Genomic profiling of native R loops with a DNA-RNA hybrid recognition sensor
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Abstract
An R loop is a unique triple-stranded structure that participates in multiple key biological processes and is relevant to human diseases. Accurate and comprehensive R loop profiling is a prerequisite for R loops studies. However, current R loop mapping methods generate large discrepancies, therefore an independent method is in urgent need. Here, we establish an independent R loop CUT&Tag (Tn5-based cleavage under targets and tagmentation) method by combining CUT&Tag and GST-His6-2×HBD (glutathione S-transferase-hexahistidine-2× hybrid-binding domain), an artificial DNA-RNA hybrid sensor that specifically recognizes the DNA-RNA hybrids. We demonstrate that the R loop CUT&Tag is sensitive, reproducible, and convenient for native R loop mapping with high resolution, and find that the capture strategies, instead of the specificity of sensors, largely contribute to the disparities among different methods. Together, we provide an independent strategy for genomic profiling of native R loops and help resolve discrepancies among multiple R loop mapping methods.
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