Robust relationship inference in genome-wide association studies

Genetic relatedness of indigenous ethnic groups in northern Borneo to neighboring populations from Southeast Asia, as inferred from genome-wide SNP data

The region of northern Borneo is home to the current state of Sabah, Malaysia. It is located closest to the southern Philippine islands and may have served as a viaduct for ancient human migration onto or off of Borneo Island. In this study, five indigenous ethnic groups from Sabah were subjected to genome-wide SNP genotyping. These individuals represent the "North Borneo"-speaking group of the great Austronesian family. They have traditionally resided in the inland region of Sabah. The dataset was merged with public datasets, and the genetic relatedness of these groups to neighboring populations from the islands of Southeast Asia, mainland Southeast Asia and southern China was inferred. Genetic structure analysis revealed that these groups formed a genetic cluster that was independent of the clusters of neighboring populations. Additionally, these groups exhibited near-absolute proportions of a genetic component that is also common among Austronesians from Taiwan and the Philippines. They showed no genetic admixture with Austro-Melanesian populations. Furthermore, phylogenetic analysis showed that they are closely related to non-Austro-Melansian Filipinos as well as to Taiwan natives but are distantly related to populations from mainland Southeast Asia. Relatively lower heterozygosity and higher pairwise genetic differentiation index (F_ST ) values than those of nearby populations indicate that these groups might have experienced genetic drift in the past, resulting in their differentiation from other Austronesians. Subsequent formal testing suggested that these populations have received no gene flow from neighboring populations. Taken together, these results imply that the indigenous ethnic groups of northern Borneo shared a common ancestor with Taiwan natives and non-Austro-Melanesian Filipinos and then isolated themselves on the inland of Sabah. This isolation presumably led to no admixture with other populations, and these individuals therefore underwent strong genetic differentiation. This report contributes to addressing the paucity of genetic data on representatives from this strategic region of ancient human migration event(s).

A 472-SNP panel for pairwise kinship testing of second-degree relatives

Kinship testing based on genetic markers, as forensic short tandem repeats (STRs) and single nucleotide polymorphisms (SNPs), has valuable practical applications. Paternity and first-degree relationship can be accurately identified by current commonly-used forensic STRs and reported SNP markers. However, second-degree and more distant relationships remain challenging. Although ∼10⁵-10⁶ SNPs can be used to estimate relatedness of higher degrees, genome-wide genotyping and analysis may be impractical for forensic use. With rapid growth of human genome data sets, it is worthwhile to explore additional markers, especially SNPs, for kinship analysis. Here, we reported an autosomal SNP panel consisted of 342 SNP selected from >84 million SNPs and 131 SNPs from previous systems. We genotyped these SNPs in 136 Chinese individuals by multiplex amplicon Massively Parallel Sequencing, and performed pairwise gender-independent kinship testing. The specificity and sensitivity of these SNPs to distinguish second-degree relatives and the unrelated was 99.9% and 100%, respectively, compared with 53.7% and 99.9% of 19 commonly-used forensic STRs. Moreover, the specificity increased to 100% by the combined use of these STRs and SNPs. The 472-SNP panel could also greatly facilitate the discrimination among different relationships. We estimated that the power of ∼6.45 SNPs were equivalent to one forensic STR in the scenario of 2nd-degree relative pedigree. Altogether, we proposed a panel of 472 SNP markers for kinship analysis, which could be important supplementary of current forensic STRs to solve the problem of second-degree relative testing.

Dominant ELOVL1 mutation causes neurological disorder with ichthyotic keratoderma, spasticity, hypomyelination and dysmorphic features

BACKGROUND

Ichthyosis and neurological involvement occur in relatively few known Mendelian disorders caused by mutations in genes relevant both for epidermis and neural function.

OBJECTIVES

To identify the cause of a similar phenotype of ichthyotic keratoderma, spasticity, mild hypomyelination (on MRI) and dysmorphic features (IKSHD) observed in two unrelated paediatric probands without family history of disease.

METHODS

Whole exome sequencing was performed in both patients. The functional effect of prioritised variant in ELOVL1 (very-long-chain fatty acids (VLCFAs) elongase) was analysed by VLCFA profiling by gas chromatography-mass spectrometry in stably transfected HEK2932 cells and in cultured patient's fibroblasts.

RESULTS

Probands shared novel heterozygous ELOVL1 p.Ser165Phe mutation (de novo in one family, while in the other family, father could not be tested). In transfected cells p.Ser165Phe: (1) reduced levels of FAs C24:0-C28:0 and C26:1 with the most pronounced effect for C26:0 (P=7.8×10^-6 vs HEK293 cells with wild type (wt) construct, no difference vs naïve HEK293) and (2) increased levels of C20:0 and C22:0 (P=6.3×10^-7, P=1.2×10^-5, for C20:0 and C22:0, respectively, comparison vs HEK293 cells with wt construct; P=2.2×10^-7, P=1.9×10^-4, respectively, comparison vs naïve HEK293). In skin fibroblasts, there was decrease of C26:1 (P=0.014), C28:0 (P=0.001) and increase of C20:0 (P=0.033) in the patient versus controls. There was a strong correlation (r=0.92, P=0.008) between the FAs profile of patient's fibroblasts and that of p.Ser165Phe transfected HEK293 cells. Serum levels of C20:0-C26:0 FAs were normal, but the C24:0/C22:0 ratio was decreased.

CONCLUSION

The ELOVL1 p.Ser165Phe mutation is a likely cause of IKSHD.

Research Techniques Made Simple: Using Genome-Wide Association Studies to Understand Complex Cutaneous Disorders

Complex cutaneous disorders result from the combined effect of many different genes and environmental factors, with individual genetic variants often having only a modest effect on disease risk. The ability to examine large numbers of samples is required for correlating genetic variants with diseases/traits. Technological advances in high-throughput genotyping, along with mapping of the human genome and its associated inter-individual variation, have allowed genetic variants to be analyzed at high density in large case-control cohorts for many diseases, including several major skin diseases. These genome-wide association studies focus on showing differences in the frequencies of variants between case and control groups, rather than co-transmission of a variant and disease through a family, as is done in linkage studies. In this review, we provide overall guidance for genome-wide association study analysis and interpreting the results. Additionally, we discuss challenges and future directions for genome-wide association studies, focusing on translation of findings to provide biological and clinical implications for dermatology.

Environment dominates over host genetics in shaping human gut microbiota

Human gut microbiome composition is shaped by multiple factors but the relative contribution of host genetics remains elusive. Here we examine genotype and microbiome data from 1,046 healthy individuals with several distinct ancestral origins who share a relatively common environment, and demonstrate that the gut microbiome is not significantly associated with genetic ancestry, and that host genetics have a minor role in determining microbiome composition. We show that, by contrast, there are significant similarities in the compositions of the microbiomes of genetically unrelated individuals who share a household, and that over 20% of the inter-person microbiome variability is associated with factors related to diet, drugs and anthropometric measurements. We further demonstrate that microbiome data significantly improve the prediction accuracy for many human traits, such as glucose and obesity measures, compared to models that use only host genetic and environmental data. These results suggest that microbiome alterations aimed at improving clinical outcomes may be carried out across diverse genetic backgrounds.

Next-Generation Sequencing Reveals Novel Mutations in X-linked Intellectual Disability

Robust diagnostics for many human genetic disorders are much needed in the pursuit of global personalized medicine. Next-generation sequencing now offers new promise for biomarker and diagnostic discovery, in developed as well as resource-limited countries. In this broader global health context, X-linked intellectual disability (XLID) is an inherited genetic disorder that is associated with a range of phenotypes impacting societies in both developed and developing countries. Although intellectual disability arises due to diverse causes, a substantial proportion is caused by genomic alterations. Studies have identified causal XLID genomic alterations in more than 100 protein-coding genes located on the X-chromosome. However, the causes for a substantial number of intellectual disability and associated phenotypes still remain unknown. Identification of causative genes and novel mutations will help in early diagnosis as well as genetic counseling of families. Advent of next-generation sequencing methods has accelerated the discovery of new genes involved in mental health disorders. In this study, we analyzed the exomes of three families from India with nonsyndromic XLID comprising seven affected individuals. The affected individuals had varying degrees of intellectual disability, microcephaly, and delayed motor and language milestones. We identified potential causal variants in three XLID genes, including PAK3 (V294M), CASK (complex structural variant), and MECP2 (P354T). Our findings reported in this study extend the spectrum of mutations and phenotypes associated with XLID, and calls for further studies of intellectual disability and mental health disorders with use of next-generation sequencing technologies.

