Recent developments in genomic selection for minor gene quantitative disease resistance plant breeding
To speed up the development of improved crop varieties, genomics assisted plant breeding
is becoming an important tool. With traditional breeding and marker assisted selection, there
have been several achievements in breeding for diseases resistance. Most research for
disease resistance has been focused on major disease resistance genes which are highly
effective although very vulnerable to breakdown with rapid changes in pathogenic races. In
contrast, breeding for minor gene quantitative resistance can produce more durable plant …
is becoming an important tool. With traditional breeding and marker assisted selection, there
have been several achievements in breeding for diseases resistance. Most research for
disease resistance has been focused on major disease resistance genes which are highly
effective although very vulnerable to breakdown with rapid changes in pathogenic races. In
contrast, breeding for minor gene quantitative resistance can produce more durable plant …
To speed up the development of improved crop varieties, genomics assisted plant breeding is becoming an important tool. With traditional breeding and marker assisted selection, there have been several achievements in breeding for diseases resistance. Most research for disease resistance has been focused on major disease resistance genes which are highly effective although very vulnerable to breakdown with rapid changes in pathogenic races. In contrast, breeding for minor gene quantitative resistance can produce more durable plant varieties although it is very slow and challenging breeding. As the genetic architecture of the plant disease resistance shifts from single major R genes to many minor quantitative genes, the most appropriate approach for molecular plant breeding is genomic selection (GS) than marker assisted selection or conventional breeding. With the advent of new genomic tools, GS has emerged as one of the most important approaches for predicting genotype performance to improve genetically complex quantitative traits. Consequently, GS helps to accelerate the rate of genetic gain in breeding by using whole genome sequence data to predict the breeding value of offspring. GS breeding for quantitative resistance will therefore necessitate whole genome prediction models and selection methodology as implemented for classical complex traits. With the implementation of GS for yield and other economically important traits, whole genome marker profiles are available for the entire set of breeding lines, enabling genomic selection for disease resistance with no additional direct cost. Therefore, recent developments in GS including a two stream GS + de novo GWAS models (GS+) and GS for combined highest level of quantitative resistance with R genes (QR +R gene) individuals are expected to further advance disease resistance plant breeding and briefly discussed.
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