Coincidence in map positions between pathogen-induced defense-responsive genes and quantitative resistance loci in rice

Quantitative disease resistance conferred by quantitative trait loci (QTLs) is presumably of wider spectrum and durable. Forty-four cDNA clones, representing 44 defense-responsive genes, were fine mapped to 56 loci distributed on 9 of the 12 rice chromosomes. The locations of 32 loci detected by 27 cDNA clones were associated with previously identified resistance QTLs for different rice diseases, including blast, bacterial blight, sheath blight and yellow mottle virus. The loci detected by the same multiple-copy cDNA clones were frequently located on similar locations of different chromosomes. Some of the multiple loci detected by the same clones were all associated with resistance QTLs. These results suggest that some of the genes may be important components in regulation of defense responses against pathogen invasion and they may be the candidates for studying the mechanism of quantitative disease resistance in rice.     

Coincidence in map positions between pathogen-induced defense-responsive genes and quantitative resistance loci in rice

Quantitative disease resistance conferred by quantitative trait loci (QTLs) is presumably of wider spectrum and durable. Forty-four cDNA clones, representing 44 defense-responsive genes, were fine mapped to 56 loci distributed on 9 of the 12 rice chromosomes. The locations of 32 loci detected by 27 cDNA clones were associated with previously identified resistance QTLs for different rice diseases, including blast, bacterial blight, sheath blight and yellow mottle virus. The loci detected by the same multiple-copy cDNA clones were frequently located on similar locations of different chromosomes. Some of the multiple loci detected by the same clones were all associated with resistance QTLs. These results suggest that some of the genes may be important components in regulation of defense responses against pathogen invasion and they may be the candidates for studying the mechanism of quantitative disease resistance in rice.     

Identification of genes contributing to quantitative disease resistance in rice

Despite the importance of quantitative disease resistance during a plant’s life, little is known about the molecular basis of this type of host-pathogen interaction, because most of the genes underlying resistance quantitative trait loci (QTLs) are unknown. To identify genes contributing to resistance QTLs in rice, we analyzed the colocalization of a set of characterized rice defense-responsive genes and resistance QTLs against different pathogens. We also examined the expression patterns of these genes in response to pathogen infection in the parents of the mapping populations, based on the strategy of validation and functional analysis of the QTLs. The results suggest that defense-responsive genes are important resources of resistance QTLs in rice. OsWRKY45-1 is the gene contributing to a major resistance QTL.NRR,OsGH3-1,and OsGLP members on chromosome 8 contribute alone or collectively to different minor resistance QTLs. These genes function in a basal resistance pathway or in major disease resistance gene-mediated race-specific pathways.     

Molecular progress on the mapping and cloning of functional genes for blast disease in rice (Oryza sativa L.): current status and future considerations

Rice blast disease, which is caused by the fungal pathogen Magnaporthe oryzae, is a recurring problem in all rice-growing regions of the world. The use of resistance (R) genes in rice improvement breeding programmes has been considered to be one of the best options for crop protection and blast management. Alternatively, quantitative resistance conferred by quantitative trait loci (QTLs) is also a valuable resource for the improvement of rice disease resistance. In the past, intensive efforts have been made to identify major R-genes as well as QTLs for blast disease using molecular techniques. A review of bibliographic references shows over 100 blast resistance genes and a larger number of QTLs (～500) that were mapped to the rice genome. Of the blast resistance genes, identified in different genotypes of rice, ～22 have been cloned and characterized at the molecular level. In this review, we have summarized the reported rice blast resistance genes and QTLs for utilization in future molecular breeding programmes to introgress high-degree resistance or to pyramid R-genes in commercial cultivars that are susceptible to M. oryzae. The goal of this review is to provide an overview of the significant studies in order to update our understanding of the molecular progress on rice and M. oryzae. This information will assist rice breeders to improve the resistance to rice blast using marker-assisted selection which continues to be a priority for rice-breeding programmes.     

