*2.6. Na*<sup>+</sup> *and K*<sup>+</sup> *Content in Shoot and Roots of the Tested Genotypes under Salt Stress*

We assayed the K<sup>+</sup> and Na<sup>+</sup> contents in shoots and roots of seedlings under salinity, since the degree of stress depends on their uptake and translocation. Under control condition, shoot K<sup>+</sup> was significantly lower in "YNU31-2-4" than in its parent (Figure 5A), whereas under salt stress, it was 1.4× the WT level in shoot and 2.6<sup>×</sup> in root (Figure 5A,D). Under control condition, Na<sup>+</sup> levels in leaves (Figure 5B) and roots (Figure 5E) of all genotypes remained similarly low. Salinity stress increased Na<sup>+</sup> concentration in WT shoots relative to the other two genotypes, reaching 6.5× that in "YNU31-2-4" plants (Figure 5B). Under control conditions, the Na+/K <sup>+</sup> ratio did not differ significantly among the tested genotypes in shoots (Figure 5C) and roots (Figure 5F). Under salinity, it was 9.2× the "YNU31-2-4" level in WT shoots and 2.9× in WT roots (Figure 5C,F).

salt tolerance than "Yukinko-mai" (WT) at the seedling stage.

**Figure 4.** Salinity tolerance of BC3F3 line "YNU31-2-4" at seedling stage. (**A**) Phenotypic comparison of "Kaijin", WT, and "YNU31-2-4" seedlings grown in 0, 75, or 125 mM NaCl for two weeks. (**B**) Survival rates, (**C**) shoot length, (**D**) root length, (**E**) shoot dry weight, and (**F**) root dry weight of seedlings shown in **A**. Data in **B**–**F** are mean ± SD of four independent biological replicates; data in **E** and **F** are dry weight (DW) of 10 plants in each treatment. Bars labeled with the same letter are not statistically different (Tukey's test, *p* < 0.05). **Figure 4.** Salinity tolerance of BC3F<sup>3</sup> line "YNU31-2-4" at seedling stage. (**A**) Phenotypic comparison of "Kaijin", WT, and "YNU31-2-4" seedlings grown in 0, 75, or 125 mM NaCl for two weeks. (**B**) Survival rates, (**C**) shoot length, (**D**) root length, (**E**) shoot dry weight, and (**F**) root dry weight of seedlings shown in **A**. Data in **B**–**F** are mean ± SD of four independent biological replicates; data in **E** and **F** are dry weight (DW) of 10 plants in each treatment. Bars labeled with the same letter are not statistically different (Tukey's test, *p* < 0.05).

*2.6. Na+ and K+ Content in Shoot and Roots of the Tested Genotypes under Salt Stress*  We assayed the K+ and Na+ contents in shoots and roots of seedlings under salinity, since the degree of stress depends on their uptake and translocation. Under control condition, shoot K+ was Under the control condition, electron probe microanalysis revealed a dense distribution of K<sup>+</sup> in the basal portion of the shoot of all genotypes, but only a very sparse distribution of Na<sup>+</sup> (Figure 6). Under salt stress, the Na<sup>+</sup> distribution in cells was increased in all genotypes, and the salt-sensitive WT accumulated significantly more Na<sup>+</sup> than the other two genotypes (Figure 6).

significantly lower in "YNU31-2-4" than in its parent (Figure 5A), whereas under salt stress, it was

#### 1.4× the WT level in shoot and 2.6× in root (Figure 5A,D). Under control condition, Na+ levels in leaves *2.7. Salinity Tolerance and Yield Assessment at Reproductive Stage*

(Figure 5B) and roots (Figure 5E) of all genotypes remained similarly low. Salinity stress increased Na+ concentration in WT shoots relative to the other two genotypes, reaching 6.5× that in "YNU31-2- 4" plants (Figure 5B). Under control conditions, the Na+/K+ ratio did not differ significantly among Under control condition at the reproductive stage, there was no obvious phenotypic difference between WT and "YNU31-2-4" plants (Figure 7A). Salt stress for five weeks caused severe burning and wilting symptoms in WT, but "YNU31-2-4" and "Kaijin" plants maintained green leaves. Under control condition, the penultimate leaves of "YNU31-2-4" plants maintained a slightly higher net CO<sup>2</sup>

