The tumor suppressor p53 is a transcription factor that coordinates the cellular response to DNA damage. Here we provide an integrated analysis of p53 genomic occupancy and p53-dependent gene regulation in the splenic B and non-B cell compartments of mice exposed to whole-body ionizing radiation, providing insight into general principles of p53 activity in vivo. In unstressed conditions, p53 bound few genomic targets; induction of p53 by ionizing radiation increased the number of p53 bound sites, leading to highly overlapping profiles in the different cell types. Comparison of these profiles with chromatin features in unstressed B cells revealed that, upon activation, p53 localized at active promoters, distal enhancers, and a smaller set of unmarked distal regions. At promoters, recognition of the canonical p53 motif as well as binding strength were associated with p53-dependent transcriptional activation, but not repression, indicating that the latter was most likely indirect. p53-activated targets constituted the core of a cell type-independent response, superimposed onto a cell type-specific program. Core response genes included most of the known p53-regulated genes, as well as many new ones. Our data represent a unique characterization of the p53-regulated response to ionizing radiation in vivo. Overall design: Total RNA profiling of gene expression in the splenic B and non-B cell compartments of wild-type and Trp53-/-mice exposed to whole-body ionizing radiation by Illumina sequencing
p53 transcriptional programs in B cells upon exposure to genotoxic stress in vivo: Computational analysis of next-generation sequencing data.
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View SamplesMutant p53 proteins, resulting from the missense mutations of the TP53 tumor suppressor gene, possess gain-of-function activities and are among the most robust oncoproteins in human tumors. They are potentially important therapeutic targets. No studies to date have distinguished common, therapeutically relevant mutant p53 gain-of-function effects from effects specific to different mutant variants and cell backgrounds. here we performed RNA-seq analysisin MDA-MB-231 (R280K) upon silencing TP53 or the control siRNA. Overall design: MDA-MB-231 (R280K) cell line was transfected with control or p53 siRNA.So The study comprises one experimental cell line,in triplicate.
Proteasome machinery is instrumental in a common gain-of-function program of the p53 missense mutants in cancer.
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View SamplesThe tumor suppressor p53 is a transcription factor that controls the response to stress. Here, we dissected the transcriptional programs triggered upon restoration of p53 in Myc-driven lymphomas, based on the integrated analysis of p53 genomic occupancy and gene regulation. p53 binding sites were identified at promoters and enhancers, both characterized by the pre-existence of active chromatin marks. p53 recruitment at these sites was mainly mediated through protein-protein or protein-chromatin interactions and, only for a small fraction, through recognition of the 20 base-pair p53 consensus motif. At promoters, p53 binding to the consensus motif was associated with gene induction, but not repression, indicating that the latter was most likely indirect. p53 also targeted unmarked distal sites devoid of activation marks, at which binding was prevalently driven by recognition of the consensus motif. At all sites, our data highlighted a functional role for the canonical, unsplit consensus element, but did not provide evidence for p53 recruitment by split motifs. Altogether, our data highlight key features of genome recognition by p53 and provide unprecedented insight into the pathways associated with p53 re-activation and tumor regression. Overall design: Total RNA profiling of gene expression in Eµ-myc lymphomas following p53 restoration by Illumina sequencing
Genome-wide analysis of p53-regulated transcription in Myc-driven lymphomas.
Specimen part, Cell line, Subject
View SamplesThe M1 and the M2 macrophage polarization programs (activated by IFN? and IL-4, respectively) lie at the opposite edges of a continuum of activation states but are frequently co-activated during co-infections and in cancer despite controlling divergent functional responses. Whether these two programs are mutually exclusive, how they influence each other, and whether one represents the prevailing response, are all open questions. Co-administration of IFN? and IL-4 exerted complex inhibitory effects over the M1 and M2 programs at the level of both epigenomic and transcriptional changes. Computational data mining and validation analyses revealed the molecular basis of the differential sensitivity of genes and cis-regulatory elements to the antagonistic effects of the opposite stimulus. For instance, while STAT1 and IRF motifs were associated with robust and IL-4-resistant responses to IFN?, their coexistence with binding sites for some auxiliary transcription factors such as AP-1, generated vulnerability to IL-4-mediated inhibition. These data provide a core mechanistic framework for the integration of signals that control macrophage activation and the starting point for understanding macrophage responses in complex environmental conditions Overall design: Analysis of transcriptional and epigenomic changes in mouse macrophages stimulated with different cytokines or their combinations
Opposing macrophage polarization programs show extensive epigenomic and transcriptional cross-talk.
