This article presents a comprehensive map of copy number variations (CNVs) identified through population-scale genome sequencing. The study analyzed 185 human genomes, integrating data from various SV discovery methods and extensive experimental validations. The resulting map includes 22,025 deletions and 6,000 additional SVs, such as insertions and tandem duplications. Most SVs were mapped at nucleotide resolution, enabling analysis of their origin and functional impact. The study found that high-frequency deletions were less likely to disrupt genes, and observed differences in SV size spectra based on formation mechanisms. A map of SV hotspots was constructed, showing common mechanisms for SV formation. The study also analyzed the population genetic properties of deletions, generating genotypes for 13,826 autosomal deletions. These genotypes showed high concordance with existing data, and allele frequency analyses revealed common polymorphisms across populations. The study found that gene deletions were more likely to be at low frequency, consistent with purifying selection. Deletions in genomic regions accessible to short read sequencing showed extensive linkage disequilibrium with SNPs, suggesting they may be identifiable through tagging SNPs in future studies. The study also analyzed SV formation mechanisms, distinguishing between non-allelic homologous recombination (NAHR), non-homologous (NH), variable number of tandem repeats (VNTR), and mobile element insertions (MEIs). The analysis revealed that NH was the dominant deletion mechanism, while MEI was the dominant insertion mechanism. SV hotspots were identified, showing clustering of SVs formed by common mechanisms. The study's findings contribute to understanding the role of structural variation in human genetics and disease. The SV map serves as a resource for sequencing-based association studies, and the study highlights the importance of population-scale sequencing in identifying and characterizing SVs. The study also discusses the limitations of current SV discovery methods and the need for further research to improve their accuracy and resolution. Overall, the study provides a detailed understanding of SVs and their impact on human genetics and disease.This article presents a comprehensive map of copy number variations (CNVs) identified through population-scale genome sequencing. The study analyzed 185 human genomes, integrating data from various SV discovery methods and extensive experimental validations. The resulting map includes 22,025 deletions and 6,000 additional SVs, such as insertions and tandem duplications. Most SVs were mapped at nucleotide resolution, enabling analysis of their origin and functional impact. The study found that high-frequency deletions were less likely to disrupt genes, and observed differences in SV size spectra based on formation mechanisms. A map of SV hotspots was constructed, showing common mechanisms for SV formation. The study also analyzed the population genetic properties of deletions, generating genotypes for 13,826 autosomal deletions. These genotypes showed high concordance with existing data, and allele frequency analyses revealed common polymorphisms across populations. The study found that gene deletions were more likely to be at low frequency, consistent with purifying selection. Deletions in genomic regions accessible to short read sequencing showed extensive linkage disequilibrium with SNPs, suggesting they may be identifiable through tagging SNPs in future studies. The study also analyzed SV formation mechanisms, distinguishing between non-allelic homologous recombination (NAHR), non-homologous (NH), variable number of tandem repeats (VNTR), and mobile element insertions (MEIs). The analysis revealed that NH was the dominant deletion mechanism, while MEI was the dominant insertion mechanism. SV hotspots were identified, showing clustering of SVs formed by common mechanisms. The study's findings contribute to understanding the role of structural variation in human genetics and disease. The SV map serves as a resource for sequencing-based association studies, and the study highlights the importance of population-scale sequencing in identifying and characterizing SVs. The study also discusses the limitations of current SV discovery methods and the need for further research to improve their accuracy and resolution. Overall, the study provides a detailed understanding of SVs and their impact on human genetics and disease.