When the two sexes of anisogamous species maximize their fitness in different ways [1], this difference creates a sexual conflict, in which traits favored in one sex are not favored in the other [2]. There are two types of sexual conflict. Intralocus sexual conflict occurs when the targets of selection are alleles at the same loci in both sexes [3]. Interlocus sexual conflict, which is less well-understood, involves alleles at separate loci [4]. Under interlocus sexual conflict, one sex evolves traits that improve its reproductive success at the expense of the other. In turn, this generates selection on the other sex to resist the effects of these traits. The outcome is thought to be an evolutionary arms race between the two sexes known as sexually antagonistic coevolution (SAC) [1].

There are two major limitations to studying SAC. First, most studies on SAC rely on phenotypic data alone. This means that compelling genomic evidence for how SAC evolves is lacking [4]. Second, there is a historical disparity in research focus: much more attention has been paid to the genetic mechanisms underlying male trait evolution than female trait evolution [5]. This is another example of the well-known disparity between studies of males and females in medicine and biology [6, 7], including in terms of reproductive tract and genital evolution [5; 8]. To establish the importance of female evolution for driving SAC, my dissertation focuses on the genetic mechanisms behind female resistance to male-induced harm.

1. Parker 1979
2. Arnqvist & Rowe 2005
3. Cox & Calsbeek 2009
4. Rowe et al. 2018
5. Ah-King et al. 2014

6. Beery & Zucker 2011
7. Zucker & Beery 2010
8. Simmons 2013

Three Aims of Dissertation

  1. Quantify variation in female resistance among different inbred lines and identify genomic regions associated with this variation.
    • A. Quantify variation in male harm among different inbred lines.
    • B. Quantify variation in female resistance among different inbred lines.
    • C. Perform genome-wide association study (GWAS) for female resistance using data from 1B.
  2. Evolve a population of females while preventing males from coevolving, and use both phenotypic and genetic data to determine if and how females evolved a higher level of resistance.
  3. Analyze the effects of genes implicated in both Aim 1 and Aim 2 to determine if they are truly involved in female resistance, and if so, to what extent.

Study System

Drosophila melanogaster exhibits extensive sexual conflict. Males have
evolved proteins in their seminal fluid (SFPs) that increase their own fitness [9; 10], but decrease the lifespan [11] and lifetime reproductive success [12] of their female partners. Much of the research surrounding sexual conflict in D. melanogaster has focused largely on males, including the identification of numerous SFPs [10; 13] and quantification of genetic variation for male harm [14; 15].

The female side of this dynamic, however, has not received as much attention. Some studies show that some females are more resistant to male harm than others [14; 16], and that females can evolve resistance to higher mating rates [17; 18]. It is unclear whether female resistance evolves in response simply to harassment due to mating rate, a behavior, or physiologically based male harm. Molecular evolution studies show that genes in the female reproductive tract are under positive directional selection [19; 20]. While this is consistent with the evolution of female resistance, it is not definitive, because evidence of positive selection at this level is not evidence about the agent of selection. There is also evidence that a variety of genes can influence female fecundity [21] and post-mating behavior [22; 23], but it is not known whether these genes are involved in female resistance to male harm. The most comprehensive genomic study to date is a genome-wide association study [24] that examined intra– rather than interlocus sexual conflict. This study did not specifically measure female resistance and obtained results that are contradictory to many theoretical predictions [25; 26].

9. Hollis et al. 2016
10. Ravi Ram & Wolfner 2007
11. Chapman et al. 1995
12. Wigby & Chapman 2005
13. Swanson & Vacquier 2002
14. Friberg 2005
15. Lew & Rice 2005
16. Lew et al. 2006
17. Wigby & Chapman 2004

18. Holland & Rice 1999
19. Lawniczak & Begun 2007
20. Swanson et al. 2004
21. Durham et al. 2014
22. Yapici et al. 2008
23. Billeter et al. 2006
24. Ruzicka et al. 2019
25. Rice 1984
26. Fry 2009