Major Ancestries Research Articles

Novel genetic association of the Furin gene polymorphism rs1981458 with COVID-19 severity among Indian populations

SARS CoV-2, the causative agent for the ongoing COVID-19 pandemic, it enters the host cell by activating the ACE2 receptor with the help of two proteasesi.e., Furin and TMPRSS2. Therefore, variations in these genes may account for differential susceptibility and severity between populations. Previous studies have shown that the role of ACE2 and TMPRSS2 gene variants in understanding COVID-19 susceptibility among Indian populations. Nevertheless, a knowledge gap exists concerning the COVID-19 susceptibility of Furin gene variants among diverse South Asian ethnic groups. Investigating the role of Furin gene variants and their global phylogeographic structure is essential to comprehensively understanding COVID-19 susceptibility in these populations. We have used 450 samples from diverse Indian states and performed linear regression to analyse the Furin gene variant's with COVID-19 Case Fatality Rate (CFR) that could be epidemiologically associated with disease severity outcomes. Associated genetic variants were further evaluated for their expression and regulatory potential through various Insilco analyses. Additionally, we examined the Furin gene using next-generation sequencing (NGS) data from 393 diverse global samples, with a particular emphasis on South Asia, to investigate its Phylogeographic structure among diverse world populations. We found a significant positive association for the SNP rs1981458 with COVID-19 CFR (p < 0.05) among diverse Indian populations at different timelines of the first and second waves. Further, QTL and other regulatory analyses showed various significant associations for positive regulatory roles of rs1981458 and Furin gene, mainly in Immune cells and virus infection process, highlighting their role in host immunity and viral assembly and processing. The Furin protein–protein interaction suggested that COVID-19 may contribute to Pulmonary arterial hypertension via a typical inflammation mechanism. The phylogeographic architecture of the Furin gene demonstrated a closer genetic affinity of South Asia with West Eurasian populations. Therefore, it is worth proposing that for the Furin gene, the COVID-19 susceptibility of South Asians will be more similar to the West Eurasian population. Our previous studies on the ACE2 and TMPRSS2 genes showed genetic affinity of South Asian with East Eurasians and West Eurasians, respectively. Therefore, with the collective information from these three important genes (ACE2, TMPRSS2 and Furin) we modelled COVID-19 susceptibilityof South Asia in between these two major ancestries with an inclination towards West Eurasia. In conclusion, this study, for the first time, concluded the role of rs1981458 in COVID-19 severity among the Indian population and outlined its regulatory potential.This study also highlights that the genetic structure for COVID-19 susceptibilityof South Asia is distinct, however, inclined to the West Eurasian population. We believe this insight may be utilised as a genetic biomarker to identify vulnerable populations, which might be directly relevant for developing policies and allocating resources more effectively during an epidemic.

ADSP Whole Genome Sequencing (WGS) Release 4 Data Update from Genome Center for Alzheimer’s Disease

