Estimation of population allele frequencies from next‐generation sequencing data: pool‐versus individual‐based genotyping

Molecular markers produced by next‐generation sequencing (NGS) technologies are revolutionizing genetic research. However, the costs of analysing large numbers of individual genomes remain prohibitive for most population genetics studies. Here, we present results based on mathematical derivations showing that, under many realistic experimental designs, NGS of DNA pools from diploid individuals allows to estimate the allele frequencies at single nucleotide polymorphisms (SNPs) with at least the same accuracy as individual‐based analyses, for considerably lower library construction and sequencing efforts. These findings remain true when taking into account the possibility of substantially unequal contributions of each individual to the final pool of sequence reads. We propose the intuitive notion of effective pool size to account for unequal pooling and derive a Bayesian hierarchical model to estimate this parameter directly from the data. We provide a user‐friendly application assessing the accuracy of allele frequency estimation from both pool‐ and individual‐based NGS population data under various sampling, sequencing depth and experimental error designs. We illustrate our findings with theoretical examples and real data sets corresponding to SNP loci obtained using restriction site–associated DNA (RAD) sequencing in pool‐ and individual‐based experiments carried out on the same population of the pine processionary moth (Thaumetopoea pityocampa). NGS of DNA pools might not be optimal for all types of studies but provides a cost‐effective approach for estimating allele frequencies for very large numbers of SNPs. It thus allows comparison of genome‐wide patterns of genetic variation for large numbers of individuals in multiple populations.     

Comparison of whole‐genome (13X) and capture (87X) resequencing methods for SNP and genotype callings

The number of polymorphisms identified with next‐generation sequencing approaches depends directly on the sequencing depth and therefore on the experimental cost. Although higher levels of depth ensure more sensitive and more specific SNP calls, economic constraints limit the increase of depth for whole‐genome resequencing (WGS). For this reason, capture resequencing is used for studies focusing on only some specific regions of the genome. However, several biases in capture resequencing are known to have a negative impact on the sensitivity of SNP detection. Within this framework, the aim of this study was to compare the accuracy of WGS and capture resequencing on SNP detection and genotype calling, which differ in terms of both sequencing depth and biases. Indeed, we have evaluated the SNP calling and genotyping accuracy in a WGS dataset (13X) and in a capture resequencing dataset (87X) performed on 11 individuals. The percentage of SNPs not identified due to a sevenfold sequencing depth decrease was estimated at 7.8% using a down‐sampling procedure on the capture sequencing dataset. A comparison of the 87X capture sequencing dataset with the WGS dataset revealed that capture‐related biases were leading with the loss of 5.2% of SNPs detected with WGS. Nevertheless, when considering the SNPs detected by both approaches, capture sequencing appears to achieve far better SNP genotyping, with about 4.4% of the WGS genotypes that can be considered as erroneous and even 10% focusing on heterozygous genotypes. In conclusion, WGS and capture deep sequencing can be considered equivalent strategies for SNP detection, as the rate of SNPs not identified because of a low sequencing depth in the former is quite similar to SNPs missed because of method biases of the latter. On the other hand, capture deep sequencing clearly appears more adapted for studies requiring great accuracy in genotyping.     

Whole genome sequencing reveals rare off‐target mutations and considerable inherent genetic or/and somaclonal variations in CRISPR/Cas9‐edited cotton plants

The CRISPR/Cas9 system has been extensively applied for crop improvement. However, our understanding of Cas9 specificity is very limited in Cas9‐edited plants. To identify on‐ and off‐target mutation in an edited crop, we described whole genome sequencing (WGS) of 14 Cas9‐edited cotton plants targeted to three genes, and three negative (Ne) control and three wild‐type (WT) plants. In total, 4188–6404 unique single‐nucleotide polymorphisms (SNPs) and 312–745 insertions/deletions (indels) were detected in 14 Cas9‐edited plants compared to WT, negative and cotton reference genome sequences. Since the majority of these variations lack a protospacer‐adjacent motif (PAM), we demonstrated that the most variations following Cas9‐edited are due either to somaclonal variation or/and pre‐existing/inherent variation from maternal plants, but not off‐target effects. Of a total of 4413 potential off‐target sites (allowing ≤5 mismatches within the 20‐bp sgRNA and 3‐bp PAM sequences), the WGS data revealed that only four are bona fide off‐target indel mutations, validated by Sanger sequencing. Moreover, inherent genetic variation of WT can generate novel off‐target sites and destroy PAMs, which suggested great care should be taken to design sgRNA for the minimizing of off‐target effect. These findings suggested that CRISPR/Cas9 system is highly specific for cotton plants.     

PMERGE: Computational filtering of paralogous sequences from RAD‐seq data

Restriction‐site associated DNA sequencing (RAD‐seq) can identify and score thousands of genetic markers from a group of samples for population‐genetics studies. One challenge of de novo RAD‐seq analysis is to distinguish paralogous sequence variants (PSVs) from true single‐nucleotide polymorphisms (SNPs) associated with orthologous loci. In the absence of a reference genome, it is difficult to differentiate true SNPs from PSVs, and their impact on downstream analysis remains unclear. Here, we introduce a network‐based approach, PMERGE that connects fragments based on their DNA sequence similarity to identify probable PSVs. Applying our method to de novo RAD‐seq data from 150 Atlantic salmon (Salmo salar) samples collected from 15 locations across the Southern Newfoundland coast allowed the identification of 87% of total PSVs identified through alignment to the Atlantic salmon genome. Removal of these paralogs altered the inferred population structure, highlighting the potential impact of filtering in RAD‐seq analysis. PMERGE is also applied to a green crab (Carcinus maenas) data set consisting of 242 samples from 11 different locations and was successfully able to identify and remove the majority of paralogous loci (62%). The PMERGE software can be run as part of the widely used Stacks analysis package.     

The design and application of a 50 K SNP chip for a threatened Aotearoa New Zealand passerine,the hihi

Next-generation sequencing has transformed the fields of ecological and evolutionary genetics by allowing for cost-effective identification of genome-wide variation. Single nucleotide polymorphism (SNP) arrays, or “SNP chips”, enable very large numbers of individuals to be consistently genotyped at a selected set of these identified markers, and also offer the advantage of being able to analyse samples of variable DNA quality. We used reduced representation restriction-aided digest sequencing (RAD-seq) of 31 birds of the threatened hihi (Notiomystis cincta; stitchbird) and low-coverage whole genome sequencing (WGS) of 10 of these birds to develop an Affymetrix 50 K SNP chip. We overcame the limitations of having no hihi reference genome and a low quantity of sequence data by separate and pooled de novo assembly of each of the 10 WGS birds. Reads from all individuals were mapped back to these de novo assemblies to identify SNPs. A subset of RAD-seq and WGS SNPs were selected for inclusion on the chip, prioritising SNPs with the highest quality scores whose flanking sequence uniquely aligned to the zebra finch (Taeniopygia guttata) genome. Of the 58,466 SNPs manufactured on the chip, 72% passed filtering metrics and were polymorphic. By genotyping 1,536 hihi on the array, we found that SNPs detected in multiple assemblies were more likely to successfully genotype, representing a cost-effective approach to identify SNPs for genotyping. Here, we demonstrate the utility of the SNP chip by describing the high rates of linkage disequilibrium in the hihi genome, reflecting the history of population bottlenecks in the species.     

Multiplex restriction amplicon sequencing: a novel next‐generation sequencing‐based marker platform for high‐throughput genotyping

To enable rapid selection of traits in marker‐assisted breeding, markers must be technically simple, low‐cost, high‐throughput and randomly distributed in a genome. We developed such a technology, designated as Multiplex Restriction Amplicon Sequencing (MRASeq), which reduces genome complexity by polymerase chain reaction (PCR) amplification of amplicons flanked by restriction sites. The first PCR primers contain restriction site sequences at 3’‐ends, preceded by 6‐10 bases of specific or degenerate nucleotide sequences and then by a unique M13‐tail sequence which serves as a binding site for a second PCR that adds sequencing primers and barcodes to allow sample multiplexing for sequencing. The sequences of restriction sites and adjacent nucleotides can be altered to suit different species. Physical mapping of MRASeq SNPs from a biparental population of allohexaploid wheat (Triticum aestivum L.) showed a random distribution of SNPs across the genome. MRASeq generated thousands of SNPs from a wheat biparental population and natural populations of wheat and barley (Hordeum vulgare L.). This novel, next‐generation sequencing‐based genotyping platform can be used for linkage mapping to screen quantitative trait loci (QTL), background selection in breeding and many other genetics and breeding applications of various species.     

Genotype‐by‐sequencing of the plant‐pathogenic fungi Pyrenophora teres and Sphaerulina musiva utilizing Ion Torrent sequence technology

Genetic and genomics tools to characterize host–pathogen interactions are disproportionately directed to the host because of the focus on resistance. However, understanding the genetics of pathogen virulence is equally important and has been limited by the high cost of de novo genotyping of species with limited marker data. Non‐resource‐prohibitive methods that overcome the limitation of genotyping are now available through genotype‐by‐sequencing (GBS). The use of a two‐enzyme restriction‐associated DNA (RAD)‐GBS method adapted for Ion Torrent sequencing technology provided robust and reproducible high‐density genotyping of several fungal species. A total of 5783 and 2373 unique loci, ‘sequence tags’, containing 16 441 and 9992 single nucleotide polymorphisms (SNPs) were identified and characterized from natural populations of Pyrenophora teres f. maculata and Sphaerulina musiva, respectively. The data generated from the P. teres f. maculata natural population were used in association mapping analysis to map the mating‐type gene to high resolution. To further validate the methodology, a biparental population of P. teres f. teres, previously used to develop a genetic map utilizing simple sequence repeat (SSR) and amplified fragment length polymorphism (AFLP) markers, was re‐analysed using the SNP markers generated from this protocol. A robust genetic map containing 1393 SNPs on 997 sequence tags spread across 15 linkage groups with anchored reference markers was generated from the P. teres f. teres biparental population. The robust high‐density markers generated using this protocol will allow positional cloning in biparental fungal populations, association mapping of natural fungal populations and population genetics studies.     

SNP discovery and genotyping using restriction‐site‐associated DNA sequencing in chickens

Single nucleotide polymorphisms (SNPs) are essential to the understanding of population genetic variation and diversity. Here, we performed restriction‐site‐associated DNA sequencing (RAD‐seq) on 72 individuals from 13 Chinese indigenous and three introduced chicken breeds. A total of 620 million reads were obtained using an Illumina Hiseq2000 sequencer. An average of 75 587 SNPs were identified from each individual. Further filtering strictly validated 28 895 SNPs candidates for all populations. When compared with the NCBI dbSNP (chicken_9031), 15 404 SNPs were new discoveries. In this study, RAD‐seq was performed for the first time on chickens, implicating the remarkable effectiveness and potential applications on genetic analysis and breeding technique for whole‐genome selection in chicken and other agricultural animals.     

