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Crop Science 41:1253-1262 (2001)
© 2001 Crop Science Society of America

CELL BIOLOGY & MOLECULAR GENETICS

Mapping of QTL for Resistance to White Mold Disease in Common Bean

Soon O. Parka, Dermot P. Coyne*,a, James R. Steadmanb and Paul W. Skrochc

a Dep. of Horticulture, Univ. of Nebraska, Lincoln, NE 68583
b Dep. of Plant Pathology, Univ. of Nebraska, Lincoln, NE 68583
c Life Sciences Informatics, Monsanto Company, St. Louis, MO 63167

* Corresponding author (dpcoyne{at}unlnotes.unl.edu)


   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
White mold (WM), incited by Sclerotinia sclerotiorum (Lib.) de Bary, is a serious disease of common bean (Phaseolus vulgaris L.). However, plant breeders have had very limited success in developing resistant (R) cultivars. Molecular markers linked to genes for R to WM may improve selection for R. The objective was to identify random amplified polymorphic DNA (RAPD) markers linked to quantitative trait loci (QTL) for partial physiological resistance (PPR), partial field resistance (PFR), porosity over the furrow (POF), and plant height (PH) in a linkage map by means of recombinant inbred lines (RILs) from the cross ‘PC-50’ (R) x XAN-159 (susceptible). The parents and RILs were inoculated in two separate greenhouse experiments for each isolate and were also infected naturally in the field. Significant correlations (0.39, 0.47) were found for the WM reactions in the greenhouse and field. Nine candidate QTL were found affecting PPR isolate 152 (comparison-wise P < 0.05) with strong evidence (genome-wise P < 0.01) for three QTL on linkage groups (LGs) 4, 7, and 8, based on composite interval mapping analysis. Candidate QTL affecting PPR to isolate 279 were found on LGs 2, 3, 4, 7, and 8 with very strong evidence (genome-wise P < 0.001) for a QTL linked to the C locus for seedcoat pattern. Seven candidate QTL for PFR were observed on LGs 4, 7, 8, and 11. Six of the seven candidate QTL for PFR were found in the same locations as QTL for PPR. However, two of the seven genomic regions were associated with PFR and POF that may contribute to disease avoidance.

Abbreviations: CBB, common bacterial blight • CIM, composite interval mapping • cM, centimorgan • LG, linkage group • MRA, multiple regression analysis • PFR, partial field resistance • PH, plant height • POF, porosity over the furrow • PPR, partial physiological resistance • QTL, quantitative trait locus(i) • RAPD, random amplified polymorphic DNA • RCBD, randomized complete block design • RIL, recombinant inbred line • WM, white mold


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
WHITE MOLD is a destructive disease of common bean that results in reduced yield, number of seeds per plant, seed weight, number of pods per plant, and seed quality in dry beans (Steadman, 1979; Kerr et al., 1978). Yield losses of common bean due to this disease range from 13 to 80% under irrigation (Kerr et al., 1978; Schwartz et al., 1987). Recently, WM has been identified as the greatest disease constraint to bean production in the USA. Development of WM on bean is favored by temperatures of 10 to 25°C and moist conditions (Weiss et al., 1980). Control of WM with fungicides is difficult to achieve on indeterminate (Type III growth habit) dry edible beans in irrigated regions of the west and west central USA (Steadman, 1983). Cultural practices such as low plant populations, wide row spacing, reduced irrigation, and use of cultivars with porous canopies can reduce the disease severity, but they also reduce yield potential (Steadman, 1979, 1983; Fuller et al., 1984b). The development of bean cultivars combining PPR and architectural avoidance to WM could provide a means to reduce disease and improve yield.

