Ancient Ancestry Informative Markers for Identifying Fine-Scale Ancient Population Structure in Eurasians

Area of Science:

• Paleogenomics
• Population Genetics
• Bioinformatics

Background:

• Ancient DNA (aDNA) analysis offers insights into past populations, but existing microarray data from modern populations can misrepresent ancient population structures.
• Ancestry informative markers (AIMs) have been used to address this, but their efficacy with aDNA, considering high missingness and haploid data, remains unclear.

Purpose of the Study:

• To define ancient AIMs (aAIMs) and establish a framework for evaluating methods to identify informative markers for aDNA.
• To assess the applicability of AIM-finding methods to aDNA data, accounting for missingness and haploid nature.

Main Methods:

• Development of a novel principal component analysis (PCA)-based method for identifying aAIMs.
• Evaluation of established and novel AIM-finding methods using a framework designed for aDNA characteristics.
• Comparison of aAIMs performance against complete marker sets for population classification and admixture detection.

Main Results:

• The novel PCA-based method for identifying aAIMs significantly outperformed existing methods in classifying ancient individuals and detecting admixed populations.
• In certain scenarios, aAIMs provided more accurate population predictions than using a complete set of genetic markers.
• The study elucidated features of ancient Eurasian population structure and strategies for aAIM identification.

Conclusions:

• The developed aAIMs and the PCA-based identification framework are effective for analyzing ancient population structures from aDNA.
• This work has implications for designing SNP microarrays and interpreting aDNA results, facilitating the testing of primordialist theories.
• Accurate ancient population structure analysis using aAIMs enhances our understanding of human history and migration patterns.