Adaptive and neutral markers both show continent‐wide population structure of mountain pine beetle (Dendroctonus ponderosae)

Assessments of population genetic structure and demographic history have traditionally been based on neutral markers while explicitly excluding adaptive markers. In this study, we compared the utility of putatively adaptive and neutral single‐nucleotide polymorphisms (SNPs) for inferring mountain pine beetle population structure across its geographic range. Both adaptive and neutral SNPs, and their combination, allowed range‐wide structure to be distinguished and delimited a population that has recently undergone range expansion across northern British Columbia and Alberta. Using an equal number of both adaptive and neutral SNPs revealed that adaptive SNPs resulted in a stronger correlation between sampled populations and inferred clustering. Our results suggest that adaptive SNPs should not be excluded prior to analysis from neutral SNPs as a combination of both marker sets resulted in better resolution of genetic differentiation between populations than either marker set alone. These results demonstrate the utility of adaptive loci for resolving population genetic structure in a nonmodel organism.     

Population differentiation determined from putative neutral and divergent adaptive genetic markers in Eulachon (Thaleichthys pacificus,Osmeridae), an anadromous Pacific smelt

Twelve eulachon (Thaleichthys pacificus, Osmeridae) populations ranging from Cook Inlet, Alaska and along the west coast of North America to the Columbia River were examined by restriction‐site‐associated DNA (RAD) sequencing to elucidate patterns of neutral and adaptive variation in this high geneflow species. A total of 4104 single‐nucleotide polymorphisms (SNPs) were discovered across the genome, with 193 putatively adaptive SNPs as determined by F_ST outlier tests. Estimates of population structure in eulachon with the putatively adaptive SNPs were similar, but provided greater resolution of stocks compared with a putatively neutral panel of 3911 SNPs or previous estimates with 14 microsatellites. A cline of increasing measures of genetic diversity from south to north was found in the adaptive panel, but not in the neutral markers (SNPs or microsatellites). This may indicate divergent selective pressures in differing freshwater and marine environments between regional eulachon populations and that these adaptive diversity patterns not seen with neutral markers could be a consideration when determining genetic boundaries for conservation purposes. Estimates of effective population size (N_e) were similar with the neutral SNP panel and microsatellites and may be utilized to monitor population status for eulachon where census sizes are difficult to obtain. Greater differentiation with the panel of putatively adaptive SNPs provided higher individual assignment accuracy compared to the neutral panel or microsatellites for stock identification purposes. This study presents the first SNPs that have been developed for eulachon, and analyses with these markers highlighted the importance of integrating genome‐wide neutral and adaptive genetic variation for the applications of conservation and management.     

Sequence‐based SNP genotyping in durum wheat

Marker development for marker‐assisted selection in plant breeding is increasingly based on next‐generation sequencing (NGS). However, marker development in crops with highly repetitive, complex genomes is still challenging. Here we applied sequence‐based genotyping (SBG), which couples AFLP^®‐based complexity reduction to NGS, for de novo single nucleotide polymorphisms (SNP) marker discovery in and genotyping of a biparental durum wheat population. We identified 9983 putative SNPs in 6372 contigs between the two parents and used these SNPs for genotyping 91 recombinant inbred lines (RILs). Excluding redundant information from multiple SNPs per contig, 2606 (41%) markers were used for integration in a pre‐existing framework map, resulting in the integration of 2365 markers over 2607 cM. Of the 2606 markers available for mapping, 91% were integrated in the pre‐existing map, containing 708 SSRs, DArT markers, and SNPs from CRoPS technology, with a map‐size increase of 492 cM (23%). These results demonstrate the high quality of the discovered SNP markers. With this methodology, it was possible to saturate the map at a final marker density of 0.8 cM/marker. Looking at the binned marker distribution (Figure 2), 63 of the 268 10‐cM bins contained only SBG markers, showing that these markers are filling in gaps in the framework map. As to the markers that could not be used for mapping, the main reason was the low sequencing coverage used for genotyping. We conclude that SBG is a valuable tool for efficient, high‐throughput and high‐quality marker discovery and genotyping for complex genomes such as that of durum wheat.     

