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International Journal of Marine Science (online), 2025, Vol. 15, No. 4 ISSN 1927-6648 http://aquapublisher.com/index.php/ijms © 2025 AquaPublisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved. Latest Content Comparative Genomics of Oysters and Evolutionary Adaptation to Marine Environments Liting Wang, Manman Li International Journal of Marine Science, 2025, Vol. 15, No. 4, 179-185 Global Genetic Flow and Population Structure of Scomberomorus spp.: Insights from Multi-Genomic Data Analysis Liqing Chen, Lingfei Jin International Journal of Marine Science, 2025, Vol. 15, No. 4, 186-198 Effect of Ocean Acidification on the Metabolism and Behavior of Tropical Sea Cucumbers Zhen Liu, Yeping Han International Journal of Marine Science, 2025, Vol. 15, No. 4, 199-208 Symbiotic and Antagonistic Relationships between Microalgae and Environmental Microorganisms Weihong Liu, Qikun Hang International Journal of Marine Science, 2025, Vol. 15, No. 4, 209-219 Strategies for Enhancing Carbon Sequestration through Mangrove Restoration and Management Hongpeng Wang, Haimei Wang International Journal of Marine Science, 2025, Vol. 15, No. 4, 220-232
International Journal of Marine Science, 2025, Vol.15, No.4, 179-185 http://www.aquapublisher.com/index.php/ijms 179 Feature Review Open Access Comparative Genomics of Oysters and Evolutionary Adaptation to Marine Environments Liting Wang, Manman Li Hainan Institute of Biotechnology, Haikou, 570206, Hainan, China Corresponding author: manman.li@hitar.org International Journal of Marine Science, 2025, Vol.15, No.4, doi: 10.5376/ijms.2025.15.0016 Received: 05 Jun., 2025 Accepted: 10 Jul., 2025 Published: 20 Jul., 2025 Copyright © 2025 Wang and Li, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Wang L.T., and Li M.M., 2025, Comparative genomics of oysters and evolutionary adaptation to marine environments, International Journal of Marine Science, 15(4): 179-185 (doi: 10.5376/ijms.2025.15.0016) Abstract Oysters are important for both marine ecosystems and aquaculture, but they are under threat from climate change, pollution, and disease.Recent studies of oyster genomes-such as the Pacific oyster (Crassostrea gigas) and the Hong Kong oyster (Magallana hongkongensis)-have uncovered key differences in their genetic structure, gene activity, and stress responses. These discoveries help explain how oysters manage to survive in environments with different salinity, temperature, and pathogens. The comparison between C. gigas and M. hongkongensis shows clear genetic divergence related to their habitats. By identifying genes linked to stress tolerance, researchers can support future breeding and conservation efforts-especially as climate conditions continue to change. Keywords Oyster genomics; Environmental adaptation; Stress response; Salinity tolerance; Conservation genetics 1 Introduction Oysters are not only delicious food on people's tables, they also have other important functions. They can purify seawater, provide habitats for small marine organisms, and help maintain the nutrient balance in coastal environments (Parker et al., 2023; Zapata-Restrepio et al., 2023). In many coastal areas, oyster farming has become part of the local economy, providing many jobs and food sources. However, oysters are under growing pressure. Warmer oceans, heavier pollution, and the emergence of new diseases are making it harder for oysters to survive and reproduce (Xu et al., 2017; Brew et al., 2020). Different oyster species react in different ways-some can handle stress better than others. To understand why some oysters can withstand these challenges, scientists began to study their genes. By comparing the genetic differences between different species and populations, researchers have found genetic characteristics related to disease resistance and environmental adaptation (Eierman and Hare, 2016; Farias et al., 2017; Sullivan and Proestou, 2021; Dupoué et al., 2023). These research results also provide a reference for future oyster breeding and resource protection. 2 Progress in Oyster Genome Sequencing 2.1 Sequencing of Crassostrea and other related oysters In recent years, oyster genome sequencing technology has been greatly improved. Several important oysters, including the Pacific oyster (Crassostrea gigas), the Yangtze River oyster (Crassostrea ariakensis), the European oyster (Ostrea edulis), and the Hong Kong oyster (Magallana hongkongensis), have completed chromosome-level genome assemblies (Li et al., 2020; Qi et al., 2021; Gundappa et al., 2022). For example, the genome of C. gigas is divided into 10 pseudochromosomes, showing complex structure and genetic diversity (Qi et al., 2021; Mrowicki and Uhl, 2024). Different sequencing projects have different focuses. Some are used to study the evolution of oysters, while others directly provide data for breeding. For example, the genome of C. ariakensis can be used for conservation research and is also suitable for reference in aquaculture breeding (Li et al., 2024a). The genome of the European
International Journal of Marine Science, 2025, Vol.15, No.4, 179-185 http://www.aquapublisher.com/index.php/ijms 180 oyster combines multiple sequencing methods to improve the accuracy of gene identification (Gundappa et al., 2022; Adkins and Mrowicki, 2023). The genome of the Hong Kong oyster helps study some ancient gene families, such as the homeobox gene (Li et al., 2020). 2.2 Common sequencing methods and existing problems There is no single method that fits all oyster species. Researchers usually combine several sequencing technologies-such as long-read platforms like PacBio and Oxford Nanopore, short-read Illumina sequencing, and Hi-C mapping to assemble the genome (Qi et al., 2021; Gundappa et al., 2022). However, assembling the oyster genome is not easy. Many oysters have a large number of repeated fragments in their DNA, sometimes even accounting for more than half, and the differences between genes are also large. In addition, some structural changes, such as gene duplication, will make the assembly process more complicated (Qi et al., 2021; Li et al., 2024b). To solve these problems, researchers will also introduce transcriptome information and genetic maps to help improve the accuracy of gene annotation (Gundappa et al., 2022). Despite these difficulties, the recently completed oyster genome has a high level of completeness, and the identification of some important genes has become clearer. These data have begun to play a role in oyster biological research, adaptation analysis and breeding practices (Qi et al., 2021; Gundappa et al., 2022). 3 Genomic Architecture and Species Variation 3.1 Genome size and repetitive elements Oyster genomes vary greatly in size, and many contain a large number of repetitive sequences. For example, the genome of the Pacific oyster (Crassostrea gigas) has many transposable elements. These “jumping genes” may increase genetic diversity and help improve adaptability (Zhang et al., 2012). Another case is the Sydney rock oyster (Saccostrea glomerata), whose genome is about 784 Mb and also rich in repetitive sequences (Powell et al., 2018). These repetitive features aren’t random noise. In marine bivalves generally, they seem to have a function: helping the organisms adapt quickly to environmental changes. That said, not every species shows the same pattern in the same way, and the relationship between genome architecture and adaptability is still being investigated (Zhang et al., 2012; Powell et al., 2018). 3.2 Species-specific genes and structural features Gene families that help oysters deal with stress and pathogens have expanded in some species more than others. In both C. gigas andS. glomerata, for example, researchers have found more copies of genes like heat shock proteins and apoptosis inhibitors-proteins that help deal with stress, salinity swings, or infections (Zhang et al., 2012; Zhang et al., 2016; Powell et al., 2018). In Crassostrea ariakensis, certain genes-especially those from solute carrier families that help cells manage salt and temperature stress-show clear signs of being favored by natural selection (Zhang et al., 2022). It’s not just the genes themselves that matter. The regions that control when and how these genes are activated also differ, which can influence how oysters respond to their environment. 4 Genomic Features of Adaptation to Marine Environments 4.1 Genes related to temperature and salt tolerance To survive in complex and changing marine environments, oysters have evolved several key gene families related to temperature and salinity tolerance. These include solute carrier genes, heat stress response genes, and various regulatory elements. In multiple oyster species, these genes exhibit signs of adaptive evolution, indicating their critical role in responding to environmental stress (She et al., 2018). For example, in the estuarine oyster, several solute carrier genes under positive selection-such as Slc23a2 and Mct12-have been identified. These genes are primarily located on chromosome 9 and form distinct gene clusters. As shown in the CIRCOS plot below, these clusters are highlighted in purple-red arcs, indicating a concentrated distribution. This pattern suggests that these regions may be under directional selection, playing a specialized role in salinity adaptation (Figure 1) (Li et al., 2021).
International Journal of Marine Science, 2025, Vol.15, No.4, 179-185 http://www.aquapublisher.com/index.php/ijms 181 Figure 1 a Estuarine oyster (photo by Lumin Qian). b Hi-C interaction heatmap showing 10 chromosomes of the estuarine oyster. c CIRCOS plot showing 10 chromosomes (a), the distribution of GC content (b), transposable elements (c), coding sequences (d), and duplicated gene cluster of the solute carrier families showing selection signals (e, also see Supplementary Figure 13). d Summary statistics of the genome assembly (Adopted from Li et al., 2021) In addition, classic stress-related genes are also involved in environmental responses. For instance, Cg_CLCN7 is responsible for chloride ion transport, and Cg_AP1 regulates apoptosis; both are significantly upregulated under high-salinity conditions (She et al., 2018). However, the distribution of these functional genes is not uniform across populations. Oysters from high-salinity or high-temperature habitats often carry more favorable gene variants (Li et al., 2020), reflecting a genetic basis for local adaptation. Nonetheless, differences at the genetic level do not always lead to observable phenotypic changes, as environmental context and gene-environment interactions remain important factors. 4.2 Metabolic and antioxidant response mechanisms In addition to activating stress-related genes, oysters also adjust their metabolism when facing harsh environments. For example, some oysters living in high-salinity seawater will activate pyruvate and taurine metabolism more frequently. These metabolic processes help cells maintain normal function and reduce damage caused by salinity stress (She et al., 2018; Zhang et al., 2022). Some gene families, such as GPCRs, are frequently duplicated and show different responses depending on the type of stress-whether heat, salinity, or pollutants (Fu et al., 2022). These flexible responses may explain why oysters are so widely distributed.
International Journal of Marine Science, 2025, Vol.15, No.4, 179-185 http://www.aquapublisher.com/index.php/ijms 182 4.3 Epigenetics and environmental response Genetics isn’t the whole picture. Epigenetic changes-especially DNA methylation—are now seen as another layer of adaptation. For example, intertidal oysters tend to show lower methylation levels and more flexibility in methylation patterns when exposed to heat stress. In contrast, subtidal species have higher, more stable methylation profiles. These methylation changes affect the expression of genes involved in cell death, development, and ion balance. In other words, it’s not just about what genes oysters have-but also how they’re regulated. This may give oysters the ability to respond quickly to environmental changes (Wang et al., 2020). 5 Functional Insights from Transcriptome Analyses 5.1 Expression in intertidal and subtidal species Not only does the environment affect the characteristics of oysters, but their gene expression also shows how they adapt step by step. The activity of some genes in different salinities is often related to the growth rate or survival rate of oysters (Wang et al., 2020; Zhang et al., 2022). However, this relationship is not absolute. Different species have different responses, and the interaction between genes and environment cannot always be accurately predicted (Liu and Huang, 2024). 5.2 Response to pollution and pathogens When oysters encounter pollution or infection, some specific genes are activated. For example, the GPCR gene family will produce different responses when facing heavy metals or pathogens (Zhang et al., 2016; Fu et al., 2022). These genes can help oysters reduce stress and are important for them to survive in harsh or polluted waters. But adaptation isn’t just controlled by one or two genes. Many of these responses involve multiple genes working together, and the effect can depend on the environment. This is known as polygenic adaptation, and it shows how complex oyster responses to stress can be (Bernatchez et al., 2018; Fu et al., 2022). 6 Evolution of Oyster Immune Systems 6.1 Innate immune gene expansions In the intertidal zones where pathogens are abundant and environmental conditions fluctuate frequently, oysters have gradually evolved a complex innate immune system. Studies have shown that several immune-related gene families have expanded in oyster genomes, particularly Toll-like receptors (TLRs), inhibitor of apoptosis proteins (IAPs), and caspases. These key genes exhibit both increased copy numbers and enhanced expression across multiple oyster species (PZhang et al., 2016; Owell et al., 2018). Such expansions help oysters recognize a wide range of pathogens and improve their ability to regulate cellular stress responses. 6.2 Pathogen recognition systems The Toll-like receptor (TLR) family has expanded considerably in oysters. This helps explain their ability to sense a wide range of pathogens in environments where microbial diversity is high (Zhang et al., 2016; Powell et al., 2018). But again, not all TLRs act the same, and some are more responsive than others depending on the challenge. Lectins and antimicrobial peptides are another major line of defense. These molecules identify and neutralize pathogens directly. Oysters show a great deal of variation in these genes, which is thought to support their survival across different microbial landscapes (Zhang et al., 2016; Powell et al., 2018). 7 Case Study: Genetic Comparison of Pacific and Hong Kong Oysters 7.1 Genetic differences and salinity adaptation There are obvious genetic differences between Pacific oysters (Crassostrea gigas) and Hong Kong oysters (Crassostrea hongkongensis). Pacific oysters are more adapted to living in seawater with higher salinity, while Hong Kong oysters are more adapted to environments with lower salinity (Zhang et al., 2022). This difference is not only reflected in their distribution areas, but also in their growth rates and survival rates, and each performs better in the environment they are adapted to. When faced with salinity changes, the genes activated by the two oysters are also different. They respond to stress through different gene regulation methods. This difference is closely related to the environment in which they live for a long time, indicating that they gradually adapt to their respective living conditions through genetic changes.
International Journal of Marine Science, 2025, Vol.15, No.4, 179-185 http://www.aquapublisher.com/index.php/ijms 183 7.2 Genetic pathways related to stress adaptation The genes of the two oysters also differ in the part that controls the response to salinity changes. Pacific oysters can activate some specific metabolic pathways under high salinity conditions, while Hong Kong oysters show similar coping mechanisms under low salinity conditions (Zhang et al., 2022). This shows that their genetic systems have formed ways to adapt to various environments, which is the result of long-term natural selection. Using the Pacific oyster (Crassostrea gigas) as a model, the core stress and immune pathways activated under various stress conditions-including high temperature, heavy metals, low salinity, and pathogen exposure—are illustrated (Figure 2) (Zhang et al., 2016). Gene families marked with bold black borders in the figure, such as HSPs, SODs, and IAPs, represent expanded genes that are significantly upregulated under multiple stress scenarios. This capacity to respond to diverse stressors is a clear sign of the evolutionary enhancement of the oyster’s innate immune system. When exposed to salinity stress, each species activates a different set of genes. These differences in gene expression show that they rely on distinct biological responses to adapt. Their genetic patterns line up with their home environments, pointing to the strong influence of local adaptation on their evolution. Figure 2 The major stress-responsive pathway-related genes inCrassostrea gigas (Adopted from Zhang et al., 2016) Image caption: Protein folding systems included HSPs and HSF in the heat shock response and GRP78, GRP94, PERK, CRT, CNX, eIF2α, and Ire1 in the endoplasmic reticulum unfolded-protein response (UPR ER). Apoptotic pathways included IAPs, BAG, Bcl2 like, caspases, BI-1, TNFR, and FADD. The xenobiotic biotransformation and antioxidant systems included CYP450, MO, SOD, Gpx, Prx, and CAT. Boxes with bold black borders indicate oyster expanded gene families, including HSPs, IAPs, and SODs, and the filled colors represent the degree of upregulation in RPKMtreatment/RPKMcontrol by stress, using transcriptomes from oysters challenged with nine different types of stressors (Adopted from Zhang et al., 2016) 8 Implications for Conservation and Aquaculture 8.1 Breeding applications of genetic markers With more is known about stress tolerance genes, especially those linked to temperature and salinity, practical applications are emerging. Molecular markers-such as adaptive SNPs-are now being used to select oyster strains better suited for particular environments. It’s not just theory anymore. High-throughput genotyping has made these tools available on a broader scale. That said, selective breeding isn't a one-size-fits-all solution. The usefulness of certain markers can vary by location and environmental condition, so there’s still a need for local adaptation strategies.
International Journal of Marine Science, 2025, Vol.15, No.4, 179-185 http://www.aquapublisher.com/index.php/ijms 184 8.2 Building resilience to climate pressure Genomic studies have revealed more than just interesting patterns-they’ve made it possible to think about resilience in a more structured way. Variations in gene regulation, family expansion, and population-level adaptation all play into how oysters cope with climate stress. This knowledge helps managers and breeders alike. If we know which populations have the genetic tools to tolerate future conditions, conservation and aquaculture planning can be more targeted. In a time of rising sea temperatures and unpredictable salinity shifts, that information could make a real difference. Acknowledgements The authors gratefully acknowledge the support provided by Cai X.G. and thank the two peer reviewers for their suggestions. Conflict of Interest Disclosure The authors confirm that the study was conducted without any commercial or financial relationships and could be interpreted as a potential conflict of interest. References Adkins P., and Mrowicki R., 2023, The genome sequence of the European flat oyster Ostrea edulis (Linnaeus 1758), Wellcome Open Research, 8: 556. https://doi.org/10.12688/wellcomeopenres.19916.1 Bernatchez S., Xuereb A., Laporte M., Benestan L., Steeves R., Laflamme M., Bernatchez L., and Mallet M., 2018, Seascape genomics of eastern oyster (Crassostrea virginica) along the Atlantic coast of Canada, Evolutionary Applications, 12: 587-609. https://doi.org/10.1111/eva.12741 Brew D.W., Black M.C., Santos M., Rodgers J., and Henderson W.M., 2020, Metabolomic investigations of the temporal effects of exposure to pharmaceuticals and personal care products and their mixture in the eastern oyster (Crassostrea virginica), Environmental Toxicology and Chemistry, 39(2): 419-436. https://doi.org/10.1002/etc.4627 Dupoué A., Mello D., Trevisan R., Dubreuil C., Quéau I., Petton S., Huvet A., Guével B., Com E., Pernet F., Salin K., Fleury E., and Corporeau C., 2023, Intertidal limits shape covariation between metabolic plasticity oxidative stress and telomere dynamics in Pacific oyster (Crassostrea gigas), Marine Environmental Research, 191: 106149. https://doi.org/10.1016/j.marenvres.2023.106149 Eierman L., and Hare M., 2016, Reef-specific patterns of gene expression plasticity in eastern oysters (Crassostrea virginica), The Journal of Heredity, 107(1): 90-100. https://doi.org/10.1093/jhered/esv057 Farias N., De Oliveira N., and Da Silva P., 2017, Perkinsus infection is associated with alterations in the level of global DNA methylation of gills and gastrointestinal tract of the oyster Crassostrea gasar, Journal of Invertebrate Pathology, 149: 76-81. https://doi.org/10.1016/j.jip.2017.08.007 Fu H., Tian J., Shi C., Li Q., and Liu S., 2022, Ecological significance of G protein-coupled receptors in the Pacific oyster (Crassostrea gigas): pervasive gene duplication and distinct transcriptional response to marine environmental stresses, Marine Pollution Bulletin, 185: 114269. https://doi.org/10.1016/j.marpolbul.2022.114269 Gundappa M., Peñaloza C., Regan T., Boutet I., Tanguy A., Houston R., Bean T., and Macqueen D., 2022, Chromosome‐level reference genome for European flat oyster (Ostrea edulis L.), Evolutionary Applications, 15: 1713-1729. https://doi.org/10.1111/eva.13460 Li A., Dai H., Guo X.M., Zhang Z.Y., Zhang K.X., Wang C.G., Wang W., Chen H.J., Li X.M., Zheng H.K., Zhang G.G., and Li L., 2021, Genome of the estuarine oyster provides insights into climate impact and adaptive plasticity, Communications Biology, 4(1): 1287. https://doi.org/10.1038/s42003-021-02823-6 Li A., Wang C., Wang W., Zhang Z., Liu M., She Z., Jia Z., Zhang G., and Li L., 2020, Molecular and fitness data reveal local adaptation of southern and northern Estuarine oysters (Crassostrea ariakensis), Frontiers in Marine Science, 7: 589099. https://doi.org/10.3389/fmars.2020.589099 Li A., Zhao J., Dai H., Zhao M., Zhang M., Wang W., Zhang G., and Li L., 2024a, Chromosome-level genome assembly of the Suminoe oyster Crassostrea ariakensis in South China, Scientific Data, 11(1): 1296. https://doi.org/10.1038/s41597-024-04145-8 Li L., Li A., Song K., Meng J., Guo X., Li S., Li C., De Wit P., Que H., Wu F., Wang W., Qi H., Xu F., Cong R., Huang B., Li Y., Wang T., Tang X., Liu S., Li B., Shi R., Liu Y., Bu C., Zhang C., He W., Zhao S., Li H., Zhang S., Zhang L., and Zhang G., 2018, Divergence and plasticity shape adaptive potential of the Pacific oyster, Nature Ecology and Evolution, 2: 1751-1760. https://doi.org/10.1038/s41559-018-0668-2 Li Y., Nong W., Baril T., Yip H.Y., Swale T., Hayward A., Ferrier D.E.K., and Hui J., 2020, Reconstruction of ancient homeobox gene linkages inferred from a new high-quality assembly of the Hong Kong oyster (Magallana hongkongensis) genome, BMC Genomics, 21(1): 713. https://doi.org/10.1186/s12864-020-07027-6
