Mu Kunting, Fei Yuhan, Xu Yiran, Zhang Qiangfeng Cliff
MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China.
Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing 100084, China.
Nucleic Acids Res. 2025 Jan 6;53(D1):D211-D219. doi: 10.1093/nar/gkae1117.
RNA molecules function in numerous biological processes by folding into intricate structures. Here we present RASP v2.0, an updated database for RNA structure probing data featuring a substantially expanded collection of datasets along with enhanced online structural analysis functionalities. Compared to the previous version, RASP v2.0 includes the following improvements: (i) the number of RNA structure datasets has increased from 156 to 438, comprising 216 transcriptome-wide RNA structure datasets, 141 target-specific RNA structure datasets, and 81 RNA-RNA interaction datasets, thereby broadening species coverage from 18 to 24, (ii) a deep learning-based model has been implemented to impute missing structural signals for 59 transcriptome-wide RNA structure datasets with low structure score coverage, significantly enhancing data quality, particularly for low-abundance RNAs, (iii) three new online analysis modules have been deployed to assist RNA structure studies, including missing structure score imputation, RNA secondary and tertiary structure prediction, and RNA binding protein (RBP) binding prediction. By providing a resource of much more comprehensive RNA structure data, RASP v2.0 is poised to facilitate the exploration of RNA structure-function relationships across diverse biological processes. RASP v2.0 is freely accessible at http://rasp2.zhanglab.net/.
RNA分子通过折叠成复杂的结构在众多生物过程中发挥作用。在此,我们展示了RASP v2.0,这是一个用于RNA结构探测数据的更新数据库,其特点是数据集大幅扩充,同时在线结构分析功能得到增强。与前一版本相比,RASP v2.0有以下改进:(i) RNA结构数据集的数量从156个增加到438个,包括216个全转录组范围的RNA结构数据集、141个靶向特异性RNA结构数据集和81个RNA-RNA相互作用数据集,从而使物种覆盖范围从18个扩大到24个;(ii) 已实施基于深度学习的模型,为59个结构得分覆盖率低的全转录组范围RNA结构数据集插补缺失的结构信号,显著提高了数据质量,特别是对于低丰度RNA;(iii) 部署了三个新的在线分析模块以协助RNA结构研究,包括缺失结构得分插补、RNA二级和三级结构预测以及RNA结合蛋白(RBP)结合预测。通过提供更全面的RNA结构数据资源,RASP v2.0有望促进对不同生物过程中RNA结构-功能关系的探索。可通过http://rasp2.zhanglab.net/免费访问RASP v2.0。