Ravi P. Singh

Agricultural crops benefit from resistance to pathogens that endures over years and generations of both pest and crop. Durable disease resistance, which may be partial or complete, can be controlled by several genes. Some of the most devastating fungal pathogens in wheat are leaf rust, stripe rust, and powdery mildew. The wheat gene Lr34 has supported resistance to these pathogens for more than 50 years. Lr34 is now shared by wheat cultivars around the world. Here, we show that the LR34 protein resembles adenosine triphosphate-binding cassette transporters of the pleiotropic drug resistance subfamily. Alleles of Lr34 conferring resistance or susceptibility differ by three genetic polymorphisms. The Lr34 gene, which functions in the adult plant, stimulates senescence-like processes in the flag leaf tips and edges.

Las royas del trigo se incluyen entre las enfermedades mas estudiadas de las plantas. A partir de las obras de Tozzeni y Fontana en 1767, existe una lista muy extensa de publicaciones cientificas sobre los agentes patogenos de las royas, las enfermedades que provocan y la resistencia a ellas. Con el proposito de proporcionar una sola fuente de informacion para el cientifico o estudiante, resenamos literatura cientifica reciente sobre los patogenos Puccinia recondita f.sp. tritici P. graminis f.sp. tritici y P.striiformis f.sp. tritici, las royas de la hoja del tallo y lineal y la resistencia a esos patogenos. Despues de una breve historia y la descripcion general de las royas del trigo, se presenta una sintesis detallada de cada una de las royas, su epidemiologia, sus hospedantes (y la resistencia de estos) y sus agentes patogenos (incluida su virulencia). Se analizan los metodos para combatir esas enfermedades mediante la resistencia, los productos quimicos y las practicas de cultivo. Se describen tambien las tecnicas empleadas en la produccion, recoleccion y almacenamiento del inoculo; los metodos de inoculacion, la evaluacion de la enfermedad, la determinacion de la resistencia; la epidemiologia, las perdidas de rendimiento y los estudios de razas fisiologicas; el aislamiento de los genes de la resistencia y la utilizacion de la misma

Abstract Advances in genomics have expedited the improvement of several agriculturally important crops but similar efforts in wheat ( Triticum spp.) have been more challenging. This is largely owing to the size and complexity of the wheat genome 1 , and the lack of genome-assembly data for multiple wheat lines 2,3 . Here we generated ten chromosome pseudomolecule and five scaffold assemblies of hexaploid wheat to explore the genomic diversity among wheat lines from global breeding programs. Comparative analysis revealed extensive structural rearrangements, introgressions from wild relatives and differences in gene content resulting from complex breeding histories aimed at improving adaptation to diverse environments, grain yield and quality, and resistance to stresses 4,5 . We provide examples outlining the utility of these genomes, including a detailed multi-genome-derived nucleotide-binding leucine-rich repeat protein repertoire involved in disease resistance and the characterization of Sm1 6 , a gene associated with insect resistance. These genome assemblies will provide a basis for functional gene discovery and breeding to deliver the next generation of modern wheat cultivars.

The availability of dense molecular markers has made possible the use of genomic selection (GS) for plant breeding. However, the evaluation of models for GS in real plant populations is very limited. This article evaluates the performance of parametric and semiparametric models for GS using wheat (Triticum aestivum L.) and maize (Zea mays) data in which different traits were measured in several environmental conditions. The findings, based on extensive cross-validations, indicate that models including marker information had higher predictive ability than pedigree-based models. In the wheat data set, and relative to a pedigree model, gains in predictive ability due to inclusion of markers ranged from 7.7 to 35.7%. Correlation between observed and predictive values in the maize data set achieved values up to 0.79. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction is an important component of genetic variability. These results indicate that GS in plant breeding can be an effective strategy for selecting among lines whose phenotypes have yet to be observed.