Dataset Information

Comparative transcriptome and metabolome analyses of two strawberry cultivars with different storability.

ABSTRACT: Postharvest storability is an important trait for breeding strawberry (Fragaria × ananassa Duch.). We evaluated the postharvest fruit quality of five strawberry cultivars ('Durihyang', 'Kingsberry', 'Maehyang', 'Seolhyang', and 'Sunnyberry') and identified differences in their fruit ripening during the transition from the big-green to fully-red stage between two cultivars with the highest ('Sunnyberry') and lowest ('Kingsberry') storability, using comparative transcriptome and -metabolome analysis. The differentially expressed genes revealed transcriptome changes related to anthocyanin biosynthesis and cell walls. Consistently, the metabolites of both cultivars showed general changes during ripening along with cultivar-specific characteristics in sugar and amino acid profiles. To identify the genes responsible for storability differences, we surveyed the expression of transcription factors, and found that the expression levels of WRKY31, WRKY70, and NAC83 correlated with delayed senescence and increased storability. Among them, the expression levels of NAC83, and its downstream target genes, in the five cultivars suggested that NAC83 expression can be used to predict postharvest strawberry fruit storability.

SUBMITTER: Min K

PROVIDER: S-EPMC7710044 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comparative transcriptome and metabolome analyses of two strawberry cultivars with different storability.

Min Kyeonglim K Yi Gibum G Lee Jeong Gu JG Kim Hyun Sook HS Hong Yoonpyo Y Choi Jeong Hee JH Lim Sooyeon S Lee Eun Jin EJ

PloS one 20201202 12

Postharvest storability is an important trait for breeding strawberry (Fragaria × ananassa Duch.). We evaluated the postharvest fruit quality of five strawberry cultivars ('Durihyang', 'Kingsberry', 'Maehyang', 'Seolhyang', and 'Sunnyberry') and identified differences in their fruit ripening during the transition from the big-green to fully-red stage between two cultivars with the highest ('Sunnyberry') and lowest ('Kingsberry') storability, using comparative transcriptome and -metabolome analys ...[more]

PMID: 33264316

Similar Datasets

Project description:Soybean is one of the important economic crops, which supplies a great deal of vegetable oil and proteins for human. The content of nutrients in different soybean seeds is different, which is related to the expression of multiple genes, but the mechanisms are complicated and still largely uncertain. In this study, to reveal the possible causes of the nutrients difference in soybeans A7 (containing low oil and high protein) and A35 (containing high oil and low protein), RNA-seq technology was performed to compare and identify the potential differential expressed genes (DEGs) at different seed developmental stages. The results showed that DEGs mainly presented at the early stages of seeds development and more DEGs were up-regulated at the early stage than the late stages. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed that the DEGs have diverged in A7 and A35. In A7, the DEGs were mainly involved in cell cycle and stresses, while in A35 were the fatty acids and sugar metabolism. Specifically, when the DEGs contributing to oil and protein metabolic pathways were analyzed, the differences between A7 and A35 mainly presented in fatty acids metabolism and seeds storage proteins (SSPs) synthesis. Furthermore, the enzymes, fatty acid dehydrogenase 2, 3-ketoacyl-CoA synthase and 9S-lipoxygenase, in the synthesis and elongation pathways of fatty acids, were revealed probably to be involved in the oil content difference between A7 and A35, the SSPs content might be due to the transcription factors: Leafy Cotyledon 2 and Abscisic acid-intensitive 3, while the sugar transporter, SWEET10a, might contribute to both oil and protein content differences. Finally, six DEGs were selected to analyze their expression using qRT-PCR, and the results were consistent with the RNA-seq results. Generally, the study provided a comprehensive and dynamic expression trends for the seed development processes, and uncovered the potential DEGs for the differences of oil in A7 and A35.

Project description:Lepidopteran larvae growth is influenced by host plant glucosinolate (GS) concentrations, which are, in turn, influenced by the phytohormone jasmonate (JA). In order to elucidate insect resistance biomarkers to lepidopteran pests, transcriptome and metabolome analyses following JA treatments were conducted with two broccoli cultivars, Green Magic and VI-158, which have differentially induced indole GSs, neoglucobrassicin and glucobrassicin, respectively. To test these two inducible GSs on growth of cabbage looper (Trichoplusia ni), eight neonate cabbage looper larvae were placed onto each of three plants per JA treatments (0, 100, 200, 400 µM) three days after treatment. After five days of feeding, weight of larvae and their survival rate was found to decrease with increasing JA concentrations in both broccoli cultivars. JA-inducible GSs were measured by high performance liquid chromatography. Neoglucobrassicin in Green Magic and glucobrassicin in VI-158 leaves were increased in a dose-dependent manner. One or both of these glucosinolates and/or their hydrolysis products showed significant inverse correlations with larval weight and survival (five days after treatment) while being positively correlated with the number of days to pupation. This implies that these two JA-inducible glucosinolates can influence the growth and survival of cabbage looper larvae. Transcriptome profiling supported the observed changes in glucosinolate and their hydrolysis product concentrations following JA treatments. Several genes related to GS metabolism differentiate the two broccoli cultivars in their pattern of transcriptional response to JA treatments. Indicative of the corresponding change in indole GS concentrations, transcripts of the transcription factor MYB122, core structure biosynthesis genes (CYP79B2, UGT74B1, SUR1, SOT16, SOT17, and SOT18), an indole glucosinolate side chain modification gene (IGMT1), and several glucosinolate hydrolysis genes (TGG1, TGG2, and ESM1) were significantly increased in Green Magic (statistically significant in most cases at 400 µM) while UGT74B1 and MYB122 were significantly increased in VI-158. Therefore, these metabolite and transcript biomarker results indicate that transcriptome profiling can identify genes associated with the formation of two different indole GS and their hydrolysis products. Therefore, these metabolite and transcript biomarkers could be useful in an effective marker-assisted breeding strategy for resistance to generalist lepidopteran pests in broccoli and potentially other Brassica vegetables.

Dataset Information

Comparative transcriptome and metabolome analyses of two strawberry cultivars with different storability.

Publications

Comparative transcriptome and metabolome analyses of two strawberry cultivars with different storability.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets