The limited population sizes used in many quantitative trait locus (QTL) detection experiments can lead to underestimation of QTL number, overestimation of QTL effects, and failure to quantify QTL interactions. We used the barley/barley stripe rust pathosystem to evaluate the effect of population size on the estimation of QTL parameters. We generated a large (n = 409) population of doubled haploid lines derived from the cross of two inbred lines, BCD47 and Baronesse. This population was evaluated for barley stripe rust severity in the Toluca Valley, Mexico, and in Washington State, USA, under field conditions. BCD47 was the principal donor of resistance QTL alleles, but the susceptible parent also contributed some resistance alleles. The major QTL, located on the long arm of chromosome 4H, close to the Mlo gene, accounted for up to 34% of the phenotypic variance. Subpopulations of different sizes were generated using three methods-resampling, selective genotyping, and selective phenotyping-to evaluate the effect of population size on the estimation of QTL parameters. In all cases, the number of QTL detected increased with population size. QTL with large effects were detected even in small populations, but QTL with small effects were detected only by increasing population size. Selective genotyping and/or selective phenotyping approaches could be effective strategies for reducing the costs associated with conducting QTL analysis in large populations. The method of choice will depend on the relative costs of genotyping versus phenotyping.
Resistance to Fusarium head blight (FHB), deoxynivalenol (DON) accumulation, and kernel discoloration (KD) in barley are difficult traits to introgress into elite varieties because current screening methods are laborious and disease levels are strongly influenced by environment. To improve breeding strategies directed toward enhancing these traits, we identified genomic regions containing quantitative trait loci (QTLs) associated with resistance to FHB, DON accumulation, and KD in a breeding population of F(4:7) lines using restriction fragment length polymorphic (RFLP) markers. We evaluated 101 F(4:7) lines, derived from a cross between the cultivar Chevron and an elite breeding line, M69, for each of the traits in three or four environments. We used 94 previously mapped RFLP markers to create a linkage map. Using composite interval mapping, we identified 10, 11, and 4 QTLs associated with resistance to FHB, DON accumulation, and KD, respectively. Markers flanking these QTLs should be useful for introgressing resistance to FHB, DON accumulation, and KD into elite barley cultivars.
The identification and location of sources of genetic resistance to plant diseases are important contributions to the development of resistant varieties. The combination of different sources and types of resistance in the same genotype should assist in the development of durably resistant varieties. Using a doubled haploid (DH), mapping population of barley, we mapped a qualitative resistance gene ( Rpsx) to barley stripe rust in the accession CI10587 (PI 243183) to the long arm of chromosome 1(7H). We combined the Rpsx gene, through a series of crosses, with three mapped and validated barley stripe rust resistance QTL alleles located on chromosomes 4(4H) (QTL4), 5(1H) (QTL5), and 7(5H) (QTL7). Three different barley DH populations were developed from these crosses, two combining Rpsx with QTL4 and QTL7, and the third combining Rpsx with QTL5. Disease severity testing in four environments and QTL mapping analyses confirmed the effects and locations of Rpsx, QTL4, and QTL5, thereby validating the original estimates of QTL location and effect. QTL alleles on chromosomes 4(4H) and 5(1H) were effective in decreasing disease severity in the absence of the resistance allele at Rpsx. Quantitative resistance effects were mainly additive, although magnitude interactions were detected. Our results indicate that combining qualitative and quantitative resistance in the same genotype is feasible. However, the durability of such resistance pyramids will require challenge from virulent isolates, which currently are not reported in North America.
Multi-environment multi-QTL mixed models were used in a GWAS context to identify QTL for disease resistance. The use of mega-environments aided the interpretation of environment-specific and general QTL. Diseases represent a major constraint for barley (Hordeum vulgare L.) production in Latin America. Spot blotch (caused by Cochliobolus sativus), stripe rust (caused by Puccinia striiformis f.sp. hordei) and leaf rust (caused by Puccinia hordei) are three of the most important diseases that affect the crop in the region. Since fungicide application is not an economically or environmentally sound solution, the development of durably resistant varieties is a priority for breeding programs. Therefore, new resistance sources are needed. The objective of this work was to detect genomic regions associated with field level plant resistance to spot blotch, stripe rust, and leaf rust in Latin American germplasm. Disease severities measured in multi-environment trials across the Americas and 1,096 SNPs in a population of 360 genotypes were used to identify genomic regions associated with disease resistance. Optimized experimental design and spatial modeling were used in each trial to estimate genotypic means. Genome-Wide Association Mapping (GWAS) in each environment was used to detect Quantitative Trait Loci (QTL). All significant environment-specific QTL were subsequently included in a multi-environment-multi-QTL (MEMQ) model. Geographical origin and inflorescence type were the main determinants of population structure. Spot blotch severity was low to intermediate while leaf and stripe rust severity was high in all environments. Mega-environments were defined by locations for spot blotch and leaf rust. Significant marker-trait associations for spot blotch (9 QTL), leaf (6 QTL) and stripe rust (7 QTL) and both global and environment-specific QTL were detected that will be useful for future breeding efforts.
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