Parallel genomic architecture underlies repeated sexual signal divergence in HawaiianLaupalacrickets
Author(s) -
Thomas Blankers,
Kevin P. Oh,
Kerry L. Shaw
Publication year - 2019
Publication title -
proceedings of the royal society b biological sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.342
H-Index - 253
eISSN - 1471-2954
pISSN - 0962-8452
DOI - 10.1098/rspb.2019.1479
Subject(s) - quantitative trait locus , genetic architecture , biology , quantitative genetics , evolutionary biology , cricket , genetics , divergence (linguistics) , trait , phenotype , genetic variation , gene , ecology , computer science , linguistics , philosophy , programming language
When the same phenotype evolves repeatedly, we can explore the predictability of genetic changes underlying phenotypic evolution. Theory suggests that genetic parallelism is less likely when phenotypic changes are governed by many small-effect loci compared to few of major effect, because different combinations of genetic changes can result in the same quantitative outcome. However, some genetic trajectories might be favoured over others, making a shared genetic basis to repeated polygenic evolution more likely. To examine this, we studied the genetics of parallel male mating song evolution in the Hawaiian cricketLaupala . We compared quantitative trait loci (QTL) underlying song divergence in three species pairs varying in phenotypic distance. We tested whether replicated song divergence between species involves the same QTL and whether the likelihood of QTL sharing is related to QTL effect size. Contrary to theoretical predictions, we find substantial parallelism in polygenic genetic architectures underlying repeated song divergence. QTL overlapped more frequently than expected based on simulated QTL analyses. Interestingly, QTL effect size did not predict QTL sharing, but did correlate with magnitude of phenotypic divergence. We highlight potential mechanisms driving these constraints on cricket song evolution and discuss a scenario that consolidates empirical quantitative genetic observations with micro-mutational theory.
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