Public Perspectives on Investigative Genetic Genealogy: Findings from a National Focus Group Study.

BACKGROUND: Investigative genetic genealogy (IGG) is a technique that involves uploading genotypes developed from perpetrator DNA left at a crime scene, or DNA from unidentified remains, to public genetic genealogy databases to identify genetic relatives and, through the creation of a family tree, the individual who was the source of the DNA. As policymakers demonstrate interest in regulating IGG, it is important to understand public perspectives on IGG to determine whether proposed policies are aligned with public attitudes. METHODS: We conducted eight focus groups with members of the public (N = 72), sampled from four geographically diverse US regions, to explore general attitudes and perspectives regarding aspects of IGG practices, applications, and policies. Five major topics were explored in each focus group: when IGG should be used; who should perform IGG; how to approach consent for genetic database users; what systems of oversight should govern IGG practitioners; and whether to notify database users if their data are involved in law enforcement (LE) matching. RESULTS: Participants were supportive of IGG in most scenarios, especially for cold and violent cases. The favorable attitudes toward IGG were, however, tempered by distrust of law enforcement among some participants. All participants agreed that databases must inform users if IGG is allowed, but they did not agree on how individual database users should be allowed to opt out or whether to notify them if their data are involved in specific investigations. All participants agreed that IGG should be subject to some prescriptive guidelines, regulations, or accountability mechanisms. CONCLUSIONS: These findings suggest broad public support for IGG, and interest in developing systems of accountability for its practice. Our study provides useful insight for policy makers, genomic database stewards, law enforcement, and other stakeholders in IGG's practice, and suggests multiple directions for future research.

Characterizing identity by descent segments in Chinese interpopulation unrelated individual pairs.

Identity by descent (IBD) segments, uninterrupted DNA segments derived from the same ancestral chromosomes, are widely used as indicators of relationships in genetics. A great deal of research focuses on IBD segments between related pairs, while the statistical analyses of segments in irrelevant individuals are rare. In this study, we investigated the basic informative features of IBD segments in unrelated pairs in Chinese populations from the 1000 Genome Project. A total of 5922 IBD segments in Chinese interpopulation unrelated individual pairs were detected via IBIS and the average length of IBD was 3.71 Mb in length. It was found that 17.86% of unrelated pairs shared at least one IBD segment in the Chinese cohort. Furthermore, a total of 49 chromosomal regions where IBD segments clustered in high abundance were identified, which might be sharing hotspots in the human genome. Such regions could also be observed in other ancestry populations, which implies that similar IBD backgrounds also exist. Altogether, these results demonstrated the distribution of common background IBD segments, which helps improve the accuracy in pedigree studies based on IBD analysis.

IGG in the trenches: Results of an in-depth interview study on the practice, politics, and future of investigative genetic genealogy.

Investigative genetic genealogy (IGG) is a new technique for identifying criminal suspects and unidentified deceased and living persons that has sparked controversy. In a criminal case, the technique involves uploading genetic information left by a putative perpetrator at the crime scene to one or more direct-to-consumer genetic genealogy databases with the intention of identifying the perpetrator's genetic relatives and, eventually, locating the perpetrator on the family tree. In 2018, IGG helped to identify the Golden State Killer, and it has since been used in hundreds of investigations in the United States. Here, we report findings from in-depth interviews with 24 U.S.-based individuals involved in IGG that are relevant to the technique's current practice and predicted future. Key findings include: an emphasis on restricting IGG as a conceptual and technical matter to lead generation; the rapid growth of a private and largely self-regulating industry to support IGG; general recognition of three categories of cases associated with distinct practical, ethical, and policy questions, as well as varying degrees of controversy; and the significant influence of perceived public opinion on IGG practice. The experiences and perspectives of individuals in the IGG trenches related to these and other issues are potentially useful inputs to ongoing efforts to regulate the technique.

Bursts of coalescence within population pedigrees whenever big families occur.

