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Genetic Dissection of the Photosynthetic Parameters of Maize (Zea mays L.) in Drought-Stressed and Well-Watered Environments

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Abstract

Photosynthesis is a critical function that allows adaptation to drought stress in maize (Zea mays L.). Therefore, elucidation of the genetic control of photosynthetic performance under drought stress and the associated molecular markers is of great importance for marker-assisted selection (MAS). Here, we detected 54 quantitative trait loci (QTLs) affecting the net photosynthetic rate (Pn), stomatal conductance (Gs), intercellular CO2 concentration (Ci), transpiration rate (Tr), ribulose 1,5-biphosphate carboxylase activity (RuBP), and water use efficiency (WUE) of the ear leaf across two F4 populations in drought-stressed and well-watered environments by single-environment mapping with composite interval mapping (CIM), and 43 QTLs identified under drought stress, indicating that the tolerance to photoinhibition is a key factor affecting drought stress tolerance in maize. We further dissected 54 QTLs via joint analysis of all environments with mixed-linear-model-based CIM (MCIM), including 24 involved in QTL-by-environment interactions (QEIs), 87.5% QEIs identified under drought stress, 14 pairs showing epistatic interactions with dominance-by-additive/dominance effects under contrasting environments. We further identified eight constitutive QTLs (cQTLs) across two populations by CIM/MCIM, which could be used for genetic improvement of maize via QTL pyramiding. The co-localization of five cQTLs in bin 1.07_1.10/6.05/7.02_7.04/8.03/10.03 under contrasting environments in both populations strongly supported pleiotropy. Additionally, 17 candidate genes located at the above-mentioned cQTLs were involved in photomorphogenesis, photosynthesis, and stress response. These results provide insights into the genetic mechanisms responsible for photosynthesis under different water availability conditions, and reveal alleles that could potentially be used for MAS-based development of drought tolerant maize cultivars.

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Funding

The study was partially supported by the Research Program Sponsored by Gansu Provincial Key Laboratory of Aridland Crop Science, Gansu Agricultural University, China (project no. GSCS-2019-8; GSCS-2020-5), the National Natural Science Foundation of China (project no. 32060486), the Scientific Research Start-up Funds for Openly-recruited Doctors, Science and Technology Innovation Funds of Gansu Agricultural University, China (project nos. GAU-KYQD-2018-19; GAU-KYQD-2018-12), the Developmental Funds of Innovation Capacity in Higher Education of Gansu, China (project nos. 2019A-052; 2019A-054), and the Transverse Project of Lanzhou Qinglü Instrument and Technology Company, China (project no. WT20191025).

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    1. Gansu Provincial Key Laboratory of Aridland Crop Science, Gansu Agricultural University, 730070, Lanzhou, China

      X. Q. Zhao & Y. Zhong

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    1. X. Q. Zhao
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    Authors X.Q. Zhao and Y. Zhong contributed equally to this work.

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    Correspondence to X. Q. Zhao.

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    This article does not contain any studies involving animals or human participants as objects of research. The authors declare that they have no conflict of interest.

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    Abbreviations: Ci—intercellular CO2 concentration; CIM— composite interval mapping; cQTLs—constitutive quantitative trait loci; GEI—genotype × environment interaction; Gs—stomatal conductance; MAS—marker-assisted selection; MCIM— mixed-linear-model-based composite interval mapping; Pn— net photosynthetic rate; QEIs—quantitative trait loci-by-environment interactions; QTLs—quantitative trait loci; RuBP— ribulose 1,5-biphosphate carboxylase activity; Tr—transpiration rate; WUE—water use efficiency.

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    Zhao, X.Q., Zhong, Y. Genetic Dissection of the Photosynthetic Parameters of Maize (Zea mays L.) in Drought-Stressed and Well-Watered Environments. Russ J Plant Physiol 68, 1125–1134 (2021). https://doi.org/10.1134/S1021443721060236

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