Reconstructing developmental trajectories using latent dynamical systems and time-resolved transcriptomics.

The snapshot nature of single-cell transcriptomics presents a challenge for studying the dynamics of cell fate decisions. Metabolic labeling and splicing can provide temporal information at single-cell level, but current methods have limitations. Here, we present a framework that overcomes these limitations: experimentally, we developed sci-FATE2, an optimized method for metabolic labeling with increased data quality, which we used to profile 45,000 embryonic stem (ES) cells differentiating into neural tube identities. Computationally, we developed a two-stage framework for dynamical modeling: VelvetVAE, a variational autoencoder (VAE) for velocity inference that outperforms all other tools tested, and VelvetSDE, a neural stochastic differential equation (nSDE) framework for simulating trajectory distributions. These recapitulate underlying dataset distributions and capture features such as decision boundaries between alternative fates and fate-specific gene expression. These methods recast single-cell analyses from descriptions of observed data to models of the dynamics that generated them, providing a framework for investigating developmental fate decisions.

A dynamical perspective: moving towards mechanism in single-cell transcriptomics.

As the field of single-cell transcriptomics matures, research is shifting focus from phenomenological descriptions of cellular phenotypes to a mechanistic understanding of the gene regulation underneath. This perspective considers the value of capturing dynamical information at single-cell resolution for gaining mechanistic insight; reviews the available technologies for recording and inferring temporal information in single cells; and explores whether better dynamical resolution is sufficient to adequately capture the causal relationships driving complex biological systems. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

Active growth signaling promotes senescence and cancer cell sensitivity to CDK7 inhibition.

Tumor growth is driven by continued cellular growth and proliferation. Cyclin-dependent kinase 7's (CDK7) role in activating mitotic CDKs and global gene expression makes it therefore an attractive target for cancer therapies. However, what makes cancer cells particularly sensitive to CDK7 inhibition (CDK7i) remains unclear. Here, we address this question. We show that CDK7i, by samuraciclib, induces a permanent cell-cycle exit, known as senescence, without promoting DNA damage signaling or cell death. A chemogenetic genome-wide CRISPR knockout screen identified that active mTOR (mammalian target of rapamycin) signaling promotes samuraciclib-induced senescence. mTOR inhibition decreases samuraciclib sensitivity, and increased mTOR-dependent growth signaling correlates with sensitivity in cancer cell lines. Reverting a growth-promoting mutation in PIK3CA to wild type decreases sensitivity to CDK7i. Our work establishes that enhanced growth alone promotes CDK7i sensitivity, providing an explanation for why some cancers are more sensitive to CDK inhibition than normally growing cells.

Single-cell transcriptome profiling of the human developing spinal cord reveals a conserved genetic programme with human-specific features.

The spinal cord receives input from peripheral sensory neurons and controls motor output by regulating muscle innervating motor neurons. These functions are carried out by neural circuits comprising molecularly distinct neuronal subtypes generated in a characteristic spatiotemporal arrangement from progenitors in the embryonic neural tube. To gain insight into the diversity and complexity of cells in the developing human neural tube, we used single-cell mRNA sequencing to profile cervical and thoracic regions in four human embryos of Carnegie stages (CS) CS12, CS14, CS17 and CS19 from gestational weeks 4-7. Analysis of progenitor and neuronal populations from the neural tube and dorsal root ganglia identified dozens of distinct cell types and facilitated the reconstruction of the differentiation pathways of specific neuronal subtypes. Comparison with mouse revealed overall similarity of mammalian neural tube development while highlighting some human-specific features. These data provide a catalogue of gene expression and cell type identity in the human neural tube that will support future studies of sensory and motor control systems. The data can be explored at https://shiny.crick.ac.uk/scviewer/neuraltube/.

RNA-directed activation of cytoplasmic dynein-1 in reconstituted transport RNPs.

Polarised mRNA transport is a prevalent mechanism for spatial control of protein synthesis. However, the composition of transported ribonucleoprotein particles (RNPs) and the regulation of their movement are poorly understood. We have reconstituted microtubule minus end-directed transport of mRNAs using purified components. A Bicaudal-D (BicD) adaptor protein and the RNA-binding protein Egalitarian (Egl) are sufficient for long-distance mRNA transport by the dynein motor and its accessory complex dynactin, thus defining a minimal transport-competent RNP. Unexpectedly, the RNA is required for robust activation of dynein motility. We show that a cis-acting RNA localisation signal promotes the interaction of Egl with BicD, which licenses the latter protein to recruit dynein and dynactin. Our data support a model for BicD activation based on RNA-induced occupancy of two Egl-binding sites on the BicD dimer. Scaffolding of adaptor protein assemblies by cargoes is an attractive mechanism for regulating intracellular transport.