Mammalia
Ontology highlight
ABSTRACT:
PROVIDER: PRJDB10441 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| DRR241399.fastq.gz | Fastqsanger.gz | |||
| DRR241400.fastq.gz | Fastqsanger.gz | |||
| DRR241401.fastq.gz | Fastqsanger.gz | |||
| DRR241402.fastq.gz | Fastqsanger.gz | |||
| DRR241403.fastq.gz | Fastqsanger.gz |
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Project description:Developmental transcription factors act in networks, but how these networks achieve cell- and tissue specificity is still poorly understood. We here explored pre-B-cell leukemia homeobox 1 (PBX1) in adult neurogenesis combining genomic, transcriptomic, and proteomic approaches. ChIP-Seq analysis uncovered PBX1 binding to a wide range of different genes. Integration of PBX1 ChIP-seq with ATAC-seq data predicted interaction partners, which were subsequently validated by mass-spectrometry. Spatial transcriptomics revealed distinct temporal expression dynamics of Pbx1 and interacting factors. Among these were class I bHLH proteins TCF3, TCF4 and TCF12. RNA-seq upon Pbx1, Tcf3 and Tcf4 knockdown identified proliferation and differentiation associated genes as shared targets. Neuronal differentiation was reduced upon depletion of either factor, suggesting functional cooperation between PBX1 and TCF3/4. Notably, while physiological PBX1-TCF interactions have not yet been described, chromosomal translocation resulting in genomic TCF3::PBX1 fusion characterizes a subtype of acute lymphoblastic leukemia. Introducing Pbx1 into Nalm6 cells, a pre B-cell line expressing TCF3 but lacking PBX1, upregulated leukemogenic genes including BLK and NOTCH3, arguing that functional PBX1-TCF cooperation likely extends to hematopoietic contexts. Our study hence uncovers a PBX1-TCF module orchestrating the balance between progenitor cell proliferation and differentiation in adult neurogenesis with implications for leukemia etiology.
2024-09-16 | PXD048222 | Pride
Project description:We studied the chromatin modification patterns induced by the presence of the MLL-AF9 fusion protein in a model of human hematopoietic stem/progenitor cells (HSPC) transduced with retrovirus expressing MLL-AF9cDNA (HSPC-MA9). Comparative ChIP-seq analysis between HSPC-MA9 and control HSPC, revealed a massive hyperacetylation of histones that was consistent with the transcriptional profile in the presence of MLL-AF9 fusion protein. Furthermore, we identified 66 MLL-AF9 targets, and found that H4ac was present along with H3K4me3 and H3K79me2 chromatin marks in over 50% of the MLL-AF9 target genes. Examination of histone aceylation and methylation changes upon expression of MLL-AF9 fusion protein in human hematopoietic stem/progenitor cells.
2015-03-01 | E-GEOD-54344 | biostudies-arrayexpress
Project description:The main goal of the project is to develop a new generation of bioinformatics resources for the integrative analysis of multiple types of 'omics data. These resources include both novel statistical methodologies as well as user-friendly software implementations. STATegra methods address many aspects of the 'omics data integration problem such as the design of multi-omics experiments, integrative transcriptional and regulatory networks, integrative variable selection, data fusion, integration of public domain data, and integrative pathway analysis. To support method development STATegra uses a model biological system, namely the differentiation process of mouse pre-B-cells. The STATegra consortium generated data focused on a critical step in the differentiation of B lymphocytes, which are key components of the adaptive immune system. Transcription factors of the Ikaros family are central to the normal differentiation of B cell progenitors and their expression increases in response to developmental stage-specific signals to terminate the proliferation of B cell progenitors and to initiate their differentiation. In particular, a novel biological system that models the transition from the pre-BI stage to the pre-BII subsequent stage, where B cell progenitors undergo growth arrest and differentiation, was used. The approach involves a pre-B cell line, B3, and an inducible version of the Ikaros transcription factor, Ikaros-ERt2. Ikaros factors act to down-regulate genes that drive proliferation and to simultaneously up-regulate the expression of genes that promote the differentiation of B cell progenitors. Hence, in the B3 system, before induction of Ikaros, cells proliferate and their gene expression pattern is similar to proliferating B cell progenitors in vivo. Following Ikaros induction, B3 cells undergo gene expression changes that resemble those that occur in vivo during the transition from cycling to resting pre-B cells, followed by a marked reduction in cellular proliferation and by G1 arrest. On this system the consortium has created a high-quality data collection consisting of a replicated time course using seven different 'omics platforms: RNA-seq, miRNA-seq, ChIP-seq, DNase-seq, Methyl-seq, proteomics and metabolomics, which is used to assess and to validate STATegra methods. The STATegra experimental design consists of a 6 point time course that captures the differentiation of B3 cells containing Ikaros-ERt2 upon Ikaros induction within a 24 hr period. The process was sampled at 0, 2, 6, 12, 18, and 24 hrs respectively after Ikaros induction by Tamoxifen. As control, B3 cells transfected with an empty vector were treated and sampled in the same way as the inducible line. Eight different 'omic technologies were measured on this system: RNA-seq, miRNA-seq, DNase-seq, RRBS-seq, ChIP-seq, scRNA-seq, Proteomics and Metabolomics. Generally, three biological replicates were obtained per platform and were processed as independent batches. Metabolomics analysis was performed using 4 biological batches (7, 8, 9 and 10) and at times 0, 2, 6, 12, 18 and 24 hrs respectively. Each sample was analyzed using gas chromatography mass spectrometry (GC-MS) and liquid chromatography mass spectrometry (LC-MS).
