International Journal of Molecular Ecology and Conservation, 2025, Vol.15, No.3, 111-122 http://ecoevopublisher.com/index.php/ijmec 117 The second category is environmental association analysis, also known as landscape genomics method. Its characteristic is to directly associate genetic variation with environmental variables and find loci where allele frequency is significantly correlated with environmental factors (such as temperature, salinity, etc.). Typical methods include genotype-environment association analysis (GEA), such as Bayenv, LFMM and other models, and spatial analysis based on pointwise regression. Compared with pure population comparison, environmental association analysis can locate specific environmental factors that drive selection (Foll and Gaggiotti, 2008). 5.3 Research progress on selection signals driven by the environment In species with highly continuous distribution, examples of weak selection signals are often observed. Segovia et al. (2024) showed that in different environments, although the overall genetic homogeneity was high, a very small number of genomic loci were detected to show signs of adaptive differentiation. By analogy to the widespread Spanish mackerel, its adaptive evolutionary signal may also be overwhelmed by a large number of neutral variations. Currently, the public genetic studies of Spanish mackerel populations rarely report significant local adaptation signals, and most believe that its population genetic structure is shallow. For example, Magallon-Gayon et al. (2016) studied the Monterey Spanish mackerel (S. concolor) from the Gulf of California and found that the genetic variation of this species in different regions of the Gulf was highly homogeneous, presenting a global population with random mating. In recent years, some high-throughput studies have begun to report genomic selection signals in Spanish mackerel and tuna. Feutry et al. (2025) used whole genome scanning to compare different geographical populations of three closely related migratory fishes in the Indian Ocean (including narrow-banded Spanish mackerel), and the results revealed a wide range of genetic differentiation structures. It is worth noting that the anthropogenic environment (such as fishing) also exerts selection on the evolution of Spanish mackerel. Long-term overfishing is believed to have led to the "artificial selection" effect (FIE) of fish, such as overfishing tending to large individuals will select small precocious individuals for survival. For Japanese Spanish mackerel, phenotypic changes such as earlier maturity age and smaller body size have been observed after decades of high-intensity trawling. In the study of adaptive evolution of swordfish, a breakthrough discovery is the role of epigenetics such as DNA methylation in local adaptation. Japanese swordfish research shows that despite the lack of genetic differentiation between populations in different waters along the Chinese coast, their epigenomes differ systematically between the north and the south. 6 Specific Case Studies of Adaptive Evolution at the Genome Level 6.1 Case analysis of temperature adaptation Temperature is a key environmental factor affecting the geographical distribution and reproductive success of marine organisms. For migratory fish such as Spanish mackerel, temperature adaptability is directly related to their annual migration range and the success or failure of spawning and hatching. The population of Pacific mackerel (similar to Spanish mackerel in ecological niche) showed a population decline under the background of climate warming, which was attributed to the reduction of habitat suitable for spawning and hatching due to rising sea temperatures (Lee et al., 2022; Ray et al., 2022). This shows that the species has not yet accumulated enough high-temperature resistant mutations through evolution to cope with the rapid rise in temperature. Atlantic silverside (Menidia menidia) is a nearshore fish with a wide distribution across latitudes. Studies have found that there are obvious differences in growth and reproduction between northern and southern populations, which are considered to be the result of local adaptation to different temperature environments. Whole-genome analysis further pointed out that there are a large number of linked genomic regions that have undergone differential selection behind these phenotypic differences. Although silverside is not a Spanish mackerel, the "genomic adaptation along the latitudinal gradient" it embodies may also exist in Spanish mackerel. 6.2 Analysis of genomic adaptation under salinity changes Spanish mackerels usually live in high-salinity marine environments, but some species also regularly enter coastal waters with low salinity, such as estuaries. Salinity fluctuations challenge the osmotic pressure regulation mechanism of fish, and therefore provide an opportunity to study the evolution of salinity adaptation. A typical
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