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In this issue of Cell, Bryska-Bishop et al. report the release of the expanded, high-depth sequencing data that characterize the fourth phase of the 1000 Genomes Project. Using extensive comparisons and benchmarks, they demonstrate how this dataset is positioned to serve as a more comprehensive and accurate resource for global genomics.

The complex pathogenesis of rheumatoid arthritis (RA) is not fully understood, with few studies exploring the genomic contribution to RA in patients from Africa. We report a genome-wide association study (GWAS) of South-Eastern Bantu-Speaking South Africans (SEBSSAs) with seropositive RA (n = 531) and population controls (n = 2653). Association testing was performed using PLINK (logistic regression assuming an additive model) with sex, age, smoking and the first three principal components as covariates. The strong association with the Human Leukocyte Antigen (HLA) region, indexed by rs602457 (near HLA-DRB1), was replicated. An additional independent signal in the HLA region represented by the lead SNP rs2523593 (near the HLA-B gene; Conditional P-value = 6.4 × 10−10) was detected. Although none of the non-HLA signals reached genome-wide significance (P

Cognitive function is an indicator for global physical and mental health, and cognitive impairment has been associated with poorer life outcomes and earlier mortality. A standard cognition test, adapted to a rural-dwelling African community, and the Oxford Cognition Screen-Plus were used to capture cognitive performance as five continuous traits (total cognition score, verbal episodic memory, executive function, language, and visuospatial ability) for 2,246 adults in this population of South Africans. A novel common variant, rs73485231, reached genome-wide significance for association with episodic memory using data for ~14 million markers imputed from the H3Africa genotyping array data. Window-based replication of previously implicated variants and regions of interest support the discovery of African-specific associated variants despite the small population size and low allele frequency. This African genome-wide association study identifies suggestive associations with general cognition and domain-specific cognitive pathways and lays the groundwork for further genomic studies on cognition in Africa.

Amyloid Aβ42 (constituents of the protein aggregates in the brains of patients with Alzheimer’s disease (AD) cleaved by ACE, and thus, a decrease in tissue ACE activity (constitutive or ACE inhibitor-induced) could be risk factor for AD. We hypothesized that subjects with heterozygous Loss-of-Function (LoF) ACE mutations are at risk for Alzheimer’s disease. Existing SNP databases were analyzed for LoF ACE mutations using PolyPhen-2 scores and compared with the topology of known ACE mutations already associated with AD. The combined frequency of >400 of these LoF-damaging ACE mutations in the general population is quite significant – up to 5 % – comparable with the frequency of AD in the population >70 years old. Our analysis suggests several mechanisms by which ACE mutations may be associated with Alzheimer’s disease. Systematic analysis of blood ACE levels in patients with all ACE mutations is likely to have clinical significance because available sequencing data will help detect persons with increased risk of late-onset Alzheimer’s disease. Patients with transport-deficient ACE mutations (about 20 % of damaging ACE mutations) may benefit from preventive or therapeutic treatment with a combination of chemical and pharmacological (e.g., centrally acting ACE inhibitors) chaperones and proteosome inhibitors to restore impaired surface ACE expression.

Most hypertension-related genome-wide association studies (GWAS) focus on non-African populations, despite hypertension (a major risk factor for cardiovascular disease) being highly prevalent in Africa. The AWI-Gen study GWAS meta-analysis for blood pressure-related traits (systolic and diastolic blood pressure, pulse pressure, mean-arterial pressure and hypertension) from three sub-Saharan African geographic regions (N=10,775), identified two genome-wide significant signals (p

Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry metaanalysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk., United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Heart Lung & Blood Institute (NHLBI) R01HL127564 R01HL142711, Wellcome Trust 201543/B/16/Z 202802/Z/16/Z, European Commission HEALTH-F2-2013-601456 608765 786833, TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation NNF15CC0018486, American Diabetes Association 1-19-ICTS-068, Academy of Finland 312062 Finnish Foundation for Cardiovascular Research, Sigrid Juselius Foundation, Finnish innovation fund Sitra (EW) Finska Lakaresallskapet, American Heart Association 15POST24470131 17POST33650016, University of Bristol NIHR Biomedical Research Centre BRC-1215-2001, MRC & WT 217065/Z/19/Z, UK Research & Innovation (UKRI), Medical Research Council UK (MRC) MC_UU_00011, CRUK Integrative Cancer Epidemiology Programme C18281/A19169, Medical Research Council UK (MRC) MC_UU_00011/1, UK National Institute for Health Research Academic Clinical Fellowship, American Heart Association 18CDA34110116, Miguel Servet contract from the ISCIII Spanish Health Institute CP17/00142, European Social Fund (ESF), Westlake Education Foundation, British Heart Foundation FS/14/66/3129 Z01HG200362 R01HL142302 R01HL105756

BackgroundAlzheimer’s disease (AD) is a complex multifactorial progressive dementia affecting all human populations. As a collaboration model between the International Hundred K+ Cohorts Consortium (IHCC) and the Davos Alzheimer Collaborative (DAC), our aim was to develop a trans-ethnic genomic informed risk assessment (GIRA) algorithm for AD.MethodsThe GIRA model was created to include a polygenic risk score (PRS) calculated from the AD GWAS loci, theAPOEhaplotypes, and non-genetic covariates including age, sex and first 3 principal components of population substructure. The model was first validated using a ancestrally diverse dataset from the eMERGE network, and subsequently validated in a South-Asian population in the UK and 3 East-Asian populations. The distributions of the PRS scores were also explored in populations from 3 African regions. In two validation sites, the PRS was tested for associated with the levels of plasma proteomics markers.ResultsWe created a trans-ethnic GIRA model for the risk prediction of AD and validated the performance of the GIRA model in different populations. The proteomic study in the participant sites identified proteins related to female infertility and autoimmune thyroiditis and associated with the risk scores of AD, highlighting molecular mechanisms underlying the previously observed correlations between these clinical phenotypes.ConclusionsAs the initial effort by the IHCC to leverage existing large scale datasets in a collaborative setting with DAC, we developed a trans-ethnic GIRA for AD with the potential of identifying individuals at high risk of developing AD for future clinical applications. The PRS scores in this model also contribute new research discoveries for the molecular pathogenesis of AD as demonstrated by the proteomic data.

Smoking is a leading risk factor for many of the top ten causes of death worldwide. Of the 1.3 billion smokers globally, 80% live in low- and middle-income countries, where the number of deaths due to tobacco use is expected to double in the next decade according to the World Health Organization. Genetic studies have helped to identify biological pathways for smoking behaviours, but have mostly focussed on individuals of European ancestry or living in either North America or Europe. We performed a genome-wide association study of two smoking behaviour traits in 10,558 men of African ancestry living in five African countries and the UK. Eight independent variants were associated with either smoking initiation or cessation at P-value –6, four being monomorphic or rare in European populations. Gene prioritisation strategy highlighted five genes, including SEMA6D, previously described as associated with several smoking behaviour traits. These results confirm the importance of analysing underrepresented populations in genetic epidemiology, and the urgent need for larger genomic studies to boost discovery power to better understand smoking behaviours, as well as many other traits.

Background/objectives: Admixed populations are a resource to study the global genetic architecture of complex phenotypes, which is critical, considering that non-European populations are severely underrepresented in genomic studies. Here, we study the genetic architecture of BMI in children, young adults, and elderly individuals from the admixed population of Brazil. Subjects/methods: Leveraging admixture in Brazilians, whose chromosomes are mosaics of fragments of Native American, European, and African origins, we used genome-wide data to perform admixture mapping/fine-mapping of body mass index (BMI) in three Brazilian population-based cohorts from Northeast (Salvador), Southeast (Bambui), and South (Pelotas). Results: We found significant associations with African-associated alleles in children from Salvador (PALD1 and ZMIZ1 genes), and in young adults from Pelotas (NOD2 and MTUS2 genes). More importantly, in Pelotas, rs114066381, mapped in a potential regulatory region, is significantly associated only in females (p = 2.76e-06). This variant is rare in Europeans but with frequencies of similar to 3% in West Africa and has a strong female-specific effect (95% CI: 2.32-5.65 kg/m(2) per each A allele). We confirmed this sex-specific association and replicated its strong effect for an adjusted fat mass index in the same Pelotas cohort, and for BMI in another Brazilian cohort from Sao Paulo (Southeast Brazil). A meta-analysis confirmed the significant association. Remarkably, we observed that while the frequency of rs114066381-A allele ranges from 0.8 to 2.1% in the studied populations, it attains similar to 9% among women with morbid obesity from Pelotas, Sao Paulo, and Bambui. The effect size of rs114066381 is at least five times higher than the FTO SNPs rs9939609 and rs1558902, already emblematic for their high effects. Conclusions: We identified six candidate SNPs associated with BMI. rs114066381 stands out for its high effect that was replicated and its high frequency in women with morbid obesity. We demonstrate how admixed populations are a source of new relevant phenotype-associated genetic variants.

Genetic associations for lipid traits have identified hundreds of variants with clear differences across European, Asian and African studies. Based on a sub-Saharan-African GWAS for lipid traits in the population cross-sectional AWI-Gen cohort (N = 10,603) we report a novel LDL-C association in the GATB region (P-value=1.56 × 10−8). Meta-analysis with four other African cohorts (N = 23,718) provides supporting evidence for the LDL-C association with the GATB/FHIP1A region and identifies a novel triglyceride association signal close to the FHIT gene (P-value =2.66 × 10−8). Our data enable fine-mapping of several well-known lipid-trait loci including LDLR, PMFBP1 and LPA. The transferability of signals detected in two large global studies (GLGC and PAGE) consistently improves with an increase in the size of the African replication cohort. Polygenic risk score analysis shows increased predictive accuracy for LDL-C levels with the narrowing of genetic distance between the discovery dataset and our cohort. Novel discovery is enhanced with the inclusion of African data.

The Cardiometabolic Disorders in African-Ancestry Populations (CARDINAL) study site is a well-powered, first-of-its-kind resource for developing, refining and validating methods for research into polygenic risk scores that accounts for local ancestry, to improve risk prediction in diverse populations.

Atherosclerosis precedes the onset of clinical manifestations of cardiovascular diseases (CVDs). We used carotid intima-media thickness (cIMT) to investigate genetic susceptibility to atherosclerosis in 7894 unrelated adults (3963 women, 3931 men; 40 to 60 years) resident in four sub-Saharan African countries. cIMT was measured by ultrasound and genotyping was performed on the H3Africa SNP Array. Two new African-specific genome-wide significant loci for mean-max cIMT, SIRPA (p = 4.7E-08), and FBXL17 (p = 2.5E-08), were identified. Sex-stratified analysis revealed associations with one male-specific locus, SNX29 (p = 6.3E-09), and two female-specific loci, LARP6 (p = 2.4E-09) and PROK1 (p = 1.0E-08). We replicate previous cIMT associations with different lead SNPs in linkage disequilibrium with SNPs primarily identified in European populations. Our study find significant enrichment for genes involved in oestrogen response from female-specific signals. The genes identified show biological relevance to atherosclerosis and/or CVDs, sex-differences and transferability of signals from non-African studies.

Two decades ago, the sequence of the first human genome was published. Since then, advances in genome technologies have resulted in whole-genome sequencing and microarray-based genotyping of millions of human genomes. However, genetic and genomic studies are predominantly based on populations of European ancestry. As a result, the potential benefits of genomic research-including better understanding of disease etiology, early detection and diagnosis, rational drug design and improved clinical care-may elude the many underrepresented populations. Here, we describe factors that have contributed to the imbalance in representation of different populations and, leveraging our experiences in setting up genomic studies in diverse global populations, we propose a roadmap to enhancing inclusion and ensuring equal health benefits of genomics advances. Our Perspective highlights the importance of sincere, concerted global efforts toward genomic equity to ensure the benefits of genomic medicine are accessible to all.

Research in European and Asian populations has reported associations between single nucleotide polymorphisms (SNPs) in CYP17A1 and SERPINA6/A1 and circulating glucocorticoid concentrations, and some key cardiometabolic risk factors. This study aimed to investigate these associations in black South African adults, who are disproportionally affected by the metabolic syndrome and its related cardiometabolic risk factors. The dataset included black South African adults (n = 4,431; 56.7% women) from the AWI-Gen study, genotyped on the H3A genotyping array and imputed using the African reference panel at the Sanger imputation service. From the imputed data, 31 CYP17A1 SNPs and 550 SERPINA6/A1 SNPs were extracted. The metabolic syndrome and its components were defined using the 2009 harmonized guidelines. Serum glucocorticoid concentrations were measured in a subset of 304 men and 573 women, using a liquid chromatography-mass spectrometry method. Genetic associations were detected using PLINK. Bonferroni correction was used to control for multiple testing. A SNP at SERPINA6/A1, rs17090691 (effect allele G), was associated with higher diastolic blood pressure (BP) in all adults combined (p = 9.47 × 10−6). Sex-stratified analyses demonstrated an association between rs1051052 (effect allele G), another SERPINA6/A1 SNP, and higher high-density lipoprotein (HDL) cholesterol concentrations in women (p = 1.23 × 10−5). No association was observed between these variants and glucocorticoids or between any of the CYP17A1 SNPs and metabolic outcomes after adjusting for multiple testing. Furthermore, there were no associations between any of the SNPs tested and the metabolic syndrome. This study reports novel genetic associations between two SNPs at SERPINA6/A1 and key cardiometabolic risk factors in black South Africans. Future replication and functional studies in larger populations are required to confirm the role of the identified SNPs in the metabolic syndrome and assess if these associations are mediated by circulating glucocorticoids.

