Introduction

Genes conferring resistance to diseases can be generally classified into two categories. The first category includes the major resistance (R) genes involved in specific recognition of a pathogen as the first step in initiating the resistant response. The second category includes defence response (DR) genes that are often downstream components of the defense pathways. Together these genes act in a coordinated manner to prevent or retard the invasion of pathogens. Structural and functional analyses of many major R genes have shown that they encode proteins with similar structural motifs—nucleotide binding site (NBS), kinase domains, leucine-rich repeats (LRR)—that are responsible for ligand recognition and signal transduction (Martin et al. 1993; Bent et al. 1996; Song et al. 1995; Cai et al. 1997; Wang et al. 1999; Bai et al. 2002; Meyers et al. 2003). A large number of defence-related genes have also been isolated from different plant species that are correlated with the expression of resistance. For example, genes encoding chitinase and lipoxygenase are associated with resistance to plant diseases and insect pests (Huang et al. 1991; Schaffrath et al. 2000). Faris et al. (1999) reported a cluster of DR genes that included a catalase, a chitinase, thaumatin, and a 14-3-3 protein that had major effects on the resistance to leaf rust of wheat. They also identified two candidate genes associated with tan spot of wheat. Ramalingam et al. (2003) reported that oxalate oxidase was associated with bacterial blight resistance, while thaumatin and dihydrofolate reductase thymidylate synthase were associated with brown planthopper resistance in rice.

Resistance to rice blast caused by the fungal pathogen Magnaporthe grisea (Hebert) Barr can be controlled by a combination of qualitative and quantitative resistances. Wang et al. (1994) conducted the first comprehensive analysis of the quantitative resistance observed in Moroberekan, a traditional rice variety in Africa with a reputation for having durable resistance against blast. They used a mapping population of recombinant inbred lines (RILs) derived from Moroberekan/CO39 (a highly susceptible rice variety) to map quantitative trait loci (QTLs). Two important observations were made in this study. First, durable resistance is contributed by a combination of major genes and QTLs. Second, some QTLs with strong phenotypic effects map at regions containing major blast resistance genes (Pi), suggesting that some QTLs are possibly a manifestation of major R genes. Since then, several mapping studies have been carried out for blast resistance but because the germplasm for genetic studies were chosen for polymorphism rather than the agronomic value favoured by farmers, no useful varieties have ever been generated from such mapping populations (Naqvi et al. 1995; D.H. Chen et al. 1997, 1999).

To address the problem of mapping experiments being disconnected from breeding objectives, Tanksley and Nelson (1996) advocated the use of advanced backcross (AB) populations to simultaneously analyse QTLs and to develop elite germplasm for commercial use. Following this strategy, we have developed an AB population with the objective of introgressing useful resistance from var. Moroberekan into a high-quality variety, Vandana, widely grown in eastern India. In the original approach of AB-QTL analysis, anonymous markers across the genome were used to determine the efficiency of the procedure. Unless markers are closely linked to the target gene, recombination between the flanking markers and the target gene often leads to a low predictability of linked markers for function. We here apply candidate genes involved in the defence pathways to analyse the backcross population. We have identified candidate genes contributing to a large degree of partial resistance. Our results indicate that the marker-tagged BC3 lines are good material for increasing blast resistance in upland rice.

Materials and methods

Plant material and population development

The F1 and the BC1 generations of the cross between Vandana, an improved indica upland rice (Oryza sativa L.) variety popular in eastern India, and Moroberekan, a traditional japonica upland rice variety from Guinea, were developed in 1995 and 1996 in the Central Rainfed Upland Rice Research Station, Bihar, India. Moroberekan was used as the donor for blast resistance and Vandana, which is moderately susceptible to leaf blast and highly susceptible to neck blast, was used as the recurrent parent.

One hundred and fifty BC1 seeds were sown in the greenhouse at IRRI in 1997, and 80 plants were crossed with the recurrent parent Vandana. One BC2F1 seed per plant was used to produce the next generation, which was backcrossed again to the recurrent parent in 1998. The BC3F1 seeds were planted in the greenhouse and the selfed seeds harvested. The BC3F2 generation was advanced to the BC3F3 generation under greenhouse conditions in 1999. All of the plants were bagged during the time it required to develop the greenhouse generations to prevent cross-pollination. The 80 lines each from the BC3F3 and BC3F4 generations were evaluated under field conditions at the IRRI farm in the Philippines. Some selection pressure at maturity for similarity to var. Vandana was applied by rouging plants differing too much from the average.

Performance in blast nursery

The BC3F3 and BC3F4 generations, parents and susceptible control CO39 were planted in the blast nursery at IRRI during the wet season in 1999 and dry season in 2000. Thirty to forty seeds were sown in a row of 10×3×1 cm. The experiment was a complete randomised block design with three replications. Border rows with a mixture of cultivars were set up around each replicate to sustain a diverse pathogen population. The scoring system of lesion type was based on Bonman et al. (1986). The percentage diseased leaf area (DLA) was estimated visually following the Standard Evaluation System (SES) for rice (IRRI 1996) once a week beginning 14 days after sowing; data collected at the 4th week were used for analysis.

Based on marker analysis and the performance of the BC3F3 in blast nursery, the five most resistant lines and five most susceptible lines from BC3F4, their parents and susceptible control CO39 were evaluated in the nursery in 2000 to observe their disease progress. The experimental design and scoring system were the same as above, but the DLA was recorded every 2 days from 2 weeks after sowing until the 4th week when the plants started recovery. Six observations were made to develop the disease progress curve for each line.

Greenhouse inoculation

An isolate, PO6-6, which is virulent to var. Vandana was chosen for inoculation of the progeny. Twenty lines with 12 seeds per line were sown in 35×28×11-cm plastic trays. A complete randomised block design with three replications was used. Plants were inoculated 14 days after sowing by spraying 20 ml inoculum per tray with a standard inoculum concentration (1×105 conidia/ml). Following inoculation, the plants were moved to cages covered with moist jute sacks overnight and then transferred the following day to a mist room maintained at 28°C. The plants were misted with water three to four times each day and then scored 6–7 days after inoculation based on the system of Bonman et al. (1986). Percentage DLA was recorded as described above from ten plants for each line per replication. The number of susceptible lesions was counted from five plants for each line per replication. Lesion size was measured on five plants per line per replication.

DNA extraction and Southern blotting

Following scoring, the diseased leaves of BC3F3 plants were removed and a handful of urea was applied to the plants for regeneration of new leaves for DNA extraction. A 5-g sample of fresh leaves from ten plants was bulked for DNA extraction using the CTAB method (Murray and Thompson 1980). Seven restriction enzymes (BamHI, DraI, EcoRI, EcoRV, HindIII, XbaI and BglII) were used for parental survey of polymorphism. Southern blotting with Hybond-N+ membrane (Amersham Phamacia Biotech, Piscataway, N.J.) was performed according to the standard procedure (Sambrook et. al. 1989). Candidate gene probes were amplified using the following profile: pre-denaturation at 94°C for 4 min; 35 cycles of 94°C for 1 min, 50°C for 1 min, 72°C for 2 min; a final extension at 72°C for 5 min. Blots were detected using ECL kits according to the manufacturers’ recommendation (Amersham Phamacia Biotech). A list of candidate genes used in this experiment is shown in Table 1.

