GxE

Accounting for genotype by environment interaction on the genetic evaluation of semen production traits in Duroc boars

---

Abstract

We investigated the potential of incorporating grid-cell-based environmental covariates (EC) in the genetic evaluation of total sperm count (TSC), sperm motility (MOT), and sperm morphology (MOR) for Duroc boars. A total of 188,665 records from 3,684 genotyped boars, born between December 2018 and October 2024 and raised in three stud farms from September 2019 to June 2025, were analyzed using multiple-trait linear-threshold models. To account for genotype by environment interactions (GE), we constructed an interaction matrix as the Hadamard product between the genomic relationship matrix and the environmental covariance matrix (GΩ). The Ω matrix was constructed based on monthly EC obtained from the NASAPOWER database for each environmental group. The environmental groups were defined in three ways: farm, farm-season, and farm-year-season. From the set of available EC, those significantly associated with TSC were retained: temperature, relative humidity, atmospheric pressure, and wind speed and direction. Five models with different GE structures were evaluated: M1 represented the baseline and included only main effects; M2, M3 and M4 included the GE modeling Ω as farm, farm-season, and farm-year-season, respectively. M5 extended M3 by adding a random farm-season interaction. Estimates of heritability for TSC, MOT, and MOR ranged from 0.03 to 0.04, 0.05 to 0.08, and 0.04 to 0.08, respectively. Corresponding repeatability ranged from 0.15 to 0.23, 0.28 to 0.49, and 0.28 to 0.49. Estimates of genetic correlation, TSC-MOT, TSC-MOR, and MOT-MOR ranged from 0.27 to 0.31, 0.24 to 0.31, and 0.98 to 0.99, respectively, with minor differences across models. Lastly, the proportion of phenotypic variance attributed to GE variance ranged from 0.00 to 0.32, 0.00 to 0.44, and 0.00 to 0.44. We validated the models using the linear regression (LR) method. Across traits and models, bias ranged from -0.05 to 0.02 (in additive genetic standard-deviation units), b1 varied from 0.88 to 0.99, the range for the correlation was from 0.75 to 0.84, and accuracy ranged from 0.41 to 0.53. Overall, LR statistics did not improve in models with GE matrices constructed with grid-cell-based environmental covariates. Especially when farm-year-season combinations were used as environmental groups (M4), we identified slight overdispersion in b1 and notable decrease of accuracy across the traits in M3 compared to the standard model. Accounting for GE with grid-cell-based environmental covariates did not improve model robustness and predictive performance in the genetic evaluation of semen production traits.

Keywords: 2026

How to Cite:

Lee, H., Gu, Y., Huang, Y., Jarquin, D., Bussiman, F. & Hidalgo, J., (2026) “Accounting for genotype by environment interaction on the genetic evaluation of semen production traits in Duroc boars”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2284919. doi: https://doi.org/10.31274/wcgalp.23622

Rights: 1