Quantitative Trait Loci Alleles Research Articles

Identification of agronomically favorable quantitative trait loci alleles from a dent corn inbred Dan232 using advanced backcross QTL analysis and comparison with the F2:3 population in popcorn

Specific traits are an important consideration in plant breeding. In popcorn, inferior agronomic traits could be improved using dent or flint corn backcrossed with popcorn. In this study, we used advanced backcross quantitative trait locus (AB-QTL) analysis to identify trait-improving QTL alleles from a dent maize inbred Dan232, and compared the detection of QTL in the BC2S1 population with QTL results using F2:3 families of the same population. Two hundred and twenty BC2S1 families developed from a cross between Dan232 and an elite popcorn inbred N04 were evaluated for nine plant traits in replicated field trials under two environments. Using composite interval mapping (CIM), a total of 28 significant QTL were detected, and of these, 23 (82.14%) had favorable alleles contributed by the dent corn parent Dan232. Nine QTL (32.14%) detected in the BC2S1 population were also located in or near the same chromosome intervals in the F2:3 population. All of the favorable QTL alleles from Dan232 could be used in marker-assisted selection (MAS) to improve the respective plant traits in popcorn breeding. In addition, their near isogenic lines (QTL-NILs) could be obtained through selfing or another 1–2 backcross with N04. Also, N04 improved for the studied plant traits could be developed from the BC2S1 families used in this study. This study demonstrated that the AB-QTL method can be applied to identify favorable QTL from dent corn inbred in popcorn breeding and, once identified, the alleles could be used in marker-assisted selection to improve the respective plant traits.

Detection of Mendelian and Parent-of-origin Quantitative Trait Loci in a Cross between Korean Native Pig and Landrace I. Growth and Body Composition Traits

This study was conducted to detect quantitative trait loci (QTL) affecting growth and body composition in an F 2 reference population of Korean native pig and Landrace crossbreds. The three-generation mapping population was generated with 411 progeny from 38 F 2 full-sib families, and 133 genetic markers were used to produce a sex-average map of the 18 autosomes. The data set was analyzed using least squares Mendelian and parent-of-origin interval-mapping models. Lack-of-fit tests between the models were used to characterize QTL for mode of expressions. A total of 8 (39) QTL were detected at the 5% genome (chromosome)-wise level for the 17 analyzed traits. Of the 47 QTL detected, 21 QTL were classified as Mendelian expressed, 13 QTL as paternally expressed, 6 QTL as maternally expressed, and 7 QTL as partially expressed. Of the detected QTL at 5% genome-wise level, two QTL had Mendelian mode of inheritance on SSC6 and SSC9 for backfat thickness and bone weight, respectively, two QTL were maternally expressed for leather weight and front leg weight on SSC6 and SSC12, respectively, one QTL was paternally expressed for birth weight on SSC4, and three QTL were partially expressed for hot carcass weight and rear leg weight on SSC6, and bone weight on SSC13. Many of the Mendelian QTL had a dominant (complete or overdominant) mode of gene action, and only a few of the QTL were primarily additive, which reflects that heterosis for growth is appreciable in a cross between Korean native pig and Landrace. Our results indicate that alternate breed alleles of growth and body composition QTL are segregating between the two breeds, which could be utilized for genetic improvement of growth via marker-assisted selection.

Nonrandom pattern of chromosome aberrations in 17β‐estradiol‐induced rat mammary tumors: Indications of distinct pathways for tumor development

