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SYNBREED A3: Genomic Performance Prediction

Project


Project code: 0315528D
Contract period: 01.09.2009 - 31.08.2014
Budget: 1,822,688 Euro
Purpose of research: Basic research

An efficient prediction of the performance of untested hybrids in hybrid breeding and of targeted matings in pure line breeding has great potential to enhance the output of breeding programs. Hitherto, performance prediction was exclusively based on phenotypic information from relatives and, therefore, was very resource consuming and of limited precision. Based on initial experimental results on the application of “genomic selection” in pure line breeding, a paradigm shift in plant and animal breeding seems very promising, where prediction based on phenotypic information is complemented or even substituted by genomic information. In the case of crosses, besides additive gene effects, dominance and epistatic effects must also be considered in the performance prediction. In this project, we plan to extend the current quantitative-genetic models for taking into account all these types of effects. In project A1, statistical tools will be developed to analyze data sets generated by SNP- genotyping and phenotyping in maize, chicken and dairy cattle, the species in which hybrid cultivars or breeds are being commercially exploited. Cross-validation will be used to examine the precision of genomic prediction. For chicken, the genomic prediction methods based on SNP data as well as biomarkers developed in project T4 will be combined to predict hatching ability. In addition, simulated data will be used to investigate the effects of marker density and the structure of relatedness on the goodness of prediction. Based on the results, we plan to develop strategies for optimal integration of genomic prediction in breeding programs for the above-mentioned species in particular and for plant and animal breeding in general. Sub-projects: A3.1: Genomic prediction in maize A3.2: Genomic prediction in chicken A3.3: Genomic prediction in cattle

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