Fine-mapping of qTGW2, a quantitative trait locus for grain weight in rice (Oryza sativa L.)

Plant materials

Nine mapping populations of indica rice were used in this study. The first one was an F_10:11 population that was previously developed from one RH in the F₇ generation of TQ/IRBB52 (Zhang et al., 2019), consisting of 250 families and segregated 16 regions distributed on the 12 rice chromosomes. This population was named W1. The remaining eight populations were developed from RHs selected from the W1 population as described below and illustrated in Fig. 1. Three plants in F₁₀, which carried heterozygous segments that covered partial or entire region of the interval Tw31911−RM266 on chromosome 2, were identified. They were selfed to produce three NIL-F₂ populations consisting of 205, 239 and 234 plants and named ZH1, ZH2 and ZH3, respectively. Two QTLs were separated, of which qTGW2 located in the downstream region was selected for further analysis. Non-recombinant homozygotes were identified in the ZH2 and ZH3 populations and selfed. Two sets of NILs named HY2 and HY3 were developed, each consisting of 35 TQ homozygous lines and 35 IRBB52 homozygous lines. They were used to validate qTGW2. Then, other three RHs, carrying heterozygous segments overlapped in the terminal region Tw35293−RM266 of chromosome 2, were identified from the W1 population. The three plants were selfed to produce three NIL-F₂ populations in F₁₂, which consisted of 174, 237 and 228 plants and named Z1, Z2 and Z3, respectively.

Field experiment and trait measurement

The rice populations were planted in the experimental stations of the China National Rice Research Institute located at either Lingshui in Hainan Province or Hangzhou in Zhejiang Province. For the F_10:11 population and two sets of NILs, the experiments followed a randomized complete block design with two replications. For each replication, twelve plants per line were planted in one row. At maturity, five of the middle ten plants in each row were harvested in bulk and sun-dried. Two samples of approximately 10 g fully filled grains were randomly selected for the measurement of TGW, GL, GW, and length/width ratio (LWR) following the procedure reported by Zhang et al. (2016). For the six NIL-F₂ populations, plants were harvested individually and sun-dried. Two samples of approximately 3 g fully filled grains of each plant were selected for the measurement of the four traits.

DNA marker analysis

For the W1 population and two NIL populations, leaf samples collected from the middle eight plants of a rice line were mixed for DNA extraction using a mini-preparation protocol (Zheng et al., 1995). For the six NIL- F₂ populations, a two cm-long leaf sample collected from an F₂ plant was used for DNA extraction using the same method. PCR amplification was performed according to Chen et al. (1997). The products were visualized on 6% non-denaturing polyacrylamide gels using silver staining. A total of 68 polymorphic markers were used, including 57 simple sequence repeats, eight insertion/deletions, one cleaved amplified polymorphic sequence, and two sequence tagged sites. Nine of them were developed according to sequence differences between TQ and IRBB52 detected with whole-genome resequencing (Table S1).

Data analysis

For the W1 and six NIL-F₂ populations, genetic maps of each populations were constructed using Mapmaker/Exp 3.0, in which genetic distances between markers were presented in centiMorgan (cM) derived with Kosambi function. QTL mapping was performed using the default setting of the BIP (QTL mapping in bi-parental populations) approach in IciMapping V4.1 (Meng et al., 2015). LOD thresholds were calculated with 1,000 permutation test (P < 0.05) and used to claim a putative QTL.

For the two NIL populations, two-way analysis of variance (ANOVA) was performed to test the phenotypic differences between the two genotypic groups in each NIL set. The analysis was performed using the SAS procedure GLM (SAS Institute Inc, 1999) as described previously (Dai et al., 2008). Given the detection of a significant difference (P < 0.05), the same data were used to estimate the genetic effect of the QTL, including additive effect and the proportion of phenotypic variance explained (R²). QTL were designated according to the rules recommended by McCouch & CGSNL (2008).

QTLs detected in the W1 population

A total of 27 QTLs for the four traits were detected, which were distributed on 14 segregating regions (Fig. 2, Table 1). Four of them had significant effects on three traits. In the Tw35293−RM266 region on chromosome 2, the IRBB52 allele increased TGW, GL and GW by 0.39 g, 0.060 mm and 0.013 mm, respectively. In the RM14032−RM14383 interval on chromosome 3, the IRBB52 allele increased GL by 0.025 mm, decreased GW by 0.014 mm and increased LWR 0.022. In the RM16252−RM335 region on chromosome 4, the IRBB52 allele decreased TGW and GW by 0.18 g and 0.017 mm, respectively, but increased LWR by 0.021. In the Tv963−RM27610 interval on chromosome 12, the IRBB52 allele increased GL by 0.031 mm, decreased GW by 0.013 mm and increased LWR 0.027. Worthy to note, the Tw35293−RM266 region had R² of 14.50% for TGW and 18.60% for GL, which were much higher than the R² values for these two traits detected in the other three regions.

