scholarly journals Exploring regulatory networks in plants: transcription factors of starch metabolism

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6841 ◽  
Author(s):  
Cristal López-González ◽  
Sheila Juárez-Colunga ◽  
Norma Cecilia Morales-Elías ◽  
Axel Tiessen

Biological networks are complex (non-linear), redundant (cyclic) and compartmentalized at the subcellular level. Rational manipulation of plant metabolism may have failed due to inherent difficulties of a comprehensive understanding of regulatory loops. We first need to identify key factors controlling the regulatory loops of primary metabolism. The paradigms of plant networks are revised in order to highlight the differences between metabolic and transcriptional networks. Comparison between animal and plant transcription factors (TFs) reveal some important differences. Plant transcriptional networks function at a lower hierarchy compared to animal regulatory networks. Plant genomes contain more TFs than animal genomes, but plant proteins are smaller and have less domains as animal proteins which are often multifunctional. We briefly summarize mutant analysis and co-expression results pinpointing some TFs regulating starch enzymes in plants. Detailed information is provided about biochemical reactions, TFs and cis regulatory motifs involved in sucrose-starch metabolism, in both source and sink tissues. Examples about coordinated responses to hormones and environmental cues in different tissues and species are listed. Further advancements require combined data from single-cell transcriptomic and metabolomic approaches. Cell fractionation and subcellular inspection may provide valuable insights. We propose that shuffling of promoter elements might be a promising strategy to improve in the near future starch content, crop yield or food quality.

Cells ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 251
Author(s):  
Matin Miryeganeh

Senescence is a major developmental transition in plants that requires a massive reprogramming of gene expression and includes various layers of regulations. Senescence is either an age-dependent or a stress-induced process, and is under the control of complex regulatory networks that interact with each other. It has been shown that besides genetic reprogramming, which is an important aspect of plant senescence, transcription factors and higher-level mechanisms, such as epigenetic and small RNA-mediated regulators, are also key factors of senescence-related genes. Epigenetic mechanisms are an important layer of this multilevel regulatory system that change the activity of transcription factors (TFs) and play an important role in modulating the expression of senescence-related gene. They include chromatin remodeling, DNA methylation, histone modification, and the RNA-mediated control of transcription factors and genes. This review provides an overview of the known epigenetic regulation of plant senescence, which has mostly been studied in the form of leaf senescence, and it also covers what has been reported about whole-plant senescence.


2008 ◽  
Vol 14 (1) ◽  
pp. 49-63 ◽  
Author(s):  
Koenraad Van Leemput ◽  
Tim Van den Bulcke ◽  
Thomas Dhollander ◽  
Bart De Moor ◽  
Kathleen Marchal ◽  
...  

The development of structure-learning algorithms for gene regulatory networks depends heavily on the availability of synthetic data sets that contain both the original network and associated expression data. This article reports the application of SynTReN, an existing network generator that samples topologies from existing biological networks and uses Michaelis-Menten and Hill enzyme kinetics to simulate gene interactions. We illustrate the effects of different aspects of the expression data on the quality of the inferred network. The tested expression data parameters are network size, network topology, type and degree of noise, quantity of expression data, and interaction types between genes. This is done by applying three well-known inference algorithms to SynTReN data sets. The results show the power of synthetic data in revealing operational characteristics of inference algorithms that are unlikely to be discovered by means of biological microarray data only.


Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 1227-1227
Author(s):  
Jian Xu ◽  
Zhen Shao ◽  
Kimberly Glass ◽  
Daniel E. Bauer ◽  
Luca Pinello ◽  
...  

