2025 Volume 75 Issue 3 Pages 210-223
In this study, we mapped quantitative trait loci (QTLs) associated with heading date and grain quality traits in a novel set of 44 chromosome segment substitution lines (CSSLs) derived from closely related rice (Oryza sativa L. ssp. japonica) cultivars ‘Yukihikari’ (good grain quality) and ‘Joiku462’ (superior eating and high grain appearance qualities). Days to heading (DTH), apparent amylose content (AAC), protein content (PC), thousand brown-grain weight (TBGW), brown grain length (BGL), brown grain width (BGWI), brown grain thickness (BGT), and the contents of 12 mineral elements (S, P, Mg, Ca, K, Mo, Cu, Zn, Mn, Fe, Sr, and Si) in polished rice were evaluated in 44 CSSLs grown in two different environments. We identified 78 QTLs, including 8, 7, 8, 8, 19, 10, and 10 for DTH, AAC, PC, TBGW, BGL, BGWI, and BGT, respectively, and 2, 1, 3, and 2 for S, Mo, Cu, and Zn contents, respectively. Several QTLs were observed in the same region, forming 17 clusters on chromosomes 1–10. These QTLs can facilitate gene isolation and breeding to develop rice cultivars with optimum heading time and improved grain quality.
Rice (Oryza sativa L.) is one of the most important staple crops, feeding almost half the world’s population. Therefore, an improvement in rice grain yield is required to ensure food security. In addition to rice yield, grain quality has received particular attention from consumers, farmers, seed producers, and the food industry (Champagne et al. 1999, Fitzgerald et al. 2009). Therefore, breeding elite rice cultivars with high yields and quality is a major goal for geneticists and breeders (Bao 2014).
Heading date is an important agronomic trait of rice and determines the regional and seasonal adaptability of rice varieties and significantly impacts grain yield and quality (Hori et al. 2012, Xue et al. 2008, Zhou et al. 2021). Moreover, it is crucial to breed rice cultivars with optimum heading dates suitable for cropping areas in which these cultivars can be used to maximize rice production. More than 40 different genes (>40 gene loci) regulating flowering time in rice have been identified using several approaches, including map-based cloning, reverse genetics using T-DNA or transposon tagging lines, and control of target gene expression via RNAi and overexpression (reviewed by Vicentini et al. 2023).
Grain quality is a complex quantitative trait determined by multiple characteristics, including the physical appearance, milling quality, nutritional value (grain components), aroma, and cooking and eating qualities of rice. Many genes have been implicated in the control of grain quality traits (Li et al. 2022). The eating quality of rice is affected by many agronomic characteristics, including heading date, grain size and weight, grain number per panicle, and spikelet fertility (Iijima et al. 2019, Juliano et al. 1993).
Apparent amylose content (AAC) is a major factor determining eating and cooking qualities in rice, particularly the sensory properties of cooked rice (Bhattacharya 1985, Fitzgerald et al. 2009). Amylose has a straight-chain structure and is one of the two components that form starch granules in rice grains (Peng et al. 2021). AAC is positively correlated with the overall hardness of rice and water absorption, indicating that an appropriate reduction in AAC can improve eating and cooking qualities (Li and Gilbert 2018). Based on their AAC, rice varieties can be classified as waxy rice (1 to 2%) and extremely low (2 to 12%), low (12 to 20%), intermediate (20 to 25%), and high (>25%) AAC rice. The waxy (Wx) gene, which encodes granule-bound starch synthase I, controls amylose synthesis in the rice endosperm (Hanashiro et al. 2008, Okagaki 1992). In addition to the Wx gene, which is directly involved in amylose synthesis, dozens of genes implicated in the transcriptional and post-transcriptional regulation of the Wx gene have been cloned (reviewed by Ren et al. 2023).
Grain protein content (PC) is another factor that affects the eating and cooking qualities of rice (Wang et al. 2017). The content and composition of rice grain protein determine the surface hardness of cooked rice (He et al. 2021, Zhong et al. 2021). PC affects the digestibility and flavor of cooked rice (Syahariza et al. 2013). Rice with a low PC has a more desirable flavor than in rice with a high PC (Champagne et al. 2004). A negative correlation exists between PC and the eating quality of rice (Hori et al. 2016). However, PC directly affects the nutritional quality of rice. Therefore, designing a reasonable regulatory strategy for increasing PC in rice can help maintain its eating and cooking qualities while enhancing its nutritional quality (Ren et al. 2023). PC is quantitatively inherited and extensively affected by environmental factors (Chattopadhyay et al. 2019, Kinoshita et al. 2017, Pradhan et al. 2019). Numerous quantitative trait loci (QTLs) for PC have been previously reported, which has been repeatedly confirmed (Chattopadhyay et al. 2019, Cheng et al. 2013, Kashiwagi and Munakata 2018, Lou et al. 2009, Tan et al. 2001, Wang et al. 2007, Yang et al. 2015, Ye et al. 2010, Zheng et al. 2011, 2012). Hence, QTLs dissected for PC frequently vary based on the structure of a given population or the environmental conditions. A few cloned genes have been associated with PC in natural rice populations (Peng et al. 2014, Yang et al. 2019).
Complex interactions between major and minor QTLs regulate grain size and shape, which, in turn, determine rice yield and grain quality (Li et al. 2020). In Japan, brown rice grains are mechanically sieved through a mesh width of 1.7–2.0 mm, depending on cultivar and location. This sieving method yields two fractions consisting of thick (>1.7 mm) and thin (<1.7 mm) grains, with the thick grains being more marketable than the thin grains (Kinoshita et al. 2017). Recently, 2.0 mm mesh has increasingly been used to separate thin brown rice grains, making it essential to use rice cultivars that produce brown rice of thickness >2.0 mm. Therefore, numerous genetic studies have been conducted to map QTLs associated with grain shape in rice. Over the past few decades, thousands of QTLs have been identified in various mapping populations (Dong et al. 2018, Hu et al. 2018, Kinoshita et al. 2017, Ying et al. 2018, Zhang et al. 2020). Of these, nearly 200 have been cloned as functional genes related to rice grain size with direct or indirect roles (reviewed by Jiang et al. 2022).
Polished rice is a staple food consumed worldwide. However, it contains limited amounts of mineral elements. Therefore, developing rice cultivars with increased mineral element contents is the most cost-effective and efficient approach for alleviating human malnutrition and nutrient deficiencies. Genes responsible for mineral element content in rice grains, mainly brown rice, have been mapped using QTLs. More than 200 QTLs have been identified (reviewed by Das et al. 2020). However, relatively little is known about the QTLs associated with the elemental content in polished rice.
In our previous studies (Kinoshita et al. 2016, 2017), QTLs associated with grain quality and yield-related traits were mapped in recombinant inbred lines (RILs) derived from closely related rice (O. sativa L. ssp. japonica) cultivars, ‘Yukihikari’ (good eating quality, released in 1981) and ‘Joiku462’ (superior eating and high grain appearance qualities, released in 2009). In these studies, days to heading (DTH), AAC, PC, brown grain length (BGL), brown grain width (BGWI), brown grain thickness (BGT), thousand brown-grain weight (TBGW) per plant, and nine yield-related traits were evaluated in 133 RILs grown in four different environments in Hokkaido, near the northernmost limit for rice paddy cultivation. A total of 72 QTLs were detected, including five for DTH, three for AAC, eight for PC, seven for TBGW, two for BGL, four for BGWI, and seven for BGT, on chromosomes 1, 2, 3, 4, 6, 7, 8, 9, 11, and 12, using 178 molecular markers. However, it is necessary to evaluate these putative QTLs to generate rice cultivars with improved grain quality and yield. Furthermore, it is crucial to identify beneficial alleles in previously cloned genes and novel QTLs of target traits for optimizing crop genomes through the accumulation of beneficial alleles (Mascher et al. 2019, Varshney et al. 2021). Takano et al. (2014) identified 1,842 non-synonymous nucleotide polymorphisms in 948 genes and 141 protein-altering indels in ‘Yukihikari’ and ‘Joiku462’. These functional mutations are potential causal genes associated with the quantitative traits.
Chromosome segment substitution lines (CSSLs) are advanced backcrossed populations in which single chromosomal segments derived from a donor are substituted in the genetic background of a recurrent cultivar. CSSLs are useful genetic materials for dissecting complex agronomic traits, such as heading date, yield components, and grain quality in rice, with high sensitivity using fewer plants than other genetic mapping populations (reviewed by Balakrishnan et al. 2019).
In the current study, we constructed a novel set of CSSLs derived from the japonica cultivars ‘Yukihikari’ and ‘Joiku462’, and backcrossing ‘Yukihikari’ as the donor and ‘Joiku462’ as the recipient. A total of 167 CSSLs were constructed. Among these, 44 CSSLs were selected as the minimum set required to cover the donor genome. QTLs determining DTH, AAC, PC, TBGW, BGL, BGWI, and BGT and 12 mineral element contents were analyzed using these 44 CSSLs.
The process involved in the development of CSSLs is illustrated in Fig. 1. F1 plants derived from a cross between ‘Yukihikari’ and ‘Joiku462’ were backcrossed to ‘Joiku462’ to produce 41 BC1F1 plants. Of 69 resulting BC2F1 plants, 24 were selected using the marker-assisted selection (MAS) technique and backcrossed to ‘Joiku462’ to generate the BC3F1 generation. Of 233 BC3F1 plants genotyped using DNA markers, 24 BC3F1 plants were screened to produce the next generation via self-pollination. In total, 1,612 BC3F2 plants were genotyped using DNA markers, and 17 BC3F2 individuals were screened using MAS to generate the next generation via self-pollination. Subsequently, 2,304 BC3F3 plants were genotyped using DNA markers, and 17 BC3F3 individuals were screened as pre-CSSLs for the homozygous substitution of one large or multiple chromosome segment(s) to cover almost all donor chromosomes using MAS. To reduce the size of the target segment, residual non-target fragments, or both derived from the donor, the 17 selected BC3F3 individuals were backcrossed to ‘Joiku462’ to generate BC4F1 generation. In total, 5,970 BC4F2 plants were self-pollinated to generate BC4F3 plants. RILs were developed from BC4F3 to BC4F5 using the single-seed descent method. In total, 3,087 BC4F5 plants were genotyped using DNA markers, and 167 individuals were screened for homozygous CSSLs using MAS.
Schematic of the development of chromosome segment substitution lines (CSSLs) carrying ‘Yukihikari’ chromosome segments in a ‘Joiku462’ genetic background. The numerator and denominator in parentheses indicate the number of plants selected and investigated by marker-assisted selection (MAS), respectively. A total of 7,305 plants were used to develop the CSSLs.
In the current study, we used 163 InDel markers (Kinoshita et al. 2016). In addition, we used seven cleaved amplified polymorphic sequence (CAPS) markers and eight derived CAPS (dCAPS) markers (Kato and Hirayama 2021, Kinoshita et al. 2016). DNA extraction, polymerase chain reaction, restriction enzyme digestion, and gel electrophoresis were performed as previously described (Kato and Hirayama 2021, Kinoshita et al. 2016).
Field trialsIn the first trial, rice seeds were sown in a greenhouse at the Obihiro University of Agriculture and Veterinary Medicine on April 25, 2019. Seedlings aged 36 days were transplanted into the paddy fields of Kamikawa Agricultural Experiment Station (KAES, Pippu, 43° 51ʹ N, 142° 48ʹ E) on May 31, 2019. In the second trial, seeds were sown in a greenhouse at KAES on May 1, 2020. Seedlings aged 28 days were transplanted into the paddy fields of KAES on May 29, 2020. All seedlings were transplanted at a density of one plant per hill and a spacing of 30 × 15 cm (22.2 plants/m2). Forty plants from each parental line and CSSL were grown in triplicates. Plants were fertilized with 8 kg N/10a, 9.7 kg P2O5/10a, and 6.9 kg K2O/10a.
Evaluation of agronomic traitsDTH was defined as the number of days from sowing to the stage with more than 50% of plants exhibiting heading. To measure TBGW, grains collected from more than eight plants of each parental line or CSSL were pooled, air-dried to a 15–16% moisture content, and weighed. The combined weight of two samples of 500 randomly chosen brown rice grains per line was defined as TBGW. BGL, BGWI, and BGT were measured in 500 randomly selected brown rice grains from each line using a Satake Grain Scanner (RGQI10B; Satake, Hiroshima, Japan) and averaged. More than 50 g of brown rice was polished to a yield of approximately 90% in a rice mill (SKM5B(1); Satake, Hiroshima, Japan). The AAC of polished rice from each line was evaluated as described (Juliano et al. 1965), and the duplicated PC of polished rice from each line was determined using an Infratec™ 1241 Grain Analyzer (Foss, Hillerød, Denmark).
Mineral element content analysesSeeds of 44 CSSLs and parental lines grown at KAES for 2 years were used for the analysis. Approximately 10 g of 90%-polished rice was crushed using a multibead shocker (Yasui Kikai, Osaka, Japan). Plant samples (100 mg each) were digested using 2 mL of 61% (w/v) nitric acid (HNO3) (EL grade; Kanto Chemical, Tokyo, Japan) at 110°C in a DigiPREP apparatus (SCP Science, Montreal, Canada) for approximately 2.0 h until the solution had almost completely evaporated. After the samples had cooled, 0.5 mL H2O2 (semiconductor grade; Santoku Chemical, Tokyo, Japan) was added, and the samples were heated to 110°C for an additional 20 min. Once digestion was complete, the tubes were cooled, and the samples were reconstituted to a volume of 10 mL by adding 2% (w/v) HNO3 in ultrapure water. The concentrations of S, P, Mg, Ca, K, Mo, Cu, Zn, Mn, Fe, Sr, and Si (acid-soluble) were measured by using an inductively coupled plasma mass spectrometer (ELAN DRC-e; PerkinElmer, Waltham, MA, USA). External calibration standards containing these elements were measured every 10 samples.
Detection of QTLsQTL analysis was performed on CSSLs that showed traits significantly different from those of the recurrent parent ‘Joiku462’, based on Dunnett’s multiple comparison tests at a 95% confidence interval (P < 0.05). Subsequently, QTLs were assigned to the chromosomal regions of these CSSLs. A QTL detected in a single CSSL was regarded as being located on non-overlapping chromosome segments, whereas QTLs detected in multiple CSSLs were considered to reside on overlapping chromosome segments. The name of each QTL consists of information regarding the abbreviation of its trait followed by ‘b’ to distinguish them from the QTLs identified in our previous study using RILs (Kinoshita et al. 2017) and chromosome number.
Candidate causal gene detectionThe physical position of each QTL was determined based on the position of the flanking InDel, CAPS, or dCAPS markers, and genes physically located within the QTLs for agronomic and grain mineral content were considered candidate genes. Genes annotated with functions related to agronomic traits, metal transport, and homeostasis were compiled, and their physical positions were determined using the Genome Browser of the Rice Annotation Project Database (https://rapdb.dna.affrc.go.jp/). The annotations and functions attributed to different candidate genes were downloaded from Oryzabase (https://shigen.nig.ac.jp/rice/oryzabase/gene/advanced/search).
All 167 ‘Yukihikari’, ‘Joiku462’ CSSLs (YJCSSLs) carried a single homozygous substituted chromosome segment, except for two CSSLs, i.e., YJCSSL-4.1.1 and YJCSSL-4.1.2, which carried two segments each (Fig. 2). Considering that recombination events occur at the midpoint between two adjacent markers, the target chromosomal segment ranged from 0.6 Mb on chromosome 5 to 29.7 Mb on chromosome 1, with a mean length of 10.7 Mb (Supplemental Table 1). Approximately 27% of substituted segments were smaller than 5 Mb, 26% of substituted segments ranged from 5 to 9.9 Mb, 17% ranged from 10 to 14.9 Mb, 15% ranged from 15 to 19.9 Mb, and 15% of substituted segments were over 20 Mb. The average coverage rate of the substitution segments per chromosome was 92.2%, ranging from 83.3% on chromosome 2 to 98.0% on chromosome 4. These CSSLs covered 92.1% (343.7 Mb) of the ‘Yukihikari’ genome. In a further experiment, 44 CSSLs that covered 92.1% of the ‘Yukihikari’ genome were evaluated for heading date and grain quality-related traits.
Graphical representation of the genotypes of the 167 chromosome segment substitution lines (CSSLs) generated in this study. White and black bars indicate homozygous chromosomal segments derived from ‘Joiku462’ and ‘Yukihikari’, respectively. The InDel and single nucleotide polymorphism (SNP), i.e., cleaved amplified polymorphic sequence (CAPS) and derived CAPS (dCAPS), markers used for marker-assisted selection (MAS) are indicated on each chromosome. Asterisks indicate the plant materials used in the field trial study.
The DTH and grain quality-related traits of the parental cultivars and CSSLs under the two experimental field conditions are represented in Table 1. Six traits, including AAC, PC, TBGW, BGL, BGWI, and BGT, differed significantly between the parental cultivars in either one or both growth environments (P < 0.05). AAC and PC were lower in ‘Joiku462’ than in ‘Yukihikari’, whereas TBGW, BGL, BGWI, and BGT were higher in ‘Joiku462’ than in ‘Yukihikari. These results indicate that ‘Joiku462’ showed improved eating quality, with lower amylose and protein contents and better grain appearance, along with larger grains with DTH similar to that in ‘Yukihikari’, as reported in Kinoshita et al. (2017).
| Genotype | DTH | AAC (%) | PC (%) | TBGW (g) | BGL (mm) | BGWI (mm) | BGT (mm) | |||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | |||||||||||||||||||||
