1. Comprehensive <scp>single‐PCR 16S</scp> and <scp>18S rRNA</scp> community analysis validated with mock communities, and estimation of sequencing bias against <scp>18S</scp>
- Author
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Lyria Berdjeb, Jed A. Fuhrman, Yi-Chun Yeh, David M. Needham, Erin B. Fichot, and Jesse McNichol
- Subjects
0303 health sciences ,biology ,030306 microbiology ,High-Throughput Nucleotide Sequencing ,Prokaryote ,Sequence Analysis, DNA ,Computational biology ,Ribosomal RNA ,Amplicon ,biology.organism_classification ,16S ribosomal RNA ,Polymerase Chain Reaction ,Microbiology ,18S ribosomal RNA ,law.invention ,03 medical and health sciences ,Bias ,law ,RNA, Ribosomal, 16S ,RNA, Ribosomal, 18S ,Mantel test ,Relative species abundance ,Ecology, Evolution, Behavior and Systematics ,Polymerase chain reaction ,030304 developmental biology - Abstract
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.
- Published
- 2021
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