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Chromatin immunoprecipitation: optimization, quantitative analysis and data normalization

BACKGROUND: Chromatin remodeling, histone modifications and other chromatin-related processes play a crucial role in gene regulation. A very useful technique to study these processes is chromatin immunoprecipitation (ChIP). ChIP is widely used for a few model systems, including Arabidopsis, but esta...

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Autores principales: Haring, Max, Offermann, Sascha, Danker, Tanja, Horst, Ina, Peterhansel, Christoph, Stam, Maike
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2077865/
https://www.ncbi.nlm.nih.gov/pubmed/17892552
http://dx.doi.org/10.1186/1746-4811-3-11
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author Haring, Max
Offermann, Sascha
Danker, Tanja
Horst, Ina
Peterhansel, Christoph
Stam, Maike
author_facet Haring, Max
Offermann, Sascha
Danker, Tanja
Horst, Ina
Peterhansel, Christoph
Stam, Maike
author_sort Haring, Max
collection PubMed
description BACKGROUND: Chromatin remodeling, histone modifications and other chromatin-related processes play a crucial role in gene regulation. A very useful technique to study these processes is chromatin immunoprecipitation (ChIP). ChIP is widely used for a few model systems, including Arabidopsis, but establishment of the technique for other organisms is still remarkably challenging. Furthermore, quantitative analysis of the precipitated material and normalization of the data is often underestimated, negatively affecting data quality. RESULTS: We developed a robust ChIP protocol, using maize (Zea mays) as a model system, and present a general strategy to systematically optimize this protocol for any type of tissue. We propose endogenous controls for active and for repressed chromatin, and discuss various other controls that are essential for successful ChIP experiments. We experienced that the use of quantitative PCR (QPCR) is crucial for obtaining high quality ChIP data and we explain why. The method of data normalization has a major impact on the quality of ChIP analyses. Therefore, we analyzed different normalization strategies, resulting in a thorough discussion of the advantages and drawbacks of the various approaches. CONCLUSION: Here we provide a robust ChIP protocol and strategy to optimize the protocol for any type of tissue; we argue that quantitative real-time PCR (QPCR) is the best method to analyze the precipitates, and present comprehensive insights into data normalization.
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spelling pubmed-20778652007-11-15 Chromatin immunoprecipitation: optimization, quantitative analysis and data normalization Haring, Max Offermann, Sascha Danker, Tanja Horst, Ina Peterhansel, Christoph Stam, Maike Plant Methods Methodology BACKGROUND: Chromatin remodeling, histone modifications and other chromatin-related processes play a crucial role in gene regulation. A very useful technique to study these processes is chromatin immunoprecipitation (ChIP). ChIP is widely used for a few model systems, including Arabidopsis, but establishment of the technique for other organisms is still remarkably challenging. Furthermore, quantitative analysis of the precipitated material and normalization of the data is often underestimated, negatively affecting data quality. RESULTS: We developed a robust ChIP protocol, using maize (Zea mays) as a model system, and present a general strategy to systematically optimize this protocol for any type of tissue. We propose endogenous controls for active and for repressed chromatin, and discuss various other controls that are essential for successful ChIP experiments. We experienced that the use of quantitative PCR (QPCR) is crucial for obtaining high quality ChIP data and we explain why. The method of data normalization has a major impact on the quality of ChIP analyses. Therefore, we analyzed different normalization strategies, resulting in a thorough discussion of the advantages and drawbacks of the various approaches. CONCLUSION: Here we provide a robust ChIP protocol and strategy to optimize the protocol for any type of tissue; we argue that quantitative real-time PCR (QPCR) is the best method to analyze the precipitates, and present comprehensive insights into data normalization. BioMed Central 2007-09-24 /pmc/articles/PMC2077865/ /pubmed/17892552 http://dx.doi.org/10.1186/1746-4811-3-11 Text en Copyright © 2007 Haring et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology
Haring, Max
Offermann, Sascha
Danker, Tanja
Horst, Ina
Peterhansel, Christoph
Stam, Maike
Chromatin immunoprecipitation: optimization, quantitative analysis and data normalization
title Chromatin immunoprecipitation: optimization, quantitative analysis and data normalization
title_full Chromatin immunoprecipitation: optimization, quantitative analysis and data normalization
title_fullStr Chromatin immunoprecipitation: optimization, quantitative analysis and data normalization
title_full_unstemmed Chromatin immunoprecipitation: optimization, quantitative analysis and data normalization
title_short Chromatin immunoprecipitation: optimization, quantitative analysis and data normalization
title_sort chromatin immunoprecipitation: optimization, quantitative analysis and data normalization
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2077865/
https://www.ncbi.nlm.nih.gov/pubmed/17892552
http://dx.doi.org/10.1186/1746-4811-3-11
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AT peterhanselchristoph chromatinimmunoprecipitationoptimizationquantitativeanalysisanddatanormalization
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