The Whitfield lab is currently working on several projects that are unified by genome-wide, systems biology approaches. The first is a translational project that uses genomic tools to study the systemic autoimmune disease scleroderma. The goal is to identify gene expression biomarkers that subset patients, predict clinical endpoints, and assess response to therapy. The second project utilizes microarrays and next generation ultrahigh-throughput sequencing to understand the regulation and gene function in the human cell division cycle. These projects are interconnected, as the 'proliferation signature' is a feature not only of cancer, but also of the scleroderma subsets.
Gene expression subsets in scleroderma. We have used genome-wide analysis of gene expression in skin to identify novel subsets of scleroderma. Genome-wide analysis has identified gene expression groups within current clinical classifications of the disease that can be mapped to distinct clinical covariates. Each group has differentially regulated pathways that could be targeted therapeutically and each is being mapped to specific mouse models that recapitulate disease phenotypes for further genetic studies. The lab is currently examining scleroderma patients for gene expression responses to therapy in order to identify biomarkers that could impact clinical decision-making. An ongoing area of investigation is to identify subsets and biomarkers in scleroderma using peripheral blood samples rather than skin samples. This would provide biomarkers in a tissue more easily accessible than skin.
Regulation of gene expression in the cell division cycle. One of the most striking observations in whole genome expression data is the coordinate regulation of groups of genes, and the finding that coordinately regulated genes are involved in similar biological processes. Our experiments are focused on determining how the G2 and M phase genes are regulated, and in investigating the function of uncharacterized genes required for cell division. We have identified novel proteins involved in the establishment of bipolar spindles, a set of forkhead proteins necessary for cell cycle progression and RNA-binding proteins that result in cell cycle defects. Specific proteins are being characterized in detail. We are integrating gene expression datasets, targeted siRNA knockdowns, and published large-scale screens to predict functions for novel cell cycle-regulated genes. Finally, we are repeating the genome-wide analysis of the human cell cycle (Whitfield et al. 2002 MBC) in different cell types to identify cell type-specific regulators.
RNA targets of Ribonucleoprotein (RNP) complexes. We are developing novel methods to identify the RNA targets in ribonucleoprotein (RNP) complexes. We have used the histone SLBP (Whitfield et al. NAR 2004, Townley-Tilson et al. RNA 20006) to develop a microarray-based approach to identify the targets of RNA binding proteins on a genome-wide scale. This method has been termed RNA-binding Protein IP (RIP) followed by microarray analysis (RIPchip) or ultra-highthroughput (UHTP) Solexa sequencing (RIPseq). We have demonstrated that this method can be extended to more general RNA-binding proteins (e.g. the AU-rich element binding protein TTP; Emmons et al., RNA 2008). The lab is currently developing novel array platforms, experimental protocols and computational algorithms for analysis of RIPchip and RIPseq data. These methods are being applied to a diverse set of RNA-binding proteins.