Mutation potentiates migration swamping in polygenic local adaptation

Locally adapted traits can exhibit a wide range of genetic architectures, from pronounced divergence at a few loci to small frequency divergence at many loci. The type of architecture that evolves depends strongly on the migration rate, as weakly selected loci experience swamping and do not make lasting contributions to divergence. Simulations from previous studies showed that even when mutations are strongly selected and should resist migration swamping, the architecture of adaptation can collapse and become transient at high mutation rates. Here, we use an analytical two-population model to study how this transition in genetic architecture depends upon population size, strength of selection, and parameters describing the mutation process. To do this, we develop a mathematical theory based on the diffusion approximation to predict the threshold mutation rate above which the transition occurs. We find that this performs well across a wide range of parameter space, based on comparisons with individual-based simulations. The threshold mutation rate depends most strongly on the average effect size of mutations, weakly on the strength of selection, and marginally on the population size. Across a wide range of the parameter space, we observe that the transition to a transient architecture occurs when the trait-wide mutation rate is 10-3-10-2, suggesting that this phenomenon is potentially relevant to complex traits with a large mutational target. On the other hand, based on the apparent stability of genetic architecture in many classic examples of local adaptation, our theory suggests that per-trait mutation rates are often relatively low.

Authors

Institutions

Publication Details

Journal
Genetics
Published
2024-10-12
DOI
https://doi.org/10.1093/genetics/iyae165
Citations
4
Primary Topic
Evolution and Genetic Dynamics
Type
article
Field-Weighted Citation Impact
2.20

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mutation potentiates migration swamping in polygenic local adaptation

Takahiro Sakamoto, James R. Whiting, Sam Yeaman
4 citations
Genetics
Evolution and Genetic Dynamics
2.20
article

Mutation potentiates migration swamping in polygenic local adaptation

Takahiro Sakamoto, James R. Whiting, Sam Yeaman
article en
4 citations

Abstract

Locally adapted traits can exhibit a wide range of genetic architectures, from pronounced divergence at a few loci to small frequency divergence at many loci. The type of architecture that evolves depends strongly on the migration rate, as weakly selected loci experience swamping and do not make lasting contributions to divergence. Simulations from previous studies showed that even when mutations are strongly selected and should resist migration swamping, the architecture of adaptation can collapse and become transient at high mutation rates. Here, we use an analytical two-population model to study how this transition in genetic architecture depends upon population size, strength of selection, and parameters describing the mutation process. To do this, we develop a mathematical theory based on the diffusion approximation to predict the threshold mutation rate above which the transition occurs. We find that this performs well across a wide range of parameter space, based on comparisons with individual-based simulations. The threshold mutation rate depends most strongly on the average effect size of mutations, weakly on the strength of selection, and marginally on the population size. Across a wide range of the parameter space, we observe that the transition to a transient architecture occurs when the trait-wide mutation rate is 10-3-10-2, suggesting that this phenomenon is potentially relevant to complex traits with a large mutational target. On the other hand, based on the apparent stability of genetic architecture in many classic examples of local adaptation, our theory suggests that per-trait mutation rates are often relatively low.

Genetics
National Institute of Genetics (JP), University of Calgary (CA)
Alberta Innovates, Alliance de recherche numérique du Canada, Natural Sciences and Engineering Research Council of Canada, Japan Society for the Promotion of Science
Openalex Percentile: Top 11%
Evolution and Genetic Dynamics
2.20
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.