Euphytica (2014) 197:99–108 DOI 10.1007/s10681-013-1055-3
Mapping of QTLs for eating and cooking quality-related traits in rice (Oryza sativa L.) Yujia Leng • Dawei Xue • Yaolong Yang • Shikai Hu • Yan Su • Lichao Huang • Lan Wang • Tingting Zheng • Guanghen Zhang • Jiang Hu • Zhenyu Gao • Longbiao Guo • Qian Qian • Dali Zeng
Received: 18 October 2013 / Accepted: 22 December 2013 / Published online: 29 January 2014 Ó Springer Science+Business Media Dordrecht 2014
Abstract The increasing living standard of customers has resulted in a demand for the improvement of the cooking, eating, and appearance quality of rice grains, which have become a priority for rice breeders and geneticists. In this study, a double haploid population derived from the cross between japonica CJ06 and indica TN1 was used to analyze the quantitative trait loci (QTLs) for amylose content, gel consistency (GC), gelatinization temperature (GT), protein content, and grain hardness under two different conditions. A total of 18 QTLs were detected on chromosomes 1, 2, 3, 6, 8, 10, and 12, with the additive heritability ranging from 10.4 to 66.3 %. Eight of them were identified both in Hangzhou and Hainan. Moreover, five-locus epistatic interactions
Yujia Leng, Dawei Xue and Yaolong Yang contributed equally to this work. Y. Leng Y. Yang S. Hu Y. Su L. Huang L. Wang T. Zheng G. Zhang J. Hu Z. Gao L. Guo Q. Qian (&) D. Zeng (&) State Key Lab for Rice Biology, China National Rice Research Institute, Hangzhou 310006, People’s Republic of China e-mail:
[email protected] D. Zeng e-mail:
[email protected] D. Xue College of Life and Environment Sciences, Hangzhou Normal University, Hangzhou 310036, People’s Republic of China
were identified except for GC, and two QTLs for GT exhibited environmental interaction effects. The results facilitate further understanding of the genetic basis for eating and cooking quality, nutritive quality, and milling quality. Keywords Rice grain quality Quantitative trait loci (QTL) Epistatic QTL-byenvironment interactions (QEs)
Introduction The complex trait of rice grain quality is the sum of a number of component traits, including cooking and eating quality, nutritional quality, milling quality, appearance quality and so on (Li et al. 2003). Eating and cooking qualities (ECQs) are important determinants of cooked rice grain quality. ECQs comprise three physical and chemical characteristics of starch in the endosperm: amylose content (AC), gel consistency (GC) and gelatinization temperature (GT) (Sun et al. 2006). AC is considered the most important factor determinant of ECQ (Delwiche et al. 1995). The interaction among AC, GC, and GT was revealed in many studies. Tan et al. (1999) reported that a single locus in the waxy (Wx) locus region also controls both GC and GT. Fan et al. (2005) reported alkali degeneration gene (ALK) impacts on GC as well as Wx. Tian et al. (2009) showed that Wx is the sole major gene controlling both AC and GC and is a minor gene
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affecting GT. Su et al. (2011) revealed Wx might be a control of GT as well as GC, whereas GC had a high negative correlation with AC. The Wx is known to encode a granule-bound starch synthase (GBSS), which is required for the synthesis of amylose in the endosperm and for the determination of AC in rice grain (Wang et al. 1995). GC is divided into three grades: hard, medium, and soft, and is primarily regulated by Wx (Su et al. 2011). GT is a physical trait responsible for rice quality, which is directly determined by cooking time; and high-quality rice varieties usually have lower GT (Tan et al. 2001b). ALK encodes a soluble starch synthase II (SSSII), which mainly determines GT in rice (Fan et al. 2005; Umemoto et al. 2002). Protein content is another important component of nutritional quality that affects the taste of rice (Ye et al. 2010). Rice nutritional quality is also important for the rice-eating population. Moreover, protein content affects the physicochemical properties of cooked rice (Hamaker et al. 1991; Marshall et al. 1990; Sun et al. 2006; Tian et al. 2009). Usually, high PC is generally taken to indicate more nutritional value but worse taste (Ye et al. 2010). Perez et al. (1996) reported that PC can be significantly affected by environmental conditions and the level of nitrogen fertilization. Hillerislambers et al. (1973) reported that heritability for PC was 13 to 37 % thinks to QEs. Shenoy et al. (1991) indicated that the heritability of PC reached up to 71 %. Grain hardness (GH) as a textural characteristic is shown by the rough rice, brown rice, and white rice forms of each variety (Webb et al. 1986). Hardness is also considered to be related to head rice and energy consumption during milling as well as to the quality of cooked rice (Roy et al. 2011). Many reports on GH have been conducted in wheat. Puroindolines are unique tryptophan-rich proteins found only in triticeae, which are only consists of two proteins style: PINA and PINB (Giroux et al. 2003). PINA and PINB are synthesized specifically in the endosperm during the kernel development of wheat. The interaction of puroindolines (PINA and PINB) with starch granules or biological membranes is associated with endosperm softening (Morris and Bhave 2008). The lack of function of PINA or PINB enhanced endosperm hardness in wheat (Giroux et al. 2003). Krishnamurthy and Giroux (2001) implement textural analysis of transgenic rice seeds indicated that expression of PINA and/or PINB from wheat reduced rice GH. In
