Published today in Evolutionary Bioinformatics is a new methodology article by Kyu-Won Kim, David W. Burt, Heebal Kim and Seoae Cho.  Read more about this paper below:

Title

Identification of Differentially Evolved Genes: An Alternative Approach to Detection of Accelerated Molecular Evolution from Genome-Wide Comparative Data

Abstract

One of the most important measures for detecting molecular adaptations between species/lineages at the gene level is the comparison of relative fixation rates of synonymous (dS) and non-synonymous (dN) mutations. This study shows that the branch model is sensitive to tree topology and proposes an alternative approach, devogs, which does not require phylogenetic topology for analysis. We compared devogs with a branch model method using virtual data and a varying ω ratio, in which parameters were obtained from real data. The positive predictive value, sensitivity, and specificity of the branch model were affected by the phylogenic tree topology. Devogs showed greater positive predictive value, whereas the branch model method had greater sensitivity. In a working example using devogs, a group of human RNA polymerase II-related genes, which are important in mediating alternative splicing, were significantly accelerated compared to four other mammals.

Click here to learn more about the article, download it and comment

share on