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Dep. of Crop and Soil Sciences, Michigan State Univ., East Lansing, MI 48824
* Corresponding author (kellyj{at}msu.edu)
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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estimates for resistance ranged from 0.10 to 0.51 for the kidney and from 0.20 to 0.82 for the cranberry IBL populations. Nine QTL significantly associated with Fusarium root rot resistance in the field and greenhouse, explained from 5 to 53% of the total phenotypic variability. The QTL associated with root rot resistance were located on linkage groups (LGs) B2 and B5 of the integrated bean map close to previously identified QTL for resistance on B2. On the basis of a linear regression model, a combination of five markers associated with QTL on two different LGs accounted for 73% of the phenotypic variation for root rot resistance. Data from the current study provides breeders the opportunity to combine, through marker-assisted backcrossing, large-effect QTL identified on different LGs to enhance root rot resistance in Andean germplasm of common bean.
Abbreviations: BJ, BAT93 x Jalo EEP558 recombinant inbred line population • CIM, composite interval mapping • cM, centimorgan • DTF, days to flower • h2N, narrow-sense heritability • IBL, inbred backcross line • LG, linkage group • LOD, log of odds • MRF, Montcalm Research Farm • NSL, Negro San Luís • NYSAES, New York State Agriculture Experimental Station • QTL, quantitative trait loci • RAPD, random amplified polymorphic DNA • RIL, recombinant inbred line • SMA, single marker analysis
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Since traits such as root rot resistance are genetically complex and difficult to evaluate, the efficiency of phenotypic selection is low resulting in limited progress in breeding for resistance. Breeders are increasingly using QTL analysis to quantify and locate quantitative resistance in plant genomes, since the approach can overcome some of the common limitations encountered by conventional selection for quantitative traits (Asíns, 2002; Beavis, 1998; Kelly and Vallejo, 2005). Indirect selection for root rot resistance based on markers linked to the resistance QTL would facilitate improvement of root rot resistance, as field selection is laborious and destructive sampling is needed to identify resistance. Quantitative trait loci analyses of dry bean recombinant inbred line (RIL) populations have led to the identification of QTL contributing to Fusarium root rot resistance. Sixteen QTL for Fusarium root rot resistance were identified using a F4:5 RIL population derived from a cross between the susceptible large-seeded red kidney ‘Montcalm’ and the root rot resistant snap bean breeding line FR266 (Schneider et al., 2001). Interval mapping revealed two QTL for Fusarium root rot resistance using an F2:6 RIL population derived from a cross between ‘A.C. Compass’, a root rot susceptible navy bean, and NY2114-12, a highly resistant root rot germplasm (Chowdbury et al., 2002). Six QTL for resistance to Fusarium root rot were identified using a RIL population derived from a cross between the root rot susceptible snap bean ‘Eagle’ and ‘Puebla 152’, a small black seeded root rot resistant dry bean (Navarro et al., 2004). Most of these QTL were located on LGs B2 and B3 of the integrated bean map (Freyre et al., 1998) close to a region where defense response genes Pgip, and ChS and pathogenesis related proteins, PvPR-1 and PvPR-2, have been identified (Schneider et al., 2001). The co-localization with genes of known function provides information on the possible role of QTL, the genetic diversity among resistance sources and emphasizes the need for cyclic breeding systems to combine QTL located in diverse genomic regions.
Balanced populations such as RIL, F2, and doubled haploid populations in which both parental alleles are present in high frequencies have been used most often in QTL studies (Butruille et al., 1999). The estimation of the number of QTL and the relative position and contribution of each QTL to the expression of a trait of interest is determined more efficiently in balanced populations. An alternative to the balanced population is the advanced backcross population where the alleles of one parent are present at a much lower frequency (Tanksley and Nelson, 1996). Unbalanced populations have been used in QTL mapping to determine the number of genes controlling a quantitative trait and to introgress desirable QTL from unadapted to better adapted germplasm, (Chetelat and Meglic, 2000; Doganlar et al., 2002; Fulton et al., 2000; Tanksley and Nelson, 1996). When using unbalanced populations for mapping and identifying QTL, there is a loss of resolution and efficiency due to the unequal allele frequency inherited in IBL populations (Butruille et al., 1999; Tanksley and Nelson, 1996). However, IBLs or backcross RILs still provide linkage information to enhance genetic maps (Doganlar et al., 2002) and unbalanced populations have the advantage of being more genetically and phenotypically similar to the recurrent parent. The advantage of using such populations is the recovery of genetic materials that resemble the recurrent parent but with the addition of desirable alleles from the donor parent (Bliss, 1993). In crosses between Middle American and Andean gene pools, unbalanced populations are more useful to reduce the frequency of phenotypically inferior genetic material that results from wide crosses between bean gene pools.
