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:MS2 data for two Indian varieties of Triticum aestivum L. (Wheat). P1 to P5 files represent MS2 data in positive ESI mode whereas N1 to N5 files represent MS2 data in negative ESI mode.
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:The pistillody mutant wheat (Triticum aestivum L.) plant HTS-1 exhibits homeotic transformation of stamens into pistils or pistil-like structures. Unlike common wheat varieties, HTS-1 produces three to six pistils per floret, potentially increasing the yield. Thus, HTS-1 is highly valuable in the study of floral development in wheat. In this study, we conducted RNA sequencing of the transcriptomes of the pistillody stamen (PS) and the pistil (P) from HTS-1 plants, and the stamen (S) from the non-pistillody control variety Chinese Spring TP to gain insights into pistil and stamen development in wheat.
Project description:We identified the long non-coding RNAs (lncRNAs) in Triticum aestivum infected with Fusarium graminearum by high-throughput RNA sequencing. More than 393 million clean reads were obtained from Illumina Hiseq 4000 system and 126,391 transcripts was identified as high-confidence lncRNAs in T. aestivum against F. graminearum by an integrated approach. Already well over 4,130 of the total 4,276 differentially expressed lncRNAs were specifically expressed at 12 h post-inoculation (hpi), but only 89 of these were specifically expressed at 24 hpi, indicating that the initial stage was the crucial stage for lncRNA-mediated gene regulation of wheat defense against F. graminearum. Target analysis showed the lncRNAs participated in various biological stress processes.
Project description:To improve our understanding of the organization and evolution of the wheat gene space, we established the first map of genes of the wheat chromosome 1BL by hybridizing the newly developed INRA GDEC Triticum aestivum NimbleGen 12x40k unigenes microarray (A-MEXP-2314) with BAC pools from the 1BL physical map as well as with genomic DNA of the sorted chromosome 1BL. By hybridizing the BAC pools with the wheat NimbleGen 40K unigenes chip we managed to map almost 1615 unigenes on the wheat chromosome 1BL BACs. By hybridizing the genomic DNA of the 1BL sorted chromosome and by comparison with 454 sequences from the sorted chromosome 1BL, we confirmed the assignation of 1223 unigenes in individual BACs from the chromosome 1BL. This data allowed us to study the organization of the wheat gene space along chromosome 1BL. The sequences of the unigenes helped to perform synteny and evolutionary analyses of these unigenes.
Project description:To improve the resources for map-based cloning and sequencing of the wheat genome, we established a physical map of the wheat chromosome 1BL with a high density of markers by hybridizing the newly developed INRA GDEC Triticum aestivum NimbleGen 12x17k ISBP microarray (A-MEXP-2312) with BAC pools from the 1BL physical map. Then, we managed to map 3912 ISBP on the wheat chromosome 1BL BACs. The values in the 'Factor Value[individual]' column represent the BAC pool that have been hybridized on the array. For example, the assay 1 correspond to the hybridization of a bulk of all DNA BAC of the plate 1 of the MTP (Minimum Tilling path) BAC library of the chromosome 1BL.
Project description:Wheat is the staple food of over 35% of the world’s population, accounts for 20% of all human calories, and its yield and quality improvement is a focus in the effort to meet new demands from population growth and changing diets. As the complexity of the wheat genome is unravelled, determining how it is used to build the protein machinery of wheat plants is a key next step in explaining detailed aspects of wheat growth and development. The specific functions of wheat organs during vegetative development and the role of metabolism, protein degradation and remobilisation in driving grain production are the foundations of crop performance and have recently become accessible through studies of the wheat proteome. With the aim of creating a resource complementary to current genome sequencing and assembly projects and to aid researchers in the specific analysis and measurement of wheat proteins of interest, we present a large scale, publicly accessible database of identified peptides and proteins derived from the proteome mapping of Triticum aestivum. This current dataset consists of twenty four organ and developmental samples in an online interactive resource allowing the selection, comparison and retrieval of proteomic data with rich biochemical annotation derived from multiple sources. Tissue specific sub-proteomes and ubiquitously expressed markers of the wheat proteome are identified alongside hierarchical assessment of protein functional classes and their presence in different tissues. The impact of wheat’s polyploid genome on proteome analysis and the effect on defining gene specific and protein family relationships is accounted for in the organisation of the data. The dataset will serve as a vehicle to build, refine and deposit confirmed targeted proteomic assays for wheat proteins and protein families to assess function.