Schloissnig, SiegfriedSotelo-Fonseca, Jesus EmilianoMoreira Pinhal, RicardoCáceres Aguilar, MarioRodríguez Martín, BernardoKorbel, Jan O.2025-10-092025-10-092025Schloissnig S, Pani S, Ebler J, Hain C, Tsapalou V, Söylev A, et al. Structural variation in 1,019 diverse humans based on long-read sequencing. Nature. 2025 Aug;644(8076):442-52. DOI: 10.1038/s41586-025-09290-70028-0836http://hdl.handle.net/10230/71442Genomic structural variants (SVs) contribute substantially to genetic diversity and human diseases1-4, yet remain under-characterized in population-scale cohorts5. Here we conducted long-read sequencing6 in 1,019 humans to construct an intermediate-coverage resource covering 26 populations from the 1000 Genomes Project. Integrating linear and graph genome-based analyses, we uncover over 100,000 sequence-resolved biallelic SVs and we genotype 300,000 multiallelic variable number of tandem repeats7, advancing SV characterization over short-read-based population-scale surveys3,4. We characterize deletions, duplications, insertions and inversions in distinct populations. Long interspersed nuclear element-1 (L1) and SINE-VNTR-Alu (SVA) retrotransposition activities mediate the transduction8,9 of unique sequence stretches in 5' or 3', depending on source mobile element class and locus. SV breakpoint analyses point to a spectrum of homology-mediated processes contributing to SV formation and recurrent deletion events. Our open-access resource underscores the value of long-read sequencing in advancing SV characterization and enables guiding variant prioritization in patient genomes.application/pdfeng© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.info:eu-repo/semantics/articlehttp://dx.doi.org/10.1038/s41586-025-09290-7Genome informaticsGenomicsMedical geneticsStructural variationinfo:eu-repo/semantics/openAccess