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DNA Microarray as a Tool in Establishing Genetic Relatedness - Current Status and Future Prospects

NCJ Number
239319
Journal
Forensic Science International: Genetics Volume: 6 Issue: 3 Dated: May 2012 Pages: 322-329
Author(s)
Daniel Kling; Jenny Welander; Andreas Tillmar; Oivind Skare; Thore Egeland; Gunilla Holmlund
Date Published
May 2012
Length
8 pages
Annotation

The aim of this study was to determine whether single nucleotide polymorphism (SNP) microarrays could be used as a tool in establishing genetic relationships where current molecular genetic methods are not sufficient.

Abstract

In the past decades, microarray technology has definitely put an edge to the field of genetic research. The authors aim was to determine whether single nucleotide polymorphism (SNP) microarrays could be used as a tool in establishing genetic relationships where current molecular genetic methods are not sufficient. The authors used the Genechip, Affymetrix GenomeWide SNP Array 6.0, which detects more than 900,000 SNP markers dispersed throughout the human genome. The intention was to find a good selection of SNP markers that could be used for statistical evaluation of relatedness in a forensic setting. The authors conducted pairwise comparisons in the R-package FEST as well as pedigree comparisons in Merlin. The methods were applied on two separate families, where relationships as distant as 3rd cousins were known. In addition, a question about a possible common ancestry between the two families was tested. Relationships as distant as 2nd cousins could be readily distinguished both from unrelated and other, genetically, closer relationships. This was achieved with a selection of 5,774 markers, where each pair of markers was separated by a genetic distance of at least 0.5cM (centiMorgan). When considering 3rd cousins, and more distant relationships, the number of markers needs to be extended, consequently decreasing the genetic distance between the markers. However, inclusion of a too large number of markers presents new challenges and our results imply that the use of too dense sets of markers always yields the highest probability for the genetically closest relationship hypothesis. Simulations confirm that this is most probably caused by the fact that the computational model assumes linkage equilibrium between markers, a problem that will be further evaluated. The results do however suggest that SNP-data derived from microarrays are well suited for kinship determination provided linkage disequilibrium is properly accounted for. (Published Abstract)