ArticleGenome medicine2019
Prioritization of genes driving congenital phenotypes of patients with de novo genomic structural variants.
Article in Genome medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- Article
- Exploring the size limits of Bionano optical genome mapping to resolve alternative structures of linked interspersed chromosomal duplications.Genome medicine · 2025Article
- Inter-chromosomal insertions at Xq27.1 associated with retinal dystrophy induce dysregulation of LINC00632 and CDR1as/ciRS-7.American journal of human genetics · 2025Article
- A distant global control region is essential for normal expression of anterior HOXA genes during mouse and human craniofacial development.Nature communications · 2024Article
- Long read sequencing on its way to the routine diagnostics of genetic diseases.Frontiers in genetics · 2024Review
- PhenoSV: interpretable phenotype-aware model for the prioritization of genes affected by structural variants.Nature communications · 2023Article
- POSTRE: a tool to predict the pathological effects of human structural variants.Nucleic acids research · 2023Article
- In it for the long run: perspectives on exploiting long-read sequencing in livestock for population scale studies of structural variants.Genetics, selection, evolution : GSE · 2023Review
- PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform.Nucleic acids research · 2023Article
- Structural Variation at a Disease Mutation Hotspot: Strategies to Investigate Gene Regulation and the 3D Genome.Frontiers in genetics · 2022Review
- Optimizing Nanopore sequencing-based detection of structural variants enables individualized circulating tumor DNA-based disease monitoring in cancer patients.Genome medicine · 2021Article
- Long-read genome sequencing for the molecular diagnosis of neurodevelopmental disorders.HGG advances · 2021Article
- Chromosomes in the genomic age. Preserving cytogenomic competence of diagnostic genome laboratories.European journal of human genetics : EJHG · 2021Review
- Interpreting the impact of noncoding structural variation in neurodevelopmental disorders.Genetics in medicine : official journal of the American College of Medical Genetics · 2021Review
- Rare or Overlooked? Structural Disruption of Regulatory Domains in Human Neurocristopathies.Frontiers in genetics · 2020Review
- Keeping up with the genomes: scaling genomic variant interpretation.Genome medicine · 2019Article
- Prioritization of genes driving congenital phenotypes of patients with de novo genomic structural variants.Genome medicine · 2019Article
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15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGenomic structural variants (SVs) can affect many genes and regulatory elements. Therefore, the molecular mechanisms driving the phenotypes of patients carrying de novo SVs are frequently unknown.
methodsWe applied a combination of systematic experimental and bioinformatic methods to improve the molecular diagnosis of 39 patients with multiple congenital abnormalities and/or intellectual disability harboring apparent de novo SVs, most with an inconclusive diagnosis after regular genetic testing.
resultsIn 7 of these cases (18%), whole-genome sequencing analysis revealed disease-relevant complexities of the SVs missed in routine microarray-based analyses. We developed a computational tool to predict the effects on genes directly affected by SVs and on genes indirectly affected likely due to the changes in chromatin organization and impact on regulatory mechanisms. By combining these functional predictions with extensive phenotype information, candidate driver genes were identified in 16/39 (41%) patients. In 8 cases, evidence was found for the involvement of multiple candidate drivers contributing to different parts of the phenotypes. Subsequently, we applied this computational method to two cohorts containing a total of 379 patients with previously detected and classified de novo SVs and identified candidate driver genes in 189 cases (50%), including 40 cases whose SVs were previously not classified as pathogenic. Pathogenic position effects were predicted in 28% of all studied cases with balanced SVs and in 11% of the cases with copy number variants.
conclusionsThese results demonstrate an integrated computational and experimental approach to predict driver genes based on analyses of WGS data with phenotype association and chromatin organization datasets. These analyses nominate new pathogenic loci and have strong potential to improve the molecular diagnosis of patients with de novo SVs.
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