scholarly journals DET1-mediated COP1 regulation avoids HY5 activity over second-site targets to tune plant photomorphogenesis

2020 ◽  
Author(s):  
Esther Cañibano ◽  
Clara Bourbousse ◽  
Marta Garcia-Leon ◽  
Lea Wolff ◽  
Camila Garcia-Baudino ◽  
...  
Keyword(s):  
Ubiquitin Ligase ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Genes ◽  
Negative Regulator ◽  
Protein Abundance ◽  
Mass Spectrometry Identification ◽  
Associated Proteins ◽  
Gene Regulatory

AbstractDE-ETIOLATED1 (DET1) is a negative regulator of plant photomorphogenesis acting as a component of the C3D complex, which can further associate to CULLIN4 to form a CRL4C3D E3 ubiquitin ligase. CRL4C3D is thought to act together with CRL4COP1SPA ubiquitin ligase, to promote the ubiquitin-mediated degradation of the master regulatory transcription factor ELONGATED HYPOCOTYL5 (HY5), thereby controlling photomorphogenic gene regulatory networks. Yet, functional links between COP1 and DET1 have long remained elusive. Here, upon mass spectrometry identification of DET1 and COP1-associated proteins, we provide in vivo evidence that DET1 associates with COP1 to promote its destabilization, a process necessary to dampen HY5 protein abundance. By regulating HY5 over-accumulation, DET1 is critical to avoid its association to second-site loci, including many PIF3 target genes. Accordingly, excessive HY5 levels result in an increased HY5 repressive activity and are sufficient to trigger fusca-like phenotypes otherwise observed typically in COP1 and COP9 signalosome mutant seedlings. This study therefore identifies that DET1-mediated regulation of COP1 stability tunes down HY5 cistrome and avoids hyper-photomorphogenic responses that might compromise plant viability.

scholarly journals Identifying genetic modulators of the connectivity between transcription factors and their transcriptional targets

2016 ◽  
Vol 113 (13) ◽  
pp. E1835-E1843 ◽  
Author(s):  
Mina Fazlollahi ◽  
Ivor Muroff ◽  
Eunjee Lee ◽  
Helen C. Causton ◽  
Harmen J. Bussemaker
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Nonsynonymous Mutation ◽  
Gene Regulatory ◽  
Genetic Modulators

Regulation of gene expression by transcription factors (TFs) is highly dependent on genetic background and interactions with cofactors. Identifying specific context factors is a major challenge that requires new approaches. Here we show that exploiting natural variation is a potent strategy for probing functional interactions within gene regulatory networks. We developed an algorithm to identify genetic polymorphisms that modulate the regulatory connectivity between specific transcription factors and their target genes in vivo. As a proof of principle, we mapped connectivity quantitative trait loci (cQTLs) using parallel genotype and gene expression data for segregants from a cross between two strains of the yeast Saccharomyces cerevisiae. We identified a nonsynonymous mutation in the DIG2 gene as a cQTL for the transcription factor Ste12p and confirmed this prediction empirically. We also identified three polymorphisms in TAF13 as putative modulators of regulation by Gcn4p. Our method has potential for revealing how genetic differences among individuals influence gene regulatory networks in any organism for which gene expression and genotype data are available along with information on binding preferences for transcription factors.

scholarly journals Nuclear Transfer Arrest Embryos Show Massive Dysregulation of Genes Involved in Transcription Pathways

2021 ◽  
Vol 22 (15) ◽  
pp. 8187
Author(s):  
Chunshen Long ◽  
Hanshuang Li ◽  
Xinru Li ◽  
Wuritu Yang ◽  
Yongchun Zuo
Keyword(s):  
Gene Regulatory Networks ◽  
Nuclear Transfer ◽  
Regulatory Networks ◽  
Target Genes ◽  
Epigenetic Modification ◽  
Cell Nuclei ◽  
Activation Of Transcription ◽  
Gene Regulatory ◽  
Catabolic Process

Somatic cell nuclear transfer (SCNT) technology can reprogram terminally differentiated cell nuclei into a totipotent state. However, the underlying molecular barriers of SCNT embryo development remain incompletely elucidated. Here, we observed that transcription-related pathways were incompletely activated in nuclear transfer arrest (NTA) embryos compared to normal SCNT embryos and in vivo fertilized (WT) embryos, which hinders the development of SCNT embryos. We further revealed the transcription pathway associated gene regulatory networks (GRNs) and found the aberrant transcription pathways can lead to the massive dysregulation of genes in NTA embryos. The predicted target genes of transcription pathways contain a series of crucial factors in WT embryos, which play an important role in catabolic process, pluripotency regulation, epigenetic modification and signal transduction. In NTA embryos, however, these genes were varying degrees of inhibition and show a defect in synergy. Overall, our research found that the incomplete activation of transcription pathways is another potential molecular barrier for SCNT embryos besides the incomplete reprogramming of epigenetic modifications, broadening the understanding of molecular mechanism of SCNT embryonic development.

