Prediction of heterosis using genome-wide SNP-marker data: application to egg
production traits in white Leghorn crosses |
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Authors: | E N Amuzu-Aweh P Bijma B P Kinghorn A Vereijken J Visscher J AM van Arendonk H Bovenhuis |
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Institution: | 1.Animal Breeding and Genomics Centre,
Wageningen University and Research Centre, Wageningen, The
Netherlands;2.Department of Animal Breeding and Genetics,
Swedish University of Agricultural Sciences, Uppsala, Sweden;3.School of Environmental and Rural Science,
University of New England, Armidale, Australia;4.Institut de Sélection Animale B.V.,
Hendrix Genetics, Boxmeer, The Netherlands |
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Abstract: | Prediction of heterosis has a long history with mixed success, partly due to low numbers
of genetic markers and/or small data sets. We investigated the prediction of heterosis
for egg number, egg weight and survival days in domestic white Leghorns, using
∼400 000 individuals from 47 crosses and allele frequencies on
∼53 000 genome-wide single nucleotide polymorphisms (SNPs). When heterosis is
due to dominance, and dominance effects are independent of allele frequencies, heterosis
is proportional to the squared difference in allele frequency (SDAF) between parental pure
lines (not necessarily homozygous). Under these assumptions, a linear model including
regression on SDAF partitions crossbred phenotypes into pure-line values and heterosis,
even without pure-line phenotypes. We therefore used models where phenotypes of crossbreds
were regressed on the SDAF between parental lines. Accuracy of prediction was determined
using leave-one-out cross-validation. SDAF predicted heterosis for egg number and weight
with an accuracy of ∼0.5, but did not predict heterosis for survival days. Heterosis
predictions allowed preselection of pure lines before field-testing, saving
∼50% of field-testing cost with only 4% loss in heterosis. Accuracies
from cross-validation were lower than from the model-fit, suggesting that accuracies
previously reported in literature are overestimated. Cross-validation also indicated that
dominance cannot fully explain heterosis. Nevertheless, the dominance model had
considerable accuracy, clearly greater than that of a general/specific combining
ability model. This work also showed that heterosis can be modelled even when pure-line
phenotypes are unavailable. We concluded that SDAF is a useful predictor of heterosis in
commercial layer breeding. |
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Keywords: | heterosis prediction dominance hybrid vigour allele frequency difference egg production white Leghorn |
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