Profiling dynamic RNA-protein interactions using small molecule-inducible RNA editing
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE207005 | GEO | 2023/04/28
REPOSITORIES: GEO
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Project description:Most current methods to identify cell-specific RNA binding protein (RBP) targets require analyzing an extract, a strategy that is problematic with small amounts of material. We previously addressed this issue by developing TRIBE, a method that expresses an RBP of interest fused to the catalytic domain (cd) of the RNA editing enzyme ADAR. TRIBE performs Adenosine-to-Inosine editing on candidate RNA targets of the RBP. However, target identification is limited by the efficiency of the ADARcd. Here we describe HyperTRIBE, which carries a previously characterized hyperactive mutation (E488Q) of the ADARcd. HyperTRIBE identifies dramatically more editing sites than TRIBE, many of which are also edited by TRIBE but at a much lower editing frequency. The data have mechanistic implications for the enhanced editing activity of the HyperADARcd as part of a RBP fusion protein and also indicate that HyperTRIBE more faithfully recapitulates the known binding specificity of its RBP than TRIBE.
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Project description:RNA binding proteins (RBPs) are key regulators of RNA processing and cellular function. Technologies to discover RNA targets of RBPs such as TRIBE (targets of RNA binding proteins identified by editing) and STAMP (surveying targets by APOBEC1 mediated profiling) utilize fusions of RNA base-editors (rBEs) to RBPs to circumvent the limitations of immunoprecipitation (CLIP)-based methods that require enzymatic digestion and large amounts of input material. To expand the collection of rBEs suitable for editing-based RBP-RNA interactome studies, we developed experimental and computational assays to systematically evaluate the editing activities of over thirty A-to-I and C-to-U rBEs in human cells. We identify rBEs that outperform Drosophila ADAR (TRIBE) and mammalian APOBEC1 (STAMP) in the characterization of the binding patterns of sequence-specific and broad-binding RBPs and recommend rBEs that pair effectively in dual-RBP-based applications. We demonstrate that the optimal choice of single or multiple rBEs to fuse to a given or pair of RBPs depends on the editing biases of the rBEs and the binding preferences of the RBPs. Our framework ENGRAVe (Editing nucleotides with general RNA-base-editor variants) reframes the use of and expands the choice of rBEs for the next generation of RBP-RNA target discoveries.
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