Computational prediction of RNA structural motifs involved in posttranscriptional regulatory processes.

Proceedings of the National Academy of Sciences of the United States of America

PubMedID: 18815376

Rabani M, Kertesz M, Segal E. Computational prediction of RNA structural motifs involved in posttranscriptional regulatory processes. Proc Natl Acad Sci USA. 2008;105(39):14885-90.
Messenger RNA molecules are tightly regulated, mostly through interactions with proteins and other RNAs, but the mechanisms that confer the specificity of such interactions are poorly understood. It is clear, however, that this specificity is determined by both the nucleotide sequence and secondary structure of the mRNA. Here, we develop RNApromo, an efficient computational tool for identifying structural elements within mRNAs that are involved in specifying posttranscriptional regulations. By analyzing experimental data on mRNA decay rates, we identify common structural elements in fast-decaying and slow-decaying mRNAs and link them with binding preferences of several RNA binding proteins. We also predict structural elements in sets of mRNAs with common subcellular localization in mouse neurons and fly embryos. Finally, by analyzing pre-microRNA stem-loops, we identify structural differences between pre-microRNAs of animals and plants, which provide insights into the mechanism of microRNA biogenesis. Together, our results reveal unexplored layers of posttranscriptional regulations in groups of RNAs and are therefore an important step toward a better understanding of the regulatory information conveyed within RNA molecules. Our new RNA motif discovery tool is available online.