Bean germplasm sources with partial resistance to WM have been reported (Leone and Tonneijck, 1990; Dickson et al., 1982; Hunter et al., 1982; Fuller et al., 1984a; Schwartz et al., 1987; Miklas et al., 1992a, b; Middleton et al., 1995). Quantitative inheritance of reactions to WM in common bean was noted by several investigators (Miklas and Grafton, 1992; Coyne et al., 1976; Fuller et al., 1984a; Lyons et al., 1987; Kolkman and Kelly, 1999), whereas a single dominant gene controlling resistance to WM in a P. vulgaris x P. coccineus L. cross was reported by Abawi et al. (1978). Low heritability of resistance to WM was reported by Coyne et al. (1976), Dickson et al. (1982), and Roberts et al. (1982), while Miklas and Grafton (1992) reported high heritability. Lyons et al. (1987) used recurrent selection as an effective breeding method for improvement of resistance to WM that is inherited quantitatively. Miklas and Grafton (1992) and Abawi et al. (1978) suggested using the backcross breeding method if a few major genes controlled partial resistance to WM.

Partial field resistance may be due to both PPR and plant architectural avoidance of WM (Steadman, 1983; Miklas and Grafton, 1992; Hunter et al., 1982). It is difficult to discriminate between these traits under field conditions because they are confounded (Miklas and Grafton, 1992). Architectural avoidance due to a porous plant canopy along with upright plant habit provides less favorable conditions for WM and reduces disease severity thus allowing selection of false positives for partial resistance (Fuller et al., 1984b; Schwartz et al., 1987). Avoidance may not hold up under severe disease conditions. Molecular markers associated with QTL affecting PPR, PFR, and plant architecture including POF would be useful for marker-assisted selection and may be the best method of selecting for WM resistance. However, markers linked to WM resistance have not been reported.

The objective of this study was to identify QTL for PPR to S. sclerotiorum isolates 152 and 279, PFR, POF, and PH in a genetic linkage map previously constructed by means of RILs from the common bean cross PC-50 (PPR and PFR) x XAN-159 (susceptible). This population was previously used to construct a genetic linkage map by random amplified polymorphic DNA (RAPD) markers. By this map, QTL and genes for resistance to common bacterial blight (CBB) incited by Xanthomonas campestris pv. phaseoli, specific (Ur-9) and adult plant (Ur-12) resistance to rust caused by Uromyces appendiculatus, and abaxial leaf pubescence (Pu-a) have been identified (Jung et al., 1997, 1998). QTL for bean seed weight and shape were also identified from this cross by Park et al. (2000). Thus, in addition to identifying QTL for WM resistance our objective was to determine the relationship between these newly identified QTL and the previously mapped QTL for CBB resistance and seed weight, and the genes for Ur-9, Ur-12, and Pu-a. An understanding of the genetic relationships of QTL for resistance to WM with QTL and genes for other traits will aid in the development of cultivars with resistance to multiple pathogens.


   MATERIALS AND METHODS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 REFERENCES
 
Plant Materials
Seventy RILs derived from the cross PC-50 x XAN-159 were developed by single-seed-descent (Arnaud-Santana et al., 1994). PC-50 was derived from a single plant selection in the landrace ‘Pompadour Checa’ in the Dominican Republic (Saladin et al., 2000). XAN-159 (Centro Internacional de Agricultura Tropical, Cali, Colombia) was derived from interspecific crosses between P. vulgaris and P. acutifolius A. Gray accession PI 319443 to introduce CBB resistance genes into a common bean genomic background (Thomas and Waines, 1984). PC-50 (Singh et al., 1991) and XAN-159 (Johns et al., 1997) possess Andean gene pool traits. Some of the important characteristics of the two parents are listed in Table 1.


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  		Table 1. A summary of selected characteristics of the two parents ‘PC-50’ and XAN-159 of Andean origin.

 
Sixty-five of the 70 RILs and the parents were planted in a randomized complete block design (RCBD) with four replications in the greenhouse at Lincoln, NE, on 12 Sept. 1997 (Exp. 1), 3 Nov. 1997 (Exp. 2), 15 Jan. 1998 (Exp. 3), and 10 March 1998 (Exp. 4) for inoculation of S. sclerotiorum isolates 152 (Exp. 1 and 2) and 279 (Exp. 3 and 4). Five of the 70 RILs in each experiment were not planted because of lack of seeds. The RILs utilized here were the same ones that were utilized previously by Jung et al. (1997) to construct the linkage map. Two plants were grown per clay pot, volume 1450 cm3, containing equal parts by volume of sand, sphagnum peat moss, vermiculite, and sharpsburg silty clay loam soil. Peters 20N:10P:20K Peat-Lite Special (Scotts-Sierra Horticultural Products Co., Marysville, OH) water soluble fertilizer was applied weekly. The chemical Orthene 75 s soluble powder (active ingredient acephate: O,S-dimethyl acetyl-phosphophoromidothioate) (Valent Co., Walnutcreek, CA) was applied weekly to control white flies [Trialeurodes vaporariorum (Westwood)]. Approximate day/night greenhouse temperatures were 26±2/22±2°C in each experiment. Lengths of natural days/nights ranged from 12/12 to 10/14 h in each experiment.

