RNA motif discovery by SHAPE and mutational profiling (SHAPE-MaP).

Abstract

Many biological processes are RNA-mediated, but higher-order structures for most RNAs are unknown, making it difficult to understand how RNA structure governs function. Here we describe SHAPE mutational profiling (SHAPE-MaP) that makes possible de novo and large-scale identification of RNA functional motifs. Sites of 2’-hydroxyl acylation by SHAPE are encoded as non-complementary nucleotides during cDNA synthesis, as measured by massively parallel sequencing. SHAPE-MaP-guided modeling identified greater than 90% of accepted base pairs in complex RNAs of known structure and was used to define a second-generation model for the HIV-1 RNA genome. The HIV-1 model contains all known structured motifs and previously unknown elements, including experimentally validated pseudoknots. SHAPE-MaP yields accurate and high-resolution secondary structure models, enables analysis of low abundance RNAs, disentangles sequence polymorphisms in single experiments, and will ultimately democratize RNA structure analysis.