Forensic genealogy—A comparison of methods to infer distant relationships based on dense SNP data

Enhancing testing efficacy of high-density SNP microarrays to distinguish pedigrees belonging to the same kinship class

Kinship testing, which involves genotyping genetic markers and comparing their profiles between individuals, holds significant applications in forensic science. However, the prevalent use of independent markers often lacks the discriminatory power to distinguish pedigrees belong to the same kinship class. While numerous studies have attempted to address this challenge through diverse approaches, the testing efficacy of high-density SNP microarrays in combination with the likelihood approach remains unclear. In this study, we further explored the utilization of linked autosomal SNPs derived from microarrays with the likelihood approach. Several SNP panels with differing numbers of loci were developed and putative pedigrees were constructed to evaluated to test their efficacy in distinguishing second-degree relationships, including grandparent-grandchild, half-siblings, and avuncular. Our findings indicate that the use of high-density SNP microarrays is theoretically feasible for discriminating second-degree relationships, with balanced classification rates ranging from 0.444 to 0.853. Moreover, to optimize the practical effectiveness of discriminating pedigrees belonging to the same kinship class, several other aspects such as adding additional SNPs or an additional relative and examining the effects of genotype errors and population selection were discussed. Our results revealed that the employment of denser marker sets with more accurate genotyping methods may be beneficial. Additionally, the inclusion of additional relatives and the selection of an appropriate reference population also appear to be crucial factors for enhancing the accuracy of kinship testing. In conclusion, our study provides insights into the potential of high-density SNPs in kinship testing and highlights the need for further optimization and examination into various factors that may contribute to enhancing testing efficacy.

Pairwise kinship inference and pedigree reconstruction using 91 microhaplotypes

Kinship inference has been a major issue in forensic genetics, and it remains to be solved when there is no prior hypothesis and the relationships between multiple individuals are unknown. In this study, we genotyped 91 microhaplotypes from 46 pedigree samples using massive parallel sequencing and inferred their relatedness by calculating the likelihood ratio (LR). Based on simulated and real data, different treatments were applied in the presence and absence of relatedness assumptions. The pedigree of multiple individuals was reconstructed by calculating pedigree likelihoods based on real pedigree samples. The results showed that the 91 MHs could discriminate pairs of second-degree relatives from unrelated individuals. And more highly polymorphic loci were needed to discriminate the pairs of second-degree or more distant relative from other degrees of relationship, but correct classification could be obtained by expanding the suspected relationship searched to other relationships with lower LR values. Multiple individuals with unknown relationships can be successfully reconstructed if they are closely related. Our study provides a solution for kinship inference when there are no prior assumptions, and explores the possibility of pedigree reconstruction when the relationships of multiple individuals are unknown.

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.

MHBase: A comprehensive database of short microhaplotypes for advancing forensic genetic analysis

Microhaplotypes (MHs) were first recommended by Prof. Kidd for use in forensics because they can improve human identification, kinship analysis, mixture deconvolution, and ancestry prediction. Since their introduction, extensive research has demonstrated the advantages of MHs in forensic applications and provided useful data for different populations. Currently, two databases, ALFRED (ALlele FREquency Database) and MicroHapDB (MicroHaplotype DataBase), house the published MH information and population data. We previously constructed a single nucleotide polymorphism SNP-SNP MH database (D-SNPsDB) of MHs within 50 bp on the whole human genome for 26 populations integrating basic data such as physical genome positions, mapping of variant identifiers (rsIDs), allele frequencies, and basic variant information. Building upon the previous research, we further selected MHs containing at least two variants (SNPs and/or insertions/deletions [InDels]) within a short DNA fragment (≤ 50 bp) in 26 populations based on the 1000 Genomes Project dataset (Phase 3) to construct a more comprehensive database. Subsequently, we established a user-friendly website that allows users to search the MH database (MHBase) based on their research objectives and study population to find suitable loci and provides other functions such as querying reported loci, performing online calculations using the PHASE software, and calculating ancestral-related parameters. The loci in the database are classified as SNP-based MHs, which include only SNPs, and InDel-including MHs, which contain at least one InDel. Here, we provide a detailed overview of the MHBase and an analysis of shared loci at the global and continental levels, ancestral markers, the genetic distance within loci, and mapping with the genome annotation file. The website is an accessible and useful tool for researchers engaged in marker discovery, population studies, assay development, and panel design.

A novel approach of kinship determination based on the physical length of genetically shared regions of chromosomes

BACKGROUND

Determination of genetic relatedness between individuals plays a crucial role in resolving numerous civil cases involving familial relationships and in forensic investigation concerning missing persons. Short tandem repeats (STRs), known for their high degree of DNA polymorphism, have traditionally been the primary choice of DNA markers in genetic testing, but their application for kinships testing is limited to cases involving close kinship. SNPs have emerged as promising supplementary markers for kinship determination. Nevertheless, the challenging remains in discriminating between third-degree or more distant relatives, such as first cousins, using SNPs.

OBJECTIVE

To investigate a kinship analysis method for distant degree of familial relationships using high-density SNP data.

METHODS

A high-density SNP data from 337 individuals of Korean families using Affymetrix Axiom KORV1.0-96 Array was obtained for this study. SNPs were aligned by chromosomal positions, and identity-by-state (IBS) was determined, and then shared regions as consecutive SNPs with IBS of 1 or 2 were investigated. The physical lengths of these IBS segments were measured and summed them to create an Index, as a measure of kinship.

RESULTS

The kinship was determined by the physical length of shared chromosomal regions that are distinguished by each kinship. Using this method, the relationship was able be distinguished up to the fourth degree of kinship, and non-relatives were clearly distinguished from true relatives. We also found a potential for this approach to be used universally, regardless of microarray platforms for SNP genotyping and populations.

CONCLUSION

This method has a potential to determine the different degree of kinship between individuals and to distinguish non-relatives from true relatives, which can be of great help for practical applications in kinship determination.

Identifying distant relatives using benchtop-scale sequencing

The genetic component of forensic genetic genealogy (FGG) is an estimate of kinship, often conducted at genome scales between a great number of individuals. The promise of FGG is substantial: in concert with genealogical records and other nongenetic information, it can indirectly identify a person of interest. A downside of FGG is cost, as it is currently expensive and requires chemistries uncommon to forensic genetic laboratories (microarrays and high throughput sequencing). The more common benchtop sequencers can be coupled with a targeted PCR assay to conduct FGG, though such approaches have limited resolution for kinship. This study evaluates low-pass sequencing, an alternative strategy that is accessible to benchtop sequencers and can produce resolutions comparable to high-pass sequencing. Samples from a three-generation pedigree were augmented to include up to 7th degree relatives (using whole genome pedigree simulations) and the ability to recover the true kinship coefficient was assessed using algorithms qualitatively similar to those found in GEDmatch. We show that up to 7th degree relatives can be reliably inferred from 1 × whole genome sequencing obtainable from desktop sequencers.

An approach to unified formulae for likelihood ratio calculation in pairwise kinship analysis

Introduction: The likelihood ratio (LR) can be an efficient means of distinguishing various relationships in forensic fields. However, traditional list-based methods for derivation and presentation of LRs in distant or complex relationships hinder code editing and software programming. This paper proposes an approach for a unified formula for LRs, in which differences in participants' genotype combinations can be ignored for specific identification. This formula could reduce the difficulty of by-hand coding, as well as running time of large-sample-size simulation. Methods: The approach is first applied to a problem of kinship identification in which at least one of the participants is alleged to be inbred. This can be divided into two parts: i) the probability of different identical by descent (IBD) states according to the alleged kinship; and ii) the ratio of the probability that specific genotype combination can be detected assuming the alleged kinship exists between the two participants to the similar probability assuming that they are unrelated, for each state. For the probability, there are usually recognized results for common identification purposes. For the ratio, subscript letters representing IBD alleles of individual A's alleles are used to eliminate differences in genotype combinations between the two individuals and to obtain a unified formula for the ratio in each state. The unification is further simplified for identification cases in which it is alleged that both of the participants are outbred. Verification is performed to show that the results obtained with the unified and list-form formulae are equivalent. Results: A series of unified formulae are derived for different identification purposes, based on which an R package named KINSIMU has been developed and evaluated for use in large-size simulations for kinship analysis. Comparison between the package with two existing tools indicated that the unified approach presented here is more convenient and time-saving with respect to the coding process for computer applications compared with the list-based approach, despite appearing more complicated. Moreover, the method of derivation could be extended to other identification problems, such as those with different hypothesis sets or those involving multiple individuals. Conclusion: The unified approach of LR calculation can be beneficial in kinship identification field.

