The Ultimate qPCR Experiment: Producing Publication Quality, Reproducible Data the First Time.

Quantitative PCR (qPCR) is one of the most common techniques for quantification of nucleic acid molecules in biological and environmental samples. Although the methodology is perceived to be relatively simple, there are a number of steps and reagents that require optimization and validation to ensure reproducible data that accurately reflect the biological question(s) being posed. This review article describes and illustrates the critical pitfalls and sources of error in qPCR experiments, along with a rigorous, stepwise process to minimize variability, time, and cost in generating reproducible, publication quality data every time. Finally, an approach to make an informed choice between qPCR and digital PCR technologies is described.

A droplet digital PCR detection method for rare L1 insertions in tumors.

BACKGROUND: The active human mobile element, long interspersed element 1 (L1) currently populates human genomes in excess of 500,000 copies per haploid genome. Through its mobility via a process called target primed reverse transcription (TPRT), L1 mobilization has resulted in over 100 de novo cases of human disease and has recently been associated with various cancer types. Large advances in high-throughput sequencing (HTS) technology have allowed for an increased understanding of the role of L1 in human cancer; however, researchers are still limited by the ability to validate potentially rare L1 insertion events detected by HTS that may occur in only a small fraction of tumor cells. Additionally, HTS detection of rare events varies greatly as a function of read depth, and new tools for de novo element discovery are needed to fill in gaps created by HTS. RESULTS: We have employed droplet digital PCR (ddPCR) to detect rare L1 loci in mosaic human genomes. Our assay allows for the detection of L1 insertions as rare as one cell in every 10,000. CONCLUSIONS: ddPCR represents a robust method to be used alongside HTS techniques for detecting, validating and quantitating rare L1 insertion events in tumors and other tissues.