Project description:To better understand the regulatory mechanisms of water stress response in wheat, the transcript profiles in roots of two wheat genotypes, namely, drought tolerant 'Luohan No.2' (LH) and drought susceptible 'Chinese Spring' (CS) under water-stress were comparatively analyzed by using the Affymetrix wheat GeneChip®. A total of 3831 transcripts displayed 2-fold or more expression changes, 1593 transcripts were induced compared with 2238 transcripts were repressed, in LH under water-stress; Relatively fewer transcripts were drought responsive in CS, 1404 transcripts were induced and 1493 were repressed. Comparatively, 569 transcripts were commonly induced and 424 transcripts commonly repressed in LH and CS under water-stress. 689 transcripts (757 probe sets) identified from LH and 537 transcripts (575 probe sets) from CS were annotated and classified into 10 functional categories, and 74 transcripts derived from 80 probe sets displayed the change ratios no less than 16 in LH or CS. Several kinds of candidate genes were differentially expressed between the LH and CS, which could be responsible for the difference in drought tolerance of the two genotypes. Two common wheat (Triticum aestivum L.) cultivars, Luohan No.2 (LH) and Chinese Spring (CS), were used for this study. Seedlings at the two leaf stage were stressed by cultured in PEG solutions for 6h, and some other seedlings were cultured in tap water as control. Root samples of LH and CS at 6h after the stress treatment and untreated control were prepared for microarray analysis.
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: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: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: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.