Abstract
Solanum habrochaites S. Knapp and D.M. Spooner accession LA1777 have reported resistance to the sweetpotato whitefly (SPWF), Bemisia tabaci (Genn.). An interspecific F2 population of 171 plants between tomato [Solanum lycopersicum L. (formerly Lycopersicon esculentum Mill.)] and LA1777 was bioassayed against adult SPWF in a greenhouse using clip cages. A selective genotyping analysis was used with 11 resistant and 10 susceptible plants to locate resistance genes by testing them with molecular markers spanning most of the tomato genome at about 10-cM intervals. Markers in four regions were found to be associated with resistance, where three of them showed significantly strong associations and one showed a weak association through chi-square and analyses of variance. However, through quantitative trait locus (QTL) analysis using molecular markers, all four regions were identified as major QTLs with logarithm of odds (LOD) values of 4.87 to 5.95. The four QTLs were identified near the markers TG313 on chromosome 10, C2_At2g41680 on chromosome 9, TG523/T0408 on chromosome 11, and TG400/cLEG-37-G17 on chromosome 11. Multiple regression analysis produced similar results as above with fixed effects of single loci as well as interaction among some of the QTLs.
Tomato is widely grown and economically one of the most important vegetable crops worldwide, with a value of over $1.4 billion in the United States alone (USDA, 2008). Biotype B of the sweetpotato whitefly (SPWF), also known as the silverleaf whitefly (Bemisia argentifolii Bellows & Perring), is one of the most damaging insects pests of tomato. The pest causes significant crop losses through phloem sap feeding and induction of plant disorders, including irregular ripening of tomato (Schuster et al., 1996). SPWF causes damage indirectly through the transmission of plant viruses, primarily begomoviruses, one of the most damaging of which is tomato yellow leaf curl virus (TYLCV) (Polston, 2001; Polston and Anderson, 1997; Zeidan et al., 1999). TYLCV can reduce yield by up to 100%, depending upon time of infection (Saikia and Muniyappa, 1989).
The SPWF is difficult to control with insecticides first because it feeds and oviposits mainly on the abaxial leaf surfaces (Sharaf, 1986), and second because it has developed resistance to most classes of insecticides applied for its control (Byrne et al., 2003; Denholm et al., 1996; Palumbo et al., 2001), including the new systemic neonicontinoid insecticides imidacloprid and thiamethoxam (Elbert and Nauen, 2000; Schuster et al., 2010). Clearly, host plant resistance could provide economical and environmentally sound management of the pest. However, breeding efforts have been hampered by association of resistance with horticulturally detrimental traits associated with the wild species (linkage drag).
Some work with broad-based virus resistance genes in tomato for whitefly-vectored begomoviruses is in progress (Ji et al., 2007; Vidavsky, 2007). Some breeding lines are available that have TYLCV-specific resistance genes from S. chilense (Dunal) Reiche, S. peruvianum L. S. pimpinellifolium L., and S. habrochaites accessions (Ji et al., 2007; Lapidot et al., 1997; Pico et al., 1999; Scott, 2007; Vidavsky and Czosnek, 1998; Zamir et al., 1994) and that provide one method to control losses to TYLCV. However, if SPWF is not controlled, irregular ripening can make fruits unmarketable (Schuster et al., 1996). Thus, breeding SPWF-resistant cultivars would be desirable as adjuncts to TYLCV-resistant cultivars.
Accessions of S. habrochaites f. glabratum C. H. Mull., S. habrochaites f. typicum Humb. & Bonpl., S. pennellii Correll, and S. pimpinellifolium have been reported to be resistant to B. tabaci (Alba et al., 2005; Berlinger et al., 1983; Dahan, 1985; Heinz and Zalom, 1995; Liedl et al., 1995; Muigai,1997; Muigai et al., 2003; Shevach-Urkin, 1983; Snyder et al., 1998; Yorit, 1986). The S. habrochaites f. typicum accession LA1777 was highly resistant to B. tabaci, resulting in fewer numbers of immature life-stages per unit area of leaflet relative to S. lycopersicum (Muigai et al., 2003). The whitefly resistance in S. habrochaites was related to naturally occurring allelochemicals present in single-lobed glandular trichomes (type IV) that do not occur in cultivated tomato (Muigai et al., 2002). In S. pennellii, acylsugars present in type IV trichomes were related to whitefly resistance (Blauth et al., 1998; Lawson et al., 1997). The S. habrochaites accession LA1777 contains volatile compounds, including germacrene D, dedecatriene, and α-farnesene (Fridman et al., 2005), and have demonstrated high levels of repellent and fumigant activity against B. tabaci adults (Muigai et al., 2002). The resistant phytochemicals have been reported to be controlled by polygenes (Frelichowski and Juvik, 2005; Maliepaard et al., 1995; Mutschler et al., 1996; Rahimi and Carter, 1993).
