Background

The single-cell transcriptome is the complete set of messenger RNA (mRNA) molecules expressed in one cell. It is extremely variable and changes according to external, physical and biochemical conditions. Hence, it is the source of the biological heterogeneity, in which the cells from the same environment are similar -but not identical- to the other ones.

Due to sensitivity shortages, most of genetic studies use bulk samples, with hundreds to thousands of cells, providing only the average gene expression. This vastly limits the study of minor populations of cells, which may poses specific properties, such as drug resistance or metastatic ability in the case of cancer. Single-cell technologies enable the analysis of the transcriptome at single cell level, unraveling the complexity of heterogenic populations. These technologies have been applied not only in cancer but in many cell biology studies, including adult tissues, stem cells, immune cells; as well as other fields such as microbiology and virology (Wen and Tang, 2016; Karaiskos et al., 2017; Rato et al., 2017; Woyke et al., 2017; Zheng et al., 2017).

There are two main single-cell transcriptome approaches: mRNA sequencing and quantitative polymerase chain reaction. Although mRNA sequencing enables the study of the whole transcriptome without prior knowledge, manipulating an extremely large amount of genes can be overwhelming for novel researchers in the field; moreover high levels of bioinformatics are required (Prieto-vila et al., 2018). To counterbalance, single-cell qPCR analysis is limited to a certain number of genes, but can be analyzed as normal qPCR, being more approachable.

In our previous research, we aimed to study a drug resistant subpopulation of cells by using single-cell qPCR in breast cancer cell lines. With that purpose, we used massively parallel single-cell amplification, that allowed us the study of 96 genes at single cell level to 96 cells per run (Prieto-Vila et al., 2019). This is one of the most commonly used techniques for single-cell qPCR in which reactions are carried in specific 96-well plates, where individual samples are reverse transcribed at the same time. The C1 nanofluidics along with the Fluidigm systems, are the most commonly used systems for sc-qPCR. C1 machine is a hydrodynamic cell trap chip, formed by a net of channels where the cells are eluted and single cells are fiscally separated their size. Thanks to this system, rarely doublets are found. The 96 single cells are then eluded into 96 individual wells. On these wells lysis, reverse transcription, and pre-amplification for qPCR are carried in parallel using a very small reaction volume (Ziegenhain et al., 2017). Following, massive parallel qPCR is done by analyzing the expression of 96 genes in the 96 individual cells in a matrix-manner chip by the Fluidigm system.

In the present protocol, we provide a single-cell transcriptome analysis protocol, including experimental details to perform single-cell qPCR with the Fluidigm systems.