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      Target 5000: Target Capture Sequencing for Inherited Retinal Degenerations

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          Abstract

          There are an estimated 5000 people in Ireland who currently have an inherited retinal degeneration (IRD). It is the goal of this study, through genetic diagnosis, to better enable these 5000 individuals to obtain a clearer understanding of their condition and improved access to potentially applicable therapies. Here we show the current findings of a target capture next-generation sequencing study of over 750 patients from over 520 pedigrees currently situated in Ireland. We also demonstrate how processes can be implemented to retrospectively analyse patient datasets for the detection of structural variants in previously obtained sequencing reads. Pathogenic or likely pathogenic mutations were detected in 68% of pedigrees tested. We report nearly 30 novel mutations including three large structural variants. The population statistics related to our findings are presented by condition and credited to their respective candidate gene mutations. Rediagnosis rates of clinical phenotypes after genotyping are discussed. Possible causes of failure to detect a candidate mutation are evaluated. Future elements of this project, with a specific emphasis on structural variants and non-coding pathogenic variants, are expected to increase detection rates further and thereby produce an even more comprehensive representation of the genetic landscape of IRDs in Ireland.

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          Most cited references44

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          dbNSFP v3.0: A One-Stop Database of Functional Predictions and Annotations for Human Nonsynonymous and Splice-Site SNVs.

          The purpose of the dbNSFP is to provide a one-stop resource for functional predictions and annotations for human nonsynonymous single-nucleotide variants (nsSNVs) and splice-site variants (ssSNVs), and to facilitate the steps of filtering and prioritizing SNVs from a large list of SNVs discovered in an exome-sequencing study. A list of all potential nsSNVs and ssSNVs based on the human reference sequence were created and functional predictions and annotations were curated and compiled for each SNV. Here, we report a recent major update of the database to version 3.0. The SNV list has been rebuilt based on GENCODE 22 and currently the database includes 82,832,027 nsSNVs and ssSNVs. An attached database dbscSNV, which compiled all potential human SNVs within splicing consensus regions and their deleteriousness predictions, add another 15,030,459 potentially functional SNVs. Eleven prediction scores (MetaSVM, MetaLR, CADD, VEST3, PROVEAN, 4× fitCons, fathmm-MKL, and DANN) and allele frequencies from the UK10K cohorts and the Exome Aggregation Consortium (ExAC), among others, have been added. The original seven prediction scores in v2.0 (SIFT, 2× Polyphen2, LRT, MutationTaster, MutationAssessor, and FATHMM) as well as many SNV and gene functional annotations have been updated. dbNSFP v3.0 is freely available at http://sites.google.com/site/jpopgen/dbNSFP.
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            Copy number variation detection and genotyping from exome sequence data

            While exome sequencing is readily amenable to single-nucleotide variant discovery, the sparse and nonuniform nature of the exome capture reaction has hindered exome-based detection and characterization of genic copy number variation. We developed a novel method using singular value decomposition (SVD) normalization to discover rare genic copy number variants (CNVs) as well as genotype copy number polymorphic (CNP) loci with high sensitivity and specificity from exome sequencing data. We estimate the precision of our algorithm using 122 trios (366 exomes) and show that this method can be used to reliably predict (94% overall precision) both de novo and inherited rare CNVs involving three or more consecutive exons. We demonstrate that exome-based genotyping of CNPs strongly correlates with whole-genome data (median r 2 = 0.91), especially for loci with fewer than eight copies, and can estimate the absolute copy number of multi-allelic genes with high accuracy (78% call level). The resulting user-friendly computational pipeline, CoNIFER ( co py n umber i nference f rom e xome r eads), can reliably be used to discover disruptive genic CNVs missed by standard approaches and should have broad application in human genetic studies of disease.
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              Frequent hypomorphic alleles account for a significant fraction of ABCA4 disease and distinguish it from age-related macular degeneration.

              Variation in the ABCA4 gene is causal for, or associated with, a wide range of phenotypes from early onset Mendelian retinal dystrophies to late-onset complex disorders such as age-related macular degeneration (AMD). Despite substantial progress in determining the causal genetic variation, even complete sequencing of the entire open reading frame and splice sites of ABCA4 identifies biallelic mutations in only 60%-70% of cases; 20%-25% remain with one mutation and no mutations are found in 10%-15% of cases with clinically confirmed ABCA4 disease. This study was designed to identify missing causal variants specifically in monoallelic cases of ABCA4 disease.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Genes (Basel)
                Genes (Basel)
                genes
                Genes
                MDPI
                2073-4425
                03 November 2017
                November 2017
                : 8
                : 11
                : 304
                Affiliations
                [1 ]The School of Genetics & Microbiology, Trinity College Dublin, Dublin 2, Ireland; peter.humphries@ 123456tcd.ie (P.H.); paul.kenna@ 123456tcd.ie (P.F.K.); carrigma@ 123456tcd.ie (M.C.); jane.farrar@ 123456tcd.ie (G.J.F.)
                [2 ]The Mater Misericordiae University Hospital, Dublin 7, Ireland; kirkstephenson@ 123456hotmail.com (K.S.); dkeegan@ 123456mater.ie (D.K.)
                [3 ]The Research Foundation, Royal Victoria Eye and Ear Hospital, Dublin 2, Ireland; wynnenc@ 123456tcd.ie
                [4 ]Department of Ophthalmology, The Royal Victoria Hospital, Belfast BT12 6BA, Northern Ireland, UK; julie.silvestri@ 123456belfasttrust.hscni.net
                [5 ]Centre for Experimental Medicine, Queen’s University Belfast, Belfast BT7 1NN, Northern Ireland, UK
                Author notes
                [* ]Correspondence: dockerya@ 123456tcd.ie
                [†]

                Authors contributed equally.

                Article
                genes-08-00304
                10.3390/genes8110304
                5704217
                29099798
                54ba7567-29a9-4caa-9e64-fb6d893bcd21
                © 2017 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 08 September 2017
                : 27 October 2017
                Categories
                Article

                retina,genetics,ophthalmology,retinitis pigmentosa,genomics
                retina, genetics, ophthalmology, retinitis pigmentosa, genomics

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