Table 1 Candidate defense gene clones used in this studya
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PCR marker genotyping

In addition to the candidate gene markers, 23 simple sequence repeat (SSR) markers were used to determine genetic relationships among the closely related lines (Table 2). PCR amplification of SSR primers (Research Genetics) was conducted as described by X. Chen et al. (1997). The products were detected using a 2.5% agarose gel or a 4% denaturing polyacrylamide gel with silver staining. Five resistance gene analogue (RGA) markers (PCR fragments amplified by primers designed from the conserved region of resistance genes) were used in the analysis (Chen et al. 1998). It has been shown that some of these markers map to chromosomal regions containing major resistance genes as well as QTLs for quantitative resistance (Shen et al. 1998; Zhuang et al. 1998; Toojinda et al. 2000; Shi et al. 2001). The five RGA primers were: RGA1F—CCG TTG GAC AGGAAG GAG; RGA1R—CCC ATA GAC CGG ACT GTT; RGA4F—TAG GGC CTC TTG CAT CGT; RGA4R—TAT AAA AAG TGC CGG ACT; RGA6F—GCA TTG GAA CAA GGT GAA; RGA6R—AGG GGG ACC ACC ACG TAG; RGA8F—ARI GCT ARI GGI ARI CC; RGA8R—GGI GGI GTI GGI AAI ACI AC; RGA14F—TTG TCA GGC CAG ATA CCC; RGA14R—GAG GAA GGA CAG GTT GCC. These were amplified based on the method described by Chen et al. (1998) with the following modifications: initial denaturation at 94°C for 4 min; 40 cycles consisting of 1 min at 94°C, 1 min at 42°C and 1.5 min at 72°C; a final extension of 8 min at 72°C. The PCR products were separated on a 4% polyacrylamide gel at 1,800 V for 2 h after a pre-run at 100 W for 1 h to reach 45–50°C before sample loading. Silver staining for the detection of DNA band patterns was performed using the method recommended by the manufacturer (Promega, Madison, Wis.). All PCR amplifications were run on a PTC-100 thermal controller (MJ Research, Waltham, Mass.).

Table 2 A list of the simple sequence repeat (SSR) markers used in this study
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Statistical analysis

To determine the genetic relationship among the lines, the numerical taxonomy and multivariate analysis system (ntsys-pc), version 1.80 (Rohlf 1993) was used for cluster analysis of BC3F3 genotypic data using simple matching coefficient and unweighted pair-group method, arithmetic mean (UPGMA). Simple and multiple regression analysis were conducted using the General Linear Model (glm) procedure in SAS (SAS Institute 1989) for test of association between candidate gene markers and phenotypes at the 0.05 and 0.01 levels of significance. Epistatic interaction between markers with significant effects was performed using the glm procedure, and a higher threshold of P=0.001 was used to declare a significant interaction. Since data without normality affects the sensitivity of QTL detection, non-parametric one-way analysis of variance (proc nariway) in SAS was also conducted on this type of data. A similar treatment of non-normal data has been reported by others (Doebley et al. 1990; Veldboom et al. 1994; Byrne et al. 1996). The proc corr procedure was used for estimating the Pearson correlation coefficient. A permutation test for simple regression analysis using SAS (version 8.2) was performed to determine the association between phenotypes and marker genotypes. Permutation was run 100 times and the topmost R2 value (P=0.01) and fifth R2 value (P=0.05) were compared with the original R2 value to determine the significance of association between marker genotype and percentage DLA in the blast nursery, percentage DLA, lesion number and lesion size measured under controlled inoculation. If the threshold values for each trait were less than the original R2 value, then the association between marker genotypes and the trait was not significant at P=0.05 or 0.01 levels.

Results

Polymorphism of candidate gene markers

A total of 50 candidate gene probes (Table 1) was surveyed for restriction fragment length polymorphism (RFLP) between vars. Vandana and Moroberekan using seven restriction enzymes. Of the 50 probes, 11 were NBS-LRRs from rice and all of these showed polymorphism between the two parents. The level of polymorphism was lower with probes of defence genes. Seven probes from other cereals, including maize and barley, gave only faint bands, thus they were not included in the progeny analysis. In total, 25 selected polymorphic probes were used for analysing the entire BC3F3 population. The candidate genes showed multiple loci, with a total of 70 bands detected by these 25 probes.

The RGA markers showed a higher degree of polymorphism between the parents than that revealed by RFLP probing with the candidate genes. All five RGA primers amplifying 60 bands showed polymorphism between the two parents. As expected, SSR markers were highly polymorphic between subspecies: 47 of the 53 SSR primers surveyed (88.7%) showed polymorphism between vars. Moroberekan and Vandana. Twenty-five markers amplified by the 23 primers listed in Table 2 were used for further analysis in this study.

Association of markers to partial resistance

We evaluated partial resistance in the BC3F3 lines by measuring percentage DLA, lesion number and lesion size against a single isolate of rice blast, PO6-6. Moroberekan showed complete resistance to PO6-6, while Vandana was moderately susceptible. Of the 80 lines tested, eight (VM14, -15, -19, -42, -46, -53, -57, -60) showed complete resistance (lesion types 1–3, Bonman et al. 1986). Distributions of percentage DLA, lesion number and lesion size are shown in Fig. 1. Among these traits, lesion number per leaf (7.79±4.11) showed the widest range of variation, followed by percentage DLA (4.60±3.98) and lesion size (3.78±1.04, in millimetres). Significant differences in DLA, lesion number and lesion size were observed among the lines. The permutation test also showed significant association between all three traits and marker genotypes at the 0.01 level of significance. In general, DLA was correlated significantly with lesion number (r=0.75) but less correlated with lesion size (r=0.48). Lesion number and lesion size were moderately correlated (r=0.56).

Fig. 1
figure 1

Distribution of percentage diseased leaf area (A), lesion number (B) and lesion size (C) in the backcross lines inoculated with rice blast isolate PO6-6

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Since resistance often results from the interaction between a resistance gene and an incompatible isolate, the effects of minor genes on quantitative resistance would be masked in the presence of major genes. To examine the contribution of candidate gene markers to partial resistance, we removed the eight lines that had been determined to be resistant to PO6-6 in the greenhouse experiment and analysed the remaining 72 lines for partial susceptibility to PO6-6.

Our analysis of DLA for BC3F3 progenies inoculated with PO6-6 suggested that four markers were significantly associated with DLA at P<0.05, of which two of these, RGA8-4 and RM215, were significant at P<0.01. Since the distribution of DLA was skewed, a non-parametric one-way analysis of variance was adopted for analysis, and this confirmed the significance of these two markers (see Materials and methods). RGA8-4 explained 11.8% and RM215 explained 9.2% of the phenotypic variation (Table 3). No epistatic interaction between these markers was observed for this trait.

Table 3 Molecular markers associated with partial blast resistance to PO 6-6 in the BC3F3 lines
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Nine markers contributed to the variation for lesion number (P<0.05). Among these, five markers, including two candidate genes (oxalate oxidase and 14-3-3 protein), two SSRs (RM21 and RM168) and one RGA marker, were highly significant (Table 3). These five markers explained from 9.1% to 28.7% of the phenotypic variation. Together, they contributed 56.4% of the total variation in the model. No epistatic interaction was found among these markers contributing to lesion number.

Seven markers were significantly associated with a reduction in lesion size at the P=0.05 level, while only RM250 was highly significant at P=0.01 (Table 3). The best-fit model for these seven markers explained 34.5% of the total variation. RM250 accounted for 9.6% of the phenotypic variation.

Disease reaction in the blast nursery

To test whether the performance of the lines against a single isolate could be correlated with that in the field, both the BC3F3 and BC3F4 populations were evaluated in IRRI blast nursery where a diverse pathogen population was maintained by planting different susceptible rice genotypes in the spreader rows. In the blast nursery var. Vandana was moderately susceptible with 28.3% DLA and var. Moroberekan was highly resistant with only a few small brown spots (type I lesion). The DLA of Moroberekan was estimated to be 0.3% due to the accumulation of small lesions (see Material and methods). The DLA of 80 lines from BC3F3 and BC3F4 showed a normal distribution, ranging from 0.3% to 78.3% (Fig. 2). Transgressive segregation was observed in both the BC3F3 and BC3F4 generations where families exhibited a higher DLA than that of the susceptible parent Vandana. For example, two lines, VM34 and VM37, were the most susceptible among the 80 lines, whereas two other lines, VM14 and VM15, exhibited complete resistance. Data collected from the first 4 weeks of the experiment were used for analysis as the plants began to recover approximately 4 weeks after sowing. A significant correlation (r=0.81, P<0.01) was found between the DLAs of the BC3F3 and BC3F4 lines. On average, the BC3F4 families showed higher DLA than that of BC3F3, suggesting fixation of variation of DLA as the lines approached homozygosity.

