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High migratory propensity constitutes a single stock of an exploited cutlassfish species in the Northwest Pacific: A microsatellite approach.

Yu-Hong GuoLorenzo C HalasanHui-Yu WangHsiu-Chin Lin
Published in: PloS one (2022)
Cutlassfishes, also known as hairtails, include multiple predatory fishes of the family Trichiuridae. They constitute a top marine fish commodity globally, yet the knowledge about their composition and intraspecific genetic structures is still limited. Trichiurus japonicus accounts for a major amount in the northwest Pacific fishery. Previous studies based on mitochondrial DNA markers reported incongruences in its population structure, hence prompting the need for high-resolution markers and avoiding possible shortcomings in its management. Here we genotyped ten novel de novo-assembled transcriptome-derived microsatellite markers on a total of 150 samples across five major fishing grounds (encompassing latitudes 22-39°N). These markers presented a high number of alleles and heterozygosity compared to other marine fishes, corresponding to the large effective population size of ~20,000 per location and cohort differentiation. Population structuring analyses suggested T. japonicus to be a homogenous well-mixed population. This configuration is likely attributed to the majority of its effective population migrates across locations, and the absence of oceanographic barriers at the continental shelves. Qingdao with reportedly high ocean productivity could be a genetic pseudosink based on the high heterozygosity and migratory preference. Moreover, the results of sign tests suggest that T. japonicus experienced a recent bottleneck likely concurrent with historical glaciation events. Further, we demonstrated satisfactory cross-amplifications of our markers on several congeners, indicating a great promise to use these markers to study the population genetics of trichiurids. Together, our findings will serve as an essential groundwork for enhancing resource conservation and management of cutlassfishes.
Keyphrases
  • mitochondrial dna
  • high resolution
  • copy number
  • genome wide
  • squamous cell carcinoma
  • gene expression
  • machine learning
  • big data
  • genetic diversity
  • deep learning