| Joiku462 | 95.3 | 87.0 | 20.6 | 19.4 | 5.6 | 5.4 | 25.4 | 26.7 | 5.11 | 5.46 | 2.98 | 2.84 | 2.02 | 2.03 | ||||||||||||||||||||
| Yukihikari | 96.3 | 87.0 | 22.8 | *** | 20.8 | ** | 6.3 | ** | 7.0 | *** | 23.0 | *** | 23.6 | *** | 4.86 | *** | 5.19 | *** | 2.92 | 2.79 | *** | 1.99 | ** | 1.97 | *** | |||||||||
| YJCSSL-1.1 | 94.7 | 85.3 | 19.5 | 18.1 | * | 5.8 | 5.5 | 25.0 | 26.4 | 4.99 | *** | 5.33 | *** | 2.96 | 2.85 | 2.03 | 2.05 | |||||||||||||||||
| YJCSSL-1.6 | 95.3 | 87.0 | 19.3 | * | 18.3 | 5.5 | 5.4 | 25.4 | 26.3 | 5.13 | 5.45 | 3.00 | 2.85 | 2.03 | 2.01 | |||||||||||||||||||
| YJCSSL-1.10 | 95.7 | 86.3 | 20.9 | 19.5 | 5.8 | 5.6 | 26.6 | * | 27.4 | 5.13 | 5.43 | 3.06 | ** | 2.87 | * | 2.05 | * | 2.07 | *** | |||||||||||||||
| YJCSSL-2.4a | 91.3 | ** | 82.0 | *** | 18.7 | *** | 17.6 | *** | 6.5 | ** | 6.2 | *** | 25.9 | 26.7 | 5.13 | 5.45 | 2.97 | 2.84 | 2.02 | 2.04 | ||||||||||||||
| YJCSSL-2.6 | 94.3 | 86.3 | 19.5 | 18.3 | 5.6 | 5.4 | 25.3 | 26.4 | 5.18 | *** | 5.46 | 2.99 | 2.85 | 2.03 | 2.02 | |||||||||||||||||||
| YJCSSL-2.7 | 93.3 | 83.3 | ** | 19.3 | * | 18.3 | 6.0 | 6.2 | *** | 25.3 | 26.7 | 5.09 | 5.41 | 3.00 | 2.85 | 2.03 | 2.04 | |||||||||||||||||
| YJCSSL-2.12 | 95.3 | 86.7 | 20.7 | 19.4 | 6.0 | 5.9 | 27.0 | *** | 28.6 | *** | 5.17 | *** | 5.52 | 3.07 | ** | 2.88 | *** | 2.05 | . | 2.05 | ||||||||||||||
| YJCSSL-3.1.3 | 95.7 | 87.0 | 21.2 | 19.8 | 5.9 | 5.7 | 26.1 | 27.2 | 5.12 | 5.44 | 3.03 | * | 2.86 | 2.04 | 2.03 | |||||||||||||||||||
| YJCSSL-3.1.5 | 95.3 | 86.7 | 20.3 | 18.8 | 5.6 | 5.8 | 25.0 | 26.5 | 5.04 | ** | 5.32 | *** | 2.99 | 2.84 | 2.03 | 2.04 | ||||||||||||||||||
| YJCSSL-3.1.7 | 94.0 | 85.0 | 21.0 | 19.5 | 5.7 | 5.8 | 26.3 | 26.8 | 5.20 | *** | 5.49 | 2.97 | 2.83 | 2.03 | 2.02 | |||||||||||||||||||
| YJCSSL-3.2.4a | 91.7 | ** | 83.3 | ** | 18.7 | *** | 17.5 | *** | 7.2 | ** | 7.3 | *** | 23.3 | *** | 25.1 | ** | 4.99 | *** | 5.38 | 2.89 | 2.81 | *** | 2.00 | 1.99 | *** | |||||||||
| YJCSSL-4.1.2 | 93.3 | 85.3 | 20.8 | 19.7 | 5.8 | 5.7 | 26.1 | 27.6 | 5.05 | * | 5.40 | 3.04 | * | 2.87 | ** | 2.05 | ** | 2.08 | *** | |||||||||||||||
| YJCSSL-4.1.5 | 95.0 | 86.3 | 21.2 | 20.2 | 5.8 | 5.7 | 25.7 | 27.6 | 5.17 | ** | 5.48 | 2.98 | 2.85 | 2.04 | 2.06 | * | ||||||||||||||||||
| YJCSSL-4.2.2a | 95.3 | 87.0 | 20.8 | 19.0 | 5.8 | 5.8 | 24.0 | ** | 26.0 | 4.99 | *** | 5.29 | *** | 2.96 | 2.83 | 2.02 | 2.03 | |||||||||||||||||
| YJCSSL-4.3.4a | 94.3 | 84.3 | . | 20.5 | 19.1 | 6.0 | 5.8 | 25.2 | 26.4 | 5.04 | ** | 5.35 | *** | 2.98 | 2.84 | 2.03 | 2.04 | |||||||||||||||||
| YJCSSL-4.3.7a | 95.3 | 87.0 | 20.8 | 19.2 | 5.8 | 5.8 | 25.5 | 26.9 | 5.13 | 5.48 | 3.02 | . | 2.84 | 2.02 | 2.01 | * | ||||||||||||||||||
| YJCSSL-5.2 | 94.3 | 88.3 | 20.8 | 19.7 | 6.0 | 5.9 | * | 25.1 | 27.0 | 5.04 | ** | 5.37 | * | 3.01 | 2.87 | * | 2.03 | 2.04 | ||||||||||||||||
| YJCSSL-5.5 | 94.3 | 87.7 | 20.5 | 19.2 | 6.0 | 5.8 | 26.0 | 27.8 | 5.17 | *** | 5.52 | 3.03 | * | 2.87 | ** | 2.04 | 2.04 | |||||||||||||||||
| YJCSSL-6.2 | 99.3 | ** | 92.3 | *** | 19.9 | 19.4 | 5.8 | 5.8 | * | 23.7 | *** | 25.9 | 5.00 | *** | 5.45 | *** | 2.99 | 2.79 | 2.01 | 1.99 | * | |||||||||||||
| YJCSSL-6.6 | 94.3 | 91.3 | *** | 20.0 | 18.8 | 5.8 | 5.9 | 24.1 | ** | 25.9 | 5.01 | *** | 5.31 | ** | 2.97 | 2.82 | 2.02 | 2.01 | ||||||||||||||||
| YJCSSL-6.14 | 100.3 | *** | 86.3 | 20.0 | 19.3 | 5.4 | 5.9 | 24.2 | * | 26.9 | 5.06 | . | 5.35 | 2.90 | 2.83 | *** | 2.00 | . | 2.02 | *** | ||||||||||||||
| YJCSSL-7.1.1a | 94.3 | 86.0 | 20.0 | 19.3 | 5.8 | 5.7 | 25.7 | 27.5 | 5.14 | 5.50 | 2.99 | 2.84 | 2.03 | 2.03 | ||||||||||||||||||||
| YJCSSL-7.2.1 | 94.7 | 86.7 | 20.5 | 19.6 | 6.1 | 6.0 | * | 25.7 | 28.0 | 5.18 | *** | 5.56 | ** | 2.99 | 2.84 | 2.03 | 2.02 | |||||||||||||||||
| YJCSSL-7.2.3 | 95.7 | 86.7 | 19.9 | 19.1 | 6.4 | ** | 6.1 | ** | 23.3 | *** | 26.1 | 4.98 | *** | 5.34 | *** | 2.95 | 2.83 | 1.99 | ** | 1.98 | *** | |||||||||||||
| YJCSSL-7.2.9 | 94.3 | 85.7 | 19.4 | * | 18.8 | 5.8 | 5.9 | 25.2 | 26.7 | 5.11 | 5.45 | 2.98 | 2.84 | 2.02 | 2.03 | |||||||||||||||||||
| YJCSSL-8.3a | 85.0 | *** | 78.7 | *** | 18.9 | *** | 18.3 | 6.8 | ** | 6.5 | *** | 26.6 | * | 28.0 | * | 5.23 | *** | 5.51 | 2.97 | 2.85 | 2.05 | 2.07 | ** | |||||||||||
| YJCSSL-8.14 | 84.7 | *** | 80.3 | *** | 19.1 | ** | 18.5 | 7.0 | ** | 6.7 | *** | 23.9 | ** | 26.8 | 5.09 | 5.44 | 2.85 | 2.82 | * | 2.01 | 2.02 | |||||||||||||
| YJCSSL-8.22a | 92.3 | * | 87.0 | 20.5 | 19.7 | 5.8 | 5.7 | 25.0 | 27.8 | 5.13 | 5.51 | 2.95 | 2.84 | 2.03 | 2.03 | |||||||||||||||||||
| YJCSSL-9.1 | 94.7 | 90.0 | * | 23.2 | *** | 21.8 | *** | 5.8 | 5.7 | 23.9 | ** | 25.2 | * | 5.01 | *** | 5.38 | * | 2.94 | 2.82 | * | 2.01 | 1.99 | *** | |||||||||||
| YJCSSL-9.5 | 95.3 | 89.0 | 23.7 | *** | 22.4 | *** | 5.5 | 5.8 | 23.6 | *** | 24.9 | *** | 4.94 | *** | 5.25 | *** | 2.97 | 2.83 | 2.02 | 2.01 | * | |||||||||||||
| YJCSSL-9.6 | 93.7 | 89.7 | 24.0 | *** | 22.7 | *** | 5.5 | 5.6 | 24.7 | 25.2 | * | 5.07 | 5.39 | 2.97 | 2.82 | * | 2.02 | 1.99 | *** | |||||||||||||||
| YJCSSL-9.7 | 94.3 | 88.3 | 24.3 | *** | 22.7 | *** | 5.6 | 5.5 | 24.2 | * | 25.6 | 5.07 | 5.43 | 2.97 | 2.82 | * | 2.02 | 2.00 | ** | |||||||||||||||
| YJCSSL-9.4 | 94.0 | 87.7 | 24.4 | *** | 22.7 | *** | 5.7 | 5.7 | 25.1 | 25.8 | 5.11 | 5.47 | 2.97 | 2.83 | 2.01 | 2.00 | *** | |||||||||||||||||
| YJCSSL-10.1.3a | 94.3 | 89.3 | 21.0 | 20.3 | 5.5 | 5.6 | 25.9 | 27.5 | 5.07 | 5.44 | 3.03 | * | 2.87 | ** | 2.05 | * | 2.06 | * | ||||||||||||||||
| YJCSSL-10.2.3a | 93.3 | 87.0 | 19.9 | 19.4 | 5.9 | 5.9 | * | 25.1 | 27.1 | 5.04 | *** | 5.46 | 2.99 | 2.86 | 2.03 | 2.03 | ||||||||||||||||||
| YJCSSL-10.2.5 | 94.3 | 87.0 | 21.2 | 20.2 | 5.6 | 5.4 | 24.9 | 27.5 | 5.07 | 5.45 | 2.99 | 2.85 | 2.03 | 2.04 | ||||||||||||||||||||
| YJCSSL-10.2.6 | 93.3 | 85.0 | 20.2 | 19.6 | 5.6 | 5.6 | 25.3 | 26.8 | 5.04 | ** | 5.43 | 3.00 | 2.84 | 2.04 | 2.04 | |||||||||||||||||||
| YJCSSL-11.1 | 95.0 | 87.3 | 21.0 | 19.6 | 5.4 | 5.5 | 25.3 | 26.5 | 5.16 | ** | 5.47 | 2.96 | 2.83 | 2.02 | 2.02 | |||||||||||||||||||
| YJCSSL-11.2 | 93.0 | 84.7 | 21.2 | 19.9 | 5.7 | 5.6 | 25.4 | 27.0 | 5.12 | 5.48 | 2.96 | 2.83 | 2.03 | 2.02 | ||||||||||||||||||||
| YJCSSL-11.3 | 94.7 | 86.3 | 20.6 | 19.4 | 5.5 | 5.6 | 25.0 | 26.3 | 5.11 | 5.46 | 3.00 | 2.83 | 2.03 | 2.03 | ||||||||||||||||||||
| YJCSSL-12.2a | 94.7 | 88.3 | 20.6 | 19.4 | 5.6 | 5.5 | 25.1 | 26.2 | 5.06 | 5.37 | 3.00 | 2.83 | 2.02 | 2.02 | ||||||||||||||||||||
| YJCSSL-12.10a | 93.7 | 85.7 | 20.7 | 19.2 | 5.6 | 5.5 | 24.8 | 26.7 | 5.07 | 5.41 | 3.00 | 2.84 | 2.02 | 2.03 | ||||||||||||||||||||
| YJCSSL-12.16 | 94.3 | 86.3 | 20.8 | 18.8 | 5.8 | 5.8 | 24.3 | . | 26.7 | 5.04 | ** | 5.38 | *** | 3.00 | 2.86 | 2.03 | 2.04 | |||||||||||||||||
| YJCSSL-12.19a | 94.0 | 86.0 | 20.6 | 19.2 | 5.5 | 5.7 | 25.1 | 25.8 | 5.02 | *** | 5.30 | * | 2.99 | 2.83 | 2.02 | 2.03 | ||||||||||||||||||
Dunnett’s multiple comparison test was conducted for each trait to compare Joiku462 with each CSSL, and “*”, “**” and “***” represented significant at P < 0.05, P < 0.01 and P < 0.001, respectively.
The concentrations of the 12 mineral elements in the polished rice of the parental cultivars and CSSLs are represented in Table 2. The contents of three of these elements, i.e., S, Zn, and Sr, differed significantly between the two parental cultivars in either one or both field environments (P < 0.05). The Zn content was lower in ‘Yukihikari’ than in ‘Joiku462’, whereas the S and Sr contents were higher in ‘Yukihikari’.
| Genotype | S (mg/g) | P (mg/g) | Mg (mg/g) | Ca (mg/g) | K (mg/g) | Mo (μg/g) | Cu (μg/g) | Zn (μg/g) | Mn (μg/g) | Fe (μg/g) | Sr (μg/g) | Acid soluble Si (μg/g) | |||||||||||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | 2019P | 2020P | ||||||||||||||||||||||||||||||||||||
| Joiku462 | 0.72 | 0.66 | 0.87 | 1.13 | 0.17 | 0.35 | 0.090 | 0.115 | 0.63 | 1.00 | 1.25 | 1.01 | 2.89 | 2.77 | 15.6 | 14.6 | 10.1 | 13.1 | 1.55 | 1.93 | 0.046 | 0.061 | 30.5 | 40.5 | |||||||||||||||||||||||||||||||||||
| Yukihikari | 0.75 | 0.79 | ** | 0.99 | 1.39 | 0.20 | 0.42 | . | 0.104 | 0.132 | 0.65 | 1.11 | 1.42 | 1.20 | 2.48 | 2.43 | 11.4 | *** | 11.4 | *** | 10.6 | 13.1 | 2.29 | 2.77 | 0.063 | ** | 0.081 | * | 29.6 | 32.2 | |||||||||||||||||||||||||||||
| YJCSSL-1.1 | 0.71 | 0.70 | 0.84 | 1.11 | 0.17 | 0.32 | 0.088 | 0.111 | 0.59 | 0.96 | 1.32 | 1.09 | 2.81 | 2.85 | 16.2 | 16.2 | 9.9 | 12.1 | 1.79 | 1.64 | 0.046 | 0.055 | 27.5 | 35.0 | |||||||||||||||||||||||||||||||||||
| YJCSSL-1.6 | 0.72 | 0.68 | 0.88 | 1.15 | 0.18 | 0.36 | 0.088 | 0.124 | 0.62 | 1.02 | 1.38 | 1.12 | 2.76 | 2.86 | 15.5 | 13.5 | 10.3 | 14.0 | 1.66 | 2.14 | 0.057 | 0.067 | 35.3 | 43.3 | |||||||||||||||||||||||||||||||||||
| YJCSSL-1.10 | 0.71 | 0.69 | 0.83 | 1.12 | 0.17 | 0.36 | 0.080 | 0.105 | 0.59 | 1.01 | 1.18 | 1.12 | 2.62 | 2.80 | 15.5 | 15.2 | 9.8 | 12.8 | 1.96 | 1.76 | 0.042 | 0.057 | 22.7 | 34.3 | |||||||||||||||||||||||||||||||||||
| YJCSSL-2.4a | 0.78 | 0.77 | . | 0.88 | 1.22 | 0.19 | 0.38 | 0.087 | 0.119 | 0.57 | 1.03 | 1.30 | 1.26 | . | 2.83 | 2.99 | 14.9 | 14.6 | 10.2 | 13.5 | 1.86 | 1.92 | 0.045 | 0.064 | 27.2 | 38.8 | |||||||||||||||||||||||||||||||||
| YJCSSL-2.6 | 0.70 | 0.69 | 0.84 | 1.15 | 0.18 | 0.34 | 0.089 | 0.122 | 0.61 | 0.97 | 1.13 | 1.12 | 2.74 | 2.92 | 14.3 | 13.7 | 10.7 | 14.0 | ND | 1.54 | 0.050 | 0.063 | 30.4 | 40.8 | |||||||||||||||||||||||||||||||||||
| YJCSSL-2.7 | 0.75 | 0.74 | 0.85 | 1.14 | 0.18 | 0.34 | 0.090 | 0.116 | 0.59 | 0.89 | 1.15 | 1.14 | 2.91 | 2.97 | 15.3 | 14.2 | 10.5 | 12.8 | 1.59 | 1.62 | 0.047 | 0.060 | 32.5 | 40.3 | |||||||||||||||||||||||||||||||||||
| YJCSSL-2.12 | 0.74 | 0.72 | 0.84 | 1.08 | 0.17 | 0.31 | 0.088 | 0.120 | 0.55 | 0.85 | 1.13 | 1.13 | 2.74 | 2.79 | 15.3 | 14.1 | 10.5 | 13.4 | 1.47 | 1.64 | 0.048 | 0.062 | 38.8 | 45.1 | |||||||||||||||||||||||||||||||||||
| YJCSSL-3.1.3 | 0.71 | 0.69 | 0.83 | 1.17 | 0.17 | 0.33 | 0.085 | 0.113 | 0.58 | 0.91 | 1.07 | 1.04 | 2.78 | 2.77 | 15.2 | 14.6 | 10.1 | 12.7 | 1.56 | 2.94 | 0.042 | 0.056 | 35.6 | 38.2 | |||||||||||||||||||||||||||||||||||
| YJCSSL-3.1.5 | 0.68 | 0.70 | 0.76 | 1.13 | 0.16 | 0.33 | 0.083 | 0.117 | 0.57 | 0.91 | 1.01 | 1.05 | 2.70 | 3.07 | 15.2 | 15.2 | 9.9 | 13.1 | 1.36 | 1.65 | 0.041 | 0.055 | 29.4 | 45.0 | |||||||||||||||||||||||||||||||||||
| YJCSSL-3.1.7 | 0.69 | 0.71 | 0.73 | 1.06 | 0.15 | 0.33 | 0.079 | 0.111 | 0.51 | 0.86 | 1.05 | 1.06 | 2.74 | 2.96 | 15.1 | 15.3 | 9.0 | 12.2 | 1.78 | 1.76 | 0.038 | 0.053 | 31.7 | 35.2 | |||||||||||||||||||||||||||||||||||
| YJCSSL-3.2.4a | 0.86 | *** | 0.85 | *** | 0.95 | 1.30 | 0.23 | . | 0.40 | 0.088 | 0.114 | 0.61 | 0.99 | 1.28 | 1.28 | * | 3.42 | * | 3.37 | * | 17.0 | 15.6 | 11.4 | 13.5 | 1.81 | 2.72 | 0.046 | 0.059 | 32.0 | 34.9 | |||||||||||||||||||||||||||||
| YJCSSL-4.1.2 | 0.71 | 0.69 | 0.80 | 1.03 | 0.18 | 0.31 | 0.084 | 0.112 | 0.59 | 0.82 | 1.06 | 1.00 | 2.85 | 2.92 | 14.8 | 14.4 | 10.4 | 12.7 | 1.64 | 1.89 | 0.044 | 0.055 | 28.7 | 36.3 | |||||||||||||||||||||||||||||||||||
| YJCSSL-4.1.5 | 0.71 | 0.68 | 0.75 | 1.06 | 0.16 | 0.31 | 0.080 | 0.110 | 0.59 | 0.89 | 1.04 | 0.98 | 2.58 | 2.76 | 14.1 | 14.3 | 10.1 | 12.9 | 1.50 | 1.90 | 0.042 | 0.056 | 24.1 | 37.5 | |||||||||||||||||||||||||||||||||||
| YJCSSL-4.2.2a | 0.70 | 0.69 | 0.80 | 1.11 | 0.17 | 0.36 | 0.085 | 0.117 | 0.59 | 0.88 | 1.05 | 1.00 | 2.71 | 2.89 | 15.0 | 14.6 | 10.0 | 13.1 | 1.65 | 1.87 | 0.044 | 0.058 | 29.5 | 40.3 | |||||||||||||||||||||||||||||||||||
| YJCSSL-4.3.4a | 0.73 | 0.68 | 0.80 | 1.01 | 0.18 | 0.32 | 0.084 | 0.107 | 0.58 | 0.87 | 1.25 | 1.03 | 2.52 | 2.59 | 14.5 | 13.1 | 9.0 | 11.3 | 1.57 | 1.78 | 0.043 | 0.056 | 32.1 | 33.6 | |||||||||||||||||||||||||||||||||||
| YJCSSL-4.3.7a | 0.73 | 0.67 | 0.79 | 1.05 | 0.16 | 0.33 | 0.083 | 0.112 | 0.56 | 0.88 | 1.13 | 0.98 | 2.82 | 2.65 | 15.3 | 13.7 | 10.4 | 13.1 | 1.48 | 2.04 | 0.043 | 0.056 | 30.6 | 37.3 | |||||||||||||||||||||||||||||||||||
| YJCSSL-5.2 | 0.72 | 0.70 | 0.79 | 1.09 | 0.16 | 0.34 | 0.081 | 0.106 | 0.56 | 0.87 | 1.10 | 1.05 | 2.70 | 3.01 | 15.4 | 14.9 | 10.0 | 12.9 | 1.46 | 1.79 | 0.043 | 0.053 | 33.2 | 36.0 | |||||||||||||||||||||||||||||||||||
| YJCSSL-5.5 | 0.73 | 0.69 | 0.77 | 1.04 | 0.16 | 0.33 | 0.081 | 0.105 | 0.56 | 0.83 | 1.19 | 1.10 | 2.86 | 2.83 | 15.4 | 14.7 | 10.2 | 12.5 | 1.61 | 2.61 | 0.042 | 0.051 | 35.5 | 35.6 | |||||||||||||||||||||||||||||||||||
| YJCSSL-6.2 | 0.72 | 0.71 | 0.84 | 1.04 | 0.17 | 0.31 | 0.087 | 0.105 | 0.68 | 0.91 | 1.00 | 1.03 | 2.29 | * | 2.28 | * | 13.7 | . | 13.8 | 10.0 | 11.8 | 1.64 | 2.35 | 0.048 | 0.057 | 36.8 | 32.1 | ||||||||||||||||||||||||||||||||
| YJCSSL-6.6 | 0.72 | 0.70 | 0.82 | 1.12 | 0.19 | 0.38 | 0.090 | 0.114 | 0.62 | 0.94 | 1.14 | 1.04 | 2.59 | 2.85 | 16.1 | 15.6 | 10.0 | 12.7 | 1.68 | 2.06 | 0.046 | 0.057 | 31.7 | 38.6 | |||||||||||||||||||||||||||||||||||
| YJCSSL-6.14 | 0.72 | 0.73 | 0.78 | 1.12 | 0.17 | 0.38 | 0.084 | 0.113 | 0.56 | 0.92 | 1.24 | 1.10 | 2.78 | 2.93 | 15.9 | 16.1 | 9.8 | 13.6 | 1.69 | 2.97 | 0.044 | 0.058 | 30.2 | 32.3 | |||||||||||||||||||||||||||||||||||
| YJCSSL-7.1.1a | 0.72 | 0.69 | 0.80 | 1.07 | 0.17 | 0.35 | 0.088 | 0.112 | 0.57 | 0.87 | 1.23 | 1.08 | 2.71 | 2.71 | 14.2 | 13.8 | 10.0 | 12.9 | 1.43 | 5.42 | 0.043 | 0.056 | 34.4 | 34.8 | |||||||||||||||||||||||||||||||||||
| YJCSSL-7.2.1 | 0.77 | 0.72 | 0.76 | 1.06 | 0.17 | 0.32 | 0.081 | 0.110 | 0.58 | 0.88 | 1.41 | 1.11 | 2.71 | 2.76 | 14.8 | 14.4 | 10.5 | 13.1 | 1.56 | 1.97 | 0.044 | 0.055 | 25.3 | 37.6 | |||||||||||||||||||||||||||||||||||
| YJCSSL-7.2.3 | 0.80 | 0.74 | 0.79 | 1.11 | 0.19 | 0.36 | 0.081 | 0.122 | 0.59 | 0.90 | 1.57 | 1.18 | 2.89 | 2.78 | 15.6 | 15.4 | 9.7 | 12.5 | 1.83 | 3.35 | 0.045 | 0.065 | 27.1 | 37.4 | |||||||||||||||||||||||||||||||||||
| YJCSSL-7.2.9 | 0.72 | 0.72 | 0.77 | 1.05 | 0.17 | 0.34 | 0.084 | 0.111 | 0.58 | 0.91 | 1.28 | 1.08 | 2.80 | 3.07 | 14.8 | 14.8 | 10.0 | 13.1 | 1.62 | 2.16 | 0.045 | 0.058 | 27.6 | 33.3 | |||||||||||||||||||||||||||||||||||
| YJCSSL-8.3a | 0.83 | ** | 0.81 | *** | 0.85 | 1.12 | 0.18 | 0.32 | 0.080 | 0.105 | 0.56 | 0.84 | 1.45 | 1.25 | . | 2.78 | 2.92 | 13.5 | * | 13.8 | 9.3 | 11.4 | 1.61 | 2.46 | 0.041 | 0.053 | 27.9 | 31.4 | |||||||||||||||||||||||||||||||
| YJCSSL-8.14 | 0.85 | *** | 0.79 | * | 0.89 | 1.10 | 0.19 | 0.32 | 0.084 | 0.103 | 0.58 | 0.88 | 1.34 | 1.23 | 2.95 | 2.79 | 13.5 | * | 13.1 | 10.2 | 11.5 | 1.57 | 2.30 | 0.043 | 0.054 | 37.2 | 32.3 | ||||||||||||||||||||||||||||||||
| YJCSSL-8.22a | 0.72 | 0.69 | 0.86 | 1.03 | 0.18 | 0.31 | 0.089 | 0.110 | 0.60 | 0.82 | 1.04 | 1.10 | 2.60 | 2.72 | 14.2 | 13.6 | 10.0 | 12.3 | 1.63 | 1.89 | 0.047 | 0.055 | 38.0 | 41.8 | |||||||||||||||||||||||||||||||||||
| YJCSSL-9.1 | 0.70 | 0.65 | 0.85 | 1.11 | 0.18 | 0.34 | 0.090 | 0.116 | 0.67 | 0.99 | 0.94 | 1.02 | 2.41 | 2.66 | 13.2 | ** | 12.6 | 10.6 | 13.6 | 1.64 | 2.06 | 0.049 | 0.063 | 27.2 | 42.6 | ||||||||||||||||||||||||||||||||||
| YJCSSL-9.5 | 0.71 | 0.66 | 0.86 | 1.20 | 0.17 | 0.36 | 0.088 | 0.115 | 0.65 | 1.02 | 1.01 | 0.97 | 2.39 | 2.53 | 12.5 | *** | 12.0 | ** | 10.0 | 13.4 | 1.41 | 1.96 | 0.050 | 0.070 | 30.0 | 33.9 | |||||||||||||||||||||||||||||||||
| YJCSSL-9.6 | 0.71 | 0.63 | 0.83 | 1.14 | 0.18 | 0.35 | 0.088 | 0.116 | 0.64 | 0.97 | 1.00 | 0.91 | 2.35 | * | 2.45 | * | 12.2 | *** | 11.7 | ** | 10.2 | 13.2 | 1.47 | 2.34 | 0.052 | 0.068 | 28.3 | 37.4 | |||||||||||||||||||||||||||||||
| YJCSSL-9.7 | 0.72 | 0.64 | 0.84 | 1.15 | 0.17 | 0.31 | 0.084 | 0.114 | 0.67 | 0.96 | 0.98 | 0.94 | 2.36 | * | 2.50 | * | 12.2 | *** | 11.7 | ** | 9.5 | 12.1 | 1.46 | 2.35 | 0.049 | 0.065 | 32.2 | 33.6 | |||||||||||||||||||||||||||||||
| YJCSSL-9.4 | 0.72 | 0.67 | 0.82 | 1.31 | 0.18 | 0.36 | 0.086 | 0.118 | 0.64 | 1.10 | 1.04 | 0.98 | 2.36 | * | 2.46 | * | 12.7 | *** | 12.8 | 9.8 | 12.5 | 1.49 | 3.24 | 0.048 | 0.065 | 29.4 | 35.7 | ||||||||||||||||||||||||||||||||
| YJCSSL-10.1.3a | 0.70 | 0.67 | 0.75 | 1.17 | 0.15 | 0.33 | 0.077 | 0.118 | 0.57 | 0.92 | 1.01 | 1.01 | 2.58 | 3.05 | 15.9 | 15.8 | 9.7 | 13.6 | 1.30 | 2.15 | 0.040 | 0.058 | 26.8 | 43.2 | |||||||||||||||||||||||||||||||||||
| YJCSSL-10.2.3a | 0.75 | 0.70 | 0.85 | 1.10 | 0.18 | 0.32 | 0.081 | 0.112 | 0.60 | 0.88 | 1.03 | 1.05 | 2.91 | 2.94 | 14.5 | 14.0 | 10.8 | 13.7 | 1.40 | 1.87 | 0.043 | 0.059 | 32.8 | 33.0 | |||||||||||||||||||||||||||||||||||
| YJCSSL-10.2.5 | 0.71 | 0.67 | 0.75 | 1.02 | 0.15 | 0.31 | 0.080 | 0.117 | 0.53 | 0.81 | 1.00 | 1.06 | 2.58 | 2.79 | 13.9 | 14.6 | 10.2 | 13.0 | 1.31 | 2.75 | 0.040 | 0.057 | 30.5 | 39.8 | |||||||||||||||||||||||||||||||||||
| YJCSSL-10.2.6 | 0.71 | 0.67 | 0.77 | 1.02 | 0.16 | 0.31 | 0.077 | 0.111 | 0.55 | 0.83 | 1.05 | 1.07 | 2.65 | 2.74 | 14.0 | 13.8 | 9.7 | 12.3 | 1.57 | 1.25 | 0.042 | 0.057 | 31.8 | 38.5 | |||||||||||||||||||||||||||||||||||
| YJCSSL-11.1 | 0.68 | 0.65 | 0.76 | 1.06 | 0.17 | 0.33 | 0.082 | 0.115 | 0.59 | 0.87 | 0.96 | 1.00 | 2.58 | 2.70 | 14.2 | 13.7 | 10.4 | 13.3 | 1.42 | 1.39 | 0.044 | 0.061 | 26.9 | 36.4 | |||||||||||||||||||||||||||||||||||
| YJCSSL-11.2 | 0.72 | 0.67 | 0.78 | 1.04 | 0.16 | 0.29 | 0.076 | 0.112 | 0.58 | 0.82 | 1.05 | 1.04 | 2.64 | 2.82 | 14.3 | 13.9 | 9.9 | 12.7 | 1.38 | 1.12 | 0.039 | 0.056 | 29.9 | 40.0 | |||||||||||||||||||||||||||||||||||
| YJCSSL-11.3 | 0.72 | 0.67 | 0.79 | 1.06 | 0.16 | 0.31 | 0.083 | 0.113 | 0.60 | 0.87 | 1.15 | 1.05 | 2.61 | 2.77 | 14.0 | 13.3 | 10.0 | 12.7 | 1.39 | 1.67 | 0.044 | 0.060 | 33.6 | 38.9 | |||||||||||||||||||||||||||||||||||
| YJCSSL-12.2a | 0.70 | 0.66 | 0.79 | 1.05 | 0.17 | 0.30 | 0.083 | 0.112 | 0.58 | 0.85 | 1.10 | 1.05 | 2.63 | 2.81 | 14.7 | 14.5 | 10.2 | 12.5 | 1.35 | 1.45 | 0.044 | 0.058 | 31.5 | 36.2 | |||||||||||||||||||||||||||||||||||
| YJCSSL-12.10a | 0.72 | 0.69 | 0.77 | 1.11 | 0.16 | 0.30 | 0.078 | 0.109 | 0.57 | 0.91 | 1.09 | 1.11 | 2.67 | 2.78 | 15.0 | 13.7 | 10.0 | 12.5 | 1.45 | 1.80 | 0.040 | 0.057 | 30.7 | 36.6 | |||||||||||||||||||||||||||||||||||
| YJCSSL-12.16 | 0.69 | 0.67 | 0.76 | 1.05 | 0.17 | 0.30 | 0.080 | 0.111 | 0.57 | 0.81 | 1.09 | 1.12 | 2.74 | 3.54 | 16.4 | 16.0 | 10.4 | 12.7 | 1.35 | 1.46 | 0.044 | 0.058 | 27.5 | 39.7 | |||||||||||||||||||||||||||||||||||
| YJCSSL-12.19a | 0.70 | 0.65 | 0.80 | 1.05 | 0.18 | 0.31 | 0.086 | 0.120 | 0.57 | 0.82 | 1.10 | 1.02 | 2.62 | 2.81 | 15.3 | 14.2 | 9.9 | 13.2 | 1.59 | 1.80 | 0.045 | 0.068 | 31.8 | 35.9 | |||||||||||||||||||||||||||||||||||
Dunnett’s multiple comparison test was conducted for each trait to compare Joiku462 with each CSSL (n = 5), and “*”, “**” and “***” represented significant at P < 0.05, P < 0.01 and P < 0.001, respectively.
