Evidence map›Paper›PMID 22046320›Full record

ArticlePloS one2011

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

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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Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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3 · Its place in the literature

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6 citing papers in PubMed.

  1. Article
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  3. Non-standard bioinformatics characterization of SARS-CoV-2.Computers in biology and medicine · 2021
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5 · Who and what money

Authors and funding

8 authors.

Guillermin Agüero-ChapinCIMAR/CIIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Porto, Portugal.
Aminael Sánchez-Rodríguez
Pedro I Hidalgo-Yanes
Yunierkis Pérez-Castillo
Reinaldo Molina-Ruiz
Kathleen Marchal
Vítor Vasconcelos
Agostinho Antunes

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

DNA, Ribosomal SpacerMolecular Sequence AnnotationPhylogenyAlgorithmsEukaryotaMethodsNeural Networks, ComputerNucleic Acid ConformationRNA FoldingDNA, Ribosomal Spacer

Identifiers

PMID22046320
PMCPMC3202569

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.