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.

Pleiotrophin (PTN) is a secreted growth factor that induces neurite outgrowth and is mitogenic for fibroblasts, epithelial, and endothelial cells. During tumor growth PTN can serve as an angiogenic factor and drive tumor invasion and metastasis. To identify a receptor for PTN, we panned a phage display human cDNA library against immobilized PTN protein as a bait. From this we isolated a phage insert that was homologous to an amino acid sequence stretch in the extracellular domain (ECD) of the orphan receptor tyrosine kinase anaplastic lymphoma kinase (ALK). In parallel with PTN, ALK is highly expressed during perinatal development of the nervous system and down-modulated in the adult. Animal studies demonstrated that PTN can serve as a ratelimiting angiogenic factor during tumor growth, invasion, and metastasis (8 -12). Clinical studies showed elevated serum levels and tumor expression of PTN in samples from patients with colon, stomach, pancreatic, and breast cancer (5, 13). Furthermore, PTN has been implicated in neonatal brain development as well as in neurodegenerative disorders (reviewed in Ref. 14).Obviously, understanding of PTN-mediated signal transduction as well as identification of a receptor for PTN would enhance studies on the biology and pathology of this growth factor family. Our previous studies have shown that the activation of mitogen-activated protein kinase and PI 3-kinase pathways is required for mitogenic activity of PTN, and we had found that the adaptor molecule Shc participated in signal transduction (15). Based on the work of different laboratories in various cell types, it was hypothesized that proteins of 170 -220 kDa that are tyrosine-phosphorylated in response to PTN could be part of the receptor complex (15-17). More recently, several cell membrane-located proteins were shown to bind PTN at low affinity and serve as potential coreceptors or modulators of signal transduction (18 -21), but none of these molecules carried the hallmarks of a signal transducing receptor predicted from the earlier work.To identify a receptor for PTN, we rationalized that panning of a phage display cDNA library against immobilized PTN as a bait would allow us to isolate phage containing a ligand binding fragment of the receptor on their surface. Because of the high levels of expression of PTN during the perinatal development of the nervous system, we hypothesized that fetal brain would most likely also express a PTN receptor. We therefore panned a human fetal brain cDNA phage display library over several rounds against purified PTN that had been tested for biological activity (15). From this we isolated a phage insert homologous to an amino acid sequence stretch in the ECD of the receptor tyrosine kinase anaplastic lymphoma kinase (ALK), a recently described orphan receptor with an apparent molecular mass of

No abstract

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).