scholarly journals Ancient Evolutionary Origin of the Neural Crest Gene Regulatory Network

2007 ◽  
Vol 13 (3) ◽  
pp. 405-420 ◽  
Author(s):  
Tatjana Sauka-Spengler ◽  
Daniel Meulemans ◽  
Matthew Jones ◽  
Marianne Bronner-Fraser
Keyword(s):  
Neural Crest ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Evolutionary Origin ◽  
Gene Regulatory

scholarly journals Migrating into Genomics with the Neural Crest

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Marianne E. Bronner
Keyword(s):  
Neural Crest ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Neural Crest Cells ◽  
Embryonic Cell ◽  
Putative Gene ◽  
Peripheral Neurons ◽  
Neural Plate Border ◽  
The Central Nervous System ◽  
Gene Regulatory

Neural crest cells are a fascinating embryonic cell type, unique to vertebrates, which arise within the central nervous system but emigrate soon after its formation and migrate to numerous and sometimes distant locations in the periphery. Following their migratory phase, they differentiate into diverse derivatives ranging from peripheral neurons and glia to skin melanocytes and craniofacial cartilage and bone. The molecular underpinnings underlying initial induction of prospective neural crest cells at the neural plate border to their migration and differentiation have been modeled in the form of a putative gene regulatory network. This review describes experiments performed in my laboratory in the past few years aimed to test and elaborate this gene regulatory network from both an embryonic and evolutionary perspective. The rapid advances in genomic technology in the last decade have greatly expanded our knowledge of important transcriptional inputs and epigenetic influences on neural crest development. The results reveal new players and new connections in the neural crest gene regulatory network and suggest that it has an ancient origin at the base of the vertebrate tree.

scholarly journals A systems biology approach uncovers the core gene regulatory network governing iridophore fate choice from the neural crest

PLoS Genetics ◽  
2018 ◽  
Vol 14 (10) ◽  
pp. e1007402 ◽  
Author(s):  
Kleio Petratou ◽  
Tatiana Subkhankulova ◽  
James A. Lister ◽  
Andrea Rocco ◽  
Hartmut Schwetlick ◽  
...  
Keyword(s):  
Systems Biology ◽  
Neural Crest ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Core Gene ◽  
The Core ◽  
Gene Regulatory

scholarly journals A direct role for murine Cdx proteins in the trunk neural crest gene regulatory network

Development ◽  
2016 ◽  
Vol 143 (8) ◽  
pp. 1363-1374 ◽  
Author(s):  
Oraly Sanchez-Ferras ◽  
Guillaume Bernas ◽  
Omar Farnos ◽  
Aboubacrine M. Touré ◽  
Ouliana Souchkova ◽  
...  
Keyword(s):  
Neural Crest ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Direct Role ◽  
Trunk Neural Crest ◽  
Gene Regulatory

scholarly journals Using Genomic Resources for Linkage Analysis in Peromyscus with an Application for Characterizing Dominant Spot

2020 ◽  
Author(s):  
Zhenhua Shang ◽  
David J Horovitz ◽  
Ronald H McKenzie ◽  
Jessica L Keisler ◽  
Michael R Felder ◽  
...  
Keyword(s):  
Linkage Analysis ◽  
Neural Crest ◽  
Candidate Gene ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Cholesterol Metabolism ◽  
Deer Mouse ◽  
Genomic Resources ◽  
Hybrid Offspring ◽  
Gene Regulatory

Abstract Background: Peromyscus are the most common mammalian species in North America and are widely used in both laboratory and field studies. The deer mouse, P. maniculatus and the old-field mouse, P. polionotus, are closely related and can generate viable and fertile hybrid offspring. The ability to generate hybrid offspring, coupled with developing genomic resources, enables researchers to conduct linkage analysis studies to identify genomic loci associated with specific traits. Results: We used available genomic data to identify DNA polymorphisms between P. maniculatus and P. polionotus and used the polymorphic data to identify the range of genetic complexity that underlies physiological and behavioral differences between the species, including cholesterol metabolism and genes associated with autism. In addition, we used the polymorphic data to conduct a candidate gene linkage analysis for the Dominant spot trait and determined that Dominant spot is linked to a region of chromosome 20 that contains a strong candidate gene, Sox10. During the linkage analysis, we found that the spot size varied quantitively in affected Peromyscus based on genetic background. Conclusions: The expanding genomic resources for Peromyscus facilitate their use in linkage analysis studies, enabling the identification of loci associated with specific traits. More specifically, we have linked a coat color spotting phenotype, Dominant spot, with Sox10, a member the neural crest gene regulatory network, and that there are likely two genetic modifiers that interact with Dominant spot. These results establish Peromyscus as a model system for identifying new alleles of the neural crest gene regulatory network.

scholarly journals The Cranial Neural Crest in a Multiomics Era

2021 ◽  
Vol 12 ◽  
Author(s):  
Vanessa Chong-Morrison ◽  
Tatjana Sauka-Spengler
Keyword(s):  
Neural Crest ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Craniofacial Development ◽  
Cranial Neural Crest ◽  
Genomic Landscape ◽  
Key Players ◽  
Gene Regulatory ◽  
Technological Improvements ◽  
Key Questions

Neural crest ontogeny plays a prominent role in craniofacial development. In this Perspective article, we discuss recent advances to the understanding of mechanisms underlying the cranial neural crest gene regulatory network (cNC-GRN) stemming fromomics-based studies. We briefly summarize how parallel considerations of transcriptome, interactome, and epigenome data significantly elaborated the roles of key players derived from pre-omicsera studies. Furthermore, the growing cohort of cNC multiomics data revealed contribution of the non-coding genomic landscape. As technological improvements are constantly being developed, we reflect on key questions we are poised to address by taking advantage of the unique perspective a multiomics approach has to offer.

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