A map of the barley genome consisting of 295 loci was constructed. These loci include 152 cDNA restriction fragment length polymorphism (RFLP), 114 genomic DNA RFLP, 14 random amplified polymorphic DNA (RAPD), five isozyme, two morphological, one disease resistance and seven specific amplicon polymorphism (SAP) markers. The RFLP-identified loci include 63 that were detected using cloned known function genes as probes. The map covers 1,250 centiMorgans (cM) with a 4.2 cM average distance between markers. The genetic lengths of the chromosomes range from 124 to 223 cM and are in approximate agreement with their physical lengths. The centromeres were localized to within a few markers on all of the barley chromosomes except chromosome 5. Telomeric regions were mapped for the short (plus) arms of chromosomes 1, 2 and 3 and the long (minus) arm of chromosomes 7.

Quantitative trait locus (QTL) main effects and QTL by environment (QTL × E) interactions for seven agronomic traits (grain yield, days to heading, days to maturity, plant height, lodging severity, kernel weight, and test weight) were investigated in a two-row barley (Hordeura vulgare L.) cross, Harrington/TR306. A 127-point base map was constructed from markers (mostly RFLP) scored in 146 random double-haploid (DH) lines from the Harrington/TR306 cross. Field experiments involving the two parents and 145 random DH lines were grown in 1992 and/or 1993 at 17 locations in North America. Analysis of QTL was based on simple and composite interval mapping. Primary QTL were declared at positions where both methods gave evidence for QTL. The number of primary QTL ranged from three to six per trait, collectively explaining 34 to 52% of the genetic variance. None of these primary QTL showed major effects, but many showed effects that were consistent across environments. The addition of secondary QTL gave models that explained 39 to 80% of the genetic variance. The QTL were dispersed throughout the barley genome and some were detected in regions where QTL have been found in previous studies. Eight chromosome regions contained pleiotropic loci and/or linked clusters of loci that affected multiple traits. One region on chromosome 7 affected all traits except days to heading. This study was an intensive effort to evaluate QTL in a narrow-base population grown in a large set of environments. The results reveal the types and distributions of QTL effects manipulated by plant breeders and provide opportunities for future testing of marker-assisted selection. M OLECULAR MAPS of plant genomes, used in conjunction with phenotypic measurements, can provide information about chromosome regions that affect quantitative traits. Although knowing whether such regions represent individual quantitative trait loci (QTL)

Fusarium head blight (FHB) in barley and wheat, caused by Fusarium graminearum, is a continual problem worldwide. Primarily, FHB reduces yield and quality, and results in the production of the toxin deoxynivalenol (DON), which can affect food safety. Identification of QTLs for FHB severity, DON level and related traits heading-date (HD) and plant-height (HT) with consistent effects across a set of environments, would provide the basis for marker-assisted selection (MAS) and potentially increase the efficiency of selection for resistance. A segregating population of 75 double-haploid lines, developed from the three-way cross Zhedar 2/ND9712//Foster, was used for genome mapping and FHB severity evaluation. A linkage map of 214 RFLP, SSR and AFLP markers was constructed. Phenotypic data were collected in replicated field trials from five environments in two growing seasons. The data were analyzed using MQTL software to detect quantitative trait locus (QTL) x environment (E) interactions. Because of the presence of QTL x E, the MQM procedure in MAPQTL was applied to identify QTLs in single environments. We identified nine QTLs for FHB severity and five for low DON. Many of the disease-related QTLs identified were coincident with FHB QTLs identified in previous studies. Only two of the QTLs identified in this study were consistent across all five environments, and both were Zhedar 2 specific. Five of the FHB QTLs were associated with HD, and two were associated with HT. Regions that appear to be promising candidates for MAS and further genetic analysis include the two FHB QTLs on chromosome 2H and one on 6H, which were also associated with low DON and later heading-date in multiple environments. This study provides a starting point for manipulating Zhedar 2-derived resistance by MAS in barley to develop cultivars that will show effective resistance under disease pressure.

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Russian wheat aphid (RWA, Diuraphis noxia Kurdjumov) infestations reduce grain yield and quality and have caused more than $1 billion in losses for barley (Hordeum vulgare L.) and wheat (Triticum aestivum L.) in the western United States since 1986. Our objective was to map quantitative trait loci (QTLs) conferring resistance to RWA feeding damage in the germplasm line STARS‐9301B via polymerase chain reaction–based marker assays of 191 F2–derived F3 families from the cross ‘Morex’/STARS‐9301B. Morex is a susceptible six‐rowed malting barley. STARS‐9301B is a selection from RWA‐resistant Afghanistan introduction PI366450. Replicated seedling reactions to RWA infestations were used to phenotype each family based on a 1 to 9 visual rating of chlorosis. A total of 107 molecular markers was used to construct a linkage map. Quantitative trait loci analysis identified two major QTLs for resistance. The QTL on the short arm of chromosome 1H was associated with B‐hordein and explained 26% of the variation for RWA reaction. A QTL on chromosome 3H associated with EBmac0541 explained 38% of the variation. A minor QTL on chromosome 2H was associated with marker GBM1523 and explained 6% of the variation. A combined analysis indicated that the marker–QTL associations explained 59% of the phenotypic variation for RWA resistance. These markers linked with QTLs will be valuable in breeding for RWA resistance. Pyramiding the genes from STARS‐9301B with genes from other sources will be helpful for long‐term protection against RWA in barley.