Project description:This SuperSeries is composed of the following subset Series:; GSE5937: wheat expression level polymorphism study parental genotypes 2 biological reps from SB location; GSE5939: Wheat expression level polymorphism study 36 genotypes 2 biological reps from SB location Experiment Overall Design: Refer to individual Series
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.
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: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: To identify abiotic stress responsive and tissue specific miRNAs at genome wide level in wheat (Triticum aestivum) Results: Small RNA libraries were constructed from four tissues (root, shoot, mature leaf and spikelets) and three stress treatments of wheat seedlings (control, high temperature, salinity and water-deficit). A total of 59.5 million reads were obtained by high throughput sequencing of eight wheat libraries, of which 32.5 million reads were found to be unique. Using UEA sRNA workbench we identified 47 conserved miRNAs belonging to 20 families, 1030 candidate novel and 51 true novel miRNAs. Several of these miRNAs displayed tissue specific expression whereas few were found to be responsive to abiotic stress treatments. Target genes were predicted for miRNAs identified in this study and their grouping into functional categories revealed that the putative targets were involved in diverse biological processes. RLM-RACE of predicted targets of three conserved miRNAs (miR156, miR160 and miR164) confirmed their mRNA cleavage, thus indicating their regulation at post-transcriptional level by corresponding miRNAs. Expression profiling of confirmed target genes of these miRNAs was also performed. Conclusions: This is the first comprehensive study on profiling of miRNAs in a variety of tissues and in response to several abiotic stresses in wheat. Our findings provide valuable resource for better understanding on the role of miRNAs in stress tolerance as well as plant development. Additionally, this information could be utilized for designing wheat plants for enhanced abiotic stress tolerance and higher productivity.
Project description:The responses to waterlogging stress of two wheat genotypes including one sensitive and one resistant were systematic investigated. The labeling-based quantitative proteomic analysis was conducted in parallel on these two genotypes in responding to waterlogging for 1-3 days, 951 and 320 differentially expressed proteins (DEP) were detected in the during treat, and 270 DEPs were shared. The results might help to reveal the regulatory mechanism of waterlogging stress tolerance in wheat.
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.