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        CrMYC1 contributes to catharanthine and ajmalicine accumulation by regulating the TIA pathway in Catharanthus roseus hairy roots

        Sazegari Sima,Niazi Ali,Shahriari-Ahmadi Farajollah,Afsharifar Alireza 한국원예학회 2022 Horticulture, Environment, and Biotechnology Vol.63 No.5

        Terpenoid indole alkaloids (TIA) are important pharmaceuticals produced in low amounts through the terpenoid indole alkaloid pathway in Catharanthus roseus. Production of these alkaloids is controlled by biosynthetic and regulatory genes. CrMYC1 is a chief transcription factor that regulates terpenoid indole alkaloid production. In this study, we cloned CrMYC1 and overexpressed it in C. roseus hairy roots to investigate its effect on the production of the TIAs ajmalicine and catharan- thine. qRT-PCR results revealed that CrMYC1 expression in transgenic CrMYC1-overexpressing hairy root lines was 3–6 times higher than that of the wild-type hairy root control line. Also, we detected a significant increase in strictosidine β-D- glucosidase (SGD) expression, a critical enzyme in TIA biosynthesis, in the overexpression lines. HPLC analysis showed that CrMYC1 overexpression significantly improved the accumulation of ajmalicine (13 to 14-fold) and catharanthine (3 to 4.4-fold) compared to the control hairy root line. These results provide insight into the role of this understudied transcription factor in TIA pathway regulation and emphasize further research objectives.

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        Mining transcriptome data to identify genes and pathways related to lemon taste using supervised and unsupervised data learning methods

        Zahra Zinati,Sima Sazegari,Hosein Amin,Ahmad Tahmasebi 한국원예학회 2021 Horticulture, Environment, and Biotechnology Vol.62 No.4

        There is a dearth of studies on the genes engaged in citrus taste. Unraveling the major genes involved in pathways related to the taste of citrus (sweet or acidic) is highly important for developing new genotypes with favorable taste. Pivotal genes linked to citrus taste can be extracted through mining a large number of expression data. To attain this objective, 10 different attribute weighting algorithms (AWAs) were applied on the expression data from three lemon (Citrus limon) genotypes differing in terms of fruit acidity. As a result, a total of 170 probe sets were identified by more than eight AWAs as the most discriminative probe sets. Subsequently, principal component analysis and hierarchical clustering heatmaps were implemented for validation of the 170 top-ranked probe sets. Noticeably, the identified top 170 probe sets significantly contributed to accurate discrimination between sweet and acidic lemon samples, which indicate the significance and accuracy of prediction of probe sets. According to the results, some genes like citrate synthase, malate dehydrogenase, proton-pumping ATPase, and flavanone 3-hydroxylase had distinct roles in differentiation of the studied genotypes and acidity. Among all of the genes, malate dehydrogenase was the most informative. To the best of our knowledge, this is the first report on identifying the most important genes contributing to lemon taste using supervised and unsupervised data learning methods.

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