Publication Date

9-1-2025

Journal

Trends in Genetics

DOI

10.1016/j.tig.2025.05.002

PMID

40461389

PMCID

PMC12486146

PubMedCentral® Posted Date

9-1-2026

PubMedCentral® Full Text Version

Author MSS

Abstract

Spatial transcriptomics (ST) enables systematic profiling of whole-transcriptome gene expression in tissues while preserving spatial context. Recent advances in sequencing- and imaging-based ST technologies have ushered in the era of microscopic-resolution ST (μST), allowing transcriptome mapping at cellular and even subcellular scales with unprecedented precision. Despite these advances, μST faces substantial challenges, including sparse transcript discovery per submicron (or micron)-sized spatial units and data fragmentation across platforms, hindering integration and analysis. There is also a growing demand for scalable, segmentation-free, and universally applicable analysis methods, as well as strategies for 3D mapping, multi-omics integration, and artificial intelligence (AI)-driven spatial analysis. In this review, we highlight recent breakthroughs, outline key challenges, and discuss emerging experimental and computational solutions shaping the future of μST.

Keywords

Humans, Transcriptome, Gene Expression Profiling, Genomics, Artificial Intelligence, Animals, Computational Biology

Published Open-Access

yes

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