International Journal of Molecular Zoology, 2024, Vol.14, No.6, 334-343 http://animalscipublisher.com/index.php/ijmz 340 Regulatory frameworks for the use of genomic technologies in animal breeding are still evolving, and there can be significant variability between regions. This lack of standardized regulations can create barriers to the implementation of genomic selection practices. Additionally, industry stakeholders may be hesitant to adopt new technologies due to the perceived risks and uncertainties associated with them. For example, the poultry industry has traditionally relied on well-established breeding practices, and transitioning to genomic selection requires a shift in both mindset and operational procedures (Wolc et al., 2016; Misztal et al., 2020). Overcoming these challenges will require concerted efforts to educate stakeholders and develop clear regulatory guidelines that support the integration of genomic technologies into breeding programs. The use of genomic selection in chicken breeding faces several challenges, including high costs of genotyping and computational infrastructure, limited genomic resources for non-model breeds, ethical and welfare concerns, and regulatory and industry-level adoption hurdles. Addressing these challenges will be crucial for the successful implementation and widespread adoption of genomic selection in the poultry industry (Teng et al., 2019). 7 Future Prospects of Genomic Selection in Chicken Breeding 7.1 Integration of GS with genome editing technologies (e.g., CRISPR/Cas9) The integration of genomic selection (GS) with genome editing technologies such as CRISPR/Cas9 holds significant promise for the future of chicken breeding. CRISPR/Cas9 allows for precise modifications at specific genomic loci, which can be used to introduce desirable traits identified through GS. For instance, the CRISPR/Cas9 system has been successfully used to create highly productive chickens with improved traits by targeting specific genes (Larkina et al., 2021). This combination can accelerate the breeding process by directly editing the genes associated with favorable traits, thereby enhancing the efficiency and effectiveness of GS. 7.2 Prospects for precision breeding and tailored poultry lines Precision breeding aims to develop poultry lines that are tailored to specific production goals or environmental conditions. By leveraging GS, breeders can predict the genetic potential of chickens with high accuracy, allowing for the selection of individuals that best meet the desired criteria. This approach can optimize traits such as growth rate, feed efficiency, and disease resistance (Wolc et al., 2016; Ndung’u et al., 2022). The ability to tailor poultry lines to specific needs not only improves productivity but also enhances animal welfare and sustainability in poultry production. 7.3 Leveraging big data and artificial intelligence in genomic evaluations The use of big data and artificial intelligence (AI) in genomic evaluations is set to revolutionize chicken breeding. Advanced computational tools and machine learning algorithms can handle the vast amounts of data generated by high-density SNP panels and whole-genome sequencing (Montesinos-López et al., 2023). These technologies can improve the predictive accuracy of genomic estimated breeding values (GEBVs) by identifying complex patterns and interactions within the genomic data. AI-driven models can also facilitate the integration of environmental and phenotypic data, further enhancing the precision of GS (Wang et al., 2018; Li et al., 2023). 7.4 Global collaboration and resource sharing for GS research Global collaboration and resource sharing are crucial for advancing GS research in chicken breeding. By pooling genetic and phenotypic data from diverse populations, researchers can create more robust reference populations, which are essential for accurate genomic predictions (Meuwissen et al., 2016; Tan et al., 2017). International partnerships can also facilitate the exchange of technological advancements and best practices, accelerating the implementation of GS across different regions and breeding programs. Collaborative efforts can lead to the development of standardized protocols and shared databases, ultimately benefiting the global poultry industry. The future of genomic selection in chicken breeding is promising, with significant advancements expected through the integration of genome editing technologies, precision breeding, big data, and AI. Global collaboration will play a pivotal role in maximizing the potential of GS, leading to more efficient and sustainable poultry production.
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