Recovering complete and draft population genomes from metagenome datasets.
Recovering complete and draft population genomes from metagenome datasets.
复制标题
DOI：
10.1186/s40168-016-0154-5
复制
发表时间：
2016-03-08
期刊：
影响因子：
15.5
通讯作者：
Gilbert JA
中科院分区：
文献类型：
--
作者：
Sangwan N;Xia F;Gilbert JA
将宏基因组序列数据组装到微生物基因组中，通过阐明难以培养的微生物的功能潜力，对提高我们对微生物生态学和代谢的理解具有重要价值。在这里，我们提供了一种综合的方法来将宏基因组组划分为物种水平组，并强调了遗传多样性、测序深度和覆盖范围如何影响分组成功。尽管应用于深度测序的复杂宏基因组（如土壤）的计算成本很高，但跨多个数据集的连续覆盖的共变模式显著改善了分箱过程。我们还讨论和比较了当前的基因组验证方法，并揭示了这些方法如何解决嵌合基因组箱的问题，即来自多个物种的序列。最后，我们探讨了群体基因组组装如何用于揭示生物地理趋势，并表征原位功能约束对全基因组进化的影响。
Assembly of metagenomic sequence data into microbial genomes is of fundamental value to improving our understanding of microbial ecology and metabolism by elucidating the functional potential of hard-to-culture microorganisms. Here, we provide a synthesis of available methods to bin metagenomic contigs into species-level groups and highlight how genetic diversity, sequencing depth, and coverage influence binning success. Despite the computational cost on application to deeply sequenced complex metagenomes (e.g., soil), covarying patterns of contig coverage across multiple datasets significantly improves the binning process. We also discuss and compare current genome validation methods and reveal how these methods tackle the problem of chimeric genome bins i.e., sequences from multiple species. Finally, we explore how population genome assembly can be used to uncover biogeographic trends and to characterize the effect of in situ functional constraints on the genome-wide evolution.