In an earlier study to locate SPWF resistance genes, 94 of the 98 recombinant inbred lines (RILs) of tomato (Monforte and Tanksley, 2000) were tested for B. tabaci egg deposition and for the presence of type IV and type VI (four-lobed) glandular trichomes (Momotaz et al., 2005). None of the RILs showed any resistance to SPWF nor had type IV trichomes. These results likely indicate that resistance is controlled polygenically, but resistance could also be controlled by a gene or genes in the 15% of the genome not covered by the RILs tested (Momotaz et al., 2005). Because no RILs were resistant to SPWF, we developed an F2 population from tomato and S. habrochaites accession LA1777 to locate SPWF resistance genes that would be combined in some of the plants.
The objective of this work was to identify quantitative trait loci (QTLs) associated with SPWF resistance derived from LA1777 using selective genotyping, QTL, and multiple regression analyses.
Materials and Methods
Plant materials.
In Spring 2002, determinate fresh market tomato inbreds Fla. 7771, Fla. 7171, and Fla. 7324 were used as seed parents and separately crossed with S. habrochaites accession LA1777 to obtain F1 seeds. In Fall 2003, bulked pollen from plants of all three F1 crosses was used to sib-pollinate all the F1 plants to produce a single F2 population as this allowed for better seed production than doing separate sib pollinations for each cross.
Whitefly and trichome bioassay.
In Spring 2004, 171 F2 plants, three control plants each of susceptible parent cultivar E6203, resistant parent LA1777, and their F1, were grown in an insect-proof greenhouse. Supplemental lighting was provided using 40-W fluorescent and 300-W incandescent light bulbs to obtain a 16/8-h (light/dark) photoperiod. The lights were suspended above the plants and were raised as the plants grew.
Plants were maintained using the cultural practices of Momotaz et al. (2005). After ≈3 to 4 weeks, the plants were moved to plant growth rooms with the temperature at about 27 °C and supplemental fluorescent lighting set at a 16/8-h (light/dark) photoperiod. Ten adult nonviruliferous whitefly females were confined in clip cages (2 cm diameter, 1 cm high) on the abaxial surface of a lateral leaflet of the leaf at the fifth node from the top of each plant. After 24 h, the number of living and dead adults and the number of eggs were counted. The bioassays were repeated two more times at about 1-week intervals to confirm the results of the first bioassay. The whitefly data were averaged over the three bioassays. The clip cages were constructed in the vegetable entomology laboratory at Wimauma, FL, with 0.49-mm size mesh, which was whitefly- and predator-proof.
At the first bioassay, the lateral leaflet opposite the one used for the insect assay was used to assess densities of type IV trichomes (Luckwill, 1943). Counts were made on two binocular-dissecting microscope fields at 50× magnification from the interior middle section of the abaxial leaf surface and a mean score was calculated (Momotaz et al., 2005). Eleven plants from the population were selected as resistant (R) based on low numbers of eggs deposited (0–17 eggs), high adult mortality, and high number of type IV trichomes, while 10 plants were selected as susceptible (S) based on their low adult mortality, high numbers of eggs deposited, and 0 to very few type IV trichomes (Table 1).
Sweet potato whitefly (SPWF) egg deposition, SPWF adult mortality, type IV trichomes, and genotypes at putative SPWF resistance loci for controls and resistant and susceptible F2 tomato plants derived from LA1777 (Solanum habrochaites) crossed with three susceptible tomato lines.
DNA extraction and marker selection.
