Customization of a DADA2-based pipeline for fungal internal transcribed spacer 1 (ITS1) amplicon data sets.

ABSTRACT: Identification and analysis of fungal communities commonly rely on internal transcribed spacer-based (ITS-based) amplicon sequencing. There is no gold standard used to infer and classify fungal constituents since methodologies have been adapted from analyses of bacterial communities. To achieve high-resolution inference of fungal constituents, we customized a DADA2-based pipeline using a mix of 11 medically relevant fungi. While DADA2 allowed the discrimination of ITS1 sequences differing by single nucleotides, quality filtering, sequencing bias, and database selection were identified as key variables determining the accuracy of sample inference. Due to species-specific differences in sequencing quality, default filtering settings removed most reads that originated from Aspergillus species

SUBMITTER: Rolling T 

PROVIDER: S-EPMC8765055 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature