The evolution, diversity and host associations of rhabdoviruses

Darren Obbard, Ben Longdon, Gemma G R Murray, William J Palmer, Jonathan P. Day, Darren J Parker, John J. Welch, Francis Jiggins

Research output: Contribution to journalArticlepeer-review


Metagenomic studies are leading to the discovery of a hidden diversity of RNA viruses. These new viruses are poorly characterized and new approaches are needed predict the host species these viruses pose a risk to. The rhabdoviruses are a diverse family of RNA viruses that includes important pathogens of humans, animals, and plants. We have discovered thirty-two new rhabdoviruses through a combination of our own RNA sequencing of insects and searching public sequence databases. Combining these with previously known sequences we reconstructed the phylogeny of 195 rhabdovirus sequences, and produced the most in depth analysis of the family to date. In most cases we know nothing about the biology of the viruses beyond the host they were identified from, but our dataset provides a powerful phylogenetic approach to predict which are vector-borne viruses and which are specific to vertebrates or arthropods. By reconstructing ancestral and present host states we found that switches between major groups of hosts have occurred rarely during rhabdovirus evolution. This allowed us to propose seventy-six new likely vector-borne vertebrate viruses among viruses identified from vertebrates or biting insects. Based on currently available data, our analysis suggests it is likely there was a single origin of the known plant viruses and arthropod-borne vertebrate viruses, while vertebrate- and arthropod-specific viruses arose at least twice. There are also few transitions between aquatic and terrestrial ecosystems. Viruses also cluster together at a finer scale, with closely related viruses tending to be found in closely related hosts. Our data therefore suggest that throughout their evolution, rhabdoviruses have occasionally jumped between distantly related host species before spreading through related hosts in the same environment. This approach offers a way to predict the most probable biology and key traits of newly discovered viruses.
Original languageEnglish
Article numbervev014
JournalVirus Evolution
Issue number1
Early online date1 Jan 2015
Publication statusE-pub ahead of print - 1 Jan 2015

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