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Modeling genome-wide transcriptional cis-regulation in n LNCaP-abl cell line after siRNA knock down of a series of gene factors [RNA-seq]

ABSTRACT: We describe, MARGE, Model-based Analysis of the Regulation of Gene Expression, a robust methodology that leverages a large library of genome-wide H3K27ac ChIP-seq profiles to predict key regulated genes and cis-regulatory regions in human or mouse. MARGE adopts a gene centric approach to define a regulatory potential that summarizes the aggregate activity of multiple cis-regulatory elements on each gene. This model is effective in describing cis-regulatory activity and, unlike the super-enhancer based approach, is highly predictive of gene expression changes in response to BET-bromodomain inhibitors. We show that linear combinations of H3K27ac defined regulatory potentials, selected from an extensive database of published H3K27ac profiles, can accurately model diverse gene sets derived from differential gene expression experiments. In addition, we demonstrate a novel semi-supervised learning approach for identifying transcription factor binding sites associated with the set of transcription factors that regulate the gene set. MARGE leverages published H3K27ac ChIP-seq data to enhance the interpretation of newly generated H3K27ac ChIP-seq profiles. MARGE can also be used to analyze gene expression studies, without the production of matched H3K27ac ChIP-seq data.

ORGANISM(S): Homo sapiens

PROVIDER: GSE72534 | GEO | 2016/05/16

SECONDARY ACCESSION(S): PRJNA294290

REPOSITORIES: GEO

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Modeling transcriptional cis-regulation with a library of genome-wide histone H3K27ac profiles

Project description:We describe, MARGE, Model-based Analysis of the Regulation of Gene Expression, a robust methodology that leverages a large library of genome-wide H3K27ac ChIP-seq profiles to predict key regulated genes and cis-regulatory regions in human or mouse. MARGE adopts a gene centric approach to define a regulatory potential that summarizes the aggregate activity of multiple cis-regulatory elements on each gene. This model is effective in describing cis-regulatory activity and, unlike the super-enhancer based approach, is highly predictive of gene expression changes in response to BET-bromodomain inhibitors. We show that linear combinations of H3K27ac defined regulatory potentials, selected from an extensive database of published H3K27ac profiles, can accurately model diverse gene sets derived from differential gene expression experiments. In addition, we demonstrate a novel semi-supervised learning approach for identifying transcription factor binding sites associated with the set of transcription factors that regulate the gene set. MARGE leverages published H3K27ac ChIP-seq data to enhance the interpretation of newly generated H3K27ac ChIP-seq profiles. MARGE can also be used to analyze gene expression studies, without the production of matched H3K27ac ChIP-seq data. Identifying genomic profiles of histone modification H3K27ac in LNCaP-abl cell line after siRNA knock down of a series of gene factors.

2016-05-16 | E-GEOD-72467 | biostudies-arrayexpress

Modeling genome-wide transcriptional cis-regulation in n LNCaP-abl cell line after siRNA knock down of a series of gene factors [RNA-seq]

Project description:We describe, MARGE, Model-based Analysis of the Regulation of Gene Expression, a robust methodology that leverages a large library of genome-wide H3K27ac ChIP-seq profiles to predict key regulated genes and cis-regulatory regions in human or mouse. MARGE adopts a gene centric approach to define a regulatory potential that summarizes the aggregate activity of multiple cis-regulatory elements on each gene. This model is effective in describing cis-regulatory activity and, unlike the super-enhancer based approach, is highly predictive of gene expression changes in response to BET-bromodomain inhibitors. We show that linear combinations of H3K27ac defined regulatory potentials, selected from an extensive database of published H3K27ac profiles, can accurately model diverse gene sets derived from differential gene expression experiments. In addition, we demonstrate a novel semi-supervised learning approach for identifying transcription factor binding sites associated with the set of transcription factors that regulate the gene set. MARGE leverages published H3K27ac ChIP-seq data to enhance the interpretation of newly generated H3K27ac ChIP-seq profiles. MARGE can also be used to analyze gene expression studies, without the production of matched H3K27ac ChIP-seq data. Transcriptome profiling in LNCaP-abl cell line after siRNA knock down of a series of gene factors.

