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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.

The underrepresentation of non-Europeans in human genetic studies so far has limited the diversity of individuals in genomic datasets and led to reduced medical relevance for a large proportion of the world’s population. Population-specific reference genome datasets as well as genome-wide association studies in diverse populations are needed to address this issue. Here we describe the pilot phase of the GenomeAsia 100K Project. This includes a whole-genome sequencing reference dataset from 1,739 individuals of 219 population groups and 64 countries across Asia. We catalogue genetic variation, population structure, disease associations and founder effects. We also explore the use of this dataset in imputation, to facilitate genetic studies in populations across Asia and worldwide. Using whole-genome sequencing data from 1,739 individuals, the GenomeAsia 100K Project catalogues genetic variation, population structure and disease associations to facilitate genetic studies in Asian populations and increase representation in genetics studies worldwide.

Background The demographic history of South and Southeast Asia (S&SEA) is complex and contentious, with multiple waves of human migration. Some of the earliest footfalls were of the ancestors of modern Austroasiatic (AA) language speakers. Understanding the history of the AA language family, comprising of over 150 languages and their speakers distributed across broad geographical region in isolated small populations of various sizes, can help shed light on the peopling of S&SEA. Here we investigated the genetic relatedness of two AA groups, their relationship with other ethno-linguistically distinct populations, and the relationship of these groups with ancient genomes of individuals living in S&SEA at different time periods, to infer about the demographic history of this region. Results We analyzed 1451 extant genomes, 189 AAs from India and Malaysia, and 43 ancient genomes from S&SEA. Population structure analysis reveals neither language nor geography appropriately correlates with genetic diversity. The inconsistency between “language and genetics” or “geography and genetics” can largely be attributed to ancient admixture with East Asian populations. We estimated a pre-Neolithic origin of AA language speakers, with shared ancestry between Indian and Malaysian populations until about 470 generations ago, contesting the existing model of Neolithic expansion of the AA culture. We observed a spatio-temporal transition in the genetic ancestry of SEA with genetic contribution from East Asia significantly increasing in the post-Neolithic period. Conclusion Our study shows that contrary to assumptions in many previous studies and despite having linguistic commonality, Indian AAs have a distinct genomic structure compared to Malaysian AAs. This linguistic-genetic discordance is reflective of the complex history of population migration and admixture shaping the genomic landscape of S&SEA. We postulate that pre-Neolithic ancestors of today’s AAs were widespread in S&SEA, and the fragmentation and dissipation of the population have largely been a resultant of multiple migrations of East Asian farmers during the Neolithic period. It also highlights the resilience of AAs in continuing to speak their language in spite of checkered population distribution and possible dominance from other linguistic groups.

Lipids foster energy production and their altered levels have been coupled with metabolic ailments. Indians feature high prevalence of metabolic diseases, yet uncharacterized for genes regulating lipid homeostasis. We performed first GWAS for quantitative lipids (total cholesterol, LDL, HDL, and triglycerides) exclusively in 5271 Indians. Further to corroborate our genetic findings, we investigated DNA methylation marks in peripheral blood in Indians at the identified loci (N = 233) and retrieved gene regulatory features from public domains. Recurrent GWAS loci-CELSR2, CETP, LPL, ZNF259, and BUD13 cropped up as lead signals in Indians, reflecting their universal applicability. Besides established variants, we found certain unreported variants at sub-genome-wide level-QKI, REEP3, TMCC2, FAM129C, FAM241B, and LOC100506207. These variants though failed to attain GWAS significance in Indians, but largely turned out to be active CpG sites in human subcutaneous adipose tissue and showed robust association to two or more lipid traits. Of which, QKI variants showed significant association to all four lipid traits and their designated region was observed to be a key gene regulatory segment denoting active transcription particularly in human subcutaneous adipose tissue. Both established and novel loci were observed to be significantly associated with altered DNA methylation in Indians for specific CpGs that resided in key regulatory elements. Further, gene-based association analysis pinpointed novel GWAS loci-LINC01340 and IQCJ-SCHIP1 for TC; IFT27, IFT88, and LINC02141 for HDL; and TEX26 for TG. Present study ascertains universality of selected known genes and also identifies certain novel loci for lipids in Indians by integrating data from various levels of gene regulation.

