diagno-syst: a tool for accurate inventories in metabarcoding

Jean-Marc Frigerio (1, 2) , Frédéric Rimet (3) , Agnes Bouchez (3) , Emilie Chancerel (1) , Philippe Chaumeil (1, 2) , Franck Salin (1, 2) , Sylvie Thérond (4) , Maria Kahlert (5) , Alain Franc (1, 2)

1 BioGeCo - Biodiversité, Gènes & Communautés
2 PLEIADE - from patterns to models in computational biodiversity and biotechnology
3 CARRTEL - Centre Alpin de Recherche sur les Réseaux Trophiques et Ecosystèmes Limniques
4 IDRIS - Institut du développement et des ressources en informatique scientifique
5 SLU - Swedish University of Agricultural Sciences = Sveriges lantbruksuniversitet

Metabarcoding on amplicons is rapidly expanding as a method to produce molecular based inventories of microbial communities. Here, we work on freshwater diatoms, which are microalgae possibly inventoried both on a morphological and a molecular basis. We have developed an algorithm, in a program called diagno-syst, based a the notion of informative read, which carries out supervised clustering of reads by mapping them exactly one by one on all reads of a well curated and taxonomically annotated reference database. This program has been run on a HPC (and HTC) infrastructure to address computation load. We compare optical and molecular based inventories on 10 samples from Léman lake, and 30 from Swedish rivers. We track all possibilities of mismatches between both approaches, and compare the results with standard pipelines (with heuristics) like Mothur. We find that the comparison with optics is more accurate when using exact calculations, at the price of a heavier computation load. It is crucial when studying the long tail of biodiversity, which may be overestimated by pipelines or algorithms using heuristics instead (more false positive). This work supports the analysis that these methods will benefit from progress in, first, building an agreement between molecular based and morphological based systematics and, second, having as complete as possible publicly available reference databases.

Domaines: Bio-informatique [q-bio.QM]

Jean-Marc Frigerio, Frédéric Rimet, Agnes Bouchez, Emilie Chancerel, Philippe Chaumeil, et al.. diagno-syst: a tool for accurate inventories in metabarcoding. 2016. ⟨hal-01426764⟩