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This Week in Science: Nov 2, 2018

In this week's Science, scientists from the University of Glasgow report the creation of a computer model that uses genomic data to investigate outbreaks of RNA virus infections. They created a dataset containing the genome sequences of more than 500 single-stranded RNA viruses to which they applied machine learning to build models that predict the animal reservoirs and arthropod vectors of the pathogens. The team used their approach to predict the epidemiology of diverse viruses across most human-infective families of single-stranded RNA viruses, including 69 viruses with previously elusive or never-investigated reservoirs or vectors. "Models such as these, which capitalize on the proliferation of low-cost genomic sequencing, can narrow the time lag between virus discovery and targeted research, surveillance, and management," the authors write. GenomeWeb has more on this, here.

And in Science Translational Medicine, a University of Massachusetts Medical School team reports the safe use of a gene-silencing molecule designed to inhibit the gene SOD 1 — which is mutated in the familial form of amyotrophic lateral sclerosis (ALS) — in non-human primates. In the study, the scientists used adeno-associated viral vectors to deliver different versions of an artificial microRNA targeting SOD1 that they had previously been shown to be effective in mouse models of ALS. There was no toxicity associated with treatment, and genetic analyses showed that the miRNAs reduced SOD1 protein expression in the motor neurons without triggering immune responses, they report.