| Title |
Identification of key genes and construction of microRNA–mRNA regulatory networks in bladder smooth muscle cell response to mechanical stimuli using microarray expression profiles and bioinformatics analysis
|
|---|---|
| Published in |
World Journal of Urology, November 2017
|
| DOI | 10.1007/s00345-017-2132-3 |
| Pubmed ID | |
| Authors |
Liao Peng, De-Yi Luo |
| Abstract |
To identify keys genes and elucidate miRNA-mRNA regulatory networks in Bladder smooth muscle cell (BSMC) response to mechanical stimuli. Human BSMCs, seeded on a silicone membrane, were subjected to mechanical stretch or without stretch. Microarray was used to analyze the differential expression of mRNAs and miRNAs between human BSMCs under mechanical stretch and control static control group. Differentially expressed genes(DEGs) and miRNAs (DEMs) in these two groups were identified. Subsequently, differentially expressed DEGs were conducted with functional analysis, and then PPI network was constructed. Finally, miRNA-mRNA regulatory network was visualized using Cytoscape. 1639 significant DEGs and three DEMs were identified between the stretch group and control static group. The PPI network of DEGs was constructed by STRING, which was composed of 1459 nodes and 1481 edges, including 188 upregulated genes and 255 downregulated genes. Moreover, 36 genes in the PPI network were identified as hub genes in BSMCs response to mechanical stretch, e.g. CCNH, CPSF2, TSNAX, ARPC5 and PSMD3 genes. Subsequently, 39 clusters were selected from PPI network using MCODE, and it was shown that the most significant cluster consisted of 14 nodes and 91 edges. Besides, miR-503HG was the most significantly downregulated miRNA and was predicted to target five upregulated genes, including SMAD7, CCND3, WIPI2, NYNRIN and PVRL1. Our data mining and integration help reveal the mechanotransduction mechanism of BSMCs' response to mechanical stimulation and contribute to the early diagnosis of bladder outlet obstruction (BOO) as well as the improvement of pathogenesis of BOO treatment. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 50% |
| United Kingdom | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 18% |
| Researcher | 1 | 6% |
| Student > Doctoral Student | 1 | 6% |
| Unknown | 12 | 71% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 18% |
| Psychology | 1 | 6% |
| Medicine and Dentistry | 1 | 6% |
| Unknown | 12 | 71% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 January 2018.
All research outputs
#13,576,042
of 23,012,811 outputs
Outputs from World Journal of Urology
#1,310
of 2,115 outputs
Outputs of similar age
#164,062
of 324,961 outputs
Outputs of similar age from World Journal of Urology
#21
of 38 outputs
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