Evaluating hybridization capture with RAD probes as a tool for museum genomics with historical bird specimens

Laboratory techniques for high‐throughput sequencing have enhanced our ability to generate DNA sequence data from millions of natural history specimens collected prior to the molecular era, but remain poorly tested at shallower evolutionary time scales. Hybridization capture using restriction site‐associated DNA probes (hyRAD) is a recently developed method for population genomics with museum specimens. The hyRAD method employs fragments produced in a restriction site‐associated double digestion as the basis for probes that capture orthologous loci in samples of interest. While promising in that it does not require a reference genome, hyRAD has yet to be applied across study systems in independent laboratories. Here, we provide an independent assessment of the effectiveness of hyRAD on both fresh avian tissue and dried tissue from museum specimens up to 140 years old and investigate how variable quantities of input DNA affect sequencing, assembly, and population genetic inference. We present a modified bench protocol and bioinformatics pipeline, including three steps for detection and removal of microbial and mitochondrial DNA contaminants. We confirm that hyRAD is an effective tool for sampling thousands of orthologous SNPs from historic museum specimens to describe phylogeographic patterns. We find that modern DNA performs significantly better than historical DNA better during sequencing but that assembly performance is largely equivalent. We also find that the quantity of input DNA predicts %GC content of assembled contiguous sequences, suggesting PCR bias. We caution against sampling schemes that include taxonomic or geographic autocorrelation across modern and historic samples.     

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.     

The easy road to genome‐wide medium density SNP screening in a non‐model species: development and application of a 10 K SNP‐chip for the house sparrow (Passer domesticus)

With the advent of next generation sequencing, new avenues have opened to study genomics in wild populations of non‐model species. Here, we describe a successful approach to a genome‐wide medium density Single Nucleotide Polymorphism (SNP) panel in a non‐model species, the house sparrow (Passer domesticus), through the development of a 10 K Illumina iSelect HD BeadChip. Genomic DNA and cDNA derived from six individuals were sequenced on a 454 GS FLX system and generated a total of 1.2 million sequences, in which SNPs were detected. As no reference genome exists for the house sparrow, we used the zebra finch (Taeniopygia guttata) reference genome to determine the most likely position of each SNP. The 10 000 SNPs on the SNP‐chip were selected to be distributed evenly across 31 chromosomes, giving on average one SNP per 100 000 bp. The SNP‐chip was screened across 1968 individual house sparrows from four island populations. Of the original 10 000 SNPs, 7413 were found to be variable, and 99% of these SNPs were successfully called in at least 93% of all individuals. We used the SNP‐chip to demonstrate the ability of such genome‐wide marker data to detect population sub‐division, and compared these results to similar analyses using microsatellites. The SNP‐chip will be used to map Quantitative Trait Loci (QTL) for fitness‐related phenotypic traits in natural populations.     

Applying genomic data in wildlife monitoring: Development guidelines for genotyping degraded samples with reduced single nucleotide polymorphism panels

The genomic era has led to an unprecedented increase in the availability of genome‐wide data for a broad range of taxa. Wildlife management strives to make use of these vast resources to enable refined genetic assessments that enhance biodiversity conservation. However, as new genomic platforms emerge, problems remain in adapting the usually complex approaches for genotyping of noninvasively collected wildlife samples. Here, we provide practical guidelines for the standardized development of reduced single nucleotide polymorphism (SNP) panels applicable for microfluidic genotyping of degraded DNA samples, such as faeces or hairs. We demonstrate how microfluidic SNP panels can be optimized to efficiently monitor European wildcat (Felis silvestris S.) populations. We show how panels can be set up in a modular fashion to accommodate informative markers for relevant population genetics questions, such as individual identification, hybridization assessment and the detection of population structure. We discuss various aspects regarding the implementation of reduced SNP panels and provide a framework that will allow both molecular ecologists and practitioners to help bridge the gap between genomics and applied wildlife conservation.     

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.     

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.     

