DISSERTATION RESEARCH: A coalescent analysis of the diversity of standing genetic variation and adaptive evolution in the threespine stickleback

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Evolution by natural selection is thought to often take thousands or millions of years. The environments in which species live can change drastically on much shorter timescales, however, and species must adapt quickly or risk extinction. Along the west coast of the US and Canada, a small fish species, the threespine stickleback, is known to adapt within decades to wildly different environments. This study will examine how stickleback achieve this feat by focusing on the influence a species' gene pool has on its ability to respond rapidly to a changing environment. Specifically, the proposed research will examine (1) how much of adaptive evolution is aided by genetic variation already existing in the stickleback gene pool, and (2) how the stickleback's history of adaptation has influenced the organization of genetic variation in its entire genome. This understanding of adaptive potential is crucial to our ability to predict how species and ecosystems will respond to future environmental shifts, and thus has implications for conservation and game management efforts, climate change mitigation, and agriculture. Standing genetic variation is the pool of available genetic variants in a population available for evolutionary change. Recent research, facilitated by next-generation DNA sequencing technologies and new analytical techniques, has revitalized the debate over the relative influence of standing genetic variation versus new mutation on adaptive evolution and speciation. The research funded by this grant will use approaches based in coalescent theory, a mathematically-rigorous approach at the interface of phylogenetics and population genetics, to understand the prevalence and influence of standing variation in natural populations of threespine stickleback fish. By combining restriction site-associated DNA sequencing, a powerful method for genome-wide inference, with new long-read sequencing capabilities, the proposed research will generate data-rich genealogies at tens of thousands of loci and provide unprecedented detail into adaptation of natural populations.