Browsing publications of the research group genomeanalytics (GMAK) by Subject (MeSH)
Now showing items 1-3 of 3
Genome-Wide Sequencing Reveals MicroRNAs Downregulated in Cerebral Cavernous Malformations.Cerebral cavernous malformations (CCM) are vascular lesions associated with loss-of-function mutations in one of the three genes encoding KRIT1 (CCM1), CCM2, and PDCD10. Recent understanding of the molecular mechanisms that lead to CCM development is limited. The role of microRNAs (miRNAs) has been demonstrated in vascular pathologies resulting in loss of tight junction proteins, increased vascular permeability and endothelial cell dysfunction. Since the relevance of miRNAs in CCM pathophysiology has not been elucidated, the primary aim of the study was to identify the miRNA-mRNA expression network associated with CCM. Using small RNA sequencing, we identified a total of 764 matured miRNAs expressed in CCM patients compared to the healthy brains. The expression of the selected miRNAs was validated by qRT-PCR, and the results were found to be consistent with the sequencing data. Upon application of additional statistical stringency, five miRNAs (let-7b-5p, miR-361-5p, miR-370-3p, miR-181a-2-3p, and miR-95-3p) were prioritized to be top CCM-relevant miRNAs. Further in silico analyses revealed that the prioritized miRNAs have a direct functional relation with mRNAs, such as MIB1, HIF1A, PDCD10, TJP1, OCLN, HES1, MAPK1, VEGFA, EGFL7, NF1, and ENG, which are previously characterized as key regulators of CCM pathology. To date, this is the first study to investigate the role of miRNAs in CCM pathology. By employing cutting edge molecular and in silico analyses on clinical samples, the current study reports global miRNA expression changes in CCM patients and provides a rich source of data set to understand detailed molecular machinery involved in CCM pathophysiology.
Genomewide analyses define different modes of transcriptional regulation by peroxisome proliferator-activated receptor-β/δ (PPARβ/δ).Peroxisome proliferator-activated receptors (PPARs) are nuclear receptors with essential functions in lipid, glucose and energy homeostasis, cell differentiation, inflammation and metabolic disorders, and represent important drug targets. PPARs heterodimerize with retinoid X receptors (RXRs) and can form transcriptional activator or repressor complexes at specific DNA elements (PPREs). It is believed that the decision between repression and activation is generally governed by a ligand-mediated switch. We have performed genomewide analyses of agonist-treated and PPARβ/δ-depleted human myofibroblasts to test this hypothesis and to identify global principles of PPARβ/δ-mediated gene regulation. Chromatin immunoprecipitation sequencing (ChIP-Seq) of PPARβ/δ, H3K4me3 and RNA polymerase II enrichment sites combined with transcriptional profiling enabled the definition of 112 bona fide PPARβ/δ target genes showing either of three distinct types of transcriptional response: (I) ligand-independent repression by PPARβ/δ; (II) ligand-induced activation and/or derepression by PPARβ/δ; and (III) ligand-independent activation by PPARβ/δ. These data identify PPRE-mediated repression as a major mechanism of transcriptional regulation by PPARβ/δ, but, unexpectedly, also show that only a subset of repressed genes are activated by a ligand-mediated switch. Our results also suggest that the type of transcriptional response by a given target gene is connected to the structure of its associated PPRE(s) and the biological function of its encoded protein. These observations have important implications for understanding the regulatory PPAR network and PPARβ/δ ligand-based drugs.
More than just a metabolic regulator--elucidation and validation of new targets of PdhR in Escherichia coli.The pyruvate dehydrogenase regulator protein (PdhR) of Escherichia coli acts as a transcriptional regulator in a pyruvate dependent manner to control central metabolic fluxes. However, the complete PdhR regulon has not yet been uncovered. To achieve an extended understanding of its gene regulatory network, we combined large-scale network inference and experimental verification of results obtained by a systems biology approach.