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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Li, B., & Dewey, C. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-323 · Cited by 22,179
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696
RNA-Seq: a revolutionary tool for transcriptomics
Wang, Z., Gerstein, M., & Snyder, M. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2484 · Cited by 13,174
Sequencing technologies – the next generation
Metzker, M. L. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2626 · Cited by 7,066
Mapping the Mouse Cell Atlas by Microwell-Seq
Han, X., Wang, R., Zhou, Y., Fei, L., Sun, H., Lai, S., Saadatpour, A., Zhou, Z., Chen, H., Ye, F., et al. (2018) · Cell · doi:10.1016/j.cell.2018.02.001 · Cited by 1,597
Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays.
Brenner, S., Johnson, M., Bridgham, J., Golda, G., Lloyd, D. H., Johnson, D., Luo, S., McCurdy, S., Foy, M., Ewan, M., et al. (2000) · Nature Biotechnology · doi:10.1038/76469 · Cited by 1,360
Single-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease
Park, J., Shrestha, R., Qiu, C., Kondo, A., Huang, S., Werth, M., Li, M., Barasch, J., & Suszták, K. (2018) · Science · doi:10.1126/science.aar2131 · Cited by 1,065
Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors
Young, M. D., Mitchell, T. J., Vieira Braga, F. A., Tran, M. G. B., Stewart, B. J., Ferdinand, J. R., Collord, G., Botting, R. A., Popescu, D.-M., Loudon, K. W., et al. (2018) · Science · doi:10.1126/science.aat1699 · Cited by 762
The Human Cell Atlas: from vision to reality
Rozenblatt-Rosen, O., Stubbington, M. J. T., Regev, A., & Teichmann, S. A. (2017) · Nature · doi:10.1038/550451a · Cited by 638
Research works printed but not linked: 1
- Sperber, 1944, Studios on the mammalian kidney, Zoologiska Bidrag fran Uppsala, 22, 249
Cited by
Sorted by citations
Decoding myofibroblast origins in human kidney fibrosis
Kuppe, C., Ibrahim, M. M., Kranz, J., Zhang, X., Ziegler, S., Perales-Patón, J., Jansen, J., Reimer, K. C., Smith, J. R., Dobie, R., et al. (2021) · Nature · doi:10.1038/s41586-020-2941-1 · Cited by 769
Denisenko, E., Guo, B. B., Jones, M., Hou, R., de Kock, L., Lassmann, T., Poppe, D., Clément, O., Simmons, R. K., Lister, R., et al. (2020) · Genome Biology · doi:10.1186/s13059-020-02048-6 · Cited by 686
Spatiotemporal immune zonation of the human kidney
Stewart, B. J., Ferdinand, J. R., Young, M. D., Mitchell, T. J., Loudon, K. W., Riding, A., Richoz, N., Frazer, G. L., Staniforth, J., Braga, F. A. V., et al. (2019) · Science · doi:10.1126/science.aat5031 · Cited by 424
Clarke, Z. A., Andrews, T. S., Atif, J., Pouyabahar, D., Innes, B. T., MacParland, S. A., & Bader, G. D. (2021) · Nature Protocols · doi:10.1038/s41596-021-00534-0 · Cited by 234
A Comprehensive Map of mRNAs and Their Isoforms across All 14 Renal Tubule Segments of Mouse
Chen, L., Chou, C.-L., & Knepper, M. A. (2021) · Journal of the American Society of Nephrology · doi:10.1681/asn.2020101406 · Cited by 208
Self-citationMetabolism at the crossroads of inflammation and fibrosis in chronic kidney disease
Miguel, V., Shaw, I., & Kramann, R. (2024) · Nature Reviews Nephrology · doi:10.1038/s41581-024-00889-z · Cited by 216
van Vliet, T., Varela-Eirin, M., Wang, B., Borghesan, M., Brandenburg, S. M., Franzin, R., Evangelou, K., Seelen, M., Gorgoulis, V., & Demaria, M. (2021) · Molecular Cell · doi:10.1016/j.molcel.2021.03.018 · Cited by 172
Janosevic, D., Myslinski, J., McCarthy, T. W., Zollman, A., Syed, F., Xuei, X., Gao, H., Liu, Y., Collins, K. S., Cheng, Y., et al. (2021) · eLife · doi:10.7554/elife.62270 · Cited by 149
Menon, R., Otto, E. A., Hoover, P., Eddy, S. F., Mariani, L. H., Godfrey, B., Berthier, C. C., Eichinger, F. H., Subramanian, L., Harder, J. L., et al. (2020) · JCI Insight · doi:10.1172/jci.insight.133267 · Cited by 146
Quantitative Proteomics of All 14 Renal Tubule Segments in Rat
Limbutara, K., Chou, C., & Knepper, M. A. (2020) · Journal of the American Society of Nephrology · doi:10.1681/asn.2020010071 · Cited by 130
Self-citationWang, G., Heijs, B., Kostidis, S., Rietjens, R. G. J., Koning, M., Yuan, L., Tiemeier, G. L., Mahfouz, A. E., Dumas, S. J., Giera, M. A., et al. (2022) · Cell stem cell · doi:10.1016/j.stem.2022.10.008 · Cited by 128
Renal-Tubule Epithelial Cell Nomenclature for Single-Cell RNA-Sequencing Studies
Chen, L., Clark, J. Z., Nelson, J. W., Kaissling, B., Ellison, D. H., & Knepper, M. A. (2019) · Journal of the American Society of Nephrology · doi:10.1681/asn.2019040415 · Cited by 109
Self-citationTargeted Single-Cell RNA-seq Identifies Minority Cell Types of Kidney Distal Nephron
Chen, L., Chou, C.-L., & Knepper, M. A. (2021) · Journal of the American Society of Nephrology · doi:10.1681/asn.2020101407 · Cited by 103
Self-citationXu, Z., Zhang, T., Chen, H., Zhu, Y., Lv, Y., Zhang, S., Chen, J., Chen, H., Yang, L., Jiang, W., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-38409-5 · Cited by 99
McEvoy, C. M., Murphy, J. M., Zhang, L., Clotet‐Freixas, S., Mathews, J. A., An, J., Karimzadeh, M., Pouyabahar, D., Su, S., Zaslaver, O., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-35297-z · Cited by 93
The Renal Physiology of Pendrin-Positive Intercalated Cells
Wall, S. M., Verlander, J. W., & Romero, C. A. (2020) · Physiological Reviews · doi:10.1152/physrev.00011.2019 · Cited by 81
Metabolic Rewiring and Communication: An Integrative View of Kidney Proximal Tubule Function
Chrysopoulou, M., & Rinschen, M. M. (2023) · Annual Review of Physiology · doi:10.1146/annurev-physiol-042222-024724 · Cited by 76
Kayhan, M., Vouillamoz, J., Rodríguez, D. G., Bugarski, M., Mitamura, Y., Gschwend, J., Schneider, C., Hall, A. M., Legouis, D., Akdiş, C. A., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-39050-y · Cited by 69
Accelerated lysine metabolism conveys kidney protection in salt-sensitive hypertension
Rinschen, M. M., Palygin, O., El‐Meanawy, A., Domingo-Almenara, X., Palermo, A., Dissanayake, L. V., Golosova, D., Schafroth, M. A., Guijas, C., Demir, F., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-31670-0 · Cited by 65
The effect of background noise and its removal on the analysis of single-cell expression data
Janssen, P., Kliesmete, Z., Vieth, B., Adiconis, X., Simmons, S., Marshall, J. L., Aubin, C., Heyn, H., Levin, J. Z., Enard, W., et al. (2023) · Genome biology · doi:10.1186/s13059-023-02978-x · Cited by 64
Siew, K., Nestler, K. A., Nelson, C., D’Ambrosio, V., Zhong, C., Li, Z., Grillo, A., Wan, E. R., Patel, V., Overbey, E. G., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-49212-1 · Cited by 66
Bacterial sepsis triggers an antiviral response that causes translation shutdown
