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Journal of Visualized Experiments
Article . 2021 . Peer-reviewed
Data sources: Crossref
Journal of Visualized Experiments
Article . 2021 . Peer-reviewed
Data sources: Crossref
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Nuclei Isolation from Adult Mouse Kidney for Single-Nucleus RNA-Sequencing

Authors: Leiz, J.; Hinze, C.; Boltengagen, A.; Braeuning, C.; Kocks, C.; Rajewsky, N.; Schmidt-Ott, K.M.;

Nuclei Isolation from Adult Mouse Kidney for Single-Nucleus RNA-Sequencing

Abstract

The kidneys regulate diverse biological processes such as water, electrolyte, and acid-base homeostasis. Physiological functions of the kidney are executed by multiple cell types arranged in a complex architecture across the corticomedullary axis of the organ. Recent advances in single-cell transcriptomics have accelerated the understanding of cell type-specific gene expression in renal physiology and disease. However, enzyme-based tissue dissociation protocols, which are frequently utilized for single-cell RNA-sequencing (scRNA-seq), require mostly fresh (non-archived) tissue, introduce transcriptional stress responses, and favor the selection of abundant cell types of the kidney cortex resulting in an underrepresentation of cells of the medulla. Here, we present a protocol that avoids these problems. The protocol is based on nuclei isolation at 4 °C from frozen kidney tissue. Nuclei are isolated from a central piece of the mouse kidney comprised of the cortex, outer medulla, and inner medulla. This reduces the overrepresentation of cortical cells typical for whole-kidney samples for the benefit of medullary cells such that data will represent the entire corticomedullary axis at sufficient abundance. The protocol is simple, rapid, and adaptable and provides a step towards the standardization of single-nuclei transcriptomics in kidney research.

Keywords

Cell Nucleus, Sequence Analysis, RNA, Kidney, Mice, Cardiovascular and Metabolic Diseases, Integrative Biomedicine [Topic 3], Animals, RNA, Technology Platforms, Genes, Cells and Cell-Based Medicine [Topic 1], Transcriptome

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Top 10%
Green
bronze