Animal Molecular Breeding 2024, Vol.14, No.2, 154-164 http://animalscipublisher.com/index.php/amb 161 carcass quality traits with reasonable accuracy. For instance, a study evaluating the predictive ability of different models for carcass traits in crossbred pigs found that the inclusion of additional records in the training set significantly improved prediction accuracies (Bergamaschi et al., 2019). This highlights the importance of large, well-annotated datasets and robust statistical models in achieving accurate genetic predictions. Figure 2 Multiple future directions for the development of CRISPR gene-editing technology (Adapted from Wang and Doudna, 2023) Furthermore, the integration of multi-omics data with traditional quantitative genetics approaches can enhance the precision of genetic predictions. By leveraging comprehensive datasets that include genomics, transcriptomics, proteomics, and metabolomics information, researchers can gain a deeper understanding of the genetic basis of complex traits and identify key genetic markers associated with desirable carcass traits (Chakraborty et al., 2022). This multi-faceted approach not only improves the accuracy of breeding value estimates but also accelerates the genetic gain by enabling the selection of superior animals at an early stage of life. As omics technologies continue to advance and become more accessible, their integration with quantitative genetics will play a pivotal role in the future of pig breeding programs (Keurentjes et al., 2008; Verardo et al., 2023). 7 Concluding Remarks This study of quantitative genetics in improving carcass traits in pigs has revealed several significant insights. Genome-wide association studies (GWAS) and quantitative trait loci (QTL) mapping have identified numerous genetic markers associated with economically important traits such as back fat thickness, meat fat ratio, carcass length, and average daily gain. For instance, pooling F2 designs and resequencing efforts have led to the discovery of over 32 million variants, including 8 million novel ones, and identified significant variant clusters on chromosomes 1, 2, 4, 7, 17, and 18. Additionally, QTL analyses in various pig populations have consistently highlighted significant loci on chromosomes 1, 2, 4, 7, and X, affecting traits like lean content, fat content, and dressing percentage. Heritability estimates for carcass and meat quality traits have been found to be moderate to high, indicating the potential for genetic improvement through selective breeding. The findings from these studies have profound implications for pig breeding and meat production. The identification of specific genetic markers and QTLs allows for the development of marker-assisted selection (MAS) programs, which can accelerate genetic improvement in pig populations. For example, the discovery of high-impact variants and candidate genes such as BMP2 can be directly utilized in breeding programs to enhance traits like back fat thickness and carcass length. The moderate to high heritability estimates for traits such as
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