Dissecting the coordinated progression of cell states in spatial transcriptomics with CoPro

, a computational framework for detecting the spatially coordinated progression of cellular states. CoPro can operate in both supervised and unsupervised modes to identify gene programs that co-vary within or between cell types, and to disentangle multiple overlapping spatial patterns. CoPro can be applied to single-cell-level spatial transcriptomics datasets, including MERFISH, SeqFISH+, Xenium, and histology-imputed transcriptomic data. We demonstrate the utility of CoPro with data collected from colon, brain, liver, and kidney tissues. In the colon, CoPro separates epithelial differentiation along the crypt axis from spatially localized inflammatory signals. In the aging liver, it identifies multiple aging-associated cellular programs superimposed on anatomical zonation. In the brain, the flexible kernel design enables the decoupling of the gene expression gradient along the dorsal-ventral and medial-lateral axes. In the kidney, CoPro identifies tubule-vasculature coordination that is essential in nephron function. These results demonstrate CoPro's utility for analyzing spatial coordination of gene expression in complex tissues and disentangling overlapping biological processes, such as anatomical organization and disease-associated variation.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-04-21
DOI
https://doi.org/10.64898/2026.04.17.719309
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
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article

Dissecting the coordinated progression of cell states in spatial transcriptomics with CoPro

Andrew P. McMahon, Zhen Miao, Laura J. Niedernhofer, Junhyong Kim et al.
bioRxiv (Cold Spring Harbor Laboratory)
Single-cell and spatial transcriptomics
article

Dissecting the coordinated progression of cell states in spatial transcriptomics with CoPro

Andrew P. McMahon, Zhen Miao, Laura J. Niedernhofer, Junhyong Kim, Alisha Aristel, Sijia Huang, L Laux, Nancy Zhang, Samuel Peters, Yilong Qu, Zhaojun Zhang
article en

Abstract

, a computational framework for detecting the spatially coordinated progression of cellular states. CoPro can operate in both supervised and unsupervised modes to identify gene programs that co-vary within or between cell types, and to disentangle multiple overlapping spatial patterns. CoPro can be applied to single-cell-level spatial transcriptomics datasets, including MERFISH, SeqFISH+, Xenium, and histology-imputed transcriptomic data. We demonstrate the utility of CoPro with data collected from colon, brain, liver, and kidney tissues. In the colon, CoPro separates epithelial differentiation along the crypt axis from spatially localized inflammatory signals. In the aging liver, it identifies multiple aging-associated cellular programs superimposed on anatomical zonation. In the brain, the flexible kernel design enables the decoupling of the gene expression gradient along the dorsal-ventral and medial-lateral axes. In the kidney, CoPro identifies tubule-vasculature coordination that is essential in nephron function. These results demonstrate CoPro's utility for analyzing spatial coordination of gene expression in complex tissues and disentangling overlapping biological processes, such as anatomical organization and disease-associated variation.

bioRxiv (Cold Spring Harbor Laboratory)
California Institute of Technology (US), University of Minnesota (US), Cape Town HVTN Immunology Laboratory / Hutchinson Centre Research Institute of South Africa (ZA), Fred Hutch Cancer Center (US), Penn Center for AIDS Research (US), University of Pennsylvania (US)
Openalex Percentile: Top 17%
Single-cell and spatial transcriptomics
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