Building Bridges in Genomics: The Role of Large-scale Databases in Connecting Genetic Variation to Health Outcomes

Mapping Genetic Diversity with the GenomeIndia Project The GenomeIndia project is a landmark initiative that has made significant strides in mapping the genetic diversity of the Indian population. Bhattacharyya et al. detailed the efforts to sequence the genomes of 9772 Indian individuals from 83 diverse communities, 30 tribal and 53 nontribal population across India. This study addresses a critical gap in global genomic research, which has historically underrepresented Indian populations. The major objective was to create a collection of genomic variations (including common and rare variants) to gain insights on genetic diversity and pharmacogenetic inferences and create haplotype to facilitate imputation. The study resulted in the identification of 130 million autosomal variants with 65% of ultrarare variants (Minor allele frequency [MAF] ≥0.01).[1] GenomeIndia’s comprehensive catalogue provides unprecedented insights into the unique genetic architecture as well as genotype–phenotype associations of Indian populations. The population-specific linkage disequilibrium structure developed by this study enables training of superior polygenic score model applicable to Indian population. The author emphasizes that ancestry-matched genomic linkage disequilibrium patterns will help in designing genotype array for Indian population for precision medicine. This study also paves the way for advancements in precision medicine, enabling the development of targeted therapies and diagnostic tools tailored to the Indian genetic makeup. This could revolutionize health care in India, leading to improved disease management and prevention.[1] UK Biobank: A Unique Resource for Discovery and Translation Research on Genetics and Neurologic Disease Taylor et al. described a large-scale prospective study by UK Biobank that has become an invaluable resource for understanding of the genetic underpinnings of neurological diseases. The UK Biobank has recruited 503,000 participants aged 40–69 years between 2006 and 2010 and has collected data on lifestyle and medical history, physical and biomedical measurements, and long-term storage of biological samples for biochemical examinations and sequencing. Along with whole-exome and genome sequencing, proteomics and metabolomics analysis was conducted on large subset of the cohort.[2] National Center for Biotechnology Information Gene Expression Omnibus: Archive for Gene Expression and Epigenomics Datasets: A 23-year Update Gene Expression Omnibus (GEO) is an international public repository of gene expression and epigenomics datasets generated by next-generation sequencing and microarray. Clough et al. reported that GEO currently houses raw data and processed files of 6.5 million samples generated through 200,000 studies from 6000 different organisms. Data from different sequencing methods such as GRO-seq (nascent RNA identification), STARR-seq (enhancer identification), ATAT-seq (chromosome accessibility), Hi-C (chromosome contacts), CRAC-seq (RNA-protein interactions), and ChIRP-seq (RNA-chromatin interactions) have been deposited. Clough et al. highlighted application of GEO2R tool that helps the user to identify differentially expressed genes and assess dataset quality in interactive graphical plots.[3] GeniePool: Genomic Database with Corresponding Annotated Samples based on a Cloud Data Lake Architecture Hadar et al. developed a genomic database utilizing cloud data lake approach for storing large amount of data in a convenient way. GeniePool aggregates data primarily from the Sequence Read Archive (SRA). The SRA contains data from a wide variety of research studies, including many large cohort studies. The primary focus of GeniePool is on providing access to the genomic data (specifically VCF files) from these studies. The integration of CHM13-T2T, AlphaMissense, and gnomAD v4 significantly enhances the depth and breadth of information available within GeniePool, supporting more comprehensive and accurate variant analysis. GeniePool’s reliance on data from the SRA means that its coverage is contingent on the availability and quality of data within that repository. There may be biases in the data available, reflecting the research priorities. Hadar et al. developed GeniePool to enable genotype–phenotype correlation and deciphering multigenic disease research.[4] The Thai Reference Exome Variant Database The Thai reference exome (T-Rex) variant database represents a significant contribution to the field of human genomics, specifically addressing the underrepresentation of non-European populations in global genomic datasets. This resource provides a comprehensive catalogue of exonic variants within the Thai population, offering critical insights into population-specific genetic diversity and its implications for both fundamental research and clinical applications. Shotelersuk et al. described that in T-REx, 1092 unrelated Thai individuals are sequenced. The construction of T-Rex has enabled identification of substantial number of short variants and copy number variations, novel and specific to the Thai population. This database illuminated subpopulation-specific patterns in the prevalence of clinically relevant variants that are currently used for the development of more tailored and effective pharmacotherapies.[5] Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.