Abstract
With conventional gene expression profiling, information concerning cellular heterogeneity is often lost in the physical mixing and averaging of millions of cells. Single-cell transcriptome analysis has the potential to address these issues. However, there is a need to determine how many cells are needed to draw meaningful conclusions in each single-cell study. Here, we introduce the concept of "digital lysate" for assessing cellular heterogeneity with a phase-switch microfluidic platform and apply it to construct a molecular map of transcriptome perturbation during the cell cycle. Using a phase-switch droplet microfluidic platform and next-generation sequencing, we obtained transcriptomes of single cells by random sampling. Digital lysates were generated by permutating and averaging multiple single-cell transcriptomes. In our studied cell populations, digital lysates converged to physical lysates ( r = 0.93), and the sample-to-sample repeatability was comparable to that of conventional analysis of a physical lysate ( r = 0.98). After determining the number of cells needed, single-cell transcriptomes were used to organize cells into a map by molecular similarity, and the map was validated by cell cycle-specific markers ( p = 0.003). Cell cycle regulatory genes were inferred using this molecular map and verified with siRNA assays. The study described here provides an effective approach, the generation and analysis of digital lysates, to investigate cellular heterogeneity.