A novel method for the normalization of ChIP-qPCR data

ChIP-qPCR permits the study of protein and chromatin interactions. The general technique can apply to the study of the interactions of protein with RNA, and the methylation state of genomic DNA. While the technique is vital to our understanding of epigenetic processes, there is much confusion around the proper normalization methods. Percent Input has recently emerged as a normalization standard, due to its reproducibility and accuracy. This method relies on the use of a constant volume of ChIP Isolate in each qPCR assay. Researchers may accidentally run qPCR assays with a constant amount of isolate, a common practice for RT-qPCR; however, the traditional Percent Input method cannot accurately normalize these data. We developed a novel method that can normalize these data to provide the same reproducible Percent Input value. Here, we present evidence that this novel method of normalizing ChIP-qPCR data works with real samples. Later, we present a mathematical proof which shows how a Percent Input value calculated from Cq (quantification cycle) values obtained from qPCR run with a constant amount (in nanograms of DNA in ChIP isolate) is equal to the traditional Percent Input calculated from quantification cycle (Cq) values obtained from running a constant volume of ChIP isolate. • Increases the number of possible data points per sample; • End values are the same % Input values as the traditional normalization method.