Estimation & Prediction

Investigating the Impact of Genetic Linkage Between Sheep Flocks on the Accuracy and Outcomes of Progeny Tests

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Abstract

Genetic gain within the New Zealand sheep industry relies on accurately estimating breeding values (EBVs) that guide selection decisions. The effectiveness of comparing EBVs across-flock relies on genetic connectedness, which is defined as the degree of genetic linkage between animals in different flocks. In practice, connectedness is typically achieved through shared sires, making it essential to understand the optimal thresholds for connectedness and refine guidelines around link-sire usage. The New Zealand sheep evaluation system 'nProve' currently applies a relatively conservative method to assess connectedness. This method evaluates across-flock linkage over a three-year interval by generating a distance matrix based on how many shared progeny there are from link sires between each pair of flocks. An alternative approach is the Genetic Connectedness Analysis (GCA) package in R, which uses Best Linear Unbiased Prediction (BLUP) mixed model equations and relationship matrices to quantify connectedness in greater depth. The aim of this study was to investigate the optimal level of genetic connectedness required between flocks in a dispersed progeny test evaluation to ensure unbiased and accurate breeding value estimation in New Zealand's sheep industry. Data were obtained from the 'nProve' database, comprising approximately 11 million records for all animals with performance data in the system. The analysis focused on two traits: growth and facial eczema. Growth is widely recorded and has strong connectedness, while facial eczema is much less recorded and has shown weaker connectedness. Data processing and filtering were carried out in SAS 9.4 to create datasets for connectedness assessment using both the standard nProve approach and the alternative GCA method. Connectedness outcomes were evaluated through examination of dendrograms. The lag-year parameter was systematically adjusted to evaluate how the number of years of data included influenced connectedness. The effect of sequentially removing highly connected flocks and the most prolific sires was also evaluated. Reducing the lag year resulted in a decline in overall connectedness, with several flocks shifting to an unconnected status. Increasing the lag year produced the opposite effect, gradually improving across-flock connectedness. Using the default lag-year parameter of five, 49.0% of flocks met the connectedness criteria for facial eczema, whereas extending the lag year by three years increased the proportion of connected flocks to 70.7%. Removing key connected flocks disrupted the linkage structure, shifting the connectedness status of multiple flocks, with some immediately losing any connection to other flocks within the evaluation. These results highlight the sensitivity of connectedness to data inclusion criteria and linking strategies, with important implications for progeny test design and the robustness of across-flock genetic evaluations.

Keywords: 2026

How to Cite:

Smith, J., Sneddon, N., Jopson, N., Martín, N., López-Villalobos, N. & van der Linden, D., (2026) “Investigating the Impact of Genetic Linkage Between Sheep Flocks on the Accuracy and Outcomes of Progeny Tests”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2295908. doi: https://doi.org/10.31274/wcgalp.24382

Rights: 1