Supplemental Digital Content is available in the text., Background African populations are characterised by high genetic diversity, which provides opportunities for discovering and elucidating novel variants of clinical importance, especially those affecting therapeutic outcome. Significantly more knowledge is however needed before such populations can take full advantage of the advances in precision medicine. Coupled with the need to concisely map and better understand the pharmacological implications of genetic diversity in populations of sub-Sharan African ancestry, the aim of this study was to identify and characterize known and novel variants present within 65 important absorption, distribution, metabolism and excretion genes. Patients and methods Targeted ultra-deep next-generation sequencing was used to screen a cohort of 40 South African individuals of Bantu ancestry. Results We identified a total of 1662 variants of which 129 are novel. Moreover, out of the 1662 variants 22 represent potential loss-of-function variants. A high level of allele frequency differentiation was observed for variants identified in this study when compared with other populations. Notably, on the basis of prior studies, many appear to be pharmacologically important in the pharmacokinetics of a broad range of drugs, including antiretrovirals, chemotherapeutic drugs, antiepileptics, antidepressants, and anticoagulants. An in-depth analysis was undertaken to interrogate the pharmacogenetic implications of this genetic diversity. Conclusion Despite the new insights gained from this study, the work illustrates that a more comprehensive understanding of population-specific differences is needed to facilitate the development of pharmacogenetic-based interventions for optimal drug therapy in patients of African ancestry.

Genetic associations for lipid traits have identified hundreds of variants with clear differences across European, Asian and African studies. Based on a sub-Saharan-African GWAS for lipid traits in the population cross-sectional AWI-Gen cohort (N = 10,603) we report a novel LDL-C association in the GATB region (P-value=1.56 × 10

Atherosclerosis precedes the onset of many clinical manifestations of cardiovascular diseases (CVDs). We used carotid intima-media thickness (cIMT) to investigate genetic susceptibility to atherosclerosis in 7894 unrelated adults (3963 women, 3931 men) aged 40 to 60 years resident in four sub-Saharan African countries. cIMT was measured by ultrasound and genotyping was performed on the H3Africa SNP Array. Two new African-specific genome-wide significant loci, SIRPA (p=4.7E-08), and FBXL17 (p=2.5E-08), were identified in the combined dataset. Sex-stratified analysis revealed associations with two male-specific loci, SNX29 (p=6.3E-09) and MAP3K7 (p=5.3E-08), and two female-specific loci, LARP6 (p=2.4E-09) and PROK1 (p=1.0E-08). Regional associations were replicated with known risk loci for atherosclerosis and CVDs with different lead SNPs than in Europeans and significant enrichment for oestrogen response genes for female-specific signals were identified. The genes identified showed biological relevance to atherosclerosis and/or CVDs, as well as sex-differences and transferability of signals from non-African studies.

Atherosclerosis precedes the onset of clinical manifestations of cardiovascular diseases (CVDs). We used carotid intima-media thickness (cIMT) to investigate genetic susceptibility to atherosclerosis in 7894 unrelated adults (3963 women, 3931 men; 40 to 60 years) resident in four sub-Saharan African countries. cIMT was measured by ultrasound and genotyping was performed on the H3Africa SNP Array. Two new African-specific genome-wide significant loci for mean-max cIMT, SIRPA (p = 4.7E-08), and FBXL17 (p = 2.5E-08), were identified. Sex-stratified analysis revealed associations with one male-specific locus, SNX29 (p = 6.3E-09), and two female-specific loci, LARP6 (p = 2.4E-09) and PROK1 (p = 1.0E-08). We replicate previous cIMT associations with different lead SNPs in linkage disequilibrium with SNPs primarily identified in European populations. Our study find significant enrichment for genes involved in oestrogen response from female-specific signals. The genes identified show biological relevance to atherosclerosis and/or CVDs, sex-differences and transferability of signals from non-African studies.

South Eastern Bantu-speaking (SEB) groups constitute more than 80% of the population in South Africa. Despite clear linguistic and geographic diversity, the genetic differences between these groups have not been systematically investigated. Based on genome-wide data of over 5000 individuals, representing eight major SEB groups, we provide strong evidence for fine-scale population structure that broadly aligns with geographic distribution and is also congruent with linguistic phylogeny (separation of Nguni, Sotho-Tswana and Tsonga speakers). Although differential Khoe-San admixture plays a key role, the structure persists after Khoe-San ancestry-masking. The timing of admixture, levels of sex-biased gene flow and population size dynamics also highlight differences in the demographic histories of individual groups. The comparisons with five Iron Age farmer genomes further support genetic continuity over ~400 years in certain regions of the country. Simulated trait genome-wide association studies further show that the observed population structure could have major implications for biomedical genomics research in South Africa., Despite linguistic and geographic diversity in South Eastern Bantu-speaking (SEB) groups of South Africa, genetic variation in these groups has not been investigated in depth. Here, the authors analyse genome-wide data from 5056 individuals, providing insights into demographic history across SEB groups.

Variations in lipid levels are attributed partly to genetic factors. Genome-wide association studies (GWASs) mainly performed in European, African American and Asian cohorts have identified variants associated with LDL-C, HDL-C, total cholesterol (TC) and triglycerides (TG), but few studies have been performed in sub-Saharan Africans. This study evaluated the effect of single nucleotide variants (SNVs) in eight candidate loci (ABCA1, LCAT, LPL, PON1, CETP, PCSK9, MVK, and MMAB) on lipid levels among 1855 Ghanaian adults. All lipid levels were measured directly using an automated analyser. DNA was extracted and genotyped using the H3Africa SNV array. Linear regression models were used to test the association between SNVs and log-transformed lipid levels, adjusting for sex, age and waist circumference. In addition Bonferroni correction was performed to account for multiple testing. Several variants of CETP, LCAT, PCSK9, and PON1 (MAF > 0.05) were associated with HDL-C, LDL-C and TC levels at p < 0.05. The lead variants for association with HDL-C were rs17231520 in CETP (β = 0.139, p < 0.0001) and rs1109166 in LCAT (β = −0.044, p = 0.028). Lower LDL-C levels were associated with an intronic variant in PCSK9 (rs11806638 [β = −0.055, p = 0.027]) and increased TC was associated with a variant in PON1 (rs854558 [β = 0.040, p = 0.020]). In silico functional analyses indicated that these variants likely influence gene function through their effect on gene transcription. We replicated a strong association between CETP variants and HDL-C and between PCSK9 variant and LDL-C in West Africans, with two potentially functional variants and identified three novel variants in linkage disequilibrium in PON1 which were associated with increasing TC levels in Ghanaians.

