Comparative Genomics to Identify Functional Blocks & HGT

比较基因组学来识别功能模块

• 批准号: 7240439
• 负责人: peter J bickel
• 金额: $ 16.38万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-06-01 至 2009-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7240439
• 关键词: Accounting; Algorithms; Animal Model; Antibiotics; Bacteria; Binding Sites; Biological; Blast Cell; Boxing; Classification; Code; Collaborations; Communicable Diseases; Communities; Computer software; DNA Sequence; Data; Databases; Development; Developmental Gene; Diagnosis; Disease; Disease regression; Disputes; Distant; Drops; Exhibits; Functional RNA; Genes; Genome; Genomics; Goals; Guanine + Cytosine Composition; Horizontal Gene Transfer; Human; Human Genome; Immunity; Individual; Joints; Knowledge; Laboratories; Learning; Length; Letters; Light; Linear Models; Link; Literature; Machine Learning; Markov Chains; Mathematics; Measurable; Measures; Methodology; Methods; Metric; Modeling; Molecular Profiling; Monte Carlo Method; Mus; Mutation; Neighborhoods; Nif Genes; None or Not Applicable; Numbers; Ontology; Pharmaceutical Preparations; Phase; Phylogenetic Analysis; Planning Techniques; Population; Probability; Process; Property; Proteins; Publications; RNA; Range; Rate; Regulation; Research; Research Design; Research Personnel; Ribosomal Proteins; Saccharomycetales; Sampling; Scheme; Score; Site; Specific qualifier value; Standards of Weights and Measures; Statistical Methods; Statistical Models; Stretching; Structure; Study models; Techniques; Tetraodontidae; Thinking; Tissues; Training; Trees; Vaccine Design; Validation; Weight; Work; analog; base; combinatorial; comparative; density; follow-up; forest; heuristics; markov model; member; novel strategies; prototype; size; statistics; transcription factor; vector; willingness

DESCRIPTION (provided by applicant): As the genomes of more and more species are sequenced it has become apparent that 1 of the most powerful techniques for detemining region function in the human genome is by comparison to the genomes of other species. The implications of such understanding for disease diagnosis and specialized drug and vaccine design are dear. Similarly, genomic comparison between bacteria can reveal regions which are functionally important in the development of infectious diseases and again aid drug and vaccine design. This project has 2 primary research goals. One (1) is the development of methodology for finding functionally predictive signatures of non-coding sequences (NCS) highly conserved across multiple species, and the other is to develop novel approaches for defecting Horizontal Gene Transfer (HG'T). The comparison of genomes is the common thread in this research. ln pursuit of their first goal, the investigators plan to integrate genomic sequence data, provided by their collaborators, with experimental and literature data, such as microarray-expression data, GO-functional-annotation for nearby genes, and ChlP-Chip data. The results will be used to evaluate the functional relevance, if any, of each NCS and then to define a signature predictive of function in terms of measurable covariates and sequence structure. For instance, if a sequence signature characterizes NCS whose nearest genes contribute to a particular function then an unknown gene close to an NCS with the same signature would be a prime candidate for interrogation of that function. The Investigators propose to attack this problem by 1). Developing non standard types of clustering methods based on supervised learning algorithms, e.g., Random Forests, 2) Representing the NCS by the parameters of a stochastic model and determining appropriate thresholds for model fitting by using resampling and other Monte Carlo methods. Under the second topic, the investigators propose 2 different approaches for determining whether functionaIly significant FGT has occurred in bacteria. The first approach is to take a known functionally important famlly (NIFgenes) for which HGT is a matter of dispute, and devise quantitative measures which they expect will enable a firm conclusion. They intend to refine similarity measures between genes in different species ,such as BLAST scores, corrected for evolutionary distance. They will compute these measures for pairs of NIF genes in different species, pairs, pairs of genes known to be HGT (antibiotic immunity conferring genes) and genes very unlikely to be HGT (ribosomal proteins). The second approach is to look for anomalously long stretches of 16s RNA conserved within substantial subsets of bacterial species which are otherwise only distantly related. Mathematical and statistical challenge include: Under approach I, standardizing comparisons of genes with different mutation rates; devising an appropriate classifier for HGT vs. non HGT, and computing appropriate estimates of the probability of classifying a gene as HGT when it isn't and vice versa; Under approach II, extending existing methods for detecting large inclusions by taking into account phylogenetic tree topology and branch lengths.

描述(申请人提供)：随着越来越多的物种的基因组被测序，很明显，确定人类基因组中区域功能的最强大的技术之一是通过与其他物种的基因组进行比较。这样的理解对疾病诊断和专门药物和疫苗设计的影响是昂贵的。同样，细菌之间的基因组比较可以揭示在传染病发展中具有重要功能的区域，并再次有助于药物和疫苗的设计。这个项目有两个主要的研究目标。一个(1)是寻找跨物种高度保守的非编码序列(NC)的功能预测特征的方法学的发展，另一个是开发新的方法来对抗水平基因转移(HG‘t)。基因组比较是本研究的共同主线。为了实现他们的第一个目标，研究人员计划将他们的合作者提供的基因组序列数据与实验和文献数据相结合，如微阵列表达数据、邻近基因的GO功能注释和ChlP芯片数据。结果将被用来评估每个NC的功能相关性，如果有的话，然后根据可测量的协变量和序列结构来定义功能的特征预测。例如，如果序列签名描述了其最近的基因对特定功能起作用的NCS，则与具有相同签名的NCS接近的未知基因将是询问该功能的首选候选。调查人员提议通过1)来解决这个问题。开发基于监督学习算法的非标准类型的聚类方法，例如随机森林，2)用随机模型的参数来表示网络控制系统，并通过使用重采样和其他蒙特卡罗方法来确定用于模型拟合的适当阈值。在第二个主题下，研究人员提出了两种不同的方法来确定是否在细菌中发生了功能显著的FGT。第一种方法是采用HGT存在争议的已知功能重要家族(NIFgene)，并设计出他们期望能够得出明确结论的量化措施。他们打算改进不同物种基因之间的相似性测量，例如BLAST分数，并根据进化距离进行校正。他们将计算不同物种中的NIF基因对、对、已知为HGT(抗生素免疫授权基因)的基因对以及不太可能是HGT(核糖体蛋白)的基因。第二种方法是寻找在细菌物种的实质性亚群中保守的异常长的16S RNA片段，否则这些细菌物种只有遥远的亲缘关系。数学和统计学方面的挑战包括：在方法一下，标准化具有不同突变率的基因的比较；为HGT和非HGT设计适当的分类器，并计算适当的估计，当一个基因不是HGT时，将其归类为HGT，反之亦然；在方法II下，通过考虑系统发育树的拓扑结构和分支长度，扩展现有的检测大型包裹体的方法。