Comparison of microbial diversity determined with the same variable tag sequence extracted from two different PCR amplicons.
Comparison of microbial diversity determined with the same variable tag sequence extracted from two different PCR amplicons.
复制标题
使用从两个不同 PCR 扩增子中提取的相同可变标签序列确定的微生物多样性的比较
DOI：
10.1186/1471-2180-13-208
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发表时间：
2013-09-14
期刊：
影响因子：
4.2
通讯作者：
Zhou HW
中科院分区：
文献类型：
--
作者：
He Y;Zhou BJ;Deng GH;Jiang XT;Zhang H;Zhou HW
背景16 S rRNA基因可变区的深度测序已成为研究微生物生态学的主要工具。随着测序数据集的积累，用不同的可变16 S rRNA基因靶标和不同的测序方法获得的序列的荟萃分析已经成为一个有趣的前景，仍有待实验评估。结果我们使用V4 F-V6 R和V6 F-V6 R引物组扩增了一组粪便样品，从两组Illumina测序数据中切除了相同的V6片段，并从α多样性、β多样性和群落结构三个方面对所得数据进行了比较。主成分分析（PCA）比较不同数据集的微生物群落结构，包括那些模拟测序错误，是非常可靠的。Procrustes分析显示，不同数据集之间的丰度加权和二进制Jaccard距离（P < 0.05）的高度一致性，单个数据集的荟萃分析得出了类似的结论。香农多样性指数也是一致的，不同数据集和不同数据集的元分析获得的值具有可比性。相比之下，丰富度估计（OTU和Chao）差异显着，丰富度估计的荟萃分析也有偏差。两个数据集的社区结构明显不同，导致显着变化的生物标志物所确定的LEfSe statistical tool.ConclusionsOur结果表明，β多样性分析和香农的多样性是相对可靠的荟萃分析，而社区结构和生物标志物是不太一致的。这些结果应该是有用的未来荟萃分析微生物从不同的数据来源。
BackgroundDeep sequencing of the variable region of 16S rRNA genes has become the predominant tool for studying microbial ecology. As sequencing datasets have accumulated, meta-analysis of sequences obtained with different variable 16S rRNA gene targets and by different sequencing methods has become an intriguing prospect that remains to be evaluated experimentally.ResultsWe amplified a group of fecal samples using both V4F-V6R and V6F-V6R primer sets, excised the same V6 fragment from the two sets of Illumina sequencing data, and compared the resulting data in terms of the α-diversity, β-diversity, and community structure. Principal component analysis (PCA) comparing the microbial community structures of different datasets, including those with simulated sequencing errors, was very reliable. Procrustes analysis showed a high degree of concordance between the different datasets for both abundance-weighted and binary Jaccard distances (P < 0.05), and a meta-analysis of individual datasets resulted in similar conclusions. The Shannon’s diversity index was consistent as well, with comparable values obtained for the different datasets and for the meta-analysis of different datasets. In contrast, richness estimators (OTU and Chao) varied significantly, and the meta-analysis of richness estimators was also biased. The community structures of the two datasets were obviously different and led to significant changes in the biomarkers identified by the LEfSe statistical tool.ConclusionsOur results suggest that beta-diversity analysis and Shannon’s diversity are relatively reliable for meta-analysis, while community structures and biomarkers are less consistent. These results should be useful for future meta-analyses of microbiomes from different data sources.
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DOI：
10.1086/593193
发表时间：
2008-12-15
期刊：
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
影响因子：
--
作者：
Heo SM;Haase EM;Lesse AJ;Gill SR;Scannapieco FA
通讯作者：
Scannapieco FA
影响因子：
4.4
作者：
Schloss, Patrick D.;Westcott, Sarah L.;Weber, Carolyn F.
通讯作者：
Weber, Carolyn F.
影响因子：
3.7
作者：
Huse SM;Ye Y;Zhou Y;Fodor AA
通讯作者：
Fodor AA
影响因子：
4.5
作者：
Huse SM;Dethlefsen L;Huber JA;Mark Welch D;Relman DA;Sogin ML
通讯作者：
Sogin ML
影响因子：
5.1
作者：
Huse SM;Welch DM;Morrison HG;Sogin ML
通讯作者：
Sogin ML