DNA mixtures with two or more contributors are a prevalent form of biological evidence. Mixture interpretation is complicated by the possibility of different genotype combinations that can explain the short tandem repeat (STR) data. Current human review simplifies this interpretation by applying thresholds to qualitatively treat STR data peaks as all-or-none events and assigning allele pairs equal likelihood. Computer review, however, can work instead with all the quantitative data to preserve more identification information. The present study examined the extent to which quantitative computer interpretation could elicit more identification information than human review from the same adjudicated two-person mixture data. The base 10 logarithm of a DNA match statistic is a standard information measure that permits such a comparison. On eight mixtures having two unknown contributors, we found that quantitative computer interpretation gave an average information increase of 6.24 log units (min = 2.32, max = 10.49) over qualitative human review. On eight other mixtures with a known victim reference and one unknown contributor, quantitative interpretation averaged a 4.67 log factor increase (min = 1.00, max = 11.31) over qualitative review. This study provides a general treatment of DNA interpretation methods (including mixtures) that encompasses both quantitative and qualitative review. Validation methods are introduced that can assess the efficacy and reproducibility of any DNA interpretation method. An in-depth case example highlights 10 reasons (at 10 different loci) why quantitative probability modeling preserves more identification information than qualitative threshold methods. The results validate TrueAllele(®) DNA mixture interpretation and establish a significant information improvement over human review.
The attack on the World Trade Center on 9/11/2001 challenged current approaches to forensic DNA typing methods. The large number of victims and the extreme thermal and physical conditions of the site necessitated special approaches to the DNA-based identification. Because of these and many additional challenges, new procedures were created or modified from routine forensic protocols. This effort facilitated the identification of 1594 of the 2749 victims. In this Policy Forum, the authors, who were were members of the World Trade Center Kinship and Data Analysis Panel, review the lessons of the attack response from the perspective of DNA forensic identification and suggest policies and procedures for future mass disasters or large-scale terrorist attacks.
In this brief review, our main emphasis has been on the analysis of the sequence diversity among various class I genes and their functional implications. The availability of complete nucleotide sequences of 7 different genes representing different loci allowed us to derive a consensus sequence. One mouse MHC Class I gene was included in these comparisons as a representative of H2 genes Evolutionary patterns can be seen on the basis of divergence of various genes from the derived consensus sequence. At least 1 human gene which has a promoter similar to that of H2 genes and which contains a single initiation codon following this promoter (unlike all other human genes and like all the H2 genes) has been identified. Both variable and homology regions can be identified in the entire length of the gene. While exons show relatively strong conservation of sequences, the introns have many variable regions, introns 6 and 7 being the most heterogeneous. Stretches of conserved nucleotide sequences are noticed at the 3' regions of most introns. Estimation of total number of class I genes is presented on the basis of cloning experiments, and the abundance of 1 particular pseudogene is discussed.
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