RNA 3D Modules in Genome-Wide Predictions of RNA 2D Structure.
RNA 3D Modules in Genome-Wide Predictions of RNA 2D Structure.
复制标题
DOI：
10.1371/journal.pone.0139900
复制
发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Gorodkin J
中科院分区：
文献类型：
--
作者：
Theis C;Zirbel CL;Zu Siederdissen CH;Anthon C;Hofacker IL;Nielsen H;Gorodkin J
最近的实验和计算进展揭示了基因组中RNA结构的巨大潜力。这是由利用相关生物体的多个基因组来识别共同序列和二级结构的计算策略驱动的。然而，这些计算方法具有两个主要挑战：它们在计算上昂贵并且它们具有相对高的错误发现率（FDR）。同时，RNA三维结构分析揭示了由非典型碱基对组成的模块，这些模块出现在非同源位置，显然是通过独立进化。例如，这些模块可以出现在RNA 2D预测中表现为内部循环的结构元件内部。因此，一个问题是，使用这种RNA 3D信息是否可以在全基因组水平上提高RNA二级结构的预测准确性。在这里，我们使用RNAz与3D模块预测工具相结合，并将其应用于基于序列的13向脊椎动物比对。我们发现，由metaRNAmodules和JAR3D预测的RNA 3D模块在筛选的窗口中显著富集，与它们的改组对应物相比。当某些3D模块预测存在于2D预测的窗口中时，47.0%的初始估计FDR降低到低于25%。我们讨论的影响和前景，进一步发展的计算策略检测RNA的二维结构的基因组序列。
Recent experimental and computational progress has revealed a large potential for RNA structure in the genome. This has been driven by computational strategies that exploit multiple genomes of related organisms to identify common sequences and secondary structures. However, these computational approaches have two main challenges: they are computationally expensive and they have a relatively high false discovery rate (FDR). Simultaneously, RNA 3D structure analysis has revealed modules composed of non-canonical base pairs which occur in non-homologous positions, apparently by independent evolution. These modules can, for example, occur inside structural elements which in RNA 2D predictions appear as internal loops. Hence one question is if the use of such RNA 3D information can improve the prediction accuracy of RNA secondary structure at a genome-wide level. Here, we use RNAz in combination with 3D module prediction tools and apply them on a 13-way vertebrate sequence-based alignment. We find that RNA 3D modules predicted by metaRNAmodules and JAR3D are significantly enriched in the screened windows compared to their shuffled counterparts. The initially estimated FDR of 47.0% is lowered to below 25% when certain 3D module predictions are present in the window of the 2D prediction. We discuss the implications and prospects for further development of computational strategies for detection of RNA 2D structure in genomic sequence.