Segregation Of Quantitative Trait Loci Research Articles

Multiomics Based Association Mapping in Wheat Reveals Genetic Architecture of Quality and Allergenic Related Proteins.

Wheat is an important staple crop since its proteins contribute to human and animal nutrition and are important for its end-use quality. However, wheat proteins can also cause adverse human reactions for a large number of people. We performed a genome wide association study (GWAS) on 114 proteins quantified by LC-MS-based proteomics and expressed in an environmentally stable manner in 148 wheat cultivars with a heritability > 0.6. For 54 proteins, we detected quantitative trait loci (QTL) that exceeded the Bonferroni-corrected significance threshold and explained 17.3−84.5% of the genotypic variance. Proteins in the same family often clustered at a very close chromosomal position or the potential homeolog. Major QTLs were found for four well-known glutenin and gliadin subunits, and the QTL segregation pattern in the protein encoding the high molecular weight glutenin subunit Dx5 could be confirmed by SDS gel-electrophoresis. For nine potential allergenic proteins, large QTLs could be identified, and their measured allele frequencies open the possibility to select for low protein abundance by markers as long as their relevance for human health has been conclusively demonstrated. A potential allergen was introduced in the beginning of 1980s that may be linked to the cluster of resistance genes introgressed on chromosome 2AS from Triticum ventricosum. The reported sequence information for the 54 major QTLs can be used to design efficient markers for future wheat breeding.

Genome analysis in Avena sativa reveals hidden breeding barriers and opportunities for oat improvement

Oat (Avena sativa L.) is an important and nutritious cereal crop, and there is a growing need to identify genes that contribute to improved oat varieties. Here we utilize a newly sequenced and annotated oat reference genome to locate and characterize quantitative trait loci (QTLs) affecting agronomic and grain-quality traits in five oat populations. We find strong and significant associations between the positions of candidate genes and QTL that affect heading date, as well as those that influence the concentrations of oil and β-glucan in the grain. We examine genome-wide recombination profiles to confirm the presence of a large, unbalanced translocation from chromosome 1 C to 1 A, and a possible inversion on chromosome 7D. Such chromosome rearrangements appear to be common in oat, where they cause pseudo-linkage and recombination suppression, affecting the segregation, localization, and deployment of QTLs in breeding programs.

Training set design in genomic prediction with multiple biparental families.

Genomic selection is a powerful tool to reduce the cycle length and enhance the genetic gain of complex traits in plant breeding. However, questions remain about the optimum design and composition of the training set. In this study, we used 944 soybean [Glycine max (L.) Merr.] recombinant inbred lines from eight families derived through a partial-diallel mating design among five parental lines. The cross-validated prediction accuracies for the six traits seed yield, 1,000-seed weight, protein yield, plant height, protein content, and oil content were high, ranging from 0.79 to 0.87. We investigated among-family predictions, making use of the special mating design with different degrees of relatedness among families. Generally, the prediction accuracy decreased from full-sibs to half-sib families to unrelated families. However, half-sib and unrelated families also showed substantial variation in their prediction accuracy for a given family, which appeared to be caused at least in part by the shared segregation of quantitative trait loci in both the training and prediction sets. Combining several half-sib families in composite training sets generally led to an increase in the prediction accuracy compared with the best family alone. The prediction accuracy increased with the size of the training set, but for comparable prediction accuracy, substantially more half-sibs were required than full-sibs. Collectively, our results highlight the potential of genomic selection for soybean breeding and, in a broader context, illustrate the importance of the targeted design of the training set.

Detection of quantitative trait loci and putative causal variants affecting somatic cell score in dairy sheep by using a 50K SNP chip and whole-genome sequencing

This study presents a scan of the ovine genome to identify quantitative trait loci (QTL) influencing the somatic cell score (SCS), a classical indicator of subclinical mastitis in sheep, and a subsequent high-resolution analysis of one of the identified QTL regions based on the analysis of whole-genome sequence data sets. A half-sib commercial population of Churra sheep genotyped with a 50K SNP chip was analyzed using linkage analysis (LA) and combined linkage and linkage disequilibrium analysis (LDLA). By LA, 2 5% chromosome-wide significant QTL on OAR5 and OAR25 and one 5% genome-wide significant QTL on ovine chromosome 20 (OAR20) were detected, whereas 22 significant associations were identified by LDLA. Two of the associations detected by LDLA replicated LA-detected effects (OAR20, OAR25). We compared the detected associations with previously reported QTL in sheep and cattle, and functional candidate genes were identified within the estimated confidence intervals. We then performed a high-resolution analysis of the OAR20 QTL region, the most significant QTL region identified by LA that replicated a QTL previously described in Churra sheep for SCS using microsatellite markers. For that, 2 segregating trios of 2 segregating families for the OAR20 QTL (each including the Qq sire and 2 daughters, QQ and qq) were selected for whole-genome sequencing. The bioinformatic analysis of the 6 sequenced samples performed across the genomic interval considered (14.2-41.7 Mb) identified a total of 227,030 variants commonly identified by 2 independent software packages. For the 3 different concordance tests considered, due to discrepancies regarding the QTL peak in the segregating families, the list of mutations concordant with the QTL segregating pattern was processed to identify the variants identified in immune-related genes that show a moderate/high impact on the encoded protein function. Among a list of 85 missense variants concordant with the QTL segregation pattern that were within candidate immune-related genes, 13 variants distributed across 7 genes [PKHD1, NOTCH4, AGER, ENSOARG00000009395 (HLA-C, Homo sapiens), ENSOARG00000015002 (HLA-B, H. sapiens), MOG, and ENSOARG00000018075 (BoLA, Bos taurus, orthologous to human HLA-A] were predicted to cause deleterious effects on protein function. Future studies should assess the possible associations of the candidate variants identified herein in commercial populations with indicator traits of udder inflammation (SCS, clinical mastitis).

MVQTLCIM: composite interval mapping of multivariate traits in a hybrid F1 population of outbred species

BackgroundWith the plummeting cost of the next-generation sequencing technologies, high-density genetic linkage maps could be constructed in a forest hybrid F1 population. However, based on such genetic maps, quantitative trait loci (QTL) mapping cannot be directly conducted with traditional statistical methods or tools because the linkage phase and segregation pattern of molecular markers are not always fixed as in inbred lines.ResultsWe implemented the traditional composite interval mapping (CIM) method to multivariate trait data in forest trees and developed the corresponding software, mvqtlcim. Our method not only incorporated the various segregations and linkage phases of molecular markers, but also applied Takeuchi’s information criterion (TIC) to discriminate the QTL segregation type among several possible alternatives. QTL mapping was performed in a hybrid F1 population of Populus deltoides and P. simonii, and 12 QTLs were detected for tree height over 6 time points. The software package allowed many options for parameters as well as parallel computing for permutation tests. The features of the software were demonstrated with the real data analysis and a large number of Monte Carlo simulations.ConclusionsWe provided a powerful tool for QTL mapping of multiple or longitudinal traits in an outbred F1 population, in which the traditional software for QTL mapping cannot be used. This tool will facilitate studying of QTL mapping and thus will accelerate molecular breeding programs especially in forest trees. The tool package is freely available from https://github.com/tongchf /mvqtlcim.

Mendelizing all Components of a Pyramid of Three Yield QTL in Tomato.

Molecular markers allowed breeders to mendelize quantitative trait loci (QTL) providing another demonstration that quantitative traits are governed by the same principles as single qualitative genes. This research extends the QTL analysis to two and three QTL and tests our ability to mendelize an oligogenic trait. In tomato, agricultural yield is determined by the weight of the fruits harvested per unit area and the total soluble solids (% Brix)–sugars and acids. The current study explores the segregation of multiple independent yield-related QTL that were identified and mapped using introgression lines (IL) of Solanum pennellii in cultivated processing tomato (S. lycopersicum). We screened 45 different double and triple IL-QTL combinations for agricultural yield, to identify QTL pyramids that behaved in an additive manner and were suitable substrate for mendelizing an oligogenic trait. A pyramid of three independent QTL that significantly improved Brix∗Yield (BXY - the soluble solids output per unit area) compared to M82 was selected. In the progenies of the tri-hybrid we bred using markers a nearly isogenic ‘immortalized F2.’ While the common mode of QTL–QTL interactions across the 45 IL-QTLs combinations was less than additive, the three QTLs in the selected triple-stack performed in an additive manner which made it an exceptional material for breeding. This study demonstrates that using the phenotypic effect of all 27 possible QTL-alleles combinations it is possible to make reliable predictions about the genotypes that will maximize the yield.

Quantitative trait loci for thermal time to flowering and photoperiod responsiveness discovered in summer annual-type Brassica napus L.

Time of flowering is a key adaptive trait in plants and is conditioned by the interaction of genes and environmental cues including length of photoperiod, ambient temperature and vernalisation. Here we investigated the photoperiod responsiveness of summer annual-types of Brassica napus (rapeseed, canola). A population of 131 doubled haploid lines derived from a cross between European and Australian parents was evaluated for days to flowering, thermal time to flowering (measured in degree-days) and the number of leaf nodes at flowering in a compact and efficient glasshouse-based experiment with replicated short and long day treatments. All three traits were under strong genetic control with heritability estimates ranging from 0.85–0.93. There was a very strong photoperiod effect with flowering in the population accelerated by 765 degree-days in the long day versus short day treatments. However, there was a strong genetic correlation of line effects (0.91) between the long and short day treatments and relatively low genotype x treatment interaction indicating that photoperiod had a similar effect across the population. Bivariate analysis of thermal time to flowering in short and long days revealed three main effect quantitative trait loci (QTLs) that accounted for 57.7% of the variation in the population and no significant interaction QTLs. These results provided insight into the contrasting adaptations of Australian and European varieties. Both parents responded to photoperiod and their alleles shifted the population to earlier flowering under long days. In addition, segregation of QTLs in the population caused wide transgressive segregation in thermal time to flowering. Potential candidate flowering time homologues located near QTLs were identified with the aid of the Brassica rapa reference genome sequence. We discuss how these results will help to guide the breeding of summer annual types of B. napus adapted to new and changing environments.

Biparental Resequencing Coupled With SNP Genotyping of a Segregating Population Offers Insights Into the Landscape of Recombination and Fixed Genomic Regions in Elite Soybean

Identification of genes underlying agronomic traits is dependent on the segregation of quantitative trait loci (QTL). A popular hypothesis is that elite lines are becoming increasingly similar to each other, resulting in large genomic regions with fixed genes. Here, we resequenced two parental modern elite soybean lines [ZhongHuang13 (ZH) and ZhongPin03-5373 (ZP)] and discovered 794,876 SNPs with reference to the published Williams82 genome. SNPs were distributed unevenly across the chromosomes, with 87.1% of SNPs clustering in 4.9% of the soybean reference genome. Most of the regions with a high density of SNP polymorphisms were located in the chromosome arms. Moreover, seven large regions that were highly similar between parental lines were identified. A GoldenGate SNP genotyping array was designed using 384 SNPs and the 254 recombinant inbred lines (F8) derived from the cross of ZP × ZH were genotyped. We constructed a genetic linkage map using a total of 485 molecular markers, including 313 SNPs from the array, 167 simple sequence repeats (SSRs), 4 expressed sequence tag–derived SSRs, and 1 insertion/deletion marker. The total length of the genetic map was 2594.34 cM, with an average marker spacing of 5.58 cM. Comparing physical and genetic distances, we found 20 hotspot and 14 coldspot regions of recombination. Our results suggest that the technology of resequencing of parental lines coupled with high-throughput SNP genotyping could efficiently bridge the genotyping gap and provide deep insights into the landscape of recombination and fixed genomic regions in biparental segregating populations of soybean with implications for fine mapping of QTL.

Genetic Architecture of Seed Dormancy in U.S. Weedy Rice in Different Genetic Backgrounds

ABSTRACTSeed dormancy (SD) is a key domestication trait closely related to preharvest sprouting tolerance. Wild and weedy rices (Oryza spp.) exhibit higher degrees of seed dormancy compared to the cultivated rice. Red rice (Oryza sativa L.), a major weed in the rice growing areas of the southern United States, was used to elucidate the genetic architecture of SD. Quantitative trait loci (QTL) analysis conducted in two recombinant inbred line (RIL) populations developed from the crosses involving two rice cultivars (Bengal and Cypress) and a red rice accession (PSRR‐1) revealed six to seven QTL for seed dormancy, which accounted for 49 to 52% of the total phenotypic variance. The magnitude of the QTL contribution to phenotypic variance was influenced by genetic backgrounds. The majority of QTL had minor effects, except the QTL linked to Rc and Sdr4. The genetic architecture for seed dormancy in U.S. red rice was distinct compared with the earlier reported weedy accessions. Four QTL were mapped onto similar positions in both populations. Both cultivars and red rice contributed alleles for increased SD. Most of the digenic epistatic interactions involved loci other than the QTL with main effects. The nucleotide polymorphisms at the Sdr4 locus could not explain the phenotypic variation for seed dormancy in our materials. The variation in SD among the rice cultivars could be attributed to segregation of minor QTL, which may be exploited to improve preharvest sprouting tolerance.

Model selection for quantitative trait loci mapping in a full-sib family

Statistical methods for mapping quantitative trait loci (QTLs) in full-sib forest trees, in which the number of alleles and linkage phase can vary from locus to locus, are still not well established. Previous studies assumed that the QTL segregation pattern was fixed throughout the genome in a full-sib family, despite the fact that this pattern can vary among regions of the genome. In this paper, we propose a method for selecting the appropriate model for QTL mapping based on the segregation of different types of markers and QTLs in a full-sib family. The QTL segregation patterns were classified into three types: test cross (1:1 segregation), F2 cross (1:2:1 segregation) and full cross (1:1:1:1 segregation). Akaike’s information criterion (AIC), the Bayesian information criterion (BIC) and the Laplace-empirical criterion (LEC) were used to select the most likely QTL segregation pattern. Simulations were used to evaluate the power of these criteria and the precision of parameter estimates. A Windows-based software was developed to run the selected QTL mapping method. A real example is presented to illustrate QTL mapping in forest trees based on an integrated linkage map with various segregation markers. The implications of this method for accurate QTL mapping in outbred species are discussed.

Genetic analysis of resistance to septoria tritici blotch in the French winter wheat cultivars Balance and Apache

The ascomycete Mycosphaerella graminicola is the causal agent of septoria tritici blotch (STB), one of the most destructive foliar diseases of bread and durum wheat globally, particularly in temperate humid areas. A screening of the French bread wheat cultivars Apache and Balance with 30 M. graminicola isolates revealed a pattern of resistant responses that suggested the presence of new genes for STB resistance. Quantitative trait loci (QTL) analysis of a doubled haploid (DH) population with five M. graminicola isolates in the seedling stage identified four QTLs on chromosomes 3AS, 1BS, 6DS and 7DS, and occasionally on 7DL. The QTL on chromosome 6DS flanked by SSR markers Xgpw5176 and Xgpw3087 is a novel QTL that now can be designated as Stb18. The QTLs on chromosomes 3AS and 1BS most likely represent Stb6 and Stb11, respectively, and the QTLs on chromosome 7DS are most probably identical with Stb4 and Stb5. However, the QTL identified on chromosome 7DL is expected to be a new Stb gene that still needs further characterization. Multiple isolates were used and show that not all isolates identify all QTLs, which clearly demonstrates the specificity in the M. graminicola–wheat pathosystem. QTL analyses were performed with various disease parameters. The development of asexual fructifications (pycnidia) in the characteristic necrotic blotches of STB, designated as parameter P, identified the maximum number of QTLs. All other parameters identified fewer but not different QTLs. The segregation of multiple QTLs in the Apache/Balance DH population enabled the identification of DH lines with single QTLs and multiple QTL combinations. Analyses of the marker data of these DH lines clearly demonstrated the positive effect of pyramiding QTLs to broaden resistance spectra as well as epistatic and additive interactions between these QTLs. Phenotyping of the Apache/Balance DH population in the field confirmed the presence of the QTLs that were identified in the seedling stage, but Stb18 was inconsistently expressed and might be particularly effective in young plants. In contrast, an additional QTL for STB resistance was identified on chromosome 2DS that is exclusively and consistently expressed in mature plants over locations and time, but it was also strongly related with earliness, tallness as well as resistance to Fusarium head blight. Although to date no Stb gene has been reported on chromosome 2D, the data provide evidence that this QTL is only indirectly related to STB resistance. This study shows that detailed genetic analysis of contemporary commercial bread wheat cultivars can unveil novel Stb genes that can be readily applied in marker-assisted breeding programs.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-011-1623-7) contains supplementary material, which is available to authorized users.

3FunMap: full-sib family functional mapping of dynamic traits

Functional mapping that embeds the developmental mechanisms of complex traits shows great power to study the dynamic pattern of genetic effects triggered by individual quantitative trait loci (QTLs). A full-sib family, produced by crossing two heterozygous parents, is characteristic of uncertainties about cross-type at a locus and linkage phase between different loci. Integrating functional mapping into a full-sib family requires a model selection procedure capable of addressing these uncertainties. 3FunMap, written in VC++ 6.0, provides a flexible and extensible platform to perform full-sib functional mapping of dynamic traits. Functions in the package encompass linkage phase determination, marker map construction and the pattern identification of QTL segregation, dynamic tests of QTL effects, permutation tests and numerical simulation. We demonstrate the features of 3FunMap through real data analysis and computer simulation. http://statgen.psu.edu/software.

