Molecular Breeding 13: 1–14, 2004. © 2004 Kluwer Academic Publishers. Printed in the Netherlands.
1
Fine mapping of QTLs of chromosome 2 affecting the fruit architecture and composition of tomato L. Lecomte1, V. Saliba-Colombani1, A. Gautier1, M.C. Gomez-Jimenez1, P. Duffé1, M. Buret2 and M. Causse1,* 1INRA,
Unité de Génétique et Amélioration des Fruits et Légumes, Domaine Saint-Maurice, BP94, 84143 Montfavet Cedex, France; 2INRA, UMR Sécurité et Qualité des Produits d’Origine Végétale, Domaine Saint-Paul, 84914 Avignon Cedex 9, France; *Author for correspondence (e-mail:
[email protected]; fax: +33 (0)4-32-72-27-02) Received 5 August 2002; accepted in revised form 18 April 2003
Key words: Fine mapping, Fruit quality, Quantitative trait locus 共QTL兲, Lycopersicon esculentum, Near-isogenic line 共NIL兲
Abstract Negative correlations between quality traits and fruit size may hamper the breeding of fresh market tomato varieties for better organoleptic qualities. In a recent QTL analysis, QTLs with large effects on fruit weight, locule number and several quality traits were detected in the distal 50 cM of chromosome 2, but favorable alleles for fruit weight and locule number were unfavorable to quality traits. Substitution mapping was undertaken to determine whether the effects were due to a single QTL or to several tightly linked QTLs. Several chromosomal segments were characterized using near-isogenic lines. Five of them appeared to be involved in one or several traits. Considering the five segments from the top to the bottom of the region, the QTLs detected in each segment controlled the variation of: 共1兲 fruit weight, 共2兲 soluble solids content and dry matter weight, 共3兲 fruit weight, 共4兲 locule number and 共5兲 fruit weight, dry matter weight, total sugars, titratable acidity and soluble solids content. This last cluster illustrates an antagonism between fruit weight and four quality traits, as favorable alleles are not conferred by the same parent in both cases. Nevertheless, several antagonistic QTLs were separated from each other in the first four segments, holding the promise for marker-assisted improvement of fruit quality traits without compromising the fruit size.
Introduction Consumer perception of organoleptic quality in tomato fruits is based on the appearance, taste, aroma and texture. Sensory analysis is the most valid method to study these organoleptic characteristics, but sensory parameters that could assist the breeders in an efficient selection for flavor have not been characterized 共Bucheli et al. 1999兲. In addition, tomato flavor has declined as variety selection and tomato production has emphasized yield, fruit size, firmness, lack of defects, disease resistance, processing per-
formance, and not the sensory aspects of fruit quality. Previous studies indicated that tomato quality could be largely improved by genetically increasing sugar and acid contents 共Jones and Scott 1983; Stevens et al. 1979兲. However efforts to develop tomato varieties with high soluble solids content 共Brix兲 were impeded by the negative correlation of this trait with fruit size, yield and other factors 共Stevens 1986兲. Wild Lycopersicon species appeared to have a significant genetic potential for greater accumulation of fruit soluble solids 共Rick 1974兲. Thanks to advances in genetics, the genetic factors involved in tomato quality
2 were mapped with processing tomato cultivars crossed to related wild tomato species 共Bernacchi et al. 1998; Chen et al. 1999; Eshed and Zamir 1996; Goldman et al. 1995; Grandillo et al. 1996; Paterson et al. 1988; Yousef and Juvik 2001兲. The overall results confirmed that although it is possible to increase Brix in large-fruited tomatoes by gene introgression from small-fruited wild species, a significant Brix increase is not likely to occur without decrease in fruit size 共Chen et al. 1999兲. The physiological relationships between fruit weight and Brix are unknown. However, it is conceivable that an increase in fruit size would result in the dilution of Brix. The potential of small-fruited Lycopersicon esculentum lines for organoleptic quality breeding of fresh market tomato has been described by Hobson et al. 共1990兲. Thus, a cherry tomato line 共Lycopersicon esculentum, var. cerasiforme 共Dun.兲 Gray兲 with 6 g fruit weight and a high overall aroma intensity, was analyzed for its potential to improve organoleptic quality traits in fresh market tomato. A recombinant inbred line population, derived from an intraspecific cross between this cherry tomato line and a large-fruited line 共a Lycopersicon esculentum Mill. line with 120 g fruit weight and a common taste兲 was created. A genetic map 共Saliba-Columbani et al. 2000兲 and a QTL analysis for organoleptic quality traits were achieved 共Causse et al. 2002; 2001; Saliba-Colombani 2001兲. Co-localization of QTLs with opposite effects on fruit weight and total sugars or dry matter weight were detected on chromosomes 2, 3 and 11. The lack of precision in QTL mapping did not allow us to distinguish the pleiotropic effect of a single gene from the effects of tightly linked genes. Indeed, the confidence intervals of the QTLs were ranging between 10 and 30 cM; thus, locating each QTL precisely on the linkage map by fine mapping proved essential. Substitution mapping, a method for the fine mapping of QTLs previously localized on chromosomal regions 共Paterson et al. 1990兲, was chosen to study a region of chromosome 2. This region carried major QTLs for organoleptic quality attributes with large but antagonistic effects. Breaking the undesirable linkage effects could render introgressions more useful in breeding programs using marker-assisted selection. The F7 progenies of five recombinant inbred lines were selected from the population used for QTL mapping as they were segregating for a part of the region studied. Near-isogenic lines 共NIL兲 were derived and a strategy of substitution mapping was set up. This paper describes: 共1兲 the molecular characteriza-
tion of these near-isogenic lines, 共2兲 the densification of the region in molecular markers, 共3兲 the analysis of quality traits variation in the NILs, 共4兲 the precise location of QTLs and prospects for their use in breeding.
