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 ◽  
...  

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.

mSystems ◽  
2017 ◽  
Vol 2 (5) ◽  
Author(s):  
Cynthia L. Darnell ◽  
Peter D. Tonner ◽  
Jordan G. Gulli ◽  
Scott C. Schmidler ◽  
Amy K. Schmid

ABSTRACT To ensure survival in the face of stress, microorganisms employ inducible damage repair pathways regulated by extensive and complex gene networks. Many archaea, microorganisms of the third domain of life, persist under extremes of temperature, salinity, and pH and under other conditions. In order to understand the cause-effect relationships between the dynamic function of the stress network and ultimate physiological consequences, this study characterized the physiological role of nearly one-third of all regulatory proteins known as transcription factors (TFs) in an archaeal organism. Using a unique quantitative phenotyping approach, we discovered functions for many novel TFs and revealed important secondary functions for known TFs. Surprisingly, many TFs are required for resisting multiple stressors, suggesting cross-regulation of stress responses. Through extensive validation experiments, we map the physiological roles of these novel TFs in stress response back to their position in the regulatory network wiring. This study advances understanding of the mechanisms underlying how microorganisms resist extreme stress. Given the generality of the methods employed, we expect that this study will enable future studies on how regulatory networks adjust cellular physiology in a diversity of organisms. Gene regulatory networks (GRNs) are critical for dynamic transcriptional responses to environmental stress. However, the mechanisms by which GRN regulation adjusts physiology to enable stress survival remain unclear. Here we investigate the functions of transcription factors (TFs) within the global GRN of the stress-tolerant archaeal microorganism Halobacterium salinarum. We measured growth phenotypes of a panel of TF deletion mutants in high temporal resolution under heat shock, oxidative stress, and low-salinity conditions. To quantitate the noncanonical functional forms of the growth trajectories observed for these mutants, we developed a novel modeling framework based on Gaussian process regression and functional analysis of variance (FANOVA). We employ unique statistical tests to determine the significance of differential growth relative to the growth of the control strain. This analysis recapitulated known TF functions, revealed novel functions, and identified surprising secondary functions for characterized TFs. Strikingly, we observed that the majority of the TFs studied were required for growth under multiple stress conditions, pinpointing regulatory connections between the conditions tested. Correlations between quantitative phenotype trajectories of mutants are predictive of TF-TF connections within the GRN. These phenotypes are strongly concordant with predictions from statistical GRN models inferred from gene expression data alone. With genome-wide and targeted data sets, we provide detailed functional validation of novel TFs required for extreme oxidative stress and heat shock survival. Together, results presented in this study suggest that many TFs function under multiple conditions, thereby revealing high interconnectivity within the GRN and identifying the specific TFs required for communication between networks responding to disparate stressors. IMPORTANCE To ensure survival in the face of stress, microorganisms employ inducible damage repair pathways regulated by extensive and complex gene networks. Many archaea, microorganisms of the third domain of life, persist under extremes of temperature, salinity, and pH and under other conditions. In order to understand the cause-effect relationships between the dynamic function of the stress network and ultimate physiological consequences, this study characterized the physiological role of nearly one-third of all regulatory proteins known as transcription factors (TFs) in an archaeal organism. Using a unique quantitative phenotyping approach, we discovered functions for many novel TFs and revealed important secondary functions for known TFs. Surprisingly, many TFs are required for resisting multiple stressors, suggesting cross-regulation of stress responses. Through extensive validation experiments, we map the physiological roles of these novel TFs in stress response back to their position in the regulatory network wiring. This study advances understanding of the mechanisms underlying how microorganisms resist extreme stress. Given the generality of the methods employed, we expect that this study will enable future studies on how regulatory networks adjust cellular physiology in a diversity of organisms.


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

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.


2019 ◽  
Vol 20 (24) ◽  
pp. 6324 ◽  
Author(s):  
Hironori Hojo ◽  
Shinsuke Ohba

Chondrogenesis is a key developmental process that molds the framework of our body and generates the skeletal tissues by coupling with osteogenesis. The developmental processes are well-coordinated by spatiotemporal gene expressions, which are hardwired with gene regulatory elements. Those elements exist as thousands of modules of DNA sequences on the genome. Transcription factors function as key regulatory proteins by binding to regulatory elements and recruiting cofactors. Over the past 30 years, extensive attempts have been made to identify gene regulatory mechanisms in chondrogenesis, mainly through biochemical approaches and genetics. More recently, newly developed next-generation sequencers (NGS) have identified thousands of gene regulatory elements on a genome scale, and provided novel insights into the multiple layers of gene regulatory mechanisms, including the modes of actions of transcription factors, post-translational histone modifications, chromatin accessibility, the concept of pioneer factors, and three-dimensional chromatin architecture. In this review, we summarize the studies that have improved our understanding of the gene regulatory mechanisms in chondrogenesis, from the historical studies to the more recent works using NGS. Finally, we consider the future perspectives, including efforts to improve our understanding of the gene regulatory landscape in chondrogenesis and potential applications to the treatment of chondrocyte-related diseases.


2020 ◽  
Author(s):  
C. A. Brackley ◽  
N. Gilbert ◽  
D. Michieletto ◽  
A. Papantonis ◽  
M. C. F. Pereira ◽  
...  

The discovery that overexpressing one or a few critical transcription factors can switch cell state suggests that gene regulatory networks are relatively simple. In contrast, genome-wide association studies (GWAS) point to complex phenotypes being determined by hundreds of loci that rarely encode transcription factors and which individually have small effects. Here, we use computer simulations and a simple fitting-free polymer model of chromosomes to show that spatial correlations arising from 3D genome organisation naturally lead to stochastic and bursty transcription plus complex small-world regulatory networks (where the transcriptional activity of each genomic region subtly affects almost all others). These effects require factors to be present at sub-saturating levels; increasing levels dramatically simplifies networks as more transcription units are pressed into use. Consequently, results from GWAS can be reconciled with those involving overexpression. We apply this pan-genomic model to predict patterns of transcriptional activity in whole human chromosomes, and, as an example, the effects of the deletion causing the diGeorge syndrome.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Arthur I. Dergilev ◽  
Nina G. Orlova ◽  
Oxana B. Dobrovolskaya ◽  
Yuriy L. Orlov

Abstract The development of high-throughput genomic sequencing coupled with chromatin immunoprecipitation technologies allows studying the binding sites of the protein transcription factors (TF) in the genome scale. The growth of data volume on the experimentally determined binding sites raises qualitatively new problems for the analysis of gene expression regulation, prediction of transcription factors target genes, and regulatory gene networks reconstruction. Genome regulation remains an insufficiently studied though plants have complex molecular regulatory mechanisms of gene expression and response to environmental stresses. It is important to develop new software tools for the analysis of the TF binding sites location and their clustering in the plant genomes, visualization, and the following statistical estimates. This study presents application of the analysis of multiple TF binding profiles in three evolutionarily distant model plant organisms. The construction and analysis of non-random ChIP-seq binding clusters of the different TFs in mammalian embryonic stem cells were discussed earlier using similar bioinformatics approaches. Such clusters of TF binding sites may indicate the gene regulatory regions, enhancers and gene transcription regulatory hubs. It can be used for analysis of the gene promoters as well as a background for transcription networks reconstruction. We discuss the statistical estimates of the TF binding sites clusters in the model plant genomes. The distributions of the number of different TFs per binding cluster follow same power law distribution for all the genomes studied. The binding clusters in Arabidopsis thaliana genome were discussed here in detail.


2015 ◽  
Author(s):  
Anton Crombach ◽  
Karl R Wotton ◽  
Eva Jimenez-Guri ◽  
Johannes Jaeger

Developmental gene networks implement the dynamic regulatory mechanisms that pattern and shape the organism. Over evolutionary time, the wiring of these networks changes, yet the patterning outcome is often preserved, a phenomenon known as “system drift”. System drift is illustrated by the gap gene network—involved in segmental patterning—in dipteran insects. In the classic model organismDrosophila melanogasterand the non-model scuttle flyMegaselia abdita, early activation and placement of gap gene expression domains show significant quantitative differences, yet the final patterning output of the system is essentially identical in both species. In this detailed modeling analysis of system drift, we use gene circuits which are fit to quantitative gap gene expression data inM. abditaand compare them to an equivalent set of models fromD. melanogaster. The results of this comparative analysis show precisely how compensatory regulatory mechanisms achieve equivalent final patterns in both species. We discuss the larger implications of the work in terms of “genotype networks” and the ways in which the structure of regulatory networks can influence patterns of evolutionary change (evolvability).


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
C. A. Brackley ◽  
N. Gilbert ◽  
D. Michieletto ◽  
A. Papantonis ◽  
M. C. F. Pereira ◽  
...  

AbstractThe discovery that overexpressing one or a few critical transcription factors can switch cell state suggests that gene regulatory networks are relatively simple. In contrast, genome-wide association studies (GWAS) point to complex phenotypes being determined by hundreds of loci that rarely encode transcription factors and which individually have small effects. Here, we use computer simulations and a simple fitting-free polymer model of chromosomes to show that spatial correlations arising from 3D genome organisation naturally lead to stochastic and bursty transcription as well as complex small-world regulatory networks (where the transcriptional activity of each genomic region subtly affects almost all others). These effects require factors to be present at sub-saturating levels; increasing levels dramatically simplifies networks as more transcription units are pressed into use. Consequently, results from GWAS can be reconciled with those involving overexpression. We apply this pan-genomic model to predict patterns of transcriptional activity in whole human chromosomes, and, as an example, the effects of the deletion causing the diGeorge syndrome.


