Whole genome sequencing of families diagnosed with cardiac channelopathies reveals structural variants missed by whole exome sequencing.

Cardiac channelopathies are a group of heritable disorders that affect the heart's electrical activity due to genetic variations present in genes coding for ion channels. With the advent of new sequencing technologies, molecular diagnosis of these disorders in patients has paved the way for early identification, therapeutic management and family screening. The objective of this retrospective study was to understand the efficacy of whole-genome sequencing in diagnosing patients with suspected cardiac channelopathies who were reported negative after whole exome sequencing and analysis. We employed a 3-tier analysis approach to identify nonsynonymous variations and loss-of-function variations missed by exome sequencing, and structural variations that are better resolved only by sequencing whole genomes. By performing whole genome sequencing and analyzing 25 exome-negative cardiac channelopathy patients, we identified 3 pathogenic variations. These include a heterozygous likely pathogenic nonsynonymous variation, CACNA1C:NM_000719:exon19:c.C2570G:p. P857R, which causes autosomal dominant long QT syndrome in the absence of Timothy syndrome, a heterozygous loss-of-function variation CASQ2:NM_001232.4:c.420+2T>C classified as pathogenic, and a 9.2 kb structural variation that spans exon 2 of the KCNQ1 gene, which is likely to cause Jervell-Lange-Nielssen syndrome. In addition, we also identified a loss-of-function variation and 16 structural variations of unknown significance (VUS). Further studies are required to elucidate the role of these identified VUS in gene regulation and decipher the underlying genetic and molecular mechanisms of these disorders. Our present study serves as a pilot for understanding the utility of WGS over clinical exomes in diagnosing cardiac channelopathy disorders.

Whole-genome sequencing of 1029 Indian individuals reveals unique and rare structural variants.

Structural variants contribute to genetic variability in human genomes and they can be presented in population-specific patterns. We aimed to understand the landscape of structural variants in the genomes of healthy Indian individuals and explore their potential implications in genetic disease conditions. For the identification of structural variants, a whole genome sequencing dataset of 1029 self-declared healthy Indian individuals from the IndiGen project was analysed. Further, these variants were evaluated for potential pathogenicity and their associations with genetic diseases. We also compared our identified variations with the existing global datasets. We generated a compendium of total 38,560 high-confident structural variants, comprising 28,393 deletions, 5030 duplications, 5038 insertions, and 99 inversions. Particularly, we identified around 55% of all these variants were found to be unique to the studied population. Further analysis revealed 134 deletions with predicted pathogenic/likely pathogenic effects and their affected genes were majorly enriched for neurological disease conditions, such as intellectual disability and neurodegenerative diseases. The IndiGenomes dataset helped us to understand the unique spectrum of structural variants in the Indian population. More than half of identified variants were not present in the publicly available global dataset on structural variants. Clinically important deletions identified in IndiGenomes might aid in improving the diagnosis of unsolved genetic diseases, particularly in neurological conditions. Along with basal allele frequency data and clinically important deletions, IndiGenomes data might serve as a baseline resource for future studies on genomic structural variant analysis in the Indian population.

1029 genomes of self-declared healthy individuals from India reveal prevalent and clinically relevant cardiac ion channelopathy variants.

BACKGROUND: The prevalence and genetic spectrum of cardiac channelopathies exhibit population-specific differences. We aimed to understand the spectrum of cardiac channelopathy-associated variations in India, which is characterised by a genetically diverse population and is largely understudied in the context of these disorders. RESULTS: We utilised the IndiGenomes dataset comprising 1029 whole genomes from self-declared healthy individuals as a template to filter variants in 36 genes known to cause cardiac channelopathies. Our analysis revealed 186,782 variants, of which we filtered 470 variants that were identified as possibly pathogenic (440 nonsynonymous, 30 high-confidence predicted loss of function ). About 26% (124 out of 470) of these variants were unique to the Indian population as they were not reported in the global population datasets and published literature. Classification of 470 variants by ACMG/AMP guidelines unveiled 13 pathogenic/likely pathogenic (P/LP) variants mapping to 19 out of the 1029 individuals. Further query of 53 probands in an independent cohort of cardiac channelopathy, using exome sequencing, revealed the presence of 3 out of the 13 P/LP variants. The identification of p.G179Sfs*62, p.R823W and c.420 + 2 T > C variants in KCNQ1, KCNH2 and CASQ2 genes, respectively, validate the significance of the P/LP variants in the context of clinical applicability as well as for large-scale population analysis. CONCLUSION: A compendium of ACMG/AMP classified cardiac channelopathy variants in 1029 self-declared healthy Indian population was created. A conservative genotypic prevalence was estimated to be 0.9-1.8% which poses a huge public health burden for a country with large population size like India. In the majority of cases, these disorders are manageable and the risk of sudden cardiac death can be alleviated by appropriate lifestyle modifications as well as treatment regimens/clinical interventions. Clinical utility of the obtained variants was demonstrated using a cardiac channelopathy patient cohort. Our study emphasises the need for large-scale population screening to identify at-risk individuals and take preventive measures. However, we suggest cautious clinical interpretation to be exercised by taking other cardiac channelopathy risk factors into account.