Hato, T., Maier, B., Syed, F., Myslinski, J., Zollman, A., Plotkin, Z., Eadon, M. T., & Dagher, P. C. (2018) · Journal of Clinical Investigation · doi:10.1172/jci123284 · Cited by 63
Transcriptomes of Major Proximal Tubule Cell Culture Models
Khundmiri, S. J., Chen, L., Lederer, E. D., Yang, C., & Knepper, M. A. (2020) · Journal of the American Society of Nephrology · doi:10.1681/asn.2020010009 · Cited by 64
Self-citationKim, D., Lim, H., Youn, J., Park, T., & Kim, D. S. (2024) · Nature Communications · doi:10.1038/s41467-024-53073-z · Cited by 66
The proteomic landscape of small urinary extracellular vesicles during kidney transplantation
Braun, F., Rinschen, M. M., Buchner, D., Bohl, K., Plagmann, I., Bachurski, D., Späth, M. R., Antczak, P., Göbel, H., Klein, C., et al. (2020) · Journal of Extracellular Vesicles · doi:10.1002/jev2.12026 · Cited by 57
Spatial transcriptomics using multiplexed deterministic barcoding in tissue
Wirth, J., Huber, N., Yin, K., Brood, S., Chang, S., Martinez‐Jimenez, C. P., & Meier, M. (2023) · Nature Communications · doi:10.1038/s41467-023-37111-w · Cited by 52
Histone Deacetylases in Kidney Physiology and Acute Kidney Injury
Hyndman, K. A. (2020) · Seminars in Nephrology · doi:10.1016/j.semnephrol.2020.01.005 · Cited by 51
How to Get Started with Single Cell RNA Sequencing Data Analysis
Balzer, M. S., Ma, Z., Zhou, J., Abedini, A., & Suszták, K. (2021) · Journal of the American Society of Nephrology · doi:10.1681/asn.2020121742 · Cited by 51
Dorraji, E., Kanapathippillai, P., Hovd, A.-M. K., Stenersrød, M. R., Horvei, K. D., Ursvik, A., Figenschau, S. L., Thiyagarajan, D. B., Fenton, C. G., Pedersen, H. L., et al. (2020) · American Journal Of Pathology · doi:10.1016/j.ajpath.2020.07.015 · Cited by 45
Molecular characterization of the human kidney interstitium in health and disease
Barwinska, D., El‐Achkar, T. M., Ferreira, R. M., Syed, F., Cheng, Y., Winfree, S., Ferkowicz, M. J., Hato, T., Collins, K. S., Dunn, K. W., et al. (2021) · Science Advances · doi:10.1126/sciadv.abd3359 · Cited by 43
Hinze, C., Karaiskos, N., Boltengagen, A., Walentin, K., Redo, K., Himmerkus, N., Bleich, M., Potter, S. S., Potter, A., Eckardt, K., et al. (2020) · Journal of the American Society of Nephrology · doi:10.1681/asn.2020070930 · Cited by 41
Enhancing gene transfer to renal tubules and podocytes by context-dependent selection of AAV capsids
Furusho, T., Das, R., Hakui, H., Sairavi, A., Adachi, K., Galbraith-Liss, M. S., Rajagopal, P., Horikawa, M., Luo, S., Li, L., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-54475-9 · Cited by 44
Novella-Rausell, C., Grudniewska, M., Peters, D. J. M., & Mahfouz, A. E. (2023) · iScience · doi:10.1016/j.isci.2023.106877 · Cited by 38
Baek, J. J., Sas, K. M., He, C., Nair, V., Giblin, W., Inoki, A., Zhang, H., Yingbao, Y., Hodgin, J. B., Nelson, R. G., et al. (2023) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2023.102960 · Cited by 35
Vitamin A and retinoid signaling in the kidneys
DiKun, K. M., & Gudas, L. J. (2023) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2023.108481 · Cited by 38
The Integrated RNA Landscape of Renal Preconditioning against Ischemia-Reperfusion Injury
Johnsen, M., Kubacki, T., Yeroslaviz, A., Späth, M. R., Mörsdorf, J., Göbel, H., Bohl, K., Ignarski, M., Meharg, C., Habermann, B. H., et al. (2020) · Journal of the American Society of Nephrology · doi:10.1681/asn.2019050534 · Cited by 34
Single-Nucleus Transcriptional Profiling of Chronic Kidney Disease after Cisplatin Nephrotoxicity
Ma, Z., Hu, X., Ding, H., Zhang, M., Huo, Y., & Dong, Z. (2022) · American Journal Of Pathology · doi:10.1016/j.ajpath.2021.12.012 · Cited by 33
High-Resolution Human Kidney Molecular Histology by Imaging Mass Spectrometry of Lipids
Martín‐Saíz, L., Mosteiro, L., Solano-Iturri, J. D., Rueda, Y., Martín‐Allende, J., Imaz, I., Grasa, I. O., Ochoa, B., Fresnedo, O., Fernández, J. A., et al. (2021) · Analytical Chemistry · doi:10.1021/acs.analchem.1c00649 · Cited by 33
Landscape of GPCR expression along the mouse nephron
Poll, B. G., Chen, L., Chou, C., Raghuram, V., & Knepper, M. A. (2021) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00077.2021 · Cited by 30
Self-citationKidney Allograft Fibrosis: Diagnostic and Therapeutic Strategies
Saritas, T., & Kramann, R. (2021) · Transplantation · doi:10.1097/tp.0000000000003678 · Cited by 29
Williams, V. R., Konvalinka, A., Song, X., Zhou, X., John, R., Pei, Y., & Scholey, J. W. (2020) · Kidney International · doi:10.1016/j.kint.2020.01.029 · Cited by 30
Edwards, A., Long, K. R., Baty, C. J., Shipman, K. E., & Weisz, O. A. (2022) · The Journal of Physiology · doi:10.1113/jp282885 · Cited by 28
Xu, D., Zhang, X., Pang, J., Li, Y., & Peng, Z. (2025) · Biomolecules · doi:10.3390/biom15060794 · Cited by 30
Prot‐Bertoye, C., Griveau, C., Skjødt, K., Cheval, L., Brideau, G., Lièvre, L., Ferrière, E., Arbaretaz, F., Garbin, K., Zamani, R., et al. (2021) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00579.2020 · Cited by 27
Tripartite Separation of Glomerular Cell Types and Proteomes from Reporter-Free Mice
Hatje, F. A., Wedekind, U., Sachs, W., Loreth, D., Reichelt, J., Demir, F., Kosub, C., Blume, L., Tomas, N. M., Huber, T. B., et al. (2021) · Journal of the American Society of Nephrology · doi:10.1681/asn.2020091346 · Cited by 26
Mechanisms of paracellular transport of magnesium in intestinal and renal epithelia
Houillier, P., Lièvre, L., Hureaux, M., & Prot‐Bertoye, C. (2023) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14953 · Cited by 25
Oligodendrocyte lineage cells: Advances in development, disease, and heterogeneity
Wang, J., Gao, M.-Y., Gao, R., Zhao, K., Zhang, Y., & Li, X. (2022) · Journal of Neurochemistry · doi:10.1111/jnc.15728 · Cited by 24
Rinschen, M. M., Harder, J. L., Carter-Timofte, M. E., Rodriguez, L. Z., Mirabelli, C., Demir, F., Kurmasheva, N., Ramakrishnan, S. K., Kunke, M., Tan, Y., et al. (2022) · Science Signaling · doi:10.1126/scisignal.abo7940 · Cited by 24
Kikuchi, H., Jung, H. J., Raghuram, V., Leo, K. T., Park, E., Yang, C., Chou, C.-L., Chen, L., & Knepper, M. A. (2021) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00204.2021 · Cited by 27
Self-citationRen, J., Liu, K., Wu, B., Lu, X., Sun, L., Privratsky, J. R., Xing, C., Robson, M. J., Mao, H., Blakely, R., et al. (2023) · Journal of the American Society of Nephrology · doi:10.1681/asn.0000000000000191 · Cited by 22
Current techniques and the future of lung preservation
Lautner, L. J., Freed, D. H., Nagendran, J., & Acker, J. P. (2020) · Cryobiology · doi:10.1016/j.cryobiol.2020.04.009 · Cited by 20
Renal cell markers: lighthouses for managing renal diseases
Agarwal, S., Sudhini, Y. R., Polat, O. K., Reiser, J., & Altintas, M. M. (2021) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00182.2021 · Cited by 21
