Biological evidence is often found at crime scenes and can comprise of DNA from the victim(s) and perpetrator(s) to a crime as well as from individuals with no direct relationship to the incident. This can complicate analysis as DNA mixtures are one of the more difficult sources of biological evidence to interpret. Probabilistic genotyping (PG) has greatly aided in mixture analysis. However, even with PG, standard bulk mixture approaches do not always result in probative results as allele overlap, artifacts, or low-level minor contributors inevitably cause genotype information loss. Therefore, deconvolution of forensic DNA mixtures into their individual component DNA (geno)types is of great investigative value. In the present work, enhanced single cell DNA typing conditions consisting of reduced reaction volumes and increased PCR cycle number were optimized and paired with a simplified micro-manipulation technique resulting in a subsampling scheme referred to as direct single cell subsampling (DSCS). Furthermore, the PG systems STRmixTM and EuroForMix were validated for use with both standard bulk DNA mixtures as well as with 1-5 cells. The DSCS approach was applied to various complex mixture scenarios including equimolar 2-6 person mixtures, mixtures comprised of 1st degree relatives, mixtures in which a minor donor is virtually undetectable (~1:50), and mixtures that had been deposited for varying time periods resulting in a probative gain of information compared to the standard mixture methods. Specifically, with the 5- and 6- person complex mixtures analyzed, DSCS recovered highly probative LRs ( > 10^20) from donors that had returned non-probative LRs ( < 10^3) by standard methods. With familial mixtures, DSCS prevented the false inclusion of non-donor relatives seen with standard methods. This approach was further applied to Y-STR mixture analysis. The DSCS approach could permit forensic scientists to analyze and recover probative evidentiary information from complex mixtures with excessive overlapping alleles such as those seen with related individuals and large contributor numbers as well as from mixtures with marginally detectable minor donors. Requiring only basic equipment and materials, the DSCS approach can easily be implemented into a casework laboratory.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2472 |
| Date | 01 January 2022 |
| Creators | Huffman, Kaitlin |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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