4/FRT42D y+ Gal80 T(4;2)X-4; T(2;4)X-4/dati (FBal0217973).

2.5.2- Heat Shock Regimens

Larvae between first and third instar were heat shocked for 1 h at 37°C in a water bath with the cotton plug pushed down to the level of the water surface. After heat shock they were allowed to recover and develop at 25°C. Larvae were removed from media in late third instar and washed twice in 1X PBS. Larvae were then sorted using a Leica DMI6000 inverted fluorescent microscope and individuals with clones in the developing central nervous system were placed into individual vials and allowed to grow until adulthood.

2.5.3- Brain Dissections, Multiplex in situ and Confocal Microscopy

Double protein and in situ stainings were performed as described elsewhere with some modifications (Kosman et al., 2004). Adult brains were dissected in cold PBT, fixed for 20 min in PBT 4% formaldehyde, rinsed three times in PBS and stored in 100% methanol at -20°C before processing. Next they were washed three times in 100% ethanol, incubated for 1 h at room temperature in a 1:1 ethanol:xylene solution and then washed in 100, 80, 50, 30% ethanol and finally water. After these washes the brains were incubated in acetone for 10 min at -20°C, washed in PBT and fixed again in

4% formaldehyde for 20 min at room temperature and washed five times in PBT to remove any trace of formaldehyde. They were then washed in 1:1 PBT:Hybe solution,

and washed three times in Hybe solution before being incubated in Hybe for 90 min at

55°C. After the incubation, a DNP-labeled probe for dati mRNA was added to the solution at 1:100, and left to hybridize overnight at 55°C. The next day, the brains were washed four times in Hybe solution 15 min each, at 55°C. After a wash in 1:1 PBT:Hybe, they were washed four times 15 min each in PBT. The brains were then blocked with 5%

PBT-Western blocking solution for 1.5 h and incubated overnight at 4°C with the primary antibodies. The primary antibodies used and their dilutions were as follows: rat anti-Elav

(1:1000), chicken anti-GFP (1:1000), and either rabbit anti-DNP (1:1000, for in situs) or mouse anti-nc82 (1:50, for protein stainings). After the incubation of the primaries, the brains were washed four times in PBT, for 15 min per wash. The brains were then incubated with DyLight donkey anti-chicken 488 (1:1000) (Jackson ImmunoResearch),

Alexa Fluor goat anti-rat 555 (1:1000) (Invitrogen), and either Alexa Fluor donkey anti- rabbit 647 (1:1000, for in situs) (Invitrogen) or Alexa Fluor donkey anti-mouse 647

(1:1000, for protein stainings) (Invitrogen) for 2 h at room temperature. Following secondary antibody incubation, the brains were again washed for 15 min in PBT, and then incubated in 1:1000 solution of DAPI for 15 min. Brains were then washed twice more for 15 min in PBT, then added to Slow Fade Gold antifade reagent (Invitrogen) overnight. The next day, the brains were mounted in Prolong Gold (Invitrogen) and stored in 4°C, until being imaged using a Zeiss LSM 700 confocal microscope.

2.5.4- Fluorescence Signal Normalization

To normalize the expression of dati mRNA in euploid and haplo-4 cells, and the signals of DAPI and GFP, we collected the pixel intensities of each point along a line in one channel and subtracted these values from the lowest value collected from that channel. The corrected value of each channel was then divided by the maximum pixel intensity value of that channel and multiplied by 100. This procedure was applied to all channels. This normalization allows the visualization of fluorescent signals that vary in intensity in a scale in which their percentages can be compared.

Figure 2.1- Schematic Overview of the System

(A) Schematic of a somatic cell in a FYT/GFA fly. One copy of the second chromosome bears FRT42D, yellow+, Gal80, and a translocation of the entire fourth chromosome. The other bears UAS-GFP on the left arm. The right arm bears a FRT42D, upstream of Actin>Gal4. One copy of the fourth chromosome bears a translocation of the second (reciprocal to the translocation of the fourth on the second). The other carries the mutation of interest. This cell appears wild-type and grows normally, as it has two second chromosomes, two fourth chromosomes, Gal4 repressed by the Gal80, and the mutation on the fourth covered by the translocation. The X chromosome is yellow white, and contains a heat shock inducible FLP-recombinase (not shown). (B) Schematic of the above cell after heat shock. Under heat shock conditions, a heat shock FLP- recombinase on the first chromosome (not shown) is activated. In cells undergoing mitosis, the FLP-recombinase will target the FRT sites on the second chromosome, causing recombination of the second chromosomes’ transgenic right arms and the translocation. This will lead some mitotic cells to yield two different daughter cells, both homozygous for the different right arms of chromosome two. (C) Schematic of the genotypes of daughter cells. One of the resultant daughter cells will be haploid for most of the second arm due to the translocation of the fourth, which is a cell lethal condition (gray). The other daughter cell will now lack the Gal80 which repressed the Gal4, and as such will now fluoresce with GFP (green). It also will lack the copy of yellow+, marking the cuticle. Most importantly, it will have lost the wild-type translocated fourth chromosome, leaving only the fourth chromosome with the recessive mutation.

Figure 2.2- FYT-generated clones in developing and adult tissues

(A) Wild-type eye from a FYT and spa individual subjected to heat shock as a larva. (B) The second eye from the same individual as in (A). Notice the clone patch which has been made Haplo-4 for a fourth chromosome bearing sparkling (outlined region). (C) Wing disc of a heat shocked GFA/FYT larvae. The haplo-4 fourth chromosome of clone cells is wild-type but cells fluoresce due to unsuppressed Actin > Gal4 activation of UAS- GFP on the second chromosome. (D) Wing of an adult heat shocked during development marked with kojak and the haplo-4 patch is devoid of trichomes (outlined region). Notice the distal edge of the wing within the clone patch is concave due to the Minute phenotype. (E) Patch of clone tissue in an adult thorax using the size corrected FYT system. The fourth chromosome is wild-type but lacks the yellow+ on the second chromosome, altering pigmentation of the cuticle and bristles (outlined region).

Figure 2.3- FYT-induced clones of pan-ciD on the wing

(A) pan-ciD/+ wing and a clone pan-ciD/0. (B) Higher magnification view of the pan-ciD/0 clone shown in (A). The limits of the clone are marked by kojak which exclusively removes trichomes on the wing surface. The removal of pan on the wing surface does not disrupt patterning. However, mutant cells reach the wing margin where wg is normally expressed and required. In this position they cause the loss of sensilla (arrow) and the appearance of sensilla with abnormal polarity (arrowhead). (C) a pan-ciD/+ wing without a clone shown for comparison. (D) Higher magnification view of (C), in the region of the clone in (B).

Figure 2.4- FYT induced clones in the adult brain and measurement of RNA levels by multiplex in situ hybridization.

(A–F) Brain from a 3 d-old female heterozygous FYT/GFA and the dati1 mutation on the fourth chromosome. Clones were induced via heat shock between second and third instar. (A) Nuclei stained with DAPI. (B) Neuronal cell bodies stained with anti-Elav fluorescent antibody. (C) Haplo-4 cells for dati1 mutation marked with GFP. (D) Neuropil stained with nc82. (E) Merged image of elav neuronal stain in red and GFP in green. Colocalization of GFP with Elav distinguishes mutant neurons from other cell types, such as glia. (F) Merged image of nc82 neuropil stain in magenta and haplo-4 cells in green showing position of clones. Note the clusters of clones on both the left and right anterior ventral lateral protocerebrum (arrowheads) as well as the optic lobe (arrow). (G) The antennal lobe (AL) of another female containing a dati1 mutant clone (right, below), stained with DAPI (blue), Elav (not shown), GFP (green) and a dati probe (gray). The Elav channel is omitted to reduce the complexity of the figure. The red line indicates the position and direction from which the pixel intensity values of the three visible channels (gray, blue and green) were collected and normalized. (H) The normalized pixel intensity levels of all three channels. On the left most part of the graph (0 to ~40 μms) we observe diplo-4 nuclei (blue) and normal levels of dati mRNA (gray). From ~40 to ~80 μms we note the strong GFP signal from the clone, which coincides with a drop in the dati mRNA. From 80–120 μm, the pixel intensity collected comes from neuropile which has no nuclei and mostly background levels can be detected on the three channels. From ~120–160 μms the signals of the three channels come from diplo-4 cell bodies and the levels of dati mRNA and DAPI rise again.

Chapter 3:

The KRÜPPEL-Like Transcription Factor DATILÓGRAFO Is Required in Specific Cholinergic Neurons for Sexual Receptivity in Drosophila Females

In this chapter, we characterize the behavioral and cellular phenotypes of the novel receptivity mutation dati. We show that dati mutants elicit courtship from males, but reject this courtship. We show dati is required in cholinergic neurons for females to be able to accept males, and show that dati’s rejection phenotype is separable from the phenotype of locomotor defects. We demonstrate that dati does not specify cholinergic neurons, or specify the projections of neurons, but does affect the proliferation of neurons. We also use a mosaic analysis of dati clones to discover regions of the brain involved in courtship acceptance.

This material was published previously in the journal PLoS Biology: Schinaman, J., Giesey, R., Mizutani, C. M., Lukacsovich, T., and Sousa-Neves, R. (2014)

3.1- Abstract

Courtship is a widespread behavior in which one gender conveys to the other a series of cues about their species identity, gender, and suitability as mates. In many species, females decode these male displays and either accept or reject them. Despite the fact that courtship has been investigated for a long time, the genes and circuits that allow females to generate these mutually exclusive responses remain largely unknown.

Here, we provide evidence that the Krüppel-like transcription factor datilógrafo (dati) is required for proper locomotion and courtship acceptance in adult Drosophila females. dati mutant females are completely unable to decode male courtship and almost invariably reject males. Molecular analyses reveal that dati is broadly expressed in the brain and its specific removal in excitatory cholinergic neurons recapitulates the female courtship behavioral phenotype but not the locomotor deficits, indicating that these are two separable functions. Clonal analyses in female brains identified three discrete foci where dati is required to generate acceptance. These include neurons around the antennal lobe, the lateral horn, and the posterior superior lateral protocerebrum.

Together, these results show that dati is required to organize and maintain a relatively simple excitatory circuit in the brain that allows females to either accept or reject courting males.

3.2- Introduction

Animals are capable of a staggering array of complex behaviors and many of them rely on innate abilities to compare different scenarios and generate specific and appropriate responses. For instance, most animals can determine with ease whether the best option is to confront or retreat from a predator or opponent. Risk assessment and similar mutually exclusive behaviors are likely to rely on neural circuits that collect information, remove irrelevant and noisy information, and quickly determine a course of action.

Courtship rituals are ancient forms of communication that allow animals to identify and rank potential mates in the midst of a noisy and usually complex environment. Thus, it is not surprising that courtships usually deploy a series of displays that involve bright colors, unusual sounds, and rhythmicities. The recipients of these displays, which in many species are females, evaluate their quality and generate the mutually exclusive behaviors of accepting or rejecting courtship.

One of the most fascinating aspects of the ability to generate courtship and respond with a decision is the fact that both behaviors are largely genetically encoded; that is, animals are capable of executing them perfectly with minimal practice and no instruction every generation. Pioneering work has established clear associations between individual male courtship behaviors with specific genes and alleles in

Drosophila (Villella & Hall, 2008), and even led to the mapping of foci in the central nervous system required to generate discrete behaviors (Dauwalder, 2011; Hall, 1979;

Sakai & Kitamoto, 2006; Yu et al., 2010). However, little is known about how females interpret and integrate aspects of the male's displays and decide if and when to accept male courtship (Ferveur, 2010). This is a longstanding question of significance not only to our understanding of the molecular mechanisms of reproductive behavior but also to any comprehensive understanding of how neural circuits generate mutually exclusive decisions.

