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This Week in PLOS: Apr 13, 2015

In PLOS One, researchers from India used comparative genomics on sequences from clinical isolates of Mycobacterium tuberculosis to put together a pangenome for the tuberculosis-causing bug. The team considered genomes from 96 M. tuberculosis complex strains for its analysis — a set that included assemblies for eight newly sequenced clinical isolates from India. Using this data, the study's authors defined more than 2,000 "hard-core" gene clusters and nearly 3,400 more that were more shared across 95 percent of strains and classified as part of the "soft-core" pangenome. The remaining gene clusters fell into the accessory genome, which included dozens of gene clusters missing from laboratory reference strains.

A team from China did de novo RNA sequencing on samples from the Venus Clam, Cyclina sinensis, to search for immune-related transcripts in that animal. As they report in another PLOS One paper, the researchers sequenced the transcriptomes of hemolymph samples from Venus clams collected off the coast of China that had or had not been injected with the bacterial pathogens Vibrio anguillarum or Micrococcus luteus. From the more than 70,000 transcripts they assembled, the investigators identified 135 transcripts representing 102 suspected immune genes. They also used sequences from more than 9,900 gene families as part of a phylogenic analysis that included the Venus clam and four related species.

A computational approach known as a Bayesian mixture model can help in simultaneously uncovering new variants, estimating contributions that such variants make to the heritability of complex traits, and predicting related phenotypes, according to a study in PLOS Genetics. An Australian team presented the approach, applying it to simulated data and to genotyping data for thousands of individuals enrolled through the Wellcome Trust Case Control Consortium. "In the analysis of seven common diseases," they write, "we show large differences in the proportion of genetic variation due to loci with different effect sizes and differences in prediction accuracy between complex traits."