综述: 新型长链非编码RNA(lncRNA)的生物信息学研究进展

非编码RNA (noncoding RNA,ncRNA)是指不被翻译成蛋白质的一类RNA,近几年来关于它们的功能研究越来越引起人们的重视．现在已经发现了一些中小型ncRNA,比如microRNA、snoRNA、tRNA等,但是关于长ncRNA(lncRNA)的研究还不够完善．本篇综述回顾了 ncRNA特别是 lncRNA的生物信息学研究进展,包括它们的研究历程、基本特点、与疾病的关系,以及对已有的预测非编码RNA的计算机方法进行了分析和比较,并且介绍了利用机器学习模型整合新一代高通量测序数据的方法．     

计算RNA组学:非编码RNA结构识别与功能预测

真核生物基因组中包含大量非编码RNA基因,计算RNA组学采用信息科学等多学科方法解析ncRNA的结构与功能.本文就ncRNA数据存储与管理、ncRNA基因识别与鉴定、ncRNA靶标识别与功能预测等问题,对目前计算RNA组学的主要研究方法和内容进行了评述.     

计算生物学在RNA研究中的应用

计算生物学在非编码RNA(non-coding RNA, ncRNA)研究领域中发挥着重要的作用.计算生物学是利用计算机科学方法来研究和理解生命科学问题的交叉学科,而ncRNA作为一类数目庞大且功能多样的RNA分子,参与了广泛的生物学过程.本文对RNA计算生物学中的常用算法和工具进行综述,并着重介绍专家系统、机器学习、深度学习等计算生物学研究策略在ncRNA鉴定、ncRNA靶标预测、RNA修饰、RNA二级结构检测、RNA-蛋白质互作及RNA功能预测中的应用.     

家蚕非编码RNA在神经系统中的表达分析

【目的】非编码RNA(non-coding RNA,ncRNA)在家蚕Bombyx mori发育过程中具有重要调控作用。本研究旨在探索ncRNA参与家蚕神经系统发育的分子机理。【方法】采用实时荧光定量PCR技术对22个中等长度的ncRNA及3个ncRNA的邻近编码基因在家蚕幼虫神经系统中的表达水平进行检测。【结果】8个ncRNA(包括1个C/D box snoRNA,4个H/ACA box snoRNA和3个不能归类的ncRNA)在家蚕5龄幼虫神经组织和非神经组织中均有表达,且在胸腹神经中的表达量明显高于头部神经中的表达量。其中,snoRNA Bm-51,Bm-18和Bm-86在胸腹神经中的表达量分别是头部神经中的23,5和4.7倍。进一步研究发现,这3个内含子起源的ncRNA与其宿主基因在家蚕神经系统中的表达趋势一致,宿主基因在胸腹神经中的表达量也明显高于头部神经中的表达量。【结论】本研究筛选到的在家蚕不同神经部位存在差异表达的ncRNA,特别是在胸腹神经中高表达的ncRNA可能协同其邻近编码基因,参与家蚕神经发育或神经活动过程。该结果为研究ncRNA参与家蚕神经系统发育提供了分子依据,为从非编码RNA角度探索鳞翅目害虫防治提供了新的思路。     

基于k-tuple组合的酵母ncRNA与mRNA的比较研究

ncRNA和mRNA一样,都是重要的功能分子。以k-tuple(k字)含量为特征,对酵母ncRNA成熟序列和mRNA的编码区、上游序列与下游序列进行了分类与比较研究,结果显示:基于ncRNA成熟序列与mRNA编码区的3-tuple的含量,ncRNA和mRNA的交叉有效性分类精度(leave-one out cross-validation,LOOCV)平均值达到93.93%;基于上游序列4-tuple和5-tuple的含量,分类精度分别为92.49%和92.76%;基于下游序列4-tuple和5-tuple的含量,分类精度分别为91.58%和90.60%;利用上游序列和下游序列的4-tuple与5-tuple的含量,其平均分类精度分别为94.68%和94.83%;通过t检验,得到了在ncRNA和mRNA上、下游序列中具有显著统计学差异的k-tuple。上述结果表明,基于ncRNA成熟序列与mRNA编码区的3-tuple含量和基于ncRNA与mRNA上、下游序列的4或5-tuple含量可以有效地区分ncRNA与mRNA。此研究结果不仅有助于准确识别ncRNA与mRNA,还有助于发现ncRNA特异的转录因子结合位点。     

植物中的非编码RNA及其作用机制

非编码RNA(non-codingRNA,ncRNA)是近年来发现的一类能够转录但不能编码蛋白质、具有特定功能的RNA分子。ncRNA参与了生命过程中的许多重要环节。该文主要介绍植物中的非编码RNA的类型、研究方法以及功能。     

基于κ-tuple组合的酵母ncRNA与mRNA的比较研究

ncRNA和mRNA一样,都是重要的功能分子.以κ-tuple(κ字)含量为特征,对酵母ncRNA成熟序列和mRNA的编码区、上游序列与下游序列进行了分类与比较研究,结果显示:基于ncRNA成熟序列与mRNA编码区的3-tuple的含量,ncRNA和mRNA的交叉有效性分类精度(leave-one out cross-validation,LOOCV)平均值达到93.93%;基于上游序列4-tuple和5-tuple的含量,分类精度分别为92.49%和92.76%;基于下游序列4-tuple和5-tuple的含量,分类精度分别为91.58%和90.60%;利用上游序列和下游序列的4-tuple与5-tuple的含量,其平均分类精度分别为94.68%和94.83%;通过t检验,得到了在ncRNA和mRNA上、下游序列中具有显著统计学差异的κ-tuple.上述结果表明,基于ncRNA成熟序列与mRNA编码区的3-tuple含量和基于ncRNA与mRNA上、下游序列的4或5-tuple含量可以有效地区分ncRNA与mRNA.此研究结果不仅有助于准确识别ncRNA与mRNA,还有助于发现ncRNA特异的转录因子结合位点.     

表现出巨大影响力的功能性RNA期待出现新的“组”

现在已经知道,基因组的70％转录为RNA,其半数以上为ncRNA。为适应这种理论框架的变化,现已开始探索新的研究方法。[编者按]     

伤寒沙门菌非编码RNA617的分子鉴定及其对生物膜形成的影响研究

本研究旨在探讨伤寒沙门菌(Salmonella enterica serovar Typhi, S. Typhi)中非编码RNA617(non-coding RNA617,ncRNA617)的分子特性,并研究其对生物膜形成的影响及作用机制。采用Northern blot方法检测ncRNA617的表达,通过cDNA 5’末端快速扩增技术(5’-rapid amplification of cDNA end,5’RACE)和逆转录-聚合酶链式反应(reverse transcriotion-polymerase chain reaction,3’RT-PCR)实验分析ncRNA617可能的转录起始位点和终止位点;构建ncRNA617缺陷菌株、回补菌株和过表达菌株等相关菌株,通过生物膜形成实验,观察ncRNA617对伤寒沙门菌生物膜形成的影响,并用实时荧光定量聚合酶链式反应(quantitative real-time polymerase chain reaction,qPCR)分析生物膜形成相关基因表达水平的变化,综合运用生物信息学方法预测ncRNA617和差异基因的结合区域,初步分析ncRNA617发挥调控作用的机制。结果显示,伤寒沙门菌确有ncRNA617的表达,长度约300 nt,其转录起始位点位于mig-14终止密码子下游967 nt处,终止位点位于t2681起始密码子上游 2 378～2 560 nt处。与野生对照菌株相比,ncRNA617缺陷菌株生物膜形成能力增强(P<0.05),回补菌株的生物膜形成能力恢复至野生菌株水平,过表达菌株的生物膜形成能力有所下降(P<0.05)。qPCR结果表明,ncRNA617可负向调控多个生物膜形成相关基因的转录表达水平(P<0.05)。经生物信息学方法预测发现,ncRNA617与差异基因有不同的结合区域。本研究结果提示,ncRNA617在伤寒沙门菌中存在,其长度约270～452 nt。ncRNA617可能通过靶向结合生物膜形成相关基因下调基因表达,从而负向调控伤寒沙门菌生物膜的生成。     

非编码RNA在胞内病原菌免疫逃逸与致病中的作用

非编码RNA(non-coding RNAs,ncRNAs)在细胞增殖、发育、分化、代谢、信号转导以及免疫调控中发挥重要调节作用。越来越多的研究证明,ncRNA在胞内病原菌的致病性和免疫逃逸中发挥重要调控作用。一方面ncRNA是细菌代谢、群体感应和毒力因子表达的调控因子,与胞内病原菌的致病性密切相关;另一方面ncRNA在调节宿主抗胞内病原菌免疫应答中发挥重要作用,深入研究ncRNA如何调节宿主免疫应答将有助于胞内菌免疫逃逸机制的研究。就非编码RNA在胞内病原菌免疫逃逸和致病中的作用作一综述。     