SNP discovery using Paired‐End RAD‐tag sequencing on pooled genomic DNA of Sisymbrium austriacum (Brassicaceae)

Single nucleotide polymorphisms SNPs are rapidly replacing anonymous markers in population genomic studies, but their use in non model organisms is hampered by the scarcity of cost‐effective approaches to uncover genome‐wide variation in a comprehensive subset of individuals. The screening of one or only a few individuals induces ascertainment bias. To discover SNPs for a population genomic study of the Pyrenean rocket (Sisymbrium austriacum subsp. chrysanthum), we undertook a pooled RAD‐PE (Restriction site Associated DNA Paired‐End sequencing) approach. RAD tags were generated from the PstI‐digested pooled genomic DNA of 12 individuals sampled across the species distribution range and paired‐end sequenced using Illumina technology to produce ~24.5 Mb of sequences, covering ~7% of the specie's genome. Sequences were assembled into ~76 000 contigs with a mean length of 323 bp (N₅₀ = 357 bp, sequencing depth = 24x). In all, >15 000 SNPs were called, of which 47% were annotated in putative genic regions based on homology with the Arabidopsis thaliana genome. Gene ontology (GO) slim categorization demonstrated that the identified SNPs covered extant genic variation well. The validation of 300 SNPs on a larger set of individuals using a KASPar assay underpinned the utility of pooled RAD‐PE as an inexpensive genome‐wide SNP discovery technique (success rate: 87%). In addition to SNPs, we discovered >600 putative SSR markers.     

Whole‐genome resequencing‐based QTL‐seq identified candidate genes and molecular markers for fresh seed dormancy in groundnut

The subspecies fastigiata of cultivated groundnut lost fresh seed dormancy (FSD) during domestication and human‐made selection. Groundnut varieties lacking FSD experience precocious seed germination during harvest imposing severe losses. Development of easy‐to‐use genetic markers enables early‐generation selection in different molecular breeding approaches. In this context, one recombinant inbred lines (RIL) population (ICGV 00350 × ICGV 97045) segregating for FSD was used for deploying QTL‐seq approach for identification of key genomic regions and candidate genes. Whole‐genome sequencing (WGS) data (87.93 Gbp) were generated and analysed for the dormant parent (ICGV 97045) and two DNA pools (dormant and nondormant). After analysis of resequenced data from the pooled samples with dormant parent (reference genome), we calculated delta‐SNP index and identified a total of 10,759 genomewide high‐confidence SNPs. Two candidate genomic regions spanning 2.4 Mb and 0.74 Mb on the B05 and A09 pseudomolecules, respectively, were identified controlling FSD. Two candidate genes—RING‐H2 finger protein and zeaxanthin epoxidase—were identified in these two regions, which significantly express during seed development and control abscisic acid (ABA) accumulation. QTL‐seq study presented here laid out development of a marker, GMFSD1, which was validated on a diverse panel and could be used in molecular breeding to improve dormancy in groundnut.     

Genetic variation and population genetic structure of Laodelphax striatellus via genome‐wide single nucleotide polymorphisms from specific‐locus amplified fragment‐sequencing

The small brown planthopper (SBPH), Laodelphax striatellus, is one of the most destructive agricultural pests that causes serious economic loss in the main rice‐producing areas of China. To clarify issues such as the genetic differentiation, gene flow and population genetic structure of SBPH populations, we investigated the genetic diversity, genetic structure and phylogeography of 27 SBPH populations at 23 sampling sites from three climatic zones of China using specific‐locus amplified fragment sequencing (SLAF‐seq) for large‐scale single nucleotide polymorphism (SNP) detection. In total, 115.95 M reads, 56,355 polymorphic specific‐locus amplified fragments were developed, and 32,556 reliable single nucleotides (SNPs) were detected. The results indicated that the genotypes of many polymorphism sites had low heterozygosity in every population. Overall, the pairwise F_ST values between the populations varied from 0.056 to 0.092; it suggested the lack of strong differentiation among three climatic zone groups, respectively. It also suggested a strong level of gene flow (Nm) among populations in different climate zones, ranging from 28.864 to 35.197. Phylogenetic analyses, principal component analysis (PCA), Bayesian clustering method and AMOVA revealed that there was no evidence genetic clustering in three main bioclimatic zones. Neutrality testing provided strong evidence for a recent rapid expansion without any recent genetic bottleneck in these populations. Accordingly, the results of the present study should be beneficial for SBPH management and provide insight into the genetics of SBPH.     

