Abstracts (first author)

Talk 

Discovery, distribution and evolutionary genomics of viruses naturally infecting Drosophila melanogaster

Author(s): Obbard DJ, Webster CL

Summary:

Drosophila melanogaster is an important model for innate immunity, and is arguably our primary model for antiviral resistance in arthropods. Several groups have used population-genetic and phylogenetic approaches to show that some antiviral immune genes in Drosophila (notably the antiviral RNAi pathway) display highly elevated rates of adaptive evolution. However, although this is consistent with a host-virus arms race, the evolutionary genetics of Drosophila viruses are almost unstudied - only a handful of viruses which naturally infect Drosophila melanogaster are known, and only Drosophila Sigma Virus (a Rhabdovirus) has been regularly isolated from wild populations.

In an attempt to understand the evolutionary genetics of Drosophila viruses, we have sequenced both RNAseq, and small-RNA, libraries from large pooled samples of wild-caught D. melanogaster. This has allowed us to identify several new viruses, including several RNA viruses (viruses with sequence similarity to Sacbrood Virus, Slow Bee Paralysis Virus, Chronic Bee paralysis virus, Acyrthosiphon Pisum Virus, Flaviviruses, and Cypoviruses) and a DNA virus (Nudivirus).

Following a geographic survey of D. melanogaster, we find that the previously known viruses of D. melanogaster (including DAV, Sigma and Nora) are widespread at low to intermediate prevalence. None of the viruses shows high rates of adaptive evolution, and in general (despite substantial synonymous divergence) protein sequences are very highly conserved. However, while this may indicate that these viruses are not engaged in ‘arms race'-like coevolution, we suspect that the short timescale of viral co-ancestry (tens to hundreds, rather than thousands, of years) makes this process extremely difficult to detect. This is in sharp contrast to viral evolution in response to vertebrate adaptive immunity, which adapts plastically on the same timescale as viral evolution.


Video


Abstracts (coauthor)

Summary:

RNAi is a major invertebrate defensive pathway, in which small RNAs are derived from a target RNA and guide an Argonaute-family protein to cleave and subsequently degrade the target. This mechanism defends against both viruses and transposable elements. These contrasting and potentially conflicting selective pressures may have driven the rapid adaptive evolution documented in Argonaute-family genes, which places them among the top 3% of the fastest evolving D. melanogaster genes. It has been hypothesised that this rapid evolution is driven by an arms race between viral suppressors of RNAi (VSRs) and the RNAi mechanism. In Drosophila, Argonaute2 (Ago2) is the effector protein in siRNA-mediated antiviral and anti-TE defence. The majority of insects possess a single Ago2; however, duplication has occurred in several Dipteran taxa including Phoridae, Glossina and Drosophila. Ago2 has undergone numerous recent duplications in the obscura group of Drosophila, producing two paralogues in D. subobscura, three in D. obscura and five in D. pseudoobscura. We present population genetic data for the Ago2 paralogues in D. subobscura, D. obscura and D. pseudoobscura. We find that most paralogues have remarkably low genetic diversity, possibly resulting from recent selective sweeps. We also find strong evidence for codon usage bias in the earliest-diverging paralogue. Additionally, we present expression data in different tissues and in response to viral exposure. These results suggest that the Ago2 paralogues in the obscura group have each evolved under different selection pressures, possibly imposed by functional specialization in an evolutionary arms race.

Contacts

Chairman: Octávio S. Paulo
Tel: 00 351 217500614 direct
Tel: 00 351 217500000 ext22359
Fax: 00 351 217500028
email: mail@eseb2013.com

Address

XIV Congress of the European Society for Evolutionary Biology

Organization Team
Department of Animal Biology (DBA)
Faculty of Sciences of the University of Lisbon
P-1749-016 Lisbon
Portugal

Website

Computational Biology & Population Genomics Group 
Close