Although less than 15% of the potential interactions were realized, the network

Likewise, the targeted disruption of the cytokine erythropoietin and its receptor have revealed an essential role for this pathway in the synthesis of definitive erythrocytes. This is not the case for primitive erythropoiesis, where a reduced population KU-0063794 938440-64-3 of primitive erythroblasts continues to mature in the bloodstream of Epo and Epor deficient embryos. Our goal is to utilize knowledge of definitive erythro poiesis to gain further insight into the mechanisms that regulate primitive erythroid maturation and to identify factors that may distinguish the maturation of these two distinct, but closely related erythroid lineages. We employ a network based systems approach to infer lineage specific transcriptional regulatory networks from annotated micro array expression data.

These data were obtained from primitive erythroid, fetal definitive erythroid and adult definitive erythroid cells isolated from mouse embryos, fetuses, and adult bone marrow, respectively. Five in dependent samples of primary erythroid precursors at three progressive stages of maturation, as well as reticulocytes, were purified by flow cy tometry and used for Lenalidomide 404950-80-7 the analysis of global gene expression on an Affymetrix platform. Gene interaction networks inferred from patterns of co expression have become increasingly popular tools for exploring gene function in biological systems. Such analyses have largely focused on identifying functionally enriched integrated sub networks of co expressed genes representing coherent functional units or biological pathways.

However, the architecture of an inter action network LY2603618 分子量 also provides insight into specific gene essentiality in the modeled system. In particular, the topological prominence of a gene or protein in an inter action network may reflect its biological role, although the association between specific measures of topology and es sentiality likely varies. Here, we applied a three stage semi supervised ma chine learning algorithm to estimate gene essentiality during erythroid precursor maturation. We employed the well characterized transcriptional control of defini tive erythropoiesis to identify topological features of in ferred transcriptional regulatory networks and patterns of gene expression during erythroid precursor matur ation that characterize known key regulators of red cell differentiation.

Using these features, we predicted poten tial regulators of primitive versus definitive erythropoiesis and these predictions were then validated experimentally. Taken together, our data indicate that differential STAT signaling plays an important role in the regulation of primitive compared to definitive erythropoiesis. Results We identified 1,080 potential transcriptional regulators expressed in the microarray expression dataset of eryth roid cells using Gene Ontology annotations. Of this set of potential key factors, 16 were known to play either essential or non essential roles in the regulation of adult definitive erythro poiesis and were used as a reference dataset for training the machine learning algorithm. Lineage specific regulatory networks were assembled by integrating factor co expression and computational predictions of TF binding based on sequence similarity.