基于RNA-Seq的长非编码RNA预测
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中国矿业大学,中国矿业大学,中国矿业大学

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中国博士后科学基金资助项目(2012M511335, 2012M511336),中央高校基本科研业务费专项基金资助项目(2010QNA47, 2010QNA50),霍英东教育基金会青年教师基金资助项目(121066)


Prediction of Long Non-Coding RNAs Based on RNA-Seq
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China University of Mining and Technology,China University of Mining and Technology,China University of Mining and Technology

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This work was supported by grants from China Postdoctoral Science Foundation (2012M511335, 2012M511336), The Central Special Fund for Operating Expenses of College Basic Research (2010QNA47, 2010QNA50) and Fok Ying-Tung Education Foundation for Young Teachers (121066)

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    摘要:

    随着新一代生物技术和生物信息学的发展,研究发现,在真核生物转录组中存在大量长非编码RNA(long non-coding RNA,lncRNA),而这些lncRNA可能在基因表达调控过程中起到关键性的功能作用.当前lncRNA研究主要采用高通量RNA-Seq测序技术,并通过生物信息学方法对测序数据进行处理和分析,以挖掘其中lncRNA的序列、结构、表达及功能等信息.本文将对基于RNA-Seq的lncRNA预测流程进行介绍,对其中涉及的生物信息学方法进行较为全面的综述,就相关问题和挑战展开讨论,并对研究进行展望.

    Abstract:

    With the development of the new generation of biotechnology and bioinformatics, studies on the transcriptome of eukaryotes have detected a number of long non-coding RNAs (lncRNAs) and the lncRNAs may play key functional roles in gene expression and regulation. Currently, high-throughput RNA-Seq has become the main technique for lncRNA study and several bioinformatic methods have been used to process and analyze the sequencing data for exploring lncRNAs' information including sequence, structure, expression, function and so on. This paper represents a pipeline for the lncRNA prediction based on RNA-Seq, and the relevant bioinformatic methods are reviewed comprehensively. We also discussed several challenges and future works related to the lncRNA study.

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孙磊,张林,刘辉.基于RNA-Seq的长非编码RNA预测[J].生物化学与生物物理进展,2012,39(12):1156-1166

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历史
  • 收稿日期:2012-06-12
  • 最后修改日期:2012-08-06
  • 接受日期:2012-08-13
  • 在线发布日期: 2013-02-28
  • 出版日期: 2012-12-20