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Spatial Transcriptomics: Biotechnologies, Computational Tools, and Neuroscience Applications
Qianwen Wang1, Hongyuan Zhu1, Lin Deng1
1Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China.
Small Methods
|January 6, 2025
Summary
Spatial transcriptomics (ST) offers new ways to study gene expression in tissues. This review covers ST technologies, computational tools, and their use in understanding brain complexity and diseases.
Area of Science:
- Molecular Biology
- Neuroscience
- Genomics
Background:
- Spatial transcriptomics (ST) revolutionizes gene expression analysis within tissue architecture.
- Understanding spatial gene expression is crucial for complex biological systems like the brain.
Purpose of the Study:
- To review advancements in ST technologies and computational tools.
- To highlight the applications of ST in neuroscience research.
- To discuss the impact of ST on brain atlas projects, development, and diseases.
Main Methods:
- Historical overview of ST techniques from image-based to sequence-based methods.
- Discussion of computational approaches for ST data analysis (preprocessing, annotation, clustering, etc.).
- Integration of 3D multi-slices data.
Main Results:
- ST provides insights into brain complexity, development, and neuroimmune disorders.
- Applications include Alzheimer's, schizophrenia, and brain tumor research.
- ST enhances understanding of neuronal vulnerability.
Conclusions:
- ST has profoundly impacted neuroscience, offering transformative potential for brain research.
- Challenges include improving sequencing technologies and computational tools.
- ST paves the way for new therapeutic insights.