Total genomic DNA was isolated from the tissues of fully expanded leaves using a simple DNA isolation procedure (Fulton et al., 1995). Over 400 polymerase chain reaction (PCR)-based molecular markers, polymorphic for the R and S parents, at about 10-cM intervals on each chromosome, were used to find regions associated with resistance. Markers were selected from the integrated Tomato-EXPEN 2000 map of Fulton et al. (2002) to screen the whole genome. These included cleaved amplified polymorphic markers (CAPs), sequence characterized amplified region (SCAR) markers, conserved orthologous sequence (COS), conserved orthologous sequence II (COSII) that were designed from public sequences available at Sol Genomics Network (SGN, 2008) or markers from the literature (Bai et al., 2003, 2004a, 2004b; Balvora et al., 2001; Doganlar et al., 1998; Fulton et al., 2002; Hemming et al., 2004; Yaghoobi et al., 2005; Williamson et al., 1994; Wu et al., 2006). Selected polymorphic markers that were associated with egg deposition or type IV trichome density through selective genotyping analysis were used to screen 138 of 171 F2 plants for QTL analysis. Codominant PCR-based markers were used because they can distinguish heterozygotes from homozygotes.
PCR amplification, electrophoresis, and visualization/molecular markers.
PCR amplification was carried out with a Gene Amp® thermocycler (Applied Biosystems, Foster City, CA) following the procedures of Momotaz et al. (2004) in 10-μL reaction volumes at various annealing temperatures, mostly 55 °C. The PCR products were then separated on 2% (w/v) agarose gels (molecular biology grade; Fisher, Pittsburgh) containing ethidium bromide (1.0 μg·mL−1) in 1× TBE buffer, visualized under ultraviolet transillumination, and photographed using AlphaImager® Imaging System (Alpha Innotech, San Leandro, CA). For CAPs markers, 4 μL of PCR product was used for restriction digestion following the manufacturer's recommendations (New England Biolabs, Ipswich, MA) (Momotaz et al., 2007). Restriction fragments were separated on 2% (w/v) agarose gel as documented above.
Selective genotyping.
Plants at the tail ends of the F2 were selected (Darvasi and Soller, 1992) for R and S based on egg deposition, adult mortality, and type IV trichome numbers. The 11 R and 10 S plants from the F2 population were each tested separately for the initial marker analysis. The DNA from R and S plants were amplified with selected codominant polymorphic markers covering the whole genome to identify the markers linked to SPWF resistance genes. Use of codominant markers allowed identification of the plants into three groups at each locus: plants homozygous (hh) for the S. habrochaites allele, heterozygous plants (he), and plants homozygous (ee) for the tomato allele. The association between markers and resistance to SPWF was assessed by chi-square and with one-way analysis of variance (ANOVA) based on the number of SPWF eggs laid on leaves after 24 h in clip cages (SAS, version 9.1; SAS Institute, Cary, NC). Chi-square analysis was performed to estimate expected frequencies of alleles in the R and S plants based on observed frequencies. We defined indicator variables for a LA1777 R allele as 1, heterozygote as 0.5, and the S allele as 0 for each marker.
QTL and stepwise multiple regression analyses.
Analysis was performed on 138 of 171 F2 plants comparing the genotypic marker data with the phenotypic egg count data and the type IV trichome counts using Map-Maker/QTL 1.1 (Lincoln et al., 1993). Acceptable DNA was not available from the other 33 plants. Interval mapping, which searches for the effects of QTL using sets of linked markers (Lander et al., 1987), was used. A LOD score of 3.0 was considered the threshold for detecting significant QTL locations. The additive effect (a), the dominance deviation (d), and the degree of dominance (d/a) were calculated for each QTL (Lincoln et al., 1993). To further understand the QTL single and cumulative effects on the phenotypic variance, stepwise multiple regression was done using the REG procedure in SAS (version 9.1; SAS Institute, Cary, NC) with all possible marker loci combinations. The phenotypic variance explained by a single QTL or cumulative QTL effect were estimated by the square of the correlation determination (R2). The variables retained in the final model were determined by a stepwise selection at a significant level of 5%.
Results
Phenotypic evaluation of the F2 population.
The number of eggs on leaves after 24 h of inoculation in clip cages for plants in the F2 population ranged from 0 to 123, and Type IV trichome counts ranged from 0 to 157 (Figs. 1 and 2). Both traits were continuously distributed, indicating control by polygenes. Type IV trichome production appears to be recessively controlled because the F1 was skewed strongly toward the susceptible parent (Fig. 2). No F2 plants had as many trichomes as LA1777. Thus, more than three genes may be required to obtain the type IV trichome density of LA1777 (Fig. 2) because two to three LA1777-like plants would be expected with control by three recessive genes. However, acceptable resistance for a tomato line may not require the level of resistance of LA1777. For instance, there were five plants in the F2 population that had no eggs deposited on their leaves but had type IV trichome numbers of 78 to 157. The 11 resistant plants had 0 to 17 eggs, 73% to 100% SPWF mortality, and 60 to 157 type IV trichomes compared with the 10 susceptible plants, which had 51 to 123 eggs, 0% to 46% SPWF mortality, and 0 to 8 type IV trichomes.
Frequency distribution of sweetpotato whitefly egg numbers in a 171 plant F2 population of Solanum lycopersicum cultivar E6203 (P1) × Solanum habrochaites accession LA1777 (P2). Arrows indicate mean of respective parents and their F1.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 135, 2; 10.21273/JASHS.135.2.134
Frequency distribution of sweetpotato whitefly egg numbers in a 171 plant F2 population of Solanum lycopersicum cultivar E6203 (P1) × Solanum habrochaites accession LA1777 (P2). Arrows indicate mean of respective parents and their F1.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 135, 2; 10.21273/JASHS.135.2.134
Frequency distribution of sweetpotato whitefly egg numbers in a 171 plant F2 population of Solanum lycopersicum cultivar E6203 (P1) × Solanum habrochaites accession LA1777 (P2). Arrows indicate mean of respective parents and their F1.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 135, 2; 10.21273/JASHS.135.2.134
Frequency distribution of type IV trichome numbers in a 171 plant F2 population of Solanum lycopersicum cultivar E6203 (P1) × Solanum habrochaites accession LA1777 (P2). Arrows indicate mean of respective parents and their F1.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 135, 2; 10.21273/JASHS.135.2.134
Frequency distribution of type IV trichome numbers in a 171 plant F2 population of Solanum lycopersicum cultivar E6203 (P1) × Solanum habrochaites accession LA1777 (P2). Arrows indicate mean of respective parents and their F1.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 135, 2; 10.21273/JASHS.135.2.134
Frequency distribution of type IV trichome numbers in a 171 plant F2 population of Solanum lycopersicum cultivar E6203 (P1) × Solanum habrochaites accession LA1777 (P2). Arrows indicate mean of respective parents and their F1.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 135, 2; 10.21273/JASHS.135.2.134
Selective genotyping analysis.
Markers in four regions (R1, R2, R3, and R4) on three different chromosomes (also designated R1/10, R2/9, R3/11a, and R4/11b, where the number after the slash indicates the chromosome number) cosegregated with R and S plants (Table 1). The resistant lines carried 5 to 7 S. habrochaites alleles and were homozygous or heterozygous at each region, while the susceptible lines carried 0 to 4 S. habrochaites alleles in three or less regions. Contingency chi-square analysis comparing 1:2:1 ratios of h and e alleles in R versus S groups indicated that the h markers in three regions (R1, R2, and R3) were significantly associated with resistance, while the h markers in the R4 region were weakly associated (P = 0.07). In other words, the four regions had unacceptable fits to 1:2:1 ratios because of an excess of h alleles in the R group and an excess of e alleles in the S group (Table 1). To verify further the association of these regions to SPWF resistance, the individual marker genotypes were tested for significant association with the mean number of eggs deposited using single-factor ANOVA analysis. Markers at R1, R2, and R3 regions showed highly significant associations with SPWF, while the markers at the R4 region showed a weak association (Table 2). Because R4 had the weak association, we included two more markers on that region in attempts to identify a more closely linked marker. The F-values for markers in that region ranged from 2.29 to 2.77 (Table 2). An additional region (R5/8) was associated with type IV trichome production, but not with egg deposition or adult mortality.
Analysis of variance of sweetpotato whitefly (SPWF) egg deposition for marker alleles at putative SPWF resistance loci in an F2 population of Solanum habrochaites accession LA1777 crossed with three susceptible tomato lines.
QTL analysis.
