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Bioinformatics matters: The accuracy of plant and soil fungal community data is highly dependent on the metabarcoding pipeline

hal.structure.identifierBiodiversité, Gènes & Communautés [BioGeCo]
dc.contributor.authorPAUVERT, Charlie
hal.structure.identifierInteractions Arbres-Microorganismes [IAM]
dc.contributor.authorBUÉE, Marc
hal.structure.identifierBIOlogie et GEstion des Risques en agriculture [BIOGER]
hal.structure.identifierUniversité Paris Saclay (COmUE)
dc.contributor.authorLAVAL, Valerie
hal.structure.identifierAgroécologie [Dijon]
dc.contributor.authorEDEL-HERMANN, Véronique
hal.structure.identifierInteractions Arbres-Microorganismes [IAM]
dc.contributor.authorFAUCHERY, Laure
hal.structure.identifierBIOlogie et GEstion des Risques en agriculture [BIOGER]
hal.structure.identifierUniversité Paris Saclay (COmUE)
dc.contributor.authorGAUTIER, Angelique
hal.structure.identifierHelixVenture
hal.structure.identifierUniversité de Bordeaux [UB]
dc.contributor.authorLESUR, Isabelle
hal.structure.identifierSanté et agroécologie du vignoble [UMR SAVE]
dc.contributor.authorVALLANCE, Jessica
hal.structure.identifierBiodiversité, Gènes & Communautés [BioGeCo]
dc.contributor.authorVACHER, Corinne
dc.date.issued2019
dc.identifier.issn1754-5048
dc.description.abstractEnFungal communities associated with plants and soil influence plant fitness and ecosystem functioning. They are frequently studied by metabarcoding approaches targeting the ribosomal internal transcribed spacer (ITS), but there is no consensus concerning the most appropriate bioinformatic approach for the analysis of these data. We sequenced an artificial fungal community composed of 189 strains covering a wide range of Ascomycota and Basidiomycota, to compare the performance of 360 software and parameter combinations. The most sensitive approaches, based on the USEARCH and VSEARCH clustering algorithms, detected almost all fungal strains but greatly overestimated the total number of strains. By contrast, approaches using DADA2 to detect amplicon sequence variants were the most effective for recovering the richness and composition of the fungal community. Our results suggest that analyzing single forward (R1) sequences with DADA2 and no filter other than the removal of low-quality and chimeric sequences is a good option for fungal community characterization. (C) 2019 Elsevier Ltd and British Mycological Society. All rights reserved.
dc.language.isoen
dc.publisherElsevier
dc.rights.urihttp://creativecommons.org/licenses/by-nc/
dc.subjectBioinformatics
dc.subjectEnvironmental DNA
dc.subjectIllumina MiSeq
dc.subject.enFungi
dc.subject.enInternal transcribed spacer (ITS)
dc.subject.enMetabarcoding
dc.title.enBioinformatics matters: The accuracy of plant and soil fungal community data is highly dependent on the metabarcoding pipeline
dc.typeArticle de revue
dc.identifier.doi10.1016/j.funeco.2019.03.005
dc.subject.halSciences du Vivant [q-bio]
dc.subject.halSciences de l'environnement
dc.subject.halSciences du Vivant [q-bio]/Biologie végétale
bordeaux.journalFungal Ecology
bordeaux.page23 - 33
bordeaux.volume41
bordeaux.peerReviewedoui
hal.identifierhal-02627344
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02627344v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Fungal%20Ecology&rft.date=2019&rft.volume=41&rft.spage=23%20-%2033&rft.epage=23%20-%2033&rft.eissn=1754-5048&rft.issn=1754-5048&rft.au=PAUVERT,%20Charlie&BU%C3%89E,%20Marc&LAVAL,%20Valerie&EDEL-HERMANN,%20V%C3%A9ronique&FAUCHERY,%20Laure&rft.genre=article


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