Evidence map›Paper›PMID 42546145›Full record

ArticleGenetics2026

The evolution of genetic drift over 50,000 generations.

Joao A Ascensao, QinQin Yu, Oskar Hallatschek

Abstract read
In one paragraph

Article in Genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Joao A AscensaoDepartment of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States.
QinQin YuDepartment of Physics, University of California Berkeley, Berkeley, CA 94720, United States.
Oskar HallatschekDepartment of Physics, University of California Berkeley, Berkeley, CA 94720, United States.ORCID 0000-0002-1312-5975

Funding

Resolving the Mechano-Chemical Regulation of Microbial Populations in Microfluidic DevicesR01GM115851 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI HALLATSCHEK, OSKAR · 2015 to 2023
$2.2M
Pacific Biosciences PacBio RS Single Molecule Real Time SequencerS10OD018174 · OD · UNIVERSITY OF CALIFORNIA BERKELEY · PI ROKHSAR, DANIEL SOLEYMAN · 2014 to 2014
$600k
Humboldt Professorship of the Alexander von Humboldt FoundationNational Science Foundation CAREER 1555330NIGMS NIH HHSNIGMS NIH HHS R01GM115851NIH HHS S10 OD018174NSFSeqCoast Genomics LLCUC Berkeley RRID:SCR_022170
6 · The paper itself

Abstract

Random variation in reproductive success-genetic drift-profoundly shapes genetic diversity and evolutionary trajectories. The strength of drift depends on the variance in descendant number, σd2, which governs key evolutionary outcomes: for instance, the establishment probability of a beneficial mutation scales inversely with σd2. However, whether σd2 itself evolves over long timescales has remained unclear, because allele-frequency fluctuations depend on drift only through the effective population size, Ne=N/σd2, which blends census population size with descendant-number variance. Here, we disentangle these components by using model-based Bayesian inference combined with joint tracking of (i) frequency fluctuations of neutrally barcoded lineages and (ii) census population sizes across growth cycles in the Escherichia coli long-term evolution experiment (LTEE). Analyzing 33 clones spanning the ancestor through 50,000 generations in two replicate populations (Ara-2 and Ara+2), we find that the strength of genetic drift evolved markedly-and divergently-between the two replicate populations. Both census size and σd2 changed substantially through time, with most variation in Ne driven by shifts in σd2 rather than census size. After approximately 2,000 generations, the σd2 of the two populations diverged sharply: Ara+2 generally remained close to a bottleneck-only null expectation, whereas Ara-2 exhibited 1.5-5× stronger drift, consistent with an evolved increase in stochasticity during growth. These results imply that mutations can alter both the mean and the variance of the descendant-number distribution, and we show that the joint distribution of mutational effects on fitness and on σd2 can substantially modulate the rate of adaptation. The key parameter governing genetic drift can therefore itself evolve in the LTEE, with direct consequences for adaptation.

Indexed as

Evolution, MolecularGenetic DriftBayes TheoremEscherichia coliGene FrequencyGenetic VariationModels, GeneticMutationPopulation DensityBayesian inferencedemographic stochasticityDNA barcodeseffective population sizegenetic driftoffspring number variance

Identifiers

PMID42546145
PMCPMC13643808

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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.