Aligning phenotypic and genetic trends: comparing trends from threshold and linear models in pigs

This study aimed to compare phenotypic and genetic trends when genomic breeding values (GEBV) were computed using linear and threshold models or when GEBV were transformed to the probability scale for wean-to-finish mortality (WFM) and front leg structure (FLS). A total of 270,064 and 998,289 observations were available for WFM measured on crossbred and FLS measured on purebred, respectively. The total number of animals in the analyses was 577,947 for WFM and 1,079,080 for FLS. The number of purebred genotyped animals was 274,365 and 239,075 for WFM and FLS, respectively. Incidences were 9.71% for WFM and 13.31% for FLS. Heritabilities on the observed scale were 0.04 for WFM and 0.23 for FLS, whereas on the liability scale they were 0.08 and 0.38. When using linear models, we applied two approaches to convert GEBV to probabilities: (1) we standardized the GEBV deviated from the mean GEBV based on the additive genetic variance and then transformed them into probabilities; (2) we used an approximation to the liability scale and then transformed the approximated liabilities to the probability scale. Genetic and phenotypic trends were obtained by averaging GEBV and phenotypes based on the birth year for animals with phenotypes. Spearman correlations among raw and transformed GEBV within trait were all ≥0.98, suggesting minimal changes when selecting candidates based on GEBV from linear or threshold models and their transformation to probabilities. The slopes of genetic trends based on raw GEBV from linear models were significantly different from zero. The sign of the slopes suggests that selections have been directed toward desirable phenotypes. After the transformation into the probability scale, genetic trends computed based on GEBV from linear and threshold models aligned the phenotypic trend for FLS. For WFM, the genetic and phenotypic trends showed less alignment, possibly due to the lower trait incidence, low heritability, and susceptibility to environmental influences. The close association between genetic and phenotypic trends for FLS was also confirmed by the slopes of the regressions of GEBV on the probability scale or phenotypes on the year of birth. Results of the present study demonstrated that GEBV from the linear scale can be transformed into the probability scale with a strong alignment with GEBV transformed from the liability scale. Aligning genetic and phenotypic trends, however, depends on the model, heritability, and trait incidence.

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Publication Details

Journal
Journal of Animal Science
Published
2025-01-01
DOI
https://doi.org/10.1093/jas/skaf236
Citations
1
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
Field-Weighted Citation Impact
1.82
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article

Aligning phenotypic and genetic trends: comparing trends from threshold and linear models in pigs

S. Tsuruta, Matias Bermann, Daniela A. L. Lourenco, Alberto Cesarani et al.
1 citations
Journal of Animal Science
Genetic and phenotypic traits in livestock
1.82
article

Aligning phenotypic and genetic trends: comparing trends from threshold and linear models in pigs

S. Tsuruta, Matias Bermann, Daniela A. L. Lourenco, Alberto Cesarani, Ching-Yi Chen, Jorge Hidalgo, Justin W. Holl
article en
1 citations

Abstract

This study aimed to compare phenotypic and genetic trends when genomic breeding values (GEBV) were computed using linear and threshold models or when GEBV were transformed to the probability scale for wean-to-finish mortality (WFM) and front leg structure (FLS). A total of 270,064 and 998,289 observations were available for WFM measured on crossbred and FLS measured on purebred, respectively. The total number of animals in the analyses was 577,947 for WFM and 1,079,080 for FLS. The number of purebred genotyped animals was 274,365 and 239,075 for WFM and FLS, respectively. Incidences were 9.71% for WFM and 13.31% for FLS. Heritabilities on the observed scale were 0.04 for WFM and 0.23 for FLS, whereas on the liability scale they were 0.08 and 0.38. When using linear models, we applied two approaches to convert GEBV to probabilities: (1) we standardized the GEBV deviated from the mean GEBV based on the additive genetic variance and then transformed them into probabilities; (2) we used an approximation to the liability scale and then transformed the approximated liabilities to the probability scale. Genetic and phenotypic trends were obtained by averaging GEBV and phenotypes based on the birth year for animals with phenotypes. Spearman correlations among raw and transformed GEBV within trait were all ≥0.98, suggesting minimal changes when selecting candidates based on GEBV from linear or threshold models and their transformation to probabilities. The slopes of genetic trends based on raw GEBV from linear models were significantly different from zero. The sign of the slopes suggests that selections have been directed toward desirable phenotypes. After the transformation into the probability scale, genetic trends computed based on GEBV from linear and threshold models aligned the phenotypic trend for FLS. For WFM, the genetic and phenotypic trends showed less alignment, possibly due to the lower trait incidence, low heritability, and susceptibility to environmental influences. The close association between genetic and phenotypic trends for FLS was also confirmed by the slopes of the regressions of GEBV on the probability scale or phenotypes on the year of birth. Results of the present study demonstrated that GEBV from the linear scale can be transformed into the probability scale with a strong alignment with GEBV transformed from the liability scale. Aligning genetic and phenotypic trends, however, depends on the model, heritability, and trait incidence.

Journal of Animal ScienceVol. 103
University of Sassari (IT), University of Georgia (US), Gender Studies (CZ)
Openalex Percentile: Top 14%
Genetic and phenotypic traits in livestock
1.82
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