In Drosophila, males show their interest in females by making wing displays, singing a courtship song, dispersing airborne and contact pheromones, and physically contacting them (Hall, 1994; Spieth, 1974; Yamamoto et al., 1997). In response to these cues, receptive females slow their movement and allow the male to proceed, to finally posture themselves to allow the male to mount them for copulation. In contrast, a disinterested or unreceptive female will engage in a number of rejection behaviors, such as fleeing, kicking the male, extruding her ovipositor, and raising or curling her abdomen

(Spieth, 1974). Early studies have shown that no single sensory modality alone determines acceptance or rejection in mature females. Instead, the likelihood of acceptance or rejection relies on different sensory modalities that individually contribute to the final behavioral output (Grillet et al., 2006; Sakai et al., 2002; Talyn &

Dowse, 2004; von Schilcher, 1976). Genes and alleles that either enhance or inhibit female receptivity have been isolated (Carhan et al., 2005; Juni & Yamamoto, 2009;

Sakai et al., 2009; Suzuki et al., 1997). Mutations in these genes provide a unique opportunity to determine the genetic contribution to cell organization and physiological responses required to generate female mate choice (Sakurai et al., 2013). In addition to

mutations, somatic mosaics have been employed to determine the regions of the brain underlying female behavior (Sakurai et al., 2013; Tompkins & Hall, 1983). Nevertheless, critical information about the neural circuitry involved in female decision-making behavior and the genes that pattern these circuits is still sorely lacking. Here, we describe dati, a neural-specific transcription factor that is required for female courtship acceptance and locomotion, and use it to begin probing the nature of the circuit by which females integrate the signals they receive from courting males to reach the correct behavioral output.

3.3- Materials and Methods

3.3.1- Mutants, Transgenes, Genotypes, and Stocks

Flies were reared at 25°C or 22°C on standard cornmeal–molasses–yeast media

(http://flystocks.bio.indiana.edu/Fly_Work/media-recipes/molassesfood.htm). The descriptions of fly stocks used and mutations therein can be found at

(http://flybase.bio.indiana.edu/), unless otherwise stated. The mutant l(4)102CDd2 (Hochman et al., 1964) was molecularly mapped in this study. The single breakpoints of the chromosomal deletions Df(4)C1-7A, Df(4)B6-4A, and Df(4)B6-

2D and the compound chromosome C(4)DRA-1 were described previously (Sousa-Neves,

2000; Sousa-Neves et al., 2005). The mutations KG02689 (dati1) and KG01667 (dati2) were also described previously (Sousa-Neves et al., 2005; Sousa-Neves & Schinaman,

2012) and correspond to single P element insertions in the second intron and 300 bp upstream of the first exon ofCG2052, respectively. datiF11.4 was generated by the

excision of the P-element KG02689inserted in dati1 and corresponds to a precise excision as revealed by direct sequencing of the region that flanks the insertion. UAS- datiF32D is a leaky UAS transgene containing the cDNA of dati (GH06573, CG2052-PA) that rescues the embryonic lethality of l(4)102CDd2 up to the first instar in the absence of a driver and its insertion was determined to be on the second chromosome in the neurally expressed gene Mmp2. The D. melanogaster stocks used were as follows: wild- type Canton-S (CS), w1118, y w, y w; Df(4)B6-4A/ciD spapol, y w; Df(4)B6-2D/ciDspapol, y w;

Df(4)C1-7A/C(4)DRA-1, y w; Df(4)BH/C(4)DRA-1, y w; C(4)DRA-1/dati1, y w;datiF11.4, y w;

SM/Cha-Gal4 UAS-GFP; C(4)DRA-1/dati1, y w hs-FLP; SM/FRT42D Actin-

Gal4;ciD spa/dati1, y w hs-FLP; SM/FYGal80T; spapol , w; UAS- mCherry.NLS, w; dati RNAi/datiRNAi [FBst0472372], w UAS-dcr-2; dati RNAi, y w hs-

FLP; SM/FRT42D Actin-Gal4; C(4)DRA-1/dati1, elav-Gal4

[FBst0008760], w; TM3, Sb/repo-Gal4 [FBst0007415], w; CyO/Cha-Gal4 UAS-GFP

[FBst0006793], w; ple-Gal4 [FBst0008848], w; Ddc-Gal4 [FBst0007009], w; Gad-Gal4 (gift of T. Sakai) (T. Sakai et al., 2009), Ubi-GFP.NLS [FBst0005626], Ubi-RFP.NLS

[FBst0035496], and FYT/GAF.

Experimental crosses were raised at 25°C, unless otherwise specified. Both males and females used for mating experiments were collected as pupae and aged 3–6 d posteclosion before mating tests. All mating tests were performed at 22°C, between 1 and 4 pm EST.

3.3.2- Recording of Mating Behavior

Mating tests were performed in small arenas made by superimposing two sliding sheets of transparent polycarbonate containing 24 wells each (2.54 cm in diameter and

1.27 cm depth) (Drapeau, 2000). Each well was divided in half by a thin removable sheet of plastic. Canton-S males and experimental females 3 to 6 d old were loaded into opposing sides of each chamber without anesthesia with a manual aspirator. Once all wells were loaded, the thin plastic sheet was removed and all pair matings began simultaneously. The chamber was lit from below by an Artograph LED LightPad

(Artograph Inc.), and mating behavior was recorded using a Sanyo FH1-A (Sanyo Inc.) camcorder for 1 h. For each experimental group, we calculated the courtship acceptance rate, defined as the number of pairs that successfully copulated in the 1 h observation period divided by the number of pairs observed. The average Courtship

Index (CI) was calculated for each experimental group. CI is defined as the fraction of time a male spent courting in a given observation period (Tompkins et al., 1980). Male courtship for each pairing was observed for 10 min, starting at the onset of courtship.

CIs for each pair mating in an experimental group were then aggregated into an average

CI. Sample sizes are shown in the corresponding figure in results.

3.3.3- Quantification of Discrete Female Behaviors

Females 3 to 5 d old of experimental and control genotypes were pair-mated to

Canton-S males in the mating chamber described above and video recorded for 1 h. For each pair mating, female behavior was analyzed for 10 min from the onset of courtship

or until mating occurred. For this time period, every time a male initiated a step of courtship, the female reaction to courtship was recorded. The following six discrete rejection behaviors were quantified: fleeing, kicking, extruding ovipositor, jumping, flicking wings, and standing still. For each female, a Behavioral Index (BI) was obtained by calculating the frequency of each behavior displayed over the frequency of all behaviors, and these indices were averaged for each genotype.

3.3.4- Analysis of Locomotor Behavior

Locomotor behavior was analyzed using an adaptation of the negative geotaxis assay (Gargano et al., 2005). Five to eight flies of 3 to 5 d old were placed in a 15 mL

Falcon tube without anesthesia and allowed to acclimate for 5 min. After this period of acclimation, the Falcon tube was inverted and rapped sharply against a fly transfer pad three times to knock flies to the bottom of the tube. The tube was then placed in front of the camcorder and flies were allowed to climb the walls. The heights reached by each of the flies after 5 s was assessed from the camcorder footage. Over 30 flies were analyzed for each experimental group. For each Falcon tube of flies, this assay was repeated for a total of five trials, spaced 30 s apart, and the heights of all flies from each trial averaged together.

3.3.5- Antibodies and Immunostaining

Antibody staining for brains was performed according to standard protocols (Sweeney et al., 2012). Primary antibodies used were chicken anti-GFP

(1:1,000, Invitrogen), rabbit anti-RFP (1:1,000, Invitrogen), mouse anti-nc82 (1:1,000,

DSHB), Guinea pig anti-Dati (1:1,000, gift from T. Isshiki) (Tsuji et al., 2008), rat anti-Elav

(1:1,000, DSHB), and mouse anti-FasII (1:100, DSHB). Secondary antibodies used were donkey anti-mouse 647 (1:500), goat anti-rat 555 (1:500, Invitrogen), donkey anti- guinea pig 647 (1:500, Invitrogen), donkey anti-chicken 488 (1:500, DyLight), and donkey anti-rabbit 555 (1:500, Invitrogen). All samples were mounted in SlowFade (Invitrogen) and scanned on a Zeiss LSM 700 confocal microscope. Images generated from Z-stacks taken at 1 or 2 µm intervals are displayed as maximum intensity projections using Zeiss

Zen 2009 or as orthogonal projections/surface projections using Image J.

3.3.6- Automated Image Analysis and Cell Counting

Automated cell counting was performed on confocal slices using Fiji software

(Schneider et al., 2012). Briefly, a two-channel stack stained for dati (green) and Cha-

Gal4 UAS-RFP.NLS (red) was converted to RGB, and the yellow overlap was segmented with white color using “Threshold Color” function. The blue channel containing the segmented nuclear overlaps was extracted and the noise removed by filtering the stack with the function “Despeckle.” Three-dimensional segmentation counts were generated by the plugin “3D Object Counter” (Bolte & Cordelieres, 2006). Due to the large size of posterior brain stacks, they were stitched together using the plugin “Pairwise Stitching” before segmentation (Preibisch et al., 2009).

3.3.7- Clonal Analyses

Clonal analyses were performed using the FYT (FLP-recombinase recognition target site-yellow+-Translocation) system previously described. After clone induction, third instar larvae containing GFP+ clones were handpicked, placed in a single vial, and allowed to develop up to adults 3 to 6 d old. Single females carrying clones were tested with single Canton-S male in the courtship arenas described above and video recorded for 1 h. After this time the number of couples that mated was recorded and the

Courtship Indices determined. In the next day, the females that rejected males were retested with new Canton-S males for rejection, and only those that passed in the double rejection test were analyzed further (Tompkins & Hall, 1983). Females that accepted and rejected males were referenced to specific wells and had their brains dissected. Each clone was located in a grid that divides the brain in 40 anterior and 40 posterior sectors. Because each brain may vary slightly in size or in the way it is mounted, the grid was manually stretched to find the best fit for each sample. In total,

491 clones from 83 brains were analyzed.

3.3.8- Olfactory Behavior Assays

In these experiments, we used a T-Maze (Tully & Quinn, 1985) with 2 µl of benzaldehyde in one of the ends. Individual flies were loaded into the elevator of the apparatus and immediately lowered to the level containing the two ends with and without odor. After 10 s, the number of flies that moved away from the aversive odorant or towards it was recorded.

3.3.9- Mushroom Body and Antennal Lobe Image Analysis

Brains of different genotypes were dissected and stained for the mushroom body marker FasII and imaged as z-stacks at 1 µm intervals. Selected z-stacks containing the gamma lobe were manually segmented using the Fiji plugin “Segmentation Editor.”

Measurement of γ lobe morphological defects was done in Fiji. A similar procedure was done to segment the antennal lobe, except that the limits of the segmented structures were defined by the expression of GFP in the pattern of CHA.

3.3.10- Statistical Analysis

All statistical analyses were performed using MiniTab 16.1.0 (Minitab Inc.). For all comparisons of courtship acceptance rate between control and experimental groups, a 2-Proportion Test was performed, and Fisher's exact p test value was used for the determination of significance level between two groups, unless otherwise indicated. CI data were arcsine transformed prior to statistical analysis as previously described

(Vanswinderen & Hall, 1995) and analyzed by one-way ANOVA. The difference in climbing ability in locomotor tests was analyzed by one-way ANOVA. Behavioral indices

(Figure 3.11) were analyzed by Mann–Whitney U Test. All other tests are two sample t tests unless otherwise noted.

3.4- Results

3.4.1- Identification of dati on the Drosophila Fourth Chromosome

We previously generated a series of molecularly mapped terminal deletions on the fourth chromosome that define relatively small genomic intervals that can be used to map mutations (Podemski et al., 2004; Sousa-Neves et al., 2005). These deletions were then used to map a collection of mutants available for this chromosome, to later test for locomotion and other behavioral abnormalities. One of them was l(4)102CDd2, an unmapped embryonic lethal mutation isolated nearly 50 years ago by Ben

Hochman (Hochman et al., 1964).

While mapping l(4)102CDd2 we found that 5%–8% of the heterozygotes between this mutation and two deletions (Df(4)B6-2D and Df(4)B6-4A) escaped the lethality of l(4)102CDd2 and exhibited a phenotype of uncoordinated movements, which becomes stronger with age (compare Movies S2 and S3). Due to the tapping of the forelegs of these genotypes, we named the mutation datilógrafo (dati), which means typist in Portuguese. Subsequent analyses revealed that mutations in dati also render females completely unable to accept male courtship, as will be shown later. We located molecularly the mutation in l(4)102CDd2, which corresponds to a deletion that disrupts dpr7 and CG2052 plus eight other genes in between, and renamed it as deficiency on the fourth chromosome of Ben Hochman [Df(4)BH] (Figure 3.1A).

Because two single fourth chromosome P-element insertions localized at the breakpoint of these deletions in the CG2052 gene (KG02689 and KG01667) exhibited the same

phenotypes as homozygotes or heterozygotes for Df(4)BH, we focused our analyses on the insertion KG02689 (dati1), the strongest of these two alleles. dati encodes a zinc finger transcription factor closely related to rotund (rn) and squeeze (sqz) with homologs in several species, including humans (Figure 3.1B).

Consistent with its reported requirement in specifying late born neurons during embryogenesis (Tsuji et al., 2008), dati is specifically expressed in the central nervous system in embryos (Figure 3.2A). In larval stages, dati is expressed in the brain and ventral nerve cord (Figure 3.2B) but not in other larval tissues (e.g., wing, leg, eye, and antennal discs; unpublished data). In adults, dati is broadly expressed in the brain

(Figure 3.2C).

3.4.2- dati Mutant Females Are Courted Normally But Fail to Accept Male Courtship

dati1 mutants usually stand still for long periods of time, but when courted by males, they can flee at considerable speed. In addition, when cornered by a courting male, they engage in a series of rejection behaviors that include kicking and curling their abdomen (Movies S1, S2, S3) (Bastock, 1956; Spieth, 1974). To investigate how the behavior of dati1 females departs from the wild-type, we quantified six discrete behaviors normally displayed by wild-type females in response to male courtship (i.e., fleeing, kicking, extruding ovopositor, jumping, flicking wings, and standing still). dati females display all of the aforementioned behaviors but spend more time kicking and less time standing still than the wild-type (Figure 3.3).

To further quantify the abnormal mating behavior of dati1 mutant females, we compared their mating success with that of wild-type Canton-S, y w, and dati precise excision revertant females. From these data it becomes evident that the behavior of dati1 is significantly different from the wild-type Canton-S, y w and the revertant datiF11.4 females, which exhibit normal acceptance rates (Figure 3.4A). To test whether the deficit in matings was exclusively due to the female rejection, we assessed the sex appeal of dati1 homozygous females using the CI (Figure 3.4B) (Chu et al., 2013;

Tompkins et al., 1980). These experiments reveal that males respond to dati1 females normally, with courtship indices indistinguishable between all four groups.

The rejection of dati mutants was tested over a longer time by measuring the frequency of females that produced progeny with a wild-type male in 6 d. The difference between the two groups is not significant (dati1 6 d = 2/14 versus dati1 1 h =

0/32, p = 0.08), but both are significantly different than Canton-S (dati1 6 d versus

Canton-S 6 d = 29/30, p<0.0001 and Figure 3.4A). This result is consistent with the fact that females that fail to accept males within 30 min are unlikely to mate afterwards

(Manning, 1967).

3.4.3- dati Is Required In Neurons for Normal Acceptance and Locomotion

To determine in which tissues dati is required for normal courtship behavior and locomotion, we knocked down its expression using RNAi and UAS-dcr-2 to enhance the knockdown. The knockdown of dati with the ubiquitous Actin-Gal4 at 25°C resulted in few adult individuals that died shortly after eclosion with extreme locomotor

abnormalities (unpublished data). To obtain a less severe phenotype more similar to dati1 homozygotes, the UAS-dcr-2 construct was removed from the genotype and the flies were reared at 18°C. Under these conditions, females expressing the dati RNAi from Actin-Gal4 showed defects in acceptance and locomotion (Figure 3.4C, 3.4D; unpublished data). Similarly, the knockdown of dati with elav-Gal4 caused rejection and locomotor defects (Figure 3.4C). elav is a bona fide postmitotic marker, except for a transient embryonic expression in glial cells and neuroblasts in thoracic and abdominal segments (Berger et al., 2007). However, we show that the knockdown of dati in glial cells usingrepo-Gal4 produced no effect (Figure 3.4), indicating that the courtship behavioral phenotypes are not generated in these cells. In addition, we later provide evidence that the behavioral effects of dati knockdown with elav-Gal4 are not associated with neuroblasts of the embryonic ventral nerve cord.

3.4.4- The Removal of dati in Cholinergic Neurons Impairs Normal Female Acceptance

But Not Locomotion

Because our previous results suggested that dati might be required in some capacity in neurons, we next asked whether a specific neuronal population could phenocopy the mating deficit observed. The fly brain employs several neurotransmitters including dopamine, acetylcholine, GABA, glutamate, serotonin, histamine, octopamine, and tyramine (Bicker, 1999; Budnik & White, 1987; Daniels et al., 2008; Dierick &

Greenspan, 2007; Littleton & Ganetzky, 2000; Waddell, 2010). To begin an unbiased search for specific neuronal populations, we first knocked down the expression

of dati by RNAi using four Gal4 drivers of genes involved in the synthesis of different neurotransmitters (Dopa decarboxylase, pale, Choline Acetyltransferase, and Glutamic acid decarboxylase 1) (Figure 3.4E, 3.4F) to later test other neuronal types if necessary.

Out of the four drivers tested, Choline Acetyltransferase Gal4 (Cha-Gal4) produced a strong and significant reduction in courtship acceptance (Figure 3.2E, 3.2F). Thus, the inability of dati females to accept males affects a particular neuronal type.

Interestingly, the removal of dati in cholinergic neurons does not impair locomotion as can be observed from “negative geotaxis” escape response tests

(Gargano et al., 2005; Watanabe & Anderson, 1976). In these tests, dati1 homozygous females normally achieve a much lower mean height 5 s after being knocked to the ground compared to wild-type Canton-S females (Figure 3.4G). Revertants also have a significantly better climbing ability than dati homozygotes (Figure 3.4G). However, their climbing ability was not completely restored to the levels of y w, indicating that although most of the climbing deficits can be ascribed to the mutation in dati, other genes in the genetic background contribute to the locomotor deficits observed. In contrast, the climbing abilities of dati RNAi knockdowns with the Cha-Gal4 driver were not different from wild-type Canton-S (Figure 3.4G), indicating that the male rejection behavior of dati1 mutants is separable from the locomotor deficits.

3.4.5- dati Mutants Exhibit Abnormal γ-Lobes of the Mushroom Bodies, But These

Defects Do Not Cause Female Rejection

The results above revealed that the acceptance deficits of the dati1 mutant are generated in cholinergic neurons. Because the mushroom bodies in Drosophila express

CHA and have been implicated in memory formation, learning, and olfactory processing, we initially tested whether this neuropile was abnormal in dati1 mutants (Balling,

Technau, & Heisenberg, 1987; McBride et al., 1999). The alpha and beta lobes of dati1mutants appear indistinguishable from the wild-type mushroom bodies, but the gamma lobes are malformed with a generally withered appearance (Figure 3.5A, 3.5B,

3.5D) and have significantly different curvature (Figure 3.5E). To determine if the gamma lobe defects could be responsible for the behavioral rejection, we asked whether the knockdown of dati expression in CHA+ cells could recapitulate the morphological defect in the gamma lobe and behavioral phenotypes observed. These experiments revealed that although Cha-Gal4 UAS-dati-RNAi females reject males, the gamma lobe is not affected (Figure 3.5C, 3.5E). Together these experiments allowed us to conclude that although the loss of dati disrupts the gamma lobe neuropile, the focus of dati-mediated courtship acceptance lies elsewhere in the brain.

3.4.6- dati Is Expressed in a Large Set of Neurons But in a Small Subset of the

Cholinergic Neurons

To narrow the region where dati is required for female acceptance, we asked whether DATI- and CHA-positive neurons corresponded to a smaller subset than CHA

neurons. DATI is broadly expressed in a complex pattern that involves a few thousand neurons. Automated cell counts indicate that there are around 2,400 neurons of the central brain that express dati, which corresponds roughly to 6.6% of all neurons of the fly's central brain (Figure 3.6) (Kei Ito & Awasaki, 2008). The overlap between CHA- and

DATI-positive neurons is much smaller, comprising 345±55.3 (mean ± s.d) neurons of the anterior central brain (N = 5), and 1,049±134 neurons of the posterior central brain (N =

8). Based on these cell counts, DATI- and CHA-positive cells (i.e., cells that cause rejection with RNAi) correspond to a modest 4% of the total neurons in the central brain. Besides reducing the complexity of the neural circuit required for acceptance, these experiments revealed that dati is not required to determine cholinergic cell identity. Instead, dati appears to specify a subtype of neuronal identity that is presumably shared by neurons that express different neurotransmitters.

3.4.7- Mapping Brain Regions Where dati Is Required to Generate Acceptance Reveals

Discrete Brain Foci

To determine the brain regions that mediate acceptance, we performed a clonal analysis using a new genetic tool we developed that allows for the systematic and efficient generation of somatic clones of fourth chromosome mutants, named the FYT system (Figure 3.7). In these experiments, we randomly removed dati in different positions in the brain, tested whether females accepted or rejected males, and located the position of each clone within a grid that divides the brain in 80 sectors (Figure 3.8A-

D). By compiling a collection of 491 clones in the brain of females that either produce

acceptance or double rejection (i.e., rejection in 2 consecutive days), it becomes clear that some regions in the brain produce significant deficits in acceptance while others do not. In the anterior brain, a single statistically significant region was identified in anterior sector B2 (AntB2, p = 0.029, Figure 3.8A). In the posterior brain, two regions stood out as highly significant (PosA3, p = 0.004 and PosC4, p≤0.001) (Figure 3.8B).

The anterior region AntB2 encompasses the first focus identified for female acceptance behavior using gynandromorphs (Tompkins & Hall, 1983)and also a region populated by extensively characterized local neurons (LNs) that express Sex lethal (Das et al., 2008; Hayashi et al., 2002). The posterior region PosA3 is located in the posterior superior lateral protocerebrum (pslpr) immediately above the lateral horn. In contrast,

PosC4 spans over the ventral part of the lateral horn, the edge of the posterior inferior lateral protocerebrum (pilpr), and posterior lateral protocerbrum (plpr) (Figure 3.8D).

