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Evaluating methods to visualize patterns of genetic differentiation on a landscape.

Geoffrey L House1, Matthew W Hahn1

  • 1Indiana University Bloomington, Bloomington, IN, USA.

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Summary

New methods like unbundled principal components (un-PC) offer a faster, model-free way to visualize genetic differentiation in landscape genetics. This approach compares favorably to existing SpaceMix and EEMS models, especially when migration patterns are complex.

Keywords:
conservation geneticsecological geneticslandscape geneticsphylogeography

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Area of Science:

  • Landscape genetics
  • Population genetics
  • Genomics

Background:

  • Advances in sequencing technology enable landscape genetics research at unprecedented scales.
  • Visualizing genetic differentiation patterns across landscapes is crucial for understanding demographic history and migration.
  • Existing methods like SpaceMix and EEMS have different sensitivities to migration distances, leading to potential discrepancies.

Purpose of the Study:

  • To compare the performance of SpaceMix and EEMS under various simulated migration scenarios.
  • To introduce and evaluate a novel, model-free visualization method, unbundled principal components (un-PC).
  • To provide tools for landscape-scale genetic simulations.

Main Methods:

  • Landscape genetics simulations were created to represent diverse migration scenarios.
  • SpaceMix and EEMS were used to analyze simulated genetic differentiation patterns.
  • Unbundled principal components (un-PC) was developed by integrating PCA with individual locations.

Main Results:

  • Both SpaceMix and EEMS performed well when simulated migration matched their model assumptions.
  • Both methods produced potentially misleading results when simulated migration deviated from their models.
  • Un-PC demonstrated effectiveness with both simulated and empirical data, showing characteristics of both SpaceMix and EEMS.

Conclusions:

  • Model-based methods (SpaceMix, EEMS) can be sensitive to the congruence between their models and empirical migration patterns.
  • Un-PC offers a robust, model-free alternative for visualizing genetic differentiation in landscape genetics.
  • The msLandscape toolset facilitates the creation and analysis of landscape-scale genetic simulations.