E-GEOD-64228
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: PRJNA270487
PROVIDER: E-GEOD-64228 | ExpressionAtlas | 2015-11-20
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-GEOD-64228-analysis-methods.tsv | Tabular | |||
| E-GEOD-64228-atlasExperimentSummary.Rdata | Rdata | |||
| E-GEOD-64228-configuration.xml | Xml | |||
| E-GEOD-64228-percentile-ranks.tsv | Tabular | |||
| E-GEOD-64228.condensed-sdrf.tsv | Tabular |
Items per page: 5 1 - 5 of 91 |
Similar Datasets
Project description:Expression data of leaves from transgenic barley expressing wheat Lr34 gene
| PRJNA270487 | ENA
Project description:Barley contains a much higher content of bioactive substances than wheat. In order to investigate the effect of genome interaction between barley and wheat on phytosterol content, we used a series of barley chromosome addition lines of common wheat. The wheat 38k-microarray was utilized for screening of genes with expression levels specifically increased by an additive effect or synergistic action between wheat and barley chromosomes. We determined the overall expression pattern of genes related to phytosterol biosynthesis in wheat and in each addition line. Together with determining the phytosterol levels of wheat, barley and each addition line, we assess the critical genes in the phytosterol pathway that can be expressed to promote phytosterol levels. Gene expression levels of each barley chromosome addition line of common wheat were compared to that of common wheat. Total RNA samples were isolated from the 2-week-old seedling leaves. The experiments were replicated three times for each addition line using independent samples.
2011-12-08 | E-GEOD-28023 | biostudies-arrayexpress
Project description:The wheat gene Lr34 (Yr18/Pm38/Sr57/Ltn1) encodes a putative ABCG-type of transporter and is a unique source of disease resistance providing durable and partial resistance against multiple fungal pathogens. Lr34 has been found to be functional as a transgene in barley. We used microarrays to decipher the changes in global gene expression governed by Lr34 expression in barley. Leaves from two independent lines of transgenic barley plants were selected at seedling (two weeks old plants) and mature (six weeks old plants) stages of development for RNA extraction and hybridization on Affymetrix microarrays. We used three biological replicates for expression profiles. Wild type plants served as controls.
2015-07-01 | E-GEOD-64228 | biostudies-arrayexpress
Project description:Barley contains a much higher content of bioactive substances than wheat. In order to investigate the effect of genome interaction between barley and wheat on phytosterol content, we used a series of barley chromosome addition lines of common wheat. The wheat 38k-microarray was utilized for screening of genes with expression levels specifically increased by an additive effect or synergistic action between wheat and barley chromosomes. We determined the overall expression pattern of genes related to phytosterol biosynthesis in wheat and in each addition line. Together with determining the phytosterol levels of wheat, barley and each addition line, we assess the critical genes in the phytosterol pathway that can be expressed to promote phytosterol levels.
2011-12-08 | GSE28023 | GEO
Project description:The analysis of gene expression during wheat development: Gene expression measurements were carried out on a developmental tissue series for wild-type wheat (cv. Chinese Spring) using the Affymetrix Wheat GeneChip. Thirteen tissues at defined developmental stages were chosen to match the barley (cv. Morex) tissue series of Druka et al. 2006 that used the Affymetrix Barley1 GeneChip. Three replicates of: root tissue at two different developmental stages, leaf, crown, caryopsis, anther, pistil, inflorescence, bracts, mesocotyl, endosperm, embryo and coleoptiles were hybridised. Comparisons between this wheat data and the barley dataset were performed and are available at http://contigcomp.acpfg.com.au [PLEXdb(http://www.plexdb.org) has submitted this series at GEO on behalf of the original contributor, Tim Sutton. The equivalent experiment is TA3 at PLEXdb.]