Natural variation in the parameters of innate immune cells is preferentially driven by genetic factors

The quantification and characterization of circulating immune cells provide key indicators of human health and disease. To identify the relative effects of environmental and genetic factors on variation in the parameters of innate and adaptive immune cells in homeostatic conditions, we combined standardized flow cytometry of blood leukocytes and genome-wide DNA genotyping of 1,000 healthy, unrelated people of Western European ancestry. We found that smoking, together with age, sex and latent infection with cytomegalovirus, were the main non-genetic factors that affected variation in parameters of human immune cells. Genome-wide association studies of 166 immunophenotypes identified 15 loci that showed enrichment for disease-associated variants. Finally, we demonstrated that the parameters of innate cells were more strongly controlled by genetic variation than were those of adaptive cells, which were driven by mainly environmental exposure. Our data establish a resource that will generate new hypotheses in immunology and highlight the role of innate immunity in susceptibility to common autoimmune diseases.

Codon based co-occurrence network motifs in human mitochondria

The nucleotide polymorphism in the human mitochondrial genome (mtDNA) tolled by codon position bias plays an indispensable role in human population dispersion and expansion. Herein, genome-wide nucleotide co-occurrence networks were constructed using data comprised of five different geographical regions and around 3000 samples for each region. We developed a powerful network model to describe complex mitochondrial evolutionary patterns among codon and non-codon positions. We found evidence that the evolution of human mitochondria DNA is dominated by adaptive forces, particularly mutation and selection, which was supported by many previous studies. The diversity observed in the mtDNA was compared with mutations, co-occurring mutations, network motifs considering codon positions as causing agent. This comparison showed that long-range nucleotide co-occurrences have a large effect on genomic diversity. Most notably, codon motifs apparently underpinned the preferences among codon positions for co-evolution which is probably highly biased during the origin of the genetic code. Our analysis also showed that variable nucleotide positions of different human sub-populations implemented the independent mtDNA evolution to its geographical dispensation. Ergo, this study has provided both a network framework and a codon glance to investigate co-occurring genomic variations that are critical in underlying complex mitochondrial evolution.

Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap

The predisposition to neuropsychiatric disease involves a complex, polygenic, and pleiotropic genetic architecture. However, little is known about how genetic variants impart brain dysfunction or pathology. We used transcriptomic profiling as a quantitative readout of molecular brain-based phenotypes across five major psychiatric disorders-autism, schizophrenia, bipolar disorder, depression, and alcoholism-compared with matched controls. We identified patterns of shared and distinct gene-expression perturbations across these conditions. The degree of sharing of transcriptional dysregulation is related to polygenic (single-nucleotide polymorphism-based) overlap across disorders, suggesting a substantial causal genetic component. This comprehensive systems-level view of the neurobiological architecture of major neuropsychiatric illness demonstrates pathways of molecular convergence and specificity.

Extended diversity analysis of cultivated grapevine Vitis vinifera with 10K genome-wide SNPs

Grapevine is a very important crop species that is mainly cultivated worldwide for fruits, wine and juice. Identification of the genetic bases of performance traits through association mapping studies requires a precise knowledge of the available diversity and how this diversity is structured and varies across the whole genome. An 18k SNP genotyping array was evaluated on a panel of Vitis vinifera cultivars and we obtained a data set with no missing values for a total of 10207 SNPs and 783 different genotypes. The average inter-SNP spacing was ~47 kbp, the mean minor allele frequency (MAF) was 0.23 and the genetic diversity in the sample was high (He = 0.32). Fourteen SNPs, chosen from those with the highest MAF values, were sufficient to identify each genotype in the sample. Parentage analysis revealed 118 full parentages and 490 parent-offspring duos, thus confirming the close pedigree relationships within the cultivated grapevine. Structure analyses also confirmed the main divisions due to an eastern-western gradient and human usage (table vs. wine). Using a multivariate approach, we refined the structure and identified a total of eight clusters. Both the genetic diversity (He, 0.26-0.32) and linkage disequilibrium (LD, 28.8-58.2 kbp) varied between clusters. Despite the short span LD, we also identified some non-recombining haplotype blocks that may complicate association mapping. Finally, we performed a genome-wide association study that confirmed previous works and also identified new regions for important performance traits such as acidity. Taken together, all the results contribute to a better knowledge of the genetics of the cultivated grapevine.

Association of rare missense variants in the second intracellular loop of NaV1.7 sodium channels with familial autism

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder often accompanied by intellectual disability, language impairment and medical co-morbidities. The heritability of autism is high and multiple genes have been implicated as causal. However, most of these genes have been identified in de novo cases. To further the understanding of familial autism, we performed whole-exome sequencing on five families in which second- and third-degree relatives were affected. By focusing on novel and protein-altering variants, we identified a small set of candidate genes. Among these, a novel private missense C1143F variant in the second intracellular loop of the voltage-gated sodium channel Na_V1.7, encoded by the SCN9A gene, was identified in one family. Through electrophysiological analysis, we show that Na_V1.7^C1143F exhibits partial loss-of-function effects, resulting in slower recovery from inactivation and decreased excitability in cultured cortical neurons. Furthermore, for the same intracellular loop of Na_V1.7, we found an excess of rare variants in a case-control variant-burden study. Functional analysis of one of these variants, M932L/V991L, also demonstrated reduced firing in cortical neurons. However, although this variant is rare in Caucasians, it is frequent in Latino population, suggesting that genetic background can alter its effects on phenotype. Although the involvement of the SCN1A and SCN2A genes encoding Na_V1.1 and Na_V1.2 channels in de novo ASD has previously been demonstrated, our study indicates the involvement of inherited SCN9A variants and partial loss-of-function of Na_V1.7 channels in the etiology of rare familial ASD.

A Genome Resequencing-Based Genetic Map Reveals the Recombination Landscape of an Outbred Parasitic Nematode in the Presence of Polyploidy and Polyandry

The parasitic nematode Haemonchus contortus is an economically and clinically important pathogen of small ruminants, and a model system for understanding the mechanisms and evolution of traits such as anthelmintic resistance. Anthelmintic resistance is widespread and is a major threat to the sustainability of livestock agriculture globally; however, little is known about the genome architecture and parameters such as recombination that will ultimately influence the rate at which resistance may evolve and spread. Here, we performed a genetic cross between two divergent strains of H. contortus, and subsequently used whole-genome resequencing of a female worm and her brood to identify the distribution of genome-wide variation that characterizes these strains. Using a novel bioinformatic approach to identify variants that segregate as expected in a pseudotestcross, we characterized linkage groups and estimated genetic distances between markers to generate a chromosome-scale F1 genetic map. We exploited this map to reveal the recombination landscape, the first for any helminth species, demonstrating extensive variation in recombination rate within and between chromosomes. Analyses of these data also revealed the extent of polyandry, whereby at least eight males were found to have contributed to the genetic variation of the progeny analyzed. Triploid offspring were also identified, which we hypothesize are the result of nondisjunction during female meiosis or polyspermy. These results expand our knowledge of the genetics of parasitic helminths and the unusual life-history of H. contortus, and enhance ongoing efforts to understand the genetic basis of resistance to the drugs used to control these worms and for related species that infect livestock and humans throughout the world. This study also demonstrates the feasibility of using whole-genome resequencing data to directly construct a genetic map in a single generation cross from a noninbred nonmodel organism with a complex lifecycle.