A resource of genome‐wide single‐nucleotide polymorphisms generated by RAD tag sequencing in the critically endangered European eel

Reduced representation genome sequencing such as restriction‐site‐associated DNA (RAD) sequencing is finding increased use to identify and genotype large numbers of single‐nucleotide polymorphisms (SNPs) in model and nonmodel species. We generated a unique resource of novel SNP markers for the European eel using the RAD sequencing approach that was simultaneously identified and scored in a genome‐wide scan of 30 individuals. Whereas genomic resources are increasingly becoming available for this species, including the recent release of a draft genome, no genome‐wide set of SNP markers was available until now. The generated SNPs were widely distributed across the eel genome, aligning to 4779 different contigs and 19 703 different scaffolds. Significant variation was identified, with an average nucleotide diversity of 0.00529 across individuals. Results varied widely across the genome, ranging from 0.00048 to 0.00737 per locus. Based on the average nucleotide diversity across all loci, long‐term effective population size was estimated to range between 132 000 and 1 320 000, which is much higher than previous estimates based on microsatellite loci. The generated SNP resource consisting of 82 425 loci and 376 918 associated SNPs provides a valuable tool for future population genetics and genomics studies and allows for targeting specific genes and particularly interesting regions of the eel genome.     

Population genomics reveals multiple drivers of population differentiation in a sex‐role‐reversed pipefish

A major goal of molecular ecology is to identify the causes of genetic and phenotypic differentiation among populations. Population genomics is suitably poised to tackle these key questions by diagnosing the evolutionary mechanisms driving divergence in nature. Here, we set out to investigate the evolutionary processes underlying population differentiation in the Gulf pipefish, Syngnathus scovelli. We sampled approximately 50 fish from each of 12 populations distributed from the Gulf coast of Texas to the Atlantic coast of Florida and performed restriction‐site‐associated DNA sequencing to identify SNPs throughout the genome. After imposing quality and stringency filters, we selected a panel of 6348 SNPs present in all 12 populations, 1753 of which were not physically linked. We identified a genome‐wide pattern of isolation by distance, in addition to a more substantial genetic break separating populations in the Gulf of Mexico from those in the Atlantic. We also used several divergence outlier approaches and tests for genotype–environment correlations to identify 400 SNPs putatively involved in local adaptation. Patterns of phenotypic differentiation and variation diverged from the overall genomic pattern, suggesting that selection, phenotypic plasticity or demographic factors may be shaping phenotypes in distinct populations. Overall, our results suggest that population divergence is driven by a variety of factors in S. scovelli, including neutral processes and selection on multiple traits.     

Development of high‐density SNP genotyping arrays for white spruce (Picea glauca) and transferability to subtropical and nordic congeners

High‐density SNP genotyping arrays can be designed for any species given sufficient sequence information of high quality. Two high‐density SNP arrays relying on the Infinium iSelect technology (Illumina) were designed for use in the conifer white spruce (Picea glauca). One array contained 7338 segregating SNPs representative of 2814 genes of various molecular functional classes for main uses in genetic association and population genetics studies. The other one contained 9559 segregating SNPs representative of 9543 genes for main uses in population genetics, linkage mapping of the genome and genomic prediction. The SNPs assayed were discovered from various sources of gene resequencing data. SNPs predicted from high‐quality sequences derived from genomic DNA reached a genotyping success rate of 64.7%. Nonsingleton in silico SNPs (i.e. a sequence polymorphism present in at least two reads) predicted from expressed sequenced tags obtained with the Roche 454 technology and Illumina GAII analyser resulted in a similar genotyping success rate of 71.6% when the deepest alignment was used and the most favourable SNP probe per gene was selected. A variable proportion of these SNPs was shared by other nordic and subtropical spruce species from North America and Europe. The number of shared SNPs was inversely proportional to phylogenetic divergence and standing genetic variation in the recipient species, but positively related to allele frequency in P. glauca natural populations. These validated SNP resources should open up new avenues for population genetics and comparative genetic mapping at a genomic scale in spruce species.     

