Euphytica (2007) 157:35–43 DOI 10.1007/s10681-007-9394-6
Detection of quantitative trait locus for leaffolder (Cnaphalocrocis medinalis (Guene´e)) resistance in rice on linkage group 1 based on damage score and flag leaf width K. Selvaraju Æ P. Shanmugasundaram Æ S. Mohankumar Æ M. Asaithambi Æ R. Balasaraswathi
Received: 10 September 2006 / Accepted: 1 March 2007 / Published online: 30 March 2007 Ó Springer Science+Business Media B.V. 2007
Abstract Rice leaffolder (RLF) (Cnaphalocrocis medinalis (Guene´e) is a destructive and widespread insect pest throughout the rice growing regions in Asia. The genetics of resistance to RLF in rice is very complex and not thoroughly explored. The present study was conducted to detect the quantitative trait loci (QTL) associated with RLF resistance involving 176 recombinant inbred lines (RILs) of F8 generation derived from a cross between IR36, a leaffolder susceptible variety and TNAULFR831311, a moderately resistant indica rice culture. Simple sequence repeat (SSR) markers were used to construct specific linkage groups of rice. All the RILs were screened to assess their level of resistance to RLF by measuring the leaf area damaged. Besides this, the length and width of the flag leaf of each RIL were measured since these two parameters were considered as correlated traits to the RLF resistance in rice. All the above parameters observed across the RILs showed quantitative variation.
Correlation analysis revealed that damage score based on greenhouse screening was positively correlated with length and width of the flag leaf. Out of 364 SSR markers analysed, 90 were polymorphic between the parents. Multi-point analysis carried out on segregating 69 SSR marker loci linkage group wise resulted in construction of linkage map with eleven groups of 42 SSR markers. Through single marker analysis, 19 SSR markers were found to have putative association with the three phenotypic traits studied. Of these markers, RM472 was identified as a locus having major effect on RLF resistance trait based on length of the flag leaf. Interval mapping detected two QTLs on linkage group 1. Among these QTLs, the QTL flanked by RM576– RM3412 were found to be associated with width of the flag leaf and RLF resistance. The putative SSR markers associated with leaffolder resistance identified in the present study may be one of the loci contributing resistance to RLF in rice.
K. Selvaraju P. Shanmugasundaram S. Mohankumar M. Asaithambi R. Balasaraswathi (&) Centre for Plant Molecular Biology, Tamil Nadu Agricultural University, Coimbatore 641 003, India e-mail:
[email protected]
Keywords Cnaphalocrocis medinalis Oryza sativa Quantitative trait loci Recombinant inbred lines
M. Asaithambi Faculty of Agriculture, Utsunomiya University, Utsunomiya 321-8505, Japan
Introduction Rice is the most important crop in the world with over 1.5 billion hectares under cultivation and a
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production of over 583.2 million tonnes (Anonymous 2004). It is grown in 117 countries and is a staple food for people in 39 countries, which include 2.7 billion people in Asia alone (Sardesai et al. 2001). With a projected increase in world population to 10 billion over the next four decades, an immediate priority is to achieve maximum production in rice in a manner that is environmentally sustainable and cost-effective. Major rice insect pests that cause huge economic loss in Asia are stem borer, rice bug, leaffolder, leaf and planthopper and gall midge (Sardesai et al. 2001). Among these insect pests, the leaffolder emerged as a major pest in the tropical Asia during green revolution of the 1960s (Gallagher et al. 1994). Among the eight leaffolder species recorded in India, Cnaphalocrocis medinalis (Guene´e) was the most widely spread and the damage due to this species ranged from 18.3% to 58.4% (Ramasamy and Jaliecksono 1996) depending on the stage of the crop at the time of infestation. About 5% of total rice growing area of world was affected by rice leaffolder (RLF) and the loss in yield was estimated to be around 4.8 kg/ha, which in economic terms leads to a loss of $22.4 million (Herdt 1991). Conventional control of insect pests in rice cultivation often depends upon the use of chemical insecticides, which attracts concern on food safety and environmental pollution. In this context, host-plant resistance (HPR) can play a viable alternative to chemical control methods (Khush and Brar 1991). Painter (1951) classified natural resistance to insect pest interactions into three categories viz., non-preference (antixenosis), antibiosis and tolerance. Among these, antixenotic resistance is due to plant characteristics including morphological, physical or structural qualities and biochemical factors that interfere with insect behaviour such as settling, mating, oviposition, feeding and food ingestion. Several plant morphological characters like flag leaf length and flag leaf width are also associated with RLF infestation (Dakshayani et al. 1993). With the advent of DNA markers, it became possible to construct saturated genetic maps and to locate genes/quantitative trait loci (QTL) for numerous phenotypes in plants. DNA markers can be used to dissect quantitative traits into
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discrete genetic loci with their individual effect on the phenotype studied (Young 1996). DNA sequence variations between individuals are used as molecular tags for genetic loci associated with complex traits. Among the various marker systems, microsatellites have been exploited in genetic map construction and QTL mapping in various crops (Roy et al. 1999; Bachman et al. 1999; Ni et al. 2001). In our earlier studies, RAPD markers linked to leaffolder resistance trait were converted as SCAR markers and mapped on to linkage groups 1, 7 and 10. Hence these 3 linkage groups were concentrated in the present study (Unpublished data). Along with these three linkage groups, other two linkage groups viz., 9 and 11 were also targeted in this genetic map construction because many insect resistance genes have been reported to be present in these two linkage groups (Su et al. 2005). Hence Considering the frequent incidence and loss in rice yield due to Cnaphalocrocis medinalis the present study was conducted to detect the genomic regions associated with resistance to RLF using simple sequence repeat (SSR) markers.
Materials and methods Plant materials A set of 176 recombinant inbred lines (RILs) developed from a cross between IR36 (indica, susceptible to RLF), and TNAULFR831311 (indica, moderately resistant to RLF), a prerelease rice culture of Tamil Nadu Agricultural University (TNAU), Coimbatore, India was selected for this study. The true F1 s obtained from IR36/TNAULFR831311 was identified and advanced upto F8 generation by single seed descent method. The field experiments were conducted during 2003 at Paddy Breeding Station (PBS), TNAU, Coimbatore. Evaluation of RILs for RLF resistance Phenotyping of the parents and RILs for RLF resistance was conducted in the entomology section at Paddy Breeding Station (PBS), TNAU, Coimbatore from August 2003 to March 2004. In
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greenhouse screening method, 25 days old seedlings were planted in pots with five replications. Single seedling was maintained per pot. After 25 days of transplanting, second instar larvae were released on each plant at 5/pot and covered with a mylar cage. When the damage was 60% in the leaves of susceptible check (TN1), the area of damage in the leaves of all the test lines were measured in grades of 0–3 (Heinrichs et al. 1985). Based on the measurement the damage grade and damage scale were calculated. Along with these screening, the length and width of the flag leaf (cm) were also recorded for parents and each RIL for 10 plants in 3 replications. Molecular marker analysis A total of 364 SSR primer pairs as reported in McCouch et al. (2002) covering five linkage groups viz., 1, 7, 9, 10 and 11 were surveyed on IR36 and TNAULFR831311 to identify polymorphic markers between the parents. The RILs were surveyed with all polymorphic SSR loci. PCR conditions were maintained as described by Panaud et al. (1996). The SSR amplified products were mixed with 4 ll of loading buffer (98% formamide, 10 mM EDTA, 0.005% each of xylene cyanol and bromophenol blue as tracking dyes), denatured at 94°C for 5 min and resolved on 5% denaturing polyacrylamide gels containing 7 M urea at a constant current of 100 W. The products were detected using silver staining procedure described by Panaud et al. (1996).
