Comparative metagenomic and rRNA microbial diversity characterization using archaeal and bacterial synthetic communities.
Comparative metagenomic and rRNA microbial diversity characterization using archaeal and bacterial synthetic communities.
复制标题
DOI：
10.1111/1462-2920.12086
复制
发表时间：
2013-06
影响因子：
5.1
通讯作者：
Podar M
中科院分区：
文献类型：
--
作者：
Shakya M;Quince C;Campbell JH;Yang ZK;Schadt CW;Podar M
下一代测序极大地改变了微生物生态学的格局，大规模和深入的多样性研究现在已经广泛使用。然而，确定分类和定量推断的准确性和比较不同方法获得的结果是复杂的实验和计算数据类型的不一致性，也缺乏真正的生态多样性的知识。在这里，我们使用高度多样化的细菌和古细菌合成社区组装纯基因组DNA比较宏基因组和SSU rRNA扩增子测序的推论。Illumina和454宏基因组数据在量化群落组成方面都优于扩增子测序，但结果取决于分析参数和平台。处理和分类扩增子的新方法可以在引物组内以高重现性重建群落的分类组成，但所有测试的引物组都会导致显着的分类特异性偏差。控制合成社区组装广泛模仿目标环境中的系统发育丰富度可以提供重要的验证微调实验和计算参数用于表征自然社区。
Next generation sequencing has dramatically changed the landscape of microbial ecology, large-scale and in-depth diversity studies being now widely accessible. However, determining the accuracy of taxonomic and quantitative inferences and comparing results obtained with different approaches are complicated by incongruence of experimental and computational data types and also by lack of knowledge of the true ecological diversity. Here we used highly diverse bacterial and archaeal synthetic communities assembled from pure genomic DNAs to compare inferences from metagenomic and SSU rRNA amplicon sequencing. Both Illumina and 454 metagenomic data outperformed amplicon sequencing in quantifying the community composition, but the outcome was dependent on analysis parameters and platform. New approaches in processing and classifying amplicons can reconstruct the taxonomic composition of the community with high reproducibility within primer sets, but all tested primers sets lead to significant taxon-specific biases. Controlled synthetic communities assembled to broadly mimic the phylogenetic richness in target environments can provide important validation for fine-tuning experimental and computational parameters used to characterize natural communities.
登录
查看更多内容
影响因子：
14.9
作者：
Cole JR;Wang Q;Cardenas E;Fish J;Chai B;Farris RJ;Kulam-Syed-Mohideen AS;McGarrell DM;Marsh T;Garrity GM;Tiedje JM
通讯作者：
Tiedje JM
DOI：
10.1073/pnas.1000080107
发表时间：
2011-03-15
影响因子：
11.1
作者：
Caporaso, J. Gregory;Lauber, Christian L.;Knight, Rob
通讯作者：
Knight, Rob
影响因子：
11
作者：
Griffen, Ann L.;Beall, Clifford J.;Leys, Eugene J.
通讯作者：
Leys, Eugene J.
影响因子：
56.9
作者：
Ley, Ruth E.;Hamady, Micah;Gordon, Jeffrey I.
通讯作者：
Gordon, Jeffrey I.
影响因子：
5.1
作者：
Huse SM;Welch DM;Morrison HG;Sogin ML
通讯作者：
Sogin ML