A HaemAtlas: characterizing gene expression in differentiated human blood cells

Harvard | Vancouver

Watkins, NA, Gusnanto, A, de Bono, B, De, S, Miranda-Saavedra, D, Hardie, DL, Angenent, WGJ, Attwood, AP, Ellis, PD, Erber, W, Foad, NS, Garner, SF, Isacke, CM, Jolley, J, Koch, K, Macaulay, IC, Morley, SL, Rendon, A, Rice, KM, Taylor, N, Thijssen-Timmer, DC, Tijssen, MR, van der Schoot, CE, Wernisch, L, Winzer, T, Dudbridge, F, Buckley, CD, Langford, CF, Teichmann, S, Göttgens, B and Ouwehand, WH. 2009. A HaemAtlas: characterizing gene expression in differentiated human blood cells. [Online]. London School of Hygiene & Tropical Medicine, London, United Kingdom. Available from: http://datacompass.lshtm.ac.uk/45/ http://dx.doi.org/10.1182/blood-2008-06-162958

Export Citation

Sharing

Description

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.

Published in a 3rd party system Date: 7 May 2009
Data capture method:
Mode of data capture
Other
Data Creators(s): Watkins, NA, Gusnanto, A, de Bono, B, De, S, Miranda-Saavedra, D, Hardie, DL, Angenent, WGJ, Attwood, AP, Ellis, PD, Erber, W, Foad, NS, Garner, SF, Isacke, CM, Jolley, J, Koch, K, Macaulay, IC, Morley, SL, Rendon, A, Rice, KM, Taylor, N, Thijssen-Timmer, DC, Tijssen, MR, van der Schoot, CE, Wernisch, L, Winzer, T, Dudbridge, F, Buckley, CD, Langford, CF, Teichmann, S, Göttgens, B and Ouwehand, WH
LSHTM Faculty/Department: Faculty of Epidemiology and Population Health > Dept of Non-Communicable Disease Epidemiology
Participating Institutions: University of Cambridge, Institute of Public Health, European Bioinformatics Institute, Laboratory of Molecular Biology, University of Birmingham, Wellcome Trust Sanger Institute, Cambridge University Hospitals National Health Service Foundation Trust, Institute of Cancer Research, University of Amsterdam

Files

Data

Related resources

LSHTM Open Access publications:

Resources

Actions

Edit Item Edit Item (admin only)