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Background  Hematopoietic ontogeny is characterized by overlapping waves of primitive, fetal definitive, and adult definitive erythroid lineages. Our aim is to identify differences in the transcriptional control of these distinct erythroid cell maturation pathways by inferring and analyzing gene-interaction networks from lineage-specific expression datasets. Inferred networks are strongly connected and do not fit a scale-free model, making it difficult to identify essential regulators using the hub-essentiality standard.    Results  We employed a semi-supervised machine learning approach to integrate measures of network topology with expression data to score gene essentiality. The algorithm was trained and tested on the adult and fetal definitive erythroid lineages. When applied to the primitive erythroid lineage, 144 high scoring transcription factors were found to be differentially expressed between the primitive and adult definitive erythroid lineages, including all expressed STAT-family members. Differential responses of primitive and definitive erythroblasts to a  Stat3  inhibitor and IFNγ  in vitro  supported the results of the computational analysis. Further investigation of the original expression data revealed a striking signature of  Stat1 -related genes in the adult definitive erythroid network. Among the potential pathways known to utilize  Stat1 , interferon (IFN) signaling-related genes were expressed almost exclusively within the adult definitive erythroid network.    Conclusions   In vitro  results support the computational prediction that differential regulation and downstream effectors of STAT signaling are key factors that distinguish the transcriptional control of primitive and definitive erythroid cell maturation.

Stat and interferon genes identified by network analysis differentially regulate primitive and definitive erythropoiesis