Genome-Wide Association Study Identified Candidate Genes for Alkalinity Tolerance in Rice

Abstract

Alkalinity stress is a major hindrance to enhancing rice production globally due to its damaging effect on plants' growth and development compared with salinity stress. However, understanding of the physiological and molecular mechanisms of alkalinity tolerance is limited. Therefore, a panel of indica and japonica rice genotypes was evaluated for alkalinity tolerance at the seedling stage in a genome-wide association study to identify tolerant genotypes and candidate genes. Principal component analysis revealed that traits such as alkalinity tolerance score, shoot dry weight, and shoot fresh weight had the highest contribution to variations in tolerance, while shoot Na⁺ concentration, shoot Na⁺:K⁺ ratio, and root-to-shoot ratio had moderate contributions. Phenotypic clustering and population structure analysis grouped the genotypes into five subgroups. Several salt-susceptible genotypes such as IR29, Cocodrie, and Cheniere placed in the highly tolerant cluster suggesting different underlying tolerance mechanisms for salinity and alkalinity tolerance. Twenty-nine significant SNPs associated with alkalinity tolerance were identified. In addition to three alkalinity tolerance QTLs, qSNK4, qSNC9, and qSKC10, which co-localized with the earlier reported QTLs, a novel QTL, qSNC7, was identified. Six candidate genes that were differentially expressed between tolerant and susceptible genotypes were selected: LOC_Os04g50090 (Helix-loop-helix DNA-binding protein), LOC_Os08g23440 (amino acid permease family protein), LOC_Os09g32972 (MYB protein), LOC_Os08g25480 (Cytochrome P450), LOC_Os08g25390 (Bifunctional homoserine dehydrogenase), and LOC_Os09g38340 (C2H2 zinc finger protein). The genomic and genetic resources such as tolerant genotypes and candidate genes would be valuable for investigating the alkalinity tolerance mechanisms and for marker-assisted pyramiding of the favorable alleles for improving alkalinity tolerance at the seedling stage in rice.

Keywords: Oryza sativa; abiotic stress; alkalinity tolerance; candidate genes; genome-wide association study; seedling stage; single nucleotide polymorphism.

Figure 1

Variation in alkalinity tolerance among the rice genotypes based on alkalinity tolerance score (AKT) at the seedling stage.

Figure 2

Performance of some of the lines (known salt-tolerance level) after 21 days of alkaline stress at the seedling stage. The scale represents the alkalinity tolerance score (AKT) after the stress on a scale of 1 (highly tolerant) to 9 (highly susceptible).

Figure 3

Frequency distribution of nine morphological and physiological traits under alkaline stress. AKT, alkalinity tolerance score; SHL, shoot length; RTL, root length; RSR, root-to-shoot ratio; inv_FW, inverse fresh weight; log_DW, log dry weight; SNC, shoot Na⁺ concentration; SKC, shoot K⁺ concentration; SNK, shoot Na⁺:K⁺ concentration.

Figure 4

Principal component analysis (PCA) plot. (a) Grouping of variables associated with nine morphological and physiological traits of rice genotypes under alkalinity stress at the seedling stage, (b) Scatter plot of the indica and japonica rice genotypes represented in the two major principal component axes. No sufficient clustering was observed between indica and japonica genotypes. AKT, alkalinity tolerance score; CHL, chlorophyll content (SPAD units); SHL, shoot length (cm); RTL, root length (cm); log_DW, log dry weight (gm); inv_FW, inverse fresh weight (gm); SNC, Shoot Na⁺ concentration (mmol/kg); SKC, shoot K⁺ concentration (mmol/kg); SNK, shoot Na⁺:K⁺ ratio.

Figure 5

Phenotypic clustering of rice genotypes by UPGMA based on Euclidean distance computed from nine morphological and physiological traits under alkalinity stress at the seedling stage.

Figure 6

Population structure analysis of rice genotypes. (a) identification of the optimum number of subpopulations using LnP(D) derived ΔK. The maximum value of ΔK was found to be at K = 5, suggesting a division of the entire population into five subpopulations. The X-axis shows the number of subgroups (K) and Y-axis shows rate change of log probability values (ΔK) with change in K (b) Assignment of rice genotypes into five subpopulations, with the X-axis and Y-axis representing genotypes and the proportion of genetic ancestry in the subgroup membership, respectively. The genotypes present in each subgroup are listed in Table S5.

Figure 7

Genome-wide average linkage disequilibrium decay across all chromosomes. The X-axis and Y-axis represent the distance (bp) and LD, respectively. The intersection of green and blue lines indicates the derived threshold for LD due to linkage at respective distance (blue line) and LD (green line).

Figure 8

Manhattan plots of the markers associated with alkalinity tolerance in rice. The X-axis shows markers along the 12 rice chromosomes and the Y-axis shows the negative log₁₀- transformed p-values for each association. Red dotted lines indicate the significance threshold. AKT, alkalinity tolerance score; SHL, shoot length; RTL, root length; RSR, root-to-shoot ratio; inv_FW, inverse fresh weight; log_DW, log dry weight; SNC, shoot Na⁺ concentration; SKC, shoot K⁺ concentration; SNK, shoot Na⁺:K⁺ ratio.

Figure 9

Expression profiles of selected genes present under alkalinity stress (6 h after imposition of stress) in the tolerant and susceptible groups. Red and blue in the bars represent tolerant and susceptible groups, respectively. Genotypes included in the experiment were: 1—JN100; 2—Cheniere, 3—Cocodrie; 4—Nipponbare; 5—N22; 6—Dular; 7—Cypress; 8—Hasawi. EF1α was used as the reference gene and gene expressions were calculated as log2-fold changes under alkaline stress compared with control in all genotypes. LOC_Os04g50090—Helix–loop–helix DNA-binding protein; LOC_Os08g23440—amino acid permease family protein; LOC_Os09g32972—MYB protein; LOC_Os10g35230—Rf1, mitochondrial precursor; LOC_Os03g25480—cytochrome P450; LOC_Os08g25390—Bifunctional homoserine dehydrogenase; LOC_Os09g38340—ZOS9-17—C2H2 zinc finger protein, LOC_Os04g58160—Fiber protein Fb34, putative.