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.

No abstract

One option to achieving greater resiliency for barley production in the face of climate change is to explore the potential of winter and facultative growth habits: for both types, low temperature tolerance (LTT) and vernalization sensitivity are key traits. Sensitivity to short-day photoperiod is a desirable attribute for facultative types. In order to broaden our understanding of the genetics of these phenotypes, we mapped quantitative trait loci (QTLs) and identified candidate genes using a genome-wide association studies (GWAS) panel composed of 882 barley accessions that was genotyped with the Illumina 9K single-nucleotide polymorphism (SNP) chip. Fifteen loci including 5 known and 10 novel QTL/genes were identified for LTT—assessed as winter survival in 10 field tests and mapped using a GWAS meta-analysis. FR-H1, FR-H2, and FR-H3 were major drivers of LTT, and candidate genes were identified for FR-H3. The principal determinants of vernalization sensitivity were VRN-H1, VRN-H2, and PPD-H1. VRN-H2 deletions conferred insensitive or intermediate sensitivity to vernalization. A subset of accessions with maximum LTT were identified as a resource for allele mining and further characterization. Facultative types comprised a small portion of the GWAS panel but may be useful for developing germplasm with this growth habit.

Recently, researches have shown that the Brazilian savannah has a great potential to supply the demand for barley grains. The purpose of this study was to assess the genetic variability in 39 elite barley (Hordeum vulgare L.) genotypes based on the agro-morphological traits of a crop irrigated in the savannah system. An irrigation experiment in the design of complete randomized block with four replicates was conducted at Federal District -Brazil. The evaluated traits were: distance from the last knot to the rachis, distance from the flag leaf to rachis, spike length, number of grains by ear, flag leaf area, plant height, silking, lodging, grain yield, thousand-seed weight, protein content and grain commercial classification. After using analysis of variance the means were used to estimate the genetic dissimilarity among all genotypes pairs based on the Mahalanobis' generalized distance. Cluster analysis using genetic distance matrix was performed having Unweighted Pair Group Method using Arithmetic Means method (UPGMA) as the criteria. Highly significant differences were found among the genotypes for all traits evaluated. The high coefficient of genetic variation indicates the possibility of having genetic gains for all traits. The traits that most contributed to the variability were the flag leaf area and silking, while the protein content and lodging were the traits that contributed the least. Based on the cluster analysis, at least three major groups of similarity were found. There was a clustering trend of two and six-rowed materials. The most divergent genotypes were PFC 2005123, Antártica-1, Nandi and FM 404.

No abstract