Exome-Wide Association Study of Pancreatic Cancer Risk

We conducted a case-control exome-wide association study to discover germline variants in coding regions that affect risk for pancreatic cancer, combining data from 5 studies. We analyzed exome and genome sequencing data from 437 patients with pancreatic cancer (cases) and 1922 individuals not known to have cancer (controls). In the primary analysis, BRCA2 had the strongest enrichment for rare inactivating variants (17/437 cases vs 3/1922 controls) (P = 3.27x10-6; exome-wide statistical significance threshold P < 2.5x10-6). Cases had more rare inactivating variants in DNA repair genes than controls, even after excluding 13 genes known to predispose to pancreatic cancer (adjusted odds ratio, 1.35; P = .045). At the suggestive threshold (P < .001), 6 genes were enriched for rare damaging variants (UHMK1, AP1G2, DNTA, CHST6, FGFR3, and EPHA1) and 7 genes had associations with pancreatic cancer risk, based on the sequence-kernel association test. We confirmed variants in BRCA2 as the most common high-penetrant genetic factor associated with pancreatic cancer and we also identified candidate pancreatic cancer genes. Large collaborations and novel approaches are needed to overcome the genetic heterogeneity of pancreatic cancer predisposition.

Genome-wide association study of Hirschsprung disease detects a novel low-frequency variant at the RET locus

Hirschsprung disease (HSCR) is a congenital disorder with a population incidence of ~1/5000 live births, defined by an absence of enteric ganglia along variable lengths of the colon. HSCR genome-wide association studies (GWAS) have found common associated variants at RET, SEMA3, and NRG1, but they still fail to explain all of its heritability. To enhance gene discovery, we performed a GWAS of 170 cases identified from the Danish nationwide pathology registry with 4717 controls, based on 6.2 million variants imputed from the haplotype reference consortium panel. We found a novel low-frequency variant (rs144432435), which, when conditioning on the lead RET single-nucleotide polymorphism (SNP), was of genome-wide significance in the discovery analysis. This conditional association signal was replicated in a Swedish HSCR cohort with discovery plus replication meta-analysis conditional odds ratio of 6.6 (P = 7.7 × 10^-10; 322 cases and 4893 controls). The conditional signal was, however, not replicated in two HSCR cohorts from USA and Finland, leading to the hypothesis that rs144432435 tags a rare haplotype present in Denmark and Sweden. Using the genome-wide complex trait analysis method, we estimated the SNP heritability of HSCR to be 88%, close to estimates based on classical family studies. Moreover, by using Lasso (least absolute shrinkage and selection operator) regression we were able to construct a genetic HSCR predictor with a area under the receiver operator characteristics curve of 76% in an independent validation set. In conclusion, we combined the largest collection of sporadic Hirschsprung cases to date (586 cases) to further elucidate HSCR's genetic architecture.

Host genetic variation and its microbiome interactions within the Human Microbiome Project

Background

Despite the increasing recognition that microbial communities within the human body are linked to health, we have an incomplete understanding of the environmental and molecular interactions that shape the composition of these communities. Although host genetic factors play a role in these interactions, these factors have remained relatively unexplored given the requirement for large population-based cohorts in which both genotyping and microbiome characterization have been performed.

Methods

We performed whole-genome sequencing of 298 donors from the Human Microbiome Project (HMP) healthy cohort study to accompany existing deep characterization of their microbiomes at various body sites. This analysis yielded an average sequencing depth of 32x, with which we identified 27 million (M) single nucleotide variants and 2.3 M insertions-deletions.

Results

Taxonomic composition and functional potential of the microbiome covaried significantly with genetic principal components in the gastrointestinal tract and oral communities, but not in the nares or vaginal microbiota. Example associations included validation of known associations between FUT2 secretor status, as well as a variant conferring hypolactasia near the LCT gene, with Bifidobacterium longum abundance in stool. The associations of microbial features with both high-level genetic attributes and single variants were specific to particular body sites, highlighting the opportunity to find unique genetic mechanisms controlling microbiome properties in the microbial communities from multiple body sites.

Conclusions

This study adds deep sequencing of host genomes to the body-wide microbiome sequences already extant from the HMP healthy cohort, creating a unique, versatile, and well-controlled reference for future studies seeking to identify host genetic modulators of the microbiome.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0515-8) contains supplementary material, which is available to authorized users.

Investigating the origins of eastern Polynesians using genome-wide data from the Leeward Society Isles

The debate concerning the origin of the Polynesian speaking peoples has been recently reinvigorated by genetic evidence for secondary migrations to western Polynesia from the New Guinea region during the 2nd millennium BP. Using genome-wide autosomal data from the Leeward Society Islands, the ancient cultural hub of eastern Polynesia, we find that the inhabitants' genomes also demonstrate evidence of this episode of admixture, dating to 1,700-1,200 BP. This supports a late settlement chronology for eastern Polynesia, commencing ~1,000 BP, after the internal differentiation of Polynesian society. More than 70% of the autosomal ancestry of Leeward Society Islanders derives from Island Southeast Asia with the lowland populations of the Philippines as the single largest potential source. These long-distance migrants into Polynesia experienced additional admixture with northern Melanesians prior to the secondary migrations of the 2nd millennium BP. Moreover, the genetic diversity of mtDNA and Y chromosome lineages in the Leeward Society Islands is consistent with linguistic evidence for settlement of eastern Polynesia proceeding from the central northern Polynesian outliers in the Solomon Islands. These results stress the complex demographic history of the Leeward Society Islands and challenge phylogenetic models of cultural evolution predicated on eastern Polynesia being settled from Samoa.

The social genome of friends and schoolmates in the National Longitudinal Study of Adolescent to Adult Health

Humans tend to form social relationships with others who resemble them. Whether this sorting of like with like arises from historical patterns of migration, meso-level social structures in modern society, or individual-level selection of similar peers remains unsettled. Recent research has evaluated the possibility that unobserved genotypes may play an important role in the creation of homophilous relationships. We extend this work by using data from 5,500 adolescents from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to examine genetic similarities among pairs of friends. Although there is some evidence that friends have correlated genotypes, both at the whole-genome level as well as at trait-associated loci (via polygenic scores), further analysis suggests that meso-level forces, such as school assignment, are a principal source of genetic similarity between friends. We also observe apparent social-genetic effects in which polygenic scores of an individual's friends and schoolmates predict the individual's own educational attainment. In contrast, an individual's height is unassociated with the height genetics of peers.

Prediction of inherited genomic susceptibility to 20 common cancer types by a supervised machine-learning method

Prevention and early intervention are the most effective ways of avoiding or minimizing psychological, physical, and financial suffering from cancer. However, such proactive action requires the ability to predict the individual's susceptibility to cancer with a measure of probability. Of the triad of cancer-causing factors (inherited genomic susceptibility, environmental factors, and lifestyle factors), the inherited genomic component may be derivable from the recent public availability of a large body of whole-genome variation data. However, genome-wide association studies have so far showed limited success in predicting the inherited susceptibility to common cancers. We present here a multiple classification approach for predicting individuals' inherited genomic susceptibility to acquire the most likely phenotype among a panel of 20 major common cancer types plus 1 "healthy" type by application of a supervised machine-learning method under competing conditions among the cohorts of the 21 types. This approach suggests that, depending on the phenotypes of 5,919 individuals of "white" ethnic population in this study, (i) the portion of the cohort of a cancer type who acquired the observed type due to mostly inherited genomic susceptibility factors ranges from about 33 to 88% (or its corollary: the portion due to mostly environmental and lifestyle factors ranges from 12 to 67%), and (ii) on an individual level, the method also predicts individuals' inherited genomic susceptibility to acquire the other types ranked with associated probabilities. These probabilities may provide practical information for individuals, heath professionals, and health policymakers related to prevention and/or early intervention of cancer.

Dispersals and genetic adaptation of Bantu-speaking populations in Africa and North America

Bantu languages are spoken by about 310 million Africans, yet the genetic history of Bantu-speaking populations remains largely unexplored. We generated genomic data for 1318 individuals from 35 populations in western central Africa, where Bantu languages originated. We found that early Bantu speakers first moved southward, through the equatorial rainforest, before spreading toward eastern and southern Africa. We also found that genetic adaptation of Bantu speakers was facilitated by admixture with local populations, particularly for the HLA and LCT loci. Finally, we identified a major contribution of western central African Bantu speakers to the ancestry of African Americans, whose genomes present no strong signals of natural selection. Together, these results highlight the contribution of Bantu-speaking peoples to the complex genetic history of Africans and African Americans.

Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank

Few replicable genetic associations for Major Depressive Disorder (MDD) have been identified. Recent studies of MDD have identified common risk variants by using a broader phenotype definition in very large samples, or by reducing phenotypic and ancestral heterogeneity. We sought to ascertain whether it is more informative to maximize the sample size using data from all available cases and controls, or to use a sex or recurrent stratified subset of affected individuals. To test this, we compared heritability estimates, genetic correlation with other traits, variance explained by MDD polygenic score, and variants identified by genome-wide meta-analysis for broad and narrow MDD classifications in two large British cohorts - Generation Scotland and UK Biobank. Genome-wide meta-analysis of MDD in males yielded one genome-wide significant locus on 3p22.3, with three genes in this region (CRTAP, GLB1, and TMPPE) demonstrating a significant association in gene-based tests. Meta-analyzed MDD, recurrent MDD and female MDD yielded equivalent heritability estimates, showed no detectable difference in association with polygenic scores, and were each genetically correlated with six health-correlated traits (neuroticism, depressive symptoms, subjective well-being, MDD, a cross-disorder phenotype and Bipolar Disorder). Whilst stratified GWAS analysis revealed a genome-wide significant locus for male MDD, the lack of independent replication, and the consistent pattern of results in other MDD classifications suggests that phenotypic stratification using recurrence or sex in currently available sample sizes is currently weakly justified. Based upon existing studies and our findings, the strategy of maximizing sample sizes is likely to provide the greater gain.

Between Lake Baikal and the Baltic Sea: genomic history of the gateway to Europe

BACKGROUND

The history of human populations occupying the plains and mountain ridges separating Europe from Asia has been eventful, as these natural obstacles were crossed westward by multiple waves of Turkic and Uralic-speaking migrants as well as eastward by Europeans. Unfortunately, the material records of history of this region are not dense enough to reconstruct details of population history. These considerations stimulate growing interest to obtain a genetic picture of the demographic history of migrations and admixture in Northern Eurasia.

RESULTS

We genotyped and analyzed 1076 individuals from 30 populations with geographical coverage spanning from Baltic Sea to Baikal Lake. Our dense sampling allowed us to describe in detail the population structure, provide insight into genomic history of numerous European and Asian populations, and significantly increase quantity of genetic data available for modern populations in region of North Eurasia. Our study doubles the amount of genome-wide profiles available for this region. We detected unusually high amount of shared identical-by-descent (IBD) genomic segments between several Siberian populations, such as Khanty and Ket, providing evidence of genetic relatedness across vast geographic distances and between speakers of different language families. Additionally, we observed excessive IBD sharing between Khanty and Bashkir, a group of Turkic speakers from Southern Urals region. While adding some weight to the "Finno-Ugric" origin of Bashkir, our studies highlighted that the Bashkir genepool lacks the main "core", being a multi-layered amalgamation of Turkic, Ugric, Finnish and Indo-European contributions, which points at intricacy of genetic interface between Turkic and Uralic populations. Comparison of the genetic structure of Siberian ethnicities and the geography of the region they inhabit point at existence of the "Great Siberian Vortex" directing genetic exchanges in populations across the Siberian part of Asia. Slavic speakers of Eastern Europe are, in general, very similar in their genetic composition. Ukrainians, Belarusians and Russians have almost identical proportions of Caucasus and Northern European components and have virtually no Asian influence. We capitalized on wide geographic span of our sampling to address intriguing question about the place of origin of Russian Starovers, an enigmatic Eastern Orthodox Old Believers religious group relocated to Siberia in seventeenth century. A comparative reAdmix analysis, complemented by IBD sharing, placed their roots in the region of the Northern European Plain, occupied by North Russians and Finno-Ugric Komi and Karelian people. Russians from Novosibirsk and Russian Starover exhibit ancestral proportions close to that of European Eastern Slavs, however, they also include between five to 10 % of Central Siberian ancestry, not present at this level in their European counterparts.

CONCLUSIONS

Our project has patched the hole in the genetic map of Eurasia: we demonstrated complexity of genetic structure of Northern Eurasians, existence of East-West and North-South genetic gradients, and assessed different inputs of ancient populations into modern populations.

The Genetic Legacy of the Indian Ocean Slave Trade: Recent Admixture and Post-admixture Selection in the Makranis of Pakistan

From the eighth century onward, the Indian Ocean was the scene of extensive trade of sub-Saharan African slaves via sea routes controlled by Muslim Arab and Swahili traders. Several populations in present-day Pakistan and India are thought to be the descendants of such slaves, yet their history of admixture and natural selection remains largely undefined. Here, we studied the genome-wide diversity of the African-descent Makranis, who reside on the Arabian Sea coast of Pakistan, as well that of four neighboring Pakistani populations, to investigate the genetic legacy, population dynamics, and tempo of the Indian Ocean slave trade. We show that the Makranis are the result of an admixture event between local Baluch tribes and Bantu-speaking populations from eastern or southeastern Africa; we dated this event to ∼300 years ago during the Omani Empire domination. Levels of parental relatedness, measured through runs of homozygosity, were found to be similar across Pakistani populations, suggesting that the Makranis rapidly adopted the traditional practice of endogamous marriages. Finally, we searched for signatures of post-admixture selection at traits evolving under positive selection, including skin color, lactase persistence, and resistance to malaria. We demonstrate that the African-specific Duffy-null blood group-believed to confer resistance against Plasmodium vivax infection-was recently introduced to Pakistan through the slave trade and evolved adaptively in this P. vivax malaria-endemic region. Our study reconstructs the genetic and adaptive history of a neglected episode of the African Diaspora and illustrates the impact of recent admixture on the diffusion of adaptive traits across human populations.

Heritability of Atrial Fibrillation

BACKGROUND

Previous reports have implicated multiple genetic loci associated with AF, but the contributions of genome-wide variation to AF susceptibility have not been quantified.

METHODS AND RESULTS

We assessed the contribution of genome-wide single-nucleotide polymorphism variation to AF risk (single-nucleotide polymorphism heritability, h2g ) using data from 120 286 unrelated individuals of European ancestry (2987 with AF) in the population-based UK Biobank. We ascertained AF based on self-report, medical record billing codes, procedure codes, and death records. We estimated h2g using a variance components method with variants having a minor allele frequency ≥1%. We evaluated h2g in age, sex, and genomic strata of interest. The h2g for AF was 22.1% (95% confidence interval, 15.6%-28.5%) and was similar for early- versus older-onset AF (≤65 versus >65 years of age), as well as for men and women. The proportion of AF variance explained by genetic variation was mainly accounted for by common (minor allele frequency, ≥5%) variants (20.4%; 95% confidence interval, 15.1%-25.6%). Only 6.4% (95% confidence interval, 5.1%-7.7%) of AF variance was attributed to variation within known AF susceptibility, cardiac arrhythmia, and cardiomyopathy gene regions.

CONCLUSIONS

Genetic variation contributes substantially to AF risk. The risk for AF conferred by genomic variation is similar to that observed for several other cardiovascular diseases. Established AF loci only explain a moderate proportion of disease risk, suggesting that further genetic discovery, with an emphasis on common variation, is warranted to understand the causal genetic basis of AF.

An Unexpectedly Complex Architecture for Skin Pigmentation in Africans

Approximately 15 genes have been directly associated with skin pigmentation variation in humans, leading to its characterization as a relatively simple trait. However, by assembling a global survey of quantitative skin pigmentation phenotypes, we demonstrate that pigmentation is more complex than previously assumed, with genetic architecture varying by latitude. We investigate polygenicity in the KhoeSan populations indigenous to southern Africa who have considerably lighter skin than equatorial Africans. We demonstrate that skin pigmentation is highly heritable, but known pigmentation loci explain only a small fraction of the variance. Rather, baseline skin pigmentation is a complex, polygenic trait in the KhoeSan. Despite this, we identify canonical and non-canonical skin pigmentation loci, including near SLC24A5, TYRP1, SMARCA2/VLDLR, and SNX13, using a genome-wide association approach complemented by targeted resequencing. By considering diverse, under-studied African populations, we show how the architecture of skin pigmentation can vary across humans subject to different local evolutionary pressures.

