Literature DB >> 32649993

Pathway identification through transcriptome analysis.

Takeshi Terabayashi1, Gregory G Germino1, Luis F Menezes2.   

Abstract

Systems-based, agnostic approaches focusing on transcriptomics data have been employed to understand the pathogenesis of polycystic kidney diseases (PKD). While multiple signaling pathways, including Wnt, mTOR and G-protein-coupled receptors, have been implicated in late stages of disease, there were few insights into the transcriptional cascade immediately downstream of Pkd1 inactivation. One of the consistent findings has been transcriptional evidence of dysregulated metabolic and cytoskeleton remodeling pathways. Recent technical developments, including bulk and single-cell RNA sequencing technologies and spatial transcriptomics, offer new angles to investigate PKD. In this article, we review what has been learned based on transcriptional approaches and consider future opportunities. Published by Elsevier Inc.

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Year:  2020        PMID: 32649993      PMCID: PMC9447370          DOI: 10.1016/j.cellsig.2020.109701

Source DB:  PubMed          Journal:  Cell Signal        ISSN: 0898-6568            Impact factor:   4.850


  84 in total

Review 1.  Microarrays: biotechnology's discovery platform for functional genomics.

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Journal:  Trends Biotechnol       Date:  1998-07       Impact factor: 19.536

2.  Visualization and analysis of gene expression in tissue sections by spatial transcriptomics.

Authors:  Patrik L Ståhl; Fredrik Salmén; Sanja Vickovic; Anna Lundmark; José Fernández Navarro; Jens Magnusson; Stefania Giacomello; Michaela Asp; Jakub O Westholm; Mikael Huss; Annelie Mollbrink; Sten Linnarsson; Simone Codeluppi; Åke Borg; Fredrik Pontén; Paul Igor Costea; Pelin Sahlén; Jan Mulder; Olaf Bergmann; Joakim Lundeberg; Jonas Frisén
Journal:  Science       Date:  2016-07-01       Impact factor: 47.728

3.  Beta4 integrin and laminin 5 are aberrantly expressed in polycystic kidney disease: role in increased cell adhesion and migration.

Authors:  Dominique Joly; Viviane Morel; Aurélie Hummel; Antonella Ruello; Patrick Nusbaum; Natacha Patey; Laure-Hélène Noël; Patricia Rousselle; Bertrand Knebelmann
Journal:  Am J Pathol       Date:  2003-11       Impact factor: 4.307

Review 4.  Murine models of polycystic kidney disease: molecular and therapeutic insights.

Authors:  Lisa M Guay-Woodford
Journal:  Am J Physiol Renal Physiol       Date:  2003-12

5.  Expression monitoring by hybridization to high-density oligonucleotide arrays.

Authors:  D J Lockhart; H Dong; M C Byrne; M T Follettie; M V Gallo; M S Chee; M Mittmann; C Wang; M Kobayashi; H Horton; E L Brown
Journal:  Nat Biotechnol       Date:  1996-12       Impact factor: 54.908

6.  Comparative transcriptomics of shear stress treated Pkd1-/- cells and pre-cystic kidneys reveals pathways involved in early polycystic kidney disease.

Authors:  Steven J Kunnen; Tareq B Malas; Chiara Formica; Wouter N Leonhard; Peter A C 't Hoen; Dorien J M Peters
Journal:  Biomed Pharmacother       Date:  2018-10-01       Impact factor: 6.529

Review 7.  The pathobiology of polycystic kidney disease from a metabolic viewpoint.

Authors:  Luis Fernando Menezes; Gregory G Germino
Journal:  Nat Rev Nephrol       Date:  2019-09-05       Impact factor: 28.314

8.  Systems biology approach to identify transcriptome reprogramming and candidate microRNA targets during the progression of polycystic kidney disease.

Authors:  Priyanka Pandey; Shan Qin; Jacqueline Ho; Jing Zhou; Jordan A Kreidberg
Journal:  BMC Syst Biol       Date:  2011-04-25

9.  Loss of cilia suppresses cyst growth in genetic models of autosomal dominant polycystic kidney disease.

Authors:  Ming Ma; Xin Tian; Peter Igarashi; Gregory J Pazour; Stefan Somlo
Journal:  Nat Genet       Date:  2013-07-28       Impact factor: 38.330

10.  A RhoA-YAP-c-Myc signaling axis promotes the development of polycystic kidney disease.

Authors:  Jing Cai; Xuewen Song; Wei Wang; Terry Watnick; York Pei; Feng Qian; Duojia Pan
Journal:  Genes Dev       Date:  2018-06-11       Impact factor: 11.361

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  3 in total

1.  Multiomic identification of factors associated with progression to cystic kidney disease in mice with nephron Ift88 disruption.

Authors:  Chunyan Hu; Katherine Beebe; Edgar J Hernandez; Jose M Lazaro-Guevara; Monica P Revelo; Yufeng Huang; J Alan Maschek; James E Cox; Donald E Kohan
Journal:  Am J Physiol Renal Physiol       Date:  2021-12-20

2.  Identification of pathological transcription in autosomal dominant polycystic kidney disease epithelia.

Authors:  Sebastian Friedrich; Hannah Müller; Caroline Riesterer; Hannah Schüller; Katja Friedrich; Carlotta Leonie Wörner; Tilman Busch; Amandine Viau; E Wolfgang Kuehn; Michael Köttgen; Alexis Hofherr
Journal:  Sci Rep       Date:  2021-07-23       Impact factor: 4.379

Review 3.  Single-Cell RNA Sequencing with Spatial Transcriptomics of Cancer Tissues.

Authors:  Rashid Ahmed; Tariq Zaman; Farhan Chowdhury; Fatima Mraiche; Muhammad Tariq; Irfan S Ahmad; Anwarul Hasan
Journal:  Int J Mol Sci       Date:  2022-03-11       Impact factor: 5.923

  3 in total

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