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Dynamic Gene Regulatory Networks Drive Hematopoietic Specification and Differentiation.

Published version
Peer-reviewed

Repository DOI


Type

Article

Change log

Authors

Goode, Debbie K 
Obier, Nadine 
Vijayabaskar, MS 
Lie-A-Ling, Michael 
Lilly, Andrew J 

Abstract

Metazoan development involves the successive activation and silencing of specific gene expression programs and is driven by tissue-specific transcription factors programming the chromatin landscape. To understand how this process executes an entire developmental pathway, we generated global gene expression, chromatin accessibility, histone modification, and transcription factor binding data from purified embryonic stem cell-derived cells representing six sequential stages of hematopoietic specification and differentiation. Our data reveal the nature of regulatory elements driving differential gene expression and inform how transcription factor binding impacts on promoter activity. We present a dynamic core regulatory network model for hematopoietic specification and demonstrate its utility for the design of reprogramming experiments. Functional studies motivated by our genome-wide data uncovered a stage-specific role for TEAD/YAP factors in mammalian hematopoietic specification. Our study presents a powerful resource for studying hematopoiesis and demonstrates how such data advance our understanding of mammalian development.

Description

Keywords

Animals, Cell Differentiation, Cell Lineage, Embryonic Stem Cells, Gene Expression Regulation, Developmental, Gene Regulatory Networks, Hematopoiesis, Hematopoietic Stem Cells, Homeodomain Proteins, Mice, Protein Binding, Transcription Factors

Journal Title

Dev Cell

Conference Name

Journal ISSN

1534-5807
1878-1551

Volume Title

36

Publisher

Elsevier BV
Sponsorship
Cancer Research Uk (None)
Biotechnology and Biological Sciences Research Council (BB/I00050X/1)
Leukemia & Lymphoma Society (7001-12)
Leukaemia & Lymphoma Research (12029)
Wellcome Trust (097922/Z/11/Z)
Medical Research Council (MC_PC_12009)
This work was funded by a Longer Larger (LoLa) consortium grant from the Biotechnology and Biological Sciences Research Council, UK, to the senior authors and the corresponding author, computing infrastructure grants from the Wellcome Trust and National Institute for Health Research to B.G., grants from Cancer Research UK to G.L. and V.K., and funding from the Bloodwise charity to C.B.