Fast and Accurate Kinship Estimation Using Sparse SNPs in Relatively Large Database Searches

Review of SNP assays for disaster victim identification: Cost, time, and performance information for decision-makers

In mass disaster events, forensic DNA laboratories may be called upon to quickly pivot their operations toward identifying bodies and reuniting remains with family members. Ideally, laboratories have considered this possibility in advance and have a plan in place. Compared with traditional short tandem repeat (STR) typing, single nucleotide polymorphisms (SNPs) may be better suited to these disaster victim identification (DVI) scenarios due to their small genomic target size, resulting in an improved success rate in degraded DNA samples. As the landscape of technology has shifted toward DNA sequencing, many forensic laboratories now have benchtop instruments available for massively parallel sequencing (MPS), facilitating this operational pivot from routine forensic STR casework to DVI SNP typing. Herein, we present the commercially available SNP sequencing assays amenable to DVI, we use data simulations to explore the potential for kinship prediction from SNP panels of varying sizes, and we give an example DVI scenario as context for presenting the matrix of considerations: kinship predictive potential, cost, and throughput of current SNP assay options. This information is intended to assist laboratories in choosing a SNP system for disaster preparedness.

Investigative genetic genealogy for human remains identification

Investigative genetic genealogy (IGG) has emerged as a highly effective tool for tying a forensic DNA sample to an identity. While much of the attention paid to IGG has focused on cases where the DNA is from an unknown suspect, IGG has also been used to help close hundreds of unidentified human remains (UHR) cases. Genome-wide single-nucleotide polymorphism (SNP) genotype data can be obtained from forensic samples using microarray genotyping or whole-genome sequencing (WGS) with protocols optimized for degraded DNA. After bioinformatic processing, the SNP data can be uploaded to public GG databases that allow law enforcement usage, where it can be compared with other users' data to find distant relatives. A genetic genealogist can then build the family trees of the relatives to narrow down the identity of the source of the forensic DNA sample. To date, 367 UHR identifications using IGG have been publicly announced. The same IGG techniques developed and refined for UHR cases have significant potential for disaster victim identification, where DNA is often extremely compromised, and close family references may not be available. This paper reviews the laboratory, bioinformatic, and genealogical techniques used in IGG for UHR cases and presents three case studies that demonstrate how IGG is assisting with remains identification.

Comparison of next generation sequencing (NGS) - (SNPs) and capillary electrophoresis (CE) - (STRs) in the genetic analysis of human remains

A pilot study was performed using two different DNA technology platforms conducted by two laboratories to analyze DNA extracted from 83-year-old, human male skeletal remains from 16 individuals, of which there are no other viable means to identify these war victims. The workflow of the more recent developed ForenSeq Kintelligence Kit and next generation sequencing was compared to that of the standard capillary electrophoresis - short tandem repeat (STR) method (Power Plex ESX17 and Y23 Systems). The findings indicate that greater amount of useful genetic data can be gained with the Kintelligence system across the range of samples under study and particularly for samples in which partial or no STR profiles are obtained. SNP data are more likely to be obtained from degraded samples, like the ones analyzed in this study. Moreover, high volume SNP data are suitable for long distance kinship associations and genetic genealogy databases to develop more investigative leads for future kinship and missing persons cases, a process not feasible by STR typing.

