非编码RNA的生物信息学研究方法:RNA结构预测及其应用  

From sequence to structure:RNA secondary structure prediction methods and the applications

作　　者：张浩文[1] 杨禹丞[1] 鲁志[1] 

机构地区：[1]清华大学生命科学学院生物信息学教育部重点实验室,北京100084

出　　处：《生命科学》2014年第3期219-227,共9页Chinese Bulletin of Life Sciences

基　　金：国家自然科学基金青年基金项目(31100601);国家自然科学基金面上项目(31271402);国家重点基础研究发展计划("973"项目)(2012CB316503);国家高技术研究发展计划("863"项目)(2014AA021100);IBM基金;Bayer基金;罗氏基金

摘　　要：近10多年来的研究逐步揭示了RNA的各种生物学功能。RNA不仅是信息从DNA传递到蛋白质的中间体,还直接参与基因沉默、表观遗传学修饰等生物学过程。单链的RNA在体内通过碱基配对折叠成一定的二级结构。介绍了现在预测RNA二级结构的主要算法及其应用,其中包括基于热力学、同源比对和统计学习的各种算法,以及如何引入实验数据辅助预测。二级结构预测算法被广泛用于寻找RNA功能单元和预测新非编码RNA等各种问题。如何利用高通量实验数据帮助结构预测,探索长非编码RNA功能,研究RNA与蛋白质相互作用,是RNA二级结构预测算法和应用的一些前沿方向。Researches in past 10 years uncovered various biological functions of RNA. Besides as the intermediate to transfer information from DNA to protein, RNA has been shown involved in gene silencing, epigenetic modifications and many other processes. RNAs are transcribed as single strand, fold into secondary structures by base pairing. Here different algorithms of RNA secondary structure prediction and their applications are reviewed, including thermodynamic algorithms, homologous alignments comparison, statistical learning and incorporating experimental data into prediction model. RNA secondary structure prediction algorithms are widely used in detection of RNA functional elements, identification of new non-coding RNAs and other researches. Challenges such as determination of secondary structures transcriptome wide under the help of high-throughput sequencing, assist to long non-coding RNA function discoveries and study of protein-RNA interactions will draw more attentions in this field.

关 键 词：RNA二级结构预测 自由能 共突变 非编码RNA 

分 类 号：Q811.4[生物学—生物工程] Q52