Effect of genetic divergence in identifying ancestral origin using HAPAA

Area of Science:

• Genetics
• Population Genetics
• Bioinformatics

Background:

• Admixed individuals' genomes are mosaics of chromosomal blocks reflecting ancestral population variations.
• Inferring ancestral origins relies on analyzing polymorphisms in admixed individuals against reference populations.

Purpose of the Study:

• To introduce HAPAA (Hidden Markov Model-based analysis of polymorphisms in admixed ancestries), a novel computational method for accurate ancestry inference.
• To develop a methodology for assessing the impact of genetic divergence and admixture timing on inference accuracy.
• To explore the boundaries of ancestry inference, particularly in closely related populations.

Main Methods:

• HAPAA models allelic and haplotypic variation within ancestral populations.
• The method incorporates linkage disequilibrium to capture correlations, enhancing accuracy.
• A new methodology evaluates inference accuracy based on population divergence and admixture time.

Main Results:

• HAPAA demonstrates significantly improved accuracy in inferring ancestral haploblock origins.
• The study quantifies the influence of genetic divergence and admixture timing on inference outcomes.
• The limits of ancestry inference were successfully explored, even for closely related populations.

Conclusions:

• HAPAA provides a powerful and accurate tool for human ancestry inference.
• Understanding population divergence and admixture timing is crucial for refining genetic ancestry estimations.
• This work advances the field of population genetics by enabling more precise analyses of admixed genomes.