The objectives of this study were to (i) use IBL populations to introgress Fusarium root rot resistance into the large-seeded Andean kidney and cranberry beans using a small-seeded black bean from the Middle American gene pool as the source of resistance; and (ii) identify significant QTL-marker associations which could be used to facilitate indirect selection for Fusarium root rot resistance in common bean.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Both BC2 generation populations were advanced by single seed descent to the BC2F4:5 generation. No selection was applied in any generation other than to maintain diversity based on pedigree, and BC1 plants were chosen randomly for additional backcrossing. Nevertheless, some parental lines were lost in subsequent generations due to lethality and photoperiod sensitivity problems. Both IBL populations were treated independently and were considered as two separate experiments to reduce error variance.
Field Trials
Resistance of the IBL populations, parents and additional checks of known root rot reaction were evaluated for Fusarium root rot resistance at maturity in 2002 and during flowering in 2003. Four field experiments were conducted at the Montcalm Research Farm (MRF) located near Entrican, MI (43°20' N; 85°01' W), in an alfisol soil, series name Montcalm/McBride loamy sand, which is naturally infected with F. solani. A fifth experiment was conducted at the New York State Agricultural Experiment Station (NYSAES) in Ontario County near Geneva, NY, where the soil type was a fairly rocky lime silt loam, with a history of bean production and root rot diseases. This field has been in continuous bean production for over 10 yr and is heavily infested with several root rot pathogens including Fusarium, Pythium, Rhizoctonia, and Thielaviopsis.
The NYSAES experiment was arranged in a 100 entry randomized block design (91 IBLs from kidney IBL population plus nine checks) with three replications and was planted on 10 to 16 June 2003. Samples were dug and rated for root rot on 22 July and 18 Aug. 2003 (G.S. Abawi, personal communication).
The kidney and cranberry IBL populations were evaluated separately in two experiments planted at MRF on 20 June 2002. The kidney IBL experiment was arranged in a 10 by 10 square lattice design (91 IBL from the kidney IBL population plus nine checks) and the cranberry IBL experiment was arranged in a 9 by 9 square lattice design (78 IBL from the cranberry IBL population plus three checks) with three replications. Each experimental unit consisted of 20 plants per row (row length 5.0 m, row width 50 cm, in-row plant spacing 20 cm). The third and fourth experiments were planted at MRF on 17 June 2003, similar to the design of the previous two experiments. The kidney population experiment was arranged in a 10 by 10 square lattice design similar to the 2002 field experiment, and the cranberry experiment was arranged in an 8 by 9 rectangular lattice design (64 IBL of the cranberry IBL population plus eight checks) with three replications. The number of IBLs for the cranberry experiment was reduced in the 2003 season due to loss of IBLs caused by a heavy infection with common bacterial blight (Xanthomonas axonopodis pv. phaseoli) in 2002. Each experimental unit in the 2003 trials consisted of 80 plants per row (row length 5.0 m, row width 50 cm, in-row plant spacing 7.6 cm). Standard agronomic practices for tillage, fertilization, insect, and weed control were applied to ensure adequate plant growth and development. All plots received supplemental irrigation. Plots were irrigated twice for a total of 41 mm in 2002 and were irrigated three times in 2003 for a total of 48 mm of supplemental water. Three random plants from each row in all three replications were carefully removed from soil and rated for Fusarium root rot symptoms at maturity during 2002 and at flowering during 2003. Care was taken that the plants at both ends of the rows were not sampled to avoid error. The root rot screening in 2002 was conducted at the end of the season, as there was insufficient seed to plant larger plots suitable for destructive sampling earlier in the season and there existed the need to save sufficient seed for more extensive testing in 2003. Disease reaction was scored using the root rating scale of 1 to 7 (Schneider and Kelly, 2000), where 1 = healthy root system with no discoloration of root or hypocotyl tissue and no reduction in root mass, and 7 = pithy or hollow hypocotyl with much extended lesions, root mass is severely reduced, and is functionally dead. The MRF data was collected by BRA during the 2002 and 2003 field and greenhouse trials, and the data was collected by G. S. Abawi, Cornell University for the NYSAES experiment.
