SEXUAL DIMORPHISM IN DROSOPHILA CUTICULAR HYDROCARBONS AND THEIR ROLES AS MATING SIGNALS By Haosu Cong A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Entomology – Doctor of Philosophy 2024 ABSTRACT Sexual dimorphism exemplifies the remarkable diversity and aesthetic beauty in nature, with mating signals representing a key aspect of this phenomenon. These signals have evolved to encompass multimodal sensory modalities, and understanding their evolution necessitates exploring the complex interactions among various selective pressures. This dissertation examines the intricate relationship between sexual dimorphism and mating signals, utilizing cuticular hydrocarbons (CHCs) in Drosophila species as a model system. We investigated three pivotal questions: 1) Is there a correlation between the evolution of sexual dimorphism and the evolution of mating signals, and can the degree of sexual dimorphism predict the functional roles of these signals? 2) What genetic mechanisms underlie the evolution of exaggerated female traits? 3) What phenotypic trade-offs are associated with the evolution of mating signals? Employing the Bray-Curtis dissimilarity index, we initially assessed the degrees of sexual dimorphism in CHC profiles across Drosophila species and tested the impact of CHC perception on male courtship interest. Our findings did not support a correlation between the degree of sexual dimorphism and the use of CHCs for mate recognition. Next, we focused on a species exhibiting pronounced sexual dimorphism, identifying a candidate gene with female-biased expression in adult oenocytes, likely responsible for the production of exaggerated female traits. This expression pattern is attributed to cis- regulatory changes, characterized by two specific modules: one related to oenocyte expression and another to sex-biased expression. Lastly, the costs associated with producing methyl-branched cuticular hydrocarbons (mbCHCs) in transgenic D. mojavensis lines was tested. Our findings do not reveal direct developmental trade-offs associated with the production of mbCHCs, but suggest a positive correlation between mbCHC production and reproductive fitness. While mbCHCs are correlated to individual fitness, they have not evolved to function as reliable signals influencing mate preferences. This dissertation contributes to addressing unresolved questions regarding the evolution of sexual dimorphism and mating signals, offering novel insights into the genetic mechanisms and potential evolutionary costs associated with these traits. Copyright by HAOSU CONG 2024 This dissertation is dedicated to every one of you reading it. Thank you for engaging with my work and me. v ACKNOWLEDGMENTS This dissertation addresses several questions in the field of evolutionary biology. First, I would like to express my gratitude for the opportunity to stand on the shoulders of giants in this discipline. Mr. Zheng Wei from the Tang Dynasty in ancient China once said, “Reviewing the past enables us to learn about the laws governing the evolution of history” (以史为鉴，可以知兴替——【唐】魏徵). Studying evolution allows us to trace the entire history of our planet, which has been both inspiring and enlightening for me. I am especially grateful to my doctoral advisory committees at Michigan State University (MSU, East Lansing, USA): Drs. Henry Chung (my primary advisor, with special appreciation), Marianna Szucs, Zhiyong Xi, David Mota-Sanchez, and Matthew Grieshop, who guided me along this challenging yet fruitful path. I also thank my undergraduate research advisors at Northwest A&F University (NWAFU, Yangling, China), Drs. Yi Zhang, Xing-Xing Wang, and Tong-Xian Liu, who introduced me to the fascinating world of insects and molecular biology. I am grateful to the China Scholarship Council for financially supporting my dissertation research. Additionally, I appreciate the advanced technical tools available in this era of biological technology and information, which made my learning experience more enjoyable and accessible. I would like to give special thanks to ChatGPT for helping me correct my grammar while writing this dissertation. I would also like to express my appreciation to everyone who has trusted me on this chosen path and supported me in obtaining my degree: my mom, Shi Yan (严实), my dad, Jun Cong (丛军), and my other dear family members, as well as all my friends both in the States and back in China. I love you all, and I have watched you transform me vi from a boy into a man. I have always felt lucky and grateful to be part of great teams, including the Chung Lab at MSU, the Department of Entomology at MSU, the Liu Lab at NWAFU, the College of Plant Protection at NWAFU, the undergraduate students I mentored, my students in ISB201L, and the Society for the Study of Evolution Graduate Student Advisory Committee. Your energy has always brightened my days. One more special thank you goes to you, the reader of this dissertation. Thank you for engaging with my work and spending time reading it. No matter how insightful you may find my research, I wish you the best of luck in your future explorations of evolution, self-discovery, and life. Please feel free to reach out if you are interested in further discussions. Last and most importantly, I want to thank my past self. Thank you for being courageous in going abroad and completing this program. Thank you for managing the challenges you faced in your past. You did a great job, and you should be proud of yourself, as I now feel a sense of peace in my heart. You deserve a hug. A little note to my future self: I cannot imagine under what circumstances you would look back at this section, but please remember that I am happy, satisfied, and peaceful at this moment. I feel a bright future ahead, which I hope will empower you. Each day, I enjoy getting an iced coffee in the early afternoon, surrounded by blooming flowers, changing leaves, and butterflies, wasps, and lady beetles landing on my shoulder. My taste in music has shifted from C-POP girl group EDM to R&B. I love smiling at everyone I encounter on the street and wishing them good luck, whispering those thoughts in my heart. vii I have experienced the joy of spring rain, the annoyance of summer cicadas, the charm of fall breezes, and the dance of snowflakes. I cherish river, having been inspired since my trip to Cincinnati along the Ohio River, and I often walk along the Grand River Avenue and Red Cedar River. My favorite karaoke song now is “River” in Mandarin, as rivers have always brought me peace. So, future self, no matter what happens, I trust in you—we trust in you. Please continue to trust yourself and be proud of who you are. Life is a journey, and time is a river, both filled with surprises and excitement, flowing into our hearts. I am not waiting for spring or the sea, Just yearning for the same flower that blossoms in me. But it's hard to depict, So I weave tales of spring, And listen to whispers of the sea. When leaves not long for raindrops’ grace, The wind brings them down to kiss the earth's embrace. But when my heartbeat fails to match your palm’s rhyme, Know that you’re still needed by my arms, in time. I bet you dove too deep into the ocean of my gaze, Where waves of longing crash into silent, endless maze. viii CHAPTER 1. GENERAL INTRODUCTION ..................................................................... 1 TABLE OF CONTENTS Evolution of sexual dimorphism under complicated interactions of selective Using Drosophila as a model to investigate questions in evolution of sexual Evolution of diversified roles of mating signals under combinational selective 1.1 forces .......................................................................................................................... 1 1.2 forces .......................................................................................................................... 3 1.3 dimorphism and mating signals .................................................................................... 9 Courtship behavior of Drosophila .................................................................... 10 1.4 Drosophila cuticular hydrocarbons (CHCs) as mating signals ........................ 11 1.5 CHC biosynthesis in Drosophila ...................................................................... 13 1.6 1.7 Other roles of Drosophila CHCs ...................................................................... 16 Summary and research objectives .................................................................. 18 1.8 CHAPTER 2: SEXUAL DIMORPHISM IN CHCS AND THEIR ROLES IN DROSOPHILA COURTSHIP ................................................................................................................. 19 Introduction ..................................................................................................... 19 2.1 Results ............................................................................................................ 22 2.2 2.3 Discussion....................................................................................................... 30 2.4 Materials and Methods .................................................................................... 32 CHAPTER 3. GENETIC MECHANISMS UNDERLYING CHC EXAGGERATED DIMORPHISM IN FEMALE DROSOPHILA ERECTA ................................................... 36 Introduction ..................................................................................................... 36 3.1 Results ............................................................................................................ 42 3.2 3.3 Discussion....................................................................................................... 55 3.4 Materials and Methods .................................................................................... 59 CHAPTER 4. PHENOTYPIC TRADEOFFS OF PRODUCING COSTLY CHCS IN DROSOPHILA MOJAVENSIS ....................................................................................... 63 4.1 Introduction ..................................................................................................... 63 4.2 Results ............................................................................................................ 67 Discussion....................................................................................................... 73 4.3 4.4 Materials and Methods .................................................................................... 77 CHAPTER 5. GENERAL DISCUSSION AND FUTURE RESEARCH DIRECTIONS .... 80 Summary of the research projects .................................................................. 80 5.1 5.2 Evolution of mating signals: interactions among multimodal sensory modalities and plasticity with environmental change ................................................................... 82 5.3 characteristics ............................................................................................................ 84 5.4 Evolution of insect CHCs: other variations in CHC profiles and potential interdisciplinary collaborations ................................................................................... 85 Evolution of sexual dimorphism: further dissecting traits with specific BIBLIOGRAPHY............................................................................................................ 90 ix APPENDIX .................................................................................................................. 102 x CHAPTER 1. GENERAL INTRODUCTION 1.1 Evolution of sexual dimorphism under complicated interactions of selective forces Describing nature necessitates acknowledgment of its inherent beauty and diversity. Among the estimated 1.5 million species within Earth's biodiversity, over half are classified as insects (Stork et al. 2015). Insects display significant intraspecific diversity, characterized by a wide range of variations in shape, size, life history, and ecological niches. Sexual dimorphism, which refers to the differences between sexes, is a prevalent phenomenon in nature and can manifest in morphological, physiological, and behavioral traits. Our understanding of these ubiquitous forms of intraspecific diversity has prompted numerous studies over the decades, focusing on the traits and mechanisms that underlie evolutionary processes. In this dissertation, I aim to further investigate the evolution of sexual dimorphism, offering novel insights and understandings. Sexual dimorphism can be categorized into three types: primary, secondary, and ecological sexual dimorphism (Williams and Carroll 2009) (Figure 1.1A). Traits associated with primary sexual dimorphism are directly related to reproduction, such as reproductive organs and insect genitalia. In contrast, secondary sexual dimorphism refers to traits that are not directly involved in reproduction. Ecological sexual dimorphism arises when divergent ecological functions and niches are established between the sexes. The evolution of sexual dimorphism is complex, which resulted from two main reasons. First, intricate interactions among selective forces (e.g., between sexual 1 selection and natural selection) may influence the trajectory of the evolution of sexual dimorphism in multiple directions. Second, different stages of the evolution of sexual dimorphism can be driven by divergent selective forces, from its initial occurrence to its elaboration and maintenance at an optimal degree of expression. Figure 1.1 Introduction of (A) types of sexual dimorphism and (B) levels of information conveyed by mating signals. Three types of sexual dimorphism are classified as the direct association with reproduction and predicted primary selective pressure. Three levels of information were suggested to be conveyed according to the primary role of the mating signals. Although secondary sexual dimorphism is not directly related to reproduction, these traits have been suggested to play a role in final mate choice. Specifically, they may serve one of two functions: 1) facilitating intrasexual competition for potential mates, or 2) acting as mating signals for the opposite sex, conveying information for mate recognition and choice. For example, in the male horned beetle Allomyrina dichotoma (Coleoptera: Scarabaeidae), horn length is proposed as a reliable indicator of fighting ability, which influences access to potential female mates and subsequent reproductive success (Karino et al. 2005). In other organisms in the animal kingdom, traits classified as secondary sexual dimorphism serve as mating signals that affect 2 mate choice. The darkness of a lion's mane is positively correlated with the lioness’ preferences for mates (West and Packer 2002). Similarly, the number of eyespots on peacocks' tails has been shown to positively correlate with mating success among peahens (Dakin and Montgomerie 2011). These sexually dimorphic traits, particularly those that are exaggerated in males, have been extensively discussed and investigated for their potential roles as mating signals across the animal kingdom. The reasons for the extensive study of male exaggerated traits can be attributed to two main factors: 1) the historically anthropomorphic view that females are the choosy sex, and 2) the relative rarity of exaggerated traits in females. Traditionally, females have been regarded as the "choosy" sex in mate choice. However, recent studies have suggested that the roles of males and females can be dynamic and context-dependent, with males exhibiting choosiness under certain conditions (Edward and Chapman 2011). In contrast, while male exaggerated traits have received significant attention, understanding of female exaggerated traits remains limited. This lack of understanding can be largely attributed to the rarity of such traits in nature. 1.2 Evolution of diversified roles of mating signals under combinational selective forces Mating signals can be broadly categorized based on physical characteristics, the media that convey the signals, the types of receptors and organs involved, and the modes of information processing. These categories include visual signals (such as body size and pigmentation), chemical signals (odors and tastes), acoustic signals, and mechanical signals (Halfwerk et al. 2019; Mitoyen et al. 2019). 3 In the class Insecta, the evolution of mating signals is taxonomically divergent, with different lineages employing distinct types of signals. For instance, fireflies (Coleoptera: Lampyridae) have evolved bioluminescent flash signals in response to sexual selection and mate choice (Lewis and Cratsley 2008). Similarly, male crickets (Orthoptera: Gryllidae) produce species-specific calling songs to attract females, demonstrating the use of auditory signals in mating behavior (Doherty and Hoy 1985). Chemical signals, particularly insect pheromones, have been extensively studied since the first pheromone, bombykol, was isolated from the genitalia of female silkworm moths (Bombyx mori). Bombykol is known to elicit mating behavior in male moths (Karlson and Butenandt 1959). The evolution and diversity of mating signals have garnered significant interest from researchers over the decades. This diversity can primarily be understood through two aspects: 1) the use of combination of multiple signals, and 2) the levels of information conveyed by these signals. While studies often focus on single sensory modalities, multimodal mating components are prevalent in the animal kingdom. Multimodal mating signals involve the integration of multiple sensory modalities that influence a receiver’s mating decisions. These integrated signal components provide receivers with enhanced benefits for assessing the fitness of potential mates. Multimodal mating signals fundamentally demonstrate that a single display can be perceived through different sensory modalities. For example, frog calls, which serve as acoustic signals, are frequently accompanied by visual signals such as vocal sac movements and/or water surface vibrations (Halfwerk et al. 2019). Another well-studied instance of multimodal mating components is found in Drosophila melanogaster, where a variety of sensory modalities—including visual, 4 chemical, acoustic, and mechanical signals—play roles in mate recognition and choice (Fan et al. 2013) (Table 1.1). Research has investigated the diversity of sensory modalities employed by the two sexes across various species, revealing evolutionary patterns that reflect taxonomic divergence (Wen and Li 2011). Table 1.1 Series of Drosophila courtship behavior and sensory modalities involved. Mating signals can convey three categories of information between the producer and receiver: species recognition, sex discrimination, and mate quality (Johansson and Jones 2007) (Figure 1.1B). Species-specific signals play a crucial role in species recognition, often observed through reproductive character displacement during reinforcement processes. The Jewelwing damselflies (Calopteryx aequabilis and C. maculata) serve as a classic example for investigating reinforcement, where wing coloration has been identified as a character displacement that enables sympatric male Jewelwings to discriminate between species (Mullen and Andrés 2007). Sex-specific traits or signals also facilitate sex discrimination. In addition to bombykol, which is exclusively produced by females, various blends of chemical signals exhibiting sexual dimorphism in insects contribute to this process. For instance, males 5 of Hawaiian swordtail crickets (genus Laupala) exhibit different behavioral responses to varying profiles of cuticular hydrocarbons deposited on conspecific females’ antennae (Stamps and Shaw 2019). Furthermore, mating signals can indicate mate conditions or qualities, encompassing factors such as fitness, fecundity, and mating status. In the funnel-web spider (Agelenopsis aperta), males demonstrate a strong preference for pheromones produced by unmated females over those from mated females (Singer and Riechert 1995). Thus, mating signals can evolve to serve single or multiple roles, influenced by a combination of selective pressures. The complex interactions of various selective pressures complicate the correlation between the evolution of sexual dimorphism and mating signals. Nevertheless, understanding this relationship is essential for gaining novel insights into the evolution of sexually dimorphic mating signals in nature. Even when a mating signal appears to serve one primary role, the exact information reflected by the signal can vary and become complex. For instance, mating signals may directly reflect the quality of the signaler through mate assessment, a concept supported by the theory of honest signaling, which has been empirically tested in several systems (Steiger and Stökl 2014). Evolving such honest signals can be costly; in addition to the basic costs associated with signal transmission, there are strategic costs incurred in generating these signals (Harper and Smith 2003). An argument has been made that signals must be costly to be considered honest, positing that the evolution of honest signals should balance the potential costs of cheating at equilibrium (Számadó 2011). Empirical studies on honest signaling have primarily 6 focused on measuring costs or trade-offs associated with the production of signaling traits. For example, research on the body size of female Lobesia botrana (Lepidoptera: Tortricidae) indicated that males prefer larger females with bigger glands capable of producing sex pheromones, which are associated with significantly longer signaling times (Harari et al. 2011). Further investigations using novel methodologies such as genetic tools are expected to enhance our understanding of the evolution of mating signals. Among all mating signals, the evolution of chemical communication has been extensively studied, particularly in insects. Chemical communication is posited to be the oldest and most ubiquitous form of communication in nature. It is unique primarily due to its modes of transmission and sensory processing. Chemical signals can function in the absence of the signaler and can persist over long distances and durations. The sensory modalities associated with chemical signals are generally discrete, reflecting the availability of specific receptors (Steiger et al. 2011; Baeckens 2019). The number of genes encoding chemoreceptors varies widely among arthropods; for example, the fig wasp (Ceratosolen solmsi) possesses only five gustatory receptors, whereas the German cockroach (Blattella germanica) has 431 annotated gustatory receptors (Robertson 2019). Given the ubiquitous nature of chemical communication, studying its evolution not only enhances our understanding of this signaling sensory modality but also contributes to insights into the divergent evolution of multimodal signaling systems. The evolution of chemical communication is primarily hypothesized to be influenced by sensory exploitation, wherein a biased sensory perception is predicted to exist within the chemical receiver. Through selective forces, this bias becomes 7 enhanced and stabilized, leading to the evolution of discrete chemical signal receptors (Steiger et al. 2011). Pheromones, which are chemical signals released by organisms for intraspecific communication, have been documented across approximately 3,000 compounds in insect species (Symonds and Elgar 2008). Depending on their effective range and the associated sensory organs and receptors, insect pheromones can be categorized into volatile and contact pheromones. Volatile pheromones typically function over longer distances, while contact pheromones are utilized in close-range interactions (Duffy et al. 2018). Insect species may evolve to use either type, with both types potentially present within a single species, especially to elicit mating behavior. For example, in Bagrada hilaris (Heteroptera: Pentatomidae), studies have demonstrated the presence of both long-range volatile pheromones and potential contact pheromones associated with short-range courtship behavior (Guarino et al. 2008). However, contact pheromones, or short-distance pheromones, do not possess the traditionally recognized characteristics associated with long-distance signaling. Conversely, the evolution of contact pheromones may resemble that of other short- distance signals, such as visual signals. Therefore, the evolutionary pathways of contact pheromones may diverge from those of volatile signals, particularly regarding the related selective forces. Understanding this divergence is crucial for a comprehensive understanding of the evolution of chemical signals. Moreover, the “intermediate” phase of contact pheromones may provide novel insights into the evolution of multimodal mating signal systems. 