Integration of spatial and single-cell transcriptomic data elucidates mouse organogenesis

Area of Science:

• Developmental Biology
• Genomics
• Molecular Biology

Background:

• Single-cell profiling advances developmental biology but often loses spatial context by dissociating cells.
• Understanding spatial gene expression is crucial for deciphering regulatory processes in tissue development.

Purpose of the Study:

• To apply an image-based transcriptomics method, seqFISH, to map gene expression in intact mouse embryo sections.
• To integrate spatial information with transcriptional data to characterize cell types and developmental patterns.
• To demonstrate the imputation of spatially resolved gene expression for genes not directly measured.

Main Methods:

• Sequential fluorescence in situ hybridization (seqFISH) was used to detect mRNAs of 387 target genes in mouse embryo tissue sections.
• Integration of spatial transcriptomic data with existing single-cell transcriptome atlases.
• Computational imputation of spatially resolved gene expression for unprofiled genes.

Main Results:

• A high-resolution spatial gene expression map of mouse embryos (8-12 somite stage) was generated.
• Cell types across the embryo were characterized with integrated spatial and transcriptional data.
• Novel axes of cell differentiation, including early dorsal-ventral patterning in the gut tube, were uncovered.

Conclusions:

• seqFISH provides crucial spatial context for understanding cell fate decisions and developmental processes.
• This method overcomes limitations of traditional scRNA-seq by preserving tissue architecture.
• The approach offers new insights into fundamental developmental patterning, such as in the midbrain-hindbrain boundary and gut tube.