Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Jain A

PROVIDER: S-EPMC7778947 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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

Jain Abhinav A Bhoyar Rahul C RC Pandhare Kavita K Mishra Anushree A Sharma Disha D Imran Mohamed M Senthivel Vigneshwar V Divakar Mohit Kumar MK Rophina Mercy M Jolly Bani B Batra Arushi A Sharma Sumit S Siwach Sanjay S Jadhao Arun G AG Palande Nikhil V NV Jha Ganga Nath GN Ashrafi Nishat N Mishra Prashant Kumar PK A K Vidhya V Jain Suman S Dash Debasis D Kumar Nachimuthu Senthil NS Vanlallawma Andrew A Sarma Ranjan Jyoti RJ Chhakchhuak Lalchhandama L Kalyanaraman Shantaraman S Mahadevan Radha R Kandasamy Sunitha S B M Pabitha P Rajagopal Raskin Erusan RE J Ezhil Ramya ER P Nirmala Devi ND Bajaj Anjali A Gupta Vishu V Mathew Samatha S Goswami Sangam S Mangla Mohit M Prakash Savinitha S Joshi Kandarp K S Sreedevi S Gajjar Devarshi D Soraisham Ronibala R Yadav Rohit R Devi Yumnam Silla YS Gupta Aayush A Mukerji Mitali M Ramalingam Sivaprakash S B K Binukumar B Scaria Vinod V Sivasubbu Sridhar S

Nucleic acids research 20210101 D1

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' prog ...[more]

PMID: 33095885

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Project description:BackgroundAutoinflammatory 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.ResultsWe 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.ConclusionWith 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.

Dataset Information

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

Publications

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

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