Sequence-based genotyping for marker discovery and co-dominant scoring in germplasm and populations

Conventional marker-based genotyping platforms are widely available, but not without their limitations. In this context, we developed Sequence-Based Genotyping (SBG), a technology for simultaneous marker discovery and co-dominant scoring, using next-generation sequencing. SBG offers users several advantages including a generic sample preparation method, a highly robust genome complexity reduction strategy to facilitate de novo marker discovery across entire genomes, and a uniform bioinformatics workflow strategy to achieve genotyping goals tailored to individual species, regardless of the availability of a reference sequence. The most distinguishing features of this technology are the ability to genotype any population structure, regardless whether parental data is included, and the ability to co-dominantly score SNP markers segregating in populations. To demonstrate the capabilities of SBG, we performed marker discovery and genotyping in Arabidopsis thaliana and lettuce, two plant species of diverse genetic complexity and backgrounds. Initially we obtained 1,409 SNPs for arabidopsis, and 5,583 SNPs for lettuce. Further filtering of the SNP dataset produced over 1,000 high quality SNP markers for each species. We obtained a genotyping rate of 201.2 genotypes/SNP and 58.3 genotypes/SNP for arabidopsis (n?=?222 samples) and lettuce (n?=?87 samples), respectively. Linkage mapping using these SNPs resulted in stable map configurations. We have therefore shown that the SBG approach presented provides users with the utmost flexibility in garnering high quality markers that can be directly used for genotyping and downstream applications. Until advances and costs will allow for routine whole-genome sequencing of populations, we expect that sequence-based genotyping technologies such as SBG will be essential for genotyping of model and non-model genomes alike.     

A Multi-Population Consensus Genetic Map Reveals Inconsistent Marker Order among Maps Likely Attributed to Structural Variations in the Apple Genome

Genetic maps serve as frameworks for determining the genetic architecture of quantitative traits, assessing structure of a genome, as well as aid in pursuing association mapping and comparative genetic studies. In this study, a dense genetic map was constructed using a high-throughput 1,536 EST-derived SNP GoldenGate genotyping platform and a global consensus map established by combining the new genetic map with four existing reliable genetic maps of apple. The consensus map identified markers with both major and minor conflicts in positioning across all five maps. These major inconsistencies among marker positions were attributed either to structural variations within the apple genome, or among mapping populations, or genotyping technical errors. These also highlighted problems in assembly and anchorage of the reference draft apple genome sequence in regions with known segmental duplications. Markers common across all five apple genetic maps resulted in successful positioning of 2875 markers, consisting of 2033 SNPs and 843 SSRs as well as other specific markers, on the global consensus map. These markers were distributed across all 17 linkage groups, with an average of 169±33 marker per linkage group and with an average distance of 0.70±0.14 cM between markers. The total length of the consensus map was 1991.38 cM with an average length of 117.14±24.43 cM per linkage group. A total of 569 SNPs were mapped onto the genetic map, consisting of 140 recombinant individuals, from our recently developed apple Oligonucleotide pool assays (OPA). The new functional SNPs, along with the dense consensus genetic map, will be useful for high resolution QTL mapping of important traits in apple and for pursuing comparative genetic studies in Rosaceae.     

Outlier SNP markers reveal fine‐scale genetic structuring across European hake populations (Merluccius merluccius)

Shallow population structure is generally reported for most marine fish and explained as a consequence of high dispersal, connectivity and large population size. Targeted gene analyses and more recently genome‐wide studies have challenged such view, suggesting that adaptive divergence might occur even when neutral markers provide genetic homogeneity across populations. Here, 381 SNPs located in transcribed regions were used to assess large‐ and fine‐scale population structure in the European hake (Merluccius merluccius), a widely distributed demersal species of high priority for the European fishery. Analysis of 850 individuals from 19 locations across the entire distribution range showed evidence for several outlier loci, with significantly higher resolving power. While 299 putatively neutral SNPs confirmed the genetic break between basins (F_CT = 0.016) and weak differentiation within basins, outlier loci revealed a dramatic divergence between Atlantic and Mediterranean populations (F_CT range 0.275–0.705) and fine‐scale significant population structure. Outlier loci separated North Sea and Northern Portugal populations from all other Atlantic samples and revealed a strong differentiation among Western, Central and Eastern Mediterranean geographical samples. Significant correlation of allele frequencies at outlier loci with seawater surface temperature and salinity supported the hypothesis that populations might be adapted to local conditions. Such evidence highlights the importance of integrating information from neutral and adaptive evolutionary patterns towards a better assessment of genetic diversity. Accordingly, the generated outlier SNP data could be used for tackling illegal practices in hake fishing and commercialization as well as to develop explicit spatial models for defining management units and stock boundaries.     

The Genome Sequence of a Widespread Apex Predator,the Golden Eagle (Aquila chrysaetos)

Biologists routinely use molecular markers to identify conservation units, to quantify genetic connectivity, to estimate population sizes, and to identify targets of selection. Many imperiled eagle populations require such efforts and would benefit from enhanced genomic resources. We sequenced, assembled, and annotated the first eagle genome using DNA from a male golden eagle (Aquila chrysaetos) captured in western North America. We constructed genomic libraries that were sequenced using Illumina technology and assembled the high-quality data to a depth of ∼40x coverage. The genome assembly includes 2,552 scaffolds >10 Kb and 415 scaffolds >1.2 Mb. We annotated 16,571 genes that are involved in myriad biological processes, including such disparate traits as beak formation and color vision. We also identified repetitive regions spanning 92 Mb (∼6% of the assembly), including LINES, SINES, LTR-RTs and DNA transposons. The mitochondrial genome encompasses 17,332 bp and is ∼91% identical to the Mountain Hawk-Eagle (Nisaetus nipalensis). Finally, the data reveal that several anonymous microsatellites commonly used for population studies are embedded within protein-coding genes and thus may not have evolved in a neutral fashion. Because the genome sequence includes ∼800,000 novel polymorphisms, markers can now be chosen based on their proximity to functional genes involved in migration, carnivory, and other biological processes.     

SNP Discovery with EST and NextGen Sequencing in Switchgrass (Panicum virgatum L.)

Although yield trials for switchgrass (Panicum virgatum L.), a potentially high value biofuel feedstock crop, are currently underway throughout North America, the genetic tools for crop improvement in this species are still in the early stages of development. Identification of high-density molecular markers, such as single nucleotide polymorphisms (SNPs), that are amenable to high-throughput genotyping approaches, is the first step in a quantitative genetics study of this model biofuel crop species. We generated and sequenced expressed sequence tag (EST) libraries from thirteen diverse switchgrass cultivars representing both upland and lowland ecotypes, as well as tetraploid and octoploid genomes. We followed this with reduced genomic library preparation and massively parallel sequencing of the same samples using the Illumina Genome Analyzer technology platform. EST libraries were used to generate unigene clusters and establish a gene-space reference sequence, thus providing a framework for assembly of the short sequence reads. SNPs were identified utilizing these scaffolds. We used a custom software program for alignment and SNP detection and identified over 149,000 SNPs across the 13 short-read sequencing libraries (SRSLs). Approximately 25,000 additional SNPs were identified from the entire EST collection available for the species. This sequencing effort generated data that are suitable for marker development and for estimation of population genetic parameters, such as nucleotide diversity and linkage disequilibrium. Based on these data, we assessed the feasibility of genome wide association mapping and genomic selection applications in switchgrass. Overall, the SNP markers discovered in this study will help facilitate quantitative genetics experiments and greatly enhance breeding efforts that target improvement of key biofuel traits and development of new switchgrass cultivars.     

