Disaster victim investigation recommendations from two simulated mass disaster scenarios utilized for user acceptance testing CODIS 6.0

Investigative genetic genealogy: Current methods, knowledge and practice

Investigative genetic genealogy (IGG) has emerged as a new, rapidly growing field of forensic science. We describe the process whereby dense SNP data, commonly comprising more than half a million markers, are employed to infer distant relationships. By distant we refer to degrees of relatedness exceeding that of first cousins. We review how methods of relationship matching and SNP analysis on an enlarged scale are used in a forensic setting to identify a suspect in a criminal investigation or a missing person. There is currently a strong need in forensic genetics not only to understand the underlying models to infer relatedness but also to fully explore the DNA technologies and data used in IGG. This review brings together many of the topics and examines their effectiveness and operational limits, while suggesting future directions for their forensic validation. We further investigated the methods used by the major direct-to-consumer (DTC) genetic ancestry testing companies as well as submitting a questionnaire where providers of forensic genetic genealogy summarized their operation/services. Although most of the DTC market, and genetic genealogy in general, has undisclosed, proprietary algorithms we review the current knowledge where information has been discussed and published more openly.

Weight-of-evidence for DNA identification of missing persons and human remains using CODIS

DNA Identification of unidentified human remains (UHR) is performed in Israel by comparing the UHR's short tandem repeat (STR) profiles to a national database of STR profiles taken from relatives of missing persons. Kinship analysis is performed using the CODIS 7.0 software and results are stated as a Joint Pedigree Likelihood Ratio (JPLR). The weight-of-evidence for JPLR has never been studied, making it difficult to interpret the meaning of specific values in terms of whether UHR are related to specific pedigrees. Therefore, the aim of this study was to statistically determine the practical meaning and context of the JPLR. We used 440 million pairs of simulated DNA profiles and 294 pairs of real ones from known siblings, parent/offspring and unrelated persons. A Score-Based Likelihood Ratio (SBLR) was empirically constructed, validated and compared to both JPLR and the LR produced by CODIS. Our results show that CODIS's JPLR and LR values for single-person pedigrees overestimate the level of support for both "parent/child" and "siblings" propositions relative to the "unrelated" proposition, by up to two orders of magnitude. A practical table is given for correcting this phenomenon, with statistical interpretation (i.e. SBLR) for each JPLR score, including verbal levels of propositional support ranging from "no support" (SBLR<2) to "extremely strong" (SBLR>1 Million).

Nails as a primary sample type for molecular genetic identification of highly decomposed human remains

For identification of badly preserved cadavers, only a few tissues can be used as a source of DNA, mostly bones and teeth, from which sampling and DNA extraction are difficult and time-consuming. In most highly decomposed remains, the nails are preserved. The aim of this study was to evaluate nails as an alternative source of DNA instead of bones and teeth in demanding routine identification cases. An automated extraction method was optimized on nails obtained from 33 cadavers with a post-mortem interval (PMI) up to 5 years. The commercially available EZ1 Investigator Kit (Qiagen) was used for extraction, and the G2 buffer included in the kit was replaced with TN_Ca buffer, and DTT was added for digestion of 5 mg of nail. The DNA was purified in a Biorobot EZ1 device (Qiagen), quantified using the PowerQuant System (Promega), and STR typing was performed with the NGM kit (TFS). From 0.3 to 270 μg DNA/g of nail was obtained from the samples analyzed, with an average yield of 36 μg DNA/g of nail. Full STR profiles were obtained from all nails except one. The optimized extraction method proved to be fast and highly efficient in the removal of PCR inhibitors, and it yields high amounts of DNA for successful STR typing. Nails were implemented as the primary sample type for obtaining DNA from highly decomposed and partially skeletonized cadavers in routine forensic identification cases in our laboratory.

GHEP-ISFG collaborative simulated exercise for DVI/MPI: Lessons learned about large-scale profile database comparisons

The GHEP-ISFG Working Group has recognized the importance of assisting DNA laboratories to gain expertise in handling DVI or missing persons identification (MPI) projects which involve the need for large-scale genetic profile comparisons. Eleven laboratories participated in a DNA matching exercise to identify victims from a hypothetical conflict with 193 missing persons. The post mortem database was comprised of 87 skeletal remain profiles from a secondary mass grave displaying a minimal number of 58 individuals with evidence of commingling. The reference database was represented by 286 family reference profiles with diverse pedigrees. The goal of the exercise was to correctly discover re-associations and family matches. The results of direct matching for commingled remains re-associations were correct and fully concordant among all laboratories. However, the kinship analysis for missing persons identifications showed variable results among the participants. There was a group of laboratories with correct, concordant results but nearly half of the others showed discrepant results exhibiting likelihood ratio differences of several degrees of magnitude in some cases. Three main errors were detected: (a) some laboratories did not use the complete reference family genetic data to report the match with the remains, (b) the identity and/or non-identity hypotheses were sometimes wrongly expressed in the likelihood ratio calculations, and (c) many laboratories did not properly evaluate the prior odds for the event. The results suggest that large-scale profile comparisons for DVI or MPI is a challenge for forensic genetics laboratories and the statistical treatment of DNA matching and the Bayesian framework should be better standardized among laboratories.

Familias 3 - Extensions and new functionality

In relationship testing the aim is to determine the most probable pedigree structure given genetic marker data for a set of persons. Disaster Victim Identification (DVI) based on DNA data from presumed relatives of the missing persons can be considered to be a collection of relationship problems. Forensic calculations in investigative mode address questions like "How many markers and reference persons are needed?" Such questions can be answered by simulations. Mutations, deviations from Hardy-Weinberg Equilibrium (or more generally, accounting for population substructure) and silent alleles cannot be ignored when evaluating forensic evidence in case work. With the advent of new markers, so called microvariants have become more common. Previous mutation models are no longer appropriate and a new model is proposed. This paper describes methods designed to deal with DVI problems and a new simulation model to study distribution of likelihoods. There are softwares available, addressing similar problems. However, for some problems including DVI, we are not aware of freely available validated software. The Familias software has long been widely used by forensic laboratories worldwide to compute likelihoods in relationship scenarios, though previous versions have lacked desired functionality, such as the above mentioned. The extensions as well as some other novel features have been implemented in the new version, freely available at www.familias.no. The implementation and validation are briefly mentioned leaving complete details to Supplementary sections.

DNA analysis in Disaster Victim Identification

DNA profiling and matching is one of the primary methods to identify missing persons in a disaster, as defined by the Interpol Disaster Victim Identification Guide. The process to identify a victim by DNA includes: the collection of the best possible ante-mortem (AM) samples, the choice of post-mortem (PM) samples, DNA-analysis, matching and statistical weighting of the genetic relationship or match. Each disaster has its own scenario, and each scenario defines its own methods for identification of the deceased.