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Dissection of QTLs for Yield Traits on the Short Arm of Rice Chromosome 6
Agricultural Sciences in China
May 2008
2008, 7(5): 513-520
Dissection of QTLs for Yield Traits on the Short Arm of Rice Chromosome 6 DU Jing-hong, FAN Ye-yang, WU Ji-rong and ZHUANG Jie-yun Chinese National Center for Rice Improvement/State Key Laboratory of Rice Science, China National Rice Research Institute, Hangzhou 310006, P.R.China
Abstract This study was undertaken to dissect quantitative trait loci (QTLs) controlling yield traits on the short arm of rice chromosome 6. A residual heterozygous line that carries a heterozygous segment extending from RM587 to RM19784 on the short arm of rice chromosome 6 was selected from an F7 population of the indica rice cross Zhenshan 97B/Milyang 46. An F2:3 population consisting of 221 lines was derived and grown in two trial sites. Six yield traits including number of panicles per plant, number of filled grains per panicle, total number of spikelets per panicle, spikelet fertility, 1 000-grain weight, and grain yield per plant were measured. An SSR marker linkage map was constructed and employed to determine QTLs for yield traits with Windows QTL Cartographer 2.5. QTLs were detected in the target interval for all the traits analyzed except NP, with phenotypic variance explained by a single QTL ranging between 6.3% and 35.2%. Most of the QTLs for yield components acted as additive QTLs, while the three QTLs for grain yield had dominance degrees of 1.65, 0.84, and -0.42, respectively. It was indicated that three or more QTLs for yield traits were located in the target region. The genetic action mode, the direction of the QTL effect, and the magnitude of the QTL effect varied among different QTLs for a given trait, and among QTLs for different traits that were located in the same interval. Key words: yield traits, residual heterozygous line, quantitative trait locus, short arm of chromosome 6, rice (Oryza sativa L.)
INTRODUCTION Grain yield and its component traits are quantitatively inherited. Such traits are controlled by quantitative trait loci (QTLs) that are generally located in clusters. QTL regions that were detected in one or more primary mapping studies can be followed to develop a population that segregates the target interval in an isogenic background. This will help to dissect different QTLs in the QTL cluster, thus providing candidates for QTL fine-mapping and positional cloning. Rice is a plant species that has attracted exceptional attention and achieved remarkable progress in QTL mapping. Nowadays, QTL analysis in rice is moving
from primary mapping to fine mapping and positional cloning. For complex traits such as yield and yield component, QTLs that were detected in two or more independent studies are considered preferential targets (Li et al. 2004; Ashikari et al. 2005; Fan et al. 2006). Development of populations that segregate a single QTL region in an isogenic background is a prerequisite for QTL fine-mapping and positional cloning. In addition to the classical near isogenic lines (NILs) that are developed by back-crossing, residual heterozygous lines (RHLs) are a new type of genetic resource for QTL fine-mapping (Yamanaka et al. 2005). Being selected from a population of the advanced generation such as F6 or F 7, an RHL is basically homozygous but has a heterozygous segment in the target region. Such a line
This paper is translated from its Chinese version in Scientia Agricultura Sinica. DU Jing-hong, Ph D, E-mail: [email protected]; Correspondence ZHUANG Jie-yun, E-mail: [email protected]
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is equivalent to an F1 that is produced by crossing a pair of NILs differing at the target region. The selfed progenies will compose a population that segregates a single region covering the target heterozygous segment, and thus can be used for QTL fine-mapping. Using F2 populations of indica rice crosses Zhenshan 97B/Milyang 46 and Xieqingzao B/Milyang 46 and an F 6:7 population of Zhenshan 97B/Milyang 46, our previous studies have located QTLs for yield traits in interval RZ398-B10 on the short arm of rice chromosome 6 (Fan et al. 2001; Zhuang et al. 2001, 2002). This QTL region has also been detected in other populations, which were developed from a variety of crosses, including indica × indica cross (Hua et al. 2002), japonica × janonica cross (Mu et al. 2005), indica × japonica cross (Redona and Mackill 1998; Mei et al. 2003; Han et al. 2005), and crosses of indica × wild rice (Moncada et al. 2001; Brondani et al. 2002; Yoon et al. 2006). In the present study, dissection of QTLs for yield traits was conducted using an F2:3 population derived from an RHL that carries a heterozygous segment in the target region on the short arm of chromosome 6.
MATERIALS AND METHODS
DU Jing-hong et al.
of 3.8, 1.1, 2.0, and 0.6 Mb, respectively. It was noted that no QTLs for yield traits were previously detected in these background regions in Zhenshan 97B/Milyang 46 populations (Fan et al. 2001; Zhuang et al. 2001, 2002). An F2 population consisting of 221 plants was derived from the RHL and grown in the summer-autumn ricegrowing season in 2004 at the China National Rice Research Institute (CNRRI), Hangzhou, Zhejiang Province, China. Seeds of each F 2 individual were divided into two parts. The two sets of F3 populations were grown in the winter-spring season in 2004-2005 in Lingshui, Hainan Province, China, and in the summerautumn season in 2005 at CNRRI, respectively. The field experiment followed a randomized complete block design with two replications. Twelve plants per line were planted at the spacing of 20 cm × 23 cm in each replication. At maturity, panicles were harvested from the middle 10 plants and sun-dried. Six traits including grain yield per plant (GYD), number of panicles per plant (NP), number of filled grains per panicle (NFGP), total number of spikelets per panicle (TNSP), spikelet fertility (SF), and 1 000-grain weight (TGWT) were measured. The mean values over two replications at each site were used for analysis.