It's all relative: A multi-generational study using ForenSeq™ Kintelligence

The successful application of Forensic Investigative Genetic Genealogy (FIGG) to the identification of unidentified human remains and perpetrators of serious crime has led to a growing interest in its use internationally, including Australia. Routinely, FIGG has relied on the generation of high-density single nucleotide polymorphism (SNP) profiles from forensic samples using whole genome array (WGA) (∼650,000 or more SNPs) or whole genome sequencing (WGS) (millions of SNPs) for DNA segment-based comparisons in commercially available genealogy databases. To date, this approach has required DNA of a quality and quantity that is often not compatible with forensic samples. Furthermore, it requires the management of large data sets that include SNPs of medical relevance. The ForenSeq™ Kintelligence kit, comprising of 10,230 SNPs including 9867 for kinship association, was designed to overcome these challenges using a targeted amplicon sequencing-based method developed for low DNA inputs, inhibited and/or degraded forensic samples. To assess the ability of the ForenSeq™ Kintelligence workflow to correctly predict biological relationships, a comparative study comprising of 12 individuals from a family (with varying degrees of relatedness from 1st to 6th degree relatives) was undertaken using ForenSeq™ Kintelligence and a WGA approach using the Illumina Global Screening Array-24 version 3.0 Beadchip. All expected 1st, 2nd, 3rd, 4th and 5th degree relationships were correctly predicted using ForenSeq™ Kintelligence, while the expected 6th degree relationships were not detected. Given the (often) limited availability of forensic samples, findings from this study will assist Australian Law enforcement and other agencies considering the use of FIGG, to determine if the ForenSeq™ Kintelligence is suitable for existing workflows and casework sample types considered for FIGG.

Prioritizing privacy and presentation of supportable hypothesis testing in forensic genetic genealogy investigations

Investigative leads are not generated by traditional forensic DNA testing, if the source of the forensic evidence or a 1st degree relative of unidentified human remains is not in the DNA database. In such cases, forensic genetic genealogy (FGG) can provide valuable leads. However, FGG generated genetic data contain private and sensitive information. Therefore, it is essential to deploy approaches that minimize unnecessary disclosure of these data to mitigate potential risks to individual privacy. We recommend protective practices that need not impact effective reporting of relationship identifications. Examples include performing one-to-one comparisons of DNA profiles of third-party samples and evidence samples offline with an "air gap" to the internet and shielding the specific shared single nucleotide polymorphisms (SNP) states and locations by binning adjacent SNPs in forensic reports. Such approaches reduce risk of unwanted access to or reverse engineering of third-party individuals' genetic data and can give these donors greater confidence to support use of their DNA profiles in FGG investigation.

Validation of the Utility of the Genetically Shared Regions of Chromosomes (GD-ICS) Measuring Method in Identifying Complicated Genetic Relatedness

BACKGROUND

Relatives share more genomic regions than unrelated individuals, with closer relatives sharing more regions. This concept, paired with the increased availability of high-throughput single nucleotide polymorphism (SNP) genotyping technologies, has made it feasible to measure the shared chromosomal regions between individuals to assess their level of relation to each other. However, such techniques have remained in the conceptual rather than practical stages in terms of applying measures or indices. Recently, we developed an index called "genetic distance-based index of chromosomal sharing (GD-ICS)" utilizing large-scale SNP data from Korean family samples and demonstrated its potential for practical applications in kinship determination. In the current study, we present validation results from various real cases demonstrating the utility of this method in resolving complex familial relationships where information obtained from traditional short tandem repeats (STRs) or lineage markers is inconclusive.

METHODS

We obtained large-scale SNP data through microarray analysis from Korean individuals involving 13 kinship cases and calculated GD-ICS values using the method described in our previous study. Based on the GD-ICS reference constructed for Korean families, each disputed kinship was evaluated and validated using a combination of traditional STRs and lineage markers.

RESULTS

The cases comprised those A) that were found to be inconclusive using the traditional approach, B) for which it was difficult to apply traditional testing methods, and C) that were more conclusively resolved using the GD-ICS method. This method has overcome the limitations faced by traditional STRs in kinship testing, particularly in a paternity case with STR mutational events and in confirming distant kinship where the individual of interest is unavailable for testing. It has also been demonstrated to be effective in identifying various relationships without specific presumptions and in confirming a lack of genetic relatedness between individuals.

CONCLUSION

This method has been proven effective in identifying familial relationships across diverse complex and practical scenarios. It is not only useful when traditional testing methods fail to provide conclusive results, but it also enhances the resolution of challenging kinship cases, which suggests its applicability in various types of practical casework.

