Enhanced power of QTL detection for Fusarium head blight resistance in wheat by means of codominant scoring of hemizygous molecular markers

Based on different marker information content mapping of QTLs for Fusarium head blight resistance in wheat was compared with regard to number and consistency of detected QTLs as well as QTL positions and effects. Therefore, two linkage maps, obtained by dominant and codominant genotyping of hemizygous markers, were constructed with 211 AFLPs, 37 SSRs and the barley RGA marker XaACT/CAA. The codominant marker set comprised 59% codominant markers, whereas the dominant map consisted of only 13%. A segregating wheat population of 94 F₄-RILs was used for QTL analysis. Fusarium head blight resistance was estimated in field trials in six environments. Conventional dominant marker scoring found seven QTLs. The phenotypic variations explained by QTLs detected in single environment analyses ranged from 11.1 to 44.6%. QTL analysis performed with the codominant marker set confirmed not only all QTL positions as revealed by dominant QTL analysis', but also 12 additional QTLs were found. QTLs in single environments explained 36.3 up to 55.7% of the phenotypic variation. In the QTL analysis across all environments, none of the QTLs could be confirmed using dominant marker scoring. However, by codominant QTL analysis' environment-specific QTLs were retrieved. STS marker XaACT/CAA was found to be significantly associated with FHB resistance only by codominant scoring. Support intervals of QTLs commonly found in both marker sets averaged to 10.3 cM in the dominant QTL analysis', whereas the length was shortened to 8.9 cM by codominant genotyping. The advantages of extracting codominant information from dominant markers are discussed.     

Quantitative resistance to barley leaf stripe (Pyrenophora graminea) is dominated by one major locus

A major gene underlying quantitative resistance of barley against Pyrenophora graminea, a seedborne pathogen causing leaf stripe, was mapped with molecular markers in a barley doubled haploid (DH) population derived from the cross Proctor x Nudinka. This quantitative trait locus (QTL) accounts for r ²= 58.5% and was mapped on barley chromosome 1, tightly linked to the naked gene. A second resistance QTL accounting for 29.3% of the variation in the trait was identified on the P arm of barley chromosome 2. Another two minor QTLs were detected by further analysis. None of the QTLs was found in the barley chromosome 2 Vada region studied by Giese et al. (1993).     

QTL analysis: further uses of ‘marker regression’

A variety of approaches are available for identifying the location and effect of QTL in segregating populations using molecular markers. However, these have problems in distinguishing two linked QTL, particularly in relation to the size of the test statistic when many independent tests are performed. An empirical method for obtaining the distribution of the test statistic for specific datasets is described, and its power for demonstrating the inadequacy of a single-QTL model is explored through computer simulation. The method is an extension of the previously described technique of marker regression, and it is applied here to demonstrate two situations in which it may be useful. Firstly, we examine the power of the technique to distinguish two, linked QTL from one and compare this ability with that of two contemporary methods, Mapmaker/QTL and regression mapping. Secondly, we show how to combine information from two, or more, populations that may be segregating for different marker loci in a given linkage group. This is illustrated for two populations having in common just two linked marker loci although the sharing of loci is not a pre-requisite. Empirical tests are used to determine whether the same or different QTL are segregating and, if they are the same QTL, whether they are the same alleles. Evidence is discussed which suggests that the upper limit to the number of QTL that can be located for any single quantitative trait in a segregating populations is 12.     

Analysis of QTLs for yield, yield components, and malting quality in a BC3-DH population of spring barley

Advanced backcross (AB)-quantitative trait locus (QTL) analysis has been successfully applied for detecting and transferring QTLs from unadapted germplasm into elite breeding lines in various plant species. Here, we describe the application of a modified AB breeding scheme to spring barley. A BC₃-doubled haploid (DH) population consisting of 181 lines derived from the German spring barley cultivar Brenda (Hordeum vulgare subsp. vulgare) as the recurrent parent and the wild species line HS213 (H. vulgare subsp. spontaneum) as the donor line was evaluated for yield and its components as well as malting quality traits. A set of 60 microsatellite markers was used to genotype the population, and phenotypic data were collected at two locations in Germany in continuous years. Altogether, 25 significant QTLs were detected by single-marker regression analysis and interval mapping. Most positive QTLs originated from the recurrent parent Brenda. A QTL, Qhd2.1, on chromosome 2HS from Brenda explained 18.3% and 20.7% of the phenotypic variation for yield and heading date, respectively. Due to the small percentage of donor-parent genome of 6.25%, the BC₃-DH lines could be directly used for the extraction of near-isogenic lines (NILs) for Qhd2.1. Consequently, it was possible to determine the precise location of the locus hd2.1 within a region of 6.5 cM, using an F₂ population consisting of 234 individuals developed from a cross between an NIL containing a defined donor segment at this locus and Brenda. The location of this QTL was consistent with the presence of a major photoperiod response gene, Ppd-H1, previously reported in this region, which is associated with pleiotropic effects on yield components. In summary, the analysis of a BC₃-DH population in barley provides a compromise between the analysis of QTLs by means of an AB scheme and the generation of defined substitution lines. Several lines carrying defined different donor segments for only one single chromosome or trait in the genetic background of Brenda could be selected for further genetic studies.     

Characterization of quantitative trait loci (QTLs) in cultivated rice contributing to field resistance to sheath blight (Rhizoctonia solani)

Sheath blight, caused by Rhizoctonia solani, is one of the most important diseases of rice. Despite extensive searches of the rice germ plasm, the major gene(s) which give complete resistance to the fungus have not been identified. However, there is much variation in quantitatively inherited resistance to R. solani, and this type of resistance can offer adequate protection against the pathogen under field conditions. Using 255 F₄ bulked populations from a cross between the susceptible variety Lemont and the resistant variety Teqing, 2 years of field disease evaluation and 113 well-distributed RFLP markers, we identified six quantitative trait loci (QTLs) contributing to resistance to R. solani. These QTLs are located on 6 of the 12 rice chromosomes and collectively explain approximately 60% of the genotypic variation or 47% of the phenotypic variation in the LemontxTeqing cross. One of these resistance QTLs (QSbr4a), which accounted for 6% of the genotypic variation in resistance to R. solani, appeared to be independent of associated morphological traits. The remaining five putative resistance loci (QSbr2a, QSbr3a, QSbr8a, QSbr9a and QSbr12a) all mapped to chromosomal regions also associated with increased plant height, three of which were also associated with QTLs causing later heading. This was consistent with the observation that heading date and plant height accounted for 47% of the genotypic variation in resistance to R. solani in this population. There were also weak associations between resistance to R. solani and leaf width, which were likely due to linkage with a QTL for this trait rather than to a physiological relationship.     

Assessment of DNA pooling strategies for mapping of QTLs

The synthesis of DNA pools from segregating populations is an efficient strategy for identifying DNA markers closely linked to genes or genomic regions of interest. To-date, DNA pooling based solely upon phenotypic information, or bulked segregant analysis, has been employed only in the analysis of simply-inherited traits. We have assessed the utility of phenotype-based DNA pools for tagging (e.g., identifying DNA markers closely-linked to) quantitative trait loci (QTLs), segregating in the presence of other such loci, and expressing phenotypes which are influenced by the environment. Theoretical estimates suggest that QTL alleles with phenotypic effects of 0.75–1.0 standard deviations (SD), or larger, should be detectable in back-cross (BC), F₂ and recombinant inbred (RI) or doubled haploid (DH) populations of manageable size (100–200 plants/lines). However, post hoc analysis of three data sets, used in QTL mapping of tomato and rice, indicate that the majority of QTLs identified had allele effects of less than 0.75 SD, and thus could not be easily tagged in DNA pools. Segregation distortion can have a large effect on the allelic composition of DNA pools, necessitating the use of more individuals in the pools to minimize false positive and false negative results. In general, we suggest that use of phenotype-based DNA pools might be successful in tagging QTLs of very large effect, but is unlikely to permit comprehensive identification of the majority of QTLs affecting a complex trait. DNA pools constructed from a priori information should, however, be useful in identifying new DNA markers for regions of the genome known to contain QTLs.     

Linkage mapping of quantitative trait loci controlling seed weight in pea (Pisum sativum L.)

Quantitative trait loci (QTLs) affecting seed weight in pea (Pisum sativum L.) were mapped using two populations, a field-grown F₂ progeny of a cross between two cultivated types (Primo and OSU442-15) and glasshouse-grown single-seed-descent recombinant inbred lines (RILs) from a wide cross between a P. sativum ssp. sativum line (Slow) and a P. sativum ssp. humile accession (JI1794). Linkage maps for these crosses consisted of 199 and 235 markers, respectively. QTLs for seed weight in the Primo x OSU442-15 cross were identified by interval mapping, bulked segregant analysis, and selective genotyping. Four QTLs were identified in this cross, demonstrating linkage to four intervals on three linkage groups. QTLs for seed weight in the JI1794 x Slow cross were identified by single-marker analyses. Linkage were demonstrated to four intervals on three linkage groups plus three unlinked loci. In the two crosses, only one common genomic region was identified as containing seed-weight QTLs. Seed-weight QTLs mapped to the same region of linkage group III in both crosses. Conserved linkage relationships were demonstrated for pea, mungbean (Vigna radiata L.), and cowpea (V. unguiculata L.) genomic regions containing seed-weight QTLs by mapping RFLP loci from the Vigna maps in the Primo x OSU442-15 and JI1794 x Slow crosses.     

