A computational genomics approach to identify cis-regulatory modules - a case study using E2F1
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE5175 | GEO | 2006/08/14
SECONDARY ACCESSION(S): PRJNA96589
REPOSITORIES: GEO
Similar Datasets
Project description:We first trained a set of experimentally identified E2F1 targets by a ChIPModules approach, the identified module of E2F1 and AP-2alpha was validated by ChIP-chip assays. We have performed 3 sets of ChIP-chip experiments in MCF-7 for E2F1 and AP-2alpha respectively. The common genes bound by both E2F1 and AP-2alpha were then identified as a co-localized set of genes. We also performed ChIP-PCR conformation for randomly selected 10 targets.
2010-07-01 | E-GEOD-5175 | biostudies-arrayexpress
Project description:Advances in high-throughput technologies, such as ChIP-chip, and the completion of human and mouse genomic sequences now allow analysis of the mechanisms of gene regulation on a systems level. In this study, we have developed a computational genomics approach (termed ChIPModules), which begins with experimentally determined binding sites and integrates positional weight matrices constructed from transcription factor binding sites, a comparative genomics approach, and statistical learning methods to identify transcriptional regulatory modules. We began with E2F1 binding site information obtained from ChIP-chip analyses of ENCODE regions, from both HeLa and MCF7 cells. Our approach not only distinguished targets from nontargets with a high specificity, but it also identified five regulatory modules for E2F1. One of the identified modules predicted a colocalization of E2F1 and AP-2alpha on a set of target promoters with an intersite distance of <270 bp. We tested this prediction using ChIP-chip assays with arrays containing approximately 14,000 human promoters. We found that both E2F1 and AP-2alpha bind within the predicted distance to a large number of human promoters, demonstrating the strength of our sequence-based, unbiased, and universal protocol. Finally, we have used our ChIPModules approach to develop a database that includes thousands of computationally identified and/or experimentally verified E2F1 target promoters.
| S-EPMC1665642 | biostudies-literature
Project description:E2F transcription factors are known regulators of the cell cycle, proliferation, apoptosis and differentiation. We reveal an essential role for E2F1 in liver through the regulation of glycolysis and lipogenesis. E2F1 deficiency leads to a decreased in glycolysis and de novo synthesis of fatty acids in hepatocytes. ChIP-Seq was performed to determine direct tagets of E2F1 in hepatocytes. We highlight that E2F1 directly binds the promoters of genes implicated in metabolic process and notably key lipogenic genes to control these pathways.
2015-12-01 | GSE74006 | GEO
Project description:2 biological replicates (array 59066 and array 64695) of HeLa E2F1 ChIP vs matched Total DNA Keywords: ChIP
2006-03-03 | GSE4319 | GEO
Project description:E2F1 binding sites in MCF7 cells were determined in the ENCODE regions Keywords: ChIP-chip
2006-03-09 | GSE4355 | GEO
Project description:Previous studies of E2F family members have suggested that protein-protein interactions may be the mechanism by which E2Fs are recruited to specific genomic regions. We have addressed this hypothesis on a genome-wide scale using ChIP-seq analysis of MCF7 cell lines that express tagged wildtype and mutant E2F1 proteins. First, we performed ChIP-seq for tagged wt E2F1. Then, we analyzed E2F1 proteins that lacked the N terminal SP1 and cyclin A binding domains, the C terminal transactivation and pocket protein binding domains, and the internal marked box domain. Surprisingly, we found that the ChIP-seq patterns of the mutant proteins were identical to that of wt E2F1. However, mutation of the DNA binding domain abrogated all E2F1 binding to the genome. These results suggested that the interaction between the E2F1 DNA binding domain and a consensus motif may be the primary determinant of E2F1 recruitment. To address this possibility, we analyzed the in vivo binding sites for the in vitro-derived consensus E2F1 motif (TTTSSCGC) and also performed de novo motif analysis. We found that only 12% of the ChIP-seq peaks contained the TTTSSCGC motif. De novo motif analysis indicated that most of the in vivo sites lacked the 5â half of the in vitro derived consensus, having instead the in vivo consensus of CGCGC. In summary, our findings do not provide support for the model that protein-protein interactions are involved in recruiting E2F1 to the genome, but rather suggest that recognition of a motif found at most human promoters is the critical determinant. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf
2011-04-04 | GSE28286 | GEO
Project description:Previous studies of E2F family members have suggested that protein-protein interactions may be the mechanism by which E2Fs are recruited to specific genomic regions. We have addressed this hypothesis on a genome-wide scale using ChIP-seq analysis of MCF7 cell lines that express tagged wildtype and mutant E2F1 proteins. First, we performed ChIP-seq for tagged wt E2F1. Then, we analyzed E2F1 proteins that lacked the N terminal SP1 and cyclin A binding domains, the C terminal transactivation and pocket protein binding domains, and the internal marked box domain. Surprisingly, we found that the ChIP-seq patterns of the mutant proteins were identical to that of wt E2F1. However, mutation of the DNA binding domain abrogated all E2F1 binding to the genome. These results suggested that the interaction between the E2F1 DNA binding domain and a consensus motif may be the primary determinant of E2F1 recruitment. To address this possibility, we analyzed the in vivo binding sites for the in vitro-derived consensus E2F1 motif (TTTSSCGC) and also performed de novo motif analysis. We found that only 12% of the ChIP-seq peaks contained the TTTSSCGC motif. De novo motif analysis indicated that most of the in vivo sites lacked the 5M-CM-"M-BM-^@M-BM-^Y half of the in vitro derived consensus, having instead the in vivo consensus of CGCGC. In summary, our findings do not provide support for the model that protein-protein interactions are involved in recruiting E2F1 to the genome, but rather suggest that recognition of a motif found at most human promoters is the critical determinant. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf 9 total ChIP-seq datasets; four different HA-ER-E2F1 mutants, and one HA ER E2F1 wild type dataset done in duplicate, from 5 different stable cell lines derived from MCF7 cells; Three Input replicates from 2 different stable cell lines derived from MCF7 cells; HA ER E2F1 wild type duplicate dataset from MCF7 stable cells; 1 HA ER E2F1 DBDmut replicate from MCF7 stable cells cells, 1 HA ER E2F1M-CM-^NM-BM-^TC replicate from MCF7 stable cells cells, 1 HA ER E2F1M-CM-^NM-BM-^TN/C replicate from MCF7 stable cells cells, 1 HA ER E2F1M-CM-^NM-BM-^TMB replicate from MCF7 stable cells cells, 1 HA ER E2F1M-CM-^NM-BM-^TMB replicate from MCF7 stable cells cells, 3 Input replicates from MCF7 stable cells cells.
