Evidence map›Paper›PMID 41954973›Full record

ArticleThe Journal of heredity2026

Polygenic and monogenic adaptation drive evolutionary rescue at different magnitudes of environmental change.

Tatiana Bellagio, Moises Exposito-Alonso

Abstract read
In one paragraph

Article in The Journal of heredity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Tatiana BellagioDepartment of Integrative Biology, University of California Berkeley, Berkeley, CA, United States.ORCID 0000-0001-7046-1695
Moises Exposito-AlonsoDepartment of Integrative Biology, University of California Berkeley, Berkeley, CA, United States.ORCID 0000-0001-5711-0700

Funding

Predicting and controlling polygenic health traits using probabilistic models and evolution-inspired gene editingDP5OD029506 · OD · UNIVERSITY OF CALIFORNIA BERKELEY · PI EXPOSITO-ALONSO, MOISES · 2020 to 2024
$2.0M
Carnegie Institution for ScienceCarnegie Institution for Science and High Performance ComputingNIH HHS DP5 OD029506Office of the Director of the National Institutes of Health's Early Investigator Award 1DP5OD029506-01the Howard Hughes Medical Institutethe University of California BerkeleyUniversity of California BerkeleyUS Department of Energy, Office of Biological and Environmental Research DE-SC0021286US National Science Foundation's DBI Biology Integration Institute WALII 2213983
6 · The paper itself

Abstract

Understanding the genetic basis of rapid adaptation is key to predicting species' evolutionary responses to environmental change. However, it is still debatable whether many small-effect mutations or a few large-effect mutations underlie rapid adaptation, and how this knowledge can predict population survival or extinction. To address this question, we performed a series of ecologically grounded forward-in-time genetic simulations to study rapid adaptation and extinction with increasing magnitudes of environmental change. These simulations were seeded with genomic variation of the plant Arabidopsis thaliana to have a realistic genomic structure, with one (monogenic) to 1,000 (polygenic) variants with varying heritabilities contributing to an environmental adaptive trait. Our results revealed two distinct scenarios of rapid adaptation and population rescue. Under small-to-moderate environmental shifts, high polygenic traits increased evolutionary rescue probability. Under extreme environmental shifts, high polygenic traits lead predictably to extinction, yet monogenic traits sometimes produce one-off winning adaptive genotypes. We interpret our rapid evolutionary rescue findings in terms of the fundamental theorem of natural selection, where trait polygenicity shapes the distribution of genetic variance in fitness across replicates and, in turn, the probability of population survival, with polygenic architectures producing more stable and predictable fitness variance and monogenic architectures generating highly skewed and variable outcomes. These results highlight the insights genomics gives us into the (un)predictability of species' evolutionary responses to global change, with management implications for assisted adaptation and conservation.

Indexed as

Adaptation, BiologicalAdaptation, PhysiologicalArabidopsisBiological EvolutionModels, GeneticMultifactorial InheritanceComputer SimulationEnvironmentGenetic FitnessGenetics, PopulationGenetic VariationGenotypePhenotypeSelection, Geneticenvironmental changeevolutionary rescuegenetic architecturepolygenic adaptationpredictability of adaptation

Identifiers

PMID41954973
PMCPMC13539452

What Socratic holds

Textmetadata
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 Socratic graph.