deepBase v2.0: identification, expression, evolution and function of small RNAs, LncRNAs and circular RNAs from deep-sequencing data.
deepBase v2.0: identification, expression, evolution and function of small RNAs, LncRNAs and circular RNAs from deep-sequencing data.
复制标题
deepBase v2.0：深度测序数据中小RNA、LncRNA和环状RNA的识别、表达、进化和功能
DOI：
10.1093/nar/gkv1273
复制
发表时间：
2016-01-04
影响因子：
14.9
通讯作者：
Qu LH
中科院分区：
文献类型：
--
作者：
Zheng LL;Li JH;Wu J;Sun WJ;Liu S;Wang ZL;Zhou H;Yang JH;Qu LH
小的非编码RNA(例如miRNAs)和长的非编码RNA(例如lincRNAs和CircRNAs)正在成为各种细胞过程的关键调节因子。然而，这些神秘的RNA中只有很小一部分被很好地描述了功能。在本研究中，我们描述了DeepBase v2.0(http://biocenter.sysu.edu.cn/deepBase/)，)，这是一个更新的平台，用于解码19个物种中不同ncRNA的进化、表达模式和功能。DeepBase v2.0已经更新，提供了从588个SRNA-Seq数据集生成的ncRNA衍生小RNA的最全面集合。此外，我们还开发了一条名为LncSeeker的管道，用于从14个物种中识别176 680个高可信的LncRNA。分析了不同ncRNA的时间和空间表达模式。我们在人类和斑马鱼之间鉴定了大约24 280个灵长类特异的lncRNA，5193个啮齿动物特异的lncRNA，以及55个高度保守的lncRNA同源基因。我们注释了14867个人类CircRNAs，其中1260个与小鼠CircRNAs同源。通过结合表达谱和功能基因组注释，我们开发了基于蛋白质-lncRNA共表达网络的lncRNAs功能预测网络服务器。这项研究有望为今后的实验研究和揭示ncRNA的功能提供大量的资源。
Small non-coding RNAs (e.g. miRNAs) and long non-coding RNAs (e.g. lincRNAs and circRNAs) are emerging as key regulators of various cellular processes. However, only a very small fraction of these enigmatic RNAs have been well functionally characterized. In this study, we describe deepBase v2.0 (http://biocenter.sysu.edu.cn/deepBase/), an updated platform, to decode evolution, expression patterns and functions of diverse ncRNAs across 19 species. deepBase v2.0 has been updated to provide the most comprehensive collection of ncRNA-derived small RNAs generated from 588 sRNA-Seq datasets. Moreover, we developed a pipeline named lncSeeker to identify 176 680 high-confidence lncRNAs from 14 species. Temporal and spatial expression patterns of various ncRNAs were profiled. We identified approximately 24 280 primate-specific, 5193 rodent-specific lncRNAs, and 55 highly conserved lncRNA orthologs between human and zebrafish. We annotated 14 867 human circRNAs, 1260 of which are orthologous to mouse circRNAs. By combining expression profiles and functional genomic annotations, we developed lncFunction web-server to predict the function of lncRNAs based on protein-lncRNA co-expression networks. This study is expected to provide considerable resources to facilitate future experimental studies and to uncover ncRNA functions.