Evidence map›Paper›PMID 25144616›Full record

ArticlePLoS computational biology2014

Defining the estimated core genome of bacterial populations using a Bayesian decision model.

Andries J van Tonder, Shilan Mistry, James E Bray, Dorothea M C Hill, Alison J Cody, Chris L Farmer, Keith P Klugman, Anne von Gottberg, Stephen D Bentley, Julian Parkhill and 3 more

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
3.6field-weighted citation impact, top 7% of its field
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

34 citing papers in PubMed, 68 citations in OpenAlex.

  1. Comparative metagenomics using pan-metagenomic graphs.bioRxiv : the preprint server for biology · 2025
    Article
  2. Article
  3. CELEBRIMBOR: core and accessory genes from metagenomes.Bioinformatics (Oxford, England) · 2024
    Article
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  9. Review
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  19. Genetic Diversity ofFrontiers in genetics · 2018
    Article
  20. Article
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

13 authors at 6 institutions in 3 countries.

Andries J van TonderNuffield Department of Medicine, The Peter Medawar Building for Pathogen Research, University of Oxford, Oxford, United Kingdom.
Shilan MistryMathematical Institute, University of Oxford, Oxford, United Kingdom.
James E BrayDepartment of Zoology, University of Oxford, Oxford, United Kingdom.
Dorothea M C HillDepartment of Zoology, University of Oxford, Oxford, United Kingdom.
Alison J CodyDepartment of Zoology, University of Oxford, Oxford, United Kingdom.
Chris L FarmerMathematical Institute, University of Oxford, Oxford, United Kingdom.
Keith P KlugmanHubert Department of Global Health Epidemiology, Rollins School of Public Health, Atlanta, Georgia, United States of America.
Anne von GottbergCentre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases, Johannesburg, South Africa.
Stephen D BentleyPathogen Genomics Team, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, United Kingdom; Department of Medicine, University of Cambridge, Addenbrookes Hospital, Cambridge, United Kingdom.
Julian ParkhillPathogen Genomics Team, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, United Kingdom.
Keith A JolleyDepartment of Zoology, University of Oxford, Oxford, United Kingdom.
Martin C J MaidenDepartment of Zoology, University of Oxford, Oxford, United Kingdom.
Angela B BrueggemannNuffield Department of Medicine, The Peter Medawar Building for Pathogen Research, University of Oxford, Oxford, United Kingdom.
University of Oxford · GBGeorgia Department of Public Health · USMedawar Building for Pathogen Research · GBNational Institute for Communicable DiseasesUniversity of Cambridge · GBWellcome Sanger Institute · GB

Funding

Wellcome Trust 083511Wellcome Trust 087622
6 · The paper itself

Abstract

The bacterial core genome is of intense interest and the volume of whole genome sequence data in the public domain available to investigate it has increased dramatically. The aim of our study was to develop a model to estimate the bacterial core genome from next-generation whole genome sequencing data and use this model to identify novel genes associated with important biological functions. Five bacterial datasets were analysed, comprising 2096 genomes in total. We developed a Bayesian decision model to estimate the number of core genes, calculated pairwise evolutionary distances (p-distances) based on nucleotide sequence diversity, and plotted the median p-distance for each core gene relative to its genome location. We designed visually-informative genome diagrams to depict areas of interest in genomes. Case studies demonstrated how the model could identify areas for further study, e.g. 25% of the core genes with higher sequence diversity in the Campylobacter jejuni and Neisseria meningitidis genomes encoded hypothetical proteins. The core gene with the highest p-distance value in C. jejuni was annotated in the reference genome as a putative hydrolase, but further work revealed that it shared sequence homology with beta-lactamase/metallo-beta-lactamases (enzymes that provide resistance to a range of broad-spectrum antibiotics) and thioredoxin reductase genes (which reduce oxidative stress and are essential for DNA replication) in other C. jejuni genomes. Our Bayesian model of estimating the core genome is principled, easy to use and can be applied to large genome datasets. This study also highlighted the lack of knowledge currently available for many core genes in bacterial genomes of significant global public health importance.

Indexed as

Databases, GeneticModels, GeneticBacterial ProteinsBayes TheoremCampylobacter jejuniGenome, BacterialGenomicsNeisseria meningitidisBacterial Proteins

Identifiers

PMID25144616
PMCPMC4140633
OpenAlexW2019758636

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.