GeneSPOT Maps Spatial Relationships and Dynamics Among Genes Across Tissues

Researchers have introduced Gene SPatial Optimal Transport, known as GeneSPOT, a computational framework developed to characterize spatial relationships among genes and quantify their reorganization across biological conditions and time. Reported in Nature Methods, the gene-centric analytical framework is designed to complement conventional cell-centric methods by mapping how the relational spatial organization of molecular features shifts across tissues.

Spatial omics technologies offer opportunities to examine how molecular programs are organized within tissues, yet existing analytical frameworks primarily focus on identifying cellular states and characterizing differentially expressed molecular features across those states. Consequently, the relational spatial organization of molecular features and its dynamics across different biological contexts have remained largely unexplored.

Although GeneSPOT was developed with a gene-centric design, the computational framework generalizes to other molecular features. By evaluating spatial arrangements beyond individual cellular states, the approach provides a quantitative framework for deciphering how spatial relationships among diverse molecular features undergo reorganization across changing biological contexts.

Across diverse applications, the computational framework successfully resolved tissue structures. In validation analyses involving the mouse brain, GeneSPOT captured biologically meaningful spatial gene programs, demonstrating its capability to identify organized molecular patterns within complex tissue architecture.

GeneSPOT also demonstrated capabilities in multi-omics data integration. The framework integrated both paired and unpaired spatial multi-omics datasets, enabling investigators to uncover cross-omics spatial relationships and examine interconnected molecular layers within tissue environments.

In developmental and aging contexts, the framework uncovered dynamic spatiotemporal gene programs. GeneSPOT unveiled the spatial convergence of gene programs during mouse embryogenesis and discovered age-dependent spatial reorganization in the aging mouse brain, identifying structural shifts among genes whose expression levels did not change significantly with age.

Subject of Research: Computational spatial transcriptomics and molecular spatial organization

Article Title: Deciphering the gene-centric spatial dynamics across tissue and time with GeneSPOT

Article References: Zou, Q., Wang, Z., Li, S., Lin, S., Han, C., Cui, Y., Li, S., Wang, L., Zhang, D., Zhang, W., Qian, B.-Z., Gao, R., & Yuan, Z. (2026). Deciphering the gene-centric spatial dynamics across tissue and time with GeneSPOT. Nature Methods. https://doi.org/10.1038/s41592-026-03308-2

Image Credits: AI Generated

DOI: 10.1038/s41592-026-03308-2

Keywords: spatial transcriptomics, computational biology, GeneSPOT, spatial omics, mouse brain, embryogenesis, tissue organization, multi-omics, Deciphering, gene-centric, spatial, dynamics