Greenhouse Trials
Both IBL populations and additional checks of known disease reaction were evaluated for root rot reaction in the greenhouse using a perlite-based protocol (Schneider and Kelly, 2000). Seventy-two-well greenhouse flats were filled with perlite and a single seed was germinated in each well, using no fewer than three seedlings per line per replication for each individual IBL population. A randomized complete block design with three replications was used, and each experiment was evaluated twice. The perlite was saturated with nutrient solution at planting and at weekly intervals. When plants were 10 d old, they were inoculated with 10 mL of 2 x 105 spore suspension of F. solani. The inoculum was applied over the base of the hypocotyl using a 4-L polyethylene hand sprayer. The inoculum was prepared by scraping PDA plates of F. solani into distilled water; quantification was conducted using a hemocytometer, and the concentration was adjusted to of 2 x 105 spores mL–1. The Hawks 2b isolate of F. solani collected by Schneider and Kelly (2000) in Presque Isle County, Michigan, was used for all inoculations. Two weeks after inoculation, seedlings were removed from the flats, and the roots were cleaned of excess perlite and rated using the scale described previously. The fungus was cultured continuously, and the pathogenicity of the culture was maintained by reisolating the fungus from infected susceptible Red Hawk plants following the procedure of Schneider and Kelly (2000).
Statistical Procedures
All experiments conducted in the greenhouse and field were analyzed as a one-way ANOVA using PROC GLM and PROC MIXED (SAS Institute, 1995). Root rot ratings collected from greenhouse and field evaluations were averaged to give a plot mean that was subsequently used for ANOVAs. Pearson correlations were conducted among agronomic traits and root rot scores using SAS PROC CORR. Agronomic data were collected for days to flower (DTF), days to maturity, growth habit, root vigor, seed yield, and seed weight. The h2N estimates for root rot scores in 2002 and 2003 were based on variance component estimates calculated on an entry mean basis (Hallauer and Miranda, 1981). Pearson rank correlation coefficients were calculated by PROC CORR to compare means of root rot ratings for IBLs between greenhouse and field evaluations (SAS Institute, 1995).
Selective Mapping
The combined selective mapping strategy used to identify random amplified polymorphic DNA (RAPD) markers linked to the genomic regions conditioning resistance to Fusarium root rot consisted of bulked segregant analysis (Michelmore et al., 1991) and selective genotyping (Lander and Botstein, 1989). The identification of markers followed a five-step process for combined selective mapping described by Miklas et al. (1996). The homozygosity of the selected BC2F4:5 IBLs, to be used in the bulks, was determined by inoculating both populations under greenhouse conditions. On the basis of these inoculations, a contrasting pair of resistant and susceptible DNA bulks was developed for each population. Each bulk represented a pool of DNA from the eight most resistant or eight most susceptible IBLs. Inoculation conditions and symptom evaluation was performed as previously described. Before inoculation with F. solani, tissue from BC2F4:5 IBL populations and parent genotypes was collected for DNA extraction from greenhouse grown plants, lyophilized, and ground. DNA was extracted using the miniprep procedure described by Afanador et al. (1993), with slight modifications. The RAPD fragments greater in size than 700 bp were amplified using Invitrogen brand Taq DNA polymerase (Life Technologies, Rockville, MD), and those bands smaller in size than 700 bp were amplified by AmpliTaq DNA polymerase, Stoffel Fragment (PerkinElmer, Norwalk, CT). The extracted DNA was standardized to uniform concentration (10 ng µL–1) using DNA fluorometer (Hoefer Pharmacia Biotech, San Francisco, CA). DNA was amplified using a PerkinElmer Cetus DNA Thermal Cycler 480 (PerkinElmer, Cetus, Norwalk, CT). Approximately 20 µL of amplified DNA from each sample was run on a 1.4% agarose gel containing 0.5 µg mL–1 of ethidium bromide, 40 mM Tris-acetate, and 1 mM EDTA. DNA was viewed under ultraviolet light and photographed for permanent record, and polymorphisms were recorded as either presence or absence of bands.