assimilation rate than the parents (Figure 7B). Salt stress for four weeks significantly reduced the net CO<sup>2</sup> assimilation rate of WT plants relative to "YNU31-2-4" and "Kaijin". Under the control condition, WT and "YNU31-2-4" plants had similar phenotypic characters and yield attributes except for a higher 1000-spikelet weight than the parents (Figure 7C–G). Under salt stress, in contrast, "YNU31-2-4" had higher plant height, yield characters, and aboveground biomass than WT (Figure 7C–G,I). Relative to control condition, salt stress reduced grain yield by 68% in WT but by 38% in "YNU31-2-4" (Figure 7H). As a result, the grain yield of "YNU31-2-4" was 10% higher than that of the donor parent "Kaijin" under control condition and 45% higher than that of WT under saline condition. *Int. J. Mol. Sci.* **2019**, *20*, x FOR PEER REVIEW 10 of 22 the tested genotypes in shoots (Figure 5C) and roots (Figure 5F). Under salinity, it was 9.2× the "YNU31-2-4" level in WT shoots and 2.9× in WT roots (Figure 5C,F). Under the control condition, electron probe microanalysis revealed a dense distribution of K+ in the basal portion of the shoot of all genotypes, but only a very sparse distribution of Na+ (Figure 6). Under salt stress, the Na+ distribution in cells was increased in all genotypes, and the salt-sensitive WT accumulated significantly more Na+ than the other two genotypes (Figure 6). *Int. J. Mol. Sci.* **2019**, *20*, x FOR PEER REVIEW 10 of 22 the tested genotypes in shoots (Figure 5C) and roots (Figure 5F). Under salinity, it was 9.2× the "YNU31-2-4" level in WT shoots and 2.9× in WT roots (Figure 5C,F). Under the control condition, electron probe microanalysis revealed a dense distribution of K+ in the basal portion of the shoot of all genotypes, but only a very sparse distribution of Na+ (Figure 6). Under salt stress, the Na+ distribution in cells was increased in all genotypes, and the salt-sensitive WT accumulated significantly more Na+ than the other two genotypes (Figure 6).

**Figure 5.** Na+ and K+ content in shoot and roots of the tested genotypes under salt stress. (**A**) Shoot K+, (**B**) shoot Na+, (**C**) shoot Na+/K+, (**D**) root K+, (**E**) root Na+, and (**F**) root Na+/K+ of 20-day-old seedlings. Data are mean ± SD of three independent biological replicates. Bars with the same letter are not statistically different (Duncan's multiple range test, *p* < 0.05). **Figure 5.** Na<sup>+</sup> and K<sup>+</sup> content in shoot and roots of the tested genotypes under salt stress. (**A**) Shoot K <sup>+</sup>, (**B**) shoot Na+, (**C**) shoot Na+/K <sup>+</sup>, (**D**) root K+, (**E**) root Na+, and (**F**) root Na+/K <sup>+</sup> of 20-day-old seedlings. Data are mean ± SD of three independent biological replicates. Bars with the same letter are not statistically different (Duncan's multiple range test, *p* < 0.05). **Figure 5.** Na+ and K+ content in shoot and roots of the tested genotypes under salt stress. (**A**) Shoot K+, (**B**) shoot Na+, (**C**) shoot Na+/K+, (**D**) root K+, (**E**) root Na+, and (**F**) root Na+/K+ of 20-day-old seedlings. Data are mean ± SD of three independent biological replicates. Bars with the same letter are not statistically different (Duncan's multiple range test, *p* < 0.05).

**Figure 6.** Accumulation and distribution of K+ and Na+ in cell clusters of 20-day-old seedlings. Relative amounts of K+ and Na+ are indicated by color coding. SE, secondary electron image; MP\_K+, mapping pattern of K+; MP\_Na+, mapping pattern of Na+. **Figure 6.** Accumulation and distribution of K+ and Na+ in cell clusters of 20-day-old seedlings. Relative amounts of K+ and Na+ are indicated by color coding. SE, secondary electron image; MP\_K+, mapping pattern of K+; MP\_Na+, mapping pattern of Na+. **Figure 6.** Accumulation and distribution of K<sup>+</sup> and Na<sup>+</sup> in cell clusters of 20-day-old seedlings. Relative amounts of K<sup>+</sup> and Na<sup>+</sup> are indicated by color coding. SE, secondary electron image; MP\_K+, mapping pattern of K+; MP\_Na+, mapping pattern of Na+.

