156 349

Cited 3 times in

Noncanonical Splice Site and Deep Intronic FRMD7 Variants Activate Cryptic Exons in X-linked Infantile Nystagmus

DC Field Value Language
dc.contributor.author변석호-
dc.contributor.author신새암-
dc.contributor.author원동주-
dc.contributor.author이승태-
dc.contributor.author이준원-
dc.contributor.author최종락-
dc.contributor.author한진우-
dc.date.accessioned2022-08-23T00:29:10Z-
dc.date.available2022-08-23T00:29:10Z-
dc.date.issued2022-06-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/189456-
dc.description.abstractPurpose: We aim to report noncoding pathogenic variants in patients with FRMD7-related infantile nystagmus (FIN). Methods: Genome sequencing (n = 2 families) and reanalysis of targeted panel next generation sequencing (n = 2 families) was performed in genetically unsolved cases of suspected FIN. Previous sequence analysis showed no pathogenic coding variants in genes associated with infantile nystagmus. SpliceAI, SpliceRover, and Alamut consensus programs were used to annotate noncoding variants. Minigene splicing assay was performed to confirm aberrant splicing. In silico analysis of exonic splicing enhancer and silencer was also performed. Results: FRMD7 intronic variants were identified based on genome sequencing and targeted next-generation sequencing analysis. These included c.285-12A>G (pedigree 1), c.284+63T>A (pedigrees 2 and 3), and c. 383-1368A>G (pedigree 4). All variants were absent in gnomAD, and the both c.285-12A>G and c.284+63T>A variants were predicted to enhance new splicing acceptor gains with SpliceAI, SpliceRover, and Alamut consensus approaches. However, the c.383-1368 A>G variant only had a significant impact score on the SpliceRover program. The c.383-1368A>G variant was predicted to promote pseudoexon inclusion by binding of exonic splicing enhancer. Aberrant exonizations were validated through minigene constructs, and all variants were segregated in the families. Conclusions: Deep learning-based annotation of noncoding variants facilitates the discovery of hidden genetic variations in patients with FIN. This study provides evidence of effectiveness of combined deep learning-based splicing tools to identify hidden pathogenic variants in previously unsolved patients with infantile nystagmus. Translational relevance: These results demonstrate robust analysis using two deep learning splicing predictions and in vitro functional study can lead to finding hidden genetic variations in unsolved patients.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherAssociation for Research in Vision and Ophthalmology-
dc.relation.isPartOfTRANSLATIONAL VISION SCIENCE & TECHNOLOGY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHCytoskeletal Proteins* / genetics-
dc.subject.MESHExons-
dc.subject.MESHGenetic Diseases, X-Linked*-
dc.subject.MESHHumans-
dc.subject.MESHIntrons-
dc.subject.MESHMembrane Proteins* / genetics-
dc.subject.MESHMutation-
dc.subject.MESHNystagmus, Congenital* / genetics-
dc.subject.MESHRNA Splicing / genetics-
dc.titleNoncanonical Splice Site and Deep Intronic FRMD7 Variants Activate Cryptic Exons in X-linked Infantile Nystagmus-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Ophthalmology (안과학교실)-
dc.contributor.googleauthorJunwon Lee-
dc.contributor.googleauthorHan Jeong-
dc.contributor.googleauthorDongju Won-
dc.contributor.googleauthorSaeam Shin-
dc.contributor.googleauthorSeung-Tae Lee-
dc.contributor.googleauthorJong Rak Choi-
dc.contributor.googleauthorSuk Ho Byeon-
dc.contributor.googleauthorHelen J Kuht-
dc.contributor.googleauthorMervyn G Thomas-
dc.contributor.googleauthorJinu Han-
dc.identifier.doi10.1167/tvst.11.6.25-
dc.contributor.localIdA01849-
dc.contributor.localIdA02108-
dc.contributor.localIdA05763-
dc.contributor.localIdA04627-
dc.contributor.localIdA03179-
dc.contributor.localIdA04182-
dc.contributor.localIdA04329-
dc.relation.journalcodeJ04101-
dc.identifier.eissn2164-2591-
dc.identifier.pmid35762937-
dc.contributor.alternativeNameByeon, Suk Ho-
dc.contributor.affiliatedAuthor변석호-
dc.contributor.affiliatedAuthor신새암-
dc.contributor.affiliatedAuthor원동주-
dc.contributor.affiliatedAuthor이승태-
dc.contributor.affiliatedAuthor이준원-
dc.contributor.affiliatedAuthor최종락-
dc.contributor.affiliatedAuthor한진우-
dc.citation.volume11-
dc.citation.number6-
dc.citation.startPage25-
dc.identifier.bibliographicCitationTRANSLATIONAL VISION SCIENCE & TECHNOLOGY, Vol.11(6) : 25, 2022-06-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Laboratory Medicine (진단검사의학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Ophthalmology (안과학교실) > 1. Journal Papers

qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.