RNA secondary structure modeling at consistent high accuracy using differential SHAPE.
RNA secondary structure modeling at consistent high accuracy using differential SHAPE.
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DOI：
10.1261/rna.043323.113
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发表时间：
2014-06
期刊：
影响因子：
--
通讯作者：
Weeks KM
中科院分区：
文献类型：
--
作者：
Rice GM;Leonard CW;Weeks KM
确定 RNA 的二级结构是一个具有挑战性且尚未完全解决的问题。使用三试剂 SHAPE 实验来检测局部核苷酸灵活性和非规范相互作用，可以对结构复杂的 RNA 进行建模，包括那些以前证明特别难以建模的 RNA，其准确度始终超过 90% 规范碱基对的恢复。 RNA 二级结构建模是一个具有挑战性的问题，最近的成功提高了准确性、一致性和易处理性的标准。通过纳入化学探针反应性数据，准确度大幅提高：将 1M7 SHAPE 反应性数据纳入 mfold 级算法后，碱基对预测的中位准确度超过 90%。然而，一些 RNA 结构的建模精度明显较低。在这里，我们表明，将 NMIA 和 1M6 试剂的差异反应性（检测非规范和三级相互作用）纳入预测算法中，可以为以前难以建模的 RNA 产生高度准确的二级结构模型。对于这些 RNA，93% 的公认碱基对在 SHAPE 导向模型中得到恢复。接受的结构和建模结构之间的差异很小，似乎反映了真正的结构差异。三试剂 SHAPE 导向建模可以简洁地扩展到结构复杂的 RNA，以解决许多类别 RNA 的溶液内二级结构分析问题。
Determining the secondary structure of RNA is a challenging and incompletely solved problem. Using a three-reagent SHAPE experiment to detect local nucleotide flexibility and noncanonical interactions, it is possible to model structurally complex RNAs, including those previously shown to be especially difficult to model, with accuracies consistently exceeding recovery of 90% of canonical base pairs. RNA secondary structure modeling is a challenging problem, and recent successes have raised the standards for accuracy, consistency, and tractability. Large increases in accuracy have been achieved by including data on reactivity toward chemical probes: Incorporation of 1M7 SHAPE reactivity data into an mfold-class algorithm results in median accuracies for base pair prediction that exceed 90%. However, a few RNA structures are modeled with significantly lower accuracy. Here, we show that incorporating differential reactivities from the NMIA and 1M6 reagents—which detect noncanonical and tertiary interactions—into prediction algorithms results in highly accurate secondary structure models for RNAs that were previously shown to be difficult to model. For these RNAs, 93% of accepted canonical base pairs were recovered in SHAPE-directed models. Discrepancies between accepted and modeled structures were small and appear to reflect genuine structural differences. Three-reagent SHAPE-directed modeling scales concisely to structurally complex RNAs to resolve the in-solution secondary structure analysis problem for many classes of RNA.
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DOI：
10.1093/bioinformatics/btp250
发表时间：
2009-08-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Darty K;Denise A;Ponty Y
通讯作者：
Ponty Y
影响因子：
3.5
作者：
Mauger DM;Siegfried NA;Weeks KM
通讯作者：
Weeks KM
影响因子：
21.8
作者：
通讯作者：
--
DOI：
10.1073/pnas.1219988110
发表时间：
2013-04-02
影响因子：
11.1
作者：
Hajdin, Christine E.;Bellaousov, Stanislav;Weeks, Kevin M.
通讯作者：
Weeks, Kevin M.
影响因子：
4.5
作者：
Rivas, Elena;Lang, Raymond;Eddy, Sean R.
通讯作者：
Eddy, Sean R.