Genetic landscape of human platelet antigen variants in the Indian population analysed from 1029 whole genomes.

Genetic variants in human platelet antigens (HPAs) considered allo- or auto antigens are associated with various disorders, including neonatal alloimmune thrombocytopenia, platelet transfusion refractoriness and post-transfusion purpura. Although global differences in genotype frequencies were observed, the distributions of HPA variants in the Indian population are largely unknown. This study aims to explore the landscape of HPA variants in India to provide a basis for risk assessment and management of related complications. Population-specific frequencies of genetic variants associated with the 35 classes of HPAs (HPA-1 to HPA-35) were estimated by systematically analysing genomic variations of 1029 healthy Indian individuals as well as from global population genome datasets. Allele frequencies of the most clinically relevant HPA systems in the Indian population were found as follows, HPA-1a - 0.884, HPA-1b - 0.117, HPA-2a - 0.941, HPA-2b - 0.059, HPA-3a - 0.653, HPA-3b - 0.347, HPA-4a - 0.999, HPA-4b - 0.0010, HPA-5a - 0.923, HPA-5b - 0.077, HPA-6a - 0.998, HPA-6b - 0.002, HPA-15a - 0.582 and HPA-15b - 0.418. This study provides the first comprehensive analysis of HPA allele and genotype frequencies using large scale representative whole genome sequencing data of the Indian population.

IndiGenomes: a comprehensive resource of genetic variants from over 1000 Indian genomes.

With the advent of next-generation sequencing, large-scale initiatives for mining whole genomes and exomes have been employed to better understand global or population-level genetic architecture. India encompasses more than 17% of the world population with extensive genetic diversity, but is under-represented in the global sequencing datasets. This gave us the impetus to perform and analyze the whole genome sequencing of 1029 healthy Indian individuals under the pilot phase of the 'IndiGen' program. We generated a compendium of 55,898,122 single allelic genetic variants from geographically distinct Indian genomes and calculated the allele frequency, allele count, allele number, along with the number of heterozygous or homozygous individuals. In the present study, these variants were systematically annotated using publicly available population databases and can be accessed through a browsable online database named as 'IndiGenomes' http://clingen.igib.res.in/indigen/. The IndiGenomes database will help clinicians and researchers in exploring the genetic component underlying medical conditions. Till date, this is the most comprehensive genetic variant resource for the Indian population and is made freely available for academic utility. The resource has also been accessed extensively by the worldwide community since it's launch.

Variants of concern responsible for SARS-CoV-2 vaccine breakthrough infections from India.

Emerging reports of SARS-CoV-2 breakthrough infections entail methodical genomic surveillance for determining the efficacy of vaccines. This study elaborates genomic analysis of isolates from breakthrough infections following vaccination with AZD1222/Covishield and BBV152/Covaxin. Variants of concern B.1.617.2 and B.1.1.7 responsible for cases surge in April-May 2021 in Delhi, were the predominant lineages among breakthrough infections.

Spectrum of rare and common mitochondrial DNA variations from 1029 whole genomes of self-declared healthy individuals from India.

Mitochondrial disorders are a class of heterogeneous disorders caused by genetic variations in the mitochondrial genome (mtDNA) as well as the nuclear genome. The spectrum of mtDNA variants remains unexplored in the Indian population. In the present study, we have cataloged 2689 high confidence single nucleotide variants, small insertions and deletions in mtDNA in 1029 healthy Indian individuals. We found a major proportion (76.5 %) of the variants being rare (AF<=0.005) in the studied population. Intriguingly, we found two 'confirmed' pathogenic variants (m.1555 A>G and m.14484 T>C) with a frequency of ∼1 in 250 individuals in our dataset. The high carrier frequency underscores the need for screening of the mtDNA pathogenic mutations in newborns in India. Interestingly, our analysis also revealed 202 variants in our dataset which have been 'reported' in disease cases as per the MITOMAP database. Additionally, we found the frequency of haplogroup M (52.2 %) to be the highest among all the 18 top-level haplogroups found in our dataset. In comparison to the global population datasets, 20 unique mtDNA variants are found in the Indian population. We hope the whole genome sequencing based compendium of mtDNA variants along with their allele frequencies and heteroplasmy levels in the Indian population will drive additional genome scale studies for mtDNA. Furthermore, the identification of clinically relevant variants in our dataset will aid in better clinical interpretation of the variants in mitochondrial disorders.

Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population.

INTRODUCTION: Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related long-term complications. India's distinct genetic architecture and its exploding burden of type 2 diabetes warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. The recent availability of large-scale whole genomes from the Indian population provides a unique opportunity to generate a population-specific map of NIAD-associated PGx variants. RESEARCH DESIGN AND METHODS: We mined 1029 Indian whole genomes for PGx variants, drug-drug interaction (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Population-wise allele frequencies were estimated and compared using Fisher's exact test. RESULTS: Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to type 2 diabetes therapy among Indians. We report remarkable interethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared with other global populations. Network analysis of shared PGx genes predicts high DDI risk during coadministration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when coadministered with proton-pump inhibitors (PPIs). CONCLUSIONS: Indians and South Asians have a distinct PGx profile for antidiabetes drugs, marked by an excess of poor treatment response-associated alleles for various NIAD classes. This suggests the possibility of a population-specific reduced drug response in atleast some NIADs. In addition, our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and South Asians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population.

Genetic landscape of human neutrophil antigen variants in India from population-scale genomes.

Antibodies against human neutrophil antigens (HNAs) play a significant role in various clinical conditions such as neonatal alloimmune neutropenia, transfusion-related acute lung injury, and other nonhemolytic transfusion reactions. This study aims to identify the genotype and allele frequencies of HNAs in the healthy Indian population. Ten genetic variants in four human genes encoding alleles of HNAs class I-V approved by the International Society of Blood Transfusion-Granulocyte Immunobiology Working Party were used in the analysis. Genetic variants from whole genome sequences of 1029 healthy Indian individuals corresponding to HNA alleles were analyzed. The frequencies of the variants were compared with global population datasets using an in-house computational pipeline. In HNA class I, allele frequencies of FCGR3B*01, FCGR3B*02, and FCGR3B*03 encoding HNA-1a, HNA-1b, and HNA-1c were 0.07, 0.8, and 0.13, respectively. HNA class 3 alleles namely SLC44A2*01 (encoding HNA-3a) and SLC44A2*02 (encoding HNA-3b) were found at allele frequencies of 0.78 and 0.22, respectively. The frequencies of ITGAM*01 encoding HNA-4a and ITGAM*02 encoding HNA-4a were 0.95 and 0.05, respectively. Furthermore, allele frequencies of HNA class 5 alleles were 0.32 for ITGAL*01 (encoding HNA-5a) and 0.68 for ITGAL*02 (encoding HNA-5b). Interestingly, it was also found that rs2230433 variant deciding the HNA class 5 alleles, was highly prevalent (78.2%) in the Indian population compared with other global populations. This study presents the first comprehensive report of HNA allele and genotype frequencies in the Indian population using population genome datasets of 1029 individuals. Significant difference was observed in the prevalence of HNA5a and HNA5b in India in comparison to other global populations.

Pharmacogenomic landscape of Indian population using whole genomes.

Ethnic differences in pharmacogenomic (PGx) variants have been well documented in literature and could significantly impact variability in response and adverse events to therapeutics. India is a large country with diverse ethnic populations of distinct genetic architecture. India's national genome sequencing initiative (IndiGen) provides a unique opportunity to explore the landscape of PGx variants using population-scale whole genome sequences. We have analyzed the IndiGen variation dataset (N = 1029 genomes) along with global population scale databases to map the most prevalent clinically actionable and potentially deleterious PGx variants among Indians. Differential frequencies for the known and novel variants were studied and interaction of the disrupted PGx genes affecting drug responses were analyzed by performing a pathway analysis. We have highlighted significant differences in the allele frequencies of clinically actionable PGx variants in Indians when compared to the global populations. We identified 134 mostly common (allele frequency [AF] > 0.1) potentially deleterious PGx variants that could alter or inhibit the function of 102 pharmacogenes in Indians. We also estimate that on, an average, each Indian individual carried eight PGx variants (single nucleotide variants) that have a direct impact on the choice of treatment or drug dosing. We have also highlighted clinically actionable PGx variants and genes for which preemptive genotyping is most recommended for the Indian population. The study has put forward the most comprehensive PGx landscape of the Indian population from whole genomes that could enable optimized drug selection and genotype-guided prescriptions for improved therapeutic outcomes and minimizing adverse events.

