Abstract

The sandfish, Holothuria scabra is a commercially important fishery and aquaculture species contributing to the high-value sea cucumber industry. Overexploited across many areas throughout its distributional range, natural populations are considered in decline. Accurate genetic assignment to population of origin is becoming increasingly important for genetics-based marine fisheries management and monitoring, especially for species experiencing depletion of natural stocks and decline in fisheries productivity due to overfishing and illegal, unreported, and unregulated (IUU) fishing. Initiatives for genetics-based applications on economically important seafood such as H. scabra have been limited by the lack of comprehensive genome or transcriptome resources. The present study developed and evaluated the use of gene-associated single nucleotide polymorphism (SNP) markers to assign sandfish to three locations in the Philippines, in the proximity of existing and emerging hatchery production centers. In silico SNP discovery pipeline using pooled RNA-Seq libraries and medium-throughput genotyping approach generated a dataset comprising 115 individuals genotyped at 88 SNPs. Population assignment using machine-learning analysis and Bayesian approach revealed that the 88 transcriptome-derived SNPs allowed the assignment of sandfish individuals to population of origin, with an overall assignment accuracy of >80%. The novel SNPs developed could find their utility in facilitating the development of geographic traceability tools applicable in the context of sandfish aquaculture, fisheries management and conservation.

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