We consider a simple diploid population-genetic model with potentially high variability of offspring numbers among individuals. Specifically, against a backdrop of Wright-Fisher reproduction and no selection there is an additional probability that a big family occurs, meaning that a pair of individuals has a number of offspring on the order of the population size. We study how the pedigree of the population generated under this model affects the ancestral genetic process of a sample of size two at a single autosomal locus without recombination. Our population model is of the type for which multiple-mergers coalescent processes have been described. We prove that the conditional distribution of the pairwise coalescence time given the random pedigree converges to a limit law as the population size tends to infinity. This limit law may or may not be the usual exponential distribution of the Kingman coalescent, depending on the frequency of big families. But because it includes the number and times of big families it differs from the usual multiple-merger coalescent models. The usual multiple-merger coalescent models are seen as describing the ancestral process marginal to, or averaging over, the pedigree. In the limiting ancestral process conditional on the pedigree, the intervals between big families can be modeled using the Kingman coalescent but each big family causes a discrete jump in the probability of coalescence. Analogous results should hold for larger samples and other population models. We illustrate these results with simulations and additional analysis, highlighting their implications for inference and understanding of multi-locus data.

Male Pedigree Toolbox: A Versatile Software for Y-STR Data Analyses.

Y-chromosomal short tandem repeats (Y-STRs) are widely used in forensic, genealogical, and population genetics. With the recent increase in the number of rapidly mutating (RM) Y-STRs, an unprecedented level of male differentiation can be achieved, widening and improving the applications of Y-STRs in various fields, including forensics. The growing complexity of Y-STR data increases the need for automated data analyses, but dedicated software tools are scarce. To address this, we present the Male Pedigree Toolbox (MPT), a software tool for the automated analysis of Y-STR data in the context of patrilineal genealogical relationships. The MPT can estimate mutation rates and male relative differentiation rates from input Y-STR pedigree data. It can aid in determining ancestral haplotypes within a pedigree and visualize the genetic variation within pedigrees in all branches of family trees. Additionally, it can provide probabilistic classifications using machine learning, helping to establish or prove the structure of the pedigree and the level of relatedness between males, even for closely related individuals with highly similar haplotypes. The tool is flexible and easy to use and can be adjusted to any set of Y-STR markers by modifying the intuitive input file formats. We introduce the MPT software tool v1.0 and make it publicly available with the goal of encouraging and supporting forensic, genealogical, and other geneticists in utilizing the full potential of Y-STRs for both research purposes and practical applications, including criminal casework.

Law enforcement use of genetic genealogy databases in criminal investigations: Nomenclature, definition and scope.

Although law enforcement use of commercial genetic genealogy databases has gained prominence since the arrest of the Golden State Killer in 2018, and it has been used in hundreds of cases in the United States and more recently in Europe and Australia, it does not have a standard nomenclature and scope. We analyzed the more common terms currently being used and propose a common nomenclature: investigative forensic genetic genealogy (iFGG). We define iFGG as the use by law enforcement of genetic genealogy combined with traditional genealogy to generate suspect investigational leads from forensic samples in criminal investigations. We describe iFGG as a proper subset of forensic genetic genealogy, that is, FGG as applied by law enforcement to criminal investigations; hence, investigative FGG or iFGG. We delineate its steps, compare and contrast it with other investigative techniques involving genetic evidence, and contextualize its use within criminal investigations. This characterization is a critical input to future studies regarding the legal status of iFGG and its implications on the right to genetic privacy.

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.

Multi-generation genetic contributions of immigrants reveal cryptic elevated and sex-biased effective gene flow within a natural meta-population.

