An alignment-free approach for eukaryotic ITS2 annotation and phylogenetic inference

PLoS ONE

Volumn 6, Issue 10, 2011, Pages

  Agüero Chapin, Guillermin ^a,b,c   Sánchez Rodríguez, Aminael ^d   Hidalgo Yanes, Pedro I ^b,e   Pérez Castillo, Yunierkis ^b   Molina Ruiz, Reinaldo ^b   Marchal, Kathleen ^d   Vasconcelos, Vítor ^a,c   Antunes, Agostinho ^a,c  

^a UNIVERSITY OF PORTO   (Portugal)

^b CENTRAL UNIVERSITY OF LAS VILLAS   (Cuba)

^c UNIVERSITY OF PORTO   (Portugal)

^d UNIVERSITY OF LEUVEN   (Belgium)

^e UNIVERSITY OF LEÓN   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; CLASSIFICATION; CONTROLLED STUDY; DNA STRUCTURE; EUKARYOTE; FUNGAL GENE; FUNGUS IDENTIFICATION; FUNGUS ISOLATION; GENE ISOLATION; GENE SEQUENCE; HIDDEN MARKOV MODEL; INTERNAL TRANSCRIBED SPACER 2 GENE; NONHUMAN; NUCLEOTIDE SEQUENCE; PHYLOGENY; PREDICTION; PROTEIN FOLDING; PROTEIN SECONDARY STRUCTURE; RNA STRUCTURE; SEQUENCE ALIGNMENT; TAXONOMY;

ALGORITHMS; DNA, RIBOSOMAL SPACER; EUKARYOTA; METHODS; MOLECULAR SEQUENCE ANNOTATION; NEURAL NETWORKS (COMPUTER); NUCLEIC ACID CONFORMATION; PHYLOGENY; RNA FOLDING;

EUKARYOTA; FUNGI;

EID: 80055061063     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0026638     Document Type: Article

References (66)

