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Determining the rate of protein evolution and identifying the causes of its variation across the genome are powerful ways to understand forces that are important for genome evolution. By using a multitissue transcriptome data set from great tit (Parus major), we analyzed patterns of molecular evolution between two passerine birds, great tit and zebra finch (Taeniopygia guttata), using the chicken genome (Gallus gallus) as an outgroup. We investigated whether a special feature of avian genomes, the highly variable recombinational landscape, modulates the efficacy of natural selection through the effects of Hill-Robertson interference, which predicts that selection should be more effective in removing deleterious mutations and incorporating beneficial mutations in high-recombination regions than in low-recombination regions. In agreement with these predictions, genes located in low-recombination regions tend to have a high proportion of neutrally evolving sites and relaxed selective constraint on sites subject to purifying selection, whereas genes that show strong support for past episodes of positive selection appear disproportionally in high-recombination regions. There is also evidence that genes located in high-recombination regions tend to have higher gene expression specificity than those located in low-recombination regions. Furthermore, more compact genes (i.e., those with fewer/shorter introns or shorter proteins) evolve faster than less compact ones. In sum, our results demonstrate that transcriptome sequencing is a powerful method to answer fundamental questions about genome evolution in nonmodel organisms.

Original publication

DOI

10.1093/gbe/evu157

Type

Journal article

Journal

Genome Biol Evol

Publication Date

08/2014

Volume

6

Pages

2061 - 2075

Keywords

Hill–Robertson interference (HRI), RNAseq, natural selection, protein evolution, recombination, tissue specificity in gene expression, Animals, Chickens, Evolution, Molecular, Finches, Genome, Passeriformes, Phylogeny, Recombination, Genetic, Selection, Genetic, Transcriptome