Computational Models for Mechanisms of Global Transcription Regulation

描述(申请人提供)：Affymetrix、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和DNA微阵列分析(ChLP-CHIP)，以研究体内转录因子(TF)的基因组水平结合。然而，平铺阵列上的ChlP芯片也产生了大量的数据，给分析算法的开发带来了挑战。我们建议开发有效的计算算法来分析基因组平铺阵列上的ChlP-ChIP实验，并建立全球转录调控机制的模型，以使生物学家能够利用ChlP-ChIP来揭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)开发了一种基于开源模型的算法，用于在Affymetrix平铺阵列上识别由Tf ChlP-ChIP富集的基因组区域。该方法将适用于单芯片复制，而不使用不匹配的探针或对照实验。(2)分析了CHLP-CHIP程序、平铺阵列平台和分析方法中引入的性能变异性。(3)实现了一个公共网络服务器，集成了哺乳动物基因组ChlP区序列分析的集成工具。(4)确定转录因子的协同结合伙伴和调控基因，并模拟其转录调控的整体机制。通过计算生物学家和实验生物学家的高度合作，包括ChlP芯片、基因表达谱、核小体占据和基序分析，我们将研究乳腺癌细胞中雌激素受体的调控。 这项拟议的项目将显著提高我们对哺乳动物基因组中全球转录调控机制的理解。Aim 4将帮助回答乳腺癌中哪些基因受到雌激素受体的调控以及为什么。

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.