1. Aguero-Chapin G, Perez-Machado G, Molina-Ruiz R, Perez-Castillo Y, Morales-Helguera A, et al. (2011) TI2BioP: Topological Indices to BioPolymers. Its practical use to unravel cryptic bacteriocin-like domains. Amino Acids 40: 431-442.
2. Aguero-Chapin G, de la Riva GA, Molina-Ruiz R, Sanchez-Rodriguez A, Perez-Machado G, et al. (2011) Non-linear models based on simple topological indices to identify RNase III protein members. J Theor Biol 273: 167-178.
3. Strope PK, Moriyama EN, (2007) Simple alignment-free methods for protein classification: a case study from G-protein-coupled receptors. Genomics 89: 602-612.
4. Finn RD, Mistry J, Tate J, Coggill P, Heger A, et al. (2009) The Pfam protein families database. Nucleic Acids Res.
5. de Jong A, van Hijum SA, Bijlsma JJ, Kok J, Kuipers OP, (2006) BAGEL: a web-based bacteriocin genome mining tool. Nucleic Acids Res 34: W273-279.
6. Selig C, Wolf M, Muller T, Dandekar T, Schultz J, (2008) The ITS2 Database II: homology modelling RNA structure for molecular systematics. Nucleic Acids Res 36: D377-380.
7. Chou KC, (2009) Automated prediction of protein attributes and its impact to biomedicine and drug discovery. In: Alterovitz G, Benson R, Ramoni MF, editors. Automation in Proteomics and Genomics: An Engineering Case-Based Approach (Harvard-MIT interdisciplinary special studies courses) UK Wiley & Sons pp. 97-143.
8. Perez-Bello A, Munteanu CR, Ubeira FM, De Magalhaes AL, Uriarte E, et al. (2009) Alignment-free prediction of mycobacterial DNA promoters based on pseudo-folding lattice network or star-graph topological indices. J Theor Biol 256: 458-466.
9. Schultz J, Maisel S, Gerlach D, Müller T, Wolf M, (2005) A common core of secondary structure of the internal transcribed spacer 2 (ITS2) throughout the Eukaryota. RNA 11: 361-364.
10. Koetschan C, Forster F, Keller A, Schleicher T, Ruderisch B, et al. (2009) The ITS2 Database III-sequences and structures for phylogeny. Nucleic Acids Res.
11. Schultz J, Müller T, Achtziger M, Seibel P, Dandekar T, et al. (2006) The internal transcribed spacer 2 database-a web server for (not only) low level phylogenetic analyses. Nucleic Acids Research 34.
12. Keller A, Schleicher T, Schultz J, Muller T, Dandekar T, et al. (2009) 5.8S-28S rRNA interaction and HMM-based ITS2 annotation. Gene 430: 50-57.
13. Nandy A, (1996) Two-dimensional graphical representation of DNA sequences and intron-exon discrimination in intron-rich sequences. Comput Appl Biosci 12: 55-62.
14. Nandy A, (2009) Empirical relationship between intra-purine and intra-pyrimidine differences in conserved gene sequences. PLoS One 4: e6829.
15. Mathews DH, (2006) RNA secondary structure analysis using RNAstructure. Curr Protoc Bioinformatics Chapter 12: Unit 12 16.
16. Thompson JD, Higgins DG, Gibson TJ, (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 22: 4673-4680.
17. Subramanian AR, Kaufmann M, Morgenstern B, (2008) DIALIGN-TX: greedy and progressive approaches for segment-based multiple sequence alignment. Algorithms Mol Biol 3: 6.
18. Katoh K, Kuma K, Miyata T, Toh H, (2005) Improvement in the accuracy of multiple sequence alignment program MAFFT. Genome Inform 16: 22-33.
19. Nilsson RH, Kristiansson E, Ryberg M, Hallenberg N, Larsson KH, (2008) Intraspecific ITS variability in the kingdom fungi as expressed in the international sequence databases and its implications for molecular species identification. Evol Bioinform Online 4: 193-201.
20. Qi FH, Jing TZ, Wang ZX, Zhan YG, (2009) Fungal endophytes from Acer ginnala Maxim: isolation, identification and their yield of gallic acid. Lett Appl Microbiol 49: 98-104.
21. Molina R, Agüero-Chapin G, Pérez-González MP, (2009) TI2BioP (Topological Indices to BioPolymers) version 1.0: Molecular Simulation and Drug Design (MSDD), Chemical Bioactives Center, Central University of Las Villas, Cuba.
22. Estrada E, (2000) On the topological sub-structural molecular design (TOSS-MODE) in QSPR/QSAR and drug design research. SAR QSAR Environ Res 11: 55-73.
23. Gutierrez Y, Estrada E, (2002) MODESLAB 1.0 (Molecular DEScriptors LABoratory) for Windows.