Estrogens play an important role in breast cancer etiology and the ACI rat provides a novel animal model for defining the mechanisms through which estrogens contribute to mammary cancer development. In crossing experiments between the susceptible ACI strain and two resistant strains, COP (Copenhagen) and BN (Brown Norway), several quantitative trait loci (QTL) that affect development of 17beta-estradiol (E2)-induced mammary tumors have been defined. Using comparative genomic hybridization (CGH), we have analyzed cytogenetic aberrations in E2-induced mammary cancers and have found clear patterns of nonrandom chromosomal involvement. Approximately two thirds of the tumors exhibited copy number changes. Losses of rat chromosome 5 (RNO5) and RNO20 were particularly common, and it was found that these two aberrations often occurred together. A third recurrent aberration involving proximal gain and distal loss in RNO6 probably defined a distinct subgroup of tumors, since it never occurred in combination with RNO5 loss. Interestingly, QTL with powerful effects on mammary cancer development have been mapped to RNO5 and RNO6. These findings suggest that there were at least two genetic pathways to tumor formation in this rat model of E2-induced mammary cancer. By performing CGH on mammary tumors from ACI rats, F1 rats from crosses between the ACI and COP or BN strains and ACI.BN-Emca8 congenic rats, which carry the BN allele of the Emca8 QTL on RNO5 on the ACI genetic background, we were able to determine that the constitution of the germ line influences the pattern of chromosomal aberrations.

Identification of Quantitative Trait Loci for Cold Response of Seedling Vigor Traits in Rice

The quantitative trait loci (QTLs) for the seedling vigor traits under 12°C cold water irrigation, such as the seedling height, the seedling fresh weight, the seedling dry weight, and their cold response index, were identified using an F 2–3 population including 200 individuals and lines derived from a cross of indica and japonica “Milyang 23/Jileng 1” with microsatellite markers. All seedling vigor traits exhibited a continuous distribution near normal in F3 lines; these traits were quantitative traits controlled by multiple genes. Twelve QTLs conferring the seedling vigor traits under cold water irrigation were detected on chromosomes 1, 2, 7, 8, and 12, which explained the observed phenotypic variance from 5.2% to 17.9%. Among them, qCSH2 and qCSH12 were located in RM262-RM263 on chromosome 2 and RM270-RM17 on chromosome 12, respectively, which were associated with the seedling height. qSDW12 and qCSDW1 were located in RM19-RM270 on chromosome 12 and RM129-RM9 on chromosome 1, respectively, which were correlated with the seedling dry weight and its cold response index, and the explained 16.6%, 17.9%, 15.9%, and 16.2% of the observed phenotypic variation, respectively. These QTLs alleles were derived from cold-tolerant parent Jileng 1; the gene actions of the two front genes showed their additive effect, and the two genes belind showed dominant and over dominant effects, respectively.

Positional Cloning of Quantitative Trait Loci for Blood Pressure: How Close Are We?

Blood pressure (BP) in any human population exhibits as a continuous variable that fits a bell-shaped curve. Hypertensive individuals are those whose BP is maintained at one extreme of the curve and above a defined cutoff. Despite progress made in identifying the mechanisms underlying certain rare monogenic forms of hypertension,1,2 the etiology and pathogenesis of essential hypertension remain poorly understood. Because existing human populations are genetically heterogeneous, and because environmental factors impacting on the pathogenesis of hypertension cannot be controlled in a given population, it is difficult to identify the molecular mechanisms that transduce the sequela of essential hypertension via direct human studies.3 To alleviate the drawbacks of human investigations, animal models, especially inbred rodents, have been developed and experimentally manipulated to identify quantitative trait loci (QTLs) for BP, because major confounding environmental factors, such as diet and genetic background, can be systematically controlled. Once identified in animal models, the molecular basis may be translated into physiological understandings of essential hypertension in humans. It is with this expectation that efforts have been launched to identify the molecular basis of BP QTLs in animal models. Because the identification of individual QTLs is primarily based on their chromosome locations unbiased by, or unrestricted to, their physiological roles, positional cloning is believed to be the most efficient strategy. Before we embark on discussions regarding QTL discovery, a definition is in order. Semantic arguments abound as to exactly what a QTL, that is, a locus,4 entails. Is it 1 gene or a collection of genes? As genetic mapping progresses from a large chromosome segment to an interval of submegabase, several regions initially thought to contain 1 BP QTL5 appear to harbor >1 in each of them,6–10 whereas several other regions turned out to harbor 1 QTL as expected.11,12 …

