MICRORNA TARGETING IN HEART FAILURE

描述(申请人提供)：microRNAs(MiRs)是一种小的非编码RNA，通过目标信使RNA(MRNAs)的失稳和/或翻译抑制来调节蛋白质的表达。与mRNAs一样，miRs的表达在心肌肥厚和心力衰竭中受到调节，可以微调心肌细胞的功能，以响应即时的生理需求。单个MIR往往调节同一功能通路中的许多效应器，通过多个平行的扰动产生一致的生理反应，因此是有吸引力的治疗靶点。然而，一个miR靶向数十或数百个不同的mRNAs，再加上心脏病中miRs和mRNAs的调控表达，使得与心脏病相关的特定miR功能的描述变得复杂。我们开发了新的技术，将大规模并行的下一代平台上的RNA测序与心脏RNA诱导的信号复合体的体内miR编程相结合，以克服这一问题。此外，我们在30个人miR的成熟miR序列中鉴定了常见的序列变体和罕见的突变，并证明了种子序列和非种子序列miR变体都可以改变mRNA靶向。因此，我们假设miR对正常和疾病心脏的影响是由miR的表达水平、表达的mRNAs的水平以及由序列互补性决定的miR-mRNA配对的效率决定的，并且miR序列的变异进一步改变miR的效应，而不依赖于miR和mRNA的表达水平。为了验证这些假设，我们提出了第一个研究，系统和全面地定义重要的miR-mRNA配对事件，并确定它们在不同病理生理条件下在遗传编程小鼠心脏中的功能后果。我们将继续进行研究，以确定人类miR序列变异和突变对心脏miR-mRNA靶向、靶蛋白表达以及心脏结构和功能的影响。通过结合我们在人类基因组学、RNA测序以及小鼠遗传模型的生成和分析方面的专业知识，我们在实现这些目标方面处于独特的地位。我们的长期目标是将人类基因变异和心脏病的研究与体外细胞和体内小鼠实验系统相结合，以充分了解MIR对心脏的影响。 与公共卫生相关：microRNAs(MiRs)代表了一种全新的、意想不到的生物调控水平，针对mRNA转录物进行降解或抑制。在人类心脏病中，MIR是动态调节的。我们发现miR序列变异在人类中令人惊讶地常见，这将影响它们与mRNAs的结合和靶向。在这里，我们建议进行研究，以确定心脏miR-mRNA的相互作用，以更好地了解正常和疾病心脏的miR生物学。这些研究将使用新颖但充分验证的下一代测序技术，结合最先进的体外和体内功能建模，将临床观察转化为机械洞察。

DESCRIPTION (provided by applicant): microRNAs (miRs) are small non-coding RNAs that regulate protein expression by destabilization and/or translational inhibition of target messenger RNAs (mRNAs). Like mRNAs, expression of miRs is regulated in cardiac hypertrophy and heart failure, fine-tuning cardiomyocyte function in response to immediate physiological demands. Single miRs tend to regulate numerous effectors within the same functional pathway, producing a coherent physiological response via multiple parallel perturbations, and are therefore attractive therapeutic targets. However, targeting of dozens or hundreds of different mRNAs by one miR, together with regulated expression of miRs and mRNAs in cardiac disease, complicates delineation of specific miR functions relevant to heart disease. We have developed new techniques combining RNA sequencing on massively parallel next generation platforms with in vivo miR programming of cardiac RNA-induced signaling complexes to overcome this problem. Additionally, we have identified common sequence variants and rare mutations within the mature miR sequence of 30 human miRs and demonstrated that both seed sequence and non-seed sequence miR variants can alter mRNA targeting. Accordingly, we hypothesize that miR effects on the normal and diseased heart are determined by the levels of expressed miRs, the levels of expressed mRNAs, and the efficiency of miR-mRNA pairing as determined by sequence complementarity, and that miR sequence variations further alter miR effects, independent of miR and mRNA expression levels. To examine these hypotheses we propose the first studies to systematically and comprehensively define important miR-mRNA pairing events and determine their functional consequences in genetically programmed mouse hearts under different pathophysiological conditions. We will follow with studies to determining the consequences of human miR sequence variants and mutations on cardiac miR-mRNA targeting, target protein expression, and cardiac structure and function. We are uniquely positioned to achieve these goals by combining our expertise in human genomics, RNA sequencing, and generation and analysis of murine genetic models. It is our long-term goal to integrate studies of human gene variation and cardiac disease with in vitro cell-based and in vivo murine experimental systems to fully understand the impact of miRs on the heart. PUBLIC HEALTH RELEVANCE: microRNAs (miRs) represent an entirely new and unexpected level of biological regulation, targeting mRNA transcripts for degradation or suppression. miRs are dynamically regulated in human cardiac disease. We have found that miR sequence variations, which will affect their binding to and targeting of mRNAs, are surprisingly common in human subjects. Here, we propose studies to define cardiac miR-mRNA interactions in order to better understand miR biology in normal and diseased hearts. These studies will employ novel but fully validated next generation sequencing technologies in combination with state-of-the art in vitro and in vivo functional modeling to translate the clinical observations into mechanistic insights.