Diversity,specificity and impacts on field epidemics of QTLs involved in components of quantitative resistance in the wheat leaf rust pathosystem

Quantitative resistance is generally associated with several genes, located in quantitative trait loci (QTLs). Although often described as non-isolate-specific and durable, some cases of erosion of this resistance have been observed. The likelihood of an erosion of quantitative resistance could be reduced, provided that this resistance rests on diversified mechanisms. We hypothesized that QTLs phenotypically expressed on different components, govern different mechanisms of resistance. A doubled haploid population of 91 lines, derived from a cross between the wheat cultivars Apache and Balance, was used to identify leaf rust resistance QTLs. After establishing a linkage map with 355 markers, 13 QTLs were found involved in field resistance, for over 2 years in two locations. Ten of these QTLs were associated with five resistance components (infection efficiency, latent period, lesion size, spore production per lesion and spore production per unit of sporulating tissue) measured in two greenhouse experiments. All but one of the QTLs found in the greenhouse were associated with one or two resistance components, supporting the hypothesis that different genetic factors are mostly involved in the expression of different resistance components. Analyzing separately different field scoring dates revealed QTLs involved at different stages of the epidemic. The QTLs displayed different degrees of isolate-specificity on field resistance, as measured by LOD scores and R ², leading to the conclusion that isolate-specificity is both a qualitative and quantitative feature of quantitative resistance. A profile of each QTL was drawn, to evaluate its usefulness according to the objectives of the breeding program.     

Genome-wide analysis of defense-responsive genes in bacterial blight resistance of rice mediated by the recessive<Emphasis Type="Italic"> R</Emphasis> gene<Emphasis Type="Italic"> xa13</Emphasis>

Defense responses triggered by dominant and recessive disease resistance ( R) genes are presumed to be regulated by different molecular mechanisms. In order to characterize the genes activated in defense responses against bacterial blight mediated by the recessive R gene xa13, two pathogen-induced subtraction cDNA libraries were constructed using the resistant rice line IRBB13—which carries xa13 —and its susceptible, near-isogenic, parental line IR24. Clustering analysis of expressed sequence tags (ESTs) identified 702 unique expressed sequences as being involved in the defense responses triggered by xa13; 16% of these are new rice ESTs. These sequences define 702 genes, putatively encoding a wide range of products, including defense-responsive genes commonly involved in different host-pathogen interactions, genes that have not previously been reported to be associated with pathogen-induced defense responses, and genes (38%) with no homology to previously described functional genes. In addition, R -like genes putatively encoding nucleotide-binding site/leucine rich repeat (NBS-LRR) and LRR receptor kinase proteins were observed to be induced in the disease resistance activated by xa13. A total of 568 defense-responsive ESTs were mapped to 588 loci on the rice molecular linkage map through bioinformatic analysis. About 48% of the mapped ESTs co-localized with quantitative trait loci (QTLs) for resistance to various rice diseases, including bacterial blight, rice blast, sheath blight and yellow mottle virus. Furthermore, some defense-responsive sequences were conserved at similar locations on different chromosomes. These results reveal the complexity of xa13 -mediated resistance. The information obtained in this study provides a large source of candidate genes for understanding the molecular bases of defense responses activated by recessive R genes and of quantitative disease resistance.Electronic Supplementary Material Supplementary material is available in the online version of this article at The first two authors contributed equally to this workCommunicated by R. Hagemann     

Genetic analysis of Verticillium wilt resistance in a backcross inbred line population and a meta-analysis of quantitative trait loci for disease resistance in cotton

Background

Verticillium wilt (VW) and Fusarium wilt (FW), caused by the soil-borne fungi Verticillium dahliae and Fusarium oxysporum f. sp. vasinfectum, respectively, are two most destructive diseases in cotton production worldwide. Root-knot nematodes (Meloidogyne incognita, RKN) and reniform nematodes (Rotylenchulus reniformis, RN) cause the highest yield loss in the U.S. Planting disease resistant cultivars is the most cost effective control method. Numerous studies have reported mapping of quantitative trait loci (QTLs) for disease resistance in cotton; however, very few reliable QTLs were identified for use in genomic research and breeding.

