Identification and Analysis of Genes Associated with Inherited Retinal Diseases

Khan, Mubeen; Fadaie, Zeinab; Cornelis, Stéphanie S.; Cremers, Frans P.M.; Roosing, Susanne

doi:10.1007/978-1-4939-8669-9_1

Cited by 12 publications

(14 citation statements)

References 112 publications

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“…Important aspects of disease diagnostics are the functional assessment of rare variants with RNA and protein effects that can only be predicted in silico and the assessment of putative splice defects. Very useful references on several key databases that provide extensive information about gene variants, phenotypic information that accompanies variants, and information about genotype-phenotype correlations were summarized [8]. Most databases make use of Human Genome Variation Society (HGVS) nomenclature to describe variants in a consistent manner (https://varnomen.hgvs.org).…”

Section: Innovative Approaches Of Modern Genomics and Cell Technologymentioning

confidence: 99%

“…In 2013, Japan began clinical trials using iPSC-derived RPE cells to treat AMD, in which the destruction of central retinal cells occurs [354]. The application of stem cell technology to generate photoreceptor precursor cells from patient somatic cells, which can subsequently be used for RNA and protein studies, has been described [8,355] Approaches to creating a functioning human retina with restoration of three-dimensional structure in vitro are being developed [355,356]. One study reported on the possibility of obtaining a fragment of the neural tissue of a human retina from human iPSCs in 3D in vitro (Johns Hopkins University School of Medicine, Baltimore, MD, USA) [356].…”

Section: Gene-based and Cellular Technologies In The Treatment Of Inhmentioning

confidence: 99%

“…The use of genome-editing technology can lead to major breakthroughs in therapy, but using it safely is impossible without knowledge of the genetic nature of the cell, the characteristics of tissues, cellular responses, and compliance with ethical and social factors. The attitude of the International Society for Stem Cell Research (ISSCR) toward research based on the use of the listed gene technologies is ambiguous [8,351,355,356]. In parallel with the study of functions and their place in the genetic regulation program, a large-scale search for molecular targets is being carried out [327,328,394].…”

Section: Conclusion/insightsmentioning

confidence: 99%

“…Homeobox genes from different classes include retina-specific regulatory genes accepted as critical for eye field specification and retinal cells type differentiation by a broad array of loss-or gain-of-function models. Among these genes are some that are known to cause inherited retinal diseases (IRDs) that disturb the development, function, and survival of rod and cone photoreceptors, ganglion cells, or retinal pigment epithelial cells [4,[6][7][8]. In this review, we focused on IRDs associated with single homeobox gene malfunctions as a result of mutations.…”

Section: Introductionmentioning

confidence: 99%

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Inherited Eye Diseases with Retinal Manifestations through the Eyes of Homeobox Genes

Markitantova

Симирский

2020

IJMS

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Retinal development is under the coordinated control of overlapping networks of signaling pathways and transcription factors. The paper was conceived as a review of the data and ideas that have been formed to date on homeobox genes mutations that lead to the disruption of eye organogenesis and result in inherited eye/retinal diseases. Many of these diseases are part of the same clinical spectrum and have high genetic heterogeneity with already identified associated genes. We summarize the known key regulators of eye development, with a focus on the homeobox genes associated with monogenic eye diseases showing retinal manifestations. Recent advances in the field of genetics and high-throughput next-generation sequencing technologies, including single-cell transcriptome analysis have allowed for deepening of knowledge of the genetic basis of inherited retinal diseases (IRDs), as well as improve their diagnostics. We highlight some promising avenues of research involving molecular-genetic and cell-technology approaches that can be effective for IRDs therapy. The most promising neuroprotective strategies are aimed at mobilizing the endogenous cellular reserve of the retina.

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Section: Innovative Approaches Of Modern Genomics and Cell Technologymentioning

confidence: 99%

Section: Gene-based and Cellular Technologies In The Treatment Of Inhmentioning

confidence: 99%

Section: Conclusion/insightsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Inherited Eye Diseases with Retinal Manifestations through the Eyes of Homeobox Genes

Markitantova

Симирский

2020

IJMS

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“…Most forms of IRD mainly affect photoreceptors but other forms can also primarily affect the retinal pigment epithelium (RPE) or the inner retina. IRDs can propagate through all modes of inheritance—autosomal dominant (AD), autosomal recessive (AR), X-linked (XL) or mitochondrial, whilst digenic cases or uniparental disomy have also been described occasionally [2].…”

Section: Introductionmentioning

confidence: 99%

Molecular Therapies for Inherited Retinal Diseases—Current Standing, Opportunities and Challenges

Vázquez-Domínguez

Garanto

Collin

2019

Genes

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Inherited retinal diseases (IRDs) are both genetically and clinically highly heterogeneous and have long been considered incurable. Following the successful development of a gene augmentation therapy for biallelic RPE65-associated IRD, this view has changed. As a result, many different therapeutic approaches are currently being developed, in particular a large variety of molecular therapies. These are depending on the severity of the retinal degeneration, knowledge of the pathophysiological mechanism underlying each subtype of IRD, and the therapeutic target molecule. DNA therapies include approaches such as gene augmentation therapy, genome editing and optogenetics. For some genetic subtypes of IRD, RNA therapies and compound therapies have also shown considerable therapeutic potential. In this review, we summarize the current state-of-the-art of various therapeutic approaches, including the pros and cons of each strategy, and outline the future challenges that lie ahead in the combat against IRDs.

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Benchmarking deep learning splice prediction tools using functional splice assays

et al. 2021

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Hereditary disorders are frequently caused by genetic variants that affect pre‐messenger RNA splicing. Though genetic variants in the canonical splice motifs are almost always disrupting splicing, the pathogenicity of variants in the noncanonical splice sites (NCSS) and deep intronic (DI) regions are difficult to predict. Multiple splice prediction tools have been developed for this purpose, with the latest tools employing deep learning algorithms. We benchmarked established and deep learning splice prediction tools on published gold standard sets of 71 NCSS and 81 DI variants in the ABCA4 gene and 61 NCSS variants in the MYBPC3 gene with functional assessment in midigene and minigene splice assays. The selection of splice prediction tools included CADD, DSSP, GeneSplicer, MaxEntScan, MMSplice, NNSPLICE, SPIDEX, SpliceAI, SpliceRover, and SpliceSiteFinder‐like. The best‐performing splice prediction tool for the different variants was SpliceRover for ABCA4 NCSS variants, SpliceAI for ABCA4 DI variants, and the Alamut 3/4 consensus approach (GeneSplicer, MaxEntScacn, NNSPLICE and SpliceSiteFinder‐like) for NCSS variants in MYBPC3 based on the area under the receiver operator curve. Overall, the performance in a real‐time clinical setting is much more modest than reported by the developers of the tools.

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Identification and Analysis of Genes Associated with Inherited Retinal Diseases

Cited by 12 publications

References 112 publications

Inherited Eye Diseases with Retinal Manifestations through the Eyes of Homeobox Genes

Inherited Eye Diseases with Retinal Manifestations through the Eyes of Homeobox Genes

Molecular Therapies for Inherited Retinal Diseases—Current Standing, Opportunities and Challenges

Benchmarking deep learning splice prediction tools using functional splice assays

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