Genetic and QTL Analysis for Low-Temperature Vigor of Germination in Rice

The quantitative trait loci (QTLs) for low-temperature vigor of germination (LVG) with a germination period of 7 d, 11 d, 14 d, and 17 d at 14 °C was identified using F 2:3 population, which included 200 individuals and lines derived from a cross of indica and japonica “Milyang 23/Jileng 1” with microsatellite markers. The correlation coefficient between LVG and other cold tolerance traits was analyzed. LVG and the cold response index for vigor of germination (CIVG) detected when the germination period was 7 d showed a continuous distribution, which was partial to lower LVG and lower CIVG in F 3 lines. LVG and CIVG detected when the germination periods were 11 d, 14 d, and 17 d showed a continuous distribution near normal, which were quantitative traits controlled by multiple genes. LVG detected when the germination period was 14 d was more correlated with other cold tolerance traits than LVG detected when the germination periods were 7 d, 11 d, and 17 d, which was significantly associated with cold tolerance during the bud bursting period, the seedling stage, the booting stage, and the growing ability under cold conditions. qLVG2 located in RM29-RM262 on chromosome 2, qLVG7-2 and qCIVG7-2 located in RM336-RM118 on chromosome 7 were detected when the germination periods were 11 d, 14 d, and 17 d. qCIVG2 located in RM29-RM262 on chromosome 2 was detected when the germination periods were 11 d and 14 d. The variation is due to the observed phenotypic variation by the above QTLs, which was increased following the germination. The variation of qLVG2 related to LVG was increased from 6.9% to 14.2%. The variation of qLVG7-2 associated with LVG was increased from 9.9% to 11.2%. The variation of qCIVG2 correlated with CIVG was increased from 6.3% to 9.0%. The variation of qCIVG7-2 associated with CIVG was increased from 8.3% to 12.9%. These QTL alleles were obtained from the tolerant parent Jileng 1, and the gene action was most likely to be partially dominant.

Of Flies and Man:Drosophilaas a Model for Human Complex Traits

Understanding the genetic and environmental factors affecting human complex genetic traits and diseases is a major challenge because of many interacting genes with individually small effects, whose expression is sensitive to the environment. Dissection of complex traits using the powerful genetic approaches available with Drosophila melanogaster has provided important lessons that should be considered when studying human complex traits. In Drosophila, large numbers of pleiotropic genes affect complex traits; quantitative trait locus alleles often have sex-, environment-, and genetic background-specific effects, and variants associated with different phenotypic are in noncoding as well as coding regions of candidate genes. Such insights, in conjunction with the strong evolutionary conservation of key genes and pathways between flies and humans, make Drosophila an excellent model system for elucidating the genetic mechanisms that affect clinically relevant human complex traits, such as alcohol dependence, sleep, and neurodegenerative diseases.

PAPPA2, an Enzyme That Cleaves an Insulin-Like Growth-Factor-Binding Protein, Is a Candidate Gene for a Quantitative Trait Locus Affecting Body Size in Mice

Identifying genes responsible for quantitative variation remains a major challenge. We previously identified a quantitative trait locus (QTL) affecting body size that segregated between two inbred strains of mice. By fine mapping, we have refined the location of this QTL to a genomic region containing only four protein-coding genes. One of these genes, PAPPA2, is a strong candidate because it codes for an enzyme that cleaves insulin-like growth-factor-binding protein 5 (IGFBP-5), an important stimulator of bone formation. Among littermates that segregate only for the four-gene region, we show that the QTL has a significant effect on the circulating levels of IGFBP-5 and IGFBP-3 (the latter subject to limited degradation by PAPPA2), but not on levels of IGFBP-2 and IGFBP-4, which are not cleaved by PAPPA2. There are 14 nonsynonymous SNPs among QTL alleles, which may affect the activity of the translated protein. The refinement of the target region to four genes and the finding that the QTL affects IGFBP-5 levels suggest that PAPPA2 may be involved with normal postnatal growth. Our mapping results also illustrate the potentially fractal nature of QTL: as we mapped our QTL with increasing resolution, what appeared to be a single QTL resolved into three closely linked QTL (previous work), and then one of these was further dissected into two in this study.

