Leveraging the genetic diversity of trout in the rivers of the British Isles and northern France to understand the movements of sea trout (Salmo trutta L.) around the English Channel.

Populations of anadromous brown trout, also known as sea trout, have suffered recent marked declines in abundance due to multiple factors, including climate change and human activities. While much is known about their freshwater phase, less is known about the species' marine feeding migrations. This situation is hindering the effective management and conservation of anadromous trout in the marine environment. Using a panel of 95 single nucleotide polymorphism markers we developed a genetic baseline, which demonstrated strong regional structuring of genetic diversity in trout populations around the English Channel and adjacent waters. Extensive baseline testing showed this structuring allowed high-confidence assignment of known-origin individuals to region of origin. This study presents new data on the movements of anadromous trout in the English Channel and southern North Sea. Assignment of anadromous trout sampled from 12 marine and estuarine localities highlighted contrasting results for these areas. The majority of these fisheries are composed predominately of stocks local to the sampling location. However, there were multiple cases of long-distance movements of anadromous trout, with several individuals originating from rivers in northeast England being caught in the English Channel and southern North Sea, in some cases more than 1000 km from their natal region. These results have implications for the management of sea trout in inshore waters around the English Channel and southern North Sea.

Temporal allele frequency changes in large-effect loci reveal potential fishing impacts on salmon life-history diversity.

Fishing has the potential to influence the life-history traits of exploited populations. However, our understanding of how fisheries can induce evolutionary genetic changes remains incomplete. The discovery of large-effect loci linked with ecologically important life-history traits, such as age at maturity in Atlantic salmon (Salmo salar), provides an opportunity to study the impacts of temporally varying fishing pressures on these traits. A 93-year archive of fish scales from wild Atlantic salmon catches from the northern Baltic Sea region allowed us to monitor variation in adaptive genetic diversity linked with age at maturity of wild Atlantic salmon populations. The dataset consisted of samples from both commercial and recreational fisheries that target salmon on their spawning migration. Using a genotyping-by-sequencing approach (GT-seq), we discovered strong within-season allele frequency changes at the vgll3 locus linked with Atlantic salmon age at maturity: fishing in the early season preferentially targeted the vgll3 variant linked with older maturation. We also found within-season temporal variation in catch proportions of different wild Atlantic salmon subpopulations. Therefore, selective pressures of harvesting may vary depending on the seasonal timing of fishing, which has the potential to cause evolutionary changes in key life-history traits and their diversity. This knowledge can be used to guide fisheries management to reduce the effects of fishing practices on salmon life-history diversity. Thus, this study provides a tangible example of using genomic approaches to infer, monitor and help mitigate human impacts on adaptively important genetic variation in nature.

Harnessing the power of regional baselines for broad-scale genetic stock identification: A multistage, integrated, and cost-effective approach.

In mixed-stock fishery analyses, genetic stock identification (GSI) estimates the contribution of each population to a mixture and is typically conducted at a regional scale using genetic baselines specific to the stocks expected in that region. Often these regional baselines cannot be combined to produce broader geographical baselines due to non-overlapping populations and genetic markers. In cases where the mixture contains stocks spanning across a wide area, a broad-scale baseline is created, but often at the cost of resolution. Here, we introduce a new GSI method to harness the resolution capabilities of baselines developed for regional applications in the analysis of mixtures containing individuals from a broad geographic range. This method employs a multistage framework that allows disparate baselines to be used in a single integrated process that produces estimates along with the propagated errors from each stage. All individuals in the mixture sample are required to be genotyped for all genetic markers in the baselines used by this model, but the baselines do not require overlap in genetic markers or populations representing the broad-scale or regional baselines. We demonstrate the utility of our integrated multistage model using a synthesized data set made up of Chinook salmon, Oncorhynchus tshawytscha, from the North Bering Sea of Alaska. The results show an improved accuracy for estimates using an integrated multistage framework, compared to the conventional framework of using separate hierarchical steps. The integrated multistage framework allows GSI of a wide geographic area without first developing a large scale, high-resolution genetic baseline or dividing a mixture sample into smaller regions beforehand. This approach is more cost-effective than updating range-wide baselines with all regionally important markers.

