62c55c67-4bcf-451b-aa09-f08b309e7e73 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001006048 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:RNA-seq was performed on cultured megakaryocytes and peripheral-blood derived granulocytes from individuals with QPD and a unaffected controls. Each group consisted of n=3 biological replicates.
| EGAD00001006053 | EGA
Project description:Hematopoiesis is a well-established model system to study molecular mechanisms of lineage-specific differentiation. Key transcription factors (TFs), such as PU.1, NF-E2 and GATA1 are implicated in crucial aspects of distinct hematopoietic lineages. How TFs collaborate with histone modificatons and how they affect the chromatin status remains to be elucidated. Chromatin-Immunoprecipitation followed by next-generation sequencing (ChIP-seq) has been proven to be an excellent tool to study chromatin modifications genome-wide. In this study, ChIP-seq was used to investigate the H3K4me2 landscape at enhancers during hematopoietic differentiation, starting from the hematopoietic stem cell (HSC) up to the fully differentiated erythrocyte, megakaryocyte or granulocyte. Although cell morphology and gene expression profiles differ extensively in committed erythrocytes, megakaryocytes and granulocytes, the genomic landscape of H3K4me2 is surprisingly alike across the three cell types. Granulocytes, in particular, seem to display an ‘erythocyte-like’ chromatin pattern. Similar results were observed for another chromatin mark, H3K27ac. Unexpectedly, the common progenitors of erythrocytes and granulocytes do not display a similar chromatin pattern, excluding the idea that the H3K4me2 mark is placed early on during differentiation. These results also suggest that the chromatin state is probably not the determining factor for lineage differentiation, but that rather lineage specific TF binding is important. In agreement with this, mature megakaryocytes loose the H3K4me2 mark surrounding erythrocyte-specific genes. This might be explained because megakaryocytes and erythrocytes both express the lineage specific TFs GATA1 and NF-E2. Altogether, we show that committed granulocytes and erythrocytes display similar H3K4me2 and H3K27ac patterns, and that those marks alone cannot predict which genes will be expressed eventually. Genomic ChIP-Seq on key transcription factors and histone modification marks in hematopoiesis
2014-07-28 | E-GEOD-42110 | biostudies-arrayexpress
Project description:Hematopoiesis is a well-established model system to study molecular mechanisms of lineage-specific differentiation. Key transcription factors (TFs), such as PU.1, NF-E2 and GATA1 are implicated in crucial aspects of distinct hematopoietic lineages. How TFs collaborate with histone modificatons and how they affect the chromatin status remains to be elucidated. Chromatin-Immunoprecipitation followed by next-generation sequencing (ChIP-seq) has been proven to be an excellent tool to study chromatin modifications genome-wide. In this study, ChIP-seq was used to investigate the H3K4me2 landscape at enhancers during hematopoietic differentiation, starting from the hematopoietic stem cell (HSC) up to the fully differentiated erythrocyte, megakaryocyte or granulocyte. Although cell morphology and gene expression profiles differ extensively in committed erythrocytes, megakaryocytes and granulocytes, the genomic landscape of H3K4me2 is surprisingly alike across the three cell types. Granulocytes, in particular, seem to display an ‘erythocyte-like’ chromatin pattern. Similar results were observed for another chromatin mark, H3K27ac. Unexpectedly, the common progenitors of erythrocytes and granulocytes do not display a similar chromatin pattern, excluding the idea that the H3K4me2 mark is placed early on during differentiation. These results also suggest that the chromatin state is probably not the determining factor for lineage differentiation, but that rather lineage specific TF binding is important. In agreement with this, mature megakaryocytes loose the H3K4me2 mark surrounding erythrocyte-specific genes. This might be explained because megakaryocytes and erythrocytes both express the lineage specific TFs GATA1 and NF-E2. Altogether, we show that committed granulocytes and erythrocytes display similar H3K4me2 and H3K27ac patterns, and that those marks alone cannot predict which genes will be expressed eventually.
2014-07-28 | GSE42110 | GEO
Project description:ChIP-seq assay was performed with anti-p45 antibody using in vitro cultured primary megakaryocytes to identify direct p45 target genes in megakaryocytes. This analysis revealed genes that regulate platelet function, which were not known previously to be p45-regulated. ChIP was performed using a day-3 primary culture of megakaryocytes from E13.5 fetal livers of wild-type mice with an anti-p45 antibody.