AbstractBackgroundThe Genome Center for Alzheimer’s Disease (GCAD) coordinates the integration of all available Alzheimer’s disease (AD) relevant whole genome sequencing (WGS) data with the goal of identifying AD risk or protective genetic variants and eventual therapeutic targets. The WGS datasets are generated through collaboration between investigators from the Alzheimer’s Disease Sequencing Project (ADSP) and GCAD. With the goal of minimizing data heterogeneity, introduced by different sequencing protocols and assays, GCAD processes all samples using standardized pipelines and performs quality control (QC)/quality assurance (QA) checks.MethodsRaw sequencing data (FASTQs or BAMs) were aligned to GRCh38/hg38 by BWA, and variant calling and joint genotyping on single nucleotide variants (SNVs), insertions and deletions (indels), were done by GATK. Structural variants (SVs) were called per sample using the Smoove, Manta, and Strelka packages. Preliminary QA checks including sex check, contamination, and genotype concordance were performed followed by QC per ADSP protocol to evaluate the quality of samples and variants. To facilitate access and usage of massive joint‐genotype called VCF files, a compact version for storing variant info and sample genotypes only was released first.ResultsWe dropped 275 (0.7%) samples of poor coverage (&lt;20×), and we flagged 219 (0.6%) samples that were of borderline quality. As a result, the dataset (ADSP Release 4, 2022) includes 36,361 genomes from 40 diverse cohorts with 4 major ancestries: 16,573 Non‐Hispanic Whites, 11,358 Hispanics; 5,422 African Americans; and 2,802 Asians. Data are deeply sequenced (average genome coverage: 40x). All samples’ CRAMs and gVCFs from GATK were deposited into NIAGADS Data Sharing Service (DSS) (https://dss.niagads.org/) for public distribution. Joint‐genotyped called VCFs are undergoing a full QC/annotation process and will be made available. This joint‐genotyped called VCF contains &gt;362M bi‐allelic variants, &gt;58M multi‐allelic variants, with 95% of variants remaining after QC. SV calling is ongoing and data will be ready prior to the conference.ConclusionThe ADSP and GCAD generate high quality SNVs, indels and SV calls. Currently GCAD is preparing the next release of ∼60,000 more ancestrally‐diverse WGS samples sequenced primarily through the ADSP Follow‐Up Study, which we anticipate will be released in 2023 to greatly benefit the AD genetics community.

69-OR: Multiancestry Genome-Wide Association Study Reveals Distinct Biological Pathways and Cell Types Driving Type 2 Diabetes Risk with Heterogeneous Effects across Diverse Populations

The Type 2 Diabetes Global Genomics Initiative aggregated genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 428,452 affected individuals and 2,107,149 controls from five major ancestries (39.7% non-European ancestry) to enhance power for locus discovery and improve understanding of the pathophysiological basis of the disease. We identified 1,289 independent association signals (P &amp;lt; 5 x 10-8) at 611 loci, of which 145 were previously unreported. We applied K-means clustering to the signals based on their associations with 37 cardiometabolic traits and identified eight clusters with distinct profiles. Three clusters were related to insulin secretion and had a positive, negative, or no effect on proinsulin levels. These clusters were significantly enriched (P &amp;lt; 0.05/222, Bonferroni correction for the number of cell types) for epigenomic annotations from single-cell ATAC-seq data in pancreatic islets but had different enrichment in pancreatic ductal cells and intestinal endocrine cells. The remaining five clusters related to insulin resistance (IR) physiology: increased body fat; unfavourable fat distribution (decreased gluteofemoral fat and increased visceral fat); obesity (increased body mass index); lipodystrophy (increased fasting insulin and decreased body fat); and liver lipid metabolism (increased liver fat and liver enzymes). IR clusters showed more diverse patterns of enrichment: obesity in adrenal cells; fat distribution in endothelial cells and pericytes in blood vessels; and lipodystrophy in adipocytes. T2D signals were more strongly enriched for ancestry-correlated heterogeneity in effect sizes in insulin secretion clusters than IR clusters. These data demonstrate distinct clusters of T2D association signals representing different trajectories to disease with observable differences in effect sizes across ancestry groups. Disclosure K.Suzuki: None. Diamante consortium: n/a. Va million veteran program: n/a. J.B.Meigs: Consultant; Quest Diagnostics. M.I.Mccarthy: Employee; Genentech, Inc., Stock/Shareholder; Roche Pharmaceuticals. A.Mahajan: Employee; Genentech, Inc. J.M.Mercader: None. C.Spracklen: None. M.Boehnke: None. M.Vujkovic: None. J.I.Rotter: None. K.Hatzikotoulas: None. B.F.Voight: None. E.Zeggini: None. A.Morris: None. Type 2 diabetes global genomics initiative: n/a. L.Southam: None. X.Yin: None. K.Lorenz: None. R.Mandla: None. H.J.Taylor: None. A.Huerta: None. N.W.Rayner: None.

