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. 2012 May 20;44(6):725-31.
doi: 10.1038/ng.2285.

A model-based approach for analysis of spatial structure in genetic data

Wen-Yun Yang  1 , John Novembre, Eleazar Eskin, Eran Halperin
Affiliations

A model-based approach for analysis of spatial structure in genetic data

Wen-Yun Yang et al. Nat Genet. .

Abstract

Characterizing genetic diversity within and between populations has broad applications in studies of human disease and evolution. We propose a new approach, spatial ancestry analysis, for the modeling of genotypes in two- or three-dimensional space. In spatial ancestry analysis (SPA), we explicitly model the spatial distribution of each SNP by assigning an allele frequency as a continuous function in geographic space. We show that the explicit modeling of the allele frequency allows individuals to be localized on the map on the basis of their genetic information alone. We apply our SPA method to a European and a worldwide population genetic variation data set and identify SNPs showing large gradients in allele frequency, and we suggest these as candidate regions under selection. These regions include SNPs in the well-characterized LCT region, as well as at loci including FOXP2, OCA2 and LRP1B.

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Figures

Figure 1
Figure 1
Examples of the allele frequency slope model. (a) Flat slope. A SNP with nearly constant allele frequency in all regions of the map. (b) Medium slope. A SNP with gradual allele frequency change. (c) Steep slope. A SNP with a sharp frequency change.
Figure 2
Figure 2
Model-based mapping convergence with random initialization. Colors represent the true country of origin of the individual (also represented by country internet code). (a–d) A map generated by SPA. Iteration 1 starts with random positioning of individuals (a). By iteration 4, the northern and southern populations are separated (b). By iteration 7, the positioning of individuals is close to convergence (c). In iteration 10, individuals have reached their final positions (d). (e) A map generated by PCA. (f) Map of Europe.
Figure 3
Figure 3
Mapping spatial structure on a globe using HGDP data. Different colors represent different continents. (a) Africa-Asia-Europe-Oceania view. (b) North Pole view. (c) Atlantic view.
Figure 4
Figure 4
The distribution of SPA scores representing allele frequency gradients. The marked positions correspond to genes discussed in the text.
Figure 5
Figure 5
Selection results of six methods in two chromosomes. The SPA, FST and Bayenv methods were run across the POPRES data set, and the iHS approach used HapMap Europe data. The plot is for 2% of POPRES SNPs and 1% of HapMap Europe SNPs. (a,b) Results are shown for chromosome 2 (a) and chromosome 7 (b).
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