ArticleNucleic acids research2020
Transcriptional network dynamics during the progression of pluripotency revealed by integrative statistical learning.
Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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Who cites it
11 citing papers in PubMed.
- Integration of the naive pluripotency gene network with the response to GSK3 inhibition by Tcf7l1-driven enhancer decommissioning.Stem cell reports · 2026Article
- CeSpGRN: inferring cell-specific gene regulatory networks from single-cell multi-omics and spatial data.Bioinformatics (Oxford, England) · 2026Article
- A cell type and state specific gene regulation network inference method for immune regulatory analysis.NPJ systems biology and applications · 2025Article
- Gene regulatory network reconstruction: harnessing the power of single-cell multi-omic data.NPJ systems biology and applications · 2023Review
- Rat epiblast-derived stem cells recapitulate the attributes of pre-gastrulation epiblast.Cell reports methods · 2023Article
- A multi-omics integrative analysis based on CRISPR screens re-defines the pluripotency regulatory network in ESCs.Communications biology · 2023Article
- Integrative analysis reveals histone demethylase LSD1 promotes RNA polymerase II pausing.iScience · 2022Article
- mRNA Translation Is Dynamically Regulated to Instruct Stem Cell Fate.Frontiers in molecular biosciences · 2022Review
- Dynamic regulatory networks of T cell trajectory dissect transcriptional control of T cell state transition.Molecular therapy. Nucleic acids · 2021Article
- Stress Decreases Host Viral Resistance and Increases Covid Susceptibility in Embryonic Stem Cells.Stem cell reviews and reports · 2021Article
- An Esrrb and Nanog Cell Fate Regulatory Module Controlled by Feed Forward Loop Interactions.Frontiers in cell and developmental biology · 2021Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
The developmental potential of cells, termed pluripotency, is highly dynamic and progresses through a continuum of naive, formative and primed states. Pluripotency progression of mouse embryonic stem cells (ESCs) from naive to formative and primed state is governed by transcription factors (TFs) and their target genes. Genomic techniques have uncovered a multitude of TF binding sites in ESCs, yet a major challenge lies in identifying target genes from functional binding sites and reconstructing dynamic transcriptional networks underlying pluripotency progression. Here, we integrated time-resolved 'trans-omic' datasets together with TF binding profiles and chromatin conformation data to identify target genes of a panel of TFs. Our analyses revealed that naive TF target genes are more likely to be TFs themselves than those of formative TFs, suggesting denser hierarchies among naive TFs. We also discovered that formative TF target genes are marked by permissive epigenomic signatures in the naive state, indicating that they are poised for expression prior to the initiation of pluripotency transition to the formative state. Finally, our reconstructed transcriptional networks pinpointed the precise timing from naive to formative pluripotency progression and enabled the spatiotemporal mapping of differentiating ESCs to their in vivo counterparts in developing embryos.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.