74-OR: Improving Performance of Type 2 Diabetes Polygenic Scores in African and Hispanic Ancestries

Most polygenic scores (PS) are developed based on data from persons of European (EUR) ancestry and perform poorly in non-EUR populations. To improve the performance of type 2 diabetes (T2D) PS in the under-studied African (AFR) and Hispanic (HIS) ancestries, we created more comprehensive reference panels using the “Tagging Iterative of single nucleotide variant in multiple populations” (TagIt) method and aggregated genome-wide association study (GWAS) meta-analyses from 5 major continental ancestries (360K cases, 1.8M controls, 32% of non-EUR ancestry). We used PRS-CS and PRS-CSx to develop ancestry-specific and multi-ancestry PSs with HapMap3 (HM3) and TagIt panels and evaluated their performance based on the variance explained by the liability R2 (lR2). Trained models were then tested in independent datasets. Compared to HM3 panels, TagIt panels for AFR and HIS ancestries had 4X improved coverage for variants with minor allele frequency 1-5% and showed significant improvement of ancestry-specific PSs (p of difference&amp;lt;0.01). Multi-ancestry PSs based on linkage disequilibrium (LD) and GWAS data from 5 ancestries outperformed the ancestry-specific PSs (lR2 AFR: 0.024 AFR-based PS vs. 0.038 multi-ancestry PS, p of difference = 1.3×10-3; lR2 HIS: 0.017 HIS-based PS vs. 0.061 multi-ancestry PS, p of difference = 4×10-8). It also outperformed the PS based on the EUR GWAS and LD data (lR2 AFR: 0.024 EUR-based PS, p of difference = 0.003; lR2 HIS: 0.045 EUR-based PS, p of difference = 0.003). TagIt reference panels did not show significant improved performance when applying multi-ancestry PS. By leveraging existing GWAS data from multiple ancestries and building more comprehensive reference panels we can improve the performance of the PS for diverse ancestries. However, increasing available GWAS data from diverse ancestries is still needed to improve performance in non-EUR populations and reduce health disparities. Disclosure A.Huerta: None. M.Vujkovic: None. B.F.Voight: None. X.Sim: None. R.J.Loos: None. J.E.Below: None. T.Ge: None. Va million veteran program: n/a. J.C.Florez: Consultant; AstraZeneca, Novo Nordisk, Other Relationship; AstraZeneca, Merck &amp; Co., Inc. A.Manning: None. M.Ng: None. J.Kim: None. J.M.Mercader: None. I.Diabetes polygenic risk scores in multiple ancestr: n/a. R.Mandla: None. Y.Lu: None. L.E.Petty: None. K.Suzuki: None. S.S.Lee: None. H.Ng: None. M.Loh: None. Funding American Diabetes Association (11-22-ICTSPM-16 to J.M.M.); National Human Genome Research Institute (U01HG011723)

Polygenic score: An anchor holding the whole life course.

Polygenic score: An anchor holding the whole life course.

Open-Access Worldwide Population STR Database Constructed Using High-Coverage Massively Parallel Sequencing Data Obtained from the 1000 Genomes Project.

Achieving accurate STR genotyping by using next-generation sequencing data has been challenging. To provide the forensic genetics community with a reliable open-access STR database, we conducted a comprehensive genotyping analysis of a set of STRs of broad forensic interest obtained from 1000 Genome populations. We analyzed 22 STR markers using files of the high-coverage dataset of Phase 3 of the 1000 Genomes Project. We used HipSTR to call genotypes from 2504 samples obtained from 26 populations. We were not able to detect the D21S11 marker. The Hardy-Weinberg equilibrium analysis coupled with a comprehensive analysis of allele frequencies revealed that HipSTR was not able to identify longer alleles, which resulted in heterozygote deficiency. Nevertheless, AMOVA, a clustering analysis that uses STRUCTURE, and a Principal Coordinates Analysis showed a clear-cut separation between the four major ancestries sampled by the 1000 Genomes Consortium. Except for larger Penta D and Penta E alleles, and two very small Penta D alleles (2.2 and 3.2) usually observed in African populations, our analyses revealed that allele frequencies and genotypes offered as an open-access database are consistent and reliable.

