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PubMed2002

Contribution of maternal effect QTL to genetic architecture of early growth in mice.

Existing approaches to characterizing quantitative trait loci (QTL) utilize a paradigm explicitly focused on the direct effects of genes, where phenotypic variation among individuals is mapped onto genetic variation of those individuals. For many characters, however, the genotype of the mother via its maternal effect accounts for a considerable portion of the genetically based variation in progeny phenotypes. Thus the focus on direct effect QTL may result in an insufficient or misleading characterization of genetic architecture due to the omission of the potentially important source of genetic variance contributed by maternal effects. We analyze the relative contribution of direct and maternal effect (ME) QTL to early growth in mice using a three-generation intercross of the Small (SM/J) and Large (LG/J) inbred mouse lineages. Using interval mapping and composite interval mapping, direct effect (DE) QTL for early growth (change in body mass during the interval from week 1 to 2) were detected in the F(2) generation of the intercross (n = 510), where no maternal genetic effect variance is present (all individuals are progeny of genetically identical F(1) mothers). ME QTL were detected by treating the phenotypes of cross-fostered F(3) pups as a characteristic of their nurse-dam (n = 168 dams with cross-fostered progeny). Five DE QTL, significant at a chromosome wide level (alpha = 0.05), were detected, with two significant at a genome wide level. FourME QTL significant at the chromosome wide level were detected, with three significant at the genome wide level. A model containing only DE QTL accounted for 11.8% of phenotypic variance, while a model containing only ME QTL accounted for 31.5% of the among litter variance in growth. There was no evidence for pleiotropy of DE and ME loci since there was no overlap between loci detected in these two analyses. Epistasis between all pairs of loci was analyzed for both DEs and MEs. Ten pairs of loci showed significant epistasis for MEs (alpha = 0.05 corrected for multiple comparisons) while four pairs showed significant epistasis for DEs on early growth.

Animals↗

PubMed2003

Detection of QTL for immune response to sheep red blood cells in laying hens.

The aim of this study is to detect quantitative trait loci (QTL) involved in the regulation of the primary and the secondary immune response to sheep red blood cells (SRBC) in a resource population using microsatellite DNA markers. The F2 resource population originates from a cross of two divergently selected lines for either high (H line) or low (L line) primary antibody response to SRBC. The F2 population consisted of six half-sib families, three families per each of reciprocal crosses. Total antibody titres to SRBC were determined by agglutination in serum from all birds. F2, F1 and F0 generations were genotyped for 170 microsatellite markers, using a whole-genome scan approach. The half-sib and the line-cross analyses were performed to determine QTL regions associated with regulation of the immune response. In the half-sib analysis, four QTL for SRBC primary response have been identified: on GGA3, GGA5, GGA16 and GGA23. No QTL was identified for SRBC secondary response under the half-sib model. In the line-cross analysis, three QTL were identified on GGA10, GGA16 and GGA27 for SRBC primary response and five QTL were identified on GGA6, GGA9, GGA15, GGA16 and GGA27 for SRBC secondary response. Subsequently, the family contribution of individual families to the QTL was analysed. The family with the largest contribution was genotyped with additional microsatellite markers in the QTL region on GGA5. The extended half-sib analysis with additional genotype information results in narrowing down the QTL region on GGA5.

Animals↗

PubMed2000

QTL fine mapping by measuring and testing for Hardy-Weinberg and linkage disequilibrium at a series of linked marker loci in extreme samples of populations.

It has recently been demonstrated that fine-scale mapping of a susceptibility locus for a complex disease can be accomplished on the basis of deviations from Hardy-Weinberg (HW) equilibrium at closely linked marker loci among affected individuals. We extend this theory to fine-scale localization of a quantitative-trait locus (QTL) from extreme individuals in populations, by means of HW and linkage-disequilibrium (LD) analyses. QTL mapping and/or linkage analyses can establish a large genomic region ( approximately 30 cM) that contains a QTL. The QTL can be fine mapped by examination of the degree of deviation from HW and LD at a series of closely linked marker loci. The tests can be performed for samples of individuals belonging to either high or low percentiles of the phenotype distribution or for combined samples of these extreme individuals. The statistical properties (the power and the size) of the tests of this fine-mapping approach are investigated and are compared extensively, under various genetic models and parameters for the QTL and marker loci. On the basis of the results, a two-stage procedure that uses extreme samples and different tests (for HW and LD) is suggested for QTL fine mapping. This two-step procedure is economic and powerful and can accurately narrow a genomic region containing a QTL from approximately 30-1 cM, a range that renders physical mapping feasible for identification of the QTL. In addition, the relationship between parameterizations of complex diseases, by means of penetrance, and those of complex quantitative traits, by means of genotypic values, is outlined. This means that many statistical genetic methods developed for searching for susceptibility loci of complex diseases can be directly adopted and/or extended to QTL mapping for quantitative traits.

Alleles↗

PubMedDate not supplied

Mapping of QTL for Body Conformation and Behavior in Cattle.

Genome scans for quantitative trait loci (QTL) in farm animals have concentrated on primary production and health traits, and information on QTL for other important traits is rare. We performed a whole genome scan in a granddaughter design to detect QTL affecting body conformation and behavior in dairy cattle. The analysis included 16 paternal half-sib families of the Holstein breed with 872 sons and 264 genetic markers. The markers were distributed across all 29 autosomes and the pseudoautosomal region of the sex chromosomes with average intervals of 13.9 cM and covering an estimated 3155.5 cM. All families were analyzed jointly for 22 traits using multimarker regression and significance thresholds determined empirically by permutation. QTL that exceeded the experiment-wise significance threshold (5% level) were detected on chromosome 6 for foot angle, teat placement, and udder depth, and on chromosome 29 for temperament. QTL approaching experiment-wise significance (10% level) were located on chromosome 6 for general quality of feet and legs and general quality of udder, on chromosome 13 for teat length, on chromosome 23 for general quality of feet and legs, and on chromosome 29 for milking speed. An additional 51 QTL significant at the 5% chromosome-wise level were distributed over 21 chromosomes. This study provides the first evidence for QTL involved in behavior of dairy cattle and identifies QTL for udder conformation on chromosome 6 that could form the basis of recently reported QTL for clinical mastitis.

Animals↗

PubMedDate not supplied

A comparison of bivariate and univariate QTL mapping in livestock populations.

This study presents a multivariate, variance component-based QTL mapping model implemented via restricted maximum likelihood (REML). The method was applied to investigate bivariate and univariate QTL mapping analyses, using simulated data. Specifically, we report results on the statistical power to detect a QTL and on the precision of parameter estimates using univariate and bivariate approaches. The model and methodology were also applied to study the effectiveness of partitioning the overall genetic correlation between two traits into a component due to many genes of small effect, and one due to the QTL. It is shown that when the QTL has a pleiotropic effect on two traits, a bivariate analysis leads to a higher statistical power of detecting the QTL and to a more precise estimate of the QTL's map position, in particular in the case when the QTL has a small effect on the trait. The increase in power is most marked in cases where the contributions of the QTL and of the polygenic components to the genetic correlation have opposite signs. The bivariate REML analysis can successfully partition the two components contributing to the genetic correlation between traits.

Animals↗

PubMed2006

Fatness QTL on chicken chromosome 5 and interaction with sex.

Quantitative trait loci (QTL) affecting fatness in male chickens were previously identified on chromosome 5 (GGA5) in a three-generation design derived from two experimental chicken lines divergently selected for abdominal fat weight. A new design, established from the same pure lines, produced 407 F2 progenies (males and females) from 4 F1-sire families. Body weight and abdominal fat were measured on the F2 at 9 wk of age. In each sire family, selective genotyping was carried out for 48 extreme individuals for abdominal fat using seven microsatellite markers from GGA5. QTL analyses confirmed the presence of QTL for fatness on GGA5 and identified a QTL by sex interaction. By crossing one F1 sire heterozygous at the QTL with lean line dams, three recombinant backcross 1 (BC1) males were produced and their QTL genotypes were assessed in backcross 2 (BC2) progenies. These results confirmed the QTL by sex interaction identified in the F2 generation and they allow mapping of the female QTL to less than 8 Mb at the distal part of the GGA5. They also indicate that fat QTL alleles were segregating in both fat and lean lines.

Abdominal Fat↗

PubMed2006

The bovine QTL viewer: a web accessible database of bovine Quantitative Trait Loci.

