Transcriptomics Integrated With Widely Targeted Metabolomics Reveals the Mechanism Underlying Grain Color Formation in Wheat at the Grain-Filling Stage
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ABSTRACT:
SUBMITTER: Li L
PROVIDER: S-EPMC8551455 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:To provide a global study of transcriptome changes under drought stress, the gene expression levels of a durum wheat genotype (Triticum durum Desf. cultivar Creso) and two bread wheat genotypes (Triticum aestivum L. cultivar Chinese Spring -CS- and its deletion line CS_5AL-10) were investigated. The 5A chromosome deletion line (5AL-10) lacks the distal part (43%) of the long arm of chromosome 5A. Each genotype was subjected to two different levels of water stress at the grain filling stage. After anthesis, three different levels of soil water content (SWC) were induced as described below: control (CTRL; SWC=28%), moderate stress (MS; SWC=18%), and severe stress (SS; SWC=12.5%). For each sample, three biological replicates were performed, for a total of 27 hybridizations. ****[PLEXdb(http://www.plexdb.org) has submitted this series at GEO on behalf of the original contributor, Alessio Aprile. The equivalent experiment is TA23 at PLEXdb.]
2011-08-31 | GSE31759 | GEO
Project description:To provide a global study of transcriptome changes under drought stress, the gene expression levels of a durum wheat genotype (Triticum durum Desf. cultivar Creso) and two bread wheat genotypes (Triticum aestivum L. cultivar Chinese Spring -CS- and its deletion line CS_5AL-10) were investigated. The 5A chromosome deletion line (5AL-10) lacks the distal part (43%) of the long arm of chromosome 5A. Each genotype was subjected to two different levels of water stress at the grain filling stage. After anthesis, three different levels of soil water content (SWC) were induced as described below: control (CTRL; SWC=28%), moderate stress (MS; SWC=18%), and severe stress (SS; SWC=12.5%). For each sample, three biological replicates were performed, for a total of 27 hybridizations. ****[PLEXdb(http://www.plexdb.org) has submitted this series at GEO on behalf of the original contributor, Alessio Aprile. The equivalent experiment is TA23 at PLEXdb.] genotype: Creso - stress condition: Control(3-replications); genotype: Creso - stress condition: Mild stress(3-replications); genotype: Creso - stress condition: Severe stress(3-replications); genotype: CS - stress condition: Control(3-replications); genotype: CS - stress condition: Mild stress(3-replications); genotype: CS - stress condition: Severe stress(3-replications); genotype: CS-5AL - stress condition: Control(3-replications); genotype: CS-5AL - stress condition: Mild stress(3-replications); genotype: CS-5AL - stress condition: Severe stress(3-replications)
2011-08-30 | E-GEOD-31759 | biostudies-arrayexpress
Project description:Drought stress in Wheat at grain filling stage
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Project description:Durum wheat highly depends on nitrogen for seed development and yield, and the obtainment of varieties with a better nitrogen use efficiency is crucial to reduce production costs and environmental pollution. In this study, sequencing of two small RNA libraries obtained from tissues of Ciccio and Svevo cultivars grown under nitrogen starvation conditions produced 84 novel, and 161 conserved miRNAs. Of these, 7 novel and 13 known miRNAs were newly identified in this work. Quantitative PCR analysis of selected miRNAs highlighted that the expression levels of some of them depends on the tissue and on the cultivar, Svevo being the most responsive to nitrogen starvation. A number of target genes were predicted to be involved in nitrogen metabolism. An inverse correlation for the qPCR expression data of miRNA/target pairs miR399b/PHO2, miR393c/AFB2, ttu-novel-61/CCAAT-TF was observed in specific tissues or cultivar. Especially, ttu-novel-61 was down-regulated and its target CCAAT-TF up-regulated in almost all tissues both in Svevo and in Ciccio. Moreover, CCAAT-TF was confirmed to be cleaved by ttu-novel-61 at the expected site. The discovery of miRNAs involved in the response to nitrogen stress represents an important step towards functional analyses, with the final aim to design strategies for improving nitrogen use efficiency in durum wheat.
