Quantitative Trait Loci Alleles Research Articles

Detection of QTLs for Stagonospora glume blotch resistance in Swiss winter wheat.

Stagonospora nodorum is the causal agent of the Stagonospora glume blotch disease in hexaploid wheat. The Swiss winter bread wheat cv. 'Arina' has a highly effective, durable and quantitative glume blotch resistance. We studied 240 single seed descent (SSD)-derived lines of an 'Arina x Forno' F(5:7) population to identify and map quantitative trait loci (QTLs) for glume blotch resistance under natural infestation. Using composite interval mapping (CIM) and LOD>4.5, we detected two chromosomal regions on chromosome arms 3BS and 4BL which were specifically associated with glume blotch resistance. These identified QTLs were designated QSng.sfr-3BS and QSng.sfr-4BL, respectively. QSng.sfr-3BS peaked at the locus Xgwm389 in the telomeric region of the short arm of chromosome 3B and explained 31.2% of the observed phenotypic variance for the resistance within the population. The responsible QSng.sfr-3BS allele originated from the resistant parent 'Arina'. The QTL QSng.sfr-4BL (19.1%) mapped to chromosome arm 4BL ('Forno' allele) very close to two known genes, TaMlo and a catalase ( Cat). Both QTL alleles combined could enhance the resistance level by about 50%. Additionally, they showed significant epistatic effects (4.4%). We found PCR-based microsatellite markers closely linked to QSng.sfr-3BS (gwm389) and QSng.sfr-4BL (gwm251) which make marker-assisted selection (MAS) for Stagonospora glume blotch resistance feasible. We also found one resistance QTL, QSng.sfr-5BL, on the long arm of chromosome 5B which overlapped with QTLs for plant height as well as heading time.

Quantitative trait locus mapping of pyrethroid resistance in Colorado potato beetle, Leptinotarsa decemlineata (Say) (Coleoptera: Chrysomelidae).

Quantitative trait locus (QTL) mapping is a valuable new tool for locating genomic regions that underlie variation in important traits such as insecticide resistance. Because QTL mapping complements a candidate gene strategy for understanding the genetic architecture of important traits, it may also facilitate the identification of genes causing important variation. After mapping the QTL locations, markers closely linked to QTL can be used for genetic analysis of population structure and to measure the spread and increase of resistance-causing QTL alleles. In this study, QTL influencing resistance to the pyrethroid insecticide esfenvalerate were mapped in the Colorado potato beetle Leptinotarsa decemlineata (Say) (CPB). Three QTL contributing to esfenvalerate resistance were identified from a mapping population of 79 individuals analyzed at 90 marker loci. One QTL had a large effect and two QTL had smaller effects. The major QTL occurs on the X chromosome, overlapping the position of a candidate gene (Leptinotarsa decemlineata Voltage sensitive sodium channel [LdVssc1]) previously implicated in pyrethroid resistance. Resistance-increasing alleles at the two minor-effect QTL originated with the susceptible parent, suggesting that alleles of small effect may be segregating in susceptible populations. Comparison of the New York population from which the susceptible parent originated with a more-susceptible population from North Carolina suggests that the minor-effect loci identified here may explain some of the variation in tolerance observed among susceptible populations. DNA sequencing of a portion of LdVssc1 shows that the resistance-conferring allele from the resistant parent does not contain the kdr mutation previously found in CPB and typically observed in other insects that are resistant to pyrethroid insecticides because of changes in this gene.

Identification of QTLs and Environmental Interactions Associated with Agronomic Traits on Chromosome 3A of Wheat

Genetic analyses of complex traits in wheat (Triticum aestivum L.) are facilitated by the availability of unique genetic tools such as chromosome substitution lines and recombinant inbred chromosome lines (RICLs) which allow the effects of genes on single chromosomes to be studied individually. Chromosome 3A of ‘Wichita’ is known to contain alleles at quantitative trait loci (QTLs) that influence variation in grain yield and agronomic performance traits relative to alleles of ‘Cheyenne’. To determine the number, location, and environmental interactions of genes related to agronomic performance on chromosome 3A, QTL and QTL × environment analyses of 98 RICLs‐3A were conducted in seven locations across Nebraska from 1999 through 2001. QTLs were detected for seven of eight agronomic traits measured and generally localized to three regions of chromosome 3A. QTL × environment interactions were detected for some QTLs and these interactions were caused by changes in magnitude and crossover interactions. Major QTLs for kernels per square meter and grain yield were associated within a 5‐centimorgan (cM) interval and appeared to represent a single QTL with pleiotropic effects. This particular QTL displayed environmental interactions caused by changes in magnitude, wherein the positive effect of the Wichita QTL allele was larger in higher yielding environments.

