Evidence map›Paper›PMID 27156482›Full record

ArticleScientific reports2016

Improved metagenome assemblies and taxonomic binning using long-read circular consensus sequence data.

J A Frank, Y Pan, A Tooming-Klunderud, V G H Eijsink, A C McHardy, A J Nederbragt, P B Pope

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed
–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

76 citing papers in PubMed.

  1. Review
  2. Metagenomic Assembly and Gene Prediction.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Sample and Library Preparation for PacBio Long-Read Sequencing in Grapevine.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  8. Article
  9. Article
  10. Long-Read Metagenomics and CAZyme Discovery.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. A Journey on the Skin Microbiome: Pitfalls and Opportunities.International journal of molecular sciences · 2021
    Review
  18. Article
  19. Article
  20. Article

16 more citing papers are in PubMed but not listed here.

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

7 authors.

J A FrankDepartment of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, 1432 Norway.
Y PanComputational Biology of Infection Research, Helmholtz Centre for Infection Research, Inhoffenstraβe 7, 38124 Braunschweig, Germany.
A Tooming-KlunderudUniversity of Oslo, Department of Biosciences, Centre for Ecological and Evolutionary Synthesis, Blindern, 0316 Norway.
V G H EijsinkDepartment of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, 1432 Norway.
A C McHardyComputational Biology of Infection Research, Helmholtz Centre for Infection Research, Inhoffenstraβe 7, 38124 Braunschweig, Germany.
A J NederbragtUniversity of Oslo, Department of Biosciences, Centre for Ecological and Evolutionary Synthesis, Blindern, 0316 Norway.
P B PopeDepartment of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, 1432 Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA assembly is a core methodological step in metagenomic pipelines used to study the structure and function within microbial communities. Here we investigate the utility of Pacific Biosciences long and high accuracy circular consensus sequencing (CCS) reads for metagenomic projects. We compared the application and performance of both PacBio CCS and Illumina HiSeq data with assembly and taxonomic binning algorithms using metagenomic samples representing a complex microbial community. Eight SMRT cells produced approximately 94 Mb of CCS reads from a biogas reactor microbiome sample that averaged 1319 nt in length and 99.7% accuracy. CCS data assembly generated a comparative number of large contigs greater than 1 kb, to those assembled from a ~190x larger HiSeq dataset (~18 Gb) produced from the same sample (i.e approximately 62% of total contigs). Hybrid assemblies using PacBio CCS and HiSeq contigs produced improvements in assembly statistics, including an increase in the average contig length and number of large contigs. The incorporation of CCS data produced significant enhancements in taxonomic binning and genome reconstruction of two dominant phylotypes, which assembled and binned poorly using HiSeq data alone. Collectively these results illustrate the value of PacBio CCS reads in certain metagenomics applications.

Indexed as

MetagenomeBase CompositionBase SequenceConsensus SequenceDNA, CircularMetagenomicsNucleotidesPhylogenySequence Analysis, DNADNA, CircularNucleotides

Identifiers

PMID27156482
PMCPMC4860591

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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.