scholarly journals TaLBD1, a LOB Transcription Factor Gene In T. Aestivum, Improves Plant N Starvation Adaptation Via Modulating N Acquisition-Associated Processes

2021 ◽  
Author(s):  
Yanyang Zhang ◽  
Chenyang Ni ◽  
Tianjiao Li ◽  
Le Han ◽  
Pingping Du ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Protein Biosynthesis ◽  
N Uptake ◽  
Root System Architecture ◽  
Starvation Tolerance ◽  
Lateral Organ ◽  
N Starvation ◽  
Pin Genes ◽  
Tf Gene ◽  
Root Tissues

Abstract Members of transcription factor (TF) families contribute largely to plant N starvation tolerance by regulating downstream stress defensive genes. In this study, we characterized TaLBD1, a Lateral Organ Boundary (LOB) TF gene in T. aestivum, in regulating plant low-N stress adaptation. TaLBD1 harbors the conserved domains specified by plant LOB proteins, targeting onto nucleus after endoplasmic reticulum (ER) assortment. The TaLBD1 transcripts were response sensitively to N starvation (NS) signaling, showing to be gradually upregulated in aerial and root tissues over a 27-h NS condition. The N. tabacum lines overexpressing TaLBD1 improved phenotype, root system architecture (RSA) establishment, biomass, and N contents of plants under NS treatment. The nitrate transporter gene NtNRT2.4 and PIN-FORMED gene NtPIN6 significantly upregulated in expression in NS-challenged lines; knockdown expression of NtNRT2.4 decreased N uptake and that of NtPIN6 alleviated RSA establishment relative to WT. These results validate the function of NRT and PIN genes in regulating plant N uptake and RSA behavior. RNA-seq analyses revealed that a quantity of genes modify expression in N-deprived lines overexpressing TaLBD1, which enriched into functional groups of signal transduction, transcription, protein biosynthesis, primary or secondary metabolism, and stress defensiveness. These findings suggested that the TaLBD1-improved NS adaptation attributes largely to its role in transcriptionally regulating NRT and PIN genes as well as in modulating those functional in various biological processes. TaLBD1 is a crucial regulator in plant N starvation tolerance and valuable target for molecular breeding high N use efficiency (NUE) crop cultivars.

scholarly journals Signaling Responses to N Starvation: Focusing on Wheat and Filling the Putative Gaps With Findings Obtained in Other Plants. A Review

2021 ◽  
Vol 12 ◽  
Author(s):  
Lingan Kong ◽  
Yunxiu Zhang ◽  
Wanying Du ◽  
Haiyong Xia ◽  
Shoujin Fan ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Target Genes ◽  
Current Knowledge ◽  
N Uptake ◽  
Root System Architecture ◽  
Root Branching ◽  
Biochemical Processes ◽  
N Starvation ◽  
N Acquisition ◽  
Physiological And Biochemical

Wheat is one of the most important food crops worldwide. In recent decades, fertilizers, especially nitrogen (N), have been increasingly utilized to maximize wheat productivity. However, a large proportion of N is not used by plants and is in fact lost into the environment and causes serious environmental pollution. Therefore, achieving a low N optimum via efficient physiological and biochemical processes in wheat grown under low-N conditions is highly important for agricultural sustainability. Although N stress-related N capture in wheat has become a heavily researched subject, how this plant adapts and responds to N starvation has not been fully elucidated. This review summarizes the current knowledge on the signaling mechanisms activated in wheat plants in response to N starvation. Furthermore, we filled the putative gaps on this subject with findings obtained in other plants, primarily rice, maize, and Arabidopsis. Phytohormones have been determined to play essential roles in sensing environmental N starvation and transducing this signal into an adjustment of N transporters and phenotypic adaptation. The critical roles played by protein kinases and critical kinases and phosphatases, such as MAPK and PP2C, as well as the multifaceted functions of transcription factors, such as NF-Y, MYB, DOF, and WRKY, in regulating the expression levels of their target genes (proteins) for low-N tolerance are also discussed. Optimization of root system architecture (RSA) via root branching and thinning, improvement of N acquisition and assimilation, and fine-tuned autophagy are pivotal strategies by which plants respond to N starvation. In light of these findings, we attempted to construct regulatory networks for RSA modification and N uptake, transport, assimilation, and remobilization.

Characterization on TaMPK14, an MAPK family gene of wheat, in modulating N-starvation response through regulating N uptake and ROS homeostasis

2020 ◽  
Vol 39 (10) ◽  
pp. 1285-1299
Author(s):  
Meihua Shi ◽  
Zhuo Wang ◽  
Zifei Ma ◽  
Wenteng Song ◽  
Wenjing Lu ◽  
...  
Keyword(s):  
N Uptake ◽  
Starvation Response ◽  
Ros Homeostasis ◽  
N Starvation ◽  
Family Gene

scholarly journals Accurate differential analysis of transcription factor activity from gene expression

2018 ◽  
Author(s):  
Viren Amin ◽  
Murat Can Cobanoglu
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Expression Data ◽  
Differential Analysis ◽  
Gene Regulatory ◽  
Context Specific ◽  
Tf Gene ◽  
Perturbation Estimation

AbstractWe present EPEE (Effector and Perturbation Estimation Engine), a method for differential analysis of transcription factor (TF) activity from gene expression data. EPEE addresses two principal challenges in the field, namely incorporating context-specific TF-gene regulatory networks, and accounting for the fact that TF activity inference is intrinsically coupled for all TFs that share targets. Our validations in well-studied immune and cancer contexts show that addressing the overlap challenge and using state-of-the-art regulatory networks enable EPEE to consistently produce accurate results. (Accessible at: https://github.com/Cobanoglu-Lab/EPEE)

scholarly journals The Candida glabrata Upc2A transcription factor is a global regulator of antifungal drug resistance pathways

PLoS Genetics ◽  
2021 ◽  
Vol 17 (9) ◽  
pp. e1009582
Author(s):  
Bao Gia Vu ◽  
Mark A. Stamnes ◽  
Yu Li ◽  
P. David Rogers ◽  
W. Scott Moye-Rowley
Keyword(s):  
Transcription Factor ◽  
Membrane Protein ◽  
Candida Glabrata ◽  
Target Genes ◽  
Protein Biosynthesis ◽  
Antifungal Drugs ◽  
Azole Resistance ◽  
Mutant Form ◽  
Pathogenic Yeast ◽  
Genes Encoding

The most commonly used antifungal drugs are the azole compounds, which interfere with biosynthesis of the fungal-specific sterol: ergosterol. The pathogenic yeast Candida glabrata commonly acquires resistance to azole drugs like fluconazole via mutations in a gene encoding a transcription factor called PDR1. These PDR1 mutations lead to overproduction of drug transporter proteins like the ATP-binding cassette transporter Cdr1. In other Candida species, mutant forms of a transcription factor called Upc2 are associated with azole resistance, owing to the important role of this protein in control of expression of genes encoding enzymes involved in the ergosterol biosynthetic pathway. Recently, the C. glabrata Upc2A factor was demonstrated to be required for normal azole resistance, even in the presence of a hyperactive mutant form of PDR1. Using genome-scale approaches, we define the network of genes bound and regulated by Upc2A. By analogy to a previously described hyperactive UPC2 mutation found in Saccharomyces cerevisiae, we generated a similar form of Upc2A in C. glabrata called G898D Upc2A. Analysis of Upc2A genomic binding sites demonstrated that wild-type Upc2A binding to target genes was strongly induced by fluconazole while G898D Upc2A bound similarly, irrespective of drug treatment. Transcriptomic analyses revealed that, in addition to the well-described ERG genes, a large group of genes encoding components of the translational apparatus along with membrane proteins were responsive to Upc2A. These Upc2A-regulated membrane protein-encoding genes are often targets of the Pdr1 transcription factor, demonstrating the high degree of overlap between these two regulatory networks. Finally, we provide evidence that Upc2A impacts the Pdr1-Cdr1 system and also modulates resistance to caspofungin. These studies provide a new perspective of Upc2A as a master regulator of lipid and membrane protein biosynthesis.

scholarly journals A microRNA-transcription factor module regulates lateral organ size and patterning in Arabidopsis

2009 ◽  
Vol 58 (3) ◽  
pp. 450-463 ◽  
Author(s):  
Clayton T. Larue ◽  
Jiangqi Wen ◽  
John C. Walker
Keyword(s):  
Transcription Factor ◽  
Organ Size ◽  
Factor Module ◽  
Lateral Organ

scholarly journals Signaling pathways underlying nitrogen-dependent changes in root system architecture: from model to crop species

2020 ◽  
Vol 71 (15) ◽  
pp. 4393-4404 ◽  
Author(s):  
Zhongtao Jia ◽  
Nicolaus von Wirén
Keyword(s):  
Nutritional Status ◽  
Root System ◽  
System Architecture ◽  
Molecular Mechanisms ◽  
N Uptake ◽  
Root System Architecture ◽  
Water Soluble ◽  
Organic N ◽  
Limiting Factor ◽  
Crop Species

Abstract Among all essential mineral elements, nitrogen (N) is required in the largest amounts and thus is often a limiting factor for plant growth. N is taken up by plant roots in the form of water-soluble nitrate, ammonium, and, depending on abundance, low-molecular weight organic N. In soils, the availability and composition of these N forms can vary over space and time, which exposes roots to various local N signals that regulate root system architecture in combination with systemic signals reflecting the N nutritional status of the shoot. Uncovering the molecular mechanisms underlying N-dependent signaling provides great potential to optimize root system architecture for the sake of higher N uptake efficiency in crop breeding. In this review, we summarize prominent signaling mechanisms and their underlying molecular players that derive from external N forms or the internal N nutritional status and modulate root development including root hair formation and gravitropism. We also compare the current state of knowledge of these pathways between Arabidopsis and graminaceous plant species.

scholarly journals NetREX: Network Rewiring using EXpression - Towards Context Specific Regulatory Networks

2017 ◽  
Author(s):  
Yijie Wang ◽  
Dong-Yeon Cho ◽  
Hangnoh Lee ◽  
Justin Fear ◽  
Brian Oliver ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Regulatory Network ◽  
Gene Network ◽  
Regulatory Networks ◽  
Tissue Type ◽  
Expression Data ◽  
Gene Regulatory ◽  
Context Specific ◽  
Tf Gene ◽  
Biological Context

AbstractUnderstanding gene regulation is a fundamental step towards understanding of how cells function and respond to environmental cues and perturbations. An important step in this direction is the ability to infer the transcription factor (TF)-gene regulatory network (GRN). However gene regulatory networks are typically constructed disregarding the fact that regulatory programs are conditioned on tissue type, developmental stage, sex, and other factors. Due to lack of the biological context specificity, these context-agnostic networks may not provide insight for revealing the precise actions of genes for a specific biological system under concern. Collecting multitude of features required for a reliable construction of GRNs such as physical features (TF binding, chromatin accessibility) and functional features (correlation of expression or chromatin patterns) for every context of interest is costly. Therefore we need methods that is able to utilize the knowledge about a context-agnostic network (or a network constructed in a related context) for construction of a context specific regulatory network.To address this challenge we developed a computational approach that utilizes expression data obtained in a specific biological context such as a particular development stage, sex, tissue type and a GRN constructed in a different but related context (alternatively an incomplete or a noisy network for the same context) to construct a context specific GRN. Our method, NetREX, is inspired by network component analysis (NCA) that estimates TF activities and their influences on target genes given predetermined topology of a TF-gene network. To predict a network under a different condition, NetREX removes the restriction that the topology of the TF-gene network is fixed and allows for adding and removing edges to that network. To solve the corresponding optimization problem, which is non-convex and non-smooth, we provide a general mathematical framework allowing use of the recently proposed Proximal Alternative Linearized Maximization technique and prove that our formulation has the properties required for convergence.We tested our NetREX on simulated data and subsequently applied it to gene expression data in adult females from 99 hemizygotic lines of the Drosophila deletion (DrosDel) panel. The networks predicted by NetREX showed higher biological consistency than alternative approaches. In addition, we used the list of recently identified targets of the Doublesex (DSX) transcription factor to demonstrate the predictive power of our method.

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