Evidence map›Paper›PMID 20923983›Full record

ArticleGenetics2010

Inference of homologous recombination in bacteria using whole-genome sequences.

Xavier Didelot, Daniel Lawson, Aaron Darling, Daniel Falush

Abstract read
In one paragraph

Article in Genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers.

0numbers the graph read from it
0cells of the map it votes in
106citing 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

106 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. A Pandemic-Scale Ancestral Recombination Graph for SARS-CoV-2.bioRxiv : the preprint server for biology · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Evolution of homologous recombination rates across bacteria.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  10. A general and efficient representation of ancestral recombination graphs.bioRxiv : the preprint server for biology · 2024
    Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Population genetic analysis of clinicalFrontiers in cellular and infection microbiology · 2024
    Article
  16. Article
  17. Article
  18. Phylogenetic Analysis of Bacterial Pathogen Genomes.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  19. Article
  20. A scalable analytical approach from bacterial genomes to epidemiology.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
    Article

46 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

4 authors.

Xavier DidelotDepartment of Statistics, University of Oxford, Oxford, UK. xavier.didelot@gmail.com
Daniel Lawson
Aaron Darling
Daniel Falush

Funding

Wellcome TrustWellcome Trust WT082930MA
6 · The paper itself

Abstract

Bacteria and archaea reproduce clonally, but sporadically import DNA into their chromosomes from other organisms. In many of these events, the imported DNA replaces an homologous segment in the recipient genome. Here we present a new method to reconstruct the history of recombination events that affected a given sample of bacterial genomes. We introduce a mathematical model that represents both the donor and the recipient of each DNA import as an ancestor of the genomes in the sample. The model represents a simplification of the previously described coalescent with gene conversion. We implement a Monte Carlo Markov chain algorithm to perform inference under this model from sequence data alignments and show that inference is feasible for whole-genome alignments through parallelization. Using simulated data, we demonstrate accurate and reliable identification of individual recombination events and global recombination rate parameters. We applied our approach to an alignment of 13 whole genomes from the Bacillus cereus group. We find, as expected from laboratory experiments, that the recombination rate is higher between closely related organisms and also that the genome contains several broad regions of elevated levels of recombination. Application of the method to the genomic data sets that are becoming available should reveal the evolutionary history and private lives of populations of bacteria and archaea. The methods described in this article have been implemented in a computer software package, ClonalOrigin, which is freely available from http://code.google.com/p/clonalorigin/.

Indexed as

Models, TheoreticalRecombination, GeneticAlgorithmsBacillus cereusGene ConversionGenome, BacterialGenomicsInternetSoftware

Identifiers

PMID20923983
PMCPMC2998322

What OpenQuestion holds

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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.