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Isolated populations with novel phenotypes present an exciting opportunity
to uncover the genetic basis of ecologically significant adaptation, and
genomic scans have often, but not always, led to candidate genes directly
related to an adaptive phenotype. However, in many cases these populations
were established by a severe bottleneck, which can make identifying
targets of selection problematic. Here, we simulate severe bottlenecks and
subsequent selection on standing variation, mimicking adaptation after
establishment of a new small population, such as an island or an
artificial selection experiment. Using simulations of single loci under
positive selection and population genetics theory, we examine how
population size and age of the population isolate affect the ability of
outlier scans for selection to identify adaptive alleles using both
single-site measures and haplotype structure. We find and explain an
optimal combination of selection strength, starting frequency, and age of
the adaptive allele, which we refer to as a Goldilocks zone, where
adaptation is likely to occur and yet the adaptive variants are most
likely to derive from a single ancestor (a ‘hard’ selective sweep); in
this zone, four commonly used statistics detect selection with high power.
Real-world examples of both island colonization and experimental evolution
studies are discussed. Our study provides concrete considerations to be
made before embarking on whole-genome sequencing of differentiated
populations.
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