We used a model system to examine the changes in the state of the erythroid transcriptome between stages corresponding to late CFU-e through basophilic erythroblasts. Our model system employed an erythroid-committed GATA-1 null murine cell line, G1E cells. To trigger simultaneous differentiation, we used a subclone in which the key erythroid transcription factor GATA-1 could be functionally activated by addition of estradiol. A second goal of this project was to identify additional GATA-1 regulated erythroid genes. In the past, we have used this model system to identify other GATA-1 regulated genes with important roles in heme synthesis and hemoglobin metabolism. Using a microarray-based approach, we are pursuing this strategy in a more comprehensive manner. As other erythroid trancriptome and proteome analyses become available, we are hopeful that the G1E dataset can be used as a scaffold for the alignment of these datasets. Features common to these models will help distinguish genes relevant for acquisition of the erythroid phenotype.
G1E-ER4 cells growing in log phase were treated with 10-7M estradiol, and allowed to differentiate for various amounts of time, ranging between 3 and 30 hours. At these time points, cells were harvested, stained for hemoglobin (benzidine stain) and morphology (May-Grunwald stain) and RNA was collected. This RNA was processed into a form which could be used to interrogate an Affymetrix MG-U74Av2 Murine GeneChip. This experiment was repeated three time for statistical purposes.
The GeneChip has about 12,500 probesets; half of which correspond to known genes and half to ESTs. After hybridization, the data were analyzed using Affymetrix MAS 5.0 software, dCHIP, and GeneCluster, as well as manually in a spreadsheet. Using PERL scripts and the genbank acession numbers provided by Affymetrix for each probeset, data were extracted from Unigene, GO and other databases to associate each probeset with functional data. Genes which underwent a two-fold induction, were considered present in at least one sample, and reached an average (of triplicates) signal value of at least 100 at leats one time point, were manually reviewed as well. The data and annotations were collected into a Microsoft Access database to facilitate analysis.
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