Gene expression studies are widely diffused in life science research. So far, the most popular techniques adopted for transcript quantification are Northern blot, reverse transcription polymerase chain reaction (RT-PCR), reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR), microarrays, and RNA sequencing (RNA-seq).
These methods can be grouped according to their throughput level. Northern blot is a classic low-throughput technique, whereas RT-PCR and quantitative real-time polymerase chain reaction (qPCR) are medium-throughput techniques thanks to their ability to analyze more than one transcript at a time. High-throughput techniques are devoted to measuring levels of thousands of transcripts per assay (microarrays and RNA-seq).
Soon after the introduction of RNA-seq to the market, the running costs were extremely high, so the technique was affordable only to high-budget groups. In recent years, although equipment investments remained relevant, running costs markedly decreased. This scenario fostered the birth of companies offering RNA-seq as a service, so RNA-seq has become affordable. On one hand, RNA-seq is now so cheap that it has to be considered even when one is interested in the expression levels of only a fraction of the transcriptome. On the other hand, RT-qPCR is regularly used to measure numerous transcripts at a time. The state of the art of the techniques and platforms mentioned in this article has been reviewed recently by Devonshire et al. .
In this article the authors try to understand when RNA-seq may be economically convenient compared with RT-qPCR (even when one is interested in the expression levels of just a few genes instead of the whole transcriptome). Therefore, they determine the break-even point between the two techniques by calculating the number of genes/samples for which it is cheaper to use one or the another technique.