Results

This study first performed a 4-year replicated test of a backcross inbred line (BIL) population for VW resistance, and 10 resistance QTLs were mapped based on a 2895 cM linkage map with 392 SSR markers. The 10 VW QTLs were then placed to a consensus linkage map with other 182 VW QTLs, 75 RKN QTLs, 27 FW QTLs, and 7 RN QTLs reported from 32 publications. A meta-analysis of QTLs identified 28 QTL clusters including 13, 8 and 3 QTL hotspots for resistance to VW, RKN and FW, respectively. The number of QTLs and QTL clusters on chromosomes especially in the A-subgenome was significantly correlated with the number of nucleotide-binding site (NBS) genes, and the distribution of QTLs between homeologous A- and D- subgenome chromosomes was also significantly correlated.

Conclusions

Ten VW resistance QTL identified in a 4-year replicated study have added useful information to the understanding of the genetic basis of VW resistance in cotton. Twenty-eight disease resistance QTL clusters and 24 hotspots identified from a total of 306 QTLs and linked SSR markers provide important information for marker-assisted selection and high resolution mapping of resistance QTLs and genes. The non-overlapping of most resistance QTL hotspots for different diseases indicates that their resistances are controlled by different genes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1682-2) contains supplementary material, which is available to authorized users.     

RFLP-facilitated investigation of the quantitative resistance of rice to brown planthopper ( Nilaparvata lugens)

Quantitative trait loci (QTLs), conferring quantitative resistance to rice brown planthopper (BPH), were investigated using 160 F₁₁ recombinant inbred lines (RILs) from the Lemont/Teqing cross, a complete RFLP map, and replicated phenotyping of seedbox inoculation. The paternal indica parent, Teqing, was more-resistant to BPH than the maternal japonica parent, Lemont. The RILs showed transgressive segregation for resistance to BPH. Seven main-effect QTLs and many epistatic QTL pairs were identified and mapped on the 12 rice chromosomes. Collectively, the main-effect and epistatic QTLs accounted for over 70% of the total variation in damage scores. Teqing has the resistance allele at four main-effect QTLs, and the Lemont allele resulted in resistance at the other three. Of the main-effect QTLs identified, QBphr5b was mapped to the vicinity of gl1, a major gene controlling leaf and stem pubescence. The Teqing allele controlling leaf and stem pubescence was associated with resistance, while the Lemont allele for glabrous stem and leaves was associated with susceptibility, indicating that this gene may have contributed to resistance through antixenosis. Similar to the reported BPH resistance genes, the other six detected main-effect QTLs were all mapped to regions where major disease resistance genes locate, suggesting they might have contributed either to antibiosis or tolerance. Our results indicated that marker-aided pyramiding of major resistance genes and QTLs should provide effective and stable control over this devastating pest. Received: 10 December 2000 / Accepted: 7 May 2001     

Identification of charcoal rot resistance QTLs in sorghum using association and <Emphasis Type="Italic">in silico</Emphasis> analyses

Charcoal rot disease, a root and stem disease caused by the soil-borne fungus Macrophomina phaseolina (Tassi) Goid., is a major biotic stress that limits sorghum productivity worldwide. Charcoal rot resistance-related parameters, e.g., pre-emergence damping-off%, post-emergence damping-off%, charcoal rot disease severity, and plant survival rates, were measured in a structured sorghum population consisting of 107 landraces. Analysis of variance of charcoal rot resistance-related parameters revealed significant variations in the response to M. phaseolina infection within evaluated accessions. Continuous phenotypic variations for resistance-related parameters were observed indicating a quantitative inheritance of resistance. The population was genotyped using 181 simple sequence repeat (SSR) markers. Association analysis identified 13 markers significantly associated with quantitative trait genes (QTLs) conferring resistance to charcoal rot disease with an R² value ranging between 9.47 to 18.87%, nine of which are environment-specific loci. Several QTL-linked markers are significantly associated with more than one resistance-related parameter, suggesting that those QTLs might contain genes involved in the plant defense response. In silico analysis of four novel major QTLs identified 11 putative gene homologs that could be considered as candidate genes for resistance against charcoal rot disease. Cluster analysis using the genotypic data of 181 SSR markers from 107 sorghum accessions identified 12 main clusters. The results provide a basis for further functional characterization of charcoal rot disease resistance or defense genes in sorghum and for further dissection of their molecular mechanisms.     

