Project description:Bread wheat (Triticum aestivum) has a large, complex and hexaploid genome consisting of A, B and D homoeologous chromosome sets. Therefore each wheat gene potentially exists as a trio of A, B and D homoeoalleles, each of which may contribute differentially to wheat phenotypes. We describe a novel approach combining wheat cytogenetic resources (chromosome substitution ‘nullisomic-tetrasomic’ lines) with next generation deep sequencing of gene transcripts (RNA-seq), to directly and accurately identify homoeologue-specific single nucleotide variants and quantify the relative homoeoallelic contribution to gene expression. We obtained mRNA-Seq datasets from non-normalized cDNA libraries created from shoot and root tissues of the euploid bread wheat cultivar Chinese Spring, from which the nullitetra lines are derived, from complete sets of chromosome 1 and 5 nullitetras, and from extant relatives of the diploid A (Triticum urartu) and D (Aegilops tauschii) genome donors, herein referred to as A and D genome diploids
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: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: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. Total eight (three stress, one control and four tissue specific small RNA libraries were pepared and sequenced independently [wheat control (WC), wheat high temperature stressed (WHTS), wheat salinity stressed (WSS) and wheat drought stressed (WDS), wheat shoot(WSH), wheat leaf (WLF), wheat flower(WFL), wheat root(WRT)] on Illumina GAIIx
Project description:We monitored by RNAseq the transcriptomic response of roots and leaves of Triticum aestivum cv chinese Spring during a long term interaction with Funneliformis mossae (2 months) with or without a pathogen infection by infiltration of Xanthomonas translucens CFBP 2054. The control condition of roots and leaves wheat without mycorhizal fungi is in E-MTAB-5891 (material produced simultaneously and treated at the same time).
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: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 1BS by hybridizing the newly developed INRA GDEC Triticum aestivum NimbleGen 12x40k unigenes microarray (A-MEXP-2314) with 3D-pools of MTP BACs of from the 1BS physical map. By hybridizing the BAC pools with the wheat NimbleGen 40K unigenes chip we managed to map almost 1063 unigenes on the wheat chromosome 1BS BACs. By comparison with 454 sequences and Illumina survey sequence contigs from the sorted chromosome 1BS, we confirmed the assignation of 849 unigenes in individual BACs from the chromosome 1BS. This data allowed us to study the organization of the wheat gene space along chromosome 1BS. The sequences of the unigenes helped to perform synteny and evolutionary analyses of these unigenes. DNA from MTP clones were pooled into 3D manner: library of MTP clones was stored in 17 plates of 384 wells (24 columns x 16 rows); plate1 pool consist of mixture of DNA from all MTP clones situated in plate 1, Row A pool consist of mixture of DNA from all MTP clones situated in Rows A (from all 17 plates, etc). The set of positive plate, column and row pools for the unigene (represented in microarray) allow to detect the list of putative positive clones (clones from the intersection of positive pools, cleaned using information on physical intersection clones based on clone fingerprints). Hence, all 57 experiments (17 for plate pools, 24 for column pools, and 16 for row pools) have the same experimental factor.