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International Journal of Marine Science, 2025, Vol.15, No.4, 186-198 http://www.aquapublisher.com/index.php/ijms 186 Research Insight Open Access Global Genetic Flow and Population Structure of Scomberomorus spp.: Insights from Multi-Genomic Data Analysis Liqing Chen1, Lingfei Jin2 1 Tropical Marine Fisheries Research Center, Hainan Institute of Tropical Agricultural Resources, Sanya, 572025, Hainan, China 2 Institute of Life Science, Jiyang College of Zhejiang A&F University, Zhuji, 311800, Zhejiang, China Corresponding author: lingfei.jin@jicat.org International Journal of Marine Science, 2025, Vol.15, No.4, doi: 10.5376/ijms.2025.15.0017 Received: 08 Jun., 2025 Accepted: 12 Jul., 2025 Published: 27 Jul., 2025 Copyright © 2025 Chen and Jin, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Chen L.Q., and Jin L.F., 2025, Global genetic flow and population structure of Scomberomorus spp.: insights from multi-genomic data analysis, International Journal of Marine Science, 15(4): 186-198 (doi: 10.5376/ijms.2025.15.0017) Abstract The genus Scomberomorus spp. is an important middle- and upper-level economic fish with significant economic and ecological value. However, high-intensity development of global fisheries puts mackerel populations at risk of decreased genetic diversity and changes in population structure. This study reviews the progress of global gene flow and population structure in the genus Mackerel fish, and focuses on the role of multigenomic data in it. We also deeply explored the influence mechanisms of environmental factors such as ocean currents, seawater temperature salts, and overfishing on gene exchange and population structure of mackerel. Studies have shown that there is a certain degree of genetic differentiation between different geographical populations of mackerels, and it also maintains genetic communication through migration and currents; among which ocean currents can play a dual role in connecting populations and isolating populations. This study finally proposes that the genetic research on mackerel population still has shortcomings such as regional coverage imbalance and single marker types. In the future, research should be strengthened in combination with multigenomic data and ecological monitoring to support the sustainable management of marine fishery resources and the effective protection of mackerel species. Keywords Mackerel; Gene flow; Population structure; Genetic diversity; Multigenomic data; Fishery management 1 Introduction The genus Scomberomorus belongs to the family Scombridae, including about 20 species such as narrowband mackerel, Japanese mackerel, and broadband mackerel. It is an important middle- and upper-level predatory fish in tropical and temperate waters around the world. The meat of mackerel is delicious, rich in high-quality protein and unsaturated fatty acids, and has high economic value worldwide. For example, Japanese mackerel (S. niphonius) is a famous edible fish "mackerel" in China and East Asia. The narrow-band mackerel (S. commercial) is widely distributed in the Indian Ocean-Western Pacific and is an important fishery resource for coastal countries. In the Western Atlantic Ocean, Brazilian mackerel (S. brasiliensis) and kingfish (S. cavalla) support local commercial and recreational fisheries (Gold et al., 2010). Since mackerels are generally located in the high trophic level of marine food networks, they play an important role in maintaining the health of marine ecosystems. In recent decades, the global fishing intensity has continued to increase, and many mackerel populations have shown signs of decline. Brazilian mackerel production has dropped significantly along the northeastern coast of Brazil and is believed to have overfished (Siccha-Ramirez et al., 2018). Offshore China, the annual catch of Japanese mackerels has exceeded 400 000 tons in recent years, making it an important catch species in the Bohai Sea, the Yellow Sea and the East China Sea. However, with offshore environmental pollution and overfishing, its germplasm resources are facing decay, and the decline in genetic diversity may endanger population sustainability. Protecting the genetic resources of marine fish such as mackerels and maintaining the stability of their population structure has become one of the important tasks of fishery management. Genetic diversity is the basis for species to adapt to environmental changes and resist risks such as disease. Improving the understanding of the genetic structure of target fish can help formulate scientific management and conservation measures.
