Forensic investigative genetic genealogy (FIGG) is a highly effective tool for generating leads and identifying individuals, involving DNA analysis and traditional genealogical research by employing large-scale single-nucleotide polymorphism (SNP) data sets in combination with comparable data from publicly available genealogy DNA databases to match biological relatives in a known system to an unknown DNA sample using segments of shared DNA. The application of SNPs to DNA profiling methods has greatly enhanced the possibilities for human identification in cases of highly degraded samples, which are commonly seen with skeletal samples. SNP markers can be successfully amplified from more degraded (fragmented) samples as they are variations at a single position in a DNA sequence; however, due to the cutting-edge nature of this type of research, many questions surrounding feasibility - particularly with degraded DNA samples - still remain. This research seeks to compare cold case bone samples across three decades to assess the feasibility of generating SNP data from skeletal remains and generate exploratory data on the impact of time since death on data recovery. Specifically, trends in performance will be assessed using the Verogen ForenSeq® Kintelligence Kit, from which recovery rates of SNP data between samples based on time since recovery will be compared. The purpose of this research is to provide an understanding of how time may factor into SNP data generation, considering DNA recovered from unidentified human remains may be degraded or low quality and therefore difficult to generate sufficient data for FIGG applications.

The Kintelligence Kit, specifically designed for forensic casework and validated by multiple studies for its ability to generate profiles from low-input DNA samples, will allow insight into the quality of SNP profiles built from cold case samples. Samples will undergo manual library preparation using the Kintelligence Kit. This kit contains 10,230 SNPs that will provide information on biogeographical ancestry, identity, phenotype, kinship lineage, and biological sex determination. The prepared libraries will be characterized using the Agilent TapeStation and quantified using the Qubit high-sensitivity DNA quantification kit. Sequencing will take place on the Illumina MiSeq FGx® Sequencing System, followed by data analysis using Universal Analysis Software (UAS). Statistical analysis will assess whether time is a significant factor in recovery of SNP-based data using the Kintelligence Kit. These results will provide information regarding the feasibility and effectiveness of this particular kit on skeletal samples ranging over three decades.

Authors

• Natalie May - Western Carolina University, Cullowhee, NC, United States of America
• Brittania Bintz - Western Carolina University, Cullowhee, NC, United States of America
• Madison Townsend - Western Carolina University, Cullowhee, NC, United States of America
• Maureen Hickman - Western Carolina University, Cullowhee, NC, United States of America
• Dr. Tiffany Fracchia - Vanderbilt University, Nashville, TN, United States of America
• Dr. Alice Gooding - Kennesaw State University, Atlanta, GA, United States of America
• Dr. Frankie West - Western Carolina University, Cullowhee, NC, United States of America