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addition, Wada et al. (2006) detected one main-effect QTL using a recombinant inbred line (RIL) population derived from two japonica cultivars. Wada et al. (2008) further identified seven QTLs for GH mapped on chromosomes 1, 2, 3, 6, 7, and 8. Takeuchi et al. (2007) found three main-effect QTLs for rice GH on chromosomes 2, 6, and 9. QTL mapping was introduced as a method for understanding the molecular and genetics mechanisms of rice quality (Li et al. 2003; Fan et al. 2005; Sun et al. 2006). Many QTLs for rice quality have been detected. Twelve main-effect QTLs were identified for rice quality using a BIL population using a seed descent method (Li et al. 2003). Fan et al. (2005) identified 12 main-effect QTLs for rice ECQs using a doubled haploid (DH) population derived from a cross between two indica varieties, Zhenshan 97 and H94. Eight main-effect QTLs and 27 epistatic QTL pairs for AC, GT, GC and PC were detected in a distribution of 12 rice chromosomes (Sun et al. 2006). A total of 49 QTLs were identified for the 13 physicochemical properties of rice using composite interval mapping (Cho et al. 2010). In this study, we demonstrated the inheritance of AC, GC, GT, PC, GH and the epistatic effects were further dissected as well as their environmental interactions. The results will facilitate to understand the genetic components of those traits.
Materials and methods Plant materials A DH population consisting of 116 lines was developed via anther culture of an F1 hybrid between a japonica cultivar CJ06 and an indica rice cultivar TN1. Uniform seeds of all DH lines and the parents were soaked in distilled water in the dark at 30 °C for 2 days, and germinated in distilled water at 35 °C for 12 h. The germinated seeds were then sown in the paddy field. After 25 days, rice seedlings were planted with a planting density of 20 9 20 cm2. The parents and each DH line were applied with three replications, and were planted to three rows with six plants in each row. The seedlings were transplanted to the paddy yields with the same N fertilization level, supplemented with 150 kg ha-1. The experiments were performed in Hangzhou (HZ) and Hainan (HN), during the 2010 and 2011 rice-growing seasons, respectively.
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Evaluation of rice grain quality Approximately 40 days after flowering, rice grains were harvested, air-dried, and stored at room temperature for 3 months before milling. Twelve grains of milled rice were selected for measuring alkali spreading values (ASV), and 10 g grains were ground to flour and used to measure the AC and GC. AC was measured as described previously with a slight modification (Juliano 1971). Briefly, samples were boiled for 10 min in volumetric flasks to disperse the grain powder completely, and the optical density of the amylose-iodine blue was measured at 620 nm using a spectrophotometer. GC was measured using 100 mg of milled rice flour. The flour was first wetted with 0.2 ml of 95 % ethanol containing 0.025 % (w/v) thymol blue in 11 9 100 mm2 culture tubes. Thereafter, 2 ml of 0.2 N KOH was added, and the solution was mixed vigorously. Tubes were covered with glass marbles, heated in a boiling water bath for 8 min, mixed again, and kept in an ice water bath for 20 min. Finally, the tubes were laid horizontally against ruled graphing paper, and gel length was measured after 1 h. ASV was determined by incubating six milled grains in 10 ml of 1.7 % KOH at 28 °C for 23 h with two replicates. The degree of spreading was rated using the following seven-point semi-quantitative criteria: (1) grain was not affected; (2) grain was swollen; (3) grain was swollen, and its collar was incomplete and narrow; (4) grain was swollen, and its collar was complete and wide; (5) grain was split, and its collar was complete and wide; (6) grain was dispersed and merged with the collar; and (7) grain was completely dispersed and intermingled with other grains. Protein content was measured using the Kjeldahl method as Hu described (Hu et al. 2012), which includes three steps: digestion, distillation, and titration, followed by the conversion of nitrogen content into protein content. GH was measured using the procedure of Webb et al. (Pomeranz and Webb 1985). The hardness score was determined by the degree of force required to compress the rice grain from top to bottom using the GH Tester.
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The QTLs were detected by interval mapping using QTLMAPPER 1.6 software, which was developed based on the mixed linear model approach (Wang et al. 1999). The QTLs were determined with a threshold of P \ 0.005 for claiming putative QTL. The genetic parameters, additive effects, and accounted variation of each QTL were also estimated. The relative contribution of a genetic component was calculated as the proportion of phenotypic variance explained by the component in the selected model (McCouch et al. 1997).
Results Phenotypic variation in parents and the DH lines Grain quality for the parents and DH population were summarized in Table 1. For AC and PC, significant difference was detected between the parents under two different conditions, whereas the AC and PC in CJ06 were lower than that in TN1. The GC (81.1 mm) in CJ06 was higher than that of in TN1 (22.8 mm) in HZ, while that is similar to the TN1 in HN. A minute difference in GT was observed between the two parents under two different conditions. It indicated that GT was not easily affected by environment. GH also showed small difference between two parents, but exhibited a significant difference in HN. For each trait, the distribution of the DH population between the 2 years was similar. A bimodal distribution of phenotypic values for AC and GC were observed, which indicated that AC and GC were controlled by a major gene as well as by some minor modifying genes. The mean value of GT exhibited little difference between two parents. However, GT varied significantly in DH population ranging from 2.54 to 7. For PC and GH, the distribution exhibited a continuous distribution; it indicates that PC and GH were also controlled by polygene (Fig. 1; Table 1). Correlation analysis of traits
Data and QTL analysis Population distribution and correlation analysis were performed using SAS8.0 statistical software. The genetic linkage map was constructed using a total of 227 SSR and STS markers distributed evenly on all 12 rice chromosomes, as previously described (Rao et al. 2010).
Correlation analysis (Table 2) showed that AC exhibited highly significant negative correlation to GC and GT whether in HZ or HN, and the correlation coefficients in HN displayed higher than that in HZ. The correlation coefficient between GC and GT showed highly significant and reached -0.496 in
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Table 1 Statistical analysis of rice quality by two parents and their DH population in 2010 and 2011 Year
Trait
Parents (mean ± SD) CJ06
2010 (Hangzhou)
2011 (Hainan)
TN1
DH population P value
Mean ± SD
Range
Skewness
Kurtosis
AC (%)
11.9 ± 1.7
22.8 ± 3.3
\0.0001
18.9 ± 5.7
8.4–27.9
-1.89
-1.38
GC (mm)
81.1 ± 5.2
30.6 ± 2.2
\0.0001
50.6 ± 3.4
25.0–96.5
0.43
-1.46
GT (ASV)
6.2 ± 0.4
6.8 ± 0.7
0.016
6.7 ± 0.5
4.9–7.0
PC (%)
9.8 ± 0.1
12.7 ± 0.1
\0.0001
11.0 ± 1.8
6.9–16.0
-0.29
3.69
0.28
0.40
GH (kg)
16.6 ± 2.7
15.6 ± 2.3
0.202
11.4 ± 2.5
6.0–16.6
0.31
-0.30
AC (%)
15.0 ± 3.7
25.3 ± 6.3
\0.0001
19.9 ± 5.1
10.3–27.8
-0.24
-1.28
GC (mm)
52.4 ± 3.1
54.3 ± 3.3
0.439
58.4 ± 25.0
25.5–100
0.06
-1.52
GT (ASV)
6.8 ± 0.4
6.6 ± 0.5
0.304
6.3 ± 1.1
4.5–7.0
-1.96
3.62
PC (%)
9.9 ± 0.8
13.1 ± 1.0
\0.0001
11.0 ± 1.5
7.4–16.0
0.71
1.36
GH (kg)
16.8 ± 1.5
15.1 ± 1.4
0.0012
11.5 ± 2.6
5.9–16.6
0.26
-0.45
Data are presented as the average ± standard deviation (SD) AC Amylose content, GC gel consistency, GT gelatinization temperature, PC protein content, GH grain hardness
HN, while that was only -0.295 in HZ. Similarly, GH presented a highly significant negative correlation to AC and GT in HN, whereas the coefficients were -0.234 and -0.315 in HZ, respectively. Surprisingly, there was no significant correlation between PC and other traits, whether in HN or HZ. Main-effect QTLs for grain quality A total of 18 QTLs, including three QTLs for AC, four QTLs for GC, two QTLs for GT, five QTLs for PC and four QTLs for GH, were identified on chromosomes 1, 2, 3, 6, 8, 10 and 12 under two different conditions (Fig. 2; Table 3). Those main-effect QTLs spanned the F-values from 10.1 to 99.8 with the additive heritability ranging from 10.4 to 66.3 %. The major QTL, qAC6, was identified on the chromosome 6 under both conditions. It explained the variation of 53.6 and 66.3 % in HZ and HN, respectively. The allele of qAC6 from CJ06 decreased AC about 3.93 % in HZ and 5.00 % in HN. Another QTL for AC, qAC3h, was detected only in HZ with the explained variation of 16.3 %. The allele of qAC3-h from CJ06 reduced the AC about 1.82 %. Four QTLs for GC were anchored on chromosomes 1, 3, and 6 under two different conditions. All alleles that increased the GC were contributed from CJ06. A major QTL, qGC6, was located on chromosome 6 between RM540 and RM587 both in HZ and HN, which increased the GC about 12.4 and 16.7 mm with the explained variation of 22.9 and 45.1 %, respectively. In addition, qGC3-h was
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detected only in HZ, while qGC1-n was identified just in HN. The interval of RM540-RM587 on chromosome 6 is a major locus affecting GT in HN, which explain the explained variation of 44.7 %. The allele derived from TN1 reduced the GT. However, no efficient QTL was detected in this locus in HZ, and a minor QTL related to GT was mapped between RM1111-RM310 on chromosome 8 in HZ. For protein content, two and three QTLs were located on chromosomes 1, 6, and 10 under two conditions, respectively. Those QTL carried the F-values from 10.5 to 14.9 with explained variation in the range of 10.5 to 15.8 %. qPC10 was detected under two conditions, and explained 15.8 and 12.3 % of the phenotypic variance in HZ and HN, respectively. Three QTLs related to PC, qPC6-h, qPC1-n and qPC6-n, were located on chromosome 1 and 6 with the explained variation from 10.5 to 14.8 %. QTLs for GH were anchored on chromosome 2 and chromosome both in HZ and HN. The allele of qGH2 from CJ06 on chromosome 2 enhanced the GH, whereas the allele of qGH12 from TN1 also increased the GH. Those QTLs ranged the explained variation from 17.3 to 22.2 %. Digenic epistasis and their interactions with environments To further understand the genetic components of those traits, the digenic epistatic effects of AC, GC, GT, PC and GH were estimated. Five-locus epistatic interactions were identified except for GC (Table 4). However, no
Euphytica (2014) 197:99–108
A
103
D
30
50
No. of lines
No. of lines
40 20
10
30 20 10
0
9
12
15
18
21
24
27
0
30
7.0
Amylose content (%)
B
E
25
8.5 10.0 11.5 13.0 14.5 16.0 Protein content (%)
30
No. of lines
No. of lines
20 15 10
20
10
5 0
0 30
40
50
60
70
80
90 100
No. of lines
C
7
9
11
13
15
17
Grain hardness
Gel consistency (mm) 60
40
20
0 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0
Gelatinization temperature (ASV)
Fig. 1 Frequency distributions of the AC, GC, GT, PC and GH in DH population. Spotted columns and arrows indicate the rice grown in Hangzhou of Zhejiang province. Grey columns and
arrows indicate the rice grown in Lingshui of Hainan province. Arrows with smooth end indicate CJ06, arrows with notch end indicate TN1
Table 2 Trait correlations for cooking and eating quality related traits from a DH population derived from the cross of CJ06/TN1 observed in Hangzhou (upper) and Hainan (lower)
significant epistasis was detected for GC, which indicated that the main effect QTL is the primary genetic basis for GC. One pair of digenic epistasis was detected for AC, which explained 5.85 % of the phenotypic variation. Two pairs of epistatic loci for PC were estimated and accounted for 2.2 and 5.0 % of the phenotypic variation, respectively. An epistatic effect for GH was scanned, the loci of which were unrelated to main-effect QTLs. To some extent, genotype–environment interaction may play an important role in determining rice grain quality. Thus, the effects and contributions of QEs for rice quality under two conditions were examined in this study. However, only two minor QTL-by-environment interactions (QEs) for GT were detected. They were mapped on
Trait
AC
GC
-0.445a
GC
GT
PC
-0.699a GT PC GH
0.463a 0.572a -0.138
-0.049
-0.079
-0.059
-0.148
0.079
-0.234
-0.018
-0.315
0.01
-0.365a
0.01
-0.342a a
-0.295 -0.496a
0.194
Significant at the level of 1 %
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Chr. 1 Dist.(cM)
Chr. 2 Dist.(cM)
Marker RM1282
12.6 RM428 19.2 1.9 7.1 2.7 6.7 2.9
23.3
RM5302 RM1 RM1195 RM490 RM575 RM259 RM600 PC RM572 RM3627 RM1287 RM23 RM3412 RM6716 RM306 RM488 RM1349 RM246 GC RM5461 RM1232 RM1297 RM1061 RM128 RM1183 RM3411 RM212 RM7180 RM486 RM5389 RM1198 RM104 RM1067
2.0 7.1 2.5 2.4 4.4
6.7 10.0
RM492 RM145 RM521 RM1358 RM290 RM324
9.1
6.4
4.4 21.0
RM263 RM526 RM525 RM318 RM450 RM5472
12.6 3.5 1.5 3.1 8.5 9.7
10.5 RM252
RM426 GH
RM240 RM250 RM425 RM5607 RM208 RM166 RM207 RM48 RM535
11.5 2.2 2.0 13.3 5.2 1.5 2.4 0.0
RM3735
RM504
11.7
Marker
15.7 RM1350 30.8
24.4 RM3199 AC RM5813 RM520b RM520 RM143 RM7000
8.7 2.8 4.6 10.3 3.5 13.0
RM514 GC RM570
8.5
Chr. 10 Dist.(cM)
RM337
RM1376
Dist.(cM)
5.1 PC
RM527
8.8
RM3
6.3 6.3
9.0 RM162 11.1
GH GH RM519
PC PC
RM1103
RM467
RM72 RM331 RM3395
18.0 RM271 6.1
RM258
RM3226 12.6
10.6
RM270 RM1108
14.7 36.4
21.5
24.6
RM223
RM17
22.4
RM340 PC
Main-effect QTL in Hangzhou RM447
RM494
Main-effect QTL in Hainan
12.9 RM3120
123
Marker
RM304
RM528
12.8
RM1113
24.6 RM4085 RM1111 GT RM310
10.1
10.3
RM280
RM1246 15.2
13.9 AP4991 RM539
7.8
13.0 19.0
13.9
RM255
17.8
RM5271
RM1235
RM6917
RM3276
Chr. 12
Marker
17.5
26.6
6.8
RM216
11.7
RM6997 RM1155
28.0
RM2334
Chr. 8
8.5
RM401
18.5
Dist.(cM)
RM8200
RM335
20.0
RM587
7.1
6.8
RM282
RM6266
10.5 8.0
RM307 11.9
RM548
49.2
AC GC AC GC GT
RM3471
33.9
RM341
Marker
Marker
13.6
RM1022 RM7 RM251 RM3280
24.9
RM540 18.6
RM489 RM5480 RM3331
1.1 8.2 17.3
RM3732
Chr. 4 Dist.(cM)
Marker
0.0
23.7
Chr. 6 Dist.(cM)
RM7451 RM154 RM3188
6.6 6.2 16.5
22.2 8.9 0.0 1.1 2.4 2.7 23.8 1.3 1.2 3.8 5.7 3.8 1.5 4.8 12.7 0.0 0.0 0.0 9.2 1.1 10.2 1.8 5.8 11.3
Chr. 3 Dist.(cM)
Marker
The epistatic QTL
Euphytica (2014) 197:99–108 b Fig. 2 Locations of main and epistasis effect QTLs for AC,
GC, GT, PC and GH on the linkage map. Open arrows indicate QTLs identified in Hangzhou. Solid arrows indicate QTLs identified in Lingshui. Arrows with same notch end indicate epistasis effect QTLs
chromosomes 2 and 8, which explained 6.2 and 12.8 % of the phenotypic variation with 0.26 and 0.37, respectively (Table 5).
Discussion Rice grain quality comprises complex traits, which include cooking and eating quality, nutritional quality, appearance quality, etc., all of which are typically quantitative traits and controlled by many major and/ or minor genes as well as epistatic QTLs and environmental interactions. The major genes (or major QTLs) are frequently the most important determinants of such traits; interactions between genes that have minor effects or even interactions between those with major effects may have sizable effects on such traits. In addition, the effects of both major and minor genes are also sometimes subject to environmental modifications (Fan et al. 2005). Over the past decades, semidwarf breeding and hybrid breeding have significantly contributed to the improvement of rice yield but degraded eating and cooking quality and nutritional quality, which thus need to be improved (Su et al. 2011). In this study, the main-effect QTLs, epistatic QTLs, and QEs associated with AC, GC, GT, PC and GH were investigated under two conditions. The results clearly show that main-effect QTLs were the most important determinants except for GT in this study. For digenic epistasis, four of them were identified in epistatic QTLs except for GC. Although the total effects of the epistatic QTLs were significantly less than their main-effect QTLs, the epistatic effect reached 9.9 % of the phenotypic variation for GH. Followed by PC, its epistatic interactions accounted for 7.2 % of the variation. Moreover, For GT, the QEs effect reached up to 33.4 % of the phenotype variation in this study. The interval between RM540 and RM580 on chromosome 6 was reported to affect AC, GC and GT simultaneously (Fan et al. 2005; Sun et al. 2006; Tan et al. 1999). Our results indicated that AC had a significant negative relation with GC and a positive relation with GT. We also found that locus carrying
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the largest effects on AC and GC. Umemoto et al. (2002) highlighted that ALK was near Wx and mainly determined GT. However, qGT6-n was detected in HN. The QEs with 33.4 % of the phenotype variation indicated that the environment in this DH population easily affected GT. The single-nucleotide polymorphism genotypes of TN1 in ALK revealed that the genotype of TN1 differed from typical indica but similar to japonica (Gao et al. 2011). Protein content is an important property that contributes to eating and cooking quality as well as to nutritional quality (Hamaker et al. 1991; Ye et al. 2010). Previous studies have shown that PC had no or weak correlation with other quality traits (Aluko et al. 2004; Tan et al. 2001a). We also found no significant correlation between PC and the other four quality traits. Several reports on the QTL analysis of PC have been published (Cho et al. 2010; Sun et al. 2006; Takeuchi et al. 2007; Tan et al. 2001a), Tan et al. detected qPC10 for PC on chromosome 10 (Sun et al. 2006; Takeuchi et al. 2007; Tan et al. 2001a). Another QTL, qPC1-n, was also detected on chromosome 1, which may be the same locus detected by (Cho et al. 2010). In addition, compared with previous studies, two novel QTLs for PC were identified under different conditions, one QTL in HZ and one QTL in HN (Cho et al. 2010; Sun et al. 2006; Tan et al. 2001a). GH is a key trait in triticeae and is an important agronomic trait associated with different end-product properties (Nadolska et al. 2009). Compared with wheat, few studies on rice GH have been conducted. Several previous studies have shown that GH possessed a significant positive correlation with AC (Cho et al. 2010; Takeuchi et al. 2007; Wada et al. 2006). Interestingly, we found that GH had a significant negative correlation with AC as well as GT, which might be attributed to the different environments and parent backgrounds. (Takeuchi et al. 2007) detected two minor QTLs for GH located on chromosomes 3 and 6 (in the Wx gene region). Cho et al. (2010) also identified two QTLs for GH. However, we identified two novel QTLs for GH on chromosomes 2 and 12 under different conditions. Moreover, these two QTLs were confirmed by previous studies (Cho et al. 2010; Wada et al. 2008, 2006). The results in this study displayed significant implications on rice grain quality improvement programs. In addition to the major genes, attention should also be considered the effects of minor QTLs, epistatic
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Table 3 QTLs for rice quality in DH population of CJ06/TN1 Trait
QTL
Chr.
