Genetic structure of a QTL hotspot on chromosome 2 in sweet cherry indicates positive selection for favorable haplotypes

A genomic region of particular interest for sweet cherry (Prunus avium L.) breeding is a quantitative trait locus (QTL) “hotspot” on chromosome 2. QTLs for fruit size, firmness, sweetness, and flowering time are reported to map to this region. An understanding of genetic diversity, allele sources, linkage relationships, and historical recombinations is critical to enable the combining of favorable alleles at multiple loci. The objectives of this study were to characterize, visualize, and interpret the genetic structure of this previously identified QTL hotspot within North American sweet cherry breeding germplasm, using a pedigree-based haploblocking approach. Across the 29.4 cM (6.3 Mbp) region defined by single nucleotide polymorphism (SNP) information from the RosBREED cherry 6K SNP array v1, a total of 12 recombination events falling into six inter-marker regions were traced within the pedigree of elite and wild germplasm (n = 55). These recombinations defined five haploblocks containing 5–15 markers and exhibiting 7–11 haplotypes each. Over the entire QTL hotspot, 30 extended haplotypes were identified for which parental gametes could be determined. When the haploblocks and their haplotypes were used to explore genetic diversity, ancestry, and recombination patterns, and then integrated with previous QTL results for fruit size, the results indicated that favorable alleles at this QTL hotspot are under positive selection in breeding. The genetic framework provided by a haploblock approach and knowledge of haplotype-level diversity sets the stage for assigning breeding utility to these haplotypes.     

Mapping and validation of QTLs for resistance to aphids and whiteflies in melon

Aphis gossypii and Bemisia tabaci are severe hemipteran pests of melon crops and breeding for resistance to both insects is required to reduce pesticide use. Resistance was evaluated for its effect on behaviour and biotic potential of both hemipterans in a population of recombinant inbred lines (RILs) derived from the cross Védrantais × PI 161375. Insect variability was considered using two A. gossypii clones and two B. tabaci populations. Two additive QTLs affected the whiteflies. Four additive QTLs and two couples of epistatic QTLs affected the aphids. Amongst them, a major QTL affects both behaviour and biotic potential of A. gossypii and therefore a same R gene induces both antixenosis and antibiosis. This major QTL colocalizes with the Vat gene belonging to the NBS-LRR gene family. No loci affected both aphids and whiteflies contrary to what was observed for the Mi1.2 gene, a NBS-LRR gene in tomato. Original populations with different allelic compositions at QTLs affecting A. gossypii were built by one inter-crossing of RILs used for the mapping process. The genetic background was shown homogeneous between these populations what allowed validating QTLs and investigating the effect of allelic combinations at QTLs. Effects of QTLs were stronger than expected and some QTLs had a wider spectrum than expected. This strategy of validation appeared rapid and low cost.     

Introgression of homeologous quantitative trait loci (QTLs) for resistance to the root-knot nematode [Meloidogyne arenaria (Neal) Chitwood] in an advanced backcross-QTL population of peanut (Arachis hypogaea L.)

Resistance to root-knot nematodes [Meloidogyne arenaria (Neal) Chitwood] is needed for cultivation of peanut in major peanut-growing areas, but significant resistance is lacking in the cultivated species (Arachis hypogaea L.). Markers to two closely-linked genes introgressed from wild relatives of peanut have been identified previously, but phenotypic evidence for the presence of additional genes in wild species and introgression lines has eluded quantitative trait locus (QTL) identification. Here, to improve sensitivity to small-effect QTLs, an advanced backcross population from a cross between a Florunner component line and the synthetic amphidiploid TxAG-6 [Arachis batizocoi × (A. cardenasii × A. diogoi)]^4× was screened for response to root-knot nematode infection. Composite interval mapping results suggested a total of seven QTLs plus three putative QTLs. These included the known major resistance gene plus a second QTL on LG1, and a potentially homeologous B-genome QTL on LG11. Additional potential homeologs were identified on linkage group (LG) 8 and LG18, plus a QTL on LG9.2 and putative QTLs on LG9.1 and 19. A QTL on LG15 had no inferred resistance-associated homeolog. Contrary to expectation, two introgressed QTLs were associated with susceptibility, and QTLs at some homeologous loci were found to confer opposite phenotypic responses. Long-term functional conservation accompanied by rapid generation of functionally divergent alleles may be a singular feature of NBS-LRR resistance gene clusters, contributing to the richness of resistance alleles available in wild relatives of crops. The significance for peanut evolution and breeding is discussed.     

