Investigation of Different Ways in Which the CODIS 7.0 May be Used in Mass Disaster Identification

DNA analysis is a key method for the identification of human remains in mass disasters. Reference samples from relatives may be used to identify missing persons by kinship analysis. Different methods of applying the CODIS in disaster victim identification (DVI) were investigated. Two searches were evaluated: (i) relating family relatives to a pedigree tree (FPT) and (ii) relating unidentified human remains to a pedigree tree (UPT). A joint pedigree likelihood ratio (JPLR) and rank were calculated for each search. Both searches were similar in average JPLR and rank. In exceptional cases, namely the existence of a mutation different from the CODIS model, a nonbiological father, a mistake in STR, or incorrect profile association, the UPT search returned one true rank, whereas the FPT search returned no results. This paper suggests a novel strategy to overcome these limitations and increase efficiency in conducting identification of mass disaster victims.     

A multifaceted,multijurisdictional, multiagency,and multidisciplinary approach to investigating unidentified and missing persons cases in Australia

Currently, there are approximately 750 unidentified human remains and 2500 long-term missing persons in Australia. The Australian Federal Police National DNA Program for Unidentified and Missing Persons (Program) is using a multifaceted, multijurisdictional, multiagency, and multidisciplinary approach in a dedicated effort to identify these unknown deceased persons, scientifically link them to known missing persons, and provide answers to their families. The nationally coordinated Program provides its police, forensic, and coronial stakeholders with a suite of contemporary forensic technologies, databases, and experts to forensically examine the skeletonised remains and recover post-mortem data for comparison to the available ante-mortem data for each missing person. Through a number of physical and virtual public outreach activities, families with missing relatives have been encouraged to provide vital ante-mortem forensic information, records, and samples to aid the identification process. To date, this unique Program has assisted to resolve a number of unidentified and missing persons cases from both historical and contemporary contexts, using a combination of genetic and non-genetic techniques, and local and national databases. The centralisation of Program capabilities, expertise, and resources to conduct this type of unique and challenging casework is proving to be the most effective and efficient way to generate investigative leads, identify human remains, and resolve long-term missing persons cases in Australia.     

Evaluating probabilistic genotyping for low-pass DNA sequencing

Most genomic methods consider the sample genotype. Data are evaluated at some location, and if the signal strength is sufficient, a genotype call is made. Conversely, sites that lack sufficient signal are treated as missing data. Such methods for genotype calling are binary, and this dichotomy limits genomic analyses to relatively high-coverage (and high-cost) massively parallel sequencing (MPS) data. It follows that bioinformatic methods that rely on genotypes may not be ideal for trace DNA samples, such as those sometimes encountered in forensic investigations, but even when applicable such analyses can be expensive. However, there are some genomic analyses where having many uncertain genotypes (with measured uncertainty) assayed over the entirety of the genome may be more powerful than current multi-locus approaches that consider a limited number of well-characterized markers. Methods for such problems may rely on genotype likelihood, which expresses the likelihood of alternative genotype calls in addition to the most likely call. One application that can benefit from genotype likelihoods is kinship analysis. NgsRelate is a bioinformatic tool that infers pairwise relatedness using a probabilistic genotyping framework, which accommodates the uncertainty associated with genotype calls for low-pass MPS data. Here, NgsRelate was used to infer kinship coefficients from low-pass whole genome sequencing data from a known pedigree. Multiple samples in a titration series (ranging from 50 ng to 0.5 ng) on a single MPS S4 flow cell were assessed. A reproducible scientific bioinformatic workflow was developed to evaluate kinship coefficients considering up to 3rd degree relatives. NgsRelate was found to provide robust assessments of kinship. Further, the use of low-pass MPS data provides a more cost-effective way to conduct forensic investigations.     

DNA identification of skeletal remains by investigator’s intuition

In June 2006 a decapitated woman was found in a parking area of the motorway in the area of Prato (Florence). Since the body was beheaded and no victim’s documents or objects were present at the crime scene, identification at that time was impossible. However, DNA profile from woman’s bones were collected. In the same year (2003), a mother had reported her daughter's disappearance but the two events were not related at that time. About ten years later the mother’s DNA profile was finally acquired for a genetic identification of another girl’s body found in the Ferrara area. These genetic profiles were completely discordant. All these genetic comparisons were carried out on behalf of the prosecutors of the cities involved in the findings of the bodies and in the disappearance complaints, but due to the lack of a database the events remained disconnected. In January 2017, the head of the scientific police of Prato who had followed the investigation and questioned the mother of the missing girl found about ten years later, suggested to the magistrate to order the comparison of the mother's DNA with the genetic profile of the bones found in 2006. This comparison finally allowed the identification of the missing daughter.This story highlights the importance of having forensic DNA database to search for missing persons and how the investigator's intuition can play a key role in resolving criminal cases. In fact, databases of unknown bodies and relatives of missing persons were created in Italy as a part of national DNA database just at the beginning of 2018.     