Forensic investigative genetic genealogy: expanding pedigree tracing and genetic inquiry in the genomic era

Genetic genealogy provides crucial insights into the complex biological relationships within contemporary and ancient human populations by analyzing shared alleles and chromosomal segments that are identical by descent to understand kinship, migration patterns, and population dynamics. Within forensic science, forensic investigative genetic genealogy (FIGG) has gained prominence by leveraging next-generation sequencing technologies and population-specific genomic resources, opening new investigative avenues. In this review, we synthesize current knowledge, underscore recent advancements, and discuss the growing role of FIGG in forensic genomics. FIGG has been pivotal in revitalizing dormant inquiries and offering new genetic leads in numerous cold cases. Its effectiveness relies on the extensive single-nucleotide polymorphism profiles contributed by individuals from diverse populations to specialized genomic databases. Advances in computational genomics and the growth of human genomic databases have spurred a profound shift in the application of genetic genealogy across forensics, anthropology, and ancient DNA studies. As the field progresses, FIGG is evolving from a nascent practice into a more sophisticated and specialized discipline, shaping the future of forensic investigations.

Effects and considerations of multiplexing ForenSeq Kintelligence libraries with a negative control

The negative template control or negative amplification control has been an essential component of the forensic DNA analysis workflow that helps monitor contamination. As such, the inclusion of a negative control in forensic DNA analysis has been a requirement for all laboratories audited under the FBI's Quality Assurance Standards. As massively parallel sequencing (MPS) becomes more conventional in forensic laboratories, considerations for the inclusion of a negative control in every sequencing run can be evaluated. Although the inclusion of a negative control in library preparation and the first sequencing run has a practical function, there is less utility for its inclusion in all subsequent sequencing runs for that library preparation. Although this is universal to all MPS assays, it is most relevant for an assay that has a low sample multiplexing capacity, such as the ForenSeq Kintelligence Kit (Qiagen/Verogen, Inc.). The ForenSeq Kintelligence Kit is an investigative genetic genealogy (IGG) sequencing-based assay that targets 10,230 forensically relevant single-nucleotide polymorphisms. The manufacturer recommends multiplexing 3 libraries per sequencing run, which includes controls. The purpose of this study was to investigate the effect of the inclusion of a negative control in every Kintelligence sequencing run. We observed that the library generated from a negative amplification control will take 7%-14% of the run output. The loss of sequencing space taken by a negative control decreased the available output for DNA-containing samples, leading in some cases to allele or locus dropout and accompanying higher numbers of sixth to seventh order unknown associations in GEDmatch PRO.

Operationalisation of the ForenSeq® Kintelligence Kit for Australian unidentified and missing persons casework

Single nucleotide polymorphism (SNP) genotyping technologies can generate investigative leads for human remains identification, including estimation of biological sex, biogeographical ancestry (BGA), externally visible characteristics (EVCs), identity, uniparental lineage and extended kinship. The ForenSeq® Kintelligence Kit provides forensic laboratories with the ability to apply this suite of genetic tools to forensic samples using one panel targeting 10,230 SNPs (including 56 ancestry-informative, 24 phenotype-informative, 94 identity-informative, 106 X chromosome, 85 Y chromosome and 9867 kinship-informative SNPs) sequenced on the MiSeq FGx® Sequencing System. The ForenSeq® Kintelligence Kit has been internally validated, optimised and operationalised by the Australian Federal Police National DNA Program for Unidentified and Missing Persons (AFP Program) for coronial casework. The internal validation was conducted according to the Scientific Working Group on DNA Analysis Methods guidelines (excluding mixture analysis), focussing on sample types typically encountered in human remains identification casework, such as bones, teeth, nail, blood and hair. The workflow was optimised for a high throughput library preparation and sequencing workflow, and additional analytical thresholds were developed to improve genotyping accuracy for low DNA input samples. Additionally, the genetic intelligence generated from the kit was compared to the self-declared biological sex, EVCs and BGA of the DNA donors to assess concordance. The kit was able to produce high quality SNP profiles from 1.0 ng down to 0.1 ng of DNA, with high repeatability and reproducibility, and minimal background noise. The prediction accuracy for biological sex (95%), hair colour (58%), eye colour (74%) and BGA inferences (consistent: 74%; partially consistent: 10%; inconclusive: 16%) was determined based on self-declared data. Additionally, SNP profiles from a volunteer family group of ten related individuals were uploaded to GEDmatch PRO™ to assess kinship accuracy. The kit was capable of detecting (97%) and accurately classifying (90%) genetic relationships spanning from first to fifth degree. The Kintelligence Kit provides the AFP Program with a robust and reliable genetic intelligence tool for unidentified and missing persons investigations, which has been designed to sequence multiple challenging samples in a single multiplexed assay using existing laboratory instrumentation.

