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Predicting functionality of protein–DNA interactions by integrating diverse evidence

Chromatin immunoprecipitation (ChIP-chip) experiments enable capturing physical interactions between regulatory proteins and DNA in vivo. However, measurement of chromatin binding alone is not sufficient to detect regulatory interactions. A detected binding event may not be biologically relevant, or...

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Detalles Bibliográficos
Autores principales: Ucar, Duygu, Beyer, Andreas, Parthasarathy, Srinivasan, Workman, Christopher T.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2687967/
https://www.ncbi.nlm.nih.gov/pubmed/19477979
http://dx.doi.org/10.1093/bioinformatics/btp213
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author Ucar, Duygu
Beyer, Andreas
Parthasarathy, Srinivasan
Workman, Christopher T.
author_facet Ucar, Duygu
Beyer, Andreas
Parthasarathy, Srinivasan
Workman, Christopher T.
author_sort Ucar, Duygu
collection PubMed
description Chromatin immunoprecipitation (ChIP-chip) experiments enable capturing physical interactions between regulatory proteins and DNA in vivo. However, measurement of chromatin binding alone is not sufficient to detect regulatory interactions. A detected binding event may not be biologically relevant, or a known regulatory interaction might not be observed under the growth conditions tested so far. To correctly identify physical interactions between transcription factors (TFs) and genes and to determine their regulatory implications under various experimental conditions, we integrated ChIP-chip data with motif binding sites, nucleosome occupancy and mRNA expression datasets within a probabilistic framework. This framework was specifically tailored for the identification of functional and non-functional DNA binding events. Using this, we estimate that only 50% of condition-specific protein–DNA binding in budding yeast is functional. We further investigated the molecular factors determining the functionality of protein–DNA interactions under diverse growth conditions. Our analysis suggests that the functionality of binding is highly condition-specific and highly dependent on the presence of specific cofactors. Hence, the joint analysis of both, functional and non-functional DNA binding, may lend important new insights into transcriptional regulation. Contact: workman@cbs.dtu.dk
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spelling pubmed-26879672009-06-02 Predicting functionality of protein–DNA interactions by integrating diverse evidence Ucar, Duygu Beyer, Andreas Parthasarathy, Srinivasan Workman, Christopher T. Bioinformatics Ismb/Eccb 2009 Conference Proceedings June 27 to July 2, 2009, Stockholm, Sweden Chromatin immunoprecipitation (ChIP-chip) experiments enable capturing physical interactions between regulatory proteins and DNA in vivo. However, measurement of chromatin binding alone is not sufficient to detect regulatory interactions. A detected binding event may not be biologically relevant, or a known regulatory interaction might not be observed under the growth conditions tested so far. To correctly identify physical interactions between transcription factors (TFs) and genes and to determine their regulatory implications under various experimental conditions, we integrated ChIP-chip data with motif binding sites, nucleosome occupancy and mRNA expression datasets within a probabilistic framework. This framework was specifically tailored for the identification of functional and non-functional DNA binding events. Using this, we estimate that only 50% of condition-specific protein–DNA binding in budding yeast is functional. We further investigated the molecular factors determining the functionality of protein–DNA interactions under diverse growth conditions. Our analysis suggests that the functionality of binding is highly condition-specific and highly dependent on the presence of specific cofactors. Hence, the joint analysis of both, functional and non-functional DNA binding, may lend important new insights into transcriptional regulation. Contact: workman@cbs.dtu.dk Oxford University Press 2009-06-15 2009-05-27 /pmc/articles/PMC2687967/ /pubmed/19477979 http://dx.doi.org/10.1093/bioinformatics/btp213 Text en © 2009 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Ismb/Eccb 2009 Conference Proceedings June 27 to July 2, 2009, Stockholm, Sweden
Ucar, Duygu
Beyer, Andreas
Parthasarathy, Srinivasan
Workman, Christopher T.
Predicting functionality of protein–DNA interactions by integrating diverse evidence
title Predicting functionality of protein–DNA interactions by integrating diverse evidence
title_full Predicting functionality of protein–DNA interactions by integrating diverse evidence
title_fullStr Predicting functionality of protein–DNA interactions by integrating diverse evidence
title_full_unstemmed Predicting functionality of protein–DNA interactions by integrating diverse evidence
title_short Predicting functionality of protein–DNA interactions by integrating diverse evidence
title_sort predicting functionality of protein–dna interactions by integrating diverse evidence
topic Ismb/Eccb 2009 Conference Proceedings June 27 to July 2, 2009, Stockholm, Sweden
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2687967/
https://www.ncbi.nlm.nih.gov/pubmed/19477979
http://dx.doi.org/10.1093/bioinformatics/btp213
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