Primer and platform effects on 16S rRNA tag sequencing

被引:372
|
作者
Tremblay, Julien [1 ,2 ]
Singh, Kanwar [1 ]
Fern, Alison [1 ]
Kirton, Edward S. [1 ]
He, Shaomei [1 ]
Woyke, Tanja [1 ]
Lee, Janey [1 ]
Chen, Feng [3 ]
Dangl, Jeffery L. [4 ,5 ]
Tringe, Susannah G. [1 ]
机构
[1] Dept Energy Joint Genome Inst, Walnut Creek, CA 94598 USA
[2] Natl Res Council Canada, Montreal, PQ, Canada
[3] Illumina Inc, San Francisco, CA USA
[4] Univ N Carolina, Dept Biol, Chapel Hill, NC USA
[5] Univ N Carolina, Dept Microbiol & Immunol, Howard Hughes Med Inst, Curriculum Genet & Mol Biol,Carolina Ctr Genome S, Chapel Hill, NC USA
关键词
16S rRNA gene sequencing; microbial population and community ecology; high throughput sequencing; microbial diversity; community assembly; amplification; sequencing error; RHIZOSPHERE MICROBIOME; GENE DATABASE; DIVERSITY; BIAS; ILLUMINA; HETERODUPLEXES; AMPLIFICATION; SENSITIVITY; DOMAIN;
D O I
10.3389/fmicb.2015.00771
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
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.
引用
收藏
页数:15
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