In total, 143 significant changes were identified in the evaluated traits in the CSSLs compared with those of the recurrent parent (Table 1), and 71 QTLs were distributed across all 12 chromosomes (Table 3).
| Trait | QTL | Chr | Position (IRGSP-1) | Representative CSSL | Trial | Positive allele | |
|---|---|---|---|---|---|---|---|
| start | end | ||||||
| DTH | qDTHb2.1 | 2 | 1 | 2,337,026 | YJCSSL-2.4a | 19P, 20P | J |
| qDTHb2.2 | 2 | 4,790,694 | 7,976,120 | YJCSSL-2.7 | 20P | J | |
| qDTHb3 | 3 | 26,908,494 | 36,413,819 | YJCSSL-3.2.4a | 19P, 20P | J | |
| qDTHb6.1 | 6 | 2,002,736 | 21,248,529 | YJCSSL-6.2, YJCSSL-6.6 | 19P, 20P | Y | |
| qDTHb6.2 | 6 | 21,248,529 | 31,248,787 | YJCSSL-6.14 | 19P, 20P | Y | |
| qDTHb8.1 | 8 | 4,063,287 | 16,939,665 | YJCSSL-8.3a, YJCSSL-8.14 | 19P, 20P | J | |
| qDTHb8.2 | 8 | 18,348,247 | 28,443,022 | YJCSSL-8.22a | 19P | J | |
| qDTHb9 | 9 | 1 | 3,057,249 | YJCSSL-9.1 | 20P | Y | |
| AAC | qAACb1 | 1 | 8,710,907 | 24,347,903 | YJCSSL-1.1, YJCSSL-1.6 | 19P, 20P | J |
| qAACb2.1 | 2 | 1 | 2,337,026 | YJCSSL-2.4a | 19P, 20P | J | |
| qAACb2.2 | 2 | 4,790,694 | 7,976,120 | YJCSSL-2.7 | 19P | J | |
| qAACb3 | 3 | 26,908,494 | 36,413,819 | YJCSSL-3.2.4a | 19P, 20P | J | |
| qAACb7 | 7 | 23,158,649 | 29,697,621 | YJCSSL-7.2.9 | 19P | J | |
| qAACb8 | 8 | 4,063,287 | 8,643,075 | YJCSSL-8.3a, YJCSSL-8.14 | 19P | J | |
| qAACb9 | 9 | 1 | 8,781,870 | YJCSSL-9.1, YJCSSL-9.5, YJCSSL-9.6, YJCSSL-9.7, YJCSSL-9.4 | 19P, 20P | Y | |
| PC | qPCb2.1 | 2 | 1 | 2,337,026 | YJCSSL-2.4a | 19P, 20P | Y |
| qPCb2.2 | 2 | 4,790,694 | 7,976,120 | YJCSSL-2.7 | 20P | Y | |
| qPCb3 | 3 | 26,908,494 | 36,413,819 | YJCSSL-3.2.4a | 19P, 20P | Y | |
| qPCb5 | 5 | 1,111,445 | 13,459,969 | YJCSSL-5.2 | 20P | Y | |
| qPCb6 | 6 | 1 | 5,155,721 | YJCSSL-6.2 | 20P | Y | |
| qPCb7 | 7 | 3,359,562 | 18,964,912 | YJCSSL-7.2.1, YJCSSL-7.2.3 | 19P, 20P | Y | |
| qPCb8 | 8 | 4,063,287 | 8,643,075 | YJCSSL-8.3a, YJCSSL-8.14 | 19P, 20P | Y | |
| qPCb10 | 10 | 10,761,946 | 16,460,614 | YJCSSL-10.2.3a | 20P | Y | |
| TBGW | qTBGWb1 | 1 | 34,385,285 | 43,270,923 | YJCSSL-1.10 | 19P | Y |
| qTBGWb2 | 2 | 15,833,180 | 35,937,250 | YJCSSL-2.12 | 19P, 20P | Y | |
| qTBGWb3 | 3 | 26,908,494 | 36,413,819 | YJCSSL-3.2.4a | 19P, 20P | J | |
| qTBGWb4 | 4 | 23,402,532 | 27,675,276 | YJCSSL-4.2.2a | 19P | J | |
| qTBGWb6 | 6 | 2,002,736 | 21,248,529 | YJCSSL-6.2, YJCSSL-6.6, YJCSSL-6.14 | 19P | J | |
| qTBGWb7 | 7 | 8,671,562 | 18,964,912 | YJCSSL-7.2.3 | 19P | J | |
| qTBGWb8 | 8 | 1 | 5,104,572 | YJCSSL-8.3a | 19P, 20P | Y | |
| qTBGWb9 | 9 | 1 | 8,781,870 | YJCSSL-9.1, YJCSSL-9.5, YJCSSL-9.6, YJCSSL-9.7 | 19P, 20P | J | |
| BGL | qBGLb1 | 1 | 1 | 9,872,404 | YJCSSL-1.1 | 19P, 20P | J |
| qBGLb2 | 2 | 15,833,180 | 35,937,250 | YJCSSL-2.12 | 19P | Y | |
| qBGLb3.1 | 3 | 15,733,146 | 23,906,861 | YJCSSL-3.1.5 | 19P, 20P | J | |
| qBGLb3.2 | 3 | 23,671,316 | 26,908,494 | YJCSSL-3.1.7 | 19P | Y | |
| qBGLb3.3 | 3 | 26,908,494 | 36,413,819 | YJCSSL-3.2.4a | 19P | J | |
| qBGLb4.1 | 4 | 1 | 8,137,472 | YJCSSL-4.1.2 | 19P | J | |
| qBGLb4.2 | 4 | 17,234,547 | 23,402,532 | YJCSSL-4.1.5 | 19P | Y | |
| qBGLb4.3 | 4 | 27,470,300 | 31,428,042 | YJCSSL-4.2.2a, YJCSSL-4.3.4a | 19P, 20P | J | |
| qBGLb5.1 | 5 | 1,111,445 | 7,957,285 | YJCSSL-5.2, YJCSSL-5.5 | 19P, 20P | J | |
| qBGLb5.2 | 5 | 8,019,584 | 29,958,434 | YJCSSL-5.5 | 19P | Y | |
| qBGLb6 | 6 | 2,002,736 | 21,248,529 | YJCSSL-6.2, YJCSSL-6.6 | 19P, 20P | J | |
| qBGLb7.1 | 7 | 3,359,562 | 4,899,924 | YJCSSL-7.2.1 | 19P, 20P | Y | |
| qBGLb7.2 | 7 | 8,671,562 | 18,964,912 | YJCSSL-7.2.3 | 19P, 20P | J | |
| qBGLb8 | 8 | 1 | 5,104,572 | YJCSSL-8.3a | 19P | Y | |
| qBGLb9 | 9 | 1 | 8,781,870 | YJCSSL-9.1, YJCSSL-9.5 | 19P, 20P | J | |
| qBGLb10.1 | 10 | 10,761,946 | 16,460,614 | YJCSSL-10.2.3a | 19P | J | |
| qBGLb10.2 | 10 | 20,489,591 | 23,207,287 | YJCSSL-10.2.6 | 19P | J | |
| qBGLb11 | 11 | 1 | 6,231,196 | YJCSSL-11.1 | 19P | Y | |
| qBGLb12 | 12 | 18,005,156 | 21,449,199 | YJCSSL-12.16, YJCSSL-12.19a | 19P, 20P | J | |
| BGWI | qBGWbI1 | 1 | 34,385,285 | 43,270,923 | YJCSSL-1.10 | 19P, 20P | Y |
| qBGWbI2 | 2 | 15,833,180 | 35,937,250 | YJCSSL-2.12 | 19P, 20P | Y | |
| qBGWIb3.1 | 3 | 1 | 10,077,921 | YJCSSL-3.1.3 | 19P, 20P | Y | |
| qBGWIb3.2 | 3 | 26,908,494 | 36,413,819 | YJCSSL-3.2.4a | 20P | J | |
| qBGWIb4 | 4 | 1 | 8,137,472 | YJCSSL-4.1.2 | 19P, 20P | Y | |
| qBGWIb5 | 5 | 1,111,445 | 7,957,285 | YJCSSL-5.2, YJCSSL-5.5 | 19P, 20P | Y | |
| qBGWIb6 | 6 | 21,248,529 | 31,248,787 | YJCSSL-6.14 | 20P | J | |
| qBGWIb8 | 8 | 5,652,612 | 16,939,665 | YJCSSL-8.14 | 20P | J | |
| qBGWIb9 | 9 | 1 | 8,781,870 | YJCSSL-9.1, YJCSSL-9.6, YJCSSL-9.7 | 20P | J | |
| qBGWIb10 | 10 | 1 | 12,667,708 | YJCSSL-10.1.3a | 19P, 20P | Y | |
| BGT | qBGTb1 | 1 | 34,385,285 | 43,270,923 | YJCSSL-1.10 | 19P, 20P | Y |
| qBGTb3 | 3 | 26,908,494 | 36,413,819 | YJCSSL-3.2.4a | 20P | J | |
| qBGTb4.1 | 4 | 4,475,561 | 19,457,371 | YJCSSL-4.1.2, YJCSSL-4.1.5 | 19P, 20P | Y | |
| qBGTb4.2 | 4 | 34,809,722 | 35,502,694 | YJCSSL-4.3.7a | 20P | J | |
| qBGTb6.1 | 6 | 1 | 5,155,721 | YJCSSL-6.2 | 20P | J | |
| qBGTb6.2 | 6 | 21,248,529 | 31,248,787 | YJCSSL-6.14 | 20P | J | |
| qBGTb7 | 7 | 8,671,562 | 18,964,912 | YJCSSL-7.2.3 | 19P, 20P | J | |
| qBGTb8 | 8 | 1 | 5,104,572 | YJCSSL-8.3a | 20P | Y | |
| qBGTb9 | 9 | 1 | 8,781,870 | YJCSSL-9.1, YJCSSL-9.5, YJCSSL-9.6, YJCSSL-9.7, YJCSSL-9.4 | 20P | J | |
| qBGTb10 | 10 | 1 | 12,667,708 | YJCSSL-10.1.3a | 19P, 20P | Y | |
| S | qSb3 | 3 | 26,908,494 | 36,413,819 | YJCSSL-3.2.4a | 19P, 20P | Y |
| qSb8 | 8 | 4,063,287 | 8,643,075 | YJCSSL-8.3a, YJCSSL-8.14 | 19P, 20P | Y | |
| Mo | qMob3 | 3 | 26,908,494 | 36,413,819 | YJCSSL-3.2.4a | 20P | Y |
| Cu | qCub3 | 3 | 26,908,494 | 36,413,819 | YJCSSL-3.2.4a | 19P, 20P | Y |
| qCub6 | 6 | 1 | 5,155,721 | YJCSSL-6.2 | 19P, 20P | J | |
| qCub9 | 9 | 11,624,154 | 20,851,851 | YJCSSL-9.6, YJCSSL-9.7, YJCSSL-9.4 | 19P, 20P | J | |
| Zn | qZnb8 | 8 | 4,063,287 | 8,643,075 | YJCSSL-8.3a, YJCSSL-8.14 | 19P, 20P | J |
| qZnb9 | 9 | 1 | 8,781,870 | YJCSSL-9.1, YJCSSL-9.5, YJCSSL-9.6, YJCSSL-9.7, YJCSSL-9.4 | 19P, 20P | J | |
Eight QTLs were associated with DTH. Five QTLs, including qDTHb2.1, qDTHb2.2, qDTHb3, qDTHb8.1, and qDTHb8.2, exhibited the inhibitory effect of ‘Yukihikari’ alleles on DTH. The remaining three QTLs, qDTHb6.1, qDTHb6.2, and qDTHb9, showed the enhancement effect of ‘Yukihikari’ alleles on DTH. Five QTLs, qDTHb2.1, qDTHb3, qDTHb6.1, qDTHb6.2, and qDTHb8.1, were stable QTLs detected in both conditions, whereas three QTLs, qDTHb2.2, qDTHb8.2, and qDTHb9 were unstable and were detected only in a single condition. Among these, three QTLs, qDTHb3, qDTHb6.1, and qDTHb9, were observed to be responsible for functional polymorphisms in the previously cloned genes based on our previous resequencing data (Takano et al. 2014) (Supplemental Table 2). In the qDTHb3 region, the OsFdC2, OsPhyC, Hd6, Hd16, OsCCT14, and OsMADS14 genes overlapped (Dai and Xue 2010, Doi et al. 2004, Li et al. 2015, Liu et al. 2016, Zhao et al. 2015). Among these, ‘Joiku462’ carried a premature stop codon identical to that in ‘Nipponbare’ at the Hd6 locus, whereas ‘Yukihikari’ carried the wild-type allele. In qDTHb6.1 region, five cloned genes, Hd3a, Hd3b, OsHGW, Hd1, and OsSDG711, were observed. Two neighboring genes, Hd1 and OsSDG711, exhibited functional polymorphisms between ‘Yukihikari’ and ‘Joiku462’. In the Hd1 coding region, G614A (R205Q) mutation was identified. In the OsSDG711 coding region, G320T (C117F) and T1397C (V466A) mutations were identified. In the qDTHb9 region, the A3029C (A1010D) mutation was identified in OsTrx1 (Jiang et al. 2018).