Impacts of immigration on micro-evolution and population dynamics fundamentally depend on net rates and forms of resulting gene flow into recipient populations. Yet, the degrees to which observed rates and sex ratios of physical immigration translate into multi-generational genetic legacies have not been explicitly quantified in natural meta-populations, precluding inference on how movements translate into effective gene flow and eco-evolutionary outcomes. Our analyses of three decades of complete song sparrow (Melospiza melodia) pedigree data show that multi-generational genetic contributions from regular natural immigrants substantially exceeded those from contemporary natives, consistent with heterosis-enhanced introgression. However, while contributions from female immigrants exceeded those from female natives by up to three-fold, male immigrants' lineages typically went locally extinct soon after arriving. Both the overall magnitude, and the degree of female bias, of effective gene flow therefore greatly exceeded those which would be inferred from observed physical arrivals, altering multiple eco-evolutionary implications of immigration.

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.

Clinical identification of a specific psychic envelope in families with anorexic symptoms.

Our clinical experience in psychoanalytic family therapy with families where one member has anorexic symptoms has shown that the therapy space is often invaded by the deathly dimension, by an absence of family historicity, and by a lack of autonomy. These different elements appear as "voids," missing pieces of a family puzzle, and reflect a psychic container damaged by the weight of inherited intergenerational trauma. Rather than disappear, these elements are passed down from one generation to the next, their effects weakening the current group whose psychic envelope develops "holes" and becomes "elastic." This paper will focus on the changes in this psychic container, which shift according to the rhythm of family functioning, oscillating between activation of the deathly toxic function within the group, on the one hand, and tension between the isomorphic and homomorphic mode, on the other. We will show how this clinical identification around the quality of the psychic envelope and its changes is valuable for family therapy.

Mixture detection with Demixtify.

The de facto genetic markers of forensics are short tandem repeats (STRs). There are many analytical tools designed to work with STRs, including techniques for analyzing and assessing DNA mixtures. In contrast, the nascent field of forensic genetic genealogy often relies on biallelic single nucleotide polymorphisms (SNPs). Tools designed for the forensic assessment of SNPs are somewhat lacking, especially for DNA mixtures. In this paper we introduce Demixtify, a program that detects DNA mixtures using biallelic SNPs. Demixtify is quite powerful; highly imbalanced mixtures can be detected (≤1:99, considering in silico and in vitro mixtures) when coverage is ample. Demixtify can also detect mixtures in low coverage (∼1×) samples (when the mixture is relatively balanced). Demixtify includes an empirical estimator of sequence error that is specific to the markers assayed, making it especially relevant to the forensic community. Orthogonal techniques are also developed to characterize in vitro mixtures, as well as samples thought to be single source, and the results of these approaches serve to validate the techniques presented.

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.

Animal welfare chauvinism in Brexit Britain: a genealogy of care and control.

This paper uses the deployment of animal welfare as an issue during the 'Brexit' referendum as a lens through which to explore the mutual shaping of discourses about care for animals in Britain and the British nation, or the nationalism of animal welfare. Adopting a genealogical outlook, it uses one political advertisement in particular-paid for by the official Vote Leave campaign-as a focalising image and means of opening up the issues, leading to an empirical emphasis on the issue of live animal export as it has mediated ideas about Europe and British identity. Introducing the idea of 'animal welfare chauvinism', the paper suggests that animal welfare messages in the context of this constitutional debate were products of chauvinistic and caring impulses which are mutually constitutive and crystallised through discourses formed in relation to contingent historical struggles. Analytically, stress is placed on the constructive role of situated and repeated discursive exchanges, occurring between animal advocates and other national political elites, within which 'care for animals' as a national ideal is forged. In this light, the article concludes with reflections on the stakes of entering into an already existing conversation on the 'national culture of care' for animals in Britain.

Determining lineages between individuals with high-density mitochondrial and Y-chromosomal single-nucleotide polymorphisms.

