Substitutional Mapping the Cooked Rice Elongation by Using Chromosome Segment Substitution Lines in Rice 
Dewei Yang1,2 
,
Yadong Zhang1 ,
Zhen Zhu1 ,
Tao Chen1 ,
Qingyong Zhao1 ,
Shu Yao1 ,
Ling Zhao1 ,
Wenyin Zhu1 ,
Cailin Wang1 
,
Yadong Zhang1 ,
Zhen Zhu1 ,
Tao Chen1 ,
Qingyong Zhao1 ,
Shu Yao1 ,
Ling Zhao1 ,
Wenyin Zhu1 ,
Cailin Wang1
1. Institute of Food Crops, Jiangsu Academy of Agricultural Sciences/ Jiangsu High Quality Rice Research & Development Center/Nanjing Branch of China National Center for Rice Improvement, Nanjing 210014, China
2. Institute of Rice, Fujian Academy of Agricultural Sciences, Fuzhou 350019, Fujian, China
Author Correspondence author
Molecular Plant Breeding, 2013, Vol. 4, No. 13 doi: 10.5376/mpb.2013.04.0013
Received: 23 Feb., 2013 Accepted: 04 Mar., 2013 Published: 31 Mar., 2013
2. Institute of Rice, Fujian Academy of Agricultural Sciences, Fuzhou 350019, Fujian, China
Author Correspondence author
Molecular Plant Breeding, 2013, Vol. 4, No. 13 doi: 10.5376/mpb.2013.04.0013
Received: 23 Feb., 2013 Accepted: 04 Mar., 2013 Published: 31 Mar., 2013
© 2013 BioPublisher Publishing Platform
This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Preferred citation for this article:
Yang et al., 2013, Substitutional Mapping the Cooked Rice Elongation by Using Chromosome Segment Substitution Lines in Rice, Molecular Plant Breeding, Vol.4, No.13 107-115 (doi: 10.5376/mpb.2013.04.0013)
Abstract
The elongation of the cooked grain is very important trait in determining the quality of cooked rice grain. In this study, 103 chromosome segment substitution lines (CSSLs) derived from 93-11/Nipponbare, an elite variety 93-11 as the recurrent parent, were used to identify quantitative trait locus (QTL) controlling milled rice length (MRL), cooked rice length (CRL), and cooked rice elongation (CRE). In total, 12 QTLs for rice elongation traits were detected on chromosomes 3, 4, 6, 8, 9, 10, and 11, among which two QTLs for MRL were located on chromosome 3, one QTL for MRL on chromosome 8, four QTLs for CRL on chromosome 3, 6, 8, and 9, and five QTLs for CRE on chromosome 4, 6, 9, 10, and 11. The additive effect of the QTL related to rice elongation ranged from -5.80 to -0.14, and the additive effect percentage of the QTL ranged from -12.26% to -1.72%. Furthermore, eight QTLs were mapped in interval less than 10.0 cM. Particularly, the qCRE-6 located in the region close to the Wx gene might be important for CRE trait, which might be primarily mapped by using CSSLS as well as could be applied in rice quality improvement based on approaches of marker-assisted selection (MAS).
Keywords
Rice (Oryza sativa L.); Chromosome segment substitution lines (CSSLs); Substitutional mapping; Cooked rice elongation; Quantitative trait locus (QTL)
Rice is considered to be one of the most important cereal crops, as it is the staple food for almost half of the world’s population. In recent years, there has been a growing interest from many rice-producing countries on improving the cooking and eating quality, two of the most important components of grain quality of rice (Juliano 1985; Unnevehr et al., 1992; Ge et al., 2005).
In the best-quality grain, the kernel elongates but its width changes little during cooking (Khush et al., 1979, which has been associated with the Basmati type (Sood et al., 1979; 1983; Ahn et al., 1993), an important commercial commodity mainly found in India, Pakistan, and Thailand (Khush et al., 1979).