Patterns of Population Structure and Introgression Among Recently Differentiated Drosophila melanogaster Populations.

Despite a century of genetic analysis, the evolutionary processes that have generated the patterns of exceptional genetic and phenotypic variation in the model organism Drosophila melanogaster remains poorly understood. In particular, how genetic variation is partitioned within its putative ancestral range in Southern Africa remains unresolved. Here, we study patterns of population genetic structure, admixture, and the spatial structuring of candidate incompatibility alleles across a global sample, including 223 new accessions, predominantly from remote regions in Southern Africa. We identify nine major ancestries, six that primarily occur in Africa and one that has not been previously described. We find evidence for both contemporary and historical admixture between ancestries, with admixture rates varying both within and between continents. For example, while previous work has highlighted an admixture zone between broadly defined African and European ancestries in the Caribbean and southeastern USA, we identify West African ancestry as the most likely African contributor. Moreover, loci showing the strongest signal of introgression between West Africa and the Caribbean/southeastern USA include several genes relating to neurological development and male courtship behavior, in line with previous work showing shared mating behaviors between these regions. Finally, while we hypothesized that potential incompatibility loci may contribute to population genetic structure across the range of D. melanogaster; these loci are, on average, not highly differentiated between ancestries. This work contributes to our understanding of the evolutionary history of a key model system, and provides insight into the partitioning of diversity across its range.

Haplotype-specific chromatin looping reveals genetic interactions of regulatory regions modulating gene expression in 8p23.1.

A major goal of genetics research is to elucidate mechanisms explaining how genetic variation contributes to phenotypic variation. The genetic variants identified in genome-wide association studies (GWASs) generally explain only a small proportion of heritability of phenotypic traits, the so-called missing heritability problem. Recent evidence suggests that additional common variants beyond lead GWAS variants contribute to phenotypic variation; however, their mechanistic underpinnings generally remain unexplored. Herein, we undertake a study of haplotype-specific mechanisms of gene regulation at 8p23.1 in the human genome, a region associated with a number of complex diseases. The FAM167A-BLK locus in this region has been consistently found in the genome-wide association studies (GWASs) of systemic lupus erythematosus (SLE) in all major ancestries. Our haplotype-specific chromatin interaction (Hi-C) experiments, allele-specific enhancer activity measurements, genetic analyses, and epigenome editing experiments revealed that: 1) haplotype-specific long-range chromatin interactions are prevalent in 8p23.1; 2) BLK promoter and cis-regulatory elements cooperatively interact with haplotype-specificity; 3) genetic variants at distal regulatory elements are allele-specific modifiers of the promoter variants at FAM167A-BLK; 4) the BLK promoter interacts with and, as an enhancer-like promoter, regulates FAM167A expression and 5) local allele-specific enhancer activities are influenced by global haplotype structure due to chromatin looping. Although systemic lupus erythematosus causal variants at the FAM167A-BLK locus are thought to reside in the BLK promoter region, our results reveal that genetic variants at distal regulatory elements modulate promoter activity, changing BLK and FAM167A gene expression and disease risk. Our results suggest that global haplotype-specific 3-dimensional chromatin looping architecture has a strong influence on local allelic BLK and FAM167A gene expression, providing mechanistic details for how regional variants controlling the BLK promoter may influence disease risk.

Bronze and Iron Age population movements underlie Xinjiang population history.

The Xinjiang region in northwest China is a historically important geographical passage between East and West Eurasia. By sequencing 201 ancient genomes from 39 archaeological sites, we clarify the complex demographic history of this region. Bronze Age Xinjiang populations are characterized by four major ancestries related to Early Bronze Age cultures from the central and eastern Steppe, Central Asian, and Tarim Basin regions. Admixtures between Middle and Late Bronze Age Steppe cultures continued during the Late Bronze and Iron Ages, along with an inflow of East and Central Asian ancestry. Historical era populations show similar admixed and diverse ancestries as those of present-day Xinjiang populations. These results document the influence that East and West Eurasian populations have had over time in the different regions of Xinjiang.

