Dutch population structure across space, time and GWAS design

被引:19
作者
Byrne, Ross P. [1 ]
van Rheenen, Wouter [2 ]
van den Berg, Leonard H. [2 ]
Veldink, Jan H. [2 ]
McLaughlin, Russell L. [1 ]
机构
[1] Trinity Coll Dublin, Smurfit Inst Genet, Dublin D02 DK07, Ireland
[2] Univ Med Ctr Utrecht, Brain Ctr Rudolf Magnus, Dept Neurol & Neurosurg, NL-3584 CX Utrecht, Netherlands
基金
爱尔兰科学基金会; 欧洲研究理事会;
关键词
SCALE GENETIC-STRUCTURE; IDENTITY; ASSOCIATION; MIGRATION; VARIANTS; DESCENT; RISK; LD;
D O I
10.1038/s41467-020-18418-4
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
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页数:11
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