QTL mapping of LRI and LWD under drought stress
In 2017, six QTLs related to LRI were identified on chromosomes 1, 4, 5, and 7. The most significant QTL (LOD value = 20.73) detected on day 32 of drought stress was qLRI5-2 on chromosome 5. This QTL explained 10.34% of the phenotypic variation and had the largest effect size. Three QTLs showed positive additive effects, indicating that the beneficial alleles came from the male parent MY23. Three QTLs showed negative additive effects, indicating that the beneficial alleles originated from the female parent JL1. In 2018, nine QTLs related to LRI were mapped to chromosomes 2, 3, 4, 7, 8, and 12. qLRI2-2, the major QTL, was repeatedly detected on days 29, 42, and 57 of drought treatment, with contribution rates of 10.59–17.04%. The beneficial alleles of all nine QTLs originated from the male parent. In 2019, eight QTLs related to LRI were discovered on chromosomes 1, 2, 5, and 12. Among them, qLRI5-4 explained the most variance (11.13%), and it was the major effect QTL. Three adjacent QTLs were mapped on chromosome 12, namely qLRI12-1, qLRI12-2, and qLRI12-3, with contribution rates of 4.75–7.32%. For all of these QTLs except qLRI2-3, the allele increasing LRI was inherited from the male parent.
In 2017, five QTLs related to LWD were detected on chromosomes 1, 3, 4, and 5, explaining 3.62–9.37% of the phenotypic variation. The additive effects of the three QTL were positive, indicating that the beneficial alleles originating from the female parent. The additive effects of two s were negative, indicating that the beneficial alleles originated from the male parent. qLWD4-1, located on chromosome 4, was detected on both day 32 and day 46 of drought stress, with contribution rates of 7.07% and 8.19%, respectively. In 2018, three QTLs related to LWD were identified on chromosomes 3, 4, and 12. Among these, qLWD4-2 on chromosome 4 was detected on days 29, 42, and 57 of drought, with contribution rates ranging from 5.14–5.71%. The beneficial allele for this QTL came from the male parent. qLWD12-1 was mapped to the same chromosome interval as qLRI12-3, which was detected in 2019. In 2019, eight QTLs associated with LWD were mapped to chromosomes 3, 5, 8, 9, and 12. These QTLs explained 3.95–8.40% of the observed phenotypic variation. The beneficial alleles of five of the QTLs were from the male parent.
During the tillering stage, 39 QTLs related to LRI and LWD were identified (Table 2). About three-fourths of these QTLs had confidence intervals less than 1 cM, with the smallest being 0.11 cM and the largest being 1.92 cM. The LOD scores ranged from 2.51 to 20.73, and the percent phenotypic variation ranged from 1.2–17.04%. Four QTLs, all of which were linked to LRI, explained more than 10% of the phenotypic variation. The positive alleles of the 25 QTLs were from the drought-tolerant parent MY23, while the positive alleles of 9 QTLs were derived from the drought-sensitive parent JL1. Overall, 23 QTLs related to LRI and 16 QTLs related to LWD were identified. Among these, qLWD5-3 and qLRI5-3, qLWD5-4 and qLRI5-4, qLWD12-2 and qLRI12-2, and qLWD12-1 and qLRI12-3 were located in the same region of the same chromosome.
Table 2
Summary of the locations and genetic effects of QTLs mapped using JL1/MY23 RILs under drought stress
Trait | Year | drought stress duration(d) | QTL | Chromosome | Genetic Interval(cM) | LOD | PVE(%) | Additive |
LRI | 2017 | 32 | qLRI1-1 | 1 | 17.99–18.10 | 2.89 | 1.2 | 0.53 |
| | 32 | qLRI4-1 | 4 | 39.20-40.32 | 3.82 | 1.63 | -0.44 |
| | 32 | qLRI5-1 | 5 | 0.00-1.28 | 12.82 | 5.85 | 0.84 |
