scholarly journals Co-expression of Foxa.a, Foxd and Fgf9/16/20 defines a transient mesendoderm regulatory state in ascidian embryos

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Clare Hudson ◽  
Cathy Sirour ◽  
Hitoyoshi Yasuo
Keyword(s):  
Gene Regulatory Networks ◽  
Ground State ◽  
Regulatory Networks ◽  
Developmental Process ◽  
Regulatory State ◽  
Transcriptional Targets ◽  
Regulatory Architecture ◽  
Ascidian Embryos ◽  
Gene Regulatory

In many bilaterian embryos, nuclear β-catenin (nβ-catenin) promotes mesendoderm over ectoderm lineages. Although this is likely to represent an evolutionary ancient developmental process, the regulatory architecture of nβ-catenin-induced mesendoderm remains elusive in the majority of animals. Here, we show that, in ascidian embryos, three nβ-catenin transcriptional targets, Foxa.a, Foxd and Fgf9/16/20, are each required for the correct initiation of both the mesoderm and endoderm gene regulatory networks. Conversely, these three factors are sufficient, in combination, to produce a mesendoderm ground state that can be further programmed into mesoderm or endoderm lineages. Importantly, we show that the combinatorial activity of these three factors is sufficient to reprogramme developing ectoderm cells to mesendoderm. We conclude that in ascidian embryos, the transient mesendoderm regulatory state is defined by co-expression of Foxa.a, Foxd and Fgf9/16/20.

Using ascidian embryos to study the evolution of developmental gene regulatory networks

2005 ◽  
Vol 83 (1) ◽  
pp. 75-89 ◽  
Author(s):  
Angela C Cone ◽  
Robert W Zeller
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Regulatory Mechanisms ◽  
Developmental Gene ◽  
Regulatory Architecture ◽  
Ascidian Embryos ◽  
Gene Regulatory ◽  
Mode Of Development ◽  
Ascidian Embryo

Ascidians are ideally positioned taxonomically at the base of the chordate tree to provide a point of comparison for developmental regulatory mechanisms that operate among protostomes, non-chordate deuterostomes, invertebrate chordates, and vertebrates. In this review, we propose a model for the gene regulatory network that gives rise to the ascidian notochord. The purpose of this model is not to clarify all of the interactions between molecules of this network, but to provide a working schematic of the regulatory architecture that leads to the specification of endoderm and the patterning of mesoderm in ascidian embryos. We describe a series of approaches, both computational and biological, that are currently being used, or are in development, for the study of ascidian embryo gene regulatory networks. It is our belief that the tools now available to ascidian biologists, in combination with a streamlined mode of development and small genome size, will allow for more rapid dissection of developmental gene regulatory networks than in more complex organisms such as vertebrates. It is our hope that the analysis of gene regulatory networks in ascidians can provide a basic template which will allow developmental biologists to superimpose the modifications and novelties that have arisen during deuterostome evolution.

scholarly journals Controlling Robots with Fractal Gene Regulatory Networks

2005 ◽  
pp. 320-339 ◽  
Author(s):  
Peter J. Bentley
Keyword(s):  
Gene Regulatory Networks ◽  
Protein Interactions ◽  
Regulatory Networks ◽  
Developmental Process ◽  
Mandelbrot Set ◽  
Gene Regulatory ◽  
Robot Path

Fractal proteins are a new evolvable method of mapping genotype to phenotype through a developmental process, where genes are expressed into proteins comprised of subsets of the Mandelbrot set. The resulting network of gene and protein interactions can be designed by evolution to produce specific patterns, which in turn can be used to solve problems. This chapter introduces the fractal development algorithm in detail and describes the use of fractal gene regulatory networks for learning a robot path through a series of obstacles. The results indicate the ability of this system to learn regularities in solutions and automatically create and use modules.

Cracking the Egg: Virtual Embryogenesis of Real Robots

2014 ◽  
Vol 20 (3) ◽  
pp. 361-383 ◽  
Author(s):  
Sylvain Cussat-Blanc ◽  
Jordan Pollack
Keyword(s):  
Single Cell ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Developmental Process ◽  
Body Plan ◽  
Living Systems ◽  
New Approach ◽  
Virtual Cells ◽  
Building Process ◽  
Gene Regulatory

All multicellular living beings are created from a single cell. A developmental process, called embryogenesis, takes this first fertilized cell down a complex path of reproduction, migration, and specialization into a complex organism adapted to its environment. In most cases, the first steps of the embryogenesis take place in a protected environment such as in an egg or in utero. Starting from this observation, we propose a new approach to the generation of real robots, strongly inspired by living systems. Our robots are composed of tens of specialized cells, grown from a single cell using a bio-inspired virtual developmental process. Virtual cells, controlled by gene regulatory networks, divide, migrate, and specialize to produce the robot's body plan (morphology), and then the robot is manually built from this plan. Because the robot is as easy to assemble as Lego, the building process could be easily automated.

scholarly journals Assessing regulatory information in developmental gene regulatory networks

2017 ◽  
Vol 114 (23) ◽  
pp. 5862-5869 ◽  
Author(s):  
Isabelle S. Peter ◽  
Eric H. Davidson
Keyword(s):  
Gene Regulatory Networks ◽  
Network Architecture ◽  
Regulatory Networks ◽  
Large Scale ◽  
Developmental Process ◽  
Genomic Sequence ◽  
Hierarchical Organization ◽  
Network Organization ◽  
Regulatory Information ◽  
Gene Regulatory

Gene regulatory networks (GRNs) provide a transformation function between the static genomic sequence and the primary spatial specification processes operating development. The regulatory information encompassed in developmental GRNs thus goes far beyond the control of individual genes. We here address regulatory information at different levels of network organization, from single node to subcircuit to large-scale GRNs and discuss how regulatory design features such as network architecture, hierarchical organization, and cis-regulatory logic contribute to the developmental function of network circuits. Using specific subcircuits from the sea urchin endomesoderm GRN, for which both circuit design and biological function have been described, we evaluate by Boolean modeling and in silico perturbations the import of given circuit features on developmental function. The examples include subcircuits encoding positive feedback, mutual repression, and coherent feedforward, as well as signaling interaction circuitry. Within the hierarchy of the endomesoderm GRN, these subcircuits are organized in an intertwined and overlapping manner. Thus, we begin to see how regulatory information encoded at individual nodes is integrated at all levels of network organization to control developmental process.

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