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Title: Optimizing de novo genome assembly from PCR-amplified metagenomes

Journal Article · · PeerJ
DOI:https://doi.org/10.7717/peerj.6902· OSTI ID:1526560
 [1];  [2];  [1];  [1];  [3];  [4];  [5];  [6];  [6];  [7];  [1];  [2];  [2];  [1];  [1]
  1. USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States)
  2. The Ohio State Univ., Columbus, OH (United States)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  4. Clark Univ., Worcester, MA (United States)
  5. Univ. of Maryland Center for Environmental Science, Cambridge, MD (United States)
  6. Univ. of Maryland Center for Environmental Science, Cambridge, MD (United States)
  7. Univ. of Southern California, Los Angeles, CA (United States)

Background. Metagenomics has transformed our understanding of microbial diversity across ecosystems, with recent advances enabling de novo assembly of genomes from metagenomes. These metagenome-assembled genomes are critical to provide ecological, evolutionary, and metabolic context for all the microbes and viruses yet to be cultivated. Metagenomes can now be generated from nanogram to subnanogram amounts of DNA. However, these libraries require several rounds of PCR amplification before sequencing, and recent data suggest these typically yield smaller and more fragmented assemblies than regular metagenomes. Methods. Here we evaluate de novo assembly methods of 169 PCR-amplified metagenomes, including 25 for which an unamplified counterpart is available, to optimize specific assembly approaches for PCR-amplified libraries. We first evaluated coverage bias by mapping reads from PCR-amplified metagenomes onto reference contigs obtained from unamplified metagenomes of the same samples. Then, we compared different assembly pipelines in terms of assembly size (number of bp in contigs ≥ 10 kb) and error rates to evaluate which are the best suited for PCR-amplified metagenomes. Results. Read mapping analyses revealed that the depth of coverage within individual genomes is significantly more uneven in PCR-amplified datasets versus unamplified metagenomes, with regions of high depth of coverage enriched in short inserts. This enrichment scales with the number of PCR cycles performed, and is presumably due to preferential amplification of short inserts. Standard assembly pipelines are confounded by this type of coverage unevenness, so we evaluated other assembly options to mitigate these issues. We found that a pipeline combining read deduplication and an assembly algorithm originally designed to recover genomes from libraries generated after whole genome amplification (single-cell SPAdes) frequently improved assembly of contigs ≥10 kb by 10 to 100-fold for low input metagenomes. Conclusions. PCR-amplified metagenomes have enabled scientists to explore communities traditionally challenging to describe, including some with extremely low biomass or from which DNA is particularly difficult to extract. Here we show that a modified assembly pipeline can lead to an improved de novo genome assembly from PCR-amplified datasets, and enables a better genome recovery from low input metagenomes.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF); Gordon & Betty Moore Foundation (GBMF)
Grant/Contract Number:
AC02-05CH11231; SC0014664; SC0010580; SC0004632; SC0016440; OCE-1031743; OCE-1136818; OCE-1737409; 3790; 5488; 3779
OSTI ID:
1526560
Journal Information:
PeerJ, Vol. 7; ISSN 2167-8359
Publisher:
PeerJ Inc.Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 18 works
Citation information provided by
Web of Science

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Cited By (3)

Studying the gut virome in the metagenomic era: challenges and perspectives journal October 2019
Towards optimized viral metagenomes for double-stranded and single-stranded DNA viruses from challenging soils journal January 2019
Benchmarking protocols for the metagenomic analysis of stream biofilm viromes journal January 2019