A local multiple alignment method for detection of non-coding RNA sequences
A local multiple alignment method for detection of non-coding RNA sequences
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DOI：
10.1093/bioinformatics/btp261
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发表时间：
2009-06
期刊：
影响因子：
5.8
通讯作者：
Yasuo Tabei;K. Asai
中科院分区：
文献类型：
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作者：
Yasuo Tabei;K. Asai
动机 非编码 RNA (ncRNA) 显示出独特的进化过程，其中远距离碱基的取代相互关联，以保存 ncRNA 分子的二级结构。因此，检测ncRNA的多重比对方法应同时考虑一级序列和二级结构。最近，用于检测 ncRNA 的多重比对研究受到了广泛关注；然而，大多数提出的方法都是为全局多重比对而设计的。因此，这些方法不适合鉴定基因组序列中局部保守的 ncRNA。需要一种更有效的局部多重比对方法来检测 ncRNA。结果我们提出了一种新的局部多重比对方法来检测 ncRNA。该方法使用受 ProDA 启发的局部多重比对构建程序，ProDA 是针对具有重复和改组元素的蛋白质序列的局部多重比对程序。为了根据二级结构信息比对序列，我们提出了一种结合二级结构特征的新比对模型。我们通过条件随机场定义比对的条件概率，并使用伽马质心估计器来比对序列。局部对齐的子序列被聚类成成对对齐之间的近似全局可对齐的子序列块。最后，这些块通过 MXSCARNA 进行多重对齐。在基准实验中，我们展示了所实现的软件 SCARNA_LM 在检测 ncRNA 的局部多重比对方面的强大能力。可用性 SCARNA_LM 的 C++ 源代码及其实验数据集可从 http://www.ncrna.org/software/scarna_lm/download 获取。补充信息 补充数据可在生物信息学在线获取。
MOTIVATION Non-coding RNAs (ncRNAs) show a unique evolutionary process in which the substitutions of distant bases are correlated in order to conserve the secondary structure of the ncRNA molecule. Therefore, the multiple alignment method for the detection of ncRNAs should take into account both the primary sequence and the secondary structure. Recently, there has been intense focus on multiple alignment investigations for the detection of ncRNAs; however, most of the proposed methods are designed for global multiple alignments. For this reason, these methods are not appropriate to identify locally conserved ncRNAs among genomic sequences. A more efficient local multiple alignment method for the detection of ncRNAs is required. RESULTS We propose a new local multiple alignment method for the detection of ncRNAs. This method uses a local multiple alignment construction procedure inspired by ProDA, which is a local multiple aligner program for protein sequences with repeated and shuffled elements. To align sequences based on secondary structure information, we propose a new alignment model which incorporates secondary structure features. We define the conditional probability of an alignment via a conditional random field and use a gamma-centroid estimator to align sequences. The locally aligned subsequences are clustered into blocks of approximately globally alignable subsequences between pairwise alignments. Finally, these blocks are multiply aligned via MXSCARNA. In benchmark experiments, we demonstrate the high ability of the implemented software, SCARNA_LM, for local multiple alignment for the detection of ncRNAs. AVAILABILITY The C++ source code for SCARNA_LM and its experimental datasets are available at http://www.ncrna.org/software/scarna_lm/download. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.