scholarly journals Senescence-Associated Glycine max (Gm)NAC Genes: Integration of Natural and Stress-Induced Leaf Senescence

2021 ◽  
Vol 22 (15) ◽  
pp. 8287
Author(s):  
Otto Teixeira Fraga ◽  
Bruno Paes de Melo ◽  
Iana Pedro Silva Quadros ◽  
Pedro Augusto Braga Reis ◽  
Elizabeth Pacheco Batista Fontes
Keyword(s):  
Leaf Senescence ◽  
Gene Networks ◽  
Regulatory Networks ◽  
Developmental Process ◽  
Regulatory Gene ◽  
Functional Class ◽  
Functional Conservation ◽  
Highly Active ◽  
Regulatory Circuit ◽  
Cell Death Program

Leaf senescence is a genetically regulated developmental process that can be triggered by a variety of internal and external signals, including hormones and environmental stimuli. Among the senescence-associated genes controlling leaf senescence, the transcriptional factors (TFs) comprise a functional class that is highly active at the onset and during the progression of leaf senescence. The plant-specific NAC (NAM, ATAF, and CUC) TFs are essential for controlling leaf senescence. Several members of Arabidopsis AtNAC-SAGs are well characterized as players in elucidated regulatory networks. However, only a few soybean members of this class display well-known functions; knowledge about their regulatory circuits is still rudimentary. Here, we describe the expression profile of soybean GmNAC-SAGs upregulated by natural senescence and their functional correlation with putative AtNAC-SAGs orthologs. The mechanisms and the regulatory gene networks underlying GmNAC081- and GmNAC030-positive regulation in leaf senescence are discussed. Furthermore, new insights into the role of GmNAC065 as a negative senescence regulator are presented, demonstrating extraordinary functional conservation with the Arabidopsis counterpart. Finally, we describe a regulatory circuit which integrates a stress-induced cell death program with developmental leaf senescence via the NRP-NAC-VPE signaling module.

scholarly journals Transcription Factors and microRNA Genes Regulatory Network Construction Under Drought Stress in Sesame (Sesamum indicum L.)

2020 ◽  
Author(s):  
Mohammad Amin Baghery ◽  
Seyed Kamal Kazemitabar ◽  
Ali Dehestani ◽  
Pooyan Mehrabanjoubani ◽  
Mohammad Mehdi Naghizadeh ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Drought Stress ◽  
Gene Networks ◽  
Regulatory Networks ◽  
Regulatory Gene ◽  
Sesamum Indicum ◽  
Regulatory Mechanisms ◽  
Oilseed Crop ◽  
Sesame Genotypes ◽  
Almost All

Abstract Background: Drought is one of the most common environmental stresses affecting crops yield and quality. Sesame is an important oilseed crop that most likely faces drought during its growth due to growing in semi-arid and arid areas. Plants responses to drought controlled by regulatory mechanisms. Despite this importance, there is little information about Sesame regulatory mechanisms against drought stress. Results: 458 drought-related genes were identified using comprehensive RNA-seq data analysis of two susceptible and tolerant sesame genotypes under drought stress. These drought-responsive genes were included secondary metabolites biosynthesis-related Like F3H, sucrose biosynthesis-related like SUS2, transporters like SUC2, and protectives like LEA and HSP families. Interactions between identified genes and regulators including TFs and miRNAs were predicted using bioinformatics tools and related regulatory gene networks were constructed. Key regulators and relations of Sesame under drought stress were detected by network analysis. TFs belonged to DREB (DREB2D), MYB (MYB63), ZFP (TFIIIA), bZIP (bZIP16), bHLH (PIF1), WRKY (WRKY30) and NAC (NAC29) families were found among key regulators. mRNAs like miR399, miR169, miR156, miR5685, miR529, miR395, miR396, and miR172 also found as key drought regulators. Furthermore, a total of 117 TFs and 133 miRNAs that might be involved in drought stress were identified with this approach. Conclusions: Most of the identified TFs and almost all of the miRNAs are introduced for the first time as potential regulators of drought response in Sesame. These regulators accompany with identified drought-related genes could be valuable candidates for future studies and breeding programs on Sesame under drought stress. Keywords: Sesamum indicum, Drought stress, Regulatory networks, miRNA, Transcription Factors.

