Published: 27 October 2019| Version 1 | DOI: 10.17632/phd622sdf7.1
Bahar Patlar,


Seminal fluid proteins (SFPs) are uniquely positioned to mediate post-mating sexual selection and sexual conflict. This role may be especially important in simultaneously hermaphroditic taxa, in which individuals will often agree to receive sperm in order to be able to donate it, shifting the arena of sexual selection to post-mating reproductive interactions. Nevertheless, just as in separate-sexed organisms, identifying the individual SFPs responsible for specific post-mating effects is difficult, owing to the complexity, rapid evolution and functional redundancy of seminal fluid. Here we sought to identify the SFPs responsible for influencing one striking post-mating behaviour seen in the simultaneously hermaphroditic flatworm Macrostomum lignano, namely the so-called suck behaviour in which worms respond to ejaculate receipt by placing their pharynx over the female genital opening and seemingly attempt to remove sperm and/or other ejaculate components. We hypothesised that sucking is counter to the sperm donor’s interests, and this should, therefore, select for SFPs that reduce the suck propensity of mating partners. We tested this using a combination of quantitative genetics and RNA interference knockdown approaches. As predicted, we found negative genetic correlations between the expression levels of six (out of 58) seminal fluid transcripts and the partner's suck propensity. RNAi knockdown then confirmed that two of these transcripts, which we here designate suckless-1 and suckless-2, indeed caused mating partners to suck less often. We suggest that these proteins are likely male counter-adaptations to recipient suck behaviour, which itself likely evolved as a female counter-adaptation in the ongoing evolutionary conflict to (re)gain control over ejaculate fate after mating in this hermaphroditic organism.



Universitat Bielefeld


Evolutionary Biology, Animal Mating, Sperm Competition, Macrostomum lignano, Sexual Conflict, Gene Expression Profiling