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Recovery of genomes from metagenomes via a dereplication, aggregation, and scoring strategy

Christian M. K. Sieber, Alexander J. Probst, Allison Sharrar, Brian C. Thomas, Matthias Hess, Susannah G. Tringe, Jillian F. Banfield
doi: https://doi.org/10.1101/107789
Christian M. K. Sieber
1 Department of Energy Joint Genome Institute, Walnut Creek, CA 94598, USA
2 Department of Earth and Planetary Science, University of California, Berkeley, CA 94720, USA
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Alexander J. Probst
2 Department of Earth and Planetary Science, University of California, Berkeley, CA 94720, USA
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Allison Sharrar
2 Department of Earth and Planetary Science, University of California, Berkeley, CA 94720, USA
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Brian C. Thomas
2 Department of Earth and Planetary Science, University of California, Berkeley, CA 94720, USA
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Matthias Hess
3 Department of Animal Science, University of California, Davis, CA, 95616, USA
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Susannah G. Tringe
1 Department of Energy Joint Genome Institute, Walnut Creek, CA 94598, USA
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Jillian F. Banfield
2 Department of Earth and Planetary Science, University of California, Berkeley, CA 94720, USA
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Abstract

Microbial communities are critical to ecosystem function. A key objective of metagenomic studies is to analyse organism-specific metabolic pathways and reconstruct community interaction networks. This requires accurate assignment of assembled genome fragments to genomes. Existing binning methods often fail to reconstruct a reasonable number of genomes and report many bins of low quality and completeness. Furthermore, the performance of existing algorithms varies between samples and biotopes. Here, we present a dereplication, aggregation and scoring strategy, DAS Tool, that combines the strengths of a flexible set of established binning algorithms. DAS Tool applied to a constructed community generated more accurate bins than any automated method. Further, when applied to environmental and host-associated samples of different complexity, DAS Tool recovered substantially more near-complete genomes, including novel lineages, than any single binning method alone. The ability to reconstruct many near-complete genomes from metagenomics data will greatly advance genome-centric analyses of ecosystems.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted February 11, 2017.
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Recovery of genomes from metagenomes via a dereplication, aggregation, and scoring strategy
Christian M. K. Sieber, Alexander J. Probst, Allison Sharrar, Brian C. Thomas, Matthias Hess, Susannah G. Tringe, Jillian F. Banfield
bioRxiv 107789; doi: https://doi.org/10.1101/107789
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Recovery of genomes from metagenomes via a dereplication, aggregation, and scoring strategy
Christian M. K. Sieber, Alexander J. Probst, Allison Sharrar, Brian C. Thomas, Matthias Hess, Susannah G. Tringe, Jillian F. Banfield
bioRxiv 107789; doi: https://doi.org/10.1101/107789

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