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This Week in Genome Biology: Jan 16, 2013

A clone of methicillin-resistant Staphylococcus aureus that expanded rapidly throughout the world has variable recombination rates, researchers led by the University of Bath's Edward Feil report in Genome Biology. Using the Bayesian Recombination Tracker, or BRATNextGen, the researchers examined evidence of recombination in sequence data from 165 MRSA isolates from around the world. They note that about 440 genes were affected by recombination, though many were in mobile genetic elements, rather than in the core genome. Through phylogeographic analysis, the researchers found that isolates from different regions had different recombination rates. "Possible explanatory variables include the size and time since emergence of each defined sub-population (as determined by the sampling frame), variation in transmission dynamics due to host movement, and changes in the bacterial genome affecting the propensity for recombination," Feil and his colleagues write.

Mihai Pop from the University of Maryland and his colleagues present a new metagenomic assembly and analysis pipeline, dubbed MetAmos, in Genome Biology this week. MetAmos, which can be downloaded here, aims to solve some problems that other genome assemblers have with metagenomic data. According to Pop and his team, "MetAMOS provides a push-button solution for analysis of metagenomic datasets, irrespective of the sequencing technology used," while also offering "a modular and flexible pipeline, integrating many metagenomic analysis tools that can be tailored and extended to meet specific analysis needs."

Finally, Washington University in St. Louis' George Weinstock and colleagues characterize the healthy human microbiome biogeography in Genome Biology. They examined the diversity, spatial relationships, and stability over time of 22 different sites on 279 healthy people. Based on sequencing the variable regions of the 16S rRNA genes from their samples, the researchers found 929 genera from 30 different phyla and noted that different sampling sites have different levels of diversity and stability: The oral microbiome appears to have higher stability as compared to the skin or vaginal microbiome. "Each habitat has its own characteristic biodiversity and taxon abundance distribution curve," the researchers write. "While there are many contributing factors to each characteristic pattern, this description of the healthy state will contribute to recognition of changes associated with disease."