High-resolution mapping of two rice brown planthopper resistance genes, Bph20(t) and Bph21(t), originating from Oryza minuta

Brown planthopper (BPH) is one of the most destructive insect pests of rice. Wild species of rice are a valuable source of resistance genes for developing resistant cultivars. A molecular marker-based genetic analysis of BPH resistance was conducted using an F₂ population derived from a cross between an introgression line, ‘IR71033-121-15’, from Oryza minuta (Accession number 101141) and a susceptible Korean japonica variety, ‘Junambyeo’. Resistance to BPH (biotype 1) was evaluated using 190 F₃ families. Two major quantitative trait loci (QTLs) and two significant digenic epistatic interactions between marker intervals were identified for BPH resistance. One QTL was mapped to 193.4-kb region located on the short arm of chromosome 4, and the other QTL was mapped to a 194.0-kb region on the long arm of chromosome 12. The two QTLs additively increased the resistance to BPH. Markers co-segregating with the two resistance QTLs were developed at each locus. Comparing the physical map positions of the two QTLs with previously reported BPH resistance genes, we conclude that these major QTLs are new BPH resistance loci and have designated them as Bph20(t) on chromosome 4 and Bph21(t) on chromosome 12. This is the first report of BPH resistance genes from the wild species O. minuta. These two new genes and markers reported here will be useful to rice breeding programs interested in new sources of BPH resistance.     

Identification of quantitative trait loci for resistance to rice black-streaked dwarf virus disease and small brown planthopper in rice

Small brown planthopper (SBPH) and its transmitted rice black-streaked dwarf virus disease (RBSDVD) cause serious damage to rice (Oryza sativa L.) production. Though breeding of resistant cultivars is believed to be one of the most important strategies for RBSDVD management, few high-resistance lines have been found to date. In the present study, we identified an indica variety, 9194, that is highly resistant to RBSDVD and analyzed the quantitative trait loci (QTLs) underlying this resistance . In total, four QTLs for RBSDVD resistance, viz. qRBSDV3, qRBSDV6, qRBSDV9, and qRBSDV11, were identified. Among them, qRBSDV6, qRBSDV9, and qRBSDV11 with LOD (logarithm [base 10] of odds) scores of 4.42–4.48, 2.11–7.26, and 5.01–7.16 were repeatedly detected in 2 years, accounting for 10.3–16.7%, 8.3–35.5%, and 20.0–31.1% of the total phenotypic variation, respectively. Further, introgression of single- or multiple-resistance QTLs into a susceptible rice variety by marker-assisted selection (MAS) indicated that stacking the QTLs could progressively enhance RBSDVD resistance, suggesting that these QTLs act additively. The same population was also used for QTL mapping of SBPH resistance. Four QTLs, viz. qSBPH1, qSBPH5, qSBPH8, and qSBPH9, with LOD scores of 2.72, 2.78, 2.15, and 2.85 were detected, explaining 13.7%, 11.0%, 12.0%, and 21.0% of the phenotypic variation, respectively. The identification of RBSDVD and SBPH resistance QTLs, and the development of single and multiple genes with pyramided lines, in this study provides innovative resources for molecular breeding of resistant rice cultivars.     

A “defeated” rice resistance gene acts as a QTL against a virulent strain of Xanthomonas oryzae pv. oryzae

The genetic components responsible for qualitative and quantitative resistance of rice plants to three strains (CR4, CXO8, and CR6) of Xanthomonas oryzae pv. oryzae (Xoo) were investigated using a set of 315 recombinant inbred lines (RILs) from the cross Lemont (japonica) × Teqing (indica) and a complete linkage map with 182 well distributed RFLP markers. We mapped a major gene (Xa4) and ten quantitative trait loci (QTLs) which were largely responsible for segregation of the resistance phenotype in the RILs. The Teqing allele at the Xa4 locus, Xa4 ^T , acted as a dominant resistance gene against CR4 and CXO8. The breakdown of Xa4 ^T -associated resistance mediated by the mutant allele at the avrXa4 locus in the virulent strain CR6 results from significant changes in both gene action (lose of dominance) and the magnitude of gene effect (≈50% reduction). Nevertheless, Xa4 ^T still acted as a recessive QTL with a significant residual effect against CR6. The mutant alleles at the avrXa4 locus in CXO8 and CR6 that lead to a reduction in effect, or “breakdown”, of Xa4 ^T were apparently accompanied by corresponding penalties for their fitness. The quantitative component of resistance to Xoo in the RILs was largely due to a number of resistance QTLs. Most resistance QTLs mapped to genomic locations where major resistance genes and/or QTLs for resistance to Xoo, blast and sheath blight were identified in the same cross. Most QTLs showed consistent levels of resistance against all three Xoo strains. Our results suggest that a high level of durable resistance to Xoo may be achieved by the cumulative effects of multiple QTLs, including the residual effects of “defeated” major resistance genes.     

Exploring the quantitative resistance to <Emphasis Type="Italic">Pseudomonas syringae</Emphasis> pv. <Emphasis Type="Italic">phaseolicola</Emphasis> in common bean (<Emphasis Type="Italic">Phaseolus vulgaris</Emphasis> L.)

Pseudomonas syringae pv. phaseolicola is an important disease that causes halo blight in common bean. The genetic mechanisms underlying quantitative halo blight resistance are poorly understood in this species, as most disease studies have focused on qualitative resistance. The present work examines the genetic basis of quantitative resistance to the nine halo blight races in different organs (primary and trifoliate leaf, stem and pod) of an Andean recombinant inbred line (RIL) progeny. Using a multi-environment quantitative trait locus (QTL) mapping approach, 76 and 101 main-effect and epistatic QTLs were identified, respectively. Most of the epistatic interactions detected were due to loci without detectable QTL additive main effects. Main and epistatic QTLs detected were mainly consistent across the environment conditions. The homologous genomic regions corresponding to 26 of the 76 main-effect detected QTLs were positive for the presence of resistance-associated gene cluster encoding nucleotide-binding and leucine-rich repeat (NL) proteins and known defence genes. Main-effect QTLs for resistance to races 3, 4 and 5 in leaf, stem and pod were located on chromosome 2 within a 3.01-Mb region, where a cluster of nine NL genes was detected. The NL gene Phvul.002G323300 is located in this region, which can be considered an important putative candidate gene for the non-organ-specific QTL identified here. The present research provides essential information not only for the better understanding of the plant-pathogen interaction but also for the application of genomic assisted breeding for halo blight resistance in common bean.     

QTL analysis of root-lesion nematode resistance in barley: 1. Pratylenchus neglectus

The root-lesion nematode Pratylenchus neglectus can cause severe losses in barley cultivation. Multiplication rates had been found to vary greatly between different barley accessions. Two winter barley cultivars, Igri and Franka, had been found to differ in their ability to resist this parasite. An existing Igri?×?Franka doubled haploid population was chosen to genetically map resistance genes after artificial inoculation with P. neglectus in the greenhouse and climate chamber. A continuous phenotypic variation was found indicating a quantitative inheritance of P. neglectus resistance. An existing map was enriched by 527 newly developed Diversity Array Technology markers (DArTs). The new genetic linkage map was comprised of 857 molecular markers that cover 1,157?cM on seven linkage groups. Using phenotypic data collected from four different experiments in 3?years, five quantitative trait loci were mapped by composite interval mapping on four (3H, 5H, 6H and 7H) linkage groups. A quantitative trait locus with a large phenotypic effect of 16% and likelihood of odds (LOD) score of 6.35 was mapped on linkage group 3H. The remaining four QTLs were classified as minor or moderate with LOD scores ranging from 2.71 to 3.55 and R ² values ranging from 8 to 10%. The DNA markers linked to the resistance QTLs should be quite useful for marker-assisted selection in barley breeding because phenotypic selection is limited due to time constraints and labor costs.     

Identification of functional candidate genes for drought tolerance in rice

Drought tolerance (DT) in rice is known to be controlled by many quantitative trait loci (QTLs) and involved differential expression of large numbers of genes, but linking QTLs with their underlying genes remains the most challenging issue in plant molecular biology. To shed some light on this issue, differential gene expression in response to PEG simulated drought in 3 unique genetic materials (a lowland rice, IR64 and its derived line, PD86 which has 11 introgressed DT QTLs, and a upland rice IRAT109) was investigated using a PCR-based subtractive hybridization strategy. More than 300 unique subtracted cDNA sequences, covering genes of diverse cellular activities and functions, were identified and confirmed by semi-quantitative and quantitative RT-PCR. Detailed bioinformatics analyses of the data revealed two interesting results. First, the levels and mechanisms of DT of the three rice lines were associated with the number and types of differentially expressed genes, suggesting different DT mechanisms in rice are controlled by different sets of genes and different metabolic pathways, and most differentially expressed genes under drought were able to contribute to DT. Second, there appeared a high correspondence in genomic location between DT QTLs and clusters of differentially expressed genes in rice, suggesting some DT QTLs may represent clusters of co-regulated and functionally related genes. Thus, differential gene expression analyses using genetically characterized materials can provide additional insights into the molecular basis of QTLs and convergent evidence to shortlist the candidate genes for target QTLs. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. Bin-Ying Fu and Jian-Hua Xiong are contributed to this work equally.     

In silico integration of quantitative trait loci for seed yield and yield-related traits in Brassica napus

Mapping quantitative trait loci (QTLs) is a foundation for molecular marker-assisted selection and map-based gene cloning. During the past decade, numerous QTLs for seed yield (SY) and yield-related traits in Brassica napus L. have been identified. However, integration of these results in order to compare QTLs from different mapping populations has not been undertaken, due to the lack of common molecular markers between studies. Using previously reported Brassica rapa and Brassica oleracea genome sequences, we carried out in silico integration of 1,960 QTLs associated with 13 SY and yield-related traits from 15 B. napus mapping experiments over the last decade. A total of 736 SY and yield-related QTLs were mapped onto 283 loci in the A and C genomes of B. napus. These QTLs were unevenly distributed across the 19 B. napus chromosomes, with the most on chromosome A3 and the least on chromosome C6. Our integrated QTL map identified 142 loci where the conserved QTLs were detected and 25 multifunctional loci, mostly for the traits of flowering time (FT), plant height, 1,000-seed weight, maturity time and SY. These conserved QTLs and multifunctional loci may result from pleiotropism or clustered genes. At the same time, a total of 146 genes underlying the QTLs for FT and other yield-related traits were identified by comparative mapping with the Arabidopsis genome. These results facilitate the retrieval of B. napus SY and yield-related QTLs for research communities, increase the density of targeted QTL-linked markers, validate the existence of QTLs across different populations, and advance the fine mapping of genes.     