Under control condition at the reproductive stage, there was no obvious phenotypic difference

Under control condition at the reproductive stage, there was no obvious phenotypic difference

*2.7. Salinity Tolerance and Yield Assessment at Reproductive Stage* 

*2.7. Salinity Tolerance and Yield Assessment at Reproductive Stage* 

condition.

and wilting symptoms in WT, but "YNU31-2-4" and "Kaijin" plants maintained green leaves. Under control condition, the penultimate leaves of "YNU31-2-4" plants maintained a slightly higher net CO2 assimilation rate than the parents (Figure 7B). Salt stress for four weeks significantly reduced the net CO2 assimilation rate of WT plants relative to "YNU31-2-4" and "Kaijin". Under the control condition, WT and "YNU31-2-4" plants had similar phenotypic characters and yield attributes except for a higher 1000-spikelet weight than the parents (Figure 7C–G). Under salt stress, in contrast, "YNU31-2-4" had higher plant height, yield characters, and aboveground biomass than WT (Figure 7C–G, I). Relative to control condition, salt stress reduced grain yield by 68% in WT but by 38% in "YNU31-2-4" (Figure 7H). As a result, the grain yield of "YNU31-2-4" was 10% higher than that of

**Figure 7.** Salinity tolerance of BC3F3 line "YNU31-2-4" at heading. (**A**) Phenotypic comparison of "Kaijin", WT, and "YNU31-2-4" plants grown with or without salt stress. Salt-stressed plants were grown in 50 mM NaCl from 60 days after germination (DAG) and then in 75 mM from 74 DAG until 95 DAG (booting stage), and then in fresh water until 110 DAG (heading). (**B**) Net CO2 assimilation rate of the penultimate leaf four weeks after imposition of salt treatment. (**C**) Comparison of plant height at 110 DAG. (**D–I**) Comparisons of (**D**) number of panicles/plant, (**E**) panicle length, (**F**) number of filled spikelets/panicle, (**G**) weight of 1000 filled spikelets, (**H**) grain yield/plant, and (**I**) dry weight **Figure 7.** Salinity tolerance of BC3F<sup>3</sup> line "YNU31-2-4" at heading. (**A**) Phenotypic comparison of "Kaijin", WT, and "YNU31-2-4" plants grown with or without salt stress. Salt-stressed plants were grown in 50 mM NaCl from 60 days after germination (DAG) and then in 75 mM from 74 DAG until 95 DAG (booting stage), and then in fresh water until 110 DAG (heading). (**B**) Net CO<sup>2</sup> assimilation rate of the penultimate leaf four weeks after imposition of salt treatment. (**C**) Comparison of plant height at 110 DAG. (**D–I**) Comparisons of (**D**) number of panicles/plant, (**E**) panicle length, (**F**) number of filled spikelets/panicle, (**G**) weight of 1000 filled spikelets, (**H**) grain yield/plant, and (**I**) dry weight of aboveground biomass at harvest. Data are mean ± SD of 6 individuals. Bars with the same letter are not statistically different (Duncan's multiple range test, *p* < 0.05).

#### **3. Discussion**

Soil salinity is a major threat to the future food production, affecting more than 6% of the total land area [54]. The rapid global warming and sea level rise pose threats to rice yield and quality in South Asian rice-growing countries. In addition, a tsunami contaminated paddy field in Miyagi prefecture, Japan, with salt in 2011 [32,37,55]. Therefore, it is important to introgress genes/QTLs/SNPs conferring salt tolerance in locally grown popular rice cultivars, focusing on higher grain yield, to ensure food security under changing climatic conditions. Cultivar improvement through conventional breeding

is feasible, but it takes a long time to minimize linkage drag through phenotypic screening [56,57]. For these reasons and to achieve breeding goals, we introgressed the *hst1* gene from "Kaijin" into "Yukinko-mai", which has excellent yield stability. We developed the BC3F<sup>3</sup> generation, named "YNU31-2-4", through SNP marker-assisted selection (Figure 1A).