2013-11-01 | E-GEOD-42249 | biostudies-arrayexpress
Project description:We characterized the binding of Smad2/3 using ChIP-SEQ in both control gastrula-stage X. tropicalis embryos and embryos depleted of the transcription factor E2a (E2a-MO). We also characterized gene expression in control and E2a-depleted embryos by RNA-Seq. For ChIP-Seq, three biological replicates of E2a-MO were performed, and two biological replicates of Control embryos were performed. For RNA-Seq, two biological replicates of E2a-MO were performed, and two biological replicates of Control embryos were performed, and the mean expression levels of each gene were compared.
2014-08-01 | GSE56169 | GEO
Project description:Quebec Platelet disorder (QPD) is a unique bleeding disorder that markedly increases urokinase plasminogen activator (uPA) in megakaryocytes and platelets but not in plasma or urine. The cause is tandem duplication of a 77 kb region of chromosome 10 containing PLAU and C10orf55. Blood cells and cultured megakaryocytes from donors (7 QPD, 10 control subjects) were prepared for total and allele-specific, quantitative reverse transcription polymerase chain reaction, immunoassays, Western blots and RNA-seq. Transcriptomes for cultured megakaryocytes and peripheral blood granulocytes from 4 control and 3 QPD individuals were analyzed using mRNA-seq.
| EGAS00001001840 | EGA
Project description:Bulk RNA-Seq: Gene expression analysis of stromal and tumor fractions of primary and metastatic lesions of polyclonal and monoclonal origin. Primary tumor control samples consist of monoclonal Thy1.1 (no replicates), monoclonal parental (no replicates), monoclonal IL11 (duplicate), monoclonal FIGF (duplicate), and monoclonal CFP (duplicate). Primary polyclonal tumor samples consist of separated Thy 1.1 (duplicate), CFP (no replicates), IL11 (triplicate), and FIGF (triplicate). Metastatic tumor samples consist of monoclonal CFP (duplicate), monoclonal IL11 (quadruplicate), monoclonal FIGF (quadruplicate), monoclonal Thy1.1 (duplicate), and polyclonal samples (duplicate). Metastatic stromal fractions consist of monoclonal CFP (duplicate), monoclonal FIGF (quadruplicate), monoclonal IL11 (quadruplicate), monoclonal parental (duplicate), monoclonal Thy1.1 (duplicate), and polyclonal samples (triplicate). Primary stromal samples consist of monoclonal CFP (duplicate), monoclonal FIGF (duplicate), monoclonal IL11 (duplicate), monoclonal parental (no replicates), monoclonal Thy1.1 (duplicate), and polyclonal samples (triplicate). Further stromal controls consisted of a single fatpad sample and lung sample. Single cell RNA-Seq: Blood, tumors and lungs were isolated from test groups (DOX+ and DOX-) and tumor-naïve animals. Samples were pooled across 3 animals per group, and CD45+populations were FACS-sorted. Two thousand single cells were targeted for each sample.
2019-09-24 | GSE109281 | GEO
Project description:ChIP-seq assay was performed with anti-p45 antibody using in vitro cultured primary megakaryocytes to identify direct p45 target genes in megakaryocytes. This analysis revealed genes that regulate platelet function, which were not known previously to be p45-regulated.
2013-11-01 | GSE42249 | GEO
Project description:<p>Gene expression is a biological process regulated at different molecular levels, including chromatin accessibility, transcription, and RNA maturation and transport. In addition, these regulatory mechanisms have strong links with cellular metabolism. Here we present a multi-omics dataset that captures different aspects of this multi-layered process in yeast. We obtained RNA-seq, metabolomics, and H4K12Ac ChIP-seq data for wild-type and mip6delta strains during a heat-shock time course. Mip6 is an RNA-binding protein that contributes to RNA export during environmental stress and is informative of the contribution of post-transcriptional regulation to control cellular adaptations to environmental changes. The experiment was performed in quadruplicate, and the different omics measurements were obtained from the same biological samples, which facilitates the integration and analysis of data using covariance-based methods. We validate our dataset by showing that ChIP-seq, RNA-seq and metabolomics signals recapitulate existing knowledge about the response of ribosomal genes and the contribution of trehalose metabolism to heat stress.</p>
2020-02-14 | MTBLS1320 | MetaboLights
Project description:This dataset contains 135 H3K27ac ChiP-seq experiments. Monocytes and granulocytes from TB and non-TB samples were obtained, ChIP-seq was performed, and the reads were aligned to hg19.
| EGAD00001004206 | EGA