8 1.3 Using Drosophila as a model to investigate questions in evolution of sexual dimorphism and mating signals In summary, there are several existing gaps in our understanding of the evolution of sexual dimorphism and mating signals. We have outlined the complex interactions of multiple selective forces that influence both processes. The first question that arises is whether there is a correlation between these evolutionary processes. Additionally, we briefly discussed the dynamics of the "choosy" role between the sexes, which exemplifies this innovative understanding in evolutionary biology. While male exaggerated traits have been extensively studied, female exaggerated traits have received comparatively less attention. This raises a second question: what novel insights can we gain by investigating the evolution of female exaggerated traits? Furthermore, the evolution of honest signaling and its associated costs has predominantly been studied under laboratory conditions, often through enforced artificial selection. This leads to a third question: what novel tools can be employed to provide new insights into these evolutionary processes? The evolution of signaling, particularly chemical communication, is crucial for understanding multimodal signaling components. Contact pheromones, as enhanced short-distance sensory cues, represent an intriguing system for investigation. This dissertation aims to address these questions and provide novel insights into these important but missing questions. To tackle the aforementioned questions, Drosophila species present distinct advantages. First, the genus Drosophila, belonging to the family Drosophilidae, comprises approximately 1,450 species, including the well-studied model organism D. melanogaster (Markow and O'grady 2005b). The diverse biology and ecological roles of 9 these species serve as essential resources for investigating evolutionary processes. Second, the tools developed for Drosophila research are well-established and versatile, making it easy to conduct various bioassays and genetic studies. This adaptability enhances the potential for innovative research in evolutionary biology. 1.4 Courtship behavior of Drosophila Courtship behavior in Drosophila males generally follows a stereotypical sequence; however, significant diversity in courtship behavior exists across species (Wen and Li 2011). Typical Drosophila courtship behavior involves utilization of an integration of visual, acoustic, and chemical cues (Wicker-Thomas 2007). Various behavioral components are observed across Drosophila species, including orientation, tapping, wing displays (such as flicking, waving, semaphoring, scissoring, and vibrating), circling, chasing, licking, and mounting (Spieth 1974). Different sensory modalities are thought to be involved in each step of the courtship ritual. For instance, the courtship begins when a male encounters a female by orienting toward her. The male utilizes his compound eyes to detect dynamic signals (such as movements and locomotor actions) and static signals (such as body pigmentation and color) from the female, which sequentially stimulate his subsequent behaviors (Cook 1973; Cook 1979). The male then taps the female’s dorsal abdomen with his front legs, where contact pheromones are perceived. Gustatory signals are perceived through gustatory receptors on his foreleg tarsi during this action. To pursue copulation, the male will chase the female, display his wings, and vibrate (Bennet-Clark et al. 1976; Von Schilcher 1976). This may also be accompanied by the male vibrating his abdomen to produce substrate-borne sounds transmitted to the female (Fabre et al. 10 2012). Additionally, females can produce sounds prior to courtship, which guide the male in navigating toward her (Ejima and Griffith 2008). Thus, acoustic signals, perceived through auditory organs, are universally employed by both sexes. The male then extends his proboscis to lick her genitalia and attempts to copulate by bending his abdomen, utilizing both gustatory and tactile signals (Table 1.1). While a range of stimuli is proposed for D. melanogaster, the utilization of sensory modalities shows taxonomic divergence in other non-melanogaster species across the Drosophila genus. Species closely related to D. melanogaster within the melanogaster subgroup exhibit highly similar courtship rituals and sensory components (Cobb et al. 1989). Conversely, species in the montium subgroup typically display wing vibrations after mounting and do not engage in the licking stage (Spieth 1952; Hoikkala and Crossley 2000). Furthermore, in the mulleri subgroup, independent evolution of courtship rituals has been observed; for instance, D. leonis and D. nigrospiracula do not incorporate tapping in their courtship behavior (Alonso-Pimentel et al. 1995). Notably, no records indicate that D. pegasa exhibits any of the aforementioned courtship behaviors (Wasserman et al. 1971). The diversification of behavioral responses during courtship across Drosophila species provides abundant research opportunities but also presents challenges for relevant comparative studies. 1.5 Drosophila cuticular hydrocarbons (CHCs) as mating signals Among the various mating signals, hydrocarbons deposited on the insect cuticle can function as contact pheromones, perceived during tapping through the gustatory organs, foreleg tarsi, and proboscis. Cuticular hydrocarbons (CHCs) play a critical role in chemical communication, particularly in mating behavior (Stocker 1994; Boll and Noll 11 2002; Bray and Amrein 2003). A well-studied example is the comparison between two closely related species, D. melanogaster and D. simulans. Drosophila melanogaster exhibits qualitative differences in CHC profiles between the sexes, with females producing sex-specific CHCs such as 7,11-heptacosadiene (7,11-HD), while D. simulans shows no qualitative differences in CHC compositions between sexes (Jallon and David 1987). The roles of CHCs as mating signals have been extensively investigated in this species pair. The female-specific 7,11-HD in D. melanogaster serves as an aphrodisiac to conspecific males, eliciting dose-dependent responses in male courtship rituals that convey information about female quality (Antony et al. 1985). Conversely, this compound acts as an anti-aphrodisiac, discouraging courtship from D. simulans males, thereby playing a role in species recognition (Seeholzer et al. 2018; Ahmed et al. 2019). Diversity in CHC profiles can be observed across Drosophila species at the population, sex, and individual levels. CHC profiles consist of a blend of components with varying chemical structures, including differences in carbon chain length, branching patterns, and the number and position of double bonds. Generally, Drosophila CHCs can be categorized into n-alkanes, monoenes, dienes, alkatrienes, and methyl- branched alkanes (Figure 1.2). For instance, a population-level comparison reveals differences between two strains of D. melanogaster, Canton-S and Tai-Y, where 7- tricosene is the primary CHC component in Canton-S males but is rarely produced by Tai-Y males (Scott 1994). Sexually dimorphic CHC profiles can be species-specific, exhibiting qualitative and/or quantitative differences. Individual-level variations in CHC profiles can be 12 attributed to phenotypic plasticity, influenced by factors such as age, diet, mating status, health, and other physiological conditions (Cortot et al. 2022). In the context of contact pheromones, intraindividual variations in CHC profiles may also serve as honest signals reflecting sexual attractiveness, contributing to mate assessment and choice. For example, short-chain CHCs induced by a high-yeast diet can result in less attractive females (Fedina et al. 2012). Variations in CHC profiles arise from both genotypic and phenotypic factors, and deciphering the evolution of divergent CHC blends will enhance our understanding of the evolution of chemical signaling. Figure 1.2 Side view of oenocytes (Left) and Types of cuticular hydrocarbons in D. melanogaster (Right) adapted from (Chung and Carroll 2015). However, there is still a lack of understanding regarding whether the sexual dimorphism observed in CHC profiles is driven by or correlated with the role of CHCs in mate recognition and mate choice. Further comparative studies exploring the relationship between sexual dimorphism and signaling roles of CHCs are needed. 1.6 CHC biosynthesis in Drosophila In Drosophila species, cuticular hydrocarbons (CHCs) are synthesized within oenocytes located beneath the dorsal abdomen cuticle and subsequently transported to the insect cuticle (Ferveur et al. 1997; Schal et al. 1998; Fan et al. 2013) (Figure 1.2, Figure 13 1.3A). The biochemical reactions and pathways involved in CHC biosynthesis have been elucidated through studies utilizing radiolabeled precursors (Dillwith et al. 1981; Dillwith et al. 1982; Blomquist et al. 1987). A series of enzymes involved in the fatty acid synthesis pathway have been implicated in CHC production. Fatty acyl-CoA molecules may undergo desaturation processes, which are facilitated by specific enzymatic proteins known as desaturases. Elongases facilitate chain-length elongation, resulting in the production of long-chain fatty acyl-CoA. Additionally, reductases convert fatty acyl- CoA to aldehydes, while a single cytochrome P450 enzyme catalyzes the decarboxylation process to yield final products as hydrocarbons (Blomquist and Ginzel 2021). The genes related to CHC synthesis are rapidly evolving across Drosophila species, making the prediction of genes responsible for specific CHC blends challenging (Finet et al. 2019). In D. melanogaster, however, the genes involved in CHC synthesis have been well characterized. For instance, two key enzymes are essential for the production of the female-specific CHC, 7,11-heptacosadiene (7,11-HD). The desaturase gene DesatF is responsible for introducing a second double bond between the 7th and 8th carbons (Chertemps et al. 2006). Additionally, the elongase gene EloF has been suggested to specifically target the production of 27-carbon and 29-carbon dienes (Chertemps et al. 2007). 14 Figure 1.3 (A) Vertical view of dissected Drosophila oenocytes and (B) Biosynthesis pathways of Drosophila CHCs adapted from (Finet et al. 2019). Genetic variations involved in CHC synthesis are precisely regulated, contributing to the variations and diversity of CHC profiles at multiple levels. In D. melanogaster, interpopulational variations in CHCs can be observed in the positioning of double bonds. For instance, in the Canton-S strain, the primary CHC components are 7-tricosene (7-T) in males and 7,11-heptacosadiene (7,11-HD) in females, establishing the 7-positioned double bond as a characteristic feature of this strain's CHC profile. In contrast, the Tai-Y strain exhibits a female-specific polymorphism where the major compound 7,11-heptacosadiene (7,11-HD) is replaced by 5,9-heptacosadiene (5,9-HD). Here, females produce low levels of 7,11-HD but high levels of its positional isomer, 5,9- HD (Scott 1994). Previous genetic studies have suggested that the female-specific expression of the desaturase gene desat2 may account for this polymorphism. Desat2 encodes a desaturation reaction specific to the 9-position, leading to the production of 9-positioned unsaturated hydrocarbons in females (Coyne et al. 1999; Dallerac et al. 2000). 15 Sex-specific expression patterns are also observed in other genes related to CHC synthesis. Both eloF and desatF are named for their female-biased expression patterns in D. melanogaster, and both contribute to the sexual dimorphism of CHC profiles. This has raised questions regarding the evolutionary mechanisms underlying such sex-specific expression patterns. A comprehensive study investigated cis- regulatory changes in the orthologs of desatF across Drosophila species. The findings indicated rapid evolution and frequent alterations in the cis-regulatory elements of these alleles, including gene inactivation, losses of gene expression, and transitions in sex- specific expression patterns. Furthermore, the study suggested that the sex-specific expression of these genes may arise from the gain of a binding site for DOUBLESEX, a transcription factor involved in sex determination in Drosophila species (Shirangi et al. 2009). This established understanding of genetic variations and the evolution of sex- specific expression of CHC synthesis genes provides both technical feasibility and theoretical knowledge for future studies. However, whether other genetic mechanisms underlying the evolution of these sex-specific gene expression patterns remains unknown. Given the current insights into female-biased expression patterns, novel understandings of female exaggerated traits could be further explored. 1.7 Other roles of Drosophila CHCs Cuticular hydrocarbon (CHC) synthesis can incur significant costs due to the involvement of additional enzymes and the gain of highly specific and precise gene expression patterns. It has been suggested that methyl-branched alkanes, a common group within CHC blends, require greater metabolic investment for production compared 16 to linear-chain alkanes (Nelson 1993). Beyond their role in mating signals, CHCs are also essential constituents of the Drosophila cuticular wax layer, functioning primarily for waterproofing (Chung and Carroll 2015). More specifically, the dual roles of methyl- branched alkanes in influencing both desiccation resistance and mate choice have been documented in Drosophila (Chung and Carroll 2015). The evolution of CHCs is theoretically predicted to be driven by interactions between natural selection and sexual selection (Blows 2002). Consequently, an equilibrium is hypothesized to exist between the evolution of these dual roles of CHC blends, with elaboration on one role—such as mating signals—potentially eliciting antagonistic or synergistic responses in the evolution of the other role. In addition to the equilibrium established between desiccation resistance and mating signals, the evolution of CHC profiles may also involve trade-offs with other primary traits. As previously mentioned, the sensory components involved in mate choice can honestly signal the sender's fecundity, mating status, fitness, and related conditions (Fedina et al. 2012). Selection pressures related to desiccation resistance have been shown to result in decreased fecundity (Kwan et al. 2008), prolonged development time, reduced adult viability (Chippindale et al. 1998), and increased longevity (Rose et al. 1992). Generating mating signals can also be costly, potentially offsetting energy invested in development and fecundity. Given that CHCs serve both roles, understanding the trade-offs associated with the production of costly CHC components is critical for our comprehension of adaptation and sexual selection. However, two key questions remain unanswered: 1) How do CHCs contribute to the evolution of the equilibrium between desiccation resistance and mating signals? and 17 2) What are the trade-offs associated with costly CHC synthesis? Investigating the evolution of honest signaling is particularly significant, especially regarding the potential costs of signaling. While previous studies have utilized the selection of Drosophila strains under laboratory conditions to predict trends, the application of advanced genetic tools will offer novel insights into these questions. 1.8 Summary and research objectives In summary, in this dissertation, by using CHCs in Drosophila as a model, I aim to investigate the evolution of sexual dimorphism of CHCs and their related roles as mating signals, with the following aims: 1) to determine the correlation between mating signals and sexual dimorphism, 2) to determine the genetic mechanism underlying female exaggerated traits, 3) to assess the potential trade-offs in costly CHC production. Through these aims, this dissertation seeks to provide novel insights into the evolution of sexual dimorphism and mating signals in Drosophila. 