RESUMO
Understanding how genetic diversity is distributed across spatiotemporal scales in species of conservation or management concern is critical for identifying large-scale mechanisms affecting local conservation status and implementing large-scale biodiversity monitoring programmes. However, cross-scale surveys of genetic diversity are often impractical within single studies, and combining datasets to increase spatiotemporal coverage is frequently impeded by using different sets of molecular markers. Recently developed molecular tools make surveys based on standardized single-nucleotide polymorphism (SNP) panels more feasible than ever, but require existing genomic information. Here, we conduct the first survey of genome-wide SNPs across the native range of brook trout (Salvelinus fontinalis), a cold-adapted species that has been the focus of considerable conservation and management effort across eastern North America. Our dataset can be leveraged to easily design SNP panels that allow datasets to be combined for large-scale analyses. We performed restriction site-associated DNA sequencing for wild brook trout from 82 locations spanning much of the native range and domestic brook trout from 24 hatchery strains used in stocking efforts. We identified over 24,000 SNPs distributed throughout the brook trout genome. We explored the ability of these SNPs to resolve relationships across spatial scales, including population structure and hatchery admixture. Our dataset captures a wide spectrum of genetic diversity in native brook trout, offering a valuable resource for developing SNP panels. We highlight potential applications of this resource with the goal of increasing the integration of genomic information into decision-making for brook trout and other species of conservation or management concern.
RESUMO
Genomic methodologies offer unprecedented opportunities for statistically robust studies of species broadly distributed in environments conducive to high gene flow, providing valuable information for wildlife conservation and management. Here, we sequence restriction site-associated DNA to characterize genome-wide single nucleotide polymorphisms (SNPs) in a broadly distributed and highly migratory large pelagic fish, striped marlin (Kajikia audax). Assessment of over 4,000 SNPs resolved spatiotemporal patterns of genetic connectivity throughout the species range in the Pacific and, for the first time, Indian oceans. Individual-based cluster analyses identified six genetically distinct populations corresponding with the western Indian, eastern Indian, western South Pacific, and eastern central Pacific oceans, as well as two populations in the North Pacific Ocean (F ST = 0.0137-0.0819). F ST outlier analyses identified a subset of SNPs (n = 59) putatively under the influence of natural selection and capable of resolving populations separated by comparatively high degrees of genetic differentiation. Temporal collections available for some regions demonstrated the stability of allele frequencies over three to five generations of striped marlin. Relative migration rates reflected lower levels of genetic connectivity between Indian Ocean populations (m R ≤ 0.37) compared with most populations in the Pacific Ocean (m R ≥ 0.57) and highlight the importance of the western South Pacific in facilitating gene flow between ocean basins. Collectively, our results provide novel insights into rangewide population structure for striped marlin and highlight substantial inconsistencies between genetically distinct populations and stocks currently recognized for fisheries management. More broadly, we demonstrate that species capable of long-distance dispersal in environments lacking obvious physical barriers to movement can display substantial population subdivision that persists over multiple generations and that may be facilitated by both neutral and adaptive processes. Importantly, surveys of genome-wide markers enable inference of population-level relationships using sample sizes practical for large pelagic fishes of conservation concern.
