Reconstruction of dynamic regulatory networks reveals signaling-induced topology changes associated with germ layer specification
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA736973 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14788911_1.fastq.gz | Fastqsanger.gz | |||
| SRR14788911_2.fastq.gz | Fastqsanger.gz | |||
| SRR14788912_1.fastq.gz | Fastqsanger.gz | |||
| SRR14788912_2.fastq.gz | Fastqsanger.gz |
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Project description:Elucidating regulatory relationships between transcription factors (TFs) and target genes is fundamental to understanding how cells control their identity and behavior. To overcome the limited scope and scalability of experimental methods in mapping this control, computational GRN reconstruction methods have been developed to infer relationships from transcriptomic data. We developed a new computational GRN reconstruction tool called Epoch, which takes advantage of single-cell RNA sequencing to address a number of shortcomings of existing tools including low precision, low sensitivity, and the limited ability to describe network topology changes over time. We used Epoch to identify the dynamic networks and key transcriptional regulators underpinning directed differentiation of mouse embryonic stem cells, and further demonstrate that modulating signaling pathways drives topological network changes that shape cell fate potential. By integrating signaling pathways with GRN structures, we traced how Wnt activation and PI3K suppression govern mesoderm and endoderm specification, respectively.
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2010-05-19 | E-GEOD-17983 | biostudies-arrayexpress
Project description:Elucidating regulatory relationships between transcription factors (TFs) and target genes is fundamental to understanding how cells control their identity and behavior. Unfortunately, existing computational gene regulatory network (GRN) reconstruction methods are imprecise, computationally burdensome, and fail to reveal dynamic regulatory topologies. Here, we present Epoch, a reconstruction tool that uses single-cell transcriptomics to accurately infer dynamic networks. We apply Epoch to identify the dynamic networks underpinning directed differentiation of mouse embryonic stem cells (ESCs) guided by multiple signaling pathways, and we demonstrate that modulating these pathways drives topological changes that bias cell fate potential. We also find that Peg3 rewires the pluripotency network to favor mesoderm specification. By integrating signaling pathways with GRNs, we trace how Wnt activation and PI3K suppression govern mesoderm and endoderm specification, respectively. Finally, we identify regulatory circuits of patterning and axis formation that distinguish in vitro and in vivo mesoderm specification.
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