Resolving the dark matter of ABCA4 for 1054 Stargardt disease probands through integrated genomics and transcriptomics
Publication year
2020Author(s)
Source
Genetics in Medicine, 22, 7, (2020), pp. 1235-1246ISSN
Publication type
Article / Letter to editor

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Organization
Human Genetics
Ophthalmology
Internal Medicine
Journal title
Genetics in Medicine
Volume
vol. 22
Issue
iss. 7
Page start
p. 1235
Page end
p. 1246
Subject
Radboudumc 12: Sensory disorders DCMN: Donders Center for Medical Neuroscience; Radboudumc 4: lnfectious Diseases and Global Health RIMLS: Radboud Institute for Molecular Life Sciences; Radboudumc 6: Metabolic Disorders RIMLS: Radboud Institute for Molecular Life SciencesAbstract
PURPOSE: Missing heritability in human diseases represents a major challenge, and this is particularly true for ABCA4-associated Stargardt disease (STGD1). We aimed to elucidate the genomic and transcriptomic variation in 1054 unsolved STGD and STGD-like probands. METHODS: Sequencing of the complete 128-kb ABCA4 gene was performed using single-molecule molecular inversion probes (smMIPs), based on a semiautomated and cost-effective method. Structural variants (SVs) were identified using relative read coverage analyses and putative splice defects were studied using in vitro assays. RESULTS: In 448 biallelic probands 14 known and 13 novel deep-intronic variants were found, resulting in pseudoexon (PE) insertions or exon elongations in 105 alleles. Intriguingly, intron 13 variants c.1938-621G>A and c.1938-514G>A resulted in dual PE insertions consisting of the same upstream, but different downstream PEs. The intron 44 variant c.6148-84A>T resulted in two PE insertions and flanking exon deletions. Eleven distinct large deletions were found, two of which contained small inverted segments. Uniparental isodisomy of chromosome 1 was identified in one proband. CONCLUSION: Deep sequencing of ABCA4 and midigene-based splice assays allowed the identification of SVs and causal deep-intronic variants in 25% of biallelic STGD1 cases, which represents a model study that can be applied to other inherited diseases.
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- Academic publications [187560]
- Faculty of Medical Sciences [74221]
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