International Journal of Molecular Veterinary Research, 2024, Vol.14, No.5, 211-218 http://animalscipublisher.com/index.php/ijmvr 215 resistance following selective breeding (Tsukahara et al., 2021). The identification of genetic markers and the use of molecular techniques have further refined these programs, allowing for more targeted selection (Estrada-Reyes et al., 2019; Omar et al., 2019). The success of these programs not only reduces reliance on anthelmintic drugs, which face increasing resistance issues, but also improves overall herd health and productivity (Kotze et al., 2016). The presence of genetic resistance within breeds like the Yichang white goat highlights the potential for developing resistant populations through selective breeding. In summary, genetic selection for resistance to Haemonchus contortus in goats is a viable strategy that leverages genetic diversity and molecular insights to combat parasitic infections, offering a sustainable alternative to chemical treatments. 6 Current Challenges and Limitations in Genetic Selection for Disease Resistance 6.1 Risks of inbreeding and loss of genetic diversity One of the primary challenges in genetic selection for disease resistance in goats is the risk of inbreeding, which can lead to a loss of genetic diversity. This is particularly concerning when selection pressure is applied to specific alleles associated with disease resistance, such as those for transmissible spongiform encephalopathies (TSE) resistance. High selection pressure on alleles like K222, D146, and S146, which confer resistance to classical scrapie, can reduce genetic diversity, especially in small or rare breeds (Ricci et al., 2017). Additionally, the fixation of certain alleles, such as those related to gastrointestinal nematode resistance, can inadvertently reduce the overall genetic variability within a population, potentially leading to inbreeding depression (Estrada-Reyes et al., 2019; Aboshady et al., 2021). 6.2 Economic and ethical considerations in genetic selection Economic and ethical considerations also pose significant challenges in the genetic selection for disease resistance. The inclusion of disease resistance traits in breeding goals can increase profitability, as demonstrated in smallholder dairy goat production systems where breeding for resistance to diseases like mastitis and helminthosis improved economic outcomes (Amayi et al., 2021). However, the cost of implementing genetic selection programs, including the necessary infrastructure for genetic evaluations and phenotyping, can be prohibitive for some farmers. Ethically, there is a concern about the welfare implications of selecting for specific traits, which may inadvertently affect other important traits such as reproduction or growth. Moreover, the potential for unintended consequences, such as the emergence of new disease susceptibilities, must be considered (Mandal et al., 2018). 6.3 Environmental and management factors affecting resistance Environmental and management factors significantly influence the effectiveness of genetic selection for disease resistance. The expression of genetic resistance can be affected by environmental conditions, such as climate and nutrition, which can alter the immune response of goats (Estrada-Reyes et al., 2019). For instance, the prevalence of Haemonchus contortus, a major gastrointestinal nematode, is influenced by environmental conditions, and genetic resistance to this parasite may vary accordingly6. Additionally, management practices, such as housing and feeding, can impact the health and disease resistance of goats, necessitating a holistic approach that combines genetic selection with optimal management strategies (Schultz et al., 2020). The integration of genetic and environmental data is crucial for accurately predicting and enhancing disease resistance in diverse goat populations (Mandal et al., 2018). The genetic selection for disease resistance in goats faces several challenges, including the risks of inbreeding and loss of genetic diversity, economic and ethical considerations, and the influence of environmental and management factors. Addressing these challenges requires a balanced approach that considers genetic diversity, cost-effectiveness, ethical implications, and the integration of environmental data to optimize disease resistance in goat populations.
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