BACKGROUND: Cbln1 is a gene whose expression is negatively correlated to seizures. Krishnan et al. has recently shown that seizures synergize with transcriptional co-regulator Ube3a to repress Cbln1 expression, which ultimately manifests as ASD associated behavioral discrepancies. (Krishnan et al., 2017) Seizures increase the expression of REST and the Cbln1 gene contains an intronic RE-1 binding site previously shown to interact with REST. This could therefore be a point of convergence for the transcriptional downregulation of Cbln1. OBJECTIVE: To determine if Cbln1’s RE-1 sequences confers gene repression to minimal promoter reporter system by REST and Ube3a. METHODS: Desired RE-1 sequences from Cbln1 were subcloned into a pGL3-basic vector using specific restriction enzymes that flanked each DNA region. Specific oligonucleotide target sequences were annealed together and ligated into the plasmid vector before transfecting into live HEK293T cells. A minimal luciferase promoter with just enough sequence for the polymerase to sit was also ligated into the cassette. A luciferase assay was then conducted on the plated cells under exposure to separate testing conditions such as excess Ube3a, REST, dnREST, and various combinations of these factors to determine the effect of these TFs on gene expression controlled by Cbln1’s RE-1 site. RESULTS: REST strongly, and Ube3a weakly, repressed the minimal promoter reporter construct when Cbln1’s RE-1 sequences were added. REST occluded the repressive effects produced by Ube3a indicating that their effects are not additive or synergistic. CONCLUSION: Both REST, that is increased by seizures (Krishnan et al., 2017), and Ube3a (more weakly) can repress gene expression when Cbln1’s RE-1 binding sequences are added. These repressive effects may help explain how seizures and Ube3a can decrease Cbln1 expression that ultimately leads to reduced sociability. / 2019-10-31

Vorhersagen von miRNA-Bindestellen enthalten oft einen hohen Prozentsatz an falsch positiven Ergebnissen (24-70%). Gleichzeitig ist es schwierig die biologischen Interaktionen von miRNAs und ihren Zieltranskripten auf experimentellem Wege und Genom weit zu messen. Daher wurde in der vorliegenden Arbeit die Frage beantwortet, ob ChIP-Sequenzierungsdaten, von denen es immer mehr gibt, verwendet werden können, um Vorhersagen von miRNA-Bindestellen zu filtern. Dabei wurde von einem Netzwerk aus miRNAs und Transkriptionsfaktoren gebraucht gemacht, die Zieltranskripte gemeinsam regulieren. Zunächst wurden verschiedene Methoden getestet, mit denen „Peaks“ aus der ChIP-Sequenzierung Zielgenen zugeordnet werden können. Zielgenlisten des transkriptionalen Repressors RE1-silencing transcription factor (REST/NRSF) wurden mithilfe von ChIP-Sequenzierungsdaten erzeugt. Ein Algorithmus zur Suche nach überrepräsentierten miRNA-Zielgenen in REST-Genlisten basierend auf Vorhersagen von TargetScanHuman wurde entwickelt und angewandt. Die detektierten „enrichment“-miRNAs waren Teil eines vielfältig regulierten REST-miRNA-Netzwerks. Mögliche Funktionen von miRNAs wurden vorgeschlagen und ihre Rolle im gemeinsamen Netzwerk mit REST und im damit gebildeten Netzwerkmotiv (Inkoherente Schleife zur Vorwärtskopplung Typ 2) wurde analysiert. Es stellte sich heraus, dass ein Filtern der Vorhersagen tatsächlich möglich ist, da Gene, die sowohl von REST als auch von einer oder mehreren „enrichment“-miRNAs reguliert werden, einen höheren Anteil an wahren miRNA-Transkript-Interaktionen haben. / Predictions of miRNA binding sites suffer from high false positive rates (24-70%) and measuring biological interactions of miRNAs and target transcripts on a genome wide scale remains challenging. In the thesis at hand the question was answered if the ever growing body of ChIP-sequencing data can be applied to filter miRNA target predictions by making use of the underlying regulatory network of miRNAs and transcription factors. First different methods for association of ChIP-sequencing peaks to target genes were tested. Target gene lists of the transcriptional repressor RE1-silencing transcription factor (REST/NRSF) were generated by means of ChIP-sequencing data. An enrichment analysis tool based on predictions from TargetScanHuman was developed and applied to find ‘enrichment’-miRNAs with over-represented targets in the REST gene lists. The detected miRNAs were shown to be part of a highly regulated REST-miRNA network. Possible functions could be assigned to them and their role in the regulatory network and special network motifs (incoherent feedforward loop of type 2) was analyzed. It turned out that miRNA target predictions of genes shared by enrichment-miRNAs and REST had a higher proportion of true positive associations than the TargetScanHuman background, thus the procedure made a filtering possible.