Hide metadata

dc.date.accessioned2015-02-25T16:01:03Z
dc.date.available2015-02-25T16:01:03Z
dc.date.created2013-12-19T12:45:46Z
dc.date.issued2013
dc.identifier.citationEgge, Elianne Sirnæs Bittner, Lucie Andersen, Tom Audic, Stéphane de Vargas, Colomban Edvardsen, Bente . 454 Pyrosequencing to Describe Microbial Eukaryotic Community Composition, Diversity and Relative Abundance: A Test for Marine Haptophytes. PLoS ONE. 2013, 8(9)
dc.identifier.urihttp://hdl.handle.net/10852/42566
dc.description.abstractNext generation sequencing of ribosomal DNA is increasingly used to assess the diversity and structure of microbial communities. Here we test the ability of 454 pyrosequencing to detect the number of species present, and assess the relative abundance in terms of cell numbers and biomass of protists in the phylum Haptophyta. We used a mock community consisting of equal number of cells of 11 haptophyte species and compared targeting DNA and RNA/cDNA, and two different V4 SSU rDNA haptophyte-biased primer pairs. Further, we tested four different bioinformatic filtering methods to reduce errors in the resulting sequence dataset. With sequencing depth of 11000–20000 reads and targeting cDNA with Haptophyta specific primers Hap454 we detected all 11 species. A rarefaction analysis of expected number of species recovered as a function of sampling depth suggested that minimum 1400 reads were required here to recover all species in the mock community. Relative read abundance did not correlate to relative cell numbers. Although the species represented with the largest biomass was also proportionally most abundant among the reads, there was generally a weak correlation between proportional read abundance and proportional biomass of the different species, both with DNA and cDNA as template. The 454 sequencing generated considerable spurious diversity, and more with cDNA than DNA as template. With initial filtering based only on match with barcode and primer we observed 100-fold more operational taxonomic units (OTUs) at 99% similarity than the number of species present in the mock community. Filtering based on quality scores, or denoising with PyroNoise resulted in ten times more OTU99% than the number of species. Denoising with AmpliconNoise reduced the number of OTU99% to match the number of species present in the mock community. Based on our analyses, we propose a strategy to more accurately depict haptophyte diversity using 454 pyrosequencing. © 2013 Egge et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_US
dc.languageEN
dc.language.isoenen_US
dc.publisherPublic Library of Science (PLoS)
dc.title454 Pyrosequencing to Describe Microbial Eukaryotic Community Composition, Diversity and Relative Abundance: A Test for Marine Haptophytesen_US
dc.typeJournal articleen_US
dc.creator.authorEgge, Elianne Sirnæs
dc.creator.authorBittner, Lucie
dc.creator.authorAndersen, Tom
dc.creator.authorAudic, Stéphane
dc.creator.authorde Vargas, Colomban
dc.creator.authorEdvardsen, Bente
cristin.unitcode185,15,21,0
cristin.unitnameInstitutt for biovitenskap (tidl. BIO)
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.cristin1079273
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=PLoS ONE&rft.volume=8&rft.spage=&rft.date=2013
dc.identifier.jtitlePLoS ONE
dc.identifier.volume8
dc.identifier.issue9
dc.identifier.pagecount15
dc.identifier.doihttp://dx.doi.org/10.1371/journal.pone.0074371
dc.identifier.urnURN:NBN:no-46959
dc.type.documentTidsskriftartikkelen_US
dc.type.peerreviewedPeer reviewed
dc.source.issn1932-6203
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/42566/2/journal.pone.0074371.pdf
dc.type.versionPublishedVersion
cristin.articleide74371


Files in this item

Appears in the following Collection

Hide metadata