Published online in Genome Research this week, investigators at the University of Connecticut and the University of Michigan report their elucidation of the regulatory divergence in two closely related Drosophila species using deep mRNA sequencing. Between D. melanogaster and D. sechellia, 78 percent of expressed genes have divergent expression, the researchers write. They also found that cis-regulatory differences contributed to more expression divergence and showed more additive inheritance. "Overall, this study illustrates the power of mRNA sequencing for investigating regulatory evolution, provides novel insight into the evolution of gene expression in Drosophila, and reveals general trends that are likely to extend to other species," the authors write.
A review article written by researchers in the US and Austria in Genome Research this week evaluates the practice of inferring population genetics from genomic sequence variation data. In it, they assess the challenges to examining whole-genome sequence polymorphism data and "discuss the potential of these data to yield new insights concerning population history and the genomic prevalence of natural selection."
In an advance, online publication of Genome Research this week, scientists report that "natural selection drives the accumulation of amino acid tandem repeats in human proteins." To evaluate the contribution of neutral and selective forces acting on amino acid repeat evolution, the authors compared AA repeat conservation in a set of orthologous proteins from 12 vertebrate species. "The results strongly indicate that selection has played a more important role than previously suspected in amino acid tandem repeat evolution, by increasing the repeat retention rate and by modulating repeat size," they write, adding that their data allowed them to identify 92 repeats thought to serve functional roles because of their "strong selective signature[s]."
Also published online, a research article by international investigators discusses the "genome-wide mapping and assembly of structural variant breakpoints in the mouse genome." The researchers developed an algorithm, called HYDRA, to localize structural variant breakpoints using paired-end mapping; in applying the algorithm to two inbred mouse strains, the team was able to accurately map diverse classes of structural variants, "including those involving repetitive elements such as transposons and segmental duplications." The authors also report that structural variants are "significantly enriched in regions of segmental duplication," independent of DNA sequence homology.