SSR genotyping Rice materials and phenotyping Following our previous study of QTL mapping using recombinant inbred lines (RILs) of Zhenshan 97B/ Milyang 46 (Zhuang et al. 2002), more SSR (simple sequence repeat) markers were selected for parental survey and polymorphic markers were applied to the assay RILs. The linkage map was updated and QTL analysis was performed again. The target region on the short arm of rice chromosome 6 for QTL finemapping was determined as RM587-RM19784. Another F7 population of the same cross was used for RHL selection. One plant of each F7 line was tested with 208 SSR markers. An RHL that carries a 7.3-Mb heterozygous segment extending from RM587 to RM19784 was selected. This RHL is homozygous in other genomic regions except for four segments, locating on the long arms of chromosomes 1 and 2, and the short arms of chromosomes 4 and 5 with length
DNAs were extracted from a leaf mixture of 10 plants for each F3 line at the first replication of the CNRRI trial in 2005. They were assayed with 15 polymorphic SSR markers in the target region and 12 in the segregating background regions, of which 6, 2, 2, and 2 markers were distributed on chromosomes 1, 2, 4, and 5, respectively. PCR products were detected on 6% non-denaturing polyacrylamide gels using silver staining (Shi et al. 2005).
Data analysis The 27 markers were grouped and ordered with MAPMAKER/EXP 3.0 (Lander et al. 1987). The distances between markers were presented in centiMorgans (cM) derived using the Kosambi function. QTLs were determined with composite interval mapping of Windows QTL Cartographer 2.5 (Wang et al. 2006).
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Dissection of QTLs for Yield Traits on the Short Arm of Rice Chromosome 6
A threshold of LOD > 3.0 was used to claim a QTL.
RESULTS Phenotypic variation The F 3 population displayed large segregation with normal distribution on the six traits in the two trials (Table 1). On comparison of the population means between the two trials, little difference was observed for NP, SF, and GYD, while the values in Hainan trial were higher for TGWT and lower for NFGP and TNSP. Linear correlation analysis showed that the trait values between the two trials were positively correlated for TGWT (r = 0.5186, P < 0.01), but the correlation was not significant for the other traits (r = -0.0667 - 0.1186, P > 0.05). This indicated that the phenotypic performance of the genotypic differences in the F 3 population may vary greatly across the two environments. Two-way ANOVA showed that genotypic differences among the F3 lines, environmental changes between the two trials, and the interaction between the two factors all had considerable effects on the phenotypic
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performance of the F 3 population (Table 2). The environmental difference showed highly significant effects for all the traits (P <0.01). The genotypic effects were significant for NP (P< 0.05) and highly significant for the other five traits (P<0.01). The interaction effects were not significant for TGWT (P > 0.05), significant for NP (P < 0.05), and highly significant for the remaining four traits (P < 0.01). This was consistent with the result of the correlation analysis, indicating that the trait performance of the F3 population was strongly influenced by the environmental factors and the genotype × environment interaction.
QTL detected in the target interval A linkage map for the target interval and the four segregating background regions was constructed. The target interval consisted of 15 SSR markers on the short arm of chromosome 6 and spanned 60.5 cM. The background intervals each included 2-6 markers and spanned 3.7-26.9 cM. The map was used for QTL analysis with composite interval mapping. QTLs were detected in the target interval for all the traits analyzed except NP (Table 3).
Table 1 Phenotypic performance of the F3 population derived from an RHL selected from Zhenshan 97B/Milyang 46 recombinant inbred population Trait1) GYD (g) NP NFGP TNSP SF (%) TGWT (g)
Trial2)
Mean ± SD
Range
Kurtosis
Skewness
HN ZJ HN ZJ HN ZJ HN ZJ HN ZJ HN ZJ
20.53 ± 2.61 19.46 ± 3.23 10.82 ± 1.01 9.06 ± 1.04 68.28 ± 7.28 90.16 ± 11.22 95.08 ± 6.64 131.10 ± 16.53 71.68 ± 4.49 69.10 ± 6.44 30.07 ± 0.56 28.24 ± 0.78
14.04-28.18 10.67-30.40 8.10-14.90 6.67-13.43 47.45-102.14 46.29-118.54 80.00-123.77 81.47-174.91 54.88-82.54 45.62-81.99 28.17-31.37 26.02-30.13
-0.29 0.48 0.86 1.13 1.29 0.54 1.50 -0.10 0.75 0.30 0.57 0.18
0.12 0.44 0.39 0.61 0.04 0.05 0.44 0.34 -0.59 -0.55 -0.39 -0.32
1)
GYD, grain yield per plant; NP, number of panicles per plant; NFGP, number of filled grains per panicle; TNSP, total number of spikelets per panicle; SF, spikelet fertility; TGWT, 1 000-grain weight. 2) HN, November 2004-April 2005, Lingshui, Hainan Province, China; ZJ, May-September 2005, Hangzhou, Zhejiang Province, China.
