Using single-step genomic best linear unbiased predictor to enhance the mitigation of seasonal losses due to heat stress in pigs

Abstract

The purposes of this study were to analyze the impact of seasonal losses due to heat stress in pigs from different breeds raised in different environments and to evaluate the accuracy improvement from adding genomic information to genetic evaluations. Data were available for 2 different swine populations: purebred Duroc animals raised in Texas and North Carolina and commercial crosses of Duroc and F females (Landrace × Large White) raised in Missouri and North Carolina; pedigrees provided links for animals from different states. Pedigree information was available for 553,442 animals, of which 8,232 pure breeds were genotyped. Traits were BW at 170 d for purebred animals and HCW for crossbred animals. Analyses were done with an animal model as either single- or 2-trait models using phenotypes measured in different states as separate traits. Additionally, reaction norm models were fitted for 1 or 2 traits using heat load index as a covariable. Heat load was calculated as temperature-humidity index greater than 70 and was averaged over 30 d prior to data collection. Variance components were estimated with average information REML, and EBV and genomic EBV (GEBV) with BLUP or single-step genomic BLUP (ssGBLUP). Validation was assessed for 146 genotyped sires with progeny in the last generation. Accuracy was calculated as a correlation between EBV and GEBV using reduced data (all animals, except the last generation) and using complete data. Heritability estimates for purebred animals were similar across states (varying from 0.23 to 0.26), and reaction norm models did not show evidence of a heat stress effect. Genetic correlations between states for heat loads were always strong (>0.91). For crossbred animals, no differences in heritability were found in single- or 2-trait analysis (from 0.17 to 0.18), and genetic correlations between states were moderate (0.43). In the reaction norm for crossbreeds, heritabilities ranged from 0.15 to 0.30 and genetic correlations between heat loads were as weak as 0.36, with heat load ranging from 0 to 12. Accuracies with ssGBLUP were, on average, 25% greater than with BLUP. Accuracies were greater in 2-trait reaction norm models and at extreme heat load values. Impacts of seasonality are evident only for crossbred animals. Genomic information can help producers mitigate heat stress in swine by identifying superior sires that are more resistant to heat stress.

Genomics of Heat Tolerance in Reproductive Performance Investigated in Four Independent Maternal Lines of Pigs

“…These results are in partial agreement with Lewis and Bunter ( 2011 ), who did not observe relevant differences in heritability estimates on TNB, NBA and ABW expressed under different year seasons. As for the higher heritability in comfortable conditions, Silva et al ( 2014 ) reported higher heritability estimates for TNB in contemporary groups with better performance and Fragomeni et al ( 2016b ) found a similar trend when assessing HT based on body weight of purebred Duroc individuals.…”

“…In general, genetic analysis of HT in growing/finishing pigs are based on a heat-load function for live or carcass weight (Zumbach et al, 2008a , b ; Fragomeni et al, 2016a ). HT based on growth traits is moderately heritable (Fragomeni et al, 2016a , b ), but there is a gap in knowledge on the genetic mechanisms of HS response in sows since only differences between maternal genetic lines have been reported (Peltoniemi et al, 1999 ; Bloemhof et al, 2008 ). Furthermore, the genetic correlations among reproductive traits expressed in different seasons of the year are lower than unity (Lewis and Bunter, 2011 ).…”

Improving accuracy of direct and maternal genetic effects in genomic evaluations using pooled boar semen: a simulation study1

“…As a common practice, variance components obtained based only on phenotypes and pedigree were used to compute both BLUP and ssGBLUP (Fragomeni et al, 2016;Oliveira et al, 2019). Accuracies of breeding values for traditional and genomic evaluations for single-boar semen and pooled semen considering unknown and known boar information are in Tables 2 and 3, respectively.…”

Genomic prediction of growth traits for pigs in the presence of genotype by environment interactions using single‐step genomic reaction norm model

“…Reproductive techniques such as artificial insemination have allowed elite animals to transmit their genetic merit in various environments, which could lead to the phenomenon of G × E interactions. Previous reports have shown the existence of G × E interactions in pigs (Fragomeni et al., 2016; Knap & Su, 2008; Silva et al., 2014).…”