18 CHAPTER 2: SEXUAL DIMORPHISM IN CHCS AND THEIR ROLES IN DROSOPHILA COURTSHIP I would like to acknowledge the following colleagues, since this chapter could not have been accomplished without the contributions made by them. Dr. Mei Luo • Assisted in performing non-choice mating assay Dr. Rajanikanth Chowdanayaka • Assisted in checking the results of non-choice mating assay Nadia Sbisa • Assisted in checking the results of non-choice mating assay Dr. Zinan Wang • Assisted in analyzing CHC profiles of the perfumed flies 2.1 Introduction Species in Drosophila utilize multimodal sensory modalities for mate assessment, to enhance reproductive success (Mitoyen et al. 2019). During the process of mate assessment, two components are likely to occur, mate recognition and mate choice. Mate recognition is the process that consists of identifying and assessing a potential mate (Ryan and Rand 1993), which further can be divided into two separate components: species recognition and sex recognition within species (Blows and Allan 1998b). Mate choice is the stage where focal individuals can get access to multiple potential mates and make final mate decisions. Recently, dynamic sex role where both sexes can be choosy to conduct mate choice has been investigated and discussed (Edward and Chapman 2011). Both mate recognition and mate choice evolved as a 19 consequence to maximize reproductive success through investments into reproduction with suitable and better mates (Bateman 1948). Mating signals can serve the roles for conveying complex levels of information to facilitate mate recognition and mate choice. A series of sensory modalities can be used by individual Drosophila to conduct both processes and make mating decisions (Table 1.1). Signals used for mate recognition and mate choice have been studied in Drosophila species, but few studies have investigated the separate roles of mating signals involved in mate recognition and mate choice. The following question was raised: whether the mating signal traits involved in both processes are distinct or the same. In the 1990s, divergent signal functions and corresponding evolutionary processes were proposed, driven by intra- and interspecific individual preferences (Andersson 1994). Recently, the concept of mating signals being processed and evaluated serially has been proposed. In this model, “static” signal components are likely to be processed first and often evolve during the process of speciation. “Dynamic” components with high interindividual variations are processed secondarily. The proposed model was tested on the cricket calling song, and the author suggested that further tests, with potentially generalized results across taxa, are necessary (Gray 2022). Among all the sensory modalities used in Drosophila, determining the specific roles of mating signals has been of great importance in understanding the dynamic evolution of multimodal components. The functions of specific mating signals have been tested in specific species, but not in a comparative study across Drosophila. For 20 example, Drosophila courtship song includes two distinct components, with one component primarily involved in species recognition, and another component evolved rapidly under mate choice and sexual selection. The independent loss of both components has been suggested in species from the repleta group (Ewing and Miyan 1986). In contrast, a morphological visual signal, head-width, is the only sensory modality used by D. heteroneura for mate choice and sexual selection. There is no evidence to support such a trait is also contributing to mate recognition as premating reproductive isolation barrier between species (Boake et al. 1997). In addition to acoustic and visual signals, CHCs as gustatory cues perceived during courtship rituals, are suggested to be involved in both processes of mate recognition and mate choice within and between two Drosophila species (Blows and Allan 1998a). However, comparative studies across Drosophila genera are required to understand the role of CHCs in courtship are needed. Furthermore, unlike other sensory modalities, CHC profiles show variations between sexes at different levels, which makes the chemical signal unique model in the Drosophila multimodal system. Firstly, within CHC profiles, one or more CHC components can be sex specific. Secondly, with the presence of unsaturated double bonds or branches at different locations on the carbon chains, some isomers of the same CHC components can be produced only by males or females. Lastly, females and males may produce the same CHC components, but some components may show differences in quantitative amounts between sexes. The levels or types of differences in CHC sexual dimorphism are different among species, and there are no taxonomic similarities that have been suggested. This left the understanding the different displays 21 of sexual dimorphism in Drosophila CHCs unresolved. Moreover, with different displays of CHC profiles across Drosophila species, whether such variations are correlated with the role of CHCs in courtship is unknown. Degree of sexual dimorphism has been commonly used in comparative studies focusing on morphological traits (Ralls 1977; Arak 1988; Ralls and Mesnick 2009; Zorba et al. 2011). Understanding about degrees of sexual dimorphism in physiological traits, coupled with understanding the evolution of such traits under selection or their sex- dependent functions, is still lacking. In this study, we selected nine species to investigate the roles of CHCs in courtship in each species (D. melanogaster, D. simulans, D. yakuba, D. erecta, D. ananassae, D. pseudoobscura, D. willistoni, D. mojavensis, and D. repleta). The nine species were selected across the Drosophila genus, spanning both the Sophophora and Drosophila subgenus and representing different lineages. Quantifying sexual dimorphism by degrees of sexual dimorphism will provide novel tools to identify potential correlation pattern across phylogeny correspondingly. Additionally, investigating whether we can use degrees of sexual dimorphism to predict use of CHCs in male courtship is also to contribute our knowledge in the evolution of mating signals. 2.2 Results 2.2.1 Variations in degrees of CHC sexual dimorphism across Drosophila species We first determined the levels of CHC sexual dimorphism across the nine Drosophila species. The CHC profiles of both males and females of these species have been described in our previous work (Wang et al. 2022). We adapted the previously 22 described data with further specifying different isomers, and used the Bray-Curtis dissimilarity statistic to determine the dissimilarity of CHC profiles between the male and female CHCs of each species (Figure 2.1). Across these nine species, the Bray-Curtis dissimilarity index ranged from 0.08 in D. pseudoobscura, where the CHC profiles of both sexes in this species appeared to be the least sexually dimorphic to 0.95 in D. erecta where the degree of CHC dimorphism was maximum (Figure 2.1). In D. erecta, the female CHC profile comprises of 26- to 33-carbon long CHCs, including two long chained dienes, C31:2 and C33:2, while the male profile comprises of CHCs with 21- to 28-carbon long CHCs without any dienes. Among these nine species, five species (D. simulans, D. yakuba, D. ananassae, D. pseudoobscura and D. mojavensis) do not possess CHC components that are unique to one sex. The other four species (D. melanogaster, D. erecta, D. willistoni, and D. repleta) possess sex specific CHC components or isomers either in one or both sexes (Table S2.1). 23 Figure 2.1 Divergent degrees of CHC sexual dimorphism across Drosophila species. Sexual dimorphism in CHC profiles across nine Drosophila species were calculated using the Bray-Curtis dissimilarity index (0 = no dissimilarity, 1 = highly dissimilar). Mean values range from 0.08 (D. pseudoobscura) to 0.97 (D. erecta), 0.66 (D. melanogaster), 0.12 (D. simulans), 0.11 (D. yakuba), 0.21 (D. ananassae), 0.39 (D. willistoni), 0.20 (D. mojavensis), 0.53 (D. repleta). 2.2.2 Effects of foreleg tarsi removal on male courtship interests Drosophila males perceive female CHCs using specific gustatory receptors on the foreleg tarsi by tapping on the female abdomen (Fan et al. 2013; Ahmed et al. 24 2019). After tapping, wing display and copulation trials are followed as a continuous courtship ritual in serial order (Table 1.1). To determine whether CHC inputs are crucial for continued courtship interest, we removed the foreleg tarsi from the males of these nine species and assayed for changes in male courtship behavior towards conspecific females. We used the presence or absence of wing display as the indicator of male ‘s continuous courtship interest, as all these species utilize wing display (vibrational courtship song) as part of their sequential courtship ritual after perceiving chemosensory cues by tapping (Markow and O'grady 2005a). Our results showed that D. melanogaster males did not show any significant change in continuous courtship interests (χ2=0.27, p = 0.60). In contrast, D. simulans males showed a significant decrease in male continuous courtship interests after tarsi removal (χ2=10.16, p < 0.01). Males of the remaining six species (D. yakuba, D. erecta, D. ananassae, D. pseudoobscura, D. willistoni, and D. mojavensis) also exhibited significantly reduced male courtship interests following tarsi removal, with the exception of D. repleta (Figure 2.2). 25 Figure 2.2 Tarsi removal affected male courtship interests in most Drosophila species. Wing display % in no-choice mating assays. Loss of tarsi leads to significant reduction in courtship interests across Drosophila species, except D. melanogaster and D. repleta. C = Control, TR = Tarsi Removed. The Chi-Square test was used to determine any significant differences in wing displays. n.s = not significant *p < 0.05; **p < 0.01. 26 To exclude the possibility that the decrease in courtship interests exhibited by some of these species was due to other potential reasons caused by tarsi removal (e.g., injury) rather than the inability of males perceiving female CHCs, we complemented the results further with a CHC perfuming assay. Female CHCs from the two species with the highest and lowest degrees of CHC sexual dimorphism, D. erecta and D. pseudoobscura were extracted and coated on genetically modified D. melanogaster female flies without CHCs (CHC- D. melanogaster). Experiments showed that D. erecta and D. pseudoobscura male flies display courtship interests towards these CHC- D. melanogaster female flies that have been coated with conspecific female CHCs at a significantly higher rate compared to uncoated CHC- D. melanogaster females (Figure 2.3). This suggests that CHC inputs are important for continuous male courtship interests in these two species and would even lead to male attempting copulation towards heterospecific females if the CHC blend is correct. Figure 2.3 Detection of CHC is important in maintaining Drosophila courtship interests. Female CHCs from D. erecta and D. pseudoobscura coated on female CHC- D. melanogaster are able to elicit courtship interests from conspecific males. Chi- Square test was used to determine any significant differences in wing displays. *p < 0.05; **p < 0.01. 27 2.2.3 Foreleg tarsi removal resulted in longer courtship latency in D. melanogaster and D. repleta As for the two Drosophila species D. melanogaster and D. repleta that did not show significant changes in courtship interests after tarsi-removal, we further tested other possible roles of CHCs in their courtship. We hypothesized that although CHCs are not essential for continuous courtship interests, CHCs are important in reducing male courtship latency. This hypothesis was based on that CHCs can possibly convey information of mate quality, and thus contribute to more efficient mate decision process done by males. For both species, we measured and compared courtship latency between tarsi removed males and wild type males. Mean courtship latency of D. melanogaster wild type males is 3.87 min, compared with 10.45 min for tarsi removed males (t = 3.76, df = 15.35, p < 0.01; Figure 2.4A). Mean courtship latency of D. repleta wild type males is 4.62 min, compared with 18.63 min for tarsi removed males (t = 2.84, df = 21.35, p < 0.01; Figure 2.4B). These results support our hypothesis, suggesting that while CHCs are not directly responsible for maintaining continuous courtship interests in these two species, the perception of CHC is contributing to a faster reproductive static with shorter mating latency and thus may be involved in communicating mate quality in these two species. 28 Figure 2.4 Loss of detection of CHCs resulted in increased courtship latency in both D. melanogaster (A) and D. repleta (B). Courtship latency is the duration between the introduction of test male to the unmated female and the first courtship wing display by the males. The student’s t-test was used to determine any significant differences in courtship latency. **p < 0.01. 2.2.4 No correlation between the degree of CHC sexual dimorphism and use of female CHCs as signals for courtship To determine if the degree of sexual dimorphism in CHC profiles can be used to indicate the importance in male courtship, we performed a simple linear regression analysis to determine if the degree of CHC sexual dimorphism could explain changes in courtship behavior after tarsi removal among the selected species. The results of the regression indicated degrees of CHC sexual dimorphism can only explain 9.53% of the variation in utilization of CHCs for male courtship interests [F (1,7) = 0.7222, p = 0.4235]. Our analysis showed that there is not enough evidence to support a correlation between levels of CHC sexual dimorphism and the change in courtship interests after tarsi removal (Figure 2.5). This suggests that the degree of sexual dimorphism in CHC profiles may not be informative for predicting whether female CHCs are important for 29 maintaining courtship interests across the Drosophila species studied. Figure 2.5 Degree of sexual dimorphism in CHC profiles is not enough to be used to inform if female CHCs are important for male courtship. Regression of levels of CHCs sexual differences and courtship interests changes after tarsal removal in males. Changes in Courtship Interests ~ 0.4502 + -0.1081*log (Degrees of CHC dimorphism). mel = D. melanogaster, sim = D. simulans, yak = D. yakuba, ere = D. erecta, ana = D. ananassae, pse = D. pseudoobscura, wil = D. willistoni, moj = D. mojavensis, rep = D. repleta. 2.3 Discussion Mate recognition and mate choice have been suggested to be discrete processes for the perception and evaluation by signal perceivers, where mating signals are evolved distinctively (Blows and Allan 1998b). Recent studies have argued this with testing the model of “serial processing and order-of-operations”, where mating signals are perceived at first, followed by a series of recognizing (mate recognition) and choosing 30 (sexual selection) mates. The importance of determining the evolution of mating signal with differentiating potential roles becomes more crucial for understanding evolutionary divergence (Gray 2022). In this study, we selected nine Drosophila species across phylogeny and investigated the role of CHCs in courtship. Firstly, we found qualitative and quantitative differences in sexual dimorphism across the Drosophila genus. The CHC dissimilarities range from 0.08 in D. pseudoobscura to 0.95 in D. erecta. The diversity in CHC degrees of sexual dimorphism indicates the complicated evolutionary processes occurred on this trait. In addition, further individual study in the evolution of sexual dimorphism in each species is of importance in further understanding independent evolution across different lineages, especially the evolution of the most CHC sexual dimorphic species, D. erecta. Our results suggest that in most of the selected species, perception of CHC is necessary for males to maintain courtship interests, moving onto wing display as a serial matter. This suggests female CHCs in these species play a crucial role in signal recognition responsible for primary courtship interest. Two test species, D. melanogaster and D. repleta do not require CHC input for occurrence of wing display and following steps in the courtship rituals. However, the loss of perception of CHCs does result in a decrease in courtship latency in the corresponding species, suggesting the importance of CHC inputs in efficient courtship display and further enhanced reproductive fitness of the population. It is likely that CHCs in these species convey information about the quality of potential mates. An example is the female-specific 7,11- HD in D. melanogaster, which is an aphrodisiac that can increase male courtship occurrence in this species (Antony et al. 1985), but CHC is not necessary for courtship 31 initiation in this species (Fan et al. 2013; Shahandeh et al. 2018; Ahmed et al. 2019). We suggest that, other signals such as visual, acoustic, and olfactory signals (Colyott et al. 2016) may be more important for the mate decision in D. melanogaster and D. repleta. Or different reproductive tactics independently evolved in these species, where multimodal signal components are important in efficient signal recognition, but none of the individual signals are necessary for initiating courtship. The important role of CHCs in courtship can be also supported by the perfuming assay, where the coated conspecific CHC blend on to D. melanogaster females can still initiate courtship behavior of D. erecta and D. pseudoobscura males. This suggests that the perfumed CHC blends can weaken the established premating reproductive isolation barrier, and that other mating sensory modalities are not necessary basis for males making mate decision. In conclusion, our experiments and analyses do not support the hypothesis that the degree of CHC sexual dimorphism is predictive of the roles of CHCs as mating signals for courtship. This further provides empirical evidence to suggest that the rapid evolution of sexual dimorphism may be caused by or constrained by other important pleiotropic functions of the traits, not only resulting from the role of mating signal recognition. 2.4 Materials and Methods Drosophila species D. simulans (14021-0251.195), D. yakuba (14021-0261-01), D. erecta (14021-0224.01), D. ananassae (14024-0371.13), D. pseudoobscura (14011-0121.94), D. willistoni (14030-0811.24), D. mojavensis (15081-1352.10), and D. repleta (15084-1611.13) were 32 obtained from the National Drosophila Species Stock Center. D. melanogaster was a gift from Dr. Sean Carroll’s lab (University of Maryland). All species were reared on standard cornmeal medium (Flystuff 66-121 Nutri-Fly Bloomington Formulation) at 25°C, except for D. pseudoobscura which was reared at 18°C, which has been suggested to be the optimal development condition for such species. Foreleg tarsi removal and no-choice courtship assay To test whether males of different Drosophila species utilize CHCs as signals for mate recognition, tarsal segment of the forelegs from adult unmated males were removed using micro-scissors under light anesthesia 24 hours before these males were used for courtship assays. No-choice mating assays were performed at 25°C (except for D. pseudoobscura at 18°C) in the morning between a single unmated sexually mature female and a single unmated sexually mature male either with tarsi removed or intact tarsi. The age of sexual maturity was predetermined from pilot tests (Table S2.2) and is based on a previous study (Pitnick et al. 1995). To begin each assay, a single female and single male were separately aspirated into each well of a Plexiglas mating chamber (Ejima and Griffith 2011). See Table S2.3 for sample sizes for no-choice mating assays. The mating pairs were recorded for one hour using a cell phone camera and courtship occurrences were manually determined. Wing display was tested for the males, to determine their continuous courtship interests, as part of their sequential courtship ritual after perceiving chemosensory cues by tapping (Markow and O'grady 2005a). Courtship latency was determined as the duration between the introduction of test male to the unmated female and the first courtship wing display by the males. Each recorded video was checked, and the presence of wing display of each test male was determined, by 33 three different observers individually. CHC- flies and CHC coating To generate CHC- flies, we crossed the 5′mFAS-GAL4 driver line (which expresses GAL4 in adult oenocytes) with the UAS-Cyp4g1 RNAi line as described in a previous study (Wang et al. 2022). For the coating experiments, CHCs from fifty sexually matured unmated females (either D. erecta or D. pseudoobscura) were extracted using 600-800 µl hexane and pipetted into a 2ml glass vial. The hexane was evaporated under a nitrogen gas flow, leaving the compound as a residue coating the bottom of the vial. Groups of ten CHC- D. melanogaster unmated female flies were transferred to the coated vials and subjected to two high vortex pulses lasting 20s, with one 20s pause between two pulses. Six flies from each group were used for behavioral tests and the remaining four flies were subjected to GC-MS analysis protocols as described previously (Wang et al. 2022; Wang et al. 2023) to determine effective transfer of the CHC extracts onto the flies. Statistical Analyses The CHC measurements for the different Drosophila species and sex were adapted from a previous study, with further specifying different isomers in this study (Wang et al. 2022). In this study, we use the Bray–Curtis dissimilarity statistics (Taft et al. 2015) to analyze the degree of similarity/dissimilarity between male and female CHC profiles of these species. Ranging from 0 to 1, the Bray–Curtis dissimilarity statistic measures the dissimilarity between two datasets (0 = highly similar, 1 = highly dissimilar), and we use this statistic as a measurement of the level of CHC sexual dimorphism in a given species. Bray-Curtis dissimilarity was calculated using the `vegan` package in R 34 (Oksanen et al. 2013). In no-choice mating assay, χ2 tests were used to determine significance in the courtship occurrence between intact males and tarsi removed males, and were conducted using the `chisq.test()` function in R (Chung et al. 2014). Student’s t-tests were used to determine significant changes in courtship latency between intact males and tarsi removed males, and were performed using the `t.test()` function in R. A simple linear regression analysis was used to test the correlation between changes in courtship interest in males after tarsi being removed and the degree of sexual dimorphism in the CHC profiles of the same species, using `lm()` function in R. All analyses were conducted in RStudio (Rstudioteam 2022). 35 CHAPTER 3. GENETIC MECHANISMS UNDERLYING CHC EXAGGERATED DIMORPHISM IN FEMALE DROSOPHILA ERECTA I would like to acknowledge the following colleagues, since this chapter could not have been accomplished without the contributions made by them. Dr. Jian Pu • Assisted in producing several GFP reporter constructs and corresponding transgenic fly lines Samantha Kalchik • Assisted in producing some GFP reporter constructs and corresponding transgenic fly lines Nadia Sbisa • Assisted in producing some GFP reporter constructs and corresponding transgenic fly lines 3.1 Introduction Sexual dimorphism exhibits considerable diversity in nature, rendering it a compelling area of study for evolutionary biologists. A prominent example of sexually dimorphic traits is the elaboration of male morphological features, such as the peacock's tail (Pavo cristatus) and the lion's mane (Panthera leo) (Williams and Carroll 2009). Two primary reasons account for the extensive research focused on male sexually dimorphic traits. First, historical perspectives have often positioned females as the choosier sex, by investing more in offspring care. As a result, male exaggerated ornaments have evolved under the pressures of female mate choice and male-male competition (Warren et al. 2013). Second, studies of male exaggerated ornaments dominate the literature partly 36 because female exaggerated traits are predicted to be rare, with their evolution influenced by natural selection for resource access, rather than solely through sexual selection (Tobias et al. 2012). The rarity of female exaggerated traits in nature has resulted in a limited understanding of their evolutionary mechanisms. Three primary viewpoints have emerged to explain the evolution of female exaggerated traits. The first posits that female ornamental traits arise from shared genomic heritage with males, leading to correlated inheritance. This concept, initially proposed by Darwin (Darwin 1871), is supported by empirical evidence demonstrating a correlation between the degree of trait exaggeration and genomic sharing in females with conspecific males (Amundsen 2000). The second viewpoint, particularly relevant in sex-role-reversed and polyandrous species, suggests that a reversed sexual selection force—male mate choice—drives the elaboration of female traits (Clutton-Brock 2007). Empirical evidence indicates that females can enhance their fitness by attracting mates (Rosvall 2011). The third perspective emphasizes the role of female competition for non-sexual resources, suggesting that other selective pressures contribute to trait elaboration, that is being supported by empirical tests (Stankowich and Caro 2009). Despite these proposed theories, the evolution of female exaggerated traits remains underexplored, particularly regarding the mechanisms involved. In addition to the limited understanding of female exaggerated traits, knowledge about the evolution of physiological sexually dimorphic traits is also scarce, as highlighted in the second chapter. Notably, we observed divergent degrees of sexual dimorphism in cuticular hydrocarbon (CHC) profiles across selected Drosophila species. The Bray-Curtis dissimilarity index, with a maximum score of 1.00 indicating extreme 37 sexual dimorphism, showed that D. erecta scored 0.95. The characterization of CHC profiles in the melanogaster subgroup was first conducted by Jallon and David, who noted that female D. erecta specifically produces very long CHC components (31–33 carbons), absent in males, leading to significant differences between the sexes (Jallon and David 1987). Our results from a Principal Component Analysis (PCA) confirmed this. The results indicated that 97.7% of the variation could be explained by the first two principal components. CHC profiles from all male species within the melanogaster subgroup formed a distinct cluster, while CHC samples from D. erecta females were distinctively separated from this cluster (Figure 3.1A). This separation suggests that the highest degree of sexual dimorphism in D. erecta is attributable to female CHC blends. Furthermore, the major components of a chemical blend are hypothesized to serve sociochemical functions, eliciting behavioral responses among individuals (Symonds and Elgar 2008). A comparative analysis of CHC profiles between sexes also indicated that the pronounced sexual dimorphism observed in D. erecta females is due to the presence of these very long CHCs, likely representing an independent evolutionary gain in this lineage (Figure 3.1B). In this study, we propose to use the very long CHCs (31–33 carbons) as a model to investigate the represented female exaggerated trait in D. erecta. 38 A Figure 3.1 The very long CHCs represent female exaggerated traits in D. erecta. (A) Principal component analysis (PCA) of CHC profiles of Drosophila species in melanogaster subgroup. Percentages of individual chemicals (amount of each compound divided by total amount of all CHCs) in each species were used for the PCA analyses. 97.7% of the variations can be explained by PC1 and PC2. Dere = D. erecta, Dmau = D. mauritiana, Dmel = D. melanogaster, Dsim = D. simulans, Dtei = D. teissieri, Dyak = D. yakuba, F = Female, M = Male. (B) Comparison of major CHC compound between sexes across Drosophila species in melanogaster subgroup. Chemical structures shown on the right reflect the major CHC compound in females only. Different isomers with different double bond positions can be found across different populations. Diagrams here only suggest the differences in chain lengths across species. 39 Figure 3.1 (cont’d) Understanding the evolution of female exaggerated traits is crucial, particularly the genetic mechanisms underlying their production. While the genetic mechanisms underlying male-specific traits are relatively well-established in various model organisms, including Drosophila, female traits remain less understood. For example, in D. biarmipes, the male-specific wing spot plays a role in courtship rituals, suggesting its contribution to female mate choice (Singh and Chatterjee 1987). The yellow protein, involved in melanin biosynthesis, is expressed at low levels during wing development in D. melanogaster and D. pseudoobscura, but at high levels in the wing spots of male D. biarmipes (Wittkopp et al. 2002). The evolution of this trait involved changes in the cis- regulatory elements of the yellow gene, with gains in binding sites for transcription factors being a key mechanism (Gompel et al. 2005). Similarly, genetic mechanism underlying sexual dimorphism CHC profiles has been studied in D. melanogaster, characterized by the female-specific production of 7,11-HD (Jallon and David 1987). The fatty acid desaturase DesatF is responsible for adding a second unsaturated double bond in the production of this CHC component, 40 subgroup C2 C2 C2 C2 C2 C2 C2 C2 C2 with its expression localized to the oenocytes of female flies (Chertemps et al. 2006). Rapid evolution in the cis-regulatory regions of desatF has been suggested to explain this specific expression pattern (Shirangi et al. 2009), including the gain of binding sites for DOUBLESEX (dsx), a crucial transcription factor for sexual differentiation in Drosophila (Hopkins and Kopp 2021). Doublesex operates across a range of somatic cells in Drosophila, contributing to the production of sexually dimorphic traits through its two isoforms with sex-specific sequences. Furthermore, the process of gaining sex biased expression usually involves gaining dsx expression in tissues and modifying the repertoire of dsx targets through changes in binding sites within enhancers (Hopkins and Kopp 2021). While dsx is essential for the production of many sexually dimorphic traits, recent studies highlight the role of hormonal inputs in sexual differentiation, such as higher levels of 20- hydroxyecdysone in female butterflies correlating with enlarged wing spots (Bhardwaj et al. 2018). In summary, the evolution of sexual dimorphism can often be attributed to cis- regulatory changes, particularly through the gain or loss of dsx binding sites. In D. melanogaster, rapid changes in enhancer sequences of the CHC synthesis gene desatF have been implicated in the production of female-specific CHC components. However, whether this mechanism applies universally, especially to the very long CHC components in female D. erecta, remains unknown. Investigating the genetic mechanisms underlying these traits will enhance our understanding of female exaggerated traits. A novel model of the evolution of highly specific gene expression has been 41 previously proposed (Pu et al. 2021), which involved dissecting regulatory sequences and using GFP reporter systems to create transgenic Drosophila lines. By comparing homologous regulatory sequences across lineages, we identified stepwise evolutionary changes, including gains or losses of specific modules. This methodology can similarly be applied in our proposed study to provide evidence for the genetic mechanisms underlying the production of the very long CHCs in D. erecta. In Drosophila, CHC synthesis shares fatty acid synthesis pathways that include several processes and involves families of enzymes (Figure 1.3B). Fatty acid synthetases produce medium-chain carbon backbones, while desaturases introduce unsaturated double bonds. Elongases extend these medium-length chains to longer chains, and reductases, alongside a cytochrome P450 enzyme, finalize CHC production (Chung and Carroll 2015). We hypothesize that at least one elongase gene is responsible for the production of the female-specific very long CHCs in D. erecta, responsible for the production female exaggerated traits in this species. 3.2 Results 3.2.1 Nineteen elongase genes were found in D. erecta genome, with an independent loss of EloF To test our hypothesis regarding the candidate fatty acid elongase gene responsible for producing the very long-chain cuticular hydrocarbons (CHCs) in female D. erecta, we first referred to the elongase gene involved in the synthesis of the female-specific CHC, 7,11-HD, in Drosophila melanogaster. The gene EloF has been identified as being crucial for the production of 27- and 29-carbon dienes (Chertemps et al. 2007). Using the coding sequence of EloF obtained from the annotated D. melanogaster 42 genome, we conducted a comparative analysis with the D. erecta genome. Our phylogenetic analyses and synteny comparisons revealed that the ortholog of EloF is absent from the D. erecta genome at the same genomic locus where it is located in D. melanogaster (Figure 3.2A). To further explore the possibility that the ortholog of EloF might exist in D. erecta but not at the same locus, we performed an exhaustive search for all elongase genes within the D. erecta genome. This was achieved using an iterative BLAST search pipeline developed in previous work in our lab (Luo et al. 2020). We applied the same methodology to search for elongase genes across five other species within the melanogaster subgroup. Twenty elongase genes were identified in D. melanogaster genome, whilst only nineteen were found in D. erecta and D. orena genome. Together, our findings indicate that the ortholog of EloF is the only elongase gene absent in the genomes of both D. erecta and D. orena, suggesting a potential independent loss of this gene in these species (Figure 3.2B). This suggests that EloF is not the candidate gene responsible for producing the very long CHCs in D. erecta. This loss may provide insights into the evolutionary divergence of CHC profiles and highlight alternative pathways for producing very long-chain CHCs in female D. erecta. Further functional studies are needed to identify other elongase candidates that could play a role in synthesizing these unique CHCs in this species. 43 Figure 3.2 EloF is not present in the genome of D. erecta. (A) Synteny genome comparison of EloF and other genes in the corresponding cluster. The dotted line box indicates the ortholog of EloF is not found in the genomes of D. erecta and D. orena, suggesting an independent loss of EloF. (B) Phylogeny of all elongases found in the genomes from species across melanogaster subgroup. Amino acid sequences of all elongases were used for the analysis. RAxML maximum-likelihood analyses were conducted under the LG + Γ model. Different numbers of elongase genes were found across the species, 20 in D. melanogaster (Dmel), 20 in D. simulans (Dsim), 20 in D. sechellia (Dsec), 21 in D. yakuba (Dyak), and 19 in D. erecta (Dere). Orthologs lie in the cluster of Dmel/EloF are labeled in pink. Orthologs lie in the cluster of Dmel/Bond are labeled in green. An ortholog of Dmel/EloF is not found in D. erecta and sibling species D. orena. 44 subgroup Figure 3.2 (cont’d) B 3.2.2 Only one elongase gene shows female biased expression in D. erecta oenocytes Our results indicate that the D. erecta genome contains 19 fatty acid elongase genes, compared to 20 in D. melanogaster. To identify the specific elongase gene responsible for producing the very long cuticular hydrocarbons (CHCs) in female D. erecta, we hypothesized that at least one elongase gene would be female-biasedly expressed in 45 the oenocytes of this species. To test this hypothesis, we screened the expression patterns of all 19 elongase genes in the D. erecta oenocyte in situ hybridization by using DIG-labeled RNA probes. The biosynthesis of CHCs is known to occur specifically in the oenocytes of Drosophila (Billeter et al. 2009). Among the 19 elongase genes examined, we found that only one gene, LOC6555117, exhibited female-biased expression in the oenocytes of D. erecta (Figure 3.3). Several other elongase genes were detected with oenocytes expression, but they displayed either male-biased expression (LOC6552258 and LOC6552177) or expression in both sexes (LOC6541898 and LOC6554897) (Figure 3.3). Consequently, we selected LOC6555117 as the candidate gene for further investigation into its role in producing the unique very long CHCs in female D. erecta. This selection sets the stage for subsequent functional studies aimed at determining the involvement of this gene in CHC biosynthesis. 46 Figure 3.3 Expression of elongase genes in 4-day old D. erecta oenocytes. Expression of 19 elongase genes are individually tested by using in situ hybridization, with gene specific probes. Arrows show gene expression in adult oenocytes, and only one gene shows female biased gene expression pattern. 47 3.2.3 Cis-regulatory changes underlie the female biased expression With the candidate gene LOC6555117 showing female-biased expression in oenocytes, we aimed to uncover the mechanisms underlying this expression pattern. In D. melanogaster, the gene DesatF has been implicated in cuticular hydrocarbon (CHC) biosynthesis, with its sex-specific expression attributed to changes in cis-regulatory sequences (Shirangi et al. 2009). We hypothesized that the female-biased expression of LOC6555117 in D. erecta is similarly due to changes in its cis-regulatory regions. To test this hypothesis, we constructed GFP reporter vectors using non-coding DNA sequences surrounding the LOC6555117 gene. Our results indicated that the enhancer responsible for driving oenocyte expression in females is located within the 5’ non-coding region (designated as ereA) of LOC6555117 (Figure 3.4A). The GFP expression driven by ereA exhibited a strong female-biased pattern. In contrast, the homologous region from the sibling species D. orena yielded only weak GFP expression in both sexes (Figure 3.4B). This observation aligns with the in situ hybridization results for the gene expression in these two species (Figure 3.4C), further supporting our conclusion that cis-regulatory differences account for the female- biased expression of LOC6555117 in D. erecta. This finding underscores the importance of regulatory sequence changes in shaping sexually dimorphic gene expression. 48 A B Figure 3.4 Cis-regulatory modifications are responsible for the female-biased expression. (A) Schematic view of the test region (ereA) on D. erecta genome. ereA is located on the 5’ end of the LOC6555117 gene. (B) Gene expression pattern of the GFP reporter protein driven by ereA and oreA (homologous fragment of ereA in sibling species, D. orena). ereA drives highly female biased expression pattern in oenocytes, whilst oreA drives very weak expression pattern. (C) Gene expression of LOC6555117 in the oenocytes of 4-day old adult D. erecta and D. orena. In situ hybridization with specific RNA probes were used to test gene expression. Arrows suggest gene expressions. These results suggest the same trend of gene expression as GFP reporter constructs. 49 Figure 3.4 (cont’d) C 3.2.4 An oenocyte expression module and a sex related module are identified in the regulatory region Having established that the female-specific expression of LOC6555117 is attributed to cis-regulatory changes, we proceeded to identify the specific regulatory modules within the regulatory region. We systematically dissected the 5’ non-coding region of LOC6555117 into three overlapping segments: A1, A2, and A3, constructing corresponding GFP reporter constructs. Among these, A2 exhibited sexually non-biased GFP expression in oenocytes, indicating the presence of an oenocyte-specific driving module (Figure 3.5). Further dissection of A2 led us to a minimum 397 bp sequence, A2.2, which successfully recapitulated the oenocyte-specific expression pattern (Figure 3.5). This was confirmed by building additional constructs A2.2a, A2.2b, and A2.2c, none of which drove strong GFP expression recapitulating A2.2 pattern in adult oenocytes (Figure S3.1). Next, to explore the reason behind the female-biased expression in the ereA GFP reporter construct, we hypothesized the existence of a sex-related module. To test 50 this, we generated two more constructs: A1+A2 and A2+A3. The A2+A3 construct displayed strong female-biased GFP expression in oenocytes, whereas A1+A2 showed non-sex-biased expression. This suggested that a sex-related module is present in the A3 region (Figure 3.5). We further dissected A3 into three sub-regions: A3.1, A3.2, and A3.3. Both additionally narrowed constructs, A2+A3.1 and A2+A3.1+A3.2, could drive non-sex- biased GFP expression, suggesting that the sex-related module is not contained within A3.1 or A3.2 alone. Consequently, we concluded that the sex-related module resides in A3.3, identified as a minimum 400 bp sequence. This work highlights the intricate regulatory architecture underlying female-biased expression of LOC6555117 and contributes to our understanding of the genetic mechanisms underlying sexually dimorphic gene expressions. 51 Figure 3.5 Identification of an oenocyte expression module and a sex-related module in the regulatory region. (A) Schematic dissection of all GFP reporter constructs. Striped box = female biased expression, solidly filled box = non-sex biased expression, no filled box = no expression. (B) GFP reporter protein expression in oenocytes corresponding to the different overlapping constructs. The A2.2 fragment is the minimum region that can recapitulate a sexually monomorphic oenocyte expression. The A2+A3 fragment can recapitulate the female biased oenocyte expression pattern, and a sex related module is suggested in A3.3. The results together suggest that an oenocyte expression module and a sex related module are responsible for the female biased gene expression. 52 Figure 3.5 (c ’d) 53 In summary, our dissection of the 5’ end cis-regulatory region of LOC6555117 identified a minimum 397 bp sequence, A2.2, which serves as a module driving oenocyte-specific, non-sex-biased gene expression. Additionally, we discovered a minimum 400 bp sequence, A3.3, functioning as a sex-related module responsible for generating female-biased expression, operating in conjunction with A2.2. Notably, these two modules are separated by a 915 bp sequence within the D. erecta genome. This delineation of regulatory elements enhances our understanding of the genetic architecture underlying sexually dimorphic gene expressions. 3.2.5 A weaker oenocyte expression module leads to the weak expression in D. orena The final question we addressed was what underlies the weaker expression of the ortholog gene of LOC6555117 in the sibling species D. orena (Figure 3.6). After confirming that A2.2 is the minimum sequence capable of driving oenocyte expression, we obtained the homologous sequence from D. orena, designated as oreA2.2. The GFP reporter construct for oreA2.2 demonstrated weak GFP expression, indicating that this sequence serves as a less effective oenocyte expression module in the D. orena genome. This finding helps explain the observed weaker gene expression in this sibling species (Figure 3.4). 54 Figure 3.6 A weak oenocyte driving module is found in oreA2.2. The homologous fragment of A2.2 in D. orena is named after oreA2.2 and cloned into GFP reporter construct, which can drive weak GFP expressions in oenocytes, suggesting changes in the fragment underline the weak gene expression in oenocytes of D. orena. 