South Eastern Bantu-speaking (SEB) groups constitute more than 80% of the population in South Africa. Despite clear linguistic and geographic diversity, the genetic differences between these groups have not been systematically investigated. Based on genome-wide data of over 5000 individuals, representing eight major SEB groups, we provide strong evidence for fine-scale population structure that broadly aligns with geographic distribution and is also congruent with linguistic phylogeny (separation of Nguni, Sotho-Tswana and Tsonga speakers). Although differential Khoe-San admixture plays a key role, the structure persists after Khoe-San ancestry-masking. The timing of admixture, levels of sex-biased gene flow and population size dynamics also highlight differences in the demographic histories of individual groups. The comparisons with five Iron Age farmer genomes further support genetic continuity over ∼400 years in certain regions of the country. Simulated trait genome-wide association studies further show that the observed population structure could have major implications for biomedical genomics research in South Africa.

Chloroquine/hydroxychloroquine have been proposed as potential treatments for COVID-19. These drugs have warning labels for use in individuals with glucose-6-phosphate dehydrogenase (G6PD) deficiency. Analysis of whole genome sequence data of 458 individuals from sub-Saharan Africa showed significant G6PD variation across the continent. We identified nine variants, of which four are potentially deleterious to G6PD function, and one (rs1050828) that is known to cause G6PD deficiency. We supplemented data for the rs1050828 variant with genotype array data from over 11,000 Africans. Although this variant is common in Africans overall, large allele frequency differences exist between sub-populations. African sub-populations in the same country can show significant differences in allele frequency (e.g. 16.0% in Tsonga vs 0.8% in Xhosa, both in South Africa, p = 2.4 × 10−3). The high prevalence of variants in the G6PD gene found in this analysis suggests that it may be a significant interaction factor in clinical trials of chloroquine and hydroxychloroquine for treatment of COVID-19 in Africans.

Chloroquine/hydroxychloroquine have been proposed as potential treatments for COVID-19. These drugs have warning labels for use in individuals with glucose-6-phosphate dehydrogenase (G6PD) deficiency. Analysis of whole-genome sequence data of 458 individuals from sub-Saharan Africa showed significant G6PD variation across the continent. We identified nine variants, of which four are potentially deleterious to G6PD function, and one (rs1050828) that is known to cause G6PD deficiency. We supplemented data for the rs1050828 variant with genotype array data from over 11,000 Africans. Although this variant is common in Africans overall, large allele frequency differences exist between sub-populations. African sub-populations in the same country can show significant differences in allele frequency (e.g. 16.0% in Tsonga vs 0.8% in Xhosa, both in South Africa, p = 2.4 × 10−3). The high prevalence of variants in the G6PD gene found in this analysis suggests that it may be a significant interaction factor in clinical trials of chloroquine and hydrochloroquine for treatment of COVID-19 in Africans.

Introduction Atherosclerosis is a key contributor to the burden of cardiovascular diseases (CVDs) and many epidemiological studies have reported on the effect of smoking on carotid intima-media thickness (cIMT) and its subsequent effect on CVD risk. Gene-environment interaction studies have contributed towards understanding some of the missing heritability of genome-wide association studies. Gene-smoking interactions on cIMT have been studied in non-African populations (European, Latino-American, and African American) but no comparable African research has been reported. Our aim was to investigate smoking-SNP interactions on cIMT in two West African populations by genome-wide analysis. Materials and methods Only male participants from Burkina Faso (Nanoro = 993) and Ghana (Navrongo = 783) were included, as smoking was extremely rare among women. Phenotype and genotype data underwent stringent QC and genotype imputation was performed using the Sanger African Imputation Panel. Smoking prevalence among men was 13.3% in Nanoro and 42.5% in Navrongo. We analyzed gene-smoking interactions with PLINK after adjusting for covariates: age and 6 PCs (Model 1); age, BMI, blood pressure, fasting glucose, cholesterol levels, MVPA, and 6 PCs (Model 2). All analyses were performed at site level and for the combined data set. Results In Nanoro, we identified new gene-smoking interaction variants for cIMT within the previously described RCBTB1 region (rs112017404, rs144170770, and rs4941649) (Model 1: p = 1.35E-07; Model 2: p = 3.08E-08). In the combined sample, two novel intergenic interacting variants were identified, rs1192824 in the regulatory region of TBC1D8 (p = 5.90E-09) and rs77461169 (p = 4.48E-06) located in an upstream region of open chromatin. In silico functional analysis suggests the involvement of genes implicated in biological processes related to cell or biological adhesion and regulatory processes in gene-smoking interactions with cIMT (as evidenced by chromatin interactions and eQTLs). Discussion This is the first gene-smoking interaction study for cIMT, as a risk factor for atherosclerosis, in sub-Saharan African populations. In addition to replicating previously known signals for RCBTB1, we identified two novel genomic regions (TBC1D8, near BCHE) involved in this gene-environment interaction.

The Southern African Human Genome Programme is a national initiative that aspires to unlock the unique genetic character of southern African populations for a better understanding of human genetic diversity. In this pilot study the Southern African Human Genome Programme characterizes the genomes of 24 individuals (8 Coloured and 16 black southeastern Bantu-speakers) using deep whole-genome sequencing. A total of ~16 million unique variants are identified. Despite the shallow time depth since divergence between the two main southeastern Bantu-speaking groups (Nguni and Sotho-Tswana), principal component analysis and structure analysis reveal significant (p, African populations show a high level of genetic diversity and extensive regional admixture. Here, the authors sequence the whole genomes of 24 South African individuals of different ethnolinguistic origin and find substantive genomic divergence between two southeastern Bantu-speaking groups.

Admixed populations are a resource to study the global genetic architecture of complex phenotypes, which is critical, considering that non-European populations are severely under-represented in genomic studies. Leveraging admixture in Brazilians, whose chromosomes are mosaics of fragments of Native American, European and African origins, we used genome-wide data to perform admixture mapping/fine-mapping of Body Mass Index (BMI) in three population-based cohorts from Northeast (Salvador), Southeast (Bambuí) and South (Pelotas) of the country. We found significant associations with African-associated alleles in children from Salvador (PALD1 and ZMIZ1 genes), and in young adults from Pelotas (NOD2 and MTUS2 genes). More importantly, in Pelotas, rs114066381, mapped in a potential regulatory region, is significantly associated only in females (p= 2.76 e-06). This variant is very rare in Europeans but with frequencies of ~3% in West Africa, and has a strong female-specific effect (95%CI: 2.32-5.65 kg/m2 per each A allele). We confirmed this sex-specific association and replicated its strong effect for an adjusted fat-mass index in the same Pelotas cohort, and for BMI in another Brazilian cohort from São Paulo (Southeast Brazil). A meta-analysis confirmed the significant association. Remarkably, we observed that while the frequency of rs114066381-A allele ranges from 0.8 to 2.1% in the studied populations, it attains ~9% among morbidly obese women from Pelotas, São Paulo, and Bambuí. The effect size of rs114066381 is at least five-times the effect size of the FTO SNPs rs9939609 and rs1558902, already emblematic for their high effects, and for which we replicated associations in Pelotas. We demonstrate how, after a decade of GWAS mostly performed in European-ancestry populations, non-European and admixed populations are a source of new relevant phenotype-associated genetic variants.