Modeling ocean distributions and abundances of natural- and hatchery-origin Chinook salmon stocks with integrated genetic and tagging data.

Background: Considerable resources are spent to track fish movement in marine environments, often with the intent of estimating behavior, distribution, and abundance. Resulting data from these monitoring efforts, including tagging studies and genetic sampling, often can be siloed. For Pacific salmon in the Northeast Pacific Ocean, predominant data sources for fish monitoring are coded wire tags (CWTs) and genetic stock identification (GSI). Despite their complementary strengths and weaknesses in coverage and information content, the two data streams rarely have been integrated to inform Pacific salmon biology and management. Joint, or integrated, models can combine and contextualize multiple data sources in a single statistical framework to produce more robust estimates of fish populations. Methods: We introduce and fit a comprehensive joint model that integrates data from CWT recoveries and GSI sampling to inform the marine life history of Chinook salmon stocks at spatial and temporal scales relevant to ongoing fisheries management efforts. In a departure from similar models based primarily on CWT recoveries, modeled stocks in the new framework encompass both hatchery- and natural-origin fish. We specifically model the spatial distribution and marine abundance of four distinct stocks with spawning locations in California and southern Oregon, one of which is listed under the U.S. Endangered Species Act. Results: Using the joint model, we generated the most comprehensive estimates of marine distribution to date for all modeled Chinook salmon stocks, including historically data poor and low abundance stocks. Estimated marine distributions from the joint model were broadly similar to estimates from a simpler, CWT-only model but did suggest some differences in distribution in select seasons. Model output also included novel stock-, year-, and season-specific estimates of marine abundance. We observed and partially addressed several challenges in model convergence with the use of supplemental data sources and model constraints; similar difficulties are not unexpected with integrated modeling. We identify several options for improved data collection that could address issues in convergence and increase confidence in model estimates of abundance. We expect these model advances and results provide management-relevant biological insights, with the potential to inform future mixed-stock fisheries management efforts, as well as a foundation for more expansive and comprehensive analyses to follow.

Genetic assignment of fisheries bycatch reveals disproportionate mortality among Alaska Northern Fulmar breeding colonies.

Global fisheries kill millions of seabirds annually through bycatch, but little is known about population-level impacts, particularly in species that form metapopulations. U.S. North Pacific groundfish fisheries catch thousands of Northern Fulmars (Fulmarus glacialis rodgersii) each year, making fulmars the most frequently caught seabird in federally managed U.S. fisheries. Here, we used genetic stock identification to assign 1,536 fulmars sampled as bycatch to one of four Alaska breeding colonies and quantified the similarity of bycatch locations at sea among colonies. We found disproportionately high bycatch from the Pribilof Islands (6% of metapopulation, 23% of bycatch), and disproportionately low bycatch from Chagulak Island (34% of metapopulation, 14% of bycatch). Overlap between fisheries and colony-specific foraging areas diverge more during the summer breeding season, leading to greater differences in bycatch susceptibility. Contemporary and historical gene flow likely contributes to low genetic differentiation among colonies (FST = 0.003-0.01), yet these values may not represent present connectivity. Our findings illustrate how genetic stock identification can link at-sea threats to colonies and inform management to reduce bycatch from impacted colonies.

In-field genetic stock identification of overwintering coho salmon in the Gulf of Alaska: Evaluation of Nanopore sequencing for remote real-time deployment.

Genetic stock identification (GSI) from genotyping-by-sequencing of single nucleotide polymorphism (SNP) loci has become the gold standard for stock of origin identification in Pacific salmon. The sequencing platforms currently applied require large batch sizes and multiday processing in specialized facilities to perform genotyping by the thousands. However, recent advances in third-generation single-molecule sequencing platforms, such as the Oxford Nanopore minION, provide base calling on portable, pocket-sized sequencers and promise real-time, in-field stock identification of variable batch sizes. Here we evaluate utility and comparability to established GSI platforms of at-sea stock identification of coho salmon (Oncorhynchus kisutch) using targeted SNP amplicon sequencing on the minION platform during a high-sea winter expedition to the Gulf of Alaska. As long read sequencers are not optimized for short amplicons, we concatenate amplicons to increase coverage and throughput. Nanopore sequencing at-sea yielded data sufficient for stock assignment for 50 out of 80 individuals. Nanopore-based SNP calls agreed with Ion Torrent-based genotypes in 83.25%, but assignment of individuals to stock of origin only agreed in 61.5% of individuals, highlighting inherent challenges of Nanopore sequencing, such as resolution of homopolymer tracts and indels. However, poor representation of assayed salmon in the queried baseline data set contributed to poor assignment confidence on both platforms. Future improvements will focus on lowering turnaround time and cost, increasing accuracy and throughput, as well as augmentation of the existing baselines. If successfully implemented, Nanopore sequencing will provide an alternative method to the large-scale laboratory approach by providing mobile small batch genotyping to diverse stakeholders.

