Understanding how cells grow, divide, and change over time is essential for studying development, disease, and tissue repair. Researchers at the Zhejiang University School of Medicine have developed a new method that combines spatial RNA sequencing with cell proliferation tracking to capture both where cells are and what they are doing.

Traditional spatial transcriptomics methods provide a snapshot of gene activity in tissues, but they often focus only on protein-coding genes and miss important non-coding RNAs. They also do not capture how cells change over time. The new approach, called SPTEdU-seq, addresses these limitations by integrating RNA sequencing with a labeling method that tracks newly dividing cells.

This method allows researchers to measure both gene expression and cell proliferation at the same time, directly within intact tissues. It also detects a wider range of RNA molecules, including non-coding RNAs and different splicing variants, providing a more complete view of cellular activity.

When applied to mouse brain tissue, SPTEdU-seq revealed how cells develop and organize over time, including patterns of long non-coding RNA expression. In models of stroke, the method identified specific cell populations involved in tissue repair, including a subtype of astrocytes linked to recovery.

The technique was also used to study cancer, where it uncovered tumor-specific gene expression changes and important genomic alterations. By capturing both spatial and temporal information, RNA sequencing can now reveal how cells interact within their natural environment and how these interactions change during disease.

Overall, this work demonstrates how advanced RNA sequencing methods can provide a more dynamic and detailed understanding of biology. By combining spatial information with cell tracking, researchers can better study development, regeneration, and cancer progression.

Availability – The original codes are available on GitHub: https://github.com/AritaZ-hang/SPTEdU-seq.