Together, these results show that dati is required in discrete neurons along a known olfactory path (Masse et al., 2009; Tanaka et al., 2004), which involves second-order olfactory neurons and also third-order neurons located around the lateral horn.

Interestingly, the ventral lateral horn has been recently identified as the region that processes pheromones (Jefferis et al., 2007; Ruta et al., 2010). In contrast, PosA3 appears to be a novel focus implicated in female receptivity.

3.4.8- Rejection Foci Contain Few dati-Positive, Cholinergic Neurons

To narrow down the position of the neurons in each sector, we analyzed the neurons that express CHA and DATI within these regions. In the anterior brain, within

the region AntB2, we can discern 13.8±2 neurons per hemi-antennal lobe (N = 16, Figure

3.9A and C). The posterior brain regions PosA3 and PosC4 that produced the most significant acceptance deficits also have very few DATI CHA neurons. Indeed, in these two regions we can identify 16.82±2.4 neurons that are positive for DATI and CHA (N =

15, Figure 3.9B and D). In the PosA3 sector (pslpr), we found 3.64±1.18 neurons (Figure

3.9D), and in the ventral lateral horn and posterior inferior lateral protocebrum (pilpr), there are 13.17±2.52 DATI CHA-positive neurons (N = 15). These results suggest that a strikingly small number of DATI CHA neurons are essential for female acceptance.

3.4.9- dati Is Required to Generate a Subtype of Cholinergic Neurons

Because we had observed that the removal of dati in olfactory neurons in the region AntB2 impairs female acceptance and dati is required in the specification of late born neurons (Tsuji et al., 2008), we expected that the mutant might fail to specify a neuronal subtype DATI CHA. To begin addressing this issue, we compared the GFP expression patterns of Cha-Gal4 in wild-type anddati1 homozygotes (Figure 3.10A–G).

These experiments revealed severe abnormalities in the cholinergic tracts of the antennal lobes (Figure 3.10B–G). A closer examination reveals that the population of dorsal lateral neurons in the region AntB2 are either reduced or transformed to cholinergic neuronal types with a distinct morphology than those normally found in this region (Figure 3.10C and F). These transformations within antennal lobe neurons affect several glomeruli, which include DA1, the target of the male pheromone cis-vaccenyl acetate (cVA) (Figure 3.10D–H) (Couto et al., 2005).

The experiments above revealed that the loss of dati disrupts olfactory glomeruli. To test whether these disruptions lead to olfactory deficits, we assayed the performance of dati mutant females in a T-Maze in which flies are tested for moving away or towards an aversive odor. In this test, only 3% of the Canton-S flies (1 out of 30) moved towards the aversive odor compared to 32% of the dati mutant females (11 out of 34), indicating that olfactory behavior is indeed impaired in dati mutants (wild-type versus dati, p =

0.001).

In the lateral horn, the loss of dati leads to a reduction of approximately 10% of the lateral horn neuropile area (Figure 3.11C and D; dati, N = 8; WT, N = 10) and the cholinergic projections from the antennal lobe towards the lateral horn are also affected

(Figure 3.12). Like in the antennal lobe, we note the presence of larger neurons in the lateral horn of dati mutants, which are not present in the wild-type (Figure 3.11A and B).

Furthermore, there are more CHA-positive cells around the lateral horn, suggesting that in the absence of dati some neuronal precursors can proliferate to later assume a cholinergic fate or, alternatively, that in the absence of dati some cells assume a cholinergic fate (Figure 3.11A–D). Together, these results show that dati is required in postmitotic neurons as well as in the precursors of these cells.

3.4.10- Nuclear Bar Coding Reveals That DATI CHA Neurons Mediate Short- and Long-

Range Connections

From the previous experiments, we found evidence that dati specifies a subpopulation of cholinergic neurons that project into the antennal olfactory glomeruli.

Olfactory neurons in the antennal lobe descend from few neuroblast lineages that generate remarkably different neurons within and across lineages (Das et al., 2008), and it has been suggested that morphologically different neurons are dedicated to specific neurocomputations (Sachse et al., 2007). This heterogeneity has been traditionally investigated in great detail in clones of single or few neurons using Gal4 drivers that reveal discrete neuronal populations (Jefferis et al., 2001; Okada et al, 2009; Yu et al.,

2010). However, we are often confronted with the opposite problem, which is to estimate whether a selected neuronal population makes simple, complex, or both simple and complex connections when a discrete Gal4 driver for these neurons is not available. This distinction is important to determine whether dati intrinsically modifies cell shapes or other aspects of neuronal physiology (Parrish et al., 2007). To that end, we developed a simple system of nuclear bar coding that distinguishes different DATI

CHA neurons by color. Nuclear Bar Coding (NBC) consists of labeling nuclei of neurons with small or large volumes with different colors by expressing a localized nuclear RFP

(mCherry.NLS) and GFP-S65T (nuclear and cytoplasmic) under the control of a Gal4 driver (in this case Cha-Gal4). Cells expressing the two fluorescent proteins from the same promoter are expected to be produced and degraded at comparable rates and result in nuclei with an overlay of two colors (Figure 3.13) (Beskow et al., 2009; Yen &

Elledge, 2008). Assuming that these two proteins are not subject to a different regulation, the overlay of two colors should vary depending on the cellular volume. In cells with long or more intricate processes, GFP-S65T should be expected to fill up the cellular processes and shift the overlay of the two signals in the cell bodies towards that

of the localized nuclear fluorescence (i.e., red color from RFP). Evidence for this shift was obtained in comparisons between cells with short and long cell processes (Figure

3.14A–C). Conversely, when both GFP and RFP are targeted to the nucleus, the shifts of nuclear bar coding are abolished (Figure 3.13). If, to this simple bar coding, we add a third color that detects DATI-positive cells (Figure 3.14D), then we can globally assess whether dati cholinergic neurons have simple or more complex projections. NBC allowed us to easily identify the descending neurons (Figure 3.14A), as well as long projection neurons located immediately above the antennal lobe, known as anterior– dorsal projection neurons (adPNs; Figure 3.14C,D), and LNs imbedded in antennal lateral neurons (Figure 3.14C–E). In addition, the NBC method reveals that the DATI CHA neurons within the region AntB2 make both short and long connections (Figure 3.14C–

E). Thus, we conclude that dati does not specify only one type of cell shape, like other transcription factors that specify particular neurons (Parrish et al., 2007).

3.5- Discussion

3.5.1- dati Encodes a Conserved ZNF Transcription Factor Related to Rotund/Squeeze and ZNF384 Required for Female Decision Making and Locomotion

Here we described DATI, a zinc finger transcription factor related to the

Drosophila Rotund and Squeeze and the vertebrate ZNF384, one of the three genes known to be involved in acute lymphoblastic leukemia (ALL)(La Starza et al., 2005;

Martini et al., 2002). A survey of the sequences related to dati suggests that it descends from a Krüppel/rotund prototype present in cnidarians (e.g., Nematostella,

gb|ABAV01025004.1|). Later this prototype evolved to become the rotund-like found in nematodes (e.g., C. elegans, Lin29) and mollusks (e.g., M. galloprovincialis, gb|GAEN01018610.1|) and was inherited by both vertebrates and invertebrates. Due to its similarity with Lin29, dati was previously referred to as Dmel/Lin29. However, orthology tests show that the ortholog of the C. elegans Lin29 is rotund, not dati. The first true ortholog of datiis found in marine arthropods (e.g., Daphnia pulex, Dpdati, gb|ACJG01001740.1|), which appeared in the Cambrian some 540 Mya (Braun et al.,

2007).

Like its vertebrate homolog, dati is expressed in the nervous system and required for stem cell development (Lukk et al., 2010; Nakamoto et al., 2004; Roth et al.,

2006; Tsuji et al., 2008). During embryogenesis, dati is one of the last genes to be activated in a serial activation of transcription factors that determines the identity of specific neuronal lineages in the ventral nerve cord (Tsuji et al., 2008). The present study shows that dati is later required to specify regions of the central brain required for appropriate female acceptance.

dati mutant flies are moderately uncoordinated and almost invariably reject male courtship (Movie S3 and Figure 3.4). This rejection is so intense and persistent that it does not seem to be due to the mere loss of single sensory modalities, which inhibit but do not abolish acceptance (Bastock, 1956). Because of this strong rejection, we expected that dati might impair either more than one path required to generate acceptance in the brain or an area in which sensory information converges. In addition,

we also tested if the locomotor and decision-making defects were associated or separable.

3.5.2- Locomotor Defects Are Separable From the Inability to Make Decisions

The mapping of foci by clonal analyses revealed individuals with clones that exhibited rejection but not locomotor defects (unpublished data). Conversely, we also found individuals with locomotor defects that were perfectly capable of accepting courtship and mating properly (unpublished data). Further evidence that locomotion and female behavior are separable was obtained in the experiments in which dati was knocked down in neurons that express different neurotransmitters (Figure 3.4). In this case, we found that none of the four drivers used (Ddc, Gad, ple, and Cha-Gal4) produced locomotor defects like those observed using either a ubiquitous driver or the neuronal driver elav-Gal4, but the removal of dati in CHA neurons resulted in strong female behavior deficits. Thus, we conclude that the locomotor defects and female acceptance map to different brain regions and distinct cells that express specific neurotransmitters.

3.5.3- dati Adds an Additional Layer to the Identity of Cholinergic Neurons That Is

Shared by Noncholinergic Neurons

Our results suggest dati has two roles in the nervous system—one developmental and another constitutive—both affecting female behavior. The over/underproliferation of cholinergic neurons in dati homozygotes suggests a

requirement in neuronal precursors, which is consistent with the previous study that showed dati is transiently expressed in developing ganglion mother cells (Tsuji et al.,

2008). However, there is a requirement in neurons, as the courtship behavioral phenotype is recapitulated when dati is removed in postmitotic neurons. Further evidence for this requirement in adult neurons is the fact that dati is indeed expressed in neurons well into adulthood, and in fact, we identified a small group of neurons that only initiates expression of dati in adult neurons (unpublished data). Together these results suggest that dati may be required to maintain a neuronal identity. Because not all dati-positive neurons are cholinergic, and vice versa, it is unlikely that its primary role would be to determine the expression of this neurotransmitter. The Nuclear Bar Coding analysis suggests that dati does not evidently define any specific cell morphology either.

We speculate that dati specifies a type of neuronal identity that allows neurons to respond to neurotransmitters that other cholinergic neurons without dati cannot. In this scenario, it is easy to see that removing dati from mature neurons would deprive them from the appropriate receptor(s) needed to receive input from their synaptic partners, and consequently silence female receptivity. Future tests should resolve whether dati indeed regulates channels/receptors to generate courtship acceptance.