scholarly journals Gene regulatory networks controlled by FLOWERING LOCUS C that confer variation in seasonal flowering and life history

2020 ◽  
Author(s):  
Eva Madrid ◽  
John W Chandler ◽  
George Coupland
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Genes ◽  
Higher Plants ◽  
Floral Transition ◽  
Environmental Cues ◽  
Flowering Locus C ◽  
Gene Regulatory ◽  
Flowering Locus

Abstract Responses to environmental cues synchronize reproduction of higher plants to the changing seasons. The genetic basis of these responses has been intensively studied in the Brassicaceae. The MADS-domain transcription factor FLOWERING LOCUS C (FLC) plays a central role in the regulatory network that controls flowering of Arabidopsis thaliana in response to seasonal cues. FLC blocks flowering until its transcription is stably repressed by extended exposure to low temperatures in autumn or winter and, therefore, FLC activity is assumed to limit flowering to spring. Recent reviews describe the complex epigenetic mechanisms responsible for FLC repression in cold. We focus on the gene regulatory networks controlled by FLC and how they influence floral transition. Genome-wide approaches determined the in vivo target genes of FLC and identified those whose transcription changes during vernalization or in flc mutants. We describe how studying FLC targets such as FLOWERING LOCUS T, SQUAMOSA PROMOTER BINDING PROTEIN-LIKE 15, and TARGET OF FLC AND SVP 1 can explain different flowering behaviours in response to vernalization and other environmental cues, and help define mechanisms by which FLC represses gene transcription. Elucidating the gene regulatory networks controlled by FLC provides access to the developmental and physiological mechanisms that regulate floral transition.

scholarly journals Connecting the molecular function of microRNAs to cell differentiation dynamics

2019 ◽  
Vol 16 (158) ◽  
pp. 20190437 ◽  
Author(s):  
Russell Posner ◽  
Reinhard Laubenbacher
Keyword(s):  
Cell Differentiation ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Genes ◽  
Scale Effects ◽  
Expression Profiles ◽  
Small Scale ◽  
Gene Regulatory ◽  
Genome Scale

MicroRNAs form a class of short, non-coding RNA molecules which are essential for proper development in tissue-based plants and animals. To help explain their role in gene regulation, a number of mathematical and computational studies have demonstrated the potential canalizing effects of microRNAs. However, such studies have typically focused on the effects of microRNAs on only one or a few target genes. Consequently, it remains unclear how these small-scale effects add up to the experimentally observed developmental outcomes resulting from microRNA perturbation at the whole-genome level. To answer this question, we built a general computational model of cell differentiation to study the effect of microRNAs in genome-scale gene regulatory networks. Our experiments show that in large gene regulatory networks, microRNAs can control differentiation time without significantly changing steady-state gene expression profiles. This temporal regulatory role cannot be naturally replicated using protein-based transcription factors alone. While several microRNAs have been shown to regulate differentiation time in vivo , our findings provide a new explanation of how the cumulative molecular actions of individual microRNAs influence genome-scale cellular dynamics. Taken together, these results may help explain why tissue-based organisms exclusively depend on miRNA-mediated regulation, while their more primitive counterparts do not.

scholarly journals In vitro gene regulatory networks predict in vivo function of liver

2010 ◽  
Vol 4 (1) ◽  
Author(s):  
Youping Deng ◽  
David R Johnson ◽  
Xin Guan ◽  
Choo Y Ang ◽  
Junmei Ai ◽  
...  
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Gene Regulatory

scholarly journals AGENT: the Arabidopsis Gene Regulatory Network Tool for Exploring and Analyzing GRNs

2021 ◽  
Author(s):  
Vincent Lau ◽  
Rachel Woo ◽  
Bruno Pereira ◽  
Asher Pasha ◽  
Eddi Esteban ◽  
...  
Keyword(s):  
Gene Regulatory Networks ◽  
Gene Network ◽  
Regulatory Networks ◽  
Target Genes ◽  
Ad Hoc ◽  
Arabidopsis Gene ◽  
Nitrate Signaling ◽  
Multi Level ◽  
Gene Regulatory

AbstractGene regulatory networks (GRNs) are complex networks that capture multi-level regulatory events between one or more regulatory macromolecules, such as transcription factors (TFs), and their target genes. Advancements in screening technologies such as enhanced yeast-one-hybrid screens have allowed for high throughput determination of GRNs. However, visualization of GRNs in Arabidopsis has been limited to ad hoc networks and are not interactive. Here, we describe the Arabidopsis GEne Network Tool (AGENT) that houses curated GRNs and provides tools to visualize and explore them. AGENT features include expression overlays, subnetwork motif scanning, and network analysis. We show how to use AGENT’s multiple built-in tools to identify key genes that are involved in flowering and seed development along with identifying temporal multi-TF control of a key transporter in nitrate signaling. AGENT can be accessed at https://bar.utoronto.ca/AGENT.

