Literature DB >> 30963776

Explorative analysis of the gene expression profile during liver regeneration of mouse: a microarray-based study.

Li Yin1, Yuanyuan Wang1, Yingzi Lin1, Guoying Yu2, Qianfeng Xia1.   

Abstract

The liver is an amazing organ due to its powerful regenerative capacity. Although many studies on liver regeneration have been documented, the detailed mechanisms remain unclear. Two-third partial hepatectomy (PH) in rodents plays a crucial role in the study of liver regeneration. In this study, the time series data of gene expression during liver regeneration in mouse were analyzed using the gene set numbered GSE6998 in GEO. A variety of bioinformatics methods, including masigPro, Weighted Gene Co-expression Network Analysis (WGCNA), spatial analysis of functional enrichment (SAFE) and ingenuity canonical pathway analysis (IPA) were used to identify and compare the significantly changed pathways, potential upstream regulators and key genes during liver regeneration. Our study showed that liver regeneration in the mouse is a coordinated process, which cell-cycle-related progress are at the centre of the interaction network involved in liver regeneration. Several candidate upstream regulators including PPARA, NFE2L2, MAD1 and CNR1 and some key genes such as Cdk1, Plk1, Cdc20, Aurka, Racgap1, Cenpa, Rrm1, Rrm2 were identified. In conclusion, these findings could contribute to revealing the molecular mechanism of liver regeneration after PH, which could provide new ideas and treatment methods for regenerative medicine, oncological drug development and oncological treatment.

Entities:  

Keywords:  Liver regeneration; SAFE; WGCNA; cell cycle; cytoscape; maSigPro

Mesh:

Year:  2019        PMID: 30963776     DOI: 10.1080/21691401.2019.1593851

Source DB:  PubMed          Journal:  Artif Cells Nanomed Biotechnol        ISSN: 2169-1401            Impact factor:   5.678


  3 in total

1.  Bayesian approach for predicting responses to therapy from high-dimensional time-course gene expression profiles.

Authors:  Arika Fukushima; Masahiro Sugimoto; Satoru Hiwa; Tomoyuki Hiroyasu
Journal:  BMC Bioinformatics       Date:  2021-03-18       Impact factor: 3.169

2.  RNA-Seq transcriptome profiling in three liver regeneration models in rats: comparative analysis of partial hepatectomy, ALLPS, and PVL.

Authors:  Dilek Colak; Olfat Al-Harazi; Osama M Mustafa; Fanwei Meng; Abdullah M Assiri; Dipok K Dhar; Dieter C Broering
Journal:  Sci Rep       Date:  2020-03-23       Impact factor: 4.379

3.  Identification of circulating hub long noncoding RNAs associated with hypertrophic cardiomyopathy using weighted correlation network analysis.

Authors:  Qi Guo; Junjie Wang; Runlu Sun; Wenli Gu; Zhijian He; Qian Chen; Wenhao Liu; Yangxin Chen; Jingfeng Wang; Yuling Zhang
Journal:  Mol Med Rep       Date:  2020-10-06       Impact factor: 2.952

  3 in total

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