Genomic predictions and GWAS for heat tolerance in pigs based on reaction norm models with performance records and data from public weather stations considering censored temperature thresholds

Authors: FRIETAS, PEDRO - Purdue University; Johnson, Jay; TIEZZI, FRANCESCO - University Of Florence; HUANG, Y. - Smithfield Foods, Inc; SCHINCKEL, ALLAN - Purdue University; BRITO, LUIZ - Purdue University

Submitted to: Journal of Animal Breeding and Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/17/2023
Publication Date: 11/27/2023
Citation: Frietas, P.H., Johnson, J.S., Tiezzi, F., Huang, Y., Schinckel, A.P., Brito, L.F. 2023. Genomic predictions and GWAS for heat tolerance in pigs based on reaction norm models with performance records and data from public weather stations considering censored temperature thresholds. Journal of Animal Breeding and Genetics. https://doi.org/10.1111/jbg.12838.
DOI: https://doi.org/10.1111/jbg.12838

Interpretive Summary: Heat stress events are increasing in frequency and severity, and this negatively impacts swine productivity and welfare. As such, swine producers are increasingly interested in new strategies to improve heat stress resilience in their herds. The present study sought to assess the applicability of using pig traits that are routinely recorded in production environments to develop breeding values for heat stress resilience in pigs based upon genomic information. It was determined that developing accurate genomic predictions for heat stress resilience in pigs using routinely recorded traits is possible. Information and methods developed through this study may be useful for implementing genomic selection for heat stress resilience in swine herds.

Technical Abstract: Genetic improvement of livestock productivity has resulted in greater production of metabolic heat which might result in greater susceptibility to heat stress. Various studies have demonstrated that there is genetic variability for heat tolerance and genetic selection for more heat tolerant individuals is possible. The rate of genetic progress tends to be greater when genomic information is added to the analyses as more accurate breeding values can be obtained for young individuals. Therefore, this study aimed (1) to evaluate the predictive ability of breeding values for heat tolerance based on routinely-recorded traits using genomic information, and (2) to investigate the genetic background of heat tolerance based on a single-step genome-wide association studies using economically important traits related to body composition, growth, and reproduction in Large White pigs. Pedigree information was available for 265,943 animals, and genotypes for 8,686 animals. The studied traits included ultrasound backfat thickness (BFT), ultrasound muscle depth (MDP), piglet weaning weight (WW), off-test weight (OTW), interval between farrowing (IBF), total number of piglets born (TNB), number of piglets born alive (NBA), number of piglets born dead (NBD), number of piglets weaned (WN), and weaning to estrus interval (IWE). The number of phenotypic records ranged from 6,059 (WN) to 172,984 (TNB). Single-step genomic reaction norm predictions were used to calculate the genomic estimated breeding values for each individual. Predictions were compared between datasets containing phenotypic records measured in the whole range of temperatures (WR) and datasets containing phenotypic records above 10' (10C) or 15' (15C), to evaluate the usefulness of these datasets that may better reflect the temperature within-barn. The use of homogeneous or heterogeneous residual variance was found to be trait dependent, where homogeneous variance presented the best fit for MDP, BFT, OTW, TNB, NBA, WN, and IBF, while the other traits (WW and IWE) had better fit with heterogeneous variance. The average predictions accuracy, dispersion, and bias values considering all traits for WR were 0.36 ± 0.05, -0.07 ± 0.13, and 0.76 ± 0.10, respectively; for 10C were 0.39 ± 0.02, -0.05 ± 0.07, and 0.81 ± 0.05, respectively; and for 15C were 0.32 ± 0.05, -0.05 ± 0.11, and 0.84 ± 0.10, respectively. Based on the studied traits, using phenotypic records collected when the outside temperature (from public weather stations) was above 10' provided better predictions for most of the traits. Forty-three candidate genomic windows were associated with the intercept, and 62 were associated with the slope term, which indicates specific biological mechanisms related to environmental sensitivity. Our results contribute to a better understanding of the genetic architecture of heat tolerance in pigs, and the genomic regions and candidate genes identified will contribute to future genomic studies and applications.