Semiautomated improvement of RNA alignments

We have developed a semiautomated RNA sequence editor (SARSE) that integrates tools for analyzing RNA alignments. The editor highlights different properties of the alignment by color, and its integrated analysis tools prevent the introduction of errors when doing alignment editing. SARSE readily connects to external tools to provide a flexible semiautomatic editing environment. A new method, Pcluster, is introduced for dividing the sequences of an RNA alignment into subgroups with secondary structure differences. Pcluster was used to evaluate 574 seed alignments obtained from the Rfam database and we identified 71 alignments with significant prediction of inconsistent base pairs and 102 alignments with significant prediction of novel base pairs. Four RNA families were used to illustrate how SARSE can be used to manually or automatically correct the inconsistent base pairs detected by Pcluster: the mir-399 RNA, vertebrate telomase RNA (vert-TR), bacterial transfer-messenger RNA (tmRNA), and the signal recognition particle (SRP) RNA. The general use of the method is illustrated by the ability to accommodate pseudoknots and handle even large and divergent RNA families. The open architecture of the SARSE editor makes it a flexible tool to improve all RNA alignments with relatively little human intervention. Online documentation and software are available at (http://sarse.ku.dk).     

RNA二级结构预测系统构建

运用下列RNA二级结构预测算法:碱基最大配对方法、Zuker极小化自由能方法、螺旋区最优堆积、螺旋区随机堆积和所有可能组合方法与基于一级螺旋区的RNA二级结构绘图技术, 构建了RNA二级结构预测系统Rnafold. 另外, 通过随机选取20个tRNA序列, 从自由能和三叶草结构两个方面比较了前4种二级结构预测算法, 并运用t检验方法分析了自由能的统计学差别. 从三叶草结构来看, 以随机堆积方法最好, 其次是螺旋区最优堆积方法和Zuker算法, 以碱基最大配对方法最差. 最后, 分析了两种极小化自由能方法之间的差别.     

Consensus folding of aligned sequences as a new measure for the detection of functional RNAs by comparative genomics

Facing the ever-growing list of newly discovered classes of functional RNAs, it can be expected that further types of functional RNAs are still hidden in recently completed genomes. The computational identification of such RNA genes is, therefore, of major importance. While most known functional RNAs have characteristic secondary structures, their free energies are generally not statistically significant enough to distinguish RNA genes from the genomic background. Additional information is required. Considering the wide availability of new genomic data of closely related species, comparative studies seem to be the most promising approach. Here, we show that prediction of consensus structures of aligned sequences can be a significant measure to detect functional RNAs. We report a new method to test multiple sequence alignments for the existence of an unusually structured and conserved fold. We show for alignments of six types of well-known functional RNA that an energy score consisting of free energy and a covariation term significantly improves sensitivity compared to single sequence predictions. We further test our method on a number of non-coding RNAs from Caenorhabditis elegans/Caenorhabditis briggsae and seven Saccharomyces species. Most RNAs can be detected with high significance. We provide a Perl implementation that can be used readily to score single alignments and discuss how the methods described here can be extended to allow for efficient genome-wide screens.     

A Secondary Structure Model of the Integrin a Subunit N-Terminal Domain Based on Analysis of Multiple Alignments

The integrins are α/β heterodimeric proteins which mediate cell-matrix and cell-cell inter-actions. Current data indicate that the N-terminal moiety of the a subunit is involved in ligand binding. This region of the receptor is made up of a seven-fold repeated sequence of unknown structure which contains EF-hand-like putative divalent cation-binding sites. Recent studies have shown that multiple sequence alignments can be analysed to yield secondary structure predictions. Therefore, to obtain a model structure for the integrin a subunit N-terminal domain repeat, a large alignment of the seven repeats from sixteen integrin sequences was generated. Two methods of analysis were used: First, Chou and Fasman and Garnier, Osguthorpe and Robson predictions were carried out for individual sequences and the consensus predictions derived. Consensus hydrophobicity and chain flexibility data were also used to provide additional data. Second, sites of conservation and variation were analysed by a computer program STAMA (STructure After Multiple Alignment) to yield a secondary structure prediction. The two analyses gave essentially the same predicted structure: undefined region, loop, α-helix, β-strand, divalent cation-binding loop, β-strand, putative turn, loop, β-strand. This is the first model structure to be presented for an integrin domain. Its implications for integrin function are discussed.     

New method to predict conserved RNA structures

RNA secondary structure prediction is one of the classic problems of bioinformatics. The most efficient approaches to solving this problem are based on comparative analysis. As a rule, multiple RNA sequence alignment and subsequent determination of a common secondary structure are used. A new algorithm was developed to obviate the need for preliminary multiple sequence alignment. The algorithm is based on a multilevel MEME-like iterative search for a generalized profile. The search for common blocks in RNA sequences is carried out at the first level. Then the algorithm refines the chains consisting of these blocks. Finally, the search for sets of common helices, matched with alignment blocks, is carried out. The algorithm was tested with a tRNA set containing additional junk sequences and with RFN riboswitches. The algorithm is available at http://bioinf.fbb.msu.ru/RNAAlign.     

RNAspace.org: An integrated environment for the prediction, annotation, and analysis of ncRNA

The annotation of noncoding RNA genes remains a major bottleneck in genome sequencing projects. Most genome sequences released today still come with sets of tRNAs and rRNAs as the only annotated RNA elements, ignoring hundreds of other RNA families. We have developed a web environment that is dedicated to noncoding RNA (ncRNA) prediction, annotation, and analysis and allows users to run a variety of tools in an integrated and flexible manner. This environment offers complementary ncRNA gene finders and a set of tools for the comparison, visualization, editing, and export of ncRNA candidates. Predictions can be filtered according to a large set of characteristics. Based on this environment, we created a public website located at http://RNAspace.org. It accepts genomic sequences up to 5 Mb, which permits for an online annotation of a complete bacterial genome or a small eukaryotic chromosome. The project is hosted as a Source Forge project (http://rnaspace.sourceforge.net/).     

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．