RNAs enact many diverse cellular functions which are often performed by specific RNA structures that mediate interactions with cellular factors, coordinate regulatory events, or in some cases perform catalysis of central biochemical reactions. RNA structure probing coupled to high-throughput sequencing is used to help determine these structures and construct models of functional RNA folds. By measuring the reactivities of nucleotides in an RNA to the chemical probes, properties of an RNA fold such as regions that are structured or unstructured can be elucidated. However, at present, RNA structure probing suffers from many limitations, including a lack of approaches that can be used to standardize measured experimental reactivities against extrinsic experimental factors that contribute to measurement noise. Because of this, mostly ad hoc normalization schemes have been used to account for these factors which has resulted in a limitation on our understanding and interpretation of reactivities. In addition, these procedures cannot accurately standardize reactivities to a defined and understood quantitative reactivity scale and therefore cause underlying intrinsic RNA structural information to be lost. Our long-term goal is to address these existing limitations. Here we propose to create an approach to standardizing experimentally determined RNA chemical probing reactivities to a quantitatively defined scale that can be used to extract meaningful and reproducible data between experiments and across labs. This standardization approach will allow a more quantitative understanding of chemical probing reactivity to be developed that will improve downstream computational approaches that use this data for RNA structural modeling. This approach will also allow for increased data sharing, understanding and integration with complementary omics datasets that interrogate additional features of RNA biochemistry beyond structure. As chemical probing is being increasingly used to address longstanding and new questions about the role of RNA structure across the cell, we anticipate these developments to contribute to a deeper understanding of RNA folding, RNA-protein interactions, RNA folding dynamics, shifts in the structural populations of RNA, and even changes in structure due to RNA modifications.
RNA is increasingly linked to human diseases through mutations in RNA sequences, mis-folding of RNA structures, mis-splicing of messenger RNA, defects in ribonucleoprotein enzymes, and its roles in key pathways of pathogenic microbes. Our ability to uncover the structural basis of these roles is directly related to our ability to accurately, reproducibly and quantitatively characterize RNA structures in a range of contexts. This program will make strides towards achieving this goal for a new generation of high-throughput RNA structure characterization methods by developing new calibration standards that can be used to facilitate comparison and integration of structural data across laboratories to uncover a rigorous, quantitative understanding of the data generated by these techniques.
