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Selection of highly informative SNP markers for population affiliation of major US populations

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Abstract

Ancestry informative markers (AIMs) can be used to detect and adjust for population stratification and predict the ancestry of the source of an evidence sample. Autosomal single nucleotide polymorphisms (SNPs) are the best candidates for AIMs. It is essential to identify the most informative AIM SNPs across relevant populations. Several informativeness measures for ancestry estimation have been used for AIMs selection: absolute allele frequency differences (δ), F statistics (F ST), and informativeness for assignment measure (In). However, their efficacy has not been compared objectively, particularly for determining affiliations of major US populations. In this study, these three measures were directly compared for AIMs selection among four major US populations, i.e., African American, Caucasian, East Asian, and Hispanic American. The results showed that the F ST panel performed slightly better for population resolution based on principal component analysis (PCA) clustering than did the δ panel and both performed better than the In panel. Therefore, the 23 AIMs selected by the F ST measure were used to characterize the four major American populations. Genotype data of nine sample populations were used to evaluate the efficiency of the 23-AIMs panel. The results indicated that individuals could be correctly assigned to the major population categories. Our AIMs panel could contribute to the candidate pool of AIMs for potential forensic identification purposes.

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Authors and Affiliations

  1. Institute of Applied Genetics, Department of Molecular and Medical Genetics, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX, 76107, USA

    Xiangpei Zeng, Ranajit Chakraborty, Jonathan L. King, Bobby LaRue & Bruce Budowle

  2. Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil

    Rodrigo S. Moura-Neto

  3. Instituto Nacional de Metrologia, Qualidade e Tecnologia, Duque de Caxias, Brazil

    Rodrigo S. Moura-Neto

  4. Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia

    Bruce Budowle

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  1. Xiangpei Zeng
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  2. Ranajit Chakraborty
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Correspondence to Xiangpei Zeng.

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Supplemental Table 1

The top AIMs selected by three measures from ASW and CEU after H-W and LD selection. The top thirty SNPs were reduced to 26, 26, 26 AIMs by δ, F ST, and In, respectively. 1–3 indicated the SNPs that were in LD, and the highlighted ones (Bold and Italic) were removed (XLSX 12 kb)

Supplemental Table 2

The top AIMs selected by three measures from ASW and CHD after H-W and LD selection. The top thirty SNPs were reduced to 24, 25, 26 AIMs by δ, F ST, and In, respectively. 1–5 indicated the SNPs that were in LD, and the highlighted ones (Bold and Italic) were removed (XLSX 13 kb)

Supplemental Table 3

The top AIMs selected by three measures from ASW and MEX after H-W and LD selection. The top thirty SNPs were reduced to 27, 26, 25 AIMs by δ, F ST, and In, respectively. 1–4 indicated the SNPs that were in LD, and the highlighted ones (Bold and Italic) were removed (XLSX 13 kb)

Supplemental Table 4

The top AIMs selected by three measures from CEU and CHD after H-W and LD selection. The top thirty SNPs were reduced to 27, 27, 29 AIMs by δ, F ST, and In, respectively. 1–3 indicated the SNPs that were in LD, and the highlighted ones (Bold and Italic) were removed (XLSX 14 kb)

Supplemental Table 5

The top AIMs selected by three measures from CEU and MEX after H-W and LD selection. The top thirty SNPs were reduced to 26, 24, 22 AIMs by δ, F ST, and In, respectively. 1–6 indicated the SNPs that were in LD, and the highlighted ones (Bold and Italic) were removed (XLSX 13 kb)

Supplemental Table 6

The top AIMs selected by three measures from CHD and MEX after H-W and LD selection. The top thirty SNPs were reduced to 22, 24, 24 AIMs by δ, F ST, and In, respectively. 1–5 indicated the SNPs that were in LD, and the highlighted ones (Bold and Italic) were removed (XLSX 13 kb)

Supplemental Table 7

The minimum number of markers to distinguish any two populations identified by three measures (δ, F ST and In) (XLSX 12 kb)

Supplemental Table 8

The correlation coefficients of PC1 and PC2 values among δ, F ST and In panels (XLSX 10 kb)

Supplemental Table 9

Ancestry prediction of HapMap individuals that fell outside the 95 % confidence interval of four major US populations (XLSX 13 kb)

Supplemental Table 10

Ancestry prediction of 1000 Genomes individuals that fell outside the 95 % confidence interval of four major US populations. All CLM individuals were listed, because CLM contains individuals from three populations (XLSX 20 kb)

Supplemental Table 11

Summary of SNPs contained in ten AIMs panels (XLSX 29 kb)

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Zeng, X., Chakraborty, R., King, J.L. et al. Selection of highly informative SNP markers for population affiliation of major US populations. Int J Legal Med 130, 341–352 (2016). https://doi.org/10.1007/s00414-015-1297-9

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