Table 2 Two-way ANOVA of phenotypic performance of the F3 population derived from an RHL selected from Zhenshan 97B/Milyang 46 recombinant inbred population Source of variation Among lines Between trials Line × trial
P GYD
NP
NFGP
TNSP
SF
TGWT
0.00096 1.56 × 10-5 0.00089
0.03094 2.06 × 10-61 0.02712
1.58 × 10 -8 5.1 × 10-103 0.00029
2.15 × 10-22 7.2 × 10-168 6.35 × 10-17
1.02 × 10-5 8.38 × 10-12 3.73 × 10-8
3.56 × 10-6 4.6 × 10-102 0.99996
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NFGP was the trait for which different QTLs in the target interval were most distinguishable. Three QTLs for NFGP were detected in the Hainan trial with clear intervals of LOD peaks and valleys (Fig.-A). These QTLs basically act as additive QTLs, with the phenotypic variance explained by a single QTL ranging from 8.5 to 5.4% (Table 3). The allele for increasing grain number was from Zhenshan 97B at qNFGP6-1 and qNFGP6-2, and from Milyang 46 at qNFGP6-3. In the Zhejiang trial, only qNFGP6-2, which had the highest effect in the Hainan trial, was detected. This QTL showed consistent effects across the two environments. TNSP was the only trait for which more QTLs were detected in the Zhejiang trial than in the Hainan trial. Three QTLs for TNSP were detected in the Zhejiang trial (Table 3), and an additional one may be located in interval RM253- RM549 according to the LOD curve (Fig.-B). The three QTLs each have their enhancing alleles from Zhenshan 97B, with the phenotypic variance explained by a single QTL ranging from 6.3 to 35.2%. Of the three QTLs, qTNSP6-2 and qTNSP6-3 have additive action mode and were not detected in the Hainan trial. The remaining QTL, qTNSP6-1, was detected in both trials; while a negative over-dominance effect was observed in the Zhejiang trial, this QTL acted as an additive QTL in the Hainan trial. Two additive QTLs were detected for SF (Table 3).
QTL qSF6-1 was only detected in the Hainan trial, accounting for 8.9% of the phenotypic variance and having the enhancing allele from Zhenshan 97B. QTL qSF6-2 was detected in both trials, showing the same action mode and having the enhancing allele from Milyang 46. The peak LOD position for qSF6-2 moved considerably across the two trials (Fig.-C), and the contribution of 33.6% to the phenotypic variance in the Hainan trial was considerably higher than the value of 7.7% in the Zhejiang trial. Dissection of QTLs for TGWT was ambiguous. The peak LOD position lay between RM402 and RM549 in the Hainan trial and between RM549 and RM19715 in the Zhejiang trial, in company with 25.1 and 15.5% contribution to the phenotypic variance, respectively (Table 3). This QTL exhibited additive action mode and had the enhancing allele from Milyang 46. An additional QTL for TGWT may be located in the middle of the target interval according to the LOD curve (Fig. -D). GYD was the only trait for which QTL showing positive over-dominance effect was detected. Three QTLs for GYD were detected in the Hainan trial, while none was detected in the Zhejiang trial (Table 3, Fig. -E). QTL qGYD6-1 displayed positive over-dominance effect, had the enhancing allele from Zhenshan 97B, and accounted for 9.6% of the phenotypic variance. QTL qGYD6-2 displayed positive partial-dominance to
Table 3 QTLs for yield traits detected in the target interval RM587-RM19784 on the short arm of chromosome 6 QTL
Site
Interval
Pos 1)
LOD
A 2)
D 3)
D/[A]
R2 (%) 4)
qNFGP6-1 qNFGP6-2
HN HN ZJ HN HN ZJ ZJ ZJ HN HN ZJ HN ZJ HN HN HN
RM510-RM204 RM253-RM276 RM276-RM402 RM19715-RM19784 RM510-RM204 RM510-RM204 RM6119-RM314 RM549-RM19715 RM1163-RM6119 RM19715-RM19784 RM549-RM19715 RM402-RM549 RM549-RM19715 RM587-RM510 RM276-RM402 RM19715-RM19784
0.7 33.2 35.0 56.8 1.7 1.7 22.9 45.7 18.1 56.8 49.7 39.0 46.7 0.0 34.0 56.8
8.44 11.72 4.44 6.91 8.13 5.39 8.33 20.68 5.94 5.53 16.54 15.11 7.85 6.66 7.05 11.24
-3.27 -6.15 -7.13 4.05 -5.00 -7.17 -11.57 -15.78 -2.23 2.09 5.16 0.69 0.35 -0.69 -1.11 1.64
1.40 0.35 -3.00 0.06 0.13 -10.56 1.11 -1.00 0.79 -0.97 -0.59 0.19 0.08 1.14 0.96 -0.69
0.43 0.06 -0.42 0.01 0.03 -1.37 0.10 -0.06 0.35 -0.46 -0.11 0.17 0.28 1.65 0.84 -0.42
10.5 15.4 9.6 8.5 14.4 6.3 13.2 35.2 8.9 7.7 33.6 25.1 15.5 9.6 10.4 17.4
qNFGP6-3 qTNSP6-1 qTNSP6-2 qTNSP6-3 qSF6-1 qSF6-2 qTGWT6-1 qGYD6-1 qGYD6-2 qGYD6-3 1)
Distances from the peak LOD position to marker RM587. Additive effect, the genetic effect when a maternal allele is replaced by a paternal allele. 3) Dominance effect. 4) The proportion of phenotypic variance explained by the given QTL. The same as below. 2)
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Dissection of QTLs for Yield Traits on the Short Arm of Rice Chromosome 6
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Fig. Locations of QTLs for yield traits in interval RM587-RM19784 on the short arm of rice chromosome 6. A, B, C, D, and E refer to NFGP, TNSP, SF, TGWT, and GYD, respectively. Outputs from the HN and ZJ experiments are indicated by suffixes 1 and 2, respectively.
complete-dominance effect, had the enhancing allele from Zhenshan 97B, and accounted for 10.4% of the phenotypic variance. QTL qGYD6-3 displayed additive action mode, had the enhancing allele from Milyang 46, and accounted for 17.4% of the phenotypic variance.
QTL detected in the segregating background regions Of the four segregating background regions, the interval
on the long arm of chromosome 1 consisted of six markers (RM488, RM5461, RM237, RM246, RM1232, and RM3336) and spanned 26.9 cM, the interval on the long arm of chromosome 2 consisted of RM3774 and RM208 with a distance of 25.3 cM, the interval on the short arm of chromosome 4 consisted of RM551 and RM16355 with a distance of 13.4 cM, and the interval on the short arm of chromosome 5 consisted of RM267 and RM405 with a distance of 3.7 cM. QTLs were detected in three of the background
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Table 4 QTLs for yield traits detected in the segregating background regions QTL
Site
Interval
Pos
LOD
A
D
D/[A]
R2 (%)
qNP1 qNFGP2 qTNSP2
HN HN HN ZJ HN HN
RM1232-RM3336 RM3774-RM208 RM3774-RM208 RM3774-RM208 RM3774-RM208 RM267-RM405
24.2 0.0 0.0 25.0 0.0 2.0
3.07 3.58 5.74 3.09 4.99 3.29
-0.32 -1.71 -1.68 2.21 0.18 -1.14
-0.05 1.65 2.58 -6.56 -0.16 1.05
-0.16 0.96 1.54 -2.97 -0.89 0.92
5.9 4.2 9.4 3.6 9.8 4.6
qTGWT2 qSF5
intervals with composite interval mapping (Table 4). In terms of the genetic effect and proportion of the phenotypic variance explained, these were generally less significant as compared with QTLs detected in the target interval. One QTL was detected on the long arm of chromosome 1 and short arm of chromosome 5, respectively. Both QTLs were only detected in the Hainan trial. The former was responsible for NP and accounted for 5.9% of the phenotypic variance. The latter was detected for SF and accounted for 4.6% of the phenotypic variance. QTLs for NFGP, TNSP, and TGWT were detected on the long arm of chromosome 2 and explained 3.6-9.8% of the phenotypic variance. Two of the QTLs, qNFGP2 and qTGWT2, were only detected in the Hainan trial. The remaining QTL, qTNSP2, was detected in both trials with opposite direction of the genetic effect and moving of the peak LOD position.
DISCUSSION Clustering of QTLs is commonly observed in primary QTL mapping where it is difficult to differentiate gene pleiotropism from tight linkage. Analysis using materials with isogenic genetic background indicated that the clustering is at least partially attributed to tight linkage of different genes (Bernacchi et al. 1998; Takeuchi et al. 2003). In our previous studies (Fan et al. 2001; Zhuang et al. 2002), a QTL cluster for yield traits was detected in interval RZ398-B10 on the short arm of rice chromosome 6 in different generations and environments, but it remained unclear whether two or more QTLs for yield traits were located in this region. In this study, QTLs for the six yield traits were determined using an F3 population having an isogenic genetic background. The QTL cluster was separated into three different ones. Firstly, three QTLs for NFGP
were distinguishable and located in the top, middle, and bottom regions of the target interval, respectively (Fig. -A). Secondly, three QTL regions, of which each was responsible for multiple traits, could be dissected. The top region of the target interval had effects on NFGP, TNSP, and GYD, showing nearly identical QTL peaks. The bottom region of the target interval had effects on NFGP, TNSP, TGWT, and GYD, showing largely identical QTL peaks. This region may also have effect on TGWT. The middle region of the target interval had effects on NFGP, TNSP, SF, TGWT, and GYD. In this region, the QTL peaks moved from trait to trait, indicating a possible existence of multiple QTLs. The maternal and paternal parents of the original cross Zhenshan 97B/Milyang 46 are the maintainer and the restorer lines of the commercial three-line hybrid rice Shanyou 10, respectively, but previous studies detected no over-dominance QTLs, and the QTL for GYD detected on the short arm of chromosome 6 exhibited no significant dominance effects (Zhuang et al. 2001). Three QTLs for GYD were detected in the present study, of which qGYD6-1 exhibited positive overdominance effect, and qGYD6-2 could be regarded as a QTL having complete dominance effect if the weakening of dominance effect in the F3 population is taken into account. Nonetheless, it is not unexpected that the cluster of the three QTLs had no significant dominance effects, because qGYD6-3 having the largest effect exhibits negative partial dominance. As reported in other studies (Graham et al. 1997; Monforte and Tanksley 2000), QTL dissection may help to unmask the genetic mechanism of heterosis. It is well known that the detection of a QTL greatly depends on its magnitude as compared with QTLs segregated in the genetic background. In a primary population, which segregates a large number of QTLs, only QTLs having larger effect can be detected. In a population with isogenic genetic background, a QTL
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Dissection of QTLs for Yield Traits on the Short Arm of Rice Chromosome 6
having minor effect may be detectable owing to the reduction of the background noise. This was seen in the present study that QTLs for yield traits were detected in three of the four segregating background regions in which no QTL for yield traits was detected in the primary populations. Populations derived from NILs have been commonly used for QTL fine-mapping and positional cloning (Bernacchi et al. 1998; Takeuchi et al. 2003; Li et al. 2004; Ashikari et al. 2005; Fan et al. 2006), but it is often labor consuming and time consuming to develop NILs. RHL is a new type of genetic resource for QTL fine-mapping (Yamanaka et al. 2005). An RHL that carries a heterozygous segment in the target region in an isogenic background can be selected from a population at advanced generation based on one run of DNA marker genotyping. The selfing progenies will consist of a population suitable for QTL fine-mapping. Since the development of RHLs does not require repeated backcrossing and selections, it is considerably simpler than the development of NILs. In addition, RHLs may be selected by simply checking the genotype data in the linkage map construction using RIL or DH populations, as long as the seeds collected from the original plant for DNA extraction are available. The important role of RHLs has become recognized, and more and more attention has been paid to the application of RHLs in QTL fine-mapping (Loudet et al. 2005; Yamanaka et al. 2005; Kobayashi et al. 2006).
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Science Foundation (Y304446), the National 863 Program of China (2006AA10Z1E8), and the Chinese Super Rice Breeding Program (200606).
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May 2008
2008, 7(5): 513-520
Dissection of QTLs for Yield Traits on the Short Arm of Rice Chromosome 6 DU Jing-hong, FAN Ye-yang, WU Ji-rong and ZHUANG Jie-yun Chinese National Center for Rice Improvement/State Key Laboratory of Rice Science, China National Rice Research Institute, Hangzhou 310006, P.R.China
Abstract This study was undertaken to dissect quantitative trait loci (QTLs) controlling yield traits on the short arm of rice chromosome 6. A residual heterozygous line that carries a heterozygous segment extending from RM587 to RM19784 on the short arm of rice chromosome 6 was selected from an F7 population of the indica rice cross Zhenshan 97B/Milyang 46. An F2:3 population consisting of 221 lines was derived and grown in two trial sites. Six yield traits including number of panicles per plant, number of filled grains per panicle, total number of spikelets per panicle, spikelet fertility, 1 000-grain weight, and grain yield per plant were measured. An SSR marker linkage map was constructed and employed to determine QTLs for yield traits with Windows QTL Cartographer 2.5. QTLs were detected in the target interval for all the traits analyzed except NP, with phenotypic variance explained by a single QTL ranging between 6.3% and 35.2%. Most of the QTLs for yield components acted as additive QTLs, while the three QTLs for grain yield had dominance degrees of 1.65, 0.84, and -0.42, respectively. It was indicated that three or more QTLs for yield traits were located in the target region. The genetic action mode, the direction of the QTL effect, and the magnitude of the QTL effect varied among different QTLs for a given trait, and among QTLs for different traits that were located in the same interval. Key words: yield traits, residual heterozygous line, quantitative trait locus, short arm of chromosome 6, rice (Oryza sativa L.)
INTRODUCTION Grain yield and its component traits are quantitatively inherited. Such traits are controlled by quantitative trait loci (QTLs) that are generally located in clusters. QTL regions that were detected in one or more primary mapping studies can be followed to develop a population that segregates the target interval in an isogenic background. This will help to dissect different QTLs in the QTL cluster, thus providing candidates for QTL fine-mapping and positional cloning. Rice is a plant species that has attracted exceptional attention and achieved remarkable progress in QTL mapping. Nowadays, QTL analysis in rice is moving
from primary mapping to fine mapping and positional cloning. For complex traits such as yield and yield component, QTLs that were detected in two or more independent studies are considered preferential targets (Li et al. 2004; Ashikari et al. 2005; Fan et al. 2006). Development of populations that segregate a single QTL region in an isogenic background is a prerequisite for QTL fine-mapping and positional cloning. In addition to the classical near isogenic lines (NILs) that are developed by back-crossing, residual heterozygous lines (RHLs) are a new type of genetic resource for QTL fine-mapping (Yamanaka et al. 2005). Being selected from a population of the advanced generation such as F6 or F 7, an RHL is basically homozygous but has a heterozygous segment in the target region. Such a line
This paper is translated from its Chinese version in Scientia Agricultura Sinica. DU Jing-hong, Ph D, E-mail: [email protected]; Correspondence ZHUANG Jie-yun, E-mail: [email protected]
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is equivalent to an F1 that is produced by crossing a pair of NILs differing at the target region. The selfed progenies will compose a population that segregates a single region covering the target heterozygous segment, and thus can be used for QTL fine-mapping. Using F2 populations of indica rice crosses Zhenshan 97B/Milyang 46 and Xieqingzao B/Milyang 46 and an F 6:7 population of Zhenshan 97B/Milyang 46, our previous studies have located QTLs for yield traits in interval RZ398-B10 on the short arm of rice chromosome 6 (Fan et al. 2001; Zhuang et al. 2001, 2002). This QTL region has also been detected in other populations, which were developed from a variety of crosses, including indica × indica cross (Hua et al. 2002), japonica × janonica cross (Mu et al. 2005), indica × japonica cross (Redona and Mackill 1998; Mei et al. 2003; Han et al. 2005), and crosses of indica × wild rice (Moncada et al. 2001; Brondani et al. 2002; Yoon et al. 2006). In the present study, dissection of QTLs for yield traits was conducted using an F2:3 population derived from an RHL that carries a heterozygous segment in the target region on the short arm of chromosome 6.
MATERIALS AND METHODS
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of 3.8, 1.1, 2.0, and 0.6 Mb, respectively. It was noted that no QTLs for yield traits were previously detected in these background regions in Zhenshan 97B/Milyang 46 populations (Fan et al. 2001; Zhuang et al. 2001, 2002). An F2 population consisting of 221 plants was derived from the RHL and grown in the summer-autumn ricegrowing season in 2004 at the China National Rice Research Institute (CNRRI), Hangzhou, Zhejiang Province, China. Seeds of each F 2 individual were divided into two parts. The two sets of F3 populations were grown in the winter-spring season in 2004-2005 in Lingshui, Hainan Province, China, and in the summerautumn season in 2005 at CNRRI, respectively. The field experiment followed a randomized complete block design with two replications. Twelve plants per line were planted at the spacing of 20 cm × 23 cm in each replication. At maturity, panicles were harvested from the middle 10 plants and sun-dried. Six traits including grain yield per plant (GYD), number of panicles per plant (NP), number of filled grains per panicle (NFGP), total number of spikelets per panicle (TNSP), spikelet fertility (SF), and 1 000-grain weight (TGWT) were measured. The mean values over two replications at each site were used for analysis.
SSR genotyping Rice materials and phenotyping Following our previous study of QTL mapping using recombinant inbred lines (RILs) of Zhenshan 97B/ Milyang 46 (Zhuang et al. 2002), more SSR (simple sequence repeat) markers were selected for parental survey and polymorphic markers were applied to the assay RILs. The linkage map was updated and QTL analysis was performed again. The target region on the short arm of rice chromosome 6 for QTL finemapping was determined as RM587-RM19784. Another F7 population of the same cross was used for RHL selection. One plant of each F7 line was tested with 208 SSR markers. An RHL that carries a 7.3-Mb heterozygous segment extending from RM587 to RM19784 was selected. This RHL is homozygous in other genomic regions except for four segments, locating on the long arms of chromosomes 1 and 2, and the short arms of chromosomes 4 and 5 with length
DNAs were extracted from a leaf mixture of 10 plants for each F3 line at the first replication of the CNRRI trial in 2005. They were assayed with 15 polymorphic SSR markers in the target region and 12 in the segregating background regions, of which 6, 2, 2, and 2 markers were distributed on chromosomes 1, 2, 4, and 5, respectively. PCR products were detected on 6% non-denaturing polyacrylamide gels using silver staining (Shi et al. 2005).
Data analysis The 27 markers were grouped and ordered with MAPMAKER/EXP 3.0 (Lander et al. 1987). The distances between markers were presented in centiMorgans (cM) derived using the Kosambi function. QTLs were determined with composite interval mapping of Windows QTL Cartographer 2.5 (Wang et al. 2006).
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Dissection of QTLs for Yield Traits on the Short Arm of Rice Chromosome 6
A threshold of LOD > 3.0 was used to claim a QTL.
RESULTS Phenotypic variation The F 3 population displayed large segregation with normal distribution on the six traits in the two trials (Table 1). On comparison of the population means between the two trials, little difference was observed for NP, SF, and GYD, while the values in Hainan trial were higher for TGWT and lower for NFGP and TNSP. Linear correlation analysis showed that the trait values between the two trials were positively correlated for TGWT (r = 0.5186, P < 0.01), but the correlation was not significant for the other traits (r = -0.0667 - 0.1186, P > 0.05). This indicated that the phenotypic performance of the genotypic differences in the F 3 population may vary greatly across the two environments. Two-way ANOVA showed that genotypic differences among the F3 lines, environmental changes between the two trials, and the interaction between the two factors all had considerable effects on the phenotypic
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performance of the F 3 population (Table 2). The environmental difference showed highly significant effects for all the traits (P <0.01). The genotypic effects were significant for NP (P< 0.05) and highly significant for the other five traits (P<0.01). The interaction effects were not significant for TGWT (P > 0.05), significant for NP (P < 0.05), and highly significant for the remaining four traits (P < 0.01). This was consistent with the result of the correlation analysis, indicating that the trait performance of the F3 population was strongly influenced by the environmental factors and the genotype × environment interaction.
QTL detected in the target interval A linkage map for the target interval and the four segregating background regions was constructed. The target interval consisted of 15 SSR markers on the short arm of chromosome 6 and spanned 60.5 cM. The background intervals each included 2-6 markers and spanned 3.7-26.9 cM. The map was used for QTL analysis with composite interval mapping. QTLs were detected in the target interval for all the traits analyzed except NP (Table 3).
Table 1 Phenotypic performance of the F3 population derived from an RHL selected from Zhenshan 97B/Milyang 46 recombinant inbred population Trait1) GYD (g) NP NFGP TNSP SF (%) TGWT (g)
Trial2)
Mean ± SD
Range
Kurtosis
Skewness
HN ZJ HN ZJ HN ZJ HN ZJ HN ZJ HN ZJ
20.53 ± 2.61 19.46 ± 3.23 10.82 ± 1.01 9.06 ± 1.04 68.28 ± 7.28 90.16 ± 11.22 95.08 ± 6.64 131.10 ± 16.53 71.68 ± 4.49 69.10 ± 6.44 30.07 ± 0.56 28.24 ± 0.78
14.04-28.18 10.67-30.40 8.10-14.90 6.67-13.43 47.45-102.14 46.29-118.54 80.00-123.77 81.47-174.91 54.88-82.54 45.62-81.99 28.17-31.37 26.02-30.13
-0.29 0.48 0.86 1.13 1.29 0.54 1.50 -0.10 0.75 0.30 0.57 0.18
0.12 0.44 0.39 0.61 0.04 0.05 0.44 0.34 -0.59 -0.55 -0.39 -0.32
1)
GYD, grain yield per plant; NP, number of panicles per plant; NFGP, number of filled grains per panicle; TNSP, total number of spikelets per panicle; SF, spikelet fertility; TGWT, 1 000-grain weight. 2) HN, November 2004-April 2005, Lingshui, Hainan Province, China; ZJ, May-September 2005, Hangzhou, Zhejiang Province, China.