Major-effect QTLs for stem and foliage resistance to late blight in the wild potato relatives <Emphasis Type="Italic">Solanum sparsipilum</Emphasis> and <Emphasis Type="Italic">S. spegazzinii</Emphasis> are mapped to chromosome X

To find out new resistance sources to late blight in the wild germplasm for potato breeding, we examined the polygenic resistance of Solanum sparsipilum and S. spegazzinii by a quantitative trait locus (QTL) analysis. We performed stem and foliage tests under controlled conditions in two diploid mapping progenies. Four traits were selected for QTL detection. A total of 30 QTLs were mapped, with a large-effect QTL region on chromosome X detected in both potato relatives. The mapping of literature-derived markers highlighted colinearities with published late blight QTLs or R-genes. Results showed (a) the resistance potential of S. sparsipilum and S. spegazzinii for late blight control, and (b) the efficacy of the stem test as a complement to the foliage test to break down the complex late blight resistance into elementary components. The relationships of late blight resistance QTLs with R-genes and maturity QTLs are discussed.     

Association Mapping and Validation of QTLs for Flour Yield in the Soft Winter Wheat Variety Kitahonami

The winter wheat variety Kitahonami shows a superior flour yield in comparison to other Japanese soft wheat varieties. To map the quantitative trait loci (QTL) associated with this trait, association mapping was performed using a panel of lines from Kitahonami’s pedigree, along with leading Japanese varieties and advanced breeding lines. Using a mixed linear model corrected for kernel types and familial relatedness, 62 marker-trait associations for flour yield were identified and classified into 21 QTLs. In eighteen of these, Kitahonami alleles showed positive effects. Pedigree analysis demonstrated that a continuous pyramiding of QTLs had occurred throughout the breeding history of Kitahonami. Linkage analyses using three sets of doubled haploid populations from crosses in which Kitahonami was used as a parent were performed, leading to the validation of five of the eight QTLs tested. Among these, QTLs on chromosomes 3B and 7A showed highly significant and consistent effects across the three populations. This study shows that pedigree-based association mapping using breeding materials can be a useful method for QTL identification at the early stages of breeding programs.     

QTL mapping and breeding value estimation through pedigree-based analysis of fruit size and weight in four diverse peach breeding programs

The narrow genetic base of peach (Prunus persica L. Batsch) challenges efforts to accurately dissect the genetic architecture of complex traits. Standardized phenotypic assessment of pedigree-linked breeding germplasm and new molecular strategies and analytical approaches developed and conducted during the RosBREED project for enabling marker-assisted breeding (MAB) in Rosaceae crops has overcome several aspects of this challenge. The genetic underpinnings of fruit size (fruit equatorial diameter (FD)) and weight (fresh weight (FW)), two most important components of yield, were investigated using the pedigree-based analysis (PBA) approach under a Bayesian framework which has emerged as an alternative strategy to study the genetics of quantitative traits within diverse breeding germplasm across breeding programs. In this study, a complex pedigree with the common founder “Orange Cling” was identified and FD and FW data from 2011 and 2012 analyzed. A genetic model including genetic additive and dominance effects was considered, and its robustness was evaluated by using various prior and initial values in the Markov chain Monte Carlo procedure. Five QTLs were identified which accounted for up to 29 and 17 % of the phenotypic variation for FD and FW, respectively. Additionally, genomic breeding values were obtained for both traits, with accuracies >85 %. This approach serves as a model study for performing PBA across diverse pedigrees. By incorporating multiple breeding programs, the method and results presented support and highlight the ability of this strategy to identify genomic resources as targets for DNA marker development and subsequent MAB within each program.     

Identification and Validation of Quantitative Trait Loci for Agronomic Traits in Advanced Backcross Breeding Lines Derived from Oryza rufipogon × Oryza sativa Cultivar MR219

A backcross breeding strategy was used to identify quantitative trait loci (QTLs) associated with 14 traits in a BC₂F₂ population derived from a cross between MR219, an indica rice cultivar and an accession of Oryza rufipogon (IRGC 105491). A total of 261 lines were genotyped with 96 microsatellite markers and evaluated for plant morphology, yield components and growth period. The genetic linkage map generated for this population with an average interval size of 16.2?cM, spanning 1,553.4?cM (Kosambi) of the rice genome. Thirty-eight QTLs were identified with composite interval mapping (CIM), whereas simple interval mapping (SIM) resulted in 47 QTLs (LOD >3.0). The O. rufipogon allele was favourable for 59% of QTLs detected through CIM. Of 261 BC₂F₂ families, 26 advanced backcross breeding lines (BC₂F₅) were used for QTL validation. These lines were selected on the basis of the yield traits potentiality in BC₂F₃ and BC₂F₄ generations. The field trial was conducted at three different locations in Malaysia using randomized complete block design with three replications. Trait based marker analysis was done for QTL determination. Twenty-five QTLs were detected in BC₂F₅ generation whereas 29 QTLs were detected in BC₂F₂ generation of the same population. Two QTLs (qPL-1 and qSPL-7) were not considered for validation due to their low R ² values and two QTLs (qPSS-3-2 and qGW-3-2) were not detected in the BC₂F₅ population. Fifteen QTLs showed the beneficial effect to enhance the trait value of the breeding lines. QTL validation aided to select the promising lines for further utilization.     

Construction of Chromosome Segment Substitution Lines in Peanut (Arachis hypogaea L.) Using a Wild Synthetic and QTL Mapping for Plant Morphology

Chromosome segment substitution lines (CSSLs) are powerful QTL mapping populations that have been used to elucidate the molecular basis of interesting traits of wild species. Cultivated peanut is an allotetraploid with limited genetic diversity. Capturing the genetic diversity from peanut wild relatives is an important objective in many peanut breeding programs. In this study, we used a marker-assisted backcrossing strategy to produce a population of 122 CSSLs from the cross between the wild synthetic allotetraploid (A. ipaënsis×A. duranensis)^4x and the cultivated Fleur11 variety. The 122 CSSLs offered a broad coverage of the peanut genome, with target wild chromosome segments averaging 39.2 cM in length. As a demonstration of the utility of these lines, four traits were evaluated in a subset of 80 CSSLs. A total of 28 lines showed significant differences from Fleur11. The line×trait significant associations were assigned to 42 QTLs: 14 for plant growth habit, 15 for height of the main stem, 12 for plant spread and one for flower color. Among the 42 QTLs, 37 were assigned to genomic regions and three QTL positions were considered putative. One important finding arising from this QTL analysis is that peanut growth habit is a complex trait that is governed by several QTLs with different effects. The CSSL population developed in this study has proved efficient for deciphering the molecular basis of trait variations and will be useful to the peanut scientific community for future QTL mapping studies.     

The genetic and functional analysis of flavor in commercial tomato: the FLORAL4 gene underlies a QTL for floral aroma volatiles in tomato fruit

Tomato (Solanum lycopersicum L.) has become a popular model for genetic studies of fruit flavor in the last two decades. In this article we present a study of tomato fruit flavor, including an analysis of the genetic, metabolic and sensorial variation of a collection of contemporary commercial glasshouse tomato cultivars, followed by a validation of the associations found by quantitative trait locus (QTL) analysis of representative biparental segregating populations. This led to the identification of the major sensorial and chemical components determining fruit flavor variation and detection of the underlying QTLs. The high representation of QTL haplotypes in the breeders’ germplasm suggests that there is great potential for applying these QTLs in current breeding programs aimed at improving tomato flavor. A QTL on chromosome 4 was found to affect the levels of the phenylalanine‐derived volatiles (PHEVs) 2‐phenylethanol, phenylacetaldehyde and 1‐nitro‐2‐phenylethane. Fruits of near‐isogenic lines contrasting for this locus and in the composition of PHEVs significantly differed in the perception of fruity and rose‐hip‐like aroma. The PHEV locus was fine mapped, which allowed for the identification of FLORAL4 as a candidate gene for PHEV regulation. Using a gene‐editing‐based (CRISPR‐CAS9) reverse‐genetics approach, FLORAL4 was demonstrated to be the key factor in this QTL affecting PHEV accumulation in tomato fruit.     

