Analytical expectations for ancestry junction accumulation in admixed genomes

Area of Science:

• Population Genetics
• Human Evolutionary Dynamics
• Genomic Variation Analysis

Background:

• Human history is marked by complex demographic events, resulting in genetic variation across genomes.
• Admixed populations, originating from distinct ancestral sources, exhibit unique evolutionary dynamics.
• Understanding recent evolutionary trajectories in admixed groups is crucial for human population genetics.

Purpose of the Study:

• To investigate the recent evolutionary dynamics of admixed populations using a novel modeling approach.
• To develop a generalizable model of admixture based on ancestry switches (recombination breakpoints).
• To analytically derive expectations for ancestry switch counts and validate them with simulations and empirical data.

Main Methods:

• Developed a discrete, generalizable model of admixture leveraging ancestry switches.
• Derived analytical expectations for ancestry switch counts based on recombination rate, heterozygosity, and population size.
• Validated theoretical predictions using forward-in-time simulations and empirical data from the 1000 Genomes Project (African American individuals).

Main Results:

• Theoretical predictions closely matched forward-in-time simulation results for ancestry junction accumulation.
• Observed minimal variability in switch counts across simulations, confirming the robustness of the theoretical expectation.
• Model-based switch counts for African American individuals aligned with empirical observations, e.g., ~6 switches per haplotype on chromosome 1.

Conclusions:

• The developed model provides a robust framework for analyzing ancestry patterns in admixed populations.
• Ancestry switches serve as a valuable tool for understanding the interplay of recombination and demography.
• This approach offers a new method to study population history without needing to separate ancestral sources.