Integrate analysis and identification for different expression genes in chondrogenesis

Background: The intricate mechanisms of articular chondrogenesis are largely unknown. Gradually, with the help of high-throughput platforms, microarrays have become an important and useful method to testify hub genes in desease. Today, advanced bioinformatic analysis of available microarray data can provide more reliable and accurate screening results by duplicating related data sets. Results: Microarray datasets GSE9451 and GSE104113 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were performed, and function enrichment analyses were demonstrated. The protein-protein interaction network (PPI) was constructed and the module analysis was performed by using STRING and Cytoscape. Quantitative PCR was used to confirm the results of bioinformatics analysis. Conclusion: Compared to individual studies, this study can provide extra reliable and accurate screening results by duplicating relevant records. Additional molecular experiments are required to confirm the discovery of candidate genes identified by chondrogenesis. S100A4 is predicted to integrate with miR-325-3p to promote osteogenesis. of the underlying mechanisms of chondrogenesis contribute to the and prognosis evaluation. In this research, by analyzing data of gene GSE9451 and GSE104113 microarrays, we screened 297 DMRs-up expression genes and 373 DMRs-down expression genes, using several bioinformatics tools. Enrichment of these genes indicates specific

Gradually, with the help of high-throughput platforms, microarrays have become an important and useful method to testify hub genes in casino and screen biomarkers of cancer [5]. Some specific genes influence chondrogenesis [1]. Gene expression profiling microarrays of chondrogenesis have been made to screen multiple differentially expressed genes (GES9451, GSE104113) [6]. However, individual studies using a limited number of overlapping gene profiles have high false-positive rates, not sufficient to identify pathways and important genes involved in various cellular processes and biological functions. Today, advanced bioinformatic analysis of available microarray data can provide more reliable and accurate screening results by duplicating related data sets.
So far, chondrogenic microarrays have no gene expression profiling results together with the other. In this study, using a series of bioinformatic tools analyzed microarray data. Gene expression profile biochips (GSE9451) and (GSE104113) were integrated and analyzed. In chondrogenesis, DEG pathways have been identified.
Networks of protein-protein interaction was established and essential genes were revealed. By using PCR technology for verification to find diagnostic markers, we fought new molecules and pathways in cartilage formation and reveal the potential molecular mechanisms that regulate cartilage formation.

Normalization of aberrantly expressed genes in chondrogenesis
The data of each microarray were respectively analyzed by GEO2R to identify GSE9451 (1515 up-regulated, 1564 down-regulated) and GSE104113 (425 upregulated, 328 down-regulated)( Fig. 1 & Fig. 2).Subsequently, by overlapping DEGs respectively, we acquired 42 DEG-down expression genes and 38 DEG-up expression genes ( Hub gene analysis and QRT-PCR confirmation A total of 5 genes were identified as hub genes. Names, full names and functions of these hub genes are shown in Table 1. The forward and reverse primers for each gene are listed in Table 2. Two genes (LGR5, S100A4) were upregulated and the other 3 were downregulated. The expression hub genes were consistent with our integrated analysis (Fig. 8). Keratin, type I cytoskeletal 18 Involved in the uptake of thrombin-antithrombin complexes by hepatic cells.
Together with KRT8, is involved in interleukin-6 (IL-6)-mediated barrier protection. KRT34 Keratin, type I cuticular Ha4 The protein encoded by this gene is a member of the keratin gene family. S100A4 Protein S100-A4 Involved in the regulation of a number of cellular processes such as cell cycle progression and differentiation. S100 genes include at least 13 members which are located as a cluster on chromosome 1q21. This protein may function in motility, invasion, and tubulin polymerization. Table 2 Primer sequence for qRT-PCR gene Primers

