In the last few years single cell-transcriptome analysis has revolutionized our understanding of biology. Unlike bulk RNA sequencing, it enables the precise definition of cell populations within complex tissues, enabling the discovery of new cell types and cell states.
One of the major challenges for single-cell transcriptomics is the high cost and low throughput of RNA-seq per cell. The recent introduction of cell barcoding and microfluidics has dramatically decreased the cost per cell. Drop-seq is the most comprehensive and low-cost microfluidic-based method. It encapsulates individual cells into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together.
Currently Drop-seq has not been implemented in tumour tissues and its optimization in this system would provide detailed information of the multiple cell populations that coexist in a tumour, such as cancer epithelial cells, immune cells and stromal cells. Therefore, for the first time, we have optimised the Drop-seq method in breast cancer using the MMTV-PyMT mouse mammary tumour model. Here we present the standard quality checks to demonstrate that our method is robust and comparable to any other single cell RNAseq method in other well-established tissues. Our quality controls include: mixing species experiments, the analysis of the presence of mitochondrial genes, batch effects and the cell clusters generation in relation to the number of cells analysed. Technical noise has been modelled comparing fresh tumour samples before and after their incubation at 4C degrees for 24h. This last quality check is important to apply this for patient samples where a precise protocol for sample preparation would be needed.
We have now established Drop-seq in tumour tissues. This new protocol has a huge potential for the high-throughput analysis of single cells in tumours at a low cost that could be easily implemented in any lab or hospital.