Phylogenetic analysis of ITS data from Endophytic fungi using Massive Parallel Bayesian Tree Inference with Exabayes

Ecological studies of fungal communities have been favored thanks to the emergence and improvement of independent culture techniques that use the ITS region as a molecular marker. This has allowed a more accurate identification compared to traditional culture-dependent methods. Next-generation seque...

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Autores Principales: Montero-Vargas, Maripaz, Umaña-Jiménez, Jean Carlo, Escudero-Leiva, Efraín, Chaverri-Echandi, Priscila
Formato: Artículo
Idioma: Inglés
Publicado: Editorial Tecnológica de Costa Rica (entidad editora) 2020
Materias:
ITS
Acceso en línea: https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/5079
https://hdl.handle.net/2238/12073
id RepoTEC12073
recordtype dspace
spelling RepoTEC120732020-09-25T23:12:53Z Phylogenetic analysis of ITS data from Endophytic fungi using Massive Parallel Bayesian Tree Inference with Exabayes Análisis Filogenético de Secuencias ITS Provenientes de Hongos Endófitos Utilizando Inferencia Bayesiana Paralela de Árboles con Exabayes Montero-Vargas, Maripaz Umaña-Jiménez, Jean Carlo Escudero-Leiva, Efraín Chaverri-Echandi, Priscila Fungi ITS Exabayes Phylogenetics Parallelization Biodiversity Hongos ITS Exabayes Filogenética Paralelización Biodiversidad Ecological studies of fungal communities have been favored thanks to the emergence and improvement of independent culture techniques that use the ITS region as a molecular marker. This has allowed a more accurate identification compared to traditional culture-dependent methods. Next-generation sequencing techniques have increased the amount of data available for the understanding of endophytic fungal communities. An important part of this process is the phylogenetic inference to decipher how the different taxa are related and interact, however, this may become one of the bioinformatic analysis that demands more time. In response to this, the bioinformatics along with high-performance computing offer solutions to accelerate and make more efficient the tools available for data processing through the implementation of supercomputers and the parallelization of tools In this study we carried out the processing of ITS sequences to then use the parallelization of Exabayes, software specialized in the analysis and creation of phylogenetic trees. Thanks to the use of this technique, it was possible to reduce the running time of Exabayes from more than 400 hours to 6 hours, which demonstrates the benefits of the use of high-performance computing platforms. Los estudios ecológicos de las comunidades fúngicas se han visto favorecidos gracias a la aparición y mejora de técnicas independientes de cultivo que utilizan la región ITS como marcador molecular. Esto ha permitido una identificación más precisa en comparación con los métodos tradicionales dependientes de la cultura. Las técnicas de secuenciación de próxima generación han aumentado la cantidad de datos disponibles para la comprensión de las comunidades de hongos endofíticos. Una parte importante de este proceso es la inferencia filogenética para descifrar cómo se relacionan e interactúan los diferentes taxones, sin embargo, este puede convertirse en uno de los análisis bioinformáticos que exige más tiempo. En respuesta a esto, la bioinformática junto con la informática de alto rendimiento ofrecen soluciones para acelerar y hacer más eficientes las herramientas disponibles para el procesamiento de datos a través de la implementación de supercomputadoras y la paralelización de herramientas. En este estudio llevamos a cabo el procesamiento de secuencias ITS para luego utilizar la paralelización de Exabayes, software especializado en el análisis y creación de árboles filogenéticos. Gracias al uso de esta técnica, fue posible reducir el tiempo de ejecución de Exabayes de más de 400 horas a 6 horas, lo que demuestra los beneficios del uso de plataformas informáticas de alto rendimiento. 2020-03-27 2020-09-25T23:12:53Z 2020-09-25T23:12:53Z info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/5079 10.18845/tm.v33i5.5079 https://hdl.handle.net/2238/12073 eng https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/5079/4801 application/pdf Editorial Tecnológica de Costa Rica (entidad editora) Tecnología en marcha Journal; 2020: Vol. 33 especial. Contribuciones a la Conferencia 6th Latin America High Performance Computing Conference (CARLA); Pág. 74-79 Revista Tecnología en Marcha; 2020: Vol. 33 especial. Contribuciones a la Conferencia 6th Latin America High Performance Computing Conference (CARLA); Pág. 74-79 2215-3241 0379-3982
institution Tecnológico de Costa Rica
collection Repositorio TEC
language Inglés
topic Fungi
ITS
Exabayes
Phylogenetics
Parallelization
Biodiversity
Hongos
ITS
Exabayes
Filogenética
Paralelización
Biodiversidad
spellingShingle Fungi
ITS
Exabayes
Phylogenetics
Parallelization
Biodiversity
Hongos
ITS
Exabayes
Filogenética
Paralelización
Biodiversidad
Montero-Vargas, Maripaz
Umaña-Jiménez, Jean Carlo
Escudero-Leiva, Efraín
Chaverri-Echandi, Priscila
Phylogenetic analysis of ITS data from Endophytic fungi using Massive Parallel Bayesian Tree Inference with Exabayes
description Ecological studies of fungal communities have been favored thanks to the emergence and improvement of independent culture techniques that use the ITS region as a molecular marker. This has allowed a more accurate identification compared to traditional culture-dependent methods. Next-generation sequencing techniques have increased the amount of data available for the understanding of endophytic fungal communities. An important part of this process is the phylogenetic inference to decipher how the different taxa are related and interact, however, this may become one of the bioinformatic analysis that demands more time. In response to this, the bioinformatics along with high-performance computing offer solutions to accelerate and make more efficient the tools available for data processing through the implementation of supercomputers and the parallelization of tools In this study we carried out the processing of ITS sequences to then use the parallelization of Exabayes, software specialized in the analysis and creation of phylogenetic trees. Thanks to the use of this technique, it was possible to reduce the running time of Exabayes from more than 400 hours to 6 hours, which demonstrates the benefits of the use of high-performance computing platforms.
format Artículo
author Montero-Vargas, Maripaz
Umaña-Jiménez, Jean Carlo
Escudero-Leiva, Efraín
Chaverri-Echandi, Priscila
author_sort Montero-Vargas, Maripaz
title Phylogenetic analysis of ITS data from Endophytic fungi using Massive Parallel Bayesian Tree Inference with Exabayes
title_short Phylogenetic analysis of ITS data from Endophytic fungi using Massive Parallel Bayesian Tree Inference with Exabayes
title_full Phylogenetic analysis of ITS data from Endophytic fungi using Massive Parallel Bayesian Tree Inference with Exabayes
title_fullStr Phylogenetic analysis of ITS data from Endophytic fungi using Massive Parallel Bayesian Tree Inference with Exabayes
title_full_unstemmed Phylogenetic analysis of ITS data from Endophytic fungi using Massive Parallel Bayesian Tree Inference with Exabayes
title_sort phylogenetic analysis of its data from endophytic fungi using massive parallel bayesian tree inference with exabayes
publisher Editorial Tecnológica de Costa Rica (entidad editora)
publishDate 2020
url https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/5079
https://hdl.handle.net/2238/12073
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score 12.140644