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:9071997
- 负责人:
- 金额:$ 57.63万
- 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 AssayClinical ResearchClofarabineComplexComputational algorithmComputersDataDiseaseEtiologyExclusionExonsGenesGenetic VariationGenomicsGoalsHumanHuman Cell LineHuman GeneticsIndividualInformaticsIntronsMachine LearningMessenger RNAMissionModelingMolecularPaclitaxelPharmaceutical PreparationsPharmacogenomicsPharmacotherapyPhenotypePopulationPopulation GeneticsPreventionPublishingRNA SplicingRegulationResearchSmall Interfering RNASourceSpliced GenesTest ResultTestingTherapeuticUnited States National Institutes of HealthValidationVariantWorkbasecytotoxiccytotoxicitydesigndisease diagnosisdisease phenotypefunctional genomicsgene functiongenetic variantgenomic datagenomic variationhigh throughput screeninghuman diseaseimprovedmRNA Precursormultidisciplinarynew technologynext generation sequencingnoveloncologyprediction algorithmprotein functionprotein structurepublic health relevanceresponsestructural genomicstranscriptome 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.
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.
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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Immune checkpoints in the CNS and HIV-associated neurocognitive disorder
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- 批准号:
10889463 - 财政年份:2023
- 资助金额:
$ 57.63万 - 项目类别:
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:
9280888 - 财政年份:2016
- 资助金额:
$ 57.63万 - 项目类别:
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