Improved Tools and Interpretation Guidelines for Examining Limited Low Copy Number DNA Obtained From Degraded Single Source Samples: Bones, Teeth, and Hairs

• NCJ Number: 251930
• Author(s): Bruce Budowle
• Date Published: August 2012
• Length: 107 pages
• Grant Number(s): 2009-DN-BX-K188
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical); Report (Study/Research); Report (Grant Sponsored); Program/Project Description

Annotation

Findings and methodology are presented for a research project whose goals were to improve the analytical DNA typing process, assess the effects of primary and secondary transfer DNA, and provide insight on the statistical issues needed to assess the significance of a low copy number (LCN) DNA typing result.

Abstract

LCN typing is a technique for typing low-quantity DNA samples, which have been defined as the analysis of any sample that contains less than 200 or 100 pg of template; however, 200 pg should not be misconstrued as a threshold that applies to all systems or all laboratories. Samples with low amounts of template DNA are subjected to exaggerated stochastic effects, and these effects impact the reliability of DNA typing results. Current LCN methods are not well-developed, and the confidence associated with such a DNA profile is not well-defined. LCN typing needs improvement so genetic data from missing-persons cases can be used to full potential, and those who make identifications will be able to use the genetic information effectively. The methods developed and evaluated by this project provide potential practical solutions for improving the yield of DNA from any source, but particularly from bone. Although hairs and teeth were initially suggested as additional sources for this study, the research focused on bones, since these samples are more challenging. The results from the analysis of bones apply to other types of evidence common in cases of missing persons. Materials and methods for the current research are described. Future work should derive empirical data from a robust technology that can be used to test and apply the single source model. 54 figures, 4 tables, and 79 references