Institute of Cardiovascular Science, University College London, London WC1E 6JF, United Kingdom.
European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge CB10 1SD, United Kingdom.
RNA. 2018 Aug;24(8):1005-1017. doi: 10.1261/rna.065565.118. Epub 2018 Jun 5.
MicroRNA regulation of key biological and developmental pathways is a rapidly expanding area of research, accompanied by vast amounts of experimental data. This data, however, is not widely available in bioinformatic resources, making it difficult for researchers to find and analyze microRNA-related experimental data and define further research projects. We are addressing this problem by providing two new bioinformatics data sets that contain experimentally verified functional information for mammalian microRNAs involved in cardiovascular-relevant, and other, processes. To date, our resource provides over 4400 Gene Ontology annotations associated with over 500 microRNAs from human, mouse, and rat and over 2400 experimentally validated microRNA:target interactions. We illustrate how this resource can be used to create microRNA-focused interaction networks with a biological context using the known biological role of microRNAs and the mRNAs they regulate, enabling discovery of associations between gene products, biological pathways and, ultimately, diseases. This data will be crucial in advancing the field of microRNA bioinformatics and will establish consistent data sets for reproducible functional analysis of microRNAs across all biological research areas.
MicroRNA 对关键生物和发育途径的调控是一个快速发展的研究领域,伴随着大量的实验数据。然而,这些数据在生物信息学资源中并不广泛可用,使得研究人员难以找到和分析与 microRNA 相关的实验数据,并确定进一步的研究项目。我们通过提供两个新的生物信息学数据集来解决这个问题,这些数据集包含了与心血管相关和其他过程相关的哺乳动物 microRNA 的实验验证功能信息。迄今为止,我们的资源提供了超过 4400 个与来自人类、小鼠和大鼠的超过 500 个 microRNA 相关的基因本体注释,以及超过 2400 个经过实验验证的 microRNA:target 相互作用。我们说明了如何使用 microRNA 的已知生物学作用及其调控的 mRNAs 来创建具有生物学背景的 microRNA 焦点交互网络,从而发现基因产物、生物途径之间的关联,并最终发现疾病之间的关联。这些数据对于推进 microRNA 生物信息学领域至关重要,并将为所有生物研究领域中 microRNA 的可重复功能分析建立一致的数据集。