Patterns of genetic connectedness between modern and medieval Estonian genomes reveal the origins of a major ancestry component of the Finnish population.

The Finnish population is a unique example of a genetic isolate affected by a recent founder event. Previous studies have suggested that the ancestors of Finnic-speaking Finns and Estonians reached the circum-Baltic region by the 1st millennium BC. However, high linguistic similarity points to a more recent split of their languages. To study genetic connectedness between Finns and Estonians directly, we first assessed the efficacy of imputation of low-coverage ancient genomes by sequencing a medieval Estonian genome to high depth (23×) and evaluated the performance of its down-sampled replicas. We find that ancient genomes imputed from >0.1× coverage can be reliably used in principal-component analyses without projection. By searching for long shared allele intervals (LSAIs; similar to identity-by-descent segments) in unphased data for >143,000 present-day Estonians, 99 Finns, and 14 imputed ancient genomes from Estonia, we find unexpectedly high levels of individual connectedness between Estonians and Finns for the last eight centuries in contrast to their clear differentiation by allele frequencies. High levels of sharing of these segments between Estonians and Finns predate the demographic expansion and late settlement process of Finland. One plausible source of this extensive sharing is the 8th-10th centuries AD migration event from North Estonia to Finland that has been proposed to explain uniquely shared linguistic features between the Finnish language and the northern dialect of Estonian and shared Christianity-related loanwords from Slavic. These results suggest that LSAI detection provides a computationally tractable way to detect fine-scale structure in large cohorts.

Trans-ethnic variation in germline variants of patients with renal cell carcinoma.

Prior studies of the renal cell carcinoma (RCC) germline landscape investigated predominantly patients of European ancestry. We examine the frequency of germline pathogenic and likely pathogenic (P/LP) variants in 1,829 patients with RCC from various ancestries. Overall, P/LP variants are found in 17% of patients, among whom 10.3% harbor one or more clinically actionable variants with potential preventive or therapeutic utility. Patients of African ancestry with RCC harbor significantly more P/LP variants in FH compared to patients of non-African ancestry with RCC and African controls from the Genome Aggregation Database (gnomAD). Patients of non-African ancestry have significantly more P/LP variants in CHEK2 compared to patients of African ancestry with RCC and non-Finnish Europeans controls. Non-Africans with RCC have more actionable variants compared to Africans with RCC. This work helps understand the underlying biological differences in RCC between Africans and non-Africans and paves the way to more comprehensive genomic characterization of underrepresented populations.

Solving the migration-recombination equation from a genealogical point of view.

We consider the discrete-time migration-recombination equation, a deterministic, nonlinear dynamical system that describes the evolution of the genetic type distribution of a population evolving under migration and recombination in a law of large numbers setting. We relate this dynamics (forward in time) to a Markov chain, namely a labelled partitioning process, backward in time. This way, we obtain a stochastic representation of the solution of the migration-recombination equation. As a consequence, one obtains an explicit solution of the nonlinear dynamics, simply in terms of powers of the transition matrix of the Markov chain. The limiting and quasi-limiting behaviour of the Markov chain are investigated, which gives immediate access to the asymptotic behaviour of the dynamical system. We finally sketch the analogous situation in continuous time.

Personalized genealogical history of UK individuals inferred from biobank-scale IBD segments.

BACKGROUND: The genealogical histories of individuals within populations are of interest to studies aiming both to uncover detailed pedigree information and overall quantitative population demographic histories. However, the analysis of quantitative details of individual genealogical histories has faced challenges from incomplete available pedigree records and an absence of objective and quantitative details in pedigree information. Although complete pedigree information for most individuals is difficult to track beyond a few generations, it is possible to describe a person's genealogical history using their genetic relatives revealed by identity by descent (IBD) segments-long genomic segments shared by two individuals within a population, which are identical due to inheritance from common ancestors. When modern biobanks collect genotype information for a significant fraction of a population, dense genetic connections of a person can be traced using such IBD segments, offering opportunities to characterize individuals in the context of the underlying populations. Here, we conducted an individual-centric analysis of IBD segments among the UK Biobank participants that represent 0.7% of the UK population. RESULTS: We made a high-quality call set of IBD segments over 5 cM among all 500,000 UK Biobank participants. On average, one UK individual shares IBD segments with 14,000 UK Biobank participants, which we refer to as "relatives." Using these segments, approximately 80% of a person's genome can be imputed. We subsequently propose genealogical descriptors based on the genetic connections of relative cohorts of individuals sharing at least one IBD segment and show that such descriptors offer important information about one's genetic makeup, personal genealogical history, and social behavior. Through analysis of relative counts sharing segments at different lengths, we identified a group, potentially British Jews, who has a distinct pattern of familial expansion history. Finally, using the enrichment of relatives in one's neighborhood, we identified regional variations of personal preference favoring living closer to one's extended families. CONCLUSIONS: Our analysis revealed genetic makeup, personal genealogical history, and social behaviors at the population scale, opening possibilities for further studies of individual's genetic connections in biobank data.

Medieval Super-Grandfather founder of Western Kazakh Clans from Haplogroup C2a1a2-M48.

Western Kazakhstan is populated by three clans totaling 2 million people. Since the clans are patrilineal, the Y-chromosome is the most informative genetic system for tracing their origin. We genotyped 40 Y-SNP and 17 Y-STR markers in 330 Western Kazakhs. High phylogenetic resolution within haplogroup C2a1a2-M48 was achieved by using additional SNPs. Three lines of evidence indicate that the Alimuly and Baiuly clans (but not the Zhetiru clan) have a common founder placed 700 ± 200 years back by the STR data and 500 ± 200 years back by the sequencing data. This supports traditional genealogy claims about the descent of these clans from Emir Alau, who lived 650 years ago and whose lineage might be carried by two-thirds of Western Kazakhs. There is accumulation of specific haplogroups in the subclans representing other lineages, confirming that the clan structure corresponds with the paternal genetic structure of the steppe population.

DNA-based genealogy reconstruction of Nebbiolo, Barbera and other ancient grapevine cultivars from northwestern Italy.

Northwestern Italy is a wine region of the world with the highest of reputations, where top quality wines of remarkable economic value are produced from traditional, long-cultivated varieties. Kinship analyses were performed using 32 microsatellite loci and more than 10 K single-nucleotide polymorphism markers on 227 traditional grapes mostly from Northwestern Italy-including those that have been neglected or are threatened. This was done to better understand the genetic grapevine origins and history of this reputable wine producing area, thus enhancing its cultural value and the marketing appeal of its wines. The work revealed a complex network of genetic relationships among varieties, with little contribution of genotypes from other areas. It revealed the major role played by a few ancient grape varieties as parents of numerous offspring, including some that are endangered today. The ancestry of many cultivars is proposed. Among these are Dolcetto, Barbera and Riesling italico. Through the inference of parent-offspring and sibling relations, marker profiles of ungenotyped putative parents were reconstructed, suggesting kinship relations and a possible parentage for Nebbiolo, one of the most ancient wine grapes worldwide. Historic and geographic implications from the resulting kinships are discussed.

The Y-chromosome of the Soliga, an ancient forest-dwelling tribe of South India.

A previous autosomal STR study provided evidence of a connection between the ancient Soliga tribe at the southern tip of the Indian subcontinent and Australian aboriginal populations, possibly reflecting an eastbound coastal migration circa (15 Kya). The Soliga are considered to be among India's earliest inhabitants. In this investigation, we focus on the Y chromosomal characteristics shared between the Soliga population and other Indian tribes as well as western Eurasia and Sub-Saharan Africa groups. Some noteworthy findings of this present analysis include the following: The three most frequent haplogroups detected in the Soliga population are F*, H1 and J2. F*, the oldest (43 to 63 Kya), has a significant frequency bias in favor of Indian tribes versus castes. This observation coupled with the fact that Y-STR haplotypes shared with sub-Saharan African populations are found only in F* males of the Soliga, Irula and Kurumba may indicate a unique genetic connection between these Indian tribes and sub-Saharan Africans. In addition, our study suggests that haplogroup H is confined mostly to South Asia and immediate neighbors and the H1 network may indicate minimal sharing of Y-STR haplotypes among South Asian collections, tribal and otherwise. Also, J2, brought into India by Neolithic farmers, is present at a significantly higher frequency in caste versus tribal communities. This last observation may reflect the marginalization of Indian tribes to isolated regions not ideal for agriculture.

The Evolving Moran Genealogy.

We study the evolution of the population genealogy in the classic neutral Moran Model of finite size n∈N and in discrete time. The stochastic transformations that shape a Moran population can be realized directly on its genealogy and give rise to a process on a state space consisting of n-sized binary increasing trees. We derive a number of properties of this process, and show that they are in agreement with existing results on the infinite-population limit of the Moran Model. Most importantly, this process admits time reversal, which makes it possible to simplify the mechanisms determining state changes, and allows for a thorough investigation of the Most Recent Common Ancestorprocess.