Single nucleotide polymorphism arrays have created new possibilities for performing genome-wide studies to detect genomic regions harboring sequence variants that affect complex traits. However, the majority of validated SNPs for which allele frequencies have been estimated are limited primarily to European breeds. The objective of this study was to perform SNP discovery in three South African indigenous breeds (Afrikaner, Drakensberger, and Nguni) using whole genome sequencing. DNA was extracted from blood and hair samples, quantified and prepared at 50 ng/μl concentration for sequencing at the Agricultural Research Council Biotechnology Platform using an Illumina HiSeq 2500. The fastq files were used to call the variants using the Genome Analysis Tool Kit. A total of 1,678,360 were identified as novel using Run 6 of 1000 Bull Genomes Project. Annotation of the identified variants classified them into functional categories. Within the coding regions, about 30% of the SNPs were non-synonymous substitutions that encode for alternate amino acids. The study of distribution of SNP across the genome identified regions showing notable differences in the densities of SNPs among the breeds and highlighted many regions of functional significance. Gene ontology terms identified genes such as MLANA, SYT10, and CDC42EP5 that have been associated with coat color in mouse, and ADAMS3, DNAJC3, and PAG5 genes have been associated with fertility in cattle. Further analysis of the variants detected 688 candidate selective sweeps (ZHp Z-scores ≤ -4) across all three breeds, of which 223 regions were assigned as being putative selective sweeps (ZHp scores ≤-5). We also identified 96 regions with extremely low ZHp Z-scores (≤-6) in Afrikaner and Nguni. Genes such as KIT and MITF that have been associated with skin pigmentation in cattle and CACNA1C, which has been associated with biopolar disorder in human, were identified in these regions. This study provides the first analysis of sequence data to discover SNPs in indigenous South African cattle breeds. The information will play an important role in our efforts to understand the genetic history of our cattle and in designing appropriate breed improvement programmes.

Esophageal squamous cell carcinoma (ESCC) has a high incidence in sub-Saharan Africa and a poor prognosis, but little is known about the genetic contribution to ESCC susceptibility in this region. We carried out a GWAS in the South African Black (SAB) population with 1,686 ESCC cases and 3,217 controls as part of the Evolving Risk Factors for Cancer in African populations (ERICA-SA) study after ethical approval and informed consent. ESCC case samples from ERICA-SA and controls from the H3A AWI-Gen study were genotyped on the 2.3 million H3 Africa SNP Illumina array and additional SNPs imputed using the Wellcome Sanger Institute imputation service. Measures for correction of population structure included Eigen decomposition for Principal Component (PC) analysis. The final imputed dataset of 14.4M SNPs for 1,686 OSCC cases and 3,217 population controls was used in linear-mixed model analysis to test for association using GEMMA. A meta-analysis of SNP sets common to both our study and a GWAS of 2,013 Chinese ESCC cases and 2,701 controls was done using METAL. The GWAS of the SAB population identified a total of 62 SNPs with suggestive association with ESCC (P < 5x10-6), from 29 independent potential risk loci. A strong signal at genome-wide significance is located upstream of the FAM120A gene on chromosome 9 (rs1237966, p=4.58x10-8) and is supported by multiple SNPs at this locus. FAM120A encodes an RNA binding protein which is a critical component of oxidative stress-induced signalling. A strong association was also observed on chromosome 2, led by rs142741123 (p=5.49x10-8) in a region spanning the MYO1B and STAT4 genes with SNPs that are absent in non-African populations, suggesting that this is an African-specific risk locus for ESCC. There was limited support for the association of ESCC risk loci reported in other populations in our study. We did a meta-analysis of the SAB GWAS with a published GWAS of Chinese ESSC cases and controls with 4.85 million SNPs shared between the two studies. A total of 12 SNPs were associated with ESCC at genome-wide significance. These included 3 loci: chromosome 9, led by rs12379660 (p-valuemeta = 9.36x10-10), chromosome 10 led by rs7099485 (p-valuemeta = 1.48x10-8) and chromosome 22 led by rs1033667 (p-valuemeta = 1.47x10-9). The chromosome 9 locus at FAM120A is the novel locus identified in our African ESCC GWAS, the chromosome 10 locus at PLCE1 shows association only in the Chinese GWAS, and the chromosome 22 locus at CHEK2 was previously identified in the Chinese ESCC GWAS, and is supported further by the African ESCC GWAS. This study is, to our knowledge, the first cancer GWAS conducted in solely in a resident African population, and has detected two novel risk loci for ESCC at or near genome-wide significance, one of which is likely specific to African populations. It also demonstrates the power of trans-ethnic meta-analysis to identify common or distinct risk loci in populations of diverse ancestry. Citation Format: Wenlong C. Chen, Jean-Tristan Brandenburg, Ananyo Choudhury, Mahtaab Hayat, Dhriti Sengupta, Chantal Babb de Villiers, Lucien Ferndale, Cassandra Soo, Sang H. Lee, Charles Curtis, Robert Newton, Tim Waterboer, Frederic Sitas, Michele Ramsay, Christian C. Abnet, Colleen Aldous, Mohamed I. Parker, Elvira Singh, Deborah Bradshaw, Cathryn M. Lewis, Christopher G. Mathew. Genome-wide association study of African esophageal squamous cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 31.

A Correction to this paper has been published: https://doi.org/10.1038/s41586-021-03286-9.

Genomic variation in Indian populations is of great interest due to the diversity of ancestral components, social stratification, endogamy and complex admixture patterns. With an expanding population of 1.2 billion, India is also a treasure trove to catalogue innocuous as well as clinically relevant rare mutations. Recent studies have revealed four dominant ancestries in populations from mainland India: Ancestral North-Indian (ANI), Ancestral South-Indian (ASI), Ancestral Tibeto-Burman (ATB) and Ancestral Austro-Asiatic (AAA). The 1000 Genomes Project (KGP) Phase-3 data include about 500 genomes from five linguistically defined Indian-Subcontinent (IS) populations (Punjabi, Gujrati, Bengali, Telugu and Tamil) some of whom are recent migrants to USA or UK. Comparative analyses show that despite the distinct geographic origins of the KGP-IS populations, the ANI component is predominantly represented in this dataset. Previous studies demonstrated population substructure in the HapMap Gujrati population, and we found evidence for additional substructure in the Punjabi and Telugu populations. These substructured populations have characteristic/significant differences in heterozygosity and inbreeding coefficients. Moreover, we demonstrate that the substructure is better explained by factors like differences in proportion of ancestral components, and endogamy driven social structure rather than invoking a novel ancestral component to explain it. Therefore, using language and/or geography as a proxy for an ethnic unit is inadequate for many of the IS populations. This highlights the necessity for more nuanced sampling strategies or corrective statistical approaches, particularly for biomedical and population genetics research in India.