International Journal of Marine Science, 2025, Vol.15, No.4, 186-198 http://www.aquapublisher.com/index.php/ijms 187 Traditionally, fishery science has studied the migration routes and population ownership of fish through marking release, catch statistics and ecological surveys. However, these methods often have difficulty accurately characterizing the degree of genetic communication. The development of molecular genetics technology provides a more direct tool for analyzing fish population structure. Since the end of the 20th century, some scholars have begun to use mitochondrial DNA sequence variation and nuclear DNA microsatellite markers to analyze the genetic diversity of mackerel populations (Johnson et al., 2021). Entering the 21st century, with the advent of high-throughput sequencing technologies, it has become possible to conduct population genetic research using genome-wide SNP markers and simplified genome sequencing methods (such as RAD-seq, etc.), allowing us to identify subtle population differentiation at the genome level (Joy et al., 2020). Based on the above background, this study reviews the systematic classification and global distribution pattern of the genus Mackerel, introduces its main species and their respective geographical distribution ranges and ecological habits; summarizes the historical progress of genetic diversity and population structure research, including the early use of genetic markers such as mitochondrial DNA and microsatellites, as well as the application of nuclear genomic SNP and multigenomic technology in recent years. Comparing different seas around the world. 2 System Classification and Geographical Distribution of Mackerel 2.1 The main species of the genus Scomberomorus spp. The genus Scomberomorus belongs to the family Macadae, commonly known as Macadae and Macadae. It is a medium-sized migratory fish species, mainly distributed in the coastal areas of China, Japan and South Korea in the northwest Pacific, and also enters the Bohai Sea and the Yellow Sea. Broadband Macadae (S. guttatus), distributed in the Indo-Western Pacific, including the South China Sea and Southeast Asia, commonly known as Spot Macadae or Indo-Pacific King Macadae; Pacific Spanish Macadae (S. maculatus) and King Macadae (S. cavalla), distributed along the western Atlantic Ocean; S. brasiliensis, distributed in the Caribbean Sea and the Atlantic Ocean in South America; and some regionally distributed species such as S. semifasciatus in Australia and West African Macadae (S. tritor) etc. In addition, the "Korean mackerel" (S. koreanus) discovered in the Indian Ocean in recent years has been identified as an independent species through morphological and genetic identification, and is distributed along the northern coast of the Indian Ocean (Jeena et al., 2022; Zeng et al., 2022). These species are medium to large (usually 30 cm to more than 1 meter in length), have slender bodies, side flatness, sharp teeth, and have many spots or stripes on their backs. They are fierce predators. Despite the similar appearance, different species have differences in scales, tooth type, spine number and body color patterns, which can be classified and identified. 2.2 Global distribution pattern and ecological habitat environment The genus mackerel mainly lives in the continental shelf and coastal waters around the islands, and is a highly migratory fish. In the Indian Ocean-Western Pacific region, narrow band mackerels are widely distributed, from the Red Sea and the Arabian Sea, through the Indian coast to Southeast Asia and the South China Sea, and extending to the Melanesian Islands in northern Australia and the Western Pacific. Japanese mackerel mainly moves in the northwest Pacific Ocean, ranging from the Bohai Sea and the Yellow Sea to the north, through the East China Sea to the northern part of the South China Sea, and to the coast of Vietnam in the south. Broadband mackerel is common in the Indian Ocean and South China Sea and offshore Southeast Asia (Jeena et al., 2022), and is an important catch in the Gulf of Bengal, the Gulf of Thailand and the Malay Islands (Figure 1). In Atlantic waters, king fish (also known as narrow-tooth mackerel) is distributed in warm waters of the Western Atlantic Ocean, extending from the southeastern coast of the United States and the Gulf of Mexico to southern Brazil; Spanish mackerel (Flower Spot Mackerel) is more common on the Atlantic coast of the United States and the northern Gulf of Mexico; Sierra mackerel is mainly distributed in the Caribbean Sea and northern coast of South America (Cunha et al., 2020). Most species prefer warm sea areas with water temperatures of 20~30℃, and have significant seasonal migration patterns throughout the year: they migrate to higher latitude spawning grounds in summer, and return to lower latitude waters to overwinter in winter.
