Imaging the transcriptome

Mol Syst Biol. 9: 710It is well known that genetically identical cells can display a high variability in their gene expression profiles. This phenomenon has a profound impact on a myriad of cellular processes, ranging from differentiation to signaling and drug resistance. Large efforts are therefore currently devoted to understand the mechanistic causes and functional consequences of cell‐to‐cell variability, often called noise (Lionnet and Singer, 2012).There are multiple sources of cell‐to‐cell variability: cell cycle stage, circadian clock, metastable epigenetic states, fluctuations in the concentration of regulatory factors, inhomogeneous microenvironments, or the stochastic nature of the molecular steps involved in gene expression. These factors are often hard to separate experimentally because they might be unknown a priori and are often challenging to control: they can range from intracellular concentrations of upstream factors to cell shape or extracellular context.As most genetic circuits involve a vast number of genes, it has proven extremely useful to study genome‐wide transcriptomes in order to understand the determinants of gene expression variability. The first applications of microarray profiling to single cells were demonstrated a decade ago (Klein et al , 2002), and RNAseq‐based methods have recently contributed to increase the assay sensitivity. As a result, these technologies can now map expression data onto …