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Development of a Dual-Index Sequencing Strategy and Curation Pipeline for Analyzing Amplicon Sequence Data on the MiSeq Illumina Sequencing Platform

机译:开发用于在MiSeq Illumina测序平台上分析扩增子序列数据的双索引测序策略和处理管线

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Rapid advances in sequencing technology have changed the experimental landscape of microbial ecology. In the last 10 years, the field has moved from sequencing hundreds of 16S rRNA gene fragments per study using clone libraries to the sequencing of millions of fragments per study using next-generation sequencing technologies from 454 and Illumina. As these technologies advance, it is critical to assess the strengths, weaknesses, and overall suitability of these platforms for the interrogation of microbial communities. Here, we present an improved method for sequencing variable regions within the 16S rRNA gene using Illumina's MiSeq platform, which is currently capable of producing paired 250-nucleotide reads. We evaluated three overlapping regions of the 16S rRNA gene that vary in length (i.e., V34, V4, and V45) by resequencing a mock community and natural samples from human feces, mouse feces, and soil. By titrating the concentration of 16S rRNA gene amplicons applied to the flow cell and using a quality score-based approach to correct discrepancies between reads used to construct contigs, we were able to reduce error rates by as much as two orders of magnitude. Finally, we reprocessed samples from a previous study to demonstrate that large numbers of samples could be multiplexed and sequenced in parallel with shotgun metagenomes. These analyses demonstrate that our approach can provide data that are at least as good as that generated by the 454 platform while providing considerably higher sequencing coverage for a fraction of the cost.
机译:测序技术的飞速发展改变了微生物生态学的实验格局。在过去的十年中,该领域已经从使用克隆文库对每个研究中的数百个16S rRNA基因片段进行测序转变为使用454和Illumina的下一代测序技术对每个研究中的数百万个片段进行测序。随着这些技术的发展,评估这些平台对微生物群落的审讯的优势,劣势和总体适用性至关重要。在这里,我们提出了一种使用Illumina的MiSeq平台对16S rRNA基因内的可变区进行测序的改进方法,该平台目前能够产生配对的250个核苷酸的读数。我们通过对模拟群落和人类粪便,小鼠粪便和土壤中的天然样品进行重新测序,评估了16S rRNA基因的三个重叠区域,这些区域的长度不同(即V34,V4和V45)。通过滴定应用于流通池的16S rRNA基因扩增子的浓度,并使用基于质量得分的方法校正用于构建重叠群的读段之间的差异,我们能够将错误率降低多达两个数量级。最后,我们对先前研究的样本进行了重新处理,以证明可以与shot弹枪基因组并行地对大量样本进行多重化和测序。这些分析表明,我们的方法可以提供至少与454平台生成的数据一样好的数据,同时只需花费一小部分成本即可提供更高的测序覆盖率。

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