A genotyping‐in‐thousands by sequencing panel to inform invasive deer management using noninvasive fecal and hair samples

Studies in ecology, evolution, and conservation often rely on noninvasive samples, making it challenging to generate large amounts of high‐quality genetic data for many elusive and at‐risk species. We developed and optimized a Genotyping‐in‐Thousands by sequencing (GT‐seq) panel using noninvasive samples to inform the management of invasive Sitka black‐tailed deer (Odocoileus hemionus sitkensis) in Haida Gwaii (Canada). We validated our panel using paired high‐quality tissue and noninvasive fecal and hair samples to simultaneously distinguish individuals, identify sex, and reconstruct kinship among deer sampled across the archipelago, then provided a proof‐of‐concept application using field‐collected feces on SGang Gwaay, an island of high ecological and cultural value. Genotyping success across 244 loci was high (90.3%) and comparable to that of high‐quality tissue samples genotyped using restriction‐site associated DNA sequencing (92.4%), while genotyping discordance between paired high‐quality tissue and noninvasive samples was low (0.50%). The panel will be used to inform future invasive species operations in Haida Gwaii by providing individual and population information to inform management. More broadly, our GT‐seq workflow that includes quality control analyses for targeted SNP selection and a modified protocol may be of wider utility for other studies and systems where noninvasive genetic sampling is employed.     

Estimating and accounting for genotyping errors in RAD‐seq experiments

In non‐model organisms, evolutionary questions are frequently addressed using reduced representation sequencing techniques due to their low cost, ease of use, and because they do not require genomic resources such as a reference genome. However, evidence is accumulating that such techniques may be affected by specific biases, questioning the accuracy of obtained genotypes, and as a consequence, their usefulness in evolutionary studies. Here, we introduce three strategies to estimate genotyping error rates from such data: through the comparison to high quality genotypes obtained with a different technique, from individual replicates, or from a population sample when assuming Hardy‐Weinberg equilibrium. Applying these strategies to data obtained with Restriction site Associated DNA sequencing (RAD‐seq), arguably the most popular reduced representation sequencing technique, revealed per‐allele genotyping error rates that were much higher than sequencing error rates, particularly at heterozygous sites that were wrongly inferred as homozygous. As we exemplify through the inference of genome‐wide and local ancestry of well characterized hybrids of two Eurasian poplar (Populus) species, such high error rates may lead to wrong biological conclusions. By properly accounting for these error rates in downstream analyses, either by incorporating genotyping errors directly or by recalibrating genotype likelihoods, we were nevertheless able to use the RAD‐seq data to support biologically meaningful and robust inferences of ancestry among Populus hybrids. Based on these findings, we strongly recommend carefully assessing genotyping error rates in reduced representation sequencing experiments, and to properly account for these in downstream analyses, for instance using the tools presented here.     

Substantial differences in bias between single‐digest and double‐digest RAD‐seq libraries: A case study

The trade‐offs of using single‐digest vs. double‐digest restriction site‐associated DNA sequencing (RAD‐seq) protocols have been widely discussed. However, no direct empirical comparisons of the two methods have been conducted. Here, we sampled a single population of Gulf pipefish (Syngnathus scovelli) and genotyped 444 individuals using RAD‐seq. Sixty individuals were subjected to single‐digest RAD‐seq (sdRAD‐seq), and the remaining 384 individuals were genotyped using a double‐digest RAD‐seq (ddRAD‐seq) protocol. We analysed the resulting Illumina sequencing data and compared the two genotyping methods when reads were analysed either together or separately. Coverage statistics, observed heterozygosity, and allele frequencies differed significantly between the two protocols, as did the results of selection components analysis. We also performed an in silico digestion of the Gulf pipefish genome and modelled five major sources of bias: PCR duplicates, polymorphic restriction sites, shearing bias, asymmetric sampling (i.e., genotyping fewer individuals with sdRAD‐seq than with ddRAD‐seq) and higher major allele frequencies. This combination of approaches allowed us to determine that polymorphic restriction sites, an asymmetric sampling scheme, mean allele frequencies and to some extent PCR duplicates all contribute to different estimates of allele frequencies between samples genotyped using sdRAD‐seq versus ddRAD‐seq. Our finding that sdRAD‐seq and ddRAD‐seq can result in different allele frequencies has implications for comparisons across studies and techniques that endeavour to identify genomewide signatures of evolutionary processes in natural populations.     

Restriction site‐associated DNA sequencing,genotyping error estimation and de novo assembly optimization for population genetic inference

Restriction site‐associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single‐nucleotide polymorphisms. As an empirical example, we use a double‐digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high‐altitude mountains in Mexico.     

MoNSTR‐seq,a restriction site‐associated DNA sequencing technique to characterize Agrobacterium‐mediated transfer‐DNA insertions in Phomopsis longicolla

Phomopsis longicolla (Hobbs) causes Phomopsis seed decay and stem lesions in soybean (Glycine max). In this study, a novel, high‐throughput adaptation of RAD‐seq termed MoNSTR‐seq (Mutation analysis via Next‐generation DNA Sequencing of T‐DNA Regions) was developed to determine the genomic location of T‐DNA insertions in P. longicolla mutants. Insertional mutants were created via Agrobacterium tumefaciens‐mediated transformation, and one mutant, strain PL343, was further investigated due to impaired stem lesion formation. Mutation analysis via Next‐generation DNA Sequencing of T‐DNA Regions, in which DNA libraries are created with two distinct restriction enzymes and customized adapters to simultaneously enrich both T‐DNA insertion borders, was developed to characterize the genomic lesion in strain PL343. MoNSTR‐seq successfully identified a T‐DNA insertion in the predicted promoter region of a gene encoding a cellobiose dehydrogenase (CDH1), and the position of the T‐DNA insertion in strain PL343 was confirmed by Sanger sequencing. Thus, MoNSTR‐seq represents an effective tool for molecular genetics in P. longicolla, and is readily adaptable for use in diverse fungal species.

Significance and Impact of the Study

This study describes MoNSTR‐seq (Mutation analysis via Next‐generation DNA Sequencing of T‐DNA Regions), an adaptation of restriction site‐associated DNA sequencing (RAD‐seq) to identify the position of transfer‐DNA (T‐DNA) insertions in the genome of Phomopsis longicolla, an important pathogen of soybean. The technique enables high‐throughput characterization of mutants generated via Agrobacterium tumefaciens‐mediated transformation (ATMT), thus accelerating gene discovery via forward genetics. This technique represents a significant advancement over existing approaches to characterize T‐DNA insertions in fungal genomes. With minor modifications, this technique could be easily adapted to taxonomically diverse fungal pathogens and additional mutagenesis cassettes.     

Genotyping‐in‐Thousands by sequencing reveals marked population structure in Western Rattlesnakes to inform conservation status

Delineation of units below the species level is critical for prioritizing conservation actions for species at‐risk. Genetic studies play an important role in characterizing patterns of population connectivity and diversity to inform the designation of conservation units, especially for populations that are geographically isolated. The northernmost range margin of Western Rattlesnakes (Crotalus oreganus) occurs in British Columbia, Canada, where it is federally classified as threatened and restricted to five geographic regions. In these areas, Western Rattlesnakes hibernate (den) communally, raising questions about connectivity within and between den complexes. At present, Western Rattlesnake conservation efforts are hindered by a complete lack of information on genetic structure and degree of isolation at multiple scales, from the den to the regional level. To fill this knowledge gap, we used Genotyping‐in‐Thousands by sequencing (GT‐seq) to genotype an optimized panel of 362 single nucleotide polymorphisms (SNPs) from individual samples (n = 461) collected across the snake's distribution in western Canada and neighboring Washington (USA). Hierarchical STRUCTURE analyses found evidence for population structure within and among the five geographic regions in BC, as well as in Washington. Within these regions, 11 genetically distinct complexes of dens were identified, with some regions having multiple complexes. No significant pattern of isolation‐by‐distance and generally low levels of migration were detected among den complexes across regions. Additionally, snakes within dens generally were more related than those among den complexes within a region, indicating limited movement. Overall, our results suggest that the single, recognized designatable unit for Western Rattlesnakes in Canada should be re‐assessed to proactively focus conservation efforts on preserving total genetic variation detected range‐wide. More broadly, our study demonstrates a novel application of GT‐seq for investigating patterns of diversity in wild populations at multiple scales to better inform conservation management.     

