Global analysis of population stratification using a smart panel of 27 continental ancestry-informative SNPs. (July 2018)

• Record Type: Journal Article
• Authors: Jiang, Li; Wei, Yi-Liang; Zhao, Lei; Li, Na; Liu, Tao; Liu, Hai-Bo; Ren, Li-Jie; Li, Jiu-Ling; Hao, Hui-Fang; Li, Qing; Li, Cai-Xia
• Is Part Of: Forensic science international. Volume 35(2018)
• Page Start: e10
• Page End: e12
• Publication Date: 2018-07
• Subjects: Population stratification -- Ancestry-informative markers -- Single nucleotide polymorphism; Forensic genetics -- Periodicals; Génétique légale -- Périodiques; Forensic genetics; Electronic journals; Periodicals; 614.1
• DOI: 10.1016/j.fsigen.2018.05.006
• Languages: English
• ISSNs: 1872-4973

Abstract

Highlights: A smart panel of 27 autosomal SNPs to infer three continental ancestry populations is developed. A high-coverage reference database of 110 global populations is gathered. The discrimination power of the panel was re-evaluated using four continental ancestry groups. High-resolution in estimating ancestry compositions and distinguishing individual origins. Abstract: Over the last decade, several panels of ancestry-informative markers have been proposed for the analysis of population genetic structure. The differentiation efficiency depends on the discriminatory ability of the included markers and the reference population coverage. We previously developed a small set of 27 autosomal single nucleotide polymorphisms (SNPs) for analyzing African, European, and East Asian ancestries. In the current study, we gathered a high-coverage reference database of 110 populations (10, 350 individuals) from across the globe. The discrimination power of the panel was re-evaluated using four continental ancestry groups (as well as Indigenous Americans). We observed that all the 27 SNPs demonstrated stratified population specificity leading to a striking ancestral discrimination. Five markers (rs728404, rs7170869, rs2470102, rs1448485, and rs4789193) showed differences (δ > 0.3) in the frequency profiles between East Asian and Indigenous American populations. Ancestry components of all involved populations were accurately accessed compared with those from previous genome-wide analyses, thereafter achieved broadly population separation. Thus, our ancestral inference panel of a small number of highly informative SNPs in combination with a large-scale reference database provides a high-resolution in estimating ancestry compositions and distinguishing individual origins. We propose extensive usage in biomedical studies and forensics.