Based on selective genotyping, the five target regions mentioned above were analyzed for numbers of eggs and type IV trichome QTL, while other regions of the chromosome were analyzed only for the numbers of eggs QTL. We were not confident in the type IV trichome analysis for the whole genome. Whereas the LOD scores in these regions were all less than 3, the analysis gave error messages that likely related to the low number of plants (138) in the analysis. A total of 124 polymorphic markers was used to associate markers and phenotypes in the F2 population (Fig. 3). Regions R1 to R4 previously identified through selective genotyping were identified here as QTLs for low numbers of eggs deposited. The LOD values for R1, R2, R3, and R4 for the numbers of eggs were 4.87, 4.70, 5.96, and 3.50, respectively. Figure 3 shows the map position of the four major QTLs marked with bold lines. The chromosomal locations of marker intervals, effect of each QTL, and coefficients of determination are presented in Table 3. On the basis of the d/a ratio, dominance effects were detected for R1 and R3, additive effects for R2, and overdominance for R4. Regions 1 to 4 were also significantly associated with type IV trichomes (Table 3). We did not find any other chromosomal region to be associated with resistance variables through QTL analysis, which is consistent with the selective genotyping analysis (Fig. 3). Source, fragment size, and map position of molecular markers linked to low numbers of eggs deposited, high adult SPWF mortality, and/or high type IV trichome density are presented in Table 4.
QTL associated with low sweetpotato whitefly egg deposition from an F2 population derived from susceptible tomato lines crossed with S. habrochaites accession LA1777. Four regions with LOD scores >3 were considered significant and are indicated with a solid line. A fifth region on chromosome 8 was associated with type IV trichomes, but not egg deposition in the selective genotyping analysis, and is indicated by the hatched line. The distances between markers are from Fulton et al., (2000).
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 135, 2; 10.21273/JASHS.135.2.134
QTL associated with low sweetpotato whitefly egg deposition from an F2 population derived from susceptible tomato lines crossed with S. habrochaites accession LA1777. Four regions with LOD scores >3 were considered significant and are indicated with a solid line. A fifth region on chromosome 8 was associated with type IV trichomes, but not egg deposition in the selective genotyping analysis, and is indicated by the hatched line. The distances between markers are from Fulton et al., (2000).
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 135, 2; 10.21273/JASHS.135.2.134
QTL associated with low sweetpotato whitefly egg deposition from an F2 population derived from susceptible tomato lines crossed with S. habrochaites accession LA1777. Four regions with LOD scores >3 were considered significant and are indicated with a solid line. A fifth region on chromosome 8 was associated with type IV trichomes, but not egg deposition in the selective genotyping analysis, and is indicated by the hatched line. The distances between markers are from Fulton et al., (2000).
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 135, 2; 10.21273/JASHS.135.2.134
Logarithm of odds (LOD), degree of dominance, and the percentage of explained phenotypic variance (R2) for QTL associated with sweetpotato whitefly egg deposition and type IV trichomes from an F2 population of Solanum habrochaites accession LA1777 crossed with three susceptible tomato lines.
Source, fragment size, and map position of molecular markers in chromosomal regions associated with sweetpotato whitefly egg deposition or type IV trichome density from an F2 population of Solanum habrochaites accession LA1777 crossed with three susceptible tomato lines.
Stepwise multiple regression analysis.
Through the single-marker analysis, significant QTLs were detected for numbers of eggs deposited for all marker loci in regions R1 to R4. Only R2 was significant for adult mortality. Regions R1, R2, and R5 were significant for type IV trichomes. For the multiple QTL models, if statistical significance was found for numbers of eggs, it was also found for adult mortality, although often the variation explained was higher for the former. The QTL combinations that were significant for type IV trichomes were often not significant for the numbers of eggs deposited or adult mortality. Regions R1, R2, and R3 were significant for egg deposition/mortality in all three models where these regions were tested, with R2 being of key importance (Table 5). In some models, significant egg deposition/mortality effects were found with R1 + R2 or R2 + R3. Regions R4 and R5 were not significant for egg deposition or adult mortality. For type IV trichomes, R1 + R4 + R2 were significant for both models where this combination was tested. Some combinations of R1 + R2 or R2 + R3 were significant for type IV trichomes, but R5 was not a significant factor in the multiple QTL models. For the numbers of eggs deposited, single regions had R2 values of 0.1 or less; with R1 + R2, the R2 increased to 0.13; with R2 + R3, the R2 increased to 0.20 to 0.21 and when R1 was added to R2 and R3, the R2 ranged from 0.23 to 0.25. These data suggest R2 and R3 combined account for much of the variation identified. For adult mortality, R2 accounted for essentially all the variation. For type IV trichomes, R1, R2, and R5 taken singly had R2 values of 0.8 to 0.11. When R1 + R2 or R2 + R4 were combined, the R2 increased to 0.16 or 0.17. When R1 + R2 + R4 were combined, the R2 increased to 0.22. Thus, it seems that loci in these three regions primarily control type IV trichome production.