Genome-wide association mapping of Fusarium head blight resistance in contemporary barley breeding germplasm

Utilization of quantitative trait loci (QTL) identified in bi-parental mapping populations has had limited success for improving complex quantitative traits with low to moderate heritability. Association mapping in contemporary breeding germplasm may lead to more effective marker strategies for crop improvement. To test this approach, we conducted association mapping of two complex traits with moderate heritability; Fusarium head blight (FHB) severity and the grain concentration of mycotoxin associated with disease, deoxynivalenol (DON). To map FHB resistance in barley, 768 breeding lines were evaluated in 2006 and 2007 in four locations. All lines were genotyped with 1,536 SNP markers and QTL were mapped using a mixed model that accounts for relatedness among lines. Average linkage disequilibrium within the breeding germplasm extended beyond 4 cM. Four QTL were identified for FHB severity and eight QTL were identified for the DON concentration in two independent sets of breeding lines. The QTL effects were small, explaining 1–3% of the phenotypic variation, as might be expected for complex polygenic traits. We show that using breeding germplasm to map QTL can complement bi-parental mapping studies by providing independent validation, mapping QTL with more precision, resolving questions of linkage and pleiotropy, and identifying genetic markers that can be applied immediately in crop improvement.     

Mapping QTL for agronomic traits in breeding populations

Detection of quantitative trait loci (QTL) in breeding populations offers the advantage that these QTL are of direct relevance for the improvement of crops via knowledge-based breeding. As phenotypic data are routinely generated in breeding programs and the costs for genotyping are constantly decreasing, it is tempting to exploit this information to unravel the genetic architecture underlying important agronomic traits in crops. This review characterizes the germplasm from breeding populations available for QTL detection, provides a classification of the different QTL mapping approaches that are available, and highlights important considerations concerning study design and biometrical models suitable for QTL analysis.     

Identification of QTLs influencing agronomic traits in <Emphasis Type="Italic">Miscanthus sinensis</Emphasis> Anderss. I. Total height,flag-leaf height and stem diameter

We have developed the first quantitative trait locus (QTL) analyses for agronomic traits in a cross between F(1.1) (P1) and F(1.7) (P7) entries of Miscanthus sinensis Anderss. Both lines are offspring of the cross between MS-90-2 and MS-88-110. A map based on random amplified polymorphic DNA markers previously constructed was used to perform the QTL analyses. This map was developed using a new mapping strategy that has been designated offspring cross. Eleven QTLs were detected for height, panicle height and diameter using the programme mapqtl 4.0 and the multiple QTL method. QTL significance was determined using several analyses, including Kruskal-Wallis analyses, empirical determination of LOD critical values using permutation tests, QTLs validation with field data over 2 years and co-localization of QTLs for correlated traits. The results obtained could be the first step in developing a marker-assisted selection programming in this species for biomass production.     

Identification of genome regions controlling cotyledon,pod wall/seed coat and pod wall resistance to pea weevil through QTL mapping

Pea weevil, Bruchus pisorum, is one of the limiting factors for field pea (Pisum sativum) cultivation in the world with pesticide application the only available method for its control. Resistance to pea weevil has been found in an accession of Pisum fulvum but transfer of this resistance to cultivated pea (P. sativum) is limited due to a lack of easy-to-use techniques for screening interspecific breeding populations. To address this problem, an interspecific population was created from a cross between cultivated field pea and P. fulvum (resistance source). Quantitative trait locus (QTL) mapping was performed to discover the regions associated with resistance to cotyledon, pod wall/seed coat and pod wall resistance. Three major QTLs, located on linkage groups LG2, LG4 and LG5 were found for cotyledon resistance explaining approximately 80 % of the phenotypic variation. Two major QTLs were found for pod wall/seed coat resistance on LG2 and LG5 explaining approximately 70 % of the phenotypic variation. Co-linearity of QTLs for cotyledon and pod wall/seed coat resistance suggested that the mechanism of resistance for these two traits might act through the same pathways. Only one QTL was found for pod wall resistance on LG7 explaining approximately 9 % of the phenotypic variation. This is the first report on the development of QTL markers to probe Pisum germplasm for pea weevil resistance genes. These flanking markers will be useful in accelerating the process of screening when breeding for pea weevil resistance.     

A Sequential Quantitative Trait Locus Fine-Mapping Strategy Using Recombinant-Derived Progeny

A thorough understanding of the quantitative trait loci(QTLs)that underlie agronomically important traits in crops would greatly increase agricultural productivity.Although advances have been made in QTL cloning,the majority of QTLs remain unknown because of their low heritability and minor contributions to phenotypic performance.Here we summarize the key advantages and disadvantages of current QTL fine-mapping methodologies,and then introduce a sequential QTL fine-mapping strategy based on both genotypes and phenotypes of progeny derived from recombinants.With this mapping strategy,experimental errors could be dramatically diminished so as to reveal the authentic genetic effect of target QTLs.The number of progeny required to detect QTLs atvarious R~2 values was calculated,and the backcross generation suitable to start QTL fine-mapping was also estimated.This mapping strategy has proved to be very powerful in narrowing down QTL regions,particularly minor-effect QTLs,as revealed by fine-mapping of various resistance QTLs in maize.Application of this sequential QTL mapping strategy should accelerate cloning of agronomically important QTLs,which is currently a substantial challenge in crops.     