Russian honey bee genotype identification through enhanced marker panel set.

Russian honey bees (RHB) are a breeding population developed by USDA-ARS as an effort to provide Varroa-resistant honey bees to beekeepers. The selection strategy for this breeding population was the first in honey bees to incorporate genetic stock identification (GSI). The original GSI approach has been in use for over a decade, and though effective, novel technologies and analytical approaches recently developed provide an opportunity for improvement. Here we outline a novel genotyping assay that capitalizes on the markers used in the GSI as well as new loci recently identified in a whole genome pooled study of commercial honey bee stocks. Our approach utilizes a microfluidic platform and machine learning analyses to arrive at an accurate, high throughput assay. This novel approach provides an improved tool that can be readily incorporated into breeding decisions towards healthier more productive bees.

Parentage-based tagging combined with genetic stock identification is a cost-effective and viable replacement for coded-wire tagging in large-scale assessments of marine Chinook salmon fisheries in British Columbia, Canada.

Wild Pacific salmon, including Chinook salmon Oncorhynchus tshawytscha, have been supplemented with hatchery propagation for over 50 years in support of increased ocean harvest, mitigation for hydroelectric development, and conservation of threatened populations. In Canada, the Wild Salmon Policy for Pacific salmon was established with the goal of maintaining and restoring healthy and diverse Pacific salmon populations, making conservation of wild salmon and their habitats the highest priority for resource management decision-making. For policy implementation, a new approach to the assessment and management of Chinook salmon and the associated hatchery production and fisheries management are needed. Implementation of genetic stock identification (GSI) and parentage-based tagging (PBT) for marine fisheries assessment may overcome problems associated with coded-wire tag-based (CWT) assessment and management of Chinook salmon fisheries, providing at a minimum information equivalent to that derived from the CWT program. GSI and PBT were used to identify Chinook salmon sampled in 2018 and 2019 marine fisheries (18,819 individuals genotyped) in British Columbia to specific conservation units (CU), populations, and broodyears. Individuals were genotyped at 391 single nucleotide polymorphisms via direct sequencing of amplicons. Very high accuracy of assignment to population and age (>99.5%) via PBT was observed for 1994 Chinook salmon of ages 2-4 years, with a 105,722-individual, 380-population baseline available for assignment. Application of a GSI-PBT system of identification to individuals in 2019 fisheries provided high-resolution estimates of stock composition, catch, and exploitation rate by CU or population, with fishery exploitation rates directly comparable to those provided by CWTs for 13 populations. GSI and PBT provide an alternate, cheaper, and more effective method in the assessment and management of Canadian-origin Chinook salmon relative to CWTs, and an opportunity for a genetics-based system to replace the current CWT system for salmon assessment.

Mixed-stock analysis using Rapture genotyping to evaluate stock-specific exploitation of a walleye population despite weak genetic structure.