FiMAP: A fast identity-by-descent mapping test for biobank-scale cohorts

Although genome-wide association studies (GWAS) have identified tens of thousands of genetic loci, the genetic architecture is still not fully understood for many complex traits. Most GWAS and sequencing association studies have focused on single nucleotide polymorphisms or copy number variations, including common and rare genetic variants. However, phased haplotype information is often ignored in GWAS or variant set tests for rare variants. Here we leverage the identity-by-descent (IBD) segments inferred from a random projection-based IBD detection algorithm in the mapping of genetic associations with complex traits, to develop a computationally efficient statistical test for IBD mapping in biobank-scale cohorts. We used sparse linear algebra and random matrix algorithms to speed up the computation, and a genome-wide IBD mapping scan of more than 400,000 samples finished within a few hours. Simulation studies showed that our new method had well-controlled type I error rates under the null hypothesis of no genetic association in large biobank-scale cohorts, and outperformed traditional GWAS single-variant tests when the causal variants were untyped and rare, or in the presence of haplotype effects. We also applied our method to IBD mapping of six anthropometric traits using the UK Biobank data and identified a total of 3,442 associations, 2,131 (62%) of which remained significant after conditioning on suggestive tag variants in the ± 3 centimorgan flanking regions from GWAS.

Concurrently mapping quantitative trait loci associations from multiple subspecies within hybrid populations

Many of the world's agriculturally important plant and animal populations consist of hybrids of subspecies. Cattle in tropical and sub-tropical regions for example, originate from two subspecies, Bos taurus indicus (Bos indicus) and Bos taurus taurus (Bos taurus). Methods to derive the underlying genetic architecture for these two subspecies are essential to develop accurate genomic predictions in these hybrid populations. We propose a novel method to achieve this. First, we use haplotypes to assign SNP alleles to ancestral subspecies of origin in a multi-breed and multi-subspecies population. Then we use a BayesR framework to allow SNP alleles originating from the different subspecies differing effects. Applying this method in a composite population of B. indicus and B. taurus hybrids, our results show that there are underlying genomic differences between the two subspecies, and these effects are not identified in multi-breed genomic evaluations that do not account for subspecies of origin effects. The method slightly improved the accuracy of genomic prediction. More significantly, by allocating SNP alleles to ancestral subspecies of origin, we were able to identify four SNP with high posterior probabilities of inclusion that have not been previously associated with cattle fertility and were close to genes associated with fertility in other species. These results show that haplotypes can be used to trace subspecies of origin through the genome of this hybrid population and, in conjunction with our novel Bayesian analysis, subspecies SNP allele allocation can be used to increase the accuracy of QTL association mapping in genetically diverse populations.

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.

