Likelihood and Bayesian analyses reveal major genes affecting body composition, carcass, meat quality and the number of false teats in a Chinese European pig line

<p>Abstract</p> <p>Segregation analyses were performed using both maximum likelihood – <it>via </it>a Quasi Newton algorithm – (ML-QN) and Bayesian – <it>via </it>Gibbs sampling – (Bayesian-GS) approaches in the Chinese European <it>Tiameslan </it&g...

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Main Authors: Le Roy Pascale, Burlot Thierry, Naveau Jean, Zhang Siqing, Bidanel Jean-Pierre, Marie-Pierre Sanchez
Format: Article
Language:deu
Published: BMC 2003-07-01
Series:Genetics Selection Evolution
Subjects:
Online Access:http://www.gsejournal.org/content/35/5/385
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author Le Roy Pascale
Burlot Thierry
Naveau Jean
Zhang Siqing
Bidanel Jean-Pierre
Marie-Pierre Sanchez
author_facet Le Roy Pascale
Burlot Thierry
Naveau Jean
Zhang Siqing
Bidanel Jean-Pierre
Marie-Pierre Sanchez
author_sort Le Roy Pascale
collection DOAJ
description <p>Abstract</p> <p>Segregation analyses were performed using both maximum likelihood – <it>via </it>a Quasi Newton algorithm – (ML-QN) and Bayesian – <it>via </it>Gibbs sampling – (Bayesian-GS) approaches in the Chinese European <it>Tiameslan </it>pig line. Major genes were searched for average ultrasonic backfat thickness (ABT), carcass fat (X2 and X4) and lean (X5) depths, days from 20 to 100 kg (D20100), Napole technological yield (NTY), number of false (FTN) and good (GTN) teats, as well as total teat number (TTN). The discrete nature of FTN was additionally considered using a threshold model under ML methodology. The results obtained with both methods consistently suggested the presence of major genes affecting ABT, X2, NTY, GTN and FTN. Major genes were also suggested for X4 and X5 using ML-QN, but not the Bayesian-GS, approach. The major gene affecting FTN was confirmed using the threshold model. Genetic correlations as well as gene effect and genotype frequency estimates suggested the presence of four different major genes. The first gene would affect fatness traits (ABT, X2 and X4), the second one a leanness trait (X5), the third one NTY and the last one GTN and FTN. Genotype frequencies of breeding animals and their evolution over time were consistent with the selection performed in the <it>Tiameslan </it>line.</p>
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spelling doaj.art-c86397c4d6c24147890c776fea973e2e2022-12-21T18:48:55ZdeuBMCGenetics Selection Evolution0999-193X1297-96862003-07-0135538540210.1186/1297-9686-35-5-385Likelihood and Bayesian analyses reveal major genes affecting body composition, carcass, meat quality and the number of false teats in a Chinese European pig lineLe Roy PascaleBurlot ThierryNaveau JeanZhang SiqingBidanel Jean-PierreMarie-Pierre Sanchez<p>Abstract</p> <p>Segregation analyses were performed using both maximum likelihood – <it>via </it>a Quasi Newton algorithm – (ML-QN) and Bayesian – <it>via </it>Gibbs sampling – (Bayesian-GS) approaches in the Chinese European <it>Tiameslan </it>pig line. Major genes were searched for average ultrasonic backfat thickness (ABT), carcass fat (X2 and X4) and lean (X5) depths, days from 20 to 100 kg (D20100), Napole technological yield (NTY), number of false (FTN) and good (GTN) teats, as well as total teat number (TTN). The discrete nature of FTN was additionally considered using a threshold model under ML methodology. The results obtained with both methods consistently suggested the presence of major genes affecting ABT, X2, NTY, GTN and FTN. Major genes were also suggested for X4 and X5 using ML-QN, but not the Bayesian-GS, approach. The major gene affecting FTN was confirmed using the threshold model. Genetic correlations as well as gene effect and genotype frequency estimates suggested the presence of four different major genes. The first gene would affect fatness traits (ABT, X2 and X4), the second one a leanness trait (X5), the third one NTY and the last one GTN and FTN. Genotype frequencies of breeding animals and their evolution over time were consistent with the selection performed in the <it>Tiameslan </it>line.</p>http://www.gsejournal.org/content/35/5/385segregation analysislikelihoodBayesianmajor genepig
spellingShingle Le Roy Pascale
Burlot Thierry
Naveau Jean
Zhang Siqing
Bidanel Jean-Pierre
Marie-Pierre Sanchez
Likelihood and Bayesian analyses reveal major genes affecting body composition, carcass, meat quality and the number of false teats in a Chinese European pig line
Genetics Selection Evolution
segregation analysis
likelihood
Bayesian
major gene
pig
title Likelihood and Bayesian analyses reveal major genes affecting body composition, carcass, meat quality and the number of false teats in a Chinese European pig line
title_full Likelihood and Bayesian analyses reveal major genes affecting body composition, carcass, meat quality and the number of false teats in a Chinese European pig line
title_fullStr Likelihood and Bayesian analyses reveal major genes affecting body composition, carcass, meat quality and the number of false teats in a Chinese European pig line
title_full_unstemmed Likelihood and Bayesian analyses reveal major genes affecting body composition, carcass, meat quality and the number of false teats in a Chinese European pig line
title_short Likelihood and Bayesian analyses reveal major genes affecting body composition, carcass, meat quality and the number of false teats in a Chinese European pig line
title_sort likelihood and bayesian analyses reveal major genes affecting body composition carcass meat quality and the number of false teats in a chinese european pig line
topic segregation analysis
likelihood
Bayesian
major gene
pig
url http://www.gsejournal.org/content/35/5/385
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