A case-control collapsing analysis identifies epilepsy genes implicated in trio sequencing studies focused on de novo mutations

Trio exome sequencing has been successful in identifying genes with de novo mutations (DNMs) causing epileptic encephalopathy (EE) and other neurodevelopmental disorders. Here, we evaluate how well a case-control collapsing analysis recovers genes causing dominant forms of EE originally implicated by DNM analysis. We performed a genome-wide search for an enrichment of "qualifying variants" in protein-coding genes in 488 unrelated cases compared to 12,151 unrelated controls. These "qualifying variants" were selected to be extremely rare variants predicted to functionally impact the protein to enrich for likely pathogenic variants. Despite modest sample size, three known EE genes (KCNT1, SCN2A, and STXBP1) achieved genome-wide significance (p<2.68×10⁻⁶). In addition, six of the 10 most significantly associated genes are known EE genes, and the majority of the known EE genes (17 out of 25) originally implicated in trio sequencing are nominally significant (p<0.05), a proportion significantly higher than the expected (Fisher’s exact p = 2.33×10⁻¹⁷). Our results indicate that a case-control collapsing analysis can identify several of the EE genes originally implicated in trio sequencing studies, and clearly show that additional genes would be implicated with larger sample sizes. The case-control analysis not only makes discovery easier and more economical in early onset disorders, particularly when large cohorts are available, but also supports the use of this approach to identify genes in diseases that present later in life when parents are not readily available.

Trio exome sequencing and de novo mutation (DNM) analysis has been the main approach to discovering genes responsible for severe sporadic disorders, including a range of neurodevelopmental disorders. This approach requires sequencing parents, identifying DNMs from trio sequence data, and comparing the observed rate of DNMs to the expected. In this study, we adopted a case-control design, performed a gene-based collapsing analysis, and rediscovered several of the epileptic encephalopathy (EE) genes originally implicated by DNM analysis of EE trios. Our collapsing analysis focused on ultra-rare, highly impactful variants (“qualifying variants”) by filtering against large-scale population datasets, and this approach revealed that most of the standing variation can be filtered out and DNMs are enriched in “qualifying variants”. Our study suggests that a case-control analysis approach can be used to identify disease genes with causal mutations that are predominantly de novo in place of trio-based analysis methods. This offers an efficient and cost effective alternative approach when large-scale trio sequencing is not possible.

Complex Patterns of Admixture across the Indonesian Archipelago

Indonesia, an island nation as large as continental Europe, hosts a sizeable proportion of global human diversity, yet remains surprisingly undercharacterized genetically. Here, we substantially expand on existing studies by reporting genome-scale data for nearly 500 individuals from 25 populations in Island Southeast Asia, New Guinea, and Oceania, notably including previously unsampled islands across the Indonesian archipelago. We use high-resolution analyses of haplotype diversity to reveal fine detail of regional admixture patterns, with a particular focus on the Holocene. We find that recent population history within Indonesia is complex, and that populations from the Philippines made important genetic contributions in the early phases of the Austronesian expansion. Different, but interrelated processes, acted in the east and west. The Austronesian migration took several centuries to spread across the eastern part of the archipelago, where genetic admixture postdates the archeological signal. As with the Neolithic expansion further east in Oceania and in Europe, genetic mixing with local inhabitants in eastern Indonesia lagged behind the arrival of farming populations. In contrast, western Indonesia has a more complicated admixture history shaped by interactions with mainland Asian and Austronesian newcomers, which for some populations occurred more than once. Another layer of complexity in the west was introduced by genetic contact with South Asia and strong demographic events in isolated local groups.

Genetic variation in populations of the earthworm, Lumbricus rubellus, across contaminated mine sites

BACKGROUND

Populations of the earthworm, Lumbricus rubellus, are commonly found across highly contaminated former mine sites and are considered to have under-gone selection for mitigating metal toxicity. Comparison of adapted populations with those found on less contaminated soils can provide insights into ecological processes that demonstrate the long-term effects of soil contamination. Contemporary sequencing methods allow for portrayal of demographic inferences and highlight genetic variation indicative of selection at specific genes. Furthermore, the occurrence of L. rubellus lineages across the UK allows for inferences of mechanisms associated with drivers of speciation and local adaptation.

RESULTS

Using RADseq, we were able to define population structure between the two lineages through the use of draft genomes for each, demonstrating an absence of admixture between lineages and that populations over extensive geographic distances form discrete populations. Between the two British lineages, we were able to provide evidence for selection near to genes associated with epigenetic and morphological functions, as well as near a gene encoding a pheromone. Earthworms inhabiting highly contaminated soils bare close genomic resemblance to those from proximal control soils. We were able to define a number of SNPs that largely segregate populations and are indicative of genes that are likely under selection for managing metal toxicity. This includes calcium and phosphate-handling mechanisms linked to lead and arsenic contaminants, respectively, while we also observed evidence for glutathione-related mechanisms, including metallothionein, across multiple populations. Population genomic end points demonstrate no consistent reduction in nucleotide diversity, or increase in inbreeding coefficient, relative to history of exposure.

CONCLUSIONS

Though we can clearly define lineage membership using genomic markers, as well as population structure between geographic localities, it is difficult to resolve markers that segregate entirely between populations in response to soil metal concentrations. This may represent a highly variable series of traits in response to the heterogenous nature of the soil environment, but ultimately demonstrates the maintenance of lineage-specific genetic variation among local populations. L. rubellus appears to provide an exemplary system for exploring drivers for speciation, with a continuum of lineages coexisting across continental Europe, while distinct lineages exist in isolation throughout the UK.

Next-generation sequencing of patients with congenital anosmia

We performed whole exome or genome sequencing in eight multiply affected families with ostensibly isolated congenital anosmia. Hypothesis-free analyses based on the assumption of fully penetrant recessive/dominant/X-linked models obtained no strong single candidate variant in any of these families. In total, these eight families showed 548 rare segregating variants that were predicted to be damaging, in 510 genes. Three Kallmann syndrome genes (FGFR1, SEMA3A, and CHD7) were identified. We performed permutation-based analysis to test for overall enrichment of these 510 genes carrying these 548 variants with genes mutated in Kallmann syndrome and with a control set of genes mutated in hypogonadotrophic hypogonadism without anosmia. The variants were found to be enriched for Kallmann syndrome genes (3 observed vs. 0.398 expected, p = 0.007), but not for the second set of genes. Among these three variants, two have been already reported in genes related to syndromic anosmia (FGFR1 (p.(R250W)), CHD7 (p.(L2806V))) and one was novel (SEMA3A (p.(T717I))). To replicate these findings, we performed targeted sequencing of 16 genes involved in Kallmann syndrome and hypogonadotrophic hypogonadism in 29 additional families, mostly singletons. This yielded an additional 6 variants in 5 Kallmann syndrome genes (PROKR2, SEMA3A, CHD7, PROK2, ANOS1), two of them already reported to cause Kallmann syndrome. In all, our study suggests involvement of 6 syndromic Kallmann genes in isolated anosmia. Further, we report a yet unreported appearance of di-genic inheritance in a family with congenital isolated anosmia. These results are consistent with a complex molecular basis of congenital anosmia.

A massively parallel strategy for STR marker development, capture, and genotyping

Short tandem repeat (STR) variants are highly polymorphic markers that facilitate powerful population genetic analyses. STRs are especially valuable in conservation and ecological genetic research, yielding detailed information on population structure and short-term demographic fluctuations. Massively parallel sequencing has not previously been leveraged for scalable, efficient STR recovery. Here, we present a pipeline for developing STR markers directly from high-throughput shotgun sequencing data without a reference genome, and an approach for highly parallel target STR recovery. We employed our approach to capture a panel of 5000 STRs from a test group of diademed sifakas (Propithecus diadema, n = 3), endangered Malagasy rainforest lemurs, and we report extremely efficient recovery of targeted loci—97.3–99.6% of STRs characterized with ≥10x non-redundant sequence coverage. We then tested our STR capture strategy on P. diadema fecal DNA, and report robust initial results and suggestions for future implementations. In addition to STR targets, this approach also generates large, genome-wide single nucleotide polymorphism (SNP) panels from flanking regions. Our method provides a cost-effective and scalable solution for rapid recovery of large STR and SNP datasets in any species without needing a reference genome, and can be used even with suboptimal DNA more easily acquired in conservation and ecological studies.

