International Journal of Molecular Ecology and Conservation, 2025, Vol.15, No.3, 111-122 http://ecoevopublisher.com/index.php/ijmec 116 of bony fish revealed that the complement 3 (C3) and factor H (Cfh) genes of bony fish have been significantly amplified in the genome (Chen et al., 2025). Similarly, the Cfh gene (complement regulatory factor) of fish has also undergone species-specific duplication, which may help to finely regulate complement activity and prevent damage to their own tissues. Therefore, in the Spanish mackerel genome, it is expected that there will also be a phenomenon of complement-related gene amplification, enabling it to fight against a variety of microbial threats in the open ocean environment. In addition to complement, other immune gene families of fish also reflect adaptive evolutionary characteristics. For example, the antiviral interferon system, antibacterial lysozyme and antimicrobial peptides, and MHC genes responsible for specific immunity have been reported to be expanded or positively selected in different species. Although there are few studies on the specific immune gene evolution of Spanish mackerel, it can be speculated that due to the wide distribution of Spanish mackerel and its migration to different sea areas, it is exposed to a variety of pathogens, and its immune genome may have undergone complex selection pressures. 4.3 Molecular basis of metabolic adaptation mechanisms Spanish mackerel is at the top of the marine food chain and needs a strong metabolic system to support its high-speed swimming and predation activities. The molecular basis of its metabolic adaptation has been a focus of research in recent years. In fish, there are many genes that affect metabolic rate and environmental tolerance, including enzyme encoding genes involved in energy metabolism pathways, hormone genes that regulate growth and development, and genes that maintain osmotic balance. The metabolic adaptive evolution of Spanish mackerel involves multiple levels, including basal metabolic rate, temperature tolerance, and nutrient utilization (Fauvelot and Borsa, 2011). Its molecular basis is the result of multi-gene coordinated evolution, including amino acid substitution and gene duplication of structural genes, as well as variation in regulatory regions and epigenetic regulation. In the future, by comparing the FADS gene family and its regulatory region sequences of Spanish mackerel and other fish, we may be able to discover genomic differences related to fat metabolism adaptation. 5 Research Progress on Environmental Selection Driving Genome Evolution of Spanish mackerel 5.1 Impact of environmental factors on genome evolution The diversity and dynamic changes of the marine environment play an important driving role in the genome evolution of marine fish. For Spanish mackerel, which is highly migratory and widely distributed, gradients in temperature, salinity, food resources, etc. in different regions may exert selection pressure on the population. Among them, water temperature gradient is often considered to be one of the key factors driving the adaptive differentiation of marine fish. In the western Pacific, due to the difference in latitude, the Yellow Sea and Bohai Sea in the north and the East China Sea and South China Sea in the south form sea areas with large seasonal temperature differences. For example, in terms of salinity, some Spanish mackerel species (such as the Indo-Pacific Spanish mackerel) prefer low-salinity environments in estuaries, which may cause them to differ in osmotic pressure regulation genes from populations that mainly live in high-salinity waters (Ito et al., 2022; Yang et al., 2022). On the issue of hypoxia, although Spanish mackerel mostly live in surface oxygen-rich waters, if a regional mid-layer hypoxic zone appears in the ocean in the future, its long-term impact may also become a new selection factor. 5.2 Methods for identifying adaptive loci in the genome Identifying adaptive loci in the genome that are affected by environmental selection is the core task of understanding environmentally driven evolution. Commonly used research methods can be summarized into two categories: detection methods based on population differentiation and detection methods based on environmental association. The first category is the population differentiation method, a typical representative of which is F_ST outlier analysis. The basic idea is to compare the degree of differentiation of different populations at each genetic marker. If the differentiation level of some loci is significantly higher than the background level under the neutral hypothesis, they are regarded as candidate loci affected by selection. This type of method includes the classic F_ST distribution method, Bayesian hierarchical model (such as BayeScan) and principal component analysis (Balding and Beaumont, 2004).
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