• Home
  • About
  • Repositories
  • Search
  • Web API
  • Feedback
<< Go Back

Metadata

Name
A Bach2-Cebp gene regulatory network for the commitment of multipotent hematopoietic progenitors [ChIP-seq]
Repository
Gene Expression Omnibus
Identifier
geo.series:GSE87503
Description
The commitment of hematopoietic stem cells and multipotent progenitors (MPPs) can be tuned to reprogram their differentiation capacity to be biased toward myeloid cells in response to an infection. Bach2, which inhibits myeloid differentiation in common lymphoid progenitors, repressed a cohort of genes of myeloid function (myeloid genes) and activated those for lymphoid function (lymphoid genes) in MPPs. In addition, Bach2 repressed both Cebpb and its target Csf1, encoding C/EBP? and macrophage colony-stimulating factor (M-CSF), respectively, whereas C/EBP? repressed Bach2 and activated the M-CSF receptor gene Csf1r. Bach2 and C/EBP? bound to overlapping regulatory regions of their myeloid target genes, suggesting the presence of a gene regulatory network (GRN) with mutual repression and antagonistic, feed-forward regulation of myeloid genes. Lipopolysaccharide reduced the expression of Bach2, resulting in enhanced myeloid differentiation. Bach2 tunes the commitment of multipotent progenitors to myeloid and lymphoid lineages under both normal and infectious conditions.
Data or Study Types
Genome binding/occupancy profiling by high throughput sequencing
Source Organization
National Center for Biotechnology Information
Access Conditions
available
Year
2017
Access Hyperlink
http://www.ncbi.nlm.nih.gov/sites/GDSbrowser?acc=GSE87503

Distributions

  • Encoding Format: Bioproject ; URL: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA344950
  • Encoding Format: TXT ; URL: ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE1nnn/GSE87503/matrix/
  • Encoding Format: MINiML ; URL: ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE1nnn/GSE87503/miniml/
  • Encoding Format: SOFT ; URL: ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE1nnn/GSE87503/soft/
This project was funded in part by grant U24AI117966 from the NIH National Institute of Allergy and Infectious Diseases as part of the Big Data to Knowledge program. We thank all members of the bioCADDIE community for their valuable input on the overall project.