The 1000 Genomes Project Consortium has generated a comprehensive map of human genetic variation by sequencing the genomes of 1,092 individuals from 14 populations. This resource integrates data from low-coverage whole-genome sequencing, targeted exome sequencing, and dense SNP genotype data to identify 38 million SNPs, 1.4 million bi-allelic indels, and over 14,000 larger deletions. The study reveals that rare and common variants vary significantly across populations, with low-frequency variants showing substantial geographic differentiation due to purifying selection. Evolutionary conservation and coding consequences are key factors in determining the strength of purifying selection, while rare-variant load varies across biological pathways. The resource captures up to 98% of accessible SNPs at a 1% frequency in related populations, enabling analysis of common and low-frequency variants in diverse populations. The study highlights the importance of low-frequency variants in understanding disease and provides insights into the functional spectrum of human variation. It shows that rare variants are enriched for potentially functional mutations and are influenced by population history. The project also demonstrates the utility of the data in medical genetics, including imputing genotypes in genome-wide association studies (GWAS) and identifying rare variants associated with disease. The data are used to fine-map association signals and detect new associations, with the potential to improve the detection of pathological variants by integrating regulatory function data. The study underscores the role of purifying selection in shaping genetic variation and the importance of considering local genetic backgrounds when interpreting rare variants. It also emphasizes the need for continued sequencing of diverse populations to characterize the full spectrum of human genetic variation and support disease studies. The project's findings contribute to the understanding of genetic factors underlying disease and provide a valuable resource for genetic research.The 1000 Genomes Project Consortium has generated a comprehensive map of human genetic variation by sequencing the genomes of 1,092 individuals from 14 populations. This resource integrates data from low-coverage whole-genome sequencing, targeted exome sequencing, and dense SNP genotype data to identify 38 million SNPs, 1.4 million bi-allelic indels, and over 14,000 larger deletions. The study reveals that rare and common variants vary significantly across populations, with low-frequency variants showing substantial geographic differentiation due to purifying selection. Evolutionary conservation and coding consequences are key factors in determining the strength of purifying selection, while rare-variant load varies across biological pathways. The resource captures up to 98% of accessible SNPs at a 1% frequency in related populations, enabling analysis of common and low-frequency variants in diverse populations. The study highlights the importance of low-frequency variants in understanding disease and provides insights into the functional spectrum of human variation. It shows that rare variants are enriched for potentially functional mutations and are influenced by population history. The project also demonstrates the utility of the data in medical genetics, including imputing genotypes in genome-wide association studies (GWAS) and identifying rare variants associated with disease. The data are used to fine-map association signals and detect new associations, with the potential to improve the detection of pathological variants by integrating regulatory function data. The study underscores the role of purifying selection in shaping genetic variation and the importance of considering local genetic backgrounds when interpreting rare variants. It also emphasizes the need for continued sequencing of diverse populations to characterize the full spectrum of human genetic variation and support disease studies. The project's findings contribute to the understanding of genetic factors underlying disease and provide a valuable resource for genetic research.