When conducting real-time PCR, you’re looking for the exact amount of a target sequence or gene in your sample. During the PCR reaction, you measure its progress by accumulation of a fluorescent signal during amplification. But there’s also a lot of background fluorescence, which you want to bypass in order to glean meaningful information from your signal.
This is where the Ct comes in. Before conducting PCR, you (or the software in your cycler) set a threshold level. This is literally a line in your graph that represents a level above background fluorescence, but that also should intersect your reaction curve somewhere in the beginning of its exponential phase (Figure 1). The spot where your reaction curve intersects your threshold line is the Ct, or “threshold cycle.” This spot shows the number of cycles it took to detect a real signal from your samples. Any real-time PCR run will have many of these curves from several samples, and therefore many Ct values.
Figure 1. Threshold level on a qPCR amplification curve.
Ct values are inverse to the amount of nucleic acid that is in your sample, and correlate to the number of copies in your sample. Lower Ct values indicate high amounts of targeted nucleic acid, while higher Ct values mean lower (and even too little) amounts of your target nucleic acid. Typically, Ct values below 29 cycles show abundant nucleic acids, and Ct values above 38 cycles indicate minimal amounts, and possibly an infection or environmental contamination. Reading the fluorescence amount at the beginning the cycle’s exponential phase is much more accurate than reading it at the reaction’s endpoint. By the time the reaction endpoint is reached, accumulated inhibitors, inactivated polymerases and limiting reagents are creating a lot of variation in endpoint values.
Your PCR instrument system will collect fluorescence data (usually from a double-strand DNA-binding dye or a dye-labeled probe) for each cycle. Once about 15 cycles has been reached, you’ll have a good idea of your background fluorescence level—this will appear as a straight line starting from the zero cycle point. The threshold level, then will be just above this, but at the point where your sample cycles start moving into exponential phase. Today, computer software calculates this exact point (and that’s the subject of another story).
Software in your cycle will also calculate and chart the Ct for your sample runs. On a graph comparing change in reactions (total reactions minus your baseline) to number of cycles, the Ct value will appear at the threshold interaction.
What could possibly go wrong?
Many factors can affect your Ct values. Some are due to biological differences in your samples (eureka!), while others are due to how various preparation steps were taken (argh!).
Fluorescence emission can be affected by pH and salt concentration in a solution. This will then, cause your change in reaction value, and therefore, your Ct.
Passive Reference Dyes
Reaction values are the ratio of the fluorescence of your FAM (reporter) dye to your ROX (passive reference) dye. Lower amounts of ROX produce higher reaction values, assuming FAM fluorescence doesn’t change.
This is dependent on the master mix performance, the assay and the sample quality (usually 90-110% efficiency is okay).
To determine efficiency, run serial dilutions with 5-log dilutions, and conduct R2 tests, a statistical analysis that shows how well one value can predict another. Your R2 value should be greater than 0.99. In addition, run at least three replicates. A higher replicate number of reactions is especially important for low copy number input.
Calling Delta Delta Ct
To truly make sure that the variations in Ct values are due to biological changes and not to technical issues, you’ll want to normalize your results. This method is known as “Delta-DeltaCt.” Here, you’ll compare Ct values of your sample to values of (one hopes) several reference control genes.
It’s important to choose a reference control gene that doesn’t change much itself. Several manufactuerers and scientist suggest genes for actin, alpha-tubulin, GAPDH or ubiquitin. It’s probably best to use at least two, so you can rule out any changes in your reference genes.
Delta-Delta Ct measures the difference between the values of your reference genes and the values of your sample. This method makes one key assumption—that the amplification (PCR) efficiencies of your reference and target samples are the same.
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