Mitochondrial DNA (deoxyribo nucleic acid) is typically used in forensic casework when small quantities of high molecular weight quality DNA is not expected to be present thus negating the chances of obtaining usable nuclear DNA. Typical samples that utilized mitochondrial DNA analysis are: hair, bones, teeth, ancient remains (samples or remains that are at least 100 years old) or very old samples (samples that are less than 100 but greater than 10 years old). The current method used to evaluate mitochondrial DNA is Sanger sequencing. Although robust, it is also time consuming and labor intensive, on the other hand pyrosequencing is a nonelectrophoretic, rapid, reliable, and sensitive sequencing method which can be easily automated. Therefore pyrosequencing could enable the widespread use of mitochondrial DNA in forensic casework and reduce the amount of time spent on each sample without compromising quality. The aim of this study is to evaluate the efficacy of pyrosequencing for forensic DNA applications, in particular mitochondrial DNA. Two dispensation orders, cyclic and directed, were examined to determine if there is any effect on the sequence generated. The accuracy of pyrosequencing was evaluated by sequencing samples of known sequence provided by the FBI. The sensitivity of pyrosequencing was evaluated by sequencing samples at different DNA concentrations and inputs. Experiments were conducted to determine the ability of pyrosequencing to detect mixtures and heteroplasmy. Additionally, the ability of pyrosequencing to sequence damaged/degraded DNA was evaluated using blood, semen, and saliva samples that were subjected to three different environmental conditions. A blind study will be conducted to confirm the accuracy of pyrosequencing. Finally, a comparison study will be conducted in which pyrosequencing will be compared to Sanger sequencing.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-1134 |
Date | 01 January 2004 |
Creators | Hastings, Patsy-Ann Susan |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations |
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