ISFG 2019

Chang Zhong, Robert Green, Wilma Norona, Chris Heid, Angie Lackey, Julio Mulero, Jianye Ge

Mitochondrial DNA (mtDNA) is typically utilized for the identification of ancient, disaster victim, missing person, and heavily degraded samples. Sanger Sequencing has been the validated gold standard in analyzing said mtDNA samples, however it is a long and laborious process. With the release of the Applied Biosystems Precision ID mtDNA Control Region Panel (mtDNA CR Panel) and Converge, laboratories can process large numbers of mtDNA samples simultaneously. However, implementation requires a laboratory validation. A validation was developed and executed for the Precision ID System, mtDNA CR Panel, and Converge. Currently published guidelines were still used, even though they are not NGS-specific. Data was generated for the following standard studies: DNA Amplification Sensitivity, Baseline/Stochastic, Accuracy, Precision Repeatability & Reproducibility, Mixture, and Known & Non-Probative. Additionally, two new studies unique to NGS, were developed: Contamination and Sequencing Sensitivity studies. A Contamination study is needed due to a combination of high mtDNA copy numbers and sensitivity of NGS systems. The lower baseline of NGS systems also affect contamination detection. Sequencing sensitivity is assessed because template preparation is a form of PCR where input library concentration may be low due to low amplification DNA input. Results from all the studies aligned with expected trends and concordance. The results and execution of the laboratory validation demonstrated that NGS is making headway in the forensic market. The adoption of the NGS system is no longer a daunting hurdle because the same mtDNA laboratory and interpretation guidelines can be followed.

Lim J, Wootton S, Roth C, Hasegawa R, Chang CW, Vijaychander S, Deng J, Gabriel M, Lackey A, Lagacé R

J. Chang, M. Gabriel, Carla Paintner, Caron Pruiett, Amy Liberty

Matthew Ludeman, Robert Green, Vivian Nguyen, Robert Eardley, Marc Short and Julio Mulero

Allison Holt, Matthew Ludeman, Charles Troup, Cevat Akin, Jacklyn Buscaino, Mattias Vangbo

Crime fighting in the 21st century necessitates improved investigation methods, and increased partnership between crime labs and investigation units. Rapid DNA technology emerged over a decade ago as a way of confirming a suspect’s identity while still in custody. Improvements in size and usability of recent Rapid DNA technology systems have enabled additional usage in non-laboratory environments such as police booking stations and border checkpoints. The next step in this evolution is the recent enhancements we present here; improved capabilities for use with investigative leads samples. These improved capabilities were achieved by enhancing the PCR amplification, improving lysis and adjusting the analysis parameters to ensure maximum recovery of alleles while still returning 100% concordant genotypes under these new conditions. The goal of this study was to assess the newly optimized Applied Biosystems RapidHIT ID System for the analysis of investigative leads samples with Applied Biosystems Globalfiler Express chemistry. This included low and mid-level saliva and blood samples, mixtures of saliva, purified DNA and casework sample types. Instrument performance was excellent, with all runs completed and 99% of samples returning a profile. Concordance studies resulted in 100% concordance for unflagged loci. For sensitivity studies, improved performance with low-level samples was demonstrated. All mixture samples were flagged appropriately. Many of the casework samples returned usable profiles. We show that the new Rapid Intelligence protocol demonstrated a significant improvement in sensitivity. The results of this study conclude that the RapidHIT ID System provides a useful solution, allowing law enforcement personnel to generate investigative leads and identify suspects faster.

Wootton S, Vijaychander S, Hasegawa R, Deng J, Lackey A, Gabriel M, Lagacé R, Lim J

