Abstract
The genetic structure of populations is often shaped by processes and events that introduce asymmetries to gene flow between geographic locations. Here, we first develop an algorithm that allows efficient computation of pairwise coalescent times in time-homogeneous models of population structure at migration-drift equilibrium. We then use the algorithm as the foundation for a new method—Fine-Resolution Asymmetric Migration Estimation (FRAME)—to infer asymmetric migration rates in spatial models of population structure. The inferred equilibrium migration rates provide a novel representation of the geographic structure of genetic variation. We assess the method using a variety of simulated histories of gene flow, and apply the method to datasets from poplar trees, North American gray wolves, and human archaeogenetic samples, revealing complex asymmetric migration signals and providing a more refined view of the geographic structure of genetic variation.
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Acknowledgements
FRAME is built upon the FEEMS codebase, which was originally developed by Joe Marcus and Wooseok Ha, and further expanded upon and developed by Vivaswat Shastry. We would further like to thank Vivaswat Shastry for helpful conversations and for advice on software development. We also thank members of the Novembre Lab collectively for input on figure design.
Funding
The research was supported by funding from NIH NIGMS grant R35-GM149521 to JN.
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Shen, H., Novembre, J. FRAME: Fine-Resolution Asymmetric Migration Estimation.
Nat Commun (2026). https://doi.org/10.1038/s41467-026-74129-2
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DOI: https://doi.org/10.1038/s41467-026-74129-2
Source: Ecology - nature.com
