bioRxivDevelopmental BiologyPreprint
Time, Space and Single-Cell Resolved Molecular Trajectory of Cell Populations and the Laterality of the Body Plan at Gastrulation
Ran WangiD, Xianfa YangiD, Jiehui CheniD, Lin ZhangiD, Jonathan A. GriffithsiD, Guizhong CuiiD, Yingying CheniD, Yun QianiD, Guangdun PengiD, Jinsong LiiD, Liantang Wang, John C. MarioniiD, Patrick TamiD, Naihe JingiD
Abstract
Understanding of the molecular drivers of lineage diversification and tissue patterning during primary germ layer development requires in-depth knowledge of the dynamic molecular trajectories of cell lineages across a series of developmental stages of gastrulation1-7. Through computational modeling, we constructed at single-cell resolution a spatio-temporal compendium of the molecular trajectories of germ-layer derivatives in gastrula-stage mouse embryos. This molecular atlas infers the developmental trajectories of single-cell populations and the molecular network activity underpinning the specification and differentiation of the germ-layer lineages. Analysis of the heterogeneity of cellular composition of cell populations at defined positions in the epiblast revealed progressive diversification of cell types, mirroring the process of lineage allocation during gastrulation. A novel observation is the difference in the contribution of cells on contralateral sides of the epiblast to mesoderm derivatives of the early organogenesis embryo, and the enhanced BMP signaling activity in right-side mesoderm of E7.5 embryo. Perturbation of BMP signaling activity at late gastrulation led to randomization of left-right (L-R) molecular asymmetry in the lateral mesoderm of early-somite-stage embryo. Our findings indicate the asymmetric BMP activity during gastrulation may be critical for the symmetry breaking process associated with specification of L-R body asymmetry ahead of the acquisition of functionality of the L-R organizer.
- organism: mouse
- assay: scRNA-seq
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 0
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