To accelerate the breeding cycle, we used a biotron speed-breeding system (Figure S1) without a CO<sup>2</sup> supply, since the application of 475 ppm CO<sup>2</sup> in growth chambers did not greatly change the breeding cycle [45], and many rice breeders do not have CO<sup>2</sup> regulation facilities owing to the high cost. By using a longer daylength (14/10 h light/dark) for first 30 days to accelerate the vegetative growth followed by a shorter daylength (10/14 h light/dark) to induce reproduction, tiller removal, and embryo rescue to decrease the period before seed maturity (Figure S1), we were able to achieve four breeding generations within 11 months (Table S1). Developing four to five generations a year is the ultimate objective [46–48]. This simplified, faster, efficient method for reducing the duration and number of breeding cycles will contribute significantly to genomic studies and the deployment of superior rice.

We used whole-genome sequencing (WGS) to characterize the advanced breeding lines and revealed genome recovery rate, genotype blocks, and putative phenotypes (Figures 2 and 3; Tables 1 and 2). WGS identified 118 454 SNPs/indels as markers. As WGS provides higher resolution of genome blocks than conventional SSR marker methods [58], it can thus be used for advancing generations from parents with low genetic variation, as here. Furthermore, in subsequent selection, knowledge of these genotype blocks helped us to rapidly fix heterozygous regions into the recipient allele through the MABC selection method (Figure S2A). Our high-resolution analysis with massive numbers of SNP/indel markers not only enabled accurate genome-wide genotyping, but also highlighted potential recombination hotspots.

Functional annotation was able to predict five SNP/indels (Table 2) that may affect agronomic traits and thus phenotype in our advanced line "YNU31-2-4". One of two non-synonymous changes in *Os09g0356200*, a putative heading-date-associated gene identified in a gene-based genome-wide association study (GWAS) [53], caused a frameshift deletion probably causing loss-of-function. BC3F<sup>3</sup> progeny of BC3F<sup>2</sup> plants harboring the *Os09g0356200* gene in the heterozygous state likely shows a wide range of heading date. Indeed, the field assessment results demonstrate the difference in the distribution of heading dates between "YNU31-2-4" and WT ("Yukinko-mai") (Table 3; Figure S2B). Additionally, the heading date of the BC3F<sup>3</sup> population was associated with the genotype of the putative heading-date-associated gene *Os09g0356200* (Table 2; Figure S2). Our finding indicates the potential value and reliability of gene-based GWAS among the Japanese rice population data set [53] in breeding by incorporating the genetic variations into those cultivars, and its practical value in predicting genes governing complex traits of agronomic phenotypes. The results of whole-genome sequencing have demonstrated the success in developing improved cultivars using our rapid breeding system. They also reveal undesirable genome regions and genes from the donor parent "Kaijin", valuable information for estimating agronomic properties without further phenotyping study. Identifying heterozygous genes can provide mechanistic insights toward homogenizing phenotypes for ongoing breeding. It is important to note that the heterozygote disadvantage has been overcome by taking advantage of the SNP-based selection of the homozygous WT allele from the YNU31-2-4 population (Figure S2). Furthermore, other morphological traits of "YNU31-2-4" were similar to those of WT (Table 3; Figure S3A–C). The field assessment results along with the high-resolution genotyping data indicate no apparent grain yield reduction in "YNU31-2-4" in relation to the presence of the target *hst1* gene. In fact, "YNU31-2-4" increased ca. 11% yield than the donor parent "Kaijin" owing to the higher number of panicles per plant and 1000-grain weight.

Rice is very sensitive to salt stress at the seedling stage [7], and its sensitivity varies with the developmental stage [59]. To assess the practical utility of *hst1* in our introgression line, we exposed seedlings to moderate (75 mM) and high (125 mM) salt stresses. Salt tolerance at this stage is of importance in saline environments, as crop establishment is fundamentally determined during the earliest stages of development. Our findings revealed that under high salt stress, the "YNU31-2-4" plants had a significantly higher survival rate, shoot, and root biomass than WT (Figure 4A–F), which suggest strong tolerance similar to that of the donor parent. The "YNU31-2-4" plants maintained significantly higher plant growth, proline content, and plant water status under salinity, which could indicate a physiological and biochemical tolerance mechanism [54,60]. In fact, previous studies showed that salinity might reduce the fertility of the spike and the translocation of assimilates to the grain in bread wheat and rice. Physiologically, the "YNU31-2-4" maintain its fully hydrated state under saline condition, which could at least partially have rapid and large effects on cell expansion, cell division, stomatal opening, maintain normal rates of transpiration, abscisic acid (ABA) accumulation, etc. Assay of soluble proline levels is a useful way to monitor physiological status and to assess stress tolerance, since plants under salt stress accumulate this osmoprotectant against ion-dependent protein degradation [61]. Proline is accumulated in taxonomically diverse sets of plants [62], providing stress tolerance by protecting the cell membrane and maintaining osmotic balance within the cell, and also serves as an organic nitrogen reserve during stress recovery [61,63,64].

