Evidence map›Paper›PMID 32167543›Full record

ArticleMolecular biology and evolution2020

GenomegaMap: Within-Species Genome-Wide dN/dS Estimation from over 10,000 Genomes.

Daniel J Wilson, CRyPTIC Consortium

Open access · hybridAbstract readEvaluation Study
In one paragraph

Article in Molecular biology and evolution, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

33 citing papers in PubMed, 53 citations in OpenAlex.

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  6. Dynamics of dN/dS within recombining bacterial populations.bioRxiv : the preprint server for biology · 2025
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  7. Leveraging FracMinHash Containment for GenomicbioRxiv : the preprint server for biology · 2025
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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

2 authors at 2 institutions in 2 countries.

Daniel J WilsonBig Data Institute, Nuffield Department of Population Health, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom.
CRyPTIC Consortium
Inserm · FRUniversity of Oxford · GB

Funding

New Tools for the interpretation of Pathogen Genomic Data with a focus on Mycobacterium tuberculosisK01ES026835 · NIEHS · MASSACHUSETTS GENERAL HOSPITAL · PI FARHAT, MAHA · 2015 to 2019
$1.1M
Medical Research Council MC_PC_16027NIEHS NIH HHS K01 ES026835Wellcome TrustWellcome Trust 101237/Z/13/BWellcome Trust 200205/Z/15/Z
6 · The paper itself

Abstract

The dN/dS ratio provides evidence of adaptation or functional constraint in protein-coding genes by quantifying the relative excess or deficit of amino acid-replacing versus silent nucleotide variation. Inexpensive sequencing promises a better understanding of parameters, such as dN/dS, but analyzing very large data sets poses a major statistical challenge. Here, I introduce genomegaMap for estimating within-species genome-wide variation in dN/dS, and I apply it to 3,979 genes across 10,209 tuberculosis genomes to characterize the selection pressures shaping this global pathogen. GenomegaMap is a phylogeny-free method that addresses two major problems with existing approaches: 1) It is fast no matter how large the sample size and 2) it is robust to recombination, which causes phylogenetic methods to report artefactual signals of adaptation. GenomegaMap uses population genetics theory to approximate the distribution of allele frequencies under general, parent-dependent mutation models. Coalescent simulations show that substitution parameters are well estimated even when genomegaMap's simplifying assumption of independence among sites is violated. I demonstrate the ability of genomegaMap to detect genuine signatures of selection at antimicrobial resistance-conferring substitutions in Mycobacterium tuberculosis and describe a novel signature of selection in the cold-shock DEAD-box protein A gene deaD/csdA. The genomegaMap approach helps accelerate the exploitation of big data for gaining new insights into evolution within species.

Indexed as

Genetic TechniquesModels, GeneticSelection, GeneticSilent MutationDEAD-box RNA HelicasesGenome, BacterialMycobacterium tuberculosisDEAD-box RNA Helicasesadaptationbig datadN/dSnatural selectionparent-dependent mutationrecombination

Identifiers

PMID32167543
PMCPMC7403622
OpenAlexW3011840618

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.