Table 2 Two-way ANOVA of phenotypic performance of the F3 population derived from an RHL selected from Zhenshan 97B/Milyang 46 recombinant inbred population Source of variation Among lines Between trials Line × trial
P GYD
NP
NFGP
TNSP
SF
TGWT
0.00096 1.56 × 10-5 0.00089
0.03094 2.06 × 10-61 0.02712
1.58 × 10 -8 5.1 × 10-103 0.00029
2.15 × 10-22 7.2 × 10-168 6.35 × 10-17
1.02 × 10-5 8.38 × 10-12 3.73 × 10-8
3.56 × 10-6 4.6 × 10-102 0.99996
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NFGP was the trait for which different QTLs in the target interval were most distinguishable. Three QTLs for NFGP were detected in the Hainan trial with clear intervals of LOD peaks and valleys (Fig.-A). These QTLs basically act as additive QTLs, with the phenotypic variance explained by a single QTL ranging from 8.5 to 5.4% (Table 3). The allele for increasing grain number was from Zhenshan 97B at qNFGP6-1 and qNFGP6-2, and from Milyang 46 at qNFGP6-3. In the Zhejiang trial, only qNFGP6-2, which had the highest effect in the Hainan trial, was detected. This QTL showed consistent effects across the two environments. TNSP was the only trait for which more QTLs were detected in the Zhejiang trial than in the Hainan trial. Three QTLs for TNSP were detected in the Zhejiang trial (Table 3), and an additional one may be located in interval RM253- RM549 according to the LOD curve (Fig.-B). The three QTLs each have their enhancing alleles from Zhenshan 97B, with the phenotypic variance explained by a single QTL ranging from 6.3 to 35.2%. Of the three QTLs, qTNSP6-2 and qTNSP6-3 have additive action mode and were not detected in the Hainan trial. The remaining QTL, qTNSP6-1, was detected in both trials; while a negative over-dominance effect was observed in the Zhejiang trial, this QTL acted as an additive QTL in the Hainan trial. Two additive QTLs were detected for SF (Table 3).
QTL qSF6-1 was only detected in the Hainan trial, accounting for 8.9% of the phenotypic variance and having the enhancing allele from Zhenshan 97B. QTL qSF6-2 was detected in both trials, showing the same action mode and having the enhancing allele from Milyang 46. The peak LOD position for qSF6-2 moved considerably across the two trials (Fig.-C), and the contribution of 33.6% to the phenotypic variance in the Hainan trial was considerably higher than the value of 7.7% in the Zhejiang trial. Dissection of QTLs for TGWT was ambiguous. The peak LOD position lay between RM402 and RM549 in the Hainan trial and between RM549 and RM19715 in the Zhejiang trial, in company with 25.1 and 15.5% contribution to the phenotypic variance, respectively (Table 3). This QTL exhibited additive action mode and had the enhancing allele from Milyang 46. An additional QTL for TGWT may be located in the middle of the target interval according to the LOD curve (Fig. -D). GYD was the only trait for which QTL showing positive over-dominance effect was detected. Three QTLs for GYD were detected in the Hainan trial, while none was detected in the Zhejiang trial (Table 3, Fig. -E). QTL qGYD6-1 displayed positive over-dominance effect, had the enhancing allele from Zhenshan 97B, and accounted for 9.6% of the phenotypic variance. QTL qGYD6-2 displayed positive partial-dominance to
Table 3 QTLs for yield traits detected in the target interval RM587-RM19784 on the short arm of chromosome 6 QTL
Site
Interval
Pos 1)
LOD
A 2)
D 3)
D/[A]
R2 (%) 4)
qNFGP6-1 qNFGP6-2
HN HN ZJ HN HN ZJ ZJ ZJ HN HN ZJ HN ZJ HN HN HN
RM510-RM204 RM253-RM276 RM276-RM402 RM19715-RM19784 RM510-RM204 RM510-RM204 RM6119-RM314 RM549-RM19715 RM1163-RM6119 RM19715-RM19784 RM549-RM19715 RM402-RM549 RM549-RM19715 RM587-RM510 RM276-RM402 RM19715-RM19784
0.7 33.2 35.0 56.8 1.7 1.7 22.9 45.7 18.1 56.8 49.7 39.0 46.7 0.0 34.0 56.8
8.44 11.72 4.44 6.91 8.13 5.39 8.33 20.68 5.94 5.53 16.54 15.11 7.85 6.66 7.05 11.24
-3.27 -6.15 -7.13 4.05 -5.00 -7.17 -11.57 -15.78 -2.23 2.09 5.16 0.69 0.35 -0.69 -1.11 1.64
1.40 0.35 -3.00 0.06 0.13 -10.56 1.11 -1.00 0.79 -0.97 -0.59 0.19 0.08 1.14 0.96 -0.69
0.43 0.06 -0.42 0.01 0.03 -1.37 0.10 -0.06 0.35 -0.46 -0.11 0.17 0.28 1.65 0.84 -0.42
10.5 15.4 9.6 8.5 14.4 6.3 13.2 35.2 8.9 7.7 33.6 25.1 15.5 9.6 10.4 17.4
qNFGP6-3 qTNSP6-1 qTNSP6-2 qTNSP6-3 qSF6-1 qSF6-2 qTGWT6-1 qGYD6-1 qGYD6-2 qGYD6-3 1)
Distances from the peak LOD position to marker RM587. Additive effect, the genetic effect when a maternal allele is replaced by a paternal allele. 3) Dominance effect. 4) The proportion of phenotypic variance explained by the given QTL. The same as below. 2)
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Dissection of QTLs for Yield Traits on the Short Arm of Rice Chromosome 6
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Fig. Locations of QTLs for yield traits in interval RM587-RM19784 on the short arm of rice chromosome 6. A, B, C, D, and E refer to NFGP, TNSP, SF, TGWT, and GYD, respectively. Outputs from the HN and ZJ experiments are indicated by suffixes 1 and 2, respectively.
complete-dominance effect, had the enhancing allele from Zhenshan 97B, and accounted for 10.4% of the phenotypic variance. QTL qGYD6-3 displayed additive action mode, had the enhancing allele from Milyang 46, and accounted for 17.4% of the phenotypic variance.
