title: Transcriptional regulatory network analysis of developing human erythroid progenitors reveals patterns of coregulation and potential transcriptional regulators.
abstract: Deciphering the molecular basis for human erythropoiesis should yield information benefiting studies of the hemoglobinopathies and other erythroid disorders. We used an in vitro erythroid differentiation system to study the developing red blood cell transcriptome derived from adult CD34+ hematopoietic progenitor cells. mRNA expression profiling was used to characterize developing erythroid cells at six time points during differentiation (days 1, 3, 5, 7, 9, and 11). Eleven thousand seven hundred sixty-three genes (20,963 Affymetrix probe sets) were expressed on day 1, and 1,504 genes, represented by 1,953 probe sets, were differentially expressed (DE) with 537 upregulated and 969 downregulated. A subset of the DE genes was validated using real-time RT-PCR. The DE probe sets were subjected to a cluster metric and could be divided into two, three, four, five, or six clusters of genes with different expression patterns in each cluster. Genes in these clusters were examined for shared transcription factor binding sites (TFBS) in their promoters by comparing enrichment of each TFBS relative to a reference set using transcriptional regulatory network analysis. The sets of TFBS enriched in genes up- and downregulated during erythropoiesis were distinct. This analysis identified transcriptional regulators critical to erythroid development, factors recently found to play a role, as well as a new list of potential candidates, including Evi-1, a potential silencer of genes upregulated during erythropoiesis. Thus this transcriptional regulatory network analysis has yielded a focused set of factors and their target genes whose role in differentiation of the hematopoietic stem cell into distinct blood cell lineages can be elucidated.
authors.affiliation: Cardeza Foundation of Hematologic Research, Jefferson Medical College, Philadelphia, Pennsylvania 19107, USA.
authors.forename: M A
authors.initials: MA
authors.lastname: Keller
authors.forename: S
authors.initials: S
authors.lastname: Addya
authors.forename: R
authors.initials: R
authors.lastname: Vadigepalli
authors.forename: B
authors.initials: B
authors.lastname: Banini
authors.forename: K
authors.initials: K
authors.lastname: Delgrosso
authors.forename: H
authors.initials: H
authors.lastname: Huang
authors.forename: S
authors.initials: S
authors.lastname: Surrey
mesh_terms: D018952:Antigens, CD34 / Q000378:metabolism; D002454:Cell Differentiation; D002478:Cells, Cultured; D016000:Cluster Analysis; D015536:Down-Regulation; D015672:Erythroid Precursor Cells / Q000378:metabolism*; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D005914:Globins / Q000378:metabolism; D006801:Humans; D008954:Models, Biological; D011485:Protein Binding; D012333:RNA, Messenger / Q000378:metabolism; D014157:Transcription Factors / Q000378:metabolism*; D014158:Transcription, Genetic
chemical_list: D018952:Antigens, CD34; D012333:RNA, Messenger; D014157:Transcription Factors; D005914:Globins