Clinical, immunological and genomic characteristics of children with X-linked agammaglobulinemia from Kerala, South India.

X-linked agammaglobulinemia (XLA) is an X-linked recessive primary immunodeficiency disorder caused due to a pathogenic variant in the Bruton tyrosine (BTK) gene with an incidence of 1:379,000 live births and 1:190,000 male births. Patients affected with XLA present with recurrent infections of the gastrointestinal and respiratory tracts. Here we report the first case series of 17 XLA patients of 10 South Indian families with a wide spectrum of clinical and genetic features. In our cohort, patients presented mainly with recurrent pneumonia, gastrointestinal infection, otitis media, pyoderma, abscesses, empyema, arthritis, and osteomyelitis. Using next-generation and Sanger sequencing we have identified 10 unique pathogenic and likely pathogenic variants in 17 patients. This encompasses three nonsynonymous, two stop-gain, two frameshifts, two structural, and one splicing variant, out of which two of them are novel. Based on the type of variant, patients had variable clinical features and treatment responses. We have also evaluated Btk protein expression for six patients in comparison to the healthy individuals and determined mosaic Btk expression patterns in four mothers. We have also performed family screening in 6 families using Sanger sequencing and identified 19 carriers for the variant. The diagnosis for the patients led to the proper treatment i.e. 15 patients were on intravenous immunoglobulin (IVIG) and the other two had successful hematopoietic stem cell transplantation (HSCT). Unfortunately, two of our patients died due to sepsis, while on IVIG. We envision the present study could help in better understanding of patients with XLA and help in family screening and prenatal diagnosis. To the best of our knowledge, this is the largest case series of patients affected with XLA from South India.

An optimized, amplicon-based approach for sequencing of SARS-CoV-2 from patient samples using COVIDSeq assay on Illumina MiSeq sequencing platforms.

Sequencing of SARS-CoV-2 genomes is crucial for understanding the genetic epidemiology of the COVID-19 pandemic. It is also critical for understanding the evolution of the virus and also for the rapid development of diagnostic tools. The present protocol is a modification of the Illumina COVIDSeq test. We describe an amplicon-based next-generation sequencing approach with short turnaround time, adapted for bench-top sequencers like MiSeq, iSeq, and MiniSeq. For complete details on the use and execution of this protocol, please refer to Bhoyar et al. (2021).

Genomic characterization and epidemiology of an emerging SARS-CoV-2 variant in Delhi, India.

Delhi, the national capital of India, experienced multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks in 2020 and reached population seropositivity of >50% by 2021. During April 2021, the city became overwhelmed by COVID-19 cases and fatalities, as a new variant, B.1.617.2 (Delta), replaced B.1.1.7 (Alpha). A Bayesian model explains the growth advantage of Delta through a combination of increased transmissibility and reduced sensitivity to immune responses generated against earlier variants (median estimates: 1.5-fold greater transmissibility and 20% reduction in sensitivity). Seropositivity of an employee and family cohort increased from 42% to 87.5% between March and July 2021, with 27% reinfections, as judged by increased antibody concentration after a previous decline. The likely high transmissibility and partial evasion of immunity by the Delta variant contributed to an overwhelming surge in Delhi.

Pharmacogenomic landscape of COVID-19 therapies from Indian population genomes.

Aim: Numerous drugs are being widely prescribed for COVID-19 treatment without any direct evidence for the drug safety/efficacy in patients across diverse ethnic populations. Materials & methods: We analyzed whole genomes of 1029 Indian individuals (IndiGen) to understand the extent of drug-gene (pharmacogenetic), drug-drug and drug-drug-gene interactions associated with COVID-19 therapy in the Indian population. Results: We identified 30 clinically significant pharmacogenetic variants and 73 predicted deleterious pharmacogenetic variants. COVID-19-associated pharmacogenes were substantially overlapped with those of metabolic disorder therapeutics. CYP3A4, ABCB1 and ALB are the most shared pharmacogenes. Fifteen COVID-19 therapeutics were predicted as likely drug-drug interaction candidates when used with four CYP inhibitor drugs. Conclusion: Our findings provide actionable insights for future validation studies and improved clinical decisions for COVID-19 therapy in Indians.

Genetic epidemiology of autoinflammatory disease variants in Indian population from 1029 whole genomes.