2009-08-11 | GSE12508 | GEO
Project description:Puccinia graminis f. sp. tritici is the cause of wheat stem rust. A microarray was designed from genes predicted from the P. graminis f. sp. tritici genome assembly, and gene expression measured for four conditions which include wheat or barley infecting growth stages initiated by urediniospores. mRNA was prepared from fresh urediniospores, uredinospores germinated for 24 hr, wheat seedlings infected with urediniospores for 8 days, and barley seedlings infected with urediniospores for 8 days. The asexual uredinial infection cycle on wheat produces additional urediniospores, which can start new cycles of wheat infection and are readily spread by aerial transport. This expression data is further described in Duplessis et al, Obligate Biotrophy Features Unraveled by the Genomic Analysis of the Rust Fungi, Melampsora larici-populina and Puccinia graminis f. sp. tritici
2010-12-31 | GSE25020 | GEO
Project description:<p>Rust fungi are plant pathogens that cause epidemics which threatens the production of many important plant species, such as wheat, soy, coffee and poplar. Melampsora larici-populina (Mlp) causes the poplar rust and encodes at least 1184 candidate effectors (CEs), however their functions are poorly known. In this study, we analysed the transcriptome and metabolome of Arabidopsis constitutively expressing CEs of Mlp to discover processes targeted by these fungal proteins. For this purpose, we sequenced the transcriptome and used mass spectrometry to analyse the metabolome of Arabidopsis plants expressing one of 14 selected CEs and of a control line. We found 2299 deregulated genes in at least one of the 14 transgenic lines. Among the down-regulated genes, the KEGG pathways “MAPK signaling pathway” and “Plant-pathogen interaction” were over-represented in six and five of the 14 transgenic lines, respectively. Moreover, the genes down-regulated across the fourteen transgenic lines are related to hormone response and defense. </p><p>Regarding the metabolome, there were 680 metabolites deregulated across the 14 transgenic lines, with highly unsaturated and phenolic compounds and peptides enriched among down-regulated and up-regulated metabolites, respectively, in almost all transgenic lines. Interestingly, we found that some transgenic lines expressing CEs with no similarity in amino acid sequence had similar patterns of gene and metabolite deregulation, while plants expressing CEs from the same family deregulated different genes and metabolites. Taken together, our results indicate that the sequence of effectors may not be a good predictor of its impact in the plant.</p>
2020-12-03 | MTBLS2096 | MetaboLights
Project description:Background: MicroRNAs regulate various biological processes in plants. Considerable data are available on miRNAs involved in the development of rice, maize and barley. In contrast, little is known about miRNAs and their functions in the development of wheat. In this study, five small RNA (sRNA) libraries from wheat seedlings, flag leaves, and developing seeds were developed and sequenced to identify miRNAs and understand their functions in wheat development. Results: Twenty-four known miRNAs belonging to 15 miRNA families were identified from 18 MIRNA loci in wheat in the present study, including 15 (9 MIRNA loci) first identified in wheat, 13 miRNA families (16 MIRNA loci) being highly conserved and 2 (2 MIRNAs loci) moderately conserved. In addition, fifty-five novel miRNAs were also identified. The potential target genes for 15 known miRNAs and 37 novel miRNAs were predicted using strict criteria, and these target genes are involved in a wide range of biological functions. Four of the 15 known miRNA families and 22 of the 55 novel miRNAs were preferentially expressed in the developing seeds with logarithm of the fold change of 1.0～7.6, and half of them were seed-specific, suggesting that they participate in regulating wheat seed development and metabolism. From 5 days post-anthesis to 20 days post-anthesis, miR164 and miR160 increased in abundance in developing seeds, whereas miR169 decreased, suggesting their coordinating functions in the different developmental stages of wheat seed. Moreover, eight known miRNA families and 28 novel miRNAs exhibited tissue-biased expression in wheat flag leaves, with the logarithm of the fold changes of 0.5～5.2. The putative targets of these tissue-preferential miRNAs were involved in various metabolism and biological processes, suggesting complexity of the regulatory networks in different tissues. Our data also suggested that wheat flag leaves have more complicated regulatory networks of miRNAs than developing seeds. Conclusions: Our work identified and characterised wheat miRNAs, their targets and expression patterns. This study is the first to elucidate the regulatory networks of miRNAs involved in wheat flag leaves and developing seeds, and provided a foundation for future studies on specific functions of these miRNAs.
2017-01-01 | GSE50524 | GEO
Project description:Background Because of its size, allohexaploid nature and high repeat content, the wheat genome has always been perceived as too complex for efficient molecular studies. However, we recently constructed the first physical map of a wheat chromosome (3B). But gene mapping is still laborious in wheat because of high redundancy between the three homoeologous genomes. In contrast, in the closely related diploid species, barley, numerous gene-based markers have been developed. This study aims at combining the unique genomic resources developed in wheat and barley to decipher the organisation of gene space on wheat chromosome 3B. Results Three dimensional pools of the minimal tiling path of wheat chromosome 3B physical map were hybridized to a barley Agilent 15K expression microarray. This led to the identification of 738 barley genes with a homolog on wheat chromosome 3B. In addition, comparative analyses revealed that 68% of the genes identified were syntenic between the wheat chromosome 3B and barley chromosome 3H and 59% between wheat chromosome 3B and rice chromosome 1, together with some wheat-specific rearrangements. Finally, it indicated an increasing gradient of gene density from the centromere to the telomeres positively correlated with the number of genes clustered in islands on wheat chromosome 3B. Conclusion Our study shows that novel structural genomics resources now available in wheat and barley can be combined efficiently to overcome specific problems of genetic anchoring of physical contigs in wheat and to perform high-resolution comparative analyses with rice for deciphering the organisation of the wheat gene space.
2010-12-02 | E-TABM-1011 | biostudies-arrayexpress
Project description:We performed RNA-sequencing of Bgh-infected barley leaves at two different time-points after infection to examine gene expression in the barley powdery mildew isolate DH14 during plant pathogenesis.
2018-05-30 | GSE106282 | GEO