Application of mtDNA sequence analysis in forensic casework for the identification of human remains

In four forensic cases of unidentified skeletal remains investigated in the last year, we were able to attach three to missing persons. In one case we could show that the discovered bone sample did not fit to a missing child. The method for mitochondrial DNA analysis for the routine identification of skeletal remains was established in our institute by typing bone samples of defined age obtained from Frankfurt's cemetery. Reproducible results were obtained for bones up to 75 years old. For analysis the bone samples were pulverised to fine powder, decalcified and DNA was extracted. From the DNA we amplified a 404-bp fragment from HV-1 and a 379-bp fragment from HV-2 of the mtDNA control region. After sequencing of the PCR products, the results were compared to the Anderson reference sequence and to putative maternal relatives.     

Application of low copy number STR typing to the identification of aged, degraded skeletal remains

Low copy number (LCN) STR typing was successfully applied to four interesting cases during developmental validation of the approach for degraded skeletal remains. Specific questions were addressed in each case, with the acquisition of STR data largely serving as additional confirmatory or investigatory information in any specific situation, and not necessarily providing the definitive evidence to establish identity. The cases involve missing U.S. service members from World War I, World War II, and the Vietnam War. The variety of these cases, in terms of the questions addressed, the age of the remains, and the type of reference material available for comparison, demonstrates the broad utility of LCN STR typing in the identification of degraded skeletal remains from missing persons.     

Identification of Missing Norwegian World War II Soldiers,in Karelia Russia

This article presents the multidisciplinary effort in trying to identify the skeletal remains of 100 Norwegian soldiers serving in the German army, killed in Karelia Russia in 1944, from the recovery of the remains through the final identification using DNA. Of the 150 bone samples sent for DNA testing, 93 DNA profiles were obtained relating to 57 unique individuals. The relatives could not be directly contacted as the soldiers were considered as traitors to Norway; therefore, only 45 reference samples, relating to 42 cases of the missing, were donated. DNA matches for 14 soldiers and 12 additional body part re‐associations for these individuals were found. Another 24 bone samples were re‐associated with 16 individuals, but no familial match was found. More than six decades after the end of WWII, DNA analysis can significantly contribute to the identification of the remains.     

DNA Typing for the Identification of Old Skeletal Remains from Korean War Victims*

Abstract: The identification of missing casualties of the Korean War (1950–1953) has been performed using mitochondrial DNA (mtDNA) profiles, but recent advances in DNA extraction techniques and approaches using smaller amplicons have significantly increased the possibility of obtaining DNA profiles from highly degraded skeletal remains. Therefore, 21 skeletal remains of Korean War victims and 24 samples from biological relatives of the supposed victims were selected based on circumstantial evidence and/or mtDNA‐matching results and were analyzed to confirm the alleged relationship. Cumulative likelihood ratios were obtained from autosomal short tandem repeat, Y‐chromosomal STR, and mtDNA‐genotyping results, and mainly confirmed the alleged relationship with values over 10⁵. The present analysis emphasizes the value of mini‐ and Y‐STR systems as well as an efficient DNA extraction method in DNA testing for the identification of old skeletal remains.     

Next generation sequencing technology in Second World War victim identification

The killings during the Second World War (WWII), with nearly 100,000 victims, is one of the greatest losses of life in Slovenia’s modern history and most of the victims are still buried in hidden mass graves and remain unidentified. Identity, ancestry, and phenotypic SNPs, as well as STR markers are already used for solving various cases with Next Generation Sequencing (NGS) technology. In this study, the Precision ID GlobalFiler NGS STR panel was used to identify the WWII victim that could not be identified with capillary electrophoresis (CE) analyses because limited statistical support was obtained after amplification of autosomal STRs using CE STR kits. Bones and teeth were analysed and compared to family references (nephew and niece on paternal line). Prior to DNA isolation 0.5 g of powder was decalcified. The DNA was purified in a Biorobot EZ1 device. The nuclear DNA of the samples was quantified with the PowerQuant kit. Because the recommended posterior probability (PP) of 99.9% was followed with the goal of high confidence of correct identification, the NGS STR Panel was used, and after the analysis of additional STR loci the statistical calculation showed a PP of 99.99986%, showing that a large enough number of genetic markers were analysed when identifying the skeletal remains of the aunt. PP value endorsed the hypothesis that the tooth and bone samples were from individual related to the family references rather than from unrelated individual. In presented case, NGS technology proved to be a powerful tool for increasing the number of autosomal STRs needed for identification of WWII victims when linear markers cannot be used for comparison and only distant relatives are available for analyses.     