3.5.4- The Regions Where dati Is Required Agree with Previous Mapping and Suggest the Existence of a Core Circuit for Female Decision Making

Different mutants and experimental approaches, including gynanders, spinster mosaics, mapping of cVA processing neurons, and the use

of dati mosaics, here have identified some common and other distinct foci for female decision making. For instance, the first focus AntB2 that we identified maps to Sp11, the first brain region identified for female acceptance using mosaic gynandromorphs

(Tompkins & Hall, 1983). AntB2 also maps within the Spin-D site identified by mosaics of spinster (Sakurai et al., 2013), a gene also required for female behavior. In addition, the two other highly significant regions, PosC4 and PosA3, flank the lateral horn, and we note that the focus PosC4 co-maps with regions previously implicated in pheromonal processing in the female brain (Jefferis et al., 2007; Tanaka et al., 2004). Notably, the lateral horn may have a larger role in sensory integration, as it receives projections from centers that process visual and mechanosensory information (Tanaka et al., 2004). Thus, the picture that emerges from previous work and the present study suggests that female decision making in Drosophila is modulated by a core circuit involving the antennal lobe and the lateral horn. However, we note that there are regions with ratios of acceptance and rejection that intuitively may appear to be relevant but that failed to reach statistical significance. In particular, there are three regions in the anterior brain

(AntB3, AntB4, and AntD3) and seven regions in the posterior brain (PosB3, PosB4,

PosC1, PosC2, PosC3, PosD2, and PosD3). We believe that these regions are unlikely foci for female receptivity, as our sample had resolution to identify the great significance of a relatively small focus like PosA3. Also, a similar study that analyzed a larger sample of

Spinster foci for female receptivity also found brain regions that did not reach statistical significance but had ratios that could be intuitively interpreted as almost significant like

ours. Like us, these authors disregarded these data as insignificant (Yamamoto &

Koganezawa, 2013).

3.5.5- dati's Requirement in Few Excitatory Neurons in Three Discrete Brain Foci

Reveals a Simple, Yet Fundamental, Mechanism of Female Decision Making in

Drosophila

Besides providing the locations where courtship acceptance decisions are generated in the brain and the type of neurotransmitter involved, our results also reveal a significant neural mechanism at play. The DATI-CHA neurons mapped in the antennal lobe correspond to a subset of extensively studied cholinergic population known as the excitatory dorsal lateral Projection Neurons (ePNs) and excitatory lateral neurons (eLNs)

(Gu & O'Dowd, 2006; Huang et al., 2007; Parnaset al., 2013; Shang et al., 2007; Silbering et al., 2008). The central role of excitatory cholinergic neurons revealed by our study and the localization of a region where sensory information is integrated constitute a nearly perfect cellular and molecular representation of the “Summation Hypothesis,” elaborated by Manning and others several decades ago based on behavioral inference

(Bastock & Manning, 1955; Ewing, 1964; Manning, 1967). This hypothesis states that acceptance of courtship involves the convergence of multiple excitatory stimulations provided by different sensory modalities until the stimulation reaches a critical threshold point that generates acceptance (Bastock & Manning, 1955). Most importantly, the Summation Hypothesis predicts that the two opposite female responses (i.e., rejection or acceptance) are not the result of opposing neural activities

(e.g., excitation and inhibition) but rather the result of two different levels of excitation.

Until now, there was no molecular and cellular evidence in support of this prediction. In this regard, our results are in agreement with this prediction, as the absence or presence of DATI in an excitatory circuit generates either complete rejection or overwhelming acceptance, respectively.

Corroborating our results, recent findings show that pheromone processing is not subject to the inhibitory mechanisms that apply to the processing of other odors

(Liang et al., 2013). Taken altogether, our results suggest that few dozen excitatory neurons converging in as few as three brain foci make the core components to generate a mating decision in Drosophila. Given that dati-related genes are present in a wide variety of organisms, it is likely that their common ancestor had the same or a similar mechanism of female acceptance.

Figure 3.1- Molecular mapping of dati1 and conservation of dati across species

(A) Physical position of dati on the fourth chromosome (highlighted in yellow). The P- elements KG02689 (dati1) and KG01667 (dati2) are represented by grey triangles. Deficiencies causing lethality in conjunction with dati1 are represented by gray bars. Note that the Deficiency of Ben Hochman [Df(4)BH] spans a region of 10 genes, between dpr7 and dati. Indicated below Df(4)BH is the sequence of the breakpoint indpr7 (gray) and dati (blue). (B) Neighbor-joining distance tree with Kimura two- parameter distances of dati sequences across multiple species. Branches of the tree with green termini represent orthologs of dati, whereas branches with red termini represent homologs.

Figure 3.2- Embryonic and larval expression of dati. (A) Antibody staining of a wild-type late stage embryo for DATI (green) and ELAV (magenta). Note the presence of DATI in neurons of each hemisegment of the ventral nerve cord. Image is from a single slice of a confocal image stack. (B) Antibody staining of a wild-type L3 larval brain for DATI (gray). (C) Adult female brain stained with anti-DATI (green). The images are maximum intensity projections of confocal stacks.

Figure 3.3- Quantification of discrete responses to male courtship displayed by dati mutant females versus wild-type females. Female response to male courtship was quantified for 10 min after initiation of courtship by wild-type males. Bars show BI of each discrete response type of control group (Canton-S females, dark bars) and experimental (dati homozygous females, light bars). dati females are capable of displaying the same array of rejection behaviors to courtship as wild-type females (i.e., fleeing, kicking, extruding ovipositor, jumping, and flicking wings). Compared to wild- type females, dati females spend more time kicking males. In contrast, dati females spend significantly less time standing still, which is considered an accepting behavior displayed by wild-type females after being courted for some time. The statistical significance of differences was evaluated by the Mann–Whitney U test (***p<0.001; **p<0.01), and error bars represent ±SEM. The sample sizes are Canton-S,N = 12 and dati1, N = 10.

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Figure 3.4- Results of pair mating and locomotor experiments using dati1 and UAS- dati-RNAi. (A, C, E) Percentage of females that accepted wild-type Canton-S male courtship within 1 h in pair mating assays. (B, D, F) Courtship indices of Canton-S males towards females tested in (A), (C), and (E), respectively. Courtship indices were arcsin transformed and subject to one-way ANOVA, and in all cases they are not significantly different from each other (p>.05). Error bars represent ±SEM of the measurements of each genotype. (A–F) Genotypes of females tested are indicated (“UAS-RNAi” means UAS-dati-RNAi). Dark and light bars in (C–F) indicate experimentals and controls, respectively. (A, B) dati1 homozygous females strongly reject males, despite being courted vigorously by Canton-S males. This rejection phenotype is reverted in revertant females homozygous for the precise excision datiF11.4 allele. Controls with Canton-S and y w females were used, as revertants lose both y+ and w+ transgenes. (C, D) Ubiquitous expression of UAS-dati-RNAi driven by Act-Gal4 or expression in postmitotic neurons driven by elav- Gal4 causes rejection of male courtship. (C) Dark bars indicate the percentage of females expressing UAS-dati-RNAi driven by different Gal4 drivers that accepted male courtship. Light bars indicate results with control females (Canton-S females and females with either UAS-dati-RNAi or a Gal4 driver). Expression of dati-RNAi in glial cells (repo-Gal4) does not cause rejection. (E, F) Expression of dati-RNAi specifically in cholinergic neurons causes the female rejection behavior. (E) Percentage of courtship acceptance in females expressing UAS-dati-RNAi driven by neuron-specific Gal4 drivers (dark bars) versus control females with either Gal4 drivers or UAS-dati-RNAi only (light bars). Ddc-Gal4 is a driver of both serotonergic and dopaminergic neurons, ple-Gal4 of dopaminergic neurons, Gad-Gal4 of GABAergic neurons, and Cha-Gal4 of cholinergic neurons. (G) Courtship acceptance and locomotor deficits in datimutant females are separable phenotypes. The graph shows the distance climbed by females of various genotypes within 5 s after being knocked to the bottom of a vial. Measurements shown are an average of five replicates from each group; error bars represent the mean ± the standard deviation. Sample size numbers are indicated inside bars in (A, D, E, G). Graphs (B, D, F) use the same datasets as (A, C, E), respectively. Statistical significance of differences in (A, C, E, G) was evaluated by the Fisher's exact probability test (***p<0.001; **p<0.01; *p<0.05).

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Figure 3.5- dati1 homozygote females exhibit mushroom body defects, whereas Cha- Gal4/UAS-dati-RNAi females do not. (A–D) 3D segmentations of mushroom bodies visualized by anti-FasII staining of (A) wild- type, (B) dati1 homozygous, and (C) Cha-Gal4/UAS-dati-RNAi females. The α lobe (magenta), β lobe (blue), γ lobe (yellow), and ellipsoid body (green) are indicated. Note that the γ lobes in (B) are more curved than the gamma lobes in (A) and (C). Note that the genotype in (C) causes rejection like dati1 homozygous females (B), but not locomotor defects (Figure 3.4G). (D) Mushroom body shown in (A, box) and measurement of the morphological defect of the γ lobe. Red lines show the base (horizontal) and height (vertical) of the mushroom body arch. (E) Graph shows that there is a significant increase in the height (h) of the mushroom body arch in comparison to wild-type andCha-Gal4UAS-dati-RNAi (N = 14).

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Figure 3.6- Cell counts of neurons expressing DATI and both DATI and CHA. Cell counts of two different classes of neurons in Canton-S adult flies: DATI CHA double-positive cells and DATI-only positive cells. Light grey bars represent counts from scans made from the front of the central brain; black bars represent counts from scans made from the rear of the central brain. Automated cell counts were performed in Fiji as described in Materials and Methods.

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Figure 3.7- The FYT system. The FYT system works in a manner similar to traditional MARCM, but with a reciprocal translocation bringing the fourth chromosome to the end of the second chromosome containing a centromeric FRT site. In this system, each cell has a heat shock-inducible source of Flippase on the X chromosome (not shown), plus two copies of the fourth chromosome (blue boxes), one carrying a mutant allele dati1 (asterisk) and the other carrying a wild-type copy translocated to the second chromosome. The second chromosome with the appended fourth chromosome contains an FRT site for somatic recombination, a y+ transgene to mark external tissues, and a ubiquitous source of the Gal4 repressor, Gal80 (red box). The homologous second chromosome carries an FRT site and a ubiquitous source of Gal4 (grey arrow) driving UAS-GFP (green box), which is repressed by Gal80. The induction of Flippase by heat shock (not shown) in a dividing cell removes the Gal80 repressor and generates two types of daughter cells. One that expresses GFP (green cell) and is hemizygous for a fourth chromosome bearing the mutation of interest, and another cell that dies due to aneuploidy (grey cell).

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Figure 3.8- Mapping regions of the brain where dati is required for normal acceptance using the GAF/FYT system. (A and B) Frequency of marked dati1 clones in the brains of rejecting (red) and accepting (blue) females. Analysis of brains is divided into anterior (A) and posterior (B), and subdivided by regions corresponding to the maps seen in (C, D). The statistical significance of differences between accepting and rejecting clones was evaluated by the Fisher's exact test. The p values are indicated in the figure. Brain images are maximum intensity projections of confocal stacks rendered in Zen 2009.

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Figure 3.9- Detailed view of DATI/CHA double-positive cells in the three foci implicated in female acceptance as revealed by clonal analysis. (A) A schematic frontal view of the brain where the antennal lobes (AL), the calyx (CA), and the lateral horn (LH) are indicated. The square indicates the position of the focus AntB2 indicated in (C). The trajectories of two projection neurons towards the lateral horn (black and blue line) and a projection of an LN are shown (grey line). The cell bodies around the antennal lobe are depicted as empty circles and the Kenyon cells as red circles. (B) Schematic rear view of the brain with the same three neuropiles and the Kenyon cells indicated in (A), the position of the foci PosA3 (upper square) and PosC4 (lower square). Cell bodies in the lateral horn are shown as empty circles. (C) Frontal maximum intensity projection of the antennal lobes as depicted in (A) with DATI protein stained in magenta, Cha-Gal4 UAS-mCherry.NLS in green, and the overlap between the two in light magenta or white (small circles). To determine the overlaps in a single image, the beginning and end of the double-labeled nuclei were identified in the z- stacks and a circle was drawn around the nucleus of the maximum intensity projections. In most cases the overlaps can be seen in the maximum intensity projection, but in a few cases this is not evident. The lateral and dorsal orientation of the neuropiles in (C) and (D) are indicated in the figure. Quantification of cell numbers and sample sizes are indicated in text.

