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Related Concept Videos

RNA Structure01:23

RNA Structure

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Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
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The basic structure of RNA consists of a string of ribonucleotides attached by phosphodiester bonds. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
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The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
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Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
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Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
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Secondary Structure Predictions for Long RNA Sequences Based on Inversion Excursions and MapReduce.

Daniel T Yehdego1, Boyu Zhang2, Vikram K R Kodimala1

  • 1The University of Texas at El Paso, El Paso, Texas 79968.

IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum : [Proceedings]. IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum
|May 30, 2015
PubMed
Summary

Predicting ribonucleic acid (RNA) secondary structures is challenging for long sequences. New methods segment RNA using inversion excursions, improving accuracy and handling pseudoknots where other programs fail.

Keywords:
HadoopPerformance analysisPrediction accuracyPseudoknotsRNA segmentation

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Area of Science:

  • Computational biology
  • Bioinformatics
  • Molecular biology

Background:

  • Ribonucleic acid (RNA) secondary structures are vital for gene expression and regulation.
  • Predicting secondary structures for long RNA sequences is computationally intensive.
  • Existing methods struggle with complex structures like pseudoknots in long RNA molecules.

Purpose of the Study:

  • To develop and evaluate novel methods for segmenting long RNA sequences to improve secondary structure prediction accuracy.
  • To address the computational limitations of predicting secondary structures for extended RNA molecules.
  • To enhance the prediction of RNA secondary structures, particularly those containing pseudoknots.

Main Methods:

  • Developed two RNA sequence segmentation methods based on inversion excursions: centered and optimized.
  • Utilized a MapReduce framework (Hadoop) for parallel processing of segmentation steps.
  • Explored inversion stem lengths and gap sizes to optimize chunking for prediction accuracy.
  • Compared prediction accuracy against non-segmented methods and known experimental structures.

Main Results:

  • The proposed segmentation methods significantly improve secondary structure prediction accuracy for long RNA sequences, especially those with pseudoknots.
  • The chunking approach successfully predicts pseudoknots in sequences where standard prediction programs fail due to length limitations.
  • Predicted structures maintain accuracy comparable to the original prediction programs against known experimental data.
  • Parallelizable steps (inversion searching, chunking, prediction) enable efficient processing.

Conclusions:

  • Segmentation of long RNA sequences based on inversion excursions offers a robust and accurate approach to secondary structure prediction.
  • This method overcomes computational barriers for predicting complex RNA structures like pseudoknots.
  • The developed techniques enhance the predictability of RNA secondary structures, maintaining high accuracy levels.