BACKGROUND: Many important agricultural traits such as weight gain, milk fat content and intramuscular fat (marbling) in cattle are quantitative traits. Most of the information on these traits has not previously been integrated into a genomic context. Without such integration application of these data to agricultural enterprises will remain slow and inefficient. Our goal was to populate a genomic database with data mined from the bovine quantitative trait literature and to make these data available in a genomic context to researchers via a user friendly query interface. DESCRIPTION: The QTL (Quantitative Trait Locus) data and related information for bovine QTL are gathered from published work and from existing databases. An integrated database schema was designed and the database (MySQL) populated with the gathered data. The bovine QTL Viewer was developed for the integration of QTL data available for cattle. The tool consists of an integrated database of bovine QTL and the QTL viewer to display QTL and their chromosomal position. CONCLUSION: We present a web accessible, integrated database of bovine (dairy and beef cattle) QTL for use by animal geneticists. The viewer and database are of general applicability to any livestock species for which there are public QTL data. The viewer can be accessed at http://bovineqtl.tamu.edu.

Animals↗

PubMed2007

Separation of base allele and sampling term effects gives new insights in variance component QTL analysis.

BACKGROUND: Variance component (VC) models are commonly used for Quantitative Trait Loci (QTL) mapping in outbred populations. Here, the QTL effect is given as a random effect and a critical part of the model is the relationship between the phenotypic values and the random effect. In the traditional VC model, each individual has a unique QTL effect and the relationship between these random effects is given as a covariance structure (known as the identity-by-descent (IBD) matrix). RESULTS: We present an alternative notation of the variance component model, where the elements of the random effect are independent base generation allele effects and sampling term effects. The relationship between the phenotypic vales and the random effect is given by an incidence matrix, which results in a novel, but statistically equivalent, version of the traditional VC model. A general algorithm to estimate this incidence matrix is presented. Since the model is given in terms of base generation allele effects and sampling term effects, these effects can be estimated separately using best linear unbiased prediction (BLUP). From simulated data, we showed that biallelic QTL effects could be accurately clustered using the BLUP obtained from our model notation when markers are fully informative, and that the accuracy increased with the size of the QTL effect. We also developed a measure indicating whether a base generation marker homozygote is a QTL heterozygote or not, by comparing the variances of the sampling term BLUP and the base generation allele BLUP. A ratio greater than one gives strong support for a QTL heterozygote. CONCLUSION: We developed a simple presentation of the VC QTL model for identification of base generation allele effects in QTL linkage analysis. The base generation allele effects and sampling term effects were separated in our model notation. This clarifies the assumptions of the model and should also enhance the development of genome scan methods.

Alleles↗

PubMed2006

[QTL analysis of starch content in maize kernels using the trisomic inheritance of the endosperm model].

Two hundred and fifty-nine F2:3 families, developed from the cross between a dent corn inbred line Dan232 and a popcorn inbred line N04, were evaluated for its starch content in the replicated experiments under two environments. One hundred and eighty three pairs of SSR markers were selected to construct a genetic linkage map, covering 1,762.2 cM (centiMorgan) and on the average distance of 9.63 cM between the markers. Quantative trait loci (QTL) were identified and its effects were analyzed, using the triploid endosperm genetic model and the interval mapping method. Ten QTL, detected on chromosome 1, 3, 4, 5 and 7 respectively, were mapped in spring and in summer. All detected QTL in spring were also identified in summer. The phenotypic variation of a single QTL varied from 4.74% to 11.26%, and the total contributions of all QTL under two environments were 36.84% and 72.65%, respectively. Two QTL of all identified QTL in spring showed over-dominant effects, but additive and partially dominant in summer respectively, the amounts of other QTL showing Additive, partially dominant and over-dominant effects were 2, 1, 5 respectively. The positive alleles of three QTL were contributed by the normal corn parent Dan232, and the other positive alleles were contributed by the popcorn parent N04.

Chromosome Mapping↗

PubMed2004

Analysis of digenic epistatic effects and QE interaction effects QTL controlling grain weight in rice.

