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Expanding Beyond the Current Core STR Loci: An Exploration of 73 STR Markers With Increased Diversity for Enhanced DNA Mixture Deconvolution

NCJ Number
253964
Annotation
Since current approaches to mixture deconvolution of complex biological samples at times do not have the capability to resolve component contributors in DNA evidence, the current study sought additional short tandem repeat (STR) loci that may improve the forensic genetic analysis of mixtures.
Abstract
This study presents exploratory data of a multiplex comprised of 73 highly polymorphic STRs (referred herein as the 73Plex) that were selected because of their high diversity due to sequence variation. These STRs (or a subset of them) may be considered as candidates that may augment current core markers capabilities for DNA mixture deconvolution. Population genetics analyses were performed for each locus using DNA samples from 451 individuals comprising three U.S. populations. Sequence-based heterozygosities ranged from 72 percent to 98 percent, where only two loci (D10A97 and D6A7) fell below 80 percent. Mixture deconvolution capabilities for two-person mixtures were assessed based on complete allele resolution per locus (i.e., four alleles observed) of pairwise mixtures using in silico methods. A subset of 20 highly informative loci (referred herein as the 20Plex) from the 73Plex was compared to the 20 CODIS core loci on all population samples with full DNA profiles for both panels (i.e., no locus dropout; n=443). Based on proportion of loci displaying four alleles, the 20Plex outperformed the CODIS core loci with increases of 82.6 percent and 89.3 percent using length-based and sequence-based alleles, respectively. A combination of 17 STR from the 20Plex and 3 CODIS loci gave the highest capacity for resolving allelic components per locus. These data illustrate the increased value of utilizing sequenced-based alleles of additional STR loci. Furthermore, there are a number of candidate STR loci that could notably augment the current core STR loci and enhance mixture interpretation capabilities. (publisher abstract modified)
Date Created: January 28, 2021