This SuperSeries is composed of the SubSeries listed below.
Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.
Specimen part, Treatment
View SamplesSkeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor coactivator 1 (PGC-1), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1 and gene expression upon PGC-1 over-expression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto underestimated number of transcription factor partners involved in mediating PGC-1 action. In particular, principal component analysis of TFBSs at PGC-1 binding regions predicts that, besides the well-known role of the estrogen-related receptor (ERR), the activator protein-1 complex (AP-1) plays a major role in regulating the PGC-1-controlled gene program of hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1.
Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.
Treatment
View SamplesThe peroxisome proliferator-activated receptor co-activator 1 (PGC-1) coordinates the transcriptional network response to promote an improved endurance capacity in skeletal muscle, e.g. by co-activating the estrogen-related receptor (ERR) in the regulation of oxidative substrate metabolism. Despite a close functional relationship, the interaction between these two proteins has not been studied on a genomic level. We now mapped the genome-wide binding of ERR to DNA in skeletal muscle cell line with elevated PGC-1 and linked the DNA recruitment to global PGC-1 target gene regulation. We found that, surprisingly, ERR co-activation by PGC-1 is only observed in the minority of all PGC-1 recruitment sites. Nevertheless, a majority of PGC-1 target gene expression is dependent on ERR. Intriguingly, the interaction between these two proteins is controlled by the genomic context of response elements, in particular the relative GC and CpG content, monomeric and dimeric repeat binding site configuration for ERR, and adjacent recruitment of the transcription factor SP1. These findings thus not only reveal an unprecedented insight into the regulatory network underlying muscle cell plasticity, but also strongly link the genomic context of DNA response elements to control transcription factor - co-regulator interactions.
The Genomic Context and Corecruitment of SP1 Affect ERRα Coactivation by PGC-1α in Muscle Cells.
Specimen part
View SamplesSkeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor coactivator 1 (PGC-1), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1 and gene expression upon PGC-1 over-expression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto underestimated number of transcription factor partners involved in mediating PGC-1 action. In particular, principal component analysis of TFBSs at PGC-1 binding regions predicts that, besides the well-known role of the estrogen-related receptor (ERR), the activator protein-1 complex (AP-1) plays a major role in regulating the PGC-1-controlled gene program of hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1.
Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.
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View SamplesThis SuperSeries is composed of the SubSeries listed below.
The Genomic Context and Corecruitment of SP1 Affect ERRα Coactivation by PGC-1α in Muscle Cells.
Specimen part
View SamplesThe patterning of the facial midline involves early specification of neural crest cells to form skeletal tissues that support the upper jaw . In order to understand the molecular mechanisms involved we have taken advantage of a beak duplication model developed in the chicken embryo. Here we can induce the transformation of the side of the beak into a second midline that is easily identifiable by the formation of a supernumerary egg tooth. The phenotype is induced by implanting two microscopic beads, one soaked in retinoic acid and the other soaked in Noggin into the side of the head of the chicken embryo. Here we use microarrays to profile expression of maxillary mesenchyme 16h after placing the beads. A subset of genes were validated using in situ hybridization and QPCR. The aims of the study are to test the function of these genes using retroviral transgenesis, knockdown with morpholinos or expression of secreted proteins and their application to the embryo.
Identification and functional analysis of novel facial patterning genes in the duplicated beak chicken embryo.
Specimen part, Treatment
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Klf4 is a transcriptional regulator of genes critical for EMT, including Jnk1 (Mapk8).
Specimen part, Treatment
View SamplesExpression profiling after Klf4 KD during EMT in NMuMG reveals a significant number of genes that are transcriptionally deregulated
Klf4 is a transcriptional regulator of genes critical for EMT, including Jnk1 (Mapk8).
Specimen part, Treatment
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Tead2 expression levels control the subcellular distribution of Yap and Taz, zyxin expression and epithelial-mesenchymal transition.
Cell line, Treatment
View SamplesMicroglia, the resident immune cells of the central nervous system (CNS), have two distinct phenotypes in the developing brain: amoeboid form, known to be amoeboid microglial cells (AMC) and ramified form, known to be ramified microglial cells (RMC) alongside several intermediate forms. The AMC are characterized by being proliferative, phagocytic and migratory whereas the RMC are quiescent and exhibit a slow turnover rate. The AMC transform into RMC with advancing age, and this transformation is indicative of the gradual shift in the microglial functions. Both AMC and RMC respond to CNS inflammation, and they become hypertrophic when they are activated by trauma, infection or neurodegenerative stimuli. The molecular mechanisms and functional significance of morphological transformation of microglia during normal development and in disease conditions is not clear. It is hypothesized that AMC and RMC are functionally regulated by a specific set of genes encoding various signaling molecules and transcription factors. To address this, we carried out cDNA microarray analysis using lectin-labeled AMC and RMC isolated from frozen tissue sections of the corpus callosum of 5-day and 4-week old rat brain respectively, by laser capture microdissection (LCM). The global gene expression profiles of both microglial phenotypes were compared and the differentially expressed genes in AMC and RMC were clustered based on their functional annotations. This genome wide comparative analysis helps in identifying genes that are specific to AMC and RMC. The novel and specific molecules identified in both microglial phenotypes can be targeted for therapeutic purposes in developing and adult brain diseases.
Transcriptome analysis of amoeboid and ramified microglia isolated from the corpus callosum of rat brain.
Specimen part
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