Mol. Cells, V ol. 24, No. 1, pp. 83-94
Quantitative Trait Loci Associated with Functional Stay-Green SNU-SG1 in Rice
Soo-Cheul Yoo†, Sung-Hwan Cho†, Haitao Zhang, Hyo-Chung Paik, Chung-Hee Lee, Jinjie Li,
Jeong-Hoon Yoo, Byun-Woo Lee, Hee-Jong Koh, Hak Soo Seo, and Nam-Chon Paek*
Department of Plant Science and Rearch Institute for Agriculture and Life Sciences, Seoul National University, Seoul 151-921, Korea. (Received February 4, 2007; Accepted April 9, 2007)
During monocarpic nescence in higher plants, func-tional stay-green delays leaf yellowing, maintaining pho-tosynthetic competence, whereas nonfunctional stay-green retains leaf greenness without sustaining photosynthetic activity. Thus, functional stay-green is considered a benefi-cial trait that can increa grain yield in cereal crops. A stay-green japonica rice ‘SNU-SG1’ had a good ed-tting rate and grain yield, indicating the prence of a functional stay-green genotype. SNU-SG1 was crosd with two regular cultivars to determine the inheritance mode and identify major QTLs conferring stay-green in SNU-SG1. For QTL analysis, linkage maps with 100 and 116 DNA marker loci were constructed using lective genotyping with F2 and RIL (recombinant inbred line) populations, res
pectively. Molecular marker-bad QTL analys with both populations revealed that the functional stay-green phenotype of SNU-SG1 is regulated by veral major QTLs accounting for a large portion of the genetic variation. Three main-effect QTLs located on chromo-somes 7 and 9 were detected in both populations and a number of epistatic-effect QTLs were also found. The amount of variation explained by veral digenic interac-tions was larger than that explained by main-effect QTLs. Two main-effect QTLs on chromosome 9 can be consid-ered the target loci that most influence the functional stay-green in SNU-SG1. The functional stay-green QTLs may help develop low-input high-yielding rice cultivars by QTL-marker-assisted breeding with SNU-SG1. Keywords: Epistasis; F2 Population; Functional Stay-Green; Recombinant Inbred Lines; QTL Mapping; Rice; Selective Genotyping; SNU-SG1.
† The authors contributed equally to this work.
* To whom correspondence should be addresd.
Tel: 82-2-880-4543; Fax: 82-2-873-2056
E-mail: ncpaek@snu.ac.kr Introduction
Leaf greenness depends on the concentration of chloro-phyll, the most important green pigment absorbing sunlight energy for photosynthesis. Leaf yellowing gener-ally results from progressive breakdown of chlorophyll during nescence. Plants assimilate carbohydrates and nitrogen in vegetative organs (source) and remobilize them to newly developing tissues during development, or to reproductive organs (sink) during nescence. To in-crea grain yield in cereal crops, source strength must be incread so that sink organs can be filled via efficient translocation. Photosynthates generated after heading are responsible for 60-90% of the total carbon accumulated in rice panicles at harvest, while 70−90% of total panicle nitrogen uptake occurs before heading and is sub-quently remobilized from leaf to grain during monocarpic nescence (Mae, 1997; Yue et al., 2006). Both persis-tence of high photosynthetic capacity and efficient nitro-gen remobilization during grain filling, therefore, have been considered key factors in increasing grain yield (Abdelkhalik et al., 2005; Yamaya et al., 2002).
Stay-greenness (or delayed nescence) during the final stage of leaf development is an important trait in increas-ing source strength in grain production, and its physio-logical and genetic bas have been studied in veral plants. Thomas and Howarth (2000) classified five stay-green phenotypes according to their nescing behaviors. Stay-green also can be generally divided into two groups, fu
nctional and nonfunctional. Functional stay-green is defined as retaining both leaf greenness and photosyn-thetic competence much longer during nescence than Abbreviations: cM, centiMorgan; DH lines, doubled haploid lines; LOD, logarithm of odds; PCR, polymera chain reaction; PSII, photosystem II; QTL, quantitative trait loci; RFLP, restric-tion fragment length polymorphism; RIL, recombinant inbred line; SSD, single ed decent; SSR, simple quence repeat.
Molecules
and
Cells
©KSMCB 2007
84 QTLs for Functional Stay-Green Rice
the wild-type, while nonfunctional stay-green is defined as maintaining only leaf greenness. Park and Lee (2003) found a stay-green variant in a japonica rice collection designated ‘SNU-SG1’. It was classified as a functional Type B stay-green japonica rice in which leaf nescence initiates on schedule but leaf photosynthetic rate and chlo-rophyll content decrea much more slowly during
nes-cence than tho of high-yielding cultivars.
Becau of the potential contribution of the stay-green trait to incread crop production, it has been intensively studied in many crops such as sorghum (Walulu, 1994), soybean (Pierce et al., 1984), maize (Gentinetta et al., 1986), Phaolus vulgaris (Fang et al., 1998), durum wheat (Spano et al., 2003) and potato (Schittenhelm et al., 2004). Some reports suggest that functional stay-green ari from delays in the initiation or rate of nescence. Functional stay-green genotypes have been reported in durum wheat, which maintains longer photosynthetic ac-tivity, has higher ed weights, and yields more grain than the parental genotype (Spano et al., 2003). One of the stay-green lines, Trinakria (designated 504), was confirmed as a functional stay-green by analyzing the differential expres-sion profile of photosynthetic parameters between stay-green and normal parental lines (Rampino et al., 2006). Schittenhelm et al. (2004) suggested that a transgenic po-tato plant, Dara-5, overexpressing phytochrome B has de-layed ont of nescence and then shows normal declines in leaf chlorophyll and protein concentrations, leaf carbon exchange rate, and Rubisco activity. Thus, Dara-5 was classified as a functional Type A stay-green. Nonfunctional stay-green mutants have been also studied intensively in many plants. The sid (nescence-induced-deficiency) mu-tant of Festuca pratensis is the most intensively-studied nonfunctional stay-green (Thomas, 1987; 1997; Th
omas and Stoddart, 1975). Cha et al. (2002) mapped a single recessive mutant gene, sgr, specifying nonfunctional stay-green to the long arm of chromosome 9 in rice. Armstead et al. (2006; 2007) recently reported that the stay-green sid locus in F. pratensis is syntenically equivalent to the sgr locus on rice chromosome 9, and genetic mapping of the green cotyledon color in peas demonstrated co-gregation of the pea Sgr locus with the yellow/green cotyledon poly-morphism (I/i) reported by Gregor Mendel in 1866.
The functional stay-green trait is generally regulated by complex factors: nescence-related genes and environ-mental factors. The identification of quantitative trait loci (QTLs) is, therefore, a uful approach to elucidating the molecular basis of functional stay-green. There have been a number of reports of QTLs affecting stay-green-related traits in plants. In sorghum, a stay-green genotype is con-sidered resistant to post-flowering drought stress (Ronow et al., 1983), and QTL mapping studies using RILs and NILs revealed both main-effect and epistatic QTLs (Harris et al., 2007; Sanchez et al., 2002; Xu et al., 2000). In Arabidopsis, four QTLs for post-bolting longevity were found on chromosomes 1, 3, 4 and 5 using 155 RILs de-rived from a cross of Cape Verde Islands (Cvi)/Landsberg erecta (L er) (Luquez et al., 2006). In rice, six QTLs for chlorophyll content were detected on five chromosomes using a backcross line (Ishimaru et al., 2001) and three QTLs for chlo
rophyll content on three chromosomes using a double haploid population derived from an indica and japonica hybrid [Teng et al. (2004)]. Jiang et al. (2004) analyzed the genetic basis of stay-green using doubled hap-loid (DH) lines derived from an indica/japonica cross and detected 46 main-effect QTLs in 25 chromosomal regions and 50 digenic interactions involving 66 loci on 12 chro-mosomes. Yue et al. (2006) also reported that six QTLs for degree of greenness and fourteen QTLs for stay-green-related traits during monocarpic nescence were resolved using RIL populations.
