Genome-Wide Association Mapping of Salinity Tolerance at the Seedling Stage in a Panel of Vietnamese Landraces Reveals New Valuable QTLs for Salinity Stress Tolerance Breeding in Rice

Abstract

Rice tolerance to salinity stress involves diverse and complementary mechanisms, such as the regulation of genome expression, activation of specific ion-transport systems to manage excess sodium at the cell or plant level, and anatomical changes that avoid sodium penetration into the inner tissues of the plant. These complementary mechanisms can act synergistically to improve salinity tolerance in the plant, which is then interesting in breeding programs to pyramidize complementary QTLs (quantitative trait loci), to improve salinity stress tolerance of the plant at different developmental stages and in different environments. This approach presupposes the identification of salinity tolerance QTLs associated with different mechanisms involved in salinity tolerance, which requires the greatest possible genetic diversity to be explored. To contribute to this goal, we screened an original panel of 179 Vietnamese rice landraces genotyped with 21,623 SNP markers for salinity stress tolerance under 100 mM NaCl treatment, at the seedling stage, with the aim of identifying new QTLs involved in the salinity stress tolerance via a genome-wide association study (GWAS). Nine salinity tolerance-related traits, including the salt injury score, chlorophyll and water content, and K⁺ and Na⁺ contents were measured in leaves. GWAS analysis allowed the identification of 26 QTLs. Interestingly, ten of them were associated with several different traits, which indicates that these QTLs act pleiotropically to control the different levels of plant responses to salinity stress. Twenty-one identified QTLs colocalized with known QTLs. Several genes within these QTLs have functions related to salinity stress tolerance and are mainly involved in gene regulation, signal transduction or hormone signaling. Our study provides promising QTLs for breeding programs to enhance salinity tolerance and identifies candidate genes that should be further functionally studied to better understand salinity tolerance mechanisms in rice.

Keywords: GWAS; QTL; Vietnamese landraces; rice; salinity tolerance.

Figure 1

Boxplots of the distribution of salinity tolerance-related traits. Indica subpanel in red; japonica subpanel in blue; statistical significance (ANOVA p-values) between the two subpanels is indicated; (a) leaf water content (WC); (b) score of visual salt injury (Score); (c) total chlorophyll content in leaves (Chl_total); (d) chlorophyll a content in leaves (Chla); (e) chlorophyll b content in leaves (Chlb); (f) chlorophyll a to chlorophyll b ratio in leaves (Chla_b); (g) K⁺ concentration in leaves (ConcK); (h) Na⁺ concentration in leaves (ConcNa); (i) ratio of Na⁺/K⁺ in leaves (Na_K).

Figure 2

Manhattan plots and Q-Q plots for GWAS of salinity tolerance-related traits in the full panel. (a) Leaf water content (WC); (b) score of visual salt injury (Score); (c) total chlorophyll content in leaves (Chl_total); (d) chlorophyll a content in leaves (Chla); (e) chlorophyll b content in leaves (Chlb); (f) chlorophyll a to chlorophyll b ratio in leaves (Chla_b); (g) K⁺ concentration in leaves (ConcK); (h) Na⁺ concentration in leaves (ConcNa); (i) ratio of Na⁺/K⁺ in leaves (Na_K). In the Manhattan plots, significant SNPs are highlighted in red.

Figure 3

QTL_25. (a) Manhattan plot for K⁺, Na⁺ and water content in leaves in the full panel; (b) linkage disequilibrium (LD) heatmap. In the Manhattan plots, significant SNPs are highlighted in red, and genes of interest are mentioned. The genomic region of QTL_25 is specified in the boundary area in the LD heatmap.