Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Transcriptome analysis of three barley varieties in response to barley yellow mosaic disease

ABSTRACT: We used a transcriptome sequencing approach to analyze different expression levels of three barley varieties under both infected and uninfected conditions

ORGANISM(S): Hordeum vulgare

PROVIDER: GSE225976 | GEO | 2023/05/24

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Transcriptome analysis of three barley varieties in response to barley yellow mosaic disease

Project description:Transcriptome analysis of three barley varieties in response to barley yellow mosaic disease

| PRJNA938131 | ENA

Transcriptional analysis in multiple barley varieties identifies signatures of waterlogging response

Project description:Waterlogging leads to major crop losses globally, particularly for waterlogging sensitive crops such as barley. Waterlogging reduces oxygen availability and results in additional stresses, leading to the activation of hypoxia and stress response pathways that promote plant survival. Although certain barley varieties have been shown to be more tolerant to waterlogging than others and some tolerance-related QTLs have been identified, the molecular mechanisms underlying this trait are mostly unknown. Transcriptomics approaches can provide very valuable information for our understanding of waterlogging tolerance. Here, we surveyed 21 barley varieties for the differential transcriptional activation of conserved hypoxia-response genes under waterlogging, and selected five varieties with different levels of induction of core hypoxia-response genes. We further characterized their phenotypic response to waterlogging in terms of shoot and root traits. RNA-sequencing to evaluate the genome-wide transcriptional responses to waterlogging of these selected varieties led to the identification of a set of 98 waterlogging-response genes common to the different datasets. Many of these genes are orthologs of the so-called ‘core hypoxia response genes’, thus highlighting the conservation of plant responses to waterlogging. Hierarchical clustering analysis also identified groups of genes with intrinsic differential expression between varieties prior to waterlogging stress. These genes could constitute interesting candidates to study ‘predisposition’ to waterlogging tolerance or sensitivity in barley.

2023-07-29 | GSE220532 | GEO

RNA-Seq of Pseudomonas fluorescens SBW25 isolated from axenic rhizospheres of the barley varieties Chevallier and Tipple one and five days post-inoculation.

Project description:Pseudomonas fluorescens SBW25 cultures were inoculated into the rhizospheres of barley seedlings of the Chevallier and Tipple varieties growing in axenic cultures. Bacterial cells were collected from the rhizosphere one and five days after inculation and RNA extracted from them. Culture used for inoculation (but not exposed to the rhizospheres) were used as control. The aim of the experiment was to determine the changes in gene expression of P. fluorescens SBW25 upon exposure to barley rhizosphere and also to determine if the rhizospehres of the two varieties of Barley had different effects on gene expression of P. fluorescens SBW25.

2023-05-15 | E-MTAB-12918 | biostudies-arrayexpress

Targeted resequencing of phenology genes in a diverse panel of barley varieties

Project description:We provide raw gene sequences of 174 flowering time regulatory genes and gene othologs across a large barley population (895 barley lines) selected from a collection of landrace, cultivated barley, and research varieties of diverse origin. This set represents the whole variety of cultivated barley lifeforms, namely two- and six-row genotypes with winter, spring, and facultative growth habits. We applied a target capture method based on in-solution hybridization using the myBaits® technology (Arbor Biosciences, Ann Arbour, MI, USA) which is based on in-solution biotinylated RNA probes. Baits were designed for flowering time regulatory genes and gene othologs, and used for production of 80mer capture oligonucleotides for hybridization. Genomic DNA was extracted from leaves of a single two-week old barley plant per variety using the cetyl-trimethyl-ammonium bromide (CTAB) method. Physical shearing of genomic DNA was performed with an average size of 275 bp. Library preparation was conducted with KAPA Hyper Prep Kit (KAPA Biosystems, Wilmington, MA). Hybridization of customised RNA baits with capture pools was performed at 65°C for 24 hours. Each pooled sequence capture library was sequenced on an Illumina HiSeq3000 instrument using three lanes to generate paired-end reads per sample. Genome sequencing was conducted at AgriBio, (Centre for AgriBioscience, Bundoora, VIC, Australia).