The genetic basis of C-glycosyl flavone B-ring modification in maize (Zea mays L.) silks.

Resistance to corn earworm (CEW) (Helicoverpa zea Boddie) has been attributed to high concentrations of C-glycosyl flavones and chlorogenic acid in maize (Zea mays L.) silks. The most common C-glycosyl flavones isolated from maize silks are maysin, apimaysin, and methoxymaysin, which are distinguished by their B-ring substitutions. For a better understanding of the genetic mechanisms underlying the synthesis of these compounds, we conducted a quantitative trait locus (QTL) study with two populations: (Tx501 x NC7A)F2 and (Tx501 x Mp708)F2. For chlorogenic acid, maysin, and methoxymaysin concentration, the major QTL for both populations was located on chromosome 4 near umc1963. For apimaysin, the major QTL in both populations was located at the position of the pr1 locus on chromosome 5. The QTL alleles on chromosome 4 that increased the synthesis of methoxymaysin significantly decreased the synthesis of maysin and chlorogenic acid. This decrease in maysin concentration was four-fold greater than the increase in methoxymaysin. Our results indicate that the QTL on chromosome 4, responsible for the increase in methoxymaysin synthesis, alters the dynamics of both the phenylpropanoid and flavonoid pathways.

Estimating allelic number and identity in state of QTLs in interconnected families

When multiple related families derived from inbred lines are jointly analysed to detect quantitative trait loci (QTLs), the analysis should estimate allelic effects as accurately as possible and estimate the probability that different parents carry alleles that are identical in state. Analyses exist that assume that all parents carry unique alleles or that all parents but one carry the same allele. In practice, many configurations are possible that group different parents according to their identity-in-state condition at a putative QTL allele. Here, we propose a variable model Bayesian analysis that selects among possible identity-in-state configurations and jointly estimates the allelic effects of identical-in-state parents. We contrast this analysis with a fixed model analysis that estimates unique allelic effects for all parents. We analyse two simulated mating designs: an experimental design in which three inbred parents were crossed to generate two families of 150 doubled haploid lines; and a breeding design in which 20 inbred parents were crossed to generate 60 families of 20 doubled haploid lines, with each parent contributing to six families. In all cases where some parents were simulated to carry alleles of identical effect (that is, they were identical in state), the variable analysis estimated allelic effects with lower mean-squared error than the fixed analysis. The variable analysis showed that, unless each family contains many individuals (more than 100), there is insufficient information in DNA-marker and phenotypic data to determine with high probability the QTL allelic number.

Fine mapping of complex trait genes combining pedigree and linkage disequilibrium information: a Bayesian unified framework.

We present a Bayesian method that combines linkage and linkage disequilibrium (LDL) information for quantitative trait locus (QTL) mapping. This method uses jointly all marker information (haplotypes) and all available pedigree information; i.e., it is not restricted to any specific experimental design and it is not required that phases are known. Infinitesimal genetic effects or environmental noise ("fixed") effects can equally be fitted. A diallelic QTL is assumed and both additive and dominant effects can be estimated. We have implemented a combined Gibbs/Metropolis-Hastings sampling to obtain the marginal posterior distributions of the parameters of interest. We have also implemented a Bayesian variant of usual disequilibrium measures like D' and r(2) between QTL and markers. We illustrate the method with simulated data in "simple" (two-generation full-sib families) and "complex" (four-generation) pedigrees. We compared the estimates with and without using linkage disequilibrium information. In general, using LDL resulted in estimates of QTL position that were much better than linkage-only estimates when there was complete disequilibrium between the mutant QTL allele and the marker. This advantage, however, decreased when the association was only partial. In all cases, additive and dominant effects were estimated accurately either with or without disequilibrium information.