Using a butterflyfish genome as a general tool for RAD‐Seq studies in specialized reef fish

Data from a large‐scale restriction site‐associated DNA sequencing (RAD‐Seq) study of nine butterflyfish species in the Red Sea and Arabian Sea provided a means to test the utility of a recently published draft genome (Chaetodon austriacus) and assess apparent bias in this method of isolating nuclear loci. We here processed double‐digest restriction site‐associated DNA (ddRAD) sequencing data to identify single nucleotide polymorphism (SNP) markers and their associated function with and without our reference genome to see whether it improves the quality of RAD‐Seq. Our analyses indicate (i) a modest gap between the number of nonannotated versus annotated SNPs across all species, (ii) an advantage of using genomic resources for closely related but not distantly related butterflyfish species based on the ability to assign putative gene function to SNPs and (iii) an enrichment of genes among sister butterflyfish taxa related to calcium transmembrane transport and binding. The latter result highlights the potential for this approach to reveal insights into adaptive mechanisms in populations inhabiting challenging coral reef environments such as the Red Sea, Arabian Sea and Arabian Gulf with further study.     

MobiSeq: De novo SNP discovery in model and non‐model species through sequencing the flanking region of transposable elements

In recent years, the availability of reduced representation library (RRL) methods has catalysed an expansion of genome‐scale studies to characterize both model and non‐model organisms. Most of these methods rely on the use of restriction enzymes to obtain DNA sequences at a genome‐wide level. These approaches have been widely used to sequence thousands of markers across individuals for many organisms at a reasonable cost, revolutionizing the field of population genomics. However, there are still some limitations associated with these methods, in particular the high molecular weight DNA required as starting material, the reduced number of common loci among investigated samples, and the short length of the sequenced site‐associated DNA. Here, we present MobiSeq, a RRL protocol exploiting simple laboratory techniques, that generates genomic data based on PCR targeted enrichment of transposable elements and the sequencing of the associated flanking region. We validate its performance across 103 DNA extracts derived from three mammalian species: grey wolf (Canis lupus), red deer complex (Cervus sp.) and brown rat (Rattus norvegicus). MobiSeq enables the sequencing of hundreds of thousands loci across the genome and performs SNP discovery with relatively low rates of clonality. Given the ease and flexibility of MobiSeq protocol, the method has the potential to be implemented for marker discovery and population genomics across a wide range of organisms—enabling the exploration of diverse evolutionary and conservation questions.     

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

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

SNP discovery in nonmodel organisms: strand bias and base‐substitution errors reduce conversion rates

Single nucleotide polymorphisms (SNPs) have become the marker of choice for genetic studies in organisms of conservation, commercial or biological interest. Most SNP discovery projects in nonmodel organisms apply a strategy for identifying putative SNPs based on filtering rules that account for random sequencing errors. Here, we analyse data used to develop 4723 novel SNPs for the commercially important deep‐sea fish, orange roughy (Hoplostethus atlanticus), to assess the impact of not accounting for systematic sequencing errors when filtering identified polymorphisms when discovering SNPs. We used SAMtools to identify polymorphisms in a velvet assembly of genomic DNA sequence data from seven individuals. The resulting set of polymorphisms were filtered to minimize ‘bycatch’—polymorphisms caused by sequencing or assembly error. An Illumina Infinium SNP chip was used to genotype a final set of 7714 polymorphisms across 1734 individuals. Five predictors were examined for their effect on the probability of obtaining an assayable SNP: depth of coverage, number of reads that support a variant, polymorphism type (e.g. A/C), strand‐bias and Illumina SNP probe design score. Our results indicate that filtering out systematic sequencing errors could substantially improve the efficiency of SNP discovery. We show that BLASTX can be used as an efficient tool to identify single‐copy genomic regions in the absence of a reference genome. The results have implications for research aiming to identify assayable SNPs and build SNP genotyping assays for nonmodel organisms.     

Genome‐wide DNA markers to support genetic management for domestication and commercial production in a large rodent,the Ghanaian grasscutter (Thryonomys swinderianus)

Domestication and commercial production of the grasscutter, Thryonomys swinderianus, a large rodent, represents an important opportunity to secure sustainable animal protein for local communities in West Africa. To support production, DNA markers are required for population diversity assessment, pedigree analysis and marker‐assisted selection. This study reports the application of double‐digest RAD sequencing to simultaneously discover and genotype SNP markers in 24 wild and recently domesticated grasscutters. An initial panel of 1209 SNP loci was characterised from a total of more than 21 000 candidate loci containing single SNPs. This genome‐wide resource represents the first application of its type to commercial production of a large rodent for food and advances the use of agricultural genomics in Ghana.     

A fair fight between molecular marker types in a seascape genetics setting

From its inception, population genetics has been nearly as concerned with the genetic data type—to which analyses are brought to bear—as it is with the analysis methods themselves. The field has traversed allozymes, microsatellites, segregating sites in multilocus alignments and, currently, single nucleotide polymorphisms (SNPs) generated by high‐throughput genomic sequencing methods, primarily whole genome sequencing and reduced representation library (RRL) sequencing. As each emerging data type has gained traction, it has been compared to existing methods, based on its relative ability to discern population structural complexity at increasing levels of resolution. However, this is usually done by comparing the gold standard in one data type to the gold standard in the new data type. These gold standards frequently differ in power and in sampling density, both across a genome and throughout a spatial range. In this issue of Molecular Ecology, D’Aloia et al. apply the high‐throughput approach as fully as possible to microsatellites, nuclear loci and SNPs genotyped through an RRL method; this is coupled with a spatially dense sampling scheme. Completing a battery of population genetics analyses across data types (including a series of down‐sampled data sets), the authors find that SNP data are slightly more sensitive to fine‐scale genetic structure, and the results are more resilient to down‐sampling than microsatellites and nonrepetitive nuclear loci. However, their results are far from an unqualified victory for RRL SNP data over all previous data types: the authors note that modest additions to the microsatellites and nuclear loci data sets may provide the necessary analytical power to delineate the fine‐scale genetic structuring identified by SNPs. As always, as the field begins to fully embrace the newest thing, good science reminds us that traditional data types are far from useless, especially when combined with a well‐designed sampling scheme.     

Developing genomic resources for the common bottlenose dolphin (Tursiops truncatus): isolation and characterization of 153 single nucleotide polymorphisms and 53 genotyping assays

Although single nucleotide polymorphisms (SNPs) are commonly used in human genetics, they have only recently been incorporated into genetic studies of non‐model organisms, including cetaceans. SNPs have several advantages over other molecular markers for studies of population genetics: they are quicker and more straightforward to score, cross‐laboratory comparisons of data are less complicated, and they can be used successfully with low‐quality DNA. We screened portions of the genome of one of the most abundant cetaceans in U.S. waters, the common bottlenose dolphin (Tursiops truncatus), and identified 153 SNPs resulting in an overall average of one SNP every 463 base pairs. Custom TaqMan^® Assays were designed for 53 of these SNPs, and their performance was tested by genotyping a set of bottlenose dolphin samples, including some with low‐quality DNA. We found that in 19% of the loci examined, the minor allele frequency (MAF) estimated during initial SNP ascertainment using a DNA pool of 10 individuals differed significantly from the final MAF after genotyping over 100 individuals, suggesting caution when making inferences about MAF values based on small data sets. For two assays, we also characterized the basis for unusual clustering patterns to determine whether their data could still be utilized for further genetic studies. Overall results support the use of these SNPs for accurate analysis of both poor and good‐quality DNA. We report the first SNP markers and genotyping assays for use in population and conservation genetic studies of bottlenose dolphins.     

