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Predict long-range enhancer regulation based on protein–protein interactions between transcription factors

Long-range regulation by distal enhancers plays critical roles in cell-type specific transcriptional programs. Computational predictions of genome-wide enhancer–promoter interactions are still challenging due to limited accuracy and the lack of knowledge on the molecular mechanisms. Based on recent...

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Autores principales: Wang, Hao, Huang, Binbin, Wang, Jianrong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8501976/
https://www.ncbi.nlm.nih.gov/pubmed/34570239
http://dx.doi.org/10.1093/nar/gkab841
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author Wang, Hao
Huang, Binbin
Wang, Jianrong
author_facet Wang, Hao
Huang, Binbin
Wang, Jianrong
author_sort Wang, Hao
collection PubMed
description Long-range regulation by distal enhancers plays critical roles in cell-type specific transcriptional programs. Computational predictions of genome-wide enhancer–promoter interactions are still challenging due to limited accuracy and the lack of knowledge on the molecular mechanisms. Based on recent biological investigations, the protein–protein interactions (PPIs) between transcription factors (TFs) have been found to participate in the regulation of chromatin loops. Therefore, we developed a novel predictive model for cell-type specific enhancer–promoter interactions by leveraging the information of TF PPI signatures. Evaluated by a series of rigorous performance comparisons, the new model achieves superior performance over other methods. The model also identifies specific TF PPIs that may mediate long-range regulatory interactions, revealing new mechanistic understandings of enhancer regulation. The prioritized TF PPIs are associated with genes in distinct biological pathways, and the predicted enhancer–promoter interactions are strongly enriched with cis-eQTLs. Most interestingly, the model discovers enhancer-mediated trans-regulatory links between TFs and genes, which are significantly enriched with trans-eQTLs. The new predictive model, along with the genome-wide analyses, provides a platform to systematically delineate the complex interplay among TFs, enhancers and genes in long-range regulation. The novel predictions also lead to mechanistic interpretations of eQTLs to decode the genetic associations with gene expression.
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spelling pubmed-85019762021-10-12 Predict long-range enhancer regulation based on protein–protein interactions between transcription factors Wang, Hao Huang, Binbin Wang, Jianrong Nucleic Acids Res Computational Biology Long-range regulation by distal enhancers plays critical roles in cell-type specific transcriptional programs. Computational predictions of genome-wide enhancer–promoter interactions are still challenging due to limited accuracy and the lack of knowledge on the molecular mechanisms. Based on recent biological investigations, the protein–protein interactions (PPIs) between transcription factors (TFs) have been found to participate in the regulation of chromatin loops. Therefore, we developed a novel predictive model for cell-type specific enhancer–promoter interactions by leveraging the information of TF PPI signatures. Evaluated by a series of rigorous performance comparisons, the new model achieves superior performance over other methods. The model also identifies specific TF PPIs that may mediate long-range regulatory interactions, revealing new mechanistic understandings of enhancer regulation. The prioritized TF PPIs are associated with genes in distinct biological pathways, and the predicted enhancer–promoter interactions are strongly enriched with cis-eQTLs. Most interestingly, the model discovers enhancer-mediated trans-regulatory links between TFs and genes, which are significantly enriched with trans-eQTLs. The new predictive model, along with the genome-wide analyses, provides a platform to systematically delineate the complex interplay among TFs, enhancers and genes in long-range regulation. The novel predictions also lead to mechanistic interpretations of eQTLs to decode the genetic associations with gene expression. Oxford University Press 2021-09-27 /pmc/articles/PMC8501976/ /pubmed/34570239 http://dx.doi.org/10.1093/nar/gkab841 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Computational Biology
Wang, Hao
Huang, Binbin
Wang, Jianrong
Predict long-range enhancer regulation based on protein–protein interactions between transcription factors
title Predict long-range enhancer regulation based on protein–protein interactions between transcription factors
title_full Predict long-range enhancer regulation based on protein–protein interactions between transcription factors
title_fullStr Predict long-range enhancer regulation based on protein–protein interactions between transcription factors
title_full_unstemmed Predict long-range enhancer regulation based on protein–protein interactions between transcription factors
title_short Predict long-range enhancer regulation based on protein–protein interactions between transcription factors
title_sort predict long-range enhancer regulation based on protein–protein interactions between transcription factors
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8501976/
https://www.ncbi.nlm.nih.gov/pubmed/34570239
http://dx.doi.org/10.1093/nar/gkab841
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