Wall, S. M. (2022) · Hypertension · doi:10.1161/hypertensionaha.121.16492 · Cited by 20
Chen, L., Jung, H. J., Datta, A., Park, E., Poll, B. G., Kikuchi, H., Leo, K. T., Mehta, Y., Lewis, S. A., Khundmiri, S. J., et al. (2021) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-052120-011012 · Cited by 20
Self-citationAxial differences in endocytosis along the kidney proximal tubule
Polesel, M., & Hall, A. M. (2019) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00459.2019 · Cited by 19
Fan, W., Wang, C., Xu, K., Liang, H., & Chi, Q. (2024) · International Immunopharmacology · doi:10.1016/j.intimp.2024.113339 · Cited by 18
Optimizing total RNA extraction method for human and mice samples
Zeng, Y., Tang, X., Chen, J., Kang, X., & Bai, D. (2024) · PeerJ · doi:10.7717/peerj.18072 · Cited by 17
Big Data in Gastroenterology Research
Alizadeh, M. A., Moura, N. S., Schledwitz, A., Patil, S. A., Ravel, J., & Raufman, J. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24032458 · Cited by 17
Shipman, K. E., & Weisz, O. A. (2020) · Function · doi:10.1093/function/zqaa017 · Cited by 16
Khatri, R., Machart, P., & Bonn, S. (2024) · Genome biology · doi:10.1186/s13059-024-03251-5 · Cited by 14
Proximal tubule hypertrophy and hyperfunction: a novel pathophysiological feature in disease states
Kanbay, M., Çöpür, S., Güldan, M., Özbek, L., Hatipoğlu, A., Covic, A. C., Mallamaci, F., & Zoccali, C. (2024) · Clinical Kidney Journal · doi:10.1093/ckj/sfae195 · Cited by 20
Edwards, A., Christensen, E., Unwin, R. J., & Norden, A. G. W. (2020) · The Journal of Physiology · doi:10.1113/jp280740 · Cited by 15
Pathway identification through transcriptome analysis
Terabayashi, T., Germino, G. G., & Menezes, L. F. (2020) · Cellular Signalling · doi:10.1016/j.cellsig.2020.109701 · Cited by 15
Quatredeniers, M., Serafin, A. S., Benmerah, A., Rausell, A., Saunier, S., & Viau, A. (2023) · Scientific Data · doi:10.1038/s41597-023-02209-9 · Cited by 15
Salt-sensitive transcriptome of isolated kidney distal tubule cells
Swanson, E. A., Nelson, J. W., Jeng, S., Erspamer, K. J., Yang, C., McWeeney, S. K., & Ellison, D. H. (2019) · Physiological Genomics · doi:10.1152/physiolgenomics.00119.2018 · Cited by 14
Generation and network analysis of an RNA-seq transcriptional atlas for the rat
SUMMERS, K. M., Bush, S. J., Wu, C., & Hume, D. A. (2022) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqac017 · Cited by 10
Urbanellis, P., McEvoy, C. M., Škrtić, M., Kaths, J. M., Kollmann, D., Linares, I., Ganesh, S., Oquendo, F., Sharma, M., Mazilescu, L., et al. (2021) · Transplantation Direct · doi:10.1097/txd.0000000000001157 · Cited by 11
Systematic bias assessment in solid tissue 10x scRNA-seq workflowsPreprint
Denisenko, E., Guo, B. B., Jones, M., Hou, R., de Kock, L., Lassmann, T., Poppe, D., Clément, O., Simmons, R. K., Lister, R., et al. (2020) · UWA Profiles and Research Repository (University of Western Australia) · Cited by 10
Deng, B., Ma, M.-Q., Deng, W., Zhang, H., Du, X., Pan, B., Wan, X. H., & Cao, C. (2025) · FEBS Journal · doi:10.1111/febs.70302 · Cited by 8
Characterization of gene expression in the kidney of renal tubular cell-specific NFAT5 knockout mice
Ono, M., Izumi, Y., Maruyama, K., Yasuoka, Y., Hiramatsu, A., Aramburu, J. F., López‐Rodríguez, C., Nonoguchi, H., Kakizoe, Y., Adachi, M., et al. (2023) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00233.2023 · Cited by 8
