Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy.
Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy.
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DOI：
10.1038/s41564-018-0171-1
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发表时间：
2018-07
影响因子：
28.3
通讯作者：
Banfield JF
中科院分区：
文献类型：
--
作者：
Sieber CMK;Probst AJ;Sharrar A;Thomas BC;Hess M;Tringe SG;Banfield JF
微生物群落对生态系统功能至关重要。宏基因组研究的一个关键目标是分析生物体特异性代谢途径和重建社区相互作用网络。这需要将组装的基因组片段准确地分配到基因组。现有的分箱方法往往无法重建合理数量的基因组，并报告许多低质量和完整性的箱子。此外，现有算法的性能在样本和生境之间变化。在这里，我们提出了一个去复制，聚合和评分策略，DAS工具，它结合了一组灵活的建立分箱算法的优势。DAS工具应用于一个构建的社区产生更准确的箱子比任何自动化的方法。事实上，当应用于不同复杂性的环境和宿主相关样本时，DAS Tool比任何单一的分箱方法都恢复了更多接近完整的基因组，包括以前未报告的谱系。从宏基因组学数据重建许多接近完整的基因组的能力将大大推进以基因组为中心的生态系统分析。在这里，作者提出了一种工具，该工具能够将一组灵活的现有分箱算法组合在一起，从而提高了分箱准确性，并与独立方法相比，从宏基因组中恢复出更接近完整的基因组。
Microbial communities are critical to ecosystem function. A key objective of metagenomic studies is to analyse organism-specific metabolic pathways and reconstruct community interaction networks. This requires accurate assignment of assembled genome fragments to genomes. Existing binning methods often fail to reconstruct a reasonable number of genomes and report many bins of low quality and completeness. Furthermore, the performance of existing algorithms varies between samples and biotopes. Here, we present a dereplication, aggregation and scoring strategy, DAS Tool, that combines the strengths of a flexible set of established binning algorithms. DAS Tool applied to a constructed community generated more accurate bins than any automated method. Indeed, when applied to environmental and host-associated samples of different complexity, DAS Tool recovered substantially more near-complete genomes, including previously unreported lineages, than any single binning method alone. The ability to reconstruct many near-complete genomes from metagenomics data will greatly advance genome-centric analyses of ecosystems. Here the authors present a tool that enables a flexible set of existing binning algorithms to be combined, resulting in improved binning accuracy and the recovery of more near-complete genomes from metagenomes compared to standalone methods.
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影响因子：
48
作者：
Langmead, Ben;Salzberg, Steven L.
通讯作者：
Salzberg, Steven L.
影响因子：
2.7
作者：
Kang DD;Froula J;Egan R;Wang Z
通讯作者：
Wang Z
影响因子：
1.9
作者：
Hawley, Erik R.;Malfatti, Stephanie A.;Hess, Matthias
通讯作者：
Hess, Matthias
影响因子：
7
作者：
Parks DH;Imelfort M;Skennerton CT;Hugenholtz P;Tyson GW
通讯作者：
Tyson GW
影响因子：
14.9
作者：
UniProt Consortium
通讯作者：
UniProt Consortium