The relationship between the stay-green trait and crop yield has been analyzed in some plants. Although the con-tribution of the stay-green genotype to stable yield pro-duction under drought stress has been studied in sorghum (Borrell et al., 2000), a meaningful correlation between leaf stay-greenness and grain yield increa has not yet been reported in rice. On the contrary, a negative relation-ship was reported (Jiang et al., 2004; Yue et al., 2006). In this study, we determined the genetic basis of SNU-SG1 and identified main- and epistatic-effect QTLs conferring a functional stay-green using F2 and RIL populations gen-erated from a cross of the stay-green japonica rice ‘SNU-SG1’ and the high-yielding tongil-type cultivar ‘Mily-ang23’. Genetic correlations between the stay-green trait and yield and yield components were also analyzed. Here we describe three QTLs detected in both F2 and RIL populations and novel QTLs for the functional stay-green trait in rice. In
particular the QTLs on chromosome 9 rep-renting most of the stay-green traits with large pheno-typic variation should be uful for developing a MAS technique for a functional stay-green molecular breeding program.
Materials and Methods
Plant materials and field conditions The functional stay-green rice, SNU-SG1, which has high chlorophyll content and delayed leaf nescence was first discovered in a field performance test with japonica rice collections introduced from China, at the Seoul National University Experimental Farm in 2001 (Park and Lee, 2003). In order to study its inheritance, SNU-SG1 was crosd with a regular japonica cultivar, Ilpumbyeo, that has a similar heading date. The two parents, F1s, and 252 F2 individu-als from the cross were ud to analyze the inheritance and the correlation between the stay-green trait and the yield and yield components. To identify the QTLs conferring functional stay-green, SNU-SG1 was crosd with a high-yielding tongil-type cultivar, Milyang23 (M23), which is derived from an indica/
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et al. 85
japonica cross and is similar to indica in its genetic make-up (Lee et al., 2006). A ‘lective genotyping’ method was ud in the F2 analysis to test the suitability of the mapping population for detecting stay-green QTLs and identify major QTLs in that population. Among 235 F2 individuals from the SNU-SG1/M23 cross, we lected for genotyping 46 that had extreme pheno-types (23 lines with extremely delayed nescence and 23 lines exhibiting early yellowing during grain filling) but similar head-ing dates. The two F2 populations, F1s, and parental lines were planted in the Seoul National University Experimental Farm in 2002. The RIL population was developed via the single ed descent (SSD) method through the F6 generation. A population of 425 F6 RILs was developed and 92 individuals with extreme phenotypes (46 with extremely delayed nescence and 46 with early yellowing during grain filling), with little variation of head-ing date, were ud to identify consistent main-effect QTLs. The parents, F1s, and RILs were planted in different blocks within the Experimental Farm. Field management followed normal rice prac-tice in Korea. The rice field was regularly irrigated to avoid drought stress to the late-maturing F2 and RIL lines. Measurement of stay-green traits The chlorophyll contents of flag and cond leaves of each F2 line were measured at heading and thereafter four times at 10-d intervals using a Minolta Chlo-rophyll Meter SPAD-502 (
Minolta, Japan), an indirect indicator of chlorophyll content. To ensure that the measurements were taken on the correct day for the right tiller, tillers were tagged on the heading date. SPAD readings were taken by measuring three panicles per plant and at least three parts of each leaf. Chlorophyll contents of flag and cond leaves measured on the heading date were designated as DCF and DCS, respectively, and DCFS was bad on the average of DCF and DCS to complement the functional stay-green trait. Cumulative chlorophyll contents of flag (CCF) and cond leaves (CCS) were calculated by summing the first to fourth SPAD values. SPAD readings of flag and cond leaves were only measured in the RIL population on the heading day using the same method as in F2 population.
Measurement of chlorophyll fluorescence, and yield and yield components Photosynthetic activities were measured with a portable PAM2000 chlorophyll fluorometer (Heinz Walz, Germany) as described by Fukushima et al. (2001). Minimum fluorescence (F0) and maximum fluorescence (F m) were meas-ured in the dark-adapted leaves, using a two-cond light pul (3000 µmol photons−2 s−1 in the range of 350 to 700 nm) to satu-rate all photosystem II (PSII) reaction centers. The photochemi-cal efficiency of PSII was calculated as the ratio of variable fluorescence (F v = F m – F o) to maximum fluorescence (F m) to determine the potential activity of PSII (F v/F m) as previously
described (Genty et al., 1989; Kooten and Snel, 1990). Yield and yield components were examined by measuring: grain yield per plant as the total grain weight (g) per plant, the number of reproductive tillers per plant, the number of grains per panicle, 1000-grain weight (g), and ed-tting rate. Seed-tting rate (or fertility) was scored as the number of grains divided by total number of spikelets from the reproductive tillers of a plant, with three replications. Trait measurements averaged for the three replications were ud in the analys.
Molecular makers Leaf tissue was harvested from each line at the maximum tillering stage. Genomic DNA was extracted using the CTAB method described by Murray and Thompson (1980). SSR and STS markers were ud for map construction. The markers of the RM-ries were designed according to Temnykh et al. (2000; 2001), and tho of the S-ries were bad on the quence differences between japonica and indica rice, using information available from the Crop Molecular Breeding Lab, Seoul National University (unpublished). The markers showing polymorphism between the parents and having a good coverage of 12 chromosomes were ud to assay both populations. The DNA amplification protocol comprid 5 min at 94°C, followed by 35 cycles of 1 min at 94°C, 1 min at 55 or 60°C, 1 min at 72°C and a final extension for 5 min at 72°C in a thermocycler (MJ Rearch, USA). PCR was performed with 50 ng of ge-nomic DNA, 0.2 μM of each primer and 1
unit of Taq DNA polymera in a 20 μl reaction volume. PCR products were re-solved on 2.5% agaro gels.
Linkage map construction and data analysis A linkage map was constructed using Mapmaker 3.0 (Lander et al., 1987; Lin-coln et al., 1993) and MapChart 2.0. Distances between markers are given in centiMorgans (cMs) using the Kosambi map func-tion (Kosambi, 1944), and the order of markers was established by three-point analysis. The chromosomal location of main-effect QTLs and epistatic interactions were determined by inter-val mapping using a mixed linear model and a QTL Mapper version 2.0 software (Gao et al., 2004). To determine the em-pirical significance threshold for declaring a QTL, 5000 permu-tations were performed to calculate LOD thresholds for each trait at p = 0.05 and p = 0.01 using the Qgene 3.06 software for Macintosh (Nelson, 1997). The proportion of phenotypic varia-tion explained by each QTL was calculated as the R2 value, and the degree of dominance of a QTL was estimated as the ratio of dominance effect to additive effect (D/A).
Results
Characterization of the stay-green trait in SNU-SG1 SNU-SG1 exhibited delayed nescence during grain fill-ing compared to the two regular domestic cultivars, Ilpumbyeo and Milyang23 (M23), ud in this study (Fig.
1). Temporal changes in chlorophyll content showed that SNU-SG1 maintained chlorophyll content much longer during monocarpic nescence than the two parental va-rieties (Fig. 2A). To evaluate photosynthetic competence, we measured the F v/F m ratio reprenting the efficiency of PSII, becau photosynthesis depends on the function of light-harvesting and electron transport systems within the chloroplasts. SNU-SG1 maintained values of F v/F m clo
86 QTLs for Functional Stay-Green Rice
Table 1. The status of the populations ud in this study.
