Genome-based prediction of test cross performance in two subsequent breeding cycles

Hofheinz, N. and Borchardt, D. and Weissleder, K. and Frisch, M. (2012) Genome-based prediction of test cross performance in two subsequent breeding cycles. TAG Theoretical and Applied Genetics. 7 p..

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Genome-based prediction of genetic values is expected to overcome shortcomings that limit the application of QTL mapping and marker-assisted selection in plant breeding. Our goal was to study the genome-based prediction of test cross performance with genetic effects that were estimated using genotypes from the preceding breeding cycle. In particular, our objectives were to employ a ridge regression approach that approximates best linear unbiased prediction of genetic effects, compare cross validation with validation using genetic material of the subsequent breeding cycle, and investigate the prospects of genome-based prediction in sugar beet breeding. We focused on the traits sugar content and standard molasses loss (ML) and used a set of 310 sugar beet lines to estimate genetic effects at 384 SNP markers. In cross validation, correlations [0.8 between observed and predicted test cross performance were observed for both traits. However, in validation with 56 lines from the next breeding cycle, a correlation of 0.8 could only be observed for sugar content, for standard ML the correlation reduced to 0.4. We found that ridge regression based on preliminary estimates of the heritability provided a very good approximation of best linear unbiased prediction and was not accompanied with a loss in prediction accuracy.

Item Type: Article
Uncontrolled Keywords: Plant Breeding, Breeding Cycles, QTL Mapping
Author Affiliation: Institute of Agronomy and Plant Breeding II, Justus Liebig University, 35392 Giessen, Germany
Subjects: Crop Improvement > Genetics/Genomics
Crop Improvement > Plant Breeding
Divisions: General
Depositing User: Mr Siva Shankar
Date Deposited: 27 Jul 2012 04:44
Last Modified: 27 Jul 2012 04:45
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