Complete Mitochondrial DNA Genome Variation in the Swedish Population

The development of complete mitochondrial genome (mitogenome) reference data for inclusion in publicly available population databases is currently underway, and the generation of more high-quality mitogenomes will only enhance the statistical power of this forensically useful locus. To characterize mitogenome variation in Sweden, the mitochondrial DNA (mtDNA) reads from the SweGen whole genome sequencing (WGS) dataset were analyzed. To overcome the interference from low-frequency nuclear mtDNA segments (NUMTs), a 10% variant frequency threshold was applied for the analysis. In total, 934 forensic-quality mitogenome haplotypes were characterized. Almost 45% of the SweGen haplotypes belonged to haplogroup H. Nearly all mitogenome haplotypes (99.1%) were assigned to European haplogroups, which was expected based on previous mtDNA studies of the Swedish population. There were signature northern Swedish and Finnish haplogroups observed in the dataset (e.g., U5b1, W1a), consistent with the nuclear DNA analyses of the SweGen data. The complete mitogenome analysis resulted in high haplotype diversity (0.9996) with a random match probability of 0.15%. Overall, the SweGen mitogenomes provide a large mtDNA reference dataset for the Swedish population and also contribute to the effort to estimate global mitogenome haplotype frequencies.

Testing of two SNP array-based genealogy algorithms using extended Han Chinese pedigrees and recommendations for improved performances in forensic practice

Distant genetic relatives can be linked to a crime scene sample by computing identity-by-state (IBS) and identity-by-descent (IBD) shared by individuals. To test the methods of genetic genealogy estimation and optimal the parameters for forensic investigation, a family-based genetic genealogy analysis was performed using a dataset of 262 Han Chinese individuals from 11 families. The dataset covered relative pairs from 1st- to 14th degrees. But the 7th-degree relative is the most distant kinship to be fully investigated, and each individual has ∼200 relatives within the 7th degree. The KING algorithm by calculating IBS and IBD statistics can correctly discriminate the first-degree relationships of monozygotic twin, parent-offspring and full sibling. The inferred relationship was reliable within the fifth-degree, false positive rate <1.8%. The IBD segment algorithm, GERMLINE + ERSA, could provide reliable inference result prolonged to eighth degree. Analysis of IBD segments produced obviously false negative estimations (<27.4%) rather than false positives (0%) within the eighth-degree inferences. We studied different minimum IBD segment threshold settings (changed from >0 to 6 cM); the inferred results did not make much difference. In distant relative analysis, genetically undetectable relationships begin to occur from the sixth degree (second cousin once removed), which means the offspring after seven meiotic divisions may share no ancestor IBD segment at all. Application of KING and GERMLINE + ERSA worked complementarily to ensure accurate inference from first degree to eighth degree. Using simulated low call rate data, the KING algorithm shows better tolerance to marker decrease compared with the GERMLINE + ERSA segment algorithm.

A computational approach for positive genetic identification and relatedness detection from low-coverage shotgun sequencing data

Several methods exist for detecting genetic relatedness or identity by comparing DNA information. These methods generally require genotype calls, either single-nucleotide polymorphisms or short tandem repeats, at the sites used for comparison. For some DNA samples, like those obtained from bone fragments or single rootless hairs, there is often not enough DNA present to generate genotype calls that are accurate and complete enough for these comparisons. Here, we describe IBDGem, a fast and robust computational procedure for detecting genomic regions of identity-by-descent by comparing low-coverage shotgun sequence data against genotype calls from a known query individual. At less than 1× genome coverage, IBDGem reliably detects segments of relatedness and can make high-confidence identity detections with as little as 0.01× genome coverage.

Recent advances in forensic biology and forensic DNA typing: INTERPOL review 2019-2022

This review paper covers the forensic-relevant literature in biological sciences from 2019 to 2022 as a part of the 20th INTERPOL International Forensic Science Managers Symposium. Topics reviewed include rapid DNA testing, using law enforcement DNA databases plus investigative genetic genealogy DNA databases along with privacy/ethical issues, forensic biology and body fluid identification, DNA extraction and typing methods, mixture interpretation involving probabilistic genotyping software (PGS), DNA transfer and activity-level evaluations, next-generation sequencing (NGS), DNA phenotyping, lineage markers (Y-chromosome, mitochondrial DNA, X-chromosome), new markers and approaches (microhaplotypes, proteomics, and microbial DNA), kinship analysis and human identification with disaster victim identification (DVI), and non-human DNA testing including wildlife forensics. Available books and review articles are summarized as well as 70 guidance documents to assist in quality control that were published in the past three years by various groups within the United States and around the world.