Detecting Genetic Ancestry and Adaptation in the Taiwanese Han People.

The Taiwanese people are composed of diverse indigenous populations and the Taiwanese Han. About 95% of the Taiwanese identify themselves as Taiwanese Han, but this may not be a homogeneous population because they migrated to the island from various regions of continental East Asia over a period of 400 years. Little is known about the underlying patterns of genetic ancestry, population admixture, and evolutionary adaptation in the Taiwanese Han people. Here, we analyzed the whole-genome single-nucleotide polymorphism genotyping data from 14,401 individuals of Taiwanese Han collected by the Taiwan Biobank and the whole-genome sequencing data for a subset of 772 people. We detected four major genetic ancestries with distinct geographic distributions (i.e., Northern, Southeastern, Japonic, and Island Southeast Asian ancestries) and signatures of population mixture contributing to the genomes of Taiwanese Han. We further scanned for signatures of positive natural selection that caused unusually long-range haplotypes and elevations of hitchhiked variants. As a result, we identified 16 candidate loci in which selection signals can be unambiguously localized at five single genes: CTNNA2, LRP1B, CSNK1G3, ASTN2, and NEO1. Statistical associations were examined in 16 metabolic-related traits to further elucidate the functional effects of each candidate gene. All five genes appear to have pleiotropic connections to various types of disease susceptibility and significant associations with at least one metabolic-related trait. Together, our results provide critical insights for understanding the evolutionary history and adaption of the Taiwanese Han population.

Systems Genetics in Human Endothelial Cells Identifies Non-coding Variants Modifying Enhancers, Expression, and Complex Disease Traits

The identification of causal variants and mechanisms underlying complex disease traits in humans is important for the progress of human disease genetics; this requires finding strategies to detect functional regulatory variants in disease-relevant cell types. To achieve this, we collected genetic and transcriptomic data from the aortic endothelial cells of up to 157 donors and four epigenomic phenotypes in up to 44 human donors representing individuals of both sexes and three major ancestries. We found thousands of expression quantitative trait loci (eQTLs) at all ranges of effect sizes not detected by the Gene-Tissue Expression Project (GTEx) in human tissues, showing that novel biological relationships unique to endothelial cells (ECs) are enriched in this dataset. Epigenetic profiling enabled discovery of over 3,000 regulatory elements whose activity is modulated by genetic variants that most frequently mutated ETS, AP-1, and NF-kB binding motifs, implicating these motifs as governors of EC regulation. Using CRISPR interference (CRISPRi), allele-specific reporter assays, and chromatin conformation capture, we validated candidate enhancer variants located up to 750 kb from their target genes, VEGFC, FGD6, and KIF26B. Regulatory SNPs identified were enriched in coronary artery disease (CAD) loci, and this result has specific implications for PECAM-1, FES, and AXL. We also found significant roles for EC regulatory variants in modifying the traits pulse pressure, blood protein levels, and monocyte count. Lastly, we present two unlinked SNPs in the promoter of MFAP2 that exhibit pleiotropic effects on human disease traits. Together, this supports the possibility that genetic predisposition for complex disease is manifested through the endothelium.