PAMAM: Power analysis in multiancestry admixture mapping.

Admixed populations arise when two or more previously isolated populations interbreed. Admixture mapping (AM) methods are used for tracing the ancestral origin of disease-susceptibility genetic loci in the admixed population such as African American and Latinos. AM is different from genome-wide association studies in that ancestry rather than genotypes are tracked in the association process. The power and sample size of AM primarily depend on proportion of admixture and differences in the risk allele frequencies among the ancestral populations. Ensuring sufficient power to detect the effect of ancestry on disease susceptibility is critical for interpretability and reliability of studies using AM approach. However, there is no power and sample size analysis tool existing for AM studies in admixed population. In this study, we developed power analysis of multiancestry AM (PAMAM) to estimate power and sample size for two-way and three-way population admixtures. PAMAM is the first web-based bioinformatics tool developed to calculate power and sample size in admixed population under a variety of genetic and disease phenotype models. It is a valuable resource for investigators to design a cost-efficient study and develop grant application to pursue AM studies. PAMAM is built on JavaScript back-end with HTML front-end. It is accessible through any modern web browser such as Firefox, Internet Explorer, and Google Chrome regardless of operating system. It is a user-friendly tool containing links for support information including user manual and examples, and freely available at https://research.cchmc.org/mershalab/PAMAM/login.html.

Molecular genealogy of Tusi Lu's family reveals their paternal relationship with Jochi, Genghis Khan's eldest son.

Genghis Khan's lineage has attracted both academic and general interest because of its mystery and large influence. However, the truth behind the mystery is complicated and continues to confound the scientific study. In this study, we surveyed the molecular genealogy of Northwestern China's Lu clan who claim to be the descendants of the sixth son of Genghis Khan, Toghan. We also investigated living members of the Huo and Tuo clans, who, according to oral tradition, were close male relatives of Lu clan. Using network analysis, we found that the Y-chromosomal haplotypes of Lu clan mainly belong to haplogroup C2b1a1b1-F1756, widely prevalent in Altaic-speaking populations, and are closely related to the Tore clan from Kazakhstan, who claim to be the descendants of the first son of Genghis Khan, Jochi. The most recent common ancestor of the special haplotype cluster that includes the Lu clan and Tore clan lived about 1000 years ago (YA), while the Huo and Tuo clans do not share any Y lineages with the Lu clan. In addition to the reported lineages, such as C3*-Star Cluster, R1b-M343, and Q, our results indicate that haplogroup C2b1a1b1-F1756 might be another candidate of the true Y lineage of Genghis Khan.

Estimating variance components in population scale family trees.

The rapid digitization of genealogical and medical records enables the assembly of extremely large pedigree records spanning millions of individuals and trillions of pairs of relatives. Such pedigrees provide the opportunity to investigate the sociological and epidemiological history of human populations in scales much larger than previously possible. Linear mixed models (LMMs) are routinely used to analyze extremely large animal and plant pedigrees for the purposes of selective breeding. However, LMMs have not been previously applied to analyze population-scale human family trees. Here, we present Sparse Cholesky factorIzation LMM (Sci-LMM), a modeling framework for studying population-scale family trees that combines techniques from the animal and plant breeding literature and from human genetics literature. The proposed framework can construct a matrix of relationships between trillions of pairs of individuals and fit the corresponding LMM in several hours. We demonstrate the capabilities of Sci-LMM via simulation studies and by estimating the heritability of longevity and of reproductive fitness (quantified via number of children) in a large pedigree spanning millions of individuals and over five centuries of human history. Sci-LMM provides a unified framework for investigating the epidemiological history of human populations via genealogical records.

Diversity of clinical, radiographic and genealogical findings in 41 families with amelogenesis imperfecta.

