Identification of QTLs by Genome-Wide Association Study in Rice for Salt Tolerance

Date Received: Feb 17, 2025

Date Accepted: Mar 27, 2025

Date Published: Mar 31, 2025

DOI: https://doi.org/10.31817/vjas.2025.8.1.

Views

11

Download

11

How to Cite:

Thu, T., & Takeo, Y. . (2025). Identification of QTLs by Genome-Wide Association Study in Rice for Salt Tolerance. Vietnam Journal of Agricultural Sciences, 8(1), 2343–2358. https://doi.org/10.31817/vjas.2025.8.1.

Identification of QTLs by Genome-Wide Association Study in Rice for Salt Tolerance

Thieu Thi Phong Thu (*) 1   , Takeo Yamakawa 2

  • Corresponding author: ttpthu@vnua.edu.vn
  • 1 Department of Cultivation Science, Faculty of Agronomy, Vietnam National University of Agriculture, Hanoi 12400, Vietnam
  • 2 Department of Agricultural Science and Technology, Faculty of Agriculture, Setsunan University, Osaka 5720000, Japan

    • Keywords

    GWAS, QTLs, rice, salt tolerance

    Abstract


    A genome-wide association study (GWAS) was performed to identify potential QTLs associated with salt stress tolerance in rice. The correlation between the genotyping data set and the phenotypic expression of 213 diverse rice accessions for 11 biochemical and agronomic traits was assessed. GWAS was run using a mixed linear model and population parameters previously defined in Tassel 5.0 to predict genomic regions associated with traits for the Japonica and Indica subpopulations. GWAS resulted in the detection of numerous SNP markers scattered over the rice genome that were associated with various salt tolerance traits. A QTL region on chromosome 3 was found to contribute to the variation in salt tolerance in the Indica subpopulation and related to the two traits of sheath Ca and sheath Mg contents. Three QTL regions on chromosomes 2, 4, and 5 were found to contribute to the variation in salt tolerance in the Japonica subpopulation and related to the traits of sheath Na content, sheath Mg content, the sheath Na/K ratio, leaf Na content, and the leaf Na/K ratio.

    References

    Bonilla P., Dvorak J., Mackill D., Deal K. & Gregorio G. (2002). RFLP and SSLP mapping of salinity tolerance genes in chromosome 1 of rice (Oryza sativa L.) using recombinant inbred lines. The Philippine Agricultural Scientist. 85(1): 68-76.

    Claes B., Dekeyser R., Villarroel R., Bulcke V. D. M., Montagu V. M. & Caplan A. (1990). Characterization of a rice gene showing organ-specific expression in response to salt stress and drought. Plant Cell. 2: 19-27.

    De Leon T. B., Linscombe S., Gregorio G. & Subudhi P. K. (2015). Genetic variation in Southern USA rice genotypes for seedling salinity tolerance. Frontier in Plant Science. 6: 374.

    Gregorio G. B., Senadhira D. & Mendoza R. D. (1997). Screening Rice for Salinity Tolerance. IRRl Discussion Paper Series. 22(22): 30.

    Grotewold E., Chappell J. & Kellogg E. A. (2015). The shifting genomic landscape in plant genes. In Genomes and Genetics. 17-44. JohnWiley and Sons, Ltd, Chichester, U.K.

    Hu S., Tao H., Qian Q. & Guo L. (2012). Genetics and molecular breeding for salt-tolerance in rice. Rice Genomics and Genetics. 3: 39-49.

    Korte A. & Farlow A. (2013). The advantages and limitations of trait analysis with GWAS: a review. Plant Methods. 9: 29.

    Kumar V., Singh A., Amitha Mithra S. V., Krishnamurthy S. L., Parida S. K., Jain S., Tiwari K. K., Kumar P., Rao A. R., Sharma S. K., Khurana J. P., Singh N. K. & Mohapatra T. (2015). Genome-wide association mapping of salinity tolerance in rice (Oryza sativa). DNA Research. 22(2): 133-145. DOI: 10.1093/dnares/dsu046.

    Moradi F. & Ismail A. M. (2007). Responses of photosynthesis, chlorophyll fluorescence and ROS-scavenging systems to salt stress during seedling and reproductive stages in rice. Annals of Botany. 99: 1161-1173.

    Niazi S. B., Littlejohn D. & Halls D. J. (1993). Rapid partial digestion of biological tissues with nitric acid for the determination of trace elements by atomic spectrometry. Analyst. 118: 821-825.

    Pandit A., Rai V., Bal S., Sinha S., Kumar V., Chauhan M. & Singh N. K. (2010). Combining QTL mapping and transcriptome profiling of bulked RILs for identification of functional polymorphism for salt tolerance genes in rice (Oryza sativa L.). Molecular Genetics and Genomics. 284: 121-136.

    Patishtan J., Hartley T. N., Fonseca de Carvalho R. & Maathuis F. J. M. (2017). Genome-wide association studies to identify rice salt-tolerance markers. Plant Cell and Environment. 41: 970-982.

    Phan N. T. H., Pham V. C., Tang H. T., Nguyen V. L., Nguyen V. L. & Bertin P. (2023). Integration of genome-wide association studies reveal loci associated with salt tolerance score of rice at the seedling stage. Journal of Applied Genetics. 64(4): 603-614. DOI: 10.1007/s13353-023-00775-7.

    Rahman M. A., Thomson M. J., Alam M. S. E., Ocampo M. D., Egdane J. & Ismail A. M. (2016). Exploring novel genetic sources of salinity tolerance in rice through molecular and physiological characterization. Annals of Botany. 117: 1083-1097.

    Ren Z. H., Gao J. P., Li L., Cai X., Huang W., Chao D. Y., Zhu M., Wang Z. Y., Luan S. & Lin H. (2005). A rice quantitative trait locus for salt tolerance encodes a sodium transporter. Nature Genetics. 37(10): 1141-1146.

    Si L., Chen J., Huang X., Gong H., Luo J., Hou Q. & Han B. (2016). OsSPL13 controls grain size in cultivated rice. Nature Genetics. 48: 447-456.

    Soda N., Ephrath J. E., Dag A., Beiersdorf I., Presnov E., Yermiyahu U. & Ben-Gal A. (2016). Root growth dynamics of olive (Olea europaea L.) affected by irrigation induced salinity. Plant and Soil. 411: 305-318.

    United Nations (2025). Population. Retrieved from https://www.un.org/en/global-issues/population#:~:text=Our%20growing%20population&text=The%20world's%20population%20is%20expected,billion%20in%20the%20mid%2D2080s on March 8, 2025.

    Waziri A., Kumar P. & Purty R. S. (2016). Saltol QTL and Their Role in Salinity Tolerance in Rice. Austin Journal of Biotechnology and Bioengineering. 3(3): 1067.

    Wu W., Yu Q., You L., Chen K., Tang H. & Liu J. (2018). Global cropping intensity gaps: Increasing food production without cropland expansion. Land Use Policy. 76: 515-525.

    Xu S., Cui J., Cao H., Liang S., Ma T., Liu H., Wang J., Yang L., Xin W., Jia Y., Zou D. & Zheng H. (2023). Identification of candidate genes for salinity tolerance in Japonica rice at the seedling stage based on genome- wide association study and linkage mapping. Frontiers in Plant Science. 14: 1184416.

    Yano K., Yamamoto E., Aya K., Takeuchi H., Lo P. C., Hu L., Yamasaki M., Yoshida S., Kitano H., Hirano K. & Matsuoka M. (2016). Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice. Nature Genetics. 48(8): 927-934.

    Yoshida S., Forno D. A., Cock J. H. & Gomez K. A. (1976). Laboratory Manual for Physiological Studies of Rice. The International Rice Institute, Manila. Philippines: 61-69.

    Zang J. P., Sun Y. & Wang Y. (2008). Dissection of genetic overlap of salt tolerance QTLs at the seedling and tillering stages using backcross introgression lines in rice. Science in China Series C: Life Sciences. 51: 583-591. DOI: 10.1007/s11427-008-0081-1.

    Zhang Q., Zhang Q. & Jensen J. (2022). Association Studies and Genomic Prediction for Genetic Improvements in Agriculture. Frontier in Plant Science. 13: 904230. DOI: 10.3389/fpls.2022.904230.