The cell is the fundamental unit of life, in which the blueprint of the genome is transcribed and translated into biological function. Most of our current understanding of the genome and transcriptome is based on analysis of millions of cells as a bulk population. These analyses are highly informative but they do not provide information of the heterogeneity and molecular dynamics that occur within a population of cells, nor any information of an underrepresented cell subpopulation that could have a differential or crucial function in a specific biological context. Thus, single cell analysis is, without doubt, an invaluable approach to understand fundamental biology in embryonic development, normal organs and disease.

Single-cell “omics” techniques ranging from isolation methods like flow cytometry, laser capture microdissection and microfluidics to PCR-based methods and next-generation sequencing are used to understand these processes. In the last four years there has been an exponential growth and advances in methods of isolation single cells (in particular with microfluidics), whole genome or transcriptome amplification and genome-wide analyses platforms (primarily next-generation sequencing devices and chemistry) leading to major advances in understanding single-cell biology. In particular, single-cell transcriptomics is the best-established area in single-cell omics and many different methodologies have been developed in order to improve the quality of the data as well as the number of cells analysed.

Here, I will review the major technological developments achieved in single cell transcriptomics as well as the technical challenges to overcome with a particular focus on the do’s and don’ts to ensure high quality data.