Nature CommunicationsGenetic & Genomic MedicinePeer-reviewed journal article
A multi-ancestry genetic reference for the Quebec population
Peyton McClellandiD, Georgette FemerlingiD, Rose Laflamme, Alejandro Mejia-GarciaiD, Mohadese Sayahian Dehkordi, Hongyu XiaoiD, Alex Diaz-PapkovichiD, Justin PelletieriD, Jean‐Christophe GrenieriD, Ken Sin LoiD, Luke Anderson-TrocméiD, Justin BellavanceiD, Vincent ChapdelaineiD, Geneviève GagnoniD, Annelie De Mori, Gerardo Martinez, Kristen Mohler, Thibault de Malliard, Catherine LabbéiD, Marjorie LabrecqueiD, Alexandre Montpetit, Dan SpiegelmaniD, Guy Armand RouleauiD, Jean‐François Théroux, Hufeng ZhouiD, , Guillaume LettreiD
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 individual Mendelian diseases in founder sub-populations. Here, we profiled and analyzed genome-wide genotyped variation in 29,337 Quebec residents from the large population-based cohort CARTaGENE (CaG), including rich phenotype and environmental data. We also sequenced the whole-genome of 2,173 CaG participants, including 163 and 132 individuals with grandparents born in Haiti and Morocco, respectively. We use this genetic information to gain insight into Quebecs demography and to help interpret the potential significance of variants identified in clinically important genes. We built an imputation panel by phasing the CaG whole-genome sequence data and showed, using genome-wide association studies (GWAS), how it improves the discovery of phenotype-genotype associations in this population. We provide allele frequency information and GWAS results through dedicated and publicly available websites. The genetic data, paired with phenotypic and environmental information, is also available for research use upon scientific and ethical review.
- organism: human
- assay: whole-genome sequencing
- research focus: GWAS / association mapping
- approach: statistical model
- approach: matrix factorization
- Citations
- 8
- FWCI
- 15.83
- Field percentile
- top 1%
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