project . 2018 - 2021 . Closed

NSFDEB-NERC: Ecological Genomics of Adaptive Polymorphism

UK Research and Innovation
Funder: UK Research and InnovationProject code: NE/P013074/2
Funded under: NERC Funder Contribution: 251,239 GBP
Status: Closed
30 Sep 2018 (Started) 29 Jun 2021 (Ended)

Accounting for high genetic diversity in ecologically-important traits is a fundamental problem in evolutionary biology. Individuals vary enormously at the genetic level, even within local populations, and we do not understand why. Recent work implicates an advantage to rare types as a critical factor maintaining genetic variation in many species, but we have little understanding of how this process actually unfolds in the wild. To address this gap, we need to (1) understand how ecological and social interactions promote or erode genetic diversity, and (2) link these interactions among organisms directly to the genes underlying the traits that mediate these interactions. This project will link a genetically diverse trait in the Trinidad guppy (Poecilia reticulata) to the ecological and social interactions that shape its evolution, and to the underlying genes that shape this diversity. Our previous work indicates that interactions with predators and with potential mates both favour rare colour patterns in this species. To determine which of the processes is most responsible for promoting diversity, we will collect data on predation risk and mating behaviour in multiple natural populations and relate these data to the degree of genetically-based diversity in colour patterns. Then, using populations and closely related species that vary in their genetic diversity, we will use whole-genome DNA sequencing to identify genes that control this highly variable trait. This will allow us to determine how ecological and molecular processes interact to promote or constrain evolution under balancing selection. Finally, we will directly test the idea that interactions between potential mates can maintain diversity in this species by observing evolution in real time in experimental populations with different opportunities for mate choice.

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