Single-Cell-Genomics-Facilitated Read Binning of Candidate Phylum EM19 Genomes from Geothermal Spring Metagenomes.

ABSTRACT: The vast majority of microbial life remains uncatalogued due to the inability to cultivate these organisms in the laboratory. This "microbial dark matter" represents a substantial portion of the tree of life and of the populations that contribute to chemical cycling in many ecosystems. In this work, we leveraged an existing single-cell genomic data set representing the candidate bacterial phylum "Calescamantes" (EM19) to calibrate machine learning algorithms and define metagenomic bins directly from pyrosequencing reads derived from Great Boiling Spring in the U.S. Great Basin. Compared to other assembly-based methods, taxonomic binning with a read-based machine learning approach yielded final assemblies with the highest predicted genome completeness of any method tested. Read-first binnin

SUBMITTER: Becraft ED 

PROVIDER: S-EPMC4751853 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature