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Climate change is rapidly affecting species distributions across the globe, particularly in the North Atlantic. For highly mobile and elusive cetaceans, the genetic data needed to understand population dynamics are often scarce. Cold-water obligate species such as the white-beaked dolphin (Lagenorhynchus albirostris) face pressures from habitat shifts due to rising sea surface temperatures in addition to other direct anthropogenic threats. Unravelling the genetic connectivity between white-beaked dolphins across their range is needed to understand the extent to which climate change and anthropogenic pressures may impact species-wide genetic diversity and identify ways to protect remaining habitat. We address this by performing a population genomic assessment of white-beaked dolphins using samples from much of their contemporary range. We show that the species displays significant population structure across the North Atlantic at multiple scales. Analysis of contemporary migration rates suggests a remarkably high connectivity between populations in the western North Atlantic, Iceland and the Barents Sea, while two regional populations in the North Sea and adjacent UK and Irish waters are highly differentiated from all other clades. Our results have important implications for the conservation of white-beaked dolphins by providing guidance for the delineation of more appropriate management units and highlighting the risk that local extirpation may have on species-wide genetic diversity. In a broader context, this study highlights the importance of understanding genetic structure of all species threatened with climate change-driven range shifts to assess the risk of loss of species-wide genetic diversity.

In this article, the last two sentences in the Results section under "Contemporary geneflow" were incorrectly given as: Interestingly, although the estimated migration rate remained similar when excluding eastern Scottish samples (m = 3265), the direction of geneflow reversed to a unidirectional influx from western Scotland and Ireland to the North Sea. All other migration rates did not exceed 0.06 migrants per generation and were therefore considered low. But should have been: Interestingly, although the estimated migration rate remained similar when excluding eastern Scottish samples (m = 0.3265), the direction of geneflow reversed to a unidirectional influx from western Scotland and Ireland to the North Sea. All other migration rates did not exceed 0.06 migrants per generation and were therefore considered low. The given value for the estimated migration rate between the two mentioned groups was wrong. In the text it says m = 3265 when it should be m = 0.3265 instead. The original article has been corrected.

In many parts of the world, human-mediated environmental change is depleting biodiversity faster than it can be characterized, while invasive species cause agricultural damage, threaten human health and disrupt native habitats. Consequently, the application of effective approaches for rapid surveillance and identification of biological specimens is increasingly important to inform conservation and biosurveillance efforts. Taxonomic assignments have been greatly advanced using sequence-based applications, such as DNA barcoding, a diagnostic technique that utilizes PCR and DNA sequence analysis of standardized genetic regions. However, in many biodiversity hotspots, endeavors are often hindered by a lack of laboratory infrastructure, funding for biodiversity research and restrictions on the transport of biological samples. A promising development is the advent of low-cost, miniaturized scientific equipment. Such tools can be assembled into functional laboratories to carry out genetic analyses in situ, at local institutions, field stations or classrooms. Here, we outline the steps required to perform amplicon sequencing applications, from DNA isolation to nanopore sequencing and downstream data analysis, all of which can be conducted outside of a conventional laboratory environment using miniaturized scientific equipment, without reliance on Internet connectivity. Depending on sample type, the protocol (from DNA extraction to full bioinformatic analyses) can be completed within 10 h, and with appropriate quality controls can be used for diagnostic identification of samples independent of core genomic facilities that are required for alternative methods.

The dramatic increase in the application of genomic techniques to non-model organisms (NMOs) over the past decade has yielded numerous valuable contributions to evolutionary biology and ecology, many of which would not have been possible with traditional genetic markers. We review this recent progression with a particular focus on genomic studies of marine mammals, a group of taxa that represent key macroevolutionary transitions from terrestrial to marine environments and for which available genomic resources have recently undergone notable rapid growth. Genomic studies of NMOs utilize an expanding range of approaches, including whole genome sequencing, restriction site-associated DNA sequencing, array-based sequencing of single nucleotide polymorphisms and target sequence probes (e.g., exomes), and transcriptome sequencing. These approaches generate different types and quantities of data, and many can be applied with limited or no prior genomic resources, thus overcoming one traditional limitation of research on NMOs. Within marine mammals, such studies have thus far yielded significant contributions to the fields of phylogenomics and comparative genomics, as well as enabled investigations of fitness, demography, and population structure. Here we review the primary options for generating genomic data, introduce several emerging techniques, and discuss the suitability of each approach for different applications in the study of NMOs.

Species identification of non-human biological evidence through DNA nucleotide sequencing is routinely used for forensic genetic analysis to support law enforcement. The gold standard for forensic genetics is conventional Sanger sequencing; however, this is gradually being replaced by high-throughput sequencing (HTS) approaches which can generate millions of individual reads in a single experiment. HTS sequencing, which now dominates molecular biology research, has already been demonstrated for use in a number of forensic genetic analysis applications, including species identification. However, the generation of HTS data to date requires expensive equipment and is cost-effective only when large numbers of samples are analysed simultaneously. The Oxford Nanopore Technologies (ONT) MinION™ is an affordable and small footprint DNA sequencing device with the potential to quickly deliver reliable and cost effective data. However, there has been no formal validation of forensic species identification using high-throughput (deep read) sequence data from the MinION making it currently impractical for many wildlife forensic end-users. Here, we present a MinION deep read sequence data validation study for species identification. First, we tested whether the clustering-based bioinformatics pipeline NGSpeciesID can be used to generate an accurate consensus sequence for species identification. Second, we systematically evaluated the read variation distribution around the generated consensus sequences to understand what confidence we have in the accuracy of the resulting consensus sequence and to determine how to interpret individual sample results. Finally, we investigated the impact of differences between the MinION consensus and Sanger control sequences on correct species identification to understand the ability and accuracy of the MinION consensus sequence to differentiate the true species from the next most similar species. This validation study establishes that ONT MinION s

Replication studies are essential for evaluating the validity of previous research findings. However, it has proven challenging to reproduce the results of ecological and evolutionary studies, partly because of the complexity and lability of many of the phenomena being investigated, but also due to small sample sizes, low statistical power and publication bias. Additionally, replication is often considered too difficult in field settings where many factors are beyond the investigator's control and where spatial and temporal dependencies may be strong. We investigated the feasibility of reproducing original research findings in the field of chemical ecology by performing an exact replication of a previous study of Antarctic fur seals (Arctocephalus gazella). In the original study, skin swabs from 41 mother-offspring pairs from two adjacent breeding colonies on Bird Island, South Georgia, were analyzed using gas chromatography-mass spectrometry. Seals from the two colonies differed significantly in their chemical fingerprints, suggesting that colony membership may be chemically encoded, and mothers were also chemically similar to their pups, hinting at the possible involvement of phenotype matching in mother-offspring recognition. In the current study, we generated and analyzed chemical data from a non-overlapping sample of 50 mother-offspring pairs from the same two colonies 5 years later. The original results were corroborated in both hypothesis testing and estimation contexts, with p-values remaining highly significant and effect sizes, standardized between studies by bootstrapping the chemical data over individuals, being of comparable magnitude. However, exact replication studies are only capable of showing whether a given effect can be replicated in a specific setting. We therefore investigated whether chemical signatures are colony-specific in general by expanding the geographic coverage of our study to include pups from a total of six colonies around Bird Isla

High density single nucleotide polymorphism (SNP) arrays allow large numbers of individuals to be rapidly and cost-effectively genotyped at large numbers of genetic markers. However, despite being widely used in studies of humans and domesticated plants and animals, SNP arrays are lacking for most wild organisms. We developed a custom 85K Affymetrix Axiom array for an intensively studied pinniped, the Antarctic fur seal (Arctocephalus gazella). SNPs were discovered from a combination of genomic and transcriptomic resources and filtered according to strict criteria. Out of a total of 85,359 SNPs tiled on the array, 75,601 (88.6%) successfully converted and were polymorphic in 270 animals from a breeding colony at Bird Island in South Georgia. Evidence was found for inbreeding, with three genomic inbreeding coefficients being strongly intercorrelated and the proportion of the genome in runs of homozygosity being non-zero in all individuals. Furthermore, analysis of genomic relatedness coefficients identified previously unknown first-degree relatives and multiple second-degree relatives among a sample of ostensibly unrelated individuals. Such “cryptic relatedness” within fur seal breeding colonies may increase the likelihood of consanguineous matings and could therefore have implications for understanding fitness variation and mate choice. Finally, we demonstrate the cross-amplification potential of the array in three related pinniped species. Overall, our SNP array will facilitate future studies of Antarctic fur seals and has the potential to serve as a more general resource for the wider pinniped research community.

Fisheries enforcement relies on visual catch identification and quantification at sea or when landed. Silage (fish dissolved in acid) and fish blocks (block frozen fish) are promising methods for on-board processing and storage of low-value catches. We examined the use of nondestructive sampling and two DNA-based methods, quantitative PCR (qPCR) and metabarcoding, to assess species composition and relative abundance in industrial grade experimental silage and fish blocks. We demonstrate the ability to identify and quantify DNA from fish species in both products. qPCR analysis of small silage samples collected over 21 days detected all target control species. DNA from one species (Atlantic wolffish) was consistently overrepresented while, for three species of gadoids (Atlantic cod, haddock and whiting), the DNA content matched input tissue proportions with high accuracy. qPCR and metabarcoding of fish blocks, sampled as run-off water and exterior swabs, provided consistent species detection, with the highest variance observed in quantification from swab samples. Our analysis shows that DNA-based methods have significant potential as a tool for species identification and quantification of complex on-board-processed seafood products and are readily applicable to taxonomically and morphologically similar fish. There is, however, a need for establishing DNA/weight calibration factors for primary fisheries species.

Replication studies are essential for evaluating the validity of previous research findings. However, it has proven challenging to reproduce the results of ecological and evolutionary studies, partly because of the complexity and lability of many of the phenomena being investigated, but also due to small sample sizes, low statistical power and publication bias. Additionally, replication is often considered too difficult in field settings where many factors are beyond the investigator's control and where spatial and temporal dependencies may be strong. We investigated the feasibility of reproducing original research findings in the field of chemical ecology by performing an exact replication of a previous study of Antarctic fur seals (Arctocephalus gazella). In the original study, skin swabs from 41 mother-offspring pairs from two adjacent breeding colonies on Bird Island, South Georgia, were analyzed using gas chromatography-mass spectrometry. Seals from the two colonies differed significantly in their chemical fingerprints, suggesting that colony membership may be chemically encoded, and mothers were also chemically similar to their pups, hinting at the possible involvement of phenotype matching in mother-offspring recognition. In the current study, we generated and analyzed chemical data from a non-overlapping sample of 50 mother-offspring pairs from the same two colonies 5 years later. The original results were corroborated in both hypothesis testing and estimation contexts, with p-values remaining highly significant and effect sizes, standardized between studies by bootstrapping the chemical data over individuals, being of comparable magnitude. However, exact replication studies are only capable of showing whether a given effect can be replicated in a specific setting. We therefore investigated whether chemical signatures are colony-specific in general by expanding the geographic coverage of our study to include pups from a total of six colonies around Bird Isla

High density single nucleotide polymorphism (SNP) arrays allow large numbers of individuals to be rapidly and cost-effectively genotyped at large numbers of genetic markers. However, despite being widely used in studies of humans and domesticated plants and animals, SNP arrays are lacking for most wild organisms. We developed a custom 85K Affymetrix Axiom array for an intensively studied pinniped, the Antarctic fur seal (Arctocephalus gazella). SNPs were discovered from a combination of genomic and transcriptomic resources and filtered according to strict criteria. Out of a total of 85,359 SNPs tiled on the array, 75,601 (88.6%) successfully converted and were polymorphic in 270 animals from a breeding colony at Bird Island in South Georgia. Evidence was found for inbreeding, with three genomic inbreeding coefficients being strongly intercorrelated and the proportion of the genome in runs of homozygosity being non-zero in all individuals. Furthermore, analysis of genomic relatedness coefficients identified previously unknown first-degree relatives and multiple second-degree relatives among a sample of ostensibly unrelated individuals. Such “cryptic relatedness” within fur seal breeding colonies may increase the likelihood of consanguineous matings and could therefore have implications for understanding fitness variation and mate choice. Finally, we demonstrate the cross-amplification potential of the array in three related pinniped species. Overall, our SNP array will facilitate future studies of Antarctic fur seals and has the potential to serve as a more general resource for the wider pinniped research community.

Practical biodiversity conservation relies on delineation of biologically meaningful units. Manta and devil rays (Mobulidae) are threatened worldwide, yet morphological similarities and a succession of recent taxonomic changes impede the development of an effective conservation strategy. Here, we generate genome-wide single nucleotide polymorphism (SNP) data from a geographically and taxonomically representative set of manta and devil ray samples to reconstruct phylogenetic relationships and evaluate species boundaries under the general lineage concept. We show that nominal species units supported by alternative data sources constitute independently evolving lineages, and find robust evidence for a putative new species of manta ray in the Gulf of Mexico. Additionally, we uncover substantial incomplete lineage sorting indicating that rapid speciation together with standing variation in ancestral populations has driven phylogenetic uncertainty within Mobulidae. Finally, we detect cryptic diversity in geographically distinct populations, demonstrating that management below the species level may be warranted in certain species. Overall, our study provides a framework for molecular genetic species delimitation that is relevant to wide-ranging taxa of conservation concern, and highlights the potential for genomic data to support effective management, conservation and law enforcement strategies.

Fisheries enforcement relies on visual catch identification and quantification at sea or when landed. Silage (fish dissolved in acid) and fish blocks (block frozen fish) are promising methods for on-board processing and storage of low-value catches. We examined the use of nondestructive sampling and two DNA-based methods, quantitative PCR (qPCR) and metabarcoding, to assess species composition and relative abundance in industrial grade experimental silage and fish blocks. We demonstrate the ability to identify and quantify DNA from fish species in both products. qPCR analysis of small silage samples collected over 21 days detected all target control species. DNA from one species (Atlantic wolffish) was consistently overrepresented while, for three species of gadoids (Atlantic cod, haddock and whiting), the DNA content matched input tissue proportions with high accuracy. qPCR and metabarcoding of fish blocks, sampled as run-off water and exterior swabs, provided consistent species detection, with the highest variance observed in quantification from swab samples. Our analysis shows that DNA-based methods have significant potential as a tool for species identification and quantification of complex on-board-processed seafood products and are readily applicable to taxonomically and morphologically similar fish. There is, however, a need for establishing DNA/weight calibration factors for primary fisheries species.

Recent advances in high throughput sequencing have transformed the study of wild organisms by facilitating the generation of high quality genome assemblies and dense genetic marker datasets. These resources have the potential to significantly advance our understanding of diverse phenomena at the level of species, populations and individuals, ranging from patterns of synteny through rates of linkage disequilibrium (LD) decay and population structure to individual inbreeding. Consequently, we used PacBio sequencing to refine an existing Antarctic fur seal (Arctocephalus gazella) genome assembly and genotyped 83 individuals from six populations using restriction site associated DNA (RAD) sequencing. The resulting hybrid genome comprised 6,169 scaffolds with an N50 of 6.21 Mb and provided clear evidence for the conservation of large chromosomal segments between the fur seal and dog (Canis lupus familiaris). Focusing on the most extensively sampled population of South Georgia, we found that LD decayed rapidly, reaching the background level by around 400 kb, consistent with other vertebrates but at odds with the notion that fur seals experienced a strong historical bottleneck. We also found evidence for population structuring, with four main Antarctic island groups being resolved. Finally, appreciable variance in individual inbreeding could be detected, reflecting the strong polygyny and site fidelity of the species. Overall, our study contributes important resources for future genomic studies of fur seals and other pinnipeds while also providing a clear example of how high throughput sequencing can generate diverse biological insights at multiple levels of organization.

