metaFlye: scalable long-read metagenome assembly using repeat graphs
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,...
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| Published in | Nature methods Vol. 17; no. 11; pp. 1103 - 1110 |
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| Main Authors | , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Nature Publishing Group US
01.11.2020
Nature Publishing Group |
| Subjects | |
| Online Access | Get full text |
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| Abstract | 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.
Long-read metagenomics offers a valuable approach for profiling bacterial communities. This work presents a long-read assembler, metaFlye, that specifically addresses the challenges of assembling metagenomes. |
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| AbstractList | 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. 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.Long-read metagenomics offers a valuable approach for profiling bacterial communities. This work presents a long-read assembler, metaFlye, that specifically addresses the challenges of assembling metagenomes. 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.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. 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. Long-read metagenomics offers a valuable approach for profiling bacterial communities. This work presents a long-read assembler, metaFlye, that specifically addresses the challenges of assembling metagenomes. |
| Audience | Academic |
| Author | Behsaz, Bahar Pevzner, Pavel A. Gurevich, Alexey Shin, Sung Bong Kuhn, Kristen Bickhart, Derek M. Rayko, Mikhail Smith, Timothy P. L. Kolmogorov, Mikhail Yuan, Jeffrey Polevikov, Evgeny |
| Author_xml | – sequence: 1 givenname: Mikhail orcidid: 0000-0002-5489-9045 surname: Kolmogorov fullname: Kolmogorov, Mikhail organization: Department of Computer Science and Engineering, University of California – sequence: 2 givenname: Derek M. surname: Bickhart fullname: Bickhart, Derek M. organization: Cell Wall Biology and Utilization Laboratory, Dairy Forage Research Center, USDA – sequence: 3 givenname: Bahar surname: Behsaz fullname: Behsaz, Bahar organization: Graduate Program in Bioinformatics and System Biology, University of California – sequence: 4 givenname: Alexey surname: Gurevich fullname: Gurevich, Alexey organization: Center for Algorithmic Biotechnology, St. Petersburg State University – sequence: 5 givenname: Mikhail orcidid: 0000-0002-3737-1521 surname: Rayko fullname: Rayko, Mikhail organization: Center for Algorithmic Biotechnology, St. Petersburg State University – sequence: 6 givenname: Sung Bong surname: Shin fullname: Shin, Sung Bong organization: USDA-ARS US Meat Animal Research Center – sequence: 7 givenname: Kristen surname: Kuhn fullname: Kuhn, Kristen organization: USDA-ARS US Meat Animal Research Center – sequence: 8 givenname: Jeffrey orcidid: 0000-0003-3855-1994 surname: Yuan fullname: Yuan, Jeffrey organization: Graduate Program in Bioinformatics and System Biology, University of California – sequence: 9 givenname: Evgeny surname: Polevikov fullname: Polevikov, Evgeny organization: Center for Algorithmic Biotechnology, St. Petersburg State University, Bioinformatics Institute – sequence: 10 givenname: Timothy P. L. orcidid: 0000-0003-1611-6828 surname: Smith fullname: Smith, Timothy P. L. organization: USDA-ARS US Meat Animal Research Center – sequence: 11 givenname: Pavel A. orcidid: 0000-0002-0418-165X surname: Pevzner fullname: Pevzner, Pavel A. email: ppevzner@ucsd.edu organization: Department of Computer Science and Engineering, University of California, Center for Microbiome Innovation, University of California |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33020656$$D View this record in MEDLINE/PubMed |
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| Title | metaFlye: scalable long-read metagenome assembly using repeat graphs |
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