International Journal of Molecular Zoology 2024, Vol.14, No.1, 22-30 http://animalscipublisher.com/index.php/ijmz 24 Studies have shown that immune-related genes are one of the important regulators of porcine disease resistance. For example, major histocompatibility complex (MHC) class genes play a key role in the immune response, and the proteins they encode are involved in the process of antigen presentation and recognition, thus affecting the pig's resistance to pathogens (Radwan et al., 2020). Pathogen receptor gene families, such as Toll-like receptor (TLR) family genes, also play an important role in disease resistance. The receptors encoded by these genes can recognize the specific molecular structure of pathogens and initiate corresponding immune responses, thus playing an important role in regulating porcine disease resistance. In addition to immune-related genes, some other genes have also been found to be closely related to disease resistance in pigs. For example, variations in some genes that regulate apoptosis (programmed cell death) and genes that regulate inflammatory responses may affect pigs' ability to clear pathogens, thereby affecting their disease resistance. The study also found that genes related to antioxidant capacity, cell signaling, etc. are also related to porcine disease resistance. The genetic basis of porcine disease resistance is a complex system of multi-gene regulation. Interactions and polymorphisms between different genes lead to the existence of rich disease resistance phenotypes in pig herds. In-depth study of the genetic basis of pigs and the discovery of key genes and genetic variations related to disease resistance are of great significance for the selection of pig breeds with strong disease resistance and excellent production performance. 1.3 The mechanism of influence of genetic variation on disease resistance SNPs present in the genome that determine an individual's level of infection and resistance to a specific disease. Studies have shown that porcine disease resistance is related to genetic variations in multiple genes involved in the regulation of the immune system, pathogen recognition and clearance, etc. By analyzing genetic variation in pigs, key genes and SNPs related to disease resistance can be discovered, providing important information for the selection of disease-resistant pig breeds. Studies have shown that immune-related genes (such as MHC genes), pathogen receptor genes (such as TLR family genes), and cytokine and chemokine genes play an important role in disease resistance in pigs. Different alleles or SNPs of these genes will affect the pig's ability to recognize and eliminate pathogens, thereby affecting its disease resistance. The study also found that some genes related to apoptosis, inflammatory response, etc. are also closely related to porcine disease resistance. Porcine disease resistance is regulated by complex genetic factors, among which genetic variation plays a key role in the formation of individual disease resistance. In-depth study of the genetic basis of pigs is of great significance for breeding pig breeds with high disease resistance and improving breeding efficiency. 2 Application of GWAS in Porcine Disease Resistance Research 2.1 Basic principles and methods of GWAS GWAS (Genome-wide association analysis) is a powerful method designed to unravel the correlation between genetic variation and complex traits. The basic principle is to discover genetic variations related to target traits by comparing genotypic differences between individuals with specific traits and normal control individuals in large-scale samples (Cano-Gamez and Trynka, 2020). The GWAS method includes multiple key steps, including sample recruitment, genotype determination, and data analysis. Sample recruitment for GWAS is the first step in research, and a sufficient number and diversity of samples need to be collected to ensure the reliability and representativeness of the results. These samples typically include individuals with the target trait and normal control individuals to allow for comparative analysis. Genotype determination is one of the key steps in GWAS (Buniello et al., 2019). Researchers used modern high-throughput sequencing technology to conduct genome-wide analysis of the DNA in the samples to determine the SNP distribution of each individual across the entire genome (Figure 2). These SNPs serve as markers of genetic variation for subsequent association analysis. Data analysis is one of the core steps of GWAS. At this stage, researchers conduct association analysis between the collected SNP data and the target traits to determine which SNPs are significantly associated with the target traits. Usually, statistical methods such as linear regression or
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