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Identification of key genes and regulators associated with carotenoid metabolism in apricot (Prunus armeniaca) fruit using weighted gene coexpression network analysis

文献类型： 外文期刊

作者： Zhang, Lina 1 ; Zhang, Qiuyun 2 ; Li, Wenhui 3 ; Zhang, Shikui 3 ; Xi, Wanpeng 1 ;

作者机构： 1.Southwest Univ, Coll Hort & Landscape Architecture, Chongqing 400716, Peoples R China

2.Zhejiang Univ, Lab Fruit Qual Biol, Zijingang Campus, Hangzhou 310058, Zhejiang, Peoples R China

3.Xinjiang Acad Agr Sci, Agr Natl Fruit Tree Germplasm Repository, Luntai 841600, Xinjiang, Peoples R China

关键词： Carotenoids; Apricot; Color; WGCNA; Prunus armeniaca L

期刊名称：BMC GENOMICS （ 影响因子：3.969； 五年影响因子：4.478 ）

ISSN： 1471-2164

年卷期： 2019 年 20 卷 1 期

页码：

收录情况： SCI

摘要： Background Carotenoids are a class of terpenoid pigments that contribute to the color and nutritional value of many fruits. Their biosynthetic pathways have been well established in a number of plant species; however, many details of the regulatory mechanism controlling carotenoid metabolism remain to be elucidated. Apricot is one of the most carotenoid-rich fruits, making it a valuable system for investigating carotenoid metabolism. The purpose of this study was to identify key genes and regulators associated with carotenoid metabolism in apricot fruit based on transcriptome sequencing. Results During fruit ripening in the apricot cultivar 'Luntaixiaobaixing' (LT), the total carotenoid content of the fruit decreased significantly, as did the levels of the carotenoids beta-carotene, lutein and violaxanthin (p < 0.01). RNA sequencing (RNA-Seq) analysis of the fruit resulted in the identification of 44,754 unigenes and 6916 differentially expressed genes (DEGs) during ripening. Among these genes, 33,498 unigenes were annotated using public protein databases. Weighted gene coexpression network analysis (WGCNA) showed that two of the 13 identified modules ('blue' and 'turquoise') were highly correlated with carotenoid metabolism, and 33 structural genes from the carotenoid biosynthetic pathway were identified. Network visualization revealed 35 intramodular hub genes that putatively control carotenoid metabolism. The expression levels of these candidate genes were determined by quantitative real-time PCR analysis, which showed ripening-associated carotenoid accumulation. This analysis revealed that a range of genes (NCED1, CCD1/4, PIF3/4, HY5, ERF003/5/12, RAP2-12, AP2, AP2-like, BZR1, MADS14, NAC2/25, MYB1R1/44, GLK1/2 and WRKY6/31/69) potentially affect apricot carotenoid metabolism during ripening. Based on deciphering the molecular mechanism involved in ripening, a network model of carotenoid metabolism in apricot fruit was proposed. Conclusions Overall, our work provides new insights into the carotenoid metabolism of apricot and other species, which will facilitate future apricot functional studies and quality breeding through molecular design.

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