AI Article Synopsis

  • Temporal data on gene expression and open chromatin states can enhance the identification of key transcription factors (TFs) and gene regulatory networks (GRNs) involved in cellular differentiation, despite the integration challenges.
  • The study introduces EPIC-DREM, a novel data-driven method that generates time-series profiles from mouse multipotent bone marrow stromal cells (ST2) differentiating into adipocytes and osteoblasts, allowing for the construction of time-resolved GRNs for both cell types.
  • The approach identified AHR and GLIS1 as crucial mesenchymal TFs, regulated by dynamic super-enhancers that suppress their expression during differentiation, indicating their role in controlling lineage commitment in ST2 cells.

Article Abstract

Temporal data on gene expression and context-specific open chromatin states can improve identification of key transcription factors (TFs) and the gene regulatory networks (GRNs) controlling cellular differentiation. However, their integration remains challenging. Here, we delineate a general approach for data-driven and unbiased identification of key TFs and dynamic GRNs, called EPIC-DREM. We generated time-series transcriptomic and epigenomic profiles during differentiation of mouse multipotent bone marrow stromal cell line (ST2) toward adipocytes and osteoblasts. Using our novel approach we constructed time-resolved GRNs for both lineages and identifed the shared TFs involved in both differentiation processes. To take an alternative approach to prioritize the identified shared regulators, we mapped dynamic super-enhancers in both lineages and associated them to target genes with correlated expression profiles. The combination of the two approaches identified aryl hydrocarbon receptor (AHR) and Glis family zinc finger 1 (GLIS1) as mesenchymal key TFs controlled by dynamic cell type-specific super-enhancers that become repressed in both lineages. AHR and GLIS1 control differentiation-induced genes and their overexpression can inhibit the lineage commitment of the multipotent bone marrow-derived ST2 cells.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6380961PMC
http://dx.doi.org/10.1093/nar/gky1240DOI Listing

Publication Analysis

Top Keywords

ahr glis1
8
identification key
8
key tfs
8
multipotent bone
8
temporal enhancer
4
enhancer profiling
4
profiling parallel
4
lineages
4
parallel lineages
4
lineages identifies
4

Similar Publications

Mechanism of transforming growth factor-1 induce renal fibrosis based on transcriptome sequencing analysis.

Zhejiang Da Xue Xue Bao Yi Xue Ban

September 2023

Department of Cell Biology, School of Medicine, Yangzhou University, Jiangsu Key Laboratory of Integrated Traditional Chinese and Western Medicine for Prevention and Treatment of Senile Diseases, Yangzhou 225009, Jiangsu Province, China.

Objectives: To explore the mechanism of transforming growth factor-β1 (TGF-β1) induce renal fibrosis.

Methods: Renal fibroblast NRK-49F cells treated with and without TGF-β1 were subjected to RNA-seq analysis. DESeq2 was used for analysis.

View Article and Find Full Text PDF
Article Synopsis
  • Temporal data on gene expression and open chromatin states can enhance the identification of key transcription factors (TFs) and gene regulatory networks (GRNs) involved in cellular differentiation, despite the integration challenges.
  • The study introduces EPIC-DREM, a novel data-driven method that generates time-series profiles from mouse multipotent bone marrow stromal cells (ST2) differentiating into adipocytes and osteoblasts, allowing for the construction of time-resolved GRNs for both cell types.
  • The approach identified AHR and GLIS1 as crucial mesenchymal TFs, regulated by dynamic super-enhancers that suppress their expression during differentiation, indicating their role in controlling lineage commitment in ST2 cells.
View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!