metaFlye: scalable long-read metagenome assembly using repeat graphs

被引:0
作者
Mikhail Kolmogorov
Derek M. Bickhart
Bahar Behsaz
Alexey Gurevich
Mikhail Rayko
Sung Bong Shin
Kristen Kuhn
Jeffrey Yuan
Evgeny Polevikov
Timothy P. L. Smith
Pavel A. Pevzner
机构
[1] University of California,Department of Computer Science and Engineering
[2] Dairy Forage Research Center,Cell Wall Biology and Utilization Laboratory
[3] USDA,Graduate Program in Bioinformatics and System Biology
[4] University of California,Center for Algorithmic Biotechnology
[5] St. Petersburg State University,Center for Microbiome Innovation
[6] USDA-ARS US Meat Animal Research Center,undefined
[7] Bioinformatics Institute,undefined
[8] University of California,undefined
来源
Nature Methods | 2020年 / 17卷
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摘要
Long-read sequencing technologies have substantially improved the assemblies of many isolate bacterial genomes as compared to fragmented short-read assemblies. However, assembling complex metagenomic datasets remains difficult even for state-of-the-art long-read assemblers. Here we present metaFlye, which addresses important long-read metagenomic assembly challenges, such as uneven bacterial composition and intra-species heterogeneity. First, we benchmarked metaFlye using simulated and mock bacterial communities and show that it consistently produces assemblies with better completeness and contiguity than state-of-the-art long-read assemblers. Second, we performed long-read sequencing of the sheep microbiome and applied metaFlye to reconstruct 63 complete or nearly complete bacterial genomes within single contigs. Finally, we show that long-read assembly of human microbiomes enables the discovery of full-length biosynthetic gene clusters that encode biomedically important natural products.
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页码:1103 / 1110
页数:7
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