Integrative physiological, transcriptome, and metabolomic unveil the chilling responses of two melon genotypes
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ABSTRACT:
PROVIDER: PRJNA938041 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The physiological indicators, transcriptome, and metabolome of two melon varieties with contrasting chilling tolerance (‘162’, chilling-tolerant; ‘13-5A’ ,chilling-sensitive) were analyzed under chilling stress.
2023-02-25 | GSE225921 | GEO
Project description:To understand the molecular mechanisms underlying chilling tolerance in rice, transcriptomic deep sequencing was performed to reveal the differentially expressed genes between chilling tolerance chromosome substitution line (CSL), DC90 and its chilling-sensitive recurrent parent 9311 under early chilling stress events. Our results revealed a set of DEGs with higher basal expression in DC90 by comparison with 9311. They were functionally enriched in GO terms, such as, response to stress, response to stimulus, and response to abiotic stimulus, suggesting their positive role in intrinsic chilling tolerance. Common up-regulated and down-regulated DEGs were enriched in 26 and 34 GO terms, including response to stimulus, response to stress, and response to abiotic stimulus, respectively. Furthermore, comparative transcriptomic analysis between DC90 and 9311 in response to early chilling stress revealed 502 DEGs specifically identified in DC90. Most of gene loci were located beyond introgressed regions, implying that the introgression led to reprogramming of transcriptome in response to early chilling stress. CARMO platform analysis of these DEGs presented a complex regulatory network, including phytohormone signaling, photosynthesis pathway, that coordinately involved in chilling tolerance response of DC90. Here, the unveiled molecular regulatory network shed light on deep understanding the mechanisms of rice chilling tolerance. As well, chilling tolerant-QTLs and co-localized DEGs in introgressed fragments, will be focused for further functional investigation of the molecular mechanisms of early chilling stress response in rice.
2017-06-25 | GSE76415 | GEO
Project description:Rice is sensitive to chilling stress, especially at the seedling stage. To elucidate the molecular genetic mechanisms of chilling tolerance in rice, comprehensive gene expressions of two rice genotypes (chilling-tolerant LTH and chilling-sensitive IR29) with contrasting responses to chilling stress were comparatively analyzed. Results revealed distinct global transcription reprogramming between the two rice genotypes under time-series chilling stress and subsequent recovery conditions. A set of genes with higher basal expression were identified in LTH, indicating their possible role in intrinsic tolerance to chilling stress. Under chilling stress, the major effect on gene expression was up-regulation in LTH and strong repression in IR29. Early responses to chilling stress in both genotypes featured commonly up-regulated genes related to transcription regulation and signal transduction, while functional categories for late phase chilling regulated genes were diverse with a wide range of functional adaptations to continuous stress. Following the cessation of chilling treatments, there was quick and efficient reversion of gene expression in LTH, while IR29 displayed considerably slower recovering capacity at the transcriptional level. In addition, the detection of differentially-regulated TF genes and enriched cis-elements demonstrated that multiple regulatory pathways, including CBF and MYBS3 regulons, were involved in chilling stress tolerance. In present study, comprehensive gene expression using an Affymetrix rice genome array revealed a diverse global transcription reprogramming between two rice genotypes under chilling stress and subsequent recovery conditions. The dominant change in gene expression at low temperature was up-regulation in the chilling-tolerant genotype and down-regulation in the chilling-sensitive genotype. Early responses to chilling stress common to both genotypes featured up-regulated genes related to transcription regulation and signal transduction, while functional categories of LR-chilling regulated genes were clearly diverse with a wide range of functional adaptations. At the end of the chilling treatments, there was quick and efficient reversion of gene expression in LTH, while IR29 displayed considerably slower recovery capacity at the transcriptional level. Finally, analysis of differentially-regulated TF genes and enriched cis-elements demonstrated that multiple regulatory pathways, including CBF and MYBS3 regulons, are involved in chilling stress tolerance.
2012-12-21 | GSE38023 | GEO
Project description:To investigate transcript abundance of flavor-associated genes in fatty acid and amino acid pathways after chilling. We then performed gene expression profiling analysis using data obtained from RNA-seq of 3 different treatments [(A) stored at 4°C for 7 d (without chilling injury), and then transferred to room temperature (~22°C) for 1 d; (B) held at 4°C for 8 d until use (without chilling injury); (C) harvested on day 8 (8 d after the fruits of first two groups). Three replicates of each group were performed, and each replicate has three fruits)].
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Project description:Postharvest chilling diminishes melon flavor via effects on volatile acetate ester biosynthesis.
| PRJNA912112 | ENA
Project description:We used a melon oligo-based microarray to investigate the gene expression responses of two melon genotypes with contrasting resistance to Monosporascus cannonballus at 1 and 3 days after infection
2012-11-30 | E-MEXP-3732 | biostudies-arrayexpress
Project description:Rice is sensitive to chilling stress, especially at the seedling stage. To elucidate the molecular genetic mechanisms of chilling tolerance in rice, comprehensive gene expressions of two rice genotypes (chilling-tolerant LTH and chilling-sensitive IR29) with contrasting responses to chilling stress were comparatively analyzed. Results revealed distinct global transcription reprogramming between the two rice genotypes under time-series chilling stress and subsequent recovery conditions. A set of genes with higher basal expression were identified in LTH, indicating their possible role in intrinsic tolerance to chilling stress. Under chilling stress, the major effect on gene expression was up-regulation in LTH and strong repression in IR29. Early responses to chilling stress in both genotypes featured commonly up-regulated genes related to transcription regulation and signal transduction, while functional categories for late phase chilling regulated genes were diverse with a wide range of functional adaptations to continuous stress. Following the cessation of chilling treatments, there was quick and efficient reversion of gene expression in LTH, while IR29 displayed considerably slower recovering capacity at the transcriptional level. In addition, the detection of differentially-regulated TF genes and enriched cis-elements demonstrated that multiple regulatory pathways, including CBF and MYBS3 regulons, were involved in chilling stress tolerance. In present study, comprehensive gene expression using an Affymetrix rice genome array revealed a diverse global transcription reprogramming between two rice genotypes under chilling stress and subsequent recovery conditions. The dominant change in gene expression at low temperature was up-regulation in the chilling-tolerant genotype and down-regulation in the chilling-sensitive genotype. Early responses to chilling stress common to both genotypes featured up-regulated genes related to transcription regulation and signal transduction, while functional categories of LR-chilling regulated genes were clearly diverse with a wide range of functional adaptations. At the end of the chilling treatments, there was quick and efficient reversion of gene expression in LTH, while IR29 displayed considerably slower recovery capacity at the transcriptional level. Finally, analysis of differentially-regulated TF genes and enriched cis-elements demonstrated that multiple regulatory pathways, including CBF and MYBS3 regulons, are involved in chilling stress tolerance. In this study, parallel transcriptomic analysis in two rice genotypes with contrasting chilling-tolerant phenotypes was performed to identify and characterize novel genes involved in chilling stress tolerance in rice.
2012-12-21 | E-GEOD-38023 | biostudies-arrayexpress
Project description:Chilling is a major stress to plants of subtropical and tropical origins including maize. To reveal molecular mechanisms underlying chilling tolerance and chilling survival, we investigated maize transcriptome responses to chilling stress in differentiated leaves and roots as well as in crowns with meristem activity for survival. Chilling stress on maize shoots and roots is found to each contribute to seedling lethality in maize. Comparison of maize lines with different chilling tolerance capacity reveals that chilling survival in maize is highly associated with upregulation in leaves and crowns of abscisic acid response pathway, transcriptional regulators and cold response as well as downregulation of heat response in crowns. Comparison of chilling treatment on whole and part of the plants reveals that response to distal-chilling is very distinct from, and sometimes opposite to, response to local- or whole-plant chilling in both leaves and roots, suggesting a communication between shoots and roots in environmental perception. In sum, this study details chilling responses in leaves, roots and crowns and reveals potential chilling survival mechanism in maize, which lays ground for further understanding survival and tolerance mechanisms under low but non-freezing temperatures in tropical and subtropical plants.
