The Trans-Omics for Precision Medicine (TOPMed) program aims to elucidate the genetic architecture and biology of heart, lung, blood, and sleep disorders to improve diagnosis, treatment, and prevention. This paper describes the TOPMed goals, design, and resources, including a variant browser, genotype imputation server, and genomic and phenotypic data available through dbGaP. The analysis of the first 53,831 TOPMed samples identified over 400 million single-nucleotide and insertion/deletion variants, with 97% having frequencies below 1% and 46% being singletons. These rare variants provide insights into mutational processes and human evolutionary history. The extensive catalog of genetic variation in TOPMed studies offers unique opportunities to explore the contributions of rare and noncoding sequence variants to phenotypic variation. The TOPMed imputation reference panel, available via an imputation server, enhances the power and reach of genome-wide association studies. The paper also discusses the distribution of genetic variation, insights into mutation processes, and the identification of putative loss-of-function variants. Additionally, it examines the distribution of genetic variation across the genome, the clustering of single nucleotide polymorphisms, and the discovery of retained non-reference ancestral sequences from unmapped reads. The TOPMed data provide a rich resource for developing and testing methods for surveying human variation, inferring demographic history, and exploring functional constraints on the genome.The Trans-Omics for Precision Medicine (TOPMed) program aims to elucidate the genetic architecture and biology of heart, lung, blood, and sleep disorders to improve diagnosis, treatment, and prevention. This paper describes the TOPMed goals, design, and resources, including a variant browser, genotype imputation server, and genomic and phenotypic data available through dbGaP. The analysis of the first 53,831 TOPMed samples identified over 400 million single-nucleotide and insertion/deletion variants, with 97% having frequencies below 1% and 46% being singletons. These rare variants provide insights into mutational processes and human evolutionary history. The extensive catalog of genetic variation in TOPMed studies offers unique opportunities to explore the contributions of rare and noncoding sequence variants to phenotypic variation. The TOPMed imputation reference panel, available via an imputation server, enhances the power and reach of genome-wide association studies. The paper also discusses the distribution of genetic variation, insights into mutation processes, and the identification of putative loss-of-function variants. Additionally, it examines the distribution of genetic variation across the genome, the clustering of single nucleotide polymorphisms, and the discovery of retained non-reference ancestral sequences from unmapped reads. The TOPMed data provide a rich resource for developing and testing methods for surveying human variation, inferring demographic history, and exploring functional constraints on the genome.