2016-05-16 | E-GEOD-72534 | biostudies-arrayexpress

Modeling transcriptional cis-regulation with a library of genome-wide histone H3K27ac profiles

2016-05-16 | GSE72467 | GEO

Regulation of Histone Acetylation by SUMOylation Through TFAP2C Binding to the Chromatin and Recruitment of HDAC Complex

Project description:Enhancers are fundamental to gene regulation. Post-translational modifications by the small ubiquitin-like modifiers (SUMO) modify chromatin regulation enzymes, including histone acetylases and deacetylases. However, it remains unclear whether SUMOylation regulates enhancer marks, acetylation at the 27th lysine residue of the histone H3 protein (H3K27Ac). We hypothesize that SUMOylation regulates H3K27Ac. To test this hypothesis, we performed genome-wide ChIP-seq analyses. We discovered that knockdown (KD) of the SUMO activating enzyme catalytic subunit UBA2 reduced H3K27Ac at most enhancers. Bioinformatic analysis revealed that TFAP2C-binding sites are enriched in enhancers whose H3K27Ac was reduced by UBA2 KD. ChIP-seq analysis in combination with molecular biological methods showed that TFAP2C binding to enhancers increased upon UBA2 KD or inhibition of SUMOylation by a small molecule SUMOylation inhibitor. However, this is not due to the SUMOylation of TFAP2C itself. Proteomics analysis of TFAP2C interactome on the chromatin identified histone deacetylation (HDAC) machinery. TFAP2C KD reduced HDAC binding to chromatin and increased H3K27Ac marks at enhancer regions, suggesting that TFAP2C is involved in recruiting HDAC. Taken together, our findings provide important insights into regulation of enhancer marks by SUMOylation.

2024-04-13 | PXD045644 | Pride

Mus musculus

Project description:Identification of a novel Aire-regulating cis-regulatory element using H3K27ac ChIP-seq

| PRJNA299575 | ENA

Genomic Analysis Reveals Distinct Mechanisms and Functional Classes of SOX10-Regulated Genes in Melanocytes [ChIP-Seq]

Project description:We performed ChIP-Seq analysis of SOX10, histone H3 lysine 27 acetylation (H3K27ac) and H3K27 trimethylation (H3K27me3) in melanocytes to profile the genomic binding sites of SOX10 and the chromatin landscape. In parallel, we generated Sox10 haploinsufficient cell lines using gene knockout approaches and conducted microarray gene expression analysis to identify functional gene targets of SOX10 transcriptional regulation in melanocytes. We demonstrate that SOX10 predominantly engages “open” chromatin, binds to melanocyte enhancer elements and plays a central role in transcriptional activation and repression of functionally distinct classes of genes. Furthermore, we identified cis-regulatory sequence motifs of putative co-regulatory transcription factors that define SOX10-activated and SOX10-repressed target genes. Our results uncover novel mechanisms and roles of SOX10 in global transcriptional regulation of diverse regulatory pathways in the melanocyte lineage. ChIP-seq profiling of SOX10, H3K27ac, and H3K27me3 in the mouse melanocyte cell line melan-Ink4a-Arf-1 (melan-a).

