Abstract
BackgroundChromatin 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.ResultsWe 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.ConclusionHere 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.
Highlights
Chromatin remodeling, histone modifications and other chromatin-related processes play a crucial role in gene regulation
One uses crosslinked chromatin sheared by sonication (X-chromatin immunoprecipitation (ChIP)), and the other native chromatin digested by nucleases (NChIP)
These potential differences in background signal levels can be caused by variation in serum components and by differences in sample handling between no-antibody control (NoAb) controls and ChIP samples
Summary
Histone modifications and other chromatin-related processes play a crucial role in gene regulation. With this method the background signals, as measured with the NoAb control, are subtracted from the signals obtained from the ChIP samples. The major shortcoming of this method is the fact that the levels of background signal in the NoAb control samples may be different from those in the ChIP samples. If the signal obtained with particular antibodies is only moderately higher than the background, subtraction will influence data interpretation and should not be done. The NoAb sample is an essential control for the interpretation of ChIP signals, as it indicates the background signal level for the various primers sets in the different samples. Differences in sample handling between input and ChIP samples affect the normalization Control sequences need to be developed. The use of this normalization method can result in a random over- or under-representation of the ChIP data
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