There is an alarming tide of cardiovascular and metabolic disease (CMD) sweeping across Africa. This may be a result of an increasingly urbanized lifestyle characterized by the growing consumption of processed and calorie-dense food, combined with physical inactivity and more sedentary behaviour. While the link between lifestyle and public health has been extensively studied in Caucasian and African American populations, few studies have been conducted in Africa. This paper describes the detailed methods for Phase 1 of the AWI-Gen study that were used to capture phenotype data and assess the associated risk factors and end points for CMD in persons over the age of 40 years in sub-Saharan Africa (SSA). We developed a population-based cross-sectional study of disease burden and phenotype in Africans, across six centres in SSA. These centres are in West Africa (Nanoro, Burkina Faso, and Navrongo, Ghana), in East Africa (Nairobi, Kenya) and in South Africa (Agincourt, Dikgale and Soweto). A total of 10,702 individuals between the ages of 40 and 60 years were recruited into the study across the six centres, plus an additional 1021 participants over the age of 60 years from the Agincourt centre. We collected socio-demographic, anthropometric, medical history, diet, physical activity, fat distribution and alcohol/tobacco consumption data from participants. Blood samples were collected for disease-related biomarker assays, and genomic DNA extraction for genome-wide association studies. Urine samples were collected to assess kidney function. The study provides base-line data for the development of a series of cohorts with a second wave of data collection in Phase 2 of the study. These data will provide valuable insights into the genetic and environmental influences on CMD on the African continent.

Objective The latest genome-wide association studies of obesity-related traits have identified several genetic loci contributing to body composition (BC). These findings have not been robustly replicated in African populations, therefore, this study aimed to assess whether European BC-associated gene loci played a similar role in a South African black population. Methods A replication and fine-mapping study was performed in participants from the Birth to Twenty cohort (N = 1,926) using the Metabochip. Measurements included body mass index (BMI), waist and hip circumference, waist-to-hip ratio (WHR), total fat mass, total lean mass and percentage fat mass (PFM). Results SNPs in several gene loci, including SEC16B (Padj −7), NEGR1 (Padj −6), FTO (Padj −5), TMEM18 (Padj −5), and WARS2(Padj −5) were similarly associated (albeit not at array-wide signficance (P ≤ 6.7 × 10−7) with various phenotypes including fat mass, PFM, WHR linked to BC in this African cohort, however the associations were driven by different sentinel SNPs. More importantly, DXA-derived BC measures revealed stronger genetic associations than simple anthropometric measures. Association signals generated in this study were shared by European and African populations, as well as unique to this African cohort. Moreover, sophisticated estimates like DXA measures enabled an enhanced characterisation of genetic associations for BC traits. Conclusion Results from this study suggest that in-depth genomic studies in larger African cohorts may reveal novel SNPs for body composition and adiposity, which will provide greater insight into the aetiology of obesity.

Genetic variation and susceptibility to disease are shaped by human demographic history and adaptation. We can now study the genomes of extant Africans and uncover traces of population migration, admixture, assimilation and selection by applying sophisticated computational algorithms. There are four major ethnolinguistic divisions among present day Africans: Hunter-gatherer populations in southern and central Africa; Nilo-Saharan speakers from north and northeast Africa; Afro-Asiatic speakers from north and east Africa; and Niger-Congo speakers who are the predominant ethnolinguistic group spread across most of sub-Saharan Africa. The enormous ethnolinguistic diversity in sub-Saharan African populations is largely paralleled by extensive genetic diversity and until a decade ago, little was known about detailed origins and divergence of these groups. Results from large-scale population genetic studies, and more recently whole genome sequence data, are unravelling the critical role of events like migration and admixture and environmental factors including diet, infectious diseases and climatic conditions in shaping current population diversity. It is now possible to start providing quantitative estimates of divergence times, population size and dynamic processes that have affected populations and their genetic risk for disease. Finally, the availability of ancient genomes from Africa provides historical insights of unprecedented depth. In this review, we highlight some key interpretations that have emerged from recent African genome studies.

The fifth of a series of seven H3ABioNet online lectures for Genome Wide Association Studies (GWAS) will introduce the concept of population structure/stratification (PS) and suggest why it is critical to consider PS in a GWAS. The lecture will begin by familiarizing the types of PS that are encountered and explain the factors that could cause them to appear in a GWAS dataset. It will then cover the methods that are commonly used to identify PS in a dataset and finally discuss the available computational approaches to correct for PS in a GWAS.

Background Cardiovascular diseases (CVDs) are the leading cause of non-communicable disease deaths globally, with hypertension being a major risk factor contributing to CVDs. Blood pressure is a heritable trait, with relatively few genetic studies having been performed in Africans. This study aimed to identify genetic variants associated with variance in systolic (SBP) and diastolic (DBP) blood pressure in black South Africans. Methods Genotyping was performed using the Metabochip in a subset of participants (mixed sex; median age 17.9) and their adult female caregivers (median age 41.0) from the Birth to Twenty cohort (n = 1947). Data were analysed as a merged dataset (all participants and caregivers together) in GEMMA (v0.94.1) using univariate linear mixed models, incorporating a centered relatedness matrix to account for the relatedness between individuals and with adjustments for age, sex, BMI and principal components of the genotype information. Results Association analysis identified regions of interest in the NOS1AP (DBP: rs112468105 - p = 7.18 × 10−5 and SBP: rs4657181 - p = 4.04 × 10−5), MYRF (SBP: rs11230796 - p = 2.16 × 10−7, rs400075 - p = 2.88 × 10−7) and POC1B (SBP: rs770373 - p = 7.05 × 10−5, rs770374 - p = 9.05 × 10−5) genes and some intergenic regions (DACH1|LOC440145 (DBP: rs17240498 - p = 4.91 × 10−6 and SBP: rs17240498 - p = 2.10 × 10−5) and INTS10|LPL (SBP: rs55830938 - p = 1.30 × 10−5, rs73599609 - p = 5.78 × 10−5, rs73667448 - p = 6.86 × 10−5)). Conclusions The study provided further insight into the contribution of genetic variants to blood pressure in black South Africans. Future functional and replication studies in larger samples are required to confirm the role of the identified loci in blood pressure regulation and whether or not these variants are African-specific. Electronic supplementary material The online version of this article (10.1186/s12920-018-0321-6) contains supplementary material, which is available to authorized users.

The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa) program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so., Author summary Many programs have been developed to boost the technical and computational skills of scientists working in low to medium income countries (LMIC), who often struggle to remain competitive with their peers in more developed parts of the world. Typically, these programs rely on intensive workshops where students acquire and exercise these skills under the supervision of experienced trainers. However, when trainees return to their home institutions, even after extensive exposure to state of the art techniques, they often find it difficult to put the skills they have acquired into practice and to establish themselves as fully independent practitioners. We have attempted to build a framework through which teams of scientists in African research groups can demonstrate that they have acquired the necessary skills to analyze different types of genomic datasets. Three teams of scientists who have successfully submitted to this assessment exercise report their positive experiences. Many potential participants have so far declined the opportunity, and we discuss the reasons for their reluctance as well as possible ways to facilitate their engagement and provide them with incentives. We argue that assessments such as this could be part of any program aiming to develop technical skills in scientists wishing to support genomic research programs.

