Dataset Information

A high-throughput approach to profile RNA structure.

ABSTRACT: Here we introduce the Computational Recognition of Secondary Structure (CROSS) method to calculate the structural profile of an RNA sequence (single- or double-stranded state) at single-nucleotide resolution and without sequence length restrictions. We trained CROSS using data from high-throughput experiments such as Selective 2?-Hydroxyl Acylation analyzed by Primer Extension (SHAPE; Mouse and HIV transcriptomes) and Parallel Analysis of RNA Structure (PARS; Human and Yeast transcriptomes) as well as high-quality NMR/X-ray structures (PDB database). The algorithm uses primary structure information alone to predict experimental structural profiles with >80% accuracy, showing high performances on large RNAs such as Xist (17 900 nucleotides; Area Under the ROC Curve AUC of 0.75 on dimethyl sulfate (DMS) experiments). We integrated CROSS in thermodynamics-based methods to predict secondary structure and observed an increase in their predictive power by up to 30%.

SUBMITTER: Delli Ponti R

PROVIDER: S-EPMC5389523 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A high-throughput approach to profile RNA structure.

Delli Ponti Riccardo R Marti Stefanie S Armaos Alexandros A Tartaglia Gian Gaetano GG

Nucleic acids research 20170301 5

Here we introduce the Computational Recognition of Secondary Structure (CROSS) method to calculate the structural profile of an RNA sequence (single- or double-stranded state) at single-nucleotide resolution and without sequence length restrictions. We trained CROSS using data from high-throughput experiments such as Selective 2΄-Hydroxyl Acylation analyzed by Primer Extension (SHAPE; Mouse and HIV transcriptomes) and Parallel Analysis of RNA Structure (PARS; Human and Yeast transcriptomes) as w ...[more]

PMID: 27899588

Similar Datasets

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.

Dataset Information

A high-throughput approach to profile RNA structure.

Publications

A high-throughput approach to profile RNA structure.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets