ena-STUDY-STANFORD UNIVERSITY-09-03-2020-18:55:13:860-1156
PPIT: an R package for inferring microbial taxonomy from nifH sequences
Amplicon sequencing of metabolic marker genes provides targeted snapshots of community metabolic potential. However, inferring microbial taxonomy from metabolic marker gene sequences remains a challenge, particularly for the nitrogen fixation marker gene nitrogenase reductase (nifH). Here, we present Phylogenetic Placement for Inferring Taxonomy (PPIT), an R package that infers microbial taxonomy from nifH amplicons using both phylogenetic placement and sequence identity approaches. After users place query sequences on the reference nifH gene tree that PPIT provides (n = 6093 full-length nifH sequences), PPIT searches the phylogenetic neighborhood of each query sequence and attempts to infer microbial taxonomy. An inference is drawn only if references in the phylogenetic neighborhood are: (1) taxonomically consistent and (2) share sufficient pairwise identity with the query, thereby avoiding erroneous inferences due to known horizontal gene transfer events. We find that PPIT returns a higher proportion of correct taxonomic inferences than BLAST-based approaches at the cost of fewer total inferences. We demonstrate PPIT on deep-sea sediment and find that Deltaproteobacteria compose most of the potential diazotroph assemblage. We additionally discuss how users can apply PPIT to the analysis of other marker genes.
Amplicon sequencing of metabolic marker genes provides targeted snapshots of community metabolic potential. However, inferring microbial taxonomy from metabolic marker gene sequences remains a challenge, particularly for the nitrogen fixation marker gene nitrogenase reductase (nifH). Here, we present Phylogenetic Placement for Inferring Taxonomy (PPIT), an R package that infers microbial taxonomy from nifH amplicons using both phylogenetic placement and sequence identity approaches. After users place query sequences on the reference nifH gene tree that PPIT provides (n = 6093 full-length nifH sequences), PPIT searches the phylogenetic neighborhood of each query sequence and attempts to infer microbial taxonomy. An inference is drawn only if references in the phylogenetic neighborhood are: (1) taxonomically consistent and (2) share sufficient pairwise identity with the query, thereby avoiding erroneous inferences due to known horizontal gene transfer events. We find that PPIT returns a higher proportion of correct taxonomic inferences than BLAST-based approaches at the cost of fewer total inferences. We demonstrate PPIT on deep-sea sediment and find that Deltaproteobacteria compose most of the potential diazotroph assemblage. We additionally discuss how users can apply PPIT to the analysis of other marker genes.