scholarly journals CSTDB: A Crop Stress-tolerance Gene and Protein Database Integrated by Convolutional Neural Networks

2018 ◽  
Author(s):  
Di Zhang ◽  
Yi Yue ◽  
Yang Zhao ◽  
Chao Wang ◽  
Xi Cheng ◽  
...  
Keyword(s):  
Stress Tolerance ◽  
Abiotic Stress Tolerance ◽  
Sequence Information ◽  
Protein Database ◽  
Crop Species ◽  
Biotic Stresses ◽  
Tolerance Gene ◽  
As Stress ◽  
User Friendly ◽  
Id Protein

AbstractNumerous studies have shown that many genes and proteins in plants are involved in the regulation of plant resistance to abiotic and biotic stresses. The researches on the stress tolerance of crops are also the focus of many researchers. To provides a reliable platform for collecting and retrieving genetic and protein information related to stress tolerance found in crops, we constructed CSTDB(Crops Stress-tolerance Database), an integrated database that includes stress-tolerance genes and proteins for many crop species. The database was developed based on convolutional neural network technology. It is a web-accessible database that contains detailed information on the stress-tolerance genes and proteins of major crop species. Currently, the database records four major crops containing 1,371 abiotic stress-tolerance genes or proteins, and 207 genes or proteins associated with biotic stress. Each gene and protein has detailed functional information and sequence information, such as stress types, Genbank ID, Pubmed ID, Protein ID, 3D model picture and FASTA files. As a user-friendly browsing tool, this database provides search functions, BALST functions and file download functions. CSTDB can be a valuable resource, which is designed to meet the broad needs of researchers working on crops stress-tolerance experiments. Database URL: http://pcsb.ahau.edu.cn:8080/CSTDB

scholarly journals Ectopic expression of the sesame MYB transcription factor SiMYB305 promotes root growth and modulates ABA-mediated tolerance to drought and salt stresses in Arabidopsis

AoB Plants ◽  
2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Komivi Dossa ◽  
Marie A Mmadi ◽  
Rong Zhou ◽  
Aili Liu ◽  
Yuanxiao Yang ◽  
...  
Keyword(s):  
Abiotic Stress ◽  
Root Growth ◽  
Stress Tolerance ◽  
Cell Damage ◽  
Abiotic Stress Tolerance ◽  
Stomatal Closure ◽  
Ectopic Expression ◽  
Myb Transcription Factor ◽  
Marker Genes ◽  
Crop Species

Abstract An increasing number of candidate genes related to abiotic stress tolerance are being discovered and proposed to improve the existing cultivars of the high oil-bearing crop sesame (Sesamum indicum L.). However, the in planta functional validation of these genes is remarkably lacking. In this study, we cloned a novel sesame R2-R3 MYB gene SiMYB75 which is strongly induced by drought, sodium chloride (NaCl), abscisic acid (ABA) and mannitol. SiMYB75 is expressed in various sesame tissues, especially in root and its protein is predicted to be located in the nucleus. Ectopic over-expression of SiMYB75 in Arabidopsis notably promoted root growth and improved plant tolerance to drought, NaCl and mannitol treatments. Furthermore, SiMYB75 over-expressing lines accumulated higher content of ABA than wild-type plants under stresses and also increased sensitivity to ABA. Physiological analyses revealed that SiMYB75 confers abiotic stress tolerance by promoting stomatal closure to reduce water loss; inducing a strong reactive oxygen species scavenging activity to alleviate cell damage and apoptosis; and also, up-regulating the expression levels of various stress-marker genes in the ABA-dependent pathways. Our data suggested that SiMYB75 positively modulates drought, salt and osmotic stresses responses through ABA-mediated pathways. Thus, SiMYB75 could be a promising candidate gene for the improvement of abiotic stress tolerance in crop species including sesame.

scholarly journals Transcription Factors Associated with Abiotic and Biotic Stress Tolerance and Their Potential for Crops Improvement

Genes ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 771 ◽  
Author(s):  
Baillo ◽  
Kimotho ◽  
Zhang ◽  
Xu
Keyword(s):  
Transcription Factors ◽  
Stress Tolerance ◽  
Stress Responses ◽  
Biotic Stress ◽  
Crop Improvement ◽  
Abiotic And Biotic Stress ◽  
Crop Species ◽  
Biotic Stresses ◽  
Wide Range ◽  
Tf Gene