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Figure 3.10- Homozygosity for dati1 causes loss of cholinergic projection neurons in the antennal lobe. (A) The location of the antennal lobe in the brain (blue square). The cell body of a single lateral cholinergic projection neuron is indicated (black circle). Some cholinergic neurons in this position connect to the antennal lobe neuropile, which include the glomerulus DA1 (red, also shown in B and C) and the lateral horn (line in black). (B) Frontal view of a wild-type antennal lobe with the glomerulus DA1 highlighted in red by 3D segmentation and the glomerulus DL3 (asterisk). The dashed lines indicate the area occupied by the neuropile of the mutant in (E) and the square lateral neurons expressing CHA. (C) The same antennal lobe in (B) viewed from the brain outwards. The DA1 glomerulus (red) and the glomerulus DL3 (asterisk) are indicated. Arrows point to lateral neurons. (D) Side view of a wild-type antennal lobe. The square indicates lateral neurons expressing CHA, the asterisk the position of glomerulus DL3 (not visible from this angle), and the heart shape outlines the position of DA1 shown in (G). (E) Frontal view of a dati mutant brain, highlighting the antennal neuropile (dashed lines), the position of the glomerulus DL3 (asterisk), the glomerulus DA1 (also segmented in red to the left of DL3, but not visible from this angle in the 3D rendering), and the lateral neurons (square). Note that the antennal lobe neuropile in (E) is smaller than in (B), which indicates defects in innervation. Also note that the neurons in the square in (B) are smaller than those in (C). (F) Mutant antennal lobe in (E) viewed from the brain outwards. Asterisks indicate glomerulus DL3, red indicates glomerulus DA1, and arrows point to lateral neurons. Note that the size of DA1 in (F) is smaller than in (C) and that the lateral neurons are larger in (F) than in (C) (arrows). (G) Side view slightly from the top of another antennal lobe mutant for dati1. The DL3 (asterisk), DA1 (red), and lateral neurons (square) are indicated. Note that the neuropile where DA1 is indicated in (G) appears darker than other parts of the antennal lobe and also darker than the corresponding region in (D) (heart-shaped outline), indicating that this region is less dense. Also note that the density of lateral neurons in (G) (square) is smaller than in (D) (square). Images are 3D projections of confocal stacks rendered in Fiji. (H) Quantification of DA1 volume in the wild-type and mutant. Error bars indicate SEM. * indicate p<0.05, and the samples sizes are Canton-S, N = 6 and dati1, N = 6. The coordinates P (posterior), A (anterior), D (dorsal), V (ventral), L (Lateral), and C (Central) are indicated.

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Figure 3.11- Homozygosity for dati1 causes abnormal distribution of cholinergic neurons and improper innervation of the lateral horn. (A) Wild-type female brain expressing GFP under the control of Cha-Gal4. The image is a single frontal confocal slice at the level of the lateral horn. The lateral horn (LH), the medulla (Me) and lobula (Lo) are indicated. Note the density of cholinergic neurons in the region between the lateral horn and optic lobe (arrow). (B) Frontal confocal slice of adati1 female brain expressing GFP under the control of Cha-Gal4 in approximately the same position shown in (A). Note increased numbers of CHA+ cells (arrow) and enlarged cells (yellow arrowheads). (C, D) Orthogonal view of the region shown in (A, B). CHA+ cells are labeled in green, and the neuropile is labeled with nc82 antibody (magenta). (C) Wild-type. (D) dati1 mutant female. Note again the excess of CHA+ cells in (D) compared to (C, brackets). Image rendering in orthogonal views in (C, D) were done in Image J.

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Figure 3.12- dati mutants exhibit defects in the trajectory of projection neurons. (A) A wild-type brain and (B) a dati1 mutant brain viewed from the brain neuropile towards the rear surface of the brain. In both images, 3D-rendered images were superimposed to 3D segmentation of the major cholinergic tracts (magenta). The lateral horn (LH) is indicated by the dashed circle. (C and D) Isolated segmentations of the major cholinergic tracts of the brain shown in (A and B, respectively) viewed from the rear brain surface. Note the thickness and complexity of the cell projection coming from the antennal lobe in (C) (red bracket) and the thinner and ill-defined projections in dati1mutants (D) (red bracket). The coordinates P (posterior), A (anterior), D (dorsal), V (ventral), L (lateral), and C (central) are indicated.

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Figure 3.13- Nuclear GFP and nuclear RFP have comparable rates of degradation. Fluorescent signals of nuclear GFP and nuclear RFP driven by the same ubiquitin promoter in the adult brain were captured and quantified. (A) A high- magnification confocal slice of the antennal lobe. The GFP and RFP pixel intensity values were collected along the white arrow. (B) Greyscale view of GFP.NLS expression from (A). (C) Greyscale view of RFP.NLS expression from (A). (D) Quantification of signals captured along the line shown in (A). Note that the levels of RFP and GFP are similar across the intensity peaks and valleys in contrast to when nuclear bar coding is performed (i.e., Figure 3.9).

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Figure 3.14- dati is expressed in neurons that have small and large volumes. (A) Maximum intensity projection of a confocal stack showing an antibody staining of a wild-type brain co-expressing nuclear RFP (red) and GFP-S65T (green) under Cha-Gal4 control. Neurons with large volumes (i.e., with long-range projections) appear with a gradation of dark orange to red (arrowhead; descending neuron), whereas neurons with small volumes (i.e., with short-range projections) appear as yellow to light orange (arrow). (B) Ratios of pixel intensity of the RFP and GFP channels of individual nucleus of the red and yellow neurons seen in (A) across all confocal slices encompassing their nuclei. Note the higher ratio of red/green from the red neuron with long processes, compared to the yellow neuron across each slice, indicating that the levels of GFP in the nuclei of long-range neurons are lower than in short-range neurons. Compare with results of the control experiment shown in Figure 3.13. (C) Overall view of the central brain. Anterior–dorsal projection neurons appear as dark red (adPNs, dotted line indicated by arrow), consistent with their long projections. LNs appear as light orange/yellow (dotted line indicated by arrowhead). (D) Superimposition of the channel detecting signal for anti-DATI staining (blue) to the image in (C). Note that adPNs appear in purple, indicating that these cells with long projections also express DATI (dotted line indicated by arrowhead). (E) High magnification of AntB2 region (box in D). DATI is expressed in cells with both small and large volumes, as indicated by color bar legend shown on the right. Neuron cell types are indicated by arrows and arrowheads, as explained in color bar legend. 3D image rendering was done in Image J.

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Chapter 4:

Conclusions and Future Directions

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4.1- dati and the Neural Circuitry of Courtship Acceptance

Female receptivity in Drosophila has been singled out as a model behavior in which to study the mechanism and genetics of signal integration for over fifty years

(Bastock, 1956; Ewing, 1964; Manning, 1967). But until very recently, little was known of the circuitry underlying female receptivity, other than that it resided in the central brain

(Tompkins & Hall, 1983), and that a number of genes affecting receptivity were expressed there (Ditch et al., 2005; Finley et al., 1998; Nakano et al., 2001). The first recent breakthrough in an attempt to trace this circuit came with the demonstration that neurons expressing Or67d detected male pheromones and were required for proper female acceptance (Kurtovic et al., 2007). The discovery of these sensory neurons established a link between a gene and the concrete neural origin of courtship signals in the nervous system, namely the first order neurons of the courtship circuit. By this time, a map of the second order neurons of olfaction had already been established

(Marin et al., 2002), which showed that the projection neurons of the antennal lobe contact ORNs at glomeruli and send projections to the mushroom body calyx and lateral horn. With the morphology of second order olfactory neurons already mapped, the groundwork was laid for finding the subset responsible for conveying courtship information. Mosaic analysis of the gene spinster would lead to the discovery of the spin-D neural cluster, a group of second order projection neurons which required the expression of spinster to allow for proper receptivity (Sakurai et al., 2013). Soon after, our mosaic analysis of dati would implicate a similar (and possibly the same) neural

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cluster in receptivity, as focus AntB2, establishing multiple genetic markers for second order neurons of a courtship receptivity circuit (Schinaman et al., 2014). In much the same way, the third order olfactory neurons were mapped to some degree before their role in receptivity was demonstrated. An enhancer trap screen first showed that contact the area of olfactory convergence in the lateral horn, regions of auditory convergence in the ventrolateral protocerebrum, and higher order brain centers such as the superior medial protocerebrum (Tanaka et al., 2004). Our work would then show that loss of dati from neurons of the lateral horn lead to increased rates of rejection, implicating 3rd order neurons of olfaction and possibly audition in receptivity

(Schinaman et al., 2014). The importance of this result was heightened by the concurrently published analysis of doublesex enhancer fragments, which showed that the pC1 neural cluster is necessary and sufficient for stimulating receptivity, and is also responsive to both auditory and olfactory courtship cues (Zhou et al., 2014). This cluster resides within and sends projections throughout the target region of lateral horn neurons, the superior medial protocerebrum. The pC1 cluster has the correct location and physiological response to stimuli consistent with what we would expect from a fourth order neuron of the courtship circuit. As such, our work, along with these other recent advances, establish a putative 4 neuron circuit from stimulus to sensory integration, with discrete genes controlling the functions for the 2nd, 3rd, and 4th order neurons (Figure 4.1). In this proposed circuit, the binding of the male pheromone cVA activates Or67d positive odorant receptor neurons, which synapse on to the DA1 glomerulus (Couto et al., 2005; Kurtovic et al., 2007). At this glomerulus, these neurons

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contact a population of spin and dati positive projection neurons (Sakurai et al., 2013).

These neurons are likely modified by an undefined cluster of Kenyon cells of the mushroom body, which would provide some degree of experience based modulation of this olfactory signal (de Belle & Heisenberg, 1994; Heisenberg et al., 1985). These dati/spin neurons would then project past the mushroom body to the lateral horn, where they synapse with one or more excitatory, dati positive neurons (Marin et al.,

2002; Sakurai et al., 2010; Schinaman et al., 2014). These third order neurons likely receive both this olfactory input, as well as auditory input from a cascade of neurons at the ventrolateral protocerebrum (Tanaka et al., 2004). These signals are then conveyed as excitatory information to dsx positive neurons of the superior medial protocerebrum, which can sum these signals temporally, and activate a further, unknown downstream cascade of neurons which control receptivity (Zhou et al., 2014). In sum, this work, alongside these other recent advancements, sets up for the first time a testable model to further study the exact neural circuitry and physiology of multimodal sensory integration and binary choice in a model system.

4.2- Revisiting the Summation Hypothesis

In light of the data of this work and the recent advances noted above, we can begin to revisit early hypotheses about courtship acceptance behavior, incorporating genetic and physiological insights not possible at the time they were first proposed

(Manning, 1967; Sakurai et al., 2013; Schinaman et al., 2014; Zhou et al., 2014). The summation hypothesis, which posited that the behavioral change from rejection to

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acceptance was the result of continuous excitation from multiple modalities, summed temporally in the brain past a threshold level, garnered early support when it was proposed in the 1960s (Cook, 1973; Ewing, 1964; Manning, 1967), but fell out of favor when several experiments could not be replicated in the ensuing decades (Robertson,

1982). However, our results, along with the recent work with doublesex and spinster, support this early view (Sakurai et al., 2013; Schinaman et al., 2014; Zhou et al., 2014).

Interestingly, all three investigations found evidence suggesting that the relevant neurons in the pathway are cholinergic, the primary excitatory neural class of the

Drosophila central nervous system, a putative chain of excitatory signals from stimulus to integration point. Furthermore, the study work in doublesex found that pC1 neural cluster was not only responsive to both song and pheromones as measured by intensity of a calcium indicator, but demonstrated that firing in response to song was stronger while in the presence of pheromones (Zhou et al., 2014). Whether this is due to two separate neural populations being activated by the different stimuli in the same region, or the same population of neurons summing the stimulation could not be conclusively distinguished, but in either case, it provides some evidence for neural summation occurring (in the first case, two separate pC1 neuronal populations are converging on the same neurons performing the summation, in the latter, these neurons would be performing the summation themselves). Thus, our work and recent work of others not only provide a testable connectivity map of the circuitry of courtship, but also some insight into the mechanism as to how these connections respond to stimuli and generate a behavioral switch.

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4.3 - Future Directions for Investigating the Neural Circuitry of Receptivity

While the proposed circuit highlighted above is a plausible interpretation of the best available data, most of the relationships between these neural populations remain to be tested. As one focus of dati overlaps a relevant focus for spinster, and the posterior dati foci are expressed near several cluster of dsx positive neurons, the simplest starting point would be to establish what coexpression, if any, exists between spin, dsx and dati. Antibodies are available for all three genes, so double labelling experiments between Spin/Dati and Dati/Dsx will reveal by colocalization whether or not coexpression is occurring in any of the dati receptivity foci, by a method similar to that used to colocalize dati and cha in Chapter 3.

Establishing synaptic connectivity between neurons will be more difficult, but several inroads can be readily made. Due to the highly tractable structure of glomeruli, the connection between first and second order neurons would be simplest to demonstrate. As pheromone responsive ORNs are known to fill discrete glomeruli

(namely, DA1, as well as VA1lv) (Couto et al., 2005), one would only need to determine if dati or spin positive projection neurons have arborizations in one or both of these glomeruli. If a dati-Gal4 line were generated, this would be relatively simple task (and several spinster-Gal4 lines are available). These lines can then be crossed to a membrane bound GFP, or a cytoplasm filling GFP, similar to the one used in cholinergic neurons in Chapter 3. As only first order sensory neurons and second order antennal lobe neurons contact glomeruli, if any GFP expression is seen in the DA1 or VA1lv

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glomeruli, it can be reasonably attributed to dati (or spin) expression in one of those two neural populations. To discern between gene expression in second order neurons, as we expect to find, and first order sensory neurons, GFP expression in first order neurons could be selectively blocked by expression of the repressor Gal80 in the pattern of Or83b, the universal coreceptor found in all ORNs (Joo et al., 2013). As an alternative to this approach, a mosaic analysis could be carried out with a dati- or spin-Gal4, in the attempt to label individual projection neurons innervating either glomerulus. This would have the additional benefit of revealing the morphology of any dati- or spin-positive projection neurons, as projection neurons from the two glomeruli of interest are innervated by both excitatory PNs that contact the mushroom body and lateral horn, and inhibitory PNs that bypass the mushroom body and contact only the lateral horn

(Jefferis et al., 2007). Our results suggest that only the loss of dati-positive excitatory neurons are required for acceptance behavior, but dati or spin could very well be expressed in both excitatory or inhibitory PNs in other roles besides courtship acceptance.

Establishing connectivity in higher order brain presents several challenges.

Higher order neurons do not form structures with as highly tractable neuropils like the glomeruli of the antennal lobe, where anatomical overlaps in cell projections are predictors of synaptic connection (Stocker, 1994). However, second and third order neurons do have some neuropils with relatively stereotyped points of contact within the lateral horn (Jefferis et al., 2007; Tanaka et al., 2004). While not as ordered as glomeruli of the antennal lobe, the lateral horn does show a degree of organization and has been

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extensively mapped (Tanaka et al., 2004). The lateral horn is ordered such that the projections of second order neurons relaying pheromonal inputs are spatially segregated from those of all other odors, with pheromonal inputs innervating the most anterior portion of the lateral horn exclusively (Jefferis et al., 2007). An earlier study focusing on the third order neurons of the lateral horn discovered six gal4 lines in a collection of four thousand labelled distinct neurons that innervated the lateral horn

(Tanaka et al., 2004). While these expression patterns were not revealed in this publication, these six lines could prove useful if they were found to innervate the most anterior portion of the lateral horn, and thus likely form connections to pheromonal second order neurons (Tanaka et al., 2004). If any of the lines are found to label neurons forming projections to this region of the lateral horn, mosaic analyses of these lines could be carried out to reveal the projection patterns of singular neurons. Such an analysis could be tied with antibody staining for DATI, in order to attempt to reveal dati positive lateral horn neurons with single cell resolution, which project to the areas of convergence of pheromone signaling. While this would still fall short of formally proving a synaptic link, it would be a groundbreaking result in terms of mapping the putative courtship circuit. This analysis would of course reveal all other downstream projections of these singular neurons as well. Whether or not these neurons project into the superior medial protocerebrum, the region innervated by doublesex neurons integrating courtship cues, as our proposed model suggests, would be immediately apparent as well.

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4.4- Further analysis of receptivity

Up to this point, the discovery of neurons involved in receptivity in Drosophila has been the end product of analysis of mutations in genes that disrupt acceptance.

Therefore, for this circuit to be further elucidated, it is imperative to continue to discover new genes and to reappraise previously discovered genes using modern techniques. How are new receptivity genes discovered? Some have been uncovered by keen observation. Dati, for example, was discovered as a part of a mapping experiment using known deletion lines, in which each deletion was also rigorously analyzed for potential phenotypes. Other genes, such as spinster, have been isolated as a result of dedicated, unbiased screens for behavioral phenotypes caused by mutagens or p- element insertions. Although effective, screening for adult behavioral phenotypes can be time and labor intensive. If we are to screen for receptivity genes, how can it be done most efficiently? Is there a way to bias the selection of candidate genes for screening to be more likely to be involved in mate choice? The study of receptivity behavior gives us a unique opportunity to exploit such a bias. In closely related species of flies, sexually naive males court females outside their own species indiscriminately, whereas virgin females must be able to discriminate against males of another species instinctually. It stands to reason then that between two genetically similar but distinct species, the greatest genetic differences are likely those that maintain speciation, such as female choice. It is even reasonable that heritable female choice for a trait is the singular

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genetic difference that causes a speciation event. As such, we would expect genes involved in mate choice to have undergone a greater number of genetic changes in closely related species relative to their genomes as a whole. This logic was the basis for finding several mate choice factors that exist between Drosophila simulans and

Drosophila sechellia, two very closely related species which diverged only .5 million years ago (Chu et al., 2013; Sousa-Neves & Rosas, 2010; Tamura et al., 2004). The method for extracting ancestral alleles, genes similar between simulans and sechellia but divergent in melanogaster (Sousa-Neves & Rosas, 2010), could be easily adapted to find genes rapidly diverging between all three species, a list likely enriched with genes influencing receptivity. By screening for receptivity defects only the likeliest genes to be involved rather than the genome as a whole, the rate of receptivity gene discovery and analysis should be greatly accelerated.

While new gene discovery is a priority, there remain a number of previously isolate receptivity genes that warrant investigation to the degree to which spin, doublesex, and dati have been analyzed. As discussed in Chapter 1, retained, dissatisfaction, and chaste are all promising genes whose negative effects on receptivity have not been analyzed systematically (Ditch et al., 2005; Finley et al., 1997; Juni &

Yamamoto, 2009). And while mutations such as chaste cause numerous pleiotropic effects (Juni & Yamamoto, 2009), our work and that of spinster and doublesex show that modern techniques can dissect out relevant phenotypes from ones not being considered (Sakurai et al., 2013; Schinaman et al., 2014; Zhou et al., 2014). Spinster’s effects on glia and neurons could be studied in isolation via targeted RNAi (Sakurai et al.,

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2013), as was dati’s effects on locomotion vs. receptivity (Schinaman et al., 2014).

Furthermore, both studies isolated neural subpopulations via mosaic analysis. The study of doublesex’s role in neurons circumvented its effects in other tissues by limiting targeted expression to that of small enhancer fragments, used also to isolate neural populations (Zhou et al., 2014). If neglected behavioral genes are to be reappraised with these modern techniques, and indeed new ones are to be discovered, which techniques will prove the most useful? On the surface, clonal analysis and enhancer fragment analysis appear similar: both are used to isolate patches of tissue for manipulation in otherwise wild-type animals. However, their approaches are quite different. Clonal analysis generates random patches of manipulated tissue in each animal, making every experimental animal different. Enhancer fragment analysis establishes stocks of flies with repeatable expression patterns that can be used to drive genetic manipulations, making every experimental animal from a given line the same, and areas of interest are then found by screening a number of such lines for phenotypes. Each method has its advantages and drawbacks, and the proper technique must be chosen based on the characteristics of each gene. The repeatability afforded by the use of enhancer fragment lines has obvious appeal in that once a line generating an interesting effect under a certain genetic manipulation is found, its significance can be assayed by performing replicates of the same experiment. Furthermore, since different manipulations can be performed on the same neurons in different animals, experiments to establish necessity and sufficiency of the neurons to the behavior being studied are straightforward.

Necessity of the neurons in a behavior can be demonstrated by shutting them off

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genetically (via tetanus toxin, shibire, expression of hyperpolarizing ion channels) and showing a decrease or abolishment of the behavior. Neurons can be shown to be sufficient for a behavior by hyperactivating them (using heat sensitive or photoactivatable ion channels) and showing that the behavior is performed more readily, or in the absence of stimuli. Due to these advantages, this paradigm has been used to isolate neurons require for receptivity, aggression and grooming (Asahina et al.,

2014; Seeds et al., 2014; Zhou et al., 2014). However, this method has several caveats.

First, the enhancer fragments frequently drive expression in areas outside the gene of interest’s normal expression pattern, and as such do not neatly define biologically relevant subsets of normal expression (Vicente-Crespo et al., 2008). This is likely due to enhancer fragments being expressed in isolation from suppressor elements which are part of the normal regulation of the gene of interest’s expression. In the work on doublesex, this was overcome by restricting the expression of the enhancer elements to just the cells where doublesex itself is normally expressed, i.e. at the intersection of the two expression patterns (Zhou et al., 2014). As the paper proves, this is a workable approach, but this increases the number of reagents required (as one expression pattern is likely to use the common Gal4 system, the intersecting pattern must use one of the much less common driver systems such as LexA, QS, or a promoter specific FLP line, which will likely mean generating a new construct and transforming flies), as well as the complexity of crosses to be performed. As there is also a constraint to how many

“intersections” can be placed in such a system, if revealing a biologically relevant subset of neurons requires the intersectional driver to be just the expression pattern of the

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gene itself, this precludes the use of more interesting intersectional lines being used, for example to look for only cholinergic or dopaminergic neurons within the enhancer subset, or those expressing a certain transcriptional regulator. Furthermore, this method cannot divide an expression pattern infinitesimally, as each gene has a finite number of enhancer elements that can be used to individually drive expression. In the case of doublesex, this was not an enormous concern: Its normal expression in the brain is confined to around 60 neurons in discrete clusters, so sparse expression can be expected once it is divided into its 17 enhancer fragment lines. However, such a method could not reasonably divide a gene like dati, expressed in ~3000 neurons spread fairly evenly across the brain, into similarly manageable chunks with a similar number of fragments (Schinaman et al., 2014). One solution to this is to screen enhancer fragments from many different genes en masse, many of which have very sparsely labelled lines.