LSGermOPA,a custom OPA of 384 EST-derived SNPs for high-throughput lettuce (<Emphasis Type="Italic">Lactuca sativa</Emphasis> L.) germplasm fingerprinting

To deploy a high-throughput genotyping platform in germplasm management, we designed and tested a custom OPA (Oligo Pool All), LSGermOPA, for assessing the genetic diversity and population structure of the USDA cultivated lettuce (Lactuca sativa L.) germplasm collection using Illumina’s GoldenGate assay. This OPA contains 384 EST (expressed sequence tag)-derived SNP (single nucleotide polymorphism) markers selected from a large set of SNP markers experimentally validated and mapped by the Compositae Genome Project. Used for genotyping were DNA samples prepared from bulked leaves of five randomly-selected seedlings from each of 380 lettuce accessions. High-quality genotype data were obtained from 354 of the 384 SNPs. The reproducibility of automatic genotype calls was 99.8% as calculated from the four pairs of duplicated DNA samples in the assay. An unexpectedly high percentage of heterozygous genotypes at the polymorphic loci for most accessions indicated a high level of heterogeneity within accessions. Only 148 homogenous accessions, collectively comprising all five horticultural types, were used in subsequent analyses to demonstrate the usefulness of LSGermOPA. The results of phylogenetic relationship, population structure and genetic differentiation analyses were consistent with previous reports using other marker systems. This suggests that LSGermOPA is capable of revealing sufficient levels of polymorphism among lettuce cultivars and is appropriate for rapid assessment of genetic diversity and population structure in the lettuce germplasm collection. Challenges and strategies for effective genotyping and managing lettuce germplasm are discussed.     

A dedicated target capture approach reveals variable genetic markers across micro‐ and macro‐evolutionary time scales in palms

Understanding the genetics of biological diversification across micro‐ and macro‐evolutionary time scales is a vibrant field of research for molecular ecologists as rapid advances in sequencing technologies promise to overcome former limitations. In palms, an emblematic, economically and ecologically important plant family with high diversity in the tropics, studies of diversification at the population and species levels are still hampered by a lack of genomic markers suitable for the genotyping of large numbers of recently diverged taxa. To fill this gap, we used a whole genome sequencing approach to develop target sequencing for molecular markers in 4,184 genome regions, including 4,051 genes and 133 non‐genic putatively neutral regions. These markers were chosen to cover a wide range of evolutionary rates allowing future studies at the family, genus, species and population levels. Special emphasis was given to the avoidance of copy number variation during marker selection. In addition, a set of 149 well‐known sequence regions previously used as phylogenetic markers by the palm biological research community were included in the target regions, to open the possibility to combine and jointly analyse already available data sets with genomic data to be produced with this new toolkit. The bait set was effective for species belonging to all three palm sub‐families tested (Arecoideae, Ceroxyloideae and Coryphoideae), with high mapping rates, specificity and efficiency. The number of high‐quality single nucleotide polymorphisms (SNPs) detected at both the sub‐family and population levels facilitates efficient analyses of genomic diversity across micro‐ and macro‐evolutionary time scales.     

Single nucleotide polymorphisms for pig identification and parentage exclusion

Single nucleotide polymorphisms (SNPs) have become an important type of marker for commercial diagnostic and parentage genotyping applications as automated genotyping systems have been developed that yield accurate genotypes. Unfortunately, allele frequencies for public SNP markers in commercial pig populations have not been available. To fulfil this need, SNP markers previously mapped in the USMARC swine reference population were tested in a panel of 155 boars that were representative of US purebred Duroc, Hampshire, Landrace and Yorkshire populations. Multiplex assay groups of 5-7 SNP assays/group were designed and genotypes were determined using Sequenom's massarray system. Of 80 SNPs that were evaluated, 60 SNPs with minor allele frequencies >0.15 were selected for the final panel of markers. Overall identity power across breeds was 4.6 x 10(-23), but within-breed values ranged from 4.3 x 10(-14) (Hampshire) to 2.6 x 10(-22) (Yorkshire). Parentage exclusion probability with only one sampled parent was 0.9974 (all data) and ranged from 0.9594 (Hampshire) to 0.9963 (Yorkshire) within breeds. Sire exclusion probability when the dam's genotype was known was 0.99998 (all data) and ranged from 0.99868 (Hampshire) to 0.99997 (Yorkshire) within breeds. Power of exclusion was compared between the 60 SNP and 10 microsatellite markers. The parental exclusion probabilities for SNP and microsatellite marker panels were similar, but the SNP panel was much more sensitive for individual identification. This panel of SNP markers is theoretically sufficient for individual identification of any pig in the world and is publicly available.     

Development of single nucleotide polymorphism (SNP) markers for use in commercial maize (Zea mays L.) germplasm

The development of single nucleotide polymorphism (SNP) markers in maize offers the opportunity to utilize DNA markers in many new areas of population genetics, gene discovery, plant breeding and germplasm identification. However, the steps from sequencing and SNP discovery to SNP marker design and validation are lengthy and expensive. Access to a set of validated SNP markers is a significant advantage to maize researchers who wish to apply SNPs in scientific inquiry. We mined 1,088 loci sequenced across 60 public inbreds that have been used in maize breeding in North America and Europe. We then selected 640 SNPs using generalized marker design criteria that enable utilization with several SNP chemistries. While SNPs were found on average every 43 bases in 1,088 maize gene sequences, SNPs that were amenable to marker design were found on average every 623 bases; representing only 7% of the total SNPs discovered. We also describe the development of a 768 marker multiplex assay for use on the Illumina^® BeadArray? platform. SNP markers were mapped on the IBM2 intermated B73 × Mo17 high resolution genetic map using either the IBM2 segregating population, or segregation in multiple parent-progeny triplets. A high degree of colinearity was found with the genetic nested association map. For each SNP presented we give information on map location, polymorphism rates in different heterotic groups and performance on the Illumina^® platform.     

A large-scale rheumatoid arthritis genetic study identifies association at chromosome 9q33.2

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease affecting both joints and extra-articular tissues. Although some genetic risk factors for RA are well-established, most notably HLA-DRB1 and PTPN22, these markers do not fully account for the observed heritability. To identify additional susceptibility loci, we carried out a multi-tiered, case-control association study, genotyping 25,966 putative functional SNPs in 475 white North American RA patients and 475 matched controls. Significant markers were genotyped in two additional, independent, white case-control sample sets (661 cases/1322 controls from North America and 596 cases/705 controls from The Netherlands) identifying a SNP, rs1953126, on chromosome 9q33.2 that was significantly associated with RA (OR(common) = 1.28, trend P(comb) = 1.45E-06). Through a comprehensive fine-scale-mapping SNP-selection procedure, 137 additional SNPs in a 668 kb region from MEGF9 to STOM on 9q33.2 were chosen for follow-up genotyping in a staged-approach. Significant single marker results (P(comb)<0.01) spanned a large 525 kb region from FBXW2 to GSN. However, a variety of analyses identified SNPs in a 70 kb region extending from the third intron of PHF19 across TRAF1 into the TRAF1-C5 intergenic region, but excluding the C5 coding region, as the most interesting (trend P(comb): 1.45E-06 --> 5.41E-09). The observed association patterns for these SNPs had heightened statistical significance and a higher degree of consistency across sample sets. In addition, the allele frequencies for these SNPs displayed reduced variability between control groups when compared to other SNPs. Lastly, in combination with the other two known genetic risk factors, HLA-DRB1 and PTPN22, the variants reported here generate more than a 45-fold RA-risk differential.     

Unraveling hierarchical genetic structure in a marine metapopulation: A comparison of three high‐throughput genotyping approaches

Marine metapopulations often exhibit subtle population structure that can be difficult to detect. Given recent advances in high‐throughput sequencing, an emerging question is whether various genotyping approaches, in concert with improved sampling designs, will substantially improve our understanding of genetic structure in the sea. To address this question, we explored hierarchical patterns of structure in the coral reef fish Elacatinus lori using a high‐resolution approach with respect to both genetic and geographic sampling. Previously, we identified three putative E. lori populations within Belize using traditional genetic markers and sparse geographic sampling: barrier reef and Turneffe Atoll; Glover's Atoll; and Lighthouse Atoll. Here, we systematically sampled individuals at ~10 km intervals throughout these reefs (1,129 individuals from 35 sites) and sequenced all individuals at three sets of markers: 2,418 SNPs; 89 microsatellites; and 57 nonrepetitive nuclear loci. At broad spatial scales, the markers were consistent with each other and with previous findings. At finer spatial scales, there was new evidence of genetic substructure, but our three marker sets differed slightly in their ability to detect these patterns. Specifically, we found subtle structure between the barrier reef and Turneffe Atoll, with SNPs resolving this pattern most effectively. We also documented isolation by distance within the barrier reef. Sensitivity analyses revealed that the number of loci (and alleles) had a strong effect on the detection of structure for all three marker sets, particularly at small spatial scales. Taken together, these results illustrate empirically that high‐throughput genotyping data can elucidate subtle genetic structure at previously‐undetected scales in a dispersive marine fish.     

Multiplex PCR amplification of 13 microsatellite loci for <Emphasis Type="Italic">Aquila chrysaetos</Emphasis> in forensic applications

The golden eagle (Aquila chrysaetos) is an endangered raptor, which is threatened mainly by illegal egg and nestling robbery. Here we describe a fluorescently labeled, multiplex PCR method using 13 microsatellite markers, which provides a powerful tool for the individual identification and parentage testing of the Golden eagle. This test should be applicable to both forensic analysis and population studies. Fifteen polymorphic loci from A. chrysaetos were cross-amplified. Subsequent PCR condition optimization led to the successful co-amplification of 13 different loci in a single PCR reaction. Fifty samples from wild-living individuals and 89 samples from captive-bred individuals were examined. The results indicated that both populations have similar levels of moderate inbreeding, unsurprising in a small population. This probability of excluding a random individual in parentage analysis was 0.9912 for the wild population and 0.9932 in the captive-bred one in the case that both the individual and its mother were examined together. The probability of identity was estimated to be 3 × 10⁻⁸ for the wild and 4 × 10⁻⁸ for the captive-bred populations. Given the size of the Slovak golden eagle population, this test should therefore be sufficient to reliably identify individual raptors and assess parentage in both conservation studies and forensic analysis.     

High-throughput genotyping and mapping of single nucleotide polymorphisms in loblolly pine (Pinus taeda L.)

The development and application of genomic tools to loblolly pine (Pinus taeda L.) offer promising insights into the organization and structure of conifer genomes. The application of a high-throughput genotyping assay across diverse forest tree species, however, is currently limited taxonomically. This is despite the ongoing development of genome-scale projects aiming at the construction of expressed sequence tag (EST) libraries and the resequencing of EST-derived unigenes for a diverse array of forest tree species. In this paper, we report on the application of Illumina’s high-throughput GoldenGate™ SNP genotyping assay to a loblolly pine mapping population. Single nucleotide polymorphisms (SNPs) were identified through resequencing of previously identified wood quality, drought tolerance, and disease resistance candidate genes prior to genotyping. From that effort, a 384 multiplexed SNP assay was developed for high-throughput genotyping. Approximately 67% of the 384 SNPs queried converted into high-quality genotypes for the 48 progeny samples. Of those 257 successfully genotyped SNPs, 70 were segregating within the mapping population. A total of 27 candidate genes were subsequently mapped onto the existing loblolly pine consensus map, which consists of 12 linkage groups spanning a total map distance of 1,227.6 cM. The ability of SNPs to be mapped to the same position as fragment-based markers previously developed within the same candidate genes, as well as the pivotal role that SNPs currently play in the dissection of complex phenotypic traits, illustrate the usefulness of high-throughput SNP genotyping technologies to the continued development of pine genomics. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Modelling habitat use and distribution of golden eagles <Emphasis Type="Italic">Aquila chrysaetos</Emphasis> in a low-density area of the Iberian Peninsula

We analyse the current situation of the Golden eagle (Aquila chrysaetos) in the region of Galicia in NW Spain. At present, the entire Galician population (five pairs) is located within an area of about 2000 km² in the province of Ourense. To identify high-priority areas for golden eagle conservation, we derived predictive models of habitat suitability using logistic regression and a Geographic Information System (GIS). Specifically, to model the distribution of the breeding population we considered topographic features, land use and degree of humanization, using a 10 × 10 km grid. Presence/absence of golden eagle nests was used as the dependent variable; analyses were performed both considering current nesting areas and considering old nesting areas (1960s and 70s). At the spatial scale considered, the best predictors of habitat suitability for breeding were topographical variables indicative of rugged relief. For current nesting areas the most parsimonious model included maximum altitude. We consider that the predictive models obtained may be of use for the monitoring and conservation management of the golden eagle population in this region. Conservation problems associated with habitat constraints such as food supply, availability of nesting sites, changes in land use and human disturbance are discussed.     

Conservation genomics of anadromous Atlantic salmon across its North American range: outlier loci identify the same patterns of population structure as neutral loci

Anadromous Atlantic salmon (Salmo salar) is a species of major conservation and management concern in North America, where population abundance has been declining over the past 30 years. Effective conservation actions require the delineation of conservation units to appropriately reflect the spatial scale of intraspecific variation and local adaptation. Towards this goal, we used the most comprehensive genetic and genomic database for Atlantic salmon to date, covering the entire North American range of the species. The database included microsatellite data from 9142 individuals from 149 sampling locations and data from a medium‐density SNP array providing genotypes for >3000 SNPs for 50 sampling locations. We used neutral and putatively selected loci to integrate adaptive information in the definition of conservation units. Bayesian clustering with the microsatellite data set and with neutral SNPs identified regional groupings largely consistent with previously published regional assessments. The use of outlier SNPs did not result in major differences in the regional groupings, suggesting that neutral markers can reflect the geographic scale of local adaptation despite not being under selection. We also performed assignment tests to compare power obtained from microsatellites, neutral SNPs and outlier SNPs. Using SNP data substantially improved power compared to microsatellites, and an assignment success of 97% to the population of origin and of 100% to the region of origin was achieved when all SNP loci were used. Using outlier SNPs only resulted in minor improvements to assignment success to the population of origin but improved regional assignment. We discuss the implications of these new genetic resources for the conservation and management of Atlantic salmon in North America.     

Continent‐wide population genomic structure and phylogeography of North America’s most destructive conifer defoliator,the spruce budworm (Choristoneura fumiferana)

The spruce budworm, Choristoneura fumiferana, is presumed to be panmictic across vast regions of North America. We examined the extent of panmixia by genotyping 3,650 single nucleotide polymorphism (SNP) loci in 1975 individuals from 128 collections across the continent. We found three spatially structured subpopulations: Western (Alaska, Yukon), Central (southeastern Yukon to the Manitoba–Ontario border), and Eastern (Manitoba–Ontario border to the Atlantic). Additionally, the most diagnostic genetic differentiation between the Central and Eastern subpopulations was chromosomally restricted to a single block of SNPs that may constitute an island of differentiation within the species. Geographic differentiation in the spruce budworm parallels that of its principal larval host, white spruce (Picea glauca), providing evidence that spruce budworm and spruce trees survived in the Beringian refugium through the Last Glacial Maximum and that at least two isolated spruce budworm populations diverged with spruce/fir south of the ice sheets. Gene flow in the spruce budworm may also be affected by mountains in western North America, habitat isolation in West Virginia, regional adaptations, factors related to dispersal, and proximity of other species in the spruce budworm species complex. The central and eastern geographic regions contain individuals that assign to Eastern and Central subpopulations, respectively, indicating that these barriers are not complete. Our discovery of previously undetected geographic and genomic structure in the spruce budworm suggests that further population modelling of this ecologically important insect should consider regional differentiation, potentially co‐adapted blocks of genes, and gene flow between subpopulations.