Fig. 2
figure 2

Distribution of percentage diseased leaf area in the BC3F3 and BC3F4 populations derived from vars. Vandana/Moroberekan in the blast nursery, IRRI. A significant correlation between the diseased leaf areas was observed in two populations (r=0.81, P=0.0001)

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DLA in the greenhouse and blast nursery was moderately correlated (r=0.48, P<0.01). Both VM14 and VM15 were completely resistant in both the greenhouse and blast nursery. VM34 and VM37 were highly susceptible in the blast nursery but were moderately susceptible to PO6-6 in the greenhouse test. VM2, VM8 and VM40 were judged to be highly susceptible in tests conducted in the greenhouse and in the blast nursery.

Association of markers to DLA in blast nursery

We identified seven markers—PIC19, PIC20, 7-4F (NBS-LRR sequences from maize), PR5 (encoding a putative thaumatin), RM21, RGA1-8 and RGA6-7—that contributed to partial resistance under conditions of natural infection in the blast nursery (Table 4). Analysis of variance suggested that these seven markers individually contributed from 9.6% to 29.6% of the variation in DLA observed in BC3F3 plants, while together they accounted for 76.0% of the total variation. Epistatic interaction among markers with significant effects was tested using glm (SAS Institute). Three pairs of digenic interaction were found between PIC19/PIC20, 7-4F/PIC20 and RGA1-8/PIC20 at the P=0.001 level of significance.

Table 4 Markers associated with percentage disease leaf area (DLA) in the BC3F3 and BC3F4 lines at the blast nursery, IRRI
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Of all the 155 markers analysed, including candidate genes, RGAs and SSR markers, four candidate genes (PIC19, PIC20, 7-4F, PR5) were highly significant and ranked among the top contributors to the resistance phenotype. A single SSR marker (RM21) was found to contribute to lesion number in the greenhouse and to DLA in the blast nursery (Tables 3, 4). RGA1-10 contributed to lesion number in the greenhouse, and RGA1-8 contributed to percentage DLA in the blast nursery. These two markers were amplified from the same primers, but they apparently represent two different loci, contributing to resistance differentially under different stress conditions.

To determine whether significant marker effects detected in the BC3F3 generation were also detected in BC3F4 plants, we analysed DLA of BC3F4 plants from the blast nursery with the genotypes of the BC3F3 generation (Table 4). Markers with high effects in BC3F3 plants (PIC19, 7-4F, PIC20, PR5, RGA1-8 and RM21) were also detected in BC3F4 plants, with the effects of PIC19 and RGA1-8 increasing by 3.7% and 3.3%, respectively, while those of the other markers were reduced by 3.1% (RM21) and 6.5% (PIC20). The only marker that was not detected in BC3F4 plants was RGA6-7, which had a relatively small effect in BC3F3 generation. The data from BC3F3 and BC3F4 together indicated a strong association between specific candidate genes and DLA observed in the blast nursery.

