Computational modeling and analysis of the morphogenetic domain signaling networks regulating C. elegans embryogenesis

Ben Niu*, Thao Nguyen Bach, Xingyu Chen, Khyati Raghunath Chandratre, John Isaac Murray, Zhongying Zhao, Michael Zhang*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review


Caenorhabditis elegans, often referred to as the ‘roundworm’, provides a powerful model for studying cell autonomous and cell–cell interactions through the direct observation of embryonic development in vivo. By leveraging the precisely mapped cell lineage at single cell resolution, we are able to study at a systems level how early embryonic cells communicate across morphogenetic domains for the coordinated processes of gene expressions and collective cellular behaviors that regulate tissue morphogenesis. In this study, we developed a computational framework for the exploration of the morphogenetic domain cell signaling networks that may regulate C. elegans gastrulation and embryonic organogenesis. We demonstrated its utility by producing the following results, i) established a virtual reference model of developing C. elegans embryos through the spatiotemporal alignment of individual embryo cell nuclear imaging samples; ii) integrated the single cell spatiotemporal gene expression profile with the established virtual embryo model by data pooling; iii) trained a Machine Learning model (Random Forest Regression), which predicts accurately the spatial positions of the cells given their gene expression profiles for a given developmental time (e.g. total cell number of the embryo); iv) enabled virtual 4-dimensional tomographic graphical modeling of single cell data; v) inferred the biology signaling pathways that act in each of morphogenetic domains by meta-data analysis. It is intriguing that the morphogenetic domain cell signaling network seems to involve some crosstalk of multiple biology signaling pathways during the formation of tissue boundary pattern. Lastly, we developed the Software tool ‘Embryo aligner version 1.0’ and provided it as an Open Source program to the research community for virtual embryo modeling, and phenotype perturbation analyses ( and

Original languageEnglish
Pages (from-to)3653-3666
Number of pages14
JournalComputational and Structural Biotechnology Journal
Early online date8 Jun 2022
Publication statusPublished - 12 Jul 2022

Scopus Subject Areas

  • Biotechnology
  • Biophysics
  • Structural Biology
  • Biochemistry
  • Genetics
  • Computer Science Applications

User-Defined Keywords

  • Collective cell behavior
  • Computational image analysis
  • Machine learning
  • Morphogenetic domain cell signaling network
  • Single cell gene expression modeling


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