Quantitative trait loci for agronomic traits in an elite barley population for Mediterranean conditions

Advances in plant breeding through marker-assisted selection (MAS) are only possible when genes or quantitative trait loci (QTLs) can contribute to the improvement of elite germplasm. A population of recombinant inbred lines (RILs) was developed for one of the best crosses of the Spanish National Barley Breeding Program, between two six-row winter barley cultivars Orria and Plaisant. The objective of this study was to identify favourable QTLs for agronomic traits in this population, which may help to optimise breeding strategies for these and other elite materials for the Mediterranean region. A genetic linkage map was developed for 217 RILs, using 382 single nucleotide polymorphism markers, selected from the barley oligonucleotide pool assay BOPA1 and two genes. A subset of 112 RILs was evaluated for several agronomic traits over a period of 2 years at three locations, Lleida and Zaragoza (Spain) and Fiorenzuola d’Arda (Italy), for a total of five field trials. An important segregation distortion occurred during population development in the region surrounding the VrnH1 locus. A QTL for grain yield and length of growth cycle was also found at this locus, apparently linked to a differential response of the VrnH1 alleles to temperature. A total of 33 QTLs was detected, most of them for important breeding targets such as plant height and thousand-grain weight. QTL × environment interactions were prevalent for most of the QTLs detected, although most interactions were of a quantitative nature. Therefore, QTLs suitable for MAS for most traits were identified.     

Single nucleotide polymorphism tightly linked to a major QTL on chromosome 7A for both kernel length and kernel weight in wheat

Thousand-kernel weight (TKW) is one of the major components of grain yield in wheat (Triticum aestivum). Identifying major quantitative trait loci (QTLs) for TKW and developing effective markers are prerequisite for success in marker-assisted selection (MAS) to improve wheat yield through breeding. This study mapped a major QTL, designated as TaTKW-7AL, for increasing TKW on the long arm of chromosome 7A of ‘Clark’ to a 1.3-cM interval between single nucleotide polymorphism (SNP) markers IWB13913 and IWA5913. This QTL explained 19.7 % of the phenotypic variation for TKW. A QTL for increasing kernel length (KL), one of the major components of TKW, was mapped in the same interval as TaTKW-7AL, suggesting that increased TKW by the QTL in ‘Clark’ is most likely due to the increased KL. Association analysis on a diversity panel of 200 US winter wheat accessions also identified a haplotype of three SNP markers (IWB13913, IWB6693 and IWA5913) that were tightly associated with the both KL and TKW. The analysis of allele frequencies of the haplotype in the diversity panel suggested that the favorable allele of TaTKW-7AL has not been strongly selected for in practice and has potential to be used to improve grain yield in US hard winter wheat breeding. Two user-friendly flanking KASPar markers, IWB13913 and IWA5913, were developed for MAS of TaTKW-7AL.     

Mixed-model QTL mapping for kernel hardness and dough strength in bread wheat

Plant breeding data comprise unbalanced phenotypic data for inbreds with complex pedigrees. As traditional methods to map quantitative trait loci (QTL) cannot exploit plant breeding data, an alternative approach is QTL mapping via a mixed-model procedure. Our objective was to validate mixed-model QTL mapping for self-pollinated crops by detecting QTL for kernel hardness and dough strength from data in a bread wheat (Triticum aestivum L.) breeding program. We studied 80 parental and 373 experimental inbreds genotyped for 65 simple sequence repeat (SSR) markers and three candidate loci. The methodology involved three steps: variance component estimation, single-marker analyses, and a final multiple-marker analysis with marker effects treated as fixed effects. Two QTLs for kernel hardness were detected on chromosomes 1A (close to candidate locus GluA3) and 5D (close to candidate locus Ha). Four QTLs were detected for dough strength on chromosomes 1A, 1B, 1D, and 5B. Candidate gene GluA1, which was associated with dough strength, was the only candidate locus found significant. Results were consistent with previously reported markers and QTLs associated with kernel hardness and dough strength. Unlike previous studies that have assumed QTL effects as random, the assumption of fixed marker effects identified the favorable marker alleles to select for. We conclude that the detection of previously mapped QTL validates the usefulness of mixed-model QTL mapping in the context of a plant-breeding program.     

