CAREER: Uncovering the regulation of low fidelity mRNA splicing

分子生物学的中心教条涉及从脱氧核糖核酸(DNA)分子中定义的基因合成核糖核酸(RNA)。然后，这些RNA分子中的一些分子充当信使，传递教学蓝图，以实现适当的细胞功能。RNA编码的信息内容通过剪接过程被放大，这使得能够从单个基因序列中产生数十个不同的RNA分子。剪接过程非常复杂，最大的分子复合体之一和许多辅助因子一起工作，以协调信使RNA的精确水平和组成。这种错综复杂的情况为剪接中的噪音和错误打开了大门，剪接可能构成细胞中相当大一部分的RNA输出。虽然在过去十年中已经确定了检查和纠正此类错误的质量控制机制，但对这些错误发生的频率以及为什么某些错误的RNA逃脱检测和移除知之甚少。该项目将使用新的基因组学和计算工具来直接识别和量化错误拼接的RNA，从而更好地了解适当的RNA合成对细胞功能的调节。更广泛地说，该项目旨在通过以下方式向未来的研究人员和教育工作者传授生物数据分析的交叉技能：(1)接待伍斯特地区的本科生进行计算生物学的暑期研究和推广体验，以及(2)促进伍斯特大学陈医学院为伍斯特公立学校科学教师提供的丰富项目。几十年来，mRNA剪接过程被认为是高效的，几乎没有偏离受监管的替代剪接决定的机会。这一想法导致了一种广泛的观点，即所有替代的mRNA异构体都必须受到调控，并且潜在地具有生物学功能。然而，最近，研究人员已经确定了普遍的、非规范的剪接位点选择，包括那些低保真的剪接体结合序列。这些发现表明，mRNA剪接机制存在广泛的错误和神秘的剪接位点使用，随机的生物噪声在塑造后生动物转录组多样性中的作用尚未被探索。该项目将使用新生RNA的高通量测序来追踪细胞间的剪接中间体，创建一个神秘剪接位点的目录，并检查与这些事件相关的遗传和生化特征。这些研究将深入了解不需要的剪接产物如何以及何时逃逸或被信使核糖核酸质量控制机制修剪。利用这一目录，将建立一个统计模型，以实现对神秘剪接位点使用的预测性理解，并使用基因编辑工具来测试该模型的预测。该项目的长期研究目标是定义信使核糖核酸剪接中的噪声构成，并利用这些研究重新定义信使核糖核酸剪接编码。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The central dogma of molecular biology involves the synthesis of ribonucleic acid (RNA) from the genes defined in deoxyribonucleic acid (DNA) molecules. Some of these RNA molecules then act as messengers that shuttle instructional blueprints to enable proper cellular function. The informational content encoded by RNA is amplified by the process of splicing, which enables the creation of dozens of different RNA molecules from a single gene sequence. The process of splicing is very complex, with one of the largest molecular complexes and many auxiliary factors working together to coordinate the precise levels and compositions of messenger RNAs. This intricacy opens the door for noise and errors in splicing that may comprise a substantial fraction of RNA output in a cell. While quality control mechanisms to check for and correct such errors have been identified over the last decade, less is known about how often these errors occur and why certain erroneous RNAs escape detection and removal. This project will use novel genomics and computational tools to identify directly and quantify erroneously spliced RNAs, gaining a better understanding of the regulation of proper RNA synthesis for cellular function. More broadly, the project aims to teach the cross-cutting skills of biological data analysis to up and coming researchers and educators by (1) hosting Worcester area undergraduates for a combined summer research and outreach experience in computational biology and (2) facilitating an enrichment program at UMass Chan Medical School for Worcester Public School science teachers.For decades, the process of mRNA splicing was thought to be highly efficient, with little opportunity for deviation outside of regulated alternative splicing decisions. This idea led to a widespread perspective that all alternative mRNA isoforms must be regulated and, potentially, have biological function. Recently, however, researchers have identified pervasive, non-canonical splice site choice, including those at low-fidelity spliceosome binding sequences. These discoveries suggest that there is widespread error and cryptic splice site usage by mRNA splicing mechanisms, with unexplored roles for stochastic, biological noise in shaping metazoan transcriptome diversity. This project will use high-throughput sequencing of nascent RNA to track splicing intermediates through cellular compartments, creating a catalog of cryptic splice sites and examining genetic and biochemical features associated with these events. These studies will provide insight into how and when undesirable splicing products escape or are pruned by mRNA quality control mechanisms. Leveraging this catalog, a statistical model will be built to enable a predictive understanding of cryptic splice site usage and employ gene editing tools to test predictions from this model. The long-term research goal of this project is to define what constitutes noise in mRNA splicing and use these studies to redefine the mRNA splicing code.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.