mixKIN: An ancestry-aware kinship estimation method for low coverage genomes
Genetic kinship analysis provides insights into the social and biological organization of past populations. However, kinship estimation from low-coverage genomes, which are common in ancient DNA (aDNA) studies, remains challenging, particularly in genetically heterogeneous or admixed populations. Approaches that assume a homogeneous background relatedness can bias estimates when individuals have…
Kinship analysis using genetic data can reveal information about the social and biological makeup of ancient populations. However, determining kinship from low-coverage genomes, a common occurrence in ancient DNA studies, is difficult, especially when dealing with genetically diverse or mixed populations. Traditional methods often assume a homogeneous relatedness background, which can lead to biased estimates when individuals have different ancestries.
To address this issue, researchers have developed mixKIN, a method specifically designed for ancestry-aware kinship estimation from low-coverage genomes.
Instead of relying on a single baseline for mismatch comparisons across all pairs, mixKIN calculates a pair-specific baseline by considering both within-population diversity and between-population divergence, factoring in the ancestry proportions of both individuals involved in each pair. The performance of mixKIN was evaluated and compared against correctKin, RelateAdmix, and READv2, a widely used approach that assumes a homogeneous population background.
To test the methods, extensive pedigree simulations were conducted across various demographic scenarios, such as admixture between distant populations, intra-population heterogeneity, and genetic outliers, at coverage levels ranging from 1x to 0.03x.
The results showed that mixKIN performed better in admixed and heterogeneous scenarios, while maintaining comparable performance in homogeneous populations. It was able to evaluate relationships up to the third degree. In a real-world application using data from a medieval English cemetery, mixKIN successfully recovered relationships involving an individual with both West African and European ancestry without requiring manual adjustments for admixture.
These findings demonstrate the practical benefits of ancestry-aware mismatch normalization for improving kinship estimation and preserving genetically diverse individuals in kinship studies.
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