The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Representation and relative abundance of cell-type selective markers in whole-kidney RNA-Seq data
Open accessAbstract
Bulk-tissue RNA-Seq is increasingly being used in the study of physiological and pathophysiological processes in the kidney; however, the presence of multiple cell types in kidney tissue complicates data interpretation. We addressed the question of which cell types are represented in whole-kidney RNA-Seq data in order to identify circumstances in which bulk-kidney RNA-Seq can be successfully interpreted. We carried out RNA-Seq in mouse whole kidneys and in microdissected renal tubule segments. To aid in the interpretation of the data, we compiled a database of cell-type selective protein markers for 43 cell types believed to be present in kidney tissue. The whole-kidney RNA-Seq analysis identified transcripts corresponding to 17,742 genes, distributed over 5 orders of magnitude of expression level. Markers for all 43 curated cell types were detectable. Analysis of the cellular makeup of mouse and rat kidney, calculated from published literature, suggests that proximal tubule cells account for more than half of the mRNA in a kidney. Comparison of RNA-Seq data from microdissected proximal tubules with data from whole kidney supports this view. RNA-Seq data for cell-type selective markers in bulk-kidney samples provide a valid means to identify changes in minority-cell abundances in kidney tissue. Because proximal tubules make up a substantial fraction of whole-kidney samples, changes in proximal tubule gene expression can be assessed presumptively by bulk-kidney RNA-Seq, although results could potentially be complicated by the presence of mRNA from other cell types.
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“Candidate CNT cells were identified as a cluster overexpressing Calb1 and Klk1 genes [34, 56].”
From Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows (2020) · cites this paper as [34]
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Metadata
- Authors
- Clark, J. Z., Chen, L., Chou, C.-L., Jung, H. J., Lee, J. W., & Knepper, M. A.
- Affiliations
- National Institutes of Health (US)
- National Cancer Center (KR)
- Corresponding author
- Knepper, Mark A.
- Venue
- Kidney International
- Publisher
- Elsevier BV
- Published
- 2019-04
- Volume
- 95
- Issue
- 4
- Pages
- 787-796
- ISSN
- 0085-2538 (ISSN-L)
- PMC
- PMC7466803
- OpenAlex
- W2915419035
- Cited by
- 136
- References
- 33
- Citations by year
- 2026: 11 · 2025: 18 · 2024: 23 · 2023: 22 · 2022: 14 · 2021: 21 · 2020: 21 · 2019: 5
- FWCI
- 5.04
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Kidney International (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases
- National Heart, Lung, and Blood Institute (ZIA-HL001285, ZIA-HL006129)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- kidney cell types, proximal tubule, cell abundance, kidney transcriptome, mouse kidney, rat kidney, gene expression
- MeSH terms
- RNA-Seq, Animals, Kidney, RNA, Messenger, Biomarkers, Gene Expression Profiling, Microdissection, Mice, Rats, Transcriptome
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