Project description:Wheat (Triticum aestivum) was infiltrated with the Stagonospora nodorum effector protein SnTox3 to identify differentially regulated genes.
Project description:We report a time series RNA-seq experiment involving two isolates of Puccinia graminis separately infecting Triticum aestivum cv. Morocco points post inoculation
Project description:One day cold (14 and 19 °C) and hydrogen peroxide (H2O2) treatment of wheat (Triticum aestivum ssp. aestivum L.) variety Chinese Spring and two chromosome 5A substitution lines of Chinese Spring, Chinese Spring(T. ae. ssp. aestivum L. Cheyenne 5A) and Chinese Spring(T. ae. ssp. spelta L. 5A).
Project description:We used microarrays to detail the Triticum aestivum response to T34 in the presence of different CN concentrations as nitrogen source. Affymdetrix wheat genome array (platform GPL3802) was used.
Project description:Triticum aestivum cultivars Scorpion 25 and Xi 19 were grown under both normal and hot/dry conditions. We compared the effect of these two growth conditions on these two closely related varieties.
Project description:Bread wheat (Triticum aestivum cv. Mace) mature and senescent flag leaves were collected over a 48 h time course in continuous conditions to investigate changes in circadian clock regulation that occur during leaf senescence.
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived Triticum aestivum transcriptome (RNA-seq) profiling methods and to evaluate genotypes associated with resistance against the Wheat dwarf virus. Methods: Triticum aestivum mRNA profiles of genotypes associated with resistance against the Wheat dwarf virus were generated by deep sequencing, in four replicates, using Illumina. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays. Conclusions: Our study represents the first detailed analysis of Triticum aestivum transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA and miRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.
Project description:Mass spectrometry-based wheat proteomics is challenging because the current interpretation of mass spectrometry data relies on public databases that are not exhaustive (UniProtKB/Swiss-Prot) or contain many redundant and poor or un-annotated entries (UniProtKB/TrEMBL). Here we report the development of a manually curated database of the metabolic proteins of Triticum aestivum (hexaploid wheat), named TriMet_DB (Triticum aestivum Metabolic Proteins DataBase). The manually curated TriMet_DB was generated in FASTA format, so that it can be read directly by programs used to interpret the mass spectrometry data. Furthermore, the complete list of entries included in the TriMet_DB is reported in a freely available resource, which includes for each protein the description, the gene code, the protein family,and the allergen name (if any). To evaluate its performance, the TriMet_DB was used to interpret the mass spectrometry data acquired on the metabolic protein fraction extracted from the MEC cultivar of Triticum aestivum.
Project description:To study the transcriptional profiling of seedling roots under different solution pH stresses in winter wheat (Triticum aestivum L.). We identify genes that are differentially expressed in response to different solution pH (4.0 and 10.0) comparing with control pH 6.5 using microarray technology.