For Exp. 5, the parents and 63 of the 70 RILs were planted in a RCBD with four replications in a field naturally infested with S. sclerotiorum in Scottsbluff, NE, on 2 June 1999. Seven of the 70 RILs in this experiment were not planted because of lack of seeds. A fertilizer containing 16N:18P:5K was applied to the plot area at the rates of 76, 85, and 24 kg ha-1, respectively. Single row plots were 1.2 m long and spaced 0.5 m apart. Fifteen to 20 seeds of each line were planted 15 to 24 cm apart. Approximate day/night field temperatures were 32±3/22±3°C and the lengths of natural days/nights ranged from 15-13/9-11 h.

Inoculation
The straw test, as reported by Petzoldt and Dickson (1996), was used to evaluate partial resistance in the greenhouse in Exp. 1 to 4. Commercial 6-mm-diam straws were cut into 5- to 7-cm segments. One end of each cut straw segment was closed with a staple and the other open end was inserted into the advancing mycelial margin of a culture of S. sclerotiorum grown on potato dextrose agar (PDA). The two S. sclerotiorum isolates, 152 and 279, used in this study were isolated from great northern (1980) and pinto (1996) beans, respectively, grown in Nebraska. The apical meristem of each plant was cut 28 d after planting using a sharp blade, then covered by the straw containing the PDA disk with S. sclerotiorum mycelium.

Phenotypic Data
The progress of infection by S. sclerotiorum isolates 152 and 279 on each plant was recorded at 10 d after inoculation in the greenhouse in Exp. 1 to 4. The disease rating scales described by Petzoldt and Dickson (1996) as follows were used: 1 = no disease, 3 = infection around the cut part of the main stem, 5 = infection up to the first node, 7 = infection at or beyond the second node, and 9 = dead plant. The percentage of the plant canopy infected by S. sclerotiorum (disease severity) was recorded for each plant on 9 Sept. 1999 in the field in Exp. 5. Porosity over the furrow was recorded for each row on 8 Sept. 1999 (Exp. 5). A scale described by Deshpande (1992) as follows was used: 1 = open space over furrow-complete porosity, 2 = most of soil surface showing through the canopy, 3 = some soil surface showing moderate porosity, 4 = no soil surface showing but some porosity within canopy, and 5 = no porosity-complete coverage of canopy. Plant height in centimeters was also recorded per row on 23 Aug. 1999 (Exp. 5).

Linkage Map Construction
The RAPD marker-based linkage map was originally developed by Jung et al. (1997) using 70 RILs of the same cross. Subsequently, to facilitate integration of this map with other RAPD and RFLP maps in bean, the segregation data were reanalyzed by Skroch (1998) with some markers being added and some omitted from the different LGs. LG names were changed from Jung et al. (1997) to reflect their correspondence with the integrated common bean linkage map (Freyre et al., 1998; Vallejos et al., 1999) as described by Skroch (1998).

A total of 10 LGs were identified by Jung et al. (1997). On the basis of the cosegregating markers used for construction of integrated RAPD-RFLP linkage maps, these 10 LGs were consolidated to nine LGs spanning 404 centimorgan (cM) (Skroch, 1998). In this report, LGs will be referenced by numbers 1 through11 to refer to LGs B1 through B11 from Freyre et al. (1998). The correspondence of the LG names in the PC-50 x XAN-159 (PX) map of Jung et al. (1997) with the LG names in the present report are PX2 = 2, PX3 = 3, PX6 = 4a, PX8 = 4b, PX7 = 5, PX5 = 6, PX4 = 7, PX1 = 8, PX9 = 10, and PX10 = 11. In addition to RAPD markers, the C locus for seedcoat pattern was previously mapped to LG 8 (PX1), the V locus for flower color (data not presented) was previously mapped to LG 6 (PX5), and the Pu-a gene for abaxial leaf pubescence (data not presented) was mapped to LG 3 (PX3) (Jung et al., 1997, 1998).

Detection of QTL
Narrow-sense heritabilities for the reactions to S. sclerotiorum isolates 152 and 279 were calculated from the components of variance method (Fehr, 1987). Correlations between traits were calculated. Deviations from normality for traits were determined by a W statistic (Shapiro and Wilk, 1965). Heritability, correlation analyses, and simple linear regression were conducted by the Statistical Analysis System (SAS, 1982). The analysis of QTL affecting PPR to isolate 152 was conducted on the basis of means from Exp. 1 and 2 (described above). The QTL conditioning PPR to isolate 279 was analyzed on the basis of means for Exp. 3 and 4. For detection of QTL for PFR, POF, or PH the analysis was based on Exp. 5.

Two methods of analysis were used to identify significant marker locus–trait associations: simple linear regression and composite interval mapping (CIM). The results of the regression analysis were very similar to, and consistent with, the results from the CIM analysis and are thus not reported in detail. The CIM analysis was applied to the trait mean and marker data to more precisely identify the locations of QTL (Zeng, 1994). CIM analysis was performed by QTL Cartographer software (Basten et al., 1996) version 1.13g. Cofactors were chosen on the basis of the results of a forward stepwise multiple regression analysis (MRA) using the QTL Cartographer program "SRmapqtl" (Model 6). Output from SRmapqtl was used directly so the number of cofactors varied for each trait depending on the number of significant markers in the MRA results. A window size of 20 cM was used. P-values were computed on a comparison-wise and genome-wise basis on the basis of the permutation test (Churchill and Doerge 1994) provided as part of the QTL Cartographer software with 1000 permutations for each test.

For comparison of QTL for PPR and PFR with QTL for seed traits, in this population, the data from Park et al. (2000) were reanalyzed as described above with a 20 cM window for CIM analysis instead of the 10 cM window used in the original study. In addition, CIM analysis was performed on the means of CBB resistance measurements taken by Jung et al. (1997) for first and later developed trifoliolate leaves, in this same population.


   RESULTS AND DISCUSSION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
REFERENCES
 
Frequency Distributions for Reaction to S. sclerotiorum
Clear separation was observed for the disease rating of the parents to both pathogen isolates in the greenhouse tests (Fig. 1). All plants of XAN-159 were completely wilted 10 d after inoculation by the straw test. In contrast, PC-50 plants were resistant to the two isolates and showed either no disease or a trace of disease on the inoculated stems. Several techniques such as the juvenile stem inoculation test (Dickson et al., 1982), the limited-term inoculation test (Hunter et al., 1982), the excised stem test (Miklas et al., 1992a), and the callus-weight assay (Miklas et al., 1992b) have been utilized to screen bean germplasm for PPR to WM in the laboratory, growth chamber, greenhouse, or in vitro. However, these techniques have some limitations such as lack of uniformity, lack of precision, nonrepeatability and complexity, and do not always correlate with field conditions (Petzoldt and Dickson, 1996; Miklas et al., 1992a; Steadman et al., 1997). The straw test (Petzoldt and Dickson, 1996) was used in this study because it provides more consistent, repeatable, and uniform results than other tests (Hall and Phillips, 1997), and also many plants can be inoculated rapidly by one person. Significant correlations have been reported between disease severity of bean plants infected naturally in the field and those inoculated by the straw test (Hall and Phillips, 1997). The PPR of PC-50, detected here by the straw test under greenhouse conditions, was also noted in our field experiment and in national WM field nurseries under natural infection (Steadman et al., 1999). The mean WM severity over four field nursery locations for the PPR entries was 27% for PC-50, 33% for G122, and 26% for ‘Ex Rico 23’ (Bunsi), while the severity for the most susceptible entries (checks) ranged from 50 to 56%. PC-50 is a useful source of resistance to WM that could be used with other germplasm sources such as G122 and ‘Ex Rico 23’.



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  		Fig. 1. Frequency distributions for greenhouse and field white mold (WM) disease caused by S. sclerotiorum, porosity over the furrow, and plant height of recombinant inbred lines derived from the common bean cross ‘PC-50’ (resistant to WM) x XAN-159 (susceptible to WM).

 
Continuous distributions for the disease reactions of the RILs to S. sclerotiorum isolates 152 and 279 were observed in greenhouse experiments (Fig. 1), suggesting that PPR to the two isolates was quantitatively inherited. This result is consistent with previous reports in common bean indicating quantitative inheritance of disease reactions to S. sclerotiorum (Miklas and Grafton, 1992; Dickson et al., 1982; Roberts et al., 1982; Fuller et al., 1984a; Lyons et al., 1987). Although Abawi et al. (1978) reported that a single dominant gene controlled PPR to WM in F2 and backcross populations derived from P. vulgaris x P. coccineus crosses, this result was not confirmed in subsequent generations. Several investigators reported additive genetic effects for PPR (Miklas and Grafton, 1992; Dickson et al., 1982; Fuller et al., 1984a; Lyons et al., 1987), while Fuller et al. (1984a) reported partial dominance in two F2 bean populations.

A continuous distribution for the reaction of the RILs to S. sclerotiorum was observed in the field (Fig. 1) suggesting quantitative inheritance for PFR to WM. Quantitative inheritance of PFR to WM has been reported in common bean (Miklas and Grafton, 1992; Coyne et al., 1976; Fuller et al., 1984a). Miklas and Grafton (1992) and Fuller et al. (1984a) also observed additive genetic effects for PFR in several populations. However, Coyne et al. (1976) found dominance effects for PFR in F2 populations. In addition, continuous distributions for POF and PH were observed in the field (Fig. 1) consistent with quantitative inheritance for these traits. Frequency distributions for the disease reactions to WM in the greenhouse and field, POF ratings, and PH were normal (P = 0.10–0.18).

Low (0.24 and 0.23) narrow-sense heritability estimates were found for the disease reactions to S. sclerotiorum isolates 152 and 279 in these RILs in the greenhouse experiments. These low heritability estimates for PPR to WM were close to the estimates reported by Roberts et al. (1982), and Miklas and Grafton (1992). However, Miklas and Grafton (1992) also reported an intermediate heritability estimate for PPR to WM in a navy x navy cross.

A significant correlation (r = 0.67) was observed between the reactions to each WM isolate in the greenhouse in this RIL population. Significant correlations (r = 0.39 and r = 0.47) were noted between the reactions to two isolates by means of the straw test in the greenhouse and the reaction to WM after natural infection in the field, indicating that selection of both PPR and PFR is feasible. These correlations were similar to those reported previously in common bean by Hall and Phillips (1997). Miklas and Grafton (1992) noted a significant correlation (r = 0.37) between the WM reaction using lesion length on excised stems from greenhouse grown plants and the WM reaction using a disease incidence index under a natural field infection in one bean population. However, they found nonsignificant correlations between these two traits in two other bean populations. A significant negative correlation of -0.33 was observed between PH and natural WM infection in the field. A correlation between POF and natural field WM infection was nonsignificant. Porosity over the furrow and PH were highly correlated (r = 0.74).

QTL Affecting Resistance to White Mold Disease
CIM results indicated strong evidence for three QTL affecting PPR to isolate 152 at marker loci AI13.700, J09.950, and H19.1250 on LGs 4a, 7, and 8 that exceeded both comparison-wise and genome-wise significance thresholds (P < 0.01) (Table 2) (Fig. 2). The results also suggested weak evidence for six additional QTL affecting PPR to isolate 152 at marker loci D05.1100, Y07.1200, O13.1350, AP07.1800, BC493.1300, and U10.1000 on LGs 5, 6, 7, 10, and 11 that exceeded only comparison-wise significance threshold (P < 0.05). When entered into a stepwise MRA, the multilocus model containing the three most significant markers and marker D05.1100 explained 39% of the phenotypic variation for the PPR trait.


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  		Table 2. Summary of the results from composite interval mapping analysis of marker and trait data for identification of QTL associated with partial physiological resistance (PPR) to white mold caused by two isolates of Sclerotinia sclerotiorum in recombinant inbred lines from the common bean cross ‘PC-50’ (PPR) x XAN-159 (susceptible) in greenhouse experiments.

 


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  		Fig. 2. Composite interval mapping (CIM) results for identification of QTL affecting partial physiological resistance (PPR) to S. sclerotiorum isolates 279 (squares) and 152 (triangles), partial field resistance (PFR) (crosses), porosity over the furrow (POF) (filled circles), and plant height (PH) (open circles). The likelihood ratio test statistic (vertical axis) is plotted against the analysis position (cM) for each linkage group (the significance of relevent peaks are indicated in Tables 2 and 3). The locations of a subset of markers are shown for reference. Results are shown for the six linkage groups with the most significant effects. To simplify the plots, the CIM results for architectural traits are shown only for those linkage groups where significant effects were found.

 

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  		Table 3. Summary of the results from composite interval mapping analysis of marker and trait data for identification of QTL associated with partial field resistance (PFR) to white mold, porosity over the furrow (POF), and plant height (PH) in recombinant inbred lines from the common bean cross ‘PC-50’ (PFR) x XAN-159 (susceptible) in the field experiment.

 
Seven candidate QTL (P < 0.05) for PPR to isolate 279 were identified on LGs 2, 3, 4, 7, and 8 by CIM analysis (Table 2) (Fig. 2). QTL linked to the C locus was also highly significant in PPR to isolate 279, as determined on the basis of genome-wise significance threshold (P < 0.001). Three markers G03.1150, J09.950, and the C locus on LGs 3, 7, and 8 were significant in the MRA with the multilocus model explaining 40% of the phenotypic variation for the trait. Markers W02.1100, U10.900, BC493.1000, and O20.1000 were not significant in the MRA. The C locus on LG 8 accounted for 26% of the phenotypic variation for the trait.

Strong evidence for two QTL controlling PFR to WM on LGs 7 and 8 that exceeded both comparison-wise and genome-wise significance thresholds (P < 0.05) was identified on the basis of CIM analysis (Table 3) (Fig. 2). Four additional QTL for PFR were detected at marker loci U10.900, R20.1250, U03.1500, and AE07.800 on LGs 4, 8, and 11 by a relatively low comparison-wise P-value (P < 0.01). Weak evidence was found for an additional QTL affecting PFR at marker locus AM07.600 on LG 8. The two most significant markers J09.950 and AO17.1050 on LGs 7 and 8 explained 16 and 9% of the phenotypic variation for the PFR trait, respectively. Overall, six of the seven genomic regions significantly associated with PFR were also significantly associated with PPR to one or both isolates.

A total of 21 significant marker locus-trait associations were identified on LGs 2, 3, 4, 5, 6, 7, 8, 10, and 11 in the population (Tables 2 and 3) indicating 7 to 9 QTL for WM resistance traits. Miklas and Grafton (1992) reported transgressive segregation for PPR and PFR in bean populations, suggesting that parents possessed different genes controlling each trait. However, for the 21 significant marker locus-trait associations identified for PPR or PFR in this study, we found that only the PC-50 parent contributed alleles associated with greater disease resistance. Marker J09.950 on LG 7 was consistently associated with PPR to both isolates in the greenhouse as well as PFR to WM, and explained 5 to 16% of the phenotypic variation for the traits (Tables 2 and 3). Miklas et al. (2000) also found a marker associated with PPR to WM on LG7 but did not detect any QTL for PPR on other LGs.

Trait correlations, if genetic in nature, imply either genetic linkage of genes controlling variation for each trait or pleiotropic control of a single gene on both traits. Six of the seven genomic regions associated with PFR were also significantly associated with PPR to one or both isolates. These results strongly suggest that RAPD markers associated with QTL affecting both PPR and PFR, particularly J09.950, could be used for simultaneous selection for both WM traits.

