Genomic analysis of uncultured marine viral communities

  1. Mya Breitbart*,
  2. Peter Salamon,
  3. Bjarne Andresen,,
  4. Joseph M. Mahaffy,
  5. Anca M. Segall*,
  6. David Mead§,
  7. Farooq Azam, and
  8. Forest Rohwer*,
  1. *Department of Biology, San Diego State University, San Diego, CA 92182-4614; Department of Mathematical Sciences, San Diego State University, San Diego, CA 92182-7720; Ørsted Laboratory, University of Copenhagen, Universitetsparken 5, DK-2100 Copenhagen Ø, Denmark;§ Lucigen, Middleton, WI 53562; and Marine Biology Division, Scripps Institution of Oceanography, La Jolla, CA 92093
  1. Communicated by Allan Campbell, Stanford University, Stanford, CA (received for review February 22, 2002)

Abstract

Viruses are the most common biological entities in the oceans by an order of magnitude. However, very little is known about their diversity. Here we report a genomic analysis of two uncultured marine viral communities. Over 65% of the sequences were not significantly similar to previously reported sequences, suggesting that much of the diversity is previously uncharacterized. The most common significant hits among the known sequences were to viruses. The viral hits included sequences from all of the major families of dsDNA tailed phages, as well as some algal viruses. Several independent mathematical models based on the observed number of contigs predicted that the most abundant viral genome comprised 2–3% of the total population in both communities, which was estimated to contain between 374 and 7,114 viral types. Overall, diversity of the viral communities was extremely high. The results also showed that it would be possible to sequence the entire genome of an uncultured marine viral community.

Footnotes

  • To whom correspondence should be addressed. E-mail: forest{at}sunstroke.sdsu.edu.

  • Data deposition: The sequences reported in this paper have been deposited in the GenBank database (accession nos. and ).

  • Abbreviations:
    1. SP, Scripps Pier

    2. MB, Mission Bay

    3. LASL, linker-amplified shotgun library

    4. MM%, minimal mismatch percentage

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