|Jo, Young-Ki - UNIV OF WISCONSIN|
|Sim, Sungchur - UNIV OF WISCONSIN|
|Jung, Geunhwa - UNIV OF WISCONSIN|
Submitted to: Theoretical and Applied Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 5, 2008
Publication Date: June 3, 2008
Citation: Jo, Y., Barker, R.E., Pfender, W.F., Warnke, S.E., Sim, S., Jung, G. 2008. Comparative Analysis of Multiple Disease Resistance in Ryegrass and Cereal Crops. Theoretical and Applied Genetics. 117(4):531-543. Interpretive Summary: Perennial ryegrass (Lolium perenne) is one of the important forage and turf grasses in temperate climate zones in the world. Rust diseases are particularly important for forage-type perennial ryegrass and seed production, directly affecting quality and yield. Use of host resistance would be a more practical way to manage rust than fungicide applications. An understanding of genetic relationships among species could perhaps assist breeders in turfgrass improvement programs. Comparative genomic analysis of quantitative disease resistance loci identified in ryegrass were conducted with loci previously reported in cereal crops to challenge the hypothesis that pathogen-specific disease resistance loci and gene loci associated with resistance to multiple diseases are conserved between ryegrass and cereal crops. Disease resistance is a complex quantitative trait that limits geographic distribution of ryegrass. Quantitative trait loci (QTLs), a term used for identifying multiple genes controlling a genetic trait, were found in 16 ryegrass genetic regions that relate to resistance of the four pathogens tested and they mapped to six of seven genetic linkage groups (LGs) of ryegrass. These QTLs were compared with resistance loci for the same or related pathogens previously identified in cereal crops. Combining multiple quantitative resistance genes responding to a single pathogen species will provide durable resistance without increasing selection pressure on the pathogen to overcome resistance. Particularly, utilization of broad-spectrum resistance loci responding to diverse pathogen species is of great interest for perennial corps that have long rotation cycle, and they might serve potential markers for marker-assisted selection to improve disease resistance in future ryegrass breeding programs.
Technical Abstract: Perennial ryegrass (Lolium perenne) is one of the most important forage crops in Europe and Australia and also a popular turfgrass in North America. Improvement of resistance to multiple diseases is desirable for such a perennial crop which has long rotation cycles. Quantitative trait loci (QTL) analysis based on a three-generation interspecific ryegrass population was conducted to define partial resistance to four different fungal diseases: leaf spot (Bipolaris sorokiniana), gray leaf spot (Magneporthe grisea), crown rust (Puccinia coronata), and stem rust (Puccinia graminis). A total of 16 QTLs conferring disease resistance to these four pathogens were mapped on six of seven genetic linkage groups (LGs). These QTLs were compared with disease resistance loci for the same or related pathogens previously in cereal crops, using the rice physical map as a reference map. Many pathogen-specific QTLs identified in ryegrass were conserved at corresponding genome positions in cereal crops. One genomic region associated with QTL for multiple disease resistances was found on ryegrass LG 4, which has a syntenic relationship with a genomic region of rice chromosome 3 where broad-spectrum resistance loci were found previously. This comparative QTL analysis integrating the ryegrass genetic map and rice physical map indicated the conservation of pathogen-specific partial resistance and broad-spectrum resistance to multiple diseases between ryegrass and cereal crops. These results indicate that genetic information on disease resistance genes identified in rice or other cereal crops can be transferred into understudied ryegrass so that breeding for multiple disease resistant cultivars can be greatly facilitated via marker-assisted selection and gene pyramiding approaches.