Evaluating 130 Microhaplotypes Across a Global Set of 83 Populations

• NCJ Number: 252252
• Journal: Forensic Science International: Genetics Volume: 29 Dated: July 2017 Pages: 29-37
• Author(s): Kenneth K. Kidd; William C. Sneed; Andrew J. Pakstis; Daniele S. Podini; Robert Lagacé; Joseph Chang; Sharon Wootton; Eva Haigh; Usha Soundararaian
• Date Published: July 2017
• Length: 9 pages
• Grant Number(s): 2013-DN-BX-K023; 2014-DN-BX-K030
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical); Program/Project Evaluation
• Award: Continued Development of FROG-kb: A Forensic Resource/Reference on Genetics knowledge base; High resolution SNP panels for forensic identification of ancestry, family, and phenotype.

Annotation

Primarily to aid in mixture deconvolution and avoid the issue of stutter, the project reported in this article has begun to investigate a new type of forensic marker, microhaplotype loci, that will provide useful information on mixtures of DNA and on ancestry when typed using massively parallel sequencing (MPS).

Abstract

Currently, the primary DNA markers used in forensics are short tandem repeat (STR) polymorphisms (STRPs), initially selected because they are highly polymorphic; however, the increasingly common need to deal with samples with a mixture of DNA from two or more individuals sometimes is complicated by the inherent stutter involved with PCR amplification, especially in strongly unbalanced mixtures when the minor component coincides with the stutter range of the major component. Also, the STRPs in use provide little evidence of ancestry of a single source sample beyond broad "continental" resolution. Methodologies for analyzing DNA have become much more powerful in recent years. Massively parallel sequencing (MPS) is a new method being considered for routine use in forensics. Using MPS, the current study identified 130 loci and estimated their haplotype (allele) frequencies in 83 different population samples. Many of these loci are shown to be highly informative for individual identification and for mixture identification and deconvolution. (Publisher abstract modified)