Literature DB >> 29622724

Single-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease.

Jihwan Park1, Rojesh Shrestha1, Chengxiang Qiu1, Ayano Kondo1, Shizheng Huang1, Max Werth2, Mingyao Li3, Jonathan Barasch2, Katalin Suszták4.   

Abstract

Our understanding of kidney disease pathogenesis is limited by an incomplete molecular characterization of the cell types responsible for the organ's multiple homeostatic functions. To help fill this knowledge gap, we characterized 57,979 cells from healthy mouse kidneys by using unbiased single-cell RNA sequencing. On the basis of gene expression patterns, we infer that inherited kidney diseases that arise from distinct genetic mutations but share the same phenotypic manifestation originate from the same differentiated cell type. We also found that the collecting duct in kidneys of adult mice generates a spectrum of cell types through a newly identified transitional cell. Computational cell trajectory analysis and in vivo lineage tracing revealed that intercalated cells and principal cells undergo transitions mediated by the Notch signaling pathway. In mouse and human kidney disease, these transitions were shifted toward a principal cell fate and were associated with metabolic acidosis.
Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

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Year:  2018        PMID: 29622724      PMCID: PMC6188645          DOI: 10.1126/science.aar2131

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  30 in total

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2.  Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.

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3.  Deep Sequencing in Microdissected Renal Tubules Identifies Nephron Segment-Specific Transcriptomes.

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4.  The Human Cell Atlas: from vision to reality.

Authors:  Orit Rozenblatt-Rosen; Michael J T Stubbington; Aviv Regev; Sarah A Teichmann
Journal:  Nature       Date:  2017-10-18       Impact factor: 49.962

5.  Comprehensive single-cell transcriptional profiling of a multicellular organism.

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Journal:  Science       Date:  2017-08-18       Impact factor: 47.728

6.  Collecting duct-derived cells display mesenchymal stem cell properties and retain selective in vitro and in vivo epithelial capacity.

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7.  Single-cell RNA-sequence analysis of mouse glomerular mesangial cells uncovers mesangial cell essential genes.

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Journal:  Nat Genet       Date:  2014-05-11       Impact factor: 38.330

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  338 in total

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Journal:  J Am Soc Nephrol       Date:  2018-12-03       Impact factor: 10.121

2.  Global transcriptomic changes occur in aged mouse podocytes.

Authors:  Yuliang Wang; Diana G Eng; Natalya V Kaverina; Carol J Loretz; Abbal Koirala; Shreeram Akilesh; Jeffrey W Pippin; Stuart J Shankland
Journal:  Kidney Int       Date:  2020-06-25       Impact factor: 10.612

3.  AP-2β/KCTD1 Control Distal Nephron Differentiation and Protect against Renal Fibrosis.

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5.  Loss of IL-27Rα Results in Enhanced Tubulointerstitial Fibrosis Associated with Elevated Th17 Responses.

Authors:  Gaia M Coppock; Lillian R Aronson; Jihwan Park; Chengxiang Qiu; Jeongho Park; Jonathan H DeLong; Enrico Radaelli; Katalin Suszták; Christopher A Hunter
Journal:  J Immunol       Date:  2020-06-10       Impact factor: 5.422

Review 6.  Kidney and organoid single-cell transcriptomics: the end of the beginning.

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Journal:  Pediatr Nephrol       Date:  2019-01-04       Impact factor: 3.714

7.  Next generation sequencing data for use in risk assessment.

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8.  ATAC-ing the mechanisms of renin regulation.

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Review 9.  Emerging Kidney Models to Investigate Metabolism, Transport, and Toxicity of Drugs and Xenobiotics.

Authors:  Piyush Bajaj; Swapan K Chowdhury; Robert Yucha; Edward J Kelly; Guangqing Xiao
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10.  SingleCellNet: A Computational Tool to Classify Single Cell RNA-Seq Data Across Platforms and Across Species.

Authors:  Yuqi Tan; Patrick Cahan
Journal:  Cell Syst       Date:  2019-07-31       Impact factor: 10.304

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