For cooked rice grain quality, greater CRE was associated with high-quality rice varieties (Tang et al., 1987). Some previous studies had performed genetic analyses andgene mapping of these cooked rice properties. By studying a collection of upland rice varieties, Hussain et al (1987) found that CRE had rather high broad-sense heritability, suggesting it is more difficult to improve CRE genetically than for either milked rice length or cooked rice length. Bao et al(2001) confirmed that CRE phenotypes are dependent on a small number of major genes.Ahn et al mapped a major CRE QTL on chromosome 8 in Oryza sativa‘Basmati 370’, and consequently Li et al (2004) detected a second CRE QTL on chromosome 3. Chromosome 2, 5, 6, and 7 were found to exert further effects on CRE (Shen et al., 2005), and a CRE QTL closely associated with Wx gene on chromosome 6 had also been described by researchers (He et al., 2003; Zhang et al., 2004; Ge et al., 2005; Tian et al., 2005). In addition, Amarawathi et al (2008) used a RIL population to detectone QTL for CRE on chromosome 11. With these populations, such as F2, F2/F3, BC1, DH, and RIL, it was difficult to differentiate QTLs,especially ones that have small and/or interacting effects from background noise (Eshed and Zamir, 1995).
For cooked rice grain quality, greater CRE was associated with high-quality rice varieties (Tang et al., 1987). Some previous studies had performed genetic analyses andgene mapping of these cooked rice properties. By studying a collection of upland rice varieties, Hussain et al (1987) found that CRE had rather high broad-sense heritability, suggesting it is more difficult to improve CRE genetically than for either milked rice length or cooked rice length. Bao et al(2001) confirmed that CRE phenotypes are dependent on a small number of major genes.Ahn et al mapped a major CRE QTL on chromosome 8 in Oryza sativa‘Basmati 370’, and consequently Li et al (2004) detected a second CRE QTL on chromosome 3. Chromosome 2, 5, 6, and 7 were found to exert further effects on CRE (Shen et al., 2005), and a CRE QTL closely associated with Wx gene on chromosome 6 had also been described by researchers (He et al., 2003; Zhang et al., 2004; Ge et al., 2005; Tian et al., 2005). In addition, Amarawathi et al (2008) used a RIL population to detectone QTL for CRE on chromosome 11. With these populations, such as F2, F2/F3, BC1, DH, and RIL, it was difficult to differentiate QTLs,especially ones that have small and/or interacting effects from background noise (Eshed and Zamir, 1995).
Eshed and Zamir (1995) proposed to apply introgression line (IL)populations so that a high-resolution mapping of QTLs can be achieved. Several permanent mapping populations in rice, such as CSSLs and backcross inbred lines (BILs), had been developed (Aida et al., 1997; Kubo et al., 1999; Xiao et al., 2005). For CSSLs, each chromosome segment substitution line (CSSL) carried a single or fewer donor segments in the background of a recurrent genotype. Interactions between donor alleles were limited to those genes on homozygous substituted tracts, thus reducing the effects of interferences from genetic background (Howell et al., 1996; Yano, 2001). Several CSSLs in rice had been developed and a lot of QTLs for traits with biological and economic interest had been detected through these CSSLs by various researchers (Kubo et al., 2002; Ebitani et al., 2005; Mei et al., 2006; Takai et al., 2007; Ye et al., 2010; Li et al., 2011; Ujiie et al., 2012; Marzougui et al., 2012). However, few studies have performed genetic analyses for CRE using CSSLs. Therefore, the objective of this study is to find specific QTLs for CRE using CSSLs, These QTLs should be helpful in marker-assisted selection (MAS) of high eating quality rice varieties and map-based cloning of desirable QTLs.
1 Results
1.1 Characteristics of the CSSLs
The substituted chromosome segments in the CSSLs covered most of the 12 chromosomes. Each line contained a substituted segment of a particular chromosomal region and additional small segments in non-target regions. If we assume that recombination occurred midway between two adjacent markers, the estimated length of the substituted segments in 103 CSSLs ranged from a minimum 1.4 cM to a maximum 79.2 cM, and had an average of 25.2 cM. The total length of the substituted segments in the CSSLs population was 2590.6 cM, which was 1.7 times that of rice genome (Zhu et al., 2009).
1.2 Traits of MRL, CRL, and CRE in parents
As illustrated in Table 1, significant phenotypic differences were detected between the parents for MRL, CRL, and CRE (t-test, P<0.01), and 93-11 showed higher level in three traits compared with Nipponbare, which indicated the approach used to evaluate the three traits in this study was valid.
.png){kind=small} Table 1 Differences of the parents among MRL, CRL, and CRE
|
1.3 Analysis of Quantitative trait loci
In total, three QTLs for MRL, designated as qMRL-3-1, qMRL-3-2, qMRL-8, were detected based on the difference oft-testbetween the mean of each CSSL and 93-11 and the additive effect ranged from -0.41 to -0.14. The QTL qMRL-3-1, with the largest effect, was located in the interval between RM6832 and RM3513 on chromosome 3. For all the three QTLs, the alleles from Nipponbare had negative effects (Table 2; Figure 1).
.png) Table 2 QTLs and their additive effect on the substituted segments in CSSLs for MRL, CRL, and CRE |
.png) Figure 1 Genetic map and chromosomal location of QTLs for MRL, CRL and CRE in rice. |
Four QTLs for CRL, qCRL-3-2, qCRL-6, qCRL-8, and qCRL-9, were detected based on the difference oft-testbetween the mean of each CSSL and 93-11, ranging from -0.41 to -0.16 for the additive effect. The QTL qCRL-6, with the largest effect, was located in the interval between RM508 and RM510 on chromosome 6. Similarly, the alleles from Nipponbare had negative effects for all four QTLs (Table 2; Figure 1).
Five QTLs for CRE, designated as qCRE-4, qCRE-6, qCRE-9, qCRE-10,and qCRE-11, were detected based on the difference oft-testbetween the mean of each CSSL and 93-11, and the rangeof the additive effect was from -5.80 to -2.82. The QTL qCRE-6with the largest effect was in the same region with Wx locus and located in the interval between RM508 and RM510 on chromosome 6. In the same way, for all five QTLs, the alleles from Nipponbare also had negative effects (Table 2; Figure 1).
1.4 Substitutional mapping QTLs
To map these QTLs, the substitution mapping was performed according to the method described by Wissuwa et al (2002). Using 5 CSSLs, qMRL-3-1 was mapped in the marker interval RM5551-RM6931, which spanned 8.5 cM in genetic distance on chromosome 3, while qMRL-3-2 and qCRL-3-2 were simultaneously located in the marker interval RM6832-RM3513, with the genetic distance of 5.3 cM (Figure 2A). Using CSSL43 and CSSL41, qCRE-4 was mapped in the marker interval RM5709-RM280 on chromosome 4 at the genetic distance of 9.5 cM ( Figure 2B). Using CSSL53 and CSSL52, qCRL-6 and qCRE-6 were both located in the marker interval RM508-RM510 on chromosome 6, and the genetic distance was 4.6 cM (Figure 2C). Using CSSL72, CSSL73, and CSSL74, qMRL-8 and qCRL-8 were located in the same marker interval RM4085-RM3395 on chromosome 8, which spanned 8.6 cM in genetic distance (Figure 2D). Using CSSL81 and CSSL83, qCRL-9 and qCRE-9 were simultaneously mapped in the marker interval RM566-RM242 on rice chromosome 9 at the genetic distance of 10.7 cM (Figure 2E). Using 5 CSSLs, qCRE-10 and qCRE-11 were respectively located in the marker interval RM8201-RM1108 on chromosome 10 and RM5349- RM2136 on chromosome 11, with the genetic distance of 14.3 cM and 27.9 cM (Figure 2F; Figure 2G).
