Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays

• Published in: PLoS genetics Vol. 4; no. 8; p. e1000167
• Main Authors: Homer, Nils, Szelinger, Szabolcs, Redman, Margot, Duggan, David, Tembe, Waibhav, Muehling, Jill, Pearson, John V., Stephan, Dietrich A., Nelson, Stanley F., Craig, David W.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.08.2008; Public Library of Science (PLoS)
• Subjects: Computer Simulation; Deoxyribonucleic acid; DNA; Forensic sciences; Genealogy; Genetics; Genetics and Genomics; Genetics and Genomics/Bioinformatics; Genetics and Genomics/Genomics; Genetics and Genomics/Medical Genetics; Genetics and Genomics/Population Genetics; Genetics, Medical; Genome, Human; Genomes; Genomics; Genotype; Humans; Methods; Mitochondrial DNA; Oligonucleotide Array Sequence Analysis - methods; Polymorphism, Single Nucleotide; Studies
• ISSN: 1553-7404; 1553-7390; 1553-7404
• DOI: 10.1371/journal.pgen.1000167

We use high-density single nucleotide polymorphism (SNP) genotyping microarrays to demonstrate the ability to accurately and robustly determine whether individuals are in a complex genomic DNA mixture. We first develop a theoretical framework for detecting an individual's presence within a mixture, then show, through simulations, the limits associated with our method, and finally demonstrate experimentally the identification of the presence of genomic DNA of specific individuals within a series of highly complex genomic mixtures, including mixtures where an individual contributes less than 0.1% of the total genomic DNA. These findings shift the perceived utility of SNPs for identifying individual trace contributors within a forensics mixture, and suggest future research efforts into assessing the viability of previously sub-optimal DNA sources due to sample contamination. These findings also suggest that composite statistics across cohorts, such as allele frequency or genotype counts, do not mask identity within genome-wide association studies. The implications of these findings are discussed.