RNA-Seq enables sensitive and comprehensive analysis of mRNA, including transcripts containing single nucleotide variants (SNVs), alternatively spliced forms, and previously unobserved sequences. Although RNA-Seq can characterize the mRNA products derived from a gene and can quantify the transcript levels in different tissues and cells, we know less about how much of the analogous protein products are expressed and what function they hold. We are interested in solving this problem by cataloguing and comparing large-scale mRNA and protein data collected from a single cell population. This comprehensive dataset will help us understand the relationship between mRNA and protein variants (including the canonical forms). Our model system uses Jurkat cells that are induced to early, mid, and late apoptosis by treatment with the pan-kinase inhibitor staurosporine (STS). From integration of the next generation sequencing and mass spectrometry-based proteomics data, we hope to correlate RNA and protein information and understand the relationship between the canonical and variant forms.
My previous research project was on identification of proteins endogenously associated with DNA. I and collaborators developed a strategy called GENECAPP, for Global ExoNuclease-based Enrichment of Chromatin-Associated Proteins for Proteomics.