Evidence map›Paper›PMID 39134411›Full record

ArticleGenome research2024

Pangenome-spanning epistasis and coselection analysis via de Bruijn graphs.

Juri Kuronen, Samuel T Horsfield, Anna K Pöntinen, Sudaraka Mallawaarachchi, Sergio Arredondo-Alonso, Harry Thorpe, Rebecca A Gladstone, Rob J L Willems, Stephen D Bentley, Nicholas J Croucher and 4 more

Abstract read
In one paragraph

Article in Genome research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. 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

14 authors.

Juri KuronenDepartment of Biostatistics, University of Oslo, 0372 Blindern, Norway.
Samuel T HorsfieldMRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London W12 0BZ, United Kingdom.ORCID 0000-0002-3859-4073
Anna K PöntinenDepartment of Biostatistics, University of Oslo, 0372 Blindern, Norway.ORCID 0000-0002-3160-2042
Sudaraka MallawaarachchiDepartment of Biostatistics, University of Oslo, 0372 Blindern, Norway.ORCID 0000-0001-8899-3323
Sergio Arredondo-AlonsoDepartment of Biostatistics, University of Oslo, 0372 Blindern, Norway.ORCID 0000-0002-4445-2442
Harry ThorpeDepartment of Biostatistics, University of Oslo, 0372 Blindern, Norway.ORCID 0000-0001-5895-3232
Rebecca A GladstoneDepartment of Biostatistics, University of Oslo, 0372 Blindern, Norway.ORCID 0000-0002-7993-3051
Rob J L WillemsDepartment of Medical Microbiology, University Medical Center Utrecht, 3584 CX Utrecht, Netherlands.ORCID 0000-0002-7370-0812
Stephen D BentleyParasites and Microbes, Wellcome Sanger Institute, Cambridge CB10 1RQ, United Kingdom.ORCID 0000-0001-8094-3751
Nicholas J CroucherMRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London W12 0BZ, United Kingdom.ORCID 0000-0001-6303-8768
Johan PensarDepartment of Mathematics, University of Oslo, 0372 Blindern, Norway.ORCID 0000-0002-5158-5761
John A LeesEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom; gerryt@uio.no jlees@ebi.ac.uk.ORCID 0000-0001-5360-1254
Gerry Tonkin-Hill *Department of Biostatistics, University of Oslo, 0372 Blindern, Norway; gerryt@uio.no jlees@ebi.ac.uk.ORCID 0000-0003-4397-2224
Jukka Corander *Department of Biostatistics, University of Oslo, 0372 Blindern, Norway.ORCID 0000-0002-7752-1942

Funding

European Research Council 742158Medical Research Council MR/S502388/1Wellcome Trust
6 · The paper itself

Abstract

Studies of bacterial adaptation and evolution are hampered by the difficulty of measuring traits such as virulence, drug resistance, and transmissibility in large populations. In contrast, it is now feasible to obtain high-quality complete assemblies of many bacterial genomes thanks to scalable high-accuracy long-read sequencing technologies. To exploit this opportunity, we introduce a phenotype- and alignment-free method for discovering coselected and epistatically interacting genomic variation from genome assemblies covering both core and accessory parts of genomes. Our approach uses a compact colored de Bruijn graph to approximate the intragenome distances between pairs of loci for a collection of bacterial genomes to account for the impacts of linkage disequilibrium (LD). We demonstrate the versatility of our approach to efficiently identify associations between loci linked with drug resistance and adaptation to the hospital niche in the major human bacterial pathogens

Indexed as

Enterococcus faecalisEpistasis, GeneticGenome, BacterialStreptococcus pneumoniaeGenomicsHumansLinkage Disequilibrium

Identifiers

PMID39134411
PMCPMC11368177

What OpenQuestion holds

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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.