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Epigenetic features improve TALE target prediction
BACKGROUND: The yield of many crop plants can be substantially reduced by plant-pathogenic Xanthomonas bacteria. The infection strategy of many Xanthomonas strains is based on transcription activator-like effectors (TALEs), which are secreted into the host cells and act as transcriptional activators...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8717664/ https://www.ncbi.nlm.nih.gov/pubmed/34965853 http://dx.doi.org/10.1186/s12864-021-08210-z |
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author | Erkes, Annett Mücke, Stefanie Reschke, Maik Boch, Jens Grau, Jan |
author_facet | Erkes, Annett Mücke, Stefanie Reschke, Maik Boch, Jens Grau, Jan |
author_sort | Erkes, Annett |
collection | PubMed |
description | BACKGROUND: The yield of many crop plants can be substantially reduced by plant-pathogenic Xanthomonas bacteria. The infection strategy of many Xanthomonas strains is based on transcription activator-like effectors (TALEs), which are secreted into the host cells and act as transcriptional activators of plant genes that are beneficial for the bacteria.The modular DNA binding domain of TALEs contains tandem repeats, each comprising two hyper-variable amino acids. These repeat-variable diresidues (RVDs) bind to their target box and determine the specificity of a TALE.All available tools for the prediction of TALE targets within the host plant suffer from many false positives. In this paper we propose a strategy to improve prediction accuracy by considering the epigenetic state of the host plant genome in the region of the target box. RESULTS: To this end, we extend our previously published tool PrediTALE by considering two epigenetic features: (i) chromatin accessibility of potentially bound regions and (ii) DNA methylation of cytosines within target boxes. Here, we determine the epigenetic features from publicly available DNase-seq, ATAC-seq, and WGBS data in rice.We benchmark the utility of both epigenetic features separately and in combination, deriving ground-truth from RNA-seq data of infections studies in rice. We find an improvement for each individual epigenetic feature, but especially the combination of both.Having established an advantage in TALE target predicting considering epigenetic features, we use these data for promoterome and genome-wide scans by our new tool EpiTALE, leading to several novel putative virulence targets. CONCLUSIONS: Our results suggest that it would be worthwhile to collect condition-specific chromatin accessibility data and methylation information when studying putative virulence targets of Xanthomonas TALEs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12864-021-08210-z). |
format | Online Article Text |
id | pubmed-8717664 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-87176642022-01-05 Epigenetic features improve TALE target prediction Erkes, Annett Mücke, Stefanie Reschke, Maik Boch, Jens Grau, Jan BMC Genomics Research BACKGROUND: The yield of many crop plants can be substantially reduced by plant-pathogenic Xanthomonas bacteria. The infection strategy of many Xanthomonas strains is based on transcription activator-like effectors (TALEs), which are secreted into the host cells and act as transcriptional activators of plant genes that are beneficial for the bacteria.The modular DNA binding domain of TALEs contains tandem repeats, each comprising two hyper-variable amino acids. These repeat-variable diresidues (RVDs) bind to their target box and determine the specificity of a TALE.All available tools for the prediction of TALE targets within the host plant suffer from many false positives. In this paper we propose a strategy to improve prediction accuracy by considering the epigenetic state of the host plant genome in the region of the target box. RESULTS: To this end, we extend our previously published tool PrediTALE by considering two epigenetic features: (i) chromatin accessibility of potentially bound regions and (ii) DNA methylation of cytosines within target boxes. Here, we determine the epigenetic features from publicly available DNase-seq, ATAC-seq, and WGBS data in rice.We benchmark the utility of both epigenetic features separately and in combination, deriving ground-truth from RNA-seq data of infections studies in rice. We find an improvement for each individual epigenetic feature, but especially the combination of both.Having established an advantage in TALE target predicting considering epigenetic features, we use these data for promoterome and genome-wide scans by our new tool EpiTALE, leading to several novel putative virulence targets. CONCLUSIONS: Our results suggest that it would be worthwhile to collect condition-specific chromatin accessibility data and methylation information when studying putative virulence targets of Xanthomonas TALEs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12864-021-08210-z). BioMed Central 2021-12-29 /pmc/articles/PMC8717664/ /pubmed/34965853 http://dx.doi.org/10.1186/s12864-021-08210-z Text en © The Author(s) 2021 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 | Research Erkes, Annett Mücke, Stefanie Reschke, Maik Boch, Jens Grau, Jan Epigenetic features improve TALE target prediction |
title | Epigenetic features improve TALE target prediction |
title_full | Epigenetic features improve TALE target prediction |
title_fullStr | Epigenetic features improve TALE target prediction |
title_full_unstemmed | Epigenetic features improve TALE target prediction |
title_short | Epigenetic features improve TALE target prediction |
title_sort | epigenetic features improve tale target prediction |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8717664/ https://www.ncbi.nlm.nih.gov/pubmed/34965853 http://dx.doi.org/10.1186/s12864-021-08210-z |
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