The future is now: Amplicon sequencing and sequence capture usher in the conservation genomics era

The genomics revolution has initiated a new era of population genetics where genome‐wide data are frequently used to understand complex patterns of population structure and selection. However, the application of genomic tools to inform management and conservation has been somewhat rare outside a few well studied species. Fortunately, two recently developed approaches, amplicon sequencing and sequence capture, have the potential to significantly advance the field of conservation genomics. Here, amplicon sequencing refers to highly multiplexed PCR followed by high‐throughput sequencing (e.g., GTseq), and sequence capture refers to using capture probes to isolate loci from reduced‐representation libraries (e.g., Rapture). Both approaches allow sequencing of thousands of individuals at relatively low costs, do not require any specialized equipment for library preparation, and generate data that can be analyzed without sophisticated computational infrastructure. Here, we discuss the advantages and disadvantages of each method and provide a decision framework for geneticists who are looking to integrate these methods into their research programme. While it will always be important to consider the specifics of the biological question and system, we believe that amplicon sequencing is best suited for projects aiming to genotype <500 loci on many individuals (>1,500) or for species where continued monitoring is anticipated (e.g., long‐term pedigrees). Sequence capture, on the other hand, is best applied to projects including fewer individuals or where >500 loci are required. Both of these techniques should smooth the transition from traditional genetic techniques to genomics, helping to usher in the conservation genomics era.     

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.     

Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions,local adaptation and geographic structure

Recent advances in sequencing allow population‐genomic data to be generated for virtually any species. However, approaches to analyse such data lag behind the ability to generate it, particularly in nonmodel species. Linkage disequilibrium (LD, the nonrandom association of alleles from different loci) is a highly sensitive indicator of many evolutionary phenomena including chromosomal inversions, local adaptation and geographical structure. Here, we present linkage disequilibrium network analysis (LDna), which accesses information on LD shared between multiple loci genomewide. In LD networks, vertices represent loci, and connections between vertices represent the LD between them. We analysed such networks in two test cases: a new restriction‐site‐associated DNA sequence (RAD‐seq) data set for Anopheles baimaii, a Southeast Asian malaria vector; and a well‐characterized single nucleotide polymorphism (SNP) data set from 21 three‐spined stickleback individuals. In each case, we readily identified five distinct LD network clusters (single‐outlier clusters, SOCs), each comprising many loci connected by high LD. In A. baimaii, further population‐genetic analyses supported the inference that each SOC corresponds to a large inversion, consistent with previous cytological studies. For sticklebacks, we inferred that each SOC was associated with a distinct evolutionary phenomenon: two chromosomal inversions, local adaptation, population‐demographic history and geographic structure. LDna is thus a useful exploratory tool, able to give a global overview of LD associated with diverse evolutionary phenomena and identify loci potentially involved. LDna does not require a linkage map or reference genome, so it is applicable to any population‐genomic data set, making it especially valuable for nonmodel species.     

Repurposing population genetics data to discern genomic architecture: A case study of linkage cohort detection in mountain pine beetle (Dendroctonus ponderosae)

Genetic surveys of the population structure of species can be used as resources for exploring their genomic architecture. By adjusting filtering assumptions, genome‐wide single‐nucleotide polymorphism (SNP) datasets can be reused to give new insights into the genetic basis of divergence and speciation without targeted resampling of specimens. Filtering only for missing data and minor allele frequency, we used a combination of principal components analysis and linkage disequilibrium network analysis to distinguish three cohorts of variable SNPs in the mountain pine beetle in western Canada, including one that was sex‐linked and one that was geographically associated. These marker cohorts indicate genomically localized differentiation, and their detection demonstrates an accessible and intuitive method for discovering potential islands of genomic divergence without a priori knowledge of a species’ genomic architecture. Thus, this method has utility for directly addressing the genomic architecture of species and generating new hypotheses for functional research.     