Identification and fine mapping of a major R gene to Magnaporthe oryzae in a broad-spectrum resistant germplasm in rice

Identification of R genes and development of associated molecular markers will facilitate their application in the development of crop cultivars resistant to disease. We evaluated the resistance of a resistant germplasm ??D69??, 10 monogenic lines, and model cultivar ??Nipponbare?? to 56 M. oryzae isolates of blast disease in rice. The results demonstrated that only D69 exhibited full-spectrum resistance among the 12 investigated materials. Resistance inheritance in D69 was analyzed using a stable isolate GD08T13 with strong pathogenicity, collected from diseased panicles. A single dominant R gene was revealed and designated as Pi51(t). Through linkage analysis and the development of new markers, Pi51(t) was subsequently delimited to an interval of ~100.8?kb flanked by markers Ind306 and RM19818, where Pi2, Pi9, Piz, Piz-t, Pigm(t), and Pi40(t) reside. Different genotypes identified by linked markers pB8, Pi9-2, zt56591, and T845, and different pathotypes to the same set of isolates, distinguished Pi51(t) from Pi2, Pi9, Piz, and Piz-t. The origin of Pi40(t) in wild rice suggests that Pi51(t) and Pi40(t) are different. Comparison of resistance spectra suggests multiple R genes in D69, making its resistance durable and valuable in breeding programs. The results of this work will facilitate future studies on cloning and functional analysis of blast resistance genes for rice improvement.     

QTL mapping in rice

In the past 10 years, interest in applying the tools of molecular genetics to the problem of increasing world rice production has resulted in the generation of two highly saturated, molecular linkage maps of rice, and the localization of numerous genes and quantitative trait loci (QTLs). Primary studies have identified QTLs associated with disease resistance, abiotic stress tolerance and yield potential of rice in a range of ecosystems. The ability to identify, manipulate and potentially clone individual genes involved in quantitatively inherited characters, combined with the demonstrated conservation of numerous linkage blocks among members of the grass family, emphasizes the contribution of map-based genetic analyses both to applied and to basic crop research.     

Toward an understanding of the molecular basis of quantitative disease resistance in rice

Rice crops are severely damaged by diseases caused by bacterial, fungal, and viral pathogens. Application of host resistance to these pathogens is the most economical and environmentally friendly approach to solve this problem. Quantitative resistance conferred by quantitative trait loci (QTL) is a valuable resource for the improvement of rice disease resistance. Although numerous resistance QTL against rice diseases have been identified, these resources have not been used effectively in rice improvement because the genetic control of quantitative resistance is complex and the genes underlying most of the resistance QTL remain unknown. This review focuses on the latest molecular progress in quantitative disease resistance in rice. This knowledge will be helpful for characterizing more resistance QTL and turning the quantitative resistance into actual resources for rice protection.     

Both stable and unstable QTLs for resistance to powdery mildew are detected in apple after four years of field assessments

Powdery mildew, caused by the ascomycete fungus Podosphaera leucotricha, is one of the most damaging diseases of apple worldwide. Polygenically determined resistance might contribute to a significant increase of resistance to this disease in new cultivars. A quantitative trait locus (QTL) analysis was performed in an F₁ progeny derived from a cross between the apple cultivar Discovery and the apple hybrid TN10-8. Powdery mildew incidence was assessed during four years (five seasons) in spring and/or autumn in a French local orchard. Seven additive and/or dominant QTLs were detected over the five seasons, with effects (R ²) ranging from 7.5% to 27.4% of the progeny phenotypic variation. Two QTLs, on linkage groups (LGs) 2 and 13, were consistently identified and accounted together from 29% to 37% of the phenotypic variation according to the year of assessment. The other QTLs were identified during one (LGs 1, 14), two (LG10), or three (LGs 8, 17) seasons. Their instability indicated a changing genetic determinism according to the year of assessment, for which several hypotheses may be put forward. The QTLs on LGs 2 and 8 mapped close to clusters of resistance gene analogs (RGAs) and major genes for resistance to mildew or apple scab previously identified. The stable QTLs identified on LGs 2 and 13, together with the strong effect QTL located on LG 8, are of special interest for breeding purposes, especially if combined with other major resistance genes.