ChIP-seq for Characterization of transcription factor function and patterns fo gene regulation in HepG2 cells
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ABSTRACT: Transcription factors (TFs) are trans-acting proteins that bind cis-regulatory elements (CREs) in DNA to control gene expression. Here, we analyze the genomic localization profiles of 529 sequence-specific TFs and 151 cofactors and chromatin regulators in the cancer cell line HepG2, for a total of 680 broadly-termed DNA-Associated Proteins (DAPs). We use this deep collection to model each TF's impact on gene expression, including identifying a cohort of 26 candidate transcriptional repressors. We examine High Occupancy Target (HOT) sites in the context of three-dimensional genome organization and show biased motif placement in enhancer-promoter connections involving HOT sites. We also find a substantial number of closed chromatin regions with multiple DAPs bound and explore their properties, finding that a MAFF/MAFK TF pair correlates with transcriptional repression. Altogether, these analyses provide novel insights into the regulatory logic of the human cell line HepG2 genome and demonstrate the usefulness of large genomic analyses for elucidation of individual TF functions.
Project description:Transcription factors (TFs) are trans-acting proteins that bind cis-regulatory elements (CREs) in DNA to control gene expression. Here, we analyze the genomic localization profiles of 529 sequence-specific TFs and 151 cofactors and chromatin regulators in the cancer cell line HepG2, for a total of 680 broadly-termed DNA-Associated Proteins (DAPs). We use this deep collection to model each TF's impact on gene expression, including identifying a cohort of 26 candidate transcriptional repressors. We examine High Occupancy Target (HOT) sites in the context of three-dimensional genome organization and show biased motif placement in enhancer-promoter connections involving HOT sites. We also find a substantial number of closed chromatin regions with multiple DAPs bound and explore their properties, finding that a MAFF/MAFK TF pair correlates with transcriptional repression. Altogether, these analyses provide novel insights into the regulatory logic of the human cell line HepG2 genome and demonstrate the usefulness of large genomic analyses for elucidation of individual TF functions.
Project description:MafF-/-: MafG+/+: MafK-/- mice are viable, while MafF-/-: MafG-/-: MafK-/- mice are embryonic lethal. To get an insight into the cause of the lethality of small Maf triple knockout mice, transcriptome analysis was performed using whole embyos of MafF-/-: MafG-/-: MafK-/- at E10.5 and those of MafF-/-: MafG+/+: MafK-/- at E9.5 or E10.5. Because MafF-/-: MafG-/-: MafK-/- embryos exhibit growth retardation, the gene expression profile of MafF-/-: MafG-/-: MafK-/- embryos at E10.5 was compared with that of MafF-/-: MafG+/+: MafK-/- embyos at E9.5. The gene expression profile of MafF-/-: MafG+/+: MafK-/- embryos at E10.5 was also examined as an alternative control. Total RNA was prepared from pooled three embryos for each sample.
Project description:MafF-/-: MafG+/+: MafK-/- mice are viable, while MafF-/-: MafG-/-: MafK-/- mice are embryonic lethal. To get an insight into the cause of the lethality of small Maf triple knockout mice, transcriptome analysis was performed using whole embyos of MafF-/-: MafG-/-: MafK-/- at E10.5 and those of MafF-/-: MafG+/+: MafK-/- at E9.5 or E10.5. Because MafF-/-: MafG-/-: MafK-/- embryos exhibit growth retardation, the gene expression profile of MafF-/-: MafG-/-: MafK-/- embryos at E10.5 was compared with that of MafF-/-: MafG+/+: MafK-/- embyos at E9.5. The gene expression profile of MafF-/-: MafG+/+: MafK-/- embryos at E10.5 was also examined as an alternative control.
Project description:To elucidate the functional roles of sMafs in the adult liver, we conditionally targeted the sMaf genes using a transgenic complementation rescue approach. MafF-/-::MafG-/-::MafK-/- (F0G0K0) mice are embryonic lethal but can be rescued by complementation of transgenic MafG expression under the regulation of the MafG regulatory domain (MGRD). Therefore, we rescued F0G0K0 mice using a MGRD transgenic mouse line with a MafG gene flanked with loxP (fMafG) sequences so that the MafG gene could be deleted by Cre-mediated recombination. The Albumin(Alb)-Cre transgenic mice were used to delete fMafG gene specifically in the liver. The genotype used are MafF-/-::MafG-/-::MafK-/-::MGRD-fMafG::Alb-Cre (liver-specific sMaf CKO) and MafF-/-::MafG+/-::MafK-/-::MGRD-fMafG::Alb-Cre (control).
Project description:Understanding how the expression of transcription factor (TF) genes is modulated is essential for reconstructing gene regulatory networks. There is increasing evidence that sequences other than upstream noncoding can contribute to modulating gene expression, but how frequently they do so remains unclear. Here, we investigated the regulation of TFs expressed in a tissue-enriched manner in Arabidopsis roots. For 61 TFs, we created GFP reporter constructs driven by each TF's upstream noncoding sequence (including the 5'UTR) fused to the GFP reporter gene alone or together with the TF's coding sequence. We compared the visually detectable GFP patterns with endogenous mRNA expression patterns, as defined by a genome-wide microarray root expression map. Experiment Overall Design: To obtain a comprehensive non-overlapping root expression map which would be compared with promoter GFP fusion lines by imaging, we identified three cell type specific GFP marker lines and profiled transcripts in selected cell types using a cell sorting-microarray technique.
Project description:Understanding how the expression of transcription factor (TF) genes is modulated is essential for reconstructing gene regulatory networks. There is increasing evidence that sequences other than upstream noncoding can contribute to modulating gene expression, but how frequently they do so remains unclear. Here, we investigated the regulation of TFs expressed in a tissue-enriched manner in Arabidopsis roots. For 61 TFs, we created GFP reporter constructs driven by each TF's upstream noncoding sequence (including the 5'UTR) fused to the GFP reporter gene alone or together with the TF's coding sequence. We compared the visually detectable GFP patterns with endogenous mRNA expression patterns, as defined by a genome-wide microarray root expression map.
Project description:Purpose: 253 GSM Samples from GSE32970 and GSE29692 was reanalyzed to find the highly occupied target (HOT) regions of 154 cell lines. Methods: 1. We assigned the binding sites of 542 TFs in 154 cell lines as GSE53962 (Our last submission). 2.We performed a Gaussian kernel density estimation across the genome with a bandwidth of 300 bp, using the centers of each of the TF binding peaks as points. Then, we scanned this density for peaks, and denoted each peak a TF region(Candidate region to find HOT regions).To determine the complexity of the TF region, we summed the Gaussian kernalized distance from the peak to each TF that contributed at least 0.1 to its strength. The TF region around eat peak was derived by finding the maximum distance (in bp) from the peak to a contributing TF, and then adding 150 bp (one half of the bandwidth). Each TF region is centered on the peak, and have a TF complexity value. 3.To define HOT region according to the TF complexity, we required a complexity cutoff for each cell line.To geometrically define the cutoff we first scaled the TF complexity such that the x and y axis were from 0-1. We then found the x axis point for which a line with a slope of 1 was tangent to the curve. We define this point as the cutoff value,TF region whose complexity above this point to be HOT region, and TF region complexity below that point to be lowly occupied target (LOT) regions. Result: Using the binding sites of 542 TFs in 145 cell lines, we assigned a TF complexity score to each TF region corresponding to the number of distinct TFs bound, resulting in HOT regions of 145 cell lines.
Project description:A library of 35,500 reporters was designed for 86 TFs in order to identify optimized TF reporters. The library was transfected into diverse cell types and probed upon almost 100 TF perturbations. To compare TF activities with TF abundances, RNA-seq data was used. For mNPCs, mESCs and HepG2 cells, RNA-seq data was generated in house. For thee TF knockdowns in HepG2 cells, RNA-seq data was generated to validate the experimental design.
Project description:The regulation of gene expression is a result of a complex interplay between chromatin remodeling, transcription factors (TFs) and signaling molecules. Cell differentiation is accompanied by chromatin remodeling of specific loci to permanently silence genes that are not essential for the differentiated cell activity. The molecular cues that recruit the chromatin remodeling machinery are not well characterized. IRF8 is an immune-cell specific TF, and thus, serves as a model gene to elucidate the molecular mechanisms governing its silencing in non-immune cells. A high-throughput shRNA library screen in IRF8 expression-restrictive cells enabled the identification of MafK as modulator of IRF8 silencing, affecting chromatin architecture. ChIP-seq analysis revealed three MafK binding-regions (-25kb, -20kb and IRF8 6th intron) in the IRF8 locus. These MafK binding-sites are sufficient to repress a reporter-gene when cloned in genome-integrated lentiviral reporter constructs in expression-restrictive cells only, while plasmid-based constructs do not demonstrate such repressive effect. Furthermore, removal of MafK-int6 binding-region from BAC-IRF8 reporter construct was sufficient to promote accessible chromatin conformation. Taken together, we identified and characterized several MafK binding elements within the IRF8 locus that mediate repressive chromatin conformation resulting in the silencing of IRF8 expression only in non-immune cells.