2015-07-03 | E-GEOD-69949 | biostudies-arrayexpress

Identification of active transcriptional regulatory elements with GRO-seq

Project description:Transcriptional regulatory elements (TREs), including enhancers and promoters, determine the transcription levels of associated genes. We have recently shown that global run-on and sequencing (GRO-seq) with enrichment for 5'-capped RNAs reveals active TREs with high accuracy. Here, we demonstrate that active TREs can be identified by applying sensitive machine-learning methods to standard GRO-seq data. This approach allows TREs to be assayed together with gene expression levels and other transcriptional features in a single experiment. Our prediction method, called discriminative Regulatory Element detection from GRO-seq (dREG), summarizes GRO-seq read counts at multiple scales and uses support vector regression to identify active TREs. The predicted TREs are more strongly enriched for several marks of transcriptional activation, including eQTL, GWAS-associated SNPs, H3K27ac, and transcription factor binding than those identified by alternative functional assays. Using dREG, we survey TREs in eight human cell types and provide new insights into global patterns of TRE function. We analyzed GRO-seq or PRO-seq data from eight human cell lines. Please note that this study comprises new sample data plus reanalysis of old Sample data submitted by another user. Existing PRO-seq or GRO-seq data was combined as detailed in the GSE66031_readme.txt. See GSM1613181 and GSM1613182 Sample records for data processing information.

2015-02-19 | E-GEOD-66031 | biostudies-arrayexpress

RNA-seq in male and female mouse liver for two mouse strains: C57BL/6J and CAST/EiJ.

Project description:Sequencing files provided here are mouse liver RNA-seq in two mouse strains: C57BL/6J and CAST/EiJ. This is part of a larger study published in PLoS Genetics (2021) "Harnessing natural variation to identify cis regulators of sex-biased gene expression in a multi-strain mouse liver model" that includes DNase-seq and H3K27ac ChIP-seq in mouse liver from the same two strains. This allows us to identify strain-shared ("core") and strain-unique sex-biased genes and enhancers.

2021-10-27 | GSE130913 | GEO

Mouse liver DNase-seq identification of DNase hypersensitive sites (DHS) in male and female mouse liver for two mouse strains: C57BL/6J and CAST/EiJ.

Project description:Sequencing files provided here are mouse liver DNase-seq in two mouse strains: C57BL/6J and CAST/EiJ. This is part of a larger study published in PLoS Genetics (2021) "Harnessing natural variation to identify cis regulators of sex-biased gene expression in a multi-strain mouse liver model" that includes RNA-seq and H3K27ac ChIP-seq in mouse liver from the same two strains. This allows us to identify strain-shared ("core") and strain-unique sex-biased genes and enhancers.

2021-10-27 | GSE130912 | GEO

Hybrid mice reveal parent-of-origin and cis- and trans-regulatory effects in the retina

Project description:A fundamental challenge in genomics is to map DNA sequence variants onto changes in gene expression. Gene expression is regulated by cis-regulatory elements (CREs, i.e., enhancers, promoters, and silencers) and the trans factors (e.g., transcription factors) that act upon them. A powerful approach to dissecting cis and trans effects is to compare F1 hybrids with F0 homozygotes. Using this approach and taking advantage of the high frequency of polymorphisms in wild-derived inbred Cast/EiJ mice relative to the reference strain C57BL/6J, we conducted allele-specific mRNA-seq analysis in the adult mouse retina, a disease-relevant neural tissue. We found that cis effects account for the bulk of gene regulatory divergence in the retina. Many CREs contained functional (i.e., activating or silencing) cis-regulatory variants mapping onto altered expression of genes, including genes associated with retinal disease. By comparing our retinal data with previously published liver data, we found that most of the cis effects identified were tissue-specific. Lastly, by comparing reciprocal F1 hybrids, we identified evidence of imprinting in the retina for the first time. Our study provides a framework and resource for mapping cis-regulatory variants onto changes in gene expression, and underscores the importance of studying cis-regulatory variants in the context of retinal disease. Retinas from four classes of 8 week old male mice were collected: F0 C57BL/6J (B6), F0 Cast/EiJ (Cast), F1 B6xCast, and F1 CastxB6. Three replicates per class were generated. Each replicate consisted of a pool of 6-8 retinas. The mRNA-seq was conducted with paired-end 2x101 sequencing on the Illumina HiSeq 2000 platform. One lane of sequencing was run for all twelve samples. An additional lane of sequencing was run for the six F1 samples.

2014-09-01 | E-GEOD-60545 | biostudies-arrayexpress

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