International Journal of Marine Science, 2025, Vol.15, No.4, 186-198 http://www.aquapublisher.com/index.php/ijms 188 2.3 Brief description of the relationship between population characteristics and evolution Due to geographical isolation and environmental differences, there may be differences in phenotypic characteristics and genetic composition of mackerel populations distributed in different sea areas. Through morphological research in the early days, some scholars divided Japanese mackerels along the coast of China into Yellow and Bohai Sea populations and East China Sea populations based on metrology characteristics, suggesting that the groups in these two major sea areas may be independent of each other. However, mitochondrial DNA sequence analysis did not detect significant genetic differentiation between the Yellow Sea and East China Sea populations, showing high genetic similarity (Zhu et al., 2016). This suggests that traditional morphological classifications may be affected by environmental shaping, and genetic markers can provide independent evidence. It is generally believed that Japanese mackerels along the coast of China may have genetic differentiation in the Yellow and Bohai Seas and the East China Sea, but the degree is relatively low. In the Indian Ocean region, studies have found that narrowband mackerels may have east-west differentiation across the "Wallace Line": East Indian populations are genetically different from Western Australian populations, similar to the pattern of differentiation of other Indo-Pacific marine organisms on both sides of this biogeographical boundary. The mackerel population along the Atlantic Ocean is completely different from the Indo-Pacific species because it is separated from the North and South American continents. But inside the Atlantic Ocean, populations in different regions are closely linked. Taking the Sierra mackerel on the coast of Brazil as an example, the populations from Kumana, Venezuela to the southern end of Brazil have low genetic diversity and frequent sharing of haplotypes, indicating that it is a single genetic library. This result suggests that the Sierra mackerel population on the western Atlantic Ocean is integrated and has no significant differentiation (Santa Brígida et al., 2007; Cunha et al., 2020). Figure 1 Digital X-ray images of Scomberomorus species (A-J) from the Northern Indian Ocean revealing the diversity, fork length (FL), and number of vertebrae (Adopted from Jeena et al., 2022) 3 Research Progress on Genetic Diversity and Population Structure 3.1 Early study of mitochondrial DNA and microsatellite markers Molecular research on the genetic structure of mackerel populations began in the late 20th and early 21st century. Mitochondrial DNA (mtDNA) is widely used in fish population geography research due to its single parental
International Journal of Marine Science, 2025, Vol.15, No.4, 186-198 http://www.aquapublisher.com/index.php/ijms 189 inheritance and high variability rate. One of the earliest related work was the analysis of the sequence of the Japanese mackerel mtDNA control region. The study found that the Japanese mackerel population in the Yellow Sea and East China Sea in China share a majority haplotype, with low nucleotide diversity and no significant geographical differentiation (Widayanti et al., 2024). Nuclear DNA microsatellite (SSR) markers are also used in early population research of mackerels due to their high polymorphism. Radhakrishnan et al. (2018) developed 12 microsatellite sites and analyzed narrowband mackerel samples from five locations in the northern Indian Ocean (Arabic Sea and Bay of Bengal). The results showed that the alleles of each population were very similar, with the overall F_ST value only 0.0023~0.027, and AMOVA showed that most of the variations came from within the population. Bayesian clustering analysis failed to distinguish the geographical origin of the samples, supporting the conclusion that narrow-band mackerels in this area belonged to a single group. This is consistent with mtDNA research, indicating that the genetic connectivity of narrowband mackerel populations is very high along the coast of India. Experts used microsatellites to detect the differences between broadband mackerels in the northern and central South China Sea, and found that there were statistical differences in the frequency of alleles in the two groups, and speculated that it may have a certain degree of isolation due to coastal water mass barriers (Zeng et al., 2012). 3.2 Advances in the application of nuclear genome and SNP markers With the advancement of molecular biology technology, researchers have begun to use single nucleotide polymorphism (SNP) markers in the nuclear genome to analyze the mackerel population structure. Nuclear DNA can reflect bi-line information of parents and has more advantages in exploring recent population dynamics. Shui et al. (2009) used AFLP (amplified fragment length polymorphism) for the first time to analyze the Yellow Sea and East China Sea Japanese mackerel. The results showed that the genetic differentiation index between the populations in the two sea areas was about 0.04, reaching a significant level. This is very different from the mitochondrial results, suggesting that the nuclear gene may have detected weak structures not reflected by the maternal marker (Li et al., 2024). Although AFLP is not as accurate as SNP, this study provides clues for the existence of hidden differentiation of mackerels. In the past decade, high-throughput sequencing has allowed people to develop thousands of SNP markers for population genetic analysis. Many recent achievements have taken advantage of this advantage (Siccha-Ramirez et al., 2018). 3.3 New perspectives brought by multigenomic technology (such as RAD-seq, WGS, ddRAD, etc.) In recent years, high-throughput sequencing technology has developed rapidly, with a variety of simplified genome sequencing methods such as whole genome resequencing, RAD-seq (restriction enzyme fragment association sequencing), ddRAD, DArTseq, etc., which can obtain massive genetic markers at one time. These multigenomic technologies have revolutionized the genetics of marine fish populations. Compared with traditional research that relies on several gene fragments or dozens of microsatellite sites, the new technology can generate thousands of SNP markers, greatly improving statistical power, and is particularly suitable for detecting subtle population differentiation and gene flow patterns. For fish with high mobility such as mackerel, previous studies have often made it difficult to distinguish the population structure due to the low genetic differences, and the application of multigenomic data overcomes this problem. Widayanti et al. (2024) used environmental DNA technology combined with high-throughput sequencing to evaluate fish diversity in Taiwan Straits, and also detected the frequency difference in the occurrence of Japanese mackerels in different seasons, suggesting that population dynamics are related to seasonal changes in ocean currents (Widayanti et al., 2024). Although this study is not aimed at the genome of mackerel, it demonstrates new technologies that can provide information on group changes in mackerels on the ecological time scale. In terms of whole genome sequencing, Li et al. (2024) have constructed a high-quality chromosomal-level reference genome of broadband mackerel. This provides a basis for future group comparisons of mackerels in the whole genome-wide range. With the reference genome, gene variants associated with population differentiation and local adaptation can be more accurately located, identifying potential adaptive genetic markers (Siccha-Ramirez et al., 2018).
