Literature DB >> 16755218

Global genetic regulatory networks controlling hematopoietic cell fates.

Matthew Loose1, Roger Patient.   

Abstract

PURPOSE OF REVIEW: The gene expression profile of a cell is a consequence of transcription factor activities, which, in turn, are controlled by extra-cellular signals. The relationships between all these regulators constitute a genetic regulatory network, which can be used to predict the behavior of the cell in changing environments. We outline the progress being made to identify Genetic Regulatory Networks for hematopoiesis, using gene-by-gene approaches or emerging genomic technologies. RECENT
FINDINGS: The construction of genetic regulatory networks for single and multicellular organisms has inspired the building of genetic regulatory networks for erythropoiesis and B-cell differentiation. genetic regulatory networks are 'scale-free', whereby some genes have many connections while others have very few. The well connected genes, or hubs, correspond to master regulators of the networks, acting to integrate signals and control the sequential passage of the cells through the differentiation process. Lineage decisions are governed by cross-antagonism between two hubs. Large datasets from genome-wide analyses support the concept of multilineage priming and will increasingly refine the network topologies.
SUMMARY: As the underlying genetic regulatory networks for hematopoiesis continue to emerge, the program for lineage choice and differentiation will be revealed. More large-scale datasets identifying network components are needed alongside continued gene-by-gene analyses.

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Mesh:

Year:  2006        PMID: 16755218     DOI: 10.1097/01.moh.0000231419.15654.7f

Source DB:  PubMed          Journal:  Curr Opin Hematol        ISSN: 1065-6251            Impact factor:   3.284


  11 in total

Review 1.  Role of helix-loop-helix proteins during differentiation of erythroid cells.

Authors:  Archana Anantharaman; I-Ju Lin; Joeva Barrow; Shermi Y Liang; Jude Masannat; John Strouboulis; Suming Huang; Jörg Bungert
Journal:  Mol Cell Biol       Date:  2011-01-31       Impact factor: 4.272

2.  Epigenetic characterization of hematopoietic stem cell differentiation using miniChIP and bisulfite sequencing analysis.

Authors:  Joanne L Attema; Peter Papathanasiou; E Camilla Forsberg; Jian Xu; Stephen T Smale; Irving L Weissman
Journal:  Proc Natl Acad Sci U S A       Date:  2007-07-18       Impact factor: 11.205

3.  Mathematical modelling of stem cell differentiation: the PU.1-GATA-1 interaction.

Authors:  Campbell Duff; Kate Smith-Miles; Leo Lopes; Tianhai Tian
Journal:  J Math Biol       Date:  2011-04-02       Impact factor: 2.259

4.  Global transcriptome analyses of human and murine terminal erythroid differentiation.

Authors:  Xiuli An; Vincent P Schulz; Jie Li; Kunlu Wu; Jing Liu; Fumin Xue; Jingping Hu; Narla Mohandas; Patrick G Gallagher
Journal:  Blood       Date:  2014-03-17       Impact factor: 22.113

5.  Global transcriptome analysis for identification of interactions between coding and noncoding RNAs during human erythroid differentiation.

Authors:  Nan Ding; Jiafei Xi; Yanming Li; Xiaoyan Xie; Jian Shi; Zhaojun Zhang; Yanhua Li; Fang Fang; Sihan Wang; Wen Yue; Xuetao Pei; Xiangdong Fang
Journal:  Front Med       Date:  2016-06-06       Impact factor: 4.592

6.  Gpr171, a putative P2Y-like receptor, negatively regulates myeloid differentiation in murine hematopoietic progenitors.

Authors:  Lara Rossi; Roberto M Lemoli; Margaret A Goodell
Journal:  Exp Hematol       Date:  2012-09-25       Impact factor: 3.084

7.  NRF2 modulates aryl hydrocarbon receptor signaling: influence on adipogenesis.

Authors:  Soona Shin; Nobunao Wakabayashi; Vikas Misra; Shyam Biswal; Gum Hwa Lee; Elin S Agoston; Masayuki Yamamoto; Thomas W Kensler
Journal:  Mol Cell Biol       Date:  2007-08-20       Impact factor: 4.272

8.  Computational Modeling of a Transcriptional Switch Underlying B-Lymphocyte Lineage Commitment of Hematopoietic Multipotent Cells.

Authors:  Luca Salerno; Carlo Cosentino; Giovanni Morrone; Francesco Amato
Journal:  PLoS One       Date:  2015-07-13       Impact factor: 3.240

9.  Computational modeling of the hematopoietic erythroid-myeloid switch reveals insights into cooperativity, priming, and irreversibility.

Authors:  Vijay Chickarmane; Tariq Enver; Carsten Peterson
Journal:  PLoS Comput Biol       Date:  2009-01-23       Impact factor: 4.475

10.  Genomic expression during human myelopoiesis.

Authors:  Francesco Ferrari; Stefania Bortoluzzi; Alessandro Coppe; Dario Basso; Silvio Bicciato; Roberta Zini; Claudia Gemelli; Gian Antonio Danieli; Sergio Ferrari
Journal:  BMC Genomics       Date:  2007-08-03       Impact factor: 3.969

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