Quantitative trait analysis of seed yield and other complex traits in hybrid spring rapeseed (Brassica napus L.): 1. Identification of genomic regions from winter germplasm

The introgression of winter germplasm into spring canola (Brassica napus L.) represents a novel approach to improve seed yield of hybrid spring canola. In this study, quantitative trait loci (QTL) for seed yield and other traits were genetically mapped to determine the effects of genomic regions introgressed from winter germplasm into spring canola. Plant materials used comprised of two populations of doubled haploid (DH) lines having winter germplasm introgression from two related French winter cultivars and their testcrosses with a spring line used in commercial hybrids. These populations were evaluated for 2 years at two locations (Wisconsin, USA and Saskatchewan, Canada). Genetic linkage maps based on RFLP loci were constructed for each DH population. Six QTL were detected in the testcross populations for which the winter alleles increased seed yield. One of these QTL explained 11 and 19% of the phenotypic variation in the two Canadian environments. The winter allele for another QTL that increased seed yield was linked in coupling to a QTL allele for high glucosinolate content, suggesting that the transition of rapeseed into canola could have resulted in the loss of favorable seed yield alleles. Most QTL for which the introgressed allele decreased seed yield of hybrids mapped to genomic regions having homoeologous non-reciprocal transpositions. This suggests that allelic configurations created by these rearrangements might make an important contribution to genetic variation for complex traits in oilseed B. napus and could account for a portion of the heterotic effects in hybrids.

Genome-wide isolation of growth and obesity QTL using mouse speed congenic strains

BackgroundHigh growth (hg) modifier and background independent quantitative trait loci (QTL) affecting growth, adiposity and carcass composition were previously identified on mouse chromosomes (MMU) 1, 2, 5, 8, 9, 11 and 17. To confirm and further characterize each QTL, two panels of speed congenic strains were developed by introgressing CAST/EiJ (CAST) QTL alleles onto either mutant C57Bl/6J-hg/hg (HG) or wild type C57Bl/6J (B6) genetic backgrounds.ResultsThe first speed congenic panel was developed by introgressing four overlapping donor regions spanning MMU2 in its entirety onto both HG and B6 backgrounds, for a total of eight strains. Phenotypic characterization of the MMU2 panel confirmed the segregation of multiple growth and obesity QTL and strongly suggested that a subset of these loci modify the effects of the hg deletion. The second panel consisted of individual donor regions on an HG background for each QTL on MMU1, 5, 8, 9, 11 and 17. Of the six developed strains, five were successfully characterized and displayed significant differences in growth and/or obesity as compared to controls. All five displayed phenotypes similar to those originally attributed to each QTL, however, novel phenotypes were unmasked in several of the strains including sex-specific effects.ConclusionThe speed congenic strains developed herein constitute an invaluable genomic resource and provide the foundation to identify the specific nature of genetic variation influencing growth and obesity.

Main Effects, Epistasis, and Environmental Interactions of Quantitative Trait Loci for Fusarium Head Blight Resistance in a Recombinant Inbred Population

ABSTRACT Chinese Spring Sumai 3 chromosome 7A disomic substitution line (CS-SM3-7ADS) is highly resistant to Fusarium head blight (FHB), and an F(7) population of recombinant inbred lines derived from the cross CS-SM3-7ADS x Annong 8455 was evaluated for resistance to FHB to investigate main effects, epistasis, and environmental interactions of quantitative trait loci (QTLs) for FHB resistance. A molecular linkage map consists of 501 simple sequence repeat and amplified fragment length polymorphism markers. A total of 10 QTLs were identified with significant main effects on the FHB resistance using MapQTL and QTLMapper software. Among them, CS-SM3-7ADS carries FHB-resistance alleles at five QTLs on chromosomes 2D, 3B, 4D, and 6A. One QTL on 3BS had the largest effect and explained 30.2% of the phenotypic variance. Susceptible QTLs were detected on chromosomes 1A, 1D, 4A, and 4B. A QTL for enhanced FHB resistance was not detected on chromosome 7A of CS-SM3-7ADS; therefore, the increased FHB resistance in CS-SM3-7ADS was not due to any major FHB-resistance QTL on 7A of Sumai 3, but more likely was due to removal of susceptible alleles of QTLs on 7A of Chinese Spring. QTLMapper detected nine pairs of additive-additive interactions at 17 loci that explained 26% phenotypic variance. QTL-environment interactions explained 49% of phenotypic variation, indicating that the environments significantly affected the expression of the QTLs, especially these epistasis QTLs. Adding FHB-enhancing QTLs or removal of susceptible QTLs both may significantly enhance the degree of wheat resistance to FHB in a wheat cultivar.

