The recent breakthrough of single-cell RNA velocity methods brings attractive promises to reveal directed trajectory on cell differentiation, states transition and response to perturbations. However, the existing RNA velocity methods are often found to return erroneous results, partly due to model violation or lack of temporal regularization. Here, we present UniTVelo, a statistical framework of RNA velocity that models the dynamics of spliced and unspliced RNAs via flexible transcription activities. Uniquely, it also supports the inference of a unified latent time across the transcriptome. With ten datasets, we demonstrate that UniTVelo returns the expected trajectory in different biological systems, including hematopoietic differentiation and those even with weak kinetics or complex branches.

The recent breakthrough of single-cell RNA velocity methods brings attractive promises to reveal directed trajectory on cell differentiation, states transition and response to perturbations. However, the existing RNA velocity methods are often found to return erroneous results, partly due to model violation or lack of temporal regularization. Here, we present UniTVelo, a statistical framework of RNA velocity that models the dynamics of spliced and unspliced RNAs via flexible transcription activities. Uniquely, it also supports the inference of a unified latent time across the transcriptome. With ten datasets, we demonstrate that UniTVelo returns the expected trajectory in different biological systems, including hematopoietic differentiation and those even with weak kinetics or complex branches.

Single-cell level characterization of embryonic development is a major benchmark of human developmental biology. Spatiotemporal analysis of stem-cell-derived embryos offers conceptual and technical advances in the field. Here, we defined the single-cell spatiotemporal gene expression landscape of human embryonic development with stem-cell-derived organoids. We established the human embryonic organoid (HEMO) from expanded potential stem cells and achieved both embryonic and extraembryonic tissues in the same organoid. Time-series single-cell RNA sequencing paired with single-cell resolution spatial revealed human embryonic development signatures such as extraembryonic placenta, yolk sac hematopoiesis neural crest, blood vessels, and cardiac mesoderm. Hematopoietic tissues eventually predominated HEMO with erythropoiesis, mekagaryopiesis, and myelopoiesis. Cell-cell communication network analysis demonstrated that trophoblast-like tissues supplied WNT signaling in neural crest cells to facilitate maturation and migration. Single-cell resolution spatial transcriptomics defined the yolk sac erythro-megakaryopoietic niche. Vitronectin-integrin signaling, a major contributor to megakaryocyte maturation, was predominant in the yolk sac niche in HEMO and to human fetal samples. Overall, our study advances the spatiotemporal analysis of human embryonic development in stem-cell-derived organoids.