期刊论文详细信息
BMC Bioinformatics
New in silico approach to assessing RNA secondary structures with non-canonical base pairs
Agnieszka Rybarczyk2  Natalia Szostak1  Maciej Antczak1  Tomasz Zok1  Mariusz Popenda3  Ryszard Adamiak3  Jacek Blazewicz2  Marta Szachniuk2 
[1] Institute of Computing Science, Poznan University of Technology, Piotrowo 2, Poznan, 60-965, Poland
[2] Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, Poznan, 61-704, Poland
[3] European Center for Bioinformatics and Genomics, Poznan University of Technology, Piotrowo 2, Poznan, 60-965, Poland
关键词: RNAComposer;    RNApdbee;    Non-canonical base pairs;    Secondary structure;    RNA;   
Others  :  1229476
DOI  :  10.1186/s12859-015-0718-6
 received in 2015-02-18, accepted in 2015-08-24,  发布年份 2015
【 摘 要 】

Background

The function of RNA is strongly dependent on its structure, so an appropriate recognition of this structure, on every level of organization, is of great importance. One particular concern is the assessment of base-base interactions, described as the secondary structure, the knowledge of which greatly facilitates an interpretation of RNA function and allows for structure analysis on the tertiary level. The RNA secondary structure can be predicted from a sequence using in silico methods often adjusted with experimental data, or assessed from 3D structure atom coordinates. Computational approaches typically consider only canonical, Watson-Crick and wobble base pairs. Handling of non-canonical interactions, important for a full description of RNA structure, is still very difficult.

Results

We introduce our novel approach to assessing an extended RNA secondary structure, which characterizes both canonical and non-canonical base pairs, along with their type classification. It is based on predicting the RNA 3D structure from a user-provided sequence or a secondary structure that only describes canonical base pairs, and then deriving the extended secondary structure from atom coordinates. In our example implementation, this was achieved by integrating the functionality of two fully automated, high fidelity methods in a computational pipeline: RNAComposer for the 3D RNA structure prediction and RNApdbee for base-pair annotation.

Conclusions

The presented methodology ties together existing applications for RNA 3D structure prediction and base-pair annotation. The example performance, applying RNAComposer and RNApdbee, reveals better accuracy in non-canonical base pair assessment than the compared methods that directly predict RNA secondary structure.

【 授权许可】

   
2015 Rybarczyk et al.

附件列表
Files Size Format View
Fig. 4. 83KB Image download
Fig. 3. 61KB Image download
Fig. 2. 24KB Image download
Fig. 1. 86KB Image download
Fig. 4. 83KB Image download
Fig. 3. 61KB Image download
Fig. 2. 24KB Image download
Fig. 1. 86KB Image download
【 图 表 】

Fig. 1.

Fig. 2.

Fig. 3.

Fig. 4.

Fig. 1.

Fig. 2.

Fig. 3.

Fig. 4.