2023-07-14 | GSE167881 | GEO
Project description:Jiashi melon and 86-1 melon were inoculated with Alternaria alternata, and the difference of gene expression was analyzed after 0, 6, 12, 18 and 24 days storage.
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Project description:Viruses are among the most destructive and difficult to control plant pathogens. Melon (Cucumismelo L.) has become the model species for the agriculturally important Cucurbitaceae family. Approaches that take advantage of recently developed genomic tools in melon are being extremely useful for understanding viral pathogenesis and can contribute to the identification of target genes to breed new resistant cultivars. In this work, we have used a recently described melon microarray for transcriptome profiling of two melon cultivars infected with two strains of Melon necrotic spot virus (MNSV) that only differ on their 3´-untranslated regions. Tissues of melon plants from cultivars Out of 7566 and 7074 genes deregulated by MNSV-Mα5 and MNSV-Mα5/3’264, 1851 and 1356, respectively, were strain-specific. Likewise, MNSV-Mα5/3’264 specifically deregulated 2925 and 1618 genes in Planters Jumbo and Tendral, respectively. Thus, significantly affected GO categories were clearly different for the different virus/host combinations. Grouping genes according to their patterns of expression allowed the identification of two groups specifically deregulated by MNSV-Mα5/3’264 with respect to MNSV-Mα5 in Tendral, and one group antagonistically regulated in Planters Jumbo vs. Tendral after MNSV-Mα5/3’264 infection. Genes in these three groups belong to a diversity of functional classes, and no obvious regulatory commonalities were identified. When data on MNSV-Mα5/Tendral infections were compared to equivalent data on cucumber mosaic virus or watermelon mosaic virus infections, cytokinin-O-glucosyltransferase2 was identified as the only gene deregulated by the three viruses, with infections dynamics correlating with the amplitude of transcriptome remodeling. Both common and strain-specific changes, as well as common but also cultivar-specific changes, have been identified by profiling transcriptomes of plants from two melon cultivars infected with two MNSV strains. No obvious regulatory features shared among deregulated genes have been identified, pointing toward regulation through differential functional implications. Viruses are among the most destructive and difficult to control plant pathogens. Melon (Cucumismelo L.) has become the model species for the agriculturally important Cucurbitaceae family. Approaches that take advantage of recently developed genomic tools in melon are being extremely useful for understanding viral pathogenesis and can contribute to the identification of target genes to breed new resistant cultivars. In this work, we have used a recently described melon microarray for transcriptome profiling of two melon cultivars infected with two strains of Melon necrotic spot virus (MNSV) that only differ on their 3´-untranslated regions. Tissues of melon plants from cultivars Out of 7566 and 7074 genes deregulated by MNSV-Mα5 and MNSV-Mα5/3’264, 1851 and 1356, respectively, were strain-specific. Likewise, MNSV-Mα5/3’264 specifically deregulated 2925 and 1618 genes in Planters Jumbo and Tendral, respectively. Thus, significantly affected GO categories were clearly different for the different virus/host combinations. Grouping genes according to their patterns of expression allowed the identification of two groups specifically deregulated by MNSV-Mα5/3’264 with respect to MNSV-Mα5 in Tendral, and one group antagonistically regulated in Planters Jumbo vs. Tendral after MNSV-Mα5/3’264 infection. Genes in these three groups belong to a diversity of functional classes, and no obvious regulatory commonalities were identified. When data on MNSV-Mα5/Tendral infections were compared to equivalent data on cucumber mosaic virus or watermelon mosaic virus infections, cytokinin-O-glucosyltransferase2 was identified as the only gene deregulated by the three viruses, with infections dynamics correlating with the amplitude of transcriptome remodeling. Both common and strain-specific changes, as well as common but also cultivar-specific changes, have been identified by profiling transcriptomes of plants from two melon cultivars infected with two MNSV strains. No obvious regulatory features shared among deregulated genes have been identified, pointing toward regulation through differential functional implications.
2016-06-07 | GSE74835 | GEO