Engelhorn Julia, Turck Franziska
Max Planck Institute for Plant Breeding Research, Carl von Linné Weg 10, 50829, Köln, Germany.
Methods Mol Biol. 2017;1456:33-50. doi: 10.1007/978-1-4899-7708-3_3.
Genome-wide analyses of chromatin factor-binding sites or histone modification localization generate lists of up to several thousand potential target genes. For many model organisms, large annotation databases are available to help with the characterization and classification of genomic datasets. The term meta-analysis has been coined for this type of multi-database comparison. In this chapter, we describe a workflow to perform a transcriptional and functional analysis of genome-wide target genes. Sources of transcription data and clustering tools to subdivide genes according to their expression pattern are described. For a functional analysis, we focus on the Gene Ontology (GO) vocabulary and methods to uncover over- or underrepresented functions among target genes. Genomic targets of the histone modification H3K27me3 are presented as a case study to demonstrate that meta-analysis can uncover functions that were hidden in genome-wide datasets.
对染色质因子结合位点或组蛋白修饰定位进行全基因组分析会生成多达数千个潜在靶基因的列表。对于许多模式生物，有大型注释数据库可用于帮助对基因组数据集进行表征和分类。这种多数据库比较被称为元分析。在本章中，我们描述了一种对全基因组靶基因进行转录和功能分析的工作流程。描述了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。对于功能分析，我们重点介绍基因本体论（GO）词汇以及揭示靶基因中功能过度或不足的方法。组蛋白修饰H3K27me3的基因组靶点作为案例研究呈现，以证明元分析可以揭示隐藏在全基因组数据集中的功能。