Li, X., Fei, Y., Luo, X., Zhang, B., Wang, C., Adiham, A., Wang, L., & Gong, P. (2024) · Food Bioscience · doi:10.1016/j.fbio.2024.104886 · Cited by 9
Nelson, J. W., McDonough, A. A., Xiang, Z., Ralph, D. L., Robertson, J. A., Giani, J. F., Bernstein, K. E., & Gurley, S. B. (2021) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00014.2021 · Cited by 8
Novel anti-inflammatory effects of the IL-1 receptor in kidney myeloid cells following ischemic AKI
Chen, Y., Lu, X., Whitney, R. L., Yu, L., Robson, M. J., Blakely, R., Chi, J., Crowley, S. D., & Privratsky, J. R. (2024) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2024.1366259 · Cited by 7
Consensus draft of the native mouse podocyte-ome
Hutzfeldt, A. D., Tan, Y., Bonin, L. L., Beck, B. B., Baumbach, J., Lassé, M., Demir, F., & Rinschen, M. M. (2022) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00058.2022 · Cited by 7
Kurlekar, S., Lima, J. D. C. C., Li, R., Lombardi, O., Masson, N., Barros, A. B., Pontecorvi, V., Mole, D. R., Pugh, C. W., Adam, J., et al. (2024) · Cancer Research · doi:10.1158/0008-5472.can-23-3248 · Cited by 8
Nilsson, L. M., Castresana-Aguirre, M., Scott, L., & Brismar, H. (2020) · Scientific Reports · doi:10.1038/s41598-020-67361-3 · Cited by 7
Du, H., Yang, K., He, Z., Su, L., Tan, X., Li, Z., Song, W., Cao, L., & Ma, Y. (2025) · Poultry Science · doi:10.1016/j.psj.2025.105006 · Cited by 6
Villani, V., Nicolas, C., Cravedi, P., Hou, X., Bin, S., Kamitakahara, A. K., Barbati, C., Buono, R., Sacco, S. D., Lemley, K. V., et al. (2024) · Science Translational Medicine · doi:10.1126/scitranslmed.adl5514 · Cited by 6
Circadian gene expression in mouse renal proximal tubule
Bingham, M. A., Neijman, K., Yang, C., Aponte, A. M., Mak, A., Kikuchi, H., Jung, H. J., Poll, B. G., Raghuram, V., Park, E., et al. (2023) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00231.2022 · Cited by 6
Self-citationCutaneous Arsenical Exposure Induces Distinct Metabolic Transcriptional Alterations of Kidney Cells
Moore, K. H., Boitet, L. M., Chandrashekar, D. S., Traylor, A., Esman, S. K., Erman, E. N., Srivastava, R. K., Khan, J., Athar, M., Agarwal, A., et al. (2023) · Journal of Pharmacology and Experimental Therapeutics · doi:10.1124/jpet.123.001742 · Cited by 6
Agoro, R., Myslinski, J., Marambio, Y. G., Janosevic, D., Jennings, K. N., Liu, S., Hibbard, L. M., Fang, F., Ni, P., Noonan, M. L., et al. (2024) · Kidney International · doi:10.1016/j.kint.2024.12.014 · Cited by 9
Maekawa, H., Zhou, Y., Aoi, Y., Fain, M. E., Kaminski, D., Kong, H., Sebo, Z. L., Chakrabarty, R. P., Howard, B. C., Andersen, G. D., et al. (2025) · Journal of Clinical Investigation · doi:10.1172/jci188933 · Cited by 8
HIFα isoform specific activities drive cell-type specificity of VHL-associated oncogenesis
Lima, J. D. C. C., Hooker, M., Li, R., Barros, A. B., Masson, N., Pugh, C. W., Mole, D. R., Adam, J., Ratcliffe, P. J., & Kurlekar, S. (2025) · Nature Communications · doi:10.1038/s41467-025-64214-3 · Cited by 5
Kcnma1 alternative splicing in mouse kidney: regulation during development and by dietary K+ intake
Whelan, S. C., Mutchler, S. M., Han, A., Priestley, C., Satlin, L. M., Kleyman, T. R., & Shi, S. (2024) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00100.2024 · Cited by 5
Comparative analysis of mouse strains for in vivo induction of reprogramming factors