We also assessed yield traits of "YNU31-2-4" under salt stress at the early reproductive to booting stages, when salt stress reduces panicle and spikelet numbers per plant, leading to significant yield losses [65,66]. The improvement of rice grain yield under salt stress is the focus of breeding [67]. Owing to the significant increases in panicle number per plant, spikelet number per panicle, and 1000-spikelet weight, the final grain yield of "YNU31-2-4" plants was 45% higher than WT under salt stress at the reproductive stage (Figure 7D,F–H). Under control condition, there was no yield difference between "YNU31-2-4" and WT (Figure 7H). Interestingly, "YNU31-2-4" has higher yield potential than the donor parent under control condition owing to the higher number of panicles per plant and 1000-spikelet weight, comparable to the field evaluation results (Figure 7D, G). The higher number of panicles can be attributable to the WT background. The higher seed weight of "YNU31-2-4" could be due, at least partly, to the improved photosynthetic efficiency (Figure 7B) due to coordination of leaf morphological (Table 3) and physiological (Figure 7B; Figure S4) traits, which has great potential for use in breeding for higher yield. Accordingly, "YNU31-2-4" showed larger flag leaf than the donor "Kaijin", which could play an important role to grain filling and hence determining yield potential. The superior tiller growth with higher leaf size rendered the source, sink, and flow stronger and more harmonized and consequently increased the cereal yield [68–72]. Thus, this study clearly shows that the introgression of *hst1* to the WT significantly increased salt resistance without any reduction in grain yield. Thus, "YNU31-2-4" has significant breeding value without a noticeable yield penalty under normal and salt stress conditions.

Roots absorb minerals and water from the soil and play a key role in transporting them to leaves. In the context of salt tolerance, roots are sensitive to NaCl and are the first site of defense, directly limiting or excluding sodium uptake [54,73]. Roots are often used as a biomarker of salt stress. Root architecture differed between WT and "YNU31-2-4" plants after two weeks of normal hydroponic culture (Figure S5). Roots of "YNU31-2-4" and "Kaijin" exposed to high salt stress elongated more than WT roots (Figure 4D). The better morphophysiological and biochemical characters of "YNU31-2-4" under salt stress demonstrate the success of introgression of *hst1* into "Yukinko-mai".

The genes involved in conferring salt tolerance, which is likely a complex trait controlled by a combination of multiple genes, are yet to be elucidated. Recent research advances have identified major genes conferring salinity tolerance in rice, including *OsHKT1;1*, *OsHKT2;1*, *OsSOS1*, *OsNHX1*, *OsCAX1*, *OsAKT1*, *OsKCO1*, *OsNRT1;2*, *OsCLC1*, *OsADS31* and *OsTPC1*; however, their functional pathways during salt stress are not coordinately linked for explaining the very complex phenomenon of salt tolerance [16,74,75]. The *hst1* (loss-of-function in *OsRR22*) gene primarily led to the upregulation of *OsHKT1;1* (encoding a high-affinity K<sup>+</sup> transporter) that functions as a Na<sup>+</sup> transporter contributing salt resistance of the *hst1* mutant and "Kaijin" [32]. In our experiment, Na<sup>+</sup> content and Na+/K <sup>+</sup> ratio in leaf and root were divergent between WT and "YNU31-2-4" and therefore may represent the effects of "basic" strategies related to salt tolerance or susceptibility. The quantification and localization results demonstrate that like "Kaijin", "YNU31-2-4" plants maintained a very low Na+/K <sup>+</sup> ratio in both