Materials and methods Characterization and development of near-isogenic lines As described in Saliba-Colombani et al. 共2000兲, F7 recombinant inbred lines 共RILs兲 were developed from an intraspecific cross between two inbred lines: Cervil and Levovil. Cervil is a cherry tomato 共Lycopersicon esculentum, var. cerasiforme 共Dun.兲 Gray兲 with small fruits 共5-10 g兲. It was chosen for its good taste and high aroma intensity. Levovil 共L. esculentum Mill.兲 is a line with bigger fruits 共90-160 g兲 and a common taste. 153 RILs were used for map construction. More markers internal to the region of interest on chromosome 2 共between the TG554 locus and the distal extremity of the chromosome兲 first needed to be mapped 共1兲 to select RILs still heterozygous for a part of the region and 共2兲 to precisely locate the recombination points. Sixty-seven RFLP probes 共CD, CT and TG probes were kindly given by Tanksley et al. 共1992兲, GC probes corresponded to cDNA probes兲 were screened for polymorphism with six restriction enzymes: EcoRI, EcoRV, HindIII, XbaI, DraI and SstI. The sequences of several RFLP probes were available 共Ganal et al. 1998兲. Seven RFLP markers of the region of interest were selected, primers 共of 20 nucleotides each兲 were defined within the sequences of the probes using the Primer3 software 共Rozen and Skaletsky 1998兲 and polymorphism between Cervil and Levovil was assessed with each pair of primers. Three AFLP markers 共H35M47-143L, H35M47162C, H33M49-245C兲 among the ten in the region of interest 共Saliba-Colombani et al. 2000兲 were cloned and sequenced. Primers were also defined and polymorphism was assessed. The F7 progenies of five recombinant inbred lines were selected for their residual segregation in one to three regions of chromosome 2, and homozygosity in the rest of the genome. Twenty-eight segregating F7 plants of each were grown in a glasshouse for genotype and phenotype evaluation. DNA from 140 共28 ⫻ 5兲 plants was extracted 共Fulton et al. 1995兲, digested with EcoRI, EcoRV, HindIII, XbaI, DraI and
3 SstI, electrophoresed in agarose gels, immobilized on Hybond N⫹ nylon membranes 共Amersham兲 and hybridized with all the markers of the segregating regions. Then, all F7 plants were selfed and F8 nearisogenic line 共NIL兲 pairs were generated. When a significant difference was observed between the NILs, it was attributed to the genotype difference within the segregating region. As some of the F7 plants were still heterozygous for a part of chromosome 2, F8 progenies were scored for segregating markers and selfed, and F9 sub-NILs were obtained. Phenotypic evaluation Four progressive phenotypic evaluations were performed with fruits harvested on the basis of their red color so that we could compare them at homogeneous ripening stage. We first confirmed that the region of chromosome 2 studied was involved in fruit quality. The 140 共28 ⫻ 5兲 segregating F7 plants were grown in a heated glasshouse from February to June 1997 at Montfavet 共Southern France兲. Parental lines 共two plants of each兲 were included, and all lines were evaluated for fruit weight 共in g兲, locule number and Brix 共in °Brix兲. Fifteen fruits per plant were harvested 共three harvests of five fruits during three weeks兲. Fruit weight and locule number were evaluated for each fruit, three Brix analyses per plant were performed with the juice of the five fresh fruits of each harvest. The three other evaluations concerned NILs. Three pairs of F8 NILs and the F1 hybrid Cervil x Levovil, each represented by four to six plots of six plants in a fully randomized trial, were first grown in a heated glasshouse at Montfavet from February to June 1998. Ninety fruits per plot were harvested 共fifteen fruits per week during six weeks兲. Each fruit was evaluated for fruit weight and only 45 fruits per plot were evaluated for locule number. The fruits were then cut and frozen 共--30 °C兲 for further chemical analyses. Chemical analyses were performed on frozen fruit powder derived from blending fifteen fruits together with liquid nitrogen. The traits analyzed were Brix, dry matter weight 共called dry weight, in g/100 g of fresh matter兲, total sugars 共in g/100 g of fresh matter兲 and titratable acidity 共called acidity, in meq H⫹/100 g of fresh matter兲. Chemical analyses were performed as recommended by the SCAR Agro-Food Tomato Working Group 共1991兲. In the second trial, eleven F9 sub-NILs, the two parental lines and their F1 hybrid were evaluated, each represented by four plots of three plants, divided into four blocks. Plants were
grown in a heated glasshouse at Montfavet from February to June 2001. Thirty-five fruits per plot were harvested during three weeks 共five crops of seven fruits兲. A total of 140 fruits per F9 sub-NIL were evaluated for fruit weight and locule number. Analyses 共Brix, dry weight, acidity and total sugars兲 were performed on frozen fruit powder derived from blending the seven fruits of each crop. The third trial was performed from July to November 2001, to precisely determine fruit weight and locule number QTL linkage. Nine F8 NILs were grown in a heated glasshouse at Montfavet, each F8 NIL being represented by five plants. Forty fruits per plant were evaluated for fruit weight and locule number during four weeks, a total of 200 共40 ⫻ 5兲 fruits per F8 NIL were analyzed. Data analysis Molecular markers analyses and QTL detection were conducted as reported by Saliba-Colombani et al. 共2000; 2001兲. Linkage analysis of markers in the targeted region of chromosome 2 was performed with the software package MAPMAKER/EXP version 3.0 共Lander et al. 1987; Lincoln et al. 1992兲. Recombination fractions were converted into map distances in centimorgans 共cM兲 using the Kosambi mapping function 共Kosambi 1944兲. Deviation from normality was tested with RIL averages for the six traits studied: fruit weight, locule number, Brix, dry weight, acidity and total sugars 共locule number data were available but have not yet been published by Saliba-Colombani et al. 2001兲. The transformations giving the least skewed distributions were used for QTL analysis 共log for fruit weight and square root for acidity兲. QTL detection was performed by composite interval mapping 共Zeng 1993; Zeng 1994兲 using the QTL-Cartographer software 共Basten et al. 1997兲, with a LOD threshold of 2.56. In the validation trial, the five F7 progenies were segregating for the regions represented in Figure 1. The effects of segregating markers were evaluated by analysis of variance 共significance was set to p ⬍ 0.001兲, using the S-Plus v3.0 software package 共Splus 1993兲. Due to linkage among markers, this analysis mainly determined the effect of each segregating region without precisely determining which marker was the most involved in the trait. For each of the three other trials, means of each trait were calculated for each NIL, and comparisons of means were performed. Only NILs derived from
4
Figure 1. Molecular linkage map of the targeted region of chromosome 2 based on RILs derived from a cross between L. esculentum and L. esculentum var. cerasiforme. Marker positions 共expressed in Kosambi centimorgans兲 from TG554 are on the left of the chromosome. Markers mapped with less than 100 RILs are in italic. Asterisks indicate markers with distorted segregation 共*p ⬍ 0.01; **p ⬍ 0.001兲. The segregating regions of each F7 progeny selected for substitution mapping are represented by striped right-angles. The QTLs detected in the RIL population for the traits studied by fine-mapping 共see Table 1兲 are indicated on the left of the linkage group, the position of each QTL was determined referring to the maximum LOD value given by QTL Cartographer software.
the same F7 progeny were compared. Thus, assuming an isogenic background, significant differences among the NILs were attributed to differences in the genotypes in the targeted region of chromosome 2. Mean comparisons were performed using the SAS software 共SAS institute 1988兲. Tukey’s method was used with a significance level of 0.001. When significance was observed, we considered that a QTL was detected. QTL effect was calculated as the percentage of variation caused by allele substitution: effect ⫽
100*|C-L|/共共C⫹L兲/2兲, where C and L are the means of NILs with homozygous Cervil and Levovil alleles, respectively. The comparisons between lines containing specific chromosomal segments were used to determine whether their presence was required for a specific phenotype. By comparing the extent to which introgressed segments overlapped, fine mapping was achieved 共Paterson et al. 1990兲.
