Hypoxia on vhl-deficient cells to obtain hif related genes through bioinformatics analysis

Vhl is responsible for degrading the transcription factor hif-1. Hif-1 transcription factors drive changes in hypoxic gene expression to adapt cells to exposure to hypoxic environments. This study hopes to analyze the effect of hypoxia on the vhl-deficient cells to obtain hif regulated genes through bioinformatics analysis. The top ten genes evaluated by connectivity degree in the PPI network were identified. CDK1, CTNNB1, NHP2, CCNA2, CTNNB1, MRPL16, CCND1 were down-regulated. CDK1, RPL12, RPL17, RPL27, RPS10 were up-regulated.


Introduction
Vhl is responsible for degrading the transcription factor hif-1. Hif-1 transcription factors drive changes in hypoxic gene expression to adapt cells to exposure to hypoxic environments. Hypoxia active the heterodimeric transcription factor hif-1 to trigger a synergistic transcriptional response resulting in solid tumours. 3 under oxygen deprivation hif1 is an essential helix-loop-helix PAS domain transcription factor. [4][5][6][7] Hif-1α dimerizes with hif-1β in the nucleus, hif-1 decreased the speed of degrading under hypoxia condition. Hypoxia response elements are the heterodimer of hif-1 binding to regulatory DNA sequences. Transcriptional co-activators Promote angiogenesis through enhancing the transcription of a lot of target genes. 4,5,8 Vhl gene is a tumour suppressor gene, and its proteins pvHL30 and pVHLl9. It has the function of tumour inhibition, and the two structures are similar, which are collectively called vhl protein(pvHL).
Hypoxia-inducible factor hif gene is a target gene of vhl gene. hif is an oxygen-dependent transcriptional activator produced by cells during hypoxia, by only B subunits. Oxygen regulates hif activity primarily through hif-a. For cell growth, inhibition of hif1 expression can be promoted, causing the death of the cells under hypoxia condition.
Therefore, this study hopes to analyze the effect of hypoxia on the vhl-deficient cells to obtain hif regulated genes through bioinformatics analysis.

Materials and methods
GPL3423: Stanford Denko EOS Human 35K GeneChip v1.1. All of the data we're freely available online. This study has not been reported by any experiment on humans and declared by any other authors.

PPI network construction and hub gene identification
In this study, we use the Search Tool for the Retrieval of Interacting Genes (STRING) database (http://string-db.org/) and GeneMANIA online database (https://genemania.org/) to analyze the PPI information and evaluate the potential PPI relationship. They were also used to identify the DEGs to analysis the PPI information. A combined score was set to 0.4, and then the PPI network was visualized by Cytoscape software (www.cytoscape.org/). The stability of the entire system was guaranteed by a higher degree node of connectivity. We calculated the degree of each protein node by using CytoHubba, a plugin in Cytoscape. Through those steps, we can select ten hub genes. 18

Identification of DEGs
Gene expression profile (GDS1772) was selected in this study. GDS1772 contained vhl minus and vhl plus samples. Based on the criteria of P＜ 0.05 and |logFC|≥1, the first group of control without hypoxia and the third group hypoxia-reoxygenation have no differential genes with each other. The second group of hypoxia, we found that a total of 376 DEGs were identified from vhl minus samples compared with vhl plus samples, including 162 upregulated genes and 214 downregulated genes( Table 2).

Functional enrichment analyses of DEGs
GO function and KEGG pathway enrichment analysis for DEGs were performed using the Cytoscape software(  (Table 4). Table 3 The enrichment analysis of differentially expressed genes between vhl minus and vhl plus * Pvalue<0.05

PPI network construction and hub gene identification
Protein interactions among the DEGs were predicted with STRING tools and GeneMANIA online database. A total of 268 nodes and 428 edges were involved in the PPI network, as presented in Figure 1. The top ten genes evaluated by connectivity degree in the PPI network were identified. The results showed that ribosomal protein L12(RPL12) was the most outstanding gene with connectivity degree=12, followed by ribosomal protein L27(RPL27; degree=13), ribosomal protein L17(RPL17; degree=10), ribosomal protein S10(RPS10; degree=11), NHP2 ribonucleoprotein(NHP2; degree=10), cyclin D1(CCND1;degree=21), cyclin A2(CCNA2; degree=14), mitochondrial ribosomal protein L16(MRPL16; degree=10), cyclin-dependent kinase 1(CDK1; degree=15), catenin beta 1(CTNNB1; degree=20). All of these hub genes were upregulated in vhl plus. However, overexpressed CyclinA2 weaken the proliferation of cardiomyocytes suggesting that CyclinA2 is an essential part of regulating cardiomyocytes growth and increasing protection of cardiomyocytes from disability of proliferation in hypoxic conditions. 9 A few days after birth, the proliferative function of mammals' cardiomyocytes almost lost because of the sharp down-regulation of CyclinA2 in the heart. 10 Previous studies indicated that in the adult heart CyclinA2 almost have no function. Increasing the content of CyclinA2 in adult animals' heart can make a difference in restoration of cardiac proliferation. 10 have not been reported, which would be the direction of our follow-up study.