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An Improved SNAP-ADAR Tool Enables Efficient RNA Base Editing to Interfere with Post-translational Protein Modification

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NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE264114
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RNA base editing applies endogenous or engineered adenosine deaminases to introduce adenosine-to-inosine changes into a target RNA in a highly programmable manner. Recently, notable success was achieved for the repair of disease-causing guanosine-to-adenosine mutations by means of RNA base editing. Here, we propose that RNA base editing could be broadly applied to perturb protein function by removal of regulatory sites of post-translational modification (PTM), like phosphorylation and/or acetylation sites. We demonstrate the feasibility of PTM interference (PTMi) on more than 70 PTM sites in various signaling proteins and identify key determinants for high editing efficiency and potent down-stream effects. Specifically, we demonstrate both negative and positive regulation of the JAK/STAT pathway by PTMi. To identify potent regulatory sites for PTMi, we applied an improved version of the SNAP-ADAR tool, which achieved high editing efficiency over a broad codon scope with tight control of bystander editing. The transient nature of RNA base editing enables the fast, dose-dependent (thus partial) and reversible manipulation of PTM sites, which is a key advantage over DNA editing approaches, where genetic compensation or lethality can conceal a phenotype. In summary, PTM interference might become a valuable field of application of RNA base editing in basic biology and medicine. To study the effect of PTMi on the interferon-induced JAK/STAT pathway,we compared the editing of six different PTM sites at the RNAs of five different players of the pathway (STAT1 Y701C, STAT1 T288A, STAT2 Y690C, JAK1 Y1034C, IFNGR1 Y457C and IFNAR1 Y466C) by transfection of the respective guide RNA (BB180, BB478, BB 349, BB355, BB304 and BB305 respectively) in HeLa-PB-SA1Q cells and global gene expression changes 24 h after IFN-α or -γ addition via next generation sequencing (DESeq analysis) was studied. THE RNA-seq data from all samples with IFN-α or -γ were compared for differential gene expression with the control sample with no IFN induction and an empty transfection.
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