International Journal of Marine Science, 2025, Vol.15, No.1, 15-27 http://www.aquapublisher.com/index.php/ijms 19 Large-scale cross-regional transport of seedlings and artificial seedling cultivation also have a direct impact on the genetic structure of oysters. In modern oyster farming, seedlings from one region are often transported to another region for breeding. Pacific oyster farming on the west coast of North America has long relied on seedling supply from Japan and the United States East Coast hatcheries. This practice may mix genes from different geographical sources, reducing genetic differences between regions. At the same time, seedlings often come from a few parents or are bred, and their genetic diversity and family structure are different from those of wild populations (Markus et al., 2021). Studies show that oyster populations in some farms in British Columbia, Canada have obvious family correlation and low nucleotide diversity, which show the characteristics of "artificial bottleneck" compared with local naturalized wild populations. When these farmed oysters are mixed with wild oysters, reproduction and infiltration may occur, affecting the gene pool composition of wild populations. 4 Genetic Connectivity Studies in Oysters 4.1 Development of molecular markers and high-throughput sequencing technologies The research on genetic connectivity of marine shellfish such as oysters depends on the continuous advancement of molecular genetic marking technology. Early studies mostly used markers such as mitochondrial DNA sequences and isoenzymes to identify population differences. The phylogenetic relationship and general genetic differentiation pattern of oyster populations can be analyzed using mitochondrial COI gene sequences. However, the amount of information about a single gene marker is limited, making it difficult to accurately quantify connectivity. Since the 1990s, highly polymorphic nuclear loci such as microsatellite DNA have been widely used in the genetic research of oyster populations. Due to its co-dominance and high variation, microsatellite markers can provide rich information such as genetic differentiation (F_ST), heterozygation, etc., and are used to evaluate the genetic structure and diversity levels of different geographical populations such as European flat oysters. Entering the 21st century, the rise of high-throughput sequencing technology has brought revolutionary changes to the genetic research of oysters. Simplified genome sequencing methods such as RAD-Seq (restricted cleavage site association sequencing) and GBS (genome degenerate sequencing) can obtain thousands of SNP markers across the genome, greatly improving resolution (Gutierrez et al., 2017). Going further, the huge whole-genome sequencing and genome assembly of oyster species have also made breakthroughs in recent years. Pacific oyster C. gigas sequenced the entire genome (about 0.59 Gb in size) as early as 2012. The genomes of species such as Eastern oyster C. virginica, turbidite oyster S. cucullata were successively published, providing a reference framework for population genomics research. Li et al. (2024) constructed the Crassostrea ariakensis genome at the Yangtze River Estuary at a near chromosome level. Combined with the whole genome resequencing data, they analyzed the genetic structure of the northern, central and southern groups of this species, as well as the effect of temperature salinity gradient on its adaptive variation. With the decline in sequencing costs, whole genome resequencing (WGS) has gradually been used in large sample population research of oysters. 4.2 Analysis model and evaluation index of population genetic structure After obtaining molecular marker data, population genetic analysis models and statistical indicators need to be used to evaluate oyster population structure and connectivity. F_statistics (such as F_ST) are the most commonly used population differentiation metrics, reflecting the proportion of genetic variance among subpopulations. Lower F_ST (close to 0) means no obvious differentiation between populations and frequent gene communication; higher F_ST (close to 1) means that most of the variation exists between populations and limited communication. In oyster studies, differences among geographic populations are often quantified by calculating paired F_ST (Silliman, 2018). Genetic diversity indicators are also important aspects of evaluating population status, including mean heterogeneity (H_O, H_E) and allelic richness. By comparing the diversity levels of different populations, it can be judged which populations have experienced bottlenecks or expansions. Under multigene marker data, clustering analysis and dimensionality reduction analysis are common tools for revealing implicit structures. Bayesian clustering methods such as STRUCTURE can attribute individuals to several genetic clusters based on
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