The three parents were screened with a total of 2500 RAPD primers. The DNA bulks were tested with only those primers shown to generate polymorphisms between the parents. Among the 2500 RAPD primers, only 14% or 350 were polymorphic either between parents of the kidney and cranberry populations. The RAPD markers that co-segregated with the disease reaction in at least 90% of the individuals comprising the DNA bulks were subsequently assayed across the entire IBL populations. Additional polymorphic markers, previously identified as associated to Fusarium root rot resistance (Schneider et al., 2001), were also included in the analysis to enhance genome coverage (Shen et al., 2003) and determine if different resistant sources possessed the same QTL as were detected in the IBL populations.
Genetic Linkage Map and QTL Analysis
None of the genetic mapping software commonly used in QTL mapping would perform the multipoint analysis and mapping of the IBL populations. However, mapping programs such as MAPMAKER and JoinMap accept two point information to build genetic maps and provide an estimate of recombination frequency and corresponding log of odds (LOD) scores. The mapping program JoinMap was chosen to construct partial LGs based on a minimum LOD score of 4 (Stam, 1993; van Ooijen and Voorrips, 2001). The addition of previously identified markers linked to root rot resistance in F4 derived RILs served as an anchor point not only for the partial LG construction but also for co-integration with the integrated bean linkage map (Freyre et al., 1998). All segregating RAPD markers from each resulting partial LG were analyzed in a multiple regression analysis using SAS PROC GLM (SAS Institute, 1995), and significance was set at P < 0.05. WinQTL-Cartographer v2.0 software package was used to map QTL using composite interval mapping (CIM; Basten et al., 2003), and single marker analysis (SMA) was used to confirm the QTL identified by CIM. Permutation analysis was performed (1000 permutations) for individual traits to identify a significance threshold of the test statistic for individual QTL (Doerge et al., 1997; Edwards et al., 1987; McMullen et al., 2001). MAPMAKER/EXP 3.0 (Lincoln et al., 1987) was used to anchor the LGs identified in this study to the integrated bean map by screening the BAT93 x Jalo EEP558 RIL population (hereafter referred to as BJ) with those markers that were polymorphic between the BAT93 and JaloEEP558 parents.
To detect significant loci and epistatic interactions as described by McMullen et al. (2001), RAPD marker data for each IBL was tested for significant associations between root rot resistance and marker genotype by QTL-cartographer SMA and CIM. Marker-QTL associations were determined by F tests with significance at P < 0.05. The presence of a QTL was declared significant whenever its LOD score exceeded the calculated threshold level determined by the permutation analysis. The estimated position of the QTL was the point where the maximum LOD score was found in the region under consideration.
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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The h2N estimates of root rot rating for the greenhouse trials were intermediate for the kidney (h2N = 0.44–0.51) and cranberry (h2N = 0.35–0.51) IBL populations (Table 1). Heritability estimates for field root rot ratings in the kidney IBL population were low (0.1–0.2) and ranged from intermediate to high (0.3–0.82) in the cranberry IBL population. Similar intermediate to high h2N estimates (0.48–0.71) for root rot ratings were reported in RIL populations of Montcalm x FR266 and ‘Isles’ x FR266 (Schneider et al., 2001). Estimates obtained in the current and previous studies suggest that the inheritance pattern for root rot was influenced by the testing procedures employed, age of plants evaluated, and the parents involved (Boomstra and Bliss, 1977; Hall and Phillips, 2004; Hassan et al., 1971). High heritability estimates (77.9% for ‘Redkote’ x 2114-12 and 79.7% for Redkote x N203) were obtained when evaluating 13-wk-old field-grown bean plants for root rot as compared with lower and dissimilar heritability estimates (33.6 and 10.0%) calculated for 5-wk-old plants (Hassan et al., 1971). The difficulty in classifying plants for degrees of resistance late in the season may have resulted in greater root rot ratings for 2002 as compared with the 2003 trials (Table 1). Rating for root rot at maturity after disease has invaded the decaying root system is challenging. Late season evaluations were a necessity in 2002 due to the need to save sufficient seed for further testing. Late season evaluations are preferred by breeders needing to advance resistant germplasm selected from segregating populations. Destructive evaluations conducted earlier in the season during anthesis should result in more effective differentiating of root rot resistance, but can only be used with advanced homozygous lines. The range in heritability estimates for root rot resistance obtained in the greenhouse and field studies indicate the quantitative nature of root rot resistance in beans. Improvement of resistance to Fusarium root rot should be possible, provided there is adequate control of the environmental conditions under which the disease is evaluated.
