摘要
The cell has been primarily studied as a part of its bulk population for decades until recent breakthroughs in single-cell omics technologies. The study of the seemingly isogenic cellular populations often buries diverse cellular characteristics. Even in cells with the same cellular history,heterogeneity inherently arises due to the stochastic fluctuation of gene expression during transcription and translation or noises in signaling pathways. These hidden cell-to-cell variations can be paramount in the diagnosis and treatment of disease. For instance,the heterogeneity in tumor cells is crucial in understanding tumor initiation,progression,metastasis,and therapeutic response. A very small subpopulation of cells that may confer the most resistance in a preclinical drug test could be responsible for tumor relapse in patients after treatment. Thus,as medicine becomes more and more personalized,there is a greater desire to more accurately represent and understand single cells and the distinct subpopulations.
