Evidence map›Paper›PMID 26496746›Full record

ArticleBMC genomics2015

Impact of library preparation protocols and template quantity on the metagenomic reconstruction of a mock microbial community.

Robert M Bowers, Alicia Clum, Hope Tice, Joanne Lim, Kanwar Singh, Doina Ciobanu, Chew Yee Ngan, Jan-Fang Cheng, Susannah G Tringe, Tanja Woyke

Abstract read
In one paragraph

Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

58 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
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  8. Article
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  12. Breaking the Ice: A Review of Phages in Polar Ecosystems.Methods in molecular biology (Clifton, N.J.) · 2024
    Review
  13. The Diversity of Bacteriophages in the Human Gut.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Robert M BowersMicrobial Genomics Program Lead, DOE Joint Genome Institute, 2800 Mitchell Dr, Walnut Creek, CA, USA. rmbowers@lbl.gov.
Alicia ClumMicrobial Genomics Program Lead, DOE Joint Genome Institute, 2800 Mitchell Dr, Walnut Creek, CA, USA. aclum@lbl.gov.
Hope TiceMicrobial Genomics Program Lead, DOE Joint Genome Institute, 2800 Mitchell Dr, Walnut Creek, CA, USA. hundley5@llnl.gov.
Joanne LimMicrobial Genomics Program Lead, DOE Joint Genome Institute, 2800 Mitchell Dr, Walnut Creek, CA, USA. jhlim@lbl.gov.
Kanwar SinghMicrobial Genomics Program Lead, DOE Joint Genome Institute, 2800 Mitchell Dr, Walnut Creek, CA, USA. ksingh@lbl.gov.
Doina CiobanuMicrobial Genomics Program Lead, DOE Joint Genome Institute, 2800 Mitchell Dr, Walnut Creek, CA, USA. dgciobanu@lbl.gov.
Chew Yee NganMicrobial Genomics Program Lead, DOE Joint Genome Institute, 2800 Mitchell Dr, Walnut Creek, CA, USA. cyngan@lbl.gov.
Jan-Fang ChengMicrobial Genomics Program Lead, DOE Joint Genome Institute, 2800 Mitchell Dr, Walnut Creek, CA, USA. jfcheng@lbl.gov.
Susannah G TringeMicrobial Genomics Program Lead, DOE Joint Genome Institute, 2800 Mitchell Dr, Walnut Creek, CA, USA. sgtringe@lbl.gov.
Tanja WoykeMicrobial Genomics Program Lead, DOE Joint Genome Institute, 2800 Mitchell Dr, Walnut Creek, CA, USA. twoyke@lbl.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe rapid development of sequencing technologies has provided access to environments that were either once thought inhospitable to life altogether or that contain too few cells to be analyzed using genomics approaches. While 16S rRNA gene microbial community sequencing has revolutionized our understanding of community composition and diversity over time and space, it only provides a crude estimate of microbial functional and metabolic potential. Alternatively, shotgun metagenomics allows comprehensive sampling of all genetic material in an environment, without any underlying primer biases. Until recently, one of the major bottlenecks of shotgun metagenomics has been the requirement for large initial DNA template quantities during library preparation.

resultsHere, we investigate the effects of varying template concentrations across three low biomass library preparation protocols on their ability to accurately reconstruct a mock microbial community of known composition. We analyze the effects of input DNA quantity and library preparation method on library insert size, GC content, community composition, assembly quality and metagenomic binning. We found that library preparation method and the amount of starting material had significant impacts on the mock community metagenomes. In particular, GC content shifted towards more GC rich sequences at the lower input quantities regardless of library prep method, the number of low quality reads that could not be mapped to the reference genomes increased with decreasing input quantities, and the different library preparation methods had an impact on overall metagenomic community composition.

conclusionsThis benchmark study provides recommendations for library creation of representative and minimally biased metagenome shotgun sequencing, enabling insights into functional attributes of low biomass ecosystem microbial communities.

Indexed as

MetagenomeMetagenomicsMicrobiotaArchaeaBacteriaBase CompositionBiomassContig MappingGene LibrarySequence Analysis, DNA

Identifiers

PMID26496746
PMCPMC4619416

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.