International Journal of Marine Science, 2025, Vol.15, No.4, 186-198 http://www.aquapublisher.com/index.php/ijms 190 4 Comparison of Mackerel Population Structure in Different Sea Areas Around the world 4.1 Differences in the Indian Ocean and Western Pacific populations The Indian Ocean and the Western Pacific waters are integrated, but they contain a complex semi-closed marginal sea and island system. For highly migratory fish such as mackerel, the population structure in this vast area has always attracted much attention. Through the aforementioned high resolution studies, we have known that the narrowband mackerel (S. commercial) has a distinct genetic differentiation pattern in the northern Indian Ocean. It is reported that narrowband mackerels sampled in the North Indian Ocean-East Indian Ocean can be divided into at least four genetic groups. Among them, groups in the northeastern Indian Ocean (the Gulf of Bengal), the eastern (near the Malay Peninsula), and the central and northern Indian Ocean were all identified as belonging to different gene clusters, and the F_ST analysis also supported significant differences between the groups (Vineesh et al., 2018). In particular, the study found that population genetic differences are positively correlated with geographical distance, showing a clear isolation by distance pattern. This means that even without absolute geographical barriers, distant groups gradually accumulate differences in gene frequencies due to limited migration individuals. 4.2 Genetic pattern of the Atlantic and Caribbean Compared with the high diversity of the Indo-Western Pacific, there are fewer species of mackerel in the Atlantic, and their population structure studies are mainly focused on kingfish and Sierra mackerel along the Western Atlantic coast. Previous studies of S. brasiliensis have shown that the species may constitute a genetic unit throughout the southwestern Atlantic Ocean (Venezuela to southern Brazil). Mitochondrial analysis found that samples from different sampling sites (Cumana, Venezuela, northeastern Brazil, southeastern Brazil) shared most haplotypes, with the interpopulation differentiation index Phi_ST and the AMOVA results were not significant. Haplotype networks have a star topology, suggesting that population expansion has been experienced historically (Figure 2) (da Cunha et al., 2020). All these evidences support that the Western Atlantic Sierra mackerel is a single genetic population. However, the application of nuclear DNA markers has revised this conclusion. By comparing microsatellite or SNP data from north-south Brazilian samples, there are signs of slight allelic frequency differences between the southern Brazilian population and the northern Brazilian population (Soeth et al., 2022). The reason may be related to the current system along the Brazilian coast: the North Brazilian warm current and the Malvinas cold current intersect in southern Brazil, forming a hydrological barrier, which restricts the exchange of fish in the north and the south. Similar phenomena may also exist on kingfish (S. cavalla). Kingfish is widely distributed in the East Coast of North America and the Gulf of Mexico, and traditional views regard it as a single management unit. However, trace element trace element trace and microsatellite studies suggest that there is a certain separation between the king fish in the Gulf of Mexico and the king fish along the Atlantic coast (Gold et al., 2010), and may each lay eggs and return to its original position, thus forming two relatively independent subgroups. 4.3 Localized population characteristics of coastal waters in Southeast Asia and China Southeast Asia and China's offshore in the western Western Pacific are important spawning and fishing areas for mackerels, and are also one of the hot spots for population structure research. The population structure of the major species, Japanese mackerel, has been controversial along the coast of China. Traditionally, it is divided into the Yellow-Bohai Group and the East China Sea Group according to the spawning ground and the fishing flood. There are certain differences in the spawning time and growth parameters of the two. Yang Linlin and others analyzed the otolithic morphology of Japanese mackerels in different spawning sites in China. The results showed that the shape differences in the breeding groups of the three major sea areas of the Bohai Sea, the Yellow Sea and the East China Sea were extremely significant. This shows that Japanese mackerels living in different sea areas have ecologically measurable differentiation characteristics, supporting their relative independence of their breeding populations. Further, the otolith morphological discrimination formula was established using discriminant analysis, which allowed the correct distinction rate of Xiangshan Port (East Sea) and Laizhou Bay (Huang and Bohai Sea) samples to reach 71%, providing a morphological basis for population discrimination. Mitochondrial studies of broadband mackerels in the Gulf of Thailand have shown that there is no obvious genetic
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