Fine mapping of a malting-quality QTL complex near the chromosome 4H S telomere in barley

Malting quality has long been an active objective in barley (Hordeum vulgare L.) breeding programs. However, it is difficult for breeders to manipulate malting-quality traits because of inheritance complexity and difficulty in evaluation of these quantitative traits. Quantitative trait locus (QTL) mapping provides breeders a promising basis with which to manipulate quantitative trait genes. A malting-quality QTL complex, QTL2, was mapped previously to a 30-cM interval in the short-arm telomere region of barley chromosome 4H in a Steptoe/Morex doubled haploid population by the North American Barley Genome Project, using an interval mapping method with a relatively low-resolution genetic map. The QTL2 complex has moderate effects on several malting-quality traits, including malt extract percentage (ME), -amylase activity (AA), diastatic power (DP), malt -glucan content (BG), and seed dormancy, which makes it a promising candidate gene source in malting barley-cultivar development. Fine mapping QTL2 is desirable for precisely studying barley malting-quality trait inheritance and for efficiently manipulating QTL2 in breeding. A reciprocal-substitution mapping method was employed to fine map QTL2. Molecular marker-assisted backcrossing was used to facilitate the generation of isolines. Fourteen different types of Steptoe isolines, including regenerated Steptoe and 13 different types of Morex isolines, including regenerated Morex, were made within a 41.5-cM interval between MWG634 and BCD265B on chromosome 4H. Duplicates were identified for 12 Steptoe and 12 Morex isoline types. The isolines together with Steptoe and Morex were grown variously at three locations in 2 years for a total of five field environments. Four malting-quality traits were measured: ME, DP, AA, and BG. Few significant differences were found between duplicate isolines for these traits. A total of 15 putative QTLs were mapped; three for ME, four for DP, six for AA, and two for BG. Background genotype seemed to make a difference in expression/detection of QTLs. Of the 15 QTLs identified, ten were from the Morex and only five from the Steptoe background. By combining the results from different years, field environments, and genetic backgrounds and taking into account overlapping QTL segments, six QTLs can be conservatively estimated: two each for ME and AA and one each for DP and BG with chromosome segments ranging from 0.7 cM to 27.9 cM. A segment of 15.8 cM from the telomere (MWG634–CDO669) includes all or a portion of all QTLs identified. Further study and marker-assisted breeding should focus on this 15.8-cM chromosome region.     

Association of RFLP markers with loci conferring broad-based resistance to the soybean cyst nematode (Heterodera glycines)

Soybean cyst nematode (SCN) is a major soybean yield-limiting pest. The present study was conducted to map broad-based SCN resistance loci from the cultivar Hartwig. Two-hundred F₂₃ lines derived from the cross Williams 82 x Hartwig were screened with a fourth-generation SCN inbred and 56 polymorphic molecular markers. Allele states and phenotypes were analyzed using stepwise regression and the model selection was made at P 0.01. Four unlinked RFLP markers (A006, A567, A487, A112) were associated with SCN resistance and the partial coefficient of determinations (R²) were 91%, 1%, 1%, and 1%. We have mapped a new, major SCN resistance locus (A006) and three minor loci (A567, A487, A112). This complete mapping will accelerate the transfer of broad-based resistance without linkage drag and aid in the determination of relationships among various SCN-resistant germplasm sources.     

