Inferring Transmission Histories of Rare Alleles in Population-Scale Genealogies

On the genes, genealogies, and geographies of Quebec

Population genetic models only provide coarse representations of real-world ancestry. We used a pedigree compiled from 4 million parish records and genotype data from 2276 French and 20,451 French Canadian individuals to finely model and trace French Canadian ancestry through space and time. The loss of ancestral French population structure and the appearance of spatial and regional structure highlights a wide range of population expansion models. Geographic features shaped migrations, and we find enrichments for migration, genetic, and genealogical relatedness patterns within river networks across regions of Quebec. Finally, we provide a freely accessible simulated whole-genome sequence dataset with spatiotemporal metadata for 1,426,749 individuals reflecting intricate French Canadian population structure. Such realistic population-scale simulations provide opportunities to investigate population genetics at an unprecedented resolution.

Wrestling with Social and Behavioral Genomics: Risks, Potential Benefits, and Ethical Responsibility

In this consensus report by a diverse group of academics who conduct and/or are concerned about social and behavioral genomics (SBG) research, the authors recount the often-ugly history of scientific attempts to understand the genetic contributions to human behaviors and social outcomes. They then describe what the current science-including genomewide association studies and polygenic indexes-can and cannot tell us, as well as its risks and potential benefits. They conclude with a discussion of responsible behavior in the context of SBG research. SBG research that compares individuals within a group according to a "sensitive" phenotype requires extra attention to responsible conduct and to responsible communication about the research and its findings. SBG research (1) on sensitive phenotypes that (2) compares two or more groups defined by (a) race, (b) ethnicity, or (c) genetic ancestry (where genetic ancestry could easily be misunderstood as race or ethnicity) requires a compelling justification to be conducted, funded, or published. All authors agree that this justification at least requires a convincing argument that a study's design could yield scientifically valid results; some authors would additionally require the study to have a socially favorable risk-benefit profile.

The effective family size of immigrant founders predicts their long-term demographic outcome: From Québec settlers to their 20th-century descendants

Population history reconstruction, using extant genetic diversity data, routinely relies on simple demographic models to project the past through ascending genealogical-tree branches. Because genealogy and genetics are intimately related, we traced descending genealogies of the Québec founders to pursue their fate and to assess their contribution to the present-day population. Focusing on the female and male founder lines, we observed important sex-biased immigration in the early colony years and documented a remarkable impact of these early immigrants on the genetic make-up of 20th-century Québec. We estimated the immigrants’ survival ratio as a proportion of lineages found in the 1931–60 Québec to their number introduced within the immigration period. We assessed the effective family size, EFS, of all immigrant parents and their Québec-born descendants. The survival ratio of the earliest immigrants was the highest and declined over centuries in association with the immigrants’ EFS. Parents with high EFS left plentiful married descendants, putting EFS as the most important variable determining the parental demographic success throughout time for generations ahead. EFS of immigrant founders appears to predict their long-term demographic and, consequently, their genetic outcome. Genealogically inferred immigrants’ "autosomal" genetic contribution to 1931–60 Québec from consecutive immigration periods follow the same yearly pattern as the corresponding maternal and paternal lines. Québec genealogical data offer much broader information on the ancestral diversity distribution than genetic scrutiny of a limited population sample. Genealogically inferred population history could assist studies of evolutionary factors shaping population structure and provide tools to target specific health interventions.

Current Developments in Detection of Identity-by-Descent Methods and Applications

Identity-by-descent (IBD), the detection of shared segments inherited from a common ancestor, is a fundamental concept in genomics with broad applications in the characterization and analysis of genomes. While historically the concept of IBD was extensively utilized through linkage analyses and in studies of founder populations, applications of IBD-based methods subsided during the genome-wide association study era. This was primarily due to the computational expense of IBD detection, which becomes increasingly relevant as the field moves toward the analysis of biobank-scale datasets that encompass individuals from highly diverse backgrounds. To address these computational barriers, the past several years have seen new methodological advances enabling IBD detection for datasets in the hundreds of thousands to millions of individuals, enabling novel analyses at an unprecedented scale. Here, we describe the latest innovations in IBD detection and describe opportunities for the application of IBD-based methods across a broad range of questions in the field of genomics.

