<p> When an evidential DNA profile does not match identified suspects or profiles from available databases, further DNA analyses targeted at inferring the possible ancestral origin and phenotypic characteristics of the perpetrator could yield valuable information. Single Nucleotide Polymorphisms (SNPs), the most common form of genetic polymorphisms, have alleles associated with specific populations and/or correlated to physical characteristics. With this research, single base primer extension (SBE) technology was used to develop a 50 SNP assay designed to predict ancestry among the primary U.S. populations (African American, East Asian, European, and Hispanic/Native American), as well as pigmentation phenotype. The assay has been optimized to a sensitivity level comparable to current forensic DNA analyses, and has shown robust performance on forensic-type samples. In addition, three prediction models were developed and evaluated for ancestry in the U.S. population, and two models were compared for eye color prediction, with the best models and interpretation guidelines yielding correct information for 98% and 100% of samples, respectively. Also, because data from additional DNA markers (STR, mitochondrial and/or Y chromosome DNA) may be available for a forensic evidence sample, the possibility of including this data in the ancestry prediction was evaluated, resulting in an improved prediction with the inclusion of STR data and decreased performance when including mitochondrial or Y chromosome data. Lastly, the possibility of using next-generation sequencing (NGS) to genotype forensic STRs (and thus, the possibility of a multimarker multiplex incorporating all forensic markers) was evaluated on a new platform, with results showing the technology incapable of meeting the needs of the forensic community at this time.</p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:3590467 |
| Date | 21 September 2013 |
| Creators | Gettings, Katherine Butler |
| Publisher | The George Washington University |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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