Seven QTLs associated with AAC were identified. Six QTLs, including qAACb1, qAACb2.1, qAACb2.2, qAACb3, qAACb7, and qAACb8, exhibited the inhibitory effect of ‘Yukihikari’ alleles on AAC. Conversely, only qAACb9 increased AAC under the effect of the associated ‘Yukihikari’ allele. Four QTLs, i.e., qAACb1, qAACb2.1, qAACb3 and qAACb9, were stable, whereas three QTLs, i.e., qAACb2.2, qAACb7, and qAACb8, were detected in 2019. No functional mutations were identified in the cloned genes that overlapped with the QTLs identified in the current study.
Eight QTLs associated with PC, including qPCb2.1, qPCb2.2, qPCb3, qPCb5, qPCb6, qPCb7, qPCb8, and qPCb10, were detected and exhibited the enhancement effect of ‘Yukihikari’ alleles on PC. Of these, four QTLs, i.e., qPCb2.1, qPCb3, qPCb7, and qPCb8, were detected across the two field conditions, suggesting that they were stable, whereas the remaining four QTLs, i.e., qPCb2.2, qPCb5, qPCb6, and qPCb10, were only detected in 2020. In the qPCb7 region, RAG2 (Zhou et al. 2017) contained three amino acid substitutions, T14I, A67G, and W128G, between ‘Yukihikari’ and ‘Joiku462’.
In addition, eight QTLs associated with TBGW were identified. Three QTLs, i.e., qTBGWb1, qTBGWb2, and qTBGWb8, exhibited the enhancement effect of ‘Yukihikari’ alleles on TBGW. Five QTLs, i.e., qTBGWb3, qTBGWb4, qTBGWb6, qTBGWb7, and qTBGWb9, exhibited the enhancement effect of ‘Joiku462’ alleles on TBGW. Among these, four QTLs, i.e., qTBGWb2, qTBGWb3, qTBGWb8, and qTBGWb9, were stable QTLs detected in both 2019 and 2022, whereas the other four QTLs, i.e., qTBGWb1, qTBGWb4, qTBGWb6, and qTBGWb7, were detected only in 2019.
Nineteen QTLs associated with BGL were identified. Seven QTLs, including qBGLb2, qBGLb3.2, qBGLb4.2, qBGLb5.2, qBGLb7.1, qBGLb8, and qBGLb11, exhibited the enhancement effect of ‘Yukihikari’ alleles on BGL. Twelve QTLs, including qBGLb1, qBGLb3.1, qBGLb3.3, qBGLb4.1, qBGLb4.3, qBGLb5.1, qBGLb6, qBGLb7.2, qBGLb9, qBGLb10.1, qBGLb10.2, and qBGLb12, exhibited the enhancement effect of ‘Joiku462’ alleles on BGL. Nine QTLs, including qBGLb1, qBGLb3.1, qBGLb4.3, qBGLb5.1, qBGLb6, qBGLb7.1, qBGLb7.2, qBGLb9, and qBGLb12, were stable QTLs observed in both field trials, whereas 10 QTLs, including qBGLb2, qBGLb3.2, qBGLb3.3, qBGLb4.1, qBGLb4.2, qBGLb5.2, qBGLb8, qBGLb10.1, qBGLb10.2, and qBGLb11, were detected only in 2019.
Ten QTLs associated with BGWI were identified. Three QTLs, i.e., qBGWIb1, qBGWIb2, and qBGWIb8, exhibited the enhancement effect of ‘Yukihikari’ alleles on BGWI. Five QTLs, including qBGWIb3, qBGWIb4, qBGWIb6, qBGWIb7, and qBGWIb9, exhibited the enhancement effect of ‘Joiku462’ alleles on BGWI. Six QTLs, including qBGWIb1, qBGWIb2, qBGWIb3.1, qBGWIb4.1, qBGWIb5, and qBGWIb10, were stable QTLs detected in both the 2019 and 2020 field trials, whereas four QTLs, i.e., qBGWIb3.2, qBGWIb6, qBGWIb8, and qBGWIb9, were detected only in 2020.
In addition, 10 QTLs associated with BGT were identified. Four QTLs, i.e., qBGTb1, qBGTb4.1, qBGTb8, and qBGTb10, exhibited the enhancement effect of ‘Yukihikari’ alleles on BGT. Six QTLs, including qBGTb3, qBGTb4.2, qBGTb6.1, qBGTb6.2, qBGTb7, and qBGTb9, exhibited the enhancement effect of ‘Joiku462’ alleles on BGT. Four QTLs, i.e., qBGTb1, qBGTb4.1, qBGTb7, and qBGTb10, were stable QTLs detected in both 2019 and 2020, whereas six QTLs, including qBGTb3, qBGTb4.2, qBGTb6.1, qBGTb6.2, qBGTb8, and qBGTb9, were detected only in 2020.
In total, 92 cloned genes for grain size overlapped with the QTLs identified in this study (Supplemental Table 2). Among these, DRW1 (Zhang et al. 2021) was reported in qTBGW9, qBGL9, and qBGWI9 and exhibited a single amino acid substitution between the parental lines. No functional polymorphisms were identified in the other cloned genes.
Twenty-seven significant changes in S, Mo, Cu, and Zn contents were identified in the CSSLs compared with those in the recurrent parent, and eight QTLs were located on chromosomes 3, 6, 8, and 9 (Table 3). Two QTLs associated with S content, i.e., qSb3 and qSb8, were detected across the two field conditions and exhibited the enhancement effect of ‘Yukihikari’ alleles on S content. A single QTL, qMob3, associated with Mo content was detected in 2020 and showed the enhancement effect of the ‘Yukihikari’ allele on Mo content. Three QTLs, qCub3, qCub6, and qCub9, associated with Cu content were detected across the two field conditions. qCub3 showed the enhancement effect of the ‘Yukihikari’ allele on Cu content. Similarly, two QTLs, i.e., qCub6 and qCub9, exhibited the enhancement effect of ‘Joiku462’ alleles on Cu content. Two QTLs, i.e., qZnb8 and qZnb9, associated with Zn content were detected in both field conditions and exhibited the enhancement effect of ‘Joiku462’ alleles. OsZIP4 (Os08g0207500) overlapped with qZnb8 without revealing any functional polymorphisms (Supplemental Table 2). Although the Sr content in ‘Yukihikari’ was higher than that in ‘Joiku462’ across the 2 years of field trials, no significant differences in Sr content were detected between each CSSL and ‘Joiku462’. However, the Sr content in the CSSLs exhibited a positive correlation between the two trials (r = 0.70, P < 0.001). Across the 2 years of field trials, three CSSLs, YJCSSL-1.6, -9.5, and -9.6, exhibited higher Sr content than the other CSSLs, suggesting that these CSSLs carry small-effect QTLs that regulate Sr content.
In this study, we identified 78 QTLs, including 8, 7, 8, 8, 19, 10, and 10 QTLs regulating DTH, AAC, PC, TBGW, BGL, BGWI, and BGT, respectively, and 2, 1, 3, and 2 QTLs regulating S, Mo, Cu, and Zn contents, respectively, in the genetic background of ‘Joiku462’ (superior eating and high grain appearance qualities). In our previous QTL analysis using the RIL population of the same cross combination, 36 QTLs, including 5, 3, 8, 7, 2, 4, and 7 QTLs regulating DTH, AAC, PC, TBGW, BGL, BGWI, and BGT, respectively, were reported (Kinoshita et al. 2017). Among them, 20 QTLs were located within the same or adjacent intervals in this study, indicating that these QTLs had stable effects on heading date and grain quality traits in the CSSLs and RILs. In contrast, 49 QTLs, including 5 (62.5%), 5 (71.4%), 4 (50.0%), 6 (75.0%), 18 (94.7%), 8 (80.0%), and 4 (40.0%) QTLs regulating DTH, AAC, PC, TBGW, BGL, BGWI, and BGT, respectively, were newly identified in the current study. These results indicate that CSSLs can help identify QTLs with relatively small genetic effects (Howell et al. 1996, Nagata et al. 2015, Okada et al. 2018).
Co-localization of QTLs for grain quality-related traits with QTLs for DTHThe date of heading is a key agronomic trait in rice that determines the regional and seasonal adaptation of rice varieties and affects grain yield and quality. Only cultivars with an extremely early heading date were adapted to Hokkaido (41–45° N latitude), which has a long natural day length of more than 15 h in summer (Fujino and Sekiguchi 2005). Although similar DTH values were observed in the parental cultivars, the ‘Yukihikari’ cultivar possessed early heading date alleles at qDTHb2.1, qDTHb2.2, qDTHb3, qDTHb8.1, and qDTHb8.2, whereas ‘Joiku462’ possessed early heading date alleles at qDTHb6.1, qDTHb6.2, and qDTHb9.
