Complex de novo structural variants are an underestimated cause of rare disorders

Complex de novo structural variants (dnSVs) are crucial genetic factors in rare disorders, yet their prevalence and characteristics in rare disorders remain poorly understood. Here, we conduct a comprehensive analysis of whole-genome sequencing data of 12,568 families, including 13,698 offspring with rare diseases, obtained as part of the UK 100,000 Genomes Project. We identify 1,870 dnSVs, constituting the largest dnSV dataset reported to date. Complex dnSVs (n = 158; 8.4%) emerge as the third most common type of SV, following simple deletions and duplications. We classify 65% of these complex dnSVs into 11 subtypes. Among probands with dnSVs (n = 1,696), 9% exhibit exon-disrupting pathogenic dnSVs associated with the probands' phenotype. Notably, 12% of exon-disrupting pathogenic dnSVs and 22% of de novo deletions or duplications previously identified by array-based or whole-exome sequencing methods are found to be complex dnSVs. We also find distinct genomic properties of de novo deletions depending on the parent of origin. This study highlights the importance of complex dnSVs in the cause of rare disorders and demonstrates the necessity of specific genomic analysis to avoid overlooking these variants.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2025-11-03
DOI
https://doi.org/10.1038/s41467-025-64722-2
Citations
1
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
1.82

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Complex de novo structural variants are an underestimated cause of rare disorders

Hyunchul Jung, Joseph Christopher, Matthew D. C. Neville, Susan Walker et al.
1 citations
Nature Communications
Genomics and Rare Diseases
1.82
article

Complex de novo structural variants are an underestimated cause of rare disorders

Hyunchul Jung, Joseph Christopher, Matthew D. C. Neville, Susan Walker, Aylwyn Scally, Peter J. Campbell, Raheleh Rahbari, Tsun-Po Yang, Petr Danecek, Helen V. Firth, Matthew E. Hurles, Isidro Cortés‐Ciriano, O. Isaac Garcia-Salinas
article en
1 citations

Abstract

Complex de novo structural variants (dnSVs) are crucial genetic factors in rare disorders, yet their prevalence and characteristics in rare disorders remain poorly understood. Here, we conduct a comprehensive analysis of whole-genome sequencing data of 12,568 families, including 13,698 offspring with rare diseases, obtained as part of the UK 100,000 Genomes Project. We identify 1,870 dnSVs, constituting the largest dnSV dataset reported to date. Complex dnSVs (n = 158; 8.4%) emerge as the third most common type of SV, following simple deletions and duplications. We classify 65% of these complex dnSVs into 11 subtypes. Among probands with dnSVs (n = 1,696), 9% exhibit exon-disrupting pathogenic dnSVs associated with the probands' phenotype. Notably, 12% of exon-disrupting pathogenic dnSVs and 22% of de novo deletions or duplications previously identified by array-based or whole-exome sequencing methods are found to be complex dnSVs. We also find distinct genomic properties of de novo deletions depending on the parent of origin. This study highlights the importance of complex dnSVs in the cause of rare disorders and demonstrates the necessity of specific genomic analysis to avoid overlooking these variants.

Nature CommunicationsVol. 16(1)
European Bioinformatics Institute (GB), University of Cambridge (GB), Cambridge University Hospitals NHS Foundation Trust (GB), Wellcome Sanger Institute (GB), Genomics England (GB)
Wellcome Trust, Cancer Research UK, National Institute for Health and Care Research, Department of Health and Social Care, Research Councils UK, Medical Research Council
Openalex Percentile: Top 11%
Genomics and Rare Diseases
1.82
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.