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Modeling relationships between calving traits: a comparison between standard and recursive mixed models.

Evangelina López de Maturana1, Gustavo de los Campos, Xiao-Lin Wu

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Structural equation models reveal nonlinear relationships between gestation length and calving difficulty/stillbirth in animal breeding. Phenotypic recursion is a key factor in genetic and environmental correlations for these traits.

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Area of Science:

  • Animal Breeding
  • Quantitative Genetics
  • Statistical Genetics

Background:

  • Structural equation models (SEMs) are increasingly used to analyze complex phenotypic relationships.
  • Modeling recursive and simultaneous relationships between traits is crucial in animal breeding.
  • This study focuses on phenotypic recursion among calving traits: gestation length (GL), calving difficulty (CD), and stillbirth (SB).

Purpose of the Study:

  • To illustrate the application of SEMs in animal breeding for modeling phenotypic recursion.
  • To investigate complex parameterizations of relationships between GL, CD, and SB liabilities.
  • To model heterogeneous recursive relationships based on GL phenotype categories.

Main Methods:

  • Comparison of four models: standard mixed model (SMM) and three recursive mixed models (RMM1, RMM2, RMM3).
  • RMMs differ in assumptions about the source of correlations (residual, contemporary groups, genetic effects).
  • Evaluation based on goodness of fit and predictive ability.

Main Results:

  • Estimates of structural coefficients were similar across all recursive mixed models.
  • A nonlinear relationship was found between GL and liabilities to CD and SB.
  • A linear relationship was observed between liabilities to CD and SB.

Conclusions:

  • A nonlinear recursive effect from gestation length (GL) onto calving difficulty (CD) and stillbirth (SB) is plausible.
  • The most restrictive model (RMM3) performed comparably to less restrictive models.
  • Phenotypic recursion appears to be a significant driver of observed genetic and environmental correlations.