Stepwise multiple regression analysis of putative QTL linked to sweetpotato whitefly resistance in an F2 population of Solanum habrochaites accession LA1777 crossed with three susceptible tomato lines. All significant associations are shown.
Discussion
The genome-wide scan for QTLs significantly affecting SPWF resistance revealed four genomic regions on three different chromosomes using chi-square tests, single-marker ANOVA analysis, QTL analysis, and multiple regression analysis. SPWF resistance (number of eggs) has been found to be correlated with the density of type IV trichomes (Muigai et al., 2003). In our study, four QTLs for numbers of eggs deposited and type IV trichome numbers were mapped to the same chromosomes. Maliepaard et al. (1995) found two QTL for numbers of eggs deposited; one on chromosome 1 (TG142) and one on chromosome 12 (TG296) and two type IV trichome QTL; one on chromosome 5 (TG379) and one on chromosome 9 (TG223) for greenhouse whitefly in S. habrochaites f. glabratum accession CGN.1561. Our study covered regions TG142 (chromosome 1), TG296 (chromosome 12), and TG379 (chromosome 5) using QTL and selective genotyping analysis, and for TG223 (chromosome 9) using selective genotyping analysis only. We did not find any association of these markers or any nearby marker for numbers of eggs deposited or type IV trichomes. We found one QTL for number of eggs and type IV trichomes on chromosome 9 at a different position near the marker C2_At2g41680, which is about17 cM away from the reported type IV trichome QTL marker TG223 from accession CGN.1561. Differences in the studies could be due to the use of different accessions and/or differences in whitefly species. No effect was detected for the six QTLs reported by Blauth et al. (1999) for acylsugar accumulation in S. pennellii. Although we did not study the chemical composition of the type IV trichome glands, our results could support the findings of Frelichowski and Juvik (2005) that found segregation for high levels of sesquiterpene carboxylic acids (SCA) in the populations of S. habrochaites LA1033 and S. habrochaites LA1777 and have suggested that inheritance of SCA is polygenic. Zamir et al. (1984) reported that the inheritance of 2-tridecanone produced by type IV trichomes in S. habrochaites f. glabratum also is polygenic. The present study also suggests polygenic inheritance for SPWF resistance, as measured by reduced egg deposition and increased adult mortality. Zamir et al. (1984), using isozyme markers with an F2 BC1 population of tomato and S. habrochaites f. glabratum, detected significant associations with five of the isozyme markers on four different chromosomes (3, 4, 6, and 7). We found no association of type IV trichome density with any of these chromosomal regions using selective genotyping analysis or on chromosomes 3 and 4 using selective genotyping and QTL analyses. However, we only studied trichome density and not the chemicals contained in trichome glands. One R plant in the present study had 60 type IV trichomes but had only 0.5 eggs deposited per leaflet, while another plant had 153 type IV trichomes but had 17 eggs deposited (Table 1). Thus, it is not necessarily the high number of type IV trichomes resulting in a high level of resistance (low egg deposition).
Future research.
Four QTLs on three different chromosomes were identified through selective genotyping, QTL analyses, and stepwise multiple regression analysis for reduced egg deposition and/or type IV trichome production. This is the first step toward our overall goal of developing SPWF-resistant breeding lines without linkage drag from the wild species. The amount of variation explained by any single QTL was not high, and combining QTL did not explain much more variation. One reason for this could be that different combinations of resistance genes can provide resistance, and thus any particular gene combination can only account for a part of the resistance variation. It is apparent that accumulating all four regions did not increase the resistance variation accounted for over lesser numbers of regions. Perhaps there was enough resistance with fewer genes, thus the additional ones were superfluous. Presently, we have made crosses and are using the molecular markers to test all combinations of the four regions for resistance. Once this is done, we will have a better concept as to what regions are necessary to attain resistance. We will then proceed to use markers and test crosses to fine map the actual resistance genes. The results presented here will enable high-resolution genetic mapping using large populations and increasing marker density within regions, which will be needed to more closely identify the regions on the chromosomes associated with resistance.
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