Evaluating the Impact of Dropout and Genotyping Error on SNP-Based Kinship Analysis With Forensic Samples

Technological advances in sequencing and single nucleotide polymorphism (SNP) genotyping microarray technology have facilitated advances in forensic analysis beyond short tandem repeat (STR) profiling, enabling the identification of unknown DNA samples and distant relationships. Forensic genetic genealogy (FGG) has facilitated the identification of distant relatives of both unidentified remains and unknown donors of crime scene DNA, invigorating the use of biological samples to resolve open cases. Forensic samples are often degraded or contain only trace amounts of DNA. In this study, the accuracy of genome-wide relatedness methods and identity by descent (IBD) segment approaches was evaluated in the presence of challenges commonly encountered with forensic data: missing data and genotyping error. Pedigree whole-genome simulations were used to estimate the genotypes of thousands of individuals with known relationships using multiple populations with different biogeographic ancestral origins. Simulations were also performed with varying error rates and types. Using these data, the performance of different methods for quantifying relatedness was benchmarked across these scenarios. When the genotyping error was low (<1%), IBD segment methods outperformed genome-wide relatedness methods for close relationships and are more accurate at distant relationship inference. However, with an increasing genotyping error (1–5%), methods that do not rely on IBD segment detection are more robust and outperform IBD segment methods. The reduced call rate had little impact on either class of methods. These results have implications for the use of dense SNP data in forensic genomics for distant kinship analysis and FGG, especially when the sample quality is low.

The overview of forensic genetic genealogy

Forensic genetic genealogy (FGG) benefits largely from popularity of genealogical research within (mostly) American society and the advent of new sequencing techniques that allow typing of challenging forensic samples. It is considered a true breakthrough for both active and especially cold cases where all other resources and methods have failed during investigation. Despite media coverage generally highlighting its powers, the method itself is considered very laborious and the investigation may easily got suspended at every stage due to many factors including no hits in the database or breaks in traceable lineages within the family tree. This review summarizes the scope of FGG use, mentions most concerns and misconceptions associated with the technique and points to the plausible solutions already suggested. It also brings together current guidelines and regulations intended to be followed by law enforcement authorities wishing to utilize genetic genealogy research.

Extended kinship analysis of historical remains using SNP capture

DNA-assisted identification of historical remains requires the genetic analysis of highly degraded DNA, along with a comparison to DNA from known relatives. This can be achieved by targeting single nucleotide polymorphisms (SNPs) using a hybridization capture and next-generation sequencing approach suitable for degraded skeletal samples. In the present study, two SNP capture panels were designed to target ~ 25,000 (25 K) and ~ 95,000 (95 K) nuclear SNPs, respectively, to enable distant kinship estimation (up to 4th degree relatives). Low-coverage SNP data were successfully recovered from 14 skeletal elements 75 years postmortem using an Illumina MiSeq benchtop sequencer. All samples contained degraded DNA but were of varying quality with mean fragment lengths ranging from 32 bp to 170 bp across the 14 samples. SNP comparison with DNA from known family references was performed in the Parabon Fx Forensic Analysis Platform, which utilizes a likelihood approach for kinship prediction that was optimized for low-coverage sequencing data with cytosine deamination. The 25 K panel produced 15,000 SNPs on average, which allowed for accurate kinship prediction with strong statistical support in 16 of the 21 pairwise comparisons. The 95 K panel increased the average SNPs to 42,000 and resulted in an additional accurate kinship prediction with strong statistical support (17 of 21 pairwise comparisons). This study demonstrates that SNP capture combined with massively parallel sequencing on a benchtop platform can yield sufficient SNP recovery from compromised samples, enabling accurate, extended kinship predictions.

