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Genetics of heat stress in purebred and crossbred pigs from different states using BLUP or ssGBLUP
The objective of this study was to evaluate potential of regular and genomic selection to mitigate impacts of heat stress in swine populations. Phenotypes of body weight were available for purebred Duroc nucleus animals from farms in North Carolina (n=151,336) and Texas (n=55,897); and for commercial crossbred animals (Duroc x Landrace-Large White), hot carcass weight was available from North Carolina (n=141,756) and Missouri (n=86,435). Pedigree file combined the two populations and included 553,442 animals. Genotypic information was available for 8,232 Duroc animals, for 60k SNP. Analyses were done with an animal model as either single- or two-trait model using phenotypes measured in different states as separate traits. Additionally, reaction norm models were fitted for one or two traits using heat load index as covariable. Heat load was calculated as temperature humidity index above 70 degrees (equivalent to 21oC and 100% relative humidity) and was averaged over 30 days prior to data collection. Variance components were estimated by AIREML and (genomic) estimated breeding values ((G)EBV) by BLUP or single-step GBLUP (ssGBLUP). Validation was assessed for 146 genotyped sires with progeny in last generation. Accuracy was calculated as correlation of (G)EBV from reduced data (all animals, except the last generation) and (G)EBV with complete data. Heritabilities for purebred animals were similar across states (varying from 0.23 to 0.26), and reaction norm models did not show evidence of heat stress effect. Genetic correlations between states and heat loads were always high (>0.91). For crossbred animals, no difference in heritabilities were found in single- or two-trait analysis (from 0.17 to 0.18), and genetic correlations between states were moderate (0.43). In the reaction norm for crossbreds, heritabilities ranged from 0.15 to 0.30 and genetic correlation between heat loads were as low as 0.36. Accuracies with genomic information by ssGBLUP were on average 25% higher than by BLUP. Accuracies were higher in two-trait reaction norm models and at extreme heat load values. Impacts of seasonality are evident only for crossbred animals. Genomic information can help mitigating heat stress in swine by identifying superior sires more resistance to heat stress.
Keywords: Genotype-by-Environment Interaction, Heat Stress, Single-Step GBLUP