scholarly journals Numerical analysis of a method for a partial integro-differential equation model in regulatory gene networks

2018 ◽  
Vol 28 (10) ◽  
pp. 2069-2095 ◽  
Author(s):  
Antonio A. Alonso ◽  
Rodolfo Bermejo ◽  
Manuel Pájaro ◽  
Carlos Vázquez
Keyword(s):  
Differential Equation ◽  
Numerical Analysis ◽  
Gene Networks ◽  
Regulatory Networks ◽  
Regulatory Gene ◽  
Spatial Dimension ◽  
Equation Model ◽  
Lagrangian Method ◽  
Second Order ◽  
Integro Differential Equation

In this paper, we propose a semi-Lagrangian Runge–Kutta method to approximate the solution of a multidimensional partial integro-differential equation (PIDE) model for regulatory networks involving multiple genes with self- and cross-regulations. For the first time in the literature, we address the numerical analysis of a semi-Lagrangian method for a PIDE model without second-order derivative terms. From this analysis, we obtain second-order convergence in time and space. Moreover, some examples with analytical solution in one spatial dimension illustrate the theoretical results, while others in higher dimensions show the expected behavior of the solution. Finally, the scalability of the method and the comparison with a previously proposed first-order semi-Lagrangian method are discussed.

scholarly journals Global transcriptome profile of the developmental principles of in vitro iPSC-to-motor neuron differentiation

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Emilia Solomon ◽  
Katie Davis-Anderson ◽  
Blake Hovde ◽  
Sofiya Micheva-Viteva ◽  
Jennifer Foster Harris ◽  
...  
Keyword(s):  
Stem Cells ◽  
Neural Stem Cells ◽  
Motor Neuron ◽  
Motor Neurons ◽  
Acetylcholine Receptors ◽  
Gene Networks ◽  
Spinal Cord Injuries ◽  
Regulatory Gene ◽  
Transcriptome Profile

Abstract Background Human induced pluripotent stem cells (iPSC) have opened new avenues for regenerative medicine. Consequently, iPSC-derived motor neurons have emerged as potentially viable therapies for spinal cord injuries and neurodegenerative disorders including Amyotrophic Lateral Sclerosis. However, direct clinical application of iPSC bears in itself the risk of tumorigenesis and other unforeseeable genetic or epigenetic abnormalities. Results Employing RNA-seq technology, we identified and characterized gene regulatory networks triggered by in vitro chemical reprogramming of iPSC into cells with the molecular features of motor neurons (MNs) whose function in vivo is to innervate effector organs. We present meta-transcriptome signatures of 5 cell types: iPSCs, neural stem cells, motor neuron progenitors, early motor neurons, and mature motor neurons. In strict response to the chemical stimuli, along the MN differentiation axis we observed temporal downregulation of tumor growth factor-β signaling pathway and consistent activation of sonic hedgehog, Wnt/β-catenin, and Notch signaling. Together with gene networks defining neuronal differentiation (neurogenin 2, microtubule-associated protein 2, Pax6, and neuropilin-1), we observed steady accumulation of motor neuron-specific regulatory genes, including Islet-1 and homeobox protein HB9. Interestingly, transcriptome profiling of the differentiation process showed that Ca2+ signaling through cAMP and LPC was downregulated during the conversion of the iPSC to neural stem cells and key regulatory gene activity of the pathway remained inhibited until later stages of motor neuron formation. Pathways shaping the neuronal development and function were well-represented in the early motor neuron cells including, neuroactive ligand-receptor interactions, axon guidance, and the cholinergic synapse formation. A notable hallmark of our in vitro motor neuron maturation in monoculture was the activation of genes encoding G-coupled muscarinic acetylcholine receptors and downregulation of the ionotropic nicotinic acetylcholine receptors expression. We observed the formation of functional neuronal networks as spontaneous oscillations in the extracellular action potentials recorded on multi-electrode array chip after 20 days of differentiation. Conclusions Detailed transcriptome profile of each developmental step from iPSC to motor neuron driven by chemical induction provides the guidelines to novel therapeutic approaches in the re-construction efforts of muscle innervation.

