Estimating population-level coancestry coefficients by an admixture F model.

Area of Science:

• Population Genetics
• Molecular Ecology
• Evolutionary Biology

Background:

• Estimating population-level coancestry coefficients is crucial for understanding genetic structure.
• Existing models like the F model have limitations in distinguishing causes of genetic differentiation.
• Genetic differentiation can arise from factors such as small population size or restricted migration.

Purpose of the Study:

• To develop and validate an admixture F model (AFM) for more nuanced estimation of population-level coancestry coefficients.
• To enable disentangling the effects of small population size versus lack of migration on genetic differentiation.
• To provide a more informative alternative to the summary statistic F(ST) for evolutionary inference.

Main Methods:

• Development of an admixture F model (AFM) based on neutral molecular markers.
• Implementation of a Bayesian estimation scheme for fitting the AFM to multiallelic data.
• Validation using simulated datasets and empirical data from ninespine sticklebacks and common shrews.

Main Results:

• The AFM successfully estimates population-level coancestry coefficients.
• The model effectively distinguishes between genetic differentiation caused by small population size and that caused by lack of migration.
• Parameterization of the AFM provides richer information on evolutionary history compared to F(ST).

Conclusions:

• The admixture F model (AFM) offers a significant advancement in understanding population genetic structure.
• AFM provides a more detailed understanding of the evolutionary processes shaping genetic differentiation.
• The developed methods are available in the R package RAFM for broader application.