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Project description:Purpose: Our goal was to evaluate the transcriptional profiles of FLS. We used genome wide approaches to uncover the interactions between SOX4 and RELA/p65, downstream of TNF signaling. Methods: ChIP-seq of mouse FLS was used to compare the global DNA binding profiles of SOX4 and RELA. Results: ChIP-seq revealed an overllap of SOX4 peak summits with RELA peak summits suggesting that both proteins bind in close-proximity on regulatory sequences, enabling them to co-operatively regulate gene expression. By integrating the ChIP-seq results with RNA-seq from SoxC-knockout FLS we identified a set of TNF-responsive genes that are targets of the RELA-SOX4 transcriptional complex. Conclusion: SOX4 and RELA, together orchestrate a multimodal regulation of gene expression downstream of TNF signaling. Their interdependent activities play a pivotal role in the transformation FLS in arthritis and in the inflammatory pathology of diverse tissues where RELA and SOX4 are co-expressed.
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Project description:The expansion of repressive epigenetic marks has been implicated in heterochromatin formation during embryonic development, but the general applicability of this mechanism is unclear. Here we show that nuclear rearrangement of repressive histone marks H3K9me3 and H3K27me3 into non-overlapping structural layers characterizes senescence-associated heterochromatic foci (SAHF) formation in human fibroblasts. However, the global landscape of these repressive marks remains unchanged upon SAHF formation, suggesting that in somatic cells heterochromatin can be formed through the spatial repositioning of pre-existing repressively marked histones. This model is reinforced by the correlation of pre-senescent replication timing with both the subsequent layered structure of SAHFs and the global landscape of the repressive marks, allowing us to integrate microscopic and genomic information. Furthermore, modulation of SAHF structure does not affect the occupancy of these repressive marks nor vice versa. These experiments reveal that high-order heterochromatin formation and epigenetic remodeling of the genome can be discrete events. ChIP-seq for different histone marks in both growing and Ras-induced senescent fibroblasts, in the presence or absence of certain sh-RNAs K9me3Grow2.bed (growing) Chip Seq Analysis of H3K9me3 in ER:Ras expressing IMR90 human diploid fibroblasts d6 4OHT K9me3Sen2.bed (senescent) Chip Seq Analysis of H3K9me3 in ER:Ras expressing IMR90 human diploid fibroblasts with no treatment K9me2Grow3.bed (growing) Chip Seq Analysis of H3K9me2 in ER:Ras expressing IMR90 human diploid fibroblasts with no treatment K9me2Sen3.bed (senescent) Chip Seq Analysis of H3K9me2 in ER:Ras expressing IMR90 human diploid fibroblasts d6 4OHT K27me3Sen3.bed (senescent) Chip Seq Analysis of H3K27me3 in ER:Ras expressing IMR90 human diploid fibroblasts d6 4OHT K27me3Grow2.bed (growing) Chip Seq Analysis of H3K27me3 in ER:Ras expressing IMR90 human diploid fibroblasts with no treatment K36me3Grow2.bed (growing) Chip Seq Analysis of H3K36me3 in ER:Ras expressing IMR90 human diploid fibroblasts with no treatment K36me3Sen2.bed (senescent) Chip Seq Analysis of H3K36me3 in ER:Ras expressing IMR90 human diploid fibroblasts d6 4OHT K4me3Grow2.bed (growing) Chip Seq Analysis of H3K4me3 in ER:Ras expressing IMR90 human diploid fibroblasts with no treatment K4me3Sen3.bed (senescent) Chip Seq Analysis of H3K4me3 in ER:Ras expressing IMR90 human diploid fibroblasts d6 4OHT
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Project description:We performed a chip-seq to determine the binding of MLL1 in mouse leukemic blast cells transduces with MLL-AF9 fusion MLL1 chip-seq in mouse leukemic blast cells
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