Genome scan detects quantitative trait loci affecting female fertility traits in Danish and Swedish Holstein cattle

Data from the joint Nordic breeding value prediction for Danish and Swedish Holstein grandsire families were used to locate quantitative trait loci (QTL) for female fertility traits in Danish and Swedish Holstein cattle. Up to 36 Holstein grandsires with over 2,000 sons were genotyped for 416 microsatellite markers. Single trait breeding values were used for 12 traits relating to female fertility and female reproductive disorders. Data were analyzed by least squares regression analysis within and across families. Twenty-six QTL were detected on 17 different chromosomes. The best evidence was found for QTL segregating on Bos taurus chromosome (BTA)1, BTA7, BTA10, and BTA26. On each of these chromosomes, several QTL were detected affecting more than one of the fertility traits investigated in this study. Evidence for segregation of additional QTL on BTA2, BTA9, and BTA24 was found.

A comprehensive analysis of QTL for abdominal fat and breast muscle weights on chicken chromosome 5 using a multivariate approach

Quantitative trait loci (QTL) influencing the weight of abdominal fat (AF) and of breast muscle (BM) were detected on chicken chromosome 5 (GGA5) using two successive F(2) crosses between two divergently selected 'Fat' and 'Lean' INRA broiler lines. Based on these results, the aim of the present study was to identify the number, location and effects of these putative QTL by performing multitrait and multi-QTL analyses of the whole available data set. Data concerned 1186 F(2) offspring produced by 10 F(1) sires and 85 F(1) dams. AF and BM traits were measured on F(2) animals at slaughter, at 8 (first cross) or 9 (second cross) weeks of age. The F(0), F(1) and F(2) birds were genotyped for 11 microsatellite markers evenly spaced along GGA5. Before QTL detection, phenotypes were adjusted for the fixed effects of sex, F(2) design, hatching group within the design, and for body weight as a covariable. Univariate analyses confirmed the QTL segregation for AF and BM on GGA5 in male offspring, but not in female offspring. Analyses of male offspring data using multitrait and linked-QTL models led us to conclude the presence of two QTL on the distal part of GGA5, each controlling one trait. Linked QTL models were applied after correction of phenotypic values for the effects of these distal QTL. Several QTL for AF and BM were then discovered in the central region of GGA5, splitting one large QTL region for AF into several distinct QTL. Neither the 'Fat' nor the 'Lean' line appeared to be fixed for any QTL genotype. These results have important implications for prospective fine mapping studies and for the identification of underlying genes and causal mutations.

Utilization of F1 information in estimating QTL effects in F2 crosses between outbred lines

Quantitative trait loci (QTL) analysis in designed experiments is investigated using a mixed model framework through the modification of segment mapping techniques. Allele effects are modelled in the F1 generation allowing the estimation of additive substitution effects while accounting for QTL segregation within lines and differences in mean QTL effects between lines. The resulting approach is called F1 segment mapping. Simulation is used to illustrate the method and its properties. F1 segment mapping has advantages over F2 segment mapping in the derivation of exact additive genetic covariances and in the computation time for variance component estimation.

Detection of Quantitative Trait Loci Influencing Recombination Using Recombinant Inbred Lines

The genetic basis of variation in recombination in higher plants is polygenic and poorly understood, despite its theoretical and practical importance. Here a method of detecting quantitative trait loci (QTL) influencing recombination in recombinant inbred lines (RILs) is proposed that relies upon the fact that genotype data within RILs carry the signature of past recombination. Behavior of the segregational genetic variance in numbers of chromosomal crossovers (recombination) over generations is described for self-, full-sib-, and half-sib-generated RILs with no dominance in true crossovers. This genetic variance, which as a fraction of the total phenotypic variance contributes to the statistical power of the method, was asymptotically greatest with half sibbing, less with sibbing, and least with selfing. The statistical power to detect a recombination QTL declined with diminishing QTL effect, genome target size, and marker density. For reasonably tight marker linkage power was greater with less intense inbreeding for later generations and vice versa for early generations. Generational optima for segregation variance and statistical power were found, whose onset and narrowness varied with marker density and mating design, being more pronounced for looser marker linkage. Application of this method to a maize RIL population derived from inbred lines Mo17 and B73 and developed by selfing suggested two putative QTL (LOD > 2.4) affecting certain chromosomes, and using a canonical transformation another putative QTL was detected. However, permutation tests failed to support their presence (experimentwise alpha = 0.05). Other populations with more statistical power and chosen specifically for recombination QTL segregation would be more effective.