Some mathematical problems in the DNA identification of victims in the 2004 tsunami and similar mass fatalities

DNA is a major and essential identification tool for mass fatality incidents including the hundreds of thousands of victims of the 2004 Indian Ocean tsunami. Mathematical complications characteristic of this sort of mass fatality include prevalence of related victims, the many races represented among the victims, and various identification modalities in tandem with DNA. Four mathematical problems of interest are discussed in this paper. (1) Other quantifiable factors (i.e. geography) can be formally accounted for by including a likelihood ratio that can be thought of as reducing the "effective number of victims." (2) When a victim is found and tentatively identified as V, but then it comes to light that the victim has a relative W who is also missing, confidence in the identity is depressed. To account for the existence of W, increment the effective number of victims by the likelihood ratio supporting W as the identity of the victim. (3) When several apparently related victims are found, their mutual identities should be calculated simultaneously. Compared to one-at-a-time, serial identifications, this is both logical and may lead to much more confidence in the identities. (4) Although there may be many different population groups represented among the missing, it is generally sufficient to consider population statistics for only a few of them in deciding whether to declare an identification.     

Kinship assignment with the ForenSeq™ DNA Signature Prep Kit: Sources of error in simulated and real cases

Kinship recognition between anonymous DNA samples is becoming a relevant issue in forensics, more so with the increasing number of DNA profiles in databanks. Also, NGS-based genotyping is being increasingly used in routine personal identification, to simultaneously type large numbers of markers of different kind. In the present work, we explored computationally and experimentally the performance of the ForenSeq™ DNA Signature Prep Kit in identifying the true relationship between two anonymous samples, distinguishing it from other possible relationships. We analyzed with Familias R series of 10,000 pairs with 9 different simulated relationships, corresponding to different degrees of autosomal sharing. For each pair we obtained likelihood ratios for five kinship hypotheses vs. unrelatedness, and used their ranking to identify the preferred relationship. We also typed 21 subjects from two pedigrees, representing from parent-child to 4th cousins relationships. As expected, the power for identifying the true relationship decays in the order of autosomal sharing. Parent-child and full siblings can be robustly identified against other relationships. For half-siblings the chance of reaching a significant conclusion is already small. For more distant relationships the proportion of cases correctly and significantly identified is 10% or less. Bidirectional errors in kinship attribution include the suggestion of relatedness when this does not exist (10–50%), and the suggestion of independence in pairs of individuals more than 4 generations apart (25–60%). The real cases revealed a relevant effect of genotype miscalling at some loci, which could only be partly avoided by modulating the analysis parameters. In conclusion, with the exception of first degree relatives, the kit can be useful to inform additional investigations, but does not usually provide probatory results.     

Enhancing accurate data collection in mass fatality kinship identifications: Lessons learned from Hurricane Katrina

A mass fatality DNA identification effort is a complex process in which direct matching and kinship analysis is used for identifying human remains. Kinship DNA identification is an important tool in the identification process in which victim's DNA profiles are compared to the profiles of “known” biologically related reference samples. Experience from the 9/11 World Trade Center DNA identification efforts showed that forms used to record biological relationships are important and that inaccurately documented information may hamper the kinship analysis and DNA identification process. In the identification efforts following Hurricane Katrina, a Family and/or Donor Reference Collection (FDRC) form was used as a means to document the reported relationship between the reference DNA donor and the purported missing individual. This FDRC form was developed based upon lessons learned from 9/11 and the Tsunami identification efforts. This paper analyses the effectiveness of the FDRC form used in the Hurricane Katrina kinship DNA identification efforts and proposes an improved sample collection form for kinship and other donor reference samples. The data presented can be used to enhance the accuracy of the data collection process through an improved sample collection form, streamlining the DNA kinship identification process and decreasing the burden on valuable resources.     

Empirical validation of a family-member prioritization approach to maximize statistical power in missing person cases

In order to prioritize the exhumation of the most informative reference relatives to increase the statistical power of a reference group, a conditional simulation approach for missing person identification that combines both exclusion and inclusion power in reference families has been previously developed. The aim of this study is to empirically validate this approach by comparing its predicted theoretical prioritization model with the observed changes in statistical power in real cases of our laboratory, in which new relatives had already been added. We conclude that this approach is a reliable tool to choose the most appropriate reference relatives to complete a family group and improve the identification power of a Missing Person (MP).     

