Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10533096 | Analytical Biochemistry | 2005 | 17 Pages |
Abstract
In traditional approaches, mitochondrial DNA (mtDNA) variation is exploited for forensic identity testing by sequencing the two hypervariable regions of the human mtDNA control region. To reduce time and labor, single nucleotide polymorphism (SNP) assays are being sought to possibly replace sequencing. However, most SNP assays capture only a portion of the total variation within the desired regions, require a priori knowledge of the position of the SNP in the genome, and are generally not quantitative. Furthermore, with mtDNA, the clustering of SNPs complicates the design of SNP extension primers or hybridization probes. This article describes an automated electrospray ionization mass spectrometry method that can detect a number of clustered SNPs within an amplicon without a priori knowledge of specific SNP positions and can do so quantitatively. With this technique, the base composition of a PCR amplicon, less than 140 nucleotides in length, can be calculated. The difference in base composition between two samples indicates the presence of an SNP. Therefore, no post-PCR analytical construct needs to be developed to assess variation within a fragment. Of the 2754 different mtDNA sequences in the public forensic mtDNA database, nearly 90% could be resolved by the assay. The mass spectrometer is well suited to characterize and quantitate heteroplasmic samples or those containing mixtures. This makes possible the interpretation of mtDNA mixtures (as well as mixtures when assaying other SNPs). This assay can be expanded to assess genetic variation in the coding region of the mtDNA genome and can be automated to facilitate analysis of a large number of samples such as those encountered after a mass disaster.
Keywords
Related Topics
Physical Sciences and Engineering
Chemistry
Analytical Chemistry
Authors
Thomas A. Hall, Bruce Budowle, Yun Jiang, Lawrence Blyn, Mark Eshoo, Kristin A. Sannes-Lowery, Rangarajan Sampath, Jared J. Drader, James C. Hannis, Patina Harrell, Vivek Samant, Neill White, David J. Ecker, Steven A. Hofstadler,