Phenotypic causal networks between boar taint compounds measured in biopsies and carcasses

被引:0
作者
Botelho, Margareth Evangelista [1 ,2 ]
Lopes, Marcos Soares [3 ,4 ]
Mathur, Pramod K. [3 ]
Knol, Egbert F. [3 ]
Marques, Daniele B. D. [2 ]
Lopes, Paulo Savio [2 ]
Fonseca e Silva, Fabyano [2 ]
Facioni Guimaraes, Simone Eliza [2 ]
Veroneze, Renata [2 ]
机构
[1] Inst Tecnol Agr Pitangui, Empresa Pesquisa Agr Minas Gerais, BR-35650000 Pitangui, Brazil
[2] Univ Fed Vicosa, Dept Anim Sci, BR-36570999 Vicosa, MG, Brazil
[3] Topigs Norsvin Res Ctr, NL-6641 SZ Beuningen, Netherlands
[4] Topigs Norsvin, BR-80420210 Curitiba, Parana, Brazil
关键词
androstenone; biopsy; boar taint; carcass; causal structure; IC algorithm; indole; skatole; ANDROSTENONE; SKATOLE; REPRODUCTION; PERFORMANCE; INDOLE;
D O I
10.1071/AN21277
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
Context Boar taint compounds (androstenone, skatole and indole) can be measured in pig carcasses, after slaughter or, alternatively, in biopsies of subcutaneous adipose tissue from selected living pigs. Measuring these compounds via biopsy enables data collection in selected animals and high standardisation regarding tissue-collection procedures for phenotyping. Because different analytical methods can be used to measure boar taint compounds, it is important to better understand the relationship between boar taint compounds measured in biopsies and in carcasses. Aims This research aimed to identify the causal relationship and causal effects among boar taint compounds (androstenone, skatole and indole) measured in pig adipose tissue from carcasses and biopsies. Methods The concentrations of androstenone (AC), skatole (SC) and indole (IC) measured in adipose tissue from pig carcasses and the concentrations of androstenone (AB), skatole (SB) and indole (IB) measured in biopsies were used to fit a multi-trait Structural Equation Model (SEM) considering causal network graphs obtained via inductive causation algorithm with or without a priori information. Models were compared using the deviance information criterion (DIC). Key results The best DIC was obtained in a model with a causal structure built using a priori information; however, this model was considered inappropriate, because it returned several null genetic correlations among traits described as positively correlated. The best structure returned using only inductive causation algorithm was IB -> SC <- AB <- AC <- SB: SC -> IC, which was obtained with an 80-70% high-probability distribution interval. This model returned positive genetic correlations and improved goodness-of-fit compared with the multi-trait model in all cases. Several causal relationships among boar taint compounds in carcasses and biopsies were identified. Conclusion Boar taint compounds measured in biopsies have direct effects on boar taint compounds measured in carcasses. Implications Knowledge concerning the causal structure of boar taint compounds may be used in breeding programs, helping in the formulation of selection indexes and improving the ability for prediction and selection of this complex trait (boar taint).
引用
收藏
页码:291 / 300
页数:10
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