Review: Computational analysis of human skeletal remains in ancient DNA and forensic genetics

Degraded DNA is used to answer questions in the fields of ancient DNA (aDNA) and forensic genetics. While aDNA studies typically center around human evolution and past history, and forensic genetics is often more concerned with identifying a specific individual, scientists in both fields face similar challenges. The overlap in source material has prompted periodic discussions and studies on the advantages of collaboration between fields toward mutually beneficial methodological advancements. However, most have been centered around wet laboratory methods (sampling, DNA extraction, library preparation, etc.). In this review, we focus on the computational side of the analytical workflow. We discuss limitations and considerations to consider when working with degraded DNA. We hope this review provides a framework to researchers new to computational workflows for how to think about analyzing highly degraded DNA and prompts an increase of collaboration between the forensic genetics and aDNA fields.

A cost-benefit analysis for use of large SNP panels and high throughput typing for forensic investigative genetic genealogy

Next-generation sequencing (NGS), also known as massively sequencing, enables large dense SNP panel analyses which generate the genetic component of forensic investigative genetic genealogy (FIGG). While the costs of implementing large SNP panel analyses into the laboratory system may seem high and daunting, the benefits of the technology may more than justify the investment. To determine if an infrastructural investment in public laboratories and using large SNP panel analyses would reap substantial benefits to society, a cost-benefit analysis (CBA) was performed. This CBA applied the logic that an increase of DNA profile uploads to a DNA database due to a sheer increase in number of markers and a greater sensitivity of detection afforded with NGS and a higher hit/association rate due to large SNP/kinship resolution and genealogy will increase investigative leads, will be more effective for identifying recidivists which in turn reduces future victims of crime, and will bring greater safety and security to communities. Analyses were performed for worst case/best case scenarios as well as by simulation sampling the range spaces with multiple input values simultaneously to generate best estimate summary statistics. This study shows that the benefits, both tangible and intangible, over the lifetime of an advanced database system would be huge and can be projected to be for less than $1 billion per year (over a 10-year period) investment can reap on average > $4.8 billion in tangible and intangible cost-benefits per year. More importantly, on average > 50,000 individuals need not become victims if FIGG were employed, assuming investigative associations generated were acted upon. The benefit to society is immense making the laboratory investment a nominal cost. The benefits likely are underestimated herein. There is latitude in the estimated costs, and even if they were doubled or tripled, there would still be substantial benefits gained with a FIGG-based approach. While the data used in this CBA are US centric (primarily because data were readily accessible), the model is generalizable and could be used by other jurisdictions to perform relevant and representative CBAs.

