Lamont, Alastair

A missing value approach for breeding value estimation

Alastair Lamont¹, Matthew Schofield¹, and Richard Barker²

1. Department of Mathematics and Statistics, University of Otago, Dunedin

2. Division of Sciences, University of Otago, Dunedin

For a particular trait, an individual’s breeding value is the genetic value it has for its progeny. Accurate breeding value estimation is a critical component of selective breeding, necessary to identify which animals will have the best offspring. As technology has improved, genetic data is often available, and can be utilised for improved breeding value estimation. While it is cost efficient to genotype some animals, it is unfeasible to genotype every individual in most populations of interest, due to either cost or logistical issues. This missing data creates challenges in the estimation of breeding values. Modern approaches adapt least-squares estimation to allow for unobserved genetic data. To do so requires particular assumptions and approximations which may not be well-suited to typical livestock data. Breeding values can also be estimated using Bayesian methods, but existing approaches do not accommodate missing genetic data. We specify a model for genetic inheritance, an approach used in human applications. This allows missing genotypes to be estimated alongside other parameters using Bayesian methods.

This presentation is eligible for the NZSA Student Prize.