shoot and root under salt stress (Figure 5C,F), which is one of the most important mechanisms used by plants to withstand salt stress [76,77]. Under salt stress, the susceptible WT plants had more Na<sup>+</sup> densely localized in shoot tissue (Figure 6). An overload of Na<sup>+</sup> can dramatically depolarize the plasma membrane, leading to K<sup>+</sup> efflux via depolarization-activated outward-rectifying K<sup>+</sup> channels [78]. It is notable that *hst1*-regulated salt stress resistance involved K<sup>+</sup> homeostasis. These results suggest that the accumulation of more K<sup>+</sup> with less Na<sup>+</sup> in "YNU31-2-4" plants would be mediated by a mechanism of K <sup>+</sup> influx and Na<sup>+</sup> efflux. The possible roles of the high-affinity K<sup>+</sup> transporter *OsHKT1;1*, upregulated by *hst1*, could mediate salt stress resistance in "YNU31-2-4". Further investigation will be needed to elucidate the molecular mechanisms mediating K<sup>+</sup> and Na<sup>+</sup> homeostasis in "YNU31-2-4".

In summary, our results demonstrate that the modified biotron breeding system coupled with SNP MAS offers a rapid and effective way to improve single traits in rice. The precise introgression of *hst1*, combined with suitable genetic resources and phenotyping results, resulted in the selection of a line, "YNU31-2-4", adapted to salt stress at the vegetative and reproductive stages with improved yield due to improved water relations, photosynthesis, ion homeostasis, regulation of Na<sup>+</sup> uptake, and xylem loading of Na<sup>+</sup> to shoot. In order to corroborate the obtained salt stress data, the future perspective of this study is to evaluate the phenotype of the promising line under large-scale field trials. "YNU31-2-4" is a potential candidate for new rice cultivar with markedly improved salinity tolerance, which might sustain grain yield and food security in a changing climate.

#### **4. Materials and Methods**

#### *4.1. Planting Materials*

Seeds of "Yukinko-mai" (elite cultivar) and "Kaijin" (salt tolerant) were obtained from the Niigata Agricultural Research Institute's Crop Research Center (Nagaoka city, Niigata, Japan) and the Iwate Biotechnology Research Center (Kitakami city, Iwate, Japan), respectively.

#### *4.2. Speed-Breeding–Modified Controlled-Biotron Breeding Conditions*

We developed advanced generations using the protocol described by Ohnishi et al. [45] with some modifications. Plants were grown in a growth chamber (CFH-415; Tomy Seiko, Tokyo, Japan) equipped with temperature, light, and humidity controls. Seeds were sterilized in 2.5% sodium hypochlorite and incubated at 30 ◦C in the dark for 2 days. They were then placed on seedling nursery trays and cultured. Ten-day-old seedlings were transplanted (1 per pot) into 230-mL plastic pots filled (4/5) with granulated rice nursery culture soil. Plants were grown under a long daylength (14/10 h light/dark) for 30 days to accelerate vegetative growth and then under a short daylength (10/14 h light/dark) to accelerate reproductive development. The temperature was maintained at 30/25 ◦C light/dark. Relative humidity was set to 70% and light intensity was set to 350 µmol m−<sup>2</sup> s −1 (Figure S1). Each plant was restricted to the main culm by removing tillers. The flowers of the female parent were emasculated and pollinated according to Ohnishi et al. [45]. At 10 days after pollination, we rescued embryos from developing seeds and cultured them for 10 days according to the protocol. Healthy rice seedlings were then transplanted and raised to the next breeding step.

#### *4.3. Developing Salt-Tolerant Line by Backcrossing "Kaijin" to "Yukinko-mai"*

We performed backcrossing to develop an advanced line for salinity tolerance due to the *hst1* gene derived from "Kaijin" using the recurrent parent "Yukinko-mai" (Figure 1A). F<sup>1</sup> plants were confirmed as heterozygous at the *hst1* (*OsRR22*) locus by Sanger sequencing, and were backcrossed to "Yukinko-mai" to produce BC1F<sup>1</sup> plants. We followed the same strategy of selecting plants heterozygous at *hst1* and backcrossing to develop BC2F<sup>1</sup> and BC3F<sup>1</sup> generations. Selected BC3F<sup>1</sup> heterozygous plants were self-pollinated to generate BC3F<sup>2</sup> lines with the donor allele in the homozygous state. We sequenced the genome of BC3F<sup>2</sup> line #31-2-4 to compare with the genomes of the parents. Self-pollinated seeds of line #31-2-4 were named "YNU31-2-4" (BC3F<sup>3</sup> generation) and used for phenotypic evaluation.