Pyramiding Quantitative Trait Locus (QTL) Alleles Determining Resistance to Barley Stripe Rust

Durable disease resistance may be achieved by pyramiding multiple qualitative resistance genes in single genotypes and by using quantitative resistance (QR) genes. Quantitative trait locus (QTL) analysis tools can be used to find determinants of QR. Resistance QTL pyramids may also lead to durable resistance, and they provide independent validation of QTL effects and QTL interactions. We used molecular markers to identify allelic architectures at three previously mapped QTL conferring resistance to barley stripe rust (caused by Puccinia striiformis Westend. f. sp. hordei) in a set of barley (Hordeum vulgare L. subsp. vulgare) doubled haploid (DH) lines. The three QTL are located on three different chromosomes. One parent contributed the resistance alleles at two QTL and another parent contributed the resistance allele at the third QTL. In this report, we focus on resistance at the seedling stage; resistance at the adult plant stage will be addressed in a future report. The DH population was phenotyped for resistance by means of four pathogen isolates that show different patterns of virulence on a set of differentials. We used molecular markers to infer the resistance QTL allele architecture of each DH line. There was no significant QTL × race interaction, although some DH lines showed differential responses to isolates. The effects and locations of two QTL, each tracing to a different parent, were validated. The third QTL did not have a significant effect on disease symptom expression. To maximize the probability of recovering the resistant phenotype, resistance alleles are necessary at both QTL.

Interaction between blood pressure quantitative trait loci in rats in which trait variation at chromosome 1 is conditional upon a specific allele at chromosome 10

We have used inbred and congenic rat strains in F2 segregation studies to discover epistasis in a polygenic model of hypertension. Previously, we have found evidence that the presence of a blood pressure quantitative trait locus (QTL) on chromosome 1 is conditional upon the allele status of chromosome 10. To prove the existence of an epistatic interaction we have analyzed congenic strains for chromosome 1 and 10 carrying high blood pressure QTL alleles from the spontaneously hypertensive rat on a normotensive background of the Wistar–Kyoto (WKY) rat. Additionally, a double congenic strain was developed with both chromosome 1 and 10 high blood pressure QTL alleles on the WKY background. Analysis of variance for blood pressure phenotypes as determined by radiotelemetry showed a significant effect for chromosome 10 but not chromosome 1 QTL alleles and demonstrated a significant interaction between the two loci (P<0.05). The interaction accounted for 5 mmHg of blood pressure. Thus, the identification of epistasis is critical to the understanding of the quantitative nature of blood pressure genetics.

Interaction between blood pressure quantitative trait loci in rats in which trait variation at chromosome 1 is conditional upon a specific allele at chromosome 10.

We have used inbred and congenic rat strains in F(2) segregation studies to discover epistasis in a polygenic model of hypertension. Previously, we have found evidence that the presence of a blood pressure quantitative trait locus (QTL) on chromosome 1 is conditional upon the allele status of chromosome 10. To prove the existence of an epistatic interaction we have analyzed congenic strains for chromosome 1 and 10 carrying high blood pressure QTL alleles from the spontaneously hypertensive rat on a normotensive background of the Wistar-Kyoto (WKY) rat. Additionally, a double congenic strain was developed with both chromosome 1 and 10 high blood pressure QTL alleles on the WKY background. Analysis of variance for blood pressure phenotypes as determined by radiotelemetry showed a significant effect for chromosome 10 but not chromosome 1 QTL alleles and demonstrated a significant interaction between the two loci (P<0.05). The interaction accounted for 5 mmHg of blood pressure. Thus, the identification of epistasis is critical to the understanding of the quantitative nature of blood pressure genetics.

Mapping of yield-related QTLs in pepper in an interspecific cross of Capsicum annuum and C. frutescens.

An advanced backcross QTL study was performed in pepper using a cross between the cultivated species Capsicum annuum cv. Maor and the wild C. frutescens BG 2816 accession. A genetic map from this cross was constructed, based on 248 BC(2) plants and 92 restriction fragment length polymorphism (RFLP) markers distributed throughout the genome. Ten yield-related traits were analyzed in the BC(2) and BC(2)S(1) generations, and a total of 58 quantitative trait loci (QTLs) were detected; the number of QTLs per trait ranged from two to ten. Most of the QTLs were found in 11 clusters, in which similar QTL positions were identified for multiple traits. Unlike the high percentage of favorable QTL alleles discovered in wild species of tomato and rice, only a few such QTL alleles were detected in BG 2816. For six QTLs (10%), alleles with effects opposite to those expected from the phenotype were detected in the wild species. The use of common RFLP markers in the pepper and tomato maps enabled possible orthologous QTLs in the two species to be determined. The degree of putative QTL orthology for the two main fruit morphology traits-weight and shape-varied considerably. While all eight QTLs identified for fruit weight in this study could be orthologous to tomato fruit weight QTLs, only one out of six fruit shape QTLs found in this study could be orthologous to tomato fruit shape QTLs.

