Researchers at 23andMe report their "Web-based, participant-driven" research protocol in PLoS Genetics this week. "The approach takes advantage of the interactivity of the Web both to gather data and to present genetic information to research participants, while taking care to correct for the population structure inherent to this study design," the authors write. Using the outlined methodology, the team was able to replicate genetic associations for hair and eye color, as well as freckling, and elucidate novel associations for "hair morphology," freckling, the " ability to smell the methanethiol produced after eating asparagus," and "photic sneeze reflex."
Also in PLoS Genetics this week, Argentinean investigators detail "multiple regulators of HIF-dependent transcription in hypoxia," which they distinguished via a genome-wide RNAi screen in Drosophila. After three rounds of selection, the authors write, "30 genes emerged as critical HIF regulators in hypoxia, most of which had not been previously associated with HIF biology," containing the ago1 gene, "a central element of the microRNA translation silencing."
Investigators at the University of Melbourne suggest that "copy-number variation and transposable elements feature in recent, ongoing adaptation at the Cyp6g1 locus" in Drosophila this week. Joshua Schmidt et al. show that "this genetic variation underpins phenotypic variation, as the more derived the allele, the greater the level of DDT resistance," they write, adding that "the Cyp6g1 locus is a major contributor to DDT resistance in field populations, and evolution at this locus features multiple adaptive steps occurring in rapid succession."
And in PLoS One this week, Aaron Darling and colleagues at the University of Wisconsin-Madison describe the methodology behind their new tool for multiple genome alignments, progressiveMauve. Darling et al. report that their approach "uses a novel alignment objective score called a sum-of-pairs breakpoint score, which facilitates accurate detection of rearrangement breakpoints when genomes have unequal gene content." The team also describes "new metrics for quantifying genome alignment accuracy which measure the quality of rearrangement breakpoint predictions and indel predictions," and suggests that their algorithm demonstrates "high accuracy" in instances where genomes have undergone rearrangement, specifically segmental gains and losses that are "biologically feasible."