Mixed-stock analyses using genetic markers have informed fisheries management in cases where strong genetic differentiation occurs among local spawning populations, yet many fisheries are supported by multiple, weakly differentiated stocks. Freshwater fisheries exemplify this problem, with many populations supported by multiple stocks of young evolutionary age and isolated across small spatial scales. Consequently, attempts to conduct genetic mixed-stock analyses of inland fisheries have often been unsuccessful. Advances in genomic sequencing offer the ability to discriminate among populations with weak population structure, providing the necessary resolution to conduct mixed-stock assignment among previously indistinguishable stocks. We used genomic data to conduct a mixed-stock analysis of eastern Lake Erie's commercial and recreational walleye (Sander vitreus) fisheries and estimate the relative harvest of weakly differentiated stocks (pairwise F ST < 0.01). Using RAD-capture (Rapture), we sequenced and genotyped individuals from western and eastern basin local spawning stocks at 12,081 loci with 95% reassignment accuracy, which was not possible in the past using microsatellite markers. A baseline assessment of 395 walleye from 11 spawning stocks identified three reporting groups and refined previous assessments of gene flow among walleye stocks. Genetic assignment of 1,075 walleye harvested in eastern Lake Erie's recreational and commercial fisheries indicated that western basin stocks constituted the majority of harvest during the peak walleye fishing season (July-September), whereas eastern basin individuals comprised much of the early season harvest (May-June). Clear spatial structure in harvest composition existed; catches in more easterly sites contained more individuals of eastern basin origin than did more westerly sites. Our study provides important stock contribution estimates for Lake Erie fishery management and demonstrates the utility of genomic data to facilitate mixed-stock analysis in exploited fish populations having weak population structure or limited existing genetic resources.

An integrated model of seasonal changes in stock composition and abundance with an application to Chinook salmon.

Population-specific spatial and temporal distribution data are necessary to identify mechanisms regulating abundance and to manage anthropogenic impacts. However the distributions of highly migratory species are often difficult to resolve, particularly when multiple populations' movements overlap. Here we present an integrated model to estimate spatially-stratified, seasonal trends in abundance and population composition, using data from extensive genetic sampling of commercial and recreational Chinook salmon (Oncorhynchus tshawytscha) fisheries in southern British Columbia. We use the model to estimate seasonal changes in population-specific standardized catch per unit effort (a proxy for abundance) across six marine regions, while accounting for annual variability in sampling effort and uncertain genetic stock assignment. We also share this model as an R package stockseasonr for application to other regions and species. Even at the relatively small spatial scales considered here, we found that patterns in seasonal abundance differed among regions and stocks. While certain locations were clearly migratory corridors, regions within the Salish Sea exhibited diverse, and often weak, seasonal patterns in abundance, emphasizing that they are important, year-round foraging habitats. Furthermore, we found evidence that stocks with similar freshwater life histories and adult run timing, as well as relatively proximate spawning locations, exhibited divergent distributions. Our findings highlight subtle, but important differences in how adult Chinook salmon use marine habitats. Down-scaled model outputs could be used to inform ecosystem-based management efforts by resolving the degree to which salmon overlap with other species of concern, as well as specific fisheries. More broadly, variation in stock-specific abundance among regions indicates efforts to identify mechanisms driving changes in size-at-maturity and natural mortality should account for distinct marine distributions.

Contemporary genetic structure affects genetic stock identification of steelhead trout in the Snake River basin.

Genetic stock identification is a widely applied tool for the mixed-stock management of salmonid species throughout the North Pacific Rim. The effectiveness of genetic stock identification is dependent on the level of differentiation among stocks which is often high due to the life history of these species that involves high homing fidelity to their natal streams. However, the utility of this tool can be reduced when natural genetic structuring has been altered by hatchery translocation and/or supplementation. We examined the genetic population structure of ESA-listed steelhead in the Snake River basin of the United States. We analyzed 9,613 natural-origin adult steelhead returning to Passive Integrated Transponder detection sites throughout the basin from 2010 through 2017. Individuals were genotyped at 180 single nucleotide polymorphic genetic markers and grouped into 20 populations based on their return location. While we expected to observe a common pattern of hierarchical genetic structuring due to isolation by distance, we observed low genetic differentiation between populations in the upper Salmon River basin compared to geographically distant populations in the lower Snake River basin. These results were consistent with lower genetic stock assignment probabilities observed for populations in this upper basin. We attribute these patterns of reduced genetic structure to the translocation of lower basin steelhead stocks and ongoing hatchery programs in the upper Salmon River basin. We discuss the implications of these findings on the utility of genetic stock identification in the basin and discuss opportunities for increasing assignment probabilities in the face of low genetic structure.

Insights on the concept of indicator populations derived from parentage-based tagging in a large-scale coho salmon application in British Columbia, Canada.