Unlocking the vault: next‐generation museum population genomics

Natural history museum collections provide unique resources for understanding how species respond to environmental change, including the abrupt, anthropogenic climate change of the past century. Ideally, researchers would conduct genome‐scale screening of museum specimens to explore the evolutionary consequences of environmental changes, but to date such analyses have been severely limited by the numerous challenges of working with the highly degraded DNA typical of historic samples. Here, we circumvent these challenges by using custom, multiplexed, exon capture to enrich and sequence ~11 000 exons (~4 Mb) from early 20th‐century museum skins. We used this approach to test for changes in genomic diversity accompanying a climate‐related range retraction in the alpine chipmunks (Tamias alpinus) in the high Sierra Nevada area of California, USA. We developed robust bioinformatic pipelines that rigorously detect and filter out base misincorporations in DNA derived from skins, most of which likely resulted from postmortem damage. Furthermore, to accommodate genotyping uncertainties associated with low‐medium coverage data, we applied a recently developed probabilistic method to call single‐nucleotide polymorphisms and estimate allele frequencies and the joint site frequency spectrum. Our results show increased genetic subdivision following range retraction, but no change in overall genetic diversity at either nonsynonymous or synonymous sites. This case study showcases the advantages of integrating emerging genomic and statistical tools in museum collection‐based population genomic applications. Such technical advances greatly enhance the value of museum collections, even where a pre‐existing reference is lacking and points to a broad range of potential applications in evolutionary and conservation biology.     

Sequence capture phylogenomics of historical ethanol‐preserved museum specimens: Unlocking the rest of the vault

Natural history collections play a crucial role in biodiversity research, and museum specimens are increasingly being incorporated into modern genetics‐based studies. Sequence capture methods have proven incredibly useful for phylogenomics, providing the additional ability to sequence historical museum specimens with highly degraded DNA, which until recently have been deemed less valuable for genetic work. The successful sequencing of ultraconserved elements (UCEs) from historical museum specimens has been demonstrated on multiple tissue types including dried bird skins, formalin‐fixed squamates and pinned insects. However, no study has thoroughly demonstrated this approach for historical ethanol‐preserved museum specimens. Alongside sequencing of “fresh” specimens preserved in >95% ethanol and stored at ?80°C, we used extraction techniques specifically designed for degraded DNA coupled with sequence capture protocols to sequence UCEs from historical museum specimens preserved in 70%–80% ethanol and stored at room temperature, the standard for such ethanol‐preserved museum collections. Across 35 fresh and 15 historical museum samples of the arachnid order Opiliones, an average of 345 UCE loci were included in phylogenomic matrices, with museum samples ranging from six to 495 loci. We successfully demonstrate the inclusion of historical ethanol‐preserved museum specimens in modern sequence capture phylogenomic studies, show a high frequency of variant bases at the species and population levels, and from off‐target reads successfully recover multiple loci traditionally sequenced in multilocus studies including mitochondrial loci and nuclear rRNA loci. The methods detailed in this study will allow researchers to potentially acquire genetic data from millions of ethanol‐preserved museum specimens held in collections worldwide.     

Sampling related individuals within ponds biases estimates of population structure in a pond‐breeding amphibian

Effective conservation and management of pond‐breeding amphibians depends on the accurate estimation of population structure, demographic parameters, and the influence of landscape features on breeding‐site connectivity. Population‐level studies of pond‐breeding amphibians typically sample larval life stages because they are easily captured and can be sampled nondestructively. These studies often identify high levels of relatedness between individuals from the same pond, which can be exacerbated by sampling the larval stage. Yet, the effect of these related individuals on population genetic studies using genomic data is not yet fully understood. Here, we assess the effect of within‐pond relatedness on population and landscape genetic analyses by focusing on the barred tiger salamanders (Ambystoma mavortium) from the Nebraska Sandhills. Utilizing genome‐wide SNPs generated using a double‐digest RADseq approach, we conducted standard population and landscape genetic analyses using datasets with and without siblings. We found that reduced sample sizes influenced parameter estimates more than the inclusion of siblings, but that within‐pond relatedness led to the inference of spurious population structure when analyses depended on allele frequencies. Our landscape genetic analyses also supported different models across datasets depending on the spatial resolution analyzed. We recommend that future studies not only test for relatedness among larval samples but also remove siblings before conducting population or landscape genetic analyses. We also recommend alternative sampling strategies to reduce sampling siblings before sequencing takes place. Biases introduced by unknowingly including siblings can have significant implications for population and landscape genetic analyses, and in turn, for species conservation strategies and outcomes.