Spatial Transcriptomics in Kidney Tissue.

Area of Science:

• Molecular Biology
• Genomics
• Histology

Background:

• Spatial transcriptome sequencing (ST-seq) offers a unique approach to analyze gene expression within the spatial architecture of tissues.
• Traditional methods like bulk and single-cell RNA sequencing lack spatial resolution.
• Integrating histology with RNA sequencing provides morphological context to gene expression data.

Purpose of the Study:

• To provide a detailed protocol for applying ST-seq to fresh frozen kidney tissue.
• To demonstrate the utility of ST-seq in characterizing kidney tissue architecture and gene expression.
• To optimize Visium Spatial Tissue Optimization (TO) and Visium Spatial Gene Expression (GEx) protocols for kidney samples.

Main Methods:

• ST-seq involves capturing transcriptomes from tissue sections placed on specialized slides with oligo-dT spots (ST-spots).
• Each captured transcriptome receives a spatial barcode corresponding to its location on the tissue.
• Sequenced data is aligned with hematoxylin and eosin (H&E) stained images for spatial context.

Main Results:

• Successful characterization of mouse and human kidney tissue using ST-seq.
• Detailed description of the Visium Spatial TO and GEx protocols applied to fresh frozen kidney tissue.
• Demonstration of integrating gene expression data with tissue morphology.

Conclusions:

• ST-seq is a powerful method for understanding tissue organization and gene expression patterns.
• The described protocols enable detailed spatial analysis of kidney tissue.
• This approach enhances the understanding of tissue-specific gene expression in its native environment.