Evidence map›Paper›PMID 28199698›Full record

ArticleMolecular biology and evolution2017

Efficient Inference of Recent and Ancestral Recombination within Bacterial Populations.

Rafal Mostowy, Nicholas J Croucher, Cheryl P Andam, Jukka Corander, William P Hanage, Pekka Marttinen

Open access · bronzeAbstract read
In one paragraph

Article in Molecular biology and evolution, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 papers.

0numbers the graph read from it
0cells of the map it votes in
114citing papers in PubMed
7.9field-weighted citation impact, top 2% 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

114 citing papers in PubMed, 182 citations in OpenAlex.

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  7. Gene exchange betweenMicrobial genomics · 2026
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  10. Population structure ofMicrobial genomics · 2025
    Article
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54 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

6 authors at 4 institutions in 4 countries.

Rafal MostowyDepartment of Infectious Disease Epidemiology, St. Mary's Campus, Imperial College London, London, United Kingdom.
Nicholas J CroucherDepartment of Infectious Disease Epidemiology, St. Mary's Campus, Imperial College London, London, United Kingdom.
Cheryl P AndamDepartment of Epidemiology, Harvard TH Chan School of Public Health, Center for Communicable Disease Dynamics, Boston, MA.
Jukka CoranderDepartment of Mathematics and Statistics, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland.
William P HanageDepartment of Epidemiology, Harvard TH Chan School of Public Health, Center for Communicable Disease Dynamics, Boston, MA.
Pekka MarttinenDepartment of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Espoo, Finland.
Center for Disease Dynamics, Economics & Policy · USImperial College London · GBAalto University · FIHelsinki Institute for Information Technology · FI

Funding

Ecological and genetic contributions to the spread of resistance in pneumococcusR01AI106786 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI HANAGE, WILLIAM · 2013 to 2017
$3.1M
NIAID NIH HHS R01 AI106786
6 · The paper itself

Abstract

Prokaryotic evolution is affected by horizontal transfer of genetic material through recombination. Inference of an evolutionary tree of bacteria thus relies on accurate identification of the population genetic structure and recombination-derived mosaicism. Rapidly growing databases represent a challenge for computational methods to detect recombinations in bacterial genomes. We introduce a novel algorithm called fastGEAR which identifies lineages in diverse microbial alignments, and recombinations between them and from external origins. The algorithm detects both recent recombinations (affecting a few isolates) and ancestral recombinations between detected lineages (affecting entire lineages), thus providing insight into recombinations affecting deep branches of the phylogenetic tree. In simulations, fastGEAR had comparable power to detect recent recombinations and outstanding power to detect the ancestral ones, compared with state-of-the-art methods, often with a fraction of computational cost. We demonstrate the utility of the method by analyzing a collection of 616 whole-genomes of a recombinogenic pathogen Streptococcus pneumoniae, for which the method provided a high-resolution view of recombination across the genome. We examined in detail the penicillin-binding genes across the Streptococcus genus, demonstrating previously undetected genetic exchanges between different species at these three loci. Hence, fastGEAR can be readily applied to investigate mosaicism in bacterial genes across multiple species. Finally, fastGEAR correctly identified many known recombination hotspots and pointed to potential new ones. Matlab code and Linux/Windows executables are available at https://users.ics.aalto.fi/~pemartti/fastGEAR/ (last accessed February 6, 2017).

Indexed as

AlgorithmsBiological EvolutionDNA, AncientEvolution, MolecularGenes, BacterialGenetics, PopulationGenome, BacterialPhylogenyRecombination, GeneticSequence Analysis, DNAStreptococcus pneumoniaeDNA, Ancientantibiotic resistancebacterial population geneticshidden Markov modelspopulation structurerecombination detectionStreptococcus pneumoniae

Identifiers

PMID28199698
PMCPMC5400400
OpenAlexW2588835098

What OpenQuestion holds

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LicenceCC BY-NC
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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.