5 Results and discussion
QTL mapping with the recombinant inbred line population
High-density mapping of chromosome 2 The accuracy of substitution mapping is determined by the ability to identify overlapping chromosomal segments. Thus, based on the map described by Saliba-Colombani et al. 2000, additional RFLP markers were screened in order to develop a high-density linkage map of chromosome 2. Referring to the tomato high-density molecular map 共Tanksley et al. 1992兲, polymorphism between Cervil and Levovil was tested using 67 RFLP probes, theoretically mapping between the TG554 locus and the distal extremity of the chromosome. Twenty-five probes proved polymorphic and were scored in the RIL population. Three PCR-based markers also proved polymorphic: ACT103-L 共primers were defined within the CT103 probe sequence兲, Rad23-C 共primers were defined within the CT232 probe sequence兲 and ASC056 共primers were defined within the H33M49-245C sequence兲. The genetic map of the targeted region of chromosome 2 was thus composed of 50 loci: 10 AFLP loci, 2 RAPD loci, 35 RFLP loci and 3 PCRbased loci. The linkage group covered 71 cM 共Kosambi map units兲 and the average distance between markers was 1.45 cM 共Figure 1兲. The percentage of RFLP polymorphism detected in this region 共41%兲 was much higher than the rate observed for the whole genome 共30%兲 共Saliba-Colombani et al. 2000兲. Indeed, polymorphism was detected with at least one restriction enzyme for 35 RFLP probes out of 86. This unexpected level of polymorphism probably resulted from the wild ancestor of Cervil, which can be considered as being part of the Lycopersicon esculentum lines the most distant of the L. esculentum modern cultivars. In a wide interspecific cross between L. esculentum and L. peruvianum, 65% of RFLP probes showed polymorphism 共Fulton et al. 1997兲. On the contrary, in a cross between L. esculentum and L. cheesmanii, one of the most closely related species to the cultivated one, only 25% of polymorphism was detected 共Paran et al. 1995兲. Intraspecific crosses between distant lines of L. esculentum may thus be a viable alternative to QTL mapping in tomato, avoiding the low level of polymorphism in common intraspecific crosses 共between modern cultivars兲 and the limits of interspecific crosses 共sterility, linkage drag, recombination shrinkage兲.
QTL detection for the six traits studied 共fruit weight, locule number, Brix, dry weight, total sugars and acidity兲 was performed by composite interval mapping on the dense map of the region of chromosome 2 studied 共Table 1兲. All the QTLs were retained 共even when two QTLs were close兲, whereas Saliba-Colombani et al. 2001 only retained the most significant QTL when two QTLs were detected within less than 20 cM. Thus, the two linked QTLs detected around the TG454 locus were noted fw2.1 and fw2.3 共Table 1兲. The QTL that mapped at the end of chromosome 2 was called fw2.2, as it could correspond to the QTL fw2.2 already cloned in this region 共Frary et al. 2000兲. The other results were in agreement with Saliba-Colombani et al. 2001. The localization of QTLs was more precise but the percentages of phenotypic variation explained by the QTLs were sometimes different. Darvasi et al. 共1993兲 had already mentioned that the precision of QTL mapping by traditional linkage analysis was a little better when using a very dense marker map. Several antagonisms were observed among the QTLs detected 共Figure 1兲. First, fw2.1 was close to QTLs for dry weight 共dmw2.2兲, Brix 共brx2.1兲 and total sugars 共sugs2.1兲, but the favorable allele for fw2.1 was conferred by Levovil whereas the favorable alleles for the three chemical traits were conferred by Cervil. Downstream, the QTL detected for locule number 共lcn2.1兲 was co-localized with QTLs for fruit weight 共fw2.3兲 and Brix 共brx2.2兲. The effect of lcn2.1 was very high 共PVE ⫽ 37.3%兲 and its co-localization with fw2.3 was not surprising since relationships between locule number and fruit size had already been mentioned 共Bohner and Bangerth 1988; Lippman and Tanksley 2001; Sawhney and Greyson 1972兲. However, the favorable alleles for these QTLs were unfavorable for brx2.2. Lastly, several major QTLs 共located near the ASC056 locus兲 illustrated another antagonism between a QTL for fruit weight 共fw2.2兲 and QTLs for acidity 共ta2.2兲, dry weight 共dmw2.3兲 and total sugars 共sugs2.2兲. Such antagonisms along the chromosome 2 could explain the difficulty encountered by breeders to simultaneously obtain in this material enhanced organoleptic quality and an acceptable fruit size 共data not shown兲, as favorable alleles for chemical traits were all provided by Cervil whereas favorable alleles for fruit weight and locule number were all provided by Levovil. Moreover, for
6 Table 1. QTLs detected in the targeted region of chromosome 2 by composite interval mapping analysis in the RIL population. The most closely associated marker locus is indicated. The position of the QTL in cM 共Kosambi兲 from TG554 共see Figure 1兲 is indicated by Pos. LOD is the log-likelihood at the QTL position. Effect is the difference in value 共after transformation兲 of the two allelic classes at the QTL. PVE is the percentage of phenotypic variation explained by the QTL. The parent increasing the trait value is shown in the Parent column 共L ⫽ Levovil, C ⫽ Cervil兲 Trait
QTL
Marker
Pos
LOD
Effect
PVE
Parent
Fruit weight 共g兲
fw2.1 fw2.3 fw2.2
TG454 GC240 TG337-C
28.5 41.0 50.0
3.64 5.26 15.75
0.042 0.052 0.096
5.2 7.0 30.8
L L L
Locule number
lcn2.1
TG463
38.0
22.84
0.490
37.3
L
Dry matter weight 共g/100g fm兲
dmw2.2 dmw2.3
CT277 TG337-C
18.0 50.0
3.09 14.12
0.255 0.592
4.7 27.0
C C
Brix 共°Brix兲
brx2.1 brx2.2
CT038 GC240
22.0 41.0
4.21 10.65
0.255 0.443
6.9 23.9
C C
Total sugars 共g/100g fm兲
sugs2.1 sugs2.2
CD035 TG337-C
31.0 50.0
8.10 5.17
0.242 0.191
18.1 10.4
C C
Titratable acidity 共meq H⫹/100g fm兲
ta2.1 ta2.2
TG554 TG337-C
2.0 50.0
2.96 6.51
0.060 0.083
6.0 12.1
C C
fruit weight, locule number, dry weight, Brix and total sugars, the QTLs on chromosome 2 had the greatest effects among all the QTLs detected 共SalibaColombani et al. 2001兲. However, within the colocalizations, QTL locations were not accurate enough to determine whether the effects were due to a single pleiotropic QTL or to several tightly linked QTLs, and the development of overlapping substitution lines proved necessary to carry out further analysis and precision mapping 共Yano et al. 1997兲. Phenotypic involvement of the region of chromosome 2 studied A validation trial was performed with five F7 progenies segregating only for one to three regions of chromosome 2 共Figure 1兲, in order to confirm the QTLs detected in the region of chromosome 2 studied, and to show that segregating regions were involved in fruit quality. Twenty-eight F7 plants per progeny were scored for the markers of the segregating regions and evaluated for fruit weight, locule number and Brix. As few recombinants were generated within each progeny, when a region was involved in a trait, most of the markers of the segregating region were significant. Nevertheless, the spanning of the regions involved was determined thanks to overlapping segments in the five progenies 共Table 2兲.
For fruit weight, no significance was observed in the top region of F7-II progeny and with F7-V progeny, so the regions around the CT277 locus or around the GC274 locus could be involved in fruit weight variation since significance was observed with F7-III progeny. The correspondence of one of these two regions with fw2.1 seemed valuable. Significance was also observed with F7-I progeny and with the bottom region of F7-II progeny, and confirmed the location of the fw2.2 QTL in the chromosomal segment spanning from the TG167 locus until the CT274 locus 共linkage between this segment and the region around the ASC056 locus explained the significance observed with F7-I progeny around the ASC056 locus兲. Similarly, the lcn2.1 QTL was clearly confirmed by F7-I, F7-II and F7-V progenies, in a segment spanning from the TG484 locus until the GC240 locus 共the significance observed in the region around the ASC056 locus and in the region inside the interval TG502-TG167 was explained by the linkage of the segment with these regions兲. For Brix, significance was observed with F7-III and F7-V progenies, but no significance was observed in the medium region of F7-II progeny. By comparing the extent to which segregating regions overlapped, the location of the brx2.1 QTL was narrowed to the segment spanning from the GC274 locus until the CD035 locus 共linkage between this segment and the region around the
7 Table 2. Significance of the segregating regions within the five F7 progenies for fruit weight 共in g兲, locule number and Brix 共in °Brix兲. For each progeny, 28 F7 plants were screened for the segregating markers and evaluated for the three traits, and involvement of the segregating markers in the trait variation was evaluated by analysis of variance. Significance was considered for p ⬍ 0.001. With F7-II lines, the significance of each of the three segregating regions 共top, medium and bottom兲 was indicated. Asterisks indicate that significance was observed for all the markers of the segregating region. NS indicate that no significance was observed in the segregating region. When significance was observed for a part of the segregating region, the interval including all the significant loci is mentioned. The spanning of the regions involved in the trait was determined thanks to the overlapping segments between the five progenies, and was summarized by writing the locus or the interval including all the loci of the region, 共⫹兲 means that the locus is inside the region, 共-兲 means that the locus is outside the region Trait
F7-I
F7-II Top
Medium
Bottom
F7-III
F7-IV
F7-V
Regions involved
Fruit weight
***
NS
NS
***
***
NS
NS
共⫹兲CT277 共⫹兲GC274 共⫹兲ASC056 共⫹兲TG167-共⫹兲CT274
Locule number
TG484-TG167
NS
***
NS
NS
NS
TG484-GC240
共⫹兲TG484-共⫹兲GC240 共⫹兲ASC056 共-兲TG502-共-兲TG167
Brix
ASC056-TG167
NS
NS
NS
***
NS
TG454-TG266
共⫹兲CT277 共⫹兲GC274-共⫹兲CD035 共⫹兲ASC056 共-兲TG502-共-兲TG167
CT277 locus explained the significance observed with F7-III progeny around the CT277 locus兲. Lastly, significance for Brix was observed with F7-I progeny, whereas no significance was observed with F7-IV progeny and in the bottom region of F7-II progeny, suggesting that brx2.2 location was narrowed to a segment including the ASC056 locus, or to a segment inside the interval TG502-TG167. Finally, the comparison for fruit weight, Brix and locule number coincided largely with the QTL detection performed with the RIL population the year before, allowing us to conclude that : 共1兲 the QTLs of the region of chromosome 2 studied were confirmed, and 共2兲 four of the five RILs selected were segregating for QTLs 共no significance was detected with the F7-IV progeny兲, providing good prospects for the fine-mapping of these QTLs using NILs. However fw2.3 共close to the GC240 locus兲 has to be confirmed as it was not detected in the medium region of F7-II or in the F7-V progenies, and as it was not possible to detect two fruit weight QTLs with the F7-I progeny 共due to the small sample size of each progeny兲. Three trials based on the comparison of NIL means were performed to fine map QTLs.
Fine-mapping of physical trait QTLs Fruit weight and locule number were studied in three trials involving different sets of NILs. F8-III, F8-IV and F8-V NILs, derived from F7-III, F7-IV and F7-V progenies, respectively, were analyzed in the first trial 共Table 3兲. F9-II and F9-V sub-NILs, derived from F8-II and F8-V lines, respectively, were analyzed in the second trial 共Figure 2兲. With F9-II sub-NILs, the effects of each of the three segregating regions 共top, medium and bottom兲 were tested. On the contrary, F9-V sub-NILs were recombinant and made it possible to study the effects of five segments within the segregating region 共as indicated in Figure 2兲. In the last trial, three groups of F8-I NILs, derived from F7-I progeny, were studied 共Table 4兲. As expected 共Table 2兲, F8-III NILs showed significant differences for fruit weight 共Table 3兲, whereas no significance was observed in the top region of F9-II sub-NILs 共Figure 2兲. Nevertheless, a recombinant F8-III NIL was evaluated for fruit weight 共data not shown兲 and allowed fw2.1 to be mapped in the region around the GC274 locus, the effect of the allele substitution in trait variation being around 10%. All the sets of NILs which differed for the chromosomal region spanning from the TG191 locus until the H35M47-162C locus indicated differences in locule number and fruit weight 共Table 3, Figure 2, Table 4兲.
