Predicting Gene Structure--Vertebrate Genome Comparison

描述(由申请人提供)：比例稳步上升 生物医学研究是对基因组序列是 可用。然而，对于许多研究问题来说，基因组是重要的。 主要是因为它的蛋白质产品。因此，基因组中的一个关键问题 分析是：所有基因的结构和确切的氨基酸是什么 他们的翻译产品序列是什么？尽管做出了重大贡献 实验生物学、高通量测序和生物信息学，我们 仍然远远不能准确地回答这个问题。 拟议的研究旨在通过开发提高基因结构预测 进化守恒的模式。 目标1专注于开发利用基因组同源性的概率模型 改进基因结构预测。提出的模型的一个新方面是 他们用“守恒序列”来表示 基因组中每个核苷酸的进化保守性待注释。一个 保守序列是潜在重叠的局部序列的合成 比对成一个序列。我们的概率模型建立在隐马尔可夫模型的基础上 模型(HMM)方法在基因结构预测中的应用 系统。 目标2专注于开发概率模型，通过以下方式改进基因预测 利用cDNAs和EST比对。基本方法与此类似 目标1.最重要的新问题是如何将来自 转录本与来自基因组同源信息的比对 不能两次计算相同的证据。 目的3重点分析脊椎动物基因组的同源性 脊椎动物基因组。最好的方法应该取决于进化的 基因组之间的距离。我们的研究将集中在基因结构上 在人类中的预测，与(A)老鼠和河豚提供的同源性， 和(B)小鼠和大鼠。 我们的基因结构预测将提供给研究界 通过我们的网站和我们在Ensambl的合作者的网站。 可靠地预测完整基因结构的能力将构成 高通量生物学的重大进展。潜在的生物医学 应用包括：(1)识别可能起作用的新蛋白质家族 作为药物靶点，以及(2)加快位置克隆项目 疾病相关基因的鉴定。

DESCRIPTION (provided by applicant): A steadily increasing proportion of biomedical research is conducted on organisms for which genomic sequence is available. For many research questions, however, a genome is important primarily because of its protein products. Thus, a critical question in genome analysis is: What are the structures of all the genes and the exact amino acid sequences of their translation products? Despite significant contributions from experimental biology, high-throughput sequencing, and bioinformatics, we are still far from being able to answer this question accurately. The proposed research aims to improve gene-structure prediction by exploiting patterns of evolutionary conservation. Aim 1 focuses on developing probability models for exploiting genomic homology to improve gene-structure prediction. A novel aspect of the proposed models is their use of "conservation sequence" to represent the degree and pattern of evolutionary conservation at each nucleotide in the genome to be annotated. A conservation sequence is a synthesis of potentially overlapping local alignments into one sequence. Our probability models build on the Hidden Markov Model (HMM) approach used in state-of-the-art gene-structure prediction systems. Aim 2 focuses on developing probability models for improving gene prediction by exploiting cDNA and EST alignments. The fundamental approach is similar to that of Aim 1. The most important new question is how to combine information from transcript alignments with information from genomic homology in a way that does not count the same evidence twice. Aim 3 focuses on analysis of vertebrate genomes using homology from multiple vertebrate genomes. The best method is expected to depend on the evolutionary distances among the genomes. Our investigations will focus on gene-structure prediction in human, with homology provided by (a) both mouse and pufferfish, and (b) both mouse and rat. Our gene-structure predictions will be provided to the research community through our web site and that of our collaborators at Ensembl. The ability to predict complete gene structures reliably would constitute significant progress in high-throughput biology. Potential biomedical applications include: (1) Identifying novel protein families that could serve as drug targets, and (2) Accelerating positional cloning projects for the identification of disease related genes.