Calvarial doughnut lesions with bone fragility in a French-Canadian family; case report and review of the literature

Calvarial Doughnut Lesions with Bone Fragility (CDL) is an autosomal dominant genetic disease, characterized by low bone mineral density, multiple fractures starting in childhood, and sclerotic doughnut-shaped lesions in the cranial bones. Aubé and colleagues described in 1988 a French-Canadian family of 12 affected members who had a clinical diagnosis of doughnut lesions of the skull, with pathological fractures, osteopenia, "bone in bone" in the vertebral bodies and squaring of metatarsal and metacarpal bones. Herein we study new members of this family. Sequential genetic testing identified a nonsense variant c.148C>T, p. Arg50^⁎ in SGMS2 previously reported in other families. SGMS2 encodes Sphingomyelin Synthase 2, which produces Sphingomyelin (SM), a major lipid component of the plasma membrane that plays a role in bone mineralization. The nonsense variant is associated with milder phenotype. The proband presents with bone in bone vertebral appearance that had been defined uniquely in the first cases described in the same family. The proband's son was identified to carry the same variant, which makes him the sixth generation with the diagnosis of CDL. We also report that the same pathogenic variant was identified in another previously described family, from France. These reports further confirm the genetic basis of CDL, the recurrence of the same variant (p.Arg50*) in individuals of the same ancestry, and the variable penetrance of some of the clinical findings.

Ancestral haplotype reconstruction in endogamous populations using identity-by-descent

In this work we develop a novel algorithm for reconstructing the genomes of ancestral individuals, given genotype or sequence data from contemporary individuals and an extended pedigree of family relationships. A pedigree with complete genomes for every individual enables the study of allele frequency dynamics and haplotype diversity across generations, including deviations from neutrality such as transmission distortion. When studying heritable diseases, ancestral haplotypes can be used to augment genome-wide association studies and track disease inheritance patterns. The building blocks of our reconstruction algorithm are segments of Identity-By-Descent (IBD) shared between two or more genotyped individuals. The method alternates between identifying a source for each IBD segment and assembling IBD segments placed within each ancestral individual. Unlike previous approaches, our method is able to accommodate complex pedigree structures with hundreds of individuals genotyped at millions of SNPs.

We apply our method to an Old Order Amish pedigree from Lancaster, Pennsylvania, whose founders came to North America from Europe during the early 18th century. The pedigree includes 1338 individuals from the past 12 generations, 394 with genotype data. The motivation for reconstruction is to understand the genetic basis of diseases segregating in the family through tracking haplotype transmission over time. Using our algorithm thread, we are able to reconstruct an average of 224 ancestral individuals per chromosome. For these ancestral individuals, on average we reconstruct 79% of their haplotypes. We also identify a region on chromosome 16 that is difficult to reconstruct—we find that this region harbors a short Amish-specific copy number variation and the gene HYDIN. thread was developed for endogamous populations, but can be applied to any extensive pedigree with the recent generations genotyped. We anticipate that this type of practical ancestral reconstruction will become more common and necessary to understand rare and complex heritable diseases in extended families.

When analyzing complex heritable traits, genomic data from many generations of an extended family increases the amount of information available for statistical inference. However, typically only genomic data from the recent generations of a pedigree are available, as ancestral individuals are deceased. In this work we present an algorithm, called thread, for reconstructing the genomes of ancestral individuals, given a complex pedigree and genomic data from the recent generations. Previous approaches have not been able to accommodate large datasets (both in terms of sites and individuals), made simplifying assumptions about pedigree structure, or did not tie reconstructed sequences back to specific individuals. We apply thread to a complex Old Order Amish pedigree of 1338 individuals, 394 with genotype data.

Historical human remains identification through maternal and paternal genetic signatures in a founder population with extensive genealogical record

OBJECTIVES

We describe a method to identify human remains excavated from unmarked graves in historical Québec cemeteries by combining parental-lineage genetic markers with the whole-population genealogy of Québec contained in the BALSAC database.

MATERIALS AND METHODS

The remains of six men were exhumed from four historical cemeteries in the province of Québec, Canada. DNA was extracted from the remains and genotyped to reveal their mitochondrial and Y-chromosome haplotypes, which were compared to a collection of haplotypes of genealogically-anchored modern volunteers. Maternal and paternal genealogies were searched in the BALSAC genealogical record for parental couples matching the mitochondrial and the Y-chromosome haplotypic signatures, to identify candidate sons from whom the remains could have originated.

RESULTS

Analysis of the matching genealogies identified the parents of one man inhumed in the cemetery of the investigated parish during its operating time. The candidate individual died in 1833 at the age of 58, a plausible age at death in light of osteological analysis of the remains.

DISCUSSION

This study demonstrates the promising potential of coupling genetic information from living individuals to genealogical data in BALSAC to identify historical human remains. If genetic coverage is increased, the genealogical information in BALSAC could enable the identification of 87% of the men (n = 178,435) married in Québec before 1850, with high discriminatory power in most cases since >75% of the parental couples have unique biparental signatures in most regions. Genotyping and identifying Québec's historical human remains are a key to reconstructing the genomes of the founders of Québec and reinhuming archeological remains with a marked grave.

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.