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Application of Laser Microdissection to Uncover Regional Transcriptomics in Human Kidney Tissue
- Source :
- J Vis Exp
- Publication Year :
- 2020
-
Abstract
- Gene expression analysis of human kidney tissue is an important tool to understand homeostasis and disease pathophysiology. Increasing the resolution and depth of this technology and extending it to the level of cells within the tissue is needed. Although the use of single nuclear and single cell RNA sequencing has become widespread, the expression signatures of cells obtained from tissue dissociation do not maintain spatial context. Laser microdissection (LMD) based on specific fluorescent markers would allow the isolation of specific structures and cell groups of interest with known localization, thereby enabling the acquisition of spatially-anchored transcriptomic signatures in kidney tissue. We have optimized an LMD methodology, guided by a rapid fluorescence-based stain, to isolate five distinct compartments within the human kidney and conduct subsequent RNA sequencing from valuable human kidney tissue specimens. We also present quality control parameters to enable the assessment of adequacy of the collected specimens. The workflow outlined in this manuscript shows the feasibility of this approach to isolate sub-segmental transcriptomic signatures with high confidence. The methodological approach presented here may also be applied to other tissue types with substitution of relevant antibody markers.
- Subjects :
- General Chemical Engineering
Cell
02 engineering and technology
Computational biology
Laser Capture Microdissection
Biology
Kidney
General Biochemistry, Genetics and Molecular Biology
Article
Transcriptome
03 medical and health sciences
Gene expression
medicine
Humans
Control parameters
030304 developmental biology
Laser capture microdissection
0303 health sciences
General Immunology and Microbiology
General Neuroscience
RNA
Human kidney
021001 nanoscience & nanotechnology
medicine.anatomical_structure
0210 nano-technology
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- J Vis Exp
- Accession number :
- edsair.doi.dedup.....bff1a4bf6f6fac1aa5d7ea9ad85ccebe