Indians undergoing socioeconomic and lifestyle transitions will be maximally affected by epidemic of type 2 diabetes (T2D). We conducted a two-stage genome-wide association study of T2D in 12,535 Indians, a less explored but high-risk group. We identified a new type 2 diabetes–associated locus at 2q21, with the lead signal being rs6723108 (odds ratio 1.31; P = 3.32 × 10−9). Imputation analysis refined the signal to rs998451 (odds ratio 1.56; P = 6.3 × 10−12) within TMEM163 that encodes a probable vesicular transporter in nerve terminals. TMEM163 variants also showed association with decreased fasting plasma insulin and homeostatic model assessment of insulin resistance, indicating a plausible effect through impaired insulin secretion. The 2q21 region also harbors RAB3GAP1 and ACMSD; those are involved in neurologic disorders. Forty-nine of 56 previously reported signals showed consistency in direction with similar effect sizes in Indians and previous studies, and 25 of them were also associated (P < 0.05). Known loci and the newly identified 2q21 locus altogether explained 7.65% variance in the risk of T2D in Indians. Our study suggests that common susceptibility variants for T2D are largely the same across populations, but also reveals a population-specific locus and provides further insights into genetic architecture and etiology of T2D.

Sarcoglycanopathy is the most frequent form of autosomal recessive limb-girdle muscular dystrophies caused by mutations in SGCB gene encoding beta-sarcoglycan proteins. In this study, we describe a shared, common haplotype co-segregating in 14 sarcoglycanopathy cases from 13 unrelated families from south Indian region with the likely pathogenic homozygous mutation c.544 T > G (p.Thr182Pro) in SGCB . Haplotype was reconstructed based on 10 polymorphic markers surrounding the c.544 T > G mutation in the cases and related family members as well as 150 unrelated controls from Indian populations using PLINK1.9. We identified haplotype H1 = G, A, G, T, G, G, A, C, T, G, T at a significantly higher frequency in cases compared to related controls and unrelated control Indian population. Upon segregation analysis within the family pedigrees, H1 is observed to co-segregate with c.544 T > G in a homozygous state in all the pedigrees of cases except one indicating a probable event of founder effect. Furthermore, Identical-by-descent and inbreeding coefficient analysis revealed relatedness among 33 new pairs of seemingly unrelated individuals from sarcoglycanopathy cohort and a higher proportion of homozygous markers, thereby indicating common ancestry. Since all these patients are from the south Indian region, we suggest this region to be a primary target of mutation screening in patients diagnosed with sarcoglycanopathy.

The contribution of chronic hepatitis B virus (HBV) infection in the pathogenesis of hepatocellular carcinoma (HCC) through progressive stages of liver fibrosis is exacerbated by the acquisition of naturally occurring mutations in its genome. This study has investigated the prevalence of single and combo mutations in the genome of HBV-genotype D from treatment naïve Indian patients of progressive liver disease stages and assessed their impact on the disease progression to HCC. The mutation profile was determined from the sequence analysis of the full-length HBV genome and compared with the reference HBV sequences. SPSS 16.0 and R software were used to delineate their statistical significance in predicting HCC occurrence. Age was identified as associated risk factor for HCC development in chronic hepatitis B (CHB) patients (p ≤ 0.01). Beyond the classical mutations in basal core promoter (BCP) (A1762T/G1764A) and precore (G1862T), persistence of progressively accumulated mutations in enhancer-I, surface, HBx and core were showed significant association to liver disease progression. BCP_T1753C, core_T147C, surface_L213I had contributed significantly in the disease progression to HCC (p < 0.05) in HBeAg positive patients whereas precore_T1858C, core_I116L, core_P130Q and preS1_S98T in HBeAg negative patients. Furthermore, the effect of individual mutation was magnified by the combination with A1762T/G1764A in HCC pathogenesis. Multivariate risk analysis had confirmed that core_P130Q [OR 20.71, 95% CI (1.64-261.77), p = 0.019] in B cell epitope and core_T147C [OR 14.58, 95% CI (1.17-181.76), p = 0.037] in CTL epitope were two independent predictors of HCC in HBeAg positive and negative patients respectively. Thus distinct pattern of mutations distributed across the entire HBV genome may be useful in predicting HCC in high-risk CHB patients and pattern of mutational combinations may exert greater impact on HCC risk prediction more accurately than point mutations and hence these predictors may support the existing surveillance strategies in proper management of the patients.