BACKGROUND: Autoinflammatory disorders are the group of inherited inflammatory disorders caused due to the genetic defect in the genes that regulates innate immune systems. These have been clinically characterized based on the duration and occurrence of unprovoked fever, skin rash, and patient's ancestry. There are several autoinflammatory disorders that are found to be prevalent in a specific population and whose disease genetic epidemiology within the population has been well understood. However, India has a limited number of genetic studies reported for autoinflammatory disorders till date. The whole genome sequencing and analysis of 1029 Indian individuals performed under the IndiGen project persuaded us to perform the genetic epidemiology of the autoinflammatory disorders in India. RESULTS: We have systematically annotated the genetic variants of 56 genes implicated in autoinflammatory disorder. These genetic variants were reclassified into five categories (i.e., pathogenic, likely pathogenic, benign, likely benign, and variant of uncertain significance (VUS)) according to the American College of Medical Genetics and Association of Molecular pathology (ACMG-AMP) guidelines. Our analysis revealed 20 pathogenic and likely pathogenic variants with significant differences in the allele frequency compared with the global population. We also found six causal founder variants in the IndiGen dataset belonging to different ancestry. We have performed haplotype prediction analysis for founder mutations haplotype that reveals the admixture of the South Asian population with other populations. The cumulative carrier frequency of the autoinflammatory disorder in India was found to be 3.5% which is much higher than reported. CONCLUSION: With such frequency in the Indian population, there is a great need for awareness among clinicians as well as the general public regarding the autoinflammatory disorder. To the best of our knowledge, this is the first and most comprehensive population scale genetic epidemiological study being reported from India.

Organellar transcriptome sequencing reveals mitochondrial localization of nuclear encoded transcripts.

Mitochondria are organelles involved in a variety of biological functions in the cell, apart from their principal role in generation of ATP, the cellular currency of energy. The mitochondria, in spite of being compact organelles, are capable of performing complex biological functions largely because of the ability to exchange proteins, RNA, chemical metabolites and other biomolecules between cellular compartments. A close network of biomolecular interactions are known to modulate the crosstalk between the mitochondria and the nuclear genome. Apart from the small repertoire of genes encoded by the mitochondrial genome, it is now known that the functionality of the organelle is highly reliant on a number of proteins encoded by the nuclear genome, which localize to the mitochondria. With exceptions to a few anecdotal examples, the transcripts that have the potential to localize to the mitochondria have been poorly studied. We used a deep sequencing approach to identify transcripts encoded by the nuclear genome which localize to the mitoplast in a zebrafish model. We prioritized 292 candidate transcripts of nuclear origin that are potentially localized to the mitochondrial matrix. We experimentally demonstrated that the transcript encoding the nuclear encoded ribosomal protein 11 (Rpl11) localizes to the mitochondria. This study represents a comprehensive analysis of the mitochondrial localization of nuclear encoded transcripts. Our analysis has provided insights into a new layer of biomolecular pathways modulating mitochondrial-nuclear cross-talk. This provides a starting point towards understanding the role of nuclear encoded transcripts that localize to mitochondria and their influence on mitochondrial function.

SAGE: a comprehensive resource of genetic variants integrating South Asian whole genomes and exomes.

South Asia is home to $\sim $20% of the world population and characterized by distinct ethnic, linguistic, cultural and genetic lineages. Only limited representative samples from the region have found its place in large population-scale international genome projects. The recent availability of genome scale data from multiple populations and datasets from South Asian countries in public domain motivated us to integrate the data into a comprehensive resource. In the present study, we have integrated a total of six datasets encompassing 1213 human exomes and genomes to create a compendium of 154 814 557 genetic variants and adding a total of 69 059 255 novel variants. The variants were systematically annotated using public resources and along with the allele frequencies are available as a browsable-online resource South Asian genomes and exomes. As a proof of principle application of the data and resource for genetic epidemiology, we have analyzed the pathogenic genetic variants causing retinitis pigmentosa. Our analysis reveals the genetic landscape of the disease and suggests subset of genetic variants to be highly prevalent in South Asia.

Pharmacogenetic landscape of DPYD variants in south Asian populations by integration of genome-scale data.

AIM: Adverse drug reactions to 5-Fluorouracil(5-FU) is frequent and largely attributable to genetic variations in the DPYD gene, a rate limiting enzyme that clears 5-FU. The study aims at understanding the pharmacogenetic landscape of DPYD variants in south Asian populations. MATERIALS & METHODS: Systematic analysis of population scale genome wide datasets of over 3000 south Asians was performed. Independent evaluation was performed in a small cohort of patients. RESULTS: Our analysis revealed significant differences in the the allelic distribution of variants in different ethnicities. CONCLUSIONS: This is the first and largest genetic map the DPYD variants associated with adverse drug reaction to 5-FU in south Asian population. Our study highlights ethnic differences in allelic frequencies.