Comparing RADseq and microsatellites to infer complex phylogeographic patterns,an empirical perspective in the Crucian carp,Carassius carassius,L.

The conservation of threatened species must be underpinned by phylogeographic knowledge. This need is epitomized by the freshwater fish Carassius carassius, which is in decline across much of its European range. Restriction site‐associated DNA sequencing (RADseq) is increasingly used for such applications; however, RADseq is expensive, and limitations on sample number must be weighed against the benefit of large numbers of markers. This trade‐off has previously been examined using simulation studies; however, empirical comparisons between these markers, especially in a phylogeographic context, are lacking. Here, we compare the results from microsatellites and RADseq for the phylogeography of C. carassius to test whether it is more advantageous to genotype fewer markers (microsatellites) in many samples, or many markers (SNPs) in fewer samples. These data sets, along with data from the mitochondrial cytochrome b gene, agree on broad phylogeographic patterns, showing the existence of two previously unidentified C. carassius lineages in Europe: one found throughout northern and central‐eastern European drainages and a second almost exclusively confined to the Danubian catchment. These lineages have been isolated for approximately 2.15 m years and should be considered separate conservation units. RADseq recovered finer population structure and stronger patterns of IBD than microsatellites, despite including only 17.6% of samples (38% of populations and 52% of samples per population). RADseq was also used along with approximate Bayesian computation to show that the postglacial colonization routes of C. carassius differ from the general patterns of freshwater fish in Europe, likely as a result of their distinctive ecology.     

Double‐digest RAD sequencing using Ion Proton semiconductor platform (ddRADseq‐ion) with nonmodel organisms

Research in evolutionary biology involving nonmodel organisms is rapidly shifting from using traditional molecular markers such as mtDNA and microsatellites to higher throughput SNP genotyping methodologies to address questions in population genetics, phylogenetics and genetic mapping. Restriction site associated DNA sequencing (RAD sequencing or RADseq) has become an established method for SNP genotyping on Illumina sequencing platforms. Here, we developed a protocol and adapters for double‐digest RAD sequencing for Ion Torrent (Life Technologies; Ion Proton, Ion PGM) semiconductor sequencing. We sequenced thirteen genomic libraries of three different nonmodel vertebrate species on Ion Proton with PI chips: Arctic charr Salvelinus alpinus, European whitefish Coregonus lavaretus and common lizard Zootoca vivipara. This resulted in ~962 million single‐end reads overall and a mean of ~74 million reads per library. We filtered the genomic data using Stacks, a bioinformatic tool to process RAD sequencing data. On average, we obtained ~11 000 polymorphic loci per library of 6–30 individuals. We validate our new method by technical and biological replication, by reconstructing phylogenetic relationships, and using a hybrid genetic cross to track genomic variants. Finally, we discuss the differences between using the different sequencing platforms in the context of RAD sequencing, assessing possible advantages and disadvantages. We show that our protocol can be used for Ion semiconductor sequencing platforms for the rapid and cost‐effective generation of variable and reproducible genetic markers.     