QTL detected in the segregating background regions Of the four segregating background regions, the interval
on the long arm of chromosome 1 consisted of six markers (RM488, RM5461, RM237, RM246, RM1232, and RM3336) and spanned 26.9 cM, the interval on the long arm of chromosome 2 consisted of RM3774 and RM208 with a distance of 25.3 cM, the interval on the short arm of chromosome 4 consisted of RM551 and RM16355 with a distance of 13.4 cM, and the interval on the short arm of chromosome 5 consisted of RM267 and RM405 with a distance of 3.7 cM. QTLs were detected in three of the background
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Table 4 QTLs for yield traits detected in the segregating background regions QTL
Site
Interval
Pos
LOD
A
D
D/[A]
R2 (%)
qNP1 qNFGP2 qTNSP2
HN HN HN ZJ HN HN
RM1232-RM3336 RM3774-RM208 RM3774-RM208 RM3774-RM208 RM3774-RM208 RM267-RM405
24.2 0.0 0.0 25.0 0.0 2.0
3.07 3.58 5.74 3.09 4.99 3.29
-0.32 -1.71 -1.68 2.21 0.18 -1.14
-0.05 1.65 2.58 -6.56 -0.16 1.05
-0.16 0.96 1.54 -2.97 -0.89 0.92
5.9 4.2 9.4 3.6 9.8 4.6
qTGWT2 qSF5
intervals with composite interval mapping (Table 4). In terms of the genetic effect and proportion of the phenotypic variance explained, these were generally less significant as compared with QTLs detected in the target interval. One QTL was detected on the long arm of chromosome 1 and short arm of chromosome 5, respectively. Both QTLs were only detected in the Hainan trial. The former was responsible for NP and accounted for 5.9% of the phenotypic variance. The latter was detected for SF and accounted for 4.6% of the phenotypic variance. QTLs for NFGP, TNSP, and TGWT were detected on the long arm of chromosome 2 and explained 3.6-9.8% of the phenotypic variance. Two of the QTLs, qNFGP2 and qTGWT2, were only detected in the Hainan trial. The remaining QTL, qTNSP2, was detected in both trials with opposite direction of the genetic effect and moving of the peak LOD position.
DISCUSSION Clustering of QTLs is commonly observed in primary QTL mapping where it is difficult to differentiate gene pleiotropism from tight linkage. Analysis using materials with isogenic genetic background indicated that the clustering is at least partially attributed to tight linkage of different genes (Bernacchi et al. 1998; Takeuchi et al. 2003). In our previous studies (Fan et al. 2001; Zhuang et al. 2002), a QTL cluster for yield traits was detected in interval RZ398-B10 on the short arm of rice chromosome 6 in different generations and environments, but it remained unclear whether two or more QTLs for yield traits were located in this region. In this study, QTLs for the six yield traits were determined using an F3 population having an isogenic genetic background. The QTL cluster was separated into three different ones. Firstly, three QTLs for NFGP
were distinguishable and located in the top, middle, and bottom regions of the target interval, respectively (Fig. -A). Secondly, three QTL regions, of which each was responsible for multiple traits, could be dissected. The top region of the target interval had effects on NFGP, TNSP, and GYD, showing nearly identical QTL peaks. The bottom region of the target interval had effects on NFGP, TNSP, TGWT, and GYD, showing largely identical QTL peaks. This region may also have effect on TGWT. The middle region of the target interval had effects on NFGP, TNSP, SF, TGWT, and GYD. In this region, the QTL peaks moved from trait to trait, indicating a possible existence of multiple QTLs. The maternal and paternal parents of the original cross Zhenshan 97B/Milyang 46 are the maintainer and the restorer lines of the commercial three-line hybrid rice Shanyou 10, respectively, but previous studies detected no over-dominance QTLs, and the QTL for GYD detected on the short arm of chromosome 6 exhibited no significant dominance effects (Zhuang et al. 2001). Three QTLs for GYD were detected in the present study, of which qGYD6-1 exhibited positive overdominance effect, and qGYD6-2 could be regarded as a QTL having complete dominance effect if the weakening of dominance effect in the F3 population is taken into account. Nonetheless, it is not unexpected that the cluster of the three QTLs had no significant dominance effects, because qGYD6-3 having the largest effect exhibits negative partial dominance. As reported in other studies (Graham et al. 1997; Monforte and Tanksley 2000), QTL dissection may help to unmask the genetic mechanism of heterosis. It is well known that the detection of a QTL greatly depends on its magnitude as compared with QTLs segregated in the genetic background. In a primary population, which segregates a large number of QTLs, only QTLs having larger effect can be detected. In a population with isogenic genetic background, a QTL
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Dissection of QTLs for Yield Traits on the Short Arm of Rice Chromosome 6
having minor effect may be detectable owing to the reduction of the background noise. This was seen in the present study that QTLs for yield traits were detected in three of the four segregating background regions in which no QTL for yield traits was detected in the primary populations. Populations derived from NILs have been commonly used for QTL fine-mapping and positional cloning (Bernacchi et al. 1998; Takeuchi et al. 2003; Li et al. 2004; Ashikari et al. 2005; Fan et al. 2006), but it is often labor consuming and time consuming to develop NILs. RHL is a new type of genetic resource for QTL fine-mapping (Yamanaka et al. 2005). An RHL that carries a heterozygous segment in the target region in an isogenic background can be selected from a population at advanced generation based on one run of DNA marker genotyping. The selfing progenies will consist of a population suitable for QTL fine-mapping. Since the development of RHLs does not require repeated backcrossing and selections, it is considerably simpler than the development of NILs. In addition, RHLs may be selected by simply checking the genotype data in the linkage map construction using RIL or DH populations, as long as the seeds collected from the original plant for DNA extraction are available. The important role of RHLs has become recognized, and more and more attention has been paid to the application of RHLs in QTL fine-mapping (Loudet et al. 2005; Yamanaka et al. 2005; Kobayashi et al. 2006).
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Science Foundation (Y304446), the National 863 Program of China (2006AA10Z1E8), and the Chinese Super Rice Breeding Program (200606).
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