8 Table 3. Means of three pairs of F8 NILs for the six traits studied: fruit weight 共in g兲, locule number, titratable acidity 共in meq H⫹/100 g fm兲, Brix 共in °Brix兲, total sugars 共in g/100 g fm兲 and dry matter weight 共in g/100 g fm兲. The segregating regions of F8-III, F8-IV and F8-V NILs are represented in Figure 1. Approximate length of the segregating region is indicated in Kosambi centimorgans. This was calculated assuming that crossover position was equidistant between recombinant markers. L and C means are means for NILs with Levovil and Cervil alleles, respectively, within the segregating region 共the standard errors are indicated in parenthesis兲. Effect was calculated as the percentage of trait variation caused by allele substitution. For each pair of NILs, significance between L and C means was tested. Significant differences are indicated by an asterisk between L and C means, and are shown in italics Pairs of F8 NILs
F8-III
F8-IV
F8-V
Segregating regions
CT277-TG454 共12 cM兲
TG502 共3.5 cM兲
TG454-TG337-C 共24 cM兲
Means
L
C
Effect L
Fruit weight Locule number Titratable acidity Brix Total sugars Dry matter weight
18.66 共2.69兲 * 2.22 共0.42兲 8.17 共0.75兲 9.51 共0.52兲 6.53 共0.82兲 11.21 共0.80兲
16.93 共2.47兲 2.15 共0.36兲 7.96 共0.57兲 9.75 共0.49兲 6.70 共0.76兲 11.36 共0.76兲
9.7 3.2 2.6 2.5 2.6 1.3
17.23 共1.46兲 2.12 共0.33兲 6.43 共0.74兲 7.66 共0.64兲 5.62 共0.76兲 8.82 共0.64兲
These differences were on one hand consistent with lcn2.1 and fw2.3 QTLs predicted from the QTL analysis 共Table 1兲, although fw2.3 was not detected in the validation trial, and on the other hand they suggested that a pleiotropic effect could be responsible for the co-localization of fw2.3 and lcn2.1. But as F8-I-c NILs were only segregating for locule number and not for fruit weight 共Table 4兲, the most likely position of fw2.3 was determined around the TG191 locus 共 ⬇ 3cM, assuming that crossover position was equidistant between recombinant markers兲, and that of lcn2.1 was determined in the region common to the five sets of NILs including the TG463 and GC240 loci 共 ⬇ 2cM兲. Thus, the hypothesis that fw2.3 and lcn2.1 were co-localized because of the pleiotropic effect of a common gene was rejected. The effect of the allele substitution in trait variation varied between 6.3 and 12.1% for fw2.3, and between 12.5 and 36.7% for lcn2.1. F8-IV NILs did not show any significant difference 共Table 3兲, whereas the bottom region of F9-II sub-NILs showed significant differences for fruit weight 共Figure 2兲. Therefore, fw2.2 was assigned to the region including the TG167 and GC187 loci 共 ⬇ 11cM兲. The effect of the allele substitution at this QTL was about 40%. A QTL with very similar phenotypic effects and gene action has also been identified and mapped to the same chromosomal region in other wild tomato accessions 共Alpert et al. 1995兲, suggesting that the distal region of chromosome 2 was conserved between Cervil and the small-fruited wild species. Allelic differences at fw2.2 between L. esculentum and wild species were recently investi-
C
Effect L
17.02 共1.29兲 2.10 共0.31兲 6.43 共0.55兲 7.46 共0.48兲 5.33 共0.71兲 8.69 共0.92兲
1.2 0.9 0.0 2.6 5.3 1.5
10.98 共0.89兲 3.42 共0.77兲 8.27 共0.64兲 9.30 共0.60兲 6.62 共0.64兲 11.54 共0.82兲
C * 9.82 共0.67兲 * 2.36 共0.50兲 8.35 共0.69兲 * 10.39 共0.51兲 7.08 共0.65兲 * 12.23 共0.49兲
Effect 11.2 36.7 1.0 11.1 6.7 5.8
gated 共Frary et al. 2000; Nesbitt and Tanksley 2002兲. Allelism between Cervil, Levovil and the wild species could give interesting information about the speciation of Cervil. Numerous studies mapped other fruit weight QTLs along chromosome 2 共Grandillo et al. 1999兲. The QTL fw2.3 was detected in several other studies involving different species, suggesting that fruit weight QTLs are well conserved between Lycopersicon species. However, no QTL was detected in the region where fw2.1 was mapped in this study, illustrating that new variability can still be found in L. esculentum lines. Grandillo and Tanksley 共1996兲 detected QTLs for locule number on chromosome 1 and 3 only, in a BC1 population of L. esculentum 共M82-1-7兲 x L. pimpinellifolium 共LA1589兲. However, Lippman and Tanksley 共2001兲 have detected two QTLs for locule number on chromosome 2 共lcn2.1 and lcn2.2兲 and one on chromosome 11 共lcn11.1兲 in a F2 population of L. esculentum var. Giant Heirloom 共which bears fruit in excess of 1000 g兲 x L. pimpinellifolium 共LA1589兲. The QTL lcn2.1 共mapped near the TG337-C locus兲, which accounted for 13% of the phenotypic variation, might correspond to the QTL lcn2.1 that was fine-mapped in this study. The QTLs lcn2.2 共mapped near TG167 locus兲 or lcn11.1 and the highly significant epistatic interaction that they detected between lcn2.1 and lcn11.1, probably conditioning extreme fruit size 共Lippman and Tanksley 2001兲, were not detected in our study.
Figure 2. Means of the F9-II and F9-V sub-NILs for fruit weight 共in g兲, locule number, titratable acidity 共in meq H⫹/100 g fm兲, Brix 共in °Brix兲, dry matter weight 共in g/100 g fm兲 and total sugars 共in g/100 g fm兲. Markers between which crossovers occurred 共crossovers are represented by dotted lines兲 were indicated and the length of the intervals 共in Kosambi centimorgans兲 was calculated assuming that crossover position was equidistant between recombinant markers. Comparison of means was performed between all the NILs of the same family. Means with the same letter are not significantly different 共standard errors are indicated in parenthesis兲. Effect was calculated as the percentage of trait variation caused by allele substitution. Effect was indicated only when significance was detected, otherwise NS 共Not Significant兲 is indicated. Within F9-II sub-NILs, effect was calculated for each segregating region. Within F9-V subNILs, when significance was attributed to a specific segment 共5 segments were isolated兲, the effect was calculated.
9
10 Table 4. Means of the three allelic combinations of F8-I-a, F8-I-b and F8-I-c NILs for fruit weight 共in g兲 and locule number. Approximate length of the segregating region is indicated in Kosambi centimorgans, it was calculated assuming that crossover position was equidistant between recombinant markers. L, H and C means are means for NILs with Levovil, Heterozygous and Cervil alleles, respectively, within the segregating region 共standard errors are indicated in parenthesis兲. Effect was calculated as the percentage of trait variation caused by allele substitution. For each sub-NIL, comparison of means was performed between L, H and C. Means with the same letter are not significantly different 共letters are indicated on the right of each mean兲. Significant differences are written in italics Fruit weight NILs
Segregating regions
F8-I-a
TG191-GC240 共5 cM兲
F8-I-b F8-I-c
L
15.03 共2.62兲 TG191-H35M47-162C 共7 cM兲 14.01 共1.84兲 TG463-TG502 共19 cM兲 14.12 共1.86兲
Locule number H
a a a
14.55 共2.13兲 14.27 共1.86兲 14.21 共1.78兲
C a/b a a
Fine-mapping of chemical trait QTLs Acidity, Brix, total sugars and dry weight were studied in two trials 共Table 3 and Figure 2兲. F8-III NILs did not show any significant difference 共Table 3兲, whereas the segregating region was involved in Brix variation with F7-III progeny 共Table 2兲. The involvement of this region in Brix variation was not confirmed, suggesting that no QTL was detected or that the QTL was dependent on environmental conditions. A recombinant F8-III NIL was evaluated for Brix 共data not shown兲 and confirmed that no QTL was detected in the region around GC274 locus. These results highlighted the importance of evaluating QTL effects in more than one set of NILs. On the contrary, F8-V NILs showed significant differences for Brix and dry weight 共Table 3兲, the significance for Brix being consistent with marker associations observed previously in the validation trial 共Table 2兲. These results were confirmed with F9-V sub-NILs 共Figure 2兲. Indeed, significance for Brix, dry weight and total sugars was clearly identified in segment 1, reducing the region length where the QTLs were mapped to a segment including TG462 and CD035 loci 共 ⬇ 3cM兲. The correspondence of these QTLs with brx2.1, dmw2.2 and sugs2.1 seemed high. The effects caused by allele substitution varied between 11 and 13% for brx2.1, and between 6 and 13% for dmw2.2. Although sugs2.1 had not been detected with F8-V NILs, it was detected and confirmed by F9-V sub-NILs with a 25% effect. F9-II sub-NILs for the bottom region showed significant differences for all the traits. As no significance was detected with F8-IV NILs, these QTLs were fine-mapped in a region in-
14.11 共2.35兲 12.41 共1.99兲 13.76 共2.06兲
Effect
L
b
6.3
b
12.1
a
2.6
2.48 共0.51兲 2.47 共0.51兲 2.49 共0.51兲
H a a a
2.29 共0.46兲 2.36 共0.48兲 2.20 共0.40兲
C b a b
2.19 共0.39兲 2.18 共0.39兲 2.08 共0.27兲
Effect b
12.4
b
12.5
b
17.9
cluding the TG167 and GC187 loci 共 ⬇ 11cM兲, with effects caused by the allele substitution of 16, 18, 20 and 22.5% for ta2.2, brx2.2, dmw2.3 and sugs2.2, respectively. These co-localizations confirmed the cluster detected by QTL mapping 共Figure 1兲 including brx2.2 which had first been detected upstream on the chromosome and for which no significance in the bottom region of F7-II had been observed in the validation trial 共Table 2兲. The co-localizations of brx2.1 with dmw2.2 and brx2.2 with dmw2.3 共Figure 3兲 appeared consistent as Brix account for approximately 75% of dry weight 共Davies and Hobson 1981兲. QTLs for Brix and total sugars were also detected in several crosses between L. esculentum and wild tomato species 共Chen et al. 1999; Fulton et al. 2002兲, but the correspondence with the QTLs of this study was not obvious. QTLs for titratable acidity and dry weight had never been mapped before. Validity of QTL mapping and effıciency of substitution fine mapping Given the cost of field trials and genotyping, in most cases population sizes used for mapping QTLs are between 100 and 300 genotypes. Therefore, analytical approaches to QTL analysis provide poor precision about QTL location and effect, unless the heritability of the studied trait is high. The process of first identifying linkage between markers and traits in a mapping population and subsequently testing the effects of markers in NILs seems to provide strong evidence for QTL positions and effects. Indeed, as shown in Figure 3, the position of the QTLs detected in the mapping population 共Table 1兲 was confirmed
11
Figure 3. Synthetic map of QTLs of the region of chromosome 2 studied for fruit architecture and composition of tomato. The QTLs detected with the RIL population 共see Table 1兲 are indicated on the left of the chromosome, the position of each QTL was determined considering the maximum LOD value given by QTL Cartographer software. The regions where QTLs were mapped by substitutionmapping are represented by arrows on the right of the chromosome. Approximate region lengths are indicated in brackets after QTL names, they are expressed in Kosambi centimorgans and were calculated assuming that crossover position was equidistant between recombinant markers.
by substitution mapping. These results clearly indicated that QTL analysis using densely mapped markers provided reliable information for mapping QTLs. Moreover, by evaluating several series of NILs that differed in overlapping regions of the genome, the location of some QTLs was determined more accurately and narrowed to small intervals. Thus, fw2.1 was isolated from three co-localized QTLs involved in organoleptic quality: brx2.1, dmw2.2 and sugs2.1. Downstream, fw2.3 was separated from lcn2.1, and both of them were clearly separated from brx2.2. This last QTL was actually located at the bottom of the chromosome, in a cluster including five QTLs: fw2.2, ta2.2, brx2.2, dmw2.3 and sugs2.2. The linkage repulsion between fruit weight and quality traits was
not solved in that case, and although fw2.2 has already been cloned 共Frary et al. 2000兲, its relationship with fruit organoleptic quality has not been studied yet. More NILs have thus to be developed to fine map this cluster. QTL effects were calculated as the percentage of trait variation caused by allele substitution. Differences in QTL effects in NILs versus RILs were observed, and can be partly explained by 共1兲: the difference in calculation of the QTL effect and 共2兲 the reduced statistical power for testing phenotypic differences in NILs versus RILs 共Tuinstra et al. 1997兲 共unless several sets of NILs contrasting at a single locus or increased number of lines within each near-isogenic background could be considered兲. The effects also varied in the different sets of NILs, mainly for lcn2.1 and sugs2.1. Two major factors could contribute to these results: epistatic or environmental interactions. Regarding lcn2.1, effects are approaching 15, 20 and 35% for NILs derived from F7-I, F7-II and F7-V progenies, respectively. This could be explained by the epistatic interactions due to the genetic background variation, although no epistatic interaction was detected with pairwise combinations of marker loci 共Charcosset et al. 1995兲. Otherwise, though the organoleptic quality of the fruit is largely determined by its genes, it is also influenced by the environment, as shown by Davies and Hobson 共1981兲 for total sugars. The QTL sugs2.1 which was not detected with F8-V NILs 共Table 3兲 was detected in segment 1 of F9-V sub-NILs 共Figure 2兲 with a 25% effect 共sugs2.1 effect was of 18% in the RIL population 共Table 1兲兲. Such discrepancy could be largely explained by environmental interactions. The difference of effect for brx2.1 and mainly for dmw2.2 between both trials 共11.1% versus 12.8% and 5.8% versus 13.1%, respectively兲 could support this hypothesis, as about 70% of Brix are determined by total sugars and as Brix accounts for approximately 75% of dry weight in cultivated tomatoes 共Davies and Hobson 1981; Petro-Turza 1987兲. A combination of QTL mapping and substitution mapping provided the basis for a realistic approach to identifying, cloning, and studying the genes involved. Indeed, locating a QTL to a smaller region is a prerequisite to isolate genes via positional cloning. Although the exact location of crossovers was unknown, we estimated the interval length containing the different QTLs assuming that the crossover position was equidistant between recombinant markers 共Figure 3兲. The smallest segment isolated was the
12 segment of about 2cM where lcn2.1 was detected, which is still too large to try to clone the QTL using a map-based approach. Nevertheless, no recombination shrinkage was observed in the vicinity of lcn2.1 in the progenies of the validation trial 共data not shown兲, so new recombinant NILs between the TG463 locus and the GC240 locus could be obtained. Implications for breeding Mapping QTLs as single Mendelian factors will have a strong impact on breeding programs using markerassisted selection. Since a QTL can be a single locus, as demonstrated with the QTLs cloned in tomato 共Frary et al. 2000; Fridman et al. 2000兲 and in rice 共Takahashi et al. 2001; Yano et al. 2000兲, it will be possible to positively remove undesirable alleles in the vicinity of target QTLs by marker-assisted selection. Therefore, using NILs is efficient not only for genetic and physiological analyses of QTLs, but also to improve agricultural traits. Among the three QTLs for fruit weight detected here, two appeared to be clearly independent of any other QTL 共Figure 3兲, and the Levovil alleles proved interesting to be selected for both of these QTLs. The QTL for locule number was separated from fw2.3, although a secondary effect of locule number QTLs on fruit size was expected 共Lippman and Tanksley 2001兲. Locule number was first shown to be controlled by the genes f 共fasciated兲 on chromosome 11 共MacArthur 1934兲 and lc 共locule number兲 on chromosome 2 共Yeager 1937兲, corresponding to the QTLs detected later by Lippman and Tanksley 共2001兲. Under the homozygous recessive condition, lc and f genes induced fruits with a larger number of locules compared to the wild-type 共Grandillo et al. 1999兲. In this study, lcn2.1 acted in an additive way, and as breeders are interested in a locule number varying from 3 to 5 for fresh market tomato varieties to avoid defaults of fruit shape or hollow fruits, the selection of Levovil allele was recommended. Three co-localized QTLs for Brix, total sugars and dry weight suggested that marker-assisted breeding would be efficient if the Cervil allele could be selected in this region. Indeed, even a small increase in Brix can significantly enhance flavor and quality 共Rick 1974; Stevens et al. 1979;Wood 1992兲. If these three QTLs were selected independently from fruit weight and locule number, it would be possible to cumulate within the same genotype QTLs for fruit weight, locule number and total sugars. However, at
the bottom of the chromosome, a QTL for fruit weight was still co-localized with QTLs for organoleptic quality. As favorable alleles are not conferred by the same parent in both cases, further studies are required to clarify the linkage of these QTLs. This study partly explained why breeders failed to improve organoleptic quality in fresh market tomatoes without reducing fruit weight. Previous attempts to transfer solids from wild to cultivated lines, with selection against undesirable wild traits have also failed 共Rick 1974兲. Paterson et al. 共1990兲 suggested that recombination shrinkage could explain failure to transfer specific attributes from wild to domestic species. Indeed, recombination shrinkage within a chromosomal region seems particularly pronounced in wide crosses 共Montforte and Tanksley 2000兲, reducing the accuracy of selection for individual genes or traits. As a conclusion, the use of an intraspecific cross proved as promising as interspecific crosses for quality breeding of fresh market tomatoes, avoiding problems of sterility, linkage drag and recombination shrinkage. Furthermore, substitution mapping was efficient to dissect genetic effects, providing important results both for breeding and QTL characterization prospects.
