Identification of candidate genes that regulate the trade-off between seedling cold tolerance and fruit quality in melon (Cucumis melo L.)

Abstract

Trade-offs between survival and growth are widely observed in plants. Melon is an annual, trailing herb that produces economically valuable fruits that are traditionally cultivated in early spring in China. Melon seedlings are sensitive to low temperatures, and thus usually suffer from cold stress during the early growth period. However, little is known about the mechanism behind the trade-offs between seedling cold tolerance and fruit quality in melon. In this study, a total of 31 primary metabolites were detected from the mature fruits of eight melon lines that differ with respect to seedling cold tolerance; these included 12 amino acids, 10 organic acids, and 9 soluble sugars. Our results showed that concentrations of most of the primary metabolites in the cold-resistant melons were generally lower than in the cold-sensitive melons; the greatest difference in metabolite levels was observed between the cold-resistant line H581 and the moderately cold-resistant line HH09. The metabolite and transcriptome data for these two lines were then subjected to weighted correlation network analysis, resulting in the identification of five key candidate genes underlying the balancing between seedling cold tolerance and fruit quality. Among these genes, CmEAF7 might play multiple roles in regulating chloroplast development, photosynthesis, and the ABA pathway. Furthermore, multi-method functional analysis showed that CmEAF7 can certainly improve both seedling cold tolerance and fruit quality in melon. Our study identified an agriculturally important gene, CmEAF7, and provides a new insight into breeding methods to develop melon cultivars with seedling cold tolerance and high fruit quality.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant numbers 31872101 and 32072564), the Henan Special Funds for Major Science and Technology (221100110400), the Excellent Youth Foundation of Henan Scientific Committee (222300420009), and the Foundation for Young Talents of Henan Agricultural University (30500728). We thank Dr. Meng Li for kindly providing the transient transformation vector.

Author contributions

Lili Li: Conceptualization, Methodology, Validation, Investigation, Writing - Original Draft, Visualization. Qiong Li: Methodology, Software, Investigation, Visualization. Bin Chen: Methodology, Software, Investigation, Visualization. Jiyu Wang: Validation, Investigation. Fei Ding: Software, Investigation, Visualization, Data Curation. Panqiao Wang: Software, Data Curation, Visualization. Xiuyue Zhang: Investigation, Visualization. Juan Hou: Investigation, Data Curation. Renren Luo: Investigation, Data Curation. Xiang Li: Investigation, Data Curation. Jingwen Zheng: Software, Data Curation. Sen Yang: Data Curation, Review & Editing. Luming Yang: Resources, Review & Editing. Lei Zhu: Resources, Review & Editing. Shouru Sun: Resources, Review & Editing. Changsheng Ma: Resources, Review & Editing. Qin Li: Resources, Review & Editing. Ying Li: Conceptualization, Methodology, Validation, Formal analysis, Writing - Review & Editing, Supervision, Project administration, Funding acquisition. Jianbin Hu: Conceptualization, Resources, Writing - Review & Editing, Supervision, Project administration, Funding acquisition.

Data availability

All data are included in the paper and in the Supplementary Materials published online.

Conflicts of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the outcome of the research reported in this paper.

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