Genome-wide functional analysis of human cell-cycle regulators

Abstract

Human cells have evolved complex signaling networks to coordinate the cell cycle. A detailed understanding of the global regulation of this fundamental process requires comprehensive identification of the genes and pathways involved in the various stages of cell-cycle progression. To this end, we report a genome-wide analysis of the human cell cycle, cell size, and proliferation by targeting >95% of the protein-coding genes in the human genome using small interfering RNAs (siRNAs). Analysis of >2 million images, acquired by quantitative fluorescence microscopy, showed that depletion of 1,152 genes strongly affected cell-cycle progression. These genes clustered into eight distinct phenotypic categories based on phase of arrest, nuclear area, and nuclear morphology. Phase-specific networks were built by interrogating knowledge-based and physical interaction databases with identified genes. Genome-wide analysis of cell-cycle regulators revealed a number of kinase, phosphatase, and proteolytic proteins and also suggests that processes thought to regulate G(1)-S phase progression like receptor-mediated signaling, nutrient status, and translation also play important roles in the regulation of G(2)/M phase transition. Moreover, 15 genes that are integral to TNF/NF-kappaB signaling were found to regulate G(2)/M, a previously unanticipated role for this pathway. These analyses provide systems-level insight into both known and novel genes as well as pathways that regulate cell-cycle progression, a number of which may provide new therapeutic approaches for the treatment of cancer.

Fig. 1.

Scheme for identifying human cell-cycle regulators by RNAi using high-content imaging. Cultured cells were transfected, fixed, stained, and imaged. The percentage of cells in each phase of the cell cycle was determined from processed images. In addition, the percentage of G₂/M cells (red ellipses) with PAR between 5.5 and 8.0 (black rectangles) was calculated for each well. DNA histograms and images for all siRNA wells resulting in significant changes in phase distribution or morphology were manually inspected before functional annotation.

Fig. 2.

Quantitative measurements and functional classification of genes from the genome-wide RNAi screen for human cell-cycle regulators. (A) Scores for the eight descriptors plotted as rank vs. standard deviations (StnD). The top 1,000 scoring genes are shown as red circles, GL3 controls (targeting luciferase) as black circles, selected known genes as red triangles, and all other genes as blue circles. (B) Cluster analysis of the normalized scores for the eight descriptors of each cell-cycle gene (x axis) resulted in eight distinct phenotypic categories (Ca, y axis). Normalized scores of ≥+3 are red, ≤−3 blue, and 0 white. (C) Pie chart showing the putative biological processes, based on GO and Interpro annotations, of cell-cycle regulators.

Fig. 3.

Examples of mitotic and cytokinetic defects after RNAi of indicated genes. U2OS cells were stained with anti-γ-tubulin antibody (red), anti-α-tubulin (green), and DAPI (blue). (Scale bars: 5 μm.)

Fig. 4.

Subnetworks showing protein associations among cell-cycle regulators. (A) G₂/M genes involved in TNF signaling. Gene symbols in black are identified in this study. Node colors represent transcription regulators (blue), enzymes (red), receptors (yellow), growth factors (green), and other proteins (brown). (B) G₁ proteins showing the clustering of translation components and genes giving rise to the small nucleus G₁ phenotype. Shown are cell-cycle regulators (red) and genes with no phenotype (blue). (C) Mitotic proteins within the G₂/M network. Color codes are the same as in B.