24. Aguero-Chapin G, Gonzalez-Diaz H, Molina R, Varona-Santos J, Uriarte E, et al. (2006) Novel 2D maps and coupling numbers for protein sequences. The first QSAR study of polygalacturonases; isolation and prediction of a novel sequence from Psidium guajava L. FEBS Lett 580: 723-730.
25. Agüero-Chapin G, Varona-Santos J, Riva Gdl, Antunes A, González-Villa T, et al. (2009) Alignment-Free Prediction of Polygalacturonases with Pseudofolding Topological Indices: Experimental Isolation from Coffea arabica and prediction of a New Sequence. J Proteome Res 8: 2122-2128.
26. González-Díaz H, Molina-Ruiz R, Hernandez I, (2007) MARCH-INSIDE v3.0 (MARkov CHains INvariants for SImulation & DEsign). 3.0 ed. pp. Windows supported version under request to the main author contact email: gonzalezdiazh@yahoo.es.
27. Pesole G, Liuni S, Grillo G, Licciulli F, Larizza A, et al. (2000) UTRdb and UTRsite: specialized databases of sequences and functional elements of 5′ and 3′ untranslated regions of eukaryotic mRNAs. Nucleic Acids Res 28: 193-196.
28. Needleman SB, Wunsch CD, (1970) A general method applicable to the search for similarities in the amino acid sequence of two proteins. J Mol Biol 48: 443-453.
29. Smith TF, Waterman MS, (1981) Identification of common molecular subsequences. J Mol Biol 147: 195-197.
30. Mathews DH, (2005) Predicting a set of minimal free energy RNA secondary structures common to two sequences. Bioinformatics 21: 2246-2253.
31. Estrada E, (1996) Spectral Moments of the Edge Adjacency Matrix in Molecular Graphs. 1. Definition and Applications to the Prediction of Physical Properties of Alkanes†. J Chem Inf Comput Sci 36: 844-849.
32. Estrada E, (1997) Spectral Moments of the Edge-Adjacency Matrix of Molecular Graphs. 2. Molecules Containing Heteroatoms and QSAR Applications. J Chem Inf Comput Sci 37: 320-328.
33. Cornell WD, Cieplak P, IBayly C, Gould IR, Merz KWJ, et al. (1995) A second generation force field for the simulation of proteins, nucleic acids, and organic molecules. J Am Chem Soc 117: 5179-5197.
34. Statsoft (2007) STATISTICA 7.0 (data analysis software system for windows). version 7.0 ed.
35. Meneses-Marcel A, Marrero-Ponce Y, Machado-Tugores Y, Montero-Torres A, Pereira DM, et al. (2005) A linear discrimination analysis based virtual screening of trichomonacidal lead-like compounds: outcomes of in silico studies supported by experimental results. Bioorg Med Chem Lett 15: 3838-3843.
36. Marrero-Ponce Y, Castillo-Garit JA, Olazabal E, Serrano HS, Morales A, et al. (2005) Atom, atom-type and total molecular linear indices as a promising approach for bioorganic and medicinal chemistry: theoretical and experimental assessment of a novel method for virtual screening and rational design of new lead anthelmintic. Bioorg Med Chem 13: 1005-1020.
37. Marrero-Ponce Y, Diaz HG, Zaldivar VR, Torrens F, Castro EA, (2004) 3D-chiral quadratic indices of the 'molecular pseudograph's atom adjacency matrix' and their application to central chirality codification: classification of ACE inhibitors and prediction of sigma-receptor antagonist activities. Bioorg Med Chem 12: 5331-5342.
38. Ponce YM, Diaz HG, Zaldivar VR, Torrens F, Castro EA, (2004) 3D-chiral quadratic indices of the 'molecular pseudograph's atom adjacency matrix' and their application to central chirality codification: classification of ACE inhibitors and prediction of sigma-receptor antagonist activities. Bioorg Med Chem 12: 5331-5342.
39. Kutner MH, Nachtsheim CJ, Neter J, Li W, (2005) Standardized Multiple Regression Model. Applied Linear Statistical Models. Fifth ed New York McGraw Hill pp. 271-277.
40. Sokolova M, Japkowicz N, Szpakowicz S., Beyond Accuracy, F-Score and ROC: A Family of Discriminant Measures for Performance Evaluation. pp. 1015-1021.
41. Zupan J, Gasteiger J, (1999) Neural Networks in Chemistry and Drug Design: An Introduction Weinheim Wiley-VCH.
42. Gotoh O, (1982) An improved algorithm for matching biological sequences. J Mol Biol 162: 705-708.
43. Krogh ABM, Mian IS, Sjeander K, Haussler D, (1994) Hidden Markov models in computational biology. Applications to protein modeling. J Mol Biol 235: 1501-1531.
44. Sacks W, Nurnberger T, Hahlbrock K, Scheel D, (1995) Molecular characterization of nucleotide sequences encoding the extracellular glycoprotein elicitor from Phytophthora megasperma. Mol Gen Genet 246: 45-55.
