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Bridging the gap between marker-assisted and genomic selection of heading time and plant height in hybrid wheat.


ABSTRACT: Based on data from field trials with a large collection of 135 elite winter wheat inbred lines and 1604 F1 hybrids derived from them, we compared the accuracy of prediction of marker-assisted selection and current genomic selection approaches for the model traits heading time and plant height in a cross-validation approach. For heading time, the high accuracy seen with marker-assisted selection severely dropped with genomic selection approaches RR-BLUP (ridge regression best linear unbiased prediction) and BayesC?, whereas for plant height, accuracy was low with marker-assisted selection as well as RR-BLUP and BayesC?. Differences in the linkage disequilibrium structure of the functional and single-nucleotide polymorphism markers relevant for the two traits were identified in a simulation study as a likely explanation for the different trends in accuracies of prediction. A new genomic selection approach, weighted best linear unbiased prediction (W-BLUP), designed to treat the effects of known functional markers more appropriately, proved to increase the accuracy of prediction for both traits and thus closes the gap between marker-assisted and genomic selection.

SUBMITTER: Zhao Y 

PROVIDER: S-EPMC4023446 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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Bridging the gap between marker-assisted and genomic selection of heading time and plant height in hybrid wheat.

Zhao Y Y   Mette M F MF   Gowda M M   Longin C F H CF   Reif J C JC  

Heredity 20140212 6


Based on data from field trials with a large collection of 135 elite winter wheat inbred lines and 1604 F1 hybrids derived from them, we compared the accuracy of prediction of marker-assisted selection and current genomic selection approaches for the model traits heading time and plant height in a cross-validation approach. For heading time, the high accuracy seen with marker-assisted selection severely dropped with genomic selection approaches RR-BLUP (ridge regression best linear unbiased pred  ...[more]

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