Informatics Platform for Mammalian Gene Regulation at Isoform-level

异构体水平的哺乳动物基因调控信息学平台

• 批准号: 8843951
• 负责人: RAMANA V DAVULURI
• 金额: $ 33.72万
• 依托单位: NORTHWESTERN UNIVERSITY AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-05-02 至 2017-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8843951
• 关键词: Adopted; Algorithms; Alternative Splicing; Arts; Autistic Disorder; Binding Sites; Bioinformatics; Bipolar Disorder; Cells; ChIP-seq; Classification; Complex; Computational algorithm; Computer Simulation; Computer software; DNA; DNA Polymerase II; DNA-Protein Interaction; Data; Data Set; Databases; Development; Disease; Embryonic Development; Fertility; Gene Expression; Gene Expression Regulation; Gene Proteins; Generations; Genes; Genetic Transcription; Genome; Genomics; Goals; Homologous Gene; Human; Human Genome; Informatics; Laboratories; Life; Malignant Neoplasms; Mammalian Cell; Methodology; Methods; Modeling; Molecular; Mus; Nature; Oncogenic; Parkinson Disease; Pathway interactions; Pattern Recognition; Process; Protein Isoforms; Protein Kinase; Proteins; Regulation; Regulator Genes; Research; Research Personnel; Resource Informatics; Resources; Schizophrenia; Secure; Signal Pathway; Solutions; Staging; Statistical Models; TP53 gene; TP73 gene; Technology; Tissues; Transcript; Transcription Initiation; Transcription factor genes; Transcriptional Regulation; Trees; Tumor Suppressor Genes; Tumor Suppressor Proteins; Variant; Work; base; cancer initiation; cost; epigenomics; forest; genome-wide analysis; improved; innovation; neuropsychiatry; next generation sequencing; novel; prevent; promoter; protein function; public health relevance; tool; transcription factor; transcriptome sequencing; tumor progression; user friendly software; user-friendly; web-accessible

DESCRIPTION (provided by applicant): In recent years, the notion of "one gene makes one protein that functions in one signaling pathway" in mammalian cells has been shown to be overly simplistic. Recent evidence suggests that more than 50% of the human genes produce multiple protein isoforms, through alternative splicing and alternative usage of transcription initiation and/or termination. Notably, the disruption of many of these genes is implicated in cancer and several neuropsychiatric disorders. For majority of human genes the resulting multiple protein isoforms are functionally different and can participate in different signaling pathways. However, nearly after a decade since the completion of the human genome draft sequence, we still assume "gene" as the basic functional unit in a cell. We argue that the isoform-level gene products - "transcript variants" and "protein isoforms" are the basic functional units in a mammalian cell, and accordingly, the informatics resources for managing and analyzing gene regulation data in mammalian cells should adopt "gene isoform centric" rather than "gene centric" approaches. We propose to build an informatics platform for understanding gene regulation at isoform-level by developing statistically rigorous bioinformatics resources for processing Next-Generation Sequencing (NGS) data. Recently, computational approaches that combine seemingly disparate experimental data have been successful in developing concise gene regulation models and transcriptional modules. We plan to extend these methodologies to perform integrative analysis of multiple high-throughput data sets currently generated across different laboratories, including ours at Wistar, into computational models to predict different transcriptional isoforms of mammalian genes and protein-DNA interactions at isoform level. We will apply innovative statistical modeling approaches that combine state-of-the-art meta-classification algorithms, such as Na¿ve Bayes Tree, Bagging and LogitBoost, with Random Forest feature selection to classify different types of target promoters with good classification accuracy and reduced instability, in order to predict gene promoters and infer the protein-DNA interactions from ChIP-seq data. The computational models and the derived information will be integrated into a novel database, which will serve as an in silico platform for transcriptional regulation studies. This will be completed by pursuing the following aims, (1) Develop statistically rigorous novel algorithms and bioinformatics pipelines to identify the orthologous promoters, corresponding transcript variants and protein isoforms that are conserved between human and mouse, (2) develop novel algorithms and informatics pipelines for integrative analysis of NGS datasets to estimate the activity and expression of both known and novel promoters and their transcript variants, in various tissues, developmental stages, and disease conditions, and (3) develop a web-accessible database for integrating the information generated. The novel bioinformatics methods developed by this project will help in silico discovery and research for accelerating the linkage of phenotypic and genomic information, at gene-isoform level.

描述（由申请人提供）：近年来，在哺乳动物细胞中“一个基因产生一个在一个信号通路中起作用的蛋白质”的概念被证明过于简单。最近的证据表明，超过50%的人类基因通过选择性剪接和转录起始和/或终止的选择性使用产生多种蛋白质亚型。值得注意的是，许多这些基因的破坏与癌症和几种神经精神疾病有关。对于大多数人类基因来说，产生的多种蛋白质亚型在功能上是不同的，并且可以参与不同的信号通路。然而，在人类基因组草图序列完成近十年后，我们仍然认为“基因”是细胞的基本功能单位。我们认为异构体水平的基因产物——“转录变体”和“蛋白质异构体”是基本的功能