Nature MethodsMolecular BiologyPeer-reviewed journal article
Single molecule co-occupancy of RNA-binding proteins with an evolved RNA deaminase
Yizhu LiniD, Samentha Kwok, Abigail E. HeiniD, Bao ThaiiD, Yewande AlabiiD, Megan S OstrowskiiD, Ke WuiD, Stephen N. FlooriD
Abstract
RNA-protein interactions broadly regulate gene expression. To understand RNA regulation, it is critical to measure RNA-protein interactions in cells. Current approaches to measure RNA-protein interactions often rely on crosslinking and shortread RNA sequencing, which has considerably advanced the understanding of gene expression but also suffers from some limitations. We present REMORA (RNA Encoded Molecular Recording in Adenosines), a new strategy to measure RNA-binding events on single RNA molecules in cells. In REMORA, adenosine deamination serves as a molecular record of RNA-protein interactions that are identified by mutations by sequencing. We performed RNA-based directed evolution to identify an RNA deaminase variant with high activity on arbitrary adenosine residues in RNA. We show that this RNA deaminase has high activity, low local sequence or structure bias, low background, and is generally applicable to diverse RNA-binding proteins. By combining our improved A-to-I RNA deaminase with the C-to-U deaminase APOBEC1 and long-read RNA sequencing, our approach enables simultaneous recording of the locations two RNA binding proteins on single mRNA molecules. Orthogonal RNA molecular recording of two Pumilio family proteins, PUM1 and PUM2, reveals that PUM1 competes with PUM2 for some but not all Pumilio binding sites in cells, despite having the same in vitro binding preferences. Our work thus measures competition between RNA-binding proteins for RNA sites in cells, and our genetically encodable RNA deaminase enables single-molecule identification of RNA-protein interactions with cell type specificity.
- organism: human
- assay: scRNA-seq
- assay: long-read sequencing
- research focus: cell type annotation
- research focus: differential expression
- research focus: protein structure prediction
- research focus: drug response / drug discovery
- approach: experimental assay
- Citations
- 24
- FWCI
- 2.13
- Field percentile
- top 11%
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