Small‐ and large‐scale heterogeneity in genetic variation across the collard flycatcher genome: implications for estimating genetic diversity in nonmodel organisms

Population genetic studies in nonmodel organisms are often hampered by a lack of reference genomes that are essential for whole‐genome resequencing. In the light of this, genotyping methods have been developed to effectively eliminate the need for a reference genome, such as genotyping by sequencing or restriction site‐associated DNA sequencing (RAD‐seq). However, what remains relatively poorly studied is how accurately these methods capture both average and variation in genetic diversity across an organism's genome. In this issue of Molecular Ecology Resources, Dutoit et al. (2016) use whole‐genome resequencing data from the collard flycatcher to assess what factors drive heterogeneity in nucleotide diversity across the genome. Using these data, they then simulate how well different sequencing designs, including RAD sequencing, could capture most of the variation in genetic diversity. They conclude that for evolutionary and conservation‐related studies focused on the estimating genomic diversity, researchers should emphasize the number of loci analysed over the number of individuals sequenced.     

Genotyping‐by‐sequencing for estimating relatedness in nonmodel organisms: Avoiding the trap of precise bias

There has been remarkably little attention to using the high resolution provided by genotyping‐by‐sequencing (i.e., RADseq and similar methods) for assessing relatedness in wildlife populations. A major hurdle is the genotyping error, especially allelic dropout, often found in this type of data that could lead to downward‐biased, yet precise, estimates of relatedness. Here, we assess the applicability of genotyping‐by‐sequencing for relatedness inferences given its relatively high genotyping error rate. Individuals of known relatedness were simulated under genotyping error, allelic dropout and missing data scenarios based on an empirical ddRAD data set, and their true relatedness was compared to that estimated by seven relatedness estimators. We found that an estimator chosen through such analyses can circumvent the influence of genotyping error, with the estimator of Ritland (Genetics Research, 67, 175) shown to be unaffected by allelic dropout and to be the most accurate when there is genotyping error. We also found that the choice of estimator should not rely solely on the strength of correlation between estimated and true relatedness as a strong correlation does not necessarily mean estimates are close to true relatedness. We also demonstrated how even a large SNP data set with genotyping error (allelic dropout or otherwise) or missing data still performs better than a perfectly genotyped microsatellite data set of tens of markers. The simulation‐based approach used here can be easily implemented by others on their own genotyping‐by‐sequencing data sets to confirm the most appropriate and powerful estimator for their data.     

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.     

Random PCR‐based genotyping by sequencing technology GRAS‐Di (genotyping by random amplicon sequencing,direct) reveals genetic structure of mangrove fishes

While various technologies for high‐throughput genotyping have been developed for ecological studies, simple methods tolerant to low‐quality DNA samples are still limited. In this study, we tested the availability of a random PCR‐based genotyping‐by‐sequencing technology, genotyping by random amplicon sequencing, direct (GRAS‐Di). We focused on population genetic analysis of estuarine mangrove fishes, including two resident species, the Amboina cardinalfish (Fibramia amboinensis, Bleeker, 1853) and the Duncker's river garfish (Zenarchopterus dunckeri, Mohr, 1926), and a marine migrant, the blacktail snapper (Lutjanus fulvus, Forster, 1801). Collections were from the Ryukyu Islands, southern Japan. PCR amplicons derived from ~130 individuals were pooled and sequenced in a single lane on a HiSeq2500 platform, and an average of three million reads was obtained per individual. Consensus contigs were assembled for each species and used for genotyping of single nucleotide polymorphisms by mapping trimmed reads onto the contigs. After quality filtering steps, 4,000–9,000 putative single nucleotide polymorphisms were detected for each species. Although DNA fragmentation can diminish genotyping performance when analysed on next‐generation sequencing technology, the effect was small. Genetic differentiation and a clear pattern of isolation‐by‐distance was observed in F. amboinensis and Z. dunckeri by means of principal component analysis, F_ST and the admixture analysis. By contrast, L. fulvus comprised a genetically homogeneous population with directional recent gene flow. These genetic differentiation patterns reflect patterns of estuary use through life history. These results showed the power of GRAS‐Di for fine‐grained genetic analysis using field samples, including mangrove fishes.     

