Disease & heat resistance

A stochastic simulation framework for evaluating genetic resistance to cattle ticks: an application to assess experimental designs for heritability estimation

---

Abstract

The cattle tick Rhipicephalus microplus is the ectoparasite with the greatest impact on the beef production chain in northwestern and northeastern Argentina. In the context of declining acaricide efficacy, genetic selection for resistance has the potential to reduce parasite burden. The objective of this study was to develop a stochastic simulation framework to represent host-parasite-environment interactions underlying cattle tick infestations, and to use this framework to evaluate experimental designs for estimating the heritability of tick resistance under realistic data constraints. The proposed framework extends an existing stochastic model describing the ecological triad involving cattle, ticks, and the environment by incorporating a genetic model for individual susceptibility to tick infestation. Susceptibility was modeled as a latent quantitative trait with an additive genetic component, generating phenotypic tick counts that naturally exhibit the highly skewed distributions observed in field data. Simulation scenarios were defined by combinations of herd number and family structure under a fixed total of 2,000 phenotypic records, including paternal half-sib families, full-sib families, and records with no explicit family design. Farms were randomly assigned to one of two contrasting environments differing in infestation challenge. Two levels of heritability (h² = 0.1 and h² = 0.3) were considered, and experimental designs were compared in terms of bias and precision of heritability estimates across simulation replicates (20 per scenario). Simulated infestation levels fell within the range reported for subtropical regions of Argentina, and seasonal variation in adult tick abundance closely matched patterns observed in field experiments. Individual parasite loads reflected infestation challenge and varied according to month of observation, initial environmental contamination, and individual susceptibility. Across experimental designs, heritability estimates were, on average, close to the true values but showed a consistent downward bias. Precision was systematically lower at the higher true heritability level (h² = 0.3), and only under this condition did full-sib designs yield more precise estimates than paternal half-sib and no-design scenarios. The stochastic simulation framework we developed provides a realistic and flexible tool for representing tick infestation dynamics and incorporating genetic variability in host susceptibility. Its application in the present study showed that, under constraints in phenotypic recording, family-based experimental designs have a negligible effect on both the bias and the precision of heritability estimates.

Keywords: 2026

How to Cite:

Munilla, S. & Watson, S., (2026) “A stochastic simulation framework for evaluating genetic resistance to cattle ticks: an application to assess experimental designs for heritability estimation”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2329486. doi: https://doi.org/10.31274/wcgalp.24395

Rights: 1