Efficient computation of the inverse of gametic relationship matrix for a marked QTL

Best linear unbiased prediction of genetic merits for a marked quantitative trait locus (QTL) using mixed model methodology includes the inverse of conditional gametic relationship matrix (G-1) for a marked QTL. When accounting for inbreeding, the conditional gametic relationships between two parents of individuals for a marked QTL are necessary to build G-1 directly. Up to now, the tabular method and its adaptations have been used to compute these relationships. In the present paper, an indirect method was implemented at the gametic level to compute these few relationships. Simulation results showed that the indirect method can perform faster with significantly less storage requirements than adaptation of the tabular method. The efficiency of the indirect method was mainly due to the use of the sparseness of G-1. The indirect method can also be applied to construct an approximate G-1 for populations with incomplete marker data, providing approximate probabilities of descent for QTL alleles for individuals with incomplete marker data.

Efficient computation of the inverse of gametic relationship matrix for a marked QTL

Best linear unbiased prediction of genetic merits for a marked quantitative trait locus (QTL) using mixed model methodology includes the inverse of conditional gametic relationship matrix (G-1) for a marked QTL. When accounting for inbreeding, the conditional gametic relationships between two parents of individuals for a marked QTL are necessary to build G-1 directly. Up to now, the tabular method and its adaptations have been used to compute these relationships. In the present paper, an indirect method was implemented at the gametic level to compute these few relationships. Simulation results showed that the indirect method can perform faster with significantly less storage requirements than adaptation of the tabular method. The efficiency of the indirect method was mainly due to the use of the sparseness of G-1. The indirect method can also be applied to construct an approximate G-1 for populations with incomplete marker data, providing approximate probabilities of descent for QTL alleles for individuals with incomplete marker data.

Gene flow's effect on the genetic architecture of a local adaptation and its consequences for QTL analyses

This paper uses computer simulations to determine how gene flow between populations affects (1) the genetic architecture of a local adaptation and (2) properties of alleles segregating in quantitative trait locus (QTL) mapping populations. Results suggest that the average magnitude of an allele that causes a phenotypic difference between populations declines as the migration rate increases, but with an increase in migration, alleles of larger magnitude cause proportionally more of the phenotypic difference between populations. Gene flow between populations that are used in a QTL study tends to cause the average magnitude and percent variance explained (PVE) of an allele in a mapping population to increase. Thus, although the average magnitude of an allele causing a difference declines with migration the average magnitude or PVE of an allele in a QTL mapping population may increase. The reason is that the probability an allele is sampled for a QTL mapping population is in direct proportion to its frequency and alleles of larger magnitude tend to segregate at relatively higher frequencies than alleles of smaller effect with an increased migration. As the rate of gene flow between populations increases, the proportion of the phenotypic difference explained by alleles that are segregating in a QTL mapping population (and therefore potentially detected) decreases. Lastly, results suggest QTL alleles of large effect (>20% PVE) should be commonly found, provided the divergence time between populations is not too long or optima of populations are not too far apart.

Optimal Haplotype Structure for Linkage Disequilibrium-Based Fine Mapping of Quantitative Trait Loci Using Identity by Descent

