AUTOMATED MICROSCOPY SCREEN TO IDENTIFY COMPONENTS REQUIRED FOR MITOTIC CELL CYCLE PROGRESSION IN HUMAN CELLS

We designed an image-based screen using automated microscopy to discover genetic factors essential for mitotic progression. Using a human genome-wide RNAi library, we performed a loss-of-function screen looking for siRNAs that arrest cells in metaphase. Supervised clustering of the multiparametric morphological data with gene ontology (GO) annotations, protein families, tissue expression and protein-protein interactions functionally classified these genes into discrete mitotic processes involved in spindle assembly. We used this approach to rapidly identify important novel genes based on their association with known genes in the clusters. We present here the automated methods used to identify these components.