| | 32 | qLRI5-2 | 5 | 2.59–3.52 | 20.73 | 10.34 | -1.12 |
| | 46 | qLRI7-1 | 7 | 14.31–15.02 | 4.71 | 6.27 | -0.49 |
| | 46 | qLRI7-2 | 7 | 51.64–52.16 | 3.58 | 4.81 | 0.43 |
| 2018 | 29 | qLRI2-1 | 2 | 82.71–83.24 | 2.95 | 4.22 | 0.25 |
| | 29 | qLRI2-2 | 2 | 103.75–104.50 | 9.69 | 12.75 | 0.44 |
| | 42 | qLRI2-2 | 2 | 103.75–104.50 | 11.26 | 17.04 | 0.61 |
| | 57 | qLRI2-2 | 2 | 103.75–104.50 | 5.68 | 10.59 | 0.42 |
| | 29 | qLRI3-1 | 3 | 102.62-103.06 | 5.24 | 6.45 | 0.33 |
| | 57 | qLRI4-2 | 4 | 2.57–3.77 | 2.66 | 4.79 | 0.28 |
| | 29 | qLRI4-3 | 4 | 54.80-55.32 | 3.47 | 4.26 | 0.25 |
| | 57 | qLRI7-3 | 7 | 45.34–46.41 | 5.92 | 11.07 | 0.43 |
| | 29 | qLRI8-1 | 8 | 14.69–15.36 | 2.88 | 3.56 | 0.23 |
| | 29 | qLRI8-2 | 8 | 66.90-67.02 | 4.49 | 5.68 | 0.29 |
| | 42 | qLRI12-1 | 12 | 12.90-13.39 | 4.3 | 6.05 | 0.36 |
| 2019 | 33 | qLRI1-2 | 1 | 20.77–21.12 | 5.2 | 6.25 | 0.39 |
| | 33 | qLRI1-3 | 1 | 135.79-136.44 | 2.81 | 3.3 | 0.21 |
| | 33 | qLRI2-3 | 2 | 41.53–42.02 | 3.81 | 4.49 | -0.24 |
| | 49 | qLRI5-3 | 5 | 89.89–90.61 | 4.01 | 8.1 | 0.21 |
| | 63 | qLRI5-4 | 5 | 93.85–94.46 | 6.3 | 11.13 | 0.41 |
| | 63 | qLRI12-1 | 12 | 12.90-13.39 | 2.75 | 4.75 | 0.27 |
| | 49 | qLRI12-2 | 12 | 13.39–14.06 | 3.67 | 7.32 | 0.2 |
| | 33 | qLRI12-3 | 12 | 14.06–15.71 | 5.26 | 6.48 | 0.3 |
LWD | 2017 | 32 | qLWD1-1 | 1 | 55.92–56.51 | 6.36 | 9.37 | -0.56 |
| | 46 | qLWD3-1 | 3 | 147.66-148.39 | 2.54 | 3.62 | 0.34 |
| | 32 | qLWD4-1 | 4 | 31.86–33.78 | 5.37 | 8.19 | -0.52 |
| | 46 | qLWD4-1 | 4 | 31.86–33.78 | 4.63 | 7.07 | -0.48 |
| | 46 | qLWD5-1 | 5 | 94.92–95.19 | 5.1 | 7.34 | 0.48 |
| | 32 | qLWD5-2 | 5 | 100.02–101.10 | 5.99 | 8.76 | 0.53 |
| 2018 | 57 | qLWD3-2 | 3 | 140.04-141.48 | 2.73 | 4.77 | 0.2 |
| | 29 | qLWD4-2 | 4 | 29.76–30.14 | 2.87 | 5.14 | 0.21 |
| | 42 | qLWD4-2 | 4 | 29.76–30.14 | 3.29 | 5.26 | 0.24 |
| | 57 | qLWD4-2 | 4 | 29.76–30.14 | 3.3 | 5.71 | 0.22 |
| | 57 | qLWD12-1 | 12 | 14.06–15.71 | 3.56 | 6.77 | 0.24 |
| 2019 | 63 | qLWD3-3 | 3 | 70.52–71.14 | 3.66 | 4.86 | -0.51 |
| | 49 | qLWD5-3 | 5 | 89.89–90.61 | 3.07 | 6.15 | 0.3 |
| | 63 | qLWD5-4 | 5 | 93.85–94.46 | 5.97 | 8.05 | 0.63 |
| | 33 | qLWD8-1 | 8 | 11.59–12.30 | 2.66 | 5.76 | -0.24 |
| | 63 | qLWD8-2 | 8 | 89.04–90.63 | 3 | 3.95 | 0.46 |
| | 33 | qLWD9-1 | 9 | 37.99–38.20 | 2.51 | 5.36 | -0.23 |
| | 63 | qLWD9-2 | 9 | 70.83–71.61 | 3.34 | 4.47 | 0.47 |
| | 49 | qLWD12-2 | 12 | 13.39–14.06 | 4.16 | 8.4 | 0.36 |
A positive additive effect indicates that the beneficial allele is derived from the male parent “Milyang 23”; a negative additive effect indicates that the beneficial allele is derived from the female parent “Jileng 1”.
Discovery of Drought-resistance Genes and Excellent Haplotypes in Rice
There were 281 genes located in the QTL region, with 201 genes located in the region with a LOD > 3. Among these genes, 147 were up-regulated and 54 were down-regulated. The most significantly up-regulated and down-regulated genes were located on chromosome 5. The gene with the highest up-regulated expression was located in a 0.00 cM–1.28 cM region with a LOD value of 12.82. Conversely, the gene with the most down-regulated expression was found in a 2.59 cM–3.52 cM region with a LOD value of 20.73. A total of 90 genes were found in the co-localized QTLs, and 31 genes were repeatedly detected in the two-year drought resistance identification. Three drought resistance genes, OsANN1, OsSLAC1, and OsTPS1, are located on chromosomes 2 (31665723–31765723 bp), 4 (29020325–28882817 bp), and 5 (25576289–26094452 bp), respectively (Zang et al. 2011; Qiao et al. 2015; Sun et al. 2016).
