Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

By D. Taliun, Daniel N Harris, M. D. Kessler, Jedidiah Carlson, Zachary A. Szpiech, Raul Torres, S. G. Taliun, A. Corvelo, Stephanie M. Gogarten, Hyun Min Kang and 167 more. Nature, 2019

1,941 citations recorded by the source corpus.

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%. The goals, resources and design of the NHLBI Trans-Omics for Precision Medicine (TOPMed) programme are described, and analyses of rare variants detected in the first 53,831 samples provide insights into mutational processes and recent human evolutionary history.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/f0ff9b9f6204c5ad69e89ecc95e54c64b4aa3a25

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Citations in the corpus

High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios (2021, neutral): “, 2020), Trans-Omics for Precision Medicine (TOPMed, ~180,000 samples) (Taliun et al., 2021), or the UK Biobank (UKBB, goal to sequence 500,000 samples by 2023) to name a few.”
Variant interpretation using population databases: lessons from gnomAD (2021, background): “Other large databases include NHLBI's Trans ‐ Omics for Precision Medicine (TOPMed) ‐ BRAVO and the Geisinger Healthcare System DiscovEHR dataset (Dewey et al., 2016; Taliun et al., 2021).”
Genome-wide association studies in ancestrally diverse populations: opportunities, methods, pitfalls, and recommendations. (2019, background): “Despite these issues, current reference panels yield high quality imputation results for most common variants in most major ancestry groups (Taliun et al., 2019).”
Missense variants causing Wiedemann-Steiner syndrome preferentially occur in the KMT2A-CXXC domain and are accurately classified using AlphaFold2 (2022, neutral): “1) [10] and the Trans-Omics for 213 Precision Medicine database (TOPmed) [11].”
Fast two-stage phasing of large-scale sequence data. (2021, methodology): “32 Both methods had similar accuracy on both types of data and similar computation time when phasing SNP array data.”
Multimodal biomedical AI (2022, background): “TOPMed collects WGS with the aim to integrate this genetic information with other omics data 89 .”
The power of genetic diversity in genome-wide association studies of lipids (2021, background): “Further gains in the depth and number of sequenced individuals of diverse ances-tries 41,42 may also improve the discovery of new variants and loci in diverse cohorts, in particular variants that are absent at present from arrays and imputation reference panels.”