F 2 population
RIL population Cross a
No. of progeny b
Selected progeny c
No. of progeny
Selected progeny
Purpo Cross Type d
SNU-SG1/M23 235 46 425 92 Mapping japonica /tongil
SNU-SG1/Ilpum 252 - - - Phenotyping japonica /japonica
a M23, Milyang23; Ilpum, Ilpumbyeo.
b
No. of progeny: total number of progeny in the population. c
Selected progeny, the number of progeny ud for map construction. d
tongil , a hybrid rice cultivar of japonica and indica.
Table 2. Descriptive statistics for the stay-green traits in the parents and F 1s of the two cross. SNU-SG1/M23b SNU-SG1/Ilpumbyeo
Trait a
SNU-SG1 M23 F 1 SNU-SG1 Ilpumbyeo F 1
DCF 46.3 ± 1.3 39.2 ± 2.0 38.6 ± 3.1 46.1 ± 1.6 39.0 ± 3.3 41.9 ± 2.0 DCS 46.7 ± 1.5 38.6 ± 1.9 37.8 ± 2.8 47.1 ± 1.4 39.7 ± 2.0 43.6 ± 1.8 DCFS
46.5 ± 1.3
38.9 ± 1.9 38.2 ± 2.9 46.6 ± 1.3 39.2 ± 2.6 42.8 ± 1.9 CCF 132.8 ± 3.4 94.8 ± 5.4 99.4 ± 5.0 131.6 ± 3.2 101.2 ± 8.1 115.5 ± 9.9 CCS 133.0 ± 5.2 91.3 ± 6.9 96.3 ± 3.0 131.9 ± 4.3 104.1 ± 5.7 115.2 ± 6.4 CCFS 132.9 ± 4.3
93.0 ± 6.1
97.9 ± 4.0
131.8 ± 3.8
102.7 ± 6.9
115.4 ± 8.2
a
DCF, degree of chlorophyll content of flag leaf at the heading date; DCS, degree of chlorophyll content of the cond leaf at the heading
date; DCFS, degree of mean chlorophyll content of the flag and cond leaves; CCF, cumulative chlorophyll content of the flag leaf; CCS, cumulative chlorophyll content of the cond leaf; CCFS, mean of cumulative chlorophyll contents of the flag and cond leaves. b
Mean ± standards deviation of SPAD readings for the parent and F 1 plants. Each pair of parents showed statistically significant differences at the 0.01 probability level.
Fig. 1. Temporal changes in leaf color during grain filling in Milyang23 (M23), SNU-SG1 and Ilpumbyeo (Ilpum). Field-grown plants were transferred to pots and photographed at head-ing (left panel), and 50 DAH (right panel). The plant color differ-ences between Milyang23, Ilpumbyeo and SNU-SG1 became significant at 50 DAH. The heading date of SNU-SG1 was 4 d earlier than Ilpumbyeo and Milyang23. DAH, days after heading.
to 0.80, which is the typical potential efficiency of PSII in non-stresd plants (Larcher, 2003), for 42 d after heading (DAH), while the values in the other two varieties de-cread rapidly after 35 DAH (Fig. 2B). Table 2 shows
the descriptive statistics of the functional stay-green traits for two parental pairs and their corresponding F 1s. Impor-tant differences were found for all traits between the par-ents. The phenotypic value of the F 1s from the SNU-SG1/Ilpumbyeo cross was near the mid-parent score, while that of the F 1s from the SNU-SG1/M23 cross was clo to that of the mapping parent M23. However, this recessive-prone pattern of the stay-green trait in the SNU-SG1/M23 cross is probably caud by environmental factors, not ge-netic factors since the heading dates of the F 1 plants in the field were delayed by about 2 weeks compared to their par-ents, as often obrved in indica /japonica hybrids. The phenotypic distributions of all traits in both the F 2 and RIL populations (Table
3) demonstrate that both populations exhibited an almost normal distribution for the stay-green trait, indicating a quantitative mode of inheritance of func-tional stay-green in SNU-SG1.
