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Integrating binding and expression data to predict transcription factors combined function

BACKGROUND: Transcription factor binding to the regulatory region of a gene induces or represses its gene expression. Transcription factors share their binding sites with other factors, co-factors and/or DNA-binding proteins. These proteins form complexes which bind to the DNA as one-units. The bind...

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Autores principales: Ahmed, Mahmoud, Min, Do Sik, Kim, Deok Ryong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7487729/
https://www.ncbi.nlm.nih.gov/pubmed/32894066
http://dx.doi.org/10.1186/s12864-020-06977-1
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author Ahmed, Mahmoud
Min, Do Sik
Kim, Deok Ryong
author_facet Ahmed, Mahmoud
Min, Do Sik
Kim, Deok Ryong
author_sort Ahmed, Mahmoud
collection PubMed
description BACKGROUND: Transcription factor binding to the regulatory region of a gene induces or represses its gene expression. Transcription factors share their binding sites with other factors, co-factors and/or DNA-binding proteins. These proteins form complexes which bind to the DNA as one-units. The binding of two factors to a shared site does not always lead to a functional interaction. RESULTS: We propose a method to predict the combined functions of two factors using comparable binding and expression data (target). We based this method on binding and expression target analysis (BETA), which we re-implemented in R and extended for this purpose. target ranks the factor’s targets by importance and predicts the dominant type of interaction between two transcription factors. We applied the method to simulated and real datasets of transcription factor-binding sites and gene expression under perturbation of factors. We found that Yin Yang 1 transcription factor (YY1) and YY2 have antagonistic and independent regulatory targets in HeLa cells, but they may cooperate on a few shared targets. CONCLUSION: We developed an R package and a web application to integrate binding (ChIP-seq) and expression (microarrays or RNA-seq) data to determine the cooperative or competitive combined function of two transcription factors.
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spelling pubmed-74877292020-09-16 Integrating binding and expression data to predict transcription factors combined function Ahmed, Mahmoud Min, Do Sik Kim, Deok Ryong BMC Genomics Software BACKGROUND: Transcription factor binding to the regulatory region of a gene induces or represses its gene expression. Transcription factors share their binding sites with other factors, co-factors and/or DNA-binding proteins. These proteins form complexes which bind to the DNA as one-units. The binding of two factors to a shared site does not always lead to a functional interaction. RESULTS: We propose a method to predict the combined functions of two factors using comparable binding and expression data (target). We based this method on binding and expression target analysis (BETA), which we re-implemented in R and extended for this purpose. target ranks the factor’s targets by importance and predicts the dominant type of interaction between two transcription factors. We applied the method to simulated and real datasets of transcription factor-binding sites and gene expression under perturbation of factors. We found that Yin Yang 1 transcription factor (YY1) and YY2 have antagonistic and independent regulatory targets in HeLa cells, but they may cooperate on a few shared targets. CONCLUSION: We developed an R package and a web application to integrate binding (ChIP-seq) and expression (microarrays or RNA-seq) data to determine the cooperative or competitive combined function of two transcription factors. BioMed Central 2020-09-07 /pmc/articles/PMC7487729/ /pubmed/32894066 http://dx.doi.org/10.1186/s12864-020-06977-1 Text en © The Author(s) 2020 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/. 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 in a credit line to the data.
spellingShingle Software
Ahmed, Mahmoud
Min, Do Sik
Kim, Deok Ryong
Integrating binding and expression data to predict transcription factors combined function
title Integrating binding and expression data to predict transcription factors combined function
title_full Integrating binding and expression data to predict transcription factors combined function
title_fullStr Integrating binding and expression data to predict transcription factors combined function
title_full_unstemmed Integrating binding and expression data to predict transcription factors combined function
title_short Integrating binding and expression data to predict transcription factors combined function
title_sort integrating binding and expression data to predict transcription factors combined function
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7487729/
https://www.ncbi.nlm.nih.gov/pubmed/32894066
http://dx.doi.org/10.1186/s12864-020-06977-1
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