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This Week in Nature: Oct 18, 2018

In Nature Genetics this week, a trio of scientists from the University of Oxford reports a method for the identification of genetic variants that affect trait variability. They develop a two-degree-of-freedom test that jointly tests mean and variance effects to identify these loci, and use it in a linear mixed model for which they provide an efficient algorithm and software. The investigators also develop a test for dispersion effects and apply it to body mass index in the subsample of the UK Biobank population with British ancestry to identify and replicate novel associations with significant variance effects that cannot be explained by the non-normality of body mass index.

And in Nature Biotechnology, a Stanford University team describes the application of read clouds —  short-read sequences tagged with long-range information — to uncultured microbiome samples to generate high-quality genome drafts in a single shotgun sequencing experiment. With a de novo assembler that uses read clouds to improve metagenomic assemblies, the researchers sequence stool samples from two healthy individuals and produce a comprehensive individual genome drafts with high contiguity, even for bacteria with relatively low raw short-read sequence coverage. They also sequence a complex marine-sediment sample and generated 24 intermediate-quality genome drafts, including nine complete ones.

Meanwhile, in Scientific Reports, a group of US and UK researchers presents data suggesting people's genetics influence their decision to attend university, as well as their academic performance there. They analyzed a UK-representative sample of 3,000 genotyped individuals and 3,000 twin pairs, and find that genetic factors accounted for 57 percent of the differences in university entrance exam scores, university enrollment, university quality, and achievement at university. "These findings suggest young adults select and modify their educational experiences in part based on their genetic propensities, and highlight the potential for DNA-based predictions of real-world outcomes," the authors write. The Scan has more on this, here.