Why in News?

The preliminary findings of the Genome India project, which aimed to sequence the whole genomes of 10,000 healthy and unrelated Indians from 83 population groups, were published in Nature Genetics.

After excluding two population groups, the study analyzed data from 9,772 individuals, including 4,696 men and 5,076 women.

What’s in Today’s Article?

• Launch of Genome India project
• Sampling Strategy
• Key Genetic Findings
• Significance of the Study

Launch of Genome India project

• It was launched in January 2020, with funding from the Department of Biotechnology.
• Scope and Sample Collection
  • The study aimed to collect blood samples and phenotype data (e.g., weight, height, hip & waist circumference, blood pressure).
  • Participants represented 83 population groups: 30 tribal; 53 non-tribal.
  • These groups were spread across India.
• Genome Sequencing
  • Whole genome sequencing was performed on DNA samples from 10,074 individuals.
  • After excluding two populations, data from 9,772 individuals was analyzed.
• Collaborating Institutions
  • The project is a collaborative effort involving 20 institutions. Genome sequencing was carried out by:
    • Centre for Brain Research, IISc Bengaluru
    • Centre for Cellular and Molecular Biology, Hyderabad
    • Institute of Genomics & Integrative Biology, Delhi
    • National Institute of Biomedical Genomics, Kolkata
    • Gujarat Biotechnology Research Centre, Gandhinagar

Sampling Strategy

• Samples were collected from 83 population groups across 100+ distinct geographical locations.
• Median samples collected:159 individuals per non-tribal group; 75 individuals per tribal group.
• Participants were unrelated to ensure accurate estimation of mutation frequencies.
• Parent-Child Pairs
  • 3 to 6 parent-child pairs were included in each group.
  • Purpose: To detect de novo mutations (mutations present in a child but absent in parents).
• Tribal and Non-Tribal Genome Coverage
  • Tribal groups sequenced:
    • Tibeto-Burman tribe
    • Indo-European tribe
    • Dravidian tribe
    • Austro-Asiatic tribe
    • Continentally admixed outgroup
  • Non-tribal groups sequenced:
    • Tibeto-Burman non-tribe
    • Indo-European non-tribe
    • Dravidian non-tribe
  • Linguistic Representation
    • Sampling aligned with India’s major language families, which correlate with genetic diversity:
      • Indo-European
      • Dravidian
      • Austro-Asiatic
      • Tibeto-Burman
  • Excluded Populations
    • Four ancient Andamanese populations (dating back ~65,000 years) &
    • Two relatively modern populations (from ~5,500 years ago)

Key Genetic Findings

• 180 million mutations identified in total:
  • 130 million in autosomes (non-sex chromosomes)
  • 50 million in sex chromosomes (X and Y)
• The large number is expected, given the 3 billion DNA base pairs and sequencing of 9,772 individuals from 83 distinct endogamous groups.
• 98% of the human genome consists of non-coding regions, and most variants are likely found here.
  • Non-coding region mutations, especially evolutionarily conserved polymorphisms, help in tracing human evolutionary history.
  • This is especially important in India, where many contemporary populations stem from a few founding groups and have remained genetically distinct due to endogamy.
• Impact of Endogamy
  • All 83 groups studied practice endogamy, though to varying degrees.
  • Long-term endogamy has led to population-specific unique mutations, including disease-causing genetic variants with amplified frequencies.
  • India’s genetic diversity has been underrepresented in global (largely Eurocentric) genome studies.
  • This project addresses that gap by capturing the genetic landscape of one of the most diverse populations globally.
• Medical Implications
  • The findings will encourage studies on genetic links to diseases specific to Indian populations.
  • It promotes precision medicine, allowing for personalized treatment strategies tailored to Indian genetic make-up.
  • Enables development of affordable diagnostic tools for early disease detection, prevention, and management in India.
  • Findings can support targeted public health policies to address population-specific genetic disorders.