Primer and platform effects on 16S rRNA tag sequencing

Tremblay, Julien; Singh, Kanwar; Fern, Alison; Kirton, Edward S.; He, Shaomei; Woyke, Tanja; Lee, Janey; Chen, Feng; Dangl, Jeffery L.; Tringe, Susannah G.

doi:10.3389/fmicb.2015.00771

Title: Primer and platform effects on 16S rRNA tag sequencing

Journal Article · Tue Aug 04 00:00:00 EDT 2015 · Frontiers in Microbiology

DOI:https://doi.org/10.3389/fmicb.2015.00771· OSTI ID:1512103

Tremblay, Julien ^[1]; Singh, Kanwar ^[2]; Fern, Alison ^[2]; Kirton, Edward S. ^[2]; He, Shaomei ^[2]; Woyke, Tanja ^[2]; Lee, Janey ^[2]; Chen, Feng ^[3]; Dangl, Jeffery L. ^[4]; Tringe, Susannah G. ^[2]

USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); National Research Council Canada, Montreal, QC (Canada)
USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States)
Illumina, Inc., San Francisco, CA (United States)
Univ. of North Carolina, Chapel Hill, NC (United States). Dept. of Biology and Howard Hughes Medical Inst., Curriculum in Genetics and Molecular Biology, Dept. of Microbiology and Immunology

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. In conclusion, beta diversity metrics are surprisingly robust to both primer and sequencing platform biases.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC02-05CH11231; KP/CH57/1; IOS-0958245

OSTI ID:: 1512103

Alternate ID(s):: OSTI ID: 1256969

Journal Information:: Frontiers in Microbiology, Vol. 6, Issue AUG; ISSN 1664-302X

Publisher:: Frontiers Research FoundationCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 207 works

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59 BASIC BIOLOGICAL SCIENCES
16S rRNA gene sequencing
microbial population and community ecology
high throughput sequencing
microbial diversity
community assembly
amplification
sequencing error