Wheat chromosome 2D carries genes controlling the activity of two DNA-degrading enzymes

DNA-degrading enzymes of 24.0 kDa and 27.0 kDa were observed to have different activities in two common wheat (Triticum aestivum L.) cultivars, Wichita and Cheyenne. A substrate-based SDS-PAGE assay revealed that these two enzymes were much more active in Wichita than in Cheyenne. Genes controlling the activities of these two enzymes were localized on chromosome 2D by testing DNA-degrading activities in reciprocal chromosome substitution lines between Wichita and Cheyenne. While the allele on Wichita chromosome 2D stimulated the activities of the 24.0- and 27.0-kDa enzymes in Cheyenne, the allele on Cheyenne chromosome 2D did not reduce the activities of the 24-kDa and 27-kDa enzymes in Wichita. Whether these genes code for the DNA-degrading enzymes themselves or for factors that regulate the enzyme activities remains unknown.This work was supported in part by USDA-Competitive Research Grants Office grant No. 90-37140-5426 to P.S.B. Contribution from Agricultural Research Division, University of Nebraska. Journal Series Number 10304     

Carbohydrate Structural Units in Glycosphingolipids as Receptors for Gal and GalNAc Reactive Lectins

Glycosphingolipids (GSLs) contain many carbohydrate epitopes or crypto-glycotopes for Gal and GalNAc reactive lectins. Many of them are in the nervous system and function as important receptors in various life processes. During the past two decades, 11 mammalian structural units have been used to express the binding domain of applied lectins. They are: F, GalNAc1 3GalNAc; A, GalNAc1 3Gal; T, Gal1 3GalNAc; I, Gal1 3GlcNAc; II, Gal1 4GlcNAc; B, Gal1 3Gal; E, Gal1 4Gal; L, Gal1 4Glc; P, GalNAc1 3Gal; S, GalNAc1 4Gal, and Tn, GalNAc1 Ser(Thr). Although 10 of them occur in GSLs, only 3 (L , S , and T ) are found in human brain, and 2 (L and II ) are present in the inner structures of human blood group active GSLs. In the families of gangliosides, L and II represent 55% of the total structural units, while the other three units (T , P , and S ) constitute the rest. To facilitate the selection of lectins that could serve as structural probes, the carbohydrate binding specificities of Gal/GalNAc reactive lectins have been classified according to their highest affinity for the structural units and their binding properties expressed by decreasing order of reactivity. Hence, the binding relation between GSLs and Gal/GalNAc specific lectins can be established.     

Power of in silico QTL mapping from phenotypic, pedigree, and marker data in a hybrid breeding program

Most quantitative trait locus (QTL) mapping studies in plants have used designed mapping populations. As an alternative to traditional QTL mapping, in silico mapping via a mixed-model approach simultaneously exploits phenotypic, genotypic, and pedigree data already available in breeding programs. The statistical power of this in silico mapping method, however, remains unknown. Our objective was to evaluate the power of in silico mapping via a mixed-model approach in hybrid crops. We used maize (Zea mays L.) as a model species to study, by computer simulation, the influence of number of QTLs (20 or 80), heritability (0.40 or 0.70), number of markers (200 or 400), and sample size (600 or 2,400 hybrids). We found that the average power to detect QTLs ranged from 0.11 to 0.59 for a significance level of =0.01, and from 0.01 to 0.47 for =0.0001. The false discovery rate ranged from 0.22 to 0.74 for =0.01, and from 0.05 to 0.46 for =0.0001. As with designed mapping experiments, a large sample size, high marker density, high heritability, and small number of QTLs led to the highest power for in silico mapping via a mixed-model approach. The power to detect QTLs with large effects was greater than the power to detect QTL with small effects. We conclude that gene discovery in hybrid crops can be initiated by in silico mapping. Finding an acceptable compromise, however, between the power to detect QTL and the proportion of false QTL would be necessary.     

Flowering response of rice to photoperiod and temperature: a QTL analysis using a phenological model

In this study we have attempted to quantify the thermal and photoperiodical responses of rice (Oryza sativa L.) flowering time QTLs jointly by a date-of-planting field experiment of a mapping population, and a phenological model analysis that separately parameterizes the two responses, based on daily temperature, daily photoperiod and flowering date. For this purpose, the three-stage Beta model, which parameterizes the sensitivity to temperature (parameter ), the sensitivity to photoperiod (parameter ), and earliness under optimal conditions (10 h photoperiod at 30°C) (parameter G), was applied to Nipponbare × Kasalath backcross inbred lines that were transplanted on five dates. QTLs for the value were detected in the four known flowering time QTL (Hd1, Hd2, Hd6 and Hd8) regions, while QTLs for the G value were detected only in the Hd1 and Hd2 regions. This result was consistent with previous reports on near-isogenic lines (NILs) of Hd1, Hd2 and Hd6, where these loci were involved in photoperiod sensitivity, and where Hd1 and Hd2 conferred altered flowering under both 10 and 14 h photoperiods, while Hd6 action was only affected by the 14 h photoperiod. Hd8 was shown to control photoperiod sensitivity for the first time. Interestingly, Hd1 and Hd2 were associated with a QTL for the value, which might support the previous hypothesis that the process of photoinduction depends on temperature. These results demonstrate that our approach can effectively quantify environmental responses of flowering time QTLs without controlled environments or NILs.     

