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IRES-dependent translated genes in fungi: computational prediction, phylogenetic conservation and functional association

BACKGROUND: The initiation of translation via cellular internal ribosome entry sites plays an important role in the stress response and certain physiological conditions in which canonical cap-dependent translation initiation is compromised. Currently, only a limited number of these regulatory elemen...

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Autores principales: Peguero-Sanchez, Esteban, Pardo-Lopez, Liliana, Merino, Enrique
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4678720/
https://www.ncbi.nlm.nih.gov/pubmed/26666532
http://dx.doi.org/10.1186/s12864-015-2266-x
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author Peguero-Sanchez, Esteban
Pardo-Lopez, Liliana
Merino, Enrique
author_facet Peguero-Sanchez, Esteban
Pardo-Lopez, Liliana
Merino, Enrique
author_sort Peguero-Sanchez, Esteban
collection PubMed
description BACKGROUND: The initiation of translation via cellular internal ribosome entry sites plays an important role in the stress response and certain physiological conditions in which canonical cap-dependent translation initiation is compromised. Currently, only a limited number of these regulatory elements have been experimentally identified. Notably, cellular internal ribosome entry sites lack conservation of both the primary sequence and mRNA secondary structure, rendering their identification difficult. Despite their biological importance, the currently available computational strategies to predict them have had limited success. We developed a bioinformatic method based on a support vector machine for the prediction of internal ribosome entry sites in fungi using the 5’-UTR sequences of 20 non-redundant fungal organisms. Additionally, we performed a comparative analysis and characterization of the functional relationships among the gene products predicted to be translated by this cap-independent mechanism. RESULTS: Using our method, we predicted 6,532 internal ribosome entry sites in 20 non-redundant fungal organisms. Some orthologous groups were enriched with our positive predictions. This is the case of the HSP70 chaperone family, which remarkably has two verified internal ribosome entry sites, one in humans and the other in flies. A second example is the orthologous group of the eIF4G repression protein Sbp1p, which has two homologous genes known to be translated by this cap-independent mechanism, one in mice and the other in yeast. These examples emphasize the wide conservation of these regulatory elements as a result of selective pressure. In addition, we performed a protein-protein interaction network characterization of the gene products of our positive predictions using Saccharomyces cerevisiae as a model, which revealed a highly connected and modular topology, suggesting a functional association. A remarkable example of this functional association is our prediction of internal ribosome entry sites elements in three components of the RNA polymerase II mediator complex. CONCLUSIONS: We developed a method for the prediction of cellular internal ribosome entry sites that may guide experimental and bioinformatic analyses to increase our understanding of protein translation regulation. Our analysis suggests that fungi show evolutionary conservation and functional association of proteins translated by this cap-independent mechanism. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-2266-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-46787202015-12-16 IRES-dependent translated genes in fungi: computational prediction, phylogenetic conservation and functional association Peguero-Sanchez, Esteban Pardo-Lopez, Liliana Merino, Enrique BMC Genomics Research Article BACKGROUND: The initiation of translation via cellular internal ribosome entry sites plays an important role in the stress response and certain physiological conditions in which canonical cap-dependent translation initiation is compromised. Currently, only a limited number of these regulatory elements have been experimentally identified. Notably, cellular internal ribosome entry sites lack conservation of both the primary sequence and mRNA secondary structure, rendering their identification difficult. Despite their biological importance, the currently available computational strategies to predict them have had limited success. We developed a bioinformatic method based on a support vector machine for the prediction of internal ribosome entry sites in fungi using the 5’-UTR sequences of 20 non-redundant fungal organisms. Additionally, we performed a comparative analysis and characterization of the functional relationships among the gene products predicted to be translated by this cap-independent mechanism. RESULTS: Using our method, we predicted 6,532 internal ribosome entry sites in 20 non-redundant fungal organisms. Some orthologous groups were enriched with our positive predictions. This is the case of the HSP70 chaperone family, which remarkably has two verified internal ribosome entry sites, one in humans and the other in flies. A second example is the orthologous group of the eIF4G repression protein Sbp1p, which has two homologous genes known to be translated by this cap-independent mechanism, one in mice and the other in yeast. These examples emphasize the wide conservation of these regulatory elements as a result of selective pressure. In addition, we performed a protein-protein interaction network characterization of the gene products of our positive predictions using Saccharomyces cerevisiae as a model, which revealed a highly connected and modular topology, suggesting a functional association. A remarkable example of this functional association is our prediction of internal ribosome entry sites elements in three components of the RNA polymerase II mediator complex. CONCLUSIONS: We developed a method for the prediction of cellular internal ribosome entry sites that may guide experimental and bioinformatic analyses to increase our understanding of protein translation regulation. Our analysis suggests that fungi show evolutionary conservation and functional association of proteins translated by this cap-independent mechanism. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-2266-x) contains supplementary material, which is available to authorized users. BioMed Central 2015-12-15 /pmc/articles/PMC4678720/ /pubmed/26666532 http://dx.doi.org/10.1186/s12864-015-2266-x Text en © Peguero-Sanchez et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Peguero-Sanchez, Esteban
Pardo-Lopez, Liliana
Merino, Enrique
IRES-dependent translated genes in fungi: computational prediction, phylogenetic conservation and functional association
title IRES-dependent translated genes in fungi: computational prediction, phylogenetic conservation and functional association
title_full IRES-dependent translated genes in fungi: computational prediction, phylogenetic conservation and functional association
title_fullStr IRES-dependent translated genes in fungi: computational prediction, phylogenetic conservation and functional association
title_full_unstemmed IRES-dependent translated genes in fungi: computational prediction, phylogenetic conservation and functional association
title_short IRES-dependent translated genes in fungi: computational prediction, phylogenetic conservation and functional association
title_sort ires-dependent translated genes in fungi: computational prediction, phylogenetic conservation and functional association
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4678720/
https://www.ncbi.nlm.nih.gov/pubmed/26666532
http://dx.doi.org/10.1186/s12864-015-2266-x
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