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Screening of differentially expressed genes associated with non-union skeletal fractures and analysis with a DNA microarray

机译:与骨不连骨骨折相关的差异表达基因的筛选和DNA微阵列分析

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摘要

The purpose of this study was to identify the feature genes that are associated with non-union skeletal fractures using samples of normal union and non-union skeletal fracture microarray data. The gene expression profile was downloaded from the Gene Expression Omnibus database and included 12 samples based on three different platforms (, and ). Each of the platforms had four sets of expression data, two from normal union skeletal fracture samples and two from non-union skeletal fracture samples. The differentially expressed genes within the three platforms of expression data were identified using packages in R language and the differentially expressed genes common to the three platforms were selected. The selected common differentially expressed genes were further analyzed using bioinformatic methods. The software HitPredict was used to search interactions of the common differentially expressed genes and then FuncAssociate was used to conduct a functional analysis of the genes in the interaction network. Further, the associated pathways were identified using the software WebGestalt. Under the three different platforms, , and , the numbers of differentially expressed genes identified were 531, 418 and 914, respectively. The common gene CLU and its interacting genes were most significantly associated with the regulation of sterol transport and the osteoclast differentiation pathway. Upregulation of the gene CLU was identified by comparing data for normal union and non-union skeletal fracture samples. According to the function of CLU and its interacting genes, it was concluded that they inhibit the normal healing process following a fracture, and result in non-union skeletal fractures through the regulation of sterol transport and the pathways of differentiation in osteoclasts.
机译:这项研究的目的是使用正常的联合和非联合骨骼骨折微阵列数据样本来鉴定与非联合骨骼骨折相关的特征基因。基因表达谱是从Gene Expression Omnibus数据库下载的,包括基于三个不同平台(和)的12个样品。每个平台都有四组表达数据,两组来自正常联合骨骼骨折样本,两组来自非骨干骨折样本。使用R语言中的程序包识别三个表达平台中的差异表达基因,并选择三个平台共有的差异表达基因。使用生物信息学方法进一步分析选择的共同差异表达基因。使用HitPredict软件搜索常见差异表达基因的相互作用,然后使用FuncAssociate对相互作用网络中的基因进行功能分析。此外,使用软件WebGestalt可以识别相关的途径。在和的三个不同平台上,鉴定出的差异表达基因的数量分别为531、418和914。共同基因CLU及其相互作用基因与固醇转运和破骨细胞分化途径的调节最显着相关。基因CLU的上调是通过比较正常联合和非联合骨骼骨折样本的数据来确定的。根据CLU及其相互作用基因的功能,可以得出结论,它们抑制骨折后的正常愈合过程,并通过调节固醇转运和破骨细胞的分化途径导致不愈合的骨骼骨折。

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