Use of molecular tools for research and improvement of aquaculture stocks

Development of molecular genetic markers provides aquaculture with tools for a number of research and practical applications. Genetic marking of experimental groups allows their evalu- ation in the same rearing units, increasing statistical power within limited research infrastructure. Parentage can be inferred for individuals in mixed-progeny groups, quantifying the contributions of individual parents and supporting the estimation of sire and dam effects. Building upon parent- age assignment, walk-back selection entails retention of the best members of each family as broodstock for the next generation. Molecular markers can be used to detect the segregation of quantitative trait loci (QTL) and knowledge of such linkages can be used for marker-assisted selection. Gene expression profiling can identify genes affecting traits of interest, providing can- didates for QTL or functional analysis. Purposeful genetic marking can be used to identify pro- prietary stocks, marketed products, and fish out-planted or escaping into natural ecosystems. Although each application has been demonstrated, genetic markers are not routinely used in commercial aquaculture. The limited practical application can be explained by the limited devel- opment of broodstocks for most aquaculture species, the small size and limited scope of most aquaculture operations, and the costs of genetic screening.

Mapping of quantitative trait loci affecting organ weights and blood variables in a broiler layer cross

1. A genome scan was performed to locate genomic regions associated with traits that are known to vary in birds (most commonly broilers) suffering from heart, lung or muscular dysfunction and for weight of the dressed carcass and some internal organs. 2. The F2 population studied was derived from a cross between a broiler and a layer line and consisted of over 460 birds that were genotyped for 101 markers. 3. There was strong support for segregation of quantitative trait loci (QTL) for carcass and organ weights and blood variables. We identified 11 genome-wide significant QTL (most of them for dressed carcass weight) and several genome-wide suggestive QTL. 4. The results point to some genome regions that may be associated with health-related traits and merit further study, with the final aim of identifying linked genetic markers that could be used in commercial breeding programmes to decrease the incidence of muscular and metabolic disorders in broiler populations.

QTL Detection in the UK Suffolk and Texel Sheep Sire Referencing Schemes

Genomic research and the detection of quantitative trait loci (QTL) provide tools to enhance genetic progress and improve understanding of the biology of commercially important traits. The large sire reference schemes in UK terminal sire sheep breeds provide a unique opportunity to investigate QTL segregation within commercial populations. This study aims to identify QTL for performance traits in commercial Suffolk and Texel sheep.

Genetic Mapping of a Macromutation and Quantitative Trait Loci underlying Fatty Acid Composition Differences in Meadowfoam Oil

The seed oil of meadowfoam (Limnanthes alba Hartw. ex Benth.) is a rich source of very long‐chain fatty acids (VLCs), primarily 20:1Δ5, 22:1Δ5, 22:1Δ13 (erucic acid), and 22:2Δ5Δ13 (dienoic acid). Wild‐type L alba ssp. versicolor populations produce more erucic and less dienoic acid than wild‐type L. alba ssp. alba populations, phenotypic differences that are caused by the macromutation E and possibly by quantitative trait loci (QTL). The aim of this study was to map the E locus and QTL affecting fatty acid concentrations among intersubspecific backcross progeny. The segregation ratio for the E locus (94 Ee to 86 ee progeny) was not significantly different from one to one (P = 0.84). The E locus was associated with 94 and 77% of the phenotypic variance for erucic and dienoic acid concentration, respectively. Erucic acid varied from 42 to 151 g kg−1 among Ee and 185 to 269 g kg−1 among ee progeny, while dienoic acid varied from 151 to 318 g kg−1 among Ee and 66 to 209 g kg−1 among ee progeny. The E locus mapped to Linkage Group 4 and pleiotropically affected every VLC. Composite interval mapping, performed with the E locus and 18 background markers as cofactors, was used to search the genome for QTL. Two significant QTL peaks were found for erucic and dienoic acid on Linkage Group 4. One QTL was centered on the E locus and produced a massive peak. The other QTL produced a marginally significant peak 30.4 cM downstream of the E locus and was associated with less than 1% of the phenotypic variance. The segregation of additional QTL in this population affecting dienoic acid cannot be ruled out.