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A HaemAtlas: characterizing gene expression in differentiated human blood cells

2009; Elsevier BV; Volume: 113; Issue: 19 Linguagem: Inglês

10.1182/blood-2008-06-162958

1528-0020

Nicholas A. Watkins, Arief Gusnanto, Bernard de Bono, Subhajyoti De, Diego Miranda‐Saavedra, Debbie L. Hardie, Will Angenent, Antony Attwood, Peter Ellis, Wendy N. Erber, Nicola Foad, Stephen F. Garner, Clare M. Isacke, Jennifer Jolley, Kerstin Koch, Iain C. Macaulay, Sarah L. Morley, Augusto Rendon, Kate Rice, Niall Taylor, Daphne C. Thijssen‐Timmer, Marloes R. Tijssen, C. Ellen van der Schoot, Lorenz Wernisch, Thilo Winzer, Frank Dudbridge, Christopher D. Buckley, Cordelia F. Langford, Sarah A. Teichmann, Berthold Göttgens, Willem H. Ouwehand,

Acute Myeloid Leukemia Research

Abstract Hematopoiesis is a carefully controlled process that is regulated by complex networks of transcription factors that are, in part, controlled by signals resulting from ligand binding to cell-surface receptors. To further understand hematopoiesis, we have compared gene expression profiles of human erythroblasts, megakaryocytes, B cells, cytotoxic and helper T cells, natural killer cells, granulocytes, and monocytes using whole genome microarrays. A bioinformatics analysis of these data was performed focusing on transcription factors, immunoglobulin superfamily members, and lineage-specific transcripts. We observed that the numbers of lineage-specific genes varies by 2 orders of magnitude, ranging from 5 for cytotoxic T cells to 878 for granulocytes. In addition, we have identified novel coexpression patterns for key transcription factors involved in hematopoiesis (eg, GATA3-GFI1 and GATA2-KLF1). This study represents the most comprehensive analysis of gene expression in hematopoietic cells to date and has identified genes that play key roles in lineage commitment and cell function. The data, which are freely accessible, will be invaluable for future studies on hematopoiesis and the role of specific genes and will also aid the understanding of the recent genome-wide association studies.