bioRxivCell Biology
Kidney pathology alters cell-clustering in single cell RNA sequencing
L. Ma, M. Murea, Y. A. Choi, A. K. Hemal, A. V. Mikhailov, J. A. Snipes, J. W. Chou, R. C. Langefeld, W. Cui, L. D. Miller, G. A. Hawkins, N. D. Palmer, C. D. Langefeld, B. I. Freedman
Abstract
Single cell RNA sequencing (scRNA-Seq) is useful to classify cell-specific gene expression profiles in kidney tissue. As viable cells are required, we report an optimized cell dissociation methodology and the necessity of screening tissue histology prior to scRNA-Seq. We demonstrate that glomerular injury can selectively reduce the appearance of groups of cells during analysis of cell clustering and we confirmed reductions in cell-specific markers among injured cells on kidney sections with fluorescence microscopy. Interpretation of scRNA-Seq results may be refined based upon these considerations.
- organism: mouse
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: clustering
- approach: experimental assay
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Kidney single-cell atlas reveals myeloid heterogeneity in progression and regression of kidney disease.
B. R. Conway, E. D. O'Sullivan, … L. Denby·bioRxiv·May 14, 2020
- Urinary single-cell sequencing captures intrarenal injury and repair processes in human acute kidney injury
Jan Klocke, Seung Joon Kim, … Philipp Enghard·Kidney InternationalPeer-reviewed·Aug 29, 2022
- Novel Human Kidney Cell Subsets Identified by Mux-Seq
Andrew Schroeder, Swastika Sur, … Minnie Sarwal·TransplantationPeer-reviewed·Aug 28, 2020
- scTrimClust: A Fast Approach to Robust scRNA-seq Analysis Using Trimmed Cell Clusters
Sergej Ruff, Klaus Jung·Bioinformatics AdvancesPeer-reviewed·Jan 1, 2026
- Statistical significance of cluster membership for determination of cell identities in single cell genomics
Neo Christopher Chung·BioinformaticsPeer-reviewed·Feb 19, 2020
- Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows
Elena Denisenko, Belinda B. Guo, … Alistair R. R. Forrest·Genome biologyPeer-reviewed·Jun 2, 2020