Promoter Prediction Using the Opening Profile of DNA

使用 DNA 开放谱预测启动子

• 批准号: 7406651
• 负责人: ANNY A USHEVA-SIMIDJIYSKA
• 金额: $ 28.26万
• 依托单位: BETH ISRAEL DEACONESS MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-05-01 至 2010-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7406651
• 关键词: Actins; Adenoviruses; Algorithms; Aspergillus Nuclease S1; Base Pairing; Biological Assay; Birds; Cells; Cereals; Classification; Complementary DNA; Computer Simulation; Consensus Sequence; DNA; DNA Fingerprinting; DNA Sequence; DNA analysis; Data; Digestion; Exhibits; Frequencies; Future; Gene Expression Regulation; Genes; Genetic Transcription; Genome; Genomics; Human; Human Genome; Hybrids; Indium; Investigation; Knowledge; Late Promoters; Left; Localized; Methodology; Methods; Modeling; Modification; Numbers; Pattern; Positioning Attribute; Predictive Value; Principal Investigator; Process; Promoter Regions; Property; Publications; Regulation; Relative (related person); Research Personnel; Research Project Grants; Sampling; Sequence Homology; Site; Smooth Muscle Myocytes; TATA Box; Techniques; Therapeutic; Transcription Initiation; Transcription Initiation Site; Viral; base; concept; cost; design; endonuclease; in vitro Assay; mathematical model; novel; physical property; predictive modeling; programs; promoter; protein folding; research study; simulation; success; tool; transcription factor

The field of promoter prediction holds almost limitless potential, but has had very limited success. Instead of analyzing DMA sequence homology, we propose a novel method of eucaryotic promoter prediction based on the physical properties of DNA which arise from the local sequence. Using computer simulations with a nonlinear mathematical model, we predict the localized opening profile of a region of DNA. For several sample eucaryotic promoters, we have demonstrated that the dominant preferential opening positions predicted by the model (and verified by S1 nuclease digestion assays) correlate well with the experimentally-determined transcriptional start sites or major regulatory sites of the gene promoters. We hypothesize that these opening profiles can be applied more generally in seeking out novel gene promoters and transcriptionally significant sites in genomic DNA. Here we propose to further validate the use of nonlinear mathematical models to predict opening profiles as indicators for eukaryotic promoter prediction using known gene core promoters with experimentally-determined transcriptional start sites. We will also seek to apply the computational promoter prediction method in proof-of-concept studies on genes with unidentified promoters and transcriptional start sites. Finally, we plan to develop numerical techniques that allow application of our promoter prediction model on a genomic scale. The simulation-based analysis of DNA opening profiles shows great potential in the prediction of human gene promoters. This method is superior to previous prediction models in that it examines sequence-derived physical properties of DNA rather than sequence homology, however, further investigation is necessary to evaluate and expand the limits of applicability of this method. One of the strongest advantages of the computational model is that it can be used to evaluate opening profiles for any sequence of eukaryotic DNA with very little cost.

启动子预测领域拥有几乎无限的潜力，但取得的成功却非常有限。我们提出了一种基于局部序列产生的 DNA 物理特性的真核启动子预测新方法，而不是分析 DMA 序列同源性。利用计算机模拟和非线性数学模型，我们预测了 DNA 区域的局部开放轮廓。对于几个真核生物启动子样本，我们已经证明模型预测的显性优先开放位置（并通过 S1 核酸酶消化测定验证）与实验确定的相关性很好 基因启动子的转录起始位点或主要调控位点。我们假设 这些开放谱可以更广泛地应用于寻找新的基因启动子和 基因组 DNA 中具有重要转录意义的位点。在这里，我们建议进一步验证使用非线性数学模型来预测开放谱，作为使用具有实验确定的转录起始位点的已知基因核心启动子进行真核启动子预测的指标。我们还将寻求将计算启动子预测方法应用于具有未识别启动子和转录起始位点的基因的概念验证研究。最后，我们计划开发数值技术，允许在基因组规模上应用我们的启动子预测模型。基于模拟的 DNA 开放谱分析在预测人类基因启动子方面显示出巨大的潜力。该方法优于以前的预测模型，因为它检查 DNA 的序列衍生物理特性而不是序列同源性，然而，需要进一步研究来评估和扩大该方法的适用性限制。计算模型的最大优势之一是它可用于评估任何真核 DNA 序列的开放谱 以很少的成本。