COMPUTATIONAL ANALYSIS OF HUMAN 'AT-RISK' DNA MOTIFS

人类“高危”DNA 基序的计算分析

• 批准号: 6133321
• 负责人: JUDITH E. STENGER
• 金额: $ 10.46万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-06-01 至 2005-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6133321
• 关键词: environmental health; environmental toxicology; gene environment interaction; gene expression; gene rearrangement; genetic susceptibility; human genetic material tag; molecular biology information system; nucleic acid repetitive sequence; nucleic acid sequence

DESCRIPTION (Taken from the Candidate's Abstract) At-Risk DNA Motifs (ARMS), which include repetitive elements such as Alu sequences, homonucleotide runs and triplet repeats, are potentially unstable segments of the human genome. ARMS are a factor in genetic susceptibility to disease, requiring particular combinations of genetic backgrounds and environmental triggers to express a disease phenotype. While some of the mechanisms are understood, it is not clear under what circumstances repetitive DNA elements mediate pathological mutagenesis. Although a high burden of these sequences is generally tolerated in humans, they can have an enormous impact on health by contributing to diseases that have devastating effects on afflicted individuals. For example, Alus have been linked to numerous diseases including Fanconi anemia, alphazerothalassemia, leukemia, hypertension, neurofibromatosis, breast, and colon cancers. Trinucleotide repeat expansions have been linked with Kennedy's Disease, Huntington's Disease, myotonic muscular dystrophy, and Friedreich ataxia. The long term objective of this proposal is to gain insight into the genetic factors that mitigate gene rearrangement in hopes of predicting when the presence of a repetitive element truly constitutes a threat to the health of an individual. The hypothesis is that the characterization of ARMS according to all possible attributes (i.e. size of repeats, separation distances between repeats, orientation, sequence similarity between repeats, nucleotide base constitution and proximity and/or containment of mutagenic and/or toxicological agent targets, DNA processive or other enzymatic target sites) can reveal largely excluded situations that can be viewed as unstable. It is also postulated that a multidimensional database of repetitive sequences characterized according to the aforementioned attributes can be used to predict repetitive elements that are most prone to mutation, ARMS, while increasing our understanding of the interactions between these genetic elements and their environment. The approach is to use a combination of computational biology and molecular genomic analysis to locate and analyze ARMS. The specific aims of this proposal are to: 1) characterize available data according to the conceivable relevant attributes of size, distance, orientation, degree of homology, base constitution and containment of known target sequences. 2) To test the hypothesis by computationally identifying loci that have already known to contain ARMS linked to a mutation resulting in disease, and then to identify specific genes that may be at-risk for mutation and experimentally testing them using molecular biological approaches. 3) To set up an interactive on-line database and program server so that the scientific community can use the information and apply it to drive experimental research.

描述（摘自候选人的摘要） 有风险的 DNA 基序 (ARMS)，其中包括 Alu 等重复元素 序列、同核苷酸序列和三联体重复序列可能不稳定 人类基因组的片段。 ARMS 是遗传易感性的一个因素 疾病，需要遗传背景的特定组合 表达疾病表型的环境触发因素。 虽然有些 机制已了解，但不清楚在什么情况下重复 DNA 元件介导病理突变。 虽然负担很大 这些序列通常在人类中是可以耐受的，它们可以产生巨大的影响 导致对健康产生破坏性影响的疾病 受苦受难的个人。 例如，Alus 已与许多 疾病包括范可尼贫血、α零地中海贫血、白血病、 高血压、神经纤维瘤病、乳腺癌和结肠癌。 三核苷酸 重复扩张与肯尼迪病、亨廷顿病有关 疾病、强直性肌营养不良症和弗里德赖希共济失调。 长期来看 该提案的目的是深入了解导致 减轻基因重排，希望预测何时存在 重复元素确实对个人健康构成威胁。 假设 ARMS 的特征是根据所有可能的 属性（即重复的大小、重复之间的间隔距离、 方向、重复之间的序列相似性、核苷酸碱基构成 以及诱变剂和/或毒理学剂的接近和/或遏制 目标、DNA 持续或其他酶目标位点）可以很大程度上揭示 排除可被视为不稳定的情况。 还假设 重复序列的多维数据库表征 根据上述属性可以用来预测重复 最容易发生突变的元素，ARMS，同时增加我们的 了解这些遗传元素及其之间的相互作用 环境。 该方法是结合使用计算生物学 和分子基因组分析来定位和分析 ARMS。 具体目标 该提案的目的是： 1）根据 尺寸、距离、方向、程度等可想象的相关属性 已知靶序列的同源性、碱基构​​成和包含情况。 2) 至 通过计算识别已经存在的基因座来检验假设 已知含有与导致疾病的突变相关的 ARMS，然后 识别可能有突变风险的特定基因并通过实验 使用分子生物学方法对其进行测试。 3）设立一个 交互式在线数据库和程序服务器，使科学 社区可以使用这些信息并将其应用于推动实验研究。