2 Discussion
.png) Figure 2 Substitutional mapping QTLs for MRL, CRL and CRE in rice
|
2 Discussion
2.1 QTLs detected through CSSLs
In this study, we used CSSLs and the substitution mapping method to analyze additive effects of QTLs on MRL, CRL, and CRE in rice. Since each CSSL used in this study contains only one substituted segment from a donor in 93-11 genetic background, all the genetic variation between each CSSL and 93-11 was contributed by the substituted segment, thus providing more reliable QTL detection and estimation of QTL effects by minimizing the background genetic effects and. In addition, the smaller substituted chromosome segments in the CSSLs will facilitate the detection of QTLs in rice. Further experiments need to be conducted to detect QTLs elsewhere in the genome and/or determine whether some segments contained more than one QTL, as the substituted chromosome segments used in this study did not include the whole genome.
2.2 Three QTLs controlling CRE might be novel
QTLs affecting CRE were detected on all chromosomes except chromosome 9 in previous studies. We did not detect a major QTL on chromosome 8 associated with cooked kernel elongation of rice in this study as previously reported by Ahn et al., which was possibly due to the presence of a genomic segment introgression from Basmati 370 (a famous variety with more than 100% elongation in length and with little increase in width after cooking) in the germplasm used in their study. Zhang et al (2004) used a DH population to identify five QTLs for CRE on chromosome 1, 3, 5, 6, and 10, respectively. One QTL for CRE was mapped to the same region on chromosome 2 using different populations (Ge et al., 2005; Liu et al., 2008), while another CRE QTL was located in the marker interval RM301-RM29 on chromosome 2 using a DH population (Tian et al., 2005). Liu et al (2008) detected three CRE QTLs on chromosome 4, 5, and 12, respectively, and the qCRE-4 on chromosome 4 near qER-4 was detected in this study. Li et al (2004) mapped a CRE QTL on chromosome 3, with the favorable allele obtained from the African rice O. glaberrima. Using a RIL population, Wang et al (2007) identified four CRE QTLs on chromosome 3, 6, 7, and 8, respectively. Interestingly, a CRE QTL on chromosome 6 closely linked to the Wx gene had been simultaneously described by previous researches (He et al., 2003;Zhang et al., 2004; Ge et al., 2005; Tian et al., 2005). In this paper, the qCRE-6 with the largest effect was located in the near region with the Waxy gene on chromosome 6 (Figure 3), and the Waxy gene region played an important role in CRE.Recently, Amarawathi et al (2008) detected one QTL for CRE on chromosome 11 using a RIL population. Two QTLs on chromosomes 4 and 6 detected here were likely in common with QTLs detected in previous studies, but other QTLs (qCRE-9, qCRE-10, and qCRE-11) detected here had not been reported (Zhang et al., 2004; Tian et al., 2005; Liu et al., 2008; Amarawathi et al., 2008).
2.3 Pleiotropic QTLs in same location
.png) Figure 3 Comparison between the results in this study and in previous researches |
2.3 Pleiotropic QTLs in same location
Some QTLs affecting MRL, CRL, and CRE were mapped to the same genome regions (Figure 1). For example, the QTL clusters corresponding to the Wx locus simultaneously controlled CRE and CRL, and the locus controlling MRL and CRL simultaneously were both detected on chromosomes 3 and 8. Co-localization of these QTLs, affected by pleiotropic or close linkage may explain the genetic basis for correlations among various quality traits. Therefore, further genetic studies, such as fine mapping of these QTLs, which are required to determine the actual number of distinct QTLs in these regions and to elucidate the genetic mechanism of the co-localization are currently underway in secondary F2 populations derived from crosses between target CSSLs and 93-11.
2.4 Genetic Improvement of cooked rice elongation
Our results have clearly demonstrated that the region of waxy gene plays a major role in determining the CRE. The presence of closely linked markers on the side of the Wx locus will greatly facilitate the precise replacement of the alleles of the poor-quality parent using MAS. Wx alleles in donor parent a specialty Japonica with low MRL, low CRL, and low CRE, are used to replace alleles from the recipient parent 93-11, a specialty Indica rice cultivar in China with high MRL, high CRL, and high CRE (Table 1). Cooked recombinant rice stayed tender and slender, suggesting93-11 could be a desirable parent for improving the quality of rice by introducing its Wx alleles into the breeding lines.
