Use of threshold and linear models to estimate variance components and breeding values for disease resistance in Italian heavy pigs

The Italian National Pig Breeders Association (ANAS) manages the breeding programs of the Italian Large White (ILW), Landrace (IL), and Duroc (ID) breeds, mainly oriented to the production of PDO hams. ANAS evaluates the inclusion of genetic resistance in its breeding scheme. This study aimed to est...

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Main Authors: M. Cappelloni, M. Gallo, A Cesarani
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:Italian Journal of Animal Science
Subjects:
Online Access:http://dx.doi.org/10.1080/1828051X.2022.2050471
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author M. Cappelloni
M. Gallo
A Cesarani
author_facet M. Cappelloni
M. Gallo
A Cesarani
author_sort M. Cappelloni
collection DOAJ
description The Italian National Pig Breeders Association (ANAS) manages the breeding programs of the Italian Large White (ILW), Landrace (IL), and Duroc (ID) breeds, mainly oriented to the production of PDO hams. ANAS evaluates the inclusion of genetic resistance in its breeding scheme. This study aimed to estimate variance components and breeding values (EBV) using threshold (TM) and linear (LM) models. During the sib test performed at the genetic station of ANAS from 1997 to 2021, 9,595 (respiratory diseases) and 12,046 (enteritis) diagnoses were collected by the veterinary. The trait was recorded as a dichotomous variable: affected animals with 1, whereas healthy with 2. A multi-breed model was applied with the breed, sex, and farm sector as fixed effects and litter, animal, and residual as random effects. The same model was also applied within each breed, removing the breed effect. The limited data size within single breed did not allow to estimate accurate variance components. With the multi-breed model, low heritabilities were estimated for respiratory (0.09) and enteritis (0.15), with TM and LM leading to the same values. The multibreed model led to more precise variance components estimation and to EBV very close to the ones from the single breed analyses. Pearson and Spearman rank correlations between EBV estimated with TM and LM in the multibreed scenario were ≥0.97. Results of this study demonstrated the feasibility of including disease resistance among the breeding goals of ANAS and that both TM and LM could be used to reach this objective.Highlights Genetic selection for disease resistance in heavy pigs is possible Low heritabilities estimated for enteritis and respiratory disorders Threshold and linear models gave similar results
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spelling doaj.art-ff55b635f5db4e7c827598aa1fa803f42023-08-25T13:51:02ZengTaylor & Francis GroupItalian Journal of Animal Science1594-40771828-051X2022-12-0121148849210.1080/1828051X.2022.20504712050471Use of threshold and linear models to estimate variance components and breeding values for disease resistance in Italian heavy pigsM. Cappelloni0M. Gallo1A Cesarani2Associazione Nazionale Allevatori Suini (ANAS)Associazione Nazionale Allevatori Suini (ANAS)Dipartimento di Agraria, Università degli Studi di SassariThe Italian National Pig Breeders Association (ANAS) manages the breeding programs of the Italian Large White (ILW), Landrace (IL), and Duroc (ID) breeds, mainly oriented to the production of PDO hams. ANAS evaluates the inclusion of genetic resistance in its breeding scheme. This study aimed to estimate variance components and breeding values (EBV) using threshold (TM) and linear (LM) models. During the sib test performed at the genetic station of ANAS from 1997 to 2021, 9,595 (respiratory diseases) and 12,046 (enteritis) diagnoses were collected by the veterinary. The trait was recorded as a dichotomous variable: affected animals with 1, whereas healthy with 2. A multi-breed model was applied with the breed, sex, and farm sector as fixed effects and litter, animal, and residual as random effects. The same model was also applied within each breed, removing the breed effect. The limited data size within single breed did not allow to estimate accurate variance components. With the multi-breed model, low heritabilities were estimated for respiratory (0.09) and enteritis (0.15), with TM and LM leading to the same values. The multibreed model led to more precise variance components estimation and to EBV very close to the ones from the single breed analyses. Pearson and Spearman rank correlations between EBV estimated with TM and LM in the multibreed scenario were ≥0.97. Results of this study demonstrated the feasibility of including disease resistance among the breeding goals of ANAS and that both TM and LM could be used to reach this objective.Highlights Genetic selection for disease resistance in heavy pigs is possible Low heritabilities estimated for enteritis and respiratory disorders Threshold and linear models gave similar resultshttp://dx.doi.org/10.1080/1828051X.2022.2050471gibbs samplinggenetic parametersthresholddisease resistance
spellingShingle M. Cappelloni
M. Gallo
A Cesarani
Use of threshold and linear models to estimate variance components and breeding values for disease resistance in Italian heavy pigs
Italian Journal of Animal Science
gibbs sampling
genetic parameters
threshold
disease resistance
title Use of threshold and linear models to estimate variance components and breeding values for disease resistance in Italian heavy pigs
title_full Use of threshold and linear models to estimate variance components and breeding values for disease resistance in Italian heavy pigs
title_fullStr Use of threshold and linear models to estimate variance components and breeding values for disease resistance in Italian heavy pigs
title_full_unstemmed Use of threshold and linear models to estimate variance components and breeding values for disease resistance in Italian heavy pigs
title_short Use of threshold and linear models to estimate variance components and breeding values for disease resistance in Italian heavy pigs
title_sort use of threshold and linear models to estimate variance components and breeding values for disease resistance in italian heavy pigs
topic gibbs sampling
genetic parameters
threshold
disease resistance
url http://dx.doi.org/10.1080/1828051X.2022.2050471
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