MorphoSeq: Full Single-Cell Transcriptome Dynamics Up to Gastrulation in a Chordate

Area of Science:

• Developmental Biology
• Genomics
• Computational Biology

Background:

• Single-cell RNA sequencing (scRNA-seq) advances cellular diversity and trajectory analysis.
• Current methods struggle to fully map spatial organization and cellular composition in developing embryos.

Purpose of the Study:

• To create a comprehensive digital reconstruction of an embryo.
• To map genome-wide gene expression trajectories for every cell and lineage up to gastrulation.
• To stratify single cells into types using an unbiased computational framework.

Main Methods:

• Integration of scRNA-seq and light-sheet imaging data.
• Development of a computational framework for unbiased cell type stratification.
• Analysis of transcriptome data to map cell position and lineage history.

Main Results:

• A canonical digital embryo of Phallusia mammillata was reconstructed.
• Complete genome-wide gene expression history was mapped for all cells and divisions in 18 lineages.
• High reproducibility was observed between symmetric embryo sides, alongside significant inter-embryonic variability.

Conclusions:

• The digital embryo provides unprecedented resolution of cellular development and gene expression.
• The study highlights both conserved developmental processes and sources of variability in embryogenesis.
• This approach offers a powerful tool for studying early embryonic development.