Advanced backcross QTL analysis for the identification of quantitative trait loci alleles from wild relatives of wheat ( Triticum aestivum L.).

Advanced backcross QTL (AB-QTL) analysis was used to identify quantitative trait loci (QTLs) for yield and yield components in a BC(2)F(2) population derived from a cross between the German winter wheat variety 'Prinz' and the synthetic wheat line W-7984 developed by CIMMYT. Two hundred and ten microsatellite markers were employed to genotype 72 pre-selected BC(2)F(2) plants and phenotypic data were collected for five agronomic traits from corresponding BC(2)F(3) families that were grown at four locations in Germany. Using single-marker regression and interval mapping, a total of 40 putative QTLs derived from W-7984 were detected, of which 11 were for yield, 16 for yield components, eight for ear emergence time and five for plant height. For 24 (60.0%) of them, alleles from the synthetic wheat W-7984 were associated with a positive effect on agronomic traits, despite the fact that synthetic wheat was overall inferior with respect to agronomic appearance and performance. The present study indicated that favorable QTL alleles could be transferred from wild relatives of wheat into an elite wheat variety for improvement of quantitative trait loci like yield by the advanced backcross QTL strategy and molecular breeding. To our knowledge, the results presented here were the first report on AB-QTL analysis in wheat.

Mapping quantitative trait loci for bean traits and ovule number in Theobroma cacao L.

Quantitative trait loci (QTL) mapping for bean traits and the number of ovules per ovary was carried out in cocoa (Theobroma cacao L.) using three test-cross progenies derived from crosses between a lower Amazon Forastero male parent (Catongo) and three female parents: one upper Amazon Forastero (IMC78) and two Trinitario (DR1 and S52). RFLP (restriction fragment length polymorphism), microsatellite, and AFLP (amplified fragment lengthpolymorphism) markers were used for mapping. Between one and six QTL for bean traits (length, weight, and shape index) and one and four QTL for the number of ovules per ovary were detected using composite interval mapping (CIM). Individual QTL explained between 5 and 24% of the phenotypic variation. QTL clusters were identified on several chromosomes, but particularly on chromosome 4. QTL related to bean traits were detected in the same region in both Trinitario parents and in a close region in the upper Amazon Forastero parent. In reference to a previous diversity study where alleles specific to Criollo and Forastero genotypes were identified, it was possible to speculate on the putative origin (Criollo or Forastero) of favorable QTL alleles segregating in both Trinitario studied.

Candidate defense genes from rice, barley, and maize and their association with qualitative and quantitative resistance in rice.

Candidate genes involved in both recognition (resistance gene analogs [RGAs]) and general plant defense (putative defense response [DR]) were used as molecular markers to test for association with resistance in rice to blast, bacterial blight (BB), sheath blight, and brown plant-hopper (BPH). The 118 marker loci were either polymerase chain reaction-based RGA markers or restriction fragment length polymorphism (RFLP) markers that included RGAs or putative DR genes from rice, barley, and maize. The markers were placed on an existing RFLP map generated from a mapping population of 116 doubled haploid (DH) lines derived from a cross between an improved indica rice cultivar, IR64, and a traditional japonica cultivar, Azucena. Most of the RGAs and DR genes detected a single locus with variable copy number and mapped on different chromosomes. Clusters of RGAs were observed, most notably on chromosome 11 where many known blast and BB resistance genes and quantitative trait loci (QTL) for blast, BB, sheath blight, and BPH were located. Major resistance genes and QTL for blast and BB resistance located on different chromosomes were associated with several candidate genes. Six putative QTL for BB were located on chromosomes 2, 3, 5, 7, and 8 and nine QTL for BPH resistance were located to chromosomes 3, 4, 6, 11, and 12. The alleles of QTL for BPH resistance were mostly from IR64 and each explained between 11.3 and 20.6% of the phenotypic variance. The alleles for BB resistance were only from the Azucena parent and each explained at least 8.4% of the variation. Several candidate RGA and DR gene markers were associated with QTL from the pathogens and pest. Several RGAs were mapped to BB QTL. Dihydrofolate reductase thymidylate synthase co-localized with two BPH QTL associated with plant response to feeding and also to blast QTL. Blast QTL also were associated with aldose reductase, oxalate oxidase, JAMyb (a jasmonic acid-induced Myb transcription factor), and peroxidase markers. The frame map provides reference points to select candidate genes for cosegregation analysis using other mapping populations, isogenic lines, and mutants.

Pyramiding Quantitative Trait Locus (QTL) Alleles Determining Resistance to Barley Stripe Rust

Durable disease resistance may be achieved by pyramiding multiple qualitative resistance genes in single genotypes and by using quantitative resistance (QR) genes. Quantitative trait locus (QTL) analysis tools can be used to find determinants of QR. Resistance QTL pyramids may also lead to durable resistance, and they provide independent validation of QTL effects and QTL interactions. We used molecular markers to identify allelic architectures at three previously mapped QTL conferring resistance to barley stripe rust (caused by Puccinia striiformis Westend. f. sp. hordei) in a set of barley (Hordeum vulgare L. subsp. vulgare) doubled haploid (DH) lines. The three QTL are located on three different chromosomes. One parent contributed the resistance alleles at two QTL and another parent contributed the resistance allele at the third QTL. In this report, we focus on resistance at the seedling stage; resistance at the adult plant stage will be addressed in a future report. The DH population was phenotyped for resistance by means of four pathogen isolates that show different patterns of virulence on a set of differentials. We used molecular markers to infer the resistance QTL allele architecture of each DH line. There was no significant QTL × race interaction, although some DH lines showed differential responses to isolates. The effects and locations of two QTL, each tracing to a different parent, were validated. The third QTL did not have a significant effect on disease symptom expression. To maximize the probability of recovering the resistant phenotype, resistance alleles are necessary at both QTL.

Use of a panel of congenic strains to evaluate differentially expressed genes as candidate genes for blood pressure quantitative trait loci.

Candidate gene(s) for multiple blood pressure (BP) quantitative trait loci (QTL) were sought by analysis of differential gene expression patterns in the kidneys of a panel of eight congenic strains, each of which carries a different low-BP QTL allele with a genetic composition that is otherwise similar to that of the hypertensive Dahl salt-sensitive (S) rat strain. First, genes differentially expressed in the kidneys of one-month-old Dahl S and salt-resistant (R) rats were identified. Then, Northern filter hybridization was used to examine the expression patterns of these genes in a panel of congenic strains. Finally, their chromosomal location was determined by radiation hybrid (RH) mapping. Seven out of 37 differentially expressed genes were mapped to congenic regions carrying BP QTLs, but only one of these genes, L-2 hydroxy acid oxidase (Hao2), showed the congenic strain-specific pattern of differential kidney gene expression predicted by its chromosomal location. This data suggests that Hao2 should be examined as a candidate gene for the rat chromosome 2 (RNO2) BP QTL.

Evaluation of marker assisted selection in pig enterprises

The profitability of using DNA markers linked to quantitative trait loci (QTL) in a pig enterprise in marker assisted selection (MAS) was evaluated, using a computer simulation of a pig population with segregating QTL and markers. The starting point for MAS was a population of pigs evolved for a large number of generations. Mutation, drift and natural selection affected both the size and frequency of segregating QTL. The QTL affected four independent traits, growth index (GI), net food intake (NFI), pigs born alive (PBA) and a meat quality index (MQI). A genome scan was conducted in the population, using a genome-wide (GW), chromosome-wide (CW) or point-wise (PW) threshold as criteria for taking QTL from the genome scan to MAS. MAS with the significant markers was conducted in a small nucleus population of 20 sows, and selection was on an index of the four quantitative traits. The extra dollar returns from the additional genetic gain from MAS schemes were calculated using an economic model of a pig enterprise (with a 100 sow nucleus, 1000 sow multiplier tier and 10 000 sow commercial tier). Returns were largest with MAS schemes using QTL detected with CW and PW thresholds. However, when the cost of genotyping per animal per marker was $4, profit (extra returns from MAS−cost of genotyping) were greatest with the GW criteria, as for this criteria the fewest markers needed to be genotyped. MAS as described in this study may be difficult to implement in commercial herds, as markers and QTL were not closely linked, and linkage phase between QTL and markers had to be established within every family. If markers could be found in linkage disequilibrium with QTL, such that marker–QTL allele associations persist across the whole population, the profitability of MAS could be increased.