For Pacific salmon, the key fisheries management goal in British Columbia (BC) is to maintain and restore healthy and diverse Pacific salmon populations, making conservation of salmon biodiversity the highest priority for resource management decision-making. Salmon status assessments are often conducted on coded-wire-tagged subsets of indicator populations based on assumptions of little differentiation within or among proximal populations. In the current study of southern BC coho salmon (Oncorhynchus kisutch) populations, parentage-based tagging (PBT) analysis provided novel information on migration and life-history patterns to test the assumptions of biological homogeneity over limited (generally < 100 km) geographic distances and, potentially, to inform management of fisheries and hatchery broodstocks. Heterogeneity for location and timing of fishery captures, family productivity, and exploitation rate was observed over small geographic scales, within regions that are, or might be expected to be, within the area encompassed by a single-tagged indicator population. These results provide little support for the suggestion that information gained from tagged indicator populations is representative of marine distribution, productivity, and exploitation patterns of proximal populations.

A GT-seq panel for walleye (Sander vitreus) provides important insights for efficient development and implementation of amplicon panels in non-model organisms.

Targeted amplicon sequencing methods, such as genotyping-in-thousands by sequencing (GT-seq), facilitate rapid, accurate, and cost-effective analysis of hundreds of genetic loci in thousands of individuals. Development of GT-seq panels is nontrivial, but studies describing trade-offs associated with different steps of GT-seq panel development are rare. Here, we construct a dual-purpose GT-seq panel for walleye (Sander vitreus), discuss trade-offs associated with different development and genotyping approaches, and provide suggestions for researchers constructing their own GT-seq panels. Our GT-seq panel was developed using an ascertainment set consisting of restriction site-associated DNA data from 954 individuals sampled from 23 populations in Minnesota and Wisconsin, USA. We conducted simulations to test the utility of all loci for parentage analysis and genetic stock identification and designed 600 primer pairs to maximize joint accuracy for these analyses. We then performed three rounds of primer optimization to remove loci that overamplified and our final panel consisted of 436 loci. We also explored different approaches for DNA extraction, multiplexed polymerase chain reaction (PCR) amplification, and cleanup steps during the GT-seq process and discovered the following: (i) inexpensive Chelex extractions performed well for genotyping; (ii) the exonuclease I and shrimp alkaline phosphatase (ExoSAP) procedure included in some current protocols did not improve results substantially and was probably unnecessary; and (iii) it was possible to PCR amplify panels separately and combine them prior to adapter ligation. Well-optimized GT-seq panels are valuable resources for conservation genetics and our findings and suggestions should aid in their construction in myriad taxa.

Variation in migration pattern, broodstock origin, and family productivity of coho salmon hatchery populations in British Columbia, Canada, derived from parentage-based tagging.

In salmonid parentage-based tagging (PBT) applications, entire hatchery broodstocks are genotyped, and subsequently, progeny can be nonlethally sampled and assigned back to their parents using parentage analysis, thus identifying their hatchery of origin and brood year (i.e., age). Inter- and intrapopulation variability in migration patterns, life history traits, and fishery contributions can be determined from PBT analysis of samples derived from both fisheries and escapements (portion of a salmon population that does not get caught in fisheries and returns to its natal river to spawn). In the current study of southern British Columbia coho salmon (Oncorhynchus kisutch) populations, PBT analysis provided novel information on intrapopulation heterogeneity among males in the total number of progeny identified in fisheries and escapements, the proportion of progeny sampled from fisheries versus escapement, the proportion of two-year-old progeny (jacks) produced, and the within-season return time of progeny. Fishery recoveries of coho salmon revealed heterogeneity in migration patterns among and within populations, with recoveries from north and central coast fisheries distinguishing "northern migrating" from "resident" populations. In northern migrating populations, the mean distance between fishery captures of sibs (brothers and sisters) was significantly less than the mean distance between nonsibs, indicating the possible presence of intrapopulation genetic heterogeneity for migration pattern. Variation among populations in productivity and within populations in fish catchability indicated that population selection and broodstock management can be implemented to optimize harvest benefits from hatcheries. Application of PBT provided valuable information for assessment and management of hatchery-origin coho salmon in British Columbia.

Comparison of coded-wire tagging with parentage-based tagging and genetic stock identification in a large-scale coho salmon fisheries application in British Columbia, Canada.

