Automatisiertes Mikroskop
Final Report Abstract
To systematically analyze genetic interactions we developed new methods monitoring the effects of single genes and gene combinations using high-throughput microscopy. The automated microscope was deployed in experiments to systematically analyse phenotypic outcomes of perturbations by RNAi in Drosophila and human cells. In experiments to characterize the interactions of signaling pathways that regulate cell growth and proliferation and cell morphology, we tested pairwise interactions between 93 genes involved in signal transduction in Drosophila cells. Each gene was targeted with two sequence-independent double-stranded RNAs and measured in multiple replicate to assess the robustness and reproducibility of the experiments. Targeted genes included annotated components of Ras-MAPK, JNK and p38 pathways and all annotated protein and lipid phosphatases expressed in Drosophila S2 cells. After single and double perturbation, cells were fixed and stained for cellular markers. Cells were subsequently imaged by high-throughput microscopy. While inhibition of gene function by RNAi is often incomplete, resulting in a hypomorphic phenotype dependent on knock-down efficiency, target protein stability and feedback regulation, we assessed in these experiments the combined phenotypes of all pairwise RNAi treatments through eight independent measurements, including all possible combinations of two RNAi reagents for both target genes. We found that phenotypic measurements were highly reproducible across replicate experiments and the two-fold coverage of each gene with independent dsRNAs allowed us to identify unspecific effects. Interestingly, we observed 135 genetic interactions generic for all phenotypes, more than 300 were specific to a single phenotypic readout. These experiments highlighted the multidimensionality of the genetic interaction space. The robust experimental design and stringent statistical analysis provides a framework for studies in other model system, including human cells. We have now significantly expanded the genetic interaction network in Drosophila as well as in human cells.
Publications
- Extracting quantitative genetic interaction phenotypes from matrix combinatorial RNAi. BMC Bioinformatics 12:342
Axelsson, E., Sandmann, T., Horn, T., Boutros, M., Huber, W., Fischer, B.
- Mapping of signaling networks through synthetic genetic interaction analysis by RNAi. Nature Methods 8:341-6
Horn, T., Sandmann, T., Fischer, B., Axelsson, E., Huber, W., Boutros, M.
- A novel phenotypic dissimilarity method for image-based highthroughput screens. BMC Bioinformatics 14:336
Zhang X, Boutros M.
- Mapping genetic interactions in human cancer cells with RNAi and multiparametric phenotyping. Nature Methods 10:427-31
Laufer, C., Fischer, B., Billmann, M., Huber, W., Boutros, M.