Acknowledgements We thank A.M. Cossalter, M. Milesi and R. Matthieu for their excellent technical assistance. Laurent Lecomte thanks the Conseil Régional ProvenceAlpes-Côte d’Azur 共France兲 for providing him with a doctoral fellowship. The experiments comply with the current French laws.
References Alpert K.B., Grandillo S. and Tanksley S.D. 1995. fw2.2:a major QTL controlling fruit weight is common to both red- and greenfruited tomato species. Theor. Appl. Genet. 91: 994–1000. Basten C.J., Weir B.S. and Zeng Z.B. 1997. QTL Cartographer. A reference manual and tutorial for QTL mapping. In: Department of Statistics 共Eds.兲, North Carolina State University, Raleigh, USA. Bernacchi D., Beck-Bunn T., Eshed Y., Lopez J., Petiard V., Uhlig J., Zamir D. and Tanksley S.D. 1998. Advanced backcross QTL analysis in tomato. I. Identification of QTLs for traits of agronomic importance from Lycopersicon hirsutum. Theor. Appl. Genet. 97: 381–397. Bohner J. and Bangerth F. 1988. Effects of fruit-set sequence and defoliation on cell number, cell size and hormone levels of to-
13 mato fruits 共Lycopersicon esculentum Mill.兲 within a truss. Plant Growth Reg. 7: 141–155. Bucheli P., Voirol E., de la Torre R., Lopez J., Rytz A., Tanksley S.D. and Pétiard V. 1999. Definition of Nonvolatile Markers for Flavor of Tomato 共Lycopersicon esculentum Mill.兲 as Tools in Selection and Breeding. J. Agric. Food Chem. 47: 659–664. Causse M., Saliba-Colombani V., Lecomte L., Duffé P., Rousselle P. and Buret M. 2002. QTL analysis of fruit quality in fresh market tomato: a few chromosome regions control the variation of sensory and instrumental traits. J. Exp. Bot. 53: 2089–2098. Causse M., Saliba-Colombani V., Lesschaeve I. and Buret M. 2001. Genetic analysis of organoleptic quality in fresh market tomato. 2. Mapping QTLs for sensory attributes. Theor. Appl. Genet. 102: 273–283. Charcosset A., Causse M., Moreau L. and Gallais A. 1995. Investigation into the effect of genetic background on QTL expression using three connected maize recombinant inbred lines 共RIL兲 populations. In: 9th meeting of the EUCARPIA section ‘Biometrics in Plant Breeding’, pp. 83–89. Chen F.Q., Foolad M.R., Hyman J., St. Clair D.A. and Beelaman R.B. 1999. Mapping of QTLs for lycopene and other fruit traits in a Lycopersicon esculentum x L. pimpinellifolium cross and comparison of QTLs across tomato species. Mol. Breed. 5: 283– 299. Darvasi A., Weinreb A., Minke V., Weller J.I. and Soller M. 1993. Detecting marker-QTL linkage and estimating QTL gene effect and map location using a saturated genetic map. Genetics 134: 943–951. Davies J.N. and Hobson G.E. 1981. The constituents of tomato fruit – The influence of environment, nutrition and genotype. Crit. Rev. Food Sci. Nutr. 15: 205–280. Eshed Y. and Zamir D. 1996. Less-than-additive epistatic interactions of quantitative trait loci in tomato. Genetics 143: 1807–1817. Frary A., Nesbitt T.C., Frary A., Grandillo S., van der Knaap E., Cong B., Liu J., Meller J., Elber R., Alpert K.B. and Tanksley S.D. 2000. fw2.2: a quantitative trait locus key to the evolution of tomato fruit size. Science 289: 85–88. Fridman E., Pleban T. and Zamir D. 2000. A recombination hotspot delimits a wild-species quantitative trait loci for tomato sugar content to 484 bp within an invertase gene. Proc. Natl. Acad. Sci. USA 97: 4718–4723. Fulton T.M., Beck-Bunn T., Emmatty D., Eshed Y., Lopez J., Petiard V., Uhlig J., Zamir D. and Tanksley S.D. 1997. QTL analysis of an advanced backcross of Lycopersicon peruvianum to the cultivated tomato and comparisons with QTLs found in other wild species. Theor. Appl. Genet. 95: 881–894. Fulton T.M., Bucheli P., Voirol E., Lopez J., Pétiard V. and Tanksley S.D. 2002. Quantitative trait loci 共QTL兲 affecting sugars, organic acids and other biochemical properties possibly contributing to flavor, identified in four advanced backcross populations of tomato. Euphytica 163: 163–177. Fulton T.M., Chunwongse J. and Tanksley S.D. 1995. Microprep protocol for extraction of DNA from tomato and other herbaceous plants. Plant Mol. Biol. Rep. 13: 207–209. Ganal M.W., Czihal R., Hannappel U., Kloos D.-U., Polley A. and Ling H.-Q. 1998. Sequencing of cDNA Clones from the Genetic Map of Tomato 共Lycopersicon esculentum兲. Genome Res. 8: 842–847. Goldman I., Paran I. and Zamir D. 1995. Quantitative trait locus analysis of a recombinant inbred line population derived from a
Lycopersicon esculentum x Lycopersicon cheesmanii cross. Theor. Appl. Genet. 90: 925–932. Grandillo S., Ku H.M. and Tanksley S.D. 1996. Characterization of fs8.1, a major QTL influencing fruit shape in tomato. Mol. Breed. 2: 251–260. Grandillo S., Ku H.M. and Tanksley S.D. 1999. Identifying the loci responsible for natural variation in fruit size and shape in tomato. Theor. Appl. Genet. 99: 978–987. Grandillo S. and Tanksley S.D. 1996. QTL analysis of horticultural traits differentiating the cultivated tomato from the closely related species Lycopersicon pimpinellifolium. Theor. Appl. Genet. 