比较单一生物16S rRNA基因测序数据的国际实验室间研究:超越共识序列比较

Q1 Biochemistry, Genetics and Molecular Biology Biomolecular Detection and Quantification Pub Date : 2015-03-01 DOI:10.1016/j.bdq.2015.01.004
Nathan D. Olson , Steven P. Lund , Justin M. Zook , Fabiola Rojas-Cornejo , Brian Beck , Carole Foy , Jim Huggett , Alexandra S. Whale , Zhiwei Sui , Anna Baoutina , Michael Dobeson , Lina Partis , Jayne B. Morrow
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引用次数: 5

摘要

本研究提出了一项实验室间测序研究的结果,我们开发了一种新的高分辨率方法,用于比较来自不同测序平台的多拷贝、同源基因的数据。PCR扩增和16S核糖体RNA基因(16S rRNA)测序的结合使细菌学发生了革命性的变化,使快速鉴定成为可能,通常不需要培养。为了评估实验室间16S rRNA测序的差异,6个实验室对大肠杆菌O157:H7菌株EDL933和单核细胞增生李斯特菌血清型4b菌株ncctc11994的16S rRNA编码基因进行了测序。参与者使用实验室提供的测序方法和方案:Sanger测序、Roche 454 pyrosequencing®或Ion Torrent PGM®。测序数据在三个层面上进行评估:(1)生物保守位置的身份,(2)具有鉴定变异的16S rRNA基因拷贝的比例,以及(3)一组16S rRNA基因拷贝中变异组合的收集。每种测序方法都鉴定出相同的一组生物保守位置。使用贝叶斯和最大似然统计的分析方法被开发来估计变异拷贝比,它描述了每个确定的生物可变位置的核苷酸比例,以及16S rRNA基因拷贝中可能存在的变异组合集。我们的研究结果表明,在生物可变位置估计的变异拷贝比仅可用于高通量测序方法。此外,可能的变异组合集只有在增加测序深度和更长的读取长度时才可重复。我们还展示了在比较多个实验室使用多种测序技术生成的多拷贝基因序列数据时评估变量位置的新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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International interlaboratory study comparing single organism 16S rRNA gene sequencing data: Beyond consensus sequence comparisons

This study presents the results from an interlaboratory sequencing study for which we developed a novel high-resolution method for comparing data from different sequencing platforms for a multi-copy, paralogous gene. The combination of PCR amplification and 16S ribosomal RNA gene (16S rRNA) sequencing has revolutionized bacteriology by enabling rapid identification, frequently without the need for culture. To assess variability between laboratories in sequencing 16S rRNA, six laboratories sequenced the gene encoding the 16S rRNA from Escherichia coli O157:H7 strain EDL933 and Listeria monocytogenes serovar 4b strain NCTC11994. Participants performed sequencing methods and protocols available in their laboratories: Sanger sequencing, Roche 454 pyrosequencing®, or Ion Torrent PGM®. The sequencing data were evaluated on three levels: (1) identity of biologically conserved position, (2) ratio of 16S rRNA gene copies featuring identified variants, and (3) the collection of variant combinations in a set of 16S rRNA gene copies. The same set of biologically conserved positions was identified for each sequencing method. Analytical methods using Bayesian and maximum likelihood statistics were developed to estimate variant copy ratios, which describe the ratio of nucleotides at each identified biologically variable position, as well as the likely set of variant combinations present in 16S rRNA gene copies. Our results indicate that estimated variant copy ratios at biologically variable positions were only reproducible for high throughput sequencing methods. Furthermore, the likely variant combination set was only reproducible with increased sequencing depth and longer read lengths. We also demonstrate novel methods for evaluating variable positions when comparing multi-copy gene sequence data from multiple laboratories generated using multiple sequencing technologies.

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来源期刊
Biomolecular Detection and Quantification
Biomolecular Detection and Quantification Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
14.20
自引率
0.00%
发文量
0
审稿时长
8 weeks
期刊最新文献
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