Using the ancestral recombination graph to study the history of rare variants in founder populations

Abstract

Gene genealogies represent the ancestry of a sample and are often encoded as ancestral recombination graphs (ARG). It has recently become possible to infer these gene genealogies from sequencing or genotyping data and use them for evolutionary and statistical genetics. Unfortunately, inferred gene genealogies can be noisy and subject to biases, making their applications more challenging. This project aims to study the application of ARG methods to systematically impute and trace the transmission of all disease variants in founder populations where long-shared haplotypes allow for accurate timing of relatedness. We applied these methods to the population of Quebec, where multiple founder events led to an uneven distribution of pathogenic variants across regions and where extensive population pedigrees are available. We validated our approach with nine founder mutations for the SLSJ region, demonstrating high accuracy for mutation age, imputation, and regional frequency estimation. Moreover, we showed that this subset of high-quality carriers is sufficient to capture previously described associations with pathogenic variants in the LPL gene. This method systematically characterizes rare variants in founder populations, establishing a fast and accurate approach to inform genetic screening programs.