Relationship between stay-green trait and the yield and yield components The stay-green trait in SNU-SG1 was positively correlated with ed-tting rate and grain yield, but there was no significant correlation with other yield components including tillers per plant, grains per panicle, or grain weight. This indicates that the functional stay-
Soo-Cheul
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et al. 87 Table 3. Phenotypic values of parents, F1 plants, F2 populations, and RIL population for the stay-green traits studied.
SNU-SG1/M23 SNU-SG1/Ilpumbyeo
Population Trait a
Range b Mean Kurtosis Skewness Range Mean
Kurtosis
Skewness
F2 DCF
29.0−49.5 39.0 −0.63 0.04 30.8−51.738.9 0.46 0.28
DCS
28.8−53.0 39.4 −0.50 −0.02
DCFS
29.2−50.8 39.2 −0.61 0.01
CCF
70.1−146.7 108.4 −0.54 −0.01 83.9−149.4113.40 −0.07 0.08
CCS
58.8−142.1 105.0 −0.37 −0.18
CCFS
65.7−143.8 106.7 −0.49 −0.09
RIL DCF 21.8−62.3 38.3 −0.12 0.22
DCS
20.6−60.0 38.2 0.10 0.09
DCFS
21.2−61.2 38.3 −0.03 0.15
a See footnote to Table 2.
b The numbers in each of the cells indicate the range of SPAD readings.
A
B
Fig. 2. Temporal changes in chlorophyll content and photosyn-thetic competence of the parents and F1s from the two cross, SNU-SG1/Ilpumbyeo and SNU-SG1/M23. A. Changes in chlo-rophyll content of the nescing leaves. Chlorophyll content was measured with a SPAD-502 chlorophyll meter. M23: Milyang 23. B. Efficiency of PSII shown as a ratio of the variable to maximal chlorophyll a fluorescence at ambient temperature in trait in SNU-SG1 contributes to incread grain yield by enhancing ed-tting rates (Table 4).
Linkage maps of F2 and RIL populations A total of 145 polymorphic SSR primer ts, out of 250 ts applied, were polymorphic between SNU-SG1 and M23, and 100 and 116 SSR loci in the F2 and RIL populations, respec-tively, with a good coverage of all 12 chromosomes, were lected to assay the entire population. A linkage map of 100 SSR markers in the F2 population in 12 linkage groups was constructed using Mapmaker 3.0 (data not shown). The map covered 1301.9 cM with an average distance of 13 cM between markers, which is less than the minimum required level, 20 cM, for QTL mapping (Lan-der and Botstein, 1989). In the RIL population, a linkage map of 116 SSR markers was constructed in 12 linkage groups, which spanned 976.3 cM with an average interval of 8.4 cM between adjacent markers (data not shown). Comparison between the resulting linkage map
s and the previous maps (Temnykh et al., 2000) revealed that al-most all of the markers were located in the expected order on the twelve chromosomes.
Degree of chlorophyll content at the heading date in the F2 population Interval mapping identified a total of eight main-effect QTLs over the LOD thresholds that were raid through permutation test p = 0.05 (Table 5 and Fig. 3) for the traits that were associated with chloro-phyll content at the heading date across the 12 chromo-somes. Two QTLs, dcf3 and dcf9, were detected for DCF on chromosomes 3 and 9, respectively, and only one QTL was detected for DCS on chromosome 3. For DCFS, the trait derived from the mean of DCF and DCS, five QTLs were independently resolved on five chromosomes. At all of the QTLs, the alleles from SNU-SG1 genotype had a positive effect on the three traits (DCF, DCS and DCFS),
88 QTLs for Functional Stay-Green Rice
Table 4. Correlations of the stay-green traits with yield and yield-component traits analyzed in the SNU-SG1/Ilpumbyeo and SNU-SG1/M23 F 2 populations.