Mutants of Arabidopsis with alterations in seed lipid fatty acid composition

Summary A diverse collection of mutants of Arabidopsis with altered seed lipid compositions was isolated by determining the fatty acid composition of samples of seed from 3,000 mutagenized lines. A series of mutations was identified that caused deficiencies in the elongation of 181 to 201, desaturation of 181 to 182, and desaturation of 182 to 183. In each of these cases the wild type exhibited incomplete dominance over the mutant allele. These results, along with results from earlier studies, point to a major influence of gene dosage in determining the fatty acid composition of seed lipids. A mutation was also isolated that resulted in increased accumulation of 183. On the basis of the effects on fatty acid composition, the nature of the biochemical lesion in three of the mutants could be tentatively attributed to deficiencies in activities of specific enzymes. The other mutant classes had relatively less pronounced changes in fatty acid composition. These mutants may represent alterations in genes that regulate lipid metabolism or seed development. The availability of the mutants should provide new opportunities to investigate the mechanisms that control seed lipid fatty acid composition.Abbreviations FAMES (fatty acid methyl esters) - PC (phosphatidylcholine) - 181 (oleic acid) - 182 (linoleic acid) - 183 (linolenic acid) - 201 (eicosenoic acid) Supported in part by grants from the USDA (No. 89-37262-4388), USDA/NSF/DOE Plant Science Center Program, the U.S. Department of Energy (No. AC02-76ER01338), Karlshamns Research Foundation, and the WSU Research and Arts Committee     

Quantitative trait locus analysis of fungal disease resistance factors on a molecular map of grapevine

A full-sibling F1 population comprising 153 individuals from the cross of Regent × Lemberger was employed to construct a genetic map based on 429 molecular markers. The newly-bred red grapevine variety Regent has multiple field-resistance to fungal diseases inherited as polygenic traits, while Lemberger is a traditional fungus-susceptible cultivar. The progeny segregate quantitatively for resistances to Plasmopara viticola and Uncinula necator, fungal pathogens that threaten viticulture in temperate areas. A double pseudo-testcross strategy was employed to construct the two parental maps under high statistical stringency for linkage to obtain a robust marker frame for subsequent quantitative trait locus (QTL) analysis. In total, 185 amplified fragment length polymorphism, 137 random amplified polymorphic DNA, 85 single sequence repeat and 22 sequence characterized amplified region or cleaved amplified polymorphic sequence markers were mapped. The maps were aligned by co-dominant or doubly heterozygous dominant anchor markers. Twelve pairs of homologous linkage groups could be integrated into consensus linkage groups. Resistance phenotypes and segregating characteristics were scored as quantitative traits in three or four growing seasons. Interval mapping reproducibly localized genetic factors that correlated with fungal disease resistances to specific regions on three linkage groups of the maternal Regent map. A QTL for resistance to Uncinula necator was identified on linkage group 16, and QTLs for endurance to Plasmopara viticola on linkage groups 9 and 10 of Regent. Additional QTLs for the onset of berry ripening (veraison), berry size and axillary shoot growth were identified. Berry color segregated as a simple trait in this cross of two red varieties and was mapped as a morphological marker. Six markers derived from functional genes could be localized. This dissection of polygenic fungus disease resistance in grapevine allows the development of marker-assisted selection for breeding, the characterization of genetic resources and the isolation of the corresponding genes.Communicated by H.C. Becker     

Identification of two RAPD markers tightly linked with the Nicotiana debneyi gene for resistance to black root rot of tobacco

Linkage of randomly amplified polymorphic DNA (RAPD) markers with a single dominant gene for resistance to black root rot (Chalara elegans Nag Raj and Kendrick; Syn. Thielaviopsis basicola [Berk. and Broome] Ferraris) of tobacco (Nicotiana tabacum L.), which was transferred from N. debneyi Domin, was investigated in this study. There were 2594 repeatable RAPD fragments generated by 441 primers on DNAs of Delgold tobacco, a BC₅F₈ near isogenic line (NIL) carrying the resistance gene in a Delgold background, and PB19, the donor parent of the resistance gene. Only 7 of these primers produced eight RAPD markers polymorphic between Delgold and PB19, indicating there are few RAPD polymorphisms between them despite relatively dissimilar pedigrees. Five of the eight RAPD markers were not polymorphic between Delgold and the NIL. All of these markers proved to be unlinked with the resistance gene in F₂ linkage tests. Of the remaining three RAPD markers polymorphic between Delgold and the NIL, two were shown to be strongly linked with the resistance gene; one in coupling and the other in repulsion. Application of the two RAPDs in the elimination of linkage drag associated with the N. debneyi resistance gene and marker-assisted selection for the breeding of new tobacco cultivars with the resistance gene is discussed.     

