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Abstract
Coordinated changes in gene expression, epigenetic regulation, protein and metabolic activities together drive disease progression and determine clinical outcomes. While spatially resolved transcriptomics has been widely adopted across biomedical fields, it offers an incomplete picture limited to transcriptomic levels. Here, we survey the latest developments in spatial multiomics technologies, with particular emphasis on platforms that extend beyond conventional transcriptomics and profile genomics, epigenomics, proteomics, or metabolomics within intact tissues. These approaches are rapidly becoming commercialized, and here we highlight major technical breakthroughs, enhanced sample compatibility, emerging applications, and computational tools for data analysis. This Review aims to equip researchers with a clear understanding of the current technological landscape and to accelerate the adoption of spatial multiomics methods in biomedical research.
Authors
Xinchen Mao, Zhuo Chen, Emily J. Hwang, Jun Liu, Junrou Huang, Haikuo Li
Usage data is cumulative from September 2026 through September 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 177 | 0 |
| 49 | 0 | |
| Figure | 52 | 0 |
| Table | 41 | 0 |
| Supplemental data | 11 | 0 |
| Citation downloads | 25 | 0 |
| Totals | 355 | 0 |
| Total Views | 355 | |
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