Applications of 1993 single nucleotide polymorphism loci in forensic pairwise kinship identifications and inferences

Kinship testing plays critical roles in criminal investigations, missing person searches, civil disputes, as well as identifying disaster victims. The existing commonly used short tandem repeat (STR) loci have limited effectiveness in the identification of second-degree and more distant kinships. In this study, a total of 1993 SNP loci of 119 Chinese Han individuals from eight families were sequenced on the MGISEQ-2000RS platform. The system powers of this panel for kinship identifications were evaluated based on both the likelihood ratio (LR) and identical by state (IBS) methods. The results indicated that this panel could be used as an effective tool to kinship analyses including paternity testing, full sibling testing, second-degree kinships, and first cousin kinship analyses. Both the LR and IBS methods could be applied in distinguishing first-degree and second-degree pairs from unrelated individuals. Based on the 1993 SNP loci, LR>1000 and LR<0.001 are recommended as the thresholds of identifying first-cousin kinships from unrelated individuals, and the system power of such thresholds was 0.9470. Besides, kinship coefficients for different kinship pairs were estimated and then were used to predict the kinships for pairwise individuals. This panel performs an effective kinship inference power for the predictions of first-degree, second-degree kinships and unrelated individual pairs, while presenting low sensitivity in the prediction of first-cousin kinships.

Applying Unique Molecular Indices with an Extensive All-in-One Forensic SNP Panel for Improved Genotype Accuracy and Sensitivity

One of the major challenges in forensic genetics is being able to detect very small amounts of DNA. Massively parallel sequencing (MPS) enables sensitive detection; however, genotype errors may exist and could interfere with the interpretation. Common errors in MPS-based analysis are often induced during PCR or sequencing. Unique molecular indices (UMIs) are short random nucleotide sequences ligated to each template molecule prior to amplification. Applying UMIs can improve the limit of detection by enabling accurate counting of initial template molecules and removal of erroneous data. In this study, we applied the FORCE panel, which includes ~5500 SNPs, with a QIAseq Targeted DNA Custom Panel (Qiagen), including UMIs. Our main objective was to investigate whether UMIs can enhance the sensitivity and accuracy of forensic genotyping and to evaluate the overall assay performance. We analyzed the data both with and without the UMI information, and the results showed that both genotype accuracy and sensitivity were improved when applying UMIs. The results showed very high genotype accuracies (>99%) for both reference DNA and challenging samples, down to 125 pg. To conclude, we show successful assay performance for several forensic applications and improvements in forensic genotyping when applying UMIs.

Revisiting informed consent in forensic genomics in light of current technologies and the times

Informed consent is based on basic ethical principles that should be considered when conducting biomedical and behavioral research involving human subjects. These principles-respect, beneficence, and justice-form the foundations of informed consent which in itself is grounded on three fundamental elements: information, comprehension, and voluntary participation. While informed consent has focused on human subjects and research, the practice has been adopted willingly in the forensic science arena primarily to acquire reference samples from family members to assist in identifying missing persons. With advances in molecular biology technologies, data mining, and access to metadata, it is important to assess whether the past informed consent process and in particular associated risks are concomitant with these increased capabilities. Given the state-of-the-art, areas in which informed consent may need to be modified and augmented are as follows: reference samples from family members in missing persons or unidentified human remains cases; targeted analysis of an individual(s) during forensic genetic genealogy cases to reduce an investigative burden; donors who provide their samples for validation studies (to include population studies and entry into databases that would be applied to forensic statistical calculations) to support implementation of procedures and operations of the forensic laboratory; family members that may contribute samples or obtain genetic information from a molecular autopsy; and use of medical and other acquired samples that could be informative for identification purposes. The informed consent process should cover (1) purpose for collection of samples; (2) process to analyze the samples (to include type of data); (3) benefits (to donor, target, family, community, etc. as applicable); (4) risks (to donor, target, family, community, etc. as applicable); (5) access to data/reports by the donor; (6) sample disposition; (7) removal of data process (i.e., expungement); (8) process to ask questions/assessment of comprehension; (9) follow-up processes; and (10) voluntary, signed, and dated consent. Issues surrounding these topics are discussed with an emphasis on addressing risk factors. Addressing informed consent will allow human subjects to make decisions voluntarily and with autonomy as well as secure the use of samples for intended use.