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Inferring Causal Relationships for Lifetime Reproductive Traits and Modelling Latent Reproductive Performance
Morteza Mokhtari1, Ali Esmailizadeh2, Mehdi Momen3
1Faculty of Agriculture, Department of Animal Science, University of Jiroft, Jiroft, Iran.
Summary
Structural equation models improved genetic analysis of reproductive traits in Murciano-Granadina goats. The ICM-BM model identified reproductive performance (RP) as a key latent variable for breeding.
Area of Science:
- Animal Genetics
- Quantitative Genetics
- Reproductive Biology
Background:
- Lifetime reproductive traits are crucial for dairy goat productivity.
- Accurate genetic evaluation requires appropriate statistical models.
- Murciano-Granadina goats are a valuable dairy breed.
Purpose of the Study:
- To apply structural equation models (SEMs) for genetic analysis of lifetime reproductive traits in Murciano-Granadina goats.
- To compare the predictive ability of different SEMs, including standard (SMM) and Inductive Causation (ICM) based models.
- To develop a latent variable model for reproductive performance (RP) and assess its heritability and genetic correlations.
Main Methods:
- Data from 2016-2023 on Murciano-Granadina goats from a private farm in Iran.
- Fitted four multivariate animal models: SMM, ICM, ICM with biological modification (ICM-BM), and fully recursive (FRM).
- Evaluated models using Mean Squared Prediction Error (MSE) and Pearson's correlation (r(y, )). Confirmatory Factor Analysis (CFA) was used for latent variable construction.
Main Results:
- The ICM-BM model demonstrated superior predictive ability (lowest MSE, highest r(y, )).
- Heritability estimates for lifetime reproductive traits (OLSB, OLSW, OLWB, OLWW) were low (0.06-0.11).
- High positive genetic correlations (0.72-0.95) and phenotypic correlations (0.81-0.95) were observed among traits and the latent RP variable.
Conclusions:
- The ICM-BM model offers advantages for genetic evaluation of reproductive traits in this breed.
- Low heritability suggests significant environmental and non-additive genetic influences on these traits.
- The latent reproductive performance (RP) variable is a promising tool for breeding programs due to strong correlations.
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