Impact of SNP microarray analysis of compromised DNA on kinship classification success in the context of investigative genetic genealogy

Single nucleotide polymorphism (SNP) data generated with microarray technologies have been used to solve murder cases via investigative leads obtained from identifying relatives of the unknown perpetrator included in accessible genomic databases, an approach referred to as investigative genetic genealogy (IGG). However, SNP microarrays were developed for relatively high input DNA quantity and quality, while DNA typically obtainable from crime scene stains is of low DNA quantity and quality, and SNP microarray data obtained from compromised DNA are largely missing. By applying the Illumina Global Screening Array (GSA) to 264 DNA samples with systematically altered quantity and quality, we empirically tested the impact of SNP microarray analysis of compromised DNA on kinship classification success, as relevant in IGG. Reference data from manufacturer-recommended input DNA quality and quantity were used to estimate genotype accuracy in the compromised DNA samples and for simulating data of different degree relatives. Although stepwise decrease of input DNA amount from 200 ng to 6.25 pg led to decreased SNP call rates and increased genotyping errors, kinship classification success did not decrease down to 250 pg for siblings and 1st cousins, 1 ng for 2nd cousins, while at 25 pg and below kinship classification success was zero. Stepwise decrease of input DNA quality via increased DNA fragmentation resulted in the decrease of genotyping accuracy as well as kinship classification success, which went down to zero at the average DNA fragment size of 150 base pairs. Combining decreased DNA quantity and quality in mock casework and skeletal samples further highlighted possibilities and limitations. Overall, GSA analysis achieved maximal kinship classification success from 800 to 200 times lower input DNA quantities than manufacturer-recommended, although DNA quality plays a key role too, while compromised DNA produced false negative kinship classifications rather than false positive ones.

Validation of a 6-Dye Short Tandem Repeat System: A Dry Kit With Lyophilized Amplification Reagent

The SureID®S6 system used a lyophilized pellet as the amplification reagent to enable multiplexing of sex-determining marker Amelogenin, 21 autosomal short tandem repeats (STRs), and one Y-STR. To assess the performance, reliability, and limitation of the dry amplification system, the validation studies including PCR condition, reproducibility, sizing and precision, analytical threshold calculation, sensitivity and stochastic threshold calculation, species specificity, stability, mixture, case sample, and population and concordance were conducted according to the Scientific Working Group on DNA Analysis Methods (SWGDAM) Validation Guidelines. Experimental data suggested that the optimal range of total input DNA was from 125 to 500 pg; the appropriate analytical threshold was 80 relative fluorescence units (RFUs) while the stochastic threshold was 260 RFUs; for the stability studies, SureID®S6 system could resist against less than 500 μmol/L of hematin, 100 ng/μl of humic acid, 4 mM of indigotin, 800 mM of tannic acid, and 800 mM of calcium ion. Population and concordance studies using 500 unrelated individuals showed that the combined probability of discrimination (CPD) and cumulative probability of exclusion (CPE) values were 0.999999999999 and 0.999999998416, respectively. The genotypes for the same sample were concordant with the previously validated HUAXIA™ Platinum kit. The validation results demonstrated that the SureID®S6 system could be used for forensic applifications.

The use of shared haplotype length information for pedigree reconstruction in asexually propagated outbreeding crops, demonstrated for apple and sweet cherry

Pedigree information is of fundamental importance in breeding programs and related genetics efforts. However, many individuals have unknown pedigrees. While methods to identify and confirm direct parent-offspring relationships are routine, those for other types of close relationships have yet to be effectively and widely implemented with plants, due to complications such as asexual propagation and extensive inbreeding. The objective of this study was to develop and demonstrate methods that support complex pedigree reconstruction via the total length of identical by state haplotypes (referred to in this study as "summed potential lengths of shared haplotypes", SPLoSH). A custom Python script, HapShared, was developed to generate SPLoSH data in apple and sweet cherry. HapShared was used to establish empirical distributions of SPLoSH data for known relationships in these crops. These distributions were then used to estimate previously unknown relationships. Case studies in each crop demonstrated various pedigree reconstruction scenarios using SPLoSH data. For cherry, a full-sib relationship was deduced for 'Emperor Francis, and 'Schmidt', a half-sib relationship for 'Van' and 'Windsor', and the paternal grandparents of 'Stella' were confirmed. For apple, 29 cultivars were found to share an unknown parent, the pedigree of the unknown parent of 'Cox's Pomona' was reconstructed, and 'Fameuse' was deduced to be a likely grandparent of 'McIntosh'. Key genetic resources that enabled this empirical study were large genome-wide SNP array datasets, integrated genetic maps, and previously identified pedigree relationships. Crops with similar resources are also expected to benefit from using HapShared for empowering pedigree reconstruction.

Getting the conclusive lead with investigative genetic genealogy - A successful case study of a 16 year old double murder in Sweden

On the morning of October 19, 2004, an eight-year-old boy and a 56-year-old woman were stabbed to death on an open street in the city of Linköping, Sweden. The perpetrator left his DNA at the crime scene, and after 15 years of various investigation efforts, including more than 9000 interrogations and mass DNA screening of more than 6000 men, there were still no clues about the identity of the unknown murderer. The successful application of investigative genetic genealogy (IGG) in the US raised the interest for this tool within the Swedish Police Authority. After legal consultations it was decided that IGG could be applied in this double murder case as a pilot case study. From extensive DNA analysis, including whole-genome sequencing and genotype imputation, DNA data sets were established and searched within both GEDmatch and FamilyTree DNA genealogy databases. A number of fairly distant relatives were found from which family trees were created. The genealogy work resulted in two candidates, two brothers, one of whom matched the crime scene samples by routine STR profiling. The suspect confessed the murders at the initial police hearing and was later convicted of the murders. In this paper we describe the successful application of an emerging technology. We disclose details of the DNA analyses which, due to the poor quality and low quantity of the DNA, required reiterative sequencing and genotype imputation efforts. The successful application of IGG in this double murder case exemplifies its applicability not only in the US but also in Europe. The pressure is now high on the involved authorities to establish IGG as a tool for cold case criminal investigations and for missing person identifications. There is, however, a continuous need to accommodate legal, social and ethical aspects as well.

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.

A likelihood ratio approach for identifying three-quarter siblings in genetic databases

The detection of family relationships in genetic databases is of interest in various scientific disciplines such as genetic epidemiology, population and conservation genetics, forensic science, and genealogical research. Nowadays, screening genetic databases for related individuals forms an important aspect of standard quality control procedures. Relatedness research is usually based on an allele sharing analysis of identity by state (IBS) or identity by descent (IBD) alleles. Existing IBS/IBD methods mainly aim to identify first-degree relationships (parent-offspring or full siblings) and second degree (half-siblings, avuncular, or grandparent-grandchild) pairs. Little attention has been paid to the detection of in-between first and second-degree relationships such as three-quarter siblings (3/4S) who share fewer alleles than first-degree relationships but more alleles than second-degree relationships. With the progressively increasing sample sizes used in genetic research, it becomes more likely that such relationships are present in the database under study. In this paper, we extend existing likelihood ratio (LR) methodology to accurately infer the existence of 3/4S, distinguishing them from full siblings and second-degree relatives. We use bootstrap confidence intervals to express uncertainty in the LRs. Our proposal accounts for linkage disequilibrium (LD) by using marker pruning, and we validate our methodology with a pedigree-based simulation study accounting for both LD and recombination. An empirical genome-wide array data set from the GCAT Genomes for Life cohort project is used to illustrate the method.

Familial DNA analysis and criminal investigation: Usage, downsides and privacy concerns

Since the discovery of Deoxyribonucleic acid (DNA) capability in forensic investigation, it has been an important part of the criminal justice system. In most criminal cases DNA profile originating from evidence sample collected from the crime scene is compared with the DNA profile from the reference sample. However, when a reference sample is not available for comparison, familial DNA analysis can provide important investigation leads in a criminal investigation process by identifying an individual. Moreover, this analysis is also proving effective in the identification of ethnicity and ancestry of an individual. A number of different methodologies and software are being used for familial DNA analysis. This review describes the importance of familial DNA analysis, methodologies used for familial DNA searching and identification, and its advantages in forensic. Moreover, ethical, legal and social issues associated with familial DNA analysis have also been discussed along with future directions for the proper implementation of this technology.