Statistical Physics Approaches to RNA Editing

技术概述：该奖项支持生物学与统计物理学的理论研究和教育。PI试图将统计物理学的方法应用于RNA编辑问题，这与生物系统如何从DNA编码的指令合成蛋白质有关。RNA是一种生物分子，深入参与分子生物学的各个方面，如蛋白质生产、基因调控和病毒复制。尽管RNA对所有生物体都很重要，但令人惊讶的是，我们对RNA生物学的许多重要方面知之甚少。围绕RNA的一个重要的生物学谜团是RNA编辑的机制。RNA编辑是在信使RNA或功能性RNA中插入、删除或替换单个或短段核苷酸的过程。不同形式的RNA编辑发生在许多不同的生物体中。在这个项目中，利用两种具有插入式RNA编辑的相关生物（多头绒泡菌和Didymium iridis）的线粒体基因组中的组合信息，以及来自其他生物的数百万个蛋白质序列，计算鉴定这两种生物中的基因，并提供关于这些基因中编辑位点位置的实验验证预测。线粒体基因组的完整注释和这些基因中编辑位点的表征解决了迄今为止难以捉摸的RNA编辑机制的两个问题：(i)从新基因的编辑位点中鉴定出的序列特征表明RNA编辑机制如何知道编辑哪些位点。（ii）新基因本身揭示了RNA编辑机制本身的一些成分。为实现这一目标而开发的新方法是基于将预测质量解释为所有可能预测空间上的复杂能源景观。这允许使用统计物理的计算方法来找到最佳预测。该项目将产生新的算法，用于识别存在RNA编辑的基因和编辑位点。这些算法以及编辑站点数据将免费提供给非商业用户。所有项目都将涉及本科生和研究生，他们将接受跨学科的教育和计算技术培训。他们将有助于解决劳动力对具有强大定量和生物学背景的个人的高需求。非技术概述：该奖项支持生物学和统计物理学的理论研究和教育。由于新的生物学实验技术和高智力机会，这一领域一直在经历爆炸式的增长。PI将应用统计物理学的方法来了解DNA中包含的指令如何用于制造蛋白质及其在其他细胞功能中的作用。DNA中包含的信息被用来制造RNA，而RNA对细胞如何制造蛋白质至关重要。通过这种方式，来自DNA的信息反映在所创造的蛋白质中。在一些生物体中，RNA在被称为RNA编辑的过程中产生后被修改，导致所产生的蛋白质发生变化。PI将使用统计物理学的方法来更好地理解RNA编辑的过程。理论和计算技术的发展将反过来促进统计物理学的方法，并用于解决其他问题。这种协同作用有助于两个领域的发展。统计力学的概念适用于我们世界上广泛的系统和现象，并有可能照亮我们的理解，以推进基础知识以及实际利益。该项目将产生新的计算方法，用于识别存在RNA编辑的基因和编辑位点。这些方法将免费提供给非商业用户。该项目将涉及本科生和研究生，他们将接受跨学科的教育和计算技术培训。他们将有助于解决劳动力对具有强大定量和生物学背景的个人的高需求。

TECHNICAL SUMMARY:This award supports theoretical research and education at the interface of biology with statistical physics. The PI seeks to apply the methods of statistical physics to the problem of RNA editing which bears on how biological systems synthesize proteins from the instructions encoded in DNA. RNA is a biomolecule that is deeply involved in all aspects of molecular biology, such as protein production, gene regulation, and viral replication. In spite of RNA's importance for all living organisms, there are many significant aspects of RNA biology that we know surprisingly little about. One such significant biological mystery surrounding RNA is the mechanism of RNA editing. RNA editing is the process in which individual or short stretches of nucleotides in a messenger or functional RNA are inserted, deleted, or substituted. Different forms of RNA editing occur in many different organisms.In this project, the combined information in the mitochondrial genomes of two related organisms with insertional RNA editing, Physarum polycephalum and Didymium iridis, and in the millions of protein sequences from other organisms is exploited to computationally identify genes in the two organisms and to provide experimentally verifiable predictions about the location of editing sites within these genes. A complete annotation of the mitochondrial genome and characterization of the editing sites in these genes addresses two questions about the so far elusive RNA editing mechanism: (i) Sequence features identified from the editing sites in the new genes indicate how the RNA editing machinery knows which sites to edit. (ii) The new genes themselves reveal what some of the constituents of the RNA editing machinery itself are. The new approaches developed to meet this end are based on interpreting prediction quality as a complex energy landscape over the space of all possible predictions. This allows computational methods from statistical physics to be used to find optimal predictions.This project will yield new algorithms for the identification of genes and editing sites in the presence of RNA editing. These algorithms as well as the editing site data will be freely accessible to non commercial users.All projects will involve undergraduate and graduate students who will receive an interdisciplinary education and training in computational techniques. They will help address the high demand in the workforce for individuals with a strong quantitative and biological background.NON-TECHNICAL SUMMARY:This award supports theoretical research and education at the interface of biology and statistical physics. This area has been experiencing explosive growth owing to new experimental techniques for biology and high intellectual opportunity. The PI will apply methods of statistical physics to understand aspects of how the instructions contained in DNA are used to create proteins and their role in other cellular functions. The information contained in DNA is used to create RNA which is instrumental in how cells make proteins. In this way, information from DNA is reflected in the created proteins. In some organisms the RNA is modified after it is created by a process known as RNA editing, leading to changes in the resulting proteins. The PI will use the methods of statistical physics to better understand the process of RNA editing. The theoretical and computational techniques that are developed will in turn contribute to the methods of statistical physics and be used to attack other problems. The synergy helps to advance both fields. The concepts of statistical mechanics are applicable to a wide range of systems and phenomena in our world and have the potential to illuminate our understanding to advance fundamental knowledge as well as for practical benefit.This project will yield new computational methods for the identification of genes and editing sites in the presence of RNA editing. These methods will be freely accessible to non commercial users.This project will involve undergraduate and graduate students who will receive an interdisciplinary education and training in computational techniques. They will help address the high demand in the workforce for individuals with a strong quantitative and biological background.