Regulation of mRNA splicing by intronic genetic variants
内含子遗传变异对 mRNA 剪接的调节
基本信息
- 批准号:9280888
- 负责人:
- 金额:$ 55.72万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:AdoptionAffectAlgorithmsAlternative SplicingBioinformaticsBiological AssayBiological ProcessCRISPR/Cas technologyCell LineCell physiologyCell-Mediated CytolysisCellular AssayClinicalClinical ResearchClofarabineComplexComputational algorithmComputersDataDiseaseEtiologyExclusionExonsGene TargetingGenesGenetic VariationGenomicsGoalsHumanHuman Cell LineHuman GeneticsIndividualInformaticsIntronsMachine LearningMessenger RNAMissionModelingMolecularPaclitaxelPharmaceutical PreparationsPharmacogenomicsPharmacotherapyPhenotypePopulationPopulation GeneticsPreventionPublishingRNA SplicingRegulationResearchSmall Interfering RNASourceSpliced GenesTest ResultTestingTherapeuticUnited States National Institutes of HealthValidationVariantWorkbasecell typecytotoxiccytotoxicitydesigndisease diagnosisdisease phenotypefunctional genomicsgene functiongenetic variantgenomic datagenomic predictorsgenomic variationhigh throughput screeninghuman diseaseimprovedmRNA Precursormultidisciplinarynew technologynext generation sequencingnoveloncologyprediction algorithmprotein functionprotein structurepublic health relevanceresponsetranscriptome sequencingtreatment response
项目摘要
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(由申请人提供):内含子的遗传变异通常通过引起 mRNA 剪接的改变来影响细胞功能,尽管许多内含子变异具有已知的功能,但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。一代测序中,已经发现了更多的内含子,其功能影响是未知的,因此,重要的是能够预测变体的影响,而无需通过昂贵且费力的检测来测试它们。是预测遗传变异对前 mRNA 剪接影响的信息学算法,但它们缺乏预测对蛋白质功能以及最终疾病和治疗表型的影响的能力。此外,还需要高通量细胞测定来测试。这里提出的研究将通过开发算法来满足这些需求,该算法根据内含子变异对剪接和基因功能的潜在影响进行优先级排序,并开发一种高通量测定法来对数千个此类预测进行功能测试。技术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。我们的首要目标是开发计算算法,根据内含子变异对前 mRNA 剪接的影响来优先考虑内含子变异。我们将利用各种基因组和结构特征以及大量基因组数据,开发一种专门设计的生物信息学算法,根据内含子变异对前 mRNA 剪接和蛋白质功能的潜在影响对其进行优先级排序。为了识别与药物诱导的细胞毒性相关的功能性内含子变异,利用来自人类细胞系群体的现有基因组学和细胞毒性反应数据,我们将识别有助于个体对氯法拉滨和紫杉醇反应的功能性内含子变异。我们的第三个目标。
我们将使用我们新型的高通量功能剪接测定来功能性测试优先内含子变异对前体 mRNA 剪接和药物细胞毒性的影响。
Aim 2 预测的功能变体对 mRNA 前体剪接的影响 此外,在完成这些研究后,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。我们希望开发出生物信息学算法,能够根据内含子变异对前 mRNA 剪接和蛋白质功能的功能影响准确地确定其优先级。此外,我们还将在细胞中测试数千种变异。前 mRNA 剪接测定并验证了其中几种功能变体对紫杉醇和氯法拉滨细胞毒性的影响。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Yunlong Liu其他文献
Yunlong Liu的其他文献
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Regulation of mRNA splicing by intronic genetic variants
内含子遗传变异对 mRNA 剪接的调节
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9071997 - 财政年份:2016
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$ 55.72万 - 项目类别:
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