Bhinge Akshay A, Kim Jonghwan, Euskirchen Ghia M, Snyder Michael, Iyer Vishwanath R
Institute for Cellular and Molecular Biology, Center for Systems and Synthetic Biology, Section of Molecular Genetics and Microbiology, University of Texas at Austin, Austin, Texas 78712, USA.
Genome Res. 2007 Jun;17(6):910-6. doi: 10.1101/gr.5574907.
Identifying the genome-wide binding sites of transcription factors is important in deciphering transcriptional regulatory networks. ChIP-chip (Chromatin immunoprecipitation combined with microarrays) has been widely used to map transcription factor binding sites in the human genome. However, whole genome ChIP-chip analysis is still technically challenging in vertebrates. We recently developed STAGE as an unbiased method for identifying transcription factor binding sites in the genome. STAGE is conceptually based on SAGE, except that the input is ChIP-enriched DNA. In this study, we implemented an improved sequencing strategy and analysis methods and applied STAGE to map the genomic binding profile of the transcription factor STAT1 after interferon treatment. STAT1 is mainly responsible for mediating the cellular responses to interferons, such as cell proliferation, apoptosis, immune surveillance, and immune responses. We present novel algorithms for STAGE tag analysis to identify enriched loci with high specificity, as verified by quantitative ChIP. STAGE identified several previously unknown STAT1 target genes, many of which are involved in mediating the response to interferon-gamma signaling. STAGE is thus a viable method for identifying the chromosomal targets of transcription factors and generating meaningful biological hypotheses that further our understanding of transcriptional regulatory networks.
识别转录因子的全基因组结合位点对于解读转录调控网络至关重要。染色质免疫沉淀结合微阵列技术(ChIP-chip)已被广泛用于绘制人类基因组中转录因子的结合位点。然而,在脊椎动物中进行全基因组ChIP-chip分析在技术上仍然具有挑战性。我们最近开发了STAGE,作为一种无偏差的方法来识别基因组中的转录因子结合位点。STAGE在概念上基于SAGE,不同之处在于输入的是ChIP富集的DNA。在本研究中,我们实施了一种改进的测序策略和分析方法,并应用STAGE来绘制干扰素处理后转录因子STAT1的基因组结合图谱。STAT1主要负责介导细胞对干扰素的反应,如细胞增殖、凋亡、免疫监视和免疫反应。我们提出了用于STAGE标签分析的新算法,以识别具有高特异性的富集位点,定量ChIP验证了这一点。STAGE识别出了几个先前未知的STAT1靶基因,其中许多基因参与介导对干扰素-γ信号的反应。因此,STAGE是一种可行的方法,可用于识别转录因子的染色体靶点并生成有意义的生物学假设,从而加深我们对转录调控网络的理解。