横向主动脉收缩多组学分析揭示了病理生理的心脏分子机制。

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-07-25 DOI:10.1093/database/baae060
Enio Gjerga, Matthias Dewenter, Thiago Britto-Borges, Johannes Grosso, Frank Stein, Jessica Eschenbach, Mandy Rettel, Johannes Backs, Christoph Dieterich
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引用次数: 0

摘要

横向主动脉缩窄(TAC)诱导的进行性心力衰竭(HF)小鼠模型的时程多组学数据为我们提供了深入了解导致收缩力衰竭和心脏结构重塑的分子机制的机会。我们采用了基于 Illumina 的转录组学、Nanopore 测序和基于质谱的蛋白质组学,对 TAC 和 Sham 手术后 1、7、21 和 56 天的左心室和右心室样本进行了分析。在这里,我们介绍横纹肌收缩多组学分析(TACOMA),它是一种交互式网络应用程序,可将在横纹肌收缩时程实验中收集到的转录组学和蛋白质组学数据进行整合和可视化。TACOMA 使用户能够直观地看到已知和新基因及其蛋白产物的表达谱。重要的是,我们还通过评估不同的转录本和外显子使用情况来捕捉替代剪接事件。基于共表达的聚类算法和功能富集分析揭示了蛋白质和基因水平上生物过程和分子功能的高比例注释。为了加强数据整合,TACOMA同步了转录组学和蛋白质组学资料,实现了交叉组学比较。通过 TACOMA (https://shiny.dieterichlab.org/app/tacoma),我们提供了丰富的网络资源,以揭示与收缩力衰竭和心肌肥大有关的分子事件和生物过程。例如,我们重点介绍了:(i) 在肥大生长和收缩功能障碍的时间过程中代谢基因和蛋白质的变化;(ii) 鉴别 RV 和 LV 之间 Tpm2 同工酶表达的 RNA 剪接变化;(iii) 可能导致高房颤症发病机制的新转录本和基因。我们计划用更多的高频房颤环境和遗传模型来扩展这些数据,以破译不同病因的心脏疾病中常见和不同的分子变化。数据库网址:https://shiny.dieterichlab.org/app/tacoma。
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Transverse aortic constriction multi-omics analysis uncovers pathophysiological cardiac molecular mechanisms.

Time-course multi-omics data of a murine model of progressive heart failure (HF) induced by transverse aortic constriction (TAC) provide insights into the molecular mechanisms that are causatively involved in contractile failure and structural cardiac remodelling. We employ Illumina-based transcriptomics, Nanopore sequencing and mass spectrometry-based proteomics on samples from the left ventricle (LV) and right ventricle (RV, RNA only) of the heart at 1, 7, 21 and 56 days following TAC and Sham surgery. Here, we present Transverse Aortic COnstriction Multi-omics Analysis (TACOMA), as an interactive web application that integrates and visualizes transcriptomics and proteomics data collected in a TAC time-course experiment. TACOMA enables users to visualize the expression profile of known and novel genes and protein products thereof. Importantly, we capture alternative splicing events by assessing differential transcript and exon usage as well. Co-expression-based clustering algorithms and functional enrichment analysis revealed overrepresented annotations of biological processes and molecular functions at the protein and gene levels. To enhance data integration, TACOMA synchronizes transcriptomics and proteomics profiles, enabling cross-omics comparisons. With TACOMA (https://shiny.dieterichlab.org/app/tacoma), we offer a rich web-based resource to uncover molecular events and biological processes implicated in contractile failure and cardiac hypertrophy. For example, we highlight: (i) changes in metabolic genes and proteins in the time course of hypertrophic growth and contractile impairment; (ii) identification of RNA splicing changes in the expression of Tpm2 isoforms between RV and LV; and (iii) novel transcripts and genes likely contributing to the pathogenesis of HF. We plan to extend these data with additional environmental and genetic models of HF to decipher common and distinct molecular changes in heart diseases of different aetiologies. Database URL: https://shiny.dieterichlab.org/app/tacoma.

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