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Author

Meng Wang

Bio: Meng Wang is an academic researcher from Baylor College of Medicine. The author has contributed to research in topics: Minigene. The author has an hindex of 1, co-authored 1 publications receiving 5 citations.
Topics: Minigene

Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors investigated the contribution of deep-intronic splice variants to inherited retinal disorders (IRDs) using whole-genome sequencing (WGS) for a cohort of 571 IRD patients who lack a confident molecular diagnosis.
Abstract: 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.

27 citations


Cited by
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Journal ArticleDOI
TL;DR: The Global Retinal Inherited Disease (GRID) dataset as mentioned in this paper contains 4798 discrete variants and 17,299 alleles published in 31 papers, showing a wide range of frequencies and complexities among the 194 genes reported in GRID.

25 citations

Journal ArticleDOI
TL;DR: The Global Retinal Inherited Disease (GRID) dataset as discussed by the authors contains 4,798 discrete variants and 17,299 alleles published in 31 papers, showing a wide range of frequencies and complexities among the 194 genes reported in GRID.

25 citations

Journal ArticleDOI
TL;DR: Five distinct approaches to gene-based therapy that have potential to treat the full spectrum of IRDs are focused on, including optogenetic approaches that aim to replace the function of native retinal photoreceptors by engineering other retinal cell types to become capable of phototransduction.
Abstract: Inherited retinal diseases (IRDs) are a heterogenous group of orphan eye diseases that typically result from monogenic mutations and are considered attractive targets for gene-based therapeutics. Following the approval of an IRD gene replacement therapy for Leber’s congenital amaurosis due to RPE65 mutations, there has been an intensive international research effort to identify the optimal gene therapy approaches for a range of IRDs and many are now undergoing clinical trials. In this review we explore therapeutic challenges posed by IRDs and review current and future approaches that may be applicable to different subsets of IRD mutations. Emphasis is placed on five distinct approaches to gene-based therapy that have potential to treat the full spectrum of IRDs: 1) gene replacement using adeno-associated virus (AAV) and nonviral delivery vectors, 2) genome editing via the CRISPR/Cas9 system, 3) RNA editing by endogenous and exogenous ADAR, 4) mRNA targeting with antisense oligonucleotides for gene knockdown and splicing modification, and 5) optogenetic approaches that aim to replace the function of native retinal photoreceptors by engineering other retinal cell types to become capable of phototransduction.

20 citations

Journal ArticleDOI
25 Aug 2021-Genes
TL;DR: In this paper, the authors investigated the sensitivity and specificity of SpliceAI, a recently introduced in silico splicing prediction algorithm in conjunction with other in-silico tools.
Abstract: Neurofibromatosis type 1, characterized by neurofibromas and cafe-au-lait macules, is one of the most common genetic disorders caused by pathogenic NF1 variants. Because of the high proportion of splicing mutations in NF1, identifying variants that alter splicing may be an essential issue for laboratories. Here, we investigated the sensitivity and specificity of SpliceAI, a recently introduced in silico splicing prediction algorithm in conjunction with other in silico tools. We evaluated 285 NF1 variants identified from 653 patients. The effect on variants on splicing alteration was confirmed by complementary DNA sequencing followed by genomic DNA sequencing. For in silico prediction of splicing effects, we used SpliceAI, MaxEntScan (MES), and Splice Site Finder-like (SSF). The sensitivity and specificity of SpliceAI were 94.5% and 94.3%, respectively, with a cut-off value of Δ Score > 0.22. The area under the curve of SpliceAI was 0.975 (p < 0.0001). Combined analysis of MES/SSF showed a sensitivity of 83.6% and specificity of 82.5%. The concordance rate between SpliceAI and MES/SSF was 84.2%. SpliceAI showed better performance for the prediction of splicing alteration for NF1 variants compared with MES/SSF. As a convenient web-based tool, SpliceAI may be helpful in clinical laboratories conducting DNA-based NF1 sequencing.

15 citations

Journal ArticleDOI
TL;DR: In this paper , a genome-wide multi-omics retinal database, RegRet, was used for fine-mapping of the interactions of the PRDM13 and IRX1 promoters and the identification of eighteen candidate cis-regulatory elements (cCREs), the activity of which was investigated by luciferase and Xenopus enhancer assays.
Abstract: North Carolina macular dystrophy (NCMD) is a rare autosomal-dominant disease affecting macular development. The disease is caused by non-coding single-nucleotide variants (SNVs) in two hotspot regions near PRDM13 and by duplications in two distinct chromosomal loci, overlapping DNase I hypersensitive sites near either PRDM13 or IRX1. To unravel the mechanisms by which these variants cause disease, we first established a genome-wide multi-omics retinal database, RegRet. Integration of UMI-4C profiles we generated on adult human retina then allowed fine-mapping of the interactions of the PRDM13 and IRX1 promoters and the identification of eighteen candidate cis-regulatory elements (cCREs), the activity of which was investigated by luciferase and Xenopus enhancer assays. Next, luciferase assays showed that the non-coding SNVs located in the two hotspot regions of PRDM13 affect cCRE activity, including two NCMD-associated non-coding SNVs that we identified herein. Interestingly, the cCRE containing one of these SNVs was shown to interact with the PRDM13 promoter, demonstrated in vivo activity in Xenopus, and is active at the developmental stage when progenitor cells of the central retina exit mitosis, suggesting that this region is a PRDM13 enhancer. Finally, mining of single-cell transcriptional data of embryonic and adult retina revealed the highest expression of PRDM13 and IRX1 when amacrine cells start to synapse with retinal ganglion cells, supporting the hypothesis that altered PRDM13 or IRX1 expression impairs interactions between these cells during retinogenesis. Overall, this study provides insight into the cis-regulatory mechanisms of NCMD and supports that this condition is a retinal enhanceropathy.

6 citations