A multi-ancestry genetic reference for the Quebec population
McClelland PPapers in this archive, Femerling GPapers in this archive, Laflamme RPapers in this archive, Mejia-Garcia APapers in this archive, Sayahian Dehkordi MPapers in this archive, Xiao HPapers in this archive, Diaz-Papkovich APapers in this archive, Pelletier JPapers in this archive, Grenier JCPapers in this archive, Lo KSPapers in this archive, Anderson-Trocmé LPapers in this archive, Bellavance JPapers in this archive, Chapdelaine VPapers in this archive, Gagnon GPapers in this archive, De Mori APapers in this archive, Martinez GPapers in this archive, Mohler KPapers in this archive, de Malliard TPapers in this archive, Labbé CPapers in this archive, Labrecque MPapers in this archive, Montpetit APapers in this archive, Spiegelman DPapers in this archive, Rouleau GAPapers in this archive, Théroux JFPapers in this archive, Zhou HPapers in this archive, Girard SLPapers in this archive, Hussin JGPapers in this archive, Laberge AMPapers in this archive, Bhérer CPapers in this archive, Tetreault MPapers in this archive, Gagliano Taliun SAPapers in this archive, Taliun DPapers in this archive, Gravel SPapers in this archive, Lettre GPapers in this archive
Abstract
While international efforts have characterized genetic variation in millions of individuals, the interplay of environmental, social, cultural and genetic factors is poorly understood for most worldwide populations. The province of Quebec in Canada has been the site of numerous genetic studies, often focusing on Mendelian diseases in founder sub-populations. Here, we analyze genome-wide genotyped variation in 29,337 Quebec residents from the multi-ancestry population-based cohort CARTaGENE (CaG) who provided DNA samples. We also sequence the whole-genome of 2,173 CaG participants with four grandparents born in Canada (n = 1879), Haiti (n = 163) and Morocco (n = 131). We use this genetic information to gain insight into Quebec’s demography and to help interpret the potential significance of variants identified in clinically important genes (e.g., SPG7 implicated in hereditary spastic paraplegia). We validate an imputation panel constructed by phasing the CaG whole-genome sequence data and find, using genome-wide association studies (GWAS) of 42 clinically relevant traits, that it increases the number of associated loci by ~7% when compared to results obtained after imputation with the larger TOPMed imputation panel. We provide allele frequency information and GWAS results through dedicated and publicly available websites. The genetic data, paired with phenotypic and environmental information, is available for global research use.
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