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

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• 作者：Xiangpei Zeng ; Ranajit Chakraborty…
• 关键词：Ancestry informative markers (AIMs) ; Single nucleotide polymorphisms (SNPs) ; Population differentiation ; HapMap ; 1000 Genomes ; F ST
• 刊名：International Journal of Legal Medicine
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：130
• 期：2
• 页码：341-352
• 全文大小：2,012 KB
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• 作者单位：Xiangpei Zeng (1)
  Ranajit Chakraborty (1)
  Jonathan L. King (1)
  Bobby LaRue (1)
  Rodrigo S. Moura-Neto (2) (3)
  Bruce Budowle (1) (4)
  
  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
  2. Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
  3. Instituto Nacional de Metrologia, Qualidade e Tecnologia, Duque de Caxias, Brazil
  4. Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia
  
• 刊物类别：Medicine
• 刊物主题：Medicine & Public Health
  Forensic Medicine
  Medical Law
  Medicine/Public Health, general
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1437-1596

文摘

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.