scholarly journals ChIP-seq analysis of genomic binding regions of five major transcription factors highlights a central role for ZIC2 in the mouse epiblast stem cell gene regulatory network

Development ◽  
2017 ◽  
Vol 144 (11) ◽  
pp. 1948-1958 ◽  
Author(s):  
Kazunari Matsuda ◽  
Tomoyuki Mikami ◽  
Shinya Oki ◽  
Hideaki Iida ◽  
Munazah Andrabi ◽  
...  
Keyword(s):  
Stem Cell ◽  
Transcription Factors ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Binding Regions ◽  
Gene Regulatory ◽  
Cell Gene ◽  
Stem Cell Gene

scholarly journals Characterization of the neural stem cell gene regulatory network identifies OLIG2 as a multifunctional regulator of self-renewal

2014 ◽  
Vol 25 (1) ◽  
pp. 41-56 ◽  
Author(s):  
Juan L. Mateo ◽  
Debbie L.C. van den Berg ◽  
Maximilian Haeussler ◽  
Daniela Drechsel ◽  
Zachary B. Gaber ◽  
...  
Keyword(s):  
Stem Cell ◽  
Gene Regulatory Network ◽  
Neural Stem Cell ◽  
Regulatory Network ◽  
Self Renewal ◽  
Gene Regulatory ◽  
Cell Gene ◽  
Stem Cell Gene

scholarly journals Corrigendum: Characterization of the neural stem cell gene regulatory network identifies OLIG2 as a multifunctional regulator of self-renewal

2017 ◽  
Vol 27 (12) ◽  
pp. 2129-2129
Author(s):  
Juan L. Mateo ◽  
Debbie L.C. van den Berg ◽  
Maximilian Haeussler ◽  
Daniela Drechsel ◽  
Zachary B. Gaber ◽  
...  
Keyword(s):  
Stem Cell ◽  
Gene Regulatory Network ◽  
Neural Stem Cell ◽  
Regulatory Network ◽  
Self Renewal ◽  
Gene Regulatory ◽  
Cell Gene ◽  
Stem Cell Gene

scholarly journals Corrigendum: Characterization of the neural stem cell gene regulatory network identifies OLIG2 as a multifunctional regulator of self-renewal

2016 ◽  
Vol 26 (11) ◽  
pp. 1626-1626
Author(s):  
Juan L. Mateo ◽  
Debbie L.C. van den Berg ◽  
Maximilian Haeussler ◽  
Daniela Drechsel ◽  
Zachary B. Gaber ◽  
...  
Keyword(s):  
Stem Cell ◽  
Gene Regulatory Network ◽  
Neural Stem Cell ◽  
Regulatory Network ◽  
Self Renewal ◽  
Gene Regulatory ◽  
Cell Gene ◽  
Stem Cell Gene

scholarly journals Integrative genomics positions MKRN 1 as a novel ribonucleoprotein within the embryonic stem cell gene regulatory network

EMBO Reports ◽  
2015 ◽  
Vol 16 (10) ◽  
pp. 1334-1357 ◽  
Author(s):  
Paul A Cassar ◽  
Richard L Carpenedo ◽  
Payman Samavarchi‐Tehrani ◽  
Jonathan B Olsen ◽  
Chang Jun Park ◽  
...  
Keyword(s):  
Stem Cell ◽  
Embryonic Stem Cell ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Embryonic Stem ◽  
Integrative Genomics ◽  
Gene Regulatory ◽  
Cell Gene ◽  
Stem Cell Gene

scholarly journals Identification of Transcription Factors Regulating Senescence in Wheat through Gene Regulatory Network Modelling

2019 ◽  
Vol 180 (3) ◽  
pp. 1740-1755 ◽  
Author(s):  
Philippa Borrill ◽  
Sophie A. Harrington ◽  
James Simmonds ◽  
Cristobal Uauy
Keyword(s):  
Transcription Factors ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Network Modelling ◽  
Gene Regulatory

scholarly journals The identification of transcription factors expressed in the notochord of Ciona intestinalis adds new potential players to the brachyury gene regulatory network

2011 ◽  
Vol 240 (9) ◽  
pp. spcone-spcone
Author(s):  
Diana S. José-Edwards ◽  
Pierre Kerner ◽  
Jamie E. Kugler ◽  
Wei Deng ◽  
Di Jiang ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Ciona Intestinalis ◽  
Gene Regulatory

scholarly journals Identification of transcription factors regulating senescence in wheat through gene regulatory network modelling

2018 ◽  
Author(s):  
Philippa Borrill ◽  
Sophie A. Harrington ◽  
James Simmonds ◽  
Cristobal Uauy
Keyword(s):  
Transcription Factors ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Time Series Data ◽  
Nutrient Content ◽  
Series Data ◽  
Network Modelling ◽  
Polyploid Wheat ◽  
Gene Regulatory ◽  
Developmental Programme

AbstractSenescence is a tightly regulated developmental programme which is coordinated by transcription factors. Identifying these transcription factors in crops will provide opportunities to tailor the senescence process to different environmental conditions and regulate the balance between yield and grain nutrient content. Here we use ten time points of gene expression data alongside gene network modelling to identify transcription factors regulating senescence in polyploid wheat. We observe two main phases of transcription changes during senescence: early downregulation of housekeeping and metabolic processes followed by upregulation of transport and hormone related genes. We have identified transcription factor families associated with these early and later waves of differential expression. Using gene regulatory network modelling alongside complementary publicly available datasets we identified candidate transcription factors for controlling senescence. We validated the function of one of these candidate transcription factors in senescence using wheat chemically-induced mutants. This study lays the ground work to understand the transcription factors which regulate senescence in polyploid wheat and exemplifies the integration of time-series data with publicly available expression atlases and networks to identify candidate regulatory genes.

scholarly journals Gene regulatory network analysis of Trichoderma reesei grown on glucose-lactose mixtures suggests links between development and cellulase production

2020 ◽  
Author(s):  
Aurélie Pirayre ◽  
Laurent Duval ◽  
Corinne Blugeon ◽  
Cyril Firmo ◽  
Sandrine Perrin ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Gene Regulatory Network ◽  
Trichoderma Reesei ◽  
Regulatory Network ◽  
Cellulase Production ◽  
Biofuel Production ◽  
Batch Mode ◽  
Lactose Concentration ◽  
Gene Regulatory ◽  
The Impact

Abstract Background: The degradation of cellulose and hemicellulose molecules into simpler sugars such as glucose is part of the second generation biofuel production process. Hydrolysis of lignocellulosic substrates is usually performed by enzymes produced and secreted by the fungus Trichoderma reesei . Studies identifying transcription factors involved in the regulation of cellulase production have been conducted but no overview of the whole regulation network is available. A transcriptomic approach with mixtures of glucose and lactose, used as a substrate for cellulase induction, was used to help us decipher missing parts in the network.Results: Experimental results confirmed the impact of sugar mixture on the enzymatic cocktail composition. The transcriptomic study shows a temporal regulation of the main transcription factors and a lactose concentration impact on the transcriptional profile. A gene regulatory network built using the BRANE Cut software reveals three sub-networks related to i) a positive correlation between lactose concentration and cellulase production, ii) a particular dependence of the lactose onto the β-glucosidase regulation and iii) a negative regulation of the development process and growth.Conclusions: This work is the first investigating a transcriptomic study regarding the effects of pure and mixed carbon sources in a fed-batch mode. Our study expose a co-orchestration of xyr1 , clr2 and ace3 for cellulase and hemicellulase induction and production, a fine regulation of the β-glucosidase and a decrease of growth in favor of cellulase production. These conclusions provide us with potential targets for further genetic engineering leading to better cellulase-producing strains.

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