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Predicting reservoir hosts and arthropod vectors from evolutionary signatures in RNA virus genomes

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Science  02 Nov 2018:
Vol. 362, Issue 6414, pp. 577-580
DOI: 10.1126/science.aap9072

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Predicting hosts and vectors

During outbreaks of mysterious infections, events can rapidly become dangerous and confusing. A combination of increasing experience with outbreaks and genome-sequencing technology now means the pathogen can often be identified within days. But for some of the most frightening viral pathogens, the originating hosts and possible vectors often remain obscure. Babayan et al. took sequence data from more than 500 single-stranded RNA viruses (see the Perspective by Woolhouse) and used machine-learning algorithms to extract evolutionary signals imprinted in the virus sequence that offer information about its original hosts and if an arthropod vector, and what type, plays a part in the virus's natural ecology.

Science, this issue p. 577; see also p. 524