Immortalized F(2) population of rice (Oryza sativa L.) was developed by randomly mating F(1) among recombinant inbred (RI) lines derived from (Zhenshan 97B x Minghui 63), which allowed replications within and across environments. QTL (quantitative trait loci) mapping analysis on kilo-grain weight of immortalized F(2) population was performed by using newly developed software for QTL mapping, QTLMapper 2.0. Eleven distinctly digenic epistatic loci included a total of 15 QTL were located on eight chromosomes. QTL main effects of additive, dominance, and additive x additive, additive x dominance, and dominance x dominance interactions were estimated. Interaction effects between QTL main effects and environments (QE) were predicted. Less than 40% of single effects, most of which were additive effects, for identified QTL were significant at 5% level. The directional difference for QTL main effects suggested that these QTL were distributed in parents in the repulsion phase. This should make it feasible to improve kilo-grain weight of both parents by selecting appropriate new recombinants. Only few of the QE interaction effects were significant. Application prospect for QTL mapping achievements in genetic breeding was discussed.

Chromosomes, Plant↗

PubMed2005

Exclusion of the swine leukocyte antigens as candidate region and reduction of the position interval for the Sus scrofa chromosome 7 QTL affecting growth and fatness.

Pig chromosome 7 (SSC 7) has been shown to be rich in QTL affecting performance and quality traits. Most studies mapped the QTL close to the swine leukocyte antigens (SLA), which has a large effect on adaptability and natural selection. Previous comparative mapping studies suggested that the 15-cM region limited by markers LRA1 (mapped at 55 cM) and S0102 (mapped at 70 cM) contains hundreds of genes. To decrease the number of candidate genes, we improved the mapping resolution with a genetic chromosome dissection through a backcross recombinant progeny test program between Meishan (MS) and European (EU; i.e., Large White or Landrace) breeds. Three first-generation backcross--(EU x MS) x EU--and two second-generation backcross--([EU x MS] x EU) x EU--sires carrying a recombination in the QTL mapping interval were progeny-tested (i.e., measured for a total of 44 growth, fatness, carcass and meat quality traits). Progeny family size varied from 29 to 119 pigs. Animals were genotyped for markers covering the region of interest. Progeny-test results allowed the QTL interval to be decreased from 15 to 20 cM down to 10 cM, and even less than 6 cM if we assumed that the EU pigs used in this study share only one QTL allele. Except for a putative QTL affecting some carcass composition traits, the SLA is excluded as a candidate region, suggesting that it might be possible to apply a marker-assisted selection strategy for this QTL, while controlling SLA allele diversity. The strong QTL effects remaining in animals with only 12.5% (issued from first-generation backcross boars) and 6.25% (issued from second-generation back-cross boars) Meishan genetic background shows that epistatic interactions are likely to be limited. Finally, the QTL does not have strong effects on meat quality traits.

Adipose Tissue↗

PubMed2003

Search for pleiotropic QTL on chromosome BTA6 affecting yield traits of milk production.

The primary aim of this study was to investigate whether previous findings of similar quantitative trait loci (QTL) positions for correlated yield traits are due to a pleiotropic QTL. We applied a multitrait variance component based QTL mapping method to a dataset involving five granddaughter families from the German Holstein dairy cattle population. The marker map contained 16 microsatellite markers, distributed across chromosome BTA6. A chromosomewise significance threshold was used, because BTA6 is known to harbor QTL for several milk traits. To evaluate the results from the multivariate, across-family analysis, we also conducted single-family analyses using the least squares method of QTL estimation. The results provided two significant QTL findings at 49 and 64 cM for milk yield in different families and putative QTL at 68 cM for fat yield and at 71 cM for protein yield in another family. The results for fat and protein yield were confirmed by a univariate, across-family variance components analysis. The multivariate analysis of three bivariate trait combinations resulted in a significant pleiotropic QTL finding at 68 cM for fat yield and protein yield, bracketed by markers TGLA37 and FBN13. The estimates of variance contribution due to this QTL were 23% and 25%, respectively.

Analysis of Variance↗

PubMed2003

[Detection and analysis of QTL for seed dormancy in rice (Oryza sativa L.) using RIL and CSSL population].

A recombinant inbred line (RIL) population and two chromosome segment substitution line (CSSL) population derived from the cross of Asominori (japonica) and IR24 (indica) were used to detect QTL controlling seed dormancy. CSSL1 were a series of IR24 chromosome segment substitution lines in Asominori background, and CSSL2 were a series of introgression lines of Asominori in the background of IR24. Three QTL were detected on chromosome 3, 6 and 9 in RIL population, and individual QTL accounted for between 12.3% and 13%. Three QTL were detected on chromosome 1, 3 and 7 in CSSL1, and individual QTL accounted for between 11.5% and 18.9%. Three QTL were detected on chromosome 1, 2 and 7 in CSSL2, and individual QTL accounted for between 11% and 16%. The QTLs on chromosome 1 and 7 were detected in CSSL1 and CSSL2 populations simultaneously, QTL came from Asomonori, the moderate dormant cultivar, increased seed dormancy, and QTL from IR24, the weakly dormant cultivar, decreased seed dormancy. It can be deduced that there exist genes controlling seed dormancy at this region.

