Understanding water conservation vs. profligation traits in vegetable legumes through a physio-transcriptomic-functional approach

Abstract

Vegetable soybean and cowpea are related warm-season legumes showing contrasting leaf water use behaviors under similar root drought stresses, whose mechanisms are not well understood. Here we conducted an integrative phenomic-transcriptomic study on the two crops grown in a feedback irrigation system that enabled precise control of soil water contents. Continuous transpiration rate monitoring demonstrated that cowpea used water more conservatively under earlier soil drought stages, but tended to maintain higher transpiration under prolonged drought. Interestingly, we observed a soybean-specific transpiration rate increase accompanied by phase shift under moderate soil drought. Time-series transcriptomic analysis suggested a dehydration avoidance mechanism of cowpea at early soil drought stage, in which the VuHAI3 and VuTIP2;3 genes were suggested to be involved. Multifactorial gene clustering analysis revealed different responsiveness of genes to drought, time of day and their interactions between the two crops, which involved species-dependent regulation of the circadian clock genes. Gene network analysis identified two co-expression modules each associated with transpiration rate in cowpea and soybean, including a pair of negatively correlated modules between species. Module hub genes, including the ABA-degrading gene GmCYP707A4 and the trehalose-phosphatase/synthase gene VuTPS9 were identified. Inter-modular network analysis revealed putative co-players of the hub genes. Transgenic analyses verified the role of VuTPS9 in regulating transpiration rate under osmotic stresses. These findings propose that species-specific transcriptomic reprograming in leaves of the two crops suffering similar soil drought was not only a result of the different drought resistance level, but a cause of it.

Acknowledgements

We thank Wenzhao Xu and Dexu Luo for assistance in the greenhouse experiment, Liang Zeng for assistance in bioinformatical analyses and Menachem Moshelion and Amir Mayo for assistance in running PlantArray. This work is supported by the National Key Research and Development Program of China (Grant No. 2022YFE0198000), National Natural Science Foundation of China (Grant No. 31772299, 31861143044), and the Natural Science Foundation of Zhejiang Province (Grant No. LQ21C150004).

Author contributions

P.X. designed the research and wrote the manuscript. P.F. participated in the experiments, data analysis, and wrote the manuscript. T.S. and A.K.P. participated in high-throughput physiological phenotyping analysis. P.F., L.J., and S.C. performed the transcriptomic data analysis. X.W. and Y.H. performed the transient overexpression assay. M.L. participated in the measurement of Tr and Gs.

Data availability

The RNA-seq raw data are accessible in GenBank with the accession numbers stored in Table S11 (see online supplementary material). The R codes for the GLM, clustering, and inter-modular network analyses are available in Data S1 (see online supplementary material).

Conflict of interests

The authors declare that they have no conflict of interest.

Supplementary data

Supplementary data is available at Horticulture Research online.

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