Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of human erythroid cell differentiation

ABSTRACT: Human mononuclear cells were cultured in 2 phases. In the 1st phase the culture medium contained cyclosporine A the 2nd phase contained SCF and erythropoietin. Cells were collected at 3 stages of differentiation; on day 6, 10, 12 and represented early erythroblasts, medium stage and normoblasts. Experiment Overall Design: RNA was extracted from each sample of cells at a different stage of differentiation and subjected to microarray studies in duplicates.

ORGANISM(S): Homo sapiens

SUBMITTER: Yuval Tabach

PROVIDER: E-GEOD-12407 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Identification of gene networks associated with erythroid differentiation.

Peller Shoshana S Tabach Yuval Y Rotschild Miri M Garach-Joshua Osnat O Cohen Yosef Y Goldfinger Naomi N Rotter Varda V

Blood cells, molecules & diseases 20090328 1

Erythropoiesis is a multistep process involving a large number of genes, which balance between proliferation, differentiation and survival of the erythroid cells. To understand the molecular mechanisms of erythropoiesis and related pathological aberrations, we analyzed three stages of in vitro differentiating human erythroid cells by expression profiling. We identified distinct clusters of genes, each with a unique expression pattern during differentiation. As JAK2 was shown to play a central ro ...[more]

PMID: 19329339

Similar Datasets

Project description:Understanding the pattern of gene expression and identifying the specific genes expressed during erythropoiesis is crucial for a synthesis of erythroid developmental biology. Here we have isolated four distinct populations of erythroblasts at successive erythropoietin-dependent stages of erythropoiesis including the terminal, pyknotic stage. The transcriptome has been determined using Affymetrix arrays. First, we show that cells sorted by surface expression profile express not only significantly fewer genes than unsorted cells, but also significantly more differences in the expression levels of particular genes between stages than unsorted cells, demonstrating the importance of working with defined cell populations to identify lineage and temporally-specific patterns of gene expression. Second, using standard software and matched filtering we identify eleven differentially regulated genes and one continuously expressed gene previously undetected in erythroid expression studies with unknown roles in erythropoiesis (CA3, CALB1, CTSL2, FKBP1B, GSDMB, ITLN1, LIN7B, RRAD, RUNDC3A, UNQ1887, ZNF805, MYL12B). Finally, using transcription factor binding site analysis we identify potential transcription factors that may regulate gene expression during terminal erythropoiesis. Our stringent lists of differentially regulated and continuously expressed transcripts are a resource for functional studies of erythropoietic protein function and gene regulation. PBMC-derived erythroblasts grown in vitro were harvested at the CFU-E, Pro-E, Int-E and Late-E stages and FACS sorted based on expression of cell surface markers. RNA was extracted from those populations which met rigorous specifications of time cultured in the presence of erythropoietin, morphology and CD36, CD71 and CD235a expression. For each stage, 3 chips were hybridised, each representing a pool of 4 different samples. In addition to these 12 chips, one chip representing a pool of RNA extracted from unsorted cells at each stages was also hybridised.

Dataset Information

Transcription profiling of human erythroid cell differentiation

Publications

Identification of gene networks associated with erythroid differentiation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets