Kraft Derek W, Conklin Emily E, Freel Evan B, Hutchinson Melanie, Spaet Julia L Y, Toonen Robert J, Forsman Zac H, Grant Michael I, Filmalter John David, Hyde John R, Gulak Simon J B, Bowen Brian W
University of Hawai'i, Hawai'i Institute of Marine Biology, Kãne'ohe, Hawai'i, USA.
Department of Zoology, University of Cambridge, Evolutionary Ecology Group, Cambridge, United Kingdom.
PeerJ. 2025 Jul 7;13:e19493. doi: 10.7717/peerj.19493. eCollection 2025.
Silky shark ( Carcharhinidae) numbers have declined steeply in recent decades due to the fin fishery and bycatch in pelagic fisheries. Due to a lack of data on stock delineations, this species is currently managed in ocean-spanning jurisdictions defined by regional fisheries management organizations (RFMOs). Here we investigate the global stock structure of silky sharks and compare population structure to the four RFMO boundaries. Using high-throughput sequencing from pooled individuals (pool-seq) based on 628 specimens collected opportunistically across 11 circumglobal regions, yielding 854 nuclear single nucleotide polymorphisms (SNPs) and 23 mtDNA SNPs. Results indicate significant population genetic structure between all 11 regional sampling locations, with discriminant analysis of principal components (DAPC) identifying seven discrete groups. Within the Atlantic and Indo-Pacific Oceans, values ranged from 0.014 to 0.035 for nuclear (nDNA) markers, and from 0.012 to 0.160 for whole mtDNA genomes, with much higher values between than within oceans (mtDNA: 0.383-0.844, nDNA: 0.042-0.078). Using an analysis of molecular variance (AMOVA) framework, 22.24% of the observed population variance is explained by RFMOs, 32.1% is explained among ocean basins, and 34.81% is explained by the DAPC-identified groups. We find significant population genetic structure within the jurisdiction of every RFMO, from which we have more than a single sampling site. Our genomic-scale results indicate discordance between population genetic structure and RFMOs, highlighting the need for a detailed study to accurately identify stock boundaries.
近几十年来，丝鲨（真鲨科）数量因鱼翅渔业和远洋渔业中的兼捕而急剧下降。由于缺乏种群划分数据，该物种目前在区域渔业管理组织（RFMO）界定的跨洋管辖区域内进行管理。在此，我们研究了丝鲨的全球种群结构，并将种群结构与四个RFMO边界进行比较。基于从11个全球区域机会性收集的628个样本，使用混合个体的高通量测序（池测序），得到854个核单核苷酸多态性（SNP）和23个线粒体DNA SNP。结果表明，所有11个区域采样地点之间存在显著的种群遗传结构，主成分判别分析（DAPC）识别出七个离散群体。在大西洋和印度洋-太平洋内，核（nDNA）标记的值在0.014至0.035之间，整个线粒体DNA基因组的值在0.012至0.160之间，海洋之间的值远高于海洋内部（线粒体DNA：0.383 - 0.844，nDNA：0.042 - 0.078）。使用分子方差分析（AMOVA）框架，观察到的种群方差的22.24%由RFMO解释，32.1%由海盆之间解释，34.81%由DAPC识别的群体解释。我们发现在每个有多个采样点的RFMO管辖范围内都存在显著的种群遗传结构。我们的基因组规模结果表明种群遗传结构与RFMO之间存在不一致，突出了进行详细研究以准确识别种群边界的必要性。
