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This Week in Nucleic Acids Research: Jan 21, 2015

A team from the UK and Singapore introduces an analytical approach called EvoTol, designed to classify disease-causing mutations and associated genes using exome sequence data. The approach takes a gene's sequence conservation, mutation tolerance predictions, and tissue-specific gene expression profiles into consideration, authors of the study say, noting that their proof-of-principle experiments uncovered disease-related gene candidates in whole-exome sequence data from individuals with epilepsy or congenital heart disease. "Application of EvoTol to the human interactome revealed networks enriched for genes intolerant to protein sequence variation," they note, "informing novel polygenic contributions to human disease."

Researchers from Denmark describe a computational method aimed at assessing transcriptional activity based on cues from intervening sequence, or intron, coverage in RNA sequence data. The approach, known as iRNA-seq, appeared to perform favorably when compared to results generated by more specialized sequencing methods such as global run-on sequencing or chromatin immunoprecipitation sequencing targeting the RNA polymerase II enzyme. "[U]nlike the current methods that are all very labor intensive and demanding in terms of sample material and technologies," the study's author argue, "iRNA-seq is cheap and easy and requires very little sample material."

German researchers report on transcriptional patterns in Candida glabrata, a fungal species that sometimes causes hospital- or healthcare center-associated infections. The team performed RNA sequencing on C. glabrata strains grown under different nutrient conditions and salinity profiles. Together with gene prediction software, this transcriptome sequence data led to dozens of predicted protein-coding genes, non-coding genes, introns, and alternative splicing patterns, improving the existing annotation for C. glabrata. Through comparisons with related fungal species such as Saccharomyces cerevisiae and C. albicans, meanwhile, the study's authors identified distinct C. glabrata features associated with response to particular pH or nitrogen conditions.