#### *4.4. Confirmation of Genotypes by Sanger Sequencing*

We used a PCR primer set to amplify a 545-bp region around the selected SNP (nucleotide 1975 of the *OsRR22* locus) [32] from genomic DNA extracted from young leaves of 20-day-old plants using the CTAB method [79]. Well defined PCR product was gel-purified with a High Pure PCR Product Purification Kit (Roche Applied Science, Tokyo, Japan). Sanger sequencing was performed using a BigDye Terminator v. 3.1 Cycle Sequencing Kit (Applied Biosystems, Foster City, CA, USA) on a Prism 3130 Genetic Analyzer (Applied Biosystems). Sequence chromatogram data were visualized in FinchTV software (Geospiza, Inc., Seattle, WA, USA) to determine the genotype at the SNP position.

#### *4.5. DNA Library Construction and Whole-Genome Sequencing*

Total genomic DNA was extracted from leaves of "Yukinko-mai" and BC3F<sup>2</sup> line #31-2-4 according to the protocol of Walbot and Warren [80] with some modifications. The quantity of genomic DNA was tested with a Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific, Inc., Waltham, MA, USA) and the quality was tested by 0.8% agarose gel electrophoresis. The DNA was sent to Macrogen Japan Corp. (Sakyo-ku, Kyoto, Japan) for Illumina HiSeq X Ten sequencing with NGS libraries prepared by the TruSeq DNA PCR-Free Library Prep Kit (Illumina, Inc., San Diego, CA, USA). The sequence data have been deposited in the DDBJ Sequence Read Archive: DRR151851 (BC3F2) and DRR151852 ("Yukinko-mai").

#### *4.6. Read Mapping, Variant Calling, and Variant Annotation*

"Kaijin" whole-genome sequencing reads (DRR021949, DRR021950, DRR021951, DRR021952) were downloaded from public databases. The raw paired-end reads from "Yukinko-mai", BC3F<sup>2</sup> #31-2-4, and "Kaijin" sequences were trimmed in Trimmomatic v. 0.33 software [81] with the following parameters: SLIDINGWINDOW, 8:20; TRAILING, 30; MINLEN, 70. The processed reads were mapped to the Nipponbare reference genome (IRGSP-1.0) by using the BWA-MEM v. 0.7.15 algorithm [82]. PCR duplicates in the binary alignment map (BAM) file of "Kaijin" were marked in Picard Tools v. 1.68 software (http://broadinstitute.github.io/picard/). Then indel realignment and base recalculation were done in Genome Analysis Toolkit (GATK) v. 3.6 software [83]. For multi-sample variant calling, we used GATK HaplotypeCaller in gVCF mode followed by GATK GenotypeGVCFs. We filtered out variants with missing data, multi-allelic sites, heterozygous sites in "Kaijin" and "Yukinko-mai", low coverage depth (DP < 6), and low quality (QUAL < 20). We further filtered out heterozygous variants in BC3F<sup>2</sup> #31-2-4 outside the range of 40%–60% allele frequency by a custom script, and then visualized the genotype map of BC3F<sup>2</sup> #31-2-4 in the gtrellis package of R software [84]. We annotated variants in SnpEff v. 4.0e software [85] and summarized the results in the Python programming language. Sequentially, we extracted "HIGH"- and "MODERATE"-impact variants flagged by SnpEff and performed functional annotation analysis based on two agronomic data sets: data set 1, the Overview of Functionally Characterized Genes in Rice Online (OGRO) database [52]; and data set 2, the potential agronomic functional gene set selected by gene-based GWAS of the Japanese rice population [53]. One of non-synonymous variant in *Os09g0356200* was sequenced by Sanger sequencing using forward primer: 5'-cactggaggtcgaaactgct-3' and reverse primer: 5'-tccggtcccagaaatgaagc-3'. The analyses were all based on gene annotation information and genome sequences from the Rice Annotation Project Database (RAP-DB: http://rapdb.dna.affrc.go.jp/).

#### *4.7. Estimation of Genome Recovery Rate*

We estimated the genome recovery rate of BC3F<sup>2</sup> #31-2-4 by calculating the "Yukinko-mai"-type allele frequency out of total variants as:

$$\text{Genome recovery rate} = \frac{\text{YY} + \text{YK}/2}{\text{YY} + \text{YK} + \text{KK}}$$

where YY = number of "Yukinko-mai" homozygous variants, YK = number of heterozygous variants, and KK = number of "Kaijin" homozygous variants.
