Dutch population structure across space, time and GWAS design

• DOI: 10.1038/s41467-020-18418-4
• Publication Date: 2020-09-11T10:09:21Z
• Authors: Ross P. Byrne; Wouter van Rheenen; ; Leonard H. van de...; Jan H. Veldink; Russell L. McLaug...
• Keywords: Gene Flow; 0301 basic medicine; Genome; Geography; Models, Genetic; Science; Q; Genetic Variation; Emigration and Immigration; Middle Aged; Polymorphism, Single Nucleotide; Article; White People; 03 medical and health sciences; Genetics, Population; Haplotypes; Case-Control Studies; Ethnicity; Cluster Analysis; Humans; Genome-Wide Association Study; Netherlands

AbstractPrevious genetic studies have identified local population structure within the Netherlands; however their resolution is limited by use of unlinked markers and absence of external reference data. Here we apply advanced haplotype sharing methods (ChromoPainter/fineSTRUCTURE) to study fine-grained population genetic structure and demographic change across the Netherlands using genome-wide single nucleotide polymorphism data (1,626 individuals) with associated geography (1,422 individuals). We identify 40 haplotypic clusters exhibiting strong north/south variation and fine-scale differentiation within provinces. Clustering is tied to country-wide ancestry gradients from neighbouring lands and to locally restricted gene flow across major Dutch rivers. North-south structure is temporally stable, with west-east differentiation more transient, potentially influenced by migrations during the middle ages. Despite superexponential population growth, regional demographic estimates reveal population crashes contemporaneous with the Black Death. Within Dutch and international data, GWAS incorporating fine-grained haplotypic covariates are less confounded than standard methods.