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A novel approach to wildlife transcriptomics provides evidence of disease‐mediated differential expression and changes to the microbiome of amphibian populations
- Campbell, Lewis J., Hammond, Stewart A., Price, Stephen J., Sharma, Manmohan D., Garner, Trenton W. J., Birol, Inanc, Helbing, Caren C., Wilfert, Lena, Griffiths, Amber G. F.
- Molecular ecology 2018 v.27 no.6 pp. 1413-1427
- Rana temporaria, Ranavirus, emerging diseases, filters, frogs, gene expression regulation, genes, immunity, messenger RNA, microbiome, non-coding RNA, protocols, sequence analysis, transcriptomics, viruses, wildlife, United Kingdom
- Ranaviruses are responsible for a lethal, emerging infectious disease in amphibians and threaten their populations throughout the world. Despite this, little is known about how amphibian populations respond to ranaviral infection. In the United Kingdom, ranaviruses impact the common frog (Rana temporaria). Extensive public engagement in the study of ranaviruses in the UK has led to the formation of a unique system of field sites containing frog populations of known ranaviral disease history. Within this unique natural field system, we used RNA sequencing (RNA‐Seq) to compare the gene expression profiles of R. temporaria populations with a history of ranaviral disease and those without. We have applied a RNA read‐filtering protocol that incorporates Bloom filters, previously used in clinical settings, to limit the potential for contamination that comes with the use of RNA‐Seq in nonlaboratory systems. We have identified a suite of 407 transcripts that are differentially expressed between populations of different ranaviral disease history. This suite contains genes with functions related to immunity, development, protein transport and olfactory reception among others. A large proportion of potential noncoding RNA transcripts present in our differentially expressed set provide first evidence of a possible role for long noncoding RNA (lncRNA) in amphibian response to viruses. Our read‐filtering approach also removed significantly more bacterial reads from libraries generated from positive disease history populations. Subsequent analysis revealed these bacterial read sets to represent distinct communities of bacterial species, which is suggestive of an interaction between ranavirus and the host microbiome in the wild.