SPACE-seq integrates spatial transcriptomics and lineage tracing in native tissues

Area of Science:

• Cell Biology
• Genomics
• Developmental Biology

Background:

• Understanding cellular dynamics in tissues requires methods that track cell lineage and spatial organization.
• Current techniques often lack the resolution or ability to integrate lineage, cell state, and spatial information simultaneously.

Purpose of the Study:

• To develop and validate SPACE-seq, a platform for in situ spatial lineage tracing and transcriptomics.
• To investigate cellular diversification within tumors and developmental tissue patterning.

Main Methods:

• SPACE-seq integrates CRISPR-based lineage recording with Slide-seq spatial transcriptomics.
• This allows simultaneous resolution of cell lineage, cell state, and tissue architecture at near-cellular resolution.
• The platform was applied to study tumor microenvironments and liver development.

Main Results:

• SPACE-seq uncovered intratumor transcriptional diversification in clonally related cells.
• It identified reciprocal tumor-stroma crosstalk influencing both malignant and stromal cell behaviors.
• The study revealed hepatoblast dispersion patterns contributing to liver lobar architecture during development.

Conclusions:

• SPACE-seq is a versatile platform for uncovering principles of cellular organization, lineage dynamics, and tissue patterning.
• It provides unprecedented insights into complex biological processes in both disease and development.
• The findings open new avenues for studying in situ cellular behavior and tissue architecture.