Spatial Transcriptomics in Kidney Tissue

Raghubar, Arti M., Crawford, Joanna, Jones, Kahli, Lam, Pui Y., Andersen, Stacey B., Matigian, Nicholas A., Ng, Monica S.Y., Healy, Helen, Kassianos, Andrew J., and Mallett, Andrew J. (2023) Spatial Transcriptomics in Kidney Tissue. In: Hewitson, Tim D., Toussaint, Nigel D., and Smith, Edward R., (eds.) Kidney Research: Experimental protocols. Methods in Molecular Biology . Springer, New York, NY, USA, pp. 233-282.

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Unlike bulk and single-cell/single-nuclei RNA sequencing methods, spatial transcriptome sequencing (ST-seq) resolves transcriptome expression within the spatial context of intact tissue. This is achieved by integrating histology with RNA sequencing. These methodologies are completed sequentially on the same tissue section placed on a glass slide with printed oligo-dT spots, termed ST-spots. Transcriptomes within the tissue section are captured by the underlying ST-spots and receive a spatial barcode in the process. The sequenced ST-spot transcriptomes are subsequently aligned with the hematoxylin and eosin (H&E) image, giving morphological context to the gene expression signatures within intact tissue. We have successfully employed ST-seq to characterize mouse and human kidney tissue. Here, we describe in detail the application of Visium Spatial Tissue Optimization (TO) and Visium Spatial Gene Expression (GEx) protocols for ST-seq in fresh frozen kidney tissue.

Item ID: 79540
Item Type: Book Chapter (Scholarly Work)
ISSN: 1940-6029
Keywords: Kidney, Spatial transcriptomics, Visium Spatial Gene Expression, Visium Spatial Tissue Optimization
Copyright Information: © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023.
Date Deposited: 20 May 2024 01:36
FoR Codes: 32 BIOMEDICAL AND CLINICAL SCIENCES > 3202 Clinical sciences > 320214 Nephrology and urology @ 50%
31 BIOLOGICAL SCIENCES > 3102 Bioinformatics and computational biology > 310204 Genomics and transcriptomics @ 50%
SEO Codes: 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280103 Expanding knowledge in the biomedical and clinical sciences @ 100%
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