Animal Molecular Breeding 2024, Vol.14, No.2, 154-164 http://animalscipublisher.com/index.php/amb 155 facilitated the development of marker-assisted selection strategies, accelerating genetic improvement in pig populations (Čepica et al., 2013; Duarte et al., 2017). This study evaluates the application of quantitative genetics in improving carcass traits in pigs. It summarizes current knowledge on the genetic basis of pig carcass traits, reviews the methodologies used in quantitative genetics to study these traits, assesses the effectiveness of quantitative genetics in enhancing carcass traits through breeding programs, identifies gaps in existing research, and suggests future directions for improving carcass traits using quantitative genetics, with the aim of providing a comprehensive understanding of how to optimize pig carcass traits through quantitative genetics, offering theoretical support for the development of the swine industry. 2 Fundamentals of Quantitative Genetics 2.1 Basic principles of quantitative genetics Quantitative genetics is the study of traits that are influenced by multiple genes and environmental factors. These traits, known as quantitative or complex traits, exhibit continuous variation and are typically measured on a numerical scale. The fundamental principles of quantitative genetics involve understanding how genetic variation contributes to phenotypic variation within a population. This is achieved through the study of quantitative trait loci (QTL), which are regions of the genome that are associated with variation in a quantitative trait. For instance, in pigs, numerous QTL have been identified for traits such as growth, meat quality, and carcass composition, highlighting the polygenic nature of these economically important traits (Duarte et al., 2017; Falker-Gieske et al., 2019; Velez-Irizary et al., 2019). The identification and analysis of QTL involve genome-wide association studies (GWAS) and other genetic mapping techniques. These methods allow researchers to pinpoint specific genetic variants that contribute to trait variation. For example, a study on pigs used a low-coverage whole-genome sequencing strategy to identify 14 QTLs associated with various agricultural traits, demonstrating the complex genetic architecture underlying these traits (Yang et al., 2021). Additionally, the use of structural equation models (SEQM) can help in modeling causal relationships between multiple variables, further elucidating the genetic basis of complex traits (Peñagaricano et al., 2015). 2.2 Heritability and its role in carcass trait selection Heritability is a key concept in quantitative genetics, representing the proportion of phenotypic variation in a population that is attributable to genetic variation. High heritability indicates that a significant portion of the variation in a trait is due to genetic differences among individuals, making it a crucial factor in selective breeding programs. For carcass traits in pigs, heritability estimates can guide breeders in selecting animals with desirable genetic profiles to improve traits such as backfat thickness, loin weight, and meat quality (Polasik et al., 2018; Falker-Gieske et al., 2019). The role of heritability in carcass trait selection is exemplified by studies that have identified specific genetic markers associated with these traits. For instance, the MYH7 single nucleotide polymorphism (SNP) has been linked to growth and carcass traits in pigs, with significant associations observed for traits like backfat thickness and loin eye area (Polasik et al., 2018). By understanding the heritability of these traits, breeders can make informed decisions to enhance the genetic potential of their herds, ultimately leading to improved carcass quality and economic gains. 2.3 Genetic correlation between different carcass traits Genetic correlation refers to the extent to which different traits share common genetic determinants. In the context of carcass traits in pigs, understanding genetic correlations is essential for simultaneous improvement of multiple traits. Positive genetic correlations indicate that selection for one trait will result in a correlated response in another trait, while negative correlations suggest that improving one trait may adversely affect another. For example, a study on pigs revealed significant genetic correlations between various carcass traits, such as backfat thickness and meat percentage (Figure 1), highlighting the interconnected nature of these traits (Polasik et al., 2018; Falker-Gieske et al., 2019).
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