Predicting Gene Structure--Vertebrate Genome Comparison

描述（由申请人提供）： 生物医学研究是对基因组序列被 available.然而，对于许多研究问题，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？ 他们的翻译产品的序列？尽管作出了重大贡献， 实验生物学、高通量测序和生物信息学，我们 还远远不能准确地回答这个问题。 这项研究旨在通过利用基因组数据来改进基因结构预测。 进化保护的模式。 目标1的重点是开发利用基因组同源性的概率模型 来改进基因结构预测。所提出的模型的一个新颖方面是 他们使用“保护序列”来代表 基因组中每个核苷酸的进化保守性被注释。一 保守序列是潜在重叠的局部序列的合成， 排列成一个序列。我们的概率模型建立在隐马尔可夫模型上 模型（HMM）方法用于最先进的基因结构预测 系统. 目标2的重点是开发概率模型，以提高基因预测， 利用cDNA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联合收割机来自 转录本与基因组同源性信息的比对， 同样的证据不能重复 目的3着重于利用多种同源性分析脊椎动物基因组 脊椎动物基因组最好的方法预计将取决于进化 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，具有由（a）小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Ensembl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。潜在生物医学 应用包括：（1）识别新的蛋白质家族， 作为药物靶点，以及（2）加速定位克隆项目 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.