ChIP-qPCR and Data Analysis

Introduction to ChIP-qPCR

Quantitative real-time PCR (qPCR) allows you to quantify DNA concentrations from multiple samples in real time by analyzing fluorescent signal intensities that are proportional to the amount of amplicon after completing the chromatin immunoprecipitation (ChIP) assay and sample purification. In qPCR, DNA samples are incubated with primers, polymerases, oligonucleotides, and detection fluorophores such as TaqMan^® (fluorescent donor:quencher hybridization) probes or SYBR^® Green intercalating dye (no specific probe required). The DNA sample undergoes cycles of amplification via DNA polymerase in which products from the previous cycle become templates for the next cycle, thus doubling the amplified DNA in each cycle, in the most optimal reactions. For successful analysis, ensure that your primers amplify the intended sequence with efficiency over 95% and that they do not form dimers that may diminish the specific signal from qPCR based on SYBR^® Green technology.

Download the % Input and Fold Enrichment calculation spreadsheet

Two commonly used detection methods for qPCR are SYBR^® Green technology and TaqMan^® probe technology. SYBR^® Green is a DNA-binding dye that drastically increases in fluorescence when bound to double-stranded DNA. The fluorescent signal, therefore, increases as the number of copies of double-stranded DNA increases. Detection can also be achieved with TaqMan^® probes. In this method, a reporter fluorophore and a quencher fluorophore are incorporated into a single, sequence-specific probe that recognizes your PCR amplicon. In the free probe, the signal from the reporter is quenched by proximity to the quencher fluorophore. Upon hybridization to the amplicon, the 5’→3’ exonuclease activity of the DNA polymerase will degrade the probe, releasing free fluorophore in proportion to the amount of template molecules available for hybridization. In both of the above qPCR techniques, fluorescent signal follows a linear phase, followed by a plateau phase when one component of the reaction becomes rate-limiting.

Comparison of SYBR^® Green and TaqMan^® Detection Methods for ChIP-qPCR

qPCR Tip

Before you begin qPCR you must reverse the crosslinks in both your input and test samples with proteinase K and heat. In some cases you may need to purify your DNA by performing a solvent (phenol:chloroform) extraction.

Fluorescent signals indicate the cycle threshold (Ct)* for each sample. The Ct is the point of the linear phase at which the fluorescent signal exceeds the background. The Ct depends on the amount of DNA in your sample. If your sample contains relatively high amounts of DNA target, fewer cycles will be required to exceed background and the Ct will be low. Conversely, if the quantity of your DNA target is low, more cycles will occur before Ct is achieved. ChIP analysis by qPCR works best when starting with more dilute DNA samples (as opposed to highly concentrated templates which can inhibit Taq polymerase when present in high concentrations). Therefore, follow available protocols describing typical volumes of ChIP’d DNA to analyze by qPCR, such as 2µL out of 50 µL ChIP sample, to avoid introducing PCR inhibitors into the reaction.

*NOTE: Current guidelines from the “Minimum Information for Publication of Quantitative Real-Time PCR Experiments” (MIQE) advise that “quantification cycle” (Cq) should be used in place of “cycle threshold” (Ct) when reporting qPCR data. For more information on this topic as well as recommendations on appropriate controls to run, standards for data analysis, and error reporting, visit http://www.rdml.org/miqe.php.

Determine the Efficiency of qPCR Reactions

To extract meaningful information from your qPCR analysis, it is important to measure certain parameters to ensure that the assay is working properly. First, test the efficiency (E) of the qPCR reaction. The efficiency of the qPCR reaction is typically expressed as a percentage value, and indicates the percentage of the template that is being amplified in each cycle. The best way to test the reaction efficiency is to generate a standard curve by running five-point serial dilutions of a sample of known concentration and plotting the corresponding Ct values to generate a standard curve.

For the DNA standard used for the qPCR optimization experiments, you can use fragmented, purified genomic DNA, or more conveniently, DNA isolated from your chromatin as your Input sample. This Input sample can be a small percentage (2 to 5%) of the total chromatin sample. The chromatin sample should be proteinase K-digested, crosslink-reversed, and purified to provide a suitable control material for assay development or efficiency calculation. In qPCR instrumentation software, the efficiency is often automatically calculated and reported if you select your sample type as “Standard”.

The efficiency of the reaction can be calculated by the formula:

Efficiency (E) =10^{-1/slope of standard curve}

% Efficiency = (E-1) x 100

For an optimized reaction, the efficiency should be from 95 to 105%. If your efficiency is not within this range, you may need to explore potential sources of experimental error:

1. Run at least three replicates of each dilution and possibly adjust the dilution
2. Use optimized buffers
   • a. Use a commercial mastermix if possible to enable more consistent results.
   • b. Run a sample containing no DNA to test buffers for contaminants
3. Use well-designed primers — ideally, Ct values should be between 18 and 30.
4. If your efficiency is still suboptimal, consider the following possible causes of inefficiency:
   • a. Amplicon is too big (keep it between 65 and 150 bases)
   • b. Poor primer integrity (use fresh primers)
   • c. Primers too concentrated (change primer dilution to avoid dimers)
   • d. Contamination from phenol, salts, or ethanol in the template DNA
   • e. Inappropriate instrument baseline or threshold settings
   • f. Contamination in no-template control (use dedicated pipettes, UV-irradiated equipment, fresh Milli-Q^® water, etc., and setup in separate room)

ChIP-qPCR Data Analysis

There are two approaches to analyzing qPCR data: absolute quantification and relative quantification.

Absolute quantification

Absolute quantification allows the determination of how much DNA is in a given quantity of sample, without performing comparative analyses with other samples. For this analysis you should do the following:

1. Prepare serial dilutions of a sample of known concentration (quantitated, purified Input DNA)
2. Include at least three replicates for each dilution
3. Run these standards alongside your test sample(s)
4. Construct a standard curve of the log quantities of sample versus the Ct values obtained from the qPCR analysis
5. Perform a regression analysis to determine the equation of the standard curve and use this equation to calculate the quantity of DNA in your unknown sample(s).

The quantity of target DNA in the test sample should fall within the linear dynamic range of the qPCR assay. If this is not the case, adjust the dilutions of the standard sample and repeat the experiment.

The fitted value derived from the extrapolated Ct measurement can be reported as “nanograms DNA recovered,” “percent of input,” “copy number,” “mean quantity,” as well as other variations that describe number of molecules. Most commonly, “percent of input” is utilized when using Input DNA as the standard in relative standard curve method.

Relative quantification

In relative quantification analysis, the test sample is expressed as a fold change relative to a control sample (immunoprecipitated using normal purified IgG or mock IP). The test sample may also be expressed as a percentage of a reference gene that is known to maintain constant expression levels under the conditions of the experiment, similar to the use of “housekeeping” protein in Western blot analyses, or housekeeping gene cDNAs for qRT-PCR expression analysis. DNA loci known to be unoccupied by the immunoprecipitated protein (negative locus) can be used in this manner as a reference gene compared to known, occupied, positive control DNA loci.

1. Calculate the percent of input for each ChIP:
   %Input = 2^{(-ΔCt [normalized ChIP])}
2. Normalize the positive locus ΔCt values to negative locus (ΔΔCt) by subtracting the ΔCt value obtained for the positive locus from the ΔCt value for negative locus:
   (^{ΔΔCt = ΔCt}positive – ^ΔCtnegative)
3. Calculate the fold enrichment of the positive locus sequence in ChIP DNA over the negative locus:
   Fold enrichment =2^ΔΔCt