Picó, S., Vílchez-Acosta, A., de Sousa, J. A., Maza, M. D. C. L., Mrabti, C., Parras, A., Desdín-Micó, G., Maroun, C. Y., Branchina, C., von Meyenn, F., et al. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115879 · Cited by 7
Early Molecular Events Mediating Loss of Aquaporin-2 during Ureteral Obstruction in Rats
Sung, C., Poll, B. G., Lin, S., Murillo‐de‐Ozores, A. R., Chou, C., Chen, L., Yang, C., Chen, M., Hsu, Y., & Knepper, M. A. (2022) · Journal of the American Society of Nephrology · doi:10.1681/asn.2022050601 · Cited by 5
Self-citationRiojas, A. M., Reeves, K. D., Shade, R. E., Puppala, S., Christensen, C. L., Birnbaum, S., Glenn, J. P., Li, C., Shaltout, H. A., Hall-Ursone, S., et al. (2022) · Physiological Genomics · doi:10.1152/physiolgenomics.00144.2021 · Cited by 5
Dowling, P., Zweyer, M., Raucamp, M., Henry, M. A., Meleady, P., Swandulla, D., & Ohlendieck, K. (2020) · Data in Brief · doi:10.1016/j.dib.2019.105067 · Cited by 4
Miao, X., Huang, Y., Ge, K. X., & Xu, Y. (2025) · Frontiers in Bioscience-Landmark · doi:10.31083/fbl26200 · Cited by 3
Pan, L., Garcia, S. G., Font‐Morón, M., Sanroque‐Muñoz, M., Clos‐Sansalvador, M., Garcia, G. D. M., Borràs, F. E., & Franquesa, M. (2025) · Extracellular Vesicles and Circulating Nucleic Acids · doi:10.20517/evcna.2025.54 · Cited by 3
Kcnn4/KCa3.1 inhibition blunts polycystic kidney disease progression in mouse models
Yao, G., Kurbegovic, A., Parrot, C., Foley, W., Roman, W., Alper, S. L., & Trudel, M. (2025) · JCI Insight · doi:10.1172/jci.insight.191311 · Cited by 3
McDermott, J. G., Goodlett, B. L., Creed, H. A., Navaneethabalakrishnan, S., Rutkowski, J. M., & Mitchell, B. M. (2024) · Kidney & Blood Pressure Research · doi:10.1159/000539721 · Cited by 3
Suzuki, Y., Kaseda, R., Nakagawa, Y., Watanabe, H., Otsuka, T., Yamamoto, S., Kaneko, Y., Goto, S., Matsusaka, T., & Narita, I. (2024) · Clinical and Experimental Nephrology · doi:10.1007/s10157-024-02608-1 · Cited by 3
Milner, A. R., Johnson, A. C., Attipoe, E. M., Wu, W., Challagundla, L., & Garrett, M. R. (2025) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00258.2024 · Cited by 3
Rasking, L., Vanbrabant, K., Sun, P., Vangeneugden, M., Strauch, M., Schins, R. P. F., Cassee, F. R., Bové, H., Vusser, K. D., Nawrot, T. S., et al. (2025) · Environmental Research · doi:10.1016/j.envres.2025.122458 · Cited by 3
Zhang, X., Hu, S., Xiang, X., Li, Z., Chen, Z., Xia, C., He, Q., Jin, J. F., & Chen, H. (2024) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2024.167206 · Cited by 3
The effect of background noise and its removal on the analysis of single-cell expression dataPreprint
Janssen, P., Kliesmete, Z., Vieth, B., Adiconis, X., Simmons, S., Marshall, J. L., Aubin, C., Heyn, H., Levin, J. Z., Enard, W., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.16.516780 · Cited by 3
A knowledge-guided kidney cell census—reconciling bulk omics with cellular heterogeneity?
Rinschen, M. M., & Müller, R. (2019) · Kidney International · doi:10.1016/j.kint.2018.12.016 · Cited by 2
Hsiao, H., Yen, T., Wu, F.-Y., Cheng, C., Liu, J., Fan, Y., Huang, J., & Nien, C.-Y. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms242115547 · Cited by 2
Chade, A., Sivasankaran, S. K., Sitz, R., McCarthy, E. A., & Eirin, A. (2025) · Kidney360 · doi:10.34067/kid.0000000945 · Cited by 2
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