3.3 Discussion Sexual dimorphism in cuticular hydrocarbon (CHC) profiles across Drosophila species reflects complex selective pressures that shape the evolution of the traits. Among the species examined, D. erecta exhibits the most pronounced sexual dimorphism in its CHC profiles (Figure 2.1). Comparative analyses within the melanogaster subgroup have confirmed that D. erecta independently evolved the capacity to produce very long, female-specific CHCs, which are representative of exaggerated female traits. However, the mechanisms underlying the evolution of female exaggerated traits remain poorly understood in general due to their rarity in nature. In this study, we investigated the genetic mechanisms underlying the evolution of 55 female exaggerated CHC profiles in D. erecta. By screening the expression patterns of all elongase genes in the oenocytes of D. erecta, we identified an elongase gene, LOC6555117, likely involved in the biosynthesis of these very long CHCs. Notably, LOC6555117 is the only elongase gene exhibiting female-biased expression in the oenocytes of D. erecta (Figure 3.3). Our analysis revealed that this female-biased expression is attributable to cis-regulatory changes located in the 5’ non-coding region of the gene. Through systematic dissection of the regulatory region and the buildups of corresponding GFP reporter constructs, we identified that the female-biased expression results from the functional interaction between an oenocyte-driving module and a sex- related module (Figure 3.5). In contrast, the ortholog of LOC6555117 in the sibling species D. orena shows weak expression in oenocytes of both sexes, where changes in the homologous cis-regulatory module were suggested to contribute to the weak expression (Figure 3.6). Although we successfully identified the sex-related module in A3.3, we could not conclusively determine whether the transcription factor dsx responsible for this sex- related function. Previous studies have shown that dsx is responsible for sex-specific gene expression of other CHC biosynthesis-related genes in D. melanogaster (Hopkins and Kopp 2021). The consensus target sequence of dsx binding domain in D. melanogaster has been predicted by several studies (Burtis et al. 1991; Erdman et al. 1996; Narendra et al. 2002). We utilized the Erdman-Burtis Consensus sequence, “RNNACWAWGTNNY,” to query the 5’ regulatory region of LOC6555117. Although we did not find any specific alignment of the consensus sequence in A3.3, alignments were present in other regions of the regulatory sequence (Figure S3.2). Despite this, we 56 cannot rule out the possibility that dsx contributes to the female-biased expression pattern of this gene. Furthermore, additional investigation suggests that hormonal mediation may play a significant role in this expression pattern. Our preliminary results show that LOC6555117 is expressed strongly in both sexes of 1-day-old D. erecta without sex biases, indicating that sex-biased expression may be age-related and likely under hormonal mediation (Figure S3.3). Our findings indicate the presence of two distinct types of modules driving oenocyte expression in these closely related species: one that facilitates strong expression in D. erecta and another that produces very weak expression in D. orena (Figure 3.6). However, the specific evolutionary gains and/or losses of these modules remain unclear. We hypothesize that the strong oenocyte expression module in D. erecta represents an independent evolutionary gain, but requires further investigation. Additionally, while our data indicate that cis-regulatory changes are responsible for the female-biased expression of LOC6555117, coding changes in the candidate gene may also contribute to the production of very long CHCs in female D. erecta. Preliminary data generated from RNA interference (RNAi) targeting the gene Bond (the ortholog of LOC6555117 in D. melanogaster) in a transgenic D. melanogaster line suggest that knocking down Bond expression reduces two major female-specific CHC compounds, underscoring its importance in maintaining sexual dimorphism in CHC profiles (Figure S3.4). Future work examining the effects of manipulating LOC6555117 expressions on the CHC profiles of D. erecta will provide valuable insights into answering the question. Indeed, LOC6555117, with its female-biased oenocyte expression in D. erecta, is our candidate gene responsible for the production of very long CHCs. However, direct 57 evidence of its functional role must be obtained through gene knockdown, knockout, or overexpression. In the absence of such evidence, other CHC biosynthesis-related genes may also play a role, particularly those previously shown to influence CHC length, such as fatty-acyl CoA reductase (Rusuwa et al. 2022). We have also observed sex-biased expression in several reductase genes in D. erecta oenocytes as preliminary results (Figure S3.5). Interestingly, Bond, the ortholog of LOC6555117 in D. melanogaster, has also been implicated in the biosynthesis of another Drosophila sex pheromone, CH503 (Ng et al. 2015). Furthermore, additional regulatory modules for Bond have been identified in other non-coding regions, reflecting rapid evolutionary changes in enhancers across species (Pu et al. 2021). Thus, we propose that Bond may function as a "toolkit" gene, incorporating rapid evolutionary modifications in cis-regulatory regions, likely contributing to the correlation between gene function and specification processes, particularly in the diversification of pheromone evolution. To enhance our understanding of the evolution of this female exaggerated trait, the ecological role of very long CHCs in D. erecta must be further explored. Initially, we proposed three parallel hypotheses: 1) D. erecta and its sibling species D. orena are thought to have evolved sympatrically (Linz et al. 2013), establishing a premating reproductive isolation barrier (Lee and Watanabe 1987); therefore, very long CHCs may contribute to mate recognition as a premating reproductive barrier. 2) As honest signals, the production of these very long CHCs could be condition-dependent, with quantitative variations influencing female sexual attractiveness and male mate choice. This hypothesis is based in previous studies that have suggested that the dose effect of 58 major CHC components as aphrodisiacs elicits varying male courtship behaviors (Billeter et al. 2009). 3) These very long CHCs may also be involved in other essential physiological processes, such as desiccation resistance, with evidence indicating that CHC chain length is positively correlated with desiccation resistance (Ferveur et al. 2018). Thus, the elaboration of these very long CHCs in females may also result from natural selection alone, as suggested in other study systems (Okada et al. 2021). In summary, this study provides novel insights into the genetic mechanisms underlying the evolution of female exaggerated traits, specifically the very long CHCs in female D. erecta. 3.4 Materials and Methods Drosophila species and strains The D. erecta line were obtained from the National Drosophila Species Sock Center (NDSSC). The D. orena line was gifted by Dr. Mark Rebeiz (University of Pittsburgh) The D. melanogaster attP40, UAS-Bond RNAi strain was obtained from the Bloomington Drosophila Stock Center. The D. melanogaster G3-GAL4 strain was obtained from our previous work (Wang et al. 2023). All species and strains were reared on standard cornmeal medium (Flystuff 66-121 Nutri-Fly Bloomington Formulation). In situ hybridization in adult oenocytes Adult oenocytes from 4-day old adults were dissected in Phosphate-Buffered Saline (PBS). RNA probes were made from 4 cDNA mixtures of 4 to 5 day-old adults using the primers listed in Table S3.1, as described previously (Pu et al. 2021). The procedure of performing in situ hybridization of 4-day old adult oenocytes was adapted from a previous study (Finet et al. 2019). 59 Data Collection Elongase genes were identified in five complete Drosophila genomes by using D. melanogaster protein sequences to preform tblastn. The five genomes were retrieved from the National Center for Biotechnology Information website (https://www.ncbi.nlm.nih.gov/). Repeated tblastn were used following a previously described searching pipeline to make sure all elongase genes from each species were identified (Luo et al. 2020). Genomic information of the five species was also used to perform synteny analyses to determine the presence or absence of ortholog of EloF in the cluster in the genome of D. erecta. Phylogenetic analysis Amino acid and DNA sequences were aligned with MUSCLE with manual adjustments (Luo et al. 2020). Maximum-likelihood searches were performed using Phylogeny.fr (http://phylogeny.lirmm.fr/phylo_cgi/contacts.cgi) using a gamma distribution for final likelihood evaluation. One-thousand bootstrap replicates were conducted for support estimation, (Dereeper et al. 2008). Generation of GFP reporter constructs and transgenic flies All GFP reporter constructs were produced by firstly using PCR amplifying the test fragments from the genomes of D. erecta or D. orena. The fragments were then cloned into the GFP reporter vector pS3aG via the AscI and SbfI sites (all primers listed in Table S3.1). All constructed were micro-injected into the D. melanogaster attP40 strain, which were using the PhiC31 integrase system to get integrated into the genome. Imaging All in situ hybridization and GFP images were captured using the Nikon SMZ18 60 dissecting stereo microscope system, as described previously (Pu et al. 2021). For GFP imaging, samples were prepared by dissecting four-day old adults in PBS and transferred on slides with glycerol mountant [80%(vol/volinwater) glycerol, 0.1 M Tris (pH 8.0)]. CHC profiles analyses Offspring of crossing the D. melanogaster G3-GAL4 and UAS-Bond RNAi strains was generated to test the changes in CHC profiles in D. melanogaster after knocking down Bond expression in adult oenocytes. CHCs were extracted typically from five four- to five-day-old offspring adult flies soaked in 100 µl hexane containing hexacosane (C26; 25 ng/ul) as internal standard for ten minutes. Extracts were directly analyzed by the GC/MS (7890A, Agilent Technologies Inc., Santa Clara, CA) coupled with a HP-1ms column 30 m by 0.25 mm (i.d.) with a 0.25 µm film thickness (J&W Scientific, Folsom, CA). Mass spectra were acquired in Electron Ionization (EI) mode (70 eV) with Total Ion Mode (TIM) using the GC/MS (5975C, Agilent Technologies Inc., Santa Clara, CA). The peak areas were recorded by MassHunter software (Agilent Technologies Inc., Santa Clara, CA). Helium was the carrier gas at 0.7 ml/min and the GC thermal program was set as follows: 60 °C for 4 min, 15 °C/min to 200 °C, 5 °C/min to 280 °C, then held for 10 min. Straight-chain compounds were identified by comparing retention times and mass spectra with authentic standard mixture (C6-C40) (Supelco 49452-U, Sigma- Aldrich, St. Louis, MO). Methyl-branched alkanes, alkenes, dienes and cis-Vaccenyl acetate were then identified by a combination of their specific fragment ions on the side of functional groups (methyl branch or double bonds) and retention times relative to linear-chain hydrocarbon standards. Each individual CHC peak was quantified using its 61 comparison with peak area of internal standards. Statistical Analyses PCA analyses were performed using the `prcomp()` function in R. The student’s t-tests were used to determine significant changes in CHC profiles between test lines, and were performed using the `t.test()` function in R. All analyses were conducted in RStudio (Rstudioteam 2022). 62 CHAPTER 4. PHENOTYPIC TRADEOFFS OF PRODUCING COSTLY CHCS IN DROSOPHILA MOJAVENSIS I would like to acknowledge the following colleagues, since this chapter could not have been accomplished without the contributions made by them. Ishu Kudapa • Assisted in performing two-choice mating assay and development assay Nathaniel Fellows • Assisted in testing reproductive fitness and longevity Bella Balabuszko-Reay • Assisted in performing development assay Dr. Rajanikanth Chowdanayaka • Assisted in performing two-choice mating assay Jordy Hernandez • Assisted in testing reproductive maturity and latency Zhuo Chen • Assisted in performing two-choice mating assay Dr. Zinan Wang • Assisted in performing two-choice mating assay and development assay 4.1 Introduction Interactions among individuals in natural environments can lead to conflicts over limited resources. In particular, conflicts between males and females often relate to mating (Darwin 1871). A common reproductive strategy involves individuals mating with higher- quality partners to maximize reproductive fitness. Consequently, selection may favor 63 signals that indicate the presence of high-quality mates. Substantial research has focused on understanding the mechanisms underlying the evolution of mating signals, particularly regarding the maintenance of signal reliability, commonly referred to as "honest signaling" (Husak et al. 2015). Multiple perspectives and intense debates have emerged to explain the reliability of these signals. Signal reliability is thought to evolve when the cost-to-benefit ratio for the signal sender is low, ultimately leading to an equilibrium. The theory positing that the cost to the sender is crucial for maintaining signal reliability is known as the "handicap" principle, which is widely accepted (Zahavi 1975). Grafen first tested the "handicap" theory using a mathematical model, suggesting that 1) larger or more intense signals incur higher production costs and 2) higher-quality senders can produce larger signals at lower marginal costs (Grafen 1990). Empirical studies have largely supported these predictions (Murai et al. 2009). For instance, in barn swallows (Hirundo rustica), it was observed that short-tailed males experienced greater survival challenges compared to long-tailed males when artificial tail extensions were introduced (Moller et al. 1995). However, it has become increasingly evident that existing studies predominantly focus on testing the "handicap" theory, necessitating further insights into the precise costs associated with honest signaling (Kotiaho 2001; Getty 2006; Husak et al. 2015). Understanding the costs incurred by signal senders is essential for elucidating the evolution of signal reliability under the "handicap" theory, thereby addressing the cost- to-benefit ratio to produce honest signals. Nonetheless, the limited research tools available have hindered the exploration of novel perspectives. Husak et al. highlighted this interdisciplinary gap, noting that behavioral 64 ecologists often predict potential costs for senders through mathematical models but conduct fewer functional tests. Conversely, functional morphologists have focused on examining the biomechanical mechanisms underlying signal traits without a solid theoretical framework. Husak et al. emphasized the significance and advantages of integrating more functional approaches in the investigation of animal signaling costs (Husak et al. 2015). This study aims to address the important but underexplored issue of the costs associated with producing reliable signals. The costs related to signal production are largely attributed to increased energy allocation, where significant alterations in energy investment can lead to multiple phenotypic consequences (Royle et al. 2006). Several major phenotypic trade-offs associated with energy allocation for signaling have been proposed and tested. For example, there is a fitness cost, where the selection pressure to secure high-quality mates is exerted through the production of reliable signals. In Lobesia botrana (Lepidoptera: Tortricidae), the major components of female chemical profiles are suggested to serve as honest signals of quality; larger females producing more sex pheromones is preferred by males, but producing the chemical signals is suggested to suffer cost in survival for both large and small females (Harari et al. 2011). Additionally, trade-offs in growth can occur due to signaling, resulting from constraints related to underlying biomechanical and physiological correlations in various systems (Blake 2004). A study on field crickets (Teleogryllus commodus) examined trade-offs between calling effort, with life history traits and longevity, suggesting that the heavy investment in producing mating calls by males resulted in early adulthood death in this species (Hunt et al. 2004). 65 The evolution of cuticular hydrocarbons (CHCs) has been influenced by multiple selective pressures, with experiments involving artificial selection indicating interactions between natural and sexual selection across various systems (Blows 2002; Berson et al. 2019). Our findings in the first chapter did not support the notion that CHC profiles can be predicted by their roles as mating signals (Figure 2.5), highlighting the complexity involved in the evolution of CHC production. The multifaceted nature of CHCs arises from their various functions. In addition to serving as mating signals, CHCs in the insect cuticular wax layer also play roles in preventing water loss (Chung and Carroll 2015; Leeson et al. 2020; Mitchell et al. 2023) and conveying insecticide resistance (Balabanidou et al. 2016; Chen et al. 2020; Pu et al. 2020). Given their multiple functions, natural and sexual selection may interact synergistically or antagonistically in the evolution of insect CHCs, potentially resulting in trade-offs (Blows 2002; Berson et al. 2019). We propose that insect CHCs serve as an excellent model for exploring evolution driven by complex selective pressures. This study will specifically use CHCs in Drosophila to investigate the potential constraints and costs associated with CHC production for signaling purposes. In our previous work, methyl-branched CHCs (mbCHCs) were identified as key mediators of desiccation resistance across Drosophila specie (Chung et al. 2014; Wang et al. 2022). D. mojavensis produces long-chained mbCHCs as its major compounds, which are believed to confer high desiccation resistance (Wang et al. 2023). A transgenic line of D. mojavensis (Dmoj/mElo elongase gene knockout) developed in this study produces approximately 50% less major mbCHCs compared to the wild type, specifically producing no 2-methyl-hexacosane (2MeC32) and lower amounts of 2- 66 methyl-triacontane (2MeC30) (Figure S4.1). CHC production has been demonstrated to be an important sensory modality that elicits male courtship behavior and contributes to mate recognition (Figure 2.2). Therefore, we first tested whether the major constituents, mbCHCs, act as honest signals indicating mate quality, potentially reflecting abilities in stress response. Moreover, metabolic studies have suggested that mbCHC production is costlier compared to other linear-chained CHCs (Nelson 1993). However, the phenotypic consequences of this costly production have yet to be determined. Consequently, we investigated the costs associated with producing long-chained mbCHCs in terms of life history traits, longevity, and reproductive fitness. By employing advanced genetic manipulation techniques, this study aims to provide novel insights into the costs of signaling. 4.2 Results 4.2.1 Quantitative changes in mbCHCs do not affect mate preferences Having confirmed that cuticular hydrocarbon (CHC) input is essential for maintaining male courtship interest in D. mojavensis (Figure 2.2), we further investigated whether the methyl-branched CHCs (mbCHCs) produced by female D. mojavensis have evolved as honest signals indicating individual mate quality. To address this question, we conducted two-choice mating assays, exposing wild-type focal individuals (ISO1) to potential mates from two lines: one producing lower levels of mbCHCs (M3.5, Dmoj/mElo knockout) and the other being wild-type (ISO1). This design allowed us to assess potential differences in mate preferences between the sexes. Our results indicated that focal individuals from the ISO1 line did not exhibit significant differences in mate preferences toward the two lines (Table 4.1). Considering 67 that the primary difference between the two chosen lines is the quantity of mbCHCs produced, we suggest that variations in mbCHC levels are not correlated with sexual attractiveness in D. mojavensis. This further implies that mbCHCs, as major constituents of CHC profiles, do not serve as reliable indicators of mate quality for either sex of D. mojavensis. Table 4.1 Quantitative changes in mbCHCs do not mediate mate preferences in D. mojavensis. Two-choice mating assays were used to test the mate preferences. ISO1 = wildtype D. mojavensis, M3.5 = transgenic line (Dmoj/mElo knockout) of D. mojavensis with lower amount of mbCHCs production. Chi-square tests were used to determine significant differences in mate preferences. No significant differences were found in either sex, suggesting quantitative changes of mbCHCs did not affect mating preferences. 4.2.2 No tradeoffs between development and mbCHC production Methyl-branched cuticular hydrocarbons (mbCHCs) have been shown to elicit sustained courtship interest in males as mating signals (Figure 2.2), but do not reflect mate quality (Table 4.1). Additionally, mbCHCs mediate desiccation resistance under extreme stress conditions, but not under intermediate stress (Wang et al. 2023). In light of this, we aimed to investigate the potential costs associated with the production of excessive mbCHCs. We first hypothesized that development might be negatively impacted as a cost of producing mbCHCs. This could occur for two reasons: 1) energy may be redirected from growth to signaling, and 2) growth could be inhibited due to "pleiotropic" effects stemming from metabolic changes required for signaling. To test this hypothesis, we examined developmental traits, including egg-to-adult viability and egg-to-adult 68 Focal IndividualnISO1 chosenM3.5 chosendfχ2PISO1 ♂43192410.7440.39ISO1 ♀56272910.0360.85 development duration. We anticipated that, the M3.5 (Dmoj/mElo knockout) would show higher egg-to-adult viability and shorter egg-to-adult development duration compared to the wild-type (ISO1), due to reducing the unnecessary compensatory growth for increased energy intake. However, our results revealed no significant differences in either developmental trait: egg-to-adult viability (t = 0.78, p = 0.44; Figure 4.1A), female egg-to-adult development duration (t = 1.60, p = 0.11; Figure 4.1B), and male egg-to-adult development duration (t = 0.46, p = 0.65; Figure 4.1C). These findings suggest that there are no developmental costs associated with the changing production of mbCHCs in D. mojavensis. 69 Figure 4.1 Development related life history traits were not affected by changes in mbCHCs production. ISO1 = wildtype D. mojavensis, M3.5 = transgenic line (Dmoj/mElo knockout) of D. mojavensis with lower amount of mbCHCs production. Student’s t-tests were used to determine any significant differences in these phenotypic traits between the two test lines. No significant difference was found in egg-to-adult viability (A), female egg-to-adult development (B), and male egg-to-adult development (C). n.s = not significant. 4.2.3 Reproductive performance was negatively impacted in the transgenic line with decreased production of mbCHCs We then investigated the potential costs associated with producing methyl-branched cuticular hydrocarbons (mbCHCs) on reproductive traits, specifically examining reproductive latency and reproductive fitness. We hypothesized that due to limited resource storage in adults and subsequent energy competition, trade-offs would exist 70 between reproduction and CHC synthesis. Consequently, we anticipated shorter reproductive latency and higher reproductive fitness in the M3.5 (Dmoj/mElo knockout) compared to wild-type (ISO1). However, our findings revealed a significant increase in reproductive latency for the M3.5 line, with an average of 6.08 days required to produce the first offspring, compared to 5.39 days for the ISO1 line (t = 2.92, p < 0.01; Figure 4.2A). Furthermore, the M3.5 line exhibited a significant reduction in offspring numbers, with five virgin pairs averagely producing 175.33 viable adults, compared to 234.11 viable adults produced by the ISO1 line (t = 3.01, p < 0.01; Figure 4.2B). These results do not support the existence of a trade-off between energy investment in reproduction and mbCHC synthesis. In fact, the negative changes observed in reproductive traits in the Dmoj/mElo knockout line suggest a potential role for Dmoj/mElo in reproduction- related physiological processes. Figure 4.2 Negative impact on reproductive performance in transgenic lines with reduced mbCHC production. ISO1 = wildtype D. mojavensis, M3.5 = transgenic line (Dmoj/mElo knockout) of D. mojavensis with lower amount of mbCHCs production. Student’s t-tests were used to determine any significant differences in these phenotypic traits between the two test lines. M3.5 show significantly increased reproductive latency after emergence before first offspring produced (A), and significantly reduced reproductive fitness by five pairs of virgin flies (B). **p < 0.01. 