课题基金 / 基金详情

Computational and Functional Analysis of Gene Networks

Computational and Functional Analysis of Gene Networks
基因网络的计算和功能分析
批准号:
6863973
负责人:
MARC S HALFON
金额:
$13.16万
依托单位国家:
美国
项目类别:
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-07-01 至 2007-06-30

项目摘要

项目成果

MARC S HALFON的其他基金

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DESCRIPTION: (provided by applicant) Metazoan development requires both intercellular signaling and the integration of these signals within cells to produce a transcriptional response. While many signaling pathways are well characterized, understanding on a global scale the interplay between signal transduction and gene transcription - genetic regulatory networks -remains a major challenge for current genomics research. We have explored in detail part of one such network, which specifies the fate of a subset of Drosophilamuscle and cardiac progenitor cells by the combined action of three signaling pathways, including the Ras pathway via input from both EGF and FGF receptors. The transcription factors downstream of these pathways, and tissue-specific factors induced by them, are integrated at a single transcriptional enhancer for a progenitor identity gene, the even skippedMuscle and Heart Enhancer (MHE). Therecent sequencing of the Drosophilagenome offers an exciting opportunity to extend the insights garnered from our investigation of the MHE on a genome-wide scale. Here, a computational analysis will be used to identify cis-regulatory elements that share features of the MHE and that regulate mesodermal gene expression in a similar spatiotemporal pattern. Invivo techniques, including the analysis of reporter transgenes, will be used to validate the computer predictions. The signaling component of the regulatory networks in which these cisregulatory elements act will be investigated using DNA microarrays. The respective contributions of the FGF and EGF-receptor pathways to Ras-mediated mesodermal signaling, non-Ras-mediated activities of these receptors, and the individual contributions of specific Ras transcriptional effectors will be determined, as will the combined effects of multiple growth factor signals. These approaches will significantly increase our understanding of combinatorial signaling and transcriptional responses by identifying new genes and regulatory elements, and provide insight into the genetic regulatory networks that mediate responses to signaling in a specific regulatory context. The research detailed in this proposal will provide the candidate with an ideal opportunity to apply a strong background in developmental genetics to the emerging fields of computational and functional genomics in a rich learning and research environment, in preparation for an independent academic research career.
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