Predicting the causative SNPs in LD blocks by allele-specific structural analysis

通过等位基因特异性结构分析预测 LD 块中的致病 SNP

• 批准号: 8792744
• 负责人: Alain T Laederach
• 金额: $ 75.13万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8792744
• 关键词: 3' Untranslated Regions; Acylation; Adopted; Affect; Algorithms; Alleles; Automobile Driving; Benchmarking; Binding Proteins; Cartilage; Cataloging; Catalogs; Cataract; Cells; Chemical Structure; Chemicals; Code; Communities; Data; Detection; Development; Disease; Elements; Entropy; Free Energy; Genetic Code; Genetic Polymorphism; Genome; Genomics; Genotype; Hair; Haplotypes; Hepatitis C virus; Higher Order Chromatin Structure; Human; Human Genome; Hydroxyl Radical; In Vitro; Indium; Individual; Inherited; Intercistronic Region; Life; Linkage Disequilibrium; Maps; Mediating; Modeling; Molecular; Molecular Conformation; Mutation; Nature; Phenotype; Play; Polymers; Predictive Value; Primer Extension; Protein Binding; Proteins; RNA; RNA Folding; RNA-Binding Proteins; Regulatory Pathway; Research Design; Retinoblastoma; Ribosomes; Risk; Role; Sampling; Single Nucleotide Polymorphism; Specificity; Structural Models; Structure; Syndrome; Transcript; Translating; Untranslated RNA; Untranslated Regions; Validation; Variant; Vision; Work; cooking; design; genetic information; genome wide association study; genotyping technology; human disease; improved; in vivo; public health relevance; research study; tool development

 DESCRIPTION (provided by applicant): Genome wide association studies are powerful for correlating human genotype to phenotype. These studies are designed to identify the polymorphisms in the genetic code that are most predictive of a phenotype. Rapid advances in genotyping technologies enable comprehensive coverage of the genome, including a majority of intergenic polymorphisms. Interestingly, when included in the association analysis, non-coding polymorphisms are often the most highly predictive of the phenotype. Furthermore, Single Nucleotide Polymorphisms (SNPs) are inherited together in Linkage Disequilibrium (LD) blocks. As a result, identifying the causative SNP in an LD block mapping to non-coding regions of the genome remains a contemporary computational and experimental challenge in the field of genomics. Although non-coding regions of the genome are not translated into protein, they are in a majority of cases transcribed in RiboNucleic Acid (RNA). Since RNA is a single stranded polymer, it will fold and the higher-order structures it adopts are integral to numerous RNA-mediated post-transcriptional regulatory functions in the cell. In detailed and focused studies of individual transcripts, our team has discovered that disruption of RNA structural features in non-coding regions of transcribed RNAs are causative in at least three human disease states - hyperferritinemia cataract syndrome, retinoblastoma and cartilage hair hypoplasia - and that altered RNA structure determines hepatitis C virus clearance efficiency. The vision of this proposal is to improve our computational ability to predict RiboSNitches (structural features in RNA that are disrupted by a SNP) by improving the accuracy of ensemble suboptimal structure sampling and pseudoknot prediction, and by using chemical structure probing data to characterize allele-specific RNA conformations, both in vitro and in healthy living cells in vivo. Ultimately, this work will substantially improve our ability to predict the causative disease-associated SNP in an LD block mapping to non-coding, intergenic regions of the human genome.

 描述(由申请人提供)：全基因组关联研究是将人类基因型别与表型联系起来的有力工具。这些研究旨在确定遗传密码中最能预测表型的多态。基因分型技术的快速发展使基因组的全面覆盖成为可能，包括大多数基因间的多态。有趣的是，当包括在关联分析中时，非编码多态通常是最高预测性的表型。此外，单核苷酸多态(SNPs)在连锁不平衡(LD)块中一起遗传。因此，在基因组学领域中，识别LD区块映射到基因组非编码区的致病SNP仍然是一个当代的计算和实验挑战。尽管基因组的非编码区没有翻译成蛋白质，但在大多数情况下，它们是在核糖核酸(RNA)中转录的。由于RNA是单链聚合物，它会折叠，它所采用的高阶结构是细胞中许多RNA介导的转录后调节功能所必需的。在对单个转录本的详细和有重点的研究中，我们的团队发现，转录RNA非编码区RNA结构特征的破坏是至少三种人类疾病状态--高铁素血症白内障综合征、视网膜母细胞瘤和软骨头发发育不良--的原因，而RNA结构的改变决定了丙型肝炎病毒的清除效率。这项建议的愿景是通过提高整体次优结构采样和假结预测的准确性，以及通过使用化学结构探测数据来表征体外和体内健康活细胞中的等位基因特异性RNA构象，从而提高我们预测RiboSNitch(被SNP破坏的RNA中的结构特征)的计算能力。最终，这项工作将大大提高我们在LD块映射到人类基因组的非编码基因间区中预测与疾病相关的SNP的能力。