PAUVERT, Charlie; BUÉE, Marc; LAVAL, Valerie; EDEL-HERMANN, Véronique; FAUCHERY, Laure; GAUTIER, Angelique; LESUR, Isabelle; VALLANCE, Jessica; VACHER, Corinne

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PAUVERT, Charlie
Biodiversité, Gènes & Communautés [BioGeCo]

BUÉE, Marc
Interactions Arbres-Microorganismes [IAM]

LAVAL, Valerie
BIOlogie et GEstion des Risques en agriculture [BIOGER]

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Autre communication scientifique (congrès sans actes - poster - séminaire...)

Ce document a été publié dans

2018-12-04, Montpellier. 2018p. np

Résumé en anglais

Fungal communities associated with plants and soil influence plant fitness and ecosystem functioning. They are classically studied by metabarcoding approaches targeting the ribosomal internal transcribed spacer (ITS), but there is no consensus concerning the most appropriate bioinformatic pipeline 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 288 software and parameter combinations. The most sensitive pipelines, based on the USEARCH and VSEARCH clustering algorithms, detected almost all fungal strains but greatly overestimated the total number of strains. By contrast, pipelines 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.< Réduire

Mots clés en anglais

Bioinformatics

Environmental DNA

Fungi

Illumina MiSeq

Internal transcribed spacer (ITS)

Metabarcoding

Mock community

DADA2

USEARCH

VSEARCH

Origine

Importé de hal

Unités de recherche

BioGeCo (Biodiversité Gènes & Communautés) - UMR 1202