Divergence of gene regulatory network linkages during specification of ectoderm and mesoderm in early development of sea urchins

AbstractDevelopmental gene regulatory networks (GRNs) are assemblages of gene regulatory interactions that direct ontogeny of animal body plans. Studies of GRNs operating in early development of euechinoid sea urchins has revealed that little appreciable change has occurred since their divergence approximately 90 million years ago (mya). These observations suggest that strong conservation of GRN architecture has been maintained in early development of the sea urchin lineage. To test whether this is true for all sea urchins, comparative analyses of echinoid taxa that diverged deeper in geological time must be conducted. Recent studies highlighted extensive divergence of skeletogenic mesoderm specification in the sister clade of euechinoids, the cidaroids, suggesting that comparative analyses of cidaroid GRN architecture may confer a greater understanding of the evolutionary dynamics of developmental GRNs. Here, we report spatiotemporal patterning of 55 regulatory genes and perturbation analyses of key regulatory genes involved in euechinoid oral-aboral patterning of non-skeletogenic mesodermal and ectodermal domains in early development of the cidaroid Eucidaris tribuloides. Our results indicate that developmental GRNs directing mesodermal and ectodermal specification have undergone marked alterations since the divergence of cidaroids and euechinoids. Notably, statistical and clustering analyses of echinoid temporal gene expression datasets indicate that regulation of mesodermal genes has diverged more markedly than regulation of ectodermal genes. Although research on indirect-developing euechinoid sea urchins suggests strong conservation of GRN circuitry during early embryogenesis, this study indicates that since the divergence of cidaroids and euechinoids developmental GRNs have undergone significant divergence.

Divergence of ectodermal and mesodermal gene regulatory network linkages in early development of sea urchins

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1612820113 ◽

2016 ◽

Vol 113 (46) ◽

pp. E7202-E7211 ◽

Cited By ~ 6

Author(s):

Eric M. Erkenbrack

Keyword(s):

Early Development ◽

Regulatory Networks ◽

Evolutionary Dynamics ◽

Sea Urchins ◽

Regulatory Genes ◽

Geological Time ◽

Appreciable Change ◽

Comparative Analyses ◽

Developmental gene regulatory networks (GRNs) are assemblages of gene regulatory interactions that direct ontogeny of animal body plans. Studies of GRNs operating in the early development of euechinoid sea urchins have revealed that little appreciable change has occurred since their divergence ∼90 million years ago (mya). These observations suggest that strong conservation of GRN architecture was maintained in early development of the sea urchin lineage. Testing whether this holds for all sea urchins necessitates comparative analyses of echinoid taxa that diverged deeper in geological time. Recent studies highlighted extensive divergence of skeletogenic mesoderm specification in the sister clade of euechinoids, the cidaroids, suggesting that comparative analyses of cidaroid GRN architecture may confer a greater understanding of the evolutionary dynamics of developmental GRNs. Here I report spatiotemporal patterning of 55 regulatory genes and perturbation analyses of key regulatory genes involved in euechinoid oral–aboral patterning of nonskeletogenic mesodermal and ectodermal domains in early development of the cidaroid Eucidaris tribuloides. These results indicate that developmental GRNs directing mesodermal and ectodermal specification have undergone marked alterations since the divergence of cidaroids and euechinoids. Notably, statistical and clustering analyses of echinoid temporal gene expression datasets indicate that regulation of mesodermal genes has diverged more markedly than regulation of ectodermal genes. Although research on indirect-developing euechinoid sea urchins suggests strong conservation of GRN circuitry during early embryogenesis, this study indicates that since the divergence of cidaroids and euechinoids, developmental GRNs have undergone significant, cell type–biased alterations.

Evolution of abbreviated development in Heliocidaris erythrogramma dramatically re-wired the highly conserved sea urchin developmental gene regulatory network to decouple signaling center function from ultimate fate

10.1101/712216 ◽

2019 ◽

Author(s):

Allison Edgar ◽

Maria Byrne ◽

David R. McClay ◽

Gregory A. Wray

Keyword(s):

Early Development ◽

Regulatory Networks ◽

Molecular Mechanisms ◽

Sea Urchins ◽

Stabilizing Selection ◽

Developmental Gene ◽

Heliocidaris Erythrogramma ◽

Signaling Center ◽

Gene Regulatory ◽

Ultimate Fate

AbstractDevelopmental gene regulatory networks (GRNs) describe the interactions among gene products that drive the differential transcriptional and cell regulatory states that pattern the embryo and specify distinct cell fates. GRNs are often deeply conserved, but whether this is the product of constraint inherent to the network structure or stabilizing selection remains unclear. We have constructed the first formal GRN for early development in Heliocidaris erythrogramma, a species with dramatically accelerated, direct development. This life history switch has important ecological consequences, arose rapidly, and has evolved independently many times in echinoderms, suggesting it is a product of selection. We find that H. erythrogramma exhibits dramatic differences in GRN topology compared with ancestral, indirect-developing sea urchins. In particular, the GRN sub-circuit that directs the early and autonomous commitment of skeletogenic cell precursors in indirect developers appears to be absent in H. erythrogramma, a particularly striking change in relation to both the prior conservation of this sub-circuit and the key role that these cells play ancestrally in early development as the embryonic signaling center. These results show that even highly conserved molecular mechanisms of early development can be substantially reconfigured in a relatively short evolutionary time span, suggesting that selection rather than constraint is responsible for the striking conservation of the GRN among other sea urchins.