Among the eight QTLs for DTH, four co-localized with the QTLs for AAC and PC and formed clusters qDTHb2.1–qAACb2.1–qPCb2.1 (chr2: ~2.3 Mb), qDTHb2.2–qAACb2.2–qPCb2.2 (chr2:15.8–35.9 Mb), qDTHb3–qAACb3–qPCb3 (chr3:26.9–36.4 Mb), and qDTHb8.1–qAACb8–qPCb8 (chr8:4.0–8.6 Mb). ‘Yukihikari’ alleles were associated with a consistent decrease in DTH and AAC and increased PC in these four clusters. Two QTLs, qDTH3–qPC3 and qDTH8–qAAC8–qPC8, identified in our previous study using RIL population derived from a cross between ‘Yukihikari’ and ‘Joiku462’ (Kinoshita et al. 2017) overlapped with qDTHb3–qAACb3–qPCb3 and qDTHb8.1–qAACb8–qPCb8, identified on chromosomes 3 and 8, respectively, in the current study. In agreement with the results obtained in the current study, qDTH3–qPC3 and qDTH8–qAAC8–qPC8 decrease DTH or AAC or both and increase PC under the effects of ‘Yukihikari’ alleles (Kinoshita et al. 2017). Therefore, these two QTL clusters had stable effects on DTH, AAC, and PC in CSSLs and RILs. Similarly, the co-localization of QTLs for DTH and PC has been reported earlier (Mo et al. 2021, Tan et al. 2001, Wada et al. 2006, Yun et al. 2016). Hitherto, the pleiotropic effects of the rice florigen gene RFT1 on the amino acid content of rice grains have been reported (Xie et al. 2020). However, the pleiotropic effects of other genes determining the head date on PC have not yet been elucidated. Nevertheless, the effects of differences in ripening temperature because of differences in DTH must be considered (Kinoshita et al. 2017). Further studies are needed to determine whether DTH, AAC, and PC are controlled by closely linked QTLs or a pleiotropic QTL. In contrast, three QTLs, qDTHb6.1, qDTHb6.2, and qDTHb9, reduced DTH under the effects of ‘Joiku462’ alleles and did not co-localize with QTLs regulating AAC or PC. Among them, two QTLs, qDTHb6.1 and qDTHb6.2, co-localized with QTLs for grain size and formed the clusters qDTHb6.1–qTBGWb6–qBGLb6 and qDTHb6.2–qBGWIb6–qBGTb6.2. Both QTL clusters decreased DTH and increased grain size under the effects of the ‘Joiku462’ alleles.
Taken together, the ‘Yukihikari’ cultivar carrying five QTLs, including qDTHb2.1, qDTHb2.2, qDTHb3, qDTHb8.1, and qDTHb8.2, exhibited an extremely early heading date. These five QTLs can be classified into two categories: the first category consists of qDTHb2.1, qDTHb2.2, qDTHb3, and qDTHb8.1, which co-localized with QTLs that reduce AAC and enhance PC, and the second category consists of qDTHb8.2, which did not co-localize with QTLs regulating other traits. Similarly, the ‘Joiku462’ cultivar carrying three QTLs, i.e., qDTHb6.1, qDTHb6.2, and qDTHb9, exhibited an extremely early heading date. These three QTLs can be classified into two categories: the first category consists of qDTHb6.1 and qDTHb6.2, which co-localized with QTLs promoting adequate grain shape, and the second category consists of qDTHb9, which did not exhibit co-localization with QTLs regulating the other traits.
In addition, the qDTHb3–qAACb3–qPCb3 cluster co-localized with additional seven QTLs, including qTBGWb3, qBGLb3.3, qBGWIb3.2, qBGTb3, qSb3, qMob3, and qCub3, and formed the largest cluster in the region of 26.9–36.4 Mb on chromosome 3. In this cluster, the ‘Yukihikari’ allele was associated with decreased DTH, AAC, and grain size (TBGW, BGL, BGWI, and BGT) and with increased PC and mineral contents (S, Mo, and Cu). Fourteen cloned genes were identified within this cluster (Supplemental Table 2). A functional mutation at Hd6 (OsCKA2) within this cluster was detected between ‘Yukihikari’ and ‘Joiku462’. Although the ‘Joiku462’ cultivar carries a premature stop codon at Hd6, the ‘Joiku462’ allele at qDTHb3/qDTH3 delayed heading compared with that caused by the wild-type allele of ‘Yukihikari’ (Kinoshita et al. 2017, Takano et al. 2014, and the current study). Takahashi et al. (2001) reported that ‘Nipponbare’ carries a premature stop codon at Hd6 and causes early heading compared with that caused by the wild-type allele of ‘Kasalath’. Further studies are needed to resolve this conflict and investigate two possibilities: first, the variation in the expression of five cloned genes, including OsFdC2, OsPhyC, Hd16, OsCCT14, and OsMADS14 (Dai and Xue 2010, Doi et al. 2004, Li et al. 2015, Liu et al. 2016, Zhao et al. 2015), regulates DTH; and second, a novel gene controlling DTH is included in qDTHb3/qDTH3.
CK2 is a heterotetramer consisting of two catalytic subunits (A or A′ or both) and two regulatory subunits (B). CK2 can affect DNA binding by phosphorylating a range of transcription factors, which, in turn, affect the expression of downstream genes. In maize, CK2 regulates seed development by modulating the phosphorylation status of the bZIP transcriptional activator Opaque2, which is specifically expressed during endosperm development and enhances the transcriptional synthesis of seed storage proteins (Ciceri et al. 1997). Future studies will be needed to determine whether a non-functional allele at OsCKA2 derived from ‘Joiku462’ reduces protein accumulation or whether another gene controls protein accumulation in rice.
QTLs regulating AAC and PC that are independent of QTLs regulating DTHqAACb9 co-localized with five QTLs, including qTBGWb9, qBGLb9, qBGWIb9, qBGTb9, and qZnb9, forming a second large QTL cluster. In this cluster, the ‘Joiku462’ allele was associated with reduced AAC and increased grain size and Zn content. qAACb9 was identified at a position identical to that of qAC9/qAAC9 using RILs derived from the crosses of ‘Joiku462’ with ‘Jokei06214’ and ‘Yukihikari’ with ‘Joiku462’, respectively (Kinoshita et al. 2017, Shinada et al. 2015). This result indicates that the allele at qAAC9/qAC9/qAACb9 derived from ‘Joiku462’ exhibits a stable reduction effect on AAC in different genetic backgrounds and environmental conditions. In addition, QTLs for grain shape-related traits, i.e., qTBGW9, qBGWI, and qBGT9, were shown to co-localize with qAAC9 in our previous study using RILs derived from the same cross combination (Kinoshita et al. 2017). qAAC9/qAC9/qAACb9, qAC-9-1(t), and qAC9 have been detected in different cross combinations (Wada et al. 2006, Wan et al. 2004). Further studies are required to determine the precise positions of QTLs for multiple traits in QTL clusters and to assess whether pleiotropic effects are because of single or closely linked QTLs.
All eight QTLs for PC exhibited an increase in PC caused by the ‘Yukihikari’ allele in the genetic background of ‘Joiku462’ (superior eating quality). Among these, four QTLs, i.e., qPCb5, qPCb6, qPCb7, and qPCb10, were independent of the QTLs determining DTH. RAG2 located within qPCb7 and contained three functional mutations, T14I, A67G, and W128G, between ‘Yukihikari’ and ‘Joiku462’ based on our previous resequencing data (Takano et al. 2014). The seeds of RAG2-overexpressing and RAG2-suppressed lines exhibited increased and decreased PC, respectively (Zhou et al. 2017). Further studies are required to determine whether natural variations in RAG2 regulate PC.
QTL clusters for grain shape-related traits‘Joiku462’ exhibited improved grain appearance, involving larger BGL, BGWI, or BGT than in ‘Yukihikari’. ‘Joiku462’ yielded consistently stable thick brown rice grains of thickness >2.0 mm, whereas ‘Yukihikari’ yielded grains of thickness <2.0 mm in the current study. In the current study, we identified 47 QTLs determining grain size distributed across all chromosomes. Among these, 30 QTLs (63.8%) were identified in common for TBGW, BGL, BGWI, and BGT and formed 11 clusters involving qTBGWb3–qBGLb3.3–qBGWIb3.2–qBGTb3 (chr3:26.9–36.4 Mb), qTBGWb6–qBGLb6 (chr6:2.0–21.2 Mb), qBGWIb6–qBGTb6.2 (chr6:21.2–31.2 Mb), qTBGWb1–qBGWIb1–qBGTb1 (chr1:34.4–43.3 Mb), qTBGWb2–qBGLb2–qBGWIb2 (chr2: ~2.3 Mb), qBGLb4.1–qBGWIb4.1 (chr4: ~8.1 Mb), qBGLb5.1–qBGWIb5 (chr5:1.1–13.5 Mb), qTBGWb7–qBGLb7.2–qBGTb7 (chr7:8.7–19.0 Mb), qTBGWb8–qBGLb8–qBGTb8 (chr8: ~5.1 Mb), qTBGWb9–qBGLb9–qBGWIb9–qBGTb9 (chr9: ~8.8 Mb), and qBGWIb10–qBGTb10 (chr10: ~12.7 Mb). These clusters were classified into three groups: the first group consisted of six clusters, including qTBGWb3–qBGLb3.3–qBGWIb3.2–qBGTb3, qTBGWb6–qBGLb6, qBGWIb6–qBGTb6.2, qTBGWb7–qBGLb7.2–qBGTb7, qTBGWb9–qBGLb9–qBGWIb9–qBGTb9, and qBGWIb10–qBGTb10, increased grain size and was associated with the ‘Joiku462’ allele; the second group consisting of three clusters, i.e., qTBGWb1–qBGWIb1–qBGTb1, qTBGWb2–qBGLb2–qBGWIb2, and qTBGWb8–qBGLb8–qBGTb8, increased grain size and was associated with the ‘Yukihikari’ allele; and the third group consisting of two clusters, i.e., qBGLb4.1–qBGWIb4.1 and qBGLb5.1–qBGWIb5, increased BGL together with reduced BGWI, resulting in slender grains and was associated with the ‘Joiku462’ allele.
The present 60 QTLs overlapped with 164 cloned genes, including 23, 11, 10, 33, 68, 14, 7, and 1, determining DTH, AAC, PC, TBGW, BGL, BGWI, BGT, and Zn, respectively. Among them, seven cloned genes (five for DTH, one for PC, and one each for TBGW, BGL, and BGWI) contained functional mutations. Of the currently known eight QTLs for mineral content, only qZnb8 overlapped OsZIP4 (Os08g0207500) without any functional mutation (Takano et al. 2014). Sixty of the 78 QTLs (76.9%) co-localized with other QTLs and formed 17 clusters on chromosomes 1–10. These QTL cluster regions are responsible for genetic features, such as linkage drag and pleiotropy, and have critical implications in rice breeding. These QTLs can facilitate gene isolation and breeding to develop rice cultivars with optimum heading time and improved grain quality.
KK, SM, TS, and TW designed the study and performed experiments. YH analyzed the data. KK, SM, and TW wrote the manuscript. All the authors have read and approved the final version of the manuscript.
This study was partially supported by grants from the CANON Foundation (to KK, TS, SM, and TW) and the Tojuro Iijima Foundation for Food Science and Technology (to KK and TS). We thank HRO GenBank for providing rice seeds. We thank Dr. M. Akimoto for the technical support in using the multibead shocker. We thank Mrs. S. Yoshikawa for providing technical assistance. We would like to thank Editage (https://www.editage.jp) for the English language editing.