2011-04-04 | E-GEOD-28286 | biostudies-arrayexpress
Project description:Lung cancer is one of the most common and fatal cancer worldwide. There are two major types of lung cancer, non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Recently, gefitinib, a small molecule, which target tyrosine kinase, has been regarded as the first-line treatment in NSCLC patients. However, several patients have been observed tumor recurrence and eventually developed progressive outcomes after target therapy. Thus, an effective therapeutic approach need to be explored. Here, we found that ectopically expressed ATP synthase on plasma membrane exhibited gefitinib-resistance properties in lung cancer cell lines. Furthermore, we unraveled that citreoviridin, an ectopic ATP synthase inhibitor, suppressed the abilities of both proliferation and colony formation in lung cancer cell lines. To elucidate the comprehensive mechanism regulated by citreoviridin, we performed microarray analysis. The results indicated that not only mRNAs but also long non-coding RNAs (lncRNAs) are involved in citreoviridin-treated cell death. One of the well-known lncRNAs, growth arrest-specific transcript (GAS5), was robustly upregulated after citreoviridin treatment. In order to investigate the upstream modulator of GAS5, we utilized chromatin immunoprecipitation (ChIP) assay and revealed that E2F transcription factor 1 (E2F1) could bind to the promoter of GAS5. Consistently, both microarray and qPCR data showed the expression level of E2F1 was negatively correlated to GAS5 after citreoviridin treatment. The evidence suggests that E2F1 might be a potential repressor of GAS5. Furthermore, combining microarray and Gene Set Enrichment Analysis (GSEA) analysis as well as qPCR demonstrated that p53 pathway was activated. To further realize the GAS5-p53 regulating network, RNA-protein pull-down assay followed by LC-MS/MS will be utilized to dissect the GAS5-interacting proteomic profiling.From the results, we identified 107 GAS5-interacting proteins in common from A549 and H1975 cell lines. Our proteomics experiments identified topoisomerase 2-alpha (TOP2A) as the key protein involved in the citreoviridin-regulated gefitinib-resistance pathway, therefore, we picked out TOP2A for further study. Additionally, we further validated the interaction between TOP2A and GAS5 by western blot and RNA immunoprecipitation (RIP). Taken together, this study suggests targeting E2F1/GAS5/p53 axis is a potential therapeutic strategy for gefitinib-resistant lung cancer.
2020-08-17 | PXD013139 | Pride
Project description:BackgroundMany studies report about detection and functional characterization of cis-regulatory motifs in untranslated regions (UTRs) of mRNAs but little is known about the nature and functional role of their distribution. To address this issue we have developed a computational approach based on the use of data mining techniques. The idea is that of mining frequent combinations of translation regulatory motifs, since their significant co-occurrences could reveal functional relationships important for the post-transcriptional control of gene expression. The experimentation has been focused on targeted mitochondrial transcripts to elucidate the role of translational control in mitochondrial biogenesis and function.ResultsThe analysis is based on a two-stepped procedure using a sequential pattern mining algorithm. The first step searches for frequent patterns (FPs) of motifs without taking into account their spatial displacement. In the second step, frequent sequential patterns (FSPs) of spaced motifs are generated by taking into account the conservation of spacers between each ordered pair of co-occurring motifs. The algorithm makes no assumption on the relation among motifs and on the number of motifs involved in a pattern. Different FSPs can be found depending on different combinations of two parameters, i.e. the threshold of the minimum percentage of sequences supporting the pattern, and the granularity of spacer discretization. Results can be retrieved at the UTRminer web site: http://utrminer.ba.itb.cnr.it/. The discovered FPs of motifs amount to 216 in the overall dataset and to 140 in the human subset. For each FP, the system provides information on the discovered FSPs, if any. A variety of search options help users in browsing the web resource. The list of sequence IDs supporting each pattern can be used for the retrieval of information from the UTRminer database.ConclusionComputational prediction of structural properties of regulatory sequences is not trivial. The presented data mining approach is able to overcome some limits observed in other competitive tools. Preliminary results on UTR sequences from nuclear transcripts targeting mitochondria are promising and lead us to be confident on the effectiveness of the approach for future developments.
| S-EPMC2697649 | biostudies-literature
Project description:These are three biological replicates. HeLa cells were crosslinked on separate days. In each case, a matched total from the same crosslinking was produced in parallel. Amplicons were made from each and hybridized onto ENCODE region tiling arrays. Two color arrays were used; ChIP was red, Total was green. Goal was determination of E2F1 binding sites in HeLa cells by using ChIP-chip methodology. See Farnham Lab website for downloadable protocol for ChIP or supplementary file (Chip_protocol.txt) below. NimbleGen performed all array processing. See NimbleGen website for information on array procedures.
2010-07-01 | E-GEOD-4306 | biostudies-arrayexpress