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使用Illumina MiSeq平台减少16S rRNA序列错误识别的改进流程。

Improved pipeline for reducing erroneous identification by 16S rRNA sequences using the Illumina MiSeq platform.

作者信息

Jeon Yoon-Seong, Park Sang-Cheol, Lim Jeongmin, Chun Jongsik, Kim Bong-Soo

机构信息

ChunLab, Inc., Seoul National University, Seoul, 151-742, Republic of Korea.

出版信息

J Microbiol. 2015 Jan;53(1):60-9. doi: 10.1007/s12275-015-4601-y. Epub 2015 Jan 4.

Abstract

The cost of DNA sequencing has decreased due to advancements in Next Generation Sequencing. The number of sequences obtained from the Illumina platform is large, use of this platform can reduce costs more than the 454 pyrosequencer. However, the Illumina platform has other challenges, including bioinformatics analysis of large numbers of sequences and the need to reduce erroneous nucleotides generated at the 3'-ends of the sequences. These erroneous sequences can lead to errors in analysis of microbial communities. Therefore, correction of these erroneous sequences is necessary for accurate taxonomic identification. Several studies that have used the Illumina platform to perform metagenomic analyses proposed curating pipelines to increase accuracy. In this study, we evaluated the likelihood of obtaining an erroneous microbial composition using the MiSeq 250 bp paired sequence platform and improved the pipeline to reduce erroneous identifications. We compared different sequencing conditions by varying the percentage of control phiX added, the concentration of the sequencing library, and the 16S rRNA gene target region using a mock community sample composed of known sequences. Our recommended method corrected erroneous nucleotides and improved identification accuracy. Overall, 99.5% of the total reads shared 95% similarity with the corresponding template sequences and 93.6% of the total reads shared over 97% similarity. This indicated that the MiSeq platform can be used to analyze microbial communities at the genus level with high accuracy. The improved analysis method recommended in this study can be applied to amplicon studies in various environments using high-throughput reads generated on the MiSeq platform.

摘要

由于下一代测序技术的进步,DNA测序成本有所降低。从Illumina平台获得的序列数量很多,使用该平台比454焦磷酸测序仪能更多地降低成本。然而,Illumina平台还存在其他挑战,包括对大量序列进行生物信息学分析以及减少序列3'端产生的错误核苷酸的需求。这些错误序列可能导致微生物群落分析出现误差。因此,为了进行准确的分类鉴定,校正这些错误序列是必要的。几项使用Illumina平台进行宏基因组分析的研究提出了优化流程以提高准确性。在本研究中,我们评估了使用MiSeq 250 bp双端序列平台获得错误微生物组成的可能性,并改进了流程以减少错误鉴定。我们使用由已知序列组成的模拟群落样本,通过改变添加的对照phiX的百分比、测序文库的浓度以及16S rRNA基因目标区域,比较了不同的测序条件。我们推荐的方法校正了错误核苷酸并提高了鉴定准确性。总体而言,99.5%的总读数与相应模板序列具有95%的相似性,93.6%的总读数具有超过97%的相似性。这表明MiSeq平台可用于高精度地分析属水平的微生物群落。本研究推荐的改进分析方法可应用于使用MiSeq平台产生的高通量读数对各种环境中的扩增子进行研究。

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