BIOCOM-PIPE: a new user-friendly metabarcoding pipeline for the characterization of microbial diversity from 16S, 18S and 23S rRNA gene amplicons

BMC Bioinformatics

Samuel Mondy¹  Mélanie Lelièvre¹  Yassin El Djoudi²  Lionel Ranjard²  Nicolas Chemidlin Prévost-Bouré²  Battle Karimi²  Samuel Dequiedt²  Aurélien Cottin²  Sébastien Terrat²  Christophe Djemiel²  Pierre-Alain Maron²  Thibault Girier²  Patrick Wincker³ 

[1] Agroécologie - Plateforme GenoSol;Agroécologie, AgroSup Dijon, INRAE, Univ. Bourgogne, Univ. Bourgogne Franche-Comté;CEA/Institut de Biologie François Jacob/Génoscope;

关键词: Ecology;    Metabarcoding;    Bacterial;    Archaeal;    Fungal;    Photosynthetic microeukaryotes;   

DOI  :  10.1186/s12859-020-03829-3

来源: DOAJ

【 摘 要 】

Abstract Background The ability to compare samples or studies easily using metabarcoding so as to better interpret microbial ecology results is an upcoming challenge. A growing number of metabarcoding pipelines are available, each with its own benefits and limitations. However, very few have been developed to offer the opportunity to characterize various microbial communities (e.g., archaea, bacteria, fungi, photosynthetic microeukaryotes) with the same tool. Results BIOCOM-PIPE is a flexible and independent suite of tools for processing data from high-throughput sequencing technologies, Roche 454 and Illumina platforms, and focused on the diversity of archaeal, bacterial, fungal, and photosynthetic microeukaryote amplicons. Various original methods were implemented in BIOCOM-PIPE to (1) remove chimeras based on read abundance, (2) align sequences with structure-based alignments of RNA homologs using covariance models, and (3) a post-clustering tool (ReClustOR) to improve OTUs consistency based on a reference OTU database. The comparison with two other pipelines (FROGS and mothur) and Amplicon Sequence Variant definition highlighted that BIOCOM-PIPE was better at discriminating land use groups. Conclusions The BIOCOM-PIPE pipeline makes it possible to analyze 16S, 18S and 23S rRNA genes in the same packaged tool. The new post-clustering approach defines a biological database from previously analyzed samples and performs post-clustering of reads with this reference database by using open-reference clustering. This makes it easier to compare projects from various sequencing runs, and increased the congruence among results. For all users, the pipeline was developed to allow for adding or modifying the components, the databases and the bioinformatics tools easily, giving high modularity for each analysis.

【 授权许可】

Unknown