For POF, four candidate QTL were indicated on LGs 2, 8, and 10 by CIM analysis (Table 3 and Fig. 2). QTL linked to marker H18.1550 on LG 8 was highly significant for POF on the basis of comparison-wise and genome-wise significance thresholds (P < 0.001). Two markers AH18.700 and AP07.1800 on LGs 8 and 10 were relatively highly associated with QTL based on comparison-wise significance threshold (P < 0.01). Marker H18.1550 accounted for 11% of the phenotypic variation for the porosity trait.

Four candidate QTL affecting PH were found on LGs 5, 7, and 8 by CIM analysis (Table 3) (Fig. 2). Marker T15.850 on LG 8 was significantly associated with PH on the basis of both comparison-wise and genome-wise significance thresholds (P < 0.01). Two additional QTL for PH were identified at marker loci BC462.1150 (LG 7) and J20.800 (LG 7) by a low comparison-wise P-value (Pc < 0.001). Marker H15.450 on LG 5 was weakly associated with an additional QTL. The three most significant markers J20.800, BC462.1150, and T15.850 accounted for 10% to 15% of the phenotypic variation for the PH trait.

Both PPR and plant architectural avoidance are involved with PFR expression (Steadman, 1983; Miklas and Grafton, 1992). PPR and architectural avoidance are confounded in field plots designed to detect reduced WM severity (Steadman, 1983; Hunter et al., 1982). It is especially difficult to differentiate the contributions of these traits under irrigated conditions in semiarid regions. Our analysis indicates QTL for PH in the most important regions for PPR on LGs 7 and 8. Resistance to S. sclerotiorum isolates in the greenhouse found in these regions should be based on physiological resistance rather than avoidance. However, without the WM test in the greenhouse, we could conclude that PFR was due to avoidance by an open plant architecture. Six of the seven QTL associated with PFR based on CIM were also found for PPR, suggesting that PFR expression was mainly due to PPR. The results suggesting that both PPR and PFR were primarily controlled by the same QTL is not consistent with the finding of Fuller et al. (1984a) who suggested that the two traits were controlled by different genes. Of seven markers associated with QTL for PFR, only one, at marker locus U03.1500 on LG 8, was also associated with canopy porosity.

Although PC-50 and XAN-159 differ architecturally, their growth habits are similar. Populations with greater variation in plant architectural traits may reveal a more dramatic relationship between POF, PH, and PFR to white mold. Thus, the relationship between physiological resistance and plant architecture needs further investigation in other populations. Architectural avoidance, due to open canopy and upright bean plant habit, is an important factor for decreasing WM severity in the field under west and west central USA conditions (Fuller et al., 1984b; Schwartz et al., 1987). A breeding approach that combines both PPR and architectural disease avoidance could enhance the PFR to WM in beans. The merit of RAPD markers and the C locus associated with QTL for PPR detected here will be investigated in breeding for enhanced WM resistance and for combination with architectural avoidance to either protect or enhance resistance, both under irrigation in semiarid regions and in rainfed production areas.

Relationships of Resistance to White Mold with Other Traits
All candidate QTL for physiological and field resistance to WM and plant architectural traits which were highly significant on the basis of the comparison-wise error rate (P < 0.001) or significant on the basis of the genome-wise error rate (P < 0.05) were found on LGs 4, 7, and 8. For these traits, only weak evidence for QTL was found on other LGs. All regions showing significant effects on these three LGs have also been associated with variation for one or more morphological traits, or resistance to CBB (Fig. 3). Perhaps the most interesting region lies on LG 8, near the C locus, where a highly significant effect for PPR to isolate 279 is linked to the largest effects for PH and POF, and a highly significant effect for PFR. Effects for all four traits in this region were significant at both the comparison-wise and genome-wise significance thresholds. Thus, both physiological resistance and favorable plant architecture are likely contributing to the identification of PFR QTL in this region.



