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Visualizing spatial population structure with estimated effective migration surfaces

Nature Genetics volume 48, pages 94–100 (2016)Cite this article

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Abstract

Genetic data often exhibit patterns broadly consistent with 'isolation by distance'—a phenomenon where genetic similarity decays with geographic distance. In a heterogeneous habitat, this may occur more quickly in some regions than in others: for example, barriers to gene flow can accelerate differentiation between neighboring groups. We use the concept of 'effective migration' to model the relationship between genetics and geography. In this paradigm, effective migration is low in regions where genetic similarity decays quickly. We present a method to visualize variation in effective migration across a habitat from geographically indexed genetic data. Our approach uses a population genetic model to relate effective migration rates to expected genetic dissimilarities. We illustrate its potential and limitations using simulations and data from elephant, human and Arabidopsis thaliana populations. The resulting visualizations highlight important spatial features of population structure that are difficult to discern using existing methods for summarizing genetic variation.

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Figure 1: A schematic overview of EEMS (Estimated Effective Migration Surfaces), using African elephant data for illustration.
Figure 2: Simulations comparing EEMS and PCA.
Figure 3: Simulations illustrate that EEMS infers effective migration rates rather than actual steady-state migration rates.
Figure 4: EEMS analysis of African elephant data.
Figure 5: EEMS analysis of human population structure in Western Europe and in sub-Saharan Africa.
Figure 6: EEMS analysis of A. thaliana data from the RegMap panel.

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Acknowledgements

We thank S. Wasser for access to the African elephant data and I. Moltke for compiling the human data set from sub-Saharan Africa. We also thank B. McRae for helpful discussions on resistance distances. This work was supported in part by US National Institutes of Health (NIH) grant U01 CA198933 to J.N. and grant HG02585 to M.S.

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Authors and Affiliations

  1. Department of Statistics, The University of Chicago, Chicago, Illinois, USA

    Desislava Petkova & Matthew Stephens

  2. Wellcome Trust Centre for Human Genetics, Oxford, UK

    Desislava Petkova

  3. Department of Human Genetics, The University of Chicago, Chicago, Illinois, USA.,

    John Novembre & Matthew Stephens

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  1. Desislava Petkova
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Contributions

M.S. and J.N. conceived the project. D.P., J.N. and M.S. developed and refined methods. D.P. implemented methods. D.P., J.N. and M.S. wrote the manuscript.

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Correspondence to John Novembre or Matthew Stephens.

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The authors declare no competing financial interests.

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Petkova, D., Novembre, J. & Stephens, M. Visualizing spatial population structure with estimated effective migration surfaces. Nat Genet 48, 94–100 (2016). https://doi.org/10.1038/ng.3464

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