Engelhorn Julia, Turck Franziska
Max Planck Institute for Plant Breeding Research, Köln, Germany.
Methods Mol Biol. 2010;631:185-207. doi: 10.1007/978-1-60761-646-7_14.
Genome-wide analysis of histone modifications via ChIP-chip (chromatin immunoprecipitation followed by whole genome tiling array hybridization) may generate lists of up to several thousand potential target genes. In the case of the model organism Arabidopsis thaliana, several databases are available to alleviate further characterization and classification of genomic data sets. The term metaanalysis has been coined for this type of multidatabase comparison. In this chapter, we describe open source software and web tools that perform transcriptional and functional analysis of target genes. Sources of transcription data and clustering tools to subdivide genes according to their expression pattern are described. The user is guided through all necessary steps, including data download and formatting. In addition, the Gene Ontology (GO) vocabulary and methods to uncover over- or underrepresented functions among target genes are introduced. Genomic targets of the histone H3K27me3 modification are presented as a case study to demonstrate that metaanalysis can uncover novel functions that were hidden in genomic data sets.
通过芯片染色质免疫沉淀技术(ChIP-chip,即染色质免疫沉淀后进行全基因组平铺阵列杂交)对组蛋白修饰进行全基因组分析,可能会生成多达数千个潜在靶基因的列表。对于模式生物拟南芥而言,有几个数据库可用于进一步减轻基因组数据集的特征描述和分类工作。这种类型的多数据库比较被称为元分析。在本章中,我们将介绍用于对靶基因进行转录和功能分析的开源软件和网络工具。还将描述转录数据的来源以及根据基因表达模式对基因进行细分的聚类工具。我们将引导用户完成所有必要步骤,包括数据下载和格式化。此外,还将介绍基因本体论(GO)词汇以及揭示靶基因中功能过度或不足的方法。作为案例研究,我们展示了组蛋白H3K27me3修饰的基因组靶点,以证明元分析可以揭示隐藏在基因组数据集中的新功能。