Klaus Tschira Institute for Integrative Computational Cardiology, University Hospital Heidelberg, Heidelberg, Germany.
Department of Internal Medicine III (Cardiology, Angiology, and Pneumology), University Hospital, Heidelberg, Germany.
J Transl Med. 2022 Nov 7;20(1):513. doi: 10.1186/s12967-022-03694-z.
Despite a recent increase in the number of RNA-seq datasets investigating heart failure (HF), accessibility and usability remain critical issues for medical researchers. We address the need for an intuitive and interactive web application to explore the transcriptional signatures of heart failure with this work.
We reanalysed the Myocardial Applied Genomics Network RNA-seq dataset, one of the largest publicly available datasets of left ventricular RNA-seq samples from patients with dilated (DCM) or hypertrophic (HCM) cardiomyopathy, as well as unmatched non-failing hearts (NFD) from organ donors and patient characteristics that allowed us to model confounding factors. We analyse differential gene expression, associated pathway signatures and reconstruct signaling networks based on inferred transcription factor activities through integer linear programming. We additionally focus, for the first time, on differential RNA transcript isoform usage (DTU) changes and predict RNA-binding protein (RBP) to target transcript interactions using a Global test approach. We report results for all pairwise comparisons (DCM, HCM, NFD).
Focusing on the DCM versus HCM contrast (DCMvsHCM), we identified 201 differentially expressed genes, some of which can be clearly associated with changes in ERK1 and ERK2 signaling. Interestingly, the signs of the predicted activity for these two kinases have been inferred to be opposite to each other: In the DCMvsHCM contrast, we predict ERK1 to be consistently less activated in DCM while ERK2 was more activated in DCM. In the DCMvsHCM contrast, we identified 149 differently used transcripts. One of the top candidates is the O-linked N-acetylglucosamine (GlcNAc) transferase (OGT), which catalyzes a common post-translational modification known for its role in heart arrhythmias and heart hypertrophy. Moreover, we reconstruct RBP - target interaction networks and showcase the examples of CPEB1, which is differentially expressed in the DCMvsHCM contrast.
Magnetique ( https://shiny.dieterichlab.org/app/magnetique ) is the first online application to provide an interactive view of the HF transcriptome at the RNA isoform level and to include transcription factor signaling and RBP:RNA interaction networks. The source code for both the analyses ( https://github.com/dieterich-lab/magnetiqueCode2022 ) and the web application ( https://github.com/AnnekathrinSilvia/magnetique ) is available to the public. We hope that our application will help users to uncover the molecular basis of heart failure.
尽管最近用于研究心力衰竭（HF）的 RNA-seq 数据集数量有所增加，但可及性和可用性仍然是医学研究人员面临的关键问题。我们通过这项工作解决了对直观的交互式 Web 应用程序的需求，以探索心力衰竭的转录特征。
我们重新分析了心肌应用基因组学网络 RNA-seq 数据集，这是最大的公开可用的左心室 RNA-seq 样本数据集之一，来自扩张型（DCM）或肥厚型（HCM）心肌病患者以及来自器官捐献者的非衰竭心脏（NFD），以及允许我们对混杂因素进行建模的患者特征。我们基于推断的转录因子活性，通过整数线性规划分析差异基因表达、相关途径特征和重构信号网络。我们还首次重点关注差异 RNA 转录本异构体使用（DTU）变化，并使用全局检验方法预测 RNA 结合蛋白（RBP）与靶转录本的相互作用。我们报告了所有成对比较（DCM、HCM、NFD）的结果。
我们专注于 DCM 与 HCM 的对比（DCMvsHCM），鉴定了 201 个差异表达基因，其中一些基因与 ERK1 和 ERK2 信号的变化明显相关。有趣的是，这两种激酶的预测活性的符号被推断为彼此相反：在 DCMvsHCM 对比中，我们预测 DCM 中 ERK1 的活性始终较低，而 DCM 中 ERK2 的活性较高。在 DCMvsHCM 对比中，我们鉴定了 149 个使用不同的转录本。候选者之一是 O-连接的 N-乙酰氨基葡萄糖（GlcNAc）转移酶（OGT），它催化一种常见的翻译后修饰，已知其在心脏心律失常和心脏肥大中起作用。此外，我们重构了 RBP-靶标相互作用网络，并展示了在 DCMvsHCM 对比中差异表达的 CPEB1 的例子。
Magnetique（https://shiny.dieterichlab.org/app/magnetique）是第一个提供 HF 转录组在 RNA 异构体水平上的交互式视图的在线应用程序，并包括转录因子信号和 RBP：RNA 相互作用网络。分析的源代码（https://github.com/dieterich-lab/magnetiqueCode2022）和 Web 应用程序（https://github.com/AnnekathrinSilvia/magnetique）都可供公众使用。我们希望我们的应用程序能够帮助用户揭示心力衰竭的分子基础。
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