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data to map distances in centimorgans. The basic statistics viz., mean, standard deviation, coefficient of variation and broad-sense heritability were worked out for all the three traits observed. Interrelationship among the traits was assessed by Pearson Correlation coefficient. A standard analysis of variance (One way ANOVA) was used to identify the mean of the groups formed based on segregation pattern of each SSR marker locus for three quantitative traits to establish phenotype marker association as suggested by Soller and Beckmann (1983) using General Linear Model (GLM) of the SAS package (SAS 2004). A significant F-test (P < 0.01) indicated segregation of marker locus with genotypic classes or with phenotype. Simple regression analysis was also performed as described by Haley and Knott (1992) using regression coefficient as a function of unknown QTL parameters. MAPMAKER/ QTL 1.1 (Lander et al. 1987) was used for interval mapping (locating the most important QTL between flanking markers by maximumlikelihood estimation) and estimating the percentage of the phenotypic variance explained by each QTL and considered a QTL to be significant if it exceeded a threshold LOD (log10- likelihood ratio) score of 2.0. One thousand permutation tests were performed using QTL Cartographer computer program software Version 2.0. (Wang et al. 2004).
Results
Statistical analysis
Phenotypic traits and their variations
v2-test was carried out to establish the expected 1:1 ratio for all the SSR loci in the F8 population. SSR loci showing higher order of segregation distortion were not included in the linkage analysis. The entire data set of markers was processed through MAPMAKER/EXP 3.0 b programme (Lander et al. 1987). Two point analyses were done involving segregating markers of each linkage group to establish the linkage between the markers. Multi-point analysis was carried out to construct the genetic map for the linkage groups 1, 7, 9, 10 and 11. The Kosambi mapping function (Kosambi 1944) was used to convert recombination
One hundred and seventy six randomly selected RILs were screened to assess the level of resistance to RLF. Resistance was directly assessed based on damage score in greenhouse screening and as an indirect assessment, the length and width of the flag leaf were recorded in parents and each of the RILs. The parents and RILs exhibited wider variation for all the traits studied. The mean, standard deviation, coefficient of variation and broad-sense heritability for above parameters are presented in Table 1. The broad sense heritability estimated for the damage score in greenhouse screening, the length and width of the flag
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Table 1 Variation for the phenotypic traits among F8 RILs Morphological traits
Damage score based on green house screening (0–9 scale) Length of the flag leaf (cm) Width of the flag leaf (cm)
IR36 TNAULFR 831311
9
5
31 1.6
23.4 1.2
RILs Mean Range
GCV PCV h2
CV (%)
SE
22.14
0.98 20.25 30.00 0.455
29.68 18.00–48.33 16.18 1.21 0.90–1.73 11.62
3.92 15.81 22.62 0.488 0.11 12.90 17.36 0.552
7.03
2.60–9.00
CV—Coefficient of variation, SE—Standard error, GCV—Genotypic coefficient of variance, PCV—Phenotypic coefficient of variance, h2—Broad-sense heritability
leaf was 0.455, 0.488 and 0.552 respectively. Transgressive segregation was noticed for all the above parameters across the 176 RILs. Under greenhouse condition, the damage score of parents viz., IR36 and TNAULFR831311 were recorded as 9.0 and 5.0 respectively. The damage score of RILs ranged from 2.6 to 9.00. Out of 176 RILs screened, one RIL was found to be resistant with a score of 2.6. Twenty eight RILs were moderately resistant with damage scale between 3 and 5, 50 RILs were found to be susceptible with a damage score between of 5.1 and 7 while the remaining 97 RILs were scored as highly susceptible with a damage score >7. The frequency distribution of RILs based on their damage scores, flag leaf length and width are shown in Fig. 1. The flag leaf-lengths were 31.0 cm and 23.4 cm respectively for IR36 and TNAULFR831311. The RILs showed a high level of variation for flag leaf length (18–48.33 cm). The width of flag leaves were 1.6 cm and 1.2 cm respectively for IR36 and TNAULFR83131. The RILs exhibited a high level of variation for width of the flag leaf (0.90– 1.73 cm). A positive correlation was seen between damage score in greenhouse screening and length and width of the flag leaf (Table 2). Linkage map construction Out of 364 SSR markers, 90 markers produced polymorphism in the 5 linkage groups showing 24.72% polymorphism between parents. These, 90 markers (28 markers on linkage group 1, 20 markers on linkage group 7, 17 markers each on linkage groups 9 and 10 and 8 markers on linkage group 11) were surveyed on 176 RILs to establish their segregation pattern.
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Fig. 1 Frequency distribution of RILs based on damage in greenhouse screening, length of the flag leaf and width of the flag leaf
Out of these 90 marker loci belonging to 5 linkage groups viz., 1, 7, 9, 10 and 11, only 31 marker loci (34.44%) showed the expected segregation ratio of 1:1 based on v2-test at 0.05 per cent and the remaining 59 marker loci (65.56%) exhibited segregation distortion across the RILs analysed. Among the 59 markers, 42 markers (71.19%) skewed towards TNAULFR831311 and 17 markers (28.81%) exhibited segregation distortion towards IR36. Among these marker loci, the loci on linkage groups 1, 7 and 9 showed skewness towards TNAULFR831311 whereas
Euphytica (2007) 157:35–43 Table 2 Correlation between the different phenotypic traits among RILs
** Significant at 1% level * Significant at 5% level
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Traits
Damage score based on green house screening (0–9 scale)
Damage score based on green house screening (0–9 scale) Length of the flag leaf (cm) Width of the flag leaf (cm)
1
loci on linkage group 10 and 11 had alleles skewed towards IR36. Sixty-nine out of 90 SSR loci showed linkage in two point analysis which includes 21 markers on linkage group 1, 15 each on linkage group 7 and 9, 13 on linkage group 10 and 5 on linkage group 11. Multipoint analysis of the segregating marker data using MAPMAKER/EXP 3.0 b programme resulted in the construction of 11 groups of 42 markers. Of these 42 SSR loci, 11 belonged to linkage group 1, 13 belonged to linkage group 7, 8 belonged to linkage group 9, 7 belonged to linkage group 10 and 3 belonged to linkage group 11. QTL detection One way ANOVA was performed to establish the marker-phenotype association which resulted in
0.197* 0.238**
Length of the flag leaf (cm)
Width of the flag leaf (cm)
1 0.392**
1
the identification of 19 SSR markers putatively associated with the three quantitative traits studied. A simple regression analysis was also performed by keeping phenotypic values as independent variables. The results of one way ANOVA and regression analysis for establishing marker phenotype association are presented (Table 3). One SSR marker, RM3412 on linkage group 1 was found to be associated with RLF resistance based on the damage score in greenhouse screening. Eight markers viz., RM220, RM9, RM297, RM212, RM543, RM472, RM244 and RM496 exhibited significant association with the length of the flag leaf. Of these, RM220, RM9, RM297, RM212, RM543 and RM472 are distributed on linkage group 1 and RM244 and RM496 are distributed on linkage group 10. Out of these eight markers, RM472 recorded the highest sig-
Table 3 Putative chromosomal locations of QTLs for phenotypic traits associated with RLF resistance based on single marker analysis Traits
SSR marker
Linkage group No
F value
R2 value
Probability
Damage score based on green house screening Length of the flag leaf
RM3412 RM220 RM9 RM297 RM212 RM543 RM472 RM244 RM496 RM495 RM600 RM576 RM3412 RM14 RM5100 RM5405 RM5380 RM3691 RM6867 RM228
1 1 1 1 1 1 1 10 10 1 1 1 1 1 7 7 7 7 9 10
7.49** 6.32** 14.27** 21.86** 15.19** 20.56** 57.60** 7.22** 7.75** 6.53** 6.89** 8.42** 10.99** 8.93** 13.28** 7.42** 8.27** 9.52** 7.14** 10.68**
0.0432 0.0373 0.0814 0.1134 0.0820 0.1090 0.2542 0.0422 0.0434 0.0374 0.0421 0.0485 0.0621 0.0523 0.0771 0.0411 0.0459 0.0558 0.0417 0.1010
0.01 0.01 0.00
