Short description:

Covering the fundamental principles of the application of linear models for the prediction of genetic merit in livestock, this new edition incorporates advances in methods of genomic prediction for pure and cross-bred animals. It provides models for the analysis of main production traits and functional traits, and includes numerous worked examples.

Long description:

Fundamental to any livestock improvement programme by animal scientists, is the prediction of genetic merit in the offspring generation for desirable production traits such as increased growth rate, or superior meat, milk and wool production. Covering the foundational principles on the application of linear models for the prediction of genetic merit in livestock, this new edition is fully updated to incorporate recent advances in genomic prediction approaches, genomic models for multi-breed and crossbred performance, dominance and epistasis. It provides models for the analysis of main production traits as well as functional traits and includes numerous worked examples. For the first time, R codes for key examples in the textbook are provided online.

The book covers:
- The relationship between the genome and the phenotype.
- BLUP models for various livestock data and structure.
- Incorporation of related ancestral parents and metafounders in prediction models.
- Models for survival analysis and social interaction.
- Advancements in genomic prediction approaches and selection.
- Genomic models for multi-breed and crossbred performance.
- Models for non-additive genetic effects including dominance and epistasis.
- Estimation of genetic parameters including Gibbs sampling approaches.
- Computation methods for solving linear mixed model equations.

Suitable for graduate and postgraduate students, researchers and lecturers of animal breeding, genetics and genomics, this established textbook provides a thorough grounding in both the basics and in new developments of linear models and animal genetics.

Table of Contents:

• 1: The Genome and phenotypes
• 2: Genetic evaluation with different sources of records
• 3: Genetic covariance between relatives
• 4: Best linear unbiased prediction of breeding value: univariate models with one random effect
• 5: Best linear unbiased prediction of breeding value: Models with random environmental effects
• 6: Best Linear unbiased prediction of breeding value: Multivariate models
• 7: Methods to reduce the dimension of multivariate models
• 8: Maternal traits models: Animal and reduced animal Models
• 9: Social interaction models
• 10: Analysis of longitudinal data
• 11: Genomic prediction and selection
• 12: Single-step approaches to genomics
• 13: Non-additive animal models
• 14: Genetic and genomic models for multibreed and crossbred analyses
• 15: Analysis of ordered categorical traits
• 16: Survival analysis
• 17: Estimation of genetic parameters
• 18: Use of Gibbs sampling in variance component estimation and breeding value prediction
• 19: Solving linear equations