Ancestry-informative markers (AIMs) can be useful alongside phenotype informative markers to limit a suspect pool or provide investigative leads when STR profiles are either incomplete or fail to provide a database match. On next-generation sequencing (NGS) platforms, these markers can be multiplexed by the hundreds and can present a comprehensive depiction of the unknown individual’s ancestry and lineage using a consolidation of both autosomal and haploid markers. Panels including the Precision ID Ancestry Panel as well as consortia grown panels such as MAPlex and VISAGE tools have led to recent software efforts to allow for customizable marker sets and allele frequencies, and to improve biogeographic prediction accuracy and error estimation. We propose a bootstrapped maximum likelihood approach to ancestry admixture prediction and assess its ability to assign biogeographical ancestry to samples from the 1000 Genomes Project and from samples typed for the ALFRED database (3). Admixed profiles were then created by simulating inheritance from randomly selected profiles, and predictions were run on the simulated offspring. Using a higher confidence interval, we demonstrate correlation between reported error and uncertainty in the prediction due to lack of differentiation. We conclude that overall, predictions are generally consistent with self-reported ancestry, and for populations with predictions of higher uncertainty, we propose inclusion of region-specific markers that can further discriminate these populations. 1 Kidd K., et al., Progress toward an efficient panel of SNPs for ancestry inference, Forensic Science International: Genetics, Volume 10, Pages 23-32. (2014) 2 Kosoy R, et al., Ancestry informative marker sets for determining continental origin and admixture proportions in common populations in America. Hum Mutat 30:69-78. (2009) 3 Rajeevan H, et al., ALFRED: an allele frequency resource for research and teaching. Nucleic Acids Research..(2011) 4 Consortium, T. 1. G. P. (n.d.). A global reference for human genetic variation. Nature, 526, 68 EP –. http://doi.org/10.1038/nature15393

Wootton S, Vijaychander S, Hasegawa R, Deng J, Lackey A, Gabriel M, Lagacé R, Lim J

1Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain 2Centre for Forensic Science, Faculty of Science, University of Technology Sydney, Broadway, NSW, Australia 3Department of Genetics, Yale University School of Medicine, CT, USA 4Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria 5Human Identification Division, Thermo Fisher Scientific, CA, USA 6Thermo Fisher Scientific, Victoria, Australia 7Department of Genetic Engineering and Biotechnology, University of Dhaka, Dhaka, Bangladesh 8DNA Analysis Laboratory, Natural Sciences Research Institute, University of the Philippines, Quezon City, Philippines 9Institute of Legal Medicine, Faculty of Medicine, University of Cologne, Germany 10Department of Legal Medicine, School of Medicine, Kansai Medical University, Japan 11Forensic Services, Victorian Institute of Forensic Medicine, Victoria, Australia 12Forensic Science South Australia, Australia 13Department of Forensic Medicine, Yonsei University College of Medicine, Seoul, Korea. 14Forensic DNA Laboratory, Division of Identification and Forensic Science (DIFS), Israel Police, National H.Q., Jerusalem, Israel. 15Forensic Biology & DNA Laboratory, Forensic Science Services, Fiji Police Force, Fiji 16Forensic Science Program, The Pennsylvania State University, PA, USA 17Office of the Chief Forensic Scientist, Forensic Services Department, Victoria Police, Australia 18National Centre for Forensic Studies, Faculty of Science and Technology, University of Canberra, Canberra, Australia Forensic DNA Intelligence has rapidly emerged as an valuable investigative tool. The ability to estimate the biogeographical ancestry (BGA) of the donor of an evidential sample enables more efficient use of valuable police and forensic resources and assist in decision making in the primary stages of an investigation. Application of massively parallel sequencing (MPS) has greatly expanded the potential for intelligence capabilities. An MPS-based ancestry informative marker panel consisting of over 217 markers was constructed with a specific focus on the differentiation of populations from South Asia, East Asia, South East Asia and Oceania in addition to differentiating between Africans, Europeans and indigenous Americans. The panel combines 112 established binary SNPs with two highly informative SNP-based marker sets; 32 multiallelic SNPs (tri-and tetra-allelic loci) and 20 microhaplotypes consisting of 73 SNPs [1]. A trial of this panel was conducted involving laboratories in the Asia Pacific and the Middle Eastern regions. Participating laboratories contributed population samples of known ancestry (n=50). In addition, to ancestry predictive performance and the development of reference population data sets, this study reports the component marker characteristics and panel optimisation indicating high reproducibility and high sensitivity with full profiles achievable using 125pg of DNA. STRUCTURE v2.3.4 analysis of the population reference set indicates differentiation of at least nine global populations: sub-Saharan Africa, North Africa, Middle East, Europe, East/Europe/Central Asia, South Asia, North Asia, East Asia, Oceania and America using MAPlex. 1.Kidd K., et al Evaluating 130 Microhaplotypes across a Global Set of 83 Populations, Forensic Sci Int Genet, 2017.