A D19S433 primer binding site mutation and the frequency in Japanese of the silent allele it causes

Short tandem repeat studies are powerful tools for parentage analysis and for identification of missing persons, victims of murder, and victims of mass fatalities when reference samples are unavailable. The primer in the Identifiler kit failed to amplify an allele at the D19S433 locus, producing a silent ("null") allele. The causal mutation is a base change (G>A) 32 nucleotides downstream from the 3' end of the AAGG repeats. The silent alleles are problematical in parentage analysis because when transmitted, they can cause a parent-child inconsistency that is unrelated to Mendelian genetics. The inconsistency is sometimes termed an "apparent opposite homozygosity" and it produces false evidence of nonparentage. Alternative primers were designed to amplify the D19S433 locus alleles and they detect the silent allele. Frequencies of the (no longer) silent allele were determined to be 0.0114 in 176 people from Shizuoka (Honshu) and 0.0128 in 156 people from Okinawa.     

Screening and identification of tissue-specific methylation for body fluid identification

Identification of body fluid stains can bring important information to crime case. Recent research in epigenome indicates that tissue-specific differentially methylated regions (tDMRs) show different DNA methylation profiles according to the type of cell or tissue, which makes it possible to identify body fluid based on analysis of DNA. This study screened and identified tDMRs from genome for forensic purpose. DNA samples from blood, saliva, semen, and vaginal fluid were analyzed by methylation sensitive represent difference analysis and Sequenom Massarray^® quantitative analysis of methylation. Six blood-specific tDMRs were obtained. Two tDMRs display blood-specific hypomethylation, and four tDMRs show blood-specific hypermethylation. These tDMRs may discriminate blood stain from other body fluids. The result indicated that tDMRs could become potential DNA markers for body fluid identification.     

特征表型信息SNP在法医学分析中的研究进展

以DNA为基础的STR和SNP遗传标记的检验,已广泛应用于各种个人识别、亲子鉴定和人口失踪案件。但现场DNA样本分型不能与相关个体匹配时,利用特征表型信息SNP则可能为侦查提供有价值线索。本文综述了近年来特征表型信息SNP在法医学应用中的研究进展,并简述其发展方向,旨在为相关研究和应用提供参考和借鉴。     

On identification problems requiring linked autosomal markers

This paper considers identification problems based on DNA marker data. The topics we discuss are general, but we will exemplify them in a simple context. There is DNA available from two persons. There is uncertainty about the relationship between the two individuals and a number of hypotheses describing the possible relationship is available. The task is to determine the most likely pedigree. This problem is fairly standard. However, there are some problems that cannot be solved using DNA from independently segregating loci. For example, the likelihoods for (i) grandparent–grandchild, (ii) uncle–niece and (iii) half-sibs coincide for such DNA data and so these relations cannot be distinguished on the basis of markers normally used for forensic identification problems: the likelihood ratio comparing any pair of hypotheses will be unity.Sometimes, but not in the examples we consider, other sources of DNA like mtDNA or sex chromosomes can help to distinguish between such equally likely possibilities. Prior information can likewise be of use. For instance, age information can exclude alternative (i) above and also indicate that alternative (iii) is apriori more likely than alternative (ii).More generally, the above problems can be solved using linked autosomal markers. To study the problem in detail and understand how linkage works in this regard, we derive an explicit formula for a pair of linked markers. The formula extends to independent pairs of linked markers. While this approach adds to the understanding of the problem, more markers are required to obtain satisfactory results and then the Lander–Green algorithm is needed. Simulation experiments are presented based on a range of scenarios and we conclude that useful results can be obtained using available freeware (MERLIN and R).The main message of this paper is that linked autosomal markers deserve greater attention in forensic genetics and that the required laboratory and statistical analyses can be performed based on existing technology and freeware.     

Tri-allelic SNP markers enable analysis of mixed and degraded DNA samples

For the analysis of degraded DNA in disaster victim identification (DVI) and criminal investigations, single nucleotide polymorphisms (SNPs) have been recognized as promising markers mainly because they can be analyzed in short sized amplicons. Most SNPs are bi-allelic and are thereby ineffective to detect mixtures, which may lead to incorrect genotyping. We developed an algorithm to find non-binary (i.e. tri-allelic or tetra-allelic) SNPs in the NCBI dbSNP database. We selected 31 potential tri-allelic SNPs with a minor allele frequency of at least 10%. The tri-allelic nature was confirmed for 15 SNPs residing on 14 different chromosomes. Multiplex SNaPshot™ assays were developed, and the allele frequencies of 16 SNPs were determined among 153 Dutch and 111 Netherlands Antilles reference samples. Using these multiplex SNP assays, the presence of a mixture of two DNA samples in a ratio up to 1:8 could be recognized reliably. Furthermore, we compared the genotyping efficiency of the tri-allelic SNP markers and short tandem repeat (STR) markers by analyzing artificially degraded DNA and DNA from 30 approximately 500-year-old bone and molar samples. In both types of degraded DNA samples, the larger sized STR amplicons failed to amplify whereas the tri-allelic SNP markers still provided valuable information. In conclusion, tri-allelic SNP markers are suited for the analysis of degraded DNA and enable the detection of a second DNA source in a sample.