Genome India Project: 10,000 Indian Genomes, the Findings and Their Uses

Genome India Project: India's National Catalogue of Genetic Variation

GenomeIndia Launch, Funding and the 10,000-Genome Milestone

The Centre for Brain Research at the Indian Institute of Science (IISc), Bengaluru, leads the project. More than 20 research institutions take part, among them IISc, the Indian Institutes of Technology (IITs), laboratories of the Council of Scientific and Industrial Research (CSIR) and institutes of the Biotechnology Research and Innovation Council (BRIC).

The first phase set out to sequence at least 10,000 Indian genomes. The whole genomes of 10,074 healthy individuals from 83 populations, sampled at 99 sites, have been sequenced. On 9 January 2025, at the Genome India Data Conclave in New Delhi, the data set was opened to researchers in India and abroad through the Indian Biological Data Centre (IBDC), and the government announced a future target of sequencing 10 million genomes. A second phase is to collect samples from patients with three kinds of disease, namely cardiovascular disease, mental illness and cancer.

Sampling India's Diversity: Rural, Urban and Tribal Populations

A reference for India has to include all of India, so the samples were spread on purpose. About 36.7 per cent came from rural, 32.2 per cent from urban and 31.1 per cent from tribal populations, with sampling spread across linguistic, social and regional groups throughout the country.

Reaching these groups was the hardest part of the work, and the teams had to overcome five obstacles:

• Remote places: Tribal regions were hard to reach, so nearby logistics hubs were set up to move samples.
• Trust: Local leaders and community representatives took part in the meetings with rural and tribal people.
• Awareness: Outreach programmes explained the purpose of genetic research and assured people that their data would stay confidential.
• Bias: Urban people were easier to reach, so campaigns kept each group in its proper proportion.
• Laboratories: Partnerships with local health institutions and advance preparation of laboratories handled the larger number of samples.

What Is Genome Sequencing: Variants and the Human Genome Project

Whole-Genome Sequencing and the Catalogue of Variation

The genome is the full set of DNA in a cell, and the human genome has about 3 × 10⁹ base pairs. Less than 2 per cent of the genome codes for proteins. Almost all of it, 99.9 per cent of the bases, is the same in every person; the 0.1 per cent that differs makes one person's biology unlike another's, including about 1.4 million places where a single base differs, the single nucleotide polymorphisms (SNPs).

Whole-genome sequencing reads nearly the entire sequence of a person's DNA. A narrow genetic test reads only chosen positions, so it finds only the variants it looks for; reading the whole genome also finds rare variants nobody knew to look for.

From thousands of sequences, a project builds a catalogue of variation, a record of which variants occur in a population and how common each one is. Later studies use it to ask whether a variant found in a patient is common and harmless or rare and linked to disease.

Human Genome Project and Other National Genome Programmes

The Human Genome Project (HGP), launched in 1990, set out to sequence the 3 billion base pairs of human DNA and identify its 20,000 to 25,000 genes. It ran for 13 years under the US Department of Energy and the National Institutes of Health, with the Wellcome Trust of the United Kingdom as a major partner and contributions from Japan, France, Germany, China and others, and it was declared complete in April 2003.

• Scale: At the starting estimate of US $3 per base pair, sequencing would cost about US $9 billion, and printing one cell's sequence would fill some 3,300 books of 1,000 pages each, which is why it was called a mega project.
• Bioinformatics: Storing and analysing the data needed high-speed computers, and this need gave rise to bioinformatics.
• Ethical, legal and social issues: The project also set out to address the ethical, legal and social questions that its findings might raise.

Other countries have since built national programmes. The United Kingdom's 100,000 Genomes Project (2013 to 2018) sequenced whole genomes of National Health Service patients, focusing on rare diseases and some common cancers, with consent to link each genome to the patient's health records. GenomeIndia's distinction is its spread: 83 populations sampled at 99 sites, nearly a third of the samples from tribal groups.

What the GenomeIndia Data Show About Indian Populations

Genetic Variants Unique to Indians, Endogamy and Founder Effects

The project has already identified more than 40 million genetic variants unique to the Indian population, and it documented extraordinary genetic diversity among the 83 sampled groups. India's populations have been shaped by thousands of years of migration, cultural diversity and marriage within communities, so geneticists stress that India cannot be treated as one genetic block and that distinct endogamous and tribal groups must be studied, not only a few urban groups.

