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RepBox: a toolbox for the identification of repetitive elements
BACKGROUND: Transposable elements (TEs) are short, mobile DNA elements that are known to play important roles in the genomes of many eukaryotic species. The identification and categorization of these elements is a critical task for many genomic studies, and the continued increase in the number of de...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10463291/ https://www.ncbi.nlm.nih.gov/pubmed/37608271 http://dx.doi.org/10.1186/s12859-023-05419-5 |
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author | Burkes-Patton, Shelvasha Cooper, Elizabeth A. Schlueter, Jessica |
author_facet | Burkes-Patton, Shelvasha Cooper, Elizabeth A. Schlueter, Jessica |
author_sort | Burkes-Patton, Shelvasha |
collection | PubMed |
description | BACKGROUND: Transposable elements (TEs) are short, mobile DNA elements that are known to play important roles in the genomes of many eukaryotic species. The identification and categorization of these elements is a critical task for many genomic studies, and the continued increase in the number of de novo assembled genomes demands new tools to improve the efficiency of this process. For this reason, we developed RepBox, a suite of Python scripts that combine several pre-existing family-specific TE detection methods into a single user-friendly pipeline. RESULTS: Based on comparisons of RepBox with the standard TE detection software RepeatModeler, we find that RepBox consistently classifies more elements and is also able to identify a more diverse array of TE families than the existing methods in plant genomes. CONCLUSIONS: The performance of RepBox on two different plant genomes indicates that our toolbox represents a significant improvement over existing TE detection methods, and should facilitate future TE annotation efforts in additional species. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05419-5. |
format | Online Article Text |
id | pubmed-10463291 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-104632912023-08-30 RepBox: a toolbox for the identification of repetitive elements Burkes-Patton, Shelvasha Cooper, Elizabeth A. Schlueter, Jessica BMC Bioinformatics Software BACKGROUND: Transposable elements (TEs) are short, mobile DNA elements that are known to play important roles in the genomes of many eukaryotic species. The identification and categorization of these elements is a critical task for many genomic studies, and the continued increase in the number of de novo assembled genomes demands new tools to improve the efficiency of this process. For this reason, we developed RepBox, a suite of Python scripts that combine several pre-existing family-specific TE detection methods into a single user-friendly pipeline. RESULTS: Based on comparisons of RepBox with the standard TE detection software RepeatModeler, we find that RepBox consistently classifies more elements and is also able to identify a more diverse array of TE families than the existing methods in plant genomes. CONCLUSIONS: The performance of RepBox on two different plant genomes indicates that our toolbox represents a significant improvement over existing TE detection methods, and should facilitate future TE annotation efforts in additional species. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05419-5. BioMed Central 2023-08-22 /pmc/articles/PMC10463291/ /pubmed/37608271 http://dx.doi.org/10.1186/s12859-023-05419-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Burkes-Patton, Shelvasha Cooper, Elizabeth A. Schlueter, Jessica RepBox: a toolbox for the identification of repetitive elements |
title | RepBox: a toolbox for the identification of repetitive elements |
title_full | RepBox: a toolbox for the identification of repetitive elements |
title_fullStr | RepBox: a toolbox for the identification of repetitive elements |
title_full_unstemmed | RepBox: a toolbox for the identification of repetitive elements |
title_short | RepBox: a toolbox for the identification of repetitive elements |
title_sort | repbox: a toolbox for the identification of repetitive elements |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10463291/ https://www.ncbi.nlm.nih.gov/pubmed/37608271 http://dx.doi.org/10.1186/s12859-023-05419-5 |
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