Abstract Abstract 1227 Erythropoiesis in mammals occurs in three waves consisting of primitive progenitors in the yolk sac, definitive erythroid precursors in the fetal liver and later in the postnatal bone marrow. The molecular determinants of developmental stage-specific gene expression programs remain largely unknown. Several transcription factors, including GATA1 and TAL1, are essential for normal erythroid development in vivo and are recognized as ‘master’ regulators. These lineage-specifying master regulators, together with other transcriptional co-regulators, act within complexes on chromatin, establish transcriptional networks, and orchestrate the differentiation process. However, it is less clear how master regulators control gene expression programs at different stages of development within the same cell lineage. We reasoned that comparative transcriptome, transcription factor, and epigenetic profiling of closely related cell types corresponding to distinct developmental stages should delineate the regulatory networks that are directly related to the associated gene expression programs. Classification of the trans- and cis-regulatory elements that are either shared or stage-specific should clarify their relative importance and prioritize functional candidates. To explore this approach, we focused on an ex vivo maturation system for human fetal and adult erythropoiesis. Primary human hematopoietic stem/progenitor cells (HSPCs) are propagated and induced for erythroid differentiation ex vivo. We first determined the mRNA expression profiles in both fetal and adult HSPCs and differentiating proerythroblasts (ProEs). Comparative transcriptome profiling revealed distinct gene expression programs at different stages of erythroid maturation. For example, 1039 and 1291 genes linked to distinct functional annotations were differentially expressed (fold change > 1.5, FDR < 0.05) in fetal and adult ProEs, respectively. To investigate the underlying basis of these distinct gene expression programs, we generated genome-wide maps for chromatin state and transcription factor occupancy by a ChIP-seq approach. Specifically, we profiled 9 histone modifications (H3K4me1/me2/me3, H3K9me3, H3K37me3, H3K36me2/me3, H3K9ac, and H3K27ac) and 6 transcription factors (GATA1, TAL1, NFE2, CTCF, RAD21, and RNA polymerase II) in both fetal and adult ProEs. Contrasting the similarities and differences between human fetal and adult erythropoiesis provides important insights into the erythroid gene expression programs and gene regulatory networks operating at different stages of development. We find that gene-distal enhancers, rather than promoters, are marked with highly stage-specific histone modifications and DNase I hypersensitivity, strongly correlate to developmental stage-specific gene expression changes, and are functionally active in a stage-specific manner. The master regulators GATA1 and TAL1 act cooperatively within active enhancers but have little predictive value for stage-specific transcriptional activity. Differential enrichment of consensus motifs for binding of transcription factors within fetal or adult stage-specific enhancers provides a strategy for identifying candidate co-regulators that drive differential gene expression and stage-specificity. By this computational approach and subsequent functional validation, we demonstrate that the interferon regulatory factors IRF2 and IRF6 are essential for activation of adult erythroid gene expression programs in cooperation with master regulators and cohesin-mediator complexes at distal enhancers. Thus, the comparative profiling of red cell development provides critical insights into the ontogeny of human erythropoiesis and temporal regulation of transcriptional networks in a mammalian genome. Disclosures: No relevant conflicts of interest to declare.


Genetics ◽  
2020 ◽  
Vol 215 (4) ◽  
pp. 1171-1189
Author(s):  
Eunsoo Do ◽  
Yong-Joon Cho ◽  
Donghyeun Kim ◽  
James W. Kronstad ◽  
Won Hee Jung

Iron is essential for the growth of the human fungal pathogen Cryptococcus neoformans within the vertebrate host, and iron sensing contributes to the elaboration of key virulence factors, including the formation of the polysaccharide capsule. C. neoformans employs sophisticated iron acquisition and utilization systems governed by the transcription factors Cir1 and HapX. However, the details of the transcriptional regulatory networks that are governed by these transcription factors and connections to virulence remain to be defined. Here, we used chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) and transcriptome analysis (RNA-seq) to identify genes directly regulated by Cir1 and/or HapX in response to iron availability. Overall, 40 and 100 genes were directly regulated by Cir1, and 171 and 12 genes were directly regulated by HapX, under iron-limited and replete conditions, respectively. More specifically, we found that Cir1 directly controls the expression of genes required for iron acquisition and metabolism, and indirectly governs capsule formation by regulating specific protein kinases, a regulatory connection not previously revealed. HapX regulates the genes responsible for iron-dependent pathways, particularly under iron-depleted conditions. By analyzing target genes directly bound by Cir1 and HapX, we predicted the binding motifs for the transcription factors and verified that the purified proteins bind these motifs in vitro. Furthermore, several direct target genes were coordinately and reciprocally regulated by Cir1 and HapX, suggesting that these transcription factors play conserved roles in the response to iron availability. In addition, biochemical analyses revealed that Cir1 and HapX are iron-containing proteins, implying that the regulatory networks of Cir1 and HapX may be influenced by the incorporation of iron into these proteins. Taken together, our identification of the genome-wide transcriptional networks provides a detailed understanding of the iron-related regulatory landscape, establishes a new connection between Cir1 and kinases that regulate capsule, and underpins genetic and biochemical analyses that reveal iron-sensing mechanisms for Cir1 and HapX in C. neoformans.


2016 ◽  
Author(s):  
Ildem Akerman ◽  
Zhidong Tu ◽  
Anthony Beucher ◽  
Delphine M.Y. Rolando ◽  
Claire Sauty-Colace ◽  
...  