Plant noncoding RNA gene discovery by "single-genome comparative genomics"

Plant genomes have undergone multiple rounds of duplications that contributed massively to the growth of gene families. The structure of resulting families has been studied in depth for protein-coding genes. However, little is known about the impact of duplications on noncoding RNA (ncRNA) genes. Here we perform a systematic analysis of duplicated regions in the rice genome in search of such ncRNA repeats. We observe that, just like their protein counterparts, most ncRNA genes have undergone multiple duplications that left visible sequence conservation footprints. The extent of ncRNA gene duplication in plants is such that these sequence footprints can be exploited for the discovery of novel ncRNA gene families on a large scale. We developed an SVM model that is able to retrieve likely ncRNA candidates among the 100,000+ repeat families in the rice genome, with a reasonably low false-positive discovery rate. Among the nearly 4000 ncRNA families predicted by this means, only 90 correspond to putative snoRNA or miRNA families. About half of the remaining families are classified as structured RNAs. New candidate ncRNAs are particularly enriched in UTR and intronic regions. Interestingly, 89% of the putative ncRNA families do not produce a detectable signal when their sequences are compared to another grass genome such as maize. Our results show that a large fraction of rice ncRNA genes are present in multiple copies and are species-specific or of recent origin. Intragenome comparison is a unique and potent source for the computational annotation of this major class of ncRNA.     

Automatic prediction of non-coding RNA genes in prokaryotes based on compositional statistics

Although non-coding RNA (ncRNA) genes do not encode proteins, they play vital roles in cells by producing functionally important RNAs. In this paper, we present a novel method for predicting ncRNA genes based on compositional features extracted directly from gene sequences. Our method consists of two Support Vector Machine (SVM) models--Codon model which uses codon usage features derived from ncRNA genes and protein-coding genes and Kmer model which utilizes features of nucleotide and dinucleotide frequency extracted respectively from ncRNA genes and randomly chosen genome sequences. The 10-fold cross-validation accuracy for the two models is found to be 92% and 91%, respectively. Thus, we could make an automatic prediction of ncRNA genes in one genome without manual filtration of protein-coding genes. After applying our method in Sulfolobus solfataricus genome, 25 prediction results have been generated according to 25 cut-off pairs. We have also applied the approach in E. coli and found our results comparable to those of previous studies. In general, our method enables automatic identification of ncRNA genes in newly sequenced prokaryotic genomes.     

Immobilization of proteins in the nucleolus by ribosomal intergenic spacer noncoding RNA

Cellular pathways are established and maintained by stochastic interactions of highly mobile molecules. The nucleolus plays a central role in the regulation of these molecular networks by capturing and immobilizing proteins. Here, we report a function for noncoding RNA (ncRNA) in the regulation of protein dynamics of key cellular factors, including VHL, Hsp70 and MDM2/PML. Stimuli-specific loci of the nucleolar intergenic spacer produce ncRNA capable of capturing and immobilizing proteins that encode a discrete peptidic code referred to as the nucleolar detention sequence (NoDS). Disruption of the NoDS/intergenic RNA interaction enables proteins to evade nucleolar sequestration and retain their dynamic profiles. Mislocalization of intergenic ncRNA triggers protein immobilization outside of the nucleolus, demonstrating that these ncRNA species can operate independently from the nucleolar architecture. We propose a model whereby protein immobilization by ncRNA is a posttranslational regulatory mechanism.     

Non-coding RNAs turn up the heat: An emerging layer of novel regulators in the mammalian heat shock response

The field of non-coding RNA (ncRNA) has expanded over the last decade following the discoveries of several new classes of regulatory ncRNA. A growing amount of evidence now indicates that ncRNAs are involved even in the most fundamental of cellular processes. The heat shock response is no exception as ncRNAs are being identified as integral components of this process. Although this area of research is only in its infancy, this article focuses on several classes of regulatory ncRNA (i.e., miRNA, lncRNA, and circRNA), while summarizing their activities in mammalian heat shock. We also present an updated model integrating the traditional heat shock response with the activities of regulatory ncRNA. Our model expands on the mechanisms for efficient execution of the stress response, while offering a more comprehensive summary of the major regulators and responders in heat shock signaling. It is our hope that much of what is discussed herein may help researchers in integrating the fields of heat shock and ncRNA in mammals.