RNA 3D modules in genome-wide predictions of RNA 2D structure

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Standard

RNA 3D modules in genome-wide predictions of RNA 2D structure. / Theis, Corinna; Zirbel, Craig L; Zu Siederdissen, Christian Höner; Anthon, Christian; Hofacker, Ivo L.; Nielsen, Henrik; Gorodkin, Jan.

In: PLOS ONE, Vol. 10, No. 10, e0139900, 2015.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Theis, C, Zirbel, CL, Zu Siederdissen, CH, Anthon, C, Hofacker, IL, Nielsen, H & Gorodkin, J 2015, 'RNA 3D modules in genome-wide predictions of RNA 2D structure', PLOS ONE, vol. 10, no. 10, e0139900. https://doi.org/10.1371/journal.pone.0139900

APA

Theis, C., Zirbel, C. L., Zu Siederdissen, C. H., Anthon, C., Hofacker, I. L., Nielsen, H., & Gorodkin, J. (2015). RNA 3D modules in genome-wide predictions of RNA 2D structure. PLOS ONE, 10(10), [e0139900]. https://doi.org/10.1371/journal.pone.0139900

Vancouver

Theis C, Zirbel CL, Zu Siederdissen CH, Anthon C, Hofacker IL, Nielsen H et al. RNA 3D modules in genome-wide predictions of RNA 2D structure. PLOS ONE. 2015;10(10). e0139900. https://doi.org/10.1371/journal.pone.0139900

Author

Theis, Corinna ; Zirbel, Craig L ; Zu Siederdissen, Christian Höner ; Anthon, Christian ; Hofacker, Ivo L. ; Nielsen, Henrik ; Gorodkin, Jan. / RNA 3D modules in genome-wide predictions of RNA 2D structure. In: PLOS ONE. 2015 ; Vol. 10, No. 10.

Bibtex

@article{cab97d255e494d519ff9039ff09a9bf6,
title = "RNA 3D modules in genome-wide predictions of RNA 2D structure",
abstract = "Recent experimental and computational progress has revealed a large potential for RNA structure in the genome. This has been driven by computational strategies that exploit multiple genomes of related organisms to identify common sequences and secondary structures. However, these computational approaches have two main challenges: they are computationally expensive and they have a relatively high false discovery rate (FDR). Simultaneously, RNA 3D structure analysis has revealed modules composed of non-canonical base pairs which occur in non-homologous positions, apparently by independent evolution. These modules can, for example, occur inside structural elements which in RNA 2D predictions appear as internal loops. Hence one question is if the use of such RNA 3D information can improve the prediction accuracy of RNA secondary structure at a genome-wide level. Here, we use RNAz in combination with 3D module prediction tools and apply them on a 13-way vertebrate sequence-based alignment. We find that RNA 3D modules predicted by metaRNAmodules and JAR3D are significantly enriched in the screened windows compared to their shuffled counterparts. The initially estimated FDR of 47.0% is lowered to below 25% when certain 3D module predictions are present in the window of the 2D prediction. We discuss the implications and prospects for further development of computational strategies for detection of RNA 2D structure in genomic sequence.",
author = "Corinna Theis and Zirbel, {Craig L} and {Zu Siederdissen}, {Christian H{\"o}ner} and Christian Anthon and Hofacker, {Ivo L.} and Henrik Nielsen and Jan Gorodkin",
year = "2015",
doi = "10.1371/journal.pone.0139900",
language = "English",
volume = "10",
journal = "PLoS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "10",

}

RIS

TY - JOUR

T1 - RNA 3D modules in genome-wide predictions of RNA 2D structure

AU - Theis, Corinna

AU - Zirbel, Craig L

AU - Zu Siederdissen, Christian Höner

AU - Anthon, Christian

AU - Hofacker, Ivo L.

AU - Nielsen, Henrik

AU - Gorodkin, Jan

PY - 2015

Y1 - 2015

N2 - Recent experimental and computational progress has revealed a large potential for RNA structure in the genome. This has been driven by computational strategies that exploit multiple genomes of related organisms to identify common sequences and secondary structures. However, these computational approaches have two main challenges: they are computationally expensive and they have a relatively high false discovery rate (FDR). Simultaneously, RNA 3D structure analysis has revealed modules composed of non-canonical base pairs which occur in non-homologous positions, apparently by independent evolution. These modules can, for example, occur inside structural elements which in RNA 2D predictions appear as internal loops. Hence one question is if the use of such RNA 3D information can improve the prediction accuracy of RNA secondary structure at a genome-wide level. Here, we use RNAz in combination with 3D module prediction tools and apply them on a 13-way vertebrate sequence-based alignment. We find that RNA 3D modules predicted by metaRNAmodules and JAR3D are significantly enriched in the screened windows compared to their shuffled counterparts. The initially estimated FDR of 47.0% is lowered to below 25% when certain 3D module predictions are present in the window of the 2D prediction. We discuss the implications and prospects for further development of computational strategies for detection of RNA 2D structure in genomic sequence.

AB - Recent experimental and computational progress has revealed a large potential for RNA structure in the genome. This has been driven by computational strategies that exploit multiple genomes of related organisms to identify common sequences and secondary structures. However, these computational approaches have two main challenges: they are computationally expensive and they have a relatively high false discovery rate (FDR). Simultaneously, RNA 3D structure analysis has revealed modules composed of non-canonical base pairs which occur in non-homologous positions, apparently by independent evolution. These modules can, for example, occur inside structural elements which in RNA 2D predictions appear as internal loops. Hence one question is if the use of such RNA 3D information can improve the prediction accuracy of RNA secondary structure at a genome-wide level. Here, we use RNAz in combination with 3D module prediction tools and apply them on a 13-way vertebrate sequence-based alignment. We find that RNA 3D modules predicted by metaRNAmodules and JAR3D are significantly enriched in the screened windows compared to their shuffled counterparts. The initially estimated FDR of 47.0% is lowered to below 25% when certain 3D module predictions are present in the window of the 2D prediction. We discuss the implications and prospects for further development of computational strategies for detection of RNA 2D structure in genomic sequence.

U2 - 10.1371/journal.pone.0139900

DO - 10.1371/journal.pone.0139900

M3 - Journal article

C2 - 26509713

VL - 10

JO - PLoS ONE

JF - PLoS ONE

SN - 1932-6203

IS - 10

M1 - e0139900

ER -

ID: 151492615