In field conditions, crops are adversely affected by a wide range of abiotic stresses including drought, cold, salt, and heat, as well as biotic stresses including pests and pathogens. These stresses can have a marked effect on crop yield. The present and future effects of climate change necessitate the improvement of crop stress tolerance. Plants have evolved sophisticated stress response strategies, and genes that encode transcription factors (TFs) that are master regulators of stress-responsive genes are excellent candidates for crop improvement. Related examples in recent studies include TF gene modulation and overexpression approaches in crop species to enhance stress tolerance. However, much remains to be discovered about the diverse plant TFs. Of the >80 TF families, only a few, such as NAC, MYB, WRKY, bZIP, and ERF/DREB, with vital roles in abiotic and biotic stress responses have been intensively studied. Moreover, although significant progress has been made in deciphering the roles of TFs in important cereal crops, fewer TF genes have been elucidated in sorghum. As a model drought-tolerant crop, sorghum research warrants further focus. This review summarizes recent progress on major TF families associated with abiotic and biotic stress tolerance and their potential for crop improvement, particularly in sorghum. Other TF families and non-coding RNAs that regulate gene expression are discussed briefly. Despite the emphasis on sorghum, numerous examples from wheat, rice, maize, and barley are included. Collectively, the aim of this review is to illustrate the potential application of TF genes for stress tolerance improvement and the engineering of resistant crops, with an emphasis on sorghum.

scholarly journals Manipulation of Ascorbate Biosynthetic, Recycling, and Regulatory Pathways for Improved Abiotic Stress Tolerance in Plants

2020 ◽  
Vol 21 (5) ◽  
pp. 1790 ◽  
Author(s):  
Ronan C. Broad ◽  
Julien P. Bonneau ◽  
Roger P. Hellens ◽  
Alexander A.T. Johnson
Keyword(s):  
Abiotic Stress ◽  
Stress Tolerance ◽  
Abiotic Stresses ◽  
Abiotic Stress Tolerance ◽  
Plant Cells ◽  
Water Soluble ◽  
Upstream Open Reading Frame ◽  
Limiting Factors ◽  
Crop Species ◽  
Regulatory Pathways

Abiotic stresses, such as drought, salinity, and extreme temperatures, are major limiting factors in global crop productivity and are predicted to be exacerbated by climate change. The overproduction of reactive oxygen species (ROS) is a common consequence of many abiotic stresses. Ascorbate, also known as vitamin C, is the most abundant water-soluble antioxidant in plant cells and can combat oxidative stress directly as a ROS scavenger, or through the ascorbate–glutathione cycle—a major antioxidant system in plant cells. Engineering crops with enhanced ascorbate concentrations therefore has the potential to promote broad abiotic stress tolerance. Three distinct strategies have been utilized to increase ascorbate concentrations in plants: (i) increased biosynthesis, (ii) enhanced recycling, or (iii) modulating regulatory factors. Here, we review the genetic pathways underlying ascorbate biosynthesis, recycling, and regulation in plants, including a summary of all metabolic engineering strategies utilized to date to increase ascorbate concentrations in model and crop species. We then highlight transgene-free strategies utilizing genome editing tools to increase ascorbate concentrations in crops, such as editing the highly conserved upstream open reading frame that controls translation of the GDP-L-galactose phosphorylase gene.

scholarly journals The BAG2 and BAG6 Genes are Involved in Multiple Abiotic Stress Tolerance in Arabidopsis Thaliana

2020 ◽  
Author(s):  
Muhammad Arif ◽  
Zitong Li ◽  
Qiong Luo ◽  
Luhua Li ◽  
Yuequan Shen ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
Heat Stress ◽  
Survival Rate ◽  
Stress Tolerance ◽  
Double Mutant ◽  
Abiotic Stress Tolerance ◽  
Drought Treatment ◽  
Positive Role ◽  
Biotic Stresses ◽  
Stress Related Genes