Genotype‐free estimation of allele frequencies reduces bias and improves demographic inference from RADSeq data

Restriction‐site associated DNA sequencing (RADSeq) facilitates rapid generation of thousands of genetic markers at relatively low cost; however, several sources of error specific to RADSeq methods often lead to biased estimates of allele frequencies and thereby to erroneous population genetic inference. Estimating the distribution of sample allele frequencies without calling genotypes was shown to improve population inference from whole genome sequencing data, but the ability of this approach to account for RADSeq‐specific biases remains unexplored. Here we assess in how far genotype‐free methods of allele frequency estimation affect demographic inference from empirical RADSeq data. Using the well‐studied pied flycatcher (Ficedula hypoleuca) as a study system, we compare allele frequency estimation and demographic inference from whole genome sequencing data with that from RADSeq data matched for samples using both genotype‐based and genotype free methods. The demographic history of pied flycatchers as inferred from RADSeq data was highly congruent with that inferred from whole genome resequencing (WGS) data when allele frequencies were estimated directly from the read data. In contrast, when allele frequencies were derived from called genotypes, RADSeq‐based estimates of most model parameters fell outside the 95% confidence interval of estimates derived from WGS data. Notably, more stringent filtering of the genotype calls tended to increase the discrepancy between parameter estimates from WGS and RADSeq data, respectively. The results from this study demonstrate the ability of genotype‐free methods to improve allele frequency spectrum‐ (AFS‐) based demographic inference from empirical RADSeq data and highlight the need to account for uncertainty in NGS data regardless of sequencing method.     

Development and preliminary evaluation of a genomewide single nucleotide polymorphisms resource generated by RAD‐seq for the small yellow croaker (Larimichthys polyactis)

Recent advances in high‐throughput sequencing technologies have offered the possibility to generate genomewide sequence data to delineate previously unidentified genetic structure, obtain more accurate estimates of demographic parameters and to evaluate potential adaptive divergence. Here, we identified 27 556 single nucleotide polymorphisms for the small yellow croaker (Larimichthys polyactis) using restriction‐site‐associated DNA (RAD) sequencing of 24 individuals from two populations. Significant sources of genetic variation were identified, with an average nucleotide diversity (π) of 0.00105 ± 0.000425 across individuals, and long‐term effective population size was thus estimated to range between 26 172 and 261 716. According to the results, no differentiation between the two populations was detected based on the SNP data set of top quality score per contig or neutral loci. However, the two analysed populations were highly differentiated based on SNP data set of both top F_ST value per contig and the outlier SNPs. Moreover, local adaptation was highlighted by an F_ST‐based outlier tests implemented in LOSITAN and a total of 538 potentially locally selected SNPs were identified. blast2go annotation of contigs containing the outlier SNPs yielded hits for 37 (66%) of 56 significant blastx matches. Candidate genes for local adaptation constituted a wide array of biological functions, including cellular response to oxidative stress, actin filament binding, ion transmembrane transport and synapse assembly. The generated SNP resources in this study provided a valuable tool for future population genetics and genomics studies of L. polyactis.     

THE GENETIC ARCHITECTURE OF REPRODUCTIVE ISOLATION DURING SPECIATION‐WITH‐GENE‐FLOW IN LAKE WHITEFISH SPECIES PAIRS ASSESSED BY RAD SEQUENCING