However, this abandons the premise that the lines defined relevant subsets of gene expression entirely, and with 5982 lines currently available (Jenett et al., 2012), a comprehensive screening can quickly become a daunting task that may be outside the means of many researchers. As such, while there are certainly tasks to which this research paradigm is reasonably amenable, it is not a singular approach to discovering neurons underlying behavior. The technique of mosaic analysis can overcome some of these limitations. Generating clones in random patterns sacrifices repeatability, but gains the advantage of being able to achieve coverage of the entire brain within a single experimental cross, so long as enough replicates are performed. This overcomes the logistical concerns of having to perform potentially thousands of crosses to find the right

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subset, with the worst case scenario being that none of the lines contains exactly the right subset. With an unbiased mosaic analysis, if the behavior is certainly mediated by the nervous system (easily testable prior to a clonal analysis by performing a knockdown with a neuronal specific driver), and the clones are truly random and capable of generating complete coverage of the nervous system, the pattern will emerge with enough data. This approach however has its own limitations. Genes with only partially penetrant effects, such as those that reduce but do not abolish acceptance, would be difficult to assess by mosaic analysis. Another disadvantage is that interesting expression patterns yielded by mosaic analysis may be difficult to replicate, due to the random nature of clone generation. This however is where there is the most synergy between classical mosaic analysis and the more recent enhancer fragment techniques.

An initial mosaic analysis can be performed to inform the driver selection for enhancer trap analysis. Once an unbiased mosaic analysis highlights areas of interest, driver lines from the large, annotated collection of enhancer fragments can be selected for sparse expression in these regions. Thus, mosaic analysis can be used to rule out the majority of lines before any are screened, with the only selection bias being that of the unbiased initial results. This method could be applied to a follow up analysis of dati, to attempt to further isolate the discrete neural population in which dati is required for normal acceptance from the three, relatively broad, candidate foci. This could also be applied to great effect to the chaste, given that it has a strong receptivity phenotype but exhibits significant pleiotropic effects. It would be of great interest to see if chaste exerts its effects alongside one of the genes in the known neural populations shown in Figure 4.1,

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or if it perhaps specifies a population of one of the hypothesized neural pathways for which no genetic determinants or markers have been found. Retained also warrants renewed interest. Retained is expressed in the mushroom bodies, a region with known synaptic connection into the receptivity circuit, as well as the suboesophageal ganglion, which contains another focus of spinster mediated receptivity. Given its smaller expression pattern and weaker receptivity phenotype, it may be suitable for enhancer fragment analysis directly. In sum, there is a wealth of tools available to reevaluate known receptivity genes and to analyze new ones as they emerge, but there is currently no singular approach amenable to each gene. For new discoveries to be made efficiently, the approach should be tailored to the specifics of each gene.

4.5- The Molecular Mechanism of the dati Gene in Cell Specification

While the major focus of this work has to been to use dati’s behavioral phenotypes to investigate neural circuitry, in so doing it has also given some insight into the cellular and molecular roles of the dati gene itself. dati was previously described as one of a number of transcription factors involved in specification of neuroblasts and non-self-renewing progeny, ganglion mother cells (GMCs). These transcription factors were found to be expressed in a sequence that advanced at each cell division, with the first neuroblasts and their resultant GMCs expressing Kruppel, the progeny of those neuroblasts, and their GMCs, expressing Hunchback, and so on (Figure 4.2A) (Tsuji et al.,

2008). This paper also found that if embryos were unable to express one of the transcription factors in the sequence, the sequence would arrest at that of the final

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functioning transcription factor, leading to downstream neuroblasts and GMCs adopting an “earlier” fate (Tsuji et al., 2008). This result is consistent with our observation that dati mutants have expansions in some cell lineages and loss of cells in others. In the anterior brain, dati mutants exhibit a loss of cholinergic neurons in the antennal lobe which normally form projection neurons (Schinaman et al., 2014). It is possible that in anterior neuroblast lineages that pattern projection neurons, dati functions to shift

GMCs into fates that form cholinergic neurons away from those that form other cell types, and the loss of dati either arrests cells in an early, non-cholinergic fate, or leaves

GMCs with an expression profile uninterpretable by developmental mechanisms, and as such they undergo apoptosis. On the other hand, the posterior neuroblast lineages that form the lateral horn neurons have an expansion of cholinergic cells in dati mutants relative to wild-type. This suggests in posterior lineages that dati normally functions to shift GMCs from a specification yielding cholinergic neurons to one yielding other cell types, and in the absence of the dati protein, GMCs become arrested in the cholinergic fate and inappropriately form ectopic cholinergic neurons. However, the exact role of the dati gene product in neuroblasts and in GMCs remains unknown.

In order to investigate the role of dati in GMC specification past the embryonic stage, we can use tools developed initially to study the neuroblast lineage of the antennal lobe. These studies isolated several enhancer trap lines that selectively label certain populations of antennal lobe neurons. One enhancer trap line in particular, known as GH146-Gal4, has been used to map the projection neurons by clonal analysis.

This line labels around 90 neurons in the antennal lobe, ~94% of which are cholinergic,

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and is expressed in around two thirds of projection neurons, with the onset of expression occurring in prior to neuron specification (Lai et al., 2008; Prieto-Godino et al., 2012; Shang et al., 2007; Stocker et al., 1997). As dati is required in cholinergic neurons of the antennal lobe, in all likelihood dati is expressed in some subset of these neurons, which could be confirmed by antibody staining of the GH146-Gal4 driver line crossed to a reporter such as GFP. If dati is indeed facilitating a transition to a cholinergic fate in a subset of these neurons, we would then expect that dati knockdown in this driver via RNAi would either reduce the number of GH146-positive cells altogether (showing the lack of proper specification by dati leads to cell death), or alter the percentage of them that are cholinergic (showing the lack of dati leads to altered cell fate). Similarly, we would expect that if dati induces a cholinergic fate in lineages forming the antennal lobe, ectopic expression of dati during earlier fates in these lineages should force GMCs to form such neurons at the expense of others. This could be assayed if a stable UAS-dati transgene was developed. Other driver lines in the antennal lobe, such as GH298-Gal4 and acj6-Gal4, give rise to a diverse array of both cholinergic and GABAergic neurons (Lai et al., 2008; Stocker et al., 1997). If these lines were made to drive ectopic expression of UAS-dati, we would expect them to yield a reduced number of GABAergic neurons and an increased number of cholinergic neurons. These experiments would elucidate dati’s mechanism in cell fate specification, with the added advantage of showing this role in a behaviorally relevant population of neurons. It would also be interesting to see if manipulating the expression of dati in this region alone is sufficient to influence receptivity.

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Furthermore, it would be interesting to establish if dati acts directly to pattern neurons for a certain role in the receptivity circuit, or indirectly by influencing the growth and proliferation of doublesex- or spinster-positive neurons. The antibody colabelling experiments proposed earlier would give us some insight into this, by at least establishing whether or not dati is coexpressed with either gene, a prerequisite for genetic or epistatic interaction. A more direct experiment to compliment this would be to stain for doublesex and spinster in dati1 homozygous females and heterozygous controls, to see if the misspecification/overproliferation phenotypes lead to the gain or loss of neurons positive for these genes. If the loss of dati does not appear to influence either cell population, this would support the idea that dati specifies an independent and unique set of neurons in the receptivity circuit, an interesting role for the new gene.

If dati does appear to influence these populations of neurons, it could also mean that dati acts upstream of doublesex and spinster, using these genes to orchestrate a larger receptivity circuit. The penetrance and strength of the dati1 phenotype are certainly extensive enough to account for dati filling such a role as a master regulator of courtship. It is also expressed in roughly the same broad pattern and number of neurons as fruitless, which performs the role of master regulator of the sexual behavior circuit in males, but which has no known analog in females (Schinaman et al., 2014; J. Y. Yu et al.,

2010). Further insight to this could be gained with the generation of a dati-Gal4, which could be used to drive expression of membrane bound GFP. A high resolution image of the projections of all dati neurons could establish, at a minimum, whether dati positive cells form some sort of closed loop circuit as do fruitless neurons (Yu et al., 2010), or if

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clusters of dati cells are synaptically isolated from one another. If such images label too many overlapping tracts to be conclusive, techniques that allow fluorescence only when synaptic connections are present, such as GRASP, could be used instead (Feinberg et al.,

2008). While these results in sum would not be conclusive proof that dati is a master regulator of female behavior, they could at least rule out such a possibility, and as such guide further study. There are other further questions about the dati gene that would be of interest, regardless of whether or not it forms a circuit. One would be whether or not dati exists as different isoforms, and if so, if these different isoforms have different roles. The Flybase records show four different possible translations of the dati gene, each of which could correspond to an isoform. Of particular interest would be if one or more isoforms regulate the role in receptivity, while another set of isoforms has a more basic function, perhaps in locomotion. Such a system would not be unprecedented, as fruitless has male specific isoforms that only regulate sexual behavior, as well as isoforms common to both sexes which are lethal when knocked out (Song et al., 2002).

Targeted mutagenesis could be employed to make alleles of dati that affect only a subset of the isoforms, in order to begin to study their individual effects on both cell patterning and behavior. Similarly, specific probes could be developed to determine the individual expression pattern of each isoform. These experiments would open up new avenues for our understanding of both development and behavior, and may yield novel insights into how early developmental events pattern neurons to give rise to behavioral paradigms later in life.

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Figure 4.1- Schematic representation of the putative receptivity circuit in Drosophila

The results of several recent publications associating the receptivity phenotypes of genes to different neuron populations suggests a putative circuit underlying courtship acceptance. The odorant receptor Or67d is expressed in neurons of “T1” trichoid sensilla and fire in the presence of the male pheromone cis-vaccenyl acetate. These T1 sensory neurons project to the glomeruli of the antennal lobe, where populations of projection neurons require dati and spinster in regions labelled AntB2 and Spin-D for proper courtship acceptance to occur. Projection neurons such as these connect to Kenyon cells of the mushroom body, where odor associated memories are formed, and project into the lateral horn, where two other neural clusters must be dati positive for proper receptivity. Lateral horn neurons receive inputs from antennal lobe projection neurons, as well as neurons from that process sound, and send projections into the superior medial protocerebrum. The superior medial protocerebrum is innervated by a cluster of doublesex positive neurons that fire in response to both cVA and the playback of courtship song, and whose activation stimulates female receptivity. The downstream neurons that mediate the behavioral response to this change in receptivity have yet to be determined.

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4.2- Proposed cellular mechanism by which dati establishes neural cell fates

Neuroblasts (top row) divide to form a daughter neuroblast (curved arrow) and a Ganglion Mother Cell (second and third row, boxed), which will give rise to neurons or glia (not shown). Neuroblasts express a specific set of transcription factors (indicated by coloration) which leads to a certain expression profile in GMCs, and advances each generation. These factors then confer certain cell fates to GMCs. In this example, based on an embryonic lineage, we see that the first six populations of GMCs do not require dati for proper fate specification and the developing brains of dati1 homozygous and wild-type animals will initially both develop identically. However, after the sixth division, dati is required for proper specification, and GMC lineages 7-11 homozygous for dati1 receive a different fate signal than their wild-type counterparts. In this example, late born dati1 homozygous GMCs would receive fates not seen in any wild-type GMCs, and as such these may either form inappropriate cell types or undergo apoptosis. Adapted from Tsuji 2008.

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