The Indian Genome Variation database (IGVdb): A project overview

Samir K. Brahmachari, Lalji Singh, Abhay Sharma, Mitali Mukerji, Kunal Ray, Susanta Roychoudhury, G. R. Chandak, K. Thangaraj, Saman Habib, D. Parmar, Partha P. Majumder, Shantanu Sengupta, Dwaipayan Bharadwaj, Debasis Dash, Srikanta K. Rath, R. Shankar, Jagmohan Singh, Komal Virdi, Samira Bahl, V. R. RaoSwapnil Sinha, Ashok Singh, Amit Mitra, Shrawan K. Mishra, B. R K Shukla, Qadar Pasha, Souvik Maiti, Amitabh Sharma, Jitender Kumar, Aarif Ahsan, Tsering Stobdan, Chitra Chauhan, Saurabh Malhotra, Ajay Vidhani, S. Siva, Aradhita Baral, Rajesh Pandey, Ravishankar Roy, Mridula Singh, S. P. Singh, Nitin Maurya, Arun Bandyopadhyay, Ganga Nath Jha, Somnath Dutta, Gautam Ghosh, Tufan Naiya, Manoj Jain, J. P. Srivatava, J. R. Gupta, Vinay Khanna, Alok Dhawan, Mohini Anand, R. S. Bharti, Madhu Singh, Arvind P. Singh, Anwar J. Khan, Kamlesh Kumar Bisht, Ashok Kumar, Balaram Ghosh, Swapan Kumar Das, Taruna Madan, Chitra Chauhan, Ranjana Verma, Uma Mittal, Anubha Mahajan, Sreenivas Chavali, Rubina Tabassum, Vijaya Banerjee, Jyotsna Batra, Rana Nagarkatti, Shilpy Sharma, Mamta Sharma, Rajshekhar Chatterjee, Jinny A. Paul, Pragya Srivastava, Rupali Chopra, Ankur Saxena, Charu Rajput, Prashant Kumar Singh, Mudit Vaid, Sumantra Das, Keya Chaudhuri, Rukhsana Chowdhury, Arijit Mukhopadhyay, Moulinath Acharya, Ashima Bhattacharyya, Atreyee Saha, Arindam Biswas, Moumita Chaki, Arnab Gupta, Saibal Mukherjee, Suddhasil Mookherjee, Ishita Chattopadhyay, Taraswi Banerjee, Meenakshi Chakravorty, Chaitali Misra, Gourish Monadal, Shiladitya Sengupta, Ishani Deb, Arunava Banerjee

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90 Scopus citations

Abstract

Indian population, comprising of more than a billion people, consists of 4693 communities with several thousands of endogamous groups, 325 functioning languages and 25 scripts. To address the questions related to ethnic diversity, migrations, founder populations, predisposition to complex disorders or pharmacogenomics, one needs to understand the diversity and relatedness at the genetic level in such a diverse population. In this backdrop, six constituent laboratories of the Council of Scientific and Industrial Research (CSIR), with funding from the Government of India, initiated a network program on predictive medicine using repeats and single nucleotide polymorphisms. The Indian Genome Variation (IGV) consortium aims to provide data on validated SNPs and repeats, both novel and reported, along with gene duplications, in over a thousand genes, in 15,000 individuals drawn from Indian subpopulations. These genes have been selected on the basis of their relevance as functional and positional candidates in many common diseases including genes relevant to pharmacogenomics. This is the first large-scale comprehensive study of the structure of the Indian population with wide-reaching implications. A comprehensive platform for Indian Genome Variation (IGV) data management, analysis and creation of IGVdb portal has also been developed. The samples are being collected following ethical guidelines of Indian Council of Medical Research (ICMR) and Department of Biotechnology (DBT), India. This paper reveals the structure of the IGV project highlighting its various aspects like genesis, objectives, strategies for selection of genes, identification of the Indian subpopulations, collection of samples and discovery and validation of genetic markers, data analysis and monitoring as well as the project's data release policy.

Original languageEnglish (US)
Pages (from-to)1-11
Number of pages11
JournalHuman Genetics
Volume118
Issue number1
DOIs
StatePublished - Nov 2005

Bibliographical note

Funding Information:
Abstract Indian population, comprising of more than a billion people, consists of 4693 communities with several thousands of endogamous groups, 325 functioning languages and 25 scripts. To address the questions related to ethnic diversity, migrations, founder populations, predisposition to complex disorders or pharmacoge-nomics, one needs to understand the diversity and relatedness at the genetic level in such a diverse population. In this backdrop, six constituent laboratories of the Council of Scientific and Industrial Research (CSIR), with funding from the Government of India, initiated a network program on predictive medicine using repeats and single nucleotide polymorphisms. The Indian Genome Variation (IGV) consortium aims to provide data on validated SNPs and repeats, both novel and reported, along with gene duplications, in over a thousand genes, in 15,000 individuals drawn from Indian subpopulations. These genes have been selected on the basis of their relevance as functional and positional candidates in many common diseases including genes relevant to pharmacogenomics. This is the first large-scale comprehensive study of the structure of the Indian population with wide-reaching implications. A comprehensive platform for Indian Genome Variation (IGV) data management, analysis and creation of IGVdb portal has also been developed. The samples are being collected following ethical guidelines of Indian Council of Medical Research (ICMR) and Department of Biotechnology (DBT), India. This paper reveals the structure of the IGV project highlighting its various aspects like genesis, objectives, strategies for selection of genes,

Funding Information:
The IGV initiative is a network program on predictive medicine that focuses on repeats and single nucleotide polymorphisms, initiated in 2003 and tenured for 5 years, by six constituent laboratories of the Council of Scientific and Industrial Research (CSIR), with funding from the Government of India. The laboratories include Institute of Genomics and Integrative Biology (IGIB), Delhi, Centre for Cellular and Molecular Biology (CCMB), Hyderabad, Indian Institute of Chemical Biology (IICB), Kolkata, Central Drug Research Institute (CDRI), Lucknow, Industrial Toxicological Research Centre (ITRC), Lucknow and Institute of Microbial technology (IMTECH), Chandigarh (Box 1). These laboratories are involved in studies related to asthma, diabetes, neuropsychiatric disorders, cancer, coronary artery disease, clot disorders, high altitude disorders, retinitis pigmentosa, predisposition to malaria as well as other infectious diseases and drug metabolism. The consortium deemed it pertinent to understand the inherent genetic variability of the subpopulations as a first step towards identifying susceptible biomarkers for any disease or understanding drug response in different subpopulations. This consortium, therefore, aims at providing information on variations in the subpopulations representing the entire country. These variations would be useful for investigators for specific candidate gene studies conducted in any part of the country.

Funding Information:
Apart from the CSIR laboratories, a key participant in the project is the Indian Statistical Institute (ISI), Kolkata, which will help us in the analysis of our data. The institute has an established expertise in human genetic variation data analysis (Tapadar et al. 2000; Basu et al. 2005). The project also involves active participation of the Anthropological Survey of India (Singh 2002) that has helped in the identification of the various Indian subpopulations. In addition to the institutional facility, the project also has collaborations with The Centre for Genomic Application (TCGA), established through the support of Department of Science and Technology (DST), CSIR with The Chatterjee Group (TCG) for high throughput sequencing and genotyping and Silic-oGene Informatics Private Limited along with Lab-Vantage, India for development of a comprehensive platform for IGV database management, analysis and portal development.

Funding Information:
Acknowledgements This work was supported by grants from the Council of Scientific and Industrial Research (CSIR), Government of India for the project ‘‘Predictive medicine using repeat and single nucleotide polymorphisms’’ (CMM0016).

Keywords

  • Ethnicity
  • Genetic structure
  • Indian genome variation database
  • Indian population
  • Repeat polymorphism
  • Single nucleotide polymorphism

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