Genotyping‐free parentage assignment using RAD‐seq reads

Parentage assignment is defined as the identification of the true parents of one focal offspring among a list of candidates and has been commonly used in zoological, ecological, and agricultural studies. Although likelihood‐based parentage assignment is the preferred method in most cases, it requires genotyping a predefined set of DNA markers and providing their population allele frequencies. In the present study, we proposed an alternative method of parentage assignment that does not depend on genotype data and prior information of allele frequencies. Our method employs the restriction site‐associated DNA sequencing (RAD‐seq) reads for clustering into the overlapped RAD loci among the compared individuals, following which the likelihood ratio of parentage assignment could be directly calculated using two parameters—the genome heterozygosity and error rate of sequencing reads. This method was validated on one simulated and two real data sets with the accurate assignment of true parents to focal offspring. However, our method could not provide a statistical confidence to conclude that the first ranked candidate is a true parent.     

Using RAD‐seq to recognize sex‐specific markers and sex chromosome systems

Next‐generation sequencing methods have initiated a revolution in molecular ecology and evolution (Tautz et al. 2010 ). Among the most impressive of these sequencing innovations is restriction site‐associated DNA sequencing or RAD‐seq (Baird et al. 2008 ; Andrews et al. 2016 ). RAD‐seq uses the Illumina sequencing platform to sequence fragments of DNA cut by a specific restriction enzyme and can generate tens of thousands of molecular genetic markers for analysis. One of the many uses of RAD‐seq data has been to identify sex‐specific genetic markers, markers found in one sex but not the other (Baxter et al. 2011 ; Gamble & Zarkower 2014 ). Sex‐specific markers are a powerful tool for biologists. At their most basic, they can be used to identify the sex of an individual via PCR. This is useful in cases where a species lacks obvious sexual dimorphism at some or all life history stages. For example, such tests have been important for studying sex differences in life history (Sheldon 1998 ; Mossman & Waser 1999 ), the management and breeding of endangered species (Taberlet et al. 1993 ; Griffiths & Tiwari 1995 ; Robertson et al. 2006 ) and sexing embryonic material (Hacker et al. 1995 ; Smith et al. 1999 ). Furthermore, sex‐specific markers allow recognition of the sex chromosome system in cases where standard cytogenetic methods fail (Charlesworth & Mank 2010 ; Gamble & Zarkower 2014 ). Thus, species with male‐specific markers have male heterogamety (XY) while species with female‐specific markers have female heterogamety (ZW). In this issue, Fowler & Buonaccorsi ( 2016 ) illustrate the ease by which RAD‐seq data can generate sex‐specific genetic markers in rockfish (Sebastes). Moreover, by examining RAD‐seq data from two closely related rockfish species, Sebastes chrysomelas and Sebastes carnatus (Fig.  1 ), Fowler & Buonaccorsi ( 2016 ) uncover shared sex‐specific markers and a conserved sex chromosome system.     

Helping decision making for reliable and cost‐effective 2b‐RAD sequencing and genotyping analyses in non‐model species

High‐throughput sequencing has revolutionized population and conservation genetics. RAD sequencing methods, such as 2b‐RAD, can be used on species lacking a reference genome. However, transferring protocols across taxa can potentially lead to poor results. We tested two different IIB enzymes (AlfI and CspCI) on two species with different genome sizes (the loggerhead turtle Caretta caretta and the sharpsnout seabream Diplodus puntazzo) to build a set of guidelines to improve 2b‐RAD protocols on non‐model organisms while optimising costs. Good results were obtained even with degraded samples, showing the value of 2b‐RAD in studies with poor DNA quality. However, library quality was found to be a critical parameter on the number of reads and loci obtained for genotyping. Resampling analyses with different number of reads per individual showed a trade‐off between number of loci and number of reads per sample. The resulting accumulation curves can be used as a tool to calculate the number of sequences per individual needed to reach a mean depth ≥20 reads to acquire good genotyping results. Finally, we demonstrated that selective‐base ligation does not affect genomic differentiation between individuals, indicating that this technique can be used in species with large genome sizes to adjust the number of loci to the study scope, to reduce sequencing costs and to maintain suitable sequencing depth for a reliable genotyping without compromising the results. Here, we provide a set of guidelines to improve 2b‐RAD protocols on non‐model organisms with different genome sizes, helping decision‐making for a reliable and cost‐effective genotyping.     

