Simultaneous prediction of RNA secondary structure and helix coaxial stacking

<p>Abstract</p> <p>Background</p> <p>RNA secondary structure plays a scaffolding role for RNA tertiary conformation. Accurate secondary structure prediction can not only identify double-stranded helices and single stranded-loops but also help provide information for pot...

Full description

Bibliographic Details
Main Authors: Shareghi Pooya, Wang Yingfeng, Malmberg Russell, Cai Liming
Format: Article
Language:English
Published: BMC 2012-06-01
Series:BMC Genomics
id doaj-c92e9ae661f746bf8b76a52ac8ca2636
record_format Article
spelling doaj-c92e9ae661f746bf8b76a52ac8ca26362020-11-25T02:34:11ZengBMCBMC Genomics1471-21642012-06-0113Suppl 3S710.1186/1471-2164-13-S3-S7Simultaneous prediction of RNA secondary structure and helix coaxial stackingShareghi PooyaWang YingfengMalmberg RussellCai Liming<p>Abstract</p> <p>Background</p> <p>RNA secondary structure plays a scaffolding role for RNA tertiary conformation. Accurate secondary structure prediction can not only identify double-stranded helices and single stranded-loops but also help provide information for potential tertiary interaction motifs critical to the 3D conformation. The average accuracy in <it>ab initio </it>prediction remains 70%; performance improvement has only been limited to short RNA sequences. The prediction of tertiary interaction motifs is difficult without multiple, related sequences that are usually not available. This paper presents research that aims to improve the secondary structure prediction performance and to develop a capability to predict coaxial stacking between helices. Coaxial stacking positions two helices on the same axis, a tertiary motif present in almost all junctions that account for a high percentage of RNA tertiary structures.</p> <p>Results</p> <p>This research identified energetic rules for coaxial stacks and geometric constraints on stack combinations, which were applied to developing an efficient dynamic programming application for simultaneous prediction of secondary structure and coaxial stacking. Results on a number of non-coding RNA data sets, of short and moderately long lengths, show a performance improvement (specially on tRNAs) for secondary structure prediction when compared with existing methods. The program also demonstrates a capability for prediction of coaxial stacking.</p> <p>Conclusions</p> <p>The significant leap of performance on tRNAs demonstrated in this work suggests that a breakthrough to a higher performance in RNA secondary structure prediction may lie in understanding contributions from tertiary motifs critical to the structure, as such information can be used to constrain geometrically as well as energetically the space of RNA secondary structure.</p>
collection DOAJ
language English
format Article
sources DOAJ
author Shareghi Pooya
Wang Yingfeng
Malmberg Russell
Cai Liming
spellingShingle Shareghi Pooya
Wang Yingfeng
Malmberg Russell
Cai Liming
Simultaneous prediction of RNA secondary structure and helix coaxial stacking
BMC Genomics
author_facet Shareghi Pooya
Wang Yingfeng
Malmberg Russell
Cai Liming
author_sort Shareghi Pooya
title Simultaneous prediction of RNA secondary structure and helix coaxial stacking
title_short Simultaneous prediction of RNA secondary structure and helix coaxial stacking
title_full Simultaneous prediction of RNA secondary structure and helix coaxial stacking
title_fullStr Simultaneous prediction of RNA secondary structure and helix coaxial stacking
title_full_unstemmed Simultaneous prediction of RNA secondary structure and helix coaxial stacking
title_sort simultaneous prediction of rna secondary structure and helix coaxial stacking
publisher BMC
series BMC Genomics
issn 1471-2164
publishDate 2012-06-01
description <p>Abstract</p> <p>Background</p> <p>RNA secondary structure plays a scaffolding role for RNA tertiary conformation. Accurate secondary structure prediction can not only identify double-stranded helices and single stranded-loops but also help provide information for potential tertiary interaction motifs critical to the 3D conformation. The average accuracy in <it>ab initio </it>prediction remains 70%; performance improvement has only been limited to short RNA sequences. The prediction of tertiary interaction motifs is difficult without multiple, related sequences that are usually not available. This paper presents research that aims to improve the secondary structure prediction performance and to develop a capability to predict coaxial stacking between helices. Coaxial stacking positions two helices on the same axis, a tertiary motif present in almost all junctions that account for a high percentage of RNA tertiary structures.</p> <p>Results</p> <p>This research identified energetic rules for coaxial stacks and geometric constraints on stack combinations, which were applied to developing an efficient dynamic programming application for simultaneous prediction of secondary structure and coaxial stacking. Results on a number of non-coding RNA data sets, of short and moderately long lengths, show a performance improvement (specially on tRNAs) for secondary structure prediction when compared with existing methods. The program also demonstrates a capability for prediction of coaxial stacking.</p> <p>Conclusions</p> <p>The significant leap of performance on tRNAs demonstrated in this work suggests that a breakthrough to a higher performance in RNA secondary structure prediction may lie in understanding contributions from tertiary motifs critical to the structure, as such information can be used to constrain geometrically as well as energetically the space of RNA secondary structure.</p>
work_keys_str_mv AT shareghipooya simultaneouspredictionofrnasecondarystructureandhelixcoaxialstacking
AT wangyingfeng simultaneouspredictionofrnasecondarystructureandhelixcoaxialstacking
AT malmbergrussell simultaneouspredictionofrnasecondarystructureandhelixcoaxialstacking
AT cailiming simultaneouspredictionofrnasecondarystructureandhelixcoaxialstacking
_version_ 1724809805297614848