Detection of�quantitative trait loci for�carcass composition traits in pigs

A quantitative trait locus (QTL) analysis of carcass composition data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. A total of 488 F2 males issued from six F1 boars and 23 F1 sows, the progeny of six LW boars and six MS sows, were slaughtered at approximately 80 kg live weight and were submitted to a standardised cutting of the carcass. Fifteen traits, i.e. dressing percentage, loin, ham, shoulder, belly, backfat, leaf fat, feet and head weights, two backfat thickness and one muscle depth measurements, ham + loin and back + leaf fat percentages and estimated carcass lean content were analysed. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using a line-cross (LC) regression method where founder lines were assumed to be fixed for different QTL alleles and a half/full sib (HFS) maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Additional analyses were performed to search for multiple linked QTL and imprinting effects. Significant gene effects were evidenced for both leanness and fatness traits in the telomeric regions of SSC 1q and SSC 2p, on SSC 4, SSC 7 and SSC X. Additional significant QTL were identified for ham weight on SSC 5, for head weight on SSC 1 and SSC 7, for feet weight on SSC 7 and for dressing percentage on SSC X. LW alleles were associated with a higher lean content and a lower fat content of the carcass, except for the fatness trait on SSC 7. Suggestive evidence of linked QTL on SSC 7 and of imprinting effects on SSC 6, SSC 7, SSC 9 and SSC 17 were also obtained.

A congenic strain of rat for investigation of control of estrogen-induced growth.

A congenic strain of rat for investigation of control of estrogen-induced growth.

QTL analysis in arbitrary pedigrees with incomplete marker information.

Mapping quantitative trait loci (QTL) in arbitrary outbred pedigrees is complicated by the combinatorial possibilities of allele flow relationships and of the founder allelic configurations. Exact methods are only available for rather short and simple pedigrees. Stochastic simulation using Markov chain Monte Carlo (MCMC) integration offers more flexibility. MCMC methods are less natural in a frequentist than in a Bayesian context, which we therefore adopt. Among the MCMC algorithms for updating marker locus genotypes, we implement the descent-graph algorithm. It can be used to update marker locus allele flow relationships and can handle arbitrarily complex pedigrees and missing marker information. Compared with updating marker genotypic information, updating QTL parameters, such as position, effects, and the allele flow relationships is relatively easy with MCMC. We treat the effect of each diploid combination of founder alleles as a random variable and only estimate the variance of these effects, ie, we model diploid genotypic effects instead of the usual partition in additive and dominance effects. This is a variant of the random model approach. The number of QTL alleles is generally unknown. In the Bayesian context, the number of QTL present on a linkage group can be treated as variable. Computer simulations suggest that the algorithm can indeed handle complex pedigrees and detect two QTL on a linkage group, but that the number of individuals in a single extended family is limited to about 50 to 100 individuals.

Estimation of quantitative trait locus allele frequency via a modified granddaughter design.

A method is described on the basis of a modification of the granddaughter design to obtain estimates of quantitative trait loci (QTL) allele frequencies in dairy cattle populations and to determine QTL genotypes for both homozygous and heterozygous grandsires. The method is based on determining the QTL allele passed from grandsires to their maternal granddaughters using haplotypes consisting of several closely linked genetic markers. This method was applied to simulated data of 10 grandsire families, each with 500 granddaughters, and a QTL with a substitution effect of 0.4 phenotypic standard deviations and to actual data for a previously analyzed QTL in the center of chromosome 6, with substitution effect of 1 phenotypic standard deviation on protein percentage. In the simulated data the standard error for the estimated QTL substitution effect with four closely linked multiallelic markers was only 7% greater than the expected standard error with completely correct identification of QTL allele origin. The method estimated the population QTL allelic frequency as 0.64 +/- 0.07, compared to the simulated value of 0.7. In the actual data, the frequency of the allele that increases protein percentage was estimated as 0.63 +/- 0.06. In both data sets the hypothesis of equal allelic frequencies was rejected at P < 0.05.