Computational Models for Mechanisms of Global Transcription Regulation

描述（由申请人提供）：来自Affyoung、Agilent和Nimblgen的全基因组平铺阵列允许生物学家进行无偏染色质免疫沉淀结合DNA微阵列分析（ChIP-芯片），以研究转录因子（TF）的基因组水平体内结合。然而，平铺阵列上的ChIP芯片也产生大量数据，并对分析算法的开发提出了挑战。我们建议开发有效的计算算法来分析ChIP芯片在基因组平铺阵列上的实验，并模拟全局转录调控机制，目的是让生物学家采用ChIP芯片来解开哺乳动物基因组中的转录调控网络。 我们的具体目标如下。(1)开发一种基于开源模型的算法，以识别在Affymbilled平铺阵列上由TF ChIP芯片富集的基因组区域。该方法将在不使用错配探针或对照实验的情况下对单个ChIP-芯片重复物起作用。(2)分析ChIP芯片程序、平铺阵列平台和分析方法中引入的性能变异性。(3)建立一个公共网络服务器，其中集成了用于哺乳动物基因组中全球ChIP区域序列分析的工具。(4)确定TF的合作结合伙伴和调控基因，并模拟其转录调控的全球机制。通过计算和实验生物学家之间的高度合作，包括ChIP芯片，基因表达谱，核小体占领和基序分析，我们将研究乳腺癌细胞中的雌激素受体调控。 拟议的项目将显着提高我们对哺乳动物基因组中的全球转录调控机制的理解。目的4：探讨乳腺癌中哪些基因受雌激素受体的调控，以及调控的原因。

DESCRIPTION (provided by applicant): Whole genome tiled arrays from Affymetrix, Agilent, and Nimblgen allow biologists to conduct unbiased chromatin immunoprecipitation coupled with DNA microarray analysis (ChlP-chip) to study the genome level in vivo binding of transcription factors (TFs). However, ChlP-chip on tiled arrays also generates massive amount data and poses a challenge for analysis algorithm development. We propose to develop effective computational algorithms to analyze ChlP-chip experiments on genome tiled arrays and model global transcription regulation mechanisms, for the goal of allowing biologists to adopt ChlP-chip to unravel the transcription regulatory network in mammalian genomes. Our specific aims are as follows. (1) Develop an open-source model-based algorithm to identify genomic regions enriched by TF ChlP-chip on Affymetrix tiled arrays. The approach will work with single ChlP-chip replicate without using mismatch probes or control experiments. (2) Analyze performance variability introduced in ChlP-chip procedures, tiled array platforms, and analysis methods. (3) Implement a public web server with integrated tools for sequence analysis of the global ChlP-regions in mammalian genomes. (4) Identify TF's cooperative binding partners and regulated genes, and model its global mechanisms of transcription regulation. Through highly collaborative efforts between computational and experimental biologists, including ChlP-chip, gene expression profiling, nucleosome occupation, and motif analyses, we will study estrogen receptor regulation in breast cancer cells. The proposed project will significantly enhance our understanding of global transcription regulatory mechanisms in mammalian genomes. Aim 4 will help answer the question what genes in breast carcinoma are regulated by estrogen receptor and why.