Animal Molecular Breeding 2024, Vol.14, No.2, 154-164 http://animalscipublisher.com/index.php/amb 156 Figure 1 Analysis of consistency and inconsistency of genetic variations among different traits (Adapted from Falker-Gieske et al., 2019) Image caption: The Venn diagram illustrates the consistency and inconsistency of genetic variations among four traits: average daily gain (ADG), backfat thickness (BFT), meat-to-fat ratio (MFR), and carcass length (CRCL); The intersecting areas represent the number of shared genetic variations among these traits, while the non-overlapping areas indicate the number of unique variations specific to each trait (Adapted from Falker-Gieske et al., 2019). Falker-Gieske et al. (2019) found that carcass length (CRCL) exhibited a degree of genetic overlap with other traits such as MFR and BFT, suggesting a potential correlation between these traits at the genetic level. This correlation is significant for breeding strategies, as selecting for one trait (e.g., carcass length) could indirectly improve other highly correlated traits (e.g., backfat thickness or meat-to-fat ratio). However, Figure 1 also reveals unique genetic variations specific to each trait, indicating that these traits are independent in certain aspects and require targeted selection during breeding. Therefore, understanding the genetic correlations between these traits can help develop more effective breeding programs that achieve simultaneous improvement of target traits. The identification of genetic correlations can also inform breeding strategies to avoid undesirable trade-offs. For instance, a study using epistatic QTL analysis found that certain genomic regions exhibited both positive and negative dominance effects on different carcass traits, such as entire belly weight and entire ham weight (Duthie et al., 2010). By considering these genetic correlations, breeders can develop more effective selection programs that optimize the overall genetic improvement of carcass traits. 2.4 Genetic architecture of economically important carcass traits in pigs The genetic architecture of economically important carcass traits in pigs is complex, involving multiple genes and their interactions. Advances in sequencing technology and genome-wide association studies have significantly enhanced our understanding of this genetic complexity. For example, a meta-analysis of GWAS data identified key transcription factors and gene networks associated with meat quality and carcass traits, such as SOX5 and NKX2-5, which play crucial roles in adipose tissue metabolism and skeletal muscle development (Duarte et al., 2017). Furthermore, the identification of novel genetic networks and epistatic interactions has provided deeper insights into the regulation of carcass traits. A study on beef cattle, which can be extrapolated to pigs, demonstrated that carcass traits rarely share genetic networks with eating quality and fatty acid composition traits, suggesting that marker-assisted selection for one category of traits would not interfere with the improvement of another (Jiang et al., 2009). This highlights the importance of understanding the genetic architecture to develop targeted breeding strategies that maximize the economic value of carcass traits in pigs. 3 Breeding Strategies for Improving Carcass Traits 3.1 Traditional breeding methods Traditional breeding methods for improving carcass traits in pigs have relied heavily on phenotypic selection. This approach involves selecting animals based on observable traits such as growth rate, feed efficiency, and carcass quality. The primary advantage of this method is its simplicity and direct application, as it does not require
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