PLoS ONE (Jan 2017)

KrillDB: A de novo transcriptome database for the Antarctic krill (Euphausia superba).

  • Gabriele Sales,
  • Bruce E Deagle,
  • Enrica Calura,
  • Paolo Martini,
  • Alberto Biscontin,
  • Cristiano De Pittà,
  • So Kawaguchi,
  • Chiara Romualdi,
  • Bettina Meyer,
  • Rodolfo Costa,
  • Simon Jarman

DOI
https://doi.org/10.1371/journal.pone.0171908
Journal volume & issue
Vol. 12, no. 2
p. e0171908

Abstract

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Antarctic krill (Euphausia superba) is a key species in the Southern Ocean with an estimated biomass between 100 and 500 million tonnes. Changes in krill population viability would have catastrophic effect on the Antarctic ecosystem. One looming threat due to elevated levels of anthropogenic atmospheric carbon dioxide (CO2) is ocean acidification (lowering of sea water pH by CO2 dissolving into the oceans). The genetics of Antarctic krill has long been of scientific interest for both for the analysis of population structure and analysis of functional genetics. However, the genetic resources available for the species are relatively modest. We have developed the most advanced genetic database on Euphausia superba, KrillDB, which includes comprehensive data sets of former and present transcriptome projects. In particular, we have built a de novo transcriptome assembly using more than 360 million Illumina sequence reads generated from larval krill including individuals subjected to different CO2 levels. The database gives access to: 1) the full list of assembled genes and transcripts; 2) their level of similarity to transcripts and proteins from other species; 3) the predicted protein domains contained within each transcript; 4) their predicted GO terms; 5) the level of expression of each transcript in the different larval stages and CO2 treatments. All references to external entities (sequences, domains, GO terms) are equipped with a link to the appropriate source database. Moreover, the software implements a full-text search engine that makes it possible to submit free-form queries. KrillDB represents the first large-scale attempt at classifying and annotating the full krill transcriptome. For this reason, we believe it will constitute a cornerstone of future approaches devoted to physiological and molecular study of this key species in the Southern Ocean food web.