2019-02-15 | E-MTAB-7362 | biostudies-arrayexpress

Genome-Wide Analysis of the MADS-box Gene Family Involved in Salt and Waterlogging Tolerance in Barley (Hordeum Vulgare. L)

Project description:To investigate the salt and waterlogging mechanism of barley, we chose salt and waterlogging sensitive and tolerant varieties as subjects. We then performed gene expression profiling analysis using data obtained from RNA-seq of two varieties at two three points.

2023-05-31 | GSE230751 | GEO

Expression data from malting barley seeds

Project description:Malting is seed germination under strictly controlled environmental conditions. Malting quality is a complex phenotype that combines a large number of interrelated components, each of which shows complex inheritance. Currently, only a few genes involved in determining malting quality have been characterized. This study combined transcript profiling with phenotypic correlations to identify candidate genes for malting quality. We used the Barley1 GeneChip® array to identify differentially expressed genes in four malting stages relative to dry seed in the barley variety Morex, and to identify differentially expressed genes among four barley varieties. Keywords: time course and genotype differences

2009-03-05 | GSE11200 | GEO

Transcriptional analysis in multiple barley varieties identifies signatures of waterlogging response

Project description:Transcriptional analysis in multiple barley varieties identifies signatures of waterlogging response

| PRJNA910139 | ENA

Molecular insights into the responses of barley to yellow mosaic disease through transcriptome analysis.

Project description:BackgroundBarley (Hordeum vulgare L.) represents the fourth most essential cereal crop in the world, vulnerable to barley yellow mosaic virus (BaYMV) and/or barley mild mosaic virus (BaMMV), leading to the significant yield reduction. To gain a better understanding of the mechanisms regarding barley crop tolerance to virus infection, we employed a transcriptome sequencing approach and investigated global gene expression among three barley varieties under both infected and control conditions.ResultsHigh-throughput sequencing outputs revealed massive genetic responses, reflected by the barley transcriptome after BaYMV and/or BaMMV infection. Significant enrichments in peptidase complex and protein processing in endoplasmic reticulum were clustered through Gene ontology and KEGG analysis. Many genes were identified as transcription factors, antioxidants, disease resistance genes and plant hormones and differentially expressed between infected and uninfected barley varieties. Importantly, general response genes, variety-specific and infection-specific genes were also discovered. Our results provide useful information for future barley breeding to resist BaYMV and BaMMV.ConclusionsOur study elucidates transcriptomic adaptations in barley response to BaYMV/BaMMV infection through high-throughput sequencing technique. The analysis outcome from GO and KEGG pathways suggests that BaYMV disease induced regulations in multiple molecular-biology processes and signalling pathways. Moreover, critical DEGs involved in defence and stress tolerance mechanisms were displayed. Further functional investigations focusing on these DEGs contributes to understanding the molecular mechanisms of plant response to BaYMV disease infection, thereby offering precious genetic resources for breeding barley varieties resistant to BaYMV disease.

| S-EPMC10197257 | biostudies-literature

Utility of a GFP-expressing Barley yellow mosaic virus for analyzing disease resistance genes.

Project description:The soil-borne plasmodiophorid Polymyxa graminis is a vector for Barley yellow mosaic virus (BaYMV), which can severely damage barley plants. Although 22 disease resistance genes have been identified, only a few have been used for breeding virus-resistant cultivars. Recently, BaYMV strains capable of overcoming the effects of some of these genes have been detected. In this study, green fluorescent protein (GFP)-expressing BaYMV was constructed and used to examine viral dynamics in inoculated barley plants. Leaf inoculations resulted in higher infection rates than root or crown inoculations. Additionally, inoculations of some resistant cultivars produced infections that were similar to those observed in a field test. The results of this study indicate that the GFP-expressing virus is a useful tool for visualizing virus replication and dynamics, and for understanding resistance mechanisms.

| S-EPMC8661491 | biostudies-literature

Impact of barley yellow dwarf virus on the composition of metabolites in

Project description:Greenhouse experiment testing the effects of Barley yellow dwarf virus on Avena sativa and the fate of isotopically labeled MAOM added to soil

2024-04-17 | MSV000094560 | MassIVE

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data