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RNAex: an RNA secondary structure prediction server enhanced by high-throughput structure-probing data.

ABSTRACT: Several high-throughput technologies have been developed to probe RNA base pairs and loops at the transcriptome level in multiple species. However, to obtain the final RNA secondary structure, extensive effort and considerable expertise is required to statistically process the probing data and combine them with free energy models. Therefore, we developed an RNA secondary structure prediction server that is enhanced by experimental data (RNAex). RNAex is a web interface that enables non-specialists to easily access cutting-edge structure-probing data and predict RNA secondary structures enhanced by in vivo and in vitro data. RNAex annotates the RNA editing, RNA modification and SNP sites on the predicted structures. It provides four structure-folding methods, restrained MaxExpect, SeqFold, RNAstructure (Fold) and RNAfold that can be selected by the user. The performance of these four folding methods has been verified by previous publications on known structures. We re-mapped the raw sequencing data of the probing experiments to the whole genome for each species. RNAex thus enables users to predict secondary structures for both known and novel RNA transcripts in human, mouse, yeast and Arabidopsis The RNAex web server is available at http://RNAex.ncrnalab.org/.

SUBMITTER: Wu Y

PROVIDER: S-EPMC4987914 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:To accelerate previous RNA structure probing approaches, which focus on analyzing one RNA sequence at a time, we have developed FragSeq, a high-throughput RNA structure probing method that uses high-throughput RNA sequencing to identify single-stranded RNA (ssRNA) regions from fragments generated by nuclease P1, which is specific for single-stranded nucleic acids. In the accompanying study, we show that we can accurately and simultaneously map ssRNA regions in multiple non-coding RNAs with known structure in experiments probing the entire mouse nuclear transcriptome. We carried out probing in two cell types to assess reproducibility. We also identified and experimentally validated structured regions in ncRNAs never previously probed. We examined mouse nuclear RNA from two cell types: undifferentiated embryonic stem cells (UNDIFF) and cells differentiated into neural precursors (D5NP). For each cell type, nuclear RNA was purified and deproteinized, denatured, and refolded in vitro, from which we prepared three barcoded samples: "nuclease" (RNA partially digested with P1 ssRNA-specific nuclease, yielding 5'-PO4/3'-OH end chemistry at each cleavage site), "control" (control for "nuclease" sample to idenfity endogenous 5'-PO4/3'-OH), and "PNK" (same as "control" but followed by a polynucleotide kinase treatment to convert 5'-OH/3'-cyclic-phosphate ends to clonable 5'-PO4/3'-OH ends). Resulting RNA fragments were cloned using the SOLiD Small RNA Expression Kit (SREK) protocol, which ligates linkers only to 5'-PO4/3'-OH containing RNA, enriching for clones of products resulting from P1 cleavage in "nuclease" sample and selecting against random degradation. Two cell types, three treatments each, thus resulted in six barcoded samples total (barcodes 01, 02, 04, 05, 07, 08). Four other barcoded samples were prepared for separate experiments not used in our study (barcodes 03, 06, 09, 10), so their preparation is not described here. The total run of ten barcodes was done on the ABI SOLiD3 platform and a custom algorithm (FragSeq v0.0.1) was used to compute "cutting scores" (as described in our paper) that show ssRNA regions in hundreds of ncRNAs.

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RNAex: an RNA secondary structure prediction server enhanced by high-throughput structure-probing data.

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