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Comprehensive single‐PCR 16S and 18S rRNA community analysis validated with mock communities, and estimation of sequencing bias against 18S
Author(s) -
Yeh YiChun,
McNichol Jesse,
Needham David M.,
Fichot Erin B.,
Berdjeb Lyria,
Fuhrman Jed A.
Publication year - 2021
Publication title -
environmental microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.954
H-Index - 188
eISSN - 1462-2920
pISSN - 1462-2912
DOI - 10.1111/1462-2920.15553
Subject(s) - biology , 18s ribosomal rna , 16s ribosomal rna , amplicon , ribosomal rna , genetics , primer (cosmetics) , eukaryote , computational biology , metagenomics , abundance (ecology) , relative species abundance , taxon , evolutionary biology , polymerase chain reaction , gene , ecology , genome , chemistry , organic chemistry
Summary Universal primers for SSU rRNA genes allow profiling of natural communities by simultaneously amplifying templates from Bacteria, Archaea, and Eukaryota in a single PCR reaction. Despite the potential to show relative abundance for all rRNA genes, universal primers are rarely used, due to various concerns including amplicon length variation and its effect on bioinformatic pipelines. We thus developed 16S and 18S rRNA mock communities and a bioinformatic pipeline to validate this approach. Using these mocks, we show that universal primers (515Y/926R) outperformed eukaryote‐specific V4 primers in observed versus expected abundance correlations (slope = 0.88 vs. 0.67–0.79), and mock community members with single mismatches to the primer were strongly underestimated (threefold to eightfold). Using field samples, both primers yielded similar 18S beta‐diversity patterns (Mantel test, p < 0.001) but differences in relative proportions of many rarer taxa. To test for length biases, we mixed mock communities (16S + 18S) before PCR and found a twofold underestimation of 18S sequences due to sequencing bias. Correcting for the twofold underestimation, we estimate that, in Southern California field samples (1.2–80 μm), there were averages of 35% 18S, 28% chloroplast 16S, and 37% prokaryote 16S rRNA genes. These data demonstrate the potential for universal primers to generate comprehensive microbiome profiles.