Literature DB >> 30574498

Understanding the Biology and Pathogenesis of the Kidney by Single-Cell Transcriptomic Analysis.

Yuting Ye1, Hui Song1, Jiong Zhang1, Shaolin Shi1.   

Abstract

BACKGROUND: Single-cell RNA-seq (scRNA-seq) has recently emerged as a revolutionary and powerful tool for biomedical research. However, there have been relatively few studies using scRNA-seq in the field of kidney study.
SUMMARY: scRNA-seq achieves gene expression profiling at single-cell resolution in contrast with the conventional methods of gene expression profiling, which are based on cell population and give averaged values of gene expression of the cells. Single-cell transcriptomic analysis is crucial because individual cells of the same type are highly heterogeneous in gene expression, which reflects the existence of subpopulations, different cellular states, or molecular dynamics, of the cells, and should be resolved for further insights. In addition, gene expression analysis of tissues or organs that usually comprise multiple cell types or subtypes results in data that are not fully applicable to any given cell type. scRNA-seq is capable of identifying all cell types and subtypes in a tissue, including those that are new or present in small quantity. With these unique capabilities, scRNA-seq has been used to dissect molecular processes in cell differentiation and to trace cell lineages in development. It is also used to analyze the cells in a lesion of disease to identify the cell types and molecular dynamics implicated in the injury. With continuous technical improvement, scRNA-seq has become extremely high throughput and cost effective, making it accessible to all laboratories. In the present review article, we provide an overall review of scRNA-seq concerning its history, improvements, and applications. In addition, we describe the available studies in which scRNA-seq was employed in the field of kidney research. Lastly, we discuss other potential uses of scRNA-seq for kidney research. KEY MESSAGE: This review article provides general information on scRNA-seq and its various uses. Particularly, we summarize the studies in the field of kidney diseases in which scRNA-seq was used and discuss potential additional uses of scRNA-seq for kidney research.

Entities:  

Keywords:  Cell subpopulation; Cell type identification; Gene expression dynamics; Kidney; Single-cell RNA-seq

Year:  2018        PMID: 30574498      PMCID: PMC6276756          DOI: 10.1159/000492470

Source DB:  PubMed          Journal:  Kidney Dis (Basel)        ISSN: 2296-9357


  84 in total

1.  Single-cell transcriptional analysis of neuronal progenitors.

Authors:  Ian Tietjen; Jason M Rihel; Yanxiang Cao; Georgy Koentges; Lisa Zakhary; Catherine Dulac
Journal:  Neuron       Date:  2003-04-24       Impact factor: 17.173

2.  Single-cell transcript analysis of pancreas development.

Authors:  Ming-Ko Chiang; Douglas A Melton
Journal:  Dev Cell       Date:  2003-03       Impact factor: 12.270

3.  AMPA receptor subunits expressed by single Purkinje cells.

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Journal:  Neuron       Date:  1992-08       Impact factor: 17.173

4.  Heterogeneous distribution of chloride channels along the distal convoluted tubule probed by single-cell RT-PCR and patch clamp.

Authors:  Antoine Nissant; Stéphane Lourdel; Sophie Baillet; Marc Paulais; Pedro Marvao; Jacques Teulon; Martine Imbert-Teboul
Journal:  Am J Physiol Renal Physiol       Date:  2004-07-27

5.  Analysis of gene expression in single live neurons.

Authors:  J Eberwine; H Yeh; K Miyashiro; Y Cao; S Nair; R Finnell; M Zettel; P Coleman
Journal:  Proc Natl Acad Sci U S A       Date:  1992-04-01       Impact factor: 11.205

6.  The transcriptional landscape of the yeast genome defined by RNA sequencing.

Authors:  Ugrappa Nagalakshmi; Zhong Wang; Karl Waern; Chong Shou; Debasish Raha; Mark Gerstein; Michael Snyder
Journal:  Science       Date:  2008-05-01       Impact factor: 47.728

7.  Intrarenal cells, not bone marrow-derived cells, are the major source for regeneration in postischemic kidney.

Authors:  Fangming Lin; Ashley Moran; Peter Igarashi
Journal:  J Clin Invest       Date:  2005-07       Impact factor: 14.808

8.  Evidence that fibroblasts derive from epithelium during tissue fibrosis.

Authors:  Masayuki Iwano; David Plieth; Theodore M Danoff; Chengsen Xue; Hirokazu Okada; Eric G Neilson
Journal:  J Clin Invest       Date:  2002-08       Impact factor: 14.808

9.  Recruitment of podocytes from glomerular parietal epithelial cells.

Authors:  Daniel Appel; David B Kershaw; Bart Smeets; Gang Yuan; Astrid Fuss; Björn Frye; Marlies Elger; Wilhelm Kriz; Jürgen Floege; Marcus J Moeller
Journal:  J Am Soc Nephrol       Date:  2008-12-17       Impact factor: 10.121

Review 10.  RNA-Seq: a revolutionary tool for transcriptomics.

Authors:  Zhong Wang; Mark Gerstein; Michael Snyder
Journal:  Nat Rev Genet       Date:  2009-01       Impact factor: 53.242

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  1 in total

1.  Single-cell RNA profiling of glomerular cells in diabetic kidney: a step forward for understanding diabetic nephropathy.

Authors:  María José Soler; Daniel Batlle
Journal:  Ann Transl Med       Date:  2019-12
  1 in total

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