Structural rearrangements in the human genome drive genetic diversity and play a critical role in health and disease, yet their complexity remains poorly understood. Complex genomic rearrangements (CGRs) are fascinating entities observed in healthy individuals, rare diseases, and cancer genomes. However, CGRs are among the most challenging types of structural variation to detect and interpret, leaving their molecular features, prevalence, and genomic impact poorly understood. Although similar patterns are observed in cancer and non-cancer cells, suggesting shared mechanisms, this has not been systematically investigated. Our recent work has demonstrated that: (i) CGRs are often more complex than they initially appear, (ii) combining classical techniques with genomic approaches provides detailed insights into the genomic architecture of CGRs, and (iii) long-read sequencing, combined with the Telomere-to-Telomere (T2T) reference, enables analysis of previously unmappable regions. Building on this work, we aim to uncover the prevalence of CGRs, investigate their formation mechanisms, and assess their impact across general populations, rare diseases patients, and cancer. We will analyze CGR patterns in in-house data (>22,000 rare disease and >1,000 cancer genomes), the Swedish Genome of Europe dataset (1,000 individuals), and additional public and collaborator datasets. Using T2T, long-read sequencing, and optical mapping, we will resolve complex chromosome structures and study chromatin interactions and the transcriptome to understand how CGRs affect genes. This proposal takes advantage of recent improvements of the human reference genome, large clinical and population datasets, and advanced genomic technologies to transform our understanding of CGR formation, genome plasticity, and their role in disease.