Methodological Improvements in the mRNA Profiling Assays for Incorporation into DNA Casework Workflows

Currently, DNA profiling is the gold standard to identify an individual. However, determining body fluid origin is important in criminal investigations, offering additional information surrounding the circumstances of a crime. However, crime labs can only definitively identify blood and semen and presumptively saliva using techniques that consume time and sample and do not simultaneously identify all forensically relevant body fluids. This causes many crime labs to want to bypass body fluid identification altogether. Therefore, advances into more definitive molecular-based body fluid methods are necessary. One such technique is mRNA profiling because it provides a highly sensitive and specific approach to definitively identifying all relevant body fluids in parallel. Although advancements have been made, improvements to mRNA profiling methodologies still need to be researched such as 1) possible mRNA recovery from established DNA workflows and 2) possible integration of mRNA profiling into an upfront male DNA screening assay for triaging sexual-assault evidence likely to contain male DNA and reduce/eliminate a significant bottleneck in the standard DNA workflow of microscopic sperm identification. This study was designed to address these two issues by evaluating a novel way to recover RNA, for body fluid identification, from the waste fractions of a PrepFiler™ DNA extraction, and from the DNA extracts directly. Next, this study aimed to provide a relatively quick molecular-based approach for screening sexual-assault evidence. It involves extraction of RNA using the Dynabeads™ mRNA DIRECT™ Kit, while saving the extraction waste fractions for downstream male-DNA quantitation and STR profiling. The RNA is then used in a rapid and sensitive 1-step combined reverse transcription-HRM assay to positively detect the presence of sperm. Both non-conventional co-extraction methods successfully addressed current body fluid identification challenges and allowed for easy integration into existing workflows when single sourced, mixture and mock casework samples were analyzed