Regulation of mRNA splicing by intronic genetic variants

内含子遗传变异对 mRNA 剪接的调节

• 批准号: 9071997
• 负责人: Yunlong Liu
• 金额: $ 57.63万
• 依托单位: INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-01 至 2019-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9071997
• 关键词: Adoption; Affect; Algorithms; Alternative Splicing; Bioinformatics; Biological Assay; Biological Process; CRISPR/Cas technology; Cell Line; Cell physiology; Cell-Mediated Cytolysis; Cellular Assay; Clinical Research; Clofarabine; Complex; Computational algorithm; Computers; Data; Disease; Etiology; Exclusion; Exons; Genes; Genetic Variation; Genomics; Goals; Human; Human Cell Line; Human Genetics; Individual; Informatics; Introns; Machine Learning; Messenger RNA; Mission; Modeling; Molecular; Paclitaxel; Pharmaceutical Preparations; Pharmacogenomics; Pharmacotherapy; Phenotype; Population; Population Genetics; Prevention; Publishing; RNA Splicing; Regulation; Research; Small Interfering RNA; Source; Spliced Genes; Test Result; Testing; Therapeutic; United States National Institutes of Health; Validation; Variant; Work; base; cytotoxic; cytotoxicity; design; disease diagnosis; disease phenotype; functional genomics; gene function; genetic variant; genomic data; genomic variation; high throughput screening; human disease; improved; mRNA Precursor; multidisciplinary; new technology; next generation sequencing; novel; oncology; prediction algorithm; protein function; protein structure; public health relevance; response; structural genomics; transcriptome sequencing; treatment response

 DESCRIPTION (provided by applicant): Genetic variations in introns commonly impact cellular functions by causing alterations in mRNA splicing. The abnormal inclusion and exclusion of exons often change protein functions and cellular phenotypes. Although many intronic variations have known functions, with the adoption of next generation sequencing, many more intronic variants have been discovered for which the functional impact is unknown. Thus, it is important to be able to predict the impact of the variants without needing to test them all in expensive and laborious assays. Although there are informatics algorithms that predict the impact of genetic variants on pre-mRNA splicing, their ability to predict the effect on protein function and ultimately disease and therapeutic phenotypes is lacking. In addition, there is a need for high-throughput cellular assays to test the results of these predictions on cellular functions. The studies proposed here will fulfill these needs by developing algorithms that prioritize the intronic variants by their potential impact on splicing and gene function, and developing a high-throughput assay to functionally test thousands of these predictions. These novel technologies will be applied to the effect of intronic variants on the pharmacogenomics of two clinically important oncology drugs, clofarabine and paclitaxel. Our long-term goals are to be able to predict the functional impact of genomic variants on human disease and therapeutic response. Our central hypothesis is that intronic genetic variants alter mRNA splicing and consequently protein function that ultimately affects the cellular response to drug therapy. Our first aim will be to develop computational algorithms that prioritize intronic variants based on their impacts on pre-mRNA splicing and protein function. Using a variety of genomic and structural features and large sets of genomic data, we will develop a bioinformatics algorithm specifically designed to prioritize intronic variants based on their potential impacts on pre-mRNA splicing and protein function. Our second aim will be to identify functional intronic variants associated with drug-induced cytotoxicity. Using existing genomics and cellular cytotoxic response data from populations of human cell lines, we will identify functional intronic variants that contribute to individuals' responses to clofarabine and paclitaxel cytotoxicity. Our third aim will be to functionally test the impact of the prioritized intronic variants on pre-mRNA splicing and drug cytotoxicity. Using our novel high- throughput functional splicing assay, we will test the effects of predicted functional variants from Aim 2 on pre- mRNA splicing. In addition, we will validate the effect of the intronic variants on cytotoxicity using exon specific siRNA and CRISPR/Cas technology to manipulate the target gene splicing. Upon completion of these studies, we expect to have developed bioinformatics algorithms that can accurately prioritize the intronic variants based on their functional impact on pre-mRNA splicing and protein function. Also, we will have tested thousands of variants in a cellular pre-mRNA splicing assay and validated the impact of several of these functional variants on paclitaxel and clofarabine cytotoxicity.

 描述（通过应用程序提供）：介绍的遗传变异通常通过引起mRNA剪接的改变来影响细胞功能。外显子的异常包含和排除通常会改变蛋白质功能和细胞表型。尽管许多内含子的变化具有已知的功能，但随着下一代测序的采用，已经发现了更多内含子的变体，其功能影响未知。这一点很重要的是，尽管有信息算法可以预测变体的影响，而无需在昂贵和实验室的测定中测试它们。尽管有信息算法可以预测遗传变异对MRNA剪接的影响，但缺乏预测对蛋白质功能以及最终疾病和治疗表型影响的能力。此外，需要高通量细胞测定法来测试这些预测对细胞功能的结果。这里提出的研究将通过开发算法来满足这些需求，从而通过对剪接和基因功能的潜在影响来确定内含子变体的优先级，并开发高通量测定法以在功能上测试数千个这些预测。这些新型技术将应用于内含子变体对两种临床重要肿瘤药物Clofarabine和Paclitaxel的药物的影响。我们的长期目标是能够预测基因组变异对人类疾病和治疗反应的功能影响。我们的中心假设是内含子的遗传变异改变了mRNA剪接，因此最终影响了细胞对药物治疗的反应。我们的第一个目的是开发基于内含子变体对MRNA剪接和蛋白质函数的影响来确定内含子变体的优先级的计算算法。使用多种基因组和结构特征以及大量基因组数据，我们将根据其对MRNA剪接和蛋白质功能的潜在影响来开发一种专门设计的生物信息学算法。我们的第二个目的是确定与药物诱导的细胞毒性相关的功能内含子变异。使用现有的基因组学和细胞细胞毒性反应数据，我们将确定功能性内含子变体，这有助于个体对克洛法拉滨和紫杉醇细胞毒性的反应。我们的第三个目标 将在功能上测试优先的内含子变体对MRNA剪接和药物细胞毒性的影响。使用我们新颖的高通量功能剪接测定法，我们将测试 AIM 2的预测功能变体对前MRNA剪接的影响。此外，我们将使用外显子特异性siRNA和CRISPR/CAS技术来验证内含子变体对细胞毒性的影响，以操纵靶基因剪接。这些研究完成后，我们希望已经开发出生物信息学算法，这些算法可以根据其功能对MRNA剪接和蛋白质功能的功能影响准确地优先考虑内含子变体。此外，我们还将在细胞前MRNA剪接测定法中测试数千种变体，并验证了这些功能变体对紫杉醇和克洛法拉滨细胞毒性的影响。