International Journal of Molecular Zoology, 2024, Vol.14, No.6, 334-343 http://animalscipublisher.com/index.php/ijmz 339 et al., 2021). In broiler chickens, genetic correlations between traits like body weight, breast meat area, and egg production were effectively assessed using genomic data, leading to optimized selection strategies (Momen et al., 2017). 5.4 Lessons learned and implications for future breeding initiatives The successful implementation of genomic selection in poultry breeding has provided several valuable lessons. One key insight is the importance of integrating both genomic and pedigree information to achieve the most accurate predictions of breeding values (Momen et al., 2017; Misztal et al., 2020). Additionally, the use of high-density SNP panels and comprehensive genomic data collection is crucial for identifying key candidate genes and genomic regions under selection (Qanbari et al., 2015; Abdelmanova et al., 2021). Future breeding initiatives can benefit from these findings by continuing to leverage genomic selection to enhance genetic progress, improve economically important traits, and maintain genetic diversity in poultry populations (Mahdabi et al. 2021). The case study of genomic selection in poultry breeding demonstrates its effectiveness in improving targeted traits and accelerating genetic progress. By integrating genomic and phenotypic data, breeders can make more informed selection decisions, ultimately leading to more productive and efficient poultry populations. The lessons learned from these implementations highlight the potential for genomic selection to revolutionize poultry breeding and set the stage for future advancements in the field. 6 Challenges and Limitations of Genomic Selection in Chicken Breeding 6.1 High costs of genotyping and computational infrastructure The implementation of genomic selection in chicken breeding is often hindered by the high costs associated with genotyping and the necessary computational infrastructure. High-density SNP panels, while effective, are expensive, limiting their widespread use in breeding programs. For instance, the cost of using a 600K Affymetrix Axiom high-density SNP chip is prohibitively high for genotyping all selection candidates, necessitating the development of lower-cost alternatives such as low-density SNP chips and imputation methods (Herry et al., 2020). Additionally, the computational resources required to process and analyze large genomic datasets further add to the overall costs, making it challenging for smaller breeding operations to adopt these technologies (Pértille et al., 2016). 6.2 Limited genomic resources in non-model chicken breeds Another significant challenge is the limited availability of genomic resources for non-model chicken breeds. Most genomic selection efforts have focused on commercial breeds, leaving indigenous and less common breeds with fewer genomic tools and resources. This disparity can hinder the genetic improvement of these breeds, which may possess valuable traits for specific environments or production systems. For example, studies have shown that while commercial breeds have been extensively genotyped and analyzed, indigenous breeds often lack comprehensive genomic data, making it difficult to apply genomic selection effectively (Ndung’u et al., 2022). This limitation underscores the need for more inclusive genomic research that encompasses a broader range of chicken breeds. 6.3 Ethical and welfare concerns The application of genomic selection in chicken breeding also raises ethical and welfare concerns. Intensive selection for specific traits can lead to unintended consequences, such as increased susceptibility to diseases or poor welfare outcomes. For instance, the selection for rapid growth in broilers has been associated with health issues like skeletal deformities and cardiovascular problems. Moreover, the focus on production traits can sometimes overshadow the importance of maintaining genetic diversity and overall animal well-being. Ethical considerations must be integrated into breeding programs to ensure that the welfare of the animals is not compromised in the pursuit of genetic gains (Marchesi et al., 2017). 6.4 Regulatory and industry-level adoption challenges Finally, the adoption of genomic selection at the regulatory and industry levels presents its own set of challenges.
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