Five regions had significant effects on two traits. In the RM12210 region on chromosome 1 the IRBB52 allele increased GL and LWR by 0.026 mm and 0.011, respectively. In the RM3321−RM274 interval on chromosome 5, the IRBB52 allele increased GL and LWR by 0.062 mm and 0.018, respectively. In the RM549 region on chromosome 6, the IRBB52 allele increased TGW and GW by 0.27 g and 0.012 mm, respectively. In the interval RM22755−RM23001 on chromosome 8, the IRBB52 allele reduced GW by 0.009 mm and increased LWR by 0.017. In the interval RM1108−RM7300 on chromosome 10, the IRBB52 allele reduced GW by 0.004 mm and increased LWR by 0.012.

The remaining five QTLs were unaccompanied with other QTLs, including qTGW7 for TGW, qGW9.1 and qGW9.2 for GW, and qLWR11 and qLWR12.2 for LWR.

Dissection of two QTLs for grain size on chromosome 2

As described above, the terminal region of chromosome 2 had relatively large effects in terms of the number of QTLs detected and R² of single QTL. Therefore, this region was chosen for further validation and fine-mapping.

Three NIL-F₂ populations, ZH1, ZH2 and ZH3, were constructed, following the results of the W1 population (Fig. 3A). To fill the long distance between Tw32437 and Tw35293, two polymorphic markers, RM14034 and RM14056, were selected (Table S1). The two markers were homozygous in all the three populations. Two segregating regions, Tw31911−Tw32437 and Tw35293−RM266, were separated in the Z1 population (Fig. 3B). As shown in Table 2, QTLs were detected in both regions. In the interval Tw31911−Tw32437, the IRBB52 allele decreased TGW and GL but increased GW and LWR, having R² of 6.05, 29.51, 13.61 and 28.52%, respectively. QTLs in this region affected GL and GW with opposite directions. The effect was larger on GL than on GW, resulting in the detection of a residual effect on TGW. Thus, this QTL was nominated as qGL2. In the Tw35293−RM266 region, the IRBB52 allele increased TGW, GL and GW, having R² of 31.76, 17.95 and 3.73%, respectively. QTLs in this region affected GL and GW with the same direction, and the accumulative effect resulted in larger influence on TGW. Thus, this QTL was nominated as qTGW2.

The ZH2 and ZH3 populations were only segregated in the Tw35293−RM266 region. In both populations, significant effects were detected on all the traits except LWR. The enhancing alleles were always derived from IRBB52, and the effects were similar between the two populations. The additive effects were 0.55 and 0.46 g on TGW, 0.065 and 0.061 mm on GL, and 0.021 and 0.020 mm on GW. The R² were 28.63 and 21.83% for TGW, 22.34 and 28.86% for GL, and 22.91 and 22.37% for GW. These results are similar to those found in the ZH1 population, indicating that qTGW2 located in the interval Tw35293−RM266 affects TGW, GL and GW with the same allelic direction. Since qTGW2 showed stable effects across the three populations, this QTL was selected for further analysis.

Validation and fine-mapping of qTGW2

Two sets of NILs, HY2 and HY3, were used to validate the genetic effects of qTGW2. Frequency distributions of the four traits were plotted using the two genotypic groups as two series (Fig. 4). For TGW, GL and GW, the difference between the TQ and IRBB52 homozygous genotypes were observed in both the populations. The IRBB52 homozygous lines were distributed in the higher-value region, and the TQ homozygous lines were distributed in the lower-value region. On the other hand, no distinction was found for LWR. These results indicate that QTLs for TGW, GL and GW were segregated in the two populations with the enhancing alleles derived from IRBB52.

Results of the two-way ANOVA on the four traits are presented in Table 3. Highly significant effects (P < 0.0001) were detected for TGW, GL and GW in both the HY2 and HY3 populations. The effects were similar between the two populations, with the IRBB52 allele always increasing the trait values. The additive effects were 0.47 and 0.45 g on TGW, 0.054 and 0.061 mm on GL, and 0.021 and 0.013 mm on GW. The R² were 60.94 and 66.02% for TGW, 48.26 and 62.12% for GL, and 36.67 and 22.74% for GW. In addition, significant influence on LWR were only detected in the HY3 population (P = 0.0003). The IRBB52 allele increased LWR by 0.009 with the R²of 12.94%. It was found that the allelic direction of qTGW2 remained unchanged across the five populations, with the IRBB52 allele always increasing TGW, GL and GW. As compared to the ZH1, ZH2 and ZH3 populations, the additive effect of qTGW2 hardly changed but the R² values increased greatly in HY2 and HY3.

To further narrow down the region of qTGW2, three polymorphic markers, RM14189, Tw35277 and Tw35395, were added (Table  S1). Three plants were identified from the W1 population and selfed to produce three NIL-F₂ populations named Z1, Z2 and Z3. As shown in Fig. 3C, the segregating regions in Z1, Z2 and Z3 were RM14189−Tw35293, Tw35293−RM266, and Tw35395−RM266, respectively. QTL analysis for TGW, GL, GW and LWR were conducted (Table 4). Significant effects were detected in Z2 but not in the other two populations. This result suggests that qTGW2 was segregated in Z2 but not in Z1 and Z3. Consequently, the qTGW2 was delimited within a 103-kb region flanked by Tw35293 and Tw35395. In Z2, the IRBB52 allele increased TGW by 0.46 g, GL by 0.053 mm and GW by 0.014 mm, with the R² of 29.93, 16.26 and 13.70%, respectively.