MetaSort untangles metagenome assembly by reducing microbial community complexity View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-01-23

AUTHORS

Peifeng Ji, Yanming Zhang, Jinfeng Wang, Fangqing Zhao

ABSTRACT

Most current approaches to analyse metagenomic data rely on reference genomes. Novel microbial communities extend far beyond the coverage of reference databases and de novo metagenome assembly from complex microbial communities remains a great challenge. Here we present a novel experimental and bioinformatic framework, metaSort, for effective construction of bacterial genomes from metagenomic samples. MetaSort provides a sorted mini-metagenome approach based on flow cytometry and single-cell sequencing methodologies, and employs new computational algorithms to efficiently recover high-quality genomes from the sorted mini-metagenome by the complementary of the original metagenome. Through extensive evaluations, we demonstrated that metaSort has an excellent and unbiased performance on genome recovery and assembly. Furthermore, we applied metaSort to an unexplored microflora colonized on the surface of marine kelp and successfully recovered 75 high-quality genomes at one time. This approach will greatly improve access to microbial genomes from complex or novel communities. More... »

PAGES

14306

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    URI

    http://scigraph.springernature.com/pub.10.1038/ncomms14306

    DOI

    http://dx.doi.org/10.1038/ncomms14306

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1074207832

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/28112173


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