SLC22A2 facilitates the transport of endogenous and exogenous cationic compounds. Many pharmacologically significant compounds are transported by SLC22A2, including the antidiabetic drug metformin, anticancer agent cisplatin, and antiretroviral lamivudine. Genetic polymorphisms in SLC22A2 can modify the pharmacokinetic profiles of such important medicines and could therefore prove useful as precision medicine biomarkers. Since the frequency of SLC22A2 polymorphisms varies among different ethnic populations, we evaluated these in South African Bantu speakers, a majority group in the South African population, who exhibit unique genetic diversity, and we subsequently functionally characterized promoter polymorphisms. We identified 11 polymorphisms within the promoter and 9 single-nucleotide polymorphisms (SNPs) within the coding region of SLC22A2. While some polymorphisms appeared with minor allele frequencies similar to other African and non-African populations, some differed considerably; this was especially notable for three missense polymorphisms. In addition, we functionally characterized two promoter polymorphisms; rs138765638, a three base-pair deletion that bioinformatics analysis suggested could alter c-Ets-1/2, Elk1, and/or STAT4 binding, and rs59695691, an SNP that could abolish TFII-I binding. Significantly higher luciferase reporter gene expression was found for rs138765638 (increase of 37%; p = 0.001) and significantly lower expression for rs59695691 (decrease of 25%; p = 0.038), in comparison to the wild-type control. These observations highlight the importance of identifying and functionally characterizing genetic variation in genes of pharmacological significance. Finally, our data for SLC22A2 attest to the importance of considering genetic variation in different populations for drug safety, response, and global pharmacogenomics, through, for example, projects such as the Human Heredity and Health in Africa initiative.

The aim of this study was to identify genetic variants associated with rheumatoid arthritis (RA) risk in black South Africans. Black South African RA patients (n = 263) were compared with healthy controls (n = 374). Genotyping was performed using the Immunochip, and four-digit high-resolution human leukocyte antigen (HLA) typing was performed by DNA sequencing of exon 2. Standard quality control measures were implemented on the data. The strongest associations were in the intergenic region between the HLA-DRB1 and HLA-DQA1 loci. After conditioning on HLA-DRB1 alleles, the effect in the rest of the extended major histocompatibility (MHC) diminished. Non-HLA single nucleotide polymorphisms (SNPs) in the intergenic regions LOC389203|RBPJ, LOC100131131|IL1R1, KIAA1919|REV3L, LOC643749|TRAF3IP2, and SNPs in the intron and untranslated regions (UTR) of IRF1 and the intronic region of ICOS and KIAA1542 showed association with RA (p < 5 × 10−5). Of the SNPs previously associated with RA in Caucasians, one SNP, rs874040, locating to the intergenic region LOC389203|RBPJ was replicated in this study. None of the variants in the PTPN22 gene was significantly associated. The seropositive subgroups showed similar results to the overall cohort. The effects observed across the HLA region are most likely due to HLA-DRB1, and secondary effects in the extended MHC cannot be detected. Seven non-HLA loci are associated with RA in black South Africans. Similar to Caucasians, the intergenic region between LOC38920 and RBPJ is associated with RA in this population. The strong association of the R620W variant of the PTPN22 gene with RA in Caucasians was not replicated since this variant was monomorphic in our study, but other SNP variants of the PTPN22 gene were also not associated with RA in black South Africans, suggesting that this locus does not play a major role in RA in this population.

Access to genotyping assays enables the identification of informative markers that discriminate between cattle breeds. Identification of these markers can assist in breed assignment, improvement and conservation. The objective of this study was to identify breed informative markers to discriminate between three South African indigenous cattle breeds. Data from BovineSNP50 and GeneSeek Genomic Profiler (GGP-80K) assays were generated for Afrikaner, Drakensberger and Nguni, and were analysed for their genetic differentiation. Hereford and Angus were included as outgroups. Breeds were differentiated using principal component analysis (PCA). Single-nucleotide polymorphisms (SNPs) within the breeds were determined when minor allele frequency (MAF) was ≥ 0.05. Breed-specific SNPs were identified using Reynolds Fst and extended Lewontin and Krakauer's (FLK) statistics. These SNPs were validated using three African breeds, namely N’Dama, Kuri and Zebu from Madagascar. PCA discriminated among the breeds. A larger number of polymorphic SNPs was detected in Drakensberger (73%) than in Afrikaner (56%) and Nguni (65%). No substantial numbers of informative SNPs (Fst ≥ 0.6) were identified among indigenous breeds. Eleven SNPs were validated as discriminating the indigenous breeds from other African breeds. This is because the SNPs on BovineSNP50 and GGP-80K assays were ascertained as being common in European taurine breeds. Lower MAF and SNP informativeness observed in this study limits the application of these assays in breed assignment, and could have other implications for genome-wide studies in South African indigenous breeds. Sequencing should therefore be considered to discover new SNPs that are common among indigenous South African breeds and also SNPs that discriminate among these indigenous breeds.

Transcription regulation by the phytohormone abscisic acid (ABA) plays a key role in responses to various stresses and has been extensively studied in Arabidopsis thaliana using different expression analysis techniques. Previous studies on comparative analysis of expression regulation by ABA and ABA-related stresses demonstrated marked differences in the targets of ABA. However, as few expression experiments were available during these studies, they encompass only a subset of ABA-regulated genes. The aim of the present work was to compare gene expression regulated by ABA administration in a wider range of expression experiments. Despite diversity in the actual set of genes regulated by ABA, all ABA-regulated transcriptomes shared some basic features, such as a common induced gene set, common functional targets and involvement of common regulatory mechanisms. Moreover, the cis-regulatory architecture of genes belonging to this set is expected to be of interest because of their sensitivity to ABA and apparent independence from other experimental variables. Comparative analysis of cis-regulatory element (CRE) enrichment also identified a novel CRE that is strongly associated with ABA signalling-mediated transcription repression.

