One of the goals of good science is to explore cellular function and find even the smallest difference that can influence the biology of a system. In this study, we looked at the transcriptome of genetically identical individual cells and compared them to each other and to two different sized cell populations. Using highly sensitive template-switching (SMART; Switching Mechanism at 5' end of RNA Template) technology, it was possible to obtain high-quality RNA-seq data from individual cells. We found that the number of transcripts expressed and the overall transcriptome differed between individual cells, perhaps indicating variation in cellular status despite growth under identical conditions. This study reinforces the idea that SMART technology can robustly produce cDNA from single cells for meaningful transcriptome analysis.
Transcriptome analysis is an effective way to obtain information regarding the state of a cell or tissue under a wide variety of conditions, including development or differentiation, response to the environment or infection, or during disease (Heaton et al. 2014; Henley et al. 2013; Saliba et al. 2014). In general, RNA-seq methods require more RNA than found in a single cell, therefore, a population of cells must be used as input. RNA-seq data from a population, no matter how small, can average out or mask the minor, but potentially important, variations in individual cells (Kanter and Kalisky, 2015; Saliba et al. 2014), or may be biased by the expression pattern of a few cells (Bengtsson et al. 2005). Performing RNA-seq using individual cells reveals these differences and offers the opportunity to study and characterize diverse types of tissue and cells, such as induced pluripotent stem cells (iPS cells), circulating tumor cells, cells from solid tumor tissue, and embryonic tissue (Fort et al. 2015; Saliba et al. 2014).
Single-cell and ultra-low-input mRNA-seq have a number of technical challenges, including sample preparation and insensitive or irreproducible cDNA synthesis. In recent years, there has been tremendous progress in methods and technology for transcriptome profiling of single cells. First, sample preparation can be improved by using cells directly. In this case, highly abundant rRNA transcripts (which may account for over 90% of all RNA) can be excluded from cDNA synthesis by using an oligo(dT)-priming method. Second, sensitive and reproducible cDNA synthesis can be achieved using SMART technology. SMART technology (Figure 1) is based on non-templated nucleotides that are added by an MMLV-based reverse transcriptase (RT) when it reaches the 5' end of the mRNA during cDNA synthesis. Template switching then occurs when a specially designed Template-Switching Oligo (TSO) bearing a complementary sequence to these non-templated nucleotides hybridizes to the first-strand cDNA. The RT switches from using the mRNA as a template to using the TSO for further cDNA synthesis. This ensures that the 5' end of the mRNA is captured and allows specific sequences to be added to each end of the cDNA for simpler amplification and enrichment of full-length cDNA (Figure 1). We have been continuously refining SMART technology over the past 20 years by optimizing the reaction conditions, the TSO, and the PCR polymerase. Recently, SMART technology has been further improved in the SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing by incorporating locked nucleic acid (LNA) modifications to the TSO, as well as other optimizations. In this initial single-cell study, we show that by using the SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing, good quality mRNA-seq data can be obtained from individual cells. We compare these single-cell data with populations of either 100 or 1,000 cells, and show similarities in the quality of the data obtained, but differences in the number of transcripts identified and transcriptome profiles. Overall these results indicate that this kit is a robust tool for single-cell studies.