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基于ChIP-Seq数据分析前列腺癌中雄激素受体相关基因

Identification and Functional Annotation of Genome-wide AR-regulated Genes in Prostate Cancer Based on ChIP-Seq data

【作者】 荆鑫华

【导师】 沈百荣;

【作者基本信息】 苏州大学 , 系统生物学, 2013, 硕士

【摘要】 雄激素受体(AR)是属于核受体超家族中一种非常重要的类固醇受体。在细胞内AR的主要功能是作为转录因子与DNA结合调控基因表达。虽然雄激素受体在前列腺癌治疗中扮演重要角色,但是它的作用机制还不是很清楚。本文利用前列腺癌相关的ChIP-Seq数据,对雄激素受体在基因组上的结合位点做了生物信息学的注释和分析,以期找到在前列腺癌中AR相关的生物调控通路。对来自于三种前列腺癌细胞系的6组数据的分析发现,AR在基因组上的结合区大部分落在内含子上,平均比例约为83.46%;而其它的16.54%则分别落在启动子,增强子,外显子,3’UTR区,5’UTR区,转录起始位点下游区和基因间区。查找AR结合的启动子序列发现了4条新的AR结合序列的motif。对AR调控的基因功能富集分析得到了21个GeneOntology条目,1条KEGG通路和26条GeneGo通路。分别对基因和富集通路之间的重复性分析验证了不同数据集的分子特征在系统水平上的相似性高于基因水平上的相似性。对26条GeneGo通路的文献报道验证发现其中5条被之前的研究报道过,其它的21条为新通路,并通过前列腺癌相关的基因表达数据和microRNA数据验证了它们与前列腺癌的相关性。

【Abstract】 As a member of Nuclear Receptor Superfamily, Androgen Receptor (AR) is animportant steroid receptor. The most important role of AR is acting as a DNA-bindingtranscript factor which regulates gene expression. AR is an important therapy target ofprostate cancer, but the mechanism of action is still unclear. In this study, we annotatedthose AR binding gens in the genome by ChIP-Seq data, and tried to discover some novelbiological pathways in prostate cancer. Analysis on6ChIP-Seq datasets from threeprostate cancer cell lines indicated that83.46%of AR binding sites were located in theintron region; the other16.54%located in the promoter, enhancer, exon,3’UTR,5’UTR,downstream and intergenic region, respectively. In the promoter region we found4novelAR binding motifs. The enrichment analysis of AR-binding genes identified21GeneOntology terms,1KEGG pathway and26GeneGo pathways. The pair-wise overlapanalysis for AR binding genes and AR related pathways verified the hypothesis that thesignificant signatures of different data sets are more similar at pathway level than at genelevel. Literature validation of26GeneGo pathways demonstrated that5pathways had beenreported previously, the rest21are novel pathways. We also verified association of thesenovel pathways and prostate cancer by prostate cancer related gene expression data andmicroRNA data.

  • 【网络出版投稿人】 苏州大学
  • 【网络出版年期】2013年 11期
  • 【分类号】R737.25
  • 【下载频次】382
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