Reaction-norm analysis of neonatal lamb mortality suggests heritability varies with cold-stress: an example in the Elsenburg Merino selection lines
C. L. Nel
A B * , Y. Steyn C , A. R. Gilmour D , D. Waters E , S. A. Clark E , J. H. J. van der Werf E , A. A. Swan F , K. Dzama B and S. W. P. Cloete B
+ Author Affiliations
- Author Affiliations
A Directorate: Animal Sciences, Western Cape Department of Agriculture, Elsenburg 7607, South Africa.
B Department of Animal Sciences, Stellenbosch University, Stellenbosch 7602, South Africa.
C Department of Animal and Dairy Science, University of Georgia, Athens, GA 30605, USA.
D 11 Holman Way, Orange, NSW 2800, Australia.
E School of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia.
F Animal Genetics & Breeding Unit, University of New England, Armidale, NSW 2350, Australia.
Animal Production Science 63(11) 1017-1030 https://doi.org/10.1071/AN22464
Submitted: 14 December 2022 Accepted: 16 March 2023 Published: 13 April 2023
© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)
Abstract
Context: Coping with high levels of cold stress should be beneficial to survival of lambs, given the high mortality rate associated with severe winter storms. The Elsenburg Merino selection experiment involved divergent selection for reproduction. Phenotypic results comparing the positively selected H-Lines and negatively selected L-Lines suggested that cold-stress adaption could have contributed to the favourable genetic trends for survival of H-Line lambs. However, observing the genetic merit of better adapted animals depends on the presence of cold stress at the time of recording. A genotype by environment component (G × E) could, thus, be important when assessing survival/mortality phenotypes.
Aim: This study proposed the genetic analysis of this possible G × E component and compared the H- and L-Lines in this regard.
Methods: The sire model allowed the use of progeny phenotypes for neonatal mortality recorded during different levels of cold stress, and the possible G × E could be investigated through the reaction-norm approach. Genetic parameters were evaluated as random regression components by implementing a Gibbs sampling approach. A data set of 5723 individual lamb records was analysed as the progeny of 213 sires.
Results: A modelled G × E component played an important role in mortality outcomes, with the mean estimate (and 95% confidence interval) for the slope (
) only marginally smaller than the corresponding estimate for the intercept (
). The reaction-norm model showed a higher heritability (h2 ± posterior standard deviation) for mortality at 3 days of age during high cold-stress (0.22 ± 0.16 at ~1100 KJm−2h−1) than during mild (0.13 ± 0.10 at ~960 KJm−2h−1) conditions, suggesting a greater ability to discriminate between sires at increasing stress levels.
Conclusions: Failure to account for this G × E component putatively contributes to the low h2 commonly reported for survival traits. The higher h2 at increased levels of cold stress could have played an important part in the higher survival of the H-Line progeny, who were better at coping with cold, wet and windy conditions.
Implications: Larger studies representing a wider environmental trajectory are recommended. This should be very feasible since cold stress can be derived from commonly available weather-station data.
Keywords: chill index, early mortality, genotype by environment interaction, Gibbs sampling, lamb survival, random regression, sheep, welfare.
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