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Updated: May 5, 2026
10:22
Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
Published on: October 31, 2025
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Dissecting the coordinated progression of cell states in spatial transcriptomics with CoPro
Zhen Miao1,2,3, Yilong Qu1, Sijia Huang4
1Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Biorxiv : the Preprint Server for Biology
|May 4, 2026
Summary
We developed CoPro, a computational framework to map coordinated gene expression changes in tissues. This tool helps understand how cellular states progress spatially and interact between cell types in health and disease.
Area of Science:
- Computational biology
- Genomics
- Bioinformatics
Background:
- Spatial transcriptomics reveals cellular coordination within tissues.
- Identifying spatially varying and cell-type-coordinated gene programs is challenging.
Purpose of the Study:
- Introduce CoPro, a computational framework for detecting spatially coordinated cellular state progression.
- Enable analysis of gene programs co-varying within or between cell types.
- Disentangle multiple overlapping spatial patterns in complex tissues.
Main Methods:
- CoPro framework for spatial transcriptomics data analysis.
- Operates in supervised and unsupervised modes.
- Applicable to various single-cell spatial transcriptomics datasets (MERFISH, SeqFISH+, Xenium, imputed data).
Main Results:
- CoPro successfully analyzed colon, brain, liver, and kidney tissues.
- Separated epithelial differentiation from inflammation in colon.
- Identified superimposed aging-associated programs in liver.
- Decoupled gene expression gradients in the brain.
- Revealed tubule-vasculature coordination in the kidney.
Conclusions:
- CoPro is a versatile tool for spatial gene expression analysis.
- Effectively disentangles anatomical organization and disease-associated variation.
- Provides insights into cellular coordination in complex biological systems.
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