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Front Microbiol. 2015 Aug 4;6:771. doi: 10.3389/fmicb.2015.00771. eCollection 2015.

Primer and platform effects on 16S rRNA tag sequencing.

Author information

1
Department of Energy Joint Genome Institute Walnut Creek, CA, USA ; National Research Council Canada Montreal, QC, Canada.
2
Department of Energy Joint Genome Institute Walnut Creek, CA, USA.
3
Illumina, Inc. San Francisco, CA, USA.
4
Department of Biology and Howard Hughes Medical Institute, Curriculum in Genetics and Molecular Biology, Department of Microbiology and Immunology, Carolina Center for Genome Sciences, University of North Carolina Chapel Hill, NC, USA.

Abstract

Sequencing of 16S rRNA gene tags is a popular method for profiling and comparing microbial communities. The protocols and methods used, however, vary considerably with regard to amplification primers, sequencing primers, sequencing technologies; as well as quality filtering and clustering. How results are affected by these choices, and whether data produced with different protocols can be meaningfully compared, is often unknown. Here we compare results obtained using three different amplification primer sets (targeting V4, V6-V8, and V7-V8) and two sequencing technologies (454 pyrosequencing and Illumina MiSeq) using DNA from a mock community containing a known number of species as well as complex environmental samples whose PCR-independent profiles were estimated using shotgun sequencing. We find that paired-end MiSeq reads produce higher quality data and enabled the use of more aggressive quality control parameters over 454, resulting in a higher retention rate of high quality reads for downstream data analysis. While primer choice considerably influences quantitative abundance estimations, sequencing platform has relatively minor effects when matched primers are used. Beta diversity metrics are surprisingly robust to both primer and sequencing platform biases.

KEYWORDS:

16S rRNA gene sequencing; amplification; community assembly; high throughput sequencing; microbial diversity; microbial population and community ecology; sequencing error

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