3 Materials and methods
3.1 Developing the CSSLs
The strategy for the development of the CSSLs is shown in Figure 4. Rice cultivar 93-11 was crossed with Nipponbare, and a resultant F1 plant was backcrossed to 93-11 to produce BC1F1, which were again backcrossed with 93-11 to produce BC2F1. Subsequently, 135 BC3F1 lines were obtained from 1500 BC4F1 individuals.In addition, 230 SSR markers selected from dense rice microsatellite maps (McCouch et al., 2002) were used to detect the polymorphism between 93-11 and Nipponbare. A whole-genome survey of the 1500 BC4F1 using the polymorphic markers identified 139 plants with most of their genomic regions homozygous of 93-11, and these plants were self-crossed to produce BC4F2 segregation populations. Finally, a total of 103 CSSLs were selected in 6192 BC4F2 plants with MAS (Zhu et al.,2008).
.png) Figure 4 Breeding strategy for developing CSSLs carrying Nipponbare segments in the genetic background of 93-11
|
3.2 Plant materials used in this research
The population used in this study consisted of 103 CSSLs, each line and both parent plants were field-grown in Jiangsu Academy of Agricultural Sciences (Nanjing, China) in 2008. Field management essentially followed normal agricultural practice. Before conducting quality analysis, all seeds samples were stored at room temperature for a period of at least 3 months after being harvested.
3.3 Assay of cooked rice elongation
The analysis of CRE was performed according to the method described by Wang et al(2007) with slight modifications. Ten intact milled grains were selected randomly from each CSSL and measured for MRL. The grains were soaked in distilled water for 30 min, which were then placed between two pieces of wet ï¬lter paper in a petridish filled with an appropriate amount of water. The dish was then placed in a covered container and the grains were cooked by steaming over boiling water for 10 min and simmering for 10 min (with power off). The cooked rice grain was transferred onto a piece of dry ï¬lter paper at the bottome of a fresh petridish, which was placed in a desiccator with a constant temperature (19℃). Then the CRL was measured. For repeated sample of eachCSSL, the two traits above were measured in duplicate, with values averaged over replications. TheCREwas calculated as follows: CRE = (CRL –MRL)/ MRL · 100%.
3.4 Determining the length of substituted segments in CSSLs
Rice microsatellite map was used to locate and determine the substituted segments in CSSLs (McCouch et al, 2002), the length of which was then estimated based on graphical genotypes (Young and Tanksley, 1989; Xi et al, 2006). 100% donor genotype was defined as a chromosome segment flanked by two markers of donor genotype (DD), whereas 0% donor genotype segment was flanked by 2 recipient genotype (RR) markers, and 50% donor genotype was flanked by one recipient marker (DR). Thus, the length of the substituted segments was estimated as the sum of the length of DD plus 1 half-length DR on each side.
The substituted segment was determined based on its location on rice microsatellite map. The length of substituted segments in CSSLs was estimated based on graphical genotypes. A chromosome segment flanked by two markers of donor genotype (DD) was considered as 100% donor genotype, a chromosome segment flanked by two markers of recipient genotype (RR) was considered as 0% donor genotype. A chromosome segment flanked by one marker of donor type and one marker of recipient type (DR) was considered as 50% donor type. In other words, the estimated length of a substituted segment was a sum of the length of DD and two of 1/2 length of DR both sides.
3.5 Substitutional mapping QTLs
QTLs were detected based on the difference oft-test between the mean of each CSSL and 93-11. A probability level of 0.01 was used as the threshold for the detection of a putative QTL. QTLs were named according to McCouch et al. (1997).We detected the exact QTL position by using the substitution mapping approach which was performed according to the method described by Wissuwa et al (2002). Moreover, the additive effect was estimated in accordance with the method described by Eshed et al (1995): The additive effect=phenotypic value of CSSLï¼phenotypic value of 93-11; The additive effect percentage=(the additive effect/phenotypic value of 93-11) ×100%.
Acknowledgement
This work was supported by the Key Support Program of Jiangsu Science and Technology (BE2008354) and Jiangsu Agriculture Science and Technology Innovation Fund (CX(12)1003).
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