During the haplotype analysis of the RIL population, two candidate genes with significant differences were noted in the intervals of 34757965–34738491 bp on chromosome 4 and 19640244–19535141 bp on chromosome 7. The sequences of non-homogeneous SNPs in the genes Os04g0574600 (LOC_Os04g48520) and OsCHR731 (LOC_Os07g32730) were extracted to identify these genes. These two genes were designated as candidate genes because of the presence of repeated allelic variants. The coding sequence of Os04g0574600, which is 2001 bp, contains four SNPs: 28922253 (T→C), 28926734 (C→T), 28927682 (G→T), and 28928513 (T→A). In the 1107 bp coding sequence of OsCHR731, there is one SNP (A→G). For both genes, there were two haplotypes, haplotype 1 (Hap1) and haplotype 2 (Hap2), present in the RIL population, there were significant differences in the phenotypic values of LRI and LWD between RILs carrying Hap1 and those carrying Hap2 (P < 0.05, P < 0.01) (Fig. 1, 2). Specifically, the phenotypic values of LRI and LWD were much lower in Hap2-carrying RILs than in Hap1-carrying RILs. These results suggest that RILs carrying Hap2 of either Os04g0574600 or OsCHR731 exhibit stronger drought resistance than those carrying Hap1.
The Expression of Candidate Genes Related to Drought Resistance Differs Between the Treatment Group and the Control Group
qRT-PCR analysis was performed to assess the difference in expression of candidate genes between the treatment and control groups. The expression levels of the candidate genes were generally higher in the treatment group than in the control group. Specifically, the expression of Os04g0574600 was significantly higher in the treatment group than in the control group in five out of seven samples tested. In the treatment group, the expression level of R8 was the highest (7.68 times that of the control group). R16 had an expression level 3.86 times higher than that the control group. R20 and R26 had expression levels 1.11 and 1.20 times higher than that of the control group, respectively, but these differences were not significant. In six out of the seven samples tested, the expression of OsCHR731 was considerably or extremely considerably higher than that of the control group. Like Os04g0574600, OsCHR731 was most highly expressed in the R8 treatment group (19.47 times that of the control group). The expression level of OsCHR731 in the R16 treatment group was 6.26 times that of the control group. These results suggest that Os04g0574600 and OsCHR731 play an important part in regulating rice drought tolerance.
Geographical Distribution of Haplotypes for Candidate Drought-Tolerance Genes
To investigate the geographical distributions of the Os04g0574600 and OsCHR731 haplotypes, we analyzed the haplotypes of 372 rice germplasm resources from 12 provinces in the Yangtze River and southern regions. The genomic data for these rice materials were obtained from the NCBI database (Liu et al. 2022). Of the rice germplasm resources, 209 were indica rice and 163 were japonica rice. There were two haplotypes (Hap1 and Hap2) of Os04g0574600 in indica rice, accounting for 8.97% and 91.03% of accessions, respectively. In japonica rice, only Hap1 was detected. There were three haplotypes of OsCHR731 in indica rice: Hap1, Hap2, and Hap3, accounting for 1.22%, 96.95%, and 1.83% of accessions, respectively. In japonica rice, 89.37%, 10.15%, and 0.48% of accessions had Hap1, Hap2, and Hap3, respectively.
Haplotype analysis of rice germplasm resources showed that the proportion of accessions with the superior Os04g0574600 haplotype Hap2 among the 12 provinces ranked as follows: Sichuan (93.33%) > Anhui (75.00%) > Yunnan (68.75%) > Fujian (66.67%) > Guangdong (64.71%) > Hunan (44.44%) > Jiangxi (37.50%) > Hubei (35.71%) > Guizhou (27.07%) > Jiangsu (25.00%) > Guangxi (23.53%) > Zhejiang (15.38%) (Fig. 5). In five of the provinces over 50% of accessions had Hap 2. The proportion of accessions with the superior haplotype of OsCHR731, Hap2, in 12 provinces ranked as follows: Sichuan (100%) > Yunnan (85.71%) > Anhui (84.62%) > Fujian (80.00%) > Guangdong (77.78%) > Hubei (50.00%) > Guangxi (47.06%) > Hunan (44.44%) > Jiangxi (43.75%) > Guizhou (37.93%) > Jiangsu (26.67%) > Zhejiang (Fig. 6). In addition, Hap2 was found in more than 50% of accessions in five other provinces. Hap2 of both genes was dominant among the local rice resources of Sichuan, Yunnan, Anhui, Fujian, and Guangdong provinces, whereas a low proportion of the local rice resources of Zhejiang carried these haplotypes (Fig. 5A, 6A).
Haplotype analysis of wild rice resources showed that 50% carried Hap1 of Os04g0574600 and 50% carried Hap4 (Fig. 5B), and 13.51%, 59.46%, and 27.03% carried Hap1, Hap2, and Hap3 of OsCHR731, respectively (Fig. 6B).