Marker interval
F-value
Additive effect (A)
H2 (A) (%)
Hangzhou AC
qAC3-h
3
RM3199-RM5813
10.8
-1.82
16.3
GC
qAC6 qGC3-h
6 3
RM540-RM587 RM514-RM570
62.6 15.7
-3.93 10.55
53.6 16.7 22.8
qGC6
6
RM540-RM587
18.2
12.36
GT
qGT8-h
8
RM1111-RM310
10.1
0.10
10.4
PC
qPC6-h
6
RM340-RM494
11.8
-0.44
11.9
qPC10
10
RM216-RM467
14.9
-0.62
15.8
qGH2
2
RM263-RM526
17.0
1.23
22.2
qGH12
12
RM1246-RM519
14.9
-1.10
17.3
GH Hainan AC
qAC6
6
RM540-RM587
99.8
-5.00
66.3
GC
qGC1-n
1
RM246-RM5461
11.3
8.12
13.1
qGC6
6
RM540-RM587
33.9
16.70
45.1
GT
qGT6-n
6
RM540-RM587
39.5
-0.32
44.7
PC
qPC1-n
1
RM600-RM572
10.5
0.60
10.5 14.8
GH
qPC6-n
6
RM539-RM527
13.3
-0.69
qPC10
10
RM216-RM467
10.5
-0.61
12.3
qGH2 qGH12
2 12
RM263-RM526 RM1246-RM519
16.2 14.6
1.19 -1.10
21.5 18.0
Table 4 Epistasis effects for grain quality in DH population of Chunjiang06/TN1 Epistasis (AA)
H2 (AA) (%)
Trait
Chr.
Marker interval
Chr.
Marker interval
P value
AC
3
RM3199-RM5813
4
RM335-RM401
3 9 10-5
1.23
4.6
GT
2
RM3188-RM3732
8
RM1111-RM310
\1 9 10-5
0.25
5.9
PC
1 2
RM259-RM600 RM48-RM535
1 6
RM246-RM5461 AP4991-RM539
0.01139 2.1 9 10-4
-0.26 -0.38
2.2 5.0
GH
1
RM104-RM1067
3
RM489-RM5480
\1 9 10-5
0.87
9.9
Table 5 Environment interactions of putative QTLs for GT in DH population P
H2A (%)
AE1
Trait
QTL
Interval
A
GT
2
RM3188-RM3732
-0.26 \1 9 10-5
6.2
-0.21
8
RM1111-RM310
0.37 \1 9 10-5
12.8
0.33
QTLs and QEs. The information obtained in this study should be useful for manipulating the QTLs for these traits through molecular marker-assisted selection. Moreover, marker-assisted selection will be particularly useful for breaking the unfavorable linkage of the genes, such as in the case of the three major QTLs for AC, GC and GT on chromosome 6 detected in this study. This process would enable he combination of all
123
PAE1
H2AE1(%)
0.01202
10.5
2 9 10-5
23.3
AE2 0.22
PAE2 0.00134
-0.32 \1 9 10-5
H2AE2(%) 10.7 22.7
favorable alleles in a single individual, which would be impossible to attain using conventional methods.
Conclusion In this study, the grain quality for AC, GC, GT, protein content and hardness were investigated in a DH
Euphytica (2014) 197:99–108
population. We identified 18 QTLs on chromosomes 1, 2, 3, 6, 8, 10, and 12, with the additive heritability ranging from 10.4 to 66.3 %. Eight of them were identified both in Hangzhou and Hainan. Moreover, five-locus epistatic interactions were identified except for GT, and two QTLs for GT exhibited environmental interaction effects. Moreover, the digenic epistasis and environment interactions show complex regulating process on grain quality. Acknowledgments This work was supported by Grants from the Ministry of Agriculture of China for transgenic research (No. 2013ZX08009003-001), the National Natural Science Foundation of China (31221004, 31171531) and the State Key Basic Research Program (2013CBA01403).
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