A linkage disequilibrium-based method for fine mapping quantitative trait loci (QTL) has been described that uses similarity between individuals' marker haplotypes to determine if QTL alleles are identical by descent (IBD) to model covariances among individuals' QTL alleles for a mixed linear model. Mapping accuracy with this method was found to be sensitive to the number of linked markers that was included in the haplotype when fitting the model at a putative position of the QTL. The objective of this study was to determine the optimal haplotype structure for this IBD-based method for fine mapping a QTL in a previously identified QTL region. Haplotypes consisting of 1, 2, 4, 6, or all 10 available markers were fit as a "sliding window" across the QTL region under ideal and nonideal simulated population conditions. It was found that using haplotypes of 4 or 6 markers as a sliding "window" resulted in the greatest mapping accuracy under nearly all conditions, although the true IBD state at a putative QTL position was most accurately predicted by IBD probabilities obtained using all markers. Using 4 or 6 markers resulted in greater discrimination of IBD probabilities between positions while maintaining sufficient accuracy of IBD probabilities to detect the QTL. Fitting IBD probabilities on the basis of a single marker resulted in the worst mapping accuracy under all conditions because it resulted in poor accuracy of IBD probabilities. In conclusion, for fine mapping using IBD methods, marker information must be used in a manner that results in sensitivity of IBD probabilities to the putative position of the QTL while maintaining sufficient accuracy of IBD probabilities to detect the QTL. Contrary to expectation, use of haplotypes of 4-6 markers to derive IBD probabilities, rather than all available markers, best fits these criteria. Thus for populations similar to those simulated here, optimal mapping accuracy for this IBD-based fine-mapping method is obtained with a haplotype structure including a subset of all available markers.

Models and partition of variance for quantitative trait loci with epistasis and linkage disequilibrium.

BackgroundA genetic model about quantitative trait loci (QTL) provides a basis to interpret the genetic basis of quantitative traits in a study population, such as additive, dominance and epistatic effects of QTL and the partition of genetic variance. The standard quantitative genetics model is based on the least squares partition of genetic effects and also genetic variance in an equilibrium population. However, over years many specialized QTL models have also been proposed for applications in some specific populations. How are these models related? How to analyze and partition a QTL model and genetic variance when both epistasis and linkage disequilibrium are considered?ResultsStarting from the classical description of Cockerham genetic model, we first represent the model in a multiple regression setting by using indicator variables to describe the segregation of QTL alleles. In this setting, the definition of additive, dominance and epistatic effects of QTL and the basis for the partition of genetic variance are elaborated. We then build the connection between this general genetic model and a few specialized models (a haploid model, a diploid F2 model and a general two-allele model), and derive the genetic effects and partition of genetic variance for multiple QTL with epistasis and linkage disequilibrium for these specialized models.ConclusionIn this paper, we study extensively the composition and property of the genetic model parameters, such as genetic effects and partition of genetic variance, when both epistasis and linkage disequilibrium are considered. This is the first time that both epistasis and linkage disequilibrium are considered in modeling multiple QTL. This analysis would help us to understand the structure of genetic parameters and relationship of various genetic quantities, such as allelic frequencies and linkage disequilibrium, on the definition of genetic effects, and will also help us to understand and properly interpret estimates of the genetic effects and variance components in a QTL mapping experiment.

Quantitative trait locus analysis for obesity reveals multiple networks of interacting loci

Obesity is a highly heritable and genetically complex trait with hundreds of potential loci identified. An intercross of 513 F2 progeny between the SM/J x NZB/BINJ inbred mouse strains was generated to identify quantitative trait loci (QTL) that are involved in the weight of four fat pads: mesenteric, inguinal, gonadal, and retroperitoneal. Sex and lean body weight were treated as covariates in the analysis of these fat pads. This analysis uncoupled genetic effects related to overall body size from those influencing the adiposity of a mouse. We identified multiple significant QTL. QTL alleles associated with increased lean body weight and individual fat pad weights are contributed by the NZB background. Adiposity loci are distinct from these body size QTLs and high-adiposity alleles are contributed by the SM background. An extended network of epistatic QTL is also observed. A QTL on Chr 19 is the center of a network of eight interacting QTL, Chr 4 is the center of six, and Chr 17 the center of four interacting QTL. We conclude that interacting networks of multiple genes characterize the regulation of fat pad depots and body weight. Haplotype patterns and a literature-driven approach were used to generate hypotheses regarding the identity of the genes and pathways underlying the QTL.

