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GSE67458
Homo sapiens
21 Downloadable Samples
Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
MEF2B mutations in non-Hodgkin lymphoma dysregulate cell migration by decreasing MEF2B target gene activation.
Sample Metadata Fields
Cell line, Treatment
View Samples- Homo sapiens
- 21 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)
Description
Myocyte enhancer factor 2B (MEF2B) is a transcription factor with somatic mutation hotspots at K4, Y69 and D83 in diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). The recurrence of these mutations indicates that they may drive lymphoma development. However, inferring the mechanisms by which they may drive lymphoma development was complicated by our limited understanding of MEF2Bs normal functions. To expand our understanding of the cellular activities of wildtype (WT) and mutant MEF2B, I developed and addressed two hypotheses: (1) identifying genes regulated by WT MEF2B will allow identification of cellular phenotypes affected by MEF2B activity and (2) contrasting the DNA binding sites, effects on gene expression and effects on cellular phenotypes of mutant and WT MEF2B will help refine hypotheses about how MEF2B mutations may contribute to lymphoma development. To address these hypotheses, I first identified genome-wide WT MEF2B binding sites and transcriptome-wide gene expression changes mediated by WT MEF2B. Using these data I identified and validated novel MEF2B target genes. I found that target genes of MEF2B included the cancer genes MYC, TGFB1, CARD11, NDRG1, RHOB, BCL2 and JUN. Identification of target genes led to findings that WT MEF2B promotes expression of mesenchymal markers, promotes HEK293A cell migration, and inhibits DLBCL cell chemotaxis. I then investigated how K4E, Y69H and D83V mutations change MEF2Bs activity. I found that K4E, Y69H and D83V mutations decreased MEF2B DNA binding and decreased MEF2Bs capacity to promote gene expression in both HEK293A and DLBCL cells. These mutations also reduced MEF2Bs capacity to alter HEK293A and DLBCL cell movement. From these data, I hypothesize that MEF2B mutations may promote DLBCL and FL development by reducing expression of MEF2B target genes that would otherwise function to help confine germinal centre B-cells to germinal centres. Overall, my research demonstrates how observations from genome-scale data can be used to identify cellular effects of candidate driver mutations. Moreover, my work provides a unique resource for exploring the role of MEF2B in cell biology: I map for the first time the MEF2B regulome, demonstrating connections between a relatively understudied transcription factor and genes significant to oncogenesis.
Publication Title
MEF2B mutations in non-Hodgkin lymphoma dysregulate cell migration by decreasing MEF2B target gene activation.
Sample Metadata Fields
Cell line, Treatment
View Samples- Homo sapiens
- 10 Downloadable Samples
IlluminaHiSeq2000
Description
Myocyte enhancer factor 2B (MEF2B) is a transcription factor with somatic mutation hotspots at K4, Y69 and D83 in diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). The recurrence of these mutations indicates that they may drive lymphoma development. However, inferring the mechanisms by which they may drive lymphoma development was complicated by our limited understanding of MEF2B’s normal functions. To expand our understanding of the cellular activities of wildtype (WT) and mutant MEF2B, I developed and addressed two hypotheses: (1) identifying genes regulated by WT MEF2B will allow identification of cellular phenotypes affected by MEF2B activity and (2) contrasting the DNA binding sites, effects on gene expression and effects on cellular phenotypes of mutant and WT MEF2B will help refine hypotheses about how MEF2B mutations may contribute to lymphoma development. To address these hypotheses, I first identified genome-wide WT MEF2B binding sites and transcriptome-wide gene expression changes mediated by WT MEF2B. Using these data I identified and validated novel MEF2B target genes. I found that target genes of MEF2B included the cancer genes MYC, TGFB1, CARD11, NDRG1, RHOB, BCL2 and JUN. Identification of target genes led to findings that WT MEF2B promotes expression of mesenchymal markers, promotes HEK293A cell migration, and inhibits DLBCL cell chemotaxis. I then investigated how K4E, Y69H and D83V mutations change MEF2B’s activity. I found that K4E, Y69H and D83V mutations decreased MEF2B DNA binding and decreased MEF2B’s capacity to promote gene expression in both HEK293A and DLBCL cells. These mutations also reduced MEF2B’s capacity to alter HEK293A and DLBCL cell movement. From these data, I hypothesize that MEF2B mutations may promote DLBCL and FL development by reducing expression of MEF2B target genes that would otherwise function to help confine germinal centre B-cells to germinal centres. Overall, my research demonstrates how observations from genome-scale data can be used to identify cellular effects of candidate driver mutations. Moreover, my work provides a unique resource for exploring the role of MEF2B in cell biology: I map for the first time the MEF2B ‘regulome’, demonstrating connections between a relatively understudied transcription factor and genes significant to oncogenesis. Overall design: RNA-seq was performed on cells expressing V5 tagged WT or mutant MEF2B and on empty vector control cells. One biological replicates was performed on cell treated with either ionomycin or a solvent-only control.
