Identification of Deep-Intronic Splice Mutations in a Large Cohort of Patients With Inherited Retinal Diseases.

TitleIdentification of Deep-Intronic Splice Mutations in a Large Cohort of Patients With Inherited Retinal Diseases.
Publication TypeJournal Article
Year of Publication2021
AuthorsQian, X, Wang, J, Wang, M, Igelman, AD, Jones, KD, Li, Y, Wang, K, Goetz, KE, Birch, DG, Yang, P, Pennesi, ME, Chen, R
JournalFront Genet
Volume12
Pagination647400
Date Published2021
ISSN1664-8021
Abstract

High throughput sequencing technologies have revolutionized the identification of mutations responsible for a diverse set of Mendelian disorders, including inherited retinal disorders (IRDs). However, the causal mutations remain elusive for a significant proportion of patients. This may be partially due to pathogenic mutations located in non-coding regions, which are largely missed by capture sequencing targeting the coding regions. The advent of whole-genome sequencing (WGS) allows us to systematically detect non-coding variations. However, the interpretation of these variations remains a significant bottleneck. In this study, we investigated the contribution of deep-intronic splice variants to IRDs. WGS was performed for a cohort of 571 IRD patients who lack a confident molecular diagnosis, and potential deep intronic variants that affect proper splicing were identified using SpliceAI. A total of six deleterious deep intronic variants were identified in eight patients. An minigene system was applied to further validate the effect of these variants on the splicing pattern of the associated genes. The prediction scores assigned to splice-site disruption positively correlated with the impact of mutations on splicing, as those with lower prediction scores demonstrated partial splicing. Through this study, we estimated the contribution of deep-intronic splice mutations to unassigned IRD patients and leveraged and methods to establish a framework for prioritizing deep intronic variant candidates for mechanistic and functional analyses.

DOI10.3389/fgene.2021.647400
Alternate JournalFront Genet
PubMed ID33737949
PubMed Central IDPMC7960924
Grant ListR01 EY009076 / EY / NEI NIH HHS / United States
S10 OD023469 / OD / NIH HHS / United States
R01 EY022356 / EY / NEI NIH HHS / United States
P30 EY002520 / EY / NEI NIH HHS / United States
R01 EY018571 / EY / NEI NIH HHS / United States