Faculty Opinions recommendation of Predicting gene regulatory networks by combining spatial and temporal gene expression data in Arabidopsis root stem cells.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.729074122.793536255 ◽

2017 ◽

Author(s):

Elena Alvarez-Buylla ◽

Monica Garcia

Keyword(s):

Gene Expression ◽

Stem Cells ◽

Gene Expression Data ◽

Regulatory Networks ◽

Expression Data ◽

Arabidopsis Root ◽

Automated Identification of Core Regulatory Genes in Human Gene Regulatory Networks

PLoS Computational Biology ◽

10.1371/journal.pcbi.1004504 ◽

2015 ◽

Vol 11 (9) ◽

pp. e1004504 ◽

Cited By ~ 19

Author(s):

Vipin Narang ◽

Muhamad Azfar Ramli ◽

Amit Singhal ◽

Pavanish Kumar ◽

Gennaro de Libero ◽

...

Keyword(s):

Regulatory Networks ◽

Human Gene ◽

Regulatory Genes ◽

Automated Identification ◽

Single Cell RNA-Seq and Machine Learning Reveal Novel Subpopulations in Low-Grade Inflammatory Monocytes With Unique Regulatory Circuits

Frontiers in Immunology ◽

10.3389/fimmu.2021.627036 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jiyoung Lee ◽

Shuo Geng ◽

Song Li ◽

Liwu Li

Keyword(s):

Machine Learning ◽

Regulatory Networks ◽

Regulatory Genes ◽

Low Grade ◽

Machine Learning Method ◽

Learning Method ◽

Cell Clusters ◽

Inflammatory Monocytes ◽

Subclinical doses of LPS (SD-LPS) are known to cause low-grade inflammatory activation of monocytes, which could lead to inflammatory diseases including atherosclerosis and metabolic syndrome. Sodium 4-phenylbutyrate is a potential therapeutic compound which can reduce the inflammation caused by SD-LPS. To understand the gene regulatory networks of these processes, we have generated scRNA-seq data from mouse monocytes treated with these compounds and identified 11 novel cell clusters. We have developed a machine learning method to integrate scRNA-seq, ATAC-seq, and binding motifs to characterize gene regulatory networks underlying these cell clusters. Using guided regularized random forest and feature selection, our method achieved high performance and outperformed a traditional enrichment-based method in selecting candidate regulatory genes. Our method is particularly efficient in selecting a few candidate genes to explain observed expression pattern. In particular, among 531 candidate TFs, our method achieves an auROC of 0.961 with only 10 motifs. Finally, we found two novel subpopulations of monocyte cells in response to SD-LPS and we confirmed our analysis using independent flow cytometry experiments. Our results suggest that our new machine learning method can select candidate regulatory genes as potential targets for developing new therapeutics against low grade inflammation.

An Optimal Boolean Approach for Computational Modeling of Gene Regulatory Networks from Temporal Gene Expression Profile

International Journal of Engineering ◽

10.5829/ije.2022.35.03c.14 ◽

2022 ◽

Vol 35 (3) ◽

pp. 604-612

Keyword(s):

Gene Expression ◽

Computational Modeling ◽

Gene Expression Profile ◽

Expression Profile ◽

Regulatory Networks ◽

Gene Regulatory ◽

Temporal Gene Expression Profile

Identification of Minimum Set of Master Regulatory Genes in Gene Regulatory Networks

IEEE/ACM Transactions on Computational Biology and Bioinformatics ◽

10.1109/tcbb.2018.2875692 ◽

2020 ◽

Vol 17 (3) ◽

pp. 999-1009

Author(s):

Somayeh Bakhteh ◽

Alireza Ghaffari-Hadigheh ◽

Nader Chaparzadeh

Keyword(s):

Regulatory Networks ◽

Regulatory Genes ◽

Evolution Towards Criticality in Ising Neural Agents

Artificial Life ◽

10.1162/artl_a_00309 ◽

2020 ◽

Vol 26 (1) ◽

pp. 112-129 ◽

Cited By ~ 1

Author(s):

Sina Khajehabdollahi ◽

Olaf Witkowski

Keyword(s):

Complex Systems ◽

Critical State ◽

Regulatory Networks ◽

Evolutionary Dynamics ◽

Subcritical State ◽

Experimental Conditions ◽

Supercritical Regime ◽

Gene Regulatory ◽

Human Brains ◽

Clear Description

Criticality is thought to be crucial for complex systems to adapt at the boundary between regimes with different dynamics, where the system may transition from one phase to another. Numerous systems, from sandpiles to gene regulatory networks to swarms to human brains, seem to work towards preserving a precarious balance right at their critical point. Understanding criticality therefore seems strongly related to a broad, fundamental theory for the physics of life as it could be, which still lacks a clear description of how life can arise and maintain itself in complex systems. In order to investigate this crucial question, we model populations of Ising agents competing for resources in a simple 2D environment subject to an evolutionary algorithm. We then compare its evolutionary dynamics under different experimental conditions. We demonstrate the utility that arises at a critical state and contrast it with the behaviors and dynamics that arise far from criticality. The results show compelling evidence that not only is a critical state remarkable in its ability to adapt and find solutions to the environment, but the evolving parameters in the agents tend to flow towards criticality if starting from a supercritical regime. We present simulations showing that a system in a supercritical state will tend to self-organize towards criticality, in contrast to a subcritical state, which remains subcritical though it is still capable of adapting and increasing its fitness.