HOMECONTACTSITE MAPIMPRINT
CeNS Center for NanoScience LMU Ludwig-Maximilians-Universität München
CeNS HomepageLMU Homepage
Home  >  Calendar

CeNS Colloquium

Place: Kleiner Physik-Hörsaal
Date: 19.04.2013, Time: 16:30h

Genome-wide models of gene expression: from transcription to implication in physiological phenotypes

Dr. Julien Gagneur
Gene Center Munich, LMU

We are interested in understanding mechanisms of gene regulation and their phenotypic impact from genome-wide assays. In this talk I will present two studies touching on both of these aspects.
1. Genome-wide transcription profiling has revealed extensive expression of non-coding RNAs antisense to genes, yet their functions, if any, remain to be understood. We have performed a systematic analysis of sense-antisense expression in response to genetic and environmental changes in yeast. We found that antisense expression allows to 'switching off' basal levels of gene expression. In addition, our data provided evidence that antisense expression initiated from bidirectional promoters enables the spreading of regulatory signals from one locus to neighbouring genes. These results indicate a general regulatory effect of antisense expression on sense genes and emphasize the importance of antisense-initiating regions downstream of genes in models of gene regulation.
2. Dissecting the molecular mechanisms that link genotype to phenotype promises to deliver the necessary insights to develop drugs tailored to the genetic background and life circumstances of the patient. Information from interventional data is scarce, and hence the challenge resides in developing causal inference strategies to exploit the breadth of observational population-level genetic and molecular profiling data being generated. We investigated in yeast to what extent environmental perturbations, combined with genetic variations, facilitate causal inference in molecular networks. Our results show that exploiting condition-specific genetic effects substantially increases the predictive accuracy over approaches based on genetic or environmental variations alone.