bioRxivEvolutionary BiologyPreprint
Evidence that genetic drift not adaptation drives fast-Z and large-Z effects in Ficedula flycatchers
Abstract
The sex chromosomes have been hypothesized to play a key role in driving adaptation and speciation across many taxa. The reason for this is thought to be the hemizygosity of the heteromorphic part of sex chromosomes in the heterogametic sex, which exposes recessive mutations to natural and sexual selection. The exposure of recessive beneficial mutations increases their rate of fixation on the sex chromosomes, which results in a faster rate of evolution. In addition, genetic incompatibilities between sex-linked loci are exposed faster in the genomic background of hybrids of divergent species, which makes sex chromosomes contribute disproportionately to reproductive isolation. However, in birds, which show a Z/W sex determination system, the disproportionate role of the Z-chromosome in adaptation and reproductive isolation is still debated. Instead, genetic drift has been proposed as the main driver of the so-called fast-Z and large-Z effects in birds. Here, we address this question in Ficedula flycatchers based on population resequencing data of six flycatcher species. Our results provide evidence for both the fast-Z and large-Z effects in Ficedula flycatchers and that these two phenomena are driven by genetic drift rather than positive selection. Genomic scans of selective sweeps and fixed differences in fact suggest a reduced action of positive selection on the Z-chromosome. We propose that the observed reduction in the efficacy of purifying selection on the Z-chromosome helps to establish genetic incompatibilities between Z-linked and autosomal loci, which could result in pronounced selective sweep signatures for compensatory mutations on the autosomes.
- organism: multiple species
- assay: whole-genome sequencing
- research focus: chromatin & epigenetic regulation
- research focus: gene regulatory network inference
- research focus: variant calling
- research focus: differential expression
- approach: statistical model
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