Accurate and complete genomes from metagenomes

Chen, Lin-Xing; Anantharaman, Karthik; Shaiber, Alon; Eren, A. Murat; Banfield, Jillian F.

doi:10.1101/gr.258640.119

Accurate and complete genomes from metagenomes

Journal Article · Wed Mar 18 00:00:00 EDT 2020 · Genome Research

DOI:https://doi.org/10.1101/gr.258640.119· OSTI ID:1625640

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Univ. of California, Berkeley, CA (United States). Dept. of Earth and Planetary Sciences; DOE/OSTI
Univ. of California, Berkeley, CA (United States). Dept. of Earth and Planetary Sciences; Univ. of Wisconsin, Madison, WI (United States). Dept. of Bacteriology
Univ. of Chicago, IL (United States). Graduate Program in Biophysical Sciences; Univ. of Chicago, IL (United States). Dept. of Medicine
Univ. of Chicago, IL (United States). Dept. of Medicine; Marine Biological Laboratory, Woods Hole, MA (United States). Bay Paul Center
Univ. of California, Berkeley, CA (United States). Dept. of Earth and Planetary Sciences; Univ. of California, Berkeley, CA (United States). Dept. of Environmental Science, Policy, and Management; Univ. of California, Berkeley, CA (United States). Earth and Environmental Sciences

Genomes are an integral component of the biological information about an organism; thus, the more complete the genome, the more informative it is. Historically, bacterial and archaeal genomes were reconstructed from pure (monoclonal) cultures, and the first reported sequences were manually curated to completion. However, the bottleneck imposed by the requirement for isolates precluded genomic insights for the vast majority of microbial life. Shotgun sequencing of microbial communities, referred to initially as community genomics and subsequently as genome-resolved metagenomics, can circumvent this limitation by obtaining metagenome-assembled genomes (MAGs); but gaps, local assembly errors, chimeras, and contamination by fragments from other genomes limit the value of these genomes. Here, we discuss genome curation to improve and, in some cases, achieve complete (circularized, no gaps) MAGs (CMAGs). To date, few CMAGs have been generated, although notably some are from very complex systems such as soil and sediment. Through analysis of about 7000 published complete bacterial isolate genomes, we verify the value of cumulative GC skew in combination with other metrics to establish bacterial genome sequence accuracy. The analysis of cumulative GC skew identified potential misassemblies in some reference genomes of isolated bacteria and the repeat sequences that likely gave rise to them. We discuss methods that could be implemented in bioinformatic approaches for curation to ensure that metabolic and evolutionary analyses can be based on very high-quality genomes.

View Accepted Manuscript (DOE)

Research Organization:: Univ. of California, Oakland, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1625640

Alternate ID(s):: OSTI ID: 1756327

Journal Information:: Genome Research, Journal Name: Genome Research Journal Issue: 3 Vol. 30; ISSN 1088-9051

Publisher:: Cold Spring Harbor Laboratory PressCopyright Statement

Country of Publication:: United States

Language:: English

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Additional file 5 of Linking genomic and physiological characteristics of psychrophilic Arthrobacter to metagenomic data to explain global environmental distribution Shen, Liang; Liu, Yongqin; Allen, Michelle A. figshare https://doi.org/10.6084/m9.figshare.14775433	dataset	January 2021
Additional file 6 of Linking genomic and physiological characteristics of psychrophilic Arthrobacter to metagenomic data to explain global environmental distribution Shen, Liang; Liu, Yongqin; Allen, Michelle A. figshare https://doi.org/10.6084/m9.figshare.14775436	dataset	January 2021
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Additional file 8 of Linking genomic and physiological characteristics of psychrophilic Arthrobacter to metagenomic data to explain global environmental distribution Shen, Liang; Liu, Yongqin; Allen, Michelle A. figshare https://doi.org/10.6084/m9.figshare.14775442	dataset	January 2021
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