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QTL detection for rice grain storage protein content and genetic effect verifications

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Abstract

Rice grain quality is a multifarious attribute mainly governed by multiple nutritional factors. Grain protein is the central component of rice grain nutrition dominantly affecting eating–cooking qualities. Grain protein content is quantitatively influenced by its protein fractions. Genetic quantification of five protein fractions—albumins, globulins, prolamins, glutelin, and grain protein content—were evaluated by exploiting two BC3F2 mapping populations, derived from Kongyu131/TKM9 (population-I) and Kongyu131/Bg94-1 (population-II), which were grown in a single environment. Correlation studies among protein fractions and grain protein content were thoroughly investigated. A genetic linkage map was developed by using 146 single sequence repeat (SSR) markers in population-I and 167 markers in population-II. In total, 40 QTLs were delineated for five traits in both populations. Approximately 22 QTLs were dissected in population-I, derived from Kongyu131/TKM9, seven QTLs for albumin content, four QTLs for globulin content, three QTLs for prolamin content, four QTLs for glutelin content, and four QTLs for grain protein content. In total, 18 QTLs were detected in population-II, derived from Kongyu131/Bg94-1, five QTLs for albumin content, three QTLs for globulin content, four QTLs for prolamin content, two QTLs for glutelin content, and four QTLs for grain protein content. Three QTLs, qAlb7.1, Alb7.2, and qGPC7.2, derived from population-II (Kongyu131/Bg94-1) for albumin and grain protein content were successfully validated in the near isogenic line (NIL) populations. The localized chromosomal locus of the validated QTLs could be helpful for fine mapping via map-based cloning to discover underlying candidate genes. The functional insights of the underlying candidate gene would furnish novel perceptivity for the foundation of rice grain protein content and trigger the development of nutritionally important rice cultivars by combining marker-assisted selection (MAS) breeding.

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The data matrixes produced during the current investigation are only accessible from the corresponding author on a justifiable request.

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Acknowledgements

The authors extend their highest appreciation for the support from the National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University.

Funding

This work was supported by grants from the National Natural Science Foundation of China (U21A20211), the Ministry of Science and Technology (2021YFF1000200, 2022YFD1200100), AgroST Project (NK20220501), and China Agriculture Research System (CARS-01–01).

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Authors and Affiliations

  1. National Key Laboratory of Crop Genetic Improvement and National Center of Crop Molecular Breeding, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, Hubei, China

    Mufid Alam, YingYing Wang, Jianxian Chen, Guangming Lou, Hanyuan Yang, Yin Zhou & Yuqing He

  2. College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China

    Saurav Luitel

  3. College of Life Science, Heilongjiang University, Haerbin, 150080, Heilongjiang, China

    Gonghao Jiang

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  1. Mufid Alam
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  2. YingYing Wang
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  3. Jianxian Chen
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  4. Guangming Lou
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  9. Yuqing He
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Contributions

MA and YH designed this experiement. MA, GJ, YW, and JC conducted this experiemnt and collected all phenotypic data. MA and GL performed data analaysis. MA, GL,YH, YZ, and SL contributed in the graphical representaion. YH supervised all investiations. MA have wrote this manusript. All authors have read and authorized this manuscript for publication.

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Correspondence to Yuqing He.

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Alam, M., Wang, Y., Chen, J. et al. QTL detection for rice grain storage protein content and genetic effect verifications. Mol Breeding 43, 89 (2023). https://doi.org/10.1007/s11032-023-01436-7

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