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  		Fig. 3. Linkage map for the ‘PC-50’ x XAN-159 mapping population with locations of QTL identified by composite interval mapping. Bars to the left of each linkage group indicate the intervals having significant trait associations based on a comparison-wise error rate of P < 0.05. Filled bars represent traits evaluated in the present study while open bars represent traits evaluated originally in this population by Park et al. (2000) and Jung et al. (1997) for seed size and common bacterial blight traits, respectively. Arrows indicate the most likely locations of QTL based on the locations of the maximum value of the composite interval mapping likelihood ratio test statistic in each region. For traits evaluated in the present study: PPR152 and PPR279 = partial physiological resistance to S. sclerotiorum isolates 152 and 279, respectively; PFR = partial field resistance; POF = porosity over the furrow; and PH = plant height. For other traits, CBB = common bacterial blight resistance; SW = seed weight; SH = seed height; and SL = seed length. Linkage groups are named B 1-B 11 and A-K to indicate their correspondence with the map of Freyre et al. (1998) and Vallejos et al. (1999), respectively. Markers that were used directly in the integration of RFLP and RAPD maps by Freyre et al. (1998) are underlined and in bold font.

 
The relationship between field resistance and physiological resistance appears to be more direct where candidate QTL for PFR were identified on LGs 4, 7, and 8 near marker H19.1250. In these three regions, highly significant effects for PPR to isolate 152 were found at the same map locations as the most likely location for PFR QTL.

As noted previously by Park et al. (2000), QTL for CBB are consistently associated with QTL for seed size or shape. Jung et al. (1997) reported that the QTL for CBB resistance in regions on LGs 6 and 8 appeared to be on DNA segments introgressed from P. acutifolius. This is consistent with the derivation of CBB resistance in XAN-159 from a small seeded P. acutifolius accession (Jung et al., 1997) and the consistent relationship between the variation in seed traits and CBB resistance in this population. Park et al. (1999) confirmed these QTL for CBB resistance in backcross and F2 populations.

The QTL for CBB on LGs 2, 6, 7, and 8 were described previously by Jung et al. (1997). However, the CIM analysis reported here indicated an additional highly significant effect (P < 0.001) for CBB resistance on LG 4 also tightly linked to significant effects for seed size and shape as well as candidate QTL for field and physiological resistance to WM. QTL for CBB resistance and seed size were also associated with resistance to WM on LGs 7 (near J09.950) and LG 8 (near marker H19.1250). Where QTL for CBB and WM resistance are linked, they are generally linked in repulsion because XAN-159 contributes the resistance to CBB and PC-50 contributes the resistance to WM. The CBB QTL associated with marker C07.900 is an exception in that the CBB resistance allele at this locus is contributed by PC-50.

Marker G03.1150 on LG 3 was associated with larger seed weight and PPR, and was also linked to the Pu-a gene at a distance of 20.2 cM. Mmbaga et al. (1996) reported that abaxial leaf pubescence contributed to adult plant resistance to rust. The Ur-9 and Ur-12 rust resistance loci were not associated with PPR and PFR. There is the potential that the RAPD markers can be used to combine PPR, PFR, larger seed size and/or CBB and rust resistance. The merit of using markers to pyramid these QTL should be investigated further.


   ACKNOWLEDGMENTS
 
We acknowledge financial support from the Title XII Bean/Cowpea CRSP (AID Contract No. DNA-1310-G-SS-6008-00), the Nebraska Dry Bean Commission, and the Nebraska Dry Bean Growers Association. We also appreciate the constructive criticism of two reviewers, Drs. James Specht and Don Lee, Department of Agronomy, University of Nebraska-Lincoln, to improve the manuscript. We also appreciate Dr. E. Arnaud-Santana, CIAS, Dominican Republic for providing seed of RIL, and Dr. G. Jung, Department of Plant Pathology, University of Wisconsin-Madison for indications of resistance to WM in PC50 in preliminary screening of PPR to WM. We also thank technicians Becky Higgins, Lisa Sutton, Clay Carlson, and James Reiser, University of Nebraska-Lincoln, for their assistance.


   NOTES
TOP
 NOTES
ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
This paper was published as paper no. 12816 Journal Series, Nebraska Agricultural Research Division. Research was conducted under Projects 20-036 and 20-042.

Received for publication June 16, 2000.


   REFERENCES
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 




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