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

Xiangpei Zeng, Ranajit Chakraborty, Jonathan L. King, Bobby LaRue, Rodrigo S. Moura-Neto, Bruce Budowle

Research output: Contribution to journalArticle

14 Scopus citations

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 (FST), 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 FST 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 FST 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.

Original languageEnglish
Pages (from-to)341-352
Number of pages12
JournalInternational journal of legal medicine
Volume130
Issue number2
DOIs
StatePublished - 1 Mar 2016

Keywords

  • 1000 Genomes
  • Ancestry informative markers (AIMs)
  • F
  • HapMap
  • Population differentiation
  • Single nucleotide polymorphisms (SNPs)

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