bioRxivDevelopmental Biology
Transcriptional regulatory network controlling the ontogeny of hematopoietic stem cells
Peng GaoiD, Changya CheniD, Elizabeth D. HowelliD, Yan LiiD, Joanna M. ToberiD, Yasin UzuniD, Bing HeiD, Long GaoiD, Qin ZhuiD, Arndt F. SiekmanniD, Nancy A. SpeckiD, Kai TaniD
Abstract
Hematopoietic stem cell (HSC) ontogeny is accompanied by dynamic changes in gene regulatory networks. We performed RNA-Seq and histone mark ChIP-Seq to define the transcriptomes and epigenomes of cells representing key developmental stages of HSC ontogeny in the mouse. The five populations analyzed were embryonic day 10.5 (E10.5) endothelium and hemogenic endothelium from the major arteries (dorsal aorta, umbilical and vitelline), an enriched population of pre-hematopoietic stem cells (pre-HSCs), fetal liver HSCs, and adult bone marrow HSCs. We observed dynamic and combinatorial epigenetic changes that mark regulatory DNA sequences including gene promoters and enhancers. Using epigenetic signatures, we identified enhancers for each developmental stage. Only 12% of enhancers are primed, and 78% are active, suggesting the vast majority of enhancers are established de novo at the developmental stages where they are required to control their target genes, without prior priming in earlier stages. We constructed developmental-stage-specific transcriptional regulatory networks during HSC ontogeny by linking enhancers and predicted bound transcription factors to their target promoters using a novel computational algorithm. Our computational analyses predicted known transcriptional regulators for the endothelial-to-hematopoietic transition, validating our overall approach, and identified putative novel transcription factors whose regulon activities correlate with the emergence of pre-HSCs. We validated roles for the broadly expressed transcription factors SP3 and MAZ in arterial hemogenic endothelium. Our data and computational analyses provide a useful resource for uncovering regulators of HSC formation.
- organism: mouse
- assay: bulk RNA-seq
- assay: ChIP-seq
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 49
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