Traits DCF CCF Yield Tillers/plant Grains/panicle Seed tting (%)CCF 0.90** (0.91**)
Yield 0.23** 0.13* Tillers/plant 0.01 −0.04 0.63** Grains/panicle 0.01 −0.05 0.34** 0.11 Seed tting (%) 0.29** 0.24** 0.56** 0.20** 0.21**
1000 Weight −0.09 −0.18** 0.33** −0.01 0.08
0.29**
A total of 235 F 2 individual lines was ud to analyze the traits.
* and ** mean significant at P < 0.05 and P < 0.001 levels, respectively.
The figure in parenthesis gives the correlation derived from the SNU-SG1/M23 cross.
Table 5. Main-effect QTLs for the traits related to stay-green, resolved using QTL Mapper 2.0 in the F 2 population derived from the SNU-SG1/M23 cross with the LOD thresholds raid through permutation tests p = 0.05 and 0.01. Permutation e Trait QTL Chr a
Interval b
LOD A c
D c
D /A
R 2d (%)
95% 99%
DCF dcf3 3 RM282-RM251 10.36 5.33 −1.56
−0.29 13.42 3.67 4.57
dcf9
9 RM257-RM566 7.58 4.98
−0.12
−0.02 11.24
Total 24.66
DCS dcs3 3 RM16-RM282 7.74 5.16 −1.10 −0.21 14.20 3.73 4.56 Total 14.20 DCFS dcfs1 1 RM24-RM9 4.70 2.41 −1.75 −0.73 3.56 3.64 4.61 dcfs3 3 RM282-RM251 8.77 4.58 −1.16 −0.25 10.52 dcfs6 6 RM253-RM587 4.70 −3.13 0.71 −0.23 4.88 dcfs7 7 RM455-RM10 3.85 3.67 −0.68 −0.19 6.65 dcfs9 9 RM257-RM566 9.59 5.20 0.10 0.02 13.14
Total 38.75
CCF ccf3a 3 RM3867-S03136 6.59 14.33 −5.66 −0.39 6.26 3.70 4.38 ccf3b 3 RM16-RM282 12.34 23.72 −2.23 −0.09 15.99 Total 22.25
CCS ccs3 3 RM282-RM251 9.04 15.08 −1.10 −0.07 13.92 3.70 4.55 ccs6 6 RM253-RM587 4.60 −9.76 −2.22 0.23 5.96
ccs9
9 RM257-RM566 5.61 12.54 −0.82
−0.07 9.62
Total 29.50
CCFS ccfs3 3 RM16-RM282 12.23 22.59 −2.09 −0.09 36.45 3.66 4.55 ccfs9 9 RM257-RM566 4.85 11.53 0.27 0.02 9.45
Total 45.90
a,b Chromosome number and marker intervals.
c
A and D are additive and dominant effects, and the positive values indicate the alleles from SNU-SG1 that increa the trait score. d
Phenotypic variation rate explained by the detected QTLs for each trait. Bold letters indicate the QTLs detected in both populations. e
The numbers in each of the cells indicate the LOD thresholds that are raid through permutation tests p = 0.05 and 0.01.
except for dcfs6, at which the Milyang23 genotype con-tributed to incread DCFS. The additive effect of the QTLs ranged from 2.41 to 5.33 SPAD units for the three traits. Taken together, the QTLs explained 24.7, 14.2 and 38.8% of the phenotypic variation for DCF, DCS and
DCFS, respectively. A total of ven digenic interactions were also detected for the three traits (Table 6). Six of the ven pairs involved loci with at least one significant QTL main-effect. Overall, the epistatic effects accounted for 68.9, 40.9 and 81.1% of the total phenotypic variation