Abstract Background: The BAG (Bcl-2 associated athanogene) family is a multi-functional group of proteins that perform functions ranges from apoptosis to environmental stress tolerance. The BAG proteins are found in yeast, plants and animals. In plants, especially in Arabidopsis thaliana (Arabidopsis), BAG proteins were found to play roles both in abiotic and biotic stresses tolerance including heat, cold, salt, drought, and pathogens. However, the function of Arabidopsis BAG2 remains largely unknown. Whereas BAG6 was found to play important roles in plants response to biotic stresses, it remains unknown whether BAG6 is involved in plants tolerance to abiotic stresses.Results: In this study, we have characterized functions of the Arabidopsis BAG2 and BAG6 genes. Promoter:GUS analysis results show that both BAG2 and BAG6 genes are expressed in various tissues in Arabidopsis thaliana. Expression of both BAG2 and BAG6 genes is induced by salt, mannitol, and heat stress treatments and by the stress-related hormones including ABA, ethylene, and SA, while BAG6 expression is additionally induced by JA. Germination of the bag2 and bag6 single and bag2 bag6 double mutant seeds are less sensitive to ABA than that of the wild type (WT). Both bag2 and bag6 single mutant and bag2 bag6 double mutant show more survival rate than WT in drought treatment but display less survival rate on 45 ℃ heat stress experiment. Consistently, transcription levels of stress-related genes such as RD29A, RD29B and NCED3 are higher in the mutant than that in the WT. Furthermore, these mutants exhibit lower content of reactive oxygen species (ROS) after drought and ABA treatment but higher ROS accumulation after heat treatment than the WT.Conclusion: These results suggest that BAG2 and BAG6 genes are negatively involved in drought stress but play a positive role in heat stress in Arabidopsis.

Genetic engineering for stress tolerance in the Triticeae

1992 ◽  
Vol 99 (3-4) ◽  
pp. 89-106 ◽  
Author(s):  
B. P. Forster
Keyword(s):  
Abiotic Stress ◽  
Genetic Engineering ◽  
Stress Tolerance ◽  
Abiotic Stress Tolerance ◽  
Genetic Maps ◽  
Crop Species ◽  
Dominance Relations ◽  
Stress Genes ◽  
Alien Genes ◽  
Chromosome Segments

SynopsisGenetic variation within a crop species is often limited and restricts improvement by conventional breeding methods. This is particularly true for environmental stresses, both biotic and abiotic. Wild relatives of crop plants, however, provide a rich source of novel variation which can be introduced into the crop. Many alien genes for biotic stress resistance have already been introduced into crops; in contrast, the genetic control of abiotic stress tolerance is poorly understood. Genetic engineering of abiotic stress tolerance in the Triticeae is the main subject discussed here with particular reference to salt tolerance in wheat and barley. Methods of alien gene transfer, including locating tolerance genes and restructuring chromosomes, are described. One of the major limitations in transferring genes for stress tolerance is the lack of good tests for resistance or tolerance which is largely due to the fact the physiological mechanisms involved are not fully understood. Genetic markers provide a new opportunity of detecting chromosome segments carrying desired genes easily and efficiently, and these will become increasingly important as the genetic maps of crop species are expanded. Although many stress genes have been located to specific chromosomes, and some have been mapped intra-chromosomally and their dominance relations determined, there is a great lack of knowledge of the control of these genes at the molecular level. Molecular studies of this type are difficult, but it is anticipated that the limitations will be overcome in the near future.

scholarly journals Recent Advances in Polyamine Metabolism and Abiotic Stress Tolerance

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Parimalan Rangan ◽  
Rajkumar Subramani ◽  
Rajesh Kumar ◽  
Amit Kumar Singh ◽  
Rakesh Singh
Keyword(s):  
Abiotic Stress ◽  
Stress Tolerance ◽  
Metabolic Pathway ◽  
Metabolic Networks ◽  
Abiotic Stress Tolerance ◽  
Stress Factors ◽  
Polyamine Metabolism ◽  
Structural Genes ◽  
Crop Species ◽  
Polyamine Biosynthesis

Global warming is an alarming problem in agriculture and its effect on yield loss has been estimated to be five per cent for every degree centigrade rise in temperature. Plants exhibit multiple mechanisms like optimizing signaling pathway, involvement of secondary messengers, production of biomolecules specifically in response to stress, modulation of various metabolic networks in accordance with stress, and so forth, in order to overcome abiotic stress factors. Many structural genes and networks of pathway were identified and reported in plant systems for abiotic stress tolerance. One such crucial metabolic pathway that is involved in normal physiological function and also gets modulated during stress to impart tolerance is polyamine metabolic pathway. Besides the role of structural genes, it is also important to know the mechanism by which these structural genes are regulated during stress. Present review highlights polyamine biosynthesis, catabolism, and its role in abiotic stress tolerance with special reference to plant systems. Additionally, a system based approach is discussed as a potential strategy to dissect the existing variation in crop species in unraveling the interacting regulatory components/genetic determinants related to PAs mediated abiotic stress tolerance.