Estimating yields of prenatal carrier screening and implications for design of expanded carrier screening panels

PurposePrenatal genetic carrier screening can identify parents at risk of having a child affected by a recessive condition. However, the conditions/genes most appropriate for screening remain a matter of debate. Estimates of carrier rates across genes are needed to guide construction of carrier screening panels. MethodWe leveraged an exome sequencing database (n=123,136) to estimate carrier rates across six major ancestries for 415 genes associated with severe recessive conditions. ResultsWe found that 32.6% (East Asian) to 62.9% (Ashkenazi Jewish) of individuals are variant carriers in at least one of the 415 genes. For couples, screening all 415 genes would identify 0.17–2.52% of couples as being at risk for having a child affected by one of these conditions. Screening just the 40 genes with carrier rate >1.0% would identify more than 76% of these at-risk couples. An ancestry-specific panel designed to capture genes with carrier rates >1.0% would include 5 to 28 genes, while a comparable panethnic panel would include 40 genes. ConclusionOur work guides the design of carrier screening panels and provides data to assist in counseling prospective parents. Our results highlight a high cumulative carrier rate across genes, underscoring the need for careful selection of genes for screening.

Major subpopulations of Plasmodium falciparum in sub-Saharan Africa.

Understanding genomic variation and population structure of Plasmodium falciparum across Africa is necessary to sustain progress toward malaria elimination. Genome clustering of 2263 P. falciparum isolates from 24 malaria-endemic settings in 15 African countries identified major western, central, and eastern ancestries, plus a highly divergent Ethiopian population. Ancestry aligned to these regional blocs, overlapping with both the parasite's origin and with historical human migration. The parasite populations are interbred and shared genomic haplotypes, especially across drug resistance loci, which showed the strongest recent identity-by-descent between populations. A recent signature of selection on chromosome 12 with candidate resistance loci against artemisinin derivatives was evident in Ghana and Malawi. Such selection and the emerging substructure may affect treatment-based intervention strategies against P. falciparum malaria.

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.

Body fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥ 5%) and 9 low frequency or rare (MAF < 5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology, and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.

Genomic reconstruction of the history of extant populations of India reveals five distinct ancestral components and a complex structure

India, occupying the center stage of Paleolithic and Neolithic migrations, has been underrepresented in genome-wide studies of variation. Systematic analysis of genome-wide data, using multiple robust statistical methods, on (i) 367 unrelated individuals drawn from 18 mainland and 2 island (Andaman and Nicobar Islands) populations selected to represent geographic, linguistic, and ethnic diversities, and (ii) individuals from populations represented in the Human Genome Diversity Panel (HGDP), reveal four major ancestries in mainland India. This contrasts with an earlier inference of two ancestries based on limited population sampling. A distinct ancestry of the populations of Andaman archipelago was identified and found to be coancestral to Oceanic populations. Analysis of ancestral haplotype blocks revealed that extant mainland populations (i) admixed widely irrespective of ancestry, although admixtures between populations was not always symmetric, and (ii) this practice was rapidly replaced by endogamy about 70 generations ago, among upper castes and Indo-European speakers predominantly. This estimated time coincides with the historical period of formulation and adoption of sociocultural norms restricting intermarriage in large social strata. A similar replacement observed among tribal populations was temporally less uniform.

Native breeds demonstrate high contributions to the molecular variation in northern European sheep

Population contribution to genetic diversity can be estimated using neutral variation. However, population expansion or hybridization of diverged ancestries may weaken correlation between neutral and non-neutral variation. Microsatellite variation was studied at 25 loci in 20 native and 12 modern or imported northern European sheep breeds. Breed contributions to total gene diversity, allelic richness and mean allele-sharing distance between individuals were measured. Indications of changes in population size and admixtures of divergent ancestries were investigated and the extent of inbreeding was estimated. The northern European sheep demonstrated signs of reduction in effective population size. Many old, small populations made a substantial positive contribution to total molecular variation, but populations with several divergent major ancestries did not contribute substantially to molecular variation, with the exception of the Norwegian Rygja sheep. However, several diverged major ancestries may cause it to contribute less to non-neutral variation than expected from the microsatellite data. Breed uniqueness and within-breed variability generally had opposite effects on breed contributions to molecular diversity. The degree of inbreeding did not reflect the breed contribution to total gene diversity or allelic richness, but inbred populations increased the mean allele-sharing distance between individuals. Our study indicates breed conservation to be especially important in maintaining allelic variation in northern European sheep and supports the evolutionary importance of peripheral populations.