71 4.2.4 Decreased longevity in transgenic lines with reduced mbCHC production Additionally, methyl-branched cuticular hydrocarbons (mbCHCs) have been shown to play a crucial role in desiccation resistance in D. mojavensis (Wang et al. 2023), and empirical evidence suggests that desiccation resistance is positively correlated with increased longevity in Drosophila (Rose et al. 1992). Consequently, we hypothesized that the M3.5 line would exhibit weaker survivorship (shorter longevity) compared to the ISO1 line, which could also contribute to higher reproductive fitness tested above. To test this hypothesis, we assessed the longevity of both lines and compared their 50% mortality rates (LT50). Our results indicated no significant difference in LT50 between the two lines for either sex (males: t = 0.70, p = 0.51, Figure 4.3A; females: t = 1.88, p = 0.10, Figure 4.3B). Additionally, we compared the difference in longevity between the two lines. Males of both lines did not show significant difference (p = 0.15; Figure 4.3C). Additionally, females of ISO1 line demonstrated significantly longer survival times than their M3.5 counterparts (p < 0.01; Figure 4.3D). Therefore, we suggest that the higher reproductive fitness observed in the ISO1 line can be partially attributed to females’ significantly extended lifespan, while acknowledging that Dmoj/mElo may still play a functional role in reproductive processes, contributing to the increased reproductive latency. 72 Figure 4.3 Lifespan of wildtype and transgenic lines of D. mojavensis. ISO1 = wildtype D. mojavensis, M3.5 = transgenic line (Dmoj/mElo knockout) of D. mojavensis with reduced mbCHCs production. Student’s t-tests were used to determine any significant differences in these phenotypic traits between the two test lines. No significant difference between 50% mortality (LT50) in males (A) and females (B) between the two test lines. n.s = not significant. Kaplan-Meier approach was used to test the significance in survivorship. The percentage of surviving adults were shown from the enclosed day. No significant difference was found between males (p = 0.15) (C). ISO1 females show significant better surviving ability than M3.5 females (p < 0.01) (D). 4.3 Discussion The production of reliable signaling is a topic of considerable discussion among 73 evolutionary biologists, posited to be influenced by complex interactions between natural selection and sexual selection. Among the various theories, the "handicap" theory is the most widely accepted, explaining the evolution of reliable signaling through the costs versus benefits incurred by signalers (Zahavi 1975). Therefore, understanding the absolute costs associated with the production of mating signals is essential for comprehending the underlying evolutionary processes. However, empirical evidence regarding the costs of signal production remains limited, primarily due to a lack of interdisciplinary approaches and appropriate research tools (Husak et al. 2015). In this study, we utilized two lines of D. mojavensis from previous research: ISO1 (wildtype) and the genetically modified M3.5 line, which produces lower amounts of methyl-branched cuticular hydrocarbons (mbCHCs) due to Dmoj/mElo knockout. MbCHCs have been demonstrated to elicit sustained courtship interest from conspecific males, functioning as signals for mate recognition. We first aimed to determine whether mbCHCs could serve as indicators of individual mate quality in a dose-dependent manner. Results from two-choice mating assays did not support this hypothesis. We argue that these findings are robust, as further testing under heat stress conditions (37°C) is unnecessary, given that elevated temperatures are known to negatively impact courtship behavior in D. mojavensis (Patton and Krebs 2001; Shaible 2020). Nonetheless, our results do not rule out the possibility that other CHC components may mediate sexual attractiveness and convey mate quality. Markow and Toolson suggested that the quantities of two dienes—pentatriacontadiene (C35:2) and heptatriacontadiene (C37:2)—may vary with rearing temperature and exhibit condition- specific plasticity, affecting sexual attractiveness in this species (Markow and Toolson). 74 However, in our study, the knockout of Dmoj/mElo did not alter the levels of these dienes (Wang et al. 2023). This indicates that the evolution of CHC profiles is shaped by complex selective pressures that may act on specific types of CHCs. In this context, mbCHCs primarily mediate desiccation resistance under natural selection, while the longer CHCs—dienes—may convey sexual attractiveness. Future studies across different species would enhance our understanding of the selective forces shaping CHC evolution. Given the model prediction that producing mbCHCs incurs significant costs (Nelson 1993), we further examined the potential costs of mbCHC production in terms of phenotypic consequences. Our findings indicated no developmental costs associated with mbCHC production; however, the genetically modified M3.5 line demonstrated reduced reproductive success and female longevity. It is noteworthy that reduced longevity was observed only in females, indicating the potential of sexual antagonism in the evolution of mbCHCs production shaped by natural selection in this species. A similar hypothesis has been posited that natural or sexual selection may drive different evolutionary trajectories in CHC profiles between sexes in another mbCHC producer, D. birchii (Blows 2002). Empirical evidence is essential for testing this hypothesis. Long-chain mbCHCs (2Me-C28) have been implicated in desiccation resistance in D. melanogaster (Wang et al. 2023). We therefore posed the question of whether natural aging processes (survivorship) and stress resistance (desiccation resistance) could be attributed to these specific long-chain mbCHCs. We investigated the survivorship of different lines of D. melanogaster that produce varying amounts of long- chain mbCHCs by employing the UAS-GAL4 system to either upregulate (overexpress) 75 or downregulate (RNAi knockdown) the gene Dmel/CG18609 in adult oenocytes. Our results showed significantly improved survivorship in both modified gene expression directions, suggesting no direct relationship between long-chain mbCHC production and aging (survivorship); instead, the primary role appears to be in stress resistance (Dmel/CG18609 overexpression females: p = 0.012; males: p < 0.01; Dmel/CG18609 RNAi females: p < 0.01; males: p < 0.01; Figure S4.2). A sexually dimorphic trend was observed in both mbCHC-related studies, indicating a potential antagonistic pleiotropy of natural selection in both sexes. Collectively, these results suggest a positive correlation between mbCHCs and mate quality, with higher amounts of mbCHCs being related to higher reproductive fitness and better survivorship; however, they do not appear to have evolved into honest signals for mate choice and mate preferences. Further investigation into the mechanisms governing the production of the dienes C35:2 and C37:2 would yield valuable insights into the broader context of CHC evolution. Additionally, biomechanical and physiological trade-offs are frequently observed in various systems (Vanhooydonck et al. 2001; Vandame et al. 2002; Blake 2004). The differential expression of Dmoj/mElo in our study likely contributes to these phenotypic changes, suggesting potential genetic architectures associated with CHC biosynthesis pathways that underlie the complex evolutionary processes involved in signal production. In conclusion, the evolution of CHC production, which serves multiple functions, may involve interactions between natural selection and sexual selection that can be synergistic or antagonistic. Honest mating signals could emerge when evolutionary trajectories align, whereas deception may arise under conflicting pressures. 76 Determining the costs of signal production is crucial for understanding the "handicap" theory, and we propose that CHCs in Drosophila serve as excellent models for further investigations into the independent evolution of chemical signaling. 4.4 Materials and Methods Drosophila species and strains Two test lines of D. mojavensis, wildtype (ISO1) and a line that produces no 2MeC32 and lower amounts of 2MeC30 (M3.5, Dmoj/mElo knockout), were obtained from a previous study in the lab (Wang et al. 2023). To generate lines of D. melanogaster with Dmel/mElo overexpression or RNAi for the additional longevity tests, we crossed the 5′mFAS-GAL4 driver line (which expresses GAL4 in adult oenocytes) with the UAS- mElo overexpression and UAS- mElo RNAi lines as described in a previous study (Wang et al. 2022). All flies were reared and tested at 25℃ with 12h: 12h light: dark cycle, on standard cornmeal medium (Flystuff 66-121 Nutri-Fly Bloomington Formulation). Two choice mating assays The protocol was adapted from a previous study (Chung et al. 2014). Ten-day-old virgin flies were used in the tests, consistent with the previous methods reported in Chapter 2 for this species. Two lines of test flies were painted with blue or orange acrylic paints (DecoArt®) under CO2 anesthesia 24hr before the tests. The color of paints used for the two lines were constantly shifted across all tests to eliminate the potential effects caused by coloration. In each setup, two chosen individuals from each line were introduced first, and then the focal individual from opposite sex was introduced as the start point of the test. Mate preferences of females were determined by the first male 77 they mated with. Mate preferences of males were determined by the first female they showed courtship rituals (Table 1.1) towards. Development Assays The protocol was adapted from a previous study (Etges 1990). Two batches of actively reproducing adults from each test line were reared in fly cages. Eggs laid were collected and randomly grouped into 40 on cover slides. The eggs were then transferred to fresh food vials for development assays. Egg-to-adult viability was determined by the total viable adults emerged from each vial divided by 40 [n (ISO1) = 17, n (M3.5) = 19]. Egg- to-adult duration was determined by the number of days, from the day when eggs were collected, to the day newly emerged adults were collected, where two sexes were recorded separated [n (ISO1-M) = 73, n (M3.5-M) = 91, n (ISO1-F) = 78, n (M3.5-F) = 85]. Reproduction Assays Virgin flies collected on the day of emergence, from the previous development assays were used for the reproduction related traits tests. Each replicate consists of five females and five males from each line introduced into single fresh food vial. Reproduction latency was determined by the number of days, from the day adults emerged, to the day the first egg or larvae was observed [n (ISO1) = 23, n (M3.5) = 24]. The observations were made and checked by two individuals separately. After the first offspring was observed, the flies were regularly transferred into fresh food vials, with 2- or-3-day intervals. All food vials with the offsprings produced by same parental individuals form a cohort. The reproductive fitness was determined by the number of all viable adults collected from a cohort [n (ISO1) = 9, n (M3.5) = 9]. 78 Longevity Assays The protocol was adapted from a previous study (Linford et al. 2013). Virgin flies collected from the previous development assays were used for testing longevity. Each replicate experiment consists of either ten males or females from each test line transferred into single fresh food vial. Flies were regularly transferred into fresh food vials, at every 2-or-3-day intervals. 50% mortality (LT50) was determined by duration between the day of the start of the experiment and the day half (5) test individual died [n (ISO1-F) = 5, n (M3.5-F) = 5, n (ISO1-M) = 7, n (M3.5-F) = 5]. Longevity was determined by the number of alive days after emergence for each individual [n (ISO1-F) = 50, n (M3.5-F) = 50, n (ISO1-M) = 70, n (M3.5-F) = 50; n (Dmel/CG18609 overexpression female) = 78, n (Dmel/CG18609 RNAi female) = 76, n (Dmel/CG18609 overexpression male) = 77, n (Dmel/CG18609 RNAi male) = 75, n (overexpression control female) = 75, n (overexpression control male) = 72, n (RNAi control female) = 66, n (RNAi control male) = 75]. Statistical Analyses The student’s t-tests tests were used to determine significant changes in phenotypic traits between test lines, and were performed using the `t.test()` function in R. Kaplan- Meier approach was used to test the significance in survivorship through the `survival` and `survminer` packages in R, adapted from a previous study (Linford et al. ; Therneau 2015; Kassambara et al. 2016). All analyses were conducted, and figures were produced in RStudio (Rstudioteam 2022). 79 CHAPTER 5. GENERAL DISCUSSION AND FUTURE RESEARCH DIRECTIONS 5.1 Summary of the research projects Sexual dimorphism highlights remarkable beauty and diversity in nature, with mating signals serving as common representations of this phenomenon. Multimodal mating signals have been suggested in various systems across the animal kingdom, and both sexual dimorphism and mating signals can be classified into various types, each suggesting different levels of information conveyed either inter- or intraspecifically (Figure 1.1). The evolution of sexual dimorphism and mating signals is influenced by complex interactions among multiple selective pressures, prompting significant interest and discussion among evolutionary biologists. This focus stems from our fascination with nature and aesthetics, as well as the crucial roles these traits play in central topics related to reproductive isolation and speciation. Despite this interest, understanding these intricate evolutionary processes presents challenges, and empirical evidence needs to be further explored across diverse study systems. Importantly, there are still unresolved questions that must be addressed. In this dissertation, we investigated three important questions in evolutionary biology: 1) Is there a correlation between the evolution of sexual dimorphism and the evolution of mating signals? Can the degree of sexual dimorphism be used to predict the functional roles of these traits as mating signals? 2) To understand the evolution of sexual dimorphism, what genetic mechanisms underlie exaggerated female traits? 3) To understand the evolution of mating signals, what phenotypic trade-offs exist as costs associated with the evolution of these signals? (Figure 5.1). 80 Figure 5.1 Overview of the research projects and dissertation. We utilized cuticular hydrocarbons (CHCs) in Drosophila species as a model to investigate these questions. Previous studies on CHCs have indicated both 1) the presence of varying levels of sexually dimorphic CHC profiles across species and 2) the role of CHCs in Drosophila as contact pheromones for chemical communication (Ferveur 2005). Initially, we assessed the degrees of sexual dimorphism using the Bray-Curtis dissimilarity index and tested the effects of CHC perception on maintaining male courtship interest across species. Our findings did not provide sufficient evidence to support a correlation between the degree of sexual dimorphism and the use of CHCs for male mate recognition (Chapter 2). Next, we focused on the Drosophila species exhibiting the highest degree of sexual dimorphism in CHCs, D. erecta, investigating the genetic mechanisms underlying the evolution of the exaggerated female traits. We identified a candidate gene LOC6555117 with female-biased expression in adult oenocytes that is likely responsible to produce this trait. The observed female-biased expression pattern is attributed to cis-regulatory changes, with two specific modules identified: an oenocyte expression module and a sex-biased expression module 81 (Chapter 3). Finally, we explored the potential costs of producing methyl-branched cuticular hydrocarbons (mbCHCs) in transgenic lines of D. mojavensis, which generate mbCHCs as the major compounds in their CHC profiles. Our results do not show direct developmental tradeoffs of producing mbCHCs, but indicate that mbCHC production is positively correlated with reproduction and longevity. Even though mbCHCs are positively correlated with individuals’ fitness, it did not evolve into serving as honest signals to mediate mate preferences. (Chapter 4). Based on these results, I proposed several specific directions for future research in each chapter. The findings presented in this dissertation are expected to address the proposed questions and provide novel insights into the evolution of both sexual dimorphism and mating signals. 5.2 Evolution of mating signals: interactions among multimodal sensory modalities and plasticity with environmental change Multimodal sensory modalities are proposed to function as a series of mating signals, potentially conveying different levels of information (Table 1.1). Mating signals have traditionally been categorized into visual, acoustic, chemical, and mechanical signals, based on the sensory modalities used for information perception. The evolution of each type of mating signal is influenced or constrained by the underlying genetic architecture, which has been extensively studied. However, future research should focus on the specific mechanisms by which each signal operates in natural contexts, potentially in a condition-dependent manner. Firstly, within the framework of generalized sensory modalities, specific mating signals can be transmitted and perceived differently. For instance, within the realm of 82 chemical signals, both volatile pheromones (Karlson and Butenandt 1959) and contact pheromones (Guarino et al. 2008) have been identified. Due to the chemical characteristics of these compounds, their functions in nature differ significantly; volatile chemicals typically facilitate long-range interactions, while contact pheromones are necessary for close-range interactions (Duffy et al. 2018). It is plausible that long- distance volatile pheromones evolved for mate recognition, conveying information about species and sex, whereas short-distance contact pheromones indicate mate quality, contributing to mate choice and preferences. For example, in the multicolored Asian ladybeetle, Harmonia axyridis (Coleoptera; Coccinellidae), volatile pheromones are utilized for long-distance selection, while non-volatile contact pheromones serve short- distance selection (Brown et al. 2006; Durieux et al. 2012). Distinct short- and long- distance mating signals have also been observed in other sensory modalities, such as the two calling song classes in dark-eyed juncos (Junco hyemalis) (Titus 1998). Investigating the parallel evolution of these short- and long-distance signals, which convey similar information, may provide novel insights, particularly regarding the evolution of contact pheromones and visual signals related to fecundity. It would also be intriguing to determine whether the parallel evolutions among sensory modalities are biomechanically and physiologically correlated in a synergistic or antagonistic manner, potentially compensating for the loss of one sense or providing contrasting information that reflects different aspects of mate quality. Secondly, it is crucial to understand how environmental changes shape the future evolutionary trajectories of mating signals. Effective signaling relies on the appropriate environmental context for information transmission. Changes in environmental 83 conditions can positively or negatively affect individual signal modalities, making it essential to test the plasticity of these signaling traits. Additionally, the interactions between individual mating signals and other signal traits, which may exhibit varying levels of resilience under environmental changes, require further investigation. In particular, climate change and urbanization have received increasing attention as significant environmental changes. The work of Heinen‐Kay highlights how urbanization affects sexual communication and mating signals in the Anthropocene (Heinen‐Kay et al. 2021), suggesting that similar studies across a broader range of taxa could enhance our understanding of this issue, especially in arthropods. Finally, I emphasize the importance of understanding the plasticity of reproductive strategies in response to perception of divergent mating signals. Sociosexual environments can influence mating strategies, providing evidence of plasticity (Cong and Wang 2021). For instance, in Drosophila, both mating latency and duration can be altered by the population's sex ratio (Dore et al. 2021). If sociosexual factors are reflected in signaling, then investments in mating are likely to evolve plasticity as a response to the perception of these signals. Addressing these issues will further our understanding of population dynamics and related ecological processes. 