Erythropoiesis is a dynamic process governed by quantitative changes in the relative levels of transcription fac-tors (TFs). Due to the current paucity of quantitative data on the proteins that constitute the transcriptional regulatory network (TRN), most models of erythropoiesis are based primarily on mRNA measurements and do not typically consider changes in the protein levels of specific TFs. This significantly limits the understanding of erythropoiesis and other transcriptionally regulated processes such as ß-globin expression, ultimately impinging on the capacity to correct hemoglobin disorders. The long-term goal is to decipher the TRN that controls erythropoiesis in health and disease. The objective of this proposal is to significantly expand our TRN model for cell fate decision during erythropoiesis by integrating dynamic bulk and single cell TF protein abundance measurements with other transcription-relevant -omics data. The central hypothesis is that relative protein levels of TFs are critical parameters in the establishment of gene expression programs during the continuum of differentiation, and that erythropoiesis is driven by graded changes in the relative amounts of specific combinations of TFs. The rationale is that integration of the dynamic and quantitative nature of the TF proteome into an expanded TRN of erythropoiesis will yield a model with improved predictive power which will serve as a benchmark for healthy erythropoiesis against which to compare erythroid-related disease states, and will facilitate the identification of pharmacological agents to restore normal erythropoiesis. Three specific aims have been designed: 1) Absolute quantification of the TF proteome during erythropoiesis; 2) Determine how changes in the abundance of multiple TFs in single cells initiate and progressively reinforce cell fate decisions along the erythroid trajectory; and 3) Computational analysis, modeling and validation of the erythropoiesis TRN. For the first aim, quantitative mass spectrometry (MS) approaches will be used to measure absolute levels of the TF proteome during ex vivo erythropoiesis of HSPCs derived from healthy donors. For the second aim, complementary CyTOF and targeted-MS proteomic approaches will be used to estimate TF protein abundances in single cells, and other single cell –omics technologies will be used to measure changes in gene expression and TF genomic binding during ex vivo erythropoiesis. For the third aim, TRN models of erythropoiesis will be built utilizing measurements of TF protein abundances, and other transcription-relevant –omics data. Functional validation will be performed for TFs that have been implicated in transcriptional control during erythropoiesis based on our recent results. The approach is innovative because it uses a novel combination of single cell and bulk proteomics methodologies to quantify large numbers of TFs during erythropoiesis in primary human cells and uses the data for integrative TRN m...