Specimen part, Cell line, Treatment, Subject
View SamplesOver-expression of the Myc transcription factor causes its widespread interaction with regulatory domains in the genome, but leads to the up- and down-regulation of discrete sets of genes. The molecular determinants of these selective transcriptional responses remain elusive. Here, we present an integrated time-course analysis of transcription and mRNA dynamics following Myc activation in proliferating mouse fibroblasts, based on chromatin immunoprecipitation, metabolic labeling of newly synthesized RNA, extensive sequencing and mathematical modeling. Transcriptional activation correlated with the highest increases in Myc binding at promoters. Repression followed a reciprocal scenario, with the lowest gains in Myc binding. Altogether, the relative abundance (henceforth, “share”) of Myc at promoters was the strongest predictor of transcriptional responses in diverse cell types, predominating over Myc's association with the co-repressor Miz1. Myc activation elicited immediate loading of RNAPII at activated promoters, followed by increases in pause-release5, while repressed promoters showed opposite effects. Gains and losses in RNAPII loading were proportional to the changes in the Myc share, suggesting that repression by Myc may be largely indirect, owing - at least in part - to competition for limiting amounts of RNAPII. Secondary to the changes in RNAPII loading, the dynamics of elongation and pre-mRNA processing were also rapidly altered at Myc regulated genes, leading to the transient accumulation of partially or aberrantly processed mRNAs. Altogether, our results shed light on how over-expressed Myc alters the various phases of the RNAPII cycle and the resulting transcriptional response. Overall design: Time course profiling of 4sU-labeled and total RNA upon Myc activation in 3T9-MycER mouse fibroblasts
Integrative analysis of RNA polymerase II and transcriptional dynamics upon MYC activation.
Specimen part, Subject
View SamplesIntroduction: The kidney is the major arbiter of extracellular phosphate homeostasis. The vast majority of glomerular filtrated phosphate is reabsorbed in the proximal tubule. Posttransplant phosphaturia is common and aggravated by sirolimus immunosuppression. The cause of sirolimus induced phosphaturia however remains elusive.
Sirolimus induced phosphaturia is not caused by inhibition of renal apical sodium phosphate cotransporters.
Sex, Specimen part
View SamplesThis SuperSeries is composed of the SubSeries listed below.
MYC regulates the core pre-mRNA splicing machinery as an essential step in lymphomagenesis.
Specimen part, Treatment
View SamplesOver-expressed MYC binds to virtually all active promoters within a cell, although with different binding affinities, and modulates gene expression, both positively and negatively. Here, we show that during lymphomagenesis in E-myc transgenic mice, MYC directly up-regulates the transcription of the core snRNP assembly genes, including PRMT5, an arginine methyltransferase, that methylates Sm proteins as an early step in lymphomagenesis. This coordinated regulatory effect is direct and is critical for snRNP biogenesis, the maintenance of effective mRNA splicing and cellular viability in cycling cells, in either fibroblasts or B-cells.
MYC regulates the core pre-mRNA splicing machinery as an essential step in lymphomagenesis.
Specimen part
View SamplesRNAseq analysis of YAP and Myc induced in quiescent and confluent 3T9 fibroblasts Overall design: RNAseq analysis of YAP and Myc induced in quiescent and confluent 3T9 fibroblasts
Transcriptional integration of mitogenic and mechanical signals by Myc and YAP.
Specimen part, Cell line, Subject
View SamplesTumors driven by activation of the transcription factor Myc generally show oncogene addiction. However, the gene-expression programs that depend upon sustained Myc activity in those tumors remain unknown. We have addressed this issue in a model of liver carcinoma driven by a reversible tet-Myc transgene, combining gene expression profiling with the mapping of Myc and RNA Polymerase II on chromatin. Switching off the oncogene in advanced carcinomas revealed that Myc is required for the continuous activation and repression of distinct sets of genes, constituting no more than half of those deregulated during tumor progression, and an even smaller subset of all Myc-bound genes. We further showed that a Myc mutant unable to associate with the co-repressor protein Miz1 is defective in the initiation of liver tumorigenesis. Altogether, our data provide the first detailed analysis of a Myc-dependent transcriptional program in a fully developed carcinoma, revealing that the critical effectors of Myc in tumor maintenance must be included within defined subsets (ca. 1,300 each) of activated and repressed genes. Overall design: RNAseq samples of control liver (n=11), tet-Myc tumors (n=16), tet-Myc tumors with short-term Myc inactivation (n=8), tet-MycVD tumors (n=11)
Identification of MYC-Dependent Transcriptional Programs in Oncogene-Addicted Liver Tumors.
Specimen part, Cell line, Subject
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