Publication Title
MEF2B mutations in non-Hodgkin lymphoma dysregulate cell migration by decreasing MEF2B target gene activation.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 12 Downloadable Samples
- Illumina Genome Analyzer II
Description
We have used deep sequencing to explore the repertoire of both poly(A)+ and poly(A)- RNAs from two standard cell lines, HeLa cells and human embryonic stem cell (hESC) H9 cells. Overall design: Examination of nonpolyadenylated and polyadenylated in 2 cell types.
Publication Title
Genomewide characterization of non-polyadenylated RNAs.
Sample Metadata Fields
Cell line, Subject
View Samples- Homo sapiens
- 4 Downloadable Samples
- IlluminaGenomeAnalyzerII
Description
We have used deep sequencing to explore the repertoire of both poly(A)+ and poly(A)- RNAs from two standard cell lines, HeLa cells and human embryonic stem cell (hESC) H9 cells. Overall design: Examination of nonpolyadenylated and polyadenylated RNA in 2 cell types.
Publication Title
Genomewide characterization of non-polyadenylated RNAs.
Sample Metadata Fields
No sample metadata fields
View Samples- Arabidopsis thaliana
- 15 Downloadable Samples
- Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)
Description
2H2O has a long history as a protein or amino acid labeling techinique, and such labeling systems have proven effective for many different types of studies. A disadvantage of a 2H2O labeling system is that plant growth is inhibited as the percentage of deuterium in the medium increases. However the molecular effects of 2H2O on plant growth has not previoulsly been investigated.
Publication Title
Measuring the turnover rates of Arabidopsis proteins using deuterium oxide: an auxin signaling case study.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 6 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
The Transcription Factor Tcf1 Contributes to Normal NK Cell Development and Function by Limiting the Expression of Granzymes.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 6 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
The transcription factor Tcf1 plays an essential role for the development of NK cells, however, its precise role for NK cell development, maturation and function is poorly understood. Here we show that distinct domains of Tcf1 direct bone marrow progenitors towards the NK cell lineage and mediate lineage commitment and NK cell expansion, and that Tcf1 downregulation is required for terminal NK cell maturation. Impaired NK cell development in the absence of Tcf1 is explained by increased cell death due to excessive expression of Granzyme family proteins, which results in NK cell self-destruction. In addition, excessive Granzyme B expression leads to target cell induced NK cell death and consequently reduced target cell killing by NK cells lacking Tcf1. Mechanistically, Tcf1 prevents excessive Granzyme B expression by binding to a newly identified enhancer element upstream of the Granzyme B locus. These data identify an unexpected requirement to limit the expression of cytotoxic effector molecules for lymphocyte development.
Publication Title
The Transcription Factor Tcf1 Contributes to Normal NK Cell Development and Function by Limiting the Expression of Granzymes.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 448 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations associated with cancer predisposition and large numbers of somatic genomic alterations. However, it remains challenging to distinguish between background, or passenger and causal, or driver cancer mutations in these datasets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. To test the hypothesis that genomic variations and tumour viruses may cause cancer via related mechanisms, we systematically examined host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways that go awry in cancer, such as Notch signalling and apoptosis. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on par with their identification through functional genomics and large-scale cataloguing of tumour mutations. These complementary approaches together result in increased specificity for cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate prioritization of cancer-causing driver genes so as to advance understanding of the genetic basis of human cancer.
Publication Title
Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins.
Sample Metadata Fields
Cell line
View Samples- Saccharomyces cerevisiae
- 10 Downloadable Samples
- Illumina HiSeq 2000
Description
In this work, we determine total mRNA decay rates in rpb1-1 and rpb1-1/caf1? cells, calculate half-lives in rpb1-1/caf1? cells relative to rpb1-1 cells and correlate them with codon optimality. Overall design: mRNA profiling was done on 10 time points in rpb1-1/caf1 cells and sequenced using a paired end protocol on an Illumina HiSeq2000 instrument. A biological duplicate was performed.
Publication Title
mRNA Deadenylation Is Coupled to Translation Rates by the Differential Activities of Ccr4-Not Nucleases.
Sample Metadata Fields
Cell line, Subject
View Samples