Genetics Selection Evolution · 2020

The impact of training on data from genetically-related lines on the accuracy of genomic predictions for feed efficiency traits in pigs

Aliakbari A, Delpuech E, Labrune Y, Riquet J, Gilbert H

The authors compare several compositions of reference populations to predict feed-efficiency traits in pigs. Combining related lines has variable effects on accuracy and bias depending on traits and scenarios, of interest for programmes with small populations.

The question: Under which conditions can related lines be combined to build a reference population for genomic selection?
The approach: Comparison of genomic prediction scenarios with different training-population compositions, and evaluation of accuracy and bias.
What the article brings: The composition of the reference population and the traits targeted influence prediction performance.
The limits: Adding individuals from another line does not systematically improve prediction: the effect depends on the trait and the scenario.

Figures from the article

Fig. 1, The impact of training on data from genetically-related lines on the accuracy of genomic predictions for feed efficiency traits in pigs — Fig. 1. Design of scenarios to predict validation animals in HRFI(a) and LRFI(b) linesOriginal caption. Aliakbari A et al. (2020), Genetics Selection Evolution. CC BY 4.0

Fig. 2, The impact of training on data from genetically-related lines on the accuracy of genomic predictions for feed efficiency traits in pigs — Fig. 2. Correlations between GEBVp and GEBVw, and their SE as error bars for the HRFI(a) and LRFI(b) lines. *Significant difference with scenarios 1 (control) based on the Williams t-test at a 0.05 level. RFI residual feed intake, ADG average daily gain, FCR feed conversion ratio, DFI daily feed intake, BFT backfat thicknessOriginal caption. Aliakbari A et al. (2020), Genetics Selection Evolution. CC BY 4.0

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The impact of training on data from genetically-related lines on the accuracy of genomic predictions for feed efficiency traits in pigs

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