Further development of the FEAST software, and its use for novel gene predictions

FEAST 软件的进一步开发及其在新基因预测中的应用

• 批准号: 7287974
• 负责人: Arian Fredericus Anthonius Smit
• 金额: $ 33.9万
• 依托单位: INSTITUTE FOR SYSTEMS BIOLOGY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2010-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7287974
• 关键词: Algorithms; Cataloging; Catalogs; Cell physiology; Class; Code; Complement component C1s; Computer software; Custom; Data; Databases; Development; Elements; Exons; Facility Construction Funding Category; Freezing; Functional RNA; Gene Cluster; Gene Structure; Genes; Genetic; Genome; Genomics; Goals; Human; Human Genome; Hybridization Array; Introns; Joints; Length; Metabolic; Methods; MicroRNAs; Modeling; Pattern; Play; Prevalence; Production; Regulation; Research Personnel; Reverse Transcriptase Polymerase Chain Reaction; Role; Signal Transduction; Small Nucleolar RNA; Small RNA; Statistical Models; Stratification; Technology; Testing; Training; Transcript; Update; Weight; anticancer research; functional genomics; gene discovery; genome sequencing; improved; novel; programs; software development; tool

DESCRIPTION (provided by applicant): We developed a suite of four transcript prediction algorithms collectively called "FEAST" (Fast Empirical Algorithms Suggesting Transcripts), which are conceptually independent of the two established classes of gene discovery algorithms, namely "ab initio" and database search methods. The main goals of this proposal are (1) to develop further this independent third class of gene prediction algorithms, (2) to apply them to the dentification of novel genes in the genome, and (3) to test the hypothesis that non-coding transcripts are prevalent in the genome, and are the medium for the expression of small RNA genes and other functional genomic elements. We will extend the statistical model and develop the software towards a fully integrated gene prediction tool capable of discovering genes in genomic sequences of one species, or in multiple species simultaneously for higher precision. We will use the new tool to produce a comprehensive catalog of predicted genes. This is the genetic "parts list", that is required for the construction of metabolic and regulatory models of cell function. We will correlate the transcript predictions to expression data from hybridization array technology, and validate novel genes experimentally by RT-PCR and sequencing. We identified an unusual class of genes (which we call "stencil" genes) in which the exons play no other role than the production of introns as precursor material for deriving one or more functional RNA molecules, like miRNAs and snoRNAs. We will put special emphasis in obtaining a comprehensive catalog of such "stencil" genes and will study computationally their prevalence, their modes of regulation and how they evolve. We expect many of the novel transcripts to be central to the genetic regulation of development, and therefore of direct importance to cancer research.

描述（由申请人提供）：我们开发了一套四种转录本预测算法，统称为“FEAST”（建议转录本的快速经验算法），它们在概念上独立于两类已建立的基因发现算法，即“ab initio”和数据库搜索方法。该提案的主要目标是（1）进一步开发这种独立的第三类基因预测算法，（2）将其应用于基因组中新基因的识别，以及（3）检验非编码基因的假设转录本在基因组中普遍存在，是小RNA基因和其他功能基因组元件表达的媒介。我们将扩展统计模型，并将软件开发为完全集成的基因预测工具，能够发现一个物种基因组序列中的基因，或同时发现多个物种中的基因，以获得更高的精度。我们将使用新工具来生成预测基因的综合目录。这是构建细胞功能代谢和调节模型所需的遗传“部件列表”。我们将转录本预测与杂交阵列技术的表达数据相关联，并通过 RT-PCR 和测序实验验证新基因。我们发现了一类不寻常的基因（我们称之为“模板”基因），其中外显子除了产生内含子作为衍生一个或多个功能性 RNA 分子（如 miRNA 和 snoRNA）的前体材料外，不发挥任何其他作用。我们将特别强调获得此类“模板”基因的全面目录，并将通过计算研究它们的流行程度、它们的调节模式以及它们如何进化。我们预计许多新的转录本对于发育的遗传调控至关重要，因此对癌症研究具有直接重要性。