In PLoS Biology this week, an international research team led by investigators at Italy's Telethon Institute of Genetics and Medicine reports its high-resolution anatomical atlas of the mouse embryo transcriptome. By creating "anatomy-based expression profiles for over 18,000 coding genes and over 400 microRNAs" via colorimetric RNA in situ hybridization, the Telethon Institute-led team found "1,002 tissue-specific genes that are a source of novel tissue-specific markers for 37 different anatomical structures."
Several researchers challenge the power of synthetic associations in PLoS Biology this week. The Queensland Institute of Medical Research's Naomi Wray et al. write in a perspectives paper that "synthetic associations ... tend to differ in some important ways to observations from GWAS," adding that "even if rare variants can, in principle, give rise to associations detectable in GWAS, the converse proposition (that, for a given trait, many, or even any, detected GWAS associations arise from rare variants) does not automatically follow." The Wellcome Trust Sanger Institute's Carl Anderson et al. say that while synthetic associations are theoretically possible, "it is worthwhile to broadly assess, in light of other theoretical and empirical evidence, the prevalence of synthetic associations in complex human disease." David Goldstein at the Duke University School of Medicine weighs in on this discussion, and says that "GWAS are a highly effective tool and well worth doing" and that while "synthetic associations are plausible," their importance can only be deduced with empirical evidence.
In PLoS One this week, a team led by investigators at Mississippi State University present a BAC library for loblolly pine tree (genotype 7-56), which "consists of 1,824,768 individually archived clones, making it the largest single BAC library constructed to date." This large library "should hasten whole genome sequencing of LP [loblolly pine]," which, like other conifers, has been neglected due to the size of its genome, the authors write.
And in PLoS Computational Biology this week, researchers at the University of California, San Francisco, present PhylOTU, an approach to quantify microbial diversity and to distinguish novel taxa from metagenomic data. PhylOTU sifts through metagenomic clustering ribosomal RNA sequence data to resolve operational taxonomic units based on "phylogenetic principles and probabilistic sequence profiles," the authors write.