Comparison of granddaughter design and general pedigree design analysis of QTL in dairy cattle: a simulation study

Traditional methods for detection and mapping of quantitative trait loci (QTL) in dairy cattle populations are usually based on daughter design (DD) or granddaughter design (GDD). Although these designs are well established and usually successful in detecting QTL, they consider sire families independently of each other, thereby ignoring relationships among other animals in the population and consequently, reducing the power of QTL detection. In this study we compared a traditional GDD with a general pedigree design (GPD) and assessed the precision and power of both methods for detecting and locating QTL in a simulated complex pedigree. QTL analyses were performed under the variance component model containing a random QTL and a random polygenic effect. The covariance matrix of the polygenic effect was a standard additive relationship matrix. The (co)variance matrix of the random QTL effect contained probabilities that QTL alleles shared by two individuals were identical by descent (IBD). In the GDD analysis, IBD probabilities were calculated using sires’ and daughters’ marker genotypes. In the GPD analysis, IBD probabilities were obtained using a deterministic approach. The estimation of QTL position and variance components was conducted using REML algorithm. Although both methods were able to locate the region of the QTL properly, the GPD method showed better precision of QTL position estimates in most cases and significantly higher power than the GDD method.  

Stacking quantitative trait loci (QTL) for Fusarium head blight resistance from non-adapted sources in an European elite spring wheat background and assessing their effects on deoxynivalenol (DON) content and disease severity

Fusarium head blight (FHB) is a devastating disease in wheat that reduces grain yield, grain quality and contaminates the harvest with deoxynivalenol (DON). As potent resistance sources Sumai 3 and its descendants from China and Frontana from Brazil had been analysed by quantitative trait loci (QTL) mapping. We introgressed and stacked two donor QTL from CM82036 (Sumai 3/Thornbird) located on chromosomes 3B and 5A and one donor QTL from Frontana on chromosome 3A in elite European spring wheat and estimated the effects of the three individual donor QTL and their four combinations on DON, Fusarium exoantigen content, and FHB rating adjusted to heading date. One class with the susceptible QTL alleles served as control. Each of the eight QTL classes was represented by 12-15 F(3)-derived lines tested in F(5) generation as bulked progeny possessing the respective marker alleles homozygously. Traits were evaluated in a field experiment across four locations with spray inoculation of Fusarium culmorum. All three individual donor-QTL alleles significantly reduced DON content and FHB severity compared to the marker class with no donor QTL. The only exception was the donor-QTL allele 3A that had a low, but non-significant effect on FHB severity. The highest effect had the stacked donor-QTL alleles 3B and 5A for both traits. They jointly reduced DON content by 78% and FHB rating by 55% compared to the susceptible QTL class. Analysis of Fusarium exoantigen content illustrates that lower disease severity is associated with less mycelium content in the grain. In conclusion, QTL from non-adapted sources could be verified in a genetic background of German elite spring wheat. Within the QTL classes significant (P<0.05) genotypic differences were found among the individual genotypes. An additional phenotypic selection would, therefore, be advantageous after performing a marker-based selection.

Mapping regulatory genes as candidates for cold and drought stress tolerance in barley

Cereal crop yield is greatly affected in many growing areas by abiotic stresses, mainly low temperature and drought. In order to find candidates for the tolerance genes for these stresses, 13 genes encoding for transcription factors and upstream regulators were screened by amplification and SSCP on six parental genotypes of three barley mapping populations ('Nure' x 'Tremois', 'Proctor' x 'Nudinka', and 'Steptoe' x 'Morex'), and mapped as newly developed STS, SNP, and SSCP markers. A new consensus function map was then drawn using the three maps above, including 16 regulatory candidate genes (CGs). The positions of barley cold and drought tolerance quantitative trait loci (QTLs) presently described in the literature were added to the consensus map to find positional candidates from among the mapped genes. A cluster of six HvCBF genes co-mapped with the Fr-H2 cold tolerance QTL, while no QTLs for the same trait were positioned on chromosome 7H, where two putative barley regulators of CBF expression, ICE1 and FRY1, found by homology search, were mapped in this work. These observations suggest that CBF gene(s) themselves, rather than their two regulators, are at present the best candidates for cold tolerance. Four out of 12 drought tolerance QTLs of the consensus map are associated with regulatory CGs, on chromosomes 2H, 5H, and 7H, and two QTLs with effector genes, on chromosomes 5H and 6H. The results obtained could be used to guide MAS applications, allowing introduction into an ideal genotype of favourable alleles of tolerance QTLs.