Genome-wide Ancestry and Demographic History of African-Descendant Maroon Communities from French Guiana and Suriname

The transatlantic slave trade was the largest forced migration in world history. However, the origins of the enslaved Africans and their admixture dynamics remain unclear. To investigate the demographic history of African-descendant Marron populations, we generated genome-wide data (4.3 million markers) from 107 individuals from three African-descendant populations in South America, as well as 124 individuals from six west African populations. Throughout the Americas, thousands of enslaved Africans managed to escape captivity and establish lasting communities, such as the Noir Marron. We find that this population has the highest proportion of African ancestry (∼98%) of any African-descendant population analyzed to date, presumably because of centuries of genetic isolation. By contrast, African-descendant populations in Brazil and Colombia harbor substantially more European and Native American ancestry as a result of their complex admixture histories. Using ancestry tract-length analysis, we detect different dates for the European admixture events in the African-Colombian (1749 CE; confidence interval [CI]: 1737-1764) and African-Brazilian (1796 CE; CI: 1789-1804) populations in our dataset, consistent with the historically attested earlier influx of Africans into Colombia. Furthermore, we find evidence for sex-specific admixture patterns, resulting from predominantly European paternal gene flow. Finally, we detect strong genetic links between the African-descendant populations and specific source populations in Africa on the basis of haplotype sharing patterns. Although the Noir Marron and African-Colombians show stronger affinities with African populations from the Bight of Benin and the Gold Coast, the African-Brazilian population from Rio de Janeiro has greater genetic affinity with Bantu-speaking populations from the Bight of Biafra and west central Africa.

Exome-wide association study reveals novel psoriasis susceptibility locus at TNFSF15 and rare protective alleles in genes contributing to type I IFN signalling

Psoriasis is a common inflammatory skin disorder for which multiple genetic susceptibility loci have been identified, but few resolved to specific functional variants. In this study, we sought to identify common and rare psoriasis-associated gene-centric variation. Using exome arrays we genotyped four independent cohorts, totalling 11 861 psoriasis cases and 28 610 controls, aggregating the dataset through statistical meta-analysis. Single variant analysis detected a previously unreported risk locus at TNFSF15 (rs6478108; P = 1.50 × 10-8, OR = 1.10), and association of common protein-altering variants at 11 loci previously implicated in psoriasis susceptibility. We validate previous reports of protective low-frequency protein-altering variants within IFIH1 (encoding an innate antiviral receptor) and TYK2 (encoding a Janus kinase), in each case establishing a further series of protective rare variants (minor allele frequency < 0.01) via gene-wide aggregation testing (IFIH1: pburden = 2.53 × 10-7, OR = 0.707; TYK2: pburden = 6.17 × 10-4, OR = 0.744). Both genes play significant roles in type I interferon (IFN) production and signalling. Several of the protective rare and low-frequency variants in IFIH1 and TYK2 disrupt conserved protein domains, highlighting potential mechanisms through which their effect may be exerted.

Genomic Patterns of De Novo Mutation in Simplex Autism

To further our understanding of the genetic etiology of autism, we generated and analyzed genome sequence data from 516 idiopathic autism families (2,064 individuals). This resource includes >59 million single-nucleotide variants (SNVs) and 9,212 private copy number variants (CNVs), of which 133,992 and 88 are de novo mutations (DNMs), respectively. We estimate a mutation rate of ∼1.5 × 10-8 SNVs per site per generation with a significantly higher mutation rate in repetitive DNA. Comparing probands and unaffected siblings, we observe several DNM trends. Probands carry more gene-disruptive CNVs and SNVs, resulting in severe missense mutations and mapping to predicted fetal brain promoters and embryonic stem cell enhancers. These differences become more pronounced for autism genes (p = 1.8 × 10-3, OR = 2.2). Patients are more likely to carry multiple coding and noncoding DNMs in different genes, which are enriched for expression in striatal neurons (p = 3 × 10-3), suggesting a path forward for genetically characterizing more complex cases of autism.

Wild Mouse Gut Microbiota Promotes Host Fitness and Improves Disease Resistance

Laboratory mice, while paramount for understanding basic biological phenomena, are limited in modeling complex diseases of humans and other free-living mammals. Because the microbiome is a major factor in mammalian physiology, we aimed to identify a naturally evolved reference microbiome to better recapitulate physiological phenomena relevant in the natural world outside the laboratory. Among 21 distinct mouse populations worldwide, we identified a closely related wild relative to standard laboratory mouse strains. Its bacterial gut microbiome differed significantly from its laboratory mouse counterpart and was transferred to and maintained in laboratory mice over several generations. Laboratory mice reconstituted with natural microbiota exhibited reduced inflammation and increased survival following influenza virus infection and improved resistance against mutagen/inflammation-induced colorectal tumorigenesis. By demonstrating the host fitness-promoting traits of natural microbiota, our findings should enable the discovery of protective mechanisms relevant in the natural world and improve the modeling of complex diseases of free-living mammals. VIDEO ABSTRACT.

Demographic history and biologically relevant genetic variation of Native Mexicans inferred from whole-genome sequencing

Understanding the genetic structure of Native American populations is important to clarify their diversity, demographic history, and to identify genetic factors relevant for biomedical traits. Here, we show a demographic history reconstruction from 12 Native American whole genomes belonging to six distinct ethnic groups representing the three main described genetic clusters of Mexico (Northern, Southern, and Maya). Effective population size estimates of all Native American groups remained below 2,000 individuals for up to 10,000 years ago. The proportion of missense variants predicted as damaging is higher for undescribed (~ 30%) than for previously reported variants (~ 15%). Several variants previously associated with biological traits are highly frequent in the Native American genomes. These findings suggest that the demographic and adaptive processes that occurred in these groups shaped their genetic architecture and could have implications in biological processes of the Native Americans and Mestizos of today.

People of Mexico have diverse historical and genetic background. Here, Romero-Hidalgo and colleagues sequence whole genomes of Native Americans of Mexico, and show demographic history and genetic variation shared among subgroups of Native Americans.

Association of Natural Killer Cell Ligand Polymorphism HLA-C Asn80Lys With the Development of Anti-SSA/Ro-Associated Congenital Heart Block

OBJECTIVE

Fetal exposure to maternal anti-SSA/Ro antibodies is necessary but not sufficient for the development of autoimmune congenital heart block (CHB), suggesting that other factors, such as fetal genetic predisposition, are important. Given the previously described association between major histocompatibility complex alleles and CHB risk, we undertook the present study to test the hypothesis that a variant form of HLA-C Asn80Lys, which binds with high affinity to an inhibitory killer cell immunoglobulin-like receptor (KIR) and thus renders natural killer (NK) cells incapable of restricting inflammation, contributes to the development of CHB.

METHODS

Members of 192 pedigrees in the US and Europe (194 cases of CHB, 91 unaffected siblings, 152 fathers, 167 mothers) and 1,073 out-of-study controls were genotyped on the Immunochip single-nucleotide polymorphism microarray. Imputation was used to identify associations at HLA-C Asn80Lys (Asn, C1; Lys, C2) and KIR. Tests for association were performed using logistic regression. McNemar's test and the pedigree disequilibrium test (PDT) were used for matched analyses between affected and unaffected children.

RESULTS

Compared with out-of-study controls of the same sex, the C2 allele was less frequent in the mothers (odds ratio [OR] 0.63, P = 0.0014) and more frequent in the fathers (OR 1.40, P = 0.0123), yielding a significant sex-by-C2 interaction (P = 0.0002). The C2 allele was more frequent in affected siblings than in unaffected siblings (OR 3.67, P = 0.0025), which was consistent with the PDT results (P = 0.016); these results were observed in both sexes and across the US and European cohorts. There was no difference in the frequency of the inhibitory KIR genotype (KIR AA) between affected and unaffected children (P = 0.55).

CONCLUSION

These data establish C2 as a novel genetic risk factor associated with CHB. This observation supports a model in which fetuses with C2 ligand expression and maternal anti-SSA/Ro positivity may have impaired NK cell surveillance, resulting in unchecked cardiac inflammation and scarring.

Genome-Wide Association Meta-Analysis Reveals Novel Juvenile Idiopathic Arthritis Susceptibility Loci

OBJECTIVE

Juvenile idiopathic arthritis (JIA) is the most common childhood rheumatic disease and has a strong genomic component. To date, JIA genetic association studies have had limited sample sizes, used heterogeneous patient populations, or included only candidate regions. The aim of this study was to identify new associations between JIA patients with oligoarticular disease and those with IgM rheumatoid factor (RF)-negative polyarticular disease, which are clinically similar and the most prevalent JIA disease subtypes.

METHODS

Three cohorts comprising 2,751 patients with oligoarticular or RF-negative polyarticular JIA were genotyped using the Affymetrix Genome-Wide SNP Array 6.0 or the Illumina HumanCoreExome-12+ Array. Overall, 15,886 local and out-of-study controls, typed on these platforms or the Illumina HumanOmni2.5, were used for association analyses. High-quality single-nucleotide polymorphisms (SNPs) were used for imputation to 1000 Genomes prior to SNP association analysis.

RESULTS

Meta-analysis showed evidence of association (P < 1 × 10^-6 ) at 9 regions: PRR9_LOR (P = 5.12 × 10^-8 ), ILDR1_CD86 (P = 6.73 × 10^-8 ), WDFY4 (P = 1.79 × 10^-7 ), PTH1R (P = 1.87 × 10^-7 ), RNF215 (P = 3.09 × 10^-7 ), AHI1_LINC00271 (P = 3.48 × 10^-7 ), JAK1 (P = 4.18 × 10^-7 ), LINC00951 (P = 5.80 × 10^-7 ), and HBP1 (P = 7.29 × 10^-7 ). Of these, PRR9_LOR, ILDR1_CD86, RNF215, LINC00951, and HBP1 were shown, for the first time, to be autoimmune disease susceptibility loci. Furthermore, associated SNPs included cis expression quantitative trait loci for WDFY4, CCDC12, MTP18, SF3A1, AHI1, COG5, HBP1, and GPR22.

CONCLUSION

This study provides evidence of both unique JIA risk loci and risk loci overlapping between JIA and other autoimmune diseases. These newly associated SNPs are shown to influence gene expression, and their bounding regions tie into molecular pathways of immunologic relevance. Thus, they likely represent regions that contribute to the pathology of oligoarticular JIA and RF-negative polyarticular JIA.

Genome-wide association study and meta-analysis in multiple populations identifies new loci for peanut allergy and establishes C11orf30/EMSY as a genetic risk factor for food allergy

BACKGROUND

Peanut allergy (PA) is a complex disease with both environmental and genetic risk factors. Previously, PA loci were identified in filaggrin (FLG) and HLA in candidate gene studies, and loci in HLA were identified in a genome-wide association study and meta-analysis.

OBJECTIVE

We sought to investigate genetic susceptibility to PA.

METHODS

Eight hundred fifty cases and 926 hyper-control subjects and more than 7.8 million genotyped and imputed single nucleotide polymorphisms (SNPs) were analyzed in a genome-wide association study to identify susceptibility variants for PA in the Canadian population. A meta-analysis of 2 phenotypes (PA and food allergy) was conducted by using 7 studies from the Canadian, American (n = 2), Australian, German, and Dutch (n = 2) populations.

RESULTS

An SNP near integrin α6 (ITGA6) reached genome-wide significance with PA (P = 1.80 × 10^-8), whereas SNPs associated with Src kinase-associated phosphoprotein 1 (SKAP1), matrix metallopeptidase 12 (MMP12)/MMP13, catenin α3 (CTNNA3), rho GTPase-activating protein 24 (ARHGAP24), angiopoietin 4 (ANGPT4), chromosome 11 open reading frame (C11orf30/EMSY), and exocyst complex component 4 (EXOC4) reached a threshold suggestive of association (P ≤ 1.49 × 10^-6). In the meta-analysis of PA, loci in or near ITGA6, ANGPT4, MMP12/MMP13, C11orf30, and EXOC4 were significant (P ≤ 1.49 × 10^-6). When a phenotype of any food allergy was used for meta-analysis, the C11orf30 locus reached genome-wide significance (P = 7.50 × 10^-11), whereas SNPs associated with ITGA6, ANGPT4, MMP12/MMP13, and EXOC4 and additional C11orf30 SNPs were suggestive (P ≤ 1.49 × 10^-6). Functional annotation indicated that SKAP1 regulates expression of CBX1, which colocalizes with the EMSY protein coded by C11orf30.

CONCLUSION

This study identifies multiple novel loci as risk factors for PA and food allergy and establishes C11orf30 as a risk locus for both PA and food allergy. Multiple genes (C11orf30/EMSY, SKAP1, and CTNNA3) identified by this study are involved in epigenetic regulation of gene expression.

Clinical utility of the low-density Infinium QC genotyping Array in a genomics-based diagnostics laboratory

Background

With 15,949 markers, the low-density Infinium QC Array-24 BeadChip enables linkage analysis, HLA haplotyping, fingerprinting, ethnicity determination, mitochondrial genome variations, blood groups and pharmacogenomics. It represents an attractive independent QC option for NGS-based diagnostic laboratories, and provides cost-efficient means for determining gender, ethnic ancestry, and sample kinships, that are important for data interpretation of NGS-based genetic tests.

Methods

We evaluated accuracy and reproducibility of Infinium QC genotyping calls by comparing them with genotyping data of the same samples from other genotyping platforms, whole genome/exome sequencing. Accuracy and robustness of determining gender, provenance, and kinships were assessed.

Results

Concordance of genotype calls between Infinium QC and other platforms was above 99%. Here we show that the chip’s ancestry informative markers are sufficient for ethnicity determination at continental and sometimes subcontinental levels, with assignment accuracy varying with the coverage for a particular region and ethnic groups. Mean accuracies of provenance prediction at a regional level were varied from 81% for Asia, to 89% for Americas, 86% for Africa, 97% for Oceania, 98% for Europe, and 100% for India. Mean accuracy of ethnicity assignment predictions was 63%. Pairwise concordances of AFR samples with the samples from any other super populations were the lowest (0.39–0.43), while the concordances within the same population were relatively high (0.55–0.61). For all populations except African, cross-population comparisons were similar in their concordance ranges to the range of within-population concordances (0.54–0.57). Gender determination was correct in all tested cases.

Conclusions

Our results indicate that the Infinium QC Array-24 chip is suitable for cost-efficient, independent QC assaying in the settings of an NGS-based molecular diagnostic laboratory; hence, we recommend its integration into the standard laboratory workflow. Low-density chips can provide sample-specific measures for variant call accuracy, prevent sample mix-ups, validate self-reported ethnicities, and detect consanguineous cases. Integration of low-density chips into QC procedures aids proper interpretation of candidate sequence variants. To enhance utility of this low-density chip, we recommend expansion of ADME and mitochondrial markers. Inexpensive Infinium-like low-density human chips have a potential to become a “Swiss army knife” among genotyping assays suitable for many applications requiring high-throughput assays.

Electronic supplementary material

The online version of this article (10.1186/s12920-017-0297-7) contains supplementary material, which is available to authorized users.

Detecting Pedigree Relationship Errors

Pedigree relationship errors often occur in family data collected for genetic studies, and unidentified errors can lead to either increased false positives or decreased power in both linkage and association analyses. Here, we review several allele sharing as well as likelihood-based statistics that were proposed to efficiently extract genealogical information from available genome-wide marker data, and the software package PREST that implements these methods. We provide the detailed analytical steps involved using two application examples, and we discuss various practical issues, including result interpretation.