scholarly journals Single cell RNA-seq reveals genes vital to in vitro fertilized embryos and parthenotes in pigs

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhi-Qiang Du ◽  
Hao Liang ◽  
Xiao-Man Liu ◽  
Yun-Hua Liu ◽  
Chonglong Wang ◽  
...  
Keyword(s):  
Embryo Development ◽  
Gene Networks ◽  
Regulatory Networks ◽  
Rna Binding ◽  
Expression Patterns ◽  
Early Embryo ◽  
Specific Factor ◽  
Early Embryos ◽  
Genome Activation

AbstractSuccessful early embryo development requires the correct reprogramming and configuration of gene networks by the timely and faithful execution of zygotic genome activation (ZGA). However, the regulatory principle of molecular elements and circuits fundamental to embryo development remains largely obscure. Here, we profiled the transcriptomes of single zygotes and blastomeres, obtained from in vitro fertilized (IVF) or parthenogenetically activated (PA) porcine early embryos (1- to 8-cell), focusing on the gene expression dynamics and regulatory networks associated with maternal-to-zygote transition (MZT) (mainly maternal RNA clearance and ZGA). We found that minor and major ZGAs occur at 1-cell and 4-cell stages for both IVF and PA embryos, respectively. Maternal RNAs gradually decay from 1- to 8-cell embryos. Top abundantly expressed genes (CDV3, PCNA, CDR1, YWHAE, DNMT1, IGF2BP3, ARMC1, BTG4, UHRF2 and gametocyte-specific factor 1-like) in both IVF and PA early embryos identified are of vital roles for embryo development. Differentially expressed genes within IVF groups are different from that within PA groups, indicating bi-parental and maternal-only embryos have specific sets of mRNAs distinctly decayed and activated. Pathways enriched from DEGs showed that RNA associated pathways (RNA binding, processing, transport and degradation) could be important. Moreover, mitochondrial RNAs are found to be actively transcribed, showing dynamic expression patterns, and for DNA/H3K4 methylation and transcription factors as well. Taken together, our findings provide an important resource to investigate further the epigenetic and genome regulation of MZT events in early embryos of pigs.

A study of structural properties of gene network graphs for mathematical modeling of integrated mosaic gene networks

2017 ◽  
Vol 15 (02) ◽  
pp. 1650045 ◽  
Author(s):  
Olga V. Petrovskaya ◽  
Evgeny D. Petrovskiy ◽  
Inna N. Lavrik ◽  
Vladimir A. Ivanisenko
Keyword(s):  
Mathematical Modeling ◽  
Gene Regulatory Networks ◽  
Gene Networks ◽  
Gene Network ◽  
Regulatory Networks ◽  
Network Modeling ◽  
Computer Experiments ◽  
Linear Control ◽  
Expression Of Genes ◽  
Gene Regulatory

Gene network modeling is one of the widely used approaches in systems biology. It allows for the study of complex genetic systems function, including so-called mosaic gene networks, which consist of functionally interacting subnetworks. We conducted a study of a mosaic gene networks modeling method based on integration of models of gene subnetworks by linear control functionals. An automatic modeling of 10,000 synthetic mosaic gene regulatory networks was carried out using computer experiments on gene knockdowns/knockouts. Structural analysis of graphs of generated mosaic gene regulatory networks has revealed that the most important factor for building accurate integrated mathematical models, among those analyzed in the study, is data on expression of genes corresponding to the vertices with high properties of centrality.

scholarly journals From blastocyst to gastrula: gene regulatory networks of embryonic stem cells and early mouse embryogenesis

2014 ◽  
Vol 369 (1657) ◽  
pp. 20130542 ◽  
Author(s):  
David-Emlyn Parfitt ◽  
Michael M. Shen
Keyword(s):  
Stem Cells ◽  
Gene Networks ◽  
Regulatory Networks ◽  
Embryonic Stem ◽  
Cell Lineage ◽  
Network Models ◽  
Cell Types ◽  
Mammalian Development ◽  
A Genome

To date, many regulatory genes and signalling events coordinating mammalian development from blastocyst to gastrulation stages have been identified by mutational analyses and reverse-genetic approaches, typically on a gene-by-gene basis. More recent studies have applied bioinformatic approaches to generate regulatory network models of gene interactions on a genome-wide scale. Such models have provided insights into the gene networks regulating pluripotency in embryonic and epiblast stem cells, as well as cell-lineage determination in vivo . Here, we review how regulatory networks constructed for different stem cell types relate to corresponding networks in vivo and provide insights into understanding the molecular regulation of the blastocyst–gastrula transition.

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.

scholarly journals Novel cancer subtyping method based on patient-specific gene regulatory network

2021 ◽  
Author(s):  
Mai Adachi Nakazawa ◽  
Yoshinori Tamada ◽  
Yoshihisa Tanaka ◽  
Marie Ikeguchi ◽  
Kako Higashihara ◽  
...  
Keyword(s):  
Gene Networks ◽  
Regulatory Networks ◽  
The Cancer Genome Atlas ◽  
Patient Specific ◽  
Specific Gene ◽  
Omics Data ◽  
Cancer Subtypes ◽  
Molecular Systems ◽  
Molecular Features ◽  
Cancer Genome Atlas

The identification of cancer subtypes is important for the understanding of tumor heterogeneity. In recent years, numerous computational methods have been proposed for this problem based on the multi-omics data of patients. It is widely accepted that different cancer subtypes are induced by different molecular regulatory networks. However, only a few incorporate the differences between their molecular systems into the classification processes. In this study, we present a novel method to classify cancer subtypes based on patient-specific molecular systems. Our method quantifies patient-specific gene networks, which are estimated from their transcriptome data. By clustering their quantified networks, our method allows for cancer subtyping, taking into consideration the differences in the molecular systems of patients. Comprehensive analyses of The Cancer Genome Atlas (TCGA) datasets applied to our method confirmed that they were able to identify more clinically meaningful cancer subtypes than the existing subtypes and found that the identified subtypes comprised different molecular features. Our findings show that the proposed method, based on a simple classification using the patient-specific molecular systems, can identify cancer subtypes even with single omics data, which cannot otherwise be captured by existing methods using multi-omics data.

scholarly journals Universal attenuators and their interactions with feedback loops in gene regulatory networks

2016 ◽  
Author(s):  
Dianbo Liu ◽  
Luca Albergante ◽  
Timothy J Newman
Keyword(s):  
Gene Expression ◽  
Gene Regulatory Networks ◽  
Gene Networks ◽  
Regulatory Networks ◽  
Human Cancer ◽  
Cancer Cell Line ◽  
Feedback Loops ◽  
Human Cancer Cell ◽  
E Coli ◽  
Gene Regulatory

AbstractUsing a combination of mathematical modelling, statistical simulation and large-scale data analysis we study the properties of linear regulatory chains (LRCs) within gene regulatory networks (GRNs). Our modelling indicates that downstream genes embedded within LRCs are highly insulated from the variation in expression of upstream genes, and thus LRCs act as attenuators. This observation implies a progressively weaker functionality of LRCs as their length increases. When analysing the preponderance of LRCs in the GRNs of E. coli K12 and several other organisms, we find that very long LRCs are essentially absent. In both E. coli and M. tuberculosis we find that four-gene LRCs are intimately linked to identical feedback loops that are involved in potentially chaotic stress response, indicating that the dynamics of these potentially destabilising motifs are strongly restrained under homeostatic conditions. The same relationship is observed in a human cancer cell line (K562), and we postulate that four-gene LRCs act as “universal attenuators”. These findings suggest a role for long LRCs in dampening variation in gene expression, thereby protecting cell identity, and in controlling dramatic shifts in cell-wide gene expression through inhibiting chaos-generating motifs.In briefWe present a general principle that linear regulatory chains exponentially attenuate the range of expression in gene regulatory networks. The discovery of a universal interplay between linear regulatory chains and genetic feedback loops in microorganisms and a human cancer cell line is analysed and discussed.HighlightsWithin gene networks, linear regulatory chains act as exponentially strong attenuators of upstream variationBecause of their exponential behaviour, linear regulatory chains beyond a few genes provide no additional functionality and are rarely observed in gene networks across a range of different organismsNovel interactions between four-gene linear regulatory chains and feedback loops were discovered in E. coli, M. tuberculosis and human cancer cells, suggesting a universal mechanism of control.

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