92: 935–951. Hobson G.E., Gough C. and Townley C. 1990. Measuring consumer reaction to the flavour of fresh tomatoes. Acta Hortic 259: 107–116. Jones R.A. and Scott S.J. 1983. Improvement of tomato flavor by genetically increasing sugar and acid contents. Euphytica 32: 845–855. Kosambi D.D. 1944. The estimation of map distances from recombination values. Ann Eugen 12: 172–175. Lander E.S., Green P., Abrahamson J., Barlox A., Daly M.J., Lincoln S.E. and Newburg L. 1987. MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics 1: 174–181. Lincoln S.E., Daly M.J. and Lander E.S. 1992. Constructing genetic maps with MAPMAKER/EXP version 3.0. 共1992兲. Lippman Z.and Tanksley S.D. 2001. Dissecting the genetic pathway to extreme fruit size in tomato using a cross between the small-fruited wild species Lycopersicon pimpinellifolium and L. esculentum var. Giant Heirloom. Genetics 158: 413–422. MacArthur J.W. 1934. Fruit size effects of qualitative genes in the tomato. Am. Nat. 58: 73–74. Monforte A.J. and Tanksley S.D. 2000. Fine mapping of a quantitative trait locus 共QTL兲 from Lycopersicon hirsutum chromosome 1 affecting fruit characteristics and agronomic traits: breaking linkage among QTLs affecting different traits and dissection of heterosis for yield. Theor. Appl. Genet. 100: 471–479. Nesbitt T.C. and Tanksley S.D. 2002. Comparative sequencing in the genus Lycopersicon: implications for the evolution of fruit size in the domestication of cultivated tomatoes. Genetics 162: 365–379. Paran I., Goldman I., Tanksley S.D. and Zamir D. 1995. Recombinant inbred lines for genetic mapping in tomato. Theor. Appl. Genet. 90: 542–548. Paterson A.H., de Verna J.W., Lanini B. and Tanksley S.D. 1990. Fine mapping of quantitative trait loci using selected overlapping recombinant chromosomes, in an interspecies cross of tomato. Genetics 124: 735–742. Paterson A.H., Lander E.S., Hewitt J.D., Peterson S., Lincoln S.E. and Tanksley S.D. 1988. Resolution of quantitative traits into Mendelian factors by using a complete linkage map of restriction fragment length polymorphisms. Nature 335: 721–726. Petro-Turza M. 1987. Flavor of tomato and tomato products. Food Rev. Int. 2: 309–351. Rick C.M. 1974. High soluble-solids content in large-fruited tomato lines derived from a wild green-fruited species. Hilgardia 42: 493–510. Rozen S. and Skaletsky H.J. 1998. Primer3. Code available at http://www-genome.wi.mit.edu/genome_software/other/primer3. html.
14 Saliba-Colombani V., Causse M., Gervais L.and Philouze J. 2000. Efficiency of AFLP, RAPD and RFLP markers for the construction of an intraspecific map of the tomato genome. Genome 43: 29–40. Saliba-Colombani V., Causse M., Langlois D., Philouze J. and Buret M. 2001. Genetic analysis of organoleptic quality in fresh market tomato. 1. Mapping QTLs for physical and chemical traits. Theor. Appl. Genet. 102: 259–272. SAS Institute 1988. SAS users guide: statistics. In: SAS Institute 共Eds.兲, Cary, North Carolina, USA. Sawhney V.K. and Greyson R.I. 1972. Fruit-size increase in tomato following application of gibberellic acid. J. Am. Soc. Hortic Sci. 97: 589–590. SCAR Agro-Food Tomato Working Group 1991. Measurement of the quality of tomatoes: recommendations of an EEC working group. In: Eccher Zerbini P., Gorini F., Polesello A. 共Eds.兲, I.V.T.P.A., Milano. Splus 1993. Splus guide to statistical and mathematical analyses. In: Mathsoft 共ed.兲, Seattle, Washington, USA. Stevens M.A. 1986. Inheritance of tomato fruit quality components. Plant Breed. Rev. 4: 273–311. Stevens M.A., Kadre A.A. and Albright M. 1979. Potential for increasing tomato flavor via sugar and acid contents. J. Am. Soc. Hortic Sci. 104: 40–42. Takahashi Y., Shomura A., Sasaki T. and Yano M. 2001. Hd6, a rice quantitative trait locus involved in photoperiod sensitivity, encodes the ␣-subunit of protein CK2. Proc. Natl. Acad. Sci. USA 98: 7922–7927. Tanksley S.D., Ganal M.W., Prince J.P., de Vicente M.C., Bonierbale M.W., Broun P., Fulton T.M., Giovannoni J.J., Grandillo S.,
Martin G.B., Messeguer R., Miller J.C., Miller L., Paterson A.H., Pineda O., Röder M.S., Wing R.A., Wu W. and Young N.D. 1992. High density molecular linkage maps of the tomato and potato genomes. Genetics 132: 1141–1160. Tuinstra M.R., Ejeta G. and Goldsbrough P.B. 1997. Heterogeneous inbred family 共HIF兲 analysis: a method for developing near-isogenic lines that differ at quantitative trait loci. Theor. Appl. Genet. 95: 1005–1011. Wood M. 1992. Solid future for tomatoes. Agric. Res. 40: 4–5. Yano M., Harushima Y., Nagamura Y., Kurata N., Minobe Y. and Sasaki T. 1997. Identification of quantitative trait loci controlling heading date in rice using a high-density linkage map. Theor. Appl. Genet. 95: 1025–1032. Yano M., Katayose Y., Ashikari M., Yamanouchi U., Monna L., Fuse T., Baba T., Yamamoto K., Umehara Y., Nagamura Y. and Sasaki T. 2000. Hd1, a major photoperiod sensitivity quantitative trait locus in rice, is closely related to the Arabidopsis flowering time gene CONSTANS. Plant Cell. 12: 2473–2484. Yeager A.F. 1973. Studies on the inheritance and development of fruit size and shape in the tomato. J Agric Res 55: 141–152. Yousef G.G., Juvik J.A. 2001. Evaluation of breeding utility of a chromosomal segment from Lycopersicon chmielewskii that enhances cultivated tomato soluble solids. Theor. Appl. Genet. 103: 1022–1027. Zeng Z.B. 1993. Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci. Proc. Natl. Acad. Sci. USA 90: 10972–10976. Zeng Z.B. 1994. Precision mapping of quantitative trait loci. Genetics 136: 1457–1468.
