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Zachry Soens, Jacques E Zaneveld, Violet Gelowani, Lichun Jiang, Ruifang Sui, Robert K Koenekoop, Rui Chen; Systematic Analysis of Non-Protein Coding Sequence Variation Reveals Putative Pathogenic Mutations Causing Inherited Human Retinal Disease. Invest. Ophthalmol. Vis. Sci. 2014;55(13):6394.
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Currently the identification of human disease-causing mutations has been largely limited to protein coding regions due to our limited knowledge of the rest of the genome. The purpose of this study is to assess the contribution to disease of identified novel sequence variations in non-protein coding regions in a cohort of more than 1000 human retinal disease patients.
Our approach combines computational and experimental methods. Based on the exon sequence of all known retinal disease genes in over 1000 patients, a statistical method was developed to estimate the contribution of noncoding mutations in each gene to each disease. Noncoding variants of the top ranked disease genes were identified using a combination of next generation sequencing and array comparative genomic hybridization. Identified variants were analyzed using an integrative approach for their potential to disrupt the function of genes required for proper retinal function. Candidate pathogenic variants were Sanger verified and functionally validated to alter gene function or expression.
16 genes that were likely to contain a significant number of noncoding pathogenic mutations, such as USH2A and ABCA4, were identified. Characterization of the genomic region of these genes in our patient cohort identified several novel candidate pathogenic noncoding variants in multiple disease cohorts including Leber congenital amaurosis, Usher syndrome, and Stargardt disease. Identified variants are predicted to disrupt gene splicing causing a proportion of transcripts to lose a typical exon or gain a cryptic exon.
We have developed a new statistical method to estimate the mutation load in the noncoding region for each known retinal disease gene. Follow up studies of top ranked genes identified multiple types of non-protein coding mutations including SNVs and indels. As a significant proportion of patients’ disease can be attributed to mutation in noncoding regions, further improving our ability to identify and interpret these types of mutations is crucial.
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