Wild Pacific salmon, including Coho salmon Onchorynchus kisutch, have been supplemented with hatchery propagation for over 50 years in support of increased ocean harvest and conservation of threatened populations. In Canada, the Wild Salmon Policy for Pacific salmon was established with the goal of maintaining and restoring healthy and diverse Pacific salmon populations, making conservation of wild salmon and their habitats the highest priority for resource management decision-making. A new approach to the assessment and management of wild coho salmon, and the associated hatchery production and fishery management is needed. Implementation of parentage-based tagging (PBT) may overcome problems associated with coded-wire tag-based (CWT) assessment and management of coho salmon fisheries, providing at a minimum information equivalent to that derived from the CWT program. PBT and genetic stock identification (GSI) were used to identify coho salmon sampled in fisheries (8,006 individuals) and escapements (1,692 individuals) in British Columbia to specific conservation units (CU), populations, and broodyears. Individuals were genotyped at 304 single nucleotide polymorphisms (SNPs) via direct sequencing of amplicons. Very high accuracy of assignment to population (100%) via PBT for 543 jack (age 2) assigned to correct age and collection location and 265 coded-wire tag (CWT, age 3) coho salmon assigned to correct age and release location was observed, with a 40,774-individual, 267-population baseline available for assignment. Coho salmon from un-CWTed enhanced populations contributed 65% of the catch in southern recreational fisheries in 2017. Application of a PBT-GSI system of identification to individuals in 2017 fisheries and escapements provided high-resolution estimates of stock composition, catch, and exploitation rate by CU or population, providing an alternate and more effective method in the assessment and management of Canadian-origin coho salmon relative to CWTs, and an opportunity for a genetic-based system to replace the current CWT system for coho salmon assessment.

Population assignment and local adaptation along an isolation-by-distance gradient in Pacific cod (Gadus macrocephalus).

The discernment of populations as management units is a fundamental prerequisite for sustainable exploitation of species. A lack of clear stock boundaries complicates not only the identification of spatial management units, but also the assessment of mixed fisheries by population assignment and mixed stock analysis. Many marine species, such as Pacific cod, are characterized by isolation by distance, showing significant differentiation but no clear stock boundaries. Here, we used restriction-site-associated DNA (RAD) sequencing to investigate population structure and assess power to genetically assign Pacific cod to putative populations of origin. Samples were collected across the species range in the eastern Pacific Ocean, from the Salish Sea to the Aleutian Islands. A total of 6,425 putative biallelic single nucleotide polymorphisms were identified from 276 individuals. We found a strong isolation-by-distance signal along coastlines that mirrored previous microsatellite results and pronounced genetic differentiation between coastal samples and those from the inland waters of the Salish Sea, with no evidence for hybridization between these two populations. Individual assignment success based on two methods was high overall (≥84%) but decreased from south to north. Assignment to geographic location of origin also was successful, with average distance between capture and assignment location of 220 km. Outlier analyses identified more loci potentially under selection along the coast than between Salish Sea and coastal samples, suggesting more diverse adaptation to latitudinal environmental factors than inshore vs. offshore environments. Our results confirm previous observations of sharp genetic differentiation of the Salish Sea population and isolation by distance along the coast, but also highlight the feasibility of using modern genomic techniques to inform stock boundaries and fisheries management in a low FST marine species.

Genetic signals of artificial and natural dispersal linked to colonization of South America by non-native Chinook salmon (Oncorhynchus tshawytscha).

Genetics data have provided unprecedented insights into evolutionary aspects of colonization by non-native populations. Yet, our understanding of how artificial (human-mediated) and natural dispersal pathways of non-native individuals influence genetic metrics, evolution of genetic structure, and admixture remains elusive. We capitalize on the widespread colonization of Chinook salmon Oncorhynchus tshawytscha in South America, mediated by both dispersal pathways, to address these issues using data from a panel of polymorphic SNPs. First, genetic diversity and the number of effective breeders (Nb) were higher among artificial than natural populations. Contemporary gene flow was common between adjacent artificial and natural and adjacent natural populations, but uncommon between geographically distant populations. Second, genetic structure revealed four distinct clusters throughout the Chinook salmon distributional range with varying levels of genetic connectivity. Isolation by distance resulted from weak differentiation between adjacent artificial and natural and between natural populations, with strong differentiation between distant Pacific Ocean and Atlantic Ocean populations, which experienced strong genetic drift. Third, genetic mixture analyses revealed the presence of at least six donor geographic regions from North America, some of which likely hybridized as a result of multiple introductions. Relative propagule pressure or the proportion of Chinook salmon propagules introduced from various geographic regions according to government records significantly influenced genetic mixtures for two of three artificial populations. Our findings support a model of colonization in which high-diversity artificial populations established first; some of these populations exhibited significant admixture resulting from propagule pressure. Low-diversity natural populations were likely subsequently founded from a reduced number of individuals.

Tracking the Genetic Stability of a Honey Bee (Hymenoptera: Apidae) Breeding Program With Genetic Markers.

A genetic stock identification (GSI) assay was developed in 2008 to distinguish Russian honey bees from other honey bee stocks that are commercially produced in the United States. Probability of assignment (POA) values have been collected and maintained since the stock release in 2008 to the Russian Honey Bee Breeders Association. These data were used to assess stability of the breeding program and the diversity levels of the contemporary breeding stock through comparison of POA values and genetic diversity parameters from the initial release to current values. POA values fluctuated throughout 2010-2016, but have recovered to statistically similar levels in 2016 (POA(2010) = 0.82, POA(2016) = 0.74; P = 0.33). Genetic diversity parameters (i.e., allelic richness and gene diversity) in 2016 also remained at similar levels when compared to those in 2010. Estimates of genetic structure revealed stability (FST(2009/2016) = 0.0058) with a small increase in the estimate of the inbreeding coefficient (FIS(2010) = 0.078, FIS(2016) = 0.149). The relationship among breeding lines, based on genetic distance measurement, was similar in 2008 and 2016 populations, but with increased homogeneity among lines (i.e., decreased genetic distance). This was expected based on the closed breeding system used for Russian honey bees. The successful application of the GSI assay in a commercial breeding program demonstrates the utility and stability of such technology to contribute to and monitor the genetic integrity of a breeding stock of an insect species.

Sequencing improves our ability to study threatened migratory species: Genetic population assignment in California's Central Valley Chinook salmon.

Effective conservation and management of migratory species requires accurate identification of unique populations, even as they mix along their migratory corridors. While telemetry has historically been used to study migratory animal movement and habitat use patterns, genomic tools are emerging as a superior alternative in many ways, allowing large-scale application at reduced costs. Here, we demonstrate the usefulness of genomic resources for identifying single-nucleotide polymorphisms (SNPs) that allow fast and accurate identification of the imperiled Chinook salmon in the Great Central Valley of California. We show that 80 well-chosen loci, drawn from a pool of over 11,500 SNPs developed from restriction site-associated DNA sequencing, can accurately identify Chinook salmon runs and select populations within run. No other SNP panel for Central Valley Chinook salmon has been able to achieve the high accuracy of assignment we show here. This panel will greatly improve our ability to study and manage this ecologically, economically, and socially important species and demonstrates the great utility of using genomics to study migratory species.

Discovery and characterization of single nucleotide polymorphisms in coho salmon, Oncorhynchus kisutch.

Molecular population genetic analyses have become an integral part of ecological investigation and population monitoring for conservation and management. Microsatellites have been the molecular marker of choice for such applications over the last several decades, but single nucleotide polymorphism (SNP) markers are rapidly expanding beyond model organisms. Coho salmon (Oncorhynchus kisutch) is native to the north Pacific Ocean and its tributaries, where it is the focus of intensive fishery and conservation activities. As it is an anadromous species, coho salmon typically migrate across multiple jurisdictional boundaries, complicating management and requiring shared data collection methods. Here, we describe the discovery and validation of a suite of novel SNPs and associated genotyping assays which can be used in the genetic analyses of this species. These assays include 91 that are polymorphic in the species and one that discriminates it from a sister species, Chinook salmon. We demonstrate the utility of these SNPs for population assignment and phylogeographic analyses, and map them against the draft trout genome. The markers constitute a large majority of all SNP markers described for coho salmon and will enable both population- and pedigree-based analyses across the southern part of the species native range.