Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells

Abstract

In the last decade, genome-wide transcriptome analyses have been routinely used to monitor tissue-, disease- and cell type-specific gene expression, but it has been technically challenging to generate expression profiles from single cells. Here we describe a novel and robust mRNA-Seq protocol (Smart-Seq) that is applicable down to single cell levels. Compared with existing methods, Smart-Seq has improved read coverage across transcripts, which significantly enhances detailed analyses of alternative transcript isoforms and identification of SNPs. We have determined the sensitivity and quantitative accuracy of Smart-Seq for single-cell transcriptomics by evaluating it on total RNA dilution series. Applying Smart-Seq to circulating tumor cells from melanomas, we identified distinct gene expression patterns, including new candidate biomarkers for melanoma circulating tumor cells. Importantly, our protocol can easily be utilized for addressing fundamental biological problems requiring genome-wide transcriptome profiling in rare cells.

Somatosensory neuron types identified by high-coverage single-cell RNA-sequencing and functional heterogeneity

“…By single-cell PCR, Chiu et al identified six subgroups of DRG neurons [25]. Single-cell RNA-seq enables a better understanding of a cell's transcriptome [26][27][28][29][30][31][32][33]. Usoskin et al performed low-coverage single-cell RNA-seq (3 574 ± 2 010 genes per neuron) and classified the mouse DRG neurons into two PEP types, three NP types, TH type and five NF200-positive types within the traditional classification framework [34].…”

Single‐cell technologies to study the immune system

“…In the past 6 years, five main methods have been developed and optimized to reverse transcribe the mRNA and amplify the cDNA from one single cell to achieve a better coverage and a lower cost per cell6, 7, 8, 9, 10, 11, 12, 13, 14 (Table 2). A parallel development of multiple algorithms has taken place in order to deal with the huge amount of data these new experiments have produced 15.…”

Application of omic technologies in cancer research

“…26 RNA-sequencing platforms can also be used to focus on specific elements of the transcriptome, such as miRNAs, and can enable a closer interrogation of actively translated genes by screening transcripts that are bound to ribosomes using ribosome profiling. 27 Recent advances have enabled the analysis of the transcriptome of single cells, 28 which can improve the understanding through selection of unique entities within a heterogeneous cell population. The development of RNA-sequencing approaches for the measurement of whole transcriptomes 26 enables users to analyse a sample for approximately £500.…”

“…The development of RNA-sequencing approaches for the measurement of whole transcriptomes 26 enables users to analyse a sample for approximately £500. A novel development enables the user to analyse the transcriptome of single cells, 29 which can be applied in a broad field of research such as the study of circulating tumour cells 28 or induced pluripotent stem cells. 30 Ren et al 31 used the RNA-seq technology for the profiling of Chinese prostate cancer patients and healthy tissue to elucidate underlying variations between races.…”