Time-dependent c-Myc transactomes mapped by Array-based nuclear run-on reveal transcriptional modules in human B cells

通过基于阵列的核连写映射的时间依赖性 c-Myc 转录组揭示了人类 B 细胞中的转录模块

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作者:Jinshui Fan, Karen Zeller, Yu-Chi Chen, Tonya Watkins, Kathleen C Barnes, Kevin G Becker, Chi V Dang, Chris Cheadle

Background

The definition of transcriptional networks through measurements of changes in gene expression profiles and mapping of transcription factor binding sites is limited by the moderate overlap between binding and gene expression changes and the inability to directly measure global nuclear transcription (coined "transactome"). Methodology/principal findings: We developed a method to measure nascent nuclear gene transcription with an Array-based Nuclear Run-On (ANRO) assay using commercial microarray platforms. This strategy provides the missing component, the transactome, to fully map transcriptional networks. ANRO measurements in an inducible c-Myc expressing human P493-6 B cell model reveals time-dependent waves of transcription, with a transactome early after c-Myc induction that does not persist at a late, steady-state phase, when genes that are regulated by c-Myc and E2F predominate. Gene set matrix analysis further uncovers functionally related groups of genes putatively regulated by waves of transcription factor motifs following Myc induction, starting with AP1 and CREB that are followed by EGR1, NFkB and STAT, and ending with E2F, Myc and ARNT/HIF motifs. Conclusions/significance: By coupling ANRO with previous global mapping of c-Myc binding sites by chromatin immunoprecipitation (ChIP) in P493-6 cells, we define a set of transcriptionally regulated direct c-Myc target genes and pave the way for the use of ANRO to comprehensively map any transcriptional network.

Significance

By coupling ANRO with previous global mapping of c-Myc binding sites by chromatin immunoprecipitation (ChIP) in P493-6 cells, we define a set of transcriptionally regulated direct c-Myc target genes and pave the way for the use of ANRO to comprehensively map any transcriptional network.

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