How many familial relationship testing results could be wrong?

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.

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.

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.

NIPAT as Non-Invasive Prenatal Paternity Testing Using a Panel of 861 SNVs

In 1997, it was discovered that maternal plasma contains Cell-Free Fetal DNA (cffDNA). cffDNA has been investigated as a source of DNA for non-invasive prenatal testing for fetal pathologies, as well as for non-invasive paternity testing. While the advent of Next Generation Sequencing (NGS) led to the routine use of Non-Invasive Prenatal Screening (NIPT or NIPS), few data are available regarding the reliability and reproducibility of Non-Invasive Prenatal Paternity Testing (NIPPT or NIPAT). Here, we present a non-invasive prenatal paternity test (NIPAT) analyzing 861 Single Nucleotide Variants (SNV) from cffDNA through NGS technology. The test, validated on more than 900 meiosis samples, generated log(CPI)(Combined Paternity Index) values for designated fathers ranging from +34 to +85, whereas log(CPI) values calculated for unrelated individuals were below -150. This study suggests that NIPAT can be used with high accuracy in real cases.

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.

A machine learning approach for missing persons cases with high genotyping errors

Estimating the relationships between individuals is one of the fundamental challenges in many fields. In particular, relationship.ip estimation could provide valuable information for missing persons cases. The recently developed investigative genetic genealogy approach uses high-density single nucleotide polymorphisms (SNPs) to determine close and more distant relationships, in which hundreds of thousands to tens of millions of SNPs are generated either by microarray genotyping or whole-genome sequencing. The current studies usually assume the SNP profiles were generated with minimum errors. However, in the missing person cases, the DNA samples can be highly degraded, and the SNP profiles generated from these samples usually contain lots of errors. In this study, a machine learning approach was developed for estimating the relationships with high error SNP profiles. In this approach, a hierarchical classification strategy was employed first to classify the relationships by degree and then the relationship types within each degree separately. As for each classification, feature selection was implemented to gain better performance. Both simulated and real data sets with various genotyping error rates were utilized in evaluating this approach, and the accuracies of this approach were higher than individual measures; namely, this approach was more accurate and robust than the individual measures for SNP profiles with genotyping errors. In addition, the highest accuracy could be obtained by providing the same genotyping error rates in train and test sets, and thus estimating genotyping errors of the SNP profiles is critical to obtaining high accuracy of relationship estimation.

Streamlining the decision-making process for international DNA kinship matching using Worldwide allele frequencies and tailored cutoff log10LR thresholds

The identification of human remains belonging to missing persons is one of the main challenges for forensic genetics. Although other means of identification can be applied to missing person investigations, DNA is often extremely valuable to further support or refute potential associations. When reference DNA samples cannot be collected from personal items belonging to a missing person, a direct DNA identification cannot be carried out. However, identifications can be made indirectly using DNA from the missing person's relatives. The ranking of likelihood ratio (LR) values, which measure the fit of a missing person for any given pedigree, is often the first step in selecting candidates in a DNA database. Although implementing DNA kinship matching in a national environment is feasible, many challenges need to be resolved before applying this method to an international configuration. In this study, we present an innovative and intuitive method to perform international DNA kinship matching and facilitate the comparison of DNA profiles when the ancestry is unknown or unsure and/or when different marker sets are used. This straightforward method, which is based on calculations performed with the DNA matching software BONAPARTE, Worldwide allele frequencies and tailored cutoff log₁₀LR thresholds, allows for the classification of potential candidates according to the strength of the DNA evidence and the predicted proportion of adventitious matches. This is a powerful method for streamlining the decision-making process in missing person investigations and DVI processes, especially when there are low numbers of overlapping typed STRs. Intuitive interpretation tables and a decision tree will help strengthen international data comparison for the identification of reported missing individuals discovered outside their national borders.

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.

Linkage and linkage disequilibrium among the markers in the forensic MPS panels

For the past two to three decades, forensic DNA evidence has been analyzed with a limited number of short tandem repeats (STRs), and these STRs are usually assumed to be independent for statistical calculations. With the development and implementation of the MPS technologies, more autosomal markers, both single nucleotide polymorphisms (SNPs) and STRs, can be analyzed. A number of these markers are physically very close to each other, and it may not be appropriate to assume all these markers are genetically unlinked or in linkage equilibrium. In this study, publicly accessible genomic data from five representative populations were used to evaluate the genetic linkage and linkage disequilibrium (LD) between autosomal markers represented in six major commercial panels (in total, 362 markers). Among the 3041 syntenic marker pairs, 1524 pairs had sex-average genetic distances <50 cM, and thus, these marker pairs can be considered as genetically linked. Among the 143 marker pairs with physical distances <1 Mb, 19 LD haplotype blocks (comprising 39 SNPs in total) were detected for at least one of the tested populations. Statistical methods for interpreting linked markers and/or markers in LD were suggested for various case scenarios.

Noninvasive Prenatal Paternity Testing with a Combination of Well-Established SNP and STR Markers Using Massively Parallel Sequencing

Cell-free fetal DNA (cffDNA) from maternal plasma has made it possible to develop noninvasive prenatal paternity testing (NIPPT). However, most studies have focused on customized single nucleotide polymorphism (SNP) typing systems and few have used conventional short tandem repeat (STR) markers. Based on massively parallel sequencing (MPS), this study used a widely-accepted forensic multiplex assay system to evaluate the effect of noninvasive prenatal paternity testing with a combination of well-established SNP and STR markers. Using a ForenSeq DNA Signature Prep Kit, NIPPT was performed in 17 real parentage cases with monovular unborn fetuses at 7 to 24 gestational weeks. Different analytical strategies for the identification of paternally inherited allele (PIA) were developed to deal with SNPs and STRs. Combined paternity index (CPI) for 17 real trios as well as 272 unrelated trios was calculated. With the combination of SNPs and A-STRs, 82.35% (14/17), 88.24% (15/17), 94.12% (16/17), and 94.12% (16/17) of real trios could be accurately determined when the likelihood ratio (LR) threshold for paternity inclusion was set to 10,000, 1000, 100, and 10, respectively. This reveals that simultaneous surveys of SNP and STR markers included in the ForenSeq DNA Signature Prep Kit offer a promising method for NIPPT using MPS technology.

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.

Forensic investigation approaches of searching relatives in DNA databases

There are several indirect database searching approaches to identify the potential source of a forensic biological sample. These DNA-based approaches are familial searching, Y-STR database searching, and investigative genetic genealogy (IGG). The first two strategies use forensic DNA databases managed by the government, and the latter uses databases managed by private citizens or companies. Each of these search strategies relies on DNA testing to identify relatives of the donor of the crime scene sample, provided such profiles reside in the DNA database(s). All three approaches have been successfully used to identify the donor of biological evidence, which assisted in solving criminal cases or identifying unknown human remains. This paper describes and compares these approaches in terms of genotyping technologies, searching methods, database structures, searching efficiency, data quality, data security, and costs, and raises some potential privacy and legal considerations for further discussion by stakeholders and scientists. Y-STR database searching and IGG are advantageous since they are able to assist in more cases than familial searching readily identifying distant relatives. In contrast, familial searching can be performed more readily with existing laboratory systems. Every country or state may have its own unique economic, technical, cultural, and legal considerations and should decide the best approach(es) to fit those circumstances. Regardless of the approach, the ultimate goal should be the same: generate investigative leads and solve active and cold criminal cases to public safety, under stringent policies and security practices designed to protect the privacy of its citizenry.