Evidence map›Paper›PMID 41672993›Full record

ArticleNature communications2026

Selective sweep probabilities in spatially expanding populations.

Alexander Stein, Kate Bostock, Ramanarayanan Kizhuttil, Maciej Bak, Robert Noble

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Alexander SteinCentre for Cancer Evolution, Barts Cancer Institute, Queen Mary University of London, London, UK. alexander.stein@ulb.be.ORCID 0000-0003-0520-0063
Kate BostockDepartment of Mathematics, City St George's, University of London, London, UK.ORCID 0009-0000-0147-4927
Ramanarayanan KizhuttilDepartment of Physics, Indian Institute of Science Education and Research, Kolkata, India.ORCID 0009-0002-6824-4928
Maciej BakDepartment of Mathematics, City St George's, University of London, London, UK.ORCID 0000-0003-1361-7301
Robert NobleDepartment of Mathematics, City St George's, University of London, London, UK. robert.noble@citystgeorges.ac.uk.ORCID 0000-0002-8057-4252

Funding

The Role of the Microbiome in Cancer Suppression and Susceptibility Across SpeciesU54CA217376 · NCI · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI MALEY, CARLO, SHIBATA, DARRYL K · 2018 to 2022
$8.6M
EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 955708Marie Składowska-Curie EvoGamesPlusUK Research and Innovation (UKRI)U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) U54CA217376
6 · The paper itself

Abstract

Evolution during range expansions shapes biological systems from microbial communities and tumours to invasive species. A fundamental question is whether, when a beneficial mutation arises during a range expansion, it will evade clonal interference and sweep to fixation. However, most theoretical investigations of range expansions have considered regimes in which selective sweeps are effectively impossible, while studies of selective sweeps have assumed constant population size or ignored spatial structure. Here we use mathematical modelling and analysis to investigate selective sweep probabilities and timings in biologically relevant scenarios, including the case in which mutants can displace a slowly spreading wildtype. Assuming constant expansion speed, we find surprisingly simple approximate and exact expressions for sweep probabilities in one, two and three dimensions, which are independent of mutation rate. Agent-based simulations confirm that our predictions are accurate for the spatial Moran process and remain informative when mutation effects on fitness are random and multiplicative. We further compare and synthesise our results with those obtained for alternative growth laws. Parameterised for human tumours, our model predicts that selective sweeps are rare except during early solid tumour growth, thus providing a general, pan-cancer explanation for findings from recent sequencing studies.

Indexed as

Models, GeneticSelection, GeneticAnimalsComputer SimulationHumansMutationMutation RateNeoplasmsProbability

Identifiers

PMID41672993
PMCPMC12960945

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LicenceCC BY
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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.