Single-cell transcriptional diversity is a hallmark of developmental potential

Single-cell RNA sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories. However, inferring both the state and direction of differentiation is challenging. Here, we demonstrate a simple, yet robust, determinant of developmental potential-the number of expressed genes per cell-and leverage this measure of transcriptional diversity to develop a computational framework (CytoTRACE) for predicting differentiation states from scRNA-seq data. When applied to diverse tissue types and organisms, CytoTRACE outperformed previous methods and nearly 19,000 annotated gene sets for resolving 52 experimentally determined developmental trajectories. Additionally, it facilitated…

• NS
  National Science Foundation

  Award: DGE-1656518
• UD
  U.S. Department of Defense

  Awards: W81XWH-12-1-0020, W81XWH-13-1-0281, W81XWH-11-1-0287
• BC
  Breast Cancer Research Foundation
• VA
  Virginia and D.K. Ludwig Fund for Cancer Research
• NC
  National Cancer Institute

  Awards: R00CA187192-03, CA09302, 5R01CA100225-09