RNA Detection and Visualization Methods and Protocols
With its complex and extensively regulated metabolism, the study of the RNA lifecycle demands tools that allow for the localization of RNAs to be observed either in an in situ setting or, preferably, under in vivo conditions. In RNA Detection and Vi
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1. Introduction RNA molecules undergo diverse post-transcriptional regulation of gene expression, including regulation of RNA transport and localization, mRNA translation, and RNA decay (1–3). In many cases, such post-transcriptional regulation occurs through elements on the mRNA molecule that interact with the hundreds of RNA binding proteins (RBPs) that exist in the cell (4). A wellknown example is the iron responsive element (IRE), a secondary structure RNA motif located on UTRs of members of the iron metabolism and transport pathway (5). The binding of the RBPs Irp1 and Irp2 to IRE elements affects the translation rate
Jeffrey E. Gerst (ed.), RNA Detection and Visualization: Methods and Protocols, Methods in Molecular Biology, vol. 714, DOI 10.1007/978-1-61779-005-8_28, © Springer Science+Business Media, LLC 2011
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of the mRNA, and by that coordinates the response to changing levels of iron in the environment. Other examples include a 118-nucleotide stem-loop structure through which mRNAs are transported to the yeast bud tip by the RBP She2 (6) and the RBP Sbp2 that is involved in mediating UGA redefinition from a stop codon to selenocysteine by binding specific stem-loop structures, termed SECIS elements, in the 3¢UTR of selenoproteins (7). In other cases, elements on the mRNA molecule interact with other RNAs that direct the regulatory effect. For example, the recognition and binding affinity of a microRNA to its mRNA target is determined by both the sequence and structure of the target mRNA (8–11). The examples above suggest that the post-transcriptional regulation of mRNAs is determined not only by its linear nucleotide sequence, but also by its secondary structure. Thus, a key goal is to understand the involvement of mRNA secondary structures in such regulation. One approach is to identify recurring patterns, termed motifs. However, linear sequence motifs, which are commonly found in DNA sequences, are not suitable in this case. Instead, we wish to identify motifs that combine primary and secondary structural elements, and are therefore better suited to describe functional elements in RNA molecules. We developed RNApromo (RNA prediction of motifs), a new computational method to identify short structural motifs in sets of long unaligned RNAs (12). RNApromo predicts motifs that include both primary sequence and secondary structure elements. We successfully applied RNApromo to analyze several specific sets of experimental data. First, we identified common structural elements in fast-decaying and slow-decaying mRNAs in yeast, and linked them with binding preferences of several RBPs. We also predicted structural elements in sets of mRNAs with common subcellular localization in mouse neurons and fly embryos. Finally, by analyzing pre-microRNA stem-loops, we identified structural differences between pre-microRNAs of animals and plants, which provide insights into the mechanism of microRNA biogenesis. RNApromo is therefore an important tool in the analysis of RNA sequences a
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