基于生物信息学的miR-1靶基因预测和分析
高阳，罗万俊，张春芳，陈胜喜
基金项目：高等学校博士学科点专项科研基金资助课题(201000162120052)；湖南省科技计划项目(2010FJ6007) 作者简介：高阳（1978－），男，主治医师，主要研究方向：心肺疾病的治疗.

（中南大学湘雅医院心胸外科，长沙 410008） 5
摘要：目的：采用生物信息学的方法对miR-1的靶基因进行预测，并对其集合进行富集分析和生物学描述。方法：分别采取TargetScan和PicTar对miR-1靶基因进行预测，取它们预测结果的合集。采用Cytospace的插件BiNGO和DAVID数据库，获得基因集合的基因本体注释和生物学通路信息并进行富集分析。结果：获得miRNA-1预测的靶基因229个；分子功能富集在生物分子结合、酶调节和催化活动等；生物学过程富集在生物组装、代谢调控、应对刺激、生物合成和代谢等。生物学通路富集在富集于剪接体、囊泡运输中SNARE相互作用和小细胞肺癌。结论：在高通量系统验证方法尚未建立的阶段，采用了生物信息学的方法，可以从miR-1调控网络中提出了进一步研究的线索。
关键词：生物信息学；miR-1；靶基因
中图分类号：R318.04
The Bioinformatics Analysis of Predicted miRNA-1 Targets Genes
GAO Yang, LUO Wanjun, ZHANG Chunfang, CHEN Shenxi
(Department of Cardiothoracic Surgery, Xiangya Hospital, Central South University, Changsha 410008)
Abstract: Objective: We aimed to predict and analyze miR-1 target genes by bioinformatic approaches. Methods: TargetScan and PicTar were used for miR-1 target gene prediction. Using BiNGO and DAVID databases, gene ontology annotations and signaling pathways were analyzed.  Results: After miRNA-1 target prediction and data enrichment, 229 target genes were collected. The data enrichment analysis found these genes may be involved in protein binding, catalytic activity, enzyme regulator activity, response to stimulus, regulation of protein metabolic process, cellular biosynthetic process. Moreover, three related signaling pathways were found. Conclusion: The methods of bioinformatics can provide clues to miR-1 regulatory network researches.
Key words: Bioinformatics; miRNA-1; Targets Genes