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This Week in PLOS: Jul 23, 2013

A team from the US and China used genotyping with high-density arrays to narrow in on candidate loci linked to high altitude adaptations in a nomadic Mongolian population called the Deedu, known to have moved into an area known as the Qinghai-Tibetan Plateau from the Mongolian steppes some 500 years ago. As they reported in PLOS Genetics, the researchers' SNP-based analysis uncovered several genes that appear to have been subject to selection in the Deedu population, including genes linked to high altitude or metabolic traits in other populations. Through whole-genome sequencing on one Deedu individual, they also got a glimpse at some of the genetic variants that may be specific to that population.

In PLOS Pathogens, a team from the Netherlands, Japan, and Russia document the architecture behind pronounced genome expansions in nidoviruses — viruses from an RNA virus order known for genome sizes that are not only unusually large but also contain sequences coding for an apparent DNA proof-reading enzyme not present in other, more diminutive RNA viruses. Results of the researchers' computational analyses led them to conclude that that enzyme "was part of a larger process with non-linear dynamics, during which distant coding regions of the nidovirus genome were expanded to accommodate both an extremely large number of mutations and virus adaptation to different host species."

A core set of a few dozen microbial species seem to rule the roost amongst microbial communities in human feces over time, according to a PLOS One study by University of Nebraska researchers. The group relied on 16S ribosomal RNA sequencing to profile members of fecal microbiomes from three individuals over a year. The data pointed to core sets of between 33 and 40 microbial species that seemed to dominate each individual's fecal microbial communities over time. On the analytical front, meanwhile, the researchers' findings indicated that "methodological artifacts of [operational taxonomic unit]-based approaches complicate core calculations, and these limitations have to be considered in the interpretation of microbiome studies."