4.6 Article

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

Journal

FRONTIERS IN GENETICS
Volume 12, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2021.647400

Keywords

inherited retinal dystrophies; whole-genome sequencing; splicing; deep-intronic mutations; minigenes

Funding

  1. National Eye Institute [EY022356, EY018571, EY002520, EY09076]
  2. Retinal Research Foundation
  3. NIH [S10OD023469]

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This study investigated the contribution of deep-intronic splice variants to inherited retinal disorders by performing whole-genome sequencing on a cohort of 571 patients. Using the SpliceAI tool, six deleterious deep intronic variants were identified, and in vitro experiments showed that mutations with lower prediction scores may result in partial splicing effects.
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 in vitro 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 in silico and in vitro methods to establish a framework for prioritizing deep intronic variant candidates for mechanistic and functional analyses.

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