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ConStrains identifies microbial strains in metagenomic datasets

机译:ConStrains在宏基因组数据集中识别微生物菌株

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摘要

An important fraction of microbial diversity is harbored in strain individuality, so identification of conspecific bacterial strains is imperative for improved understanding of microbial community functions. Limitations in bioinformatics and sequencing technologies have to date precluded strain identification owing to difficulties in phasing short reads to faithfully recover the original strain-level genotypes, which have highly similar sequences. We present ConStrains, an open-source algorithm that identifies conspecific strains from metagenomic sequence data and reconstructs the phylogeny of these strains in microbial communities. The algorithm uses single-nucleotide polymorphism (SNP) patterns in a set of universal genes to infer within-species structures that represent strains. Applying ConStrains to simulated and host-derived data sets provides insights into microbial community dynamics.
机译:微生物多样性的重要组成部分在于菌株的个体性,因此鉴定同种细菌菌株对于改善对微生物群落功能的了解势在必行。由于难以分阶段短读以忠实地恢复具有高度相似序列的原始菌株水平基因型的困难,迄今为止,生物信息学和测序技术的局限性还无法进行菌株鉴定。我们提出了ConStrains,这是一种开放源代码算法,可从宏基因组序列数据中识别同种菌株,并在微生物群落中重建这些菌株的系统发育。该算法使用一组通用基因中的单核苷酸多态性(SNP)模式来推断代表菌株的种内结构。将ConStrains应用于模拟数据和宿主数据集可洞悉微生物群落动态。

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