Two terms explain why. Endogamy is the practice of marrying only within one's own social group, caste or community. The founder effect is the loss of genetic variation when a new population begins from a very small number of people. When a group founded by a few people also marries within itself for generations, a harmful variant that one founder happened to carry can stay common, so a disease rare elsewhere becomes frequent in that community; many harmful variants found in Indian groups are seen nowhere else.

Disease patterns follow the same logic. Sickle cell anaemia is a major problem in tribal society, yet the problem found in one region may be absent in another, which is why a national study of genetic differences matters for health policy and planning.

Why European Genomic Data Fail Indian Patients

Most genetic research has studied people of European descent. Between 2005 and 2025, more than 86 per cent of the participants in genome-wide association studies were of European ancestry and less than 1 per cent were South Asian.

A genome-wide association study (GWAS) compares millions of common variants across large groups of people with and without a condition, to see which variants are more frequent in one group. For common diseases the risk is polygenic, the combined effect of thousands of variants with environment and chance, so researchers add these small effects into a single polygenic risk score.

Such scores are less accurate in other populations, because the frequencies of variants differ by ancestry. South Asians face higher rates of type 2 diabetes, heart disease and asthma than people of European ancestry, and the number of people with diabetes in India is projected to reach 12.5 crore by 2045, so tools that fit Indians poorly fail the people who need them most. Even a single Indian ancestry label is too broad, since GenomeIndia alone sampled 83 distinct groups. As of August 2026, polygenic risk scores for schizophrenia, bipolar disorder and depression were not yet accurate enough for routine clinical prediction.

Uses of GenomeIndia: Precision Medicine and Genetic Medicine

Precision Medicine, Drug Response and Indian Diagnostics

The catalogue is reference data for later research. The Department of Biotechnology funds translational research on it in four main directions:

• Indigenous chips and diagnostics: Genomic chips tailored to the Indian population, which make genetic studies more precise, and diagnostics and therapeutics built on Indian data.
• Genetic disorders: Finding the variants behind inherited diseases, including those that cluster in endogamous and tribal groups, to counter genetic and hereditary diseases.
• Drug response: Pharmacogenomics, the study of the role of the genome in drug response, aims to optimise drug therapy for a patient's genotype, identify the best dose and move away from a one-dose-fits-all approach.
• New products: Research on mRNA-based vaccines, protein manufacturing and treatments for genetic disorders.

Precision medicine brings these uses together. It fits prevention and treatment to a person's own genetic make-up rather than to an average patient. For families in a community with a known inherited disease, tests built on Indian data can guide screening and counselling.

Genetic Medicine and Gene Therapy

Genetic medicine goes one step further and treats the gene itself. Gene therapy is a set of methods for correcting a gene defect by inserting genes into a person's cells and tissues. A normal gene is delivered into the person's cells to take over from, and compensate for, the faulty one. The most common form delivers DNA carrying a working gene to replace a mutated one; it does not rewrite the whole genome.

The first clinical gene therapy was given in 1990 to a four-year-old girl with adenosine deaminase (ADA) deficiency, an immune disorder caused by the deletion of one gene. In this therapy the patient's lymphocytes are grown outside the body, given a working ADA gene through a retroviral vector and returned; because these cells are not immortal, the infusions have to be repeated.

Two kinds of carrier take the working gene into cells:

• Viral vectors: Engineered viruses carry the gene into cells; Zolgensma, for spinal muscular atrophy, uses an adeno-associated virus.
• Lipid nanoparticles: Tiny fat-based carriers, first approved for drug delivery in 2018 and used to carry the fragile mRNA of some COVID‑19 vaccines.

Genomic Data Governance, Ethics and India's Bioeconomy

Biotech-PRIDE Guidelines, FeED Protocols and Data Privacy

Genomic data are deeply personal, so access is governed rather than free. The data are shared under the Biotech-PRIDE Guidelines of 2021, where PRIDE stands for Promotion of Research and Innovation through Data Exchange, and under the Framework for Exchange of Data (FeED) protocols launched with the release, which govern how researchers gain access to the data and use them.

• Anonymised data: The released data are anonymised to protect individual identities, and researchers must follow the access rules.
• Open questions: Fair sharing of benefits with the communities that gave samples, data security, and keeping commercial enthusiasm from running ahead of the science.

The project is also part of a wider government push on biotechnology. India's bioeconomy was valued at over US $130 billion in 2024, up from US $10 billion in 2014, with a target of US $300 billion by 2030; biotech start-ups rose from 50 in 2014 to over 8,500 in 2023.