Amelogenesis imperfecta (AI) is a group of enamel development disorders that alter the structure and chemical composition of the tissue. There is great variability in the clinical presentation; according to Witkop, AI can be categorized into 14 subtypes, which makes its diagnosis extremely complex. OBJECTIVE: This study aimed to describe and determine the frequency of clinical and radiographic features and inheritance patterns found in 41 Chilean families diagnosed with diverse types of AI. MATERIAL AND METHODS: We analyzed the clinical records, photographs, pedigrees and radiographs of 121 individuals recruited between 2003 and 2016. All of the information was included in a database that was analyzed using the application Stata 14. RESULTS: The 72 affected individuals had average age of 16 years, and no sex association with the presence of AI was found. The most frequent clinical subtypes were as follows: 43% hypomature, 25% hypoplastic, 21% hypomature/hypoplastic, 7% hypocalcified and 4% hypocalcified/hypoplastic. The number of severely affected teeth was 22, which occurred in the patients with hypocalcified and hypocalcified/hypoplasic AI who presented the highest number of damaged teeth. Caries and periodontal disease were found in 47 and 32% of the patients, respectively. Malocclusions were observed in 43% of the individuals with AI, with open bite being the most frequent. Radiographically, the thickness of the enamel decreased in 51% of the patients, and 80% showed decreased radiopacity of the enamel compared to that of dentin. Autosomal dominant inheritance pattern was found in 37% of the families with hypoplastic AI, and autosomal recessive pattern was present in 56% of the other clinical subtypes, but more frequently in those affected with hypomature and hypocalcified AI. CONCLUSION: Of the five clinical subtypes, autosomal recessive hypomature, autosomal dominant hypoplastic and autosomal recessive hypomature/hypoplastic AI were the most prevalent subtypes in this group.

Lineage: Visualizing Multivariate Clinical Data in Genealogy Graphs.

The majority of diseases that are a significant challenge for public and individual heath are caused by a combination of hereditary and environmental factors. In this paper we introduce Lineage, a novel visual analysis tool designed to support domain experts who study such multifactorial diseases in the context of genealogies. Incorporating familial relationships between cases with other data can provide insights into shared genomic variants and shared environmental exposures that may be implicated in such diseases. We introduce a data and task abstraction, and argue that the problem of analyzing such diseases based on genealogical, clinical, and genetic data can be mapped to a multivariate graph visualization problem. The main contribution of our design study is a novel visual representation for tree-like, multivariate graphs, which we apply to genealogies and clinical data about the individuals in these families. We introduce data-driven aggregation methods to scale to multiple families. By designing the genealogy graph layout to align with a tabular view, we are able to incorporate extensive, multivariate attributes in the analysis of the genealogy without cluttering the graph. We validate our designs by conducting case studies with our domain collaborators.

Ancient Fennoscandian genomes reveal origin and spread of Siberian ancestry in Europe.

European population history has been shaped by migrations of people, and their subsequent admixture. Recently, ancient DNA has brought new insights into European migration events linked to the advent of agriculture, and possibly to the spread of Indo-European languages. However, little is known about the ancient population history of north-eastern Europe, in particular about populations speaking Uralic languages, such as Finns and Saami. Here we analyse ancient genomic data from 11 individuals from Finland and north-western Russia. We show that the genetic makeup of northern Europe was shaped by migrations from Siberia that began at least 3500 years ago. This Siberian ancestry was subsequently admixed into many modern populations in the region, particularly into populations speaking Uralic languages today. Additionally, we show that ancestors of modern Saami inhabited a larger territory during the Iron Age, which adds to the historical and linguistic information about the population history of Finland.

The social life of DNA: racial reconciliation and institutional morality after the genome.

This 2017 British Journal of Sociology Lecture builds upon ideas developed in The Social Life of DNA: Race, Reparations, and Reconciliation after the Genome (Nelson 2016). I argue that one of the more significant developments of the postgenomic era is the circulation of DNA analysis outside of the life sciences, especially commercial applications such as direct-to-consumer genealogical testing. These tests are increasingly taken up in 'reconciliation projects' - endeavours in which DNA analysis is put to the use of repairing the past, including a recently launched attempt in the United States to locate descendants of enslaved persons sold by the Jesuit stewards of Georgetown College in order to bolster that institution's finances. With this reconciliation project, genetic genealogy has become a vehicle for a form of social repair, and most particularly, the reuniting of 'lost' kin. This use of genetic genealogy takes place against the backdrop of an expanding, national inquiry into ties between education and slavery. In the process, the legacy of racial slavery is rendered both contemporary and proximate, despite a 'colour-blind' racial project that aims to negate the significance of this history and its coeval development with US higher education. Elite educational institutions such as Georgetown that elect to excavate these histories are soon after faced with the choice of how to respond, on campus and beyond, to revelations of entanglements between edification and bondage. However imperfectly, colleges and universities are among the few institutional settings where the contested issue of structural racism (and remedies to it) may be aired. It is in these fraught debates that the exercise of 'institutional morality' can take shape; organizations engage in practices that articulate institutional values and are faced with a choice of symbolic and distributional responses.