Primary open angle glaucoma (POAG) is a multi-factorial optic disc neuropathy characterized by accelerating damage of the retinal ganglion cells and atrophy of the optic nerve head. The vulnerability of the optic nerve damage leading to POAG has been postulated to result from oxidative stress and mitochondrial dysfunction. In this study, we investigated the possible involvement of the mitochondrial genomic variants in 101 patients and 71 controls by direct sequencing of the entire mitochondrial genome. The number of variable positions in the mtDNA with respect to the revised Cambridge Reference Sequence (rCRS), have been designated \"Segregating Sites\". The segregating sites present only in the patients or controls have been designated \"Unique Segregating Sites (USS)\". The population mutation rate (θ = 4Neμ) as estimated by Watterson's θ (θw), considering only the USS, was significantly higher among the patients (p = 9.8 × 10(-15)) compared to controls. The difference in θw and the number of USS were more pronounced when restricted to the coding region (p<1.31 × 10(-21) and p = 0.006607, respectively). Further analysis of the region revealed non-synonymous variations were significantly higher in Complex I among the patients (p = 0.0053). Similar trends were retained when USS was considered only within complex I (frequency 0.49 vs 0.31 with p<0.0001 and mutation rate p-value <1.49×10(-43)) and ND5 within its gene cluster (frequency 0.47 vs 0.23 with p<0.0001 and mutation rate p-value <4.42×10(-47)). ND5 is involved in the proton pumping mechanism. Incidentally, glaucomatous trabecular meshwork cells have been reported to be more sensitive to inhibition of complex I activity. Thus mutations in ND5, expected to inhibit complex I activity, could lead to generation of oxidative stress and favor glaucomatous condition.

Obesity, a risk factor for multiple diseases (e.g. diabetes, hypertension, cancers) originates through complex interactions between genes and prevailing environment (food habit and lifestyle) that varies across populations. Indians exhibit a unique obesity phenotype with high abdominal adiposity for a given body weight compared to matched white populations suggesting presence of population-specific genetic and environmental factors influencing obesity. However, Indian population-specific genetic contributors for obesity have not been explored yet. Therefore, to identify potential genetic contributors, we performed a two-staged genome-wide association study (GWAS) for body mass index (BMI), a common measure to evaluate obesity in 5973 Indian adults and the lead findings were further replicated in 1286 Indian adolescents. Our study revealed novel association of variants—rs6913677 in BAI3 gene (p = 1.08 × 10−8) and rs2078267 in SLC22A11 gene (p = 4.62 × 10−8) at GWAS significance, and of rs8100011 in ZNF45 gene (p = 1.04 × 10−7) with near GWAS significance. As genetic loci may dictate the phenotype through modulation of epigenetic processes, we overlapped genetic data of identified signals with their DNA methylation patterns in 236 Indian individuals and performed methylation quantitative trait loci (meth-QTL) analysis. Further, functional roles of discovered variants and underlying genes were speculated using publicly available gene regulatory databases (ENCODE, JASPAR, GeneHancer, GTEx). The identified variants in BAI3 and SLC22A11 genes were found to dictate methylation patterns at unique CpGs harboring critical cis-regulatory elements. Further, BAI3, SLC22A11 and ZNF45 variants were located in repressive chromatin, active enhancer, and active chromatin regions, respectively, in human subcutaneous adipose tissue in ENCODE database. Additionally, these genomic regions represented potential binding sites for key transcription factors implicated in obesity and/or metabolic disorders. Interestingly, GTEx portal identify rs8100011 as a robust cis-expression quantitative trait locus (cis-eQTL) in subcutaneous adipose tissue (p = 1.6 × 10−7), and ZNF45 gene expression in skeletal muscle of Indian subjects showed an inverse correlation with BMI indicating its possible role in obesity. In conclusion, our study discovered 3 novel population-specific functional genetic variants (rs6913677, rs2078267, rs8100011) in 2 novel (SLC22A11 and ZNF45) and 1 earlier reported gene (BAI3) for BMI in Indians. Our study decodes key genomic loci underlying obesity phenotype in Indians that may serve as prospective drug targets in future.