Cluster analysis of selected lines and their resistance performance

Based on the DNA profiles of 155 bands derived from fingerprinting with candidate genes, RGAs and SSRs, all of the lines were genetically distant (less than 55% similarity) from the donor parent Moroberekan. The lines showed an average similarity of 91±8% to Vandana, as was expected in the BC3 generation. A single line, VM66 which had all of its alleles from Vandana and showed 35% DLA, was probably a selfed progeny of Vandana. Contrary to our expectation, there was no clear relationship between genotypic groups and phenotypes in the whole population (data not shown). Figure 3 shows the genetic relationships of the five most resistant and five most susceptible lines (5% DLA in the left tail and the right tail of Fig. 1) and their parents in the dendrogram. At 80% similarity level, there are four distinct groups. VM14, VM15 and var. Moroberekan, which were all highly resistant, appear as a singleton in three separate branches. Among the five resistant lines, VM15 showed complete resistance with mostly hypersensitive brown spots and resembled Moroberekan with respect to leaf morphology and plant type, whereas VM14 was resistant but genetically more similar to var. Vandana (66% similarity). The main cluster contains both partial resistance and susceptible lines, all of them resembling Vandana. VM76, VM46 and VM19 resembled Vandana with a similarity of 89%, 95% and 96%, respectively, but with an improved level of partial blast resistance in the field (Fig. 3). The five most susceptible lines (VM2, VM40, VM67, VM34 and VM37) were genetically similar (85–95%) to Vandana.

Fig. 3
figure 3

Dendrogram of five most resistant (VM14, -15, 19, -46, -76) and five most susceptible lines (VM2, -34, -37, -40, -67) based on 155 molecular markers. Moro Morobereken, Vdna Vandana. Numbers to the right of each line indicate percentage diseased leaf area

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The performance of the selected lines under natural infection was determined by planting ten representative lines from the BC3F3 generation—completely resistant lines (VM14 and VM15), partially resistant lines (VM19, VM46 and VM76), susceptible lines (VM2, VM34, VM37, VM40 and VM67), the two parents and susceptible check CO39—in the blast nursery. Disease progress curves observed over a 4-week period showed that the partially resistant lines had a low DLA and relatively slow disease development (Fig. 4). At 4 weeks after sowing, resistant lines VM14 and VM15 remained highly resistant with no susceptible lesions; the partially resistant lines had a DLA ranging from 2.7% to 9.7%, while susceptible lines had a DLA ranging from 51.7% to 91.7% and CO39 had a DLA of 81.7% (Fig. 4). The performance of these lines between the BC3F3 and BC3F4 generations was also highly correlated (r=0.93, P<0.01).

Fig. 4
figure 4

Disease progress in the five most resistant and five most susceptible lines (see Fig. 3) in the blast nursery. Moro Morobereken, Vdna Vandana, CO39 susceptible control. Numbers to the right indicate percentage diseased leaf area at 28 days after sowing

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Discussion

To improve the resistance of upland variety Vandana, a set of backcross lines was generated by introgressing resistance from a traditional variety, Moroberekan, that is known to have blast resistance (Wang et al. 1994). We applied a panel of candidate defence genes to characterise the backcross population. Markers were identified to be associated with blast resistance following artificial inoculation of the plants with a single pathogen isolate and following exposure to diverse pathogen populations in the field. Using both control and field conditions to evaluate blast resistance has the advantage of not only gaining insights into the genetic control but also revealing the agronomic performance in advanced backcross progeny. In the present study, a total of eight putative QTLs, including five candidate genes, were identified to be associated with blast partial resistance against a single rice blast isolate, PO6-6. The number of QTLs detected was proportional to the variation of the trait: four for lesion number, three for DLA and one for lesion size. A similar phenomenon was observed by Wang et al. (1994).

Our results are consistent with those of previous reports which indicated that some candidate genes, such as oxalate oxidase and 14-3-3 protein, might play important roles in disease response. Faris et al. (1999) reported that both oxalate oxidase and 14-3-3 protein are significantly associated with leaf rust and tan spot in wheat. These two proteins have also been associated with quantitative blast resistance in rice variety Shanhuangzhan 2 from southern China (Liu et al., personal communication). Oxalate oxidase is involved in the production of active oxygen species that attack and inhibit pathogens (Lamb and Dixon 1997) and can be induced in response to the attack of the powdery mildew fungus in barley (Zhang et al. 1995). Therefore, this enzyme is likely to be involved in resistance to various diseases in different plant species. Interestingly, both of these two candidate genes were not detected for DLA and lesion size, even though the three traits were moderately correlated. Under the natural condition in the blast nursery, six candidate genes including, four NBS-LRR sequences (PIC19, PIC 20, 7-4F and RGA1-8), a kinase RGA (Pto kinase) and PR5 protein were identified as having strong effects on DLA. RM21, a microsatellite on chromosome 11 linked to Xa21, was also associated with DLA variation. RM21 was located about 9 cM from the Xa21 gene (X. Chen et al. 1997) and RGA1-8 was a fragment amplified by the primers designed from Xa21. It would be interesting to further investigate what gene(s) nearby Xa21 may act as a QTL for blast resistance.