Genetic genealogy has been more frequently used in forensic investigations in identifying criminals. However, the current genetic genealogy applications usually do not consider lineage markers (including both Y and mitochondrial deoxyribonucleic acid (DNA)), which is probably because not all distant relatives share the same lineage markers. In addition, there is no study to show how to use lineage markers and what methods or thresholds should be applied in genetic genealogy. In this study, we developed a method to quickly determine if two single-nucleotide polymorphism (SNP) profiles are from the same paternal or material lineages by using a mismatch frequency of the SNPs in Y-chromosomal or mitochondrial DNA. For both Y and mitochondrial SNPs, profile pairs from the same or different lineages can be decided with high accuracies (i.e., 0.380% or 0.157% error rates with Y and mitochondrial DNA, respectively). With kinship coefficient filtering based on autosomal SNPs, the accuracies of determining maternal and paternal lineage can be further improved (i.e., 0.120% or 0.057% error rates with Y and mitochondrial DNA, respectively, using a threshold of kinship coefficient >0). This study shows that lineage markers can be very powerful tools with high accuracies to determine lineages, which could help solve cases and reduce costs for genetic genealogy investigations.

Modelling the spread of cystic fibrosis in Brittany using genealogical data over five centuries.

BACKGROUND: The French region of Brittany presents one of the highest cystic fibrosis (CF)-causing allele frequency in Europe. Here, we tested two hypotheses: i) CF-causing allele carriers arrived by sea in the middle of the 1st millennium AD, and ii) a selective advantage for healthy carriers explains this high rate. METHODS: From the census of cystic fibrosis patients, frequency maps of the most widespread alleles were established. A mathematical model was developed, based on birth date and place of the ancestors of these patients over 5 centuries, to determine the distribution of local migrations and their parameters for inter-generational intervals of 32 years. This model was applied to simulate the spread of CF-causing variant carriers, according to different scenarios that corresponded to the immigration of a given number of variant carriers at different times (year) and places, and to compare their results to current frequency maps. RESULTS: Migrants carrying a CFTR variant settled in several locations, around which they spread, notably in Central Brittany (F508del variant), Léon (G551D variant) and Cornouaille (1078delT variant). Until the end of the 18th century, the spreading of disease-causing allele carriers was relatively slow, and allele frequencies progressively increased. Then, the mean migration distances increased rapidly, leading to a decline in local frequencies. CONCLUSIONS: The main CFTR variants could only have reached their current frequencies through a selective advantage for healthy carriers of the order of 4-6 % at each generation. For the most widespread variant (F508del), the model supports the hypothesis that it appeared around 190 generations ago.

The era of the ARG: an empiricist's guide to ancestral recombination graphs.

In the presence of recombination, the evolutionary relationships between a set of sampled genomes cannot be described by a single genealogical tree. Instead, the genomes are related by a complex, interwoven collection of genealogies formalized in a structure called an ancestral recombination graph (ARG). An ARG extensively encodes the ancestry of the genome(s) and thus is replete with valuable information for addressing diverse questions in evolutionary biology. Despite its potential utility, technological and methodological limitations, along with a lack of approachable literature, have severely restricted awareness and application of ARGs in empirical evolution research. Excitingly, recent progress in ARG reconstruction and simulation have made ARG-based approaches feasible for many questions and systems. In this review, we provide an accessible introduction and exploration of ARGs, survey recent methodological breakthroughs, and describe the potential for ARGs to further existing goals and open avenues of inquiry that were previously inaccessible in evolutionary genomics. Through this discussion, we aim to more widely disseminate the promise of ARGs in evolutionary genomics and encourage the broader development and adoption of ARG-based inference.

The Swedish Kinship Universe: A Demographic Account of the Number of Children, Parents, Siblings, Grandchildren, Grandparents, Aunts/Uncles, Nieces/Nephews, and Cousins Using National Population Registers.