Chromosome Mapping↗

PubMed2002

An AFLP and RFLP linkage map and quantitative trait locus (QTL) analysis of growth traits in Salix.

A genetic linkage map of Salix (2n = 38), composed of 325 AFLP and 38 RFLP markers has been constructed. The map was based on a population ( n = 87) derived from a cross between the male hybrid clone "Björn" ( Salix viminalis x Salix schwerinii) and the female clone "78183" ( S. viminalis). Three hundred fifty seven AFLPs corresponding to DNA polymorphisms heterozygous in one parent and null in the other were scored. A total of 87 RFLP probes, most (83) derived from the Populus genome, yielded 39 and 11 polymorphic loci segregating in a 1:1 and 1:2:1 ratio respectively. Two maps, one for each parent, were constructed according to the "two-way pseudo-testcross" mapping strategy. The S. viminalis x S. schwerinii map (2,404 cM) included 217 markers and formed 26 major linkage groups while S. viminalis (1,844 cM) consisted of 146 markers placed on 18 major groups. In addition, eight and 14 additional minor linkage groups composed of less than four markers (doubles and triplets) were obtained in the S. viminalis x S. schwerinii and the S. viminalis maps, respectively. Both maps provided 70-80% genome coverage with an average density of markers of 14 cM. To investigate possible homologies between the parental maps, 20 AFLPs and 11 RFLPs segregating in 3:1 or 1:2:1 ratios were included in the linkage analysis. Eight linkage groups homologous between the two maps were detected. The present genetic map was used to identify quantitative trait loci (QTLs) affecting growth-related traits. Eleven QTLs were identified; seven QTLs for height growth, one QTL for stem diameter, one QTL for the height: diameter ratio, one QTL for the number of vegetative buds during flowering time and one QTL for the number of shoots. The estimated magnitude of the QTL effect ranged from 14 to 22% of the total phenotypic variance. One QTL associated with height growth and one affecting the height: diameter ratio were overlapping in the same marker interval with the QTL affecting stem diameter. QTL stability over years was estimated for traits measured in multiple years. Generally, QTLs were only significant in a single year although two QTLs for height growth were close to reaching the significance level in 2 consecutive years.

Journal Article↗

PubMed2003

QTL analysis of morphological traits in eggplant and implications for conservation of gene function during evolution of solanaceous species.

An interspecific F(2) population from a cross between cultivated eggplant, Solanum melongena, and its wild relative, S. linnaeanum, was analyzed for quantitative trait loci (QTL) affecting leaf, flower, fruit and plant traits. A total of 58 plants were genotyped for 207 restriction fragment length polymorphism (RFLP) markers and phenotyped for 18 characters. One to eight loci were detected for each trait with a total of 63 QTL identified. Overall, 46% of the QTL had allelic effects that were the reverse of those predicted from the parental phenotypes. Wild alleles that were agronomically superior to the cultivated alleles were identified for 42% of the QTL identified for flowering time, flower and fruit number, fruit set, calyx size and fruit glossiness. Comparison of the map positions of eggplant loci with those for similar traits in tomato, potato and pepper revealed that 12 of the QTL have putative orthologs in at least one of these other species and that putative orthology was most often observed between eggplant and tomato. Traits showing potential orthology were: leaf length, shape and lobing; days to flowering; number of flowers per inflorescence; plant height and apex, leaf and stem hairiness. The functionally conserved loci included a major leaf lobing QTL ( llob6.1) that is putatively orthologous to the potato leaf ( c) and/or Petroselinum ( Pts) mutants of tomato, two flowering time QTL ( dtf1.1, dtf2.1) that also have putative counterparts in tomato and four QTL for trichomes that have potential orthologs in tomato and potato. These results support the mounting evidence of conservation of gene function during the evolution of eggplant and its relatives from their last common ancestor and indicate that this conservation was not limited to domestication traits.

