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

机译：比对序列的共识折叠是通过比较基因组学检测功能性RNA的新方法

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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. (C) 2004 Elsevier Ltd. All rights reserved.
机译：面对新发现的功能性RNA种类不断增长的清单，可以预期，在最近完成的基因组中仍将隐藏其他类型的功能性RNA。因此，这种RNA基因的计算鉴定非常重要。尽管大多数已知的功能性RNA具有特征性的二级结构，但它们的自由能通常在统计学上不足以区分RNA基因和基因组背景。需要其他信息。考虑到密切相关物种的新基因组数据的广泛可用性，比较研究似乎是最有前途的方法。在这里，我们表明，比对序列的共有结构的预测可以是检测功能性RNA的重要措施。我们报告了一种新的方法来测试多个序列比对中是否存在异常结构化和保守的折叠。我们显示了六种类型的众所周知的功能性RNA的比对，与单个序列预测相比，由自由能和协变量项组成的能量得分显着提高了灵敏度。我们进一步测试了我们的方法，从秀丽隐杆线虫/布里氏秀丽隐杆线虫和七个酵母菌的许多非编码RNA上进行测试。可以检测到大多数RNA，具有很高的意义。我们提供了一个Perl实施方案，可以轻松地对单个比对进行评分，并讨论如何扩展此处描述的方法以实现有效的全基因组筛选。 （C）2004 Elsevier Ltd.保留所有权利。

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