Abstract

Previous 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.

Genetic variation in modern humans can reveal information about a population’s history and migration patterns. Here, the authors describe the ancestry and geospatial genetic structure of the Netherlands, and demonstrate the utility of haplotype-based covariates in genome-wide association studies.

Details

Title
Dutch population structure across space, time and GWAS design
Author
Byrne, Ross P 1   VIAFID ORCID Logo  ; Wouter, van Rheenen 2   VIAFID ORCID Logo  ; van den Berg Leonard H 2 ; Veldink, Jan H 2   VIAFID ORCID Logo  ; McLaughlin, Russell L 1   VIAFID ORCID Logo 

 Trinity College Dublin, Smurfit Institute of Genetics, Dublin, Republic of Ireland (GRID:grid.8217.c) (ISNI:0000 0004 1936 9705) 
 University Medical Center Utrecht, Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, Utrecht, The Netherlands (GRID:grid.7692.a) (ISNI:0000000090126352) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2441673404
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.