Chromosome Mapping↗

PubMed2005

Application of a new IBD-based QTL mapping method to common wheat breeding population: analysis of kernel hardness and dough strength.

Mapping quantitative trait loci (QTL) in plants is usually conducted using a population derived from a cross between two inbred lines. The power of such QTL detection and the estimation of the effects highly depend on the choice of the two parental lines. Thus, the QTL found represent only a small part of the genetic architecture and can be of limited economical interest in marker-assisted selection. On the other hand, applied breeding programmes evaluate large numbers of progeny derived from multiple-related crosses for a wide range of agronomic traits. It is assumed that the development of statistical techniques to deal with pedigrees in existing plant populations would increase the relevance and cost effectiveness of QTL mapping in a breeding context. In this study, we applied a two-step IBD-based-variance component method to a real wheat breeding population, composed of 374 F6 lines derived from 80 different parents. Two bread wheat quality related traits were analysed by the method. Results obtained show very close agreement with major genes and QTL already known for those two traits. With this new QTL mapping strategy, inferences about QTL can be drawn across the breeding programme rather than being limited to the sample of progeny from a single cross and thus the use of the detected QTL in assisting breeding would be facilitated.

Breeding↗

PubMed2005

QTL analysis of Fusarium head blight resistance using a high-density linkage map in barley.

Fusarium head blight (FHB) resistance was evaluated in a set of recombinant inbred (RI) lines from a cross between Russia 6 (resistant) and H.E.S. 4 (susceptible), which had one of the widest differences of FHB resistance reactions among ca. 5,000 barley germplasm accessions in Okayama University. Field-grown spikes were sampled and inoculated by the 'cut-spike test'. Resistance reactions on the parents and RI lines were scored by eleven grades, from resistant (0) to susceptible (10). Quantitative trait loci (QTL) analysis detected three QTL: two located on the long arm of chromosome 2H, and another on the short arm of chromosome 5H. A QTL located on chromosome 2H was coincident with the vrs1 locus, which governs inflorescence row type. The other QTL on chromosome 2H was positioned in the vicinity of cleistogamy locus (cly1 or Cly2) that determines inflorescence opening/closing. Resistant gene analog (RGA) and expressed sequence tag (EST) markers with homology for disease resistance genes were integrated into the high-density linkage map. Most of these markers were not localized near the identified resistance QTL, except for one RGA marker (FXLRRfor_XLRRrev170) localized in the vicinity of the cly1/Cly2 locus. Five AFLP markers localized in the vicinity of the identified QTL were sequenced to convert them into sequence tagged site (STS) markers. Genotyping of each RI line using two AFLP-STS markers and the vrs1 locus indicated that the RI lines with three Russia 6 QTL alleles exhibited the same level of high FHB resistance reactions as Russia 6. In contrast, RI lines with three susceptible alleles showed reactions close to H.E.S. 4. Therefore, the markers closely linked to the QTL can be efficiently used for the selection of resistance.

Chromosome Mapping↗

PubMed2006

Power of mixed-model QTL mapping from phenotypic, pedigree and marker data in self-pollinated crops.

The power of QTL mapping by a mixed-model approach has been studied for hybrid crops but remains unknown in self-pollinated crops. Our objective was to evaluate the usefulness of mixed-model QTL mapping in the context of a breeding program for a self-pollinated crop. Specifically, we simulated a soybean (Glycine max L. Merr.) breeding program and applied a mixed-model approach that comprised three steps: variance component estimation, single-marker analyses, and multiple-marker analysis. Average power to detect QTL ranged from <1 to 47% depending on the significance level (0.01 or 0.0001), number of QTL (20 or 80), heritability of the trait (0.40 or 0.70), population size (600 or 1,200 inbreds), and number of markers (300 or 600). The corresponding false discovery rate ranged from 2 to 43%. Larger populations, higher heritability, and fewer QTL controlling the trait led to a substantial increase in power and to a reduction in the false discovery rate and bias. A stringent significance level reduced both the power and false discovery rate. There was greater power to detect major QTL than minor QTL. Power was higher and the false discovery rate was lower in hybrid crops than in self-pollinated crops. We conclude that mixed-model QTL mapping is useful for gene discovery in plant breeding programs of self-pollinated crops.

Chromosome Mapping↗