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增强基于长读长的菌株感知宏基因组组装

Enhancing Long-Read-Based Strain-Aware Metagenome Assembly.

作者信息

Luo Xiao, Kang Xiongbin, Schönhuth Alexander

机构信息

Genome Data Science, Faculty of Technology, Bielefeld University, Bielefeld, Germany.

Life Science and Health, Centrum Wiskunde and Informatica, Amsterdam, Netherlands.

出版信息

Front Genet. 2022 May 13;13:868280. doi: 10.3389/fgene.2022.868280. eCollection 2022.

Abstract

Microbial communities are usually highly diverse and often involve multiple strains from the participating species due to the rapid evolution of microorganisms. In such a complex microecosystem, different strains may show different biological functions. While reconstruction of individual genomes at the strain level is vital for accurately deciphering the composition of microbial communities, the problem has largely remained unresolved so far. Next-generation sequencing has been routinely used in metagenome assembly but there have been struggles to generate strain-specific genome sequences due to the short-read length. This explains why long-read sequencing technologies have recently provided unprecedented opportunities to carry out haplotype- or strain-resolved genome assembly. Here, we propose MetaBooster and MetaBooster-HiFi, as two pipelines for strain-aware metagenome assembly from PacBio CLR and Oxford Nanopore long-read sequencing data. Benchmarking experiments on both simulated and real sequencing data demonstrate that either the MetaBooster or the MetaBooster-HiFi pipeline drastically outperforms the state-of-the-art metagenome assemblers, in terms of all relevant metagenome assembly criteria, involving genome fraction, contig length, and error rates.

摘要

由于微生物的快速进化,微生物群落通常具有高度的多样性,并且往往涉及来自参与物种的多个菌株。在这样一个复杂的微生态系统中,不同的菌株可能表现出不同的生物学功能。虽然在菌株水平上重建个体基因组对于准确解读微生物群落的组成至关重要,但到目前为止,这个问题在很大程度上仍未得到解决。下一代测序已常规用于宏基因组组装,但由于读长较短,在生成菌株特异性基因组序列方面一直存在困难。这就解释了为什么长读长测序技术最近为进行单倍型或菌株解析的基因组组装提供了前所未有的机会。在这里,我们提出了MetaBooster和MetaBooster-HiFi这两种流程,用于从PacBio CLR和牛津纳米孔长读长测序数据中进行菌株感知的宏基因组组装。对模拟和真实测序数据的基准实验表明,无论是MetaBooster还是MetaBooster-HiFi流程,在所有相关的宏基因组组装标准方面,包括基因组比例、重叠群长度和错误率,都大大优于目前最先进的宏基因组组装工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/532e/9136235/bd71eab22ba5/fgene-13-868280-g001.jpg

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