Attack of the PCR clones: Rates of clonality have little effect on RAD‐seq genotype calls

Interpretation of high‐throughput sequence data requires an understanding of how decisions made during bioinformatic data processing can influence results. One source of bias that is often cited is PCR clones (or PCR duplicates). PCR clones are common in restriction site‐associated sequencing (RAD‐seq) data sets, which are increasingly being used for molecular ecology. To determine the influence PCR clones and the bioinformatic handling of clones have on genotyping, we evaluate four RAD‐seq data sets. Data sets were compared before and after clones were removed to estimate the number of clones present in RAD‐seq data, quantify how often the presence of clones in a data set causes genotype calls to change compared to when clones were removed, investigate the mechanisms that lead to genotype call changes and test whether clones bias heterozygosity estimates. Our RAD‐seq data sets contained 30%–60% PCR clones, but 95% of RAD‐tags had five or fewer clones. Relatively few genotypes changed once clones were removed (5%–10%), and the vast majority of these changes (98%) were associated with genotypes switching from a called to no‐call state or vice versa. PCR clones had a larger influence on genotype calls in individuals with low read depth but appeared to influence genotype calls at all loci similarly. Removal of PCR clones reduced the number of called genotypes by 2% but had almost no influence on estimates of heterozygosity. As such, while steps should be taken to limit PCR clones during library preparation, PCR clones are likely not a substantial source of bias for most RAD‐seq studies.     

Double‐digest RAD sequencing outperforms microsatellite loci at assigning paternity and estimating relatedness: A proof of concept in a highly promiscuous bird

Information on genetic relationships among individuals is essential to many studies of the behaviour and ecology of wild organisms. Parentage and relatedness assays based on large numbers of single nucleotide polymorphism (SNP) loci hold substantial advantages over the microsatellite markers traditionally used for these purposes. We present a double‐digest restriction site‐associated DNA sequencing (ddRAD‐seq) analysis pipeline that, as such, simultaneously achieves the SNP discovery and genotyping steps and which is optimized to return a statistically powerful set of SNP markers (typically 150–600 after stringent filtering) from large numbers of individuals (up to 240 per run). We explore the trade‐offs inherent in this approach through a set of experiments in a species with a complex social system, the variegated fairy‐wren (Malurus lamberti) and further validate it in a phylogenetically broad set of other bird species. Through direct comparisons with a parallel data set from a robust panel of highly variable microsatellite markers, we show that this ddRAD‐seq approach results in substantially improved power to discriminate among potential relatives and considerably more precise estimates of relatedness coefficients. The pipeline is designed to be universally applicable to all bird species (and with minor modifications to many other taxa), to be cost‐ and time‐efficient, and to be replicable across independent runs such that genotype data from different study periods can be combined and analysed as field samples are accumulated.     

Population structure of Atlantic mackerel inferred from RAD‐seq‐derived SNP markers: effects of sequence clustering parameters and hierarchical SNP selection

Restriction‐site‐associated DNA sequencing (RAD‐seq) and related methods are revolutionizing the field of population genomics in nonmodel organisms as they allow generating an unprecedented number of single nucleotide polymorphisms (SNPs) even when no genomic information is available. Yet, RAD‐seq data analyses rely on assumptions on nature and number of nucleotide variants present in a single locus, the choice of which may lead to an under‐ or overestimated number of SNPs and/or to incorrectly called genotypes. Using the Atlantic mackerel (Scomber scombrus L.) and a close relative, the Atlantic chub mackerel (Scomber colias), as case study, here we explore the sensitivity of population structure inferences to two crucial aspects in RAD‐seq data analysis: the maximum number of mismatches allowed to merge reads into a locus and the relatedness of the individuals used for genotype calling and SNP selection. Our study resolves the population structure of the Atlantic mackerel, but, most importantly, provides insights into the effects of alternative RAD‐seq data analysis strategies on population structure inferences that are directly applicable to other species.