QTL Analysis
A linkage map was constructed using JoinMap (Stam, 1993) by placing 33 out of 350 polymorphic RAPD markers on 10 partial LGs for a total length of 183 centimorgans (cM). The limited coverage represents approximately 15% of the estimated total length (1200 cM) of the bean genome (Kelly et al., 2003) and is the direct result of the narrow genetic base of the IBL populations investigated. The partial LGs were anchored to the integrated bean map by genotyping the BJ RIL population with markers identified as linked to QTL for root rot resistance that were previously mapped to the consensus map (Freyre et al., 1998). Three LGs (LG 1, 7, and 9) possessing QTL associated with root rot resistance co-integrated with LGs B2 and B5 of the integrated map (Table 2), but LG5 and LG8 remained unassigned. In the current study, QTL analysis was conducted for each year of the study separately due to the high genotype-by-environment interaction obtained when combining data for the 2002 and 2003 field trials. Coefficient of determination (R2) values, which reflect the amount of variation explained by a given QTL, ranged from 5.0 to 53.3% for root rot resistance detected in different environments (Table 2). Support for the presence of putative QTL, associated with root rot resistance on B5, comes from the detection of QTL in both populations grown in different environments. Two QTL identified in the kidney IBL population explained 19.0% (G6.2000–G17.900) in 2003 and 30.0% (G17.900–AL20.350) of the phenotypic variation for root rot resistance in 2002 trials in MRF. Both of these QTL have a common flanking marker (G17.900), suggesting that they may share a common genomic region of LG 7 (B5; Fig. 2). Additional support for QTL for root rot resistance in this region of B5 comes from the kidney IBL population grown in 2002. The third QTL was detected in the same general region spanning 
13.0 cM between G6.2000 and AL20.350 on B5 that explained 29% of the phenotypic variability in MRF02 (Table 2). This QTL also shares a common marker (G6.2000) with the QTL (G6.2000–G17.900 interval), described above. In previous work with different resistance sources, a QTL for root rot resistance linked to the common G17.900 marker was reported, but that QTL was not mapped (Schneider et al., 2001). The QTL in the current study displayed highly significant large effects (R2 = 29 and 30%) and were supported by LOD values > 8.0, significantly above the threshold value (LOD = 7.57). Additional QTL (AL20.700–G6.2000) that explained 33% of the variation for root rot resistance in MRF03, but explained only 1.2% of the phenotypic variation in the MRF02, were anchored to B5 with AL20.700 marker in the kidney IBL population (Fig. 2). The QTL with the small effect (1.2%) was not significant (P < 0.0526) but was highly significant in 2003 (P < 0.001; Table 2).
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25 cM on LG 1 (B5) between AL20.850 and G8.1400 in the cranberry IBL population (Fig. 2). The large-effect QTL that explained 53.3% of the phenotypic variability for root rot resistance in MRF02 was supported with a significant LOD score > 15 (LOD threshold value = 3.58; Table 2). The QTL in the cranberry IBL population on B5 shared a common flanking marker (AL20.850) with the QTL detected in the kidney IBL population, and the AL20.850 marker also served as an anchor to the integrated bean map. Most of the QTL on B5 could be considered major QTL due to their large effect supported by the high LOD values, relative to the QTL peak and threshold values determined by the permutation analyses (Table 2). Large-effect QTL (those QTL that explained 30% or more of the phenotypic variability) associated with resistance to root rot are useful starting points for marker-assisted selection. A large-effect QTL might also be due to a series of linked QTL, each of small effect (Flint and Mott, 2001). The regions where QTL are localized can be quite large as in the current study, and such regions may contain a number of minor QTL that can only be confirmed with additional fine mapping. Additional QTL were detected on a different region of B5 based on data from the kidney IBL population evaluated in trials in NY and in the greenhouse. These QTL, detected between AL20.850 and AJ4.3000 markers, explained 27 and 9.8% of the phenotypic variation for root rot resistance in the NYSAES and greenhouse trials, respectively (Fig. 2). Support for additional QTL in this region of B5 comes from another QTL (R2 = 7.3, P < 0.001) detected in cranberry population in MRF02 between AL20.850 and O12.800 markers (Table 2). Marker O12.800 was previously identified by Schneider et al. (2001) as linked to QTL for resistance to root rot, but the marker was not assigned to a LG. Although a QTL was not identified between O12.800 and G8.1400 in the kidney IBL population, the same RAPD markers displayed the expected size polymorphic fragments between Red Hawk and NSL and segregated in the IBL population, but these markers remained unassigned when creating the partial LGs for the kidney IBL population. Despite some inconsistencies between populations and location effects, the QTL analysis has clearly identified B5 as an important LG for the root rot resistance in common bean. Previously unassigned markers linked to resistance QTL for root rot were also mapped to B5. Other resistance factors previously mapped to B5 (Kelly et al., 2003) include QTL for resistance to common bacterial and halo blight (Pseudomonas syringae pv. phaseolicola) and the lipoxygenase gene, Lox-1, required during development of bean plants under desiccation stress (Porta et al., 1999). Despite the obvious connection between root health and water stress, the potential role of lipoxygenases in root rot resistance is speculative in the absence of direct evidence for co-localization of the Lox-1 gene and QTL for root rot resistance.
The second LG, where major-effect QTL for root rot resistance were detected, was B2. A QTL associated with the AJ4.350–X3.3054 markers explained a significant portion (R2 = 15.0, P < 0.001) of variation for root rot resistance in the kidney IBL population in NYSAES03 (Table 2). The AJ4.350 marker on LG 9 was anchored to B2 in the vicinity of the chalcone synthase locus, ChS (Ryder et al., 1987; Mohr et al., 1998), polygalacturonase-inhibiting protein, Pgip (Toubart et al., 1992; De Lorenzo et al., 2002), and the pathogenesis related protein, PvPR-2 (Walter et al., 1990). Plant defense response is a complex mechanism that is triggered by pathogen attack. In beans, several defense response genes co-localize with resistance QTL suggesting a functional relationship between the QTL and the defense response genes (Geffroy et al., 2000). Other QTL for resistance to root rot and white mold have been previously mapped to regions close to ChS, Pgip, and the PVPR-2 on B2, suggesting that physiological resistance to Fusarium root rot and white mold [Sclerotinia sclerotiorum (Lib.) de Bary] is associated with a generalized host defense response (Schneider et al., 2001; Kelly and Vallejo, 2005). A study of the biochemical response of soybean to F. solani f. sp. glycine infection showed that soybean roots inoculated in soil induced phenylalanine ammonia-lysase (Lozovaya et al., 2004). Phenylalanine ammonia-lysase is the first enzyme in the phenylpropanoid biosynthetic pathway that produces the phytoalexin glyceollin, and lignin, indicating that these defense response compounds may be involved in the partial resistance response to Fusarium. In addition, a QTL (V6.1500–P10.1600) that explained only 1.8% of the phenotypic variation for root vigor was detected in the cranberry IBL population. The small effect QTL was significant as it was supported by a maximum LOD value of 7.78 (LOD threshold value = 6.5). Root vigor was significantly and positively correlated with root rot scores for the cranberry IBL (r = 0.24; P < 0.001) population in MRF03. The QTL was located in the vicinity of the locus for the pathogenicity related protein PvPR-2 protein on B2. All the markers anchored to B2 of the integrated map were located close to marker (P10.1660) previously identified by Schneider et al. (2001) as associated with root rot resistance in common bean. The detection of the same QTL in different root rot resistance sources would suggest a more common generalized resistance response than the specific specialized response conditioned by major resistance genes.
The remaining QTL identified on LGs 5 and 8 could not be assigned to specific LGs on the bean consensus map due to the limited number of polymorphic markers common to the BJ RIL mapping population and the IBL populations evaluated in this study. In the cranberry IBL population, a QTL explaining 10.7% of the phenotypic variability for root rot resistance in the first greenhouse study and 33.6% of phenotypic variability in a second greenhouse study was detected in the same region of LG 5 (Table 2). The QTL spanned a distance of 11 cM between S19.1000 and S19.1100, but interestingly, C97407, not the NSL parent, contributed the favorable allele for this QTL. Lower root rot scores were also observed for C97409 parent (4.1–4.3) compared with Red Hawk parent (5.2–5.6) in the field, suggesting the presence of moderate levels of resistance in the cranberry parent (Table 1). Quantitative trait loci detected under greenhouse conditions in the susceptible parent C97407 must be expressed at an early stage of bean development as root rot evaluations were delayed to anthesis in the field environment. In the kidney IBL population, a QTL was identified between AN19.1300–H4.1200 markers that explained 39.0% of the phenotypic variability for root rot resistance in the second greenhouse evaluation (Table 2). Despite the lack of information on the location of these greenhouse associated resistance QTL, they can still be used in marker-aided breeding for root rot resistance. The lack of association between QTL identified in field or greenhouse experiments could result from masking of the genetic variation for physiological resistance present in the field by environmental factors and/or the interaction with other known root rot pathogens as in the NYSAES field environment. The quantification of root rot diseases is made more difficult by the presence of other soil borne pathogens and the large environmental variation in temperature and moisture that affect growth of F. solani in the field. In the current and previous studies of root rot in common bean, markers significantly associated with field root rot ratings were not significantly associated with greenhouse root rot ratings and vice versa, with the exception of AL20.850 marker on B5, which was significantly associated with greenhouse and field trials (Fig. 2). Detecting similar QTL associated with root rot resistance over years and/or locations is challenging.
Alternatively, breeders can use QTL associated with root rot resistance on different LGs to select and intermate progeny possessing complementary QTL for resistance. Multiple regression analyses using combinations of significant markers linked to QTL for root rot resistance and their interactions revealed that epistatic interactions were not significant. Up to 7.6 and 73.8% of phenotypic variation for greenhouse and field ratings, respectively, was explained by a set of QTL flanking markers that included AL20.850 (B5), G17.900 (B5), AJ4.350 (B2), O12.800 (B5), and V6.1500 (B2). In previous studies, 50% of the total phenotypic variation for root rot resistance was explained by two QTL (Chowdbury et al., 2002), whereas a subset of four markers accounted for only 29% of the phenotypic variation for root rot resistance (Schneider et al., 2001). In the current study, five marker-QTL associations were identified that accounted for up to 73% of the phenotypic variation for root rot resistance in the field. These markers included G17.900, O12.800, AL20.850 on B5, and AJ4.350 and V6.1500 on B2. G17.900 and O12.800 markers were linked to QTL previously identified by Schneider et al. (2001), but were unassigned. On the basis of linkage to other markers mapped to B5 on the bean integrated map, G17.900 and O12.800 markers must reside on B5 but appear to be associated with different QTL on that LG (Fig. 2). To enhance root rot resistance, the QTL linked to AL20.850 and AL20.500 on B5 could be combined with other QTL linked to the O12.800 marker on B5. AL20.850 was linked to the large-effect QTL (R2 = 27 and 53.3%) in both the kidney and cranberry IBL populations as well as in one greenhouse trial (R2 = 9.8%). The QTL linked to AL20.500 in the cranberry IBL population was also polymorphic in the kidney IBL population. Although the later QTL were not identified in both populations, the markers linked to this QTL associated with resistance can be utilized to enhance conventional breeding approaches by providing information that breeders can use to make educated choices of which putatively linked resistance loci, with large-effect QTL to combine in future bean cultivars.
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CONCLUSIONS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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ACKNOWLEDGMENTS |
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Received for publication January 10, 2005.
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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