45. White TJ, Bruns T, Lee S, Taylor J, (1990) Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In: Innis MA, Gelfand DH, Sninsky JJ, White TJ, editors. PCR Protocols: A Guide to Methods and Applications San Diego Academic Press pp. 315-322.
46. Aguero-Chapin G, Varona-Santos J, de la Riva GA, Antunes A, Gonzalez-Vlla T, et al. (2009) Alignment-free prediction of polygalacturonases with pseudofolding topological indices: experimental isolation from Coffea arabica and prediction of a new sequence. J Proteome Res 8: 2122-2128.
47. Gonzalez-Diaz H, Aguero-Chapin G, Varona J, Molina R, Delogu G, et al. (2007) 2D-RNA-coupling numbers: a new computational chemistry approach to link secondary structure topology with biological function. J Comput Chem 28: 1049-1056.
48. Aguero-Chapin G, Gonzalez-Diaz H, de la Riva G, Rodriguez E, Sanchez-Rodriguez A, et al. (2008) MMM-QSAR recognition of ribonucleases without alignment: comparison with an HMM model and isolation from Schizosaccharomyces pombe, prediction, and experimental assay of a new sequence. J Chem Inf Model 48: 434-448.
49. Rumelhart DE, McClelland JL, (1986) Parallel distributed processing: Explorations in the microstructure of cognition Cambridge, MA MIT Press.
50. Gonzalez-Diaz H, Gonzalez-Diaz Y, Santana L, Ubeira FM, Uriarte E, (2008) Proteomics, networks and connectivity indices. Proteomics 8: 750-778.
51. Gonzalez-Diaz H, Aguero-Chapin G, Varona-Santos J, Molina R, de la Riva G, et al. (2005) 2D RNA-QSAR: assigning ACC oxidase family membership with stochastic molecular descriptors; isolation and prediction of a sequence from Psidium guajava L. Bioorg Med Chem Lett 15: 2932-2937.
52. Schattner P, (2002) Searching for RNA genes using base-composition statistics. Nucleic Acids Res 30: 2076-2082.
53. Wong TK, Lam TW, Sung WK, Yiu SM, (2010) Adjacent nucleotide dependence in ncRNA and order-1 SCFG for ncRNA identification. PLoS One 5.
54. Rivals I, Personnaz L, (1999) On cross validation for model selection. Neural Comput 11: 863-870.
55. Caballero J, Fernandez M, (2008) Artificial neural networks from MATLAB in medicinal chemistry. Bayesian-regularized genetic neural networks (BRGNN): application to the prediction of the antagonistic activity against human platelet thrombin receptor (PAR-1). Curr Top Med Chem 8: 1580-1605.
56. Fernandez M, Caballero J, Fernandez L, Abreu JI, Garriga M, (2007) Protein radial distribution function (P-RDF) and Bayesian-Regularized Genetic Neural Networks for modeling protein conformational stability: chymotrypsin inhibitor 2 mutants. J Mol Graph Model 26: 748-759.
57. Fernandez M, Caballero J, Fernandez L, Sarai A, (2010) Genetic algorithm optimization in drug design QSAR: Bayesian-regularized genetic neural networks (BRGNN) and genetic algorithm-optimized support vectors machines (GA-SVM). Mol Divers.
58. Winters-Hilt S, (2006) Hidden Markov model variants and their application. BMC Bioinformatics 7 (Suppl 2): S14.
59. Sieber TN., Endophytic fungi in forest trees: are they mutualists? Fungal Biology Reviews 21: 75-89.
60. Nagano Y, Elborn JS, Millar BC, Walker JM, Goldsmith CE, et al. (2009) Comparison of techniques to examine the diversity of fungi in adult patients with cystic fibrosis. Med Mycol pp. 1-12.
61. Von Arx JA, (1981) The Genera of Fungi Sporulating in Pure Culture: Lubrecht & Cramer Ltd.
62. Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ, (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucl Acids Res 25: 3389-3402.
63. Bisby F, Roskov Y, Ruggiero M, Orrell T, Paglinawan L, et al. (2007) Species 2000 & ITIS Catalogue of Life: 2007 Annual Checklist Taxonomic Classification. CD-ROM; Species 2000: Reading, U.K.
64. Katoh K, Kuma K, Toh H, Miyata T, (2005) MAFFT version 5: improvement in accuracy of multiple sequence alignment. Nucleic Acids Res 33: 511-518.
65. Kirk PM, Cannon PF, Stalpers JA, (2008) The dictionary of the Fungi; In: Paul MKirk, Paul FCannon, David WMinter, Stalpers aJA, editors. UK CABI.
66. Arx von J, Müller E, (1975) A re-evaluation of the bitunicate ascomycetes with keys to families and genera. Studies in Mycology 9: 1-159.