【 参考文献 】
  • [1]RNA 3D Structure Analysis and Prediction. Volume 27. Springer Berlin Heidelberg, Berlin, Heidelberg; 2012. [Nucleic Acids and Molecular Biology]
  • [2]Gesteland RF. The RNA World, Third Edition. 3rd ed. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY; 2005.
  • [3]Saenger W. Principles of Nucleic Acid Structure. Springer New York, New York, NY; 1984. [Cantor CR (Series editor): Springer Advanced Texts in Chemistry]
  • [4]Leontis NB, Westhof E. Geometric nomenclature and classification of RNA base pairs. RNA. 2001; 7:499-512.
  • [5]Parisien M, Major F. The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data. Nature. 2008; 452:51-5.
  • [6]Leontis NB, Stombaugh J, Westhof E. The non-Watson-Crick base pairs and their associated isostericity matrices. Nucleic Acids Res. 2002; 30:3497-531.
  • [7]Höner zu Siederdissen C, Bernhart SH, Stadler PF, Hofacker IL. A folding algorithm for extended RNA secondary structures. Bioinformatics. 2011; 27:i129-36.
  • [8]Yang H, Jossinet F, Leontis NB, Chen L, Westbrook J, Berman H, Westhof E. Tools for the automatic identification and classification of RNA base pairs. Nucleic Acids Res. 2003; 31:3450-60.
  • [9]Gendron P, Lemieux S, Major F. Quantitative analysis of nucleic acid three-dimensional structures1. J Mol Biol. 2001; 308:919-36.
  • [10]Lu X-J, Olson WK. 3DNA: a software package for the analysis, rebuilding and visualization of three-dimensional nucleic acid structures. Nucleic Acids Res. 2003; 31:5108-21.
  • [11]Antczak M, Zok T, Popenda M, Lukasiak P, Adamiak RW, Blazewicz J, Szachniuk M. RNApdbee—a webserver to derive secondary structures from pdb files of knotted and unknotted RNAs. Nucleic Acids Res. 2014; 42(Web Server issue):W368-72.
  • [12]Das R, Karanicolas J, Baker D. Atomic accuracy in predicting and designing noncanonical RNA structure. Nat Methods. 2010; 7:291-4.
  • [13]Dokholyan NV, Buldyrev SV, Stanley HE, Shakhnovich EI. Discrete molecular dynamics studies of the folding of a protein-like model. Fold Des. 1998; 3:577-87.
  • [14]Xu X, Zhao P, Chen S-J. Vfold: A Web Server for RNA Structure and Folding Thermodynamics Prediction. PLoS ONE. 2014; 9:e107504.
  • [15]Zhao Y, Huang Y, Gong Z, Wang Y, Man J, Xiao Y. Automated and fast building of three-dimensional RNA structures. Sci Rep. 2012;2.
  • [16]Popenda M, Szachniuk M, Antczak M, Purzycka KJ, Lukasiak P, Bartol N, et. al. Automated 3D structure composition for large RNAs. Nucleic Acids Res. 2012:gks339.
  • [17]Popenda M, Blazewicz M, Szachniuk M, Adamiak RW. RNA FRABASE version 1.0: an engine with a database to search for the three-dimensional fragments within RNA structures. Nucleic Acids Res. 2008; 36(Database issue):D386-91.
  • [18]Reuter JS, Mathews DH. RNAstructure: software for RNA secondary structure prediction and analysis. BMC Bioinformatics. 2010; 11:129. BioMed Central Full Text
  • [19]Hofacker IL, Fontana W, Stadler PF, Bonhoeffer LS, Tacker M, Schuster P. Fast folding and comparison of RNA secondary structures. Monatshefte Für Chem Chem Mon. 1994; 125:167-88.
  • [20]Do CB, Woods DA, Batzoglou S. CONTRAfold: RNA secondary structure prediction without physics-based models. Bioinformatics. 2006; 22:e90-8.
  • [21]Parisien M, Cruz JA, Westhof E, Major F. New metrics for comparing and assessing discrepancies between RNA 3D structures and models. RNA. 2009; 15:1875-85.
  • [22]Andronescu M, Bereg V, Hoos HH, Condon A. RNA STRAND: the RNA secondary structure and statistical analysis database. BMC Bioinformatics. 2008; 9:340. BioMed Central Full Text
  • [23]Kobayashi T, Nureki O, Ishitani R, Yaremchuk A, Tukalo M, Cusack S, Sakamoto K, Yokoyama S. Structural basis for orthogonal tRNA specificities of tyrosyl-tRNA synthetases for genetic code expansion. Nat Struct Biol. 2003; 10:425-32.
  • [24]Puton T, Kozlowski LP, Rother KM, Bujnicki JM. CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction. Nucleic Acids Res. 2013; 41:4307-23.
  • [25]Darty K, Denise A, Ponty Y. VARNA: Interactive drawing and editing of the RNA secondary structure. Bioinformatics. 2009; 25:1974-5.
  • [26]Lai D, Proctor JR, Zhu JYA, Meyer IM. R-CHIE: a web server and R package for visualizing RNA secondary structures. Nucleic Acids Res. 2012; 40:e95.
  • [27]Petrov AI, Zirbel CL, Leontis NB. Automated classification of RNA 3D motifs and the RNA 3D Motif Atlas. RNA. 2013.
  • [28]Rose PW, Beran B, Bi C, Bluhm WF, Dimitropoulos D, Goodsell DS, Prlic A, Quesada M, Quinn GB, Westbrook JD, Young J, Yukich B, Zardecki C, Berman HM, Bourne PE. The RCSB Protein Data Bank: redesigned web site and web services. Nucleic Acids Res. 2011; 39(Database issue):D392-401.
  • [29]Berman HM, Olson WK, Beveridge DL, Westbrook J, Gelbin A, Demeny T, Hsieh SH, Srinivasan AR, Schneider B. The Nucleic Acid Database. A comprehensive relational database of three-dimensional structures of nucleic acids. Biophys J. 1992; 63:751-9.
  • [30]Bottaro S, Di Palma F, Bussi G. The Role of Nucleobase Interactions in RNA Structure and Dynamics. Nucleic Acids Res. 2014; 42:13306-14.
  • [31]Hendrix DK, Brenner SE, Holbrook SR. RNA structural motifs: building blocks of a modular biomolecule. Q Rev Biophys. 2005; 38:221-43.
  • [32]Cruz JA, Westhof E. Sequence-based identification of 3D structural modules in RNA with RMDetect. Nat Methods. 2011; 8:513-21.
  • [33]Szostak N, Royo F, Rybarczyk A, Szachniuk M, Blazewicz J, del Sol A, Falcon-Perez JM. Sorting signal targeting mRNA into hepatic extracellular vesicles. RNA Biol. 2014; 11:836-44.
  • [34]Blazewicz J, Figlerowicz M, Kasprzak M, Nowacka M, Rybarczyk A. RNA partial degradation problem: motivation, complexity, algorithm. J Comput Biol J Comput Mol Cell Biol. 2011; 18:821-34.
  • [35]Nowacka M, Jackowiak P, Rybarczyk A, Magacz T, Strozycki PM, Barciszewski J, Figlerowicz M. 2D-PAGE as an effective method of RNA degradome analysis. Mol Biol Rep. 2012; 39:139-46.
  文献评价指标  
  下载次数:106次 浏览次数:31次