Dating genomic variants and shared ancestry in population-scale sequencing data

Area of Science:

• Evolutionary biology
• Population genetics
• Genomics

Background:

• The origin and evolutionary trajectory of genetic variants are fundamental to understanding species evolution.
• While genetic variation frequency and impact are studied, variant evolutionary histories remain largely unexplored.

Purpose of the Study:

• To develop and validate a novel nonparametric method for estimating the age of genetic variants from large-scale sequencing data.
• To create a comprehensive database of human single-nucleotide polymorphism (SNP) ages and explore their relationship with frequency and geographical distribution.

Main Methods:

• Developed a nonparametric statistical approach to estimate variant origin dates.
• Applied the method to human genomic diversity data from public resources.
• Validated the approach through simulations to ensure accuracy and robustness.

Main Results:

• Estimated the age of over 45 million single-nucleotide polymorphisms (SNPs) in the human genome.
• Released the Atlas of Variant Age as a publicly accessible online database.
• Characterized the relationship between variant age, frequency, and geographical location.

Conclusions:

• Variant age is a valuable metric for interpreting functional and selective importance.
• Allele age estimates enable rapid inference of shared ancestry and genealogical relationships.
• The developed method and database provide powerful tools for exploring human population evolutionary history.