To investigate the mechanism of increased expression of caspase-1 caused by exogenous Hippi, observed earlier in HeLa and Neuro2A cells, in this work we identified a specific motif AAAGACATG (- 101 to - 93) at the caspase-1 gene upstream sequence where HIPPI could bind. Various mutations in this specific sequence compromised the interaction, showing the specificity of the interactions. In the luciferase reporter assay, when the reporter gene was driven by caspase-1 gene upstream sequences (- 151 to - 92) with the mutation G to T at position - 98, luciferase activity was decreased significantly in green fluorescent protein-Hippi-expressing HeLa cells in comparison to that obtained with the wild-type caspase-1 gene 60 bp upstream sequence, indicating the biological significance of such binding. It was observed that the C-terminal 'pseudo' death effector domain of HIPPI interacted with the 60 bp (- 151 to - 92) upstream sequence of the caspase-1 gene containing the motif. We further observed that expression of caspase-8 and caspase-10 was increased in green fluorescent protein-Hippi-expressing HeLa cells. In addition, HIPPI interacted in vitro with putative promoter sequences of these genes, containing a similar motif. In summary, we identified a novel function of HIPPI; it binds to specific upstream sequences of the caspase-1, caspase-8 and caspase-10 genes and alters the expression of the genes. This result showed the motif-specific interaction of HIPPI with DNA, and indicates that it could act as transcription regulator.

Given the importance of Africa to studies of human origins and disease susceptibility, detailed characterization of African genetic diversity is needed. The African Genome Variation Project provides a resource with which to design, implement and interpret genomic studies in sub-Saharan Africa and worldwide. The African Genome Variation Project represents dense genotypes from 1,481 individuals and whole-genome sequences from 320 individuals across sub-Saharan Africa. Using this resource, we find novel evidence of complex, regionally distinct hunter-gatherer and Eurasian admixture across sub-Saharan Africa. We identify new loci under selection, including loci related to malaria susceptibility and hypertension. We show that modern imputation panels (sets of reference genotypes from which unobserved or missing genotypes in study sets can be inferred) can identify association signals at highly differentiated loci across populations in sub-Saharan Africa. Using whole-genome sequencing, we demonstrate further improvements in imputation accuracy, strengthening the case for large-scale sequencing efforts of diverse African haplotypes. Finally, we present an efficient genotype array design capturing common genetic variation in Africa.

Background Population differentiation is the result of demographic and evolutionary forces. Whole genome datasets from the 1000 Genomes Project (October 2012) provide an unbiased view of genetic variation across populations from Europe, Asia, Africa and the Americas. Common population-specific SNPs (MAF > 0.05) reflect a deep history and may have important consequences for health and wellbeing. Their interpretation is contextualised by currently available genome data. Results The identification of common population-specific (CPS) variants (SNPs and SSV) is influenced by admixture and the sample size under investigation. Nine of the populations in the 1000 Genomes Project (2 African, 2 Asian (including a merged Chinese group) and 5 European) revealed that the African populations (LWK and YRI), followed by the Japanese (JPT) have the highest number of CPS SNPs, in concordance with their histories and given the populations studied. Using two methods, sliding 50-SNP and 5-kb windows, the CPS SNPs showed distinct clustering across large genome segments and little overlap of clusters between populations. iHS enrichment score and the population branch statistic (PBS) analyses suggest that selective sweeps are unlikely to account for the clustering and population specificity. Of interest is the association of clusters close to recombination hotspots. Functional analysis of genes associated with the CPS SNPs revealed over-representation of genes in pathways associated with neuronal development, including axonal guidance signalling and CREB signalling in neurones. Conclusions Common population-specific SNPs are non-randomly distributed throughout the genome and are significantly associated with recombination hotspots. Since the variant alleles of most CPS SNPs are the derived allele, they likely arose in the specific population after a split from a common ancestor. Their proximity to genes involved in specific pathways, including neuronal development, suggests evolutionary plasticity of selected genomic regions. Contrary to expectation, selective sweeps did not play a large role in the persistence of population-specific variation. This suggests a stochastic process towards population-specific variation which reflects demographic histories and may have some interesting implications for health and susceptibility to disease.

Supplementary material, approximately 2.7 MB.

Background HIP1 Protein Interactor (HIPPI) is a pro-apoptotic protein that induces Caspase8 mediated apoptosis in cell. We have shown earlier that HIPPI could interact with a specific 9 bp sequence motif, defined as the HIPPI binding site (HBS), present in the upstream promoter of Caspase1 gene and regulate its expression. We also have shown that HIPPI, without any known nuclear localization signal, could be transported to the nucleus by HIP1, a NLS containing nucleo-cytoplasmic shuttling protein. Thus our present work aims at the investigation of the role of HIPPI as a global transcription regulator. Results We carried out genome wide search for the presence of HBS in the upstream sequences of genes. Our result suggests that HBS was predominantly located within 2 Kb upstream from transcription start site. Transcription factors like CREBP1, TBP, OCT1, EVI1 and P53 half site were significantly enriched in the 100 bp vicinity of HBS indicating that they might co-operate with HIPPI for transcription regulation. To illustrate the role of HIPPI on transcriptome, we performed gene expression profiling by microarray. Exogenous expression of HIPPI in HeLa cells resulted in up-regulation of 580 genes (p < 0.05) while 457 genes were down-regulated. Several transcription factors including CBP, REST, C/EBP beta were altered by HIPPI in this study. HIPPI also interacted with P53 in the protein level. This interaction occurred exclusively in the nuclear compartment and was absent in cells where HIP1 was knocked down. HIPPI-P53 interaction was necessary for HIPPI mediated up-regulation of Caspase1 gene. Finally, we analyzed published microarray data obtained with post mortem brains of Huntington's disease (HD) patients to investigate the possible involvement of HIPPI in HD pathogenesis. We observed that along with the transcription factors like CREB, P300, SREBP1, Sp1 etc. which are already known to be involved in HD, HIPPI binding site was also significantly over-represented in the upstream sequences of genes altered in HD. Conclusions Taken together, the results suggest that HIPPI could act as an important transcription regulator in cell regulating a vast array of genes, particularly transcription factors and at least, in part, play a role in transcription deregulation observed in HD.

The populations of Africa harbour the greatest human genetic diversity following an evolutionary history tracing its beginnings on the continent to time before the emergence of Homo sapiens. Signatures of selection are detectable as responses to ancient environments and cultural practices, modulated by more recent events including infectious epidemics, migrations, admixture and, of course, chance. The age of high-throughput biology is not passing Africa by. African-based cohort studies and networks with an African footprint are ideal springboards for disease-related genetic and genomic studies. Initiatives like HapMap, the 1000 Genomes Project, MalariaGEN, the INDEPTH network and Human Heredity and Health in Africa are catalysts to exploring African genetic diversity and its role in the spectrum from health to disease. The challenges are abundant in dissecting biological questions in the light of linguistic, cultural, geographic and political boundaries and their respective roles in shaping health-related profiles. Will studies based on African populations lead to a new wave of discovery of genetic contributors to disease?

The effects of abscisic acid (ABA) induction on Arabidopsis thaliana transcriptome have been investigated by various expression studies. We have assembled and analyzed data from available expression studies related to ABA signaling in Arabidopsis along with other available microarray data, functional annotations and information related to occurrence of cis-regulatory elements in promoters of Arabidopsis genes in a database called TRABAS. TRABAS is expected to provide a simple, user-friendly platform to facilitate the study of different aspects of ABA mediated transcription regulation and is freely available at http://www.bioinformatics.org/trabas/.