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 the identification of quiescent stem cells and revealed genes that contribute to breast tumorigenesis. This study thus establishes a key RNA-based feature of developmental potential and a platform for delineation of cellular hierarchies.

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Single-cell RNA-sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories. However, inferring both the state and direction of differentiation without prior knowledge has remained challenging. Here we describe a simple yet robust determinant of developmental potential-the number of detectably expressed genes per celland leverage this measure of transcriptional diversity to develop a new framework for predicting ordered differentiation states from scRNA-seq data. When evaluated on ~150,000 single-cell transcriptomes spanning 53 lineages and five species, our approach, called CytoTRACE, outperformed previous methods and ~19,000 molecular signatures for resolving experimentallyconfirmed developmental trajectories. In addition, it enabled unbiased identification of tissueresident stem cells, including cells with long-term regenerative potential. When used to analyze human breast tumors, we discovered candidate genes associated with less-differentiated luminal progenitor cells and validated GULP1 as a novel gene involved in tumorigenesis. Our study establishes a key RNA-based correlate of developmental potential and provides a new platform for robust delineation of cellular hierarchies (https://cytotrace.stanford.edu).

The appearance of jaws was a turning point in vertebrate evolution because it allowed primitive vertebrates to capture and process large, motile prey. The vertebrate jaw consists of separate dorsal and ventral skeletal elements connected by a joint. How this structure evolved from the unjointed gill bar of a jawless ancestor is an unresolved question in vertebrate evolution. To understand the developmental bases of this evolutionary transition, we examined the expression of 12 genes involved in vertebrate pharyngeal patterning in the modern jawless fish lamprey. We find nested expression of Dlx genes, as well as combinatorial expression of Msx, Hand and Gsc genes along the dorso-ventral (DV) axis of the lamprey pharynx, indicating gnathostome-type pharyngeal patterning evolved before the appearance of the jaw. In addition, we find that Bapx and Gdf5/6/7 , key regulators of joint formation in gnathostomes, are not expressed in the lamprey first arch, whereas Barx , which is absent from the intermediate first arch in gnathostomes, marks this domain in lamprey. Taken together, these data support a new scenario for jaw evolution in which incorporation of Bapx and Gdf5/6/7 into a preexisting DV patterning program drove the evolution of the jaw by altering the identity of intermediate first-arch chondrocytes. We present this “Pre-pattern/Cooption” model as an alternative to current models linking the evolution of the jaw to the de novo appearance of sophisticated pharyngeal DV patterning.

From bacteria to humans, individual cells within isogenic populations can show significant variation in stress tolerance, but the nature of this heterogeneity is not clear. To investigate this, we used single-cell RNA sequencing to quantify transcript heterogeneity in single Saccharomyces cerevisiae cells treated with and without salt stress to explore population variation and identify cellular covariates that influence the stress-responsive transcriptome. Leveraging the extensive knowledge of yeast transcriptional regulation, we uncovered significant regulatory variation in individual yeast cells, both before and after stress. We also discovered that a subset of cells appears to decouple expression of ribosomal protein genes from the environmental stress response in a manner partly correlated with the cell cycle but unrelated to the yeast ultradian metabolic cycle. Live-cell imaging of cells expressing pairs of fluorescent regulators, including the transcription factor Msn2 with Dot6, Sfp1, or MAP kinase Hog1, revealed both coordinated and decoupled nucleocytoplasmic shuttling. Together with transcriptomic analysis, our results suggest that cells maintain a cellular filter against decoupled bursts of transcription factor activation but mount a stress response upon coordinated regulation, even in a subset of unstressed cells.