Suppr超能文献

随机森林模型揭示了N6-甲基腺嘌呤修饰与RNA结合蛋白之间的相互作用。

Random Forest model reveals the interaction between N6-methyladenosine modifications and RNA-binding proteins.

作者信息

Hong Wei, Zhao Yanding, Weng Yi-Lan, Cheng Chao

机构信息

Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA.

Center for Neuroregeneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, USA.

出版信息

iScience. 2023 Feb 20;26(3):106250. doi: 10.1016/j.isci.2023.106250. eCollection 2023 Mar 17.

Abstract

RNA-binding proteins (RBPs) have critical roles in N6-methyladenosine (m6A) modification process. We designed a Random Forest (RF) model to systematically analyze the interaction among RBPs and m6A modifications by integrating the binding signals from hundreds of RBPs. Accurate prediction of m6A sites demonstrated significant connections between RBP bindings and m6A modifications. The relative importance of different RBPs from the model provided a quantitative metric to evaluate their interactions with m6A modifications. Redundancy analysis showed that several RBPs may have similar binding patterns with m6A sites. The RF model exhibited fairly high prediction accuracy across cell lines, suggesting a conservative RBP interaction network regulates m6A occupancy. Specific RBPs can engage to the corresponding regional m6A sites and deploy distinct regulatory processes, such as cleavage site selection of the alternative polyadenylation (APA). We also integrated histone modifications into our RF model, which demonstrated H3K36me3 and H3K27me3 as determining features for m6A distribution.

摘要

RNA结合蛋白(RBPs)在N6-甲基腺苷(m6A)修饰过程中发挥着关键作用。我们设计了一种随机森林(RF)模型,通过整合数百种RBPs的结合信号,系统地分析RBPs与m6A修饰之间的相互作用。对m6A位点的准确预测表明RBP结合与m6A修饰之间存在显著联系。该模型中不同RBPs的相对重要性提供了一个定量指标,以评估它们与m6A修饰的相互作用。冗余分析表明,几种RBPs可能与m6A位点具有相似的结合模式。RF模型在不同细胞系中表现出相当高的预测准确性,表明一个保守的RBP相互作用网络调节m6A占据情况。特定的RBPs可以与相应区域的m6A位点结合,并开展不同的调控过程,如可变聚腺苷酸化(APA)的切割位点选择。我们还将组蛋白修饰整合到我们的RF模型中,结果表明H3K36me3和H3K27me3是m6A分布的决定因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7683/10009289/e83d4532a523/fx1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验