Estimation of kinship coefficient in structured and admixed populations using sparse sequencing data

Knowledge of biological relatedness between samples is important for many genetic studies. In large-scale human genetic association studies, the estimated kinship is used to remove cryptic relatedness, control for family structure, and estimate trait heritability. However, estimation of kinship is challenging for sparse sequencing data, such as those from off-target regions in target sequencing studies, where genotypes are largely uncertain or missing. Existing methods often assume accurate genotypes at a large number of markers across the genome. We show that these methods, without accounting for the genotype uncertainty in sparse sequencing data, can yield a strong downward bias in kinship estimation. We develop a computationally efficient method called SEEKIN to estimate kinship for both homogeneous samples and heterogeneous samples with population structure and admixture. Our method models genotype uncertainty and leverages linkage disequilibrium through imputation. We test SEEKIN on a whole exome sequencing dataset (WES) of Singapore Chinese and Malays, which involves substantial population structure and admixture. We show that SEEKIN can accurately estimate kinship coefficient and classify genetic relatedness using off-target sequencing data down sampled to ~0.15X depth. In application to the full WES dataset without down sampling, SEEKIN also outperforms existing methods by properly analyzing shallow off-target data (~0.75X). Using both simulated and real phenotypes, we further illustrate how our method improves estimation of trait heritability for WES studies.

Inference of genetic relatedness from molecular markers has broad applications in many areas, including quantitative genetics, forensics, evolution and ecology. Classic estimators, however, are not suitable for low-coverage sequencing data, which have high levels of genotype uncertainty and missing data. We evaluate existing methods and describe a new method for kinship estimation using sparse sequencing data. Our method leverages correlations between neighboring markers and models genotype uncertainty in kinship estimators for both homogeneous populations and admixed populations. We show that our method can accurately estimate kinship coefficient even when the sequencing depth is as low as ~0.15X, while existing methods have strong downward bias. Our method can be applied to estimate kinship using sparse off-target data and thus enables control of family structure and estimation of heritability in target sequencing studies, in which the deeply sequenced target regions are often too small to infer genetic relatedness. Even for whole exome sequencing, we show that our method can improve kinship and heritability estimation by including off-target data, compared to conventional analyses solely based on the target regions.

Genome-wide linkage and association analysis of primary open-angle glaucoma endophenotypes in the Norfolk Island isolate

PURPOSE

Primary open-angle glaucoma (POAG) refers to a group of heterogeneous diseases involving optic nerve damage. Two well-established risk factors for POAG are elevated intraocular pressure (IOP) and a thinner central corneal thickness (CCT). These endophenotypes exhibit a high degree of heritability across populations. Large-scale genome-wide association studies (GWASs) of outbred populations have robustly implicated several susceptibility gene variants for both IOP and CCT. Despite this progress, a substantial amount of genetic variance remains unexplained. Population-specific variants that might be rare in outbred populations may also influence POAG endophenotypes. The Norfolk Island population is a founder-effect genetic isolate that has been well characterized for POAG endophenotypes. This population is therefore a suitable candidate for mapping new variants that influence these complex traits.

METHODS

Three hundred and thirty participants from the Norfolk Island Eye Study (NIES) core pedigree provided DNA. Ocular measurements of CCT and IOP were also taken for analysis. Heritability analyses and genome-wide linkage analyses of short tandem repeats (STRs) were conducted using SOLAR. Pedigree-based GWASs of single-nucleotide polymorphisms (SNPs) were performed using the GenABEL software.

RESULTS

CCT was the most heritable endophenotype in this cohort (h² = 0.77, p = 6×10^-6), while IOP showed a heritability of 0.39 (p = 0.008). A genome-wide linkage analysis of these POAG phenotypes identified a maximum logarithm of the odds (LOD) score of 1.9 for CCT on chromosome 20 (p = 0.0016) and 1.3 for IOP on chromosome 15 (p = 0.0072). The GWAS results revealed a study-wise significant association for IOP at rs790357, which is located within DLG2 on chr11q14.1 (p = 1.02×10^-7). DLG2 is involved in neuronal signaling and development, and while it has not previously been associated with IOP, it has been associated with myopia. An analysis of 12 known SNPs for IOP showed that rs12419342 in RAPSN on chromosome 11 was nominally associated in Norfolk Island (NI; p = 0.0021). For CCT, an analysis of 26 known SNPs showed rs9938149 in BANP-ZNF469 on chromosome 16 was nominally associated in NI (p = 0.002).

CONCLUSIONS

These study results indicate that CCT and IOP exhibit a substantial degree of heritability in the NI pedigree, indicating a genetic component. A genome-wide linkage analysis of POAG endophenotypes did not reveal any major effect loci, but the GWASs did implicate several known loci, as well as a potential new locus in DLG2, suggesting a role for neuronal signaling in development in IOP and perhaps POAG. These results also highlight the need to target rarer variants via whole genome sequencing in this genetic isolate.

Ultrafast Comparison of Personal Genomes via Precomputed Genome Fingerprints

We present an ultrafast method for comparing personal genomes. We transform the standard genome representation (lists of variants relative to a reference) into “genome fingerprints” via locality sensitive hashing. The resulting genome fingerprints can be meaningfully compared even when the input data were obtained using different sequencing technologies, processed using different pipelines, represented in different data formats and relative to different reference versions. Furthermore, genome fingerprints are robust to up to 30% missing data. Because of their reduced size, computation on the genome fingerprints is fast and requires little memory. For example, we could compute all-against-all pairwise comparisons among the 2504 genomes in the 1000 Genomes data set in 67 s at high quality (21 μs per comparison, on a single processor), and achieved a lower quality approximation in just 11 s. Efficient computation enables scaling up a variety of important genome analyses, including quantifying relatedness, recognizing duplicative sequenced genomes in a set, population reconstruction, and many others. The original genome representation cannot be reconstructed from its fingerprint, effectively decoupling genome comparison from genome interpretation; the method thus has significant implications for privacy-preserving genome analytics.

A Neolithic expansion, but strong genetic structure, in the independent history of New Guinea

New Guinea shows human occupation since ~50 thousand years ago (ka), independent adoption of plant cultivation ~10 ka, and great cultural and linguistic diversity today. We performed genome-wide single-nucleotide polymorphism genotyping on 381 individuals from 85 language groups in Papua New Guinea and find a sharp divide originating 10 to 20 ka between lowland and highland groups and a lack of non-New Guinean admixture in the latter. All highlanders share ancestry within the last 10 thousand years, with major population growth in the same period, suggesting population structure was reshaped following the Neolithic lifestyle transition. However, genetic differentiation between groups in Papua New Guinea is much stronger than in comparable regions in Eurasia, demonstrating that such a transition does not necessarily limit the genetic and linguistic diversity of human societies.

A model-based approach to characterize individual inbreeding at both global and local genomic scales

Inbreeding results from the mating of related individuals and may be associated with reduced fitness because it brings together deleterious variants in one individual. In general, inbreeding is estimated with respect to an arbitrary base population consisting of ancestors that are assumed unrelated. We herein propose a model-based approach to estimate and characterize individual inbreeding at both global and local genomic scales by assuming the individual genome is a mosaic of homozygous-by-descent (HBD) and non-HBD segments. The HBD segments may originate from ancestors tracing back to different periods in the past defining distinct age-related classes. The lengths of the HBD segments are exponentially distributed with class-specific parameters reflecting that inbreeding of older origin generates on average shorter stretches of observed homozygous markers. The model is implemented in a hidden Markov model framework that uses marker allele frequencies, genetic distances, genotyping error rates and the sequences of observed genotypes. Note that genotyping errors, low-fold sequencing or genotype-by-sequencing data are easily accommodated under this framework. Based on simulations under the inference model, we show that the genomewide inbreeding coefficients and the parameters of the model are accurately estimated. In addition, when several inbreeding classes are simulated, the model captures them if their ages are sufficiently different. Complementary analyses, either on data sets simulated under more realistic models or on human, dog and sheep real data, illustrate the range of applications of the approach and how it can reveal recent demographic histories among populations (e.g., very recent bottlenecks or founder effects). The method also allows to clearly identify individuals resulting from extreme consanguineous matings.