Dataset Information

EpiCas-DL: Predicting sgRNA activity for CRISPR-mediated epigenome editing by deep learning.

ABSTRACT: CRISPR-mediated epigenome editing enables gene expression regulation without changing the underlying DNA sequence, and thus has vast potential for basic research and gene therapy. Effective selection of a single guide RNA (sgRNA) with high on-target efficiency and specificity would facilitate the application of epigenome editing tools. Here we performed an extensive analysis of CRISPR-mediated epigenome editing tools on thousands of experimentally examined on-target sites and established EpiCas-DL, a deep learning framework to optimize sgRNA design for gene silencing or activation. EpiCas-DL achieves high accuracy in sgRNA activity prediction for targeted gene silencing or activation and outperforms other available in silico methods. In addition, EpiCas-DL also identifies both epigenetic and sequence features that affect sgRNA efficacy in gene silencing and activation, facilitating the application of epigenome editing for research and therapy. EpiCas-DL is available at http://www.sunlab.fun:3838/EpiCas-DL.

SUBMITTER: Yang Q

PROVIDER: S-EPMC9763632 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

<i>EpiCas-DL</i>: Predicting sgRNA activity for CRISPR-mediated epigenome editing by deep learning.

Yang Qianqian Q Wu Leilei L Meng Juan J Ma Lei L Zuo Erwei E Sun Yidi Y

Computational and structural biotechnology journal 20221119

CRISPR-mediated epigenome editing enables gene expression regulation without changing the underlying DNA sequence, and thus has vast potential for basic research and gene therapy. Effective selection of a single guide RNA (sgRNA) with high on-target efficiency and specificity would facilitate the application of epigenome editing tools. Here we performed an extensive analysis of CRISPR-mediated epigenome editing tools on thousands of experimentally examined on-target sites and established <i>EpiC ...[more]

PMID: 36582444

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Project description:RationaleDSP (desmoplakin), the most abundant component of desmosomes, which maintain the mechanical integrity of epithelium, is a genome-wide association study-identified genetic risk locus in human idiopathic pulmonary fibrosis (IPF). Subjects with IPF express a significantly higher level of DSP than control subjects.ObjectivesDetermine potential mechanisms by which DSP is regulated in lung fibrosis.MethodsMatrigel-coated soft and stiff polyacrylamide gels were made to simulate the stiffness of normal and fibrotic lungs. Quantitative chromatin immunoprecipitation and electrophoretic mobility shift assay were used to evaluate transcription factor binding to the DSP promoter. Targeted DNA methylation was achieved by CRISPR (clustered regularly interspaced short palindromic repeats)/dCas9 (deactivated CRISPR-associated protein-9 nuclease)-mediated Dnmt3A (DNA methyltransferase 3A) expression under the guidance of sequence-specific single guide RNAs.Measurements and main resultsStiff matrix promotes DSP gene expression in both human and rodent lung epithelial cells as compared with soft matrix. A conserved region in the proximal DSP promoter is hypermethylated under soft matrix conditions and becomes hypomethylated/demethylated under stiff matrix conditions. Demethylation of this conserved DSP promoter region is associated with transactivation of transcription factor EGR1 (early growth response protein 1), resulting in EGR1-dependent DSP overexpression. Targeted DNA methylation by CRISPR/dCas9/Dnmt3A-mediated epigenome editing blocks EGR1 binding to the DSP promoter and inhibits stiff matrix-induced DSP overexpression.ConclusionsDSP is a matrix stiffness-regulated mechanosensitive gene. CRISPR/dCas9-Dnmt3A-mediated epigenome editing reverses DSP overexpression by reestablishment of the epigenetic control of DSP under the mechanically homeostatic environment. It provides a useful tool for investigations of the functional role of DSP in the pathogenesis of lung fibrosis.

Dataset Information

EpiCas-DL: Predicting sgRNA activity for CRISPR-mediated epigenome editing by deep learning.

Publications

<i>EpiCas-DL</i>: Predicting sgRNA activity for CRISPR-mediated epigenome editing by deep learning.

Similar Datasets

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