The performance of several multiple-sequence alignment programs in relation to secondary-structure features for an rRNA sequence
The performance of several multiple-sequence alignment programs in relation to secondary-structure features for an rRNA sequence
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DOI：
10.1093/oxfordjournals.molbev.a026333
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发表时间：
2000-04-01
影响因子：
10.7
通讯作者：
Perrey, SW
中科院分区：
文献类型：
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作者：
Hickson, RE;Simon, C;Perrey, SW
使用动物线粒体小亚基 (12S) rRNA 分子的一部分评估了五个全局多序列比对程序（CLUSTAL W、Divide and Conquer、Malign、PileUp 和 TreeAlign）的性能。源自基于二级结构信息的比对的保守序列基序用于对每个程序在一系列参数值上比对五种脊椎动物和五种无脊椎动物类群的数据集的程度进行评分。所有程序都可以在至少一组参数条件下以合理的精度比对基序，尽管如果考虑整个序列，结构比对的相似度仅为 25%-34%。使用小间隙成本通常会产生更准确的结果，尽管当间隙成本较低时，Malign 和 TreeAlign 会生成更长的对齐方式。当差距成本不同时，这些程序的一致性会有所不同； CLUSTAL W、Divide and Conquer 和 TreeAlign 是最准确和稳健的，而 PileUp 由于间隙成本值增加而表现不佳，并且 Malign 的准确性波动。程序的默认设置并未给出最佳结果，并且尝试在不同程序中选择相似的参数值并不总是会导致更相似的对齐。如果这些基序靠近插入或缺失的位点，即使是非常保守的基序也会出现对齐不良的情况。由于没有先验方法来确定缺口成本，并且这种成本可能因基因而异，因此 rRNA 序列的比对，特别是保守性较差的区域，应仔细处理，并在二级结构和保守基序的帮助下进行。有些基序是单碱基，因此通常对于比对程序来说是不可见的。我们的测试涉及 12S rRNA 基因最保守的区域，不太保守的区域的比对会出现更多问题。我们检查的比对都没有为数据集产生完全解析的系统发育，这表明 12S rRNA 的这一部分不足以解析远距离进化关系。
The performances of five global multiple-sequence alignment programs (CLUSTAL W, Divide and Conquer, Malign, PileUp, and TreeAlign) were evaluated using part of the animal mitochondrial small subunit (12S) rRNA molecule. Conserved sequence motifs derived from an alignment based on secondary structural information were used to score how well each program aligned a data set of five vertebrate and five invertebrate taxa over a range of parameter values. All of the programs could align the motifs with reasonable accuracy for at least one set of parameter conditions, although if the whole sequence was considered, similarity to the structural alignment was only 25%-34%. Use of small gap costs generally gave more accurate results, although Malign and TreeAlign generated longer alignments when gap costs were low. The programs differed in the consistency of the alignments when gap cost was varied; CLUSTAL W, Divide and Conquer, and TreeAlign were the most accurate and robust, while PileUp performed poorly as gap cost values increased, and the accuracy of Malign fluctuated. Default settings for the programs did not give the best results, and attempting to select similar parameter values in different programs did not always result in more similar alignments. Poor alignment of even well-conserved motifs can occur if these are near sites with insertions or deletions. Since there is no a priori way to determine gap costs and because such costs can vary over the gene, alignment of rRNA sequences, particularly the less well conserved regions, should be treated carefully and aided by secondary structure and conserved motifs. Some motifs are single bases and so are often invisible to alignment programs. Our tests involved the most conserved regions of the 12S rRNA gene, and alignment of less well conserved regions will be more problematical. None of the alignments we examined produced a fully resolved phylogeny for the data set, indicating that this portion of 12S rRNA is insufficient for resolution of distant evolutionary relationships.