Endogenous abscisic acid and 2-trans-abscisic acid in alternate bearing ‘Wilking’ mandarin trees

The relationship of abscisic acid (ABA) and 2-trans-abscisic acid (t-ABA) to alternate bearing has been examined in Wilking mandarin (Citrus reticulata Blanco) trees. Leaves, stems and buds of trees loaded with fruit (on trees) had 4.3, 6.0 and 2.2 fold higher ABA levels than the corresponding organs from off trees. Leaves had higher ABA levels than stems and buds in both on and off trees. t-ABA was non-detectable in Wilking leaf, stem and bud tissue. Amounts of t-ABA not exceeding 40% of the ABA content, were found in Shamouti and Valencia orange buds and in Wilking fruit peel.The elevated levels of ABA in on tree organs may reflect a stress imposed by the fruit overload.     

UDP-galactose:lactosylceramide α-galactosyltransferase activity in human placenta

The activity of UDP-Gal: LacCer galactosyltransferase in human placenta was studied by using crude homogenate and Triton CF-54 extract as the source of enzyme. Transfer of galactose to lactosylceramide was optimal in the presence of 0.1% Triton CF-54 and Mn²⁺ at pH 6.3, and the reaction product was susceptible to -galactosidase.Abbreviations LacCer lactosylceramide (Gal1-4Glc1-1Cer) - Gb₃ globotriaosylceramide (Gal1-4Gal1-4Glc1-1Cer) - Gb₄ globoside (GalNAc1-3Gal1-4Gal1-4Glc1-1Cer) - TLC thin-layer chromatography - GC/MS gas chromatography/mass spectrometry - NMR nuclear magnetic resonance - EDTA ethylenediamine tetraacetic acid - CHAPS 3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate     

Compartmentation of α- and β-Carbonic Anhydrases in Cells of Halo- and Alkalophilic Cyanobacteria Rhabdoderma lineare

The organization of carbonic anhydrase (CA) system in halo- and alkalophilic cyanobacteria Rhabdoderma lineare was studied by Western blot analysis and immunocytochemical electron microscopy. The presence of extracellular -CA (60 kD) in the glycocalyx, forming a tight sheath around the cell, and of two intracellular -CA is reported. One -CA (60 kD) is associated with polypeptides of photosystem II (PSII) and is a constitutive enzyme. Another -carbonic anhydrase (25 kD) was induced by low content of bicarbonate in the culture medium; this inducible CA was found in the fraction of total soluble proteins. The expressed synthesis of inducible -CA was accompanied by the increase in the intracellular pool of inorganic carbon, which suggests an important role of this enzyme in the functioning of CO₂-concentrating mechanism.     

Exploiting selective genotyping to study genetic diversity of resistance to Fusarium head blight in barley

Numerous barley cultivars from around the world have been identified as potential sources of Fusarium head blight (FHB) resistance genes. All of these cultivars exhibit partial resistance, and several mapping studies have shown that resistance to FHB is controlled by multiple genes. Successful development of barley cultivars with high levels of FHB resistance will require combining genes from multiple sources. We characterized five potential new sources of FHB resistance (AC Oxbow, Atahualpa, HOR211, PFC88209, and Zhedar#1) to determine if they contain new FHB resistance genes. Cluster analysis, using a set of 80 SSR markers distributed throughout the genome, showed that most of the new sources of resistance were not similar to three cultivars that have been used in previous FHB mapping studies (Chevron, Frederickson, and Gobernadora), with Atahualpa and HOR211 being the most dissimilar. By selective genotyping, we determined whether markers linked to six known FHB resistance quantitative trait loci (QTLs), discovered in other genotypes, explained variation for resistance in advanced breeding populations created from the new sources of resistance. Markers linked to four of the six known QTLs were associated with FHB severity in at least one of the populations. However, none of the six QTL regions were associated with variation for FHB severity in populations derived from crosses that utilized sources of resistance HOR211 or PFC88209. Selective genotyping is an efficient method for breeders to utilize current QTL information about disease resistance to search for new resistance genes.