Tracking Early Mammalian Organogenesis – Prediction and Validation of Differentiation Trajectories at Whole Organism Scale

Abstract

Early organogenesis represents a key step in animal development, where pluripotent cells divide and diversify to initiate formation of all major organs. Here, we used scRNA-Seq to profile over 300,000 single cell transcriptomes sampled in 6 hour intervals from mouse embryos between E8.5 and E9.5. Combining this dataset with our previous E6.5 to E8.5 atlas resulted in a densely-sampled time course of over 400,000 cells from early gastrulation to organogenesis. Computational lineage reconstruction at full organismal scale identified complex waves of blood and endothelial development, including a new molecular programme for somite-derived endothelium. To assess developmental fates across the primitive streak, we dissected the E7.5 primitive streak into four adjacent regions, performed scRNA-Seq and predicted cell fates computationally. We next defined early developmental state/fate relationships experimentally by a combination of orthotopic grafting, microscopic analysis of graft contribution as well as scRNA-Seq to transcriptionally determine cell fates of the grafted primitive streak regions after 24h of in vitro embryo culture. Experimentally determined fate outcomes were in good agreement with the fates predicted computationally, thus demonstrating how classical grafting experiments can be revisited to establish high-resolution cell state/fate relationships. Such interdisciplinary approaches will benefit future studies in both developmental biology as well as guide the in vitro production of cells for organ regeneration and repair.

Bespoke single cell molecular and tissue-scale analysis reveals mechanisms underpinning development and disease in complex developing cell populations

“…Implementation of perturbSuite on the T -/- chimera dataset validated our method by reproducing results from previous analyses(Guibentif et al 2021), with strong effects of T depletion on the NMP population and somitic mesoderm. Using the extended mouse gastrulation atlas(Imaz-Rosshandler et al 2023) as a reference provided more statistical power, and more effects reached statistical significance in agreement with the literature, for instance in the case of Notochord(Beddington, Rashbass, and Wilson 1992; Chesley 1935) and Allantois(Gluecksohn-Schoenheimer 1944). In addition, mesenchyme was depleted in these chimeras, and showed a delay in lineage development.…”

“…PerturbSuite is a method to infer perturbation effects in complex systems that is independent of the choice of method used to map the data to the reference data set. Here we used mutual nearest neighbours (Haghverdi et al 2018) for consistency with our reference set (Imaz-Rosshandler et al 2023). PerturbSuite is flexible enough to use any batch mapping (Hao et al 2021;Kiselev, Yiu, and Hemberg 2018;Lotfollahi et al 2022), cell lineage estimation (Lange et al 2022), and pseudotime/cell ordering method.…”

“…The mapped cell type of a cell from a chimera sample is the most frequent cell type among its 10 nearest neighbours in the extended mouse gastrulation atlas. UMAP(McInnes et al 2018) coordinates for the low- dimensional representation for visualisation, WOT scores(Schiebinger et al 2019) for the extended mouse gastrulation atlas were taken from (Imaz-Rosshandler et al 2023). Each chimeric cell was assigned the WOT scores of its nearest neighbour among the atlas cells, i.e.…”

“…A) UMAP representation of extended mouse gastrulation atlas, coloured by cell types(Imaz-Rosshandler et al 2023) (i) and stages (ii) B) Expression of T and Mixl1 in the extended mouse gastrulation atlas. C) Mapping of the WT chimera to the extended mouse gastrulation data set shows differences between tdTom + (red) and tdTom - (blue) .…”

“…Profiling the chimeric embryos using single-cell transcriptomics (scRNA-seq), in conjunction with reference single-cell atlases (Imaz-Rosshandler et al 2023) of early development opens exciting possibilities for studying the effects of perturbations during cellular diversification (Fig1B, Supp. Fig.…”