scholarly journals The emerging landscape of in vitro and in vivo epigenetic allelic effects

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 2108 ◽  
Author(s):  
Christopher Gregg
Keyword(s):  
Cell Fate ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Disease Susceptibility ◽  
Monoallelic Expression ◽  
Functional Studies ◽  
Cell Type Specific ◽  
Gene Regulatory

Epigenetic mechanisms that cause maternally and paternally inherited alleles to be expressed differently in offspring have the potential to radically change our understanding of the mechanisms that shape disease susceptibility, phenotypic variation, cell fate, and gene expression. However, the nature and prevalence of these effects in vivo have been unclear and are debated. Here, I consider major new studies of epigenetic allelic effects in cell lines and primary cells and in vivo. The emerging picture is that these effects take on diverse forms, and this review attempts to clarify the nature of the different forms that have been uncovered for genomic imprinting and random monoallelic expression (RME). I also discuss apparent discrepancies between in vitro and in vivo studies. Importantly, multiple studies suggest that allelic effects are prevalent and can be developmental stage- and cell type-specific. I propose some possible functions and consider roles for allelic effects within the broader context of gene regulatory networks, cellular diversity, and plasticity. Overall, the field is ripe for discovery and is in need of mechanistic and functional studies.

scholarly journals Evolution of Mendelian Dominance in Gene Regulatory Networks Associated With Phenotypic Robustness

2021 ◽  
Author(s):  
Kenji Okubo ◽  
Kunihiko Kaneko
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Genes ◽  
Classical Case ◽  
Mendelian Inheritance ◽  
Degree Of Dominance ◽  
Gene Expression Dynamics ◽  
Phenotypic Robustness ◽  
Robustness To Noise ◽  
Gene Regulatory

Abstract Background: Mendelian inheritance is a fundamental law of genetics. Considering two alleles in a diploid, a phenotype of a heterotype is dominated by a particular homotype according to the law of dominance. This picture is usually based on simple genotype-phenotype mapping in which one gene regulates one phenotype. However, in reality, some interactions between genes can result in deviation from Mendelian dominance. Result: Here, by using the numerical evolution of diploid gene regulatory networks (GRNs), we discuss whether Mendelian dominance evolves beyond the classical case of one-to-one genotype-phenotype mapping. We examine whether complex genotype-phenotype mapping can achieve Mendelian dominance through the evolution of the GRN with interacting genes. Specifically, we extend the GRN model to a diploid case, in which two GRN matrices are added to give gene expression dynamics, and simulate evolution with meiosis and recombination. Our results reveal that Mendelian dominance evolves even under complex genotype-phenotype mapping. This dominance is achieved via a group of genotypes that differ from each other but have a common phenotype given by the expression of target genes. Calculating the degree of dominance shows that it increases through the evolution, correlating closely with the decrease in phenotypic fluctuations and the increase in robustness to initial noise. This evolution of Mendelian dominance is associated with phenotypic robustness against meiosis-induced genome mixing, whereas sexual recombination arising from the mixing of chromosomes from the parents further enhances dominance and robustness. Owing to this dominance, the robustness to genetic differences increases, while the optimal fitness is sustained up to a large difference between the two genomes. Conclusion: Mendelian dominance is achieved by groups of genotypes that are associated with the increase in phenotypic robustness to noise.

Data-driven Gene Regulatory Networks Inference Based on Classification Algorithms

2021 ◽  
Vol 30 (04) ◽  
pp. 2150022
Author(s):  
Sergio Peignier ◽  
Pauline Schmitt ◽  
Federica Calevro
Keyword(s):  
Gene Expression ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Genes ◽  
Data Driven ◽  
Classification Algorithms ◽  
New Family ◽  
Gene Regulatory ◽  
High Throughput Gene Expression ◽  
Inference Methods

Inferring Gene Regulatory Networks from high-throughput gene expression data is a challenging problem, addressed by the systems biology community. Most approaches that aim at unraveling the gene regulation mechanisms in a data-driven way, analyze gene expression datasets to score potential regulatory links between transcription factors and target genes. So far, three major families of approaches have been proposed to score regulatory links. These methods rely respectively on correlation measures, mutual information metrics, and regression algorithms. In this paper we present a new family of data-driven inference methods. This new family, inspired by the regression-based paradigm, relies on the use of classification algorithms. This paper assesses and advocates for the use of this paradigm as a new promising approach to infer gene regulatory networks. Indeed, the development and assessment of five new inference methods based on well-known classification algorithms shows that the classification-based inference family exhibits good results when compared to well-established paradigms.

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