Dataset Information

Chilling susceptibility in mungbean varieties is associated with their differentially expressed genes.

ABSTRACT:

Background

Mungbean (Vigna radiata L. Wilczek) is an economically important legume of high nutritional value, however, its cultivation is limited by susceptibility to chilling. Varieties NM94 and VC1973A, with differential susceptibility to stress, serve as good materials for uncovering how they differ in chilling tolerance. This study aimed to identify the ultrastructural, physiological and molecular changes to provide new insights on the differential susceptibility to chilling between varieties VC1973A and NM94.

Results

Chilling stress caused a greater reduction in relative growth rate, a more significant decrease in maximum photochemical efficiency of PSII and DPPH scavenging activity and more-pronounced ultrastructural changes in VC1973A than in NM94 seedlings. Comparative analyses of transcriptional profiles in NM94 and VC1973A revealed that the higher expression of chilling regulated genes (CORs) in NM94. The transcript levels of lipid transfer protein (LTP), dehydrin (DHN) and plant defensin (PDF) in NM94 seedlings after 72 h at 4 °C was higher than that in its parental lines VC1973A, 6601 and VC2768A.

Conclusions

Our results suggested that LTP, DHN and PDF may mediate chilling tolerance in NM94 seedlings.

SUBMITTER: Chen LR

PROVIDER: S-EPMC5432936 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Chilling susceptibility in mungbean varieties is associated with their differentially expressed genes.

Chen Li-Ru LR Ko Chia-Yun CY Folk William R WR Lin Tsai-Yun TY

Botanical studies 20170109 1

<h4>Background</h4>Mungbean (Vigna radiata L. Wilczek) is an economically important legume of high nutritional value, however, its cultivation is limited by susceptibility to chilling. Varieties NM94 and VC1973A, with differential susceptibility to stress, serve as good materials for uncovering how they differ in chilling tolerance. This study aimed to identify the ultrastructural, physiological and molecular changes to provide new insights on the differential susceptibility to chilling between ...[more]

PMID: 28510190

Similar Datasets

Project description:Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs) among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs). However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods. Through analysis of data from experimental microarrays and simulation studies, the proposed model-based approach was shown to provide a more powerful result than the naïve approach and the hierarchical approach. Since our approach is model-based, it is very flexible and can easily handle different types of covariates.

Project description:ObjectiveWound healing is a complex process involving the coordinated interaction of various genes and molecularpathways. The study aimed to uncover novel therapeutic targets, biomarkers and candidate genes for drug developmentto improve successful wound repair interventions.Materials and Methods: This study is a network-meta analysis study. Nine wound healing microarray datasets obtainedfrom the Gene Expression Omnibus (GEO) database were used for this study. Differentially expressed genes (DEGs)were described using the Limma package and shared genes were used as input for weighted gene co-expressionnetwork analysis. The Gene Ontology analysis was performed using the EnrichR web server, and construction of aprotein-protein interaction (PPI) network was achieved by the STRING and Cytoscape.Results: A total of 424 DEGs were determined. A co-expression network was constructed using 7692 shared genesbetween nine data sets, resulting in the identification of seven modules. Among these modules, those with the top 20genes of up and down-regulation were selected. The top down-regulated genes, including TJP1, SEC61A1, PLEK,ATP5B, PDIA6, PIK3R1, SRGN, SDC2, and RBBP7, and the top up-regulated genes including RPS27A, EEF1A1,HNRNPA1, CTNNB1, POLR2A, CFL1, CSNk1E, HSPD1, FN1, and AURKB, which can potentially serve as therapeutictargets were identified. The KEGG pathway analysis found that the majority of the genes are enriched in the "Wntsignaling pathway".Conclusion: In our study of nine wound healing microarray datasets, we identified DEGs and co-expressed modulesusing WGCNA. These genes are involved in important cellular processes such as transcription, translation, and posttranslationalmodifications. We found nine down-regulated genes and ten up-regulated genes, which could serve aspotential therapeutic targets for further experimental validation. Targeting pathways related to protein synthesis and celladhesion and migration may enhance wound healing, but additional experimental validation is needed to confirm theeffectiveness and safety of targeted interventions.

Project description:Ferroptosis-related genes may play a critical regulatory role in the pathogenesis of Crohn's disease (CD). The purpose of the present study was to identify genes expressed in CD that are associated with ferroptosis, and to provide guidance in the diagnosis and therapy of CD. CD mRNA expression data were initially gathered from the Gene Expression Omnibus (GEO) database. GSE75214 and GSE102133 datasets were selected as the major targets and were analyzed for differentially expressed genes (DEGs). Subsequently, R software was used to analyze the common genes among the DEGs between CD and ferroptosis-related genes. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genome pathway analysis were conducted to identify related pathways and functions. Protein-protein interaction (PPI) analysis was performed to identify target genes. The DSigDB website was used to predict potential target drugs for hub genes. Reverse transcription-quantitative (RT-q) PCR was employed to detect the expression of these ferroptosis-related genes in clinical samples obtained from healthy controls and patients with CD. According to the two GEO datasets, 13 ferroptosis DEGs (11 upregulated genes and two downregulated genes) were identified in CD with thresholds of P<0.05 and |log2 fold change|>1, and were selected for further analysis. PPI analysis indicated the mutual effects among these genes and filtered out five hub genes. The top 10 potential targeted drugs were selected. The qPCR results showed that the expression levels of three genes, namely, IL-6, prostaglandin-endoperoxide synthase 2 (PTGS2) and dual oxidase 2 (DUOX2), were different between CD samples and healthy samples. This result was consistent with the results obtained from the bioinformatics analysis. In conclusion, bioinformatics analysis identified a total of 13 ferroptosis-associated genes in CD. Further verification by qPCR showed that IL-6, PTGS2 and DUOX2 may affect the process of CD by regulating ferroptosis. These findings might provide new biomarkers, diagnostic and therapeutic markers for CD.

Dataset Information

Chilling susceptibility in mungbean varieties is associated with their differentially expressed genes.

Background

Results

Conclusions

Publications

Chilling susceptibility in mungbean varieties is associated with their differentially expressed genes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets