Evidence map›Paper›PMID 26033487›Full record

ArticleBMC systems biology2015

Increased robustness of early embryogenesis through collective decision-making by key transcription factors.

Ali Sharifi-Zarchi, Mehdi Totonchi, Keynoush Khaloughi, Razieh Karamzadeh, Marcos J Araúzo-Bravo, Hossein Baharvand, Ruzbeh Tusserkani, Hamid Pezeshk, Hamidreza Chitsaz, Mehdi Sadeghi

Abstract read
In one paragraph

Article in BMC systems biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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  8. Development and utilization of human decidualization reporter cell line uncovers new modulators of female fertility.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Ali Sharifi-ZarchiDepartment of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran. a.sharifi@ibb.ut.ac.ir.
Mehdi TotonchiDepartment of Stem Cells and Developmental Biology at Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran. totonchimehdi@gmail.com.
Keynoush KhaloughiDepartment of Stem Cells and Developmental Biology at Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran. keynoosh_khalooghi@yahoo.com.
Razieh KaramzadehDepartment of Stem Cells and Developmental Biology at Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran. razieh.karamzadeh@gmail.com.
Marcos J Araúzo-BravoComputational Biology and Bioinformatics Group, Max Planck Institute for Molecular Biomedicine, Münster, Germany. mararabra@yahoo.co.uk.
Hossein BaharvandDepartment of Stem Cells and Developmental Biology at Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran. Baharvand@royaninstitute.org.
Ruzbeh TusserkaniSchool of Computer Science, Institute for Research in Fundamental Sciences, Tehran, Iran. ruztus@yahoo.com.
Hamid PezeshkSchool of Mathematics, Statistics and Computer Sciences, Center of Excellence in Biomathematics, College of Science, University of Tehran, Tehran, Iran. pezeshk@khayam.ut.ac.ir.
Hamidreza ChitsazComputer Science Department, Colorado State University, Fort Collins, Colorado, 80523, USA. chitsaz@chitsazlab.org.
Mehdi SadeghiSchool of Biological Science, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran. sadeghi@nigeb.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUnderstanding the mechanisms by which hundreds of diverse cell types develop from a single mammalian zygote has been a central challenge of developmental biology. Conrad H. Waddington, in his metaphoric "epigenetic landscape" visualized the early embryogenesis as a hierarchy of lineage bifurcations. In each bifurcation, a single progenitor cell type produces two different cell lineages. The tristable dynamical systems are used to model the lineage bifurcations. It is also shown that a genetic circuit consisting of two auto-activating transcription factors (TFs) with cross inhibitions can form a tristable dynamical system.

resultsWe used gene expression profiles of pre-implantation mouse embryos at the single cell resolution to visualize the Waddington landscape of the early embryogenesis. For each lineage bifurcation we identified two clusters of TFs - rather than two single TFs as previously proposed - that had opposite expression patterns between the pair of bifurcated cell types. The regulatory circuitry among each pair of TF clusters resembled a genetic circuit of a pair of single TFs; it consisted of positive feedbacks among the TFs of the same cluster, and negative interactions among the members of the opposite clusters. Our analyses indicated that the tristable dynamical system of the two-cluster regulatory circuitry is more robust than the genetic circuit of two single TFs.

conclusionsWe propose that a modular hierarchy of regulatory circuits, each consisting of two mutually inhibiting and auto-activating TF clusters, can form hierarchical lineage bifurcations with improved safeguarding of critical early embryogenesis against biological perturbations. Furthermore, our computationally fast framework for modeling and visualizing the epigenetic landscape can be used to obtain insights from experimental data of development at the single cell resolution.

Indexed as

Embryonic DevelopmentModels, BiologicalAnimalsBlastocystGene Expression ProfilingMiceSingle-Cell AnalysisTranscription FactorsTranscription Factors

Identifiers

PMID26033487
PMCPMC4450992

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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.