2021 ◽  
Author(s):  
Chris Brackley ◽  
Nick Gilbert ◽  
Davide Michieletto ◽  
Argyris Papantonis ◽  
Maria Pereira ◽  
...  

Abstract The discovery that overexpressing one or a few critical transcription factors can switch cell state suggests that gene regulatory networks are relatively simple. In contrast, genome-wide association studies (GWAS) point to complex phenotypes being determined by hundreds of loci that rarely encode transcription factors and which in- dividually have small effects. Here, we use computer simulations and a simple fitting-free polymer model of chromosomes to show that spatial correlations arising from 3D genome organisation naturally lead to stochastic and bursty transcription as well as complex small-world regulatory networks (where the transcriptional activity of each genomic region subtly affects almost all others). These effects require factors to be present at sub-saturating levels; increasing levels dramatically simplifiies networks as more transcription units are pressed into use. Consequently, results from GWAS can be reconciled with those involving overexpression. We apply this pan-genomic model to predict patterns of transcriptional activity in whole human chromosomes, and, as an example, the effects of the deletion causing the diGeorge syndrome.


2021 ◽  
Author(s):  
Maryam Mehmood ◽  
Muhammad Jadoon Khan ◽  
Muhammad Jawad Khan ◽  
Nadeem Akhtar ◽  
Fizza Mughal ◽  
...  

Abstract Sesame is a very ancient oilseed crop. Sesame sensitivity to drought stress at early seedling stage is one of the limiting factors affecting its growth and yield in the world. HD-ZIP transcription factors family is one of the most important families involved in drought stress responses in plants. In this study, total sixty one sesame HD-ZIP (SiHZ) proteins were identified in sesame, based on protein sequence homology with Arabidopsis and protein domain(s) architectures were predicted by Hidden Markov model (HMM). HD-ZIP proteins were then classified into four classes (HD-ZIP Class I-IV) according to the phylogenetic, conserved domain(s) motifs and gene structure analyses in sesame. Based on comparative phylogenetic analysis of sesame with Arabidopsis and maize HD-ZIP protein sequences, HD-ZIP Class I was subdivided into four subgroups α (SiHZ25, SiHZ43, SiHZ9 and SiHZ16), β1 (SiHZ10, SiHZ30, SiHZ32 and SiHZ26), β2 (SiHZ42 and SiHZ45) and (SiHZ17, SiHZ7 and SiHZ35). Twenty-one days old Sesame seedling were exposed to severe drought stress by withholding water for 7 days. Gene expression of 13 members of HD-ZIP Class I was performed in well- watered (control) and water stressed (treatment) seedlings. The results of gene expression analysis showed that, SiHZ7 (6.8 fold) and SiHZ35 (2.6 fold) from subgroup showed significantly high gene expression levels under drought stress in sesame seedlings. Thus, this study provides useful molecular information pinpointing the role SiHD-ZIP Class I in drought stress responses at early seedling stage and to develop sesame novel varieties with improved drought tolerance in sesame.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Micheale Yifter Weldemichael ◽  
Yemane Tsehaye Baryatsion ◽  
Desta Berhe Sbhatu ◽  
Girmay Gebresamuel Abraha ◽  
Hagos Mohammedseid Juhar ◽  
...  

The emerging oilseed crop Sesamum indicum, also known as the queen of oilseeds, is being grown globally for its oil content for medicinal and nutritional values. One of the key challenges of sesame cultivation is its low productivity. In the present study, sodium azide (NaN3) was used as a chemical mutagen. The aim of this study was to examine the effect of NaN3 on quantitative and qualitative stem traits in the M2 generation of Ethiopian sesame (Sesamum indicum L.) genotypes. Seeds of fourteen sesame genotypes were used in this study and germinated and grown under greenhouse conditions. Different qualitative and quantitative data were collected and analyzed. Traits such as plant height, ground distance to first distance, and internode length were significantly affected by NaN3 treatment. The highest plant height was recorded in the control on Humera 1 and Baha Necho genotypes, while the lowest was observed on Setit 2 and Hirhir treated with the chemical. The highest ground distance to the first branch was observed in Gumero, while the least ground distance was recorded in Setit 1 in the treated and control genotypes, respectively. The best internode length was recorded on Setit 2 and ADI in the control, while the lowest internode length was observed in Setit 1 genotype treated with sodium azide. Genotypes such as ACC44, ADI, Baha Necho, Borkena, Gonder 1, and Setit 1 treated with NaN3 have showed glabrous type of stem hairiness. All the fourteen genotypes (both treated and control) were clustered into four groups. In conclusion, we observed a highly significant variation among the genotypes due the effect of the chemical and genotypes themselves. Hence, this report would create more genetic diversity for further sesame genetic research improvements.


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