SummaryRecent studies have uncovered thousands of long non-coding RNAs (IncRNAs) in human pancreatic β cells. β cell lncRNAs are often cell type-specific, and exhibit dynamic regulation during differentiation or upon changing glucose concentrations. Although these features hint at a role of lncRNAs in β cell gene regulation and diabetes, the function of β cell lncRNAs remains largely unknown. In this study, we investigated the function of β cell-specific lncRNAs and transcription factors using transcript knockdowns and co-expression network analysis. This revealed lncRNAs that function in concert with transcription factors to regulate β cell-specific transcriptional networks. We further demonstrate that lncRNA PLUTO affects local three-dimensional chromatin structure and transcription of PDX1, encoding a key β cell transcription factor, and that both PLUTO and PDX1 are downregulated in islets from donors with type 2 diabetes or impaired glucose tolerance. These results implicate lncRNAs in the regulation of β cell-specific transcription factor networks.


2012 ◽  
Vol 302 (3) ◽  
pp. G277-G286 ◽  
Author(s):  
Anders Krüger Olsen ◽  
Mette Boyd ◽  
Erik Thomas Danielsen ◽  
Jesper Thorvald Troelsen

Upon developmental or environmental cues, the composition of transcription factors in a transcriptional regulatory network is deeply implicated in controlling the signature of the gene expression and thereby specifies the cell or tissue type. Novel methods including ChIP-chip and ChIP-Seq have been applied to analyze known transcription factors and their interacting regulatory DNA elements in the intestine. The intestine is an example of a dynamic tissue where stem cells in the crypt proliferate and undergo a differentiation process toward the villus. During this differentiation process, specific regulatory networks of transcription factors are activated to target specific genes, which determine the intestinal cell fate. The expanding genomewide mapping of transcription factor binding sites and construction of transcriptional regulatory networks provide new insight into how intestinal differentiation occurs. This review summarizes the current overview of the transcriptional regulatory networks driving epithelial differentiation in adult intestine. The novel technologies that have been implied to study these networks are presented and their prospects for implications in future research are also addressed.


2014 ◽  
Vol 462 (3) ◽  
pp. 397-413 ◽  
Author(s):  
Asuka Eguchi ◽  
Garrett O. Lee ◽  
Fang Wan ◽  
Graham S. Erwin ◽  
Aseem Z. Ansari

Transcription factors control the fate of a cell by regulating the expression of genes and regulatory networks. Recent successes in inducing pluripotency in terminally differentiated cells as well as directing differentiation with natural transcription factors has lent credence to the efforts that aim to direct cell fate with rationally designed transcription factors. Because DNA-binding factors are modular in design, they can be engineered to target specific genomic sequences and perform pre-programmed regulatory functions upon binding. Such precision-tailored factors can serve as molecular tools to reprogramme or differentiate cells in a targeted manner. Using different types of engineered DNA binders, both regulatory transcriptional controls of gene networks, as well as permanent alteration of genomic content, can be implemented to study cell fate decisions. In the present review, we describe the current state of the art in artificial transcription factor design and the exciting prospect of employing artificial DNA-binding factors to manipulate the transcriptional networks as well as epigenetic landscapes that govern cell fate.


2019 ◽  
Vol 19 (6) ◽  
pp. 413-425 ◽  
Author(s):  
Athanasios Alexiou ◽  
Stylianos Chatzichronis ◽  
Asma Perveen ◽  
Abdul Hafeez ◽  
Ghulam Md. Ashraf

Background:Latest studies reveal the importance of Protein-Protein interactions on physiologic functions and biological structures. Several stochastic and algorithmic methods have been published until now, for the modeling of the complex nature of the biological systems.Objective:Biological Networks computational modeling is still a challenging task. The formulation of the complex cellular interactions is a research field of great interest. In this review paper, several computational methods for the modeling of GRN and PPI are presented analytically.Methods:Several well-known GRN and PPI models are presented and discussed in this review study such as: Graphs representation, Boolean Networks, Generalized Logical Networks, Bayesian Networks, Relevance Networks, Graphical Gaussian models, Weight Matrices, Reverse Engineering Approach, Evolutionary Algorithms, Forward Modeling Approach, Deterministic models, Static models, Hybrid models, Stochastic models, Petri Nets, BioAmbients calculus and Differential Equations.Results:GRN and PPI methods have been already applied in various clinical processes with potential positive results, establishing promising diagnostic tools.Conclusion:In literature many stochastic algorithms are focused in the simulation, analysis and visualization of the various biological networks and their dynamics interactions, which are referred and described in depth in this review paper.


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