Establishing single cell RNA transcriptomics: a brief guide

Abstract

Single cell RNA sequencing is a tool for evaluating the specific transcriptome usage of different cell types within an organism. By tagging mRNA molecules from single cells or nuclei, a non-biased assay of the active transcriptome is captured. The method relies on high-quality cell suspensions, which can be challenging to obtain from whole organisms. While the costs per cell are rapidly falling as this technology matures, there is still a requirement for a non-trivial economic investment. Data analyses pipelines are also rapidly maturing, yet gold standards for data integration methods and trajectory inference are still lacking. Here, I review the standard procedures for generating these data from emerging models and highlight prerequisites to consider during project design, including the choice between cells and nuclei, fresh or fixed material, target capture numbers and methods, sequencing depth, and finally expected analysis outcomes.