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Project description:The rubber tree is the primary source of natural rubber and is mainly cultivated in Southeast Asian countries. Low temperature is the major abiotic stress affecting the yield of the rubber tree. Therefore, uncovering the cold resistance mechanism in the rubber tree is necessary. The present study used RNA-sequencing technology and ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) to analyze the transcriptomic and metabolomic changes in two rubber tree clones with different cold resistance capacities (temperature-sensitive Reyan 8-79 and cold-resistant Yunyan 77-4) at 0 h, 2 h, 6 h, and 20 h of exposure to 4°C. Independent analysis of the transcriptome and metabolitome showed that under prolonged low-temperature treatment, Yunyan 77-4 expressed more genes involved in regulating enzyme activity, changing cell permeability, and synthesizing significant metabolites, such as flavonoids and amino acids, than Reyan 8-79. The KEGG annotation and enrichment analysis identified arginine metabolism and biosynthesis of flavonoids as the major pathway associated with cold resistance. Integrated transcriptome and metabolome analysis showed that the increase in the expression of genes modulated flavonoid biosynthesis, arginine biosynthesis, and anthocyanins biosynthesis, resulting in higher levels of metabolites, such as naringenin chalcone, apigenin, dihydroquercetin, cyanidin 3-glucoside, L-arginosuccinate, N-acetyl-ornithine, ornithine, and N-acetyl-glutamate, in Yunyan 77-4 than in Reyan 8-79 after prolonged low-temperature treatment. Phylogenetic analysis identified the genes, such as CHS (gene356) and F3H (gene33147) of flavonoid biosynthesis and NAGS (gene16028, gene33765), ArgC (gene2487), and ASS (gene6161) of arginine biosynthesis were the key genes involved in the cold resistant of rubber tree. Thus, the present study provides novel insights into how rubber clones resist cold and is a valuable reference for cold-resistance breeding.
| S-EPMC9871781 | biostudies-literature
Project description:Wheat is one of the most significant crops in terms of human consumption in the world. In a climate change scenario, extreme weather event such as heatwaves will be more frequent especially during the grain-filling (GF) stage and could affect grain weight and quality of crops. Molecular mechanisms underlying the response to short heat stress (HS) have been widely reported for the hexaploid wheat (Triticum aestivum) but the regulatory heat stress mechanisms in tetraploid durum wheat (Triticum turgidum ssp. durum) remain partially understood. In this work, we performed a transcriptomic analysis of durum wheat grains to HS during early GF to identify key HS response genes and their predicted regulatory networks under glasshouse conditions.
2021-10-26 | GSE186472 | GEO
Project description:Thousand grain weight is one of the components determining wheat grain yield. It represents the average value of individual grain weights which depends on position within the ear and on positon within the spikelet. Our objective was to quantify the influences of individual floret anthesis date, of carpel weight at anthesis and of rate and duration of grain filling, on variation in individual final grain weight. Two bread wheat cultivars were grown in a greenhouse and their ears were sampled from anthesis through to harvest. Each ear was divided into three parts-basal, central and apical-where the two proximal grains were dissected from each of two spikelets. We analysed (i) the flowering time shift within the ear and within the spikelet; and (ii) the growth kinetics during grain filling in relation to position along the ear. For both cultivars, florets located in the central part of the ear were the first to reach anthesis followed by those in the apical part and then the basal part. Within a spikelet, the floret located nearest the rachis flowered first followed by the more distal ones. We found no significant systematic effect of flowering time-shift on final grain weight. Nevertheless, grains in the central part were heavier than the basal ones (9.75% smaller) and than the apical ones (18.25% smaller). These differences were explained mainly by differences in mean grain filling rates. Analysis of growth kinetics enabled an improved explanation of the variability of individual grain weight along the ear.
