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bioRxiv · 10.1101/2022.07.20.500680

On the Genes, Genealogies, and Geographies of Quebec

Abstract

Population genetic models only provide coarse representations of real-world ancestry. We use a pedigree compiled from four million parish records and genotype data from 2,276 French and 20,451 French Canadian (FC) individuals, to finely model and trace FC ancestry through space and time. The loss of ancestral French population structure and the appearance of spatial and regional structure highlights a wide range of population expansion models. Geographic features shaped migrations throughout, and we find enrichments for migration, genetic and genealogical relatedness patterns within river networks across Quebec regions. Finally, we provide a freely accessible simulated whole-genome sequence dataset with spatiotemporal metadata for 1,426,749 individuals reflecting intricate FC population structure. Such realistic populations-scale simulations provide new opportunities to investigate population genetics at an unprecedented resolution. Lay SummaryWe all share common ancestors ranging from a couple generations ago to hundreds of thousands of years ago. The genetic differences between individuals today mostly depends on how closely related they are. The only problem is that the actual genealogies that relate all of us are often forgotten over time. Some geneticists have tried to come up with simple models of our shared ancestry but they dont really explain the full, rich history of humanity. Our study uses a multi-institutional project in Quebec that has digitized parish records into a single unified genealogical database that dates back to the arrival of the first French settlers four hundred years ago. This genealogy traces the ancestry of millions of French-Canadian and we have used it to build a very high resolution genetic map. We used this genetic map to study in detail how certain historical events, and landscapes have influenced the genomes of French-Canadians today. One-Sentence SummaryWe present an accurate and high resolution spatiotemporal model of genetic variation in a founder population.

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BibTeXRIS

Anderson-Trocme, L., Nelson, D., Zabad, S., Diaz-Papkovich, A., Baya, N., Touvier, M., Jeffery, B., Dina, C., Vezina, H., Kelleher, J., Gravel, S.. 2022-07-21. On the Genes, Genealogies, and Geographies of Quebec. https://doi.org/10.1101/2022.07.20.500680

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