2013-01-25

Simulation of different strategies to implement genomic selection in plant breeding

Our submitted abstract for the VIPCA conference.

Gorjanc G, Crossa J, Dreisigacker S, Autrique E, Hickey J

Genomic information provides a rich resource for plant improvement. The greatest advantage of genomic information is achived when used early in a programme. The aim of this contribution was to present different ways of utilizing genomic information in cross and self pollinated species early in the bi-parental population (BP) cycle in the F2 generation by simulation. Simulation mimicked a real breeding programme with BP of different degree of relationship. Simulated trait heritability was 0.5. Predictions were always within a focal BP (BPX) avoiding the effect of inflated accuracy due to population structure. Measure of interest was the correlation between true and predicted additive genetic value (accuracy). Predictions were based on training on collected data within BPX, from BP having one parent in common with BPX (BPPC), from BP having one grand-parent in common with BPX (BPGC), and from unrelated BP (BPUR). Results show that genomic predictions can be accurate early in the cycle. Accurate predictions within the BPX can be obtained with a small number of markers and moderate phenotyping of F2 derived lines. With 200 markers and 50 phenotypes accuracy was around 0.60 and increased to 0.80 with 100 phenotypes. Use of information from relatives requires denser marker panels and more phenotypes to properly model the expanding number of linkage blocks in progressively distantly related BP. However, these requirements can be spread over many related BP reducing the cost per BP. For example accuracy of 0.6 can be achieved by using 1,000 markers and 50 phenotypes from 4 BPPC and 40 BPUR or by using 10,000 markers and 50 phenotypes from 8 BPGC and 50 BPUR. Requirement for denser marker panels increases needed investment, which can be offset by proper use of imputation method making the whole procedure cost effective for real applications.

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