MorphoSeq: Full Single-Cell Transcriptome Dynamics Up to Gastrulation in a Chordate.
IF: 66.850
Cited by: 35


Single-cell RNA sequencing (scRNA-seq) provides a leap forward in resolving cellular diversity and developmental trajectories but fails to comprehensively delineate the spatial organization and precise cellular makeup of individual embryos. Here, we reconstruct from scRNA-seq and light sheet imaging data a canonical digital embryo that captures the genome-wide gene expression trajectory of every single cell at every cell division in the 18 lineages up to gastrulation in the ascidian Phallusia mammillata. By using high-coverage scRNA-seq, we devise a computational framework that stratifies single cells of individual embryos into cell types without prior knowledge. Unbiased transcriptome data analysis mapped each cell's physical position and lineage history, yielding the complete history of gene expression at the genome-wide level for every single cell in a developing embryo. A comparison of individual embryos reveals both extensive reproducibility between symmetric embryo sides and a large inter-embryonic variability due to small differences in embryogenesis timing.


Spatial reconstruction
Gene Expression
cell fate specification
cell type classification
gene expression noise
light sheet imaging
lineage reconstruction
single-cell RNA sequencing
spatial reconstruction

MeSH terms

Cell Lineage
Computational Biology
Gene Expression Profiling
Gene Expression Regulation, Developmental
Reproducibility of Results
Sequence Analysis, RNA
Single-Cell Analysis


Sladitschek, Hanna L
Fiuza, Ulla-Maj
Pavlinic, Dinko
Benes, Vladimir
Hufnagel, Lars
Neveu, Pierre A

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