Discussion
Elucidation of the underlying mechanisms of chondrogenesis contribute to the diagnosis, and prognosis evaluation. In this research, by analyzing data of gene expression GSE9451 and GSE104113 microarrays, we screened 297 DMRs-up expression genes and 373 DMRs-down expression genes, using several bioinformatics tools. Enrichment of these genes indicates specific pathways and central genes affected by aberrant methylation, and could provide novel information on the pathogenesis of chondrogenesis.
KRT19, Involved in the organization of myofibers. Together with KRT8, helps to link the contractile apparatus to dystrophin at the costameres of striated muscle [7].
Intervertebral disc degeneration has been treatment by using Mesenchymal stem cell (MSC)-based therapies [8]. Intervertebral discs receiving chondroprogenitor cells exhibited higher expression of nucleus pulposus-specific human markers KRT19 [9]. Research has shown that perspectives of biomaterials and cellular treatments combining chondrocytes, chondrogenesis and MSC are optimistic [10].
Therefore, KRT19 can be the master regulators of chondrogenesis. This potentially provides new cell candidates for chondrogenesis treatment.
LGR5, Receptor for R-spondins that potentiates the canonical Wnt signaling pathway and acts as a stem cell marker of the intestinal epithelium and the hair follicle [11].
Upon binding to R-spondins, associates with phosphorylated LRP6 and frizzled receptors that are activated by extracellular Wnt receptors, triggering the canonical Wnt signaling pathway to increase expression of target genes. Involved in the development and/or maintenance of the adult intestinal stem cells during postembryonic development [12][13][14]. Recently study has shown that inhibition of Bone morphogenetic protein (BMP) signaling activate LGR5 + cells during inflammation [15,16]. Thus, LGR5 can be a novel marker of chondrogenesis.
KRT18 was involved in the uptake of thrombin-antithrombin complexes by hepatic cells. When phosphorylated, plays a role in filament reorganization. Involved in the delivery of mutated CFTR to the plasma membrane. Together with KRT8, is involved in interleukin-6 (IL-6)-mediated barrier protection [17,18]. A study showed that nucleus pulposus derived stem cells (NPDCs) keep the regeneration ability similar to BMSCs [19]. Research has confirmed that KRT18 was nucleus pulposus specific gene [20]. So KRT18 can be a key growth factor of chondrogenesis KRT34, the protein encoded by this gene is a member of the keratin gene family. As a type I hair keratin, it is an acidic protein which heterodimerizes with type II keratins to form hair and nails. The type I hair keratins are clustered in a region of chromosome 17q12-q21 and have the same direction of transcription [21,22]. alternatively spliced variants, encoding the same protein, have been identified [24,25]. S100A4 has been used as osteoarthritis markers in research [26]. By using Target Scan (v7.2) [27], S100A4 is predicted to integrate with miR-325-3p to promote osteogenesis. But the molecular mechanisms require further research.

Conclusion
In summary, our study united bioinformatics analysis of gene expressed microarrays to disclose the following factor: organization of myofibers, the development and/or maintenance of the intestinal stem cells, interleukin-6 (IL-6)-mediated barrier protection, the regulation of a number of cellular processes. Functions of hub genes act as an abnormal biomarker for accurate diagnosis and treatment of future

Microarray data
In this study, the gene expression profiling datasets GSE9451 and GSE104113 were

Data processing
Normalization and background correction of the initial raw data were performed by using R software sva and limma package. Next, probe names were annotated gene symbols according to annotation files, and probe without a corresponding gene symbol was filtered. Subsequently, the average value of gene symbols with multiple probes were calculated and data were log2-transformed. The differently expressed mRNAs were filtered applying R software limma package, with the criterion of |log 2 (fold change) | > 1 and P-value < 0.05. Finally, hierarchical cluster analysis was used R software pheatmap package.

Functional and pathway enrichment analysis of DEGs
To carry out functional and pathway enrichment analysis, an R package called clusterProfiler was used for Note, Visualization and Enrichment Discovery [28]. GO is a professional bioinformatics tool for gene annotation and biological process analysis of these genes [29]. P.adjust< 0.05 was thought as statistically significant.
KEGG is a database for understanding of advanced functions and biological systems of molecular data generated by high-throughput experimental techniques [30]. The software performs an enrichment analysis of top 10 target genes to all known GO and KEGG pathways.
PPI network constructions, module analysis and Hub genes analysis.  Gene ontology analysis of aberrantly expressed genes in chondrogenesis.