| S-EPMC6312219 | biostudies-literature
Project description:Individual grain weight is a major yield component in wheat. To provide a comprehensive understanding of grain weight determination, the carpel size at anthesis, grain dry matter accumulation, grain water uptake and loss, grain morphological expansion, and final grain weight at different positions within spikelets were investigated in a recombinant inbred line mapping population of bread wheat (Triticum aestivum L.)×spelt (Triticum spelta L.). Carpel size, grain dry matter and water accumulation, and grain dimensions interacted strongly with each other. Furthermore, larger carpels, a faster grain filling rate, earlier and longer grain filling, more grain water, faster grain water absorption and loss rates, and larger grain dimensions were associated with higher grain weight. Frequent quantitative trait locus (QTL) coincidences between these traits were observed, particularly those on chromosomes 2A, 3B, 4A, 5A, 5DL, and 7B, each of which harboured 16-49 QTLs associated with >12 traits. Analysis of the allelic effects of coincident QTLs confirmed their physiological relationships, indicating that the complex but orderly grain filling processes result mainly from pleiotropy or the tight linkages of functionally related genes. After grain filling, distal grains within spikelets were smaller than basal grains, primarily due to later grain filling and a slower initial grain filling rate, followed by synchronous maturation among different grains. Distal grain weight was improved by increased assimilate availability from anthesis. These findings provide deeper insight into grain weight determination in wheat, and the high level of QTL coincidences allows simultaneous improvement of multiple grain filling traits in breeding.
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Project description:Phenolic compounds are important bioactive phytochemicals with potential health benefits. In this study, integrated metabolomics and transcriptomics analysis was used to analyze the metabolites and differentially expressed genes in grains of two wheat cultivars (HPm512 with high antioxidant activity, and ZM22 with low antioxidant activity) during grain development. A total of 188 differentially expressed phenolic components, including 82 phenolic acids, 81 flavonoids, 10 lignans, and 15 other phenolics, were identified in the developing wheat grains, of which apigenin glycosides were identified as the primary flavonoid component. The relative abundance of identified phenolics showed a decreasing trend with grain development. Additionally, 51 differentially expressed phenolic components were identified between HPm512 and ZM22, of which 41 components, including 23 flavonoids, were up-regulated in HPm512. In developing grain, most of the identified differentially expressed genes involved in phenolic accumulation followed a similar trend. Integrated metabolomics and transcriptomics analysis revealed that certain genes encoding structural proteins, glycosyltransferase, and transcription factors were closely related to metabolite accumulation. The relatively higher accumulation of phenolics in HPm512 could be due to up-regulated structural and regulatory genes. A sketch map was drawn to depict the synthetic pathway of identified phenolics and their corresponding genes. This study enhanced the current understanding of the accumulation of phenolics in wheat grains. Besides, active components and their related genes were also identified, providing crucial information for the improvement of wheat's nutritional quality.
| S-EPMC8888538 | biostudies-literature
Project description:Grain filling is essential for wheat yield formation, but is very susceptible to environmental stresses, such as high temperatures, especially in the context of global climate change. Grain RGB images include rich color, shape, and texture information, which can explicitly reveal the dynamics of grain filling. However, it is still challenging to further quantitatively predict the days after anthesis (DAA) from grain RGB images to monitor grain development.ResultsThe WheatGrain dataset revealed dynamic changes in color, shape, and texture traits during grain development. To predict the DAA from RGB images of wheat grains, we tested the performance of traditional machine learning, deep learning, and few-shot learning on this dataset. The results showed that Random Forest (RF) had the best accuracy of the traditional machine learning algorithms, but it was far less accurate than all deep learning algorithms. The precision and recall of the deep learning classification model using Vision Transformer (ViT) were the highest, 99.03% and 99.00%, respectively. In addition, few-shot learning could realize fine-grained image recognition for wheat grains, and it had a higher accuracy and recall rate in the case of 5-shot, which were 96.86% and 96.67%, respectively.Materials and methodsIn this work, we proposed a complete wheat grain dataset, WheatGrain, which covers thousands of wheat grain images from 6 DAA to 39 DAA, which can characterize the complete dynamics of grain development. At the same time, we built different algorithms to predict the DAA, including traditional machine learning, deep learning, and few-shot learning, in this dataset, and evaluated the performance of all models.ConclusionsTo obtain wheat grain filling dynamics promptly, this study proposed an RGB dataset for the whole growth period of grain development. In addition, detailed comparisons were conducted between traditional machine learning, deep learning, and few-shot learning, which provided the possibility of recognizing the DAA of the grain timely. These results revealed that the ViT could improve the performance of deep learning in predicting the DAA, while few-shot learning could reduce the need for a number of datasets. This work provides a new approach to monitoring wheat grain filling dynamics, and it is beneficial for disaster prevention and improvement of wheat production.
| S-EPMC10708398 | biostudies-literature