Given that surprisingly little is known about the demography of human kinship, we provide a demographic account of the kinship networks of individuals in Sweden in 2017 across sex and cohort between ages 0 and 102. We used administrative register data of the full population of Sweden to provide the first kinship enumeration for a complete population based on empirical data. We created ego-focused kinship networks of children, parents, siblings, grandchildren, grandparents, aunts and uncles, nieces and nephews, and cousins. We show the average number of kin of different types, the distribution of the number of kin, and changes in dispersion over time. A large share of all kin of an individual are horizontal kin, such as cousins. We observe the highest number of kin-on average, roughly 20-around age 35. We show differences between matrilineal and patrilineal kin and differences in the kinship structure arising from fertility with more than one childbearing partner, such as half-siblings. The results demonstrate substantial variability in kinship within a population. We discuss our findings in the context of other methods to estimate kinship.

Genealogical structure of the Colombian Romosinuano Creole cattle.

The Romosinuano cattle breed is one of the most important Creole genetic resources in Colombia, and interesting traits like adaptation or reproductive efficiency have promoted its use in different countries in America. To consolidate the genealogical historical records, the review of very first yield records in this population was used to reconstruct the genealogy of the breed since the first animals incorporated to the in vivo germplasm bank and estimate different demographic parameters. The complete genealogy comprises 17,136 animals with 5.8 years of generation interval for two pathways. The estimated average inbreeding for the population and inbred animals was 2.53% and 6.32% respectively, with a progressive increase of inbred animals across the generations. Almost 48% of the total animals presented some level of consanguinity. Effective population size (Ne) based on the inbreeding rate estimated by regression in all generations was 120 animals whereas Ne estimated by equivalent generations was 69 animals. Effective number of founders (Fe), effective number of ancestors (Fa), and ancestors explaining 50% of variability were 75, 48, and 22, respectively. The relation between Fa/Fe of 64% indicates a genetic bottleneck effect in the population studied.

Sublinear information bottleneck based two-stage deep learning approach to genealogy layout recognition.

As an important part of human cultural heritage, the recognition of genealogy layout is of great significance for genealogy research and preservation. This paper proposes a novel method for genealogy layout recognition using our introduced sublinear information bottleneck (SIB) and two-stage deep learning approach. We first proposed an SIB for extracting relevant features from the input image, and then uses the deep learning classifier SIB-ResNet and object detector SIB-YOLOv5 to identify and localize different components of the genealogy layout. The proposed method is evaluated on a dataset of genealogy images and achieves promising results, outperforming existing state-of-the-art methods. This work demonstrates the potential of using information bottleneck and deep learning object detection for genealogy layout recognition, which can have applications in genealogy research and preservation.

On the number of genealogical ancestors tracing to the source groups of an admixed population.

Members of genetically admixed populations possess ancestry from multiple source groups, and studies of human genetic admixture frequently estimate ancestry components corresponding to fractions of individual genomes that trace to specific ancestral populations. However, the same numerical ancestry fraction can represent a wide array of admixture scenarios within an individual's genealogy. Using a mechanistic model of admixture, we consider admixture genealogically: how many ancestors from the source populations does the admixture represent? We consider African-Americans, for whom continent-level estimates produce a 75-85% value for African ancestry on average and 15-25% for European ancestry. Genetic studies together with key features of African-American demographic history suggest ranges for parameters of a simple three-epoch model. Considering parameter sets compatible with estimates of current ancestry levels, we infer that if all genealogical lines of a random African-American born during 1960-1965 are traced back until they reach members of source populations, the mean over parameter sets of the expected number of genealogical lines terminating with African individuals is 314 (interquartile range 240-376), and the mean of the expected number terminating in Europeans is 51 (interquartile range 32-69). Across discrete generations, the peak number of African genealogical ancestors occurs in birth cohorts from the early 1700s, and the probability exceeds 50% that at least one European ancestor was born more recently than 1835. Our genealogical perspective can contribute to further understanding the admixture processes that underlie admixed populations. For African-Americans, the results provide insight both on how many of the ancestors of a typical African-American might have been forcibly displaced in the Transatlantic Slave Trade and on how many separate European admixture events might exist in a typical African-American genealogy.