4.4 Article

Genetic regulatory networks programming hematopoietic stem cells and erythroid lineage specification

期刊

DEVELOPMENTAL BIOLOGY
卷 294, 期 2, 页码 525-540

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ydbio.2006.02.051

关键词

stem cell; transcriptional regulatory network; network motif; blood; hematopoiesis; erythroid lineage

资金

  1. Medical Research Council [MC_U137981013] Funding Source: Medline
  2. Medical Research Council [MC_U137981013] Funding Source: researchfish
  3. MRC [MC_U137981013] Funding Source: UKRI

向作者/读者索取更多资源

Erythroid cell production results from passage through cellular hierarchies dependent on differential gene expression under the control of transcription factors responsive to changing niches. We have constructed Genetic Regulatory Networks (GRNs) describing this process, based predominantly on mouse data. Regulatory network motifs identified in E. coli and yeast GRNs are found in combination in these GRNs. Feed-forward motifs with autoregulation generate for-ward momentum and also control its rate, which is at its lowest in hematopoietic stem cells (HSCs). The simultaneous requirement for multiple regulators in multi-input motifs (MIMs) provides tight control over expression of target genes. Combinations of MIMs, exemplified by the SCL/LMO2 complexes, which have variable content and binding sites, explain how individual regulators can have different targets in HSCs and crythroid cells and possibly also how HSCs maintain stem cell functions while expressing lineage-affiliated genes at low level, so-called multi-lineage priming. MIMs combined with cross-antagonism describe the relationship between PU.1 and GATA-I and between two of their target genes, Fli-1 and EKLF, with victory for GATA-I and EKLF leading to erythroid lineage specification. These GRNs are useful repositories for current regulatory information, are accessible in interactive form via the internet, enable the consequences of perturbation to be predicted, and can act as seed networks to organize the rapidly accumulating microarray data. (c) 2006 Elsevier Inc. All rights reserved.

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