Calcium-Dependent Protein Kinases (CDPK) in Abiotic Stress Tolerance

2018 ◽  
Vol 34 (2) ◽  
pp. 259-265 ◽  
Author(s):  
Hemant B Kardile ◽  
◽  
Vikrant ◽  
Nirmal Kant Sharma ◽  
Ankita Sharma ◽  
...  
Keyword(s):  
Abiotic Stress ◽  
Stress Tolerance ◽  
Protein Kinases ◽  
Abiotic Stress Tolerance ◽  
Calcium Dependent ◽  
Dependent Protein ◽  
Calcium Dependent Protein Kinases

pLoc_bal-mPlant: Predict Subcellular Localization of Plant Proteins by General PseAAC and Balancing Training Dataset

2019 ◽  
Vol 24 (34) ◽  
pp. 4013-4022 ◽  
Author(s):  
Xiang Cheng ◽  
Xuan Xiao ◽  
Kuo-Chen Chou
Keyword(s):  
Subcellular Localization ◽  
Basic Research ◽  
Training Dataset ◽  
Sequence Information ◽  
Plant Proteins ◽  
Protein Subcellular Localization ◽  
Computational Tools ◽  
Validation Tests ◽  
User Friendly ◽  
Better Than

Knowledge of protein subcellular localization is vitally important for both basic research and drug development. With the avalanche of protein sequences emerging in the post-genomic age, it is highly desired to develop computational tools for timely and effectively identifying their subcellular localization based on the sequence information alone. Recently, a predictor called “pLoc-mPlant” was developed for identifying the subcellular localization of plant proteins. Its performance is overwhelmingly better than that of the other predictors for the same purpose, particularly in dealing with multi-label systems in which some proteins, called “multiplex proteins”, may simultaneously occur in two or more subcellular locations. Although it is indeed a very powerful predictor, more efforts are definitely needed to further improve it. This is because pLoc-mPlant was trained by an extremely skewed dataset in which some subsets (i.e., the protein numbers for some subcellular locations) were more than 10 times larger than the others. Accordingly, it cannot avoid the biased consequence caused by such an uneven training dataset. To overcome such biased consequence, we have developed a new and bias-free predictor called pLoc_bal-mPlant by balancing the training dataset. Cross-validation tests on exactly the same experimentconfirmed dataset have indicated that the proposed new predictor is remarkably superior to pLoc-mPlant, the existing state-of-the-art predictor in identifying the subcellular localization of plant proteins. To maximize the convenience for the majority of experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc_bal-mPlant/, by which users can easily get their desired results without the need to go through the detailed mathematics.

pLoc_bal-mEuk: Predict Subcellular Localization of Eukaryotic Proteins by General PseAAC and Quasi-balancing Training Dataset

2019 ◽  
Vol 15 (5) ◽  
pp. 472-485 ◽  
Author(s):  
Kuo-Chen Chou ◽  
Xiang Cheng ◽  
Xuan Xiao
Keyword(s):  
Drug Development ◽  
Subcellular Localization ◽  
Basic Research ◽  
The Other ◽  
Training Dataset ◽  
Sequence Information ◽  
Eukaryotic Proteins ◽  
Validation Tests ◽  
User Friendly ◽  
Better Than

<P>Background/Objective: Information of protein subcellular localization is crucially important for both basic research and drug development. With the explosive growth of protein sequences discovered in the post-genomic age, it is highly demanded to develop powerful bioinformatics tools for timely and effectively identifying their subcellular localization purely based on the sequence information alone. Recently, a predictor called “pLoc-mEuk” was developed for identifying the subcellular localization of eukaryotic proteins. Its performance is overwhelmingly better than that of the other predictors for the same purpose, particularly in dealing with multi-label systems where many proteins, called “multiplex proteins”, may simultaneously occur in two or more subcellular locations. Although it is indeed a very powerful predictor, more efforts are definitely needed to further improve it. This is because pLoc-mEuk was trained by an extremely skewed dataset where some subset was about 200 times the size of the other subsets. Accordingly, it cannot avoid the biased consequence caused by such an uneven training dataset. </P><P> Methods: To alleviate such bias, we have developed a new predictor called pLoc_bal-mEuk by quasi-balancing the training dataset. Cross-validation tests on exactly the same experimentconfirmed dataset have indicated that the proposed new predictor is remarkably superior to pLocmEuk, the existing state-of-the-art predictor in identifying the subcellular localization of eukaryotic proteins. It has not escaped our notice that the quasi-balancing treatment can also be used to deal with many other biological systems. </P><P> Results: To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc_bal-mEuk/. </P><P> Conclusion: It is anticipated that the pLoc_bal-Euk predictor holds very high potential to become a useful high throughput tool in identifying the subcellular localization of eukaryotic proteins, particularly for finding multi-target drugs that is currently a very hot trend trend in drug development.</P>

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