During speciation‐with‐gene‐flow, effective migration varies across the genome as a function of several factors, including proximity of selected loci, recombination rate, strength of selection, and number of selected loci. Genome scans may provide better empirical understanding of the genome‐wide patterns of genetic differentiation, especially if the variance due to the previously mentioned factors is partitioned. In North American lake whitefish (Coregonus clupeaformis), glacial lineages that diverged in allopatry about 60,000 years ago and came into contact 12,000 years ago have independently evolved in several lakes into two sympatric species pairs (a normal benthic and a dwarf limnetic). Variable degrees of reproductive isolation between species pairs across lakes offer a continuum of genetic and phenotypic divergence associated with adaptation to distinct ecological niches. To disentangle the complex array of genetically based barriers that locally reduce the effective migration rate between whitefish species pairs, we compared genome‐wide patterns of divergence across five lakes distributed along this divergence continuum. Using restriction site associated DNA (RAD) sequencing, we combined genetic mapping and population genetics approaches to identify genomic regions resistant to introgression and derive empirical measures of the barrier strength as a function of recombination distance. We found that the size of the genomic islands of differentiation was influenced by the joint effects of linkage disequilibrium maintained by selection on many loci, the strength of ecological niche divergence, as well as demographic characteristics unique to each lake. Partial parallelism in divergent genomic regions likely reflected the combined effects of polygenic adaptation from standing variation and independent changes in the genetic architecture of postzygotic isolation. This study illustrates how integrating genetic mapping and population genomics of multiple sympatric species pairs provide a window on the speciation‐with‐gene‐flow mechanism.     

Population genomic analyses from low‐coverage RAD‐Seq data: a case study on the non‐model cucurbit bottle gourd

Restriction site‐associated DNA sequencing (RAD‐Seq), a next‐generation sequencing‐based genome ‘complexity reduction’ protocol, has been useful in population genomics in species with a reference genome. However, the application of this protocol to natural populations of genomically underinvestigated species, particularly under low‐to‐medium sequencing depth, has not been well justified. In this study, a Bayesian method was developed for calling genotypes from an F₂ population of bottle gourd [Lagenaria siceraria (Mol.) Standl.] to construct a high‐density genetic map. Low‐depth genome shotgun sequencing allowed the assembly of scaffolds/contigs comprising approximately 50% of the estimated genome, of which 922 were anchored for identifying syntenic regions between species. RAD‐Seq genotyping of a natural population comprising 80 accessions identified 3226 single nuclear polymorphisms (SNPs), based on which two sub‐gene pools were suggested for association with fruit shape. The two sub‐gene pools were moderately differentiated, as reflected by the Hudson's F_ST value of 0.14, and they represent regions on LG7 with strikingly elevated F_ST values. Seven‐fold reduction in heterozygosity and two times increase in LD (r²) were observed in the same region for the round‐fruited sub‐gene pool. Outlier test suggested the locus LX3405 on LG7 to be a candidate site under selection. Comparative genomic analysis revealed that the cucumber genome region syntenic to the high F_ST island on LG7 harbors an ortholog of the tomato fruit shape gene OVATE. Our results point to a bright future of applying RAD‐Seq to population genomic studies for non‐model species even under low‐to‐medium sequencing efforts. The genomic resources provide valuable information for cucurbit genome research.     

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.     

Canadian polar bear population structure using genome‐wide markers

Predicting the consequences of environmental changes, including human‐mediated climate change on species, requires that we quantify range‐wide patterns of genetic diversity and identify the ecological, environmental, and historical factors that have contributed to it. Here, we generate baseline data on polar bear population structure across most Canadian subpopulations (n = 358) using 13,488 genome‐wide single nucleotide polymorphisms (SNPs) identified with double‐digest restriction site‐associated DNA sequencing (ddRAD). Our ddRAD dataset showed three genetic clusters in the sampled Canadian range, congruent with previous studies based on microsatellites across the same regions; however, due to a lack of sampling in Norwegian Bay, we were unable to confirm the existence of a unique cluster in that subpopulation. These data on the genetic structure of polar bears using SNPs provide a detailed baseline against which future shifts in population structure can be assessed, and opportunities to develop new noninvasive tools for monitoring polar bears across their range.