Comparison of three QTL detection models on biochemical,sensory, and yield characters in Coffea canephora

Coffea canephora is subject to enormous competitive challenges from other crops, especially for farmer sustainability and consumer requirements. Coffee breeding programs have to focus on specific traits linked to these two key targets, such as quality character, largely depending on the bean’s biochemical composition and field yield. Two segregating populations A and B, from crosses between a hybrid (Congolese?×?Guinean) FRT58 parental clone and a Congolese FRT51 genotype and between two Congolese parents FRT67 and FRT51, respectively, were used to characterize the quantitative trait loci (QTL) involved in agronomic and biochemical traits. A consensus genetic map was established using 249 SSRs covering 1,201 cM. Three QTL detection models per population with MapQTL (model I) and MCQTL (model II) followed by a connected population approach with MCQTL (model III) were compared based on their efficiency, precision for QTL detection, and their genetic effect assessment (additive, dominance, and parental-favorable allele). The analysis detected a total of 143 QTLs, 60 of which were shared between the three models; 28 found with two models; and two, 13, and 40 specific from models I, II, and III, respectively. The last model III based on connected populations is much more efficient in detecting QTLs with low variance explained and led to the genetic characterization of favorable allele. Thanks to this comparison of three QTL detection models on our quantitative genetic study, we will give a new insight for coffee breeding programs dedicated to managing complex agronomic or qualitative traits.     

Quantitative Trait Loci for Light Sensitivity,Body Weight,Body Size,and Morphological Eye Parameters in the Bumblebee,Bombus terrestris

Bumblebees such as Bombus terrestris are essential pollinators in natural and managed ecosystems. In addition, this species is intensively used in agriculture for its pollination services, for instance in tomato and pepper greenhouses. Here we performed a quantitative trait loci (QTL) analysis on B. terrestris using 136 microsatellite DNA markers to identify genes linked with 20 traits including light sensitivity, body size and mass, and eye and hind leg measures. By composite interval mapping (IM), we found 83 and 34 suggestive QTLs for 19 of the 20 traits at the linkage group wide significance levels of p = 0.05 and 0.01, respectively. Furthermore, we also found five significant QTLs at the genome wide significant level of p = 0.05. Individual QTLs accounted for 7.5-53.3% of the phenotypic variation. For 15 traits, at least one QTL was confirmed with multiple QTL model mapping. Multivariate principal components analysis confirmed 11 univariate suggestive QTLs but revealed three suggestive QTLs not identified by the individual traits. We also identified several candidate genes linked with light sensitivity, in particular the Phosrestin-1-like gene is a primary candidate for its phototransduction function. In conclusion, we believe that the suggestive and significant QTLs, and markers identified here, can be of use in marker-assisted breeding to improve selection towards light sensitive bumblebees, and thus also the pollination service of bumblebees.     

Fruit size QTL identification and the prediction of parental QTL genotypes and breeding values in multiple pedigreed populations of sweet cherry

Large fruit size is a critical trait for any new sweet cherry (Prunus avium L.) cultivar, as it is directly related to grower profitability. Therefore, determining the genetic control of fruit size in relevant breeding germplasm is a high priority. The objectives of this study were (1) to determine the number and positions of quantitative trait loci (QTL) for sweet cherry fruit size utilizing data simultaneously from multiple families and their pedigreed ancestors, and (2) to estimate fruit size QTL genotype probabilities and genomic breeding values for the plant materials. The sweet cherry material used was a five-generation pedigree consisting of 23 founders and parents and 424 progeny individuals from four full-sib families, which were phenotyped for fruit size and genotyped with 78 RosCOS single nucleotide polymorphism and 86 simple sequence repeat markers. These data were analyzed by a Bayesian approach implemented in FlexQTL? software. Six QTL were identified: three on linkage group (G) 2 with one each on groups 1, 3, and 6. Of these QTL, the second G2 QTL and the G6 QTL were previously discovered while other QTL were novel. The predicted QTL genotypes show that some QTL were segregating in all families while other QTL were segregating in a subset of the families. The progeny varied for breeding value, with some progeny having higher breeding values than their parents. The results illustrate the use of multiple pedigree-linked families for integrated QTL mapping in an outbred crop to discover novel QTL and predict QTL genotypes and breeding values.