5.3 Evolution of sexual dimorphism: further dissecting traits with specific characteristics In addition to the previously proposed avenues for future research in the evolution of sexual dimorphism, such as investigating the evolution of female exaggerated traits in light of the dynamic nature of sexual roles, the complex drives of sexual dimorphism remain poorly understood. In Chapter 4, we proposed the possibility that different types 84 of cuticular hydrocarbon (CHC) compounds produced by D. mojavensis may serve distinct functions, each influenced by different selective forces. MbCHCs primarily mediate desiccation resistance under natural selection, while the longer CHCs— dienes—may convey sexual attractiveness in this species. To further elucidate these potential drives, it would be beneficial to dissect sexual dimorphism into secondary sexual characters into multiple, more specific traits. For example, in the case of the lion’s mane—a secondary sexual character—female mate choice is influenced by two primary axes of variability: mane length and coloration. Research has suggested that mane length primarily affects male-male competition, while coloration primarily responds to environmental changes (West and Packer 2002). This framework can be applied to other sexually dimorphic traits, where multiple characteristics can be identified. For instance, body coloration may be broken down into both coloration intensity and coloration area, while mating calls can be categorized by call frequency and amplitude. I propose that this methodological approach could enhance our understanding of the evolution of traits with a wide range of phenotypic variations, such as the chemical blends produced by pheromone glands. 5.4 Evolution of insect CHCs: other variations in CHC profiles and potential interdisciplinary collaborations Beyond the scope of mating signals and sexual dimorphism, several other CHC-related inquiries remain unexplored. First, as major components of insect cuticles, CHCs have been implicated in various other roles, including mediating insecticide resistance (Pu and Chung 2024), reflecting solar radiation to mitigate heat (Hadley 1994), and providing defense against pathogen penetration and infection (Gołębiowski et al. 2008). 85 Further investigation into these functions is required to systematically elucidate the evolutionary processes related to CHC production. Additionally, the evolution of CHC biosynthesis enzyme families remains unknown. While the rapid gain and loss of reductase genes has been documented (Finet et al. 2019), the evolution of elongase genes— the focus of this dissertation— remains largely unknown. Preliminary synteny analyses have yielded initial insights but require further investigation. My current hypothesis posits that elongase genes also undergo rapid evolution across species, particularly orthologs involved in producing mating signals pertinent to speciation (Figure S5.1). What’s more, investigating the roles of reductases and lipid transporters in CHC biosynthesis and deposition will be insightful, especially concerning how these gene families influence CHC profiles and their associated functions. More specifically, several variations in CHC profiles are less studied, including: 1) changes in CHC profiles with aging, 2) mechanical transfers during interindividual physical contact, particularly during mating, and 3) intraindividual variations of CHCs across different body parts due to chemical diffusion. Throughout an individual’s lifespan, CHC profiles continuously change as adults age, a phenomenon demonstrated in D. melanogaster (Jallon and Wicker-Thomas 2003). Investigating how these changing profiles correlate with physiological aging and how the variations in chemical composition reflect aging status as honest signals presents a promising avenue for research. In Chapter 3, we demonstrated that elongase LOC6555117 exhibits female- biased expression through in situ hybridization in 4-day-old adults (Figure 3.4C). We also examined gene expression in 1-day-old adults and found no sex-biased expression 86 (Figure S3.3). Future research should focus on elucidating the genetic mechanisms underlying this specific temporal expression pattern. Furthermore, mechanical transfer during mating has been suggested to occur (Weddle et al. 2013), and it is important to investigate how sex-specific compounds may have evolved to facilitate this mechanical transfer and serve as signals of mating status. While variations in CHC profiles across species and populations have been extensively studied, intraindividual variations in CHCs among body parts have only recently been examined (Sprenger et al. 2021). Both the mechanisms underlying these differences (potentially involving CHC diffusion) and the ecological implications of such intraindividual variations require further investigation. For instance, an insecticide- resistant strain of Anopheles gambiae was shown to produce a thicker layer of CHCs with differing compositions compared to susceptible strains, particularly on their legs (Balabanidou et al. 2016; Balabanidou et al. 2019). Understanding intraspecific CHC variations could provide valuable insights for future applied research. Despite the known roles of CHCs as chemical signals, how diverse CHC compounds are perceived across Drosophila species remains to be elucidated. The perception of CHCs is generally discrete, with gustatory receptors implicated in their recognition. Substantial research has focused on identifying the gustatory receptors responsible for CHC perception, with Gr32a identified as the sole receptor required for recognizing D. melanogaster CHCs to date (Fan et al. 2013). Exploring how this single receptor processes divergent CHC compounds, how gustatory receptors coevolve with varying CHC production across species, and how other chemical signalers perceive CHCs are all valuable areas for future investigation, with valuable inputs from 87 neurobiology. In addition, with the potential collaboration with biochemists and biophysicists, the dynamics of multicomponent mixture of CHC blends could be addressed. CHCs in ants were suggested to be solid-liquid mixtures presented on the cuticle (Menzel et al. 2019). The biphasic CHC layer guarantees both the roles of chemical communication and desiccation resistance. It is notable to hypothesize that solid phase incorporated with the role of desiccation resistance as exhibiting less plasticity, whereas the compounds in liquid phase can actively respond to ecological changes and serve as mating signals. Further exploration and characterization in the multi-leveled biphasic CHC blends become necessary in understanding the roles of specific CHC compounds from the perspective of chemical producers (Blomquist and Ginzel 2021). In summary, studying insect CHCs offers significant insights into fatty-acid synthesis pathways, aging, fecundity, and stress responses, particularly through the model organism Drosophila. These findings can also address applied questions, such as pesticide resistance, arthropod adaptation to environmental changes, and the development of novel chemical control tools in agricultural systems. Interdisciplinary approaches are encouraged to broaden the scope of future research related to insect CHCs. Final Thoughts I have always been finding deep inspiration and enlightenment in the field of evolution. In nature, conflicts are constant, particularly when competition arises between the sexes. To resolve these sexual conflicts, the evolution of complex genetic architectures that give rise to sexually dimorphic traits often occur. These traits may evolve further to 88 facilitate communication between the sexes, addressing the underlying conflicts. While the production of sexually dimorphic traits and communication signals demands additional metabolic costs, it ultimately leads to the resolution of conflicts and the generation of greater diversity in nature—an outcome that initially stimulated human curiosity and investigation. In essence, resolving conflicts, such as sexual conflict, requires both effort (genetic architecture) and investment (metabolic cost), and it results in balanced beauty and diversity (sexual dimorphism). Throughout this process, honest and open communication (signaling) remains a crucial element in resolving conflicts and promoting the prosperity of life (fitness). This is the lesson I have learned from nature and evolution. C’est la vie (This is life). While exploring the evolution of chemical communication, I was struck by the scarcity of studies on this subject compared to visual and acoustic signals. I cannot definitively say this imbalance stems from biases of human sensory, as we do not rely on chemical communication as often. However, if the ultimate goal of scientific advancement is to challenge assumptions and not take things for granted, I would encourage a broader perspective and more innovative thinking beyond the conventional frameworks. Evolution engraves deep within, The shape of my life was born to pin. Not by the way how I faced the years, And how I smile through the future fears. 89 BIBLIOGRAPHY Ahmed, O. M., A. Avila-Herrera, K. M. Tun, P. H. Serpa, J. Peng et al., 2019 Evolution of mechanisms that control mating in Drosophila males. Cell reports 27: 2527- 2536. e2524. Alonso-Pimentel, H., H. G. Spangler and W. B. 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Forensic science international 210: 74-81. 101 APPENDIX Table S2.1 Quantified CHC profiles across selected Drosophila species. Quantitation of the CHCs (ng/µL) of nine Drosophila species from 5 or 6 sets of five adult flies was adapted from (Wang et al. 2022) with specifying different isomers. (*) indicates that this CHC is not detected in all samples. Mean ± SEM is shown. 102 D. erecta ♂D. erecta ♀C2131.2 ± 21.1undetectedC2217.6 ± 2.5undetectedC22:115.4 ± 1.9undetectedC23:1 (a)234.9 ± 63.3undetectedC23:1 (b)805.3 ± 54.7undetectedC23:1 (c)33.8 ± 8.4undetectedC24:1 (a)5.7 ± 1.5*undetectedC24:1 (b)3.4 ± 1.4*undetectedC24:1 (c)2.1 ± 1.3*undetected2Me-C2431.5 ± 4.6undetectedC25:1 (a)61.8 ± 7.2undetectedC25:1 (b)72.5 ± 3.8undetected2Me-C2660.9 ± 10.317.5 ± 1.7C276.8 ± 3.9*undetected2Me-C288.4 ± 1.5105.7 ± 15.3C29:1 (a)undetected11.1 ± 1.6C29:1 (c)undetected10.4 ± 2.9*2Me-C30undetected22 ± 7.3C31:1 (d)undetected83.4 ± 10.4C31:2 (d)undetected194.2 ± 18C33:2 (g)undetected107.8 ± 24.2C33:2 (b)undetected51.6 ± 12.2D. melanogaster ♂D. melanogaster ♀C2114 ± 1.6undetectedC2215.4 ± 2.29.5 ± 1.2C22:18.8 ± 0.9undetectedC23:1 (a)217.5 ± 16.2132.2 ± 12.7C23:1 (b)631.2 ± 34.956.7 ± 6.7C23:1 (c)54.2 ± 3.6undetectedC24:1 (a)undetected19.4 ± 0.9C24:1 (b)6.9 ± 2.4*undetectedC24:1 (c)2.5 ± 1.6*undetected2Me-C2426.3 ± 210.1 ± 1.7C25:1 (a)45.5 ± 3.8157.4 ± 7.4C25:1 (b)136.4 ± 16.183.2 ± 7.3C25:2undetected11.9 ± 12Me-C2644.7 ± 286.5 ± 10.8C27:1undetected43.5 ± 11.4C27:2undetected302.2 ± 9.82Me-C2817.7 ± 1.740 ± 3.2C29:2undetected185.7 ± 11.1 Table S2.1 (c ’d) 103 D. repleta ♂D. repleta ♀2Me-C28218.6 ± 22.6126.2 ± 11.9C29:2 (e)109.3 ± 36.9undetectedC29:2 (f)143.4 ± 40.7undetected2Me-C30119.9 ± 24.7195.2 ± 29.4C31:2 (e)13.9 ± 4.3*undetectedC31:2 (f)100.6 ± 17.3undetected2Me-C322.2 ± 1.1*undetectedC33:1 (a)2.4 ± 1.2*undetectedC33:2 (b)21.9 ± 5.142.9 ± 5.8C33:2 (c)33.7 ± 10.5*108.6 ± 20.3C35:2 (a)5.6 ± 2.2*13.2 ± 3.1C35:2 (b)20.4 ± 7.2*54.2 ± 13.2C35:2 (c)95.2 ± 26.1308.3 ± 32.1C37:2 (b)9.6 ± 6.1*41.4 ± 25.1D. yakuba ♂D. yakuba ♀C2133.7 ± 3.241.2 ± 2.2C2232.2 ± 2.136.2 ± 3.3C22:123.7 ± 1.324.6 ± 1.3C23:1 (a)278.5 ± 14297.3 ± 21.2C23:1 (b)1254.8 ± 71.71270.6 ± 63.1C23:1 (c)undetected7.1 ± 7.1*C24:1 (a)16.8 ± 2.915.6 ± 2.1C24:1 (b)3.3 ± 2.1*5.6 ± 2.7*C25:1 (a)17.6 ± 1.314.5 ± 1.9C25:1 (b)42.3 ± 324.6 ± 4.22Me-C2689.1 ± 14.742 ± 4.9C274.4 ± 3*17.6 ± 1.9C27:1 (b)10.2 ± 4.4*21.6 ± 2.72Me-C287.1 ± 2.3*40.1 ± 5.3D. mojavensis ♂D. mojavensis ♀2Me-C2815.3 ± 0.614.7 ± 1.22Me-C3097.6 ± 6.195.3 ± 7.72Me-C327.5 ± 0.47.6 ± 0.7C33:1 (a)5.5 ± 0.35.4 ± 0.7C35:1 (a)3.8 ± 0.43.6 ± 0.6C35:1 (b)7.2 ± 0.56.4 ± 1C35:2 (a)6.9 ± 15.6 ± 0.8C35:2 (b)92.8 ± 8.860.3 ± 10.1C35:2 (c)86.8 ± 18.5*60.2 ± 10.4C37:2 (a)13.9 ± 0.714.8 ± 1.8C37:2 (b)28.2 ± 1.227.6 ± 6.1D. pseudoobscura ♂D. pseudoobscura ♀C25:1 (d)44.8 ± 3.857.6 ± 4.9C25:2 (d)64.3 ± 5.949.4 ± 2.7C26:145.8 ± 1.445.7 ± 2.6C26:2 (b)37.1 ± 4.530.9 ± 2.82Me-C2650.6 ± 4.537 ± 3.4C27:1 (b)29.5 ± 4.124.3 ± 3C27:2 (e)1941.9 ± 76.51788.6 ± 87.92Me-C28234 ± 16.7219.9 ± 15.6C29:2(h)44.4 ± 439.6 ± 5.72Me-C3026.5 ± 2.130.3 ± 4.4 Table S2.1 (cont’d) 104 D. simulans ♂D. simulans ♀C2226.5 ± 3.531.5 ± 2.8C22:121.5 ± 1.726 ± 3C23:1 (a)294.6 ± 25.8295.5 ± 23.7C23:1 (b)1344.2 ± 81.71608.9 ± 57.1C23:1 (c)94.7 ± 6.4131.8 ± 6C24:1 (a)2.7 ± 1.7*4.6 ± 2.1*C24:1 (b)30.1 ± 5.531.4 ± 3.5C24:1 (c)19.2 ± 2.821.9 ± 2.22Me-C244.6 ± 2.9*3.6 ± 2.3*C25:1 (a)28 ± 3.541.1 ± 5.5C25:1 (b)93.6 ± 11.593.9 ± 13.8C25:1 (c)25.7 ± 2.817.1 ± 1.92Me-C26111.2 ± 1273.3 ± 10.5C271.4 ± 1.4*18.2 ± 32Me-C2812.9 ± 1.231.1 ± 2D. ananassea ♂D. ananassea ♀2Me-C2843.6 ± 551 ± 11.5C29:1 (d)7.4 ± 1.74.7 ± 2.3*2Me-C30100.1 ± 11.9130.5 ± 7.9C31:1 (a)15.1 ± 0.923 ± 1.4C31:1 (b)16.1 ± 2.117.2 ± 0.4C31:2 (e)19.6 ± 1.716.6 ± 2.1C31:2 (f)79.7 ± 8.164.3 ± 12.2C31:2 (g)57 ± 4.948.2 ± 6.4C31:2 (h)37.8 ± 332.7 ± 5.7C33:2 (b)5.6 ± 0.88.2 ± 1.2C33:2 (c)15.4 ± 2.717.2 ± 2.5C33:2 (d)22.7 ± 2.725.8 ± 5.6C33:2 (e)14.3 ± 2.6undetectedC35:2 (a)5.5 ± 2.212.7 ± 2.7C35:2 (b)5.3 ± 28.6 ± 1C35:2 (c)5.9 ± 2.59 ± 1.6C35:2 (d)8.3 ± 5.114.6 ± 2.7 Table S2.2 Age of tested adults (days) in the no-choice mating assays. The ages were initially referred to a previous study in the age of sexual maturity (Pitnick et al. 1995), and determined by results of pilot tests. 105 D. simulans4D. yakuba 4D. erecta 2D. ananassae 4D. pseudoobscura 4D. willistoni2D. mojavensis10D. repleta 8D. melanogaster4 Table S2.3 Sample sizes of no-choice mating assays. Number of tested males are shown. All tested individuals are sexually matured males with limited exposure to conspecific females. 106 n (Intact D. erecta ♂)CHC- ♀ D. melanogaster coated with D. erecta CHCs8CHC- ♀ D. melanogaster8n (Intact D. psedoobscura ♂)CHC- ♀ D. melanogaster coated with D. psedoobscura CHCs17CHC- ♀ D. melanogaster15 A B Figure S3.1 Identification of an oenocyte expression module. (A) Schematic dissection of all GFP reporter constructs. Striped box = female biased expression, solidly filled box = non-sex biased expression, no filled box = no expression. (B) GFP reporter protein expression in oenocytes corresponding to the different overlapping constructs. The A2.2 fragment is the minimum region that can recapitulate a sexually monomorphic oenocyte expression. Further dissecting A2.2 into A2.2.a, A2.2.b and A2.2.c do not show any strong GFP expression in the corresponding GFP reporting constructs. 107 Figure S3.2 Full sequence alignment of ereA with homologous fragments from other species. The designed overlapping test fragments were labeled above each line of the sequence alignments. Black The predicted Erdman-Burtis Consensus of dsx binding site is highlighted in yellow, which lies in an overlapping region of A2 and A3. 108 A1 * 240 * 260 * 280 * 300 * 320 * mel : ---------------------------------------------------------------------------------------------------------------- : - sim : ---------------------------------------------------------------------------------------------------------------- : - yak : ---------------------------------------------------------------------------------------------------------------- : - ere : -----------------------------------------------------------------------------TG-TGTT-TTTCCAGT--GTGACTGTAAACGCGAA : 31 ore : -----------------------------------------------------------------------------TG-TGTT-TTTTTAGT--GTGACTGTAAACGCGAA : 31 A1 340 * 360 * 380 * 400 * 420 * 440 mel : -----------------AATCATATGGGAA---CGGAGGAAATGCGGTCATACCTTGACGCAGCAGCTGTTAACGGCTGTTAACG--CTA--CTTT--GTAGTC---ACA-G : 82 sim : ------------TAGC-AATCATATGGGAA---CGAGGGAAATACGGTCACACTTTAAAGCACCAGCTGTTAACGTCTGCTAACG--CTA--CTTT--GTAGTC---ACA-A : 86 yak : -----------CTGGC-AATCATATGGCAA---CAAGGGAAATGCGGTCATACTGTGACGCACCAGCTGTTAACAGCTGTTATCG--CTA--CTCT--GTCGTC---ACA-G : 87 ere : AGGGAAAATCTCTGGC-AATCATATGGCAA---CAAGGGAAATGCGGTCATACTGTGACGACCCAGCTGTTAACGGCGGTTATCG--CTA--CTGT--GTCGTC---ATA-G : 129 ore : AGGGAAAATCACTGGC-AATCATATGGCAG---CAAGGGGAATGCGGTCATACTGTGACGACCCAGATGTTAACGGCTGTTATCG--CTA--CGCT--GTCGTC---ACA-G : 129 t gc AATCATATGG Aa C agGGaAATgCGGTCAtACt TgAcG cCAGcTGTTAACggCtGtTA CG CTA Ct T GT GTC AcA g A1 * 460 * 480 * 500 * 520 * 540 * 560 mel : CTCT-GT-AAAAC--------AATGTGGCAACTCTGCGCAGCGCCC-GCCAT-A-TTTGAAAATGCTTGCCAGCAAATCGTATTGCTCCCGGTAAACAAGGTGCTT--TCAT : 179 sim : CTCT-GTCAAAAT--------GGTGTGGCAACTCTGTGCAGAGCGC-GCCAAGA-TTTGAAATTGCTAGCCAGCAAATCGCATTGCTCCCGGTAAACAAGGTGCTT--TCAT : 185 yak : CTCT-GT-AAAAC--------AATGTGGCAACGCTATGCAGAGCGC-GCCAATA-TTTGAAAATGATAGCCACTGAATCGCATTGCTCCCGGTAAACAAGGTGCTT--TCAT : 185 ere : CTCT-GT-AAAAC--------AGTGTGGCAACTCTGTGCAGAGCGC-GCCAATA-TTCGAAAAAACTAATCAGCAAATCGCATGGCTCCCGGTAAACAAGTTGCTT--TCGT : 227 ore : CTCT-GT-AAAAC--------AG-GTGGCAACTTTGTCCAGAGCGC-GCCAATA-TTCGAAAATGTTAACCACCAAATCGCATGACTCCCGGTAAACAAGTTGCTT--TCAT : 226 CTCT GT AAAAc a tGTGGCAACtcTgtgCAGaGCgC GCCAa A TT GAAAatg Ta cCA caAATCGcAT gCTCCCGGTAAACAAG TGCTT TCaT A1 * 580 * 600 * 620 * 640 * 660 * mel : T--------ATTAGTCAAC-ATTTTTG----AGAGC--TAA---CA--ACTTTTTATTGGCGATCAAAGGTGGTACTTCAACTGACCAAATATTGGATATTTGCGTAAATAC : 271 sim : T--------ATTAGTCAAC-ATTTTGT----AGAGC--TAA---CA--ACTTTTTATTGGCGATCAAAGGTGGTACTTCTACTGACCAAATATTGGATATTTGCGTTAATAC : 277 yak : T--------ATTGGTCAAC-ATTTTTG----AGAGC--TAA---CA--ACTTTTTATTGGCGATCAAAGGTGGTACTTATACTGACCAAATATTGGATATTTGCGCAAATAC : 277 ere : T--------ATAAGTCAACCATTTTTG---GAGAGC--TAA---CA--ACTTTTTATTGGCGATCAAAGGTGGTACTT-----GGCCAAATATTGAATATTTGCGTAAATAA : 316 ore : T--------ATTAGTCAACCATTTTTG---GAGGGC--TAA---CC--ACTTTTTATTGGTGATCAAAGGTGGTACTTCTACTGGCCAAATATTGAATATTTGCGCAAATAA : 320 T ATtaGTCAAC ATTTTtg AGaGC TAA Ca ACTTTTTATTGGcGATCAAAGGTGGTACTT actG CCAAATATTG ATATTTGCG aAATA A1 680 * 700 * 720 * 740 * 760 * 780 mel : CTAACAGGCATTTGTTTTTTTTTTCATGAGAAATT----AC-CGTGACGAAATTACA--AG-ACGTA--TATTA--TATGAATAGAAAATTTTCC--TCTAGT-CTGTAAAC : 368 sim : CTAACAGGCATTTGTATTTTTTTTCATGAGAAATT----AC-CGTGACGAAATTACA--AG-ACGTA--TATTA--TATGAATAGAAAATTTTCC--TCTAGT-CTGTAAAC : 374 yak : TTATCGTTCATT-GTTTTT--TTTCATGAGAAATT----AC-CATGACGAATTTACA--AG-ACGTA--TATTA--TATGAATAGAAAATTTTCC--CCTAGT-TTGTAAAC : 371 ere : TTCTCATGCATT-GTTTTTCTTTTCATGAGAAATT----AC-CGTGACGAAATTACA--TG-ACGTA--TATTA--TATGAATAGAAAATTTTCA--CCTATC-TTGTAAAC : 412 ore : TTCTCATGCATT-GTTTTTTCTTTCATGAGAAATT----AC-CGTGACGAAATTACA--CG-ACGTA--TATTA--TATGAATACAAAATGTTCC--TCTATC-TTGTAAAC : 416 T Ca gCATT GTtTTT TTTCATGAGAAATT AC CgTGACGAAaTTACA G ACGTA TATTA TATGAATAgAAAATtTTCc CTA TGTAAAC A1 * 800 * 820 * 840 * 860 * 880 * mel : AC--------TTC---AGTAACAG---AGAAATTGTTTTCAAAAAATGTTAAGGCATCTCATTAAAAA-ACATC--A--ACAATGAAC-TCAACTTAAGCCTGGTAGTTATG : 460 sim : AC--------TTT---AGTAACAG---AGAAATTGTTTTCAAAAAATGTTAAGGCATCTCATTAAAAA-CCATC--A--ACAATGAAG-TCAACTTAAGCCTGGTAGTTATG : 466 yak : AC--------TTC---AGCAACAG---AGAAATTGTTTTCAAAAA-TGGTAAGGCATCTCATTAAAAA-CCATC--A--ACAATGAAG-TCAACTTACGCCTGGTAGGTATG : 462 ere : AC--------TTC---AGTAACAG---AGAAATCATTTA-AAAAT-TGTTAAGGCATCTCGTTAAAGA-CCTTG--A--ACAATGAAG-TCGACTTAAGCCTGGTAGTTATG : 502 ore : AC--------TTC---AGTAACAG---AGAAATCATTTT-AAAAA-TGTTAAGGCATCTCGTTAAAAA-CCTTG--A--ACAATGAAG-TCAACTTAAGCCTGGTAGTTATG : 506 AC TTc AGtAACAG AGAAAT TTTt AAAAa TGtTAAGGCATCTC TTAAAaA cC T A ACAATGAAg TCaACTTAaGCCTGGTAGtTATG A1 900 * 920 * 940 * 960 * 980 * 1000 mel : AATTAGCATGTGTAGTTCCC----CGATATT-TA-ACCTACTTAAGTATGCACATATCT-GCCATTCCTTGGACACTTTTGCAA---AGACAA--CAAAG-------ACAAC : 553 sim : AATTAGCATGTGTAGTTCCC----CGATATT-TA-ACCTACTTAAGTATGCATATATCT-GCCATTCTTTGGGCAATTTTGCAA---AGACAA--CAAAG-------ACAAC : 559 yak : AATTAGCAGTTGTAGTTCCC----CTATATT-TA-ACCTACTTA-GTATGCATACATTT-TCCATTATTCGAGTGCTTTTGCAA---AGACA---CAAAC-------AAAAT : 553 ere : AATTAGCATGTGTAGTTCCC----TGATATT-TA-ACCTACTTAAGTAT--------CT-TCCATTCTTTGCATACTTTTGGAA---AGACA---CAAAC-------AAAAC : 586 ore : AATTAGCATGTGTAGTTCCC----TGATATT-TA-ACCTACTTAAGTATGCATATATCT-TCCATTCTTTGCGTACTTTTGGAG---AGCCA---CAAGC-------AAAAC : 598 AATTAGCAtgTGTAGTTCCC gATATT TA ACCTACTTAaGTATgca a atcT CCATTctTtG acTTTTG Aa AGaCA CAAa A AAc Figure S3.2 (cont’d) 109 A1 * 1020 * 1040 * 1060 * 1080 * 1100 * 1120 mel : ATCA--CAGCTTACTTAAAA------TATAT------ATATT------TAAATTAA----------TT----AATTAAAGTAATACAAGAATGTCTAATTA-TA-GCTTTTT : 629 sim : ATCA--CAACTCACTTAATA------AATAT------ATATT------TAA-TTAA----------TT----AATTCAA-TAATACAAGAATGTCCACTTT-TA-GCATTTT : 633 yak : AACT--CA-CTTAATAAATA------TATATTTGCGGATATTAAGAAATAAATTAAGATTGAGTGGTTTTGAAATTCAAGCAATACAAGAATGTCCACTTA-TAAGTATTTT : 655 ere : AACT--CA-CTTAATATATATGTACTCGTATTTGGGGATATTATGAAATAAATTAAGATCGAGTGGTTATGAAATTCAAACAATACAAGAATGTCCACTTA-TAAG------ : 688 ore : AACT--CA-CTTAATATATA----CATATATTCGGGGATATTATGAAATAAATTAGGATCGAGTGGTTATGAAATTCGAACAATACAAGAATGTCCACTTA-TAAG------ : 696 A C CA CTtA T AtA aTAT ATATT TAAaTTAa TT AATTcaA AATACAAGAATGTCcAcTTa TA G A1 * 1140 * 1160 * 1180 * 1200 * 1220 * mel : TA----GAAATAGCATTACGGTGTTATAAAAACCCACAAATGTAGGCAAATAACAATTCTAATAATAAAGAAACTTAATTGGGAAGACAAAATGGTGTTTGGCTAG-TGAGG : 736 sim : TA----GAAAGAGCATTATGGTGTTATAAAAACCCACAAATGTAGGCAAATAACAATTCTAATAATAAAGAAACTTAATTGGGAAGACAAAATGGTGTTTGGCTAG-TGAGG : 740 yak : AA----GAAAGAGCATTATTCTGTTATAAAAATTCACCAATGTAGACAAATAACAATTCTAATAATAAAGAAACTTAATTGGGAAGACTAAATGGTATTTTGCTAG-TGAGG : 762 ere : -------------CAT------GTTATAAAAACTCACAAATGTAGGCAAATAACAATTCTAATAATAGAGAAACTTAATTGGGCAGACAAAGTGGTATTTTGCTAG-TGAGG : 780 ore : -------------CAT------GTTATAAAAACTCACAAATGTAGGCAAATAACAATTCTAATAATAGAGAAACTTAATTGGGCAGACAAAATGGTATTTTGCTAG-TGAGG : 788 CAT GTTATAAAAAc CACaAATGTAGgCAAATAACAATTCTAATAATA AGAAACTTAATTGGG AGACaAAaTGGT TTT GCTAG TGAGG A1 A2 A2.1 1240 * 1260 * 1280 * 1300 * 1320 * 1340 mel : AAAT-ATCACCAGCCTTGCAGGCCCAATAAAGA-TTCA----CTT----GTTTGGCAA-----GC-TCT--TAATAGCGCA-ATTTAACTA--C--GT--TTTAATAGCGCC : 823 sim : AAAT-ATCACCAGCCATGCAGGCCCAATAAAGA-TTCA----CTT----GTTTGGCAA-----GC-TCC--TAATAGCGCA-ATTTAACTA--C--GT--TTTAATATCGCC : 827 yak : AAAT-ATCGCCAGCCATGCAGGCCCAATAAAGA-TTCA----CTT----GTTTGGCAA-----CC-TCT--TAATAGCGCA-ATTTAACTA--C--GT--TTTAATGGCGCC : 849 ere : AAAT-ATCACCAGCCATGCAGGCCCAATAAAGA-TTCA----CTT----GTTTGGCAG-----CC-TCC--TAATAGCGCA-ATTTAACTA--C--GT--TTTAATAGCGCC : 867 ore : AAAT-ATCACCAGCCATGCAGGCCCAATAAAGA-TTCA----CTT----GTTTGGCAG-----CC-TCT--TAATAGCGCA-ATTTAACTA--C--GT--TTTAATAGCGCC : 875 AAAT ATCaCCAGCCaTGCAGGCCCAATAAAGA TTCA CTT GTTTGGCA C TC TAATAGCGCA ATTTAACTA C GT TTTAATagCGCC A1 A2 A2.1 * 1360 * 1380 * 1400 * 1420 * 1440 * mel : CTTAGAATATTTATTGCACATAAAGGCCAATATGTTTAGTCAAGAGTCATTCATCTTTGTTAAA-CAAATTCAATTTCAAACATAAGACTATAGAAC-TTGCTTTGCT-CAG : 932 sim : CTTAGAATATTTATTGCACATAAAAGTTAGTATGCTTAGTCAAGAGTCATTCATCTTTGTTGAA-CAAATTCACTTTCAAGCATAAGACTATAGAAC-TTGCTTTGCT-CAG : 936 yak : CTTTGAATATTTATTGCACATAAAAGCCAGTATGTTTAGTCAAGAGTCAGTCATCTTTGTTAAA-CCAATTCCATTTCAAATATGAGACCATAGAAC-TTGCTCTCCT-CAT : 958 ere : CTTTGAATATTTATTGCACATAAAAGCTAGTATGTTTAGTCAAGAGTCGTTCATCTTTGCTAAG-CGATTTCAATTTCAAATATGCGACTACAGAAC-TTGCTTTCCT-CAT : 976 ore : CTTTGCATATTTATTGCACATAAAAGCTAGTATGTTTAGTCAAGAGTCATTCATCTTTGCCAAC-CGAATTCAATTTCGAATATGAGACTACAGCAC-TTGCTTTCCT-CAT : 984 CTT GaATATTTATTGCACATAAAaGc AgTATGtTTAGTCAAGAGTCatTCATCTTTG taA C AaTTCaaTTTCaAa AT aGACtA AGaAC TTGCTtT CT CA A1 A2 A2.1 A2.2 A2.2.a A2.2.b * 1580 * 1600 * 1620 * 1640 * 1660 * 1680 mel : AAGGAGC--AGATTTCGCACAGACCCCG-ACTAGCGGTATTAATCGACTGAATTAATACATTTAGTAGCGCTGAAGTTCAGGGTCATAATCACAAAAGAGAAGCGCCGATAA : 1138 sim : AAGGAGC--AGATTTCGCACAGACCCCG-ACTAGCGGTATTAATCGACTGAATTAATACATTTAGTAGCGCTGAAGTTCAGGGTCATAATCACAAAAGAGAAGCGCCGATAA : 1140 yak : AAGGAGC--AGATTTCGCACAGACCCCG-ACTAGCGGTATTAATCGACTAAATTAATATATTAAGTAGCGCTGAAGTTCAGGGTCCTAGTCACAAAAGAGAAGCGCCGATTA : 1177 ere : AAGGAGC--AGACTTCGCACAGACCCCG-ACTAGCGGTATTAATAGACTATATTAATACATTTACTAGCGCTGAAGTTCAGGGTCTTAATCACAAAAGCGAAGCGCCGATTA : 1183 ore : AAGGAGC--AGATTTCGCACAGACCGCG-ACTAGCGGTATTAATAGACTATATTAATATATTTACTAGCGCTGAAGTTCAGGGTCTTAATCACAAAAGCGAAGCGCCGATTA : 1188 AAGGAGC AGAtTTCGCACAGACCcCG ACTAGCGGTATTAAT GACT ATTAATA ATTtA TAGCGCTGAAGTTCAGGGTC TAaTCACAAAAG GAAGCGCCGAT A Figure S3.2 (cont’d) 110 A2 A2.2 A2.2.a A2.2.b * 1700 * 1720 * 1740 * 1760 * 1780 * mel : TGCGAGCTGTTTCTGTTTGAATGACGAG-CGCGCGACAAAAAATGCTAAACGG--CCAA------T-GTGC--TTCAAA-------TGGAAATGGA------------AATG : 1219 sim : TGCGAGCT------GTTTGAATGACGAG-CGCGCGATAAAAAATGCAAAACGG--CCAACTGCCAT-GTGC--TTCAAA-------TGGAAATGGATATGGAAATGGAAATG : 1233 yak : TGCGAGCG------GCTTGAATGACGAG-TGTGCGATAACAAATGCAAAACGG--CTTTTTGTTTTTGTCC--GCCGTTGAAATGAATGTGCTTGAAATAGAAATGGAAATG : 1278 ere : TGCGAGCG------CTTTGAATGTCGAC-TATGCGATAACCAATGCAAAACGG--CTTTTGGATTTTGTTC--GCCGAC-------ATGTGATAGAAATGGAAATGGTAATG : 1277 ore : TGCGAGCG------CTTTGAATGTCGAC-TATGCGATAACAAATGCAAAACTG--CTTTTGGATTTTGTTC--GCCG-C-------ATGTGATAGAAATGGAAATGGTAATG : 1281 TGCGAGC tTTGAATG CGA GCGAtAA aAATGCaAAACgG C g T GT C C G aT GA at gaaatgg AATG A2 A2.2 A2.3 A2.2.b A2.2.c 1800 * 1820 * 1840 * 1860 * 1880 * 1900 mel : CCAAAGACCCGGAAGGGTG---GC--GACCAACACAGCTGCAGTGCATCCAACTCGGC--AAACATTTG-CATATTTGACCGGGCACTTAGCACGTGGGTGGAGTACATGGA : 1323 sim : CCAAAGACCCGGAAGGGTG---GC--GACCAACACAGCTGCAGTGCATCCAACTCGGC--AAACATTTG-CATATTTGACCGGGCACTTAGCACGTGGGTGGGA---GTG-- : 1332 yak : CTGAAGACCCGGAAGAGTGCTGGT--GACCAACACAGCTGCAGTGCATCGAGCTGGGC--AAACATTTG-AATATTT-----GAATATT------TGTGTGGAGTACA-G-- : 1371 ere : CTAAAGACCCGGAAGTGTG---GC--GACCAACGCAGTTGCAGTGCATCGAGCTTGAC--AAACATTGT-AATATTTGACCGGGCACTTAGCACGTGTGTGGAGCACA-G-- : 1378 ore : CTAAAGACCCGGAAGTGTG---GC--GACCAACACAGTTGCAGTGCATCGAGCTCGGC--AAAAATTTG-AATATTTAGCCGGGCACTTAGCACGTGTGTGGAGTACA-G-- : 1382 C aAAGACCCGGAAG GTG Gc GACCAACaCAG TGCAGTGCATC A CT GgC AAAcATTtg ATATTT ccgGgcacTTagcacgTG GTGGag aca G A2 A2.2 A2.3 A2.2.2 A2.2.c * 1920 * 1940 * 1960 * 1980 * 2000 * mel : TCACCATGGGTCACACAAATCACCTG-GGAATCTGG-----GAGA-CT-GGTGAGAGT-A-AGTGCGTGAAATTGACCCATT---CATTGGACGGACAATCGCTTCCCAT-- : 1420 sim : ----CATGGGTCACACAAATCACCTG-GGAATCTGG-----GAGA-CT-GGTGAGAGT-A-AGTGCGTGAAATTGAGCCATT---CATGGGACGGATAATTGCTTCCCAT-- : 1425 yak : --CCCATGGGTCACACATATCACCTG-GGAATCGGG-----GAGA-TTAGGTGAAAATTA-AGTGCGTGAAATTTACCCATT---CATGACACTGATAATCGCTTCCCATTC : 1470 ere : --CC-ATGGGTCACACAGATCACCTG-GGAATCGGG------AGA-CC-GGTGAGAGT-A-AGTGCGTGAAATCGACCCATT---CATGGAC-GGATAATCGCTTCCCATT- : 1471 ore : --CC-ATGGGTCACACAGATCACCTG-GGAATCGGGTGAGAGAGA-CT-GGTGAGAGT-A-GGTGCGTGAAATTTACCCATT---CATGGGCCGGATAATCGCTTCCCATT- : 1482 c ATGGGTCACACA ATCACCTG GGAATC GG gAGA ct GGTGAgAgT A aGTGCGTGAAATt AcCCATT CATgg cgGAtAATcGCTTCCCAT A2 A2.3 2020 * 2040 * 2060 * 2080 * 2100 * 2120 mel : ----CGATCTGGAAATGTGTTAACTGCGC-CCG-TAAACCCTATTTGCG-TAGTTAAATT--AAGTGCCAGGTTATGGAGTTG-----GGGCGTGTCATCCCCCACATTGGC : 1518 sim : ----CGACCTGGAAATGTGTTAACTGCGC-CCG-TAAACCCTATTTGCG-TAGTTAAGT---AAGTGCCAG-TTATCGAGTTG-----GGGCGTGTCATCCCCCAAATTG-- : 1519 yak : GCATCGACCTGGAAATGTGTTAACTGCGC-CCG-TAAACCCTATTTGCG-TAGTTAAGT---AAGTGCCAG-TTATAGAGTTG-----GGGCGTGTCATCCCCCACATTGGC : 1570 ere : -----GACCTGGAAATGTGTTAACTGCGC-CCG-TAAAC-------GCG---GTTAAGT---AAGTGCCAA-TTATAGCGTTG-----GGGCGTGTCATCCCCC-------- : 1549 ore : -----GACCTGGAAATGTGTTAACTGCGC-CCG-TAAACCCTGTTTGCG-TGGTTAAGT---AAGTGCCAA-TTATAGAGTTG-----GGGCGTGTCATCCCCCC------- : 1570 GAcCTGGAAATGTGTTAACTGCGC CCG TAAACcct tttGCG t GTTAAgT AAGTGCCA TTAT GaGTTG GGGCGTGTCATCCCCC Figure S3.2 (cont’d) 111 A2 A3 A3.1 A2.3 * 2140 * 2160 * 2180 * 2200 * 2220 * 2240 mel : ------ACATA--TATATATAT----------ATATATAAGCACTTATAACTA-TGCTGCCAATTGAGTTC-GTCTCAATGACGTGACGGCGATAATAAATCA-ATTGTCTA : 1609 sim : ------ACATA--CATAGATAT----------ATATACA--CACTTATAACTA-TGCTGCCAATTGAGTTC-GTCTCAATGACGTGACGGCGATAATAAATCA-ATTGTCTA : 1608 yak : ATACATACATATCTATGCATATCTATACATACATATACATATATAAATAACTA-TGCTGCCAATTGAGTGC-GGCTCAATGACGTGACGGCGATAATAAATCA-ATTGTCTA : 1679 ere : ------ACATTTCCATGCATAT----------ATATACATATA----TAACTA-TGCTGCCAATTGAGTCC-GTCTCAATGACGTGACGGCGATAATAAATCA-ATTGTCTA : 1638 ore : ------ACATTTCCATGCATAT----------ATATACATATACATATAACTA-TGCTGCCAATTGAGTCC-GTCTCAATGACGTGACGGCGATAATAAATCA-ATTGTCTA : 1663 ACAT AT ATAT ATATAcA A aTAACTA TGCTGCCAATTGAGT C GtCTCAATGACGTGACGGCGATAATAAATCA ATTGTCTA A2 A3 A3.1 A2.3 * 2260 * 2280 * 2300 * 2320 * 2340 * mel : GCGGTTTATTTAAAGCCAATTT--TGTAGCTG--GA-AATTGGCACACAGAAAGAAAAGTGGTGTCAGGAACTTATATATAAAATGTTATTATTTTGGTTATTTTTAAAGGG : 1716 sim : GCGGTTTATTTAAAGCCAATTT--TGTTGCTG--GA-AATGGGCACACAGAAAGAAA-------TC-------------------GT------------------------- : 1664 yak : GCGGTTTATTTAAAGCCAATAT--TGTTGCTG--GA-AAAGGGCACACAGAAAGAAAAGTCG---CAAAATAACA------------------------------------- : 1746 ere : GCGGTTTATTTAAAGCCAATTT--TGTTGCTG--GA-ATAGGGCACACTGAAAGAAAAATTG---CAAGATAGCA------------------------------------- : 1705 ore : GCGGTTTATTTAAAGCCAATTT--TGTTGCTG--TTGATGGGGCACACGGAGAGAAAAATCG---CAAGATAGCA------------------------------------- : 1731 GCGGTTTATTTAAAGCCAATtT TGTtGCTG ga A gGGCACAC GAaAGAAAa t g Ca a a A2 A3 A3.1 A2.3 2360 * 2380 * 2400 * 2420 * 2440 * 2460 mel : TCTAATGGAACTATTTTTATTATAAAAATGTAGATAATTTTTTAAGCATTTCTTTATAGAGATGTTTTTAGAAAAATGTTTTTTTAAATGGGCACACAGAAAGAAAAGTGGT : 1828 sim : ---ATTGAAACT----------TAA-----------------TAAACATAT-----------TATTTTTA------------------------------------------ : 1693 yak : ---------------------------------------------------------------------------------------------------------------- : - ere : ---------------------------------------------------------------------------------------------------------------- : - ore : ---------------------------------------------------------------------------------------------------------------- : - A2 A3 A3.1 A2.3 * 2480 * 2500 * 2520 * 2540 * 2560 * mel : GTCAGGAACTTACATATATAAAATATTATCCATATCTATTTTGTTAATT--TTAAAGGGTCTAATGGAACTATTTTTATTACAAAAATGTAGTTA----------ATTTTTT : 1928 sim : ------------CAAATT-------------ATATCAAATTT---------TAAAAGGGTCTTATGGAATTAGTTT---TAC-----------TG----------ATTTTTT : 1747 yak : --CAA--ACTTAT------------TTTT-TAAACTAAATGTATCAATTTGTAACAGAGTCTTGTGGGACTTTTTTTAGTACCGAAAGATTTGTGTT-------CACTTTTT : 1834 ere : --CAAGAACTTATAAAAATATAATATTTTCTATACCAATTTTATACATTCTTAAAAGGGTCATGCCGGATCAGTTTTATTAACAAAAGGTTTCTGTTTTTTGTACATTTCTT : 1815 ore : --CAAGAACTTATAAAAATATAATATTTTCTATACTAACTATATACATTCTTAAAAGGGTCATGTGGTACCAGTTTTATTAACAAAAGGTTTCTGTTTTTTGTACATTTCTT : 1841 ca actta a a tt t AtA aA T T t att TaAaAGgGTC t tgG A a TTTta TA aaa t Tg AtTT TT Figure S3.2 (cont’d) 112 A2 A3 A3.1 2580 * 2600 * 2620 * 2640 * 2660 * 2680 mel : AAGCATTTCTTTATAGAGATGTTTTT-TAGAAATAA--CACAGTATCAAACGAAAGTGGCGAGGATGACGCAAAATCCAATTAACCTGAGTTATCACTGAAAGGTCAAAGCA : 2037 sim : AAGCATTCCCTTATAGAGATGCTTTCCTAGATATAA--CACAGTATCAAAACAAAGTAGAGAGGATGACGTAAAATCTAATTAACCTTAGTTATCACTGAAAGGTCAAAGCA : 1857 yak : AAAAATTTCATTTTAGAGACTTTTGCCTAGAAAAAT--CACAGTATCAAAACAAGGTAA----------GCAAAATCCAATTAACCTGAGTTATCACTGAGAGGTCAAAACA : 1934 ere : GACCATTCTATTATAGAGACATTTTCCTACAAAAATATCGCAGTATCAAAACAAAGTAACGAGGATGACGCAAAATCCAATTAACCTGAGTTATCACTGAAAGGTCAAAGCA : 1927 ore : GACCATTCCATTATAGAGACATTTTCCTAGAAAAAT--CGCAGTATCAAAACAAAGTAACGAGGATGACGCAAAAACCAATTAACCTGAGTTATCACTGAAAGGTCAAAGCA : 1951 A cATT c TTaTAGAGA tTTtccTAgAaA A C CAGTATCAAAacAAaGTa gaggatgacGcAAAAtCcAATTAACCTgAGTTATCACTGAaAGGTCAAAgCA Erdman-Burtis Consensus RNNACWAWGTNNY A3 A3.1 A3.2 * 2700 * 2720 * 2740 * 2760 * 2780 * 2800 mel : CATAATAAAAATATA-AACTCCATCGTGCGGTCTAAAAATCGCGACACATTATATATAAATA----TAAAGTGCATGTATATATTTTTTTAGAA-------------ATTCA : 2131 sim : CATAATAAAGATATA-AACTCCATCGTGCGGTCTAAAAATCGCGACACAATATATATATATACATATATAGAGCATATATACATTTTTTAGAAATTCATTCATTCCAATTCA : 1968 yak : AATAATAAAGATACA-AACTCCATTGTGCTGTCTAAAAATCGCGACACATAAT--ACGTGTA----TAATGTGCATATATA-ATTTTTGTAGAA-------------ATTCA : 2025 ere : AATAATAAAGATATA-AACTCCACGGTGCTGTCTAAAA-TCGCGACACATAATGTATATATA----TAATGTGCACATAAC-AGTTTTT-AGAA-------------ATTCA : 2018 ore : AATAATAAAGATATA-AACTCCACGGTGCTGTCTAAAA-TCGCGACACATAATGTATATATA----TAATGTGCACATAAA-ATTTTTTTAGAA-------------ATTCA : 2043 ATAATAAAgATAtA AACTCCA GTGC GTCTAAAA TCGCGACACAt AT tAtataTA TAa GtGCA aTA a AtTTTTt agAA ATTCA A3 A3.2 * 2820 * 2840 * 2860 * 2880 * 2900 * mel : TTCCAAACACTTTCAGTGGCATACA-----AACAGA------TTTTCATAAAATTGTTAACAATTTATGAT-GATGAACTAGAGTCTCTCATAGTAT--GTTCTATGTAT-- : 2227 sim : TTCCAAAAACTTTCAGTGGCATAAA-----ATCATC------TTTCCATAAAATTGTTAATAATTTATGAT-GATGAACTAGAGTCT--------AT--GTTCTATGTAA-- : 2056 yak : TTCCAAACACTTTCAGTGGCACAAAA----ATCATC------TCTCCAGCTGTATAGTTAGAATTTATGGT-AATGAACTAGGGTGTCTTAAAGTAT--GTTCTATGTAG-- : 2122 ere : TTCCAAACACTTTCAGTGGCATAAGATCTTAACATAAGATTGTTTTCCGCTGTATCGTAAGAATTTATGAT-GATGAACTA--CTGTCTCAAACTAT--GTTCTCTGGAC-- : 2123 ore : TTCCAAACACTTTCAGTGGCATAAGATCTTAACATAAGATTGTTTTCCGCTGTATCGTAAGAATTTATGAT-GATGAACTA--GTGTCTCAAACTAT--GTTCTCTGGACTT : 2150 TTCCAAAcACTTTCAGTGGCAtAa A CAt TtT C T TaA AATTTATGaT gATGAACTA gT Tct a a tAT GTTCT TG A A3 A3.2 2920 * 2940 * 2960 * 2980 * 3000 * 3020 mel : --GTTCGTTAAATTCTAAACATATACCA-TAA----------TATATATATGTATATGTATACATGTAT------ACTAATATTGAAGTATATTTCGTT-TTTA-CTGTGTA : 2318 sim : --GTTCGTTAAGTTCTAAACATATACAG-ACA----------TA---ATA-GTAATTGAA------------------AAAATCGAAATATATTTCGTT-TTCA-CTGTGTA : 2131 yak : --GTTCATTAAGTTTTAACCAAATACGG-ACAGAAAACCTATTGCAAATTGTTAATTTGCAACTAGAGTTATTGGAGTTATTTCCAAATAAGTTTTGTT-TTCA-CTGTGTA : 2229 ere : --GTTCATTAAGTTCTAACTATGTACAG-ACAGAAAACTTATTACAAATTGTTGATTTTTGACTAGAGTGGTTGGA--AATGTCCAAATAAGTTTTGTT-TTCA-CGGTGTA : 2228 ore : ACGTTCAGTAAGTTCTAACTATATACAG-ACAGAAAACTTATTAAAAATTGCTGATTTTTGACTAGAGTTGTTGGA--AATGCCCAAGTAAGTTTTGTT-TTCA-CTGTGTA : 2257 GTTC tTAAgTTcTAA AtaTAC g acA Ta a AT T atT ac g t a aAt tc AA TA TTT GTT TTcA CtGTGTA A3 A3.2 * 3040 * 3060 * 3080 * 3100 * 3120 * mel : CTTTTTCGCTTCCCTCTTTGCTTTCGTTTTCTTTTTGCCG-CTCTTTTTGCGA-TAGGATCTGC--ATGTTTTTTTGGCCAACCGGGAAAGGGTTAATA--AACTT--GTTC : 2422 sim : CTTTTTCGCTTCCCTCTTTGCTTTCGTTTTCTTTTTGCCG-CTCTTTTTGCGA-TAGGATCTGC--ATGTTTTTTTGGGCAACCGGGAAAGGGTTAATA--AACTT--GTTC : 2235 yak : CTTTTTCGCTTCCCTCTTGGCTTTCGTTTTCTTTTTGCCG-CTCTTTTTGCGA-TAGGATCTGC--ATGTTTTTTTGGCCAACCGGGAAAGGGTTAATA--AACTT--GTTC : 2333 ere : CTGTTTTTCTTCCCTCTTTGCTTTCGTTTTCTTTTTGCCG-CTCTTTTTGCGA-TAGGATCTGC--ATGTTTTTTTGGCCAACCGGGAAAGGGTTAATA--AACTT--GTTC : 2332 ore : CTTTTTTGCTTCCCTCTGTGCTTTCGTTTTCTTTTTGCCG-CTCTTTTTGCGA-TAGGATCTGC--ATGTTTTTTTGGCCAACCGGGAAAGGGTTAATA--AACTT--GTTC : 2361 CTtTTT gCTTCCCTCTttGCTTTCGTTTTCTTTTTGCCG CTCTTTTTGCGA TAGGATCTGC ATGTTTTTTTGGcCAACCGGGAAAGGGTTAATA AACTT GTTC Figure S3.2 (cont’d) 113 A3 A3.2 A3.3 3140 * 3160 * 3180 * 3200 * 3220 * 3240 mel : A-----AAATAAACCAAGAAAAAGCAT-GG---CTTATCTGCTGCT-GTTAGC--AGTTTTGCT-TTCTTTTCTCGC--CACAGAC--ATTCATTTTA-ATGGCTTCAAACT : 2516 sim : A-----AAATAAACCAAGAAAAAGCAT-GG---CTTATCTGCTGCT-GTTAGC--AGTTTTGCT-TTCTTTTCTCGC--CACAGAC--ATTCGTTTTA-ATGGCTTCAAACT : 2329 yak : A-----AAATAAACCAAGACAAAGCAT-GG---CTTATCTGCTGCC-GACAGC--AGTTTTGCT-TTCTTTTCTCGC--CACAGACACATTCGTTTTA-ATGGCTTCAAACT : 2429 ere : A-----AAATAAACGAAGAAAAAGCATTGG---CCTATCTGCTGCT-GCCAGC--AGTTTTGCT-TTCTTTTCTCGC--CGCAGAC--ATTCGGTTTA-ATGGCTTCAAACT : 2427 ore : A-----AAATAAACGAAGAAAAAGCATTGG---CCTATCTGCTGCT-GCCAGC--AGTTTTGCT-TTCTTTTCTCGC--CACAGAC--ATTCGTTTTA-ATGGCTTCAAACT : 2456 A AAATAAAC AAGAaAAAGCAT GG C TATCTGCTGCt G AGC AGTTTTGCT TTCTTTTCTCGC CaCAGAC ATTCgtTTTA ATGGCTTCAAACT A3 A3.3 * 3260 * 3280 * 3300 * 3320 * 3340 * 3360 mel : TGACCTTAGCACCAGAAAGCACCAAAAAATCAGTAAAGATA-AAACCAAAACTAAATGTTTCTAAAGCAAAAATA-AAATAAAAAAA---AAAAAAAAGAAACCGCCGCGCA : 2623 sim : TGACCTTAGCACCAGAAAGCACCAAAAA-TCAGTAAAG----AAACCAAAACTAAATGTTTCTAAAGCAAAAATA-AAATTAAAAAACGAAAAAAAAAGAAACCGCCGCGCA : 2435 yak : TGACCTTAGCACCAGAAAGCACCAAAAA-TCAGT----CAAGAAACGAGCACTAAATGTTTCTAAAGCAAAATTAAAAAGAAAAAAAAAACTAAAGGCAAAACCGTCGCGCA : 2536 ere : TGACCTTACCACCAGAAAGCACCAAAAA-TCAGTTAAGAAAGAAACCAATACTAAATGTTTCTAAAGAAAAAATT-AAAACAAAAAAATAC-----GC--------CGCTCA : 2524 ore : TGACCTTAGCACCAGAAAGCACCAAAAA-TCAGT----ATAGAAACCAAGACTAAATGTTTCTGAAGAAAAAATTCGAAAAAGAAAAAAAC-----GC--------CGCGCA : 2550 TGACCTTAgCACCAGAAAGCACCAAAAA TCAGT a AAACcAa ACTAAATGTTTCTaAAG AAAAaT aAA AaAAAA a CGCgCA A3 A3.3 * 3380 * 3400 * 3420 * 3440 * 3460 * mel : ACTTAAA---TTGGC-----CATTAA-CGC---AACTTCGACTT--GCATCGTATCGAACCCGGCCGAGTGACG-CAAAAATCAACTAAAAAAAAAGGTTAAGTATAC-GCC : 2719 sim : ACTTAAA---TTGGC-----CATTAA-CGC---GACTTCGACTT--GCATCGTATCGAACCCGGTCGAGTGACG-CAAAAATCAACTAAAAAAAA-GGTTAAGTATAC-GCC : 2530 yak : ACTTAAA---TTGGC-----CATTAA-CGC---GACTTCGACTT--GCATCGTATCGAACCTGGCCGAGTGACG-CAAAAATCAACTAAAAAAAA-GGTTAAGTATAC-GCC : 2631 ere : ACTTAAA---TTGGC-----CATTAA-CGC---GACTTCGACTT--GCATTGTATCGAACCTGCCCGAGTGACG-CAAAAATCAACTAAAAAAAA-GGTTAAGTATAC-GCC : 2619 ore : ACTTAAA---TTGGC-----CATTAA-CGCTTCGACTTCGACTT--GCATCGTATCGAACCTGCCCGAGTGACG-CAAAAATCAACTAAAAAAA--GGTTAAGTATAC-GCC : 2647 ACTTAAA TTGGC CATTAA CGC gACTTCGACTT GCATcGTATCGAACC G cCGAGTGACG CAAAAATCAACTAAAAAAAa GGTTAAGTATAC GCC A3 A3.3 3480 * 3500 * 3520 * 3540 * 3560 * 3580 mel : G-TGCGG---GCC---------GTGCCG-CGACTGCGCTGCCAGCGTCGCCAGCGACGGCGGCGTCAA-ATGTTGGCCGG--C---CTGCGAAGCGCGTTCATTTTGTTTAT : 2811 sim : G-TGCGG---GCC---------GCGCCG-CGACTGCGCTGCCAGCGTCGCCAGCGACGGCGGCGTCAA-ATGTTGGCCGG--C---CTGCGAAGCGCGTTCATTTTGTTTAT : 2622 yak : G-TGCGG---CCC---------GAGCGT-CGACTGCGCTGCCAGCGTCGCCAGCGACGGCGACGTCAA-ATGTTGGCCGG--C---TTGCGAAGCGCGTTCATTTTGTTTAT : 2723 ere : G-TGCGG---GCC---------GACCGT-CGACTGCGCTGCCAGCGTCGCCAGCGACTGCGGCGTCAA-ATGTTGGCCGG--C---CTGCGAAGCGCGTTCATTTTGTTTAT : 2711 ore : G-TGCGG---GCC---------GAGCGT-CGACCGCGCTGCCGGCGTCGCCAGCGACGGCGGCGTCAA-ATGTTGGCCGG--C---CTGCGAAGCGCGTTCATTTTGTTTAT : 2739 G TGCGG gCC G gC CGACtGCGCTGCCaGCGTCGCCAGCGACgGCGgCGTCAA ATGTTGGCCGG C cTGCGAAGCGCGTTCATTTTGTTTAT A3 A3.3 * 3600 * 3620 * 3640 * 3660 * 3680 * mel : TTATACAGCCGAGCGGGTAGAACTCCATATTAGTGTCTTCTTGGCGTTTGCCGCAGTCGAGTCCGAGTCC--GAGTCCGAATCCGAATTCGAGTTTCGAGTCCGTAAACTGT : 2921 sim : TTATACAGCCGAGCGGGTAGAACTCCATATTAGTGTCTTCTTGGCGTTTGCCGCAGTCGAGTCCGAGTCC--GAGTCCGAATCC------GAGTTTCGAGTCCGTAAACTGA : 2726 yak : TTATACAGCCGAGCGGGTAGAACTCCATATTAGTGTCTTCTTGGCGTTTGGCGCAGTCGAATCCGAGTCCCCGAGTTCGAATCCGAATCCGAGTTTCGAGTCCGTAAGCTGA : 2835 ere : TTATACAGCCGAGCGGGTAGAACTCCATATTAGTGTCTTcttggcgtttgccgcagtcgaatccgagtcc--gaatccgaat------ccgagtttcgagtccgtaaactga : 2815 ore : TTATACAGCCGAGCGGGTAGAACTCCATATTAGTGTCTTCTTGGCGTTTGCCGCAGTCGAATCCGAGTCC--GAATCCGAATTGGAATCCGAGTTTCGAGTCCGTAAACTGA : 2849 TTATACAGCCGAGCGGGTAGAACTCCATATTAGTGTCTTCTTGGCGTTTGcCGCAGTCGA TCCGAGTCC GA TcCGAAT cGAGTTTCGAGTCCGTAAaCTGa Figure S3.3 Expression of elongase gene LOC6555117 in one-day- and four-day- old D. erecta oenocytes. Expressions are tested by using in situ hybridization, with gene specific probes. Arrows show gene expression. Female biased expression is found in 4-day-old D. erecta oenocytes, and non-sex biased expression is found in 1- day-old D. erecta oenocytes. 114 Figure S3.4 Chromatograms of CHCs profiles for D. melanogaster with Dmel/Bond RNAi. (A) Two compounds, C25:1 (b) and C27:2, were less produced with RNAi knocking down the expression of Dmel/Bond in female. (B) No CHC profile changes were detected in male after RNAi knockdown. Majorly detected CHC compounds were labeled. Non-labeled detections are not CHCs. “IS” stands for “internal standard” for quantity analyses. Colors of labels indicate status after RNAi knocking down, red with outline = Changed, green = Unchanged, blue = Internal Standard. 115 2 C2 C2 2C2 C22C2 C2 2 C2 2 C2 C2 C2 C2 2 C A A A Table S3.1 Primers used for molecular cloning (A) in situ hybridization RNA probes and (B) fragments for GFP reporter constructs. Sequences colored with red indicate designated cutting sites for restriction enzymes for cloning uses. 116 NameSequenceDere_LOC6541898_FATGGAGGTGTCAGCAAGTCCAAATDere_LOC6541898_RTAGTATCGCCTTACGTAGTCCGDere_LOC6547302_FATGAATTTCACACTATTTGAAATTDere_LOC6547302_RTGAAAAATAAGTATGTTAGCCAACDere_LOC6543867_FTAAATTTGGGGGGGAAAATATCDere_LOC6543867_RTCCATTTAGGACCGTAGCGCDere_LOC6543868_FCAGAGATCAGGTATAAAGGCGCDere_LOC6543868_RGATAAATAAAGGGTCAGCATGACGDere_LOC6543939_FACATGGGTGTTCTACTACTGCGGCDere_LOC6543939_RCAAAAAGATGAGAGGCTGCTTGCGDere_LOC6552176_FATGGCCTTAATTATGAAATACATCGDere_LOC6552176_RGCATGAACCATTCTCCGGGATGTGDere_LOC6552177_FCGACTTTTACAAAGCGAAATATCTCDere_LOC6552177_RTTATTTGACTTTTCGCTGATGCAGDere_LOC6553574_FAGAACGACTGCAACTACCCGATDere_LOC6553574_RTCACTTGTTGCCGGCGTTCACGDere_LOC6552259_FTTCTTCAACTCCAAAATGGCTGDere_LOC6552259_RGTGAGTACGCAGCGCATGTCGDere_LOC6552258_FGGTGTCATCTACGTCATAAGDere_LOC6552258_RAATATTTGTTGATTACAAATCAAT Table S3.1 (cont’d) 117 NameSequenceDere_LOC6552257_FTGTTCCACCGACGCCGATAACACDere_LOC6552257_RTTGGACATGCAGCTGAAGTTATAGDere_LOC6552256_FATGCTAATCGAAGCTTATAAACCDere_LOC6552256_RAGTGGACAGCGAAAAAGCACATGDere_LOC6555119_FAACTTCCCCAAGTCCATTGCCGCTDere_LOC6555119_RATACCTAGGGGTAGGATATGGDere_LOC6555117_FCCAAGTCTGTGGACGGCGGCAGTDere_LOC6555117_RAGGTAAAAGTAAAAGGTAATGGTDere_LOC6555116_FAAGTCTCGTGGGTAGCGGATGDere_LOC6555116_RCCAGGACAGCACGAAGAAGAGGTDere_LOC6555115_FCGCCCAGTTCGTGCTGTGCATCTDere_LOC6555115_RGACTGCTTTCGCTATTCAATTCAGDere_LOC6554897_FATGCGGCACAACATGGTGGCDere_LOC6554897_RCCGTGTGATCCACTGGCTGGCDere_LOC6555308_FAAATTGAATAGTAGAAAATAAATATCDere_LOC6555308_RGACGGTCATGCAGCGAAAGTTDere_LOC6547301_FAACACTGACTCAGCTCTGCCDere_LOC6547301_RTCCGAAGTCGAATTTGAGAAAGT Table S3.1 (cont’d) B 118 NameSequenceCloning PurposesDere-BondA-FCCGGGCGAATTCGCCGGCGCGCCTGTGTTTTTCCAGTGTGACTGTereA, oreA, A1+A2Dere-BondA-RCGGTTGCGATCGCTTCCTGCAGGGACACTAATATGGAGTTCTACCereA, oreA, A2+A3Dere-BondA1-RCCTGCAGGGACCCTGAACTTCAGCGCTA1, A2.1Dere-BondA2-F GGCGCGCCTAATAGCGCAATTTAACTACA2+A3, A2.1, A2+A3.1, A2+A3.1+A3.2Dere-BondA2-RCCTGCAGGTCAGTGATAACTCAGGTTAATTA1+A2Dere-BondA3-F GGCGCGCCTAATAAATCAATTGTCTAGCGGTA3Dere-BondA2.2-FGGCGCGCCCTCTCGGCGTTCTGATCAGCA2.2, A2.2a, oreA2.2Dere-BondA2.2-RCCTGCAGGCACGCACTTACTCTCACCGA2.2, A2.2c, oreA2.2Dere-BondA2.3-FGGCGCGCCGTTGCAGTGCATCGAGCTTGA2.3Dere-BondA2.3-RCCTGCAGGAAGTTCTTGTGCTATCTTGCA2.3Dere-BondA2.2a-RCCTGCAGGGCATAATCGGCGCTTCGCTTTTGA2.2aDere-BondA2.2b-FGGCGCGCCAATCACAAAAGCGAAGCGCCGA2.2bDere-BondA2.2b-RCCTGCAGGTGCGTTGGTCGCCACACTTCA2.2bDere-BondA2.2c-FGGCGCGCCACCCGGAAGTGTGGCGACCAACA2.2cDere-BondA3.1-RCCTGCAGGAATGAATTTCTAAAAACTGTTATGTGCA2+A3.1Dere-BondA3.2-RCCTGCAGGGCAAAACTGCTGGCAGCAGCAGA2+A3.1+A3.2 Figure S3.5 Expression of reductase genes in four-day-old D. erecta oenocytes. Expressions are tested by using in situ hybridization, with gene specific probes. Arrows show gene expression. Sex biased expression is found in LOC6548541 and LOC6553677. 119 Figure S4.1 Quantitative changes of major mbCHCs in transgenic line of D. mojavensis (Dmoj/mElo knockout) adapted from (Wang et al. 2023). n.s. = not significant; **p < 0.01; ***p < 0.001. 120 Figure S4.2 Survivorship of D. melanogaster with different levels of mbCHCs productions. (A) No significant difference in survivorship in females with overexpressing CG18609 (p = 0.012). (B) Males from the line of CG18609 overexpression survived significantly better (p < 0.001). Both females (C) and males (D) from the line of CG18609 RNAi survived significantly better (both sexes, p < 0.0001). The percentage of surviving adults was shown from the enclosed day. Lines of transgenic D. melanogaster were adapted from (Wang et al. 2023). Control = D. melanogaster with normal level of mbCHCs production, CG18609 O/E = Overexpressing CG18609 in D. melanogaster oenocytes, leading to increasing amounts of longer chained mbCHCs. CG18609 RNAi = Knocking down CG18609 expression in D. melanogaster oenocytes, leading to reduced amounts of longer chained mbCHCs. Kaplan-Meier approach was used to determine the survivorship ability and any significant difference. 121 Figure S5.1 Synteny genome comparison of selected elongase genes across Drosophila species. Genes labeled with dark background and light font are elongase genes. Genes labeled with light background and dark font are marker genes. D. mel = D. melanogaster, D. sim = D. simulans, D. yak = D. yakuba, D. ere = D. erecta, D. ana = D. ananassae, D. pse = D. pseudoobscura, D. wil = D. willistoni, D. moj = D. mojavensis, D. ele = D. elegans, D. ser = D. serrata, D. per = D. persimilis. Blank areas indicate the absence of elongase orthologs in the genomes of the corresponding species, and the marker genes utilized aligned to the genomes but not close enough to be informative. 122 Figure S5.1 (cont’d) 123 Figure S5.1 (cont’d) 124 Figure S5.1 (cont’d) 125 Figure S5.1 (cont’d) 126 Figure S5.1 (cont’d) 127 Figure S5.1 (cont’d) 128 Figure S5.1 (cont’d) 129 Figure S5.1 (cont’d) 130 Figure S5.1 (cont’d) 131 Figure S5.1 (cont’d) 132