Identification of Drosophila Mitotic Genes by Combining Co-Expression Analysis and RNA Interference

Abstract

RNAi screens have, to date, identified many genes required for mitotic divisions of Drosophila tissue culture cells. However, the inventory of such genes remains incomplete. We have combined the powers of bioinformatics and RNAi technology to detect novel mitotic genes. We found that Drosophila genes involved in mitosis tend to be transcriptionally co-expressed. We thus constructed a co-expression–based list of 1,000 genes that are highly enriched in mitotic functions, and we performed RNAi for each of these genes. By limiting the number of genes to be examined, we were able to perform a very detailed phenotypic analysis of RNAi cells. We examined dsRNA-treated cells for possible abnormalities in both chromosome structure and spindle organization. This analysis allowed the identification of 142 mitotic genes, which were subdivided into 18 phenoclusters. Seventy of these genes have not previously been associated with mitotic defects; 30 of them are required for spindle assembly and/or chromosome segregation, and 40 are required to prevent spontaneous chromosome breakage. We note that the latter type of genes has never been detected in previous RNAi screens in any system. Finally, we found that RNAi against genes encoding kinetochore components or highly conserved splicing factors results in identical defects in chromosome segregation, highlighting an unanticipated role of splicing factors in centromere function. These findings indicate that our co-expression–based method for the detection of mitotic functions works remarkably well. We can foresee that elaboration of co-expression lists using genes in the same phenocluster will provide many candidate genes for small-scale RNAi screens aimed at completing the inventory of mitotic proteins. Mitosis is the evolutionarily conserved process that enables a dividing cell to equally partition its genetic material between the two daughter cells. The fidelity of mitotic division is crucial for normal development of multicellular organisms and to prevent cancer or birth defects. Understanding the molecular mechanisms of mitosis requires the identification of genes involved in this process. Previous studies have shown that such genes can be readily identified by RNA interference (RNAi) in Drosophila tissue culture cells. Because the inventory of mitotic genes is still incomplete, we have undertaken an RNAi screen using a novel approach. We used a co-expression–based bioinformatic procedure to select a group of 1,000 genes enriched in mitotic functions from a dataset of 13,166 Drosophila genes. This group includes roughly half of the known mitotic genes, implying that it should contain half of all mitotic genes, including those that are currently unknown. We performed RNAi against each of the 1,000 genes in the group. By limiting the number of genes to be examined, we were able to perform a very detailed phenotypic analysis of RNAi cells. This analysis allowed the identification of 70 genes whose mitotic role was previously unknown; 30 are required for proper chromosome segregation and 40 are required to maintain chromosome integrity.