染色质免疫沉淀
大规模并行测序
生物
染色质
芯片排序
免疫沉淀
DNA测序
巨量平行
计算生物学
基因组
分子生物学
DNA
人类基因组
遗传学
基因
发起人
基因表达
染色质重塑
计算机科学
并行计算
作者
Gordon Robertson,Martin Hirst,Matthew N. Bainbridge,Misha Bilenky,Yongjun Zhao,Thomas Zeng,Ghia Euskirchen,Bridget Bernier,Richard Varhol,Allen Delaney,Nina Thiessen,Obi L. Griffith,Ann He,Marco A. Marra,M Snyder,Steven J.M. Jones
出处
期刊:Nature Methods
[Nature Portfolio]
日期:2007-06-11
卷期号:4 (8): 651-657
被引量:1404
摘要
We developed a method, ChIP-sequencing (ChIP-seq), combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing to identify mammalian DNA sequences bound by transcription factors in vivo. We used ChIP-seq to map STAT1 targets in interferon-gamma (IFN-gamma)-stimulated and unstimulated human HeLa S3 cells, and compared the method's performance to ChIP-PCR and to ChIP-chip for four chromosomes. By ChIP-seq, using 15.1 and 12.9 million uniquely mapped sequence reads, and an estimated false discovery rate of less than 0.001, we identified 41,582 and 11,004 putative STAT1-binding regions in stimulated and unstimulated cells, respectively. Of the 34 loci known to contain STAT1 interferon-responsive binding sites, ChIP-seq found 24 (71%). ChIP-seq targets were enriched in sequences similar to known STAT1 binding motifs. Comparisons with two ChIP-PCR data sets suggested that ChIP-seq sensitivity was between 70% and 92% and specificity was at least 95%.
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