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

The ITS2 gene class shows a high sequence divergence among its members that have complicated its annotation and its use for reconstructing phylogenies at a higher taxonomical level (beyond species and genus). Several alignment strategies have been implemented to improve the ITS2 annotation quality a...

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Autores principales: Guillermin Agüero-Chapin, Aminael Sánchez-Rodríguez, Pedro I Hidalgo-Yanes, Yunierkis Pérez-Castillo, Reinaldo Molina-Ruiz, Kathleen Marchal, Vítor Vasconcelos, Agostinho Antunes
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Publicado: Public Library of Science (PLoS) 2011
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spelling oai:doaj.org-article:d21d467703db4c5886500106cf4999912021-11-18T07:35:43ZAn alignment-free approach for eukaryotic ITS2 annotation and phylogenetic inference.1932-620310.1371/journal.pone.0026638https://doaj.org/article/d21d467703db4c5886500106cf4999912011-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22046320/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203The ITS2 gene class shows a high sequence divergence among its members that have complicated its annotation and its use for reconstructing phylogenies at a higher taxonomical level (beyond species and genus). Several alignment strategies have been implemented to improve the ITS2 annotation quality and its use for phylogenetic inferences. Although, alignment based methods have been exploited to the top of its complexity to tackle both issues, no alignment-free approaches have been able to successfully address both topics. By contrast, the use of simple alignment-free classifiers, like the topological indices (TIs) containing information about the sequence and structure of ITS2, may reveal to be a useful approach for the gene prediction and for assessing the phylogenetic relationships of the ITS2 class in eukaryotes. Thus, we used the TI2BioP (Topological Indices to BioPolymers) methodology [1], [2], freely available at http://ti2biop.sourceforge.net/ to calculate two different TIs. One class was derived from the ITS2 artificial 2D structures generated from DNA strings and the other from the secondary structure inferred from RNA folding algorithms. Two alignment-free models based on Artificial Neural Networks were developed for the ITS2 class prediction using the two classes of TIs referred above. Both models showed similar performances on the training and the test sets reaching values above 95% in the overall classification. Due to the importance of the ITS2 region for fungi identification, a novel ITS2 genomic sequence was isolated from Petrakia sp. This sequence and the test set were used to comparatively evaluate the conventional classification models based on multiple sequence alignments like Hidden Markov based approaches, revealing the success of our models to identify novel ITS2 members. The isolated sequence was assessed using traditional and alignment-free based techniques applied to phylogenetic inference to complement the taxonomy of the Petrakia sp. fungal isolate.Guillermin Agüero-ChapinAminael Sánchez-RodríguezPedro I Hidalgo-YanesYunierkis Pérez-CastilloReinaldo Molina-RuizKathleen MarchalVítor VasconcelosAgostinho AntunesPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 6, Iss 10, p e26638 (2011)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Guillermin Agüero-Chapin
Aminael Sánchez-Rodríguez
Pedro I Hidalgo-Yanes
Yunierkis Pérez-Castillo
Reinaldo Molina-Ruiz
Kathleen Marchal
Vítor Vasconcelos
Agostinho Antunes
An alignment-free approach for eukaryotic ITS2 annotation and phylogenetic inference.
description The ITS2 gene class shows a high sequence divergence among its members that have complicated its annotation and its use for reconstructing phylogenies at a higher taxonomical level (beyond species and genus). Several alignment strategies have been implemented to improve the ITS2 annotation quality and its use for phylogenetic inferences. Although, alignment based methods have been exploited to the top of its complexity to tackle both issues, no alignment-free approaches have been able to successfully address both topics. By contrast, the use of simple alignment-free classifiers, like the topological indices (TIs) containing information about the sequence and structure of ITS2, may reveal to be a useful approach for the gene prediction and for assessing the phylogenetic relationships of the ITS2 class in eukaryotes. Thus, we used the TI2BioP (Topological Indices to BioPolymers) methodology [1], [2], freely available at http://ti2biop.sourceforge.net/ to calculate two different TIs. One class was derived from the ITS2 artificial 2D structures generated from DNA strings and the other from the secondary structure inferred from RNA folding algorithms. Two alignment-free models based on Artificial Neural Networks were developed for the ITS2 class prediction using the two classes of TIs referred above. Both models showed similar performances on the training and the test sets reaching values above 95% in the overall classification. Due to the importance of the ITS2 region for fungi identification, a novel ITS2 genomic sequence was isolated from Petrakia sp. This sequence and the test set were used to comparatively evaluate the conventional classification models based on multiple sequence alignments like Hidden Markov based approaches, revealing the success of our models to identify novel ITS2 members. The isolated sequence was assessed using traditional and alignment-free based techniques applied to phylogenetic inference to complement the taxonomy of the Petrakia sp. fungal isolate.
format article
author Guillermin Agüero-Chapin
Aminael Sánchez-Rodríguez
Pedro I Hidalgo-Yanes
Yunierkis Pérez-Castillo
Reinaldo Molina-Ruiz
Kathleen Marchal
Vítor Vasconcelos
Agostinho Antunes
author_facet Guillermin Agüero-Chapin
Aminael Sánchez-Rodríguez
Pedro I Hidalgo-Yanes
Yunierkis Pérez-Castillo
Reinaldo Molina-Ruiz
Kathleen Marchal
Vítor Vasconcelos
Agostinho Antunes
author_sort Guillermin Agüero-Chapin
title An alignment-free approach for eukaryotic ITS2 annotation and phylogenetic inference.
title_short An alignment-free approach for eukaryotic ITS2 annotation and phylogenetic inference.
title_full An alignment-free approach for eukaryotic ITS2 annotation and phylogenetic inference.
title_fullStr An alignment-free approach for eukaryotic ITS2 annotation and phylogenetic inference.
title_full_unstemmed An alignment-free approach for eukaryotic ITS2 annotation and phylogenetic inference.
title_sort alignment-free approach for eukaryotic its2 annotation and phylogenetic inference.
publisher Public Library of Science (PLoS)
publishDate 2011
url https://doaj.org/article/d21d467703db4c5886500106cf499991
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