Primer and platform effects on 16S rRNA tag sequencing

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 resul...

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Main Authors:	Tremblay, Julien, Singh, Kanwar, Fern, Alison, Kirton, Edward S., He, Shaomei, Woyke, Tanja, Lee, Janey, Chen, Feng, Dangl, Jeffery L., Tringe, Susannah G.
Format:	Online
Language:	English
Published:	Frontiers Media S.A. 2015
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4523815/

id	pubmed-4523815
recordtype	oai_dc
spelling	pubmed-45238152015-08-21 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. Microbiology 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. Frontiers Media S.A. 2015-08-04 /pmc/articles/PMC4523815/ /pubmed/26300854 http://dx.doi.org/10.3389/fmicb.2015.00771 Text en Copyright © 2015 Tremblay, Singh, Fern, Kirton, He, Woyke, Lee, Chen, Dangl and Tringe. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Tremblay, Julien Singh, Kanwar Fern, Alison Kirton, Edward S. He, Shaomei Woyke, Tanja Lee, Janey Chen, Feng Dangl, Jeffery L. Tringe, Susannah G.
spellingShingle	Tremblay, Julien Singh, Kanwar Fern, Alison Kirton, Edward S. He, Shaomei Woyke, Tanja Lee, Janey Chen, Feng Dangl, Jeffery L. Tringe, Susannah G. Primer and platform effects on 16S rRNA tag sequencing
author_facet	Tremblay, Julien Singh, Kanwar Fern, Alison Kirton, Edward S. He, Shaomei Woyke, Tanja Lee, Janey Chen, Feng Dangl, Jeffery L. Tringe, Susannah G.
author_sort	Tremblay, Julien
title	Primer and platform effects on 16S rRNA tag sequencing
title_short	Primer and platform effects on 16S rRNA tag sequencing
title_full	Primer and platform effects on 16S rRNA tag sequencing
title_fullStr	Primer and platform effects on 16S rRNA tag sequencing
title_full_unstemmed	Primer and platform effects on 16S rRNA tag sequencing
title_sort	primer and platform effects on 16s rrna tag sequencing
description	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.
publisher	Frontiers Media S.A.
publishDate	2015
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4523815/
_version_	1613255427385982976

Primer and platform effects on 16S rRNA tag sequencing

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