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Pathogenic structural and non-coding variants in retinal dystrophy identified through the 100,000 genomes project

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Abstract Number: 1755

AuthorBlock: Gavin Arno1,2, Jamie Ellingford3, Fabiana Louise Motta4, Kathryn Oprych1, Rola Ba-Abbad1,2, Omar Abdul Rahman Mahroo1,2, Anthony Moore5,2, Graeme Black3, Michel Michaelides1,2, Andrew Webster1,2
1UCL Institute of Ophthalmology, London, United Kingdom; 2Moorfields Eye Hospital, London, United Kingdom; 3Manchester Centre for Genomic Medicine, University of Manchester, Manchester, United Kingdom; 4Department of Ophthalmology, Universidade Federal de São Paulo, São Paulo, Brazil; 5Ophthalmology, UCSF School of Medicine, University of California San Francisco, San Francisco, California, United States;

DisclosureBlock: Gavin Arno, None; Jamie Ellingford, None; Fabiana Louise Motta, None; Kathryn Oprych, None; Rola Ba-Abbad, None; Omar Abdul Rahman Mahroo, None; Anthony Moore, None; Graeme Black, None; Michel Michaelides, None; Andrew Webster, None;

To characterise pathogenic variants in whole genome sequencing (WGS) data from a cohort of patients with inherited retinal disease (IRD).

Patients and families were recruited from the inherited retinal disease clinics at Moorfields Eye Hospital, London as part of the UK 100,000 genomes project. A cohort of 358 probands with a broad spectrum of IRD underwent WGS and bioinformatic analysis for pathogenic variants in a virtual panel of 313 genes associated with posterior segment abnormalities. Potential pathogenic structural and non-coding variants were selected for downstream functional analysis by applying an integrated analysis pipeline incorporating deep phenotyping, variant filtering, and interpretation tools in patients unsolved following coding variant analysis. Variant effects were confirmed where possible using molecular biology techniques.

Our analysis pipeline identified candidate pathogenic structural and non-coding variants in the ABCA4, BEST1, CHM, CRB1, EYS, GUCY2D, IFT140, PDE6B, PRPF31 and USH2A genes. These variants included: 1. Splice region and deep intronic single nucleotide variants that result in altered splicing by weakening existing splice sites or creating cryptic splice sites. 2. Upstream gene regulatory region variants that alter the level of gene transcription through changes in transcription factor binding sites. 3. An entirely intronic complex structural rearrangement in the CHM gene comprising a 5 kilobase deletion and a 220 base inversion at the 3’ breakpoint, predicted to lead to an altered transcript. 4. Variants affecting the canonical splice-site of the non-coding first exons of the PRPF31 and BEST1 genes.

Implementation of WGS in a clinical genomic pipeline enables detection and interpretation of potential pathogenic variants across the entire genomic footprint of a diagnostic gene panel. We report newly identified variants otherwise missed by exon-focused diagnostic strategies that account for a significant proportion of missing heritability in IRD. In silico and functional investigation confirmed the pathogenicity of these variants and should be integrated in future clinical diagnostic pipelines incorporating WGS screening.

Layman Abstract (optional): Provide a 50-200 word description of your work that non-scientists can understand. Describe the big picture and the implications of your findings, not the study itself and the associated details.
Inherited retinal disease (IRD) affects the light sensitive cells at the back of the eye and is a major cause of blindness worldwide.

IRD is caused by spelling mistakes (mutations) in the genes that help enable vision. Over 300 of these genes have been implicated so far and modern high throughput DNA testing has revolutionized our ability to read these genes quickly and easily. However, we still cannot find the responsible mutation in up to half of patients for several reasons including the fact that we still do not understand the function of the vast majority of the 3 billion letters in the human DNA (genome) outside of the gene segments (exons) that make proteins.

We report on using the latest whole genome sequencing technology to analyse IRD patient DNA on a scale never before possible. This study has identified likely disease causing mutations in the largely overlooked regions of the genes implicated in IRD. These findings will improve our understanding of inherited disease mechanisms, provide a molecular diagnosis for patients and identify new targets for therapies.