Evidence of an association between a QTL and a member of a multigene family has been reported by Wang et al. (1998). Xa21D, a member of the Xa21 family, encoded a receptor-like protein with a LRR domain and conferred partial resistance to bacterial blight. The major gene, Xa4, was reported to behave as a recessive QTL against strain CR6 (Li et al. 1999). Results from mapping studies also suggested that some QTLs are located near major genes. In rice blast, a QTL for partial resistance was found near the major gene Pi7(t) (Wang et al.1994). QTLs for percentage DLA and lesion number were located near Pi11(t) on chromosome 11 in a RIL population derived from Zhong 156/ Gumei 2 (Zhuang et al. 2002a). It is interesting that Xa21 and Pi7(t) are tightly linked based on map position (Causse et al. 1994). There is also circumstantial evidence suggesting co-localisation of QTLs for multiple diseases. QTLs for blast resistance (Zhong 156/Gumei 2) and bacterial blight resistance (Ramalingam et al. 2003) were identified near PIC20 on chromosome 1. This might provide an opportunity to study relationships between QTLs conferring resistance to bacterial blight or blast in rice.

Although we considered var. Moroberekan to be the resistance gene donor in this experiment, the candidate defence gene markers showing significant effects are largely var. Vandana alleles. At least two possible explanations may account for this seemingly anomalous result. First, even though Vandana was used as the susceptible recurrent parent in the backcrossing scheme, it was originally released as a variety with moderate resistance to leaf blast in eastern India. Vandana was a popular upland variety until it succumbed to neck blast. Thus, it is not surprising that beneficial alleles for resistance are present in Vandana. Second, only a relatively small number of candidate gene markers were used in this study. It is likely that most of the positive Moroberekan alleles were not detected using our limited set of probes.

Epistatic interaction of QTLs from a donor parent is considered to be difficult to detect, especially in advanced backcross generations, since they do not have enough donor genetic background (Tanksley and Nelson 1996). Nevertheless, backcross lines allow dissection of introgressed QTLs. It is interesting that PIC19 was the only candidate gene involved in all three pairs of digenic interaction among the seven markers with significant effects. It is a well-established fact that incompatible interaction between major resistance genes and avirulent pathogen strains is epistatic to compatible interaction. PIC19, being an NBS-LRR sequence, may have a role in the recognition of the invading pathogen, triggering the signal tranduction pathway to activate a downstream defence response. It is possible that diverse pathogen isolates in the field may trigger strong epistatic interaction. This interpretation seems to be consistent with the observation that we did not detect any interaction in experiments in which a single isolate was used. Since there is a diversity of pathogen strains in the field, it is likely that epistasis could play an important role in resistance to blast under natural conditions. The importance of epistasis has been reported in complex traits such as grain yield and its components (Li et al. 1997; Yu et al. 1997; Zhuang et al. 2002b).

Field performance of the lines selected from the BC3F3 population indicated that the major QTLs have been captured in the BC lines. The selected lines exhibited partial blast resistance with a coefficient r=0.93 between BC3F3 and BC3F4 in the blast nursery. The variability of the BC3F4 population is slightly less than that of the BC3F3 population. Although a small proportion of alleles were from Moroberekan, these partial resistant lines will be useful for improving blast resistance in a breeding programme. Our current work is directed towards extending the phenotypic marker analysis to correlate seedling resistance with neck blast resistance under high disease pressure in upland environments.