Literature DB >> 28994152

Genomics of adaptive divergence with chromosome-scale heterogeneity in crossover rate.

Daniel Berner1, Marius Roesti1,2.   

Abstract

Genetic differentiation between divergent populations is often greater in chromosome centres than peripheries. Commonly overlooked, this broadscale differentiation pattern is sometimes ascribed to heterogeneity in crossover rate and hence linked selection within chromosomes, but the underlying mechanisms remain incompletely understood. A literature survey across 46 organisms reveals that most eukaryotes indeed exhibit a reduced crossover rate in chromosome centres relative to the peripheries. Using simulations of populations diverging into ecologically different habitats through sorting of standing genetic variation, we demonstrate that such chromosome-scale heterogeneity in crossover rate, combined with polygenic divergent selection, causes stronger hitchhiking and especially barriers to gene flow across chromosome centres. Without requiring selection on new mutations, this rapidly leads to elevated population differentiation in the low-crossover centres relative to the high-crossover peripheries of chromosomes ("Chromosome Centre-Biased Differentiation", CCBD). Using simulated and empirical data, we then show that strong CCBD between populations can provide evidence of polygenic adaptive divergence with a phase of gene flow. We further demonstrate that chromosome-scale heterogeneity in crossover rate impacts analyses beyond that of population differentiation, including the inference of phylogenies and parallel adaptive evolution among populations, the detection of genetic loci under selection, and the interpretation of the strength of selection on genomic regions. Overall, our results call for a greater appreciation of chromosome-scale heterogeneity in crossover rate in evolutionary genomics.
© 2017 John Wiley & Sons Ltd.

Keywords:  barrier to gene flow; hitchhiking; linked selection; population differentiation; recombination; standing genetic variation

Mesh:

Year:  2017        PMID: 28994152     DOI: 10.1111/mec.14373

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


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