The genomic revolution has provided researchers with the opportunity to address broadreaching questions in ecology, evolution and conservation with greater power and precision than ever before. It is nowpossible to sequence genomes and produce high-resolution genomic marker datasets for practically any species for which high quality DNA can be collected. There are a vast and expanding number of ways in which to develop genomic resources, but the gold standard is to create a permanent and diverse toolkit, as this is likely to provide the greatest power for addressing outstanding and timely questions long into the future. The Antarctic fur seal (Arctocephalus gazella) is an important polar predator and arguably one of the most intensely monitored pinniped species in the world. During the 18th and 19th century it was the target of large-scale commercial exploitation and despite having rebounded, worsening environmental conditions in the South Atlantic have meant that many fur seal populations are in decline again. Nevertheless, the Antarctic fur seal is yet to benefit from the genomic revolution and as such, many fundamental aspects of its biology remain poorly understood. In my dissertation, I developed a permanent genomic toolkit for the Antarctic fur seal and used this to investigate a broad range of phenomena including inbreeding, population structure and demography. In the first chapters of my thesis, I lay the genomic and methodological foundation for many of the subsequent elements of my PhD. In Chapter 2, I present the first genome assembly for the Antarctic fur seal and use this to explore the genomic characteristics of 144 SNP probe sequences in order to optimize the development of a custom genotyping array. I found that probes mapping uniquely and completely to the fur seal genome were more likely to successfully validate, a pattern that holds up across a variety of species. In Chapter 3, I describe a hybrid transcriptome assembly comprising information from

Recent advances in high throughput sequencing have transformed the study of wild organisms by facilitating the generation of high quality genome assemblies and dense genetic marker datasets. These resources have the potential to significantly advance our understanding of diverse phenomena at the level of species, populations and individuals, ranging from patterns of synteny through rates of linkage disequilibrium (LD) decay and population structure to individual inbreeding. Consequently, we used PacBio sequencing to refine an existing Antarctic fur seal (Arctocephalus gazella) genome assembly and genotyped 83 individuals from six populations using restriction site associated DNA (RAD) sequencing. The resulting hybrid genome comprised 6,169 scaffolds with an N50 of 6.21 Mb and provided clear evidence for the conservation of large chromosomal segments between the fur seal and dog (Canis lupus familiaris). Focusing on the most extensively sampled population of South Georgia, we found that LD decayed rapidly, reaching the background level by around 400 kb, consistent with other vertebrates but at odds with the notion that fur seals experienced a strong historical bottleneck. We also found evidence for population structuring, with four main Antarctic island groups being resolved. Finally, appreciable variance in individual inbreeding could be detected, reflecting the strong polygyny and site fidelity of the species. Overall, our study contributes important resources for future genomic studies of fur seals and other pinnipeds while also providing a clear example of how high throughput sequencing can generate diverse biological insights at multiple levels of organization.

Recent advances in high throughput sequencing have transformed the study of wild organisms by facilitating the generation of high quality genome assemblies and dense genetic marker datasets. These resources have the potential to significantly advance our understanding of diverse phenomena at the level of species, populations and individuals, ranging from patterns of synteny through rates of linkage disequilibrium (LD) decay and population structure to individual inbreeding. Consequently, we used PacBio sequencing to refine an existing Antarctic fur seal (Arctocephalus gazella) genome assembly and genotyped 83 individuals from six populations using restriction site associated DNA (RAD) sequencing. The resulting hybrid genome comprised 6,169 scaffolds with an N50 of 6.21 Mb and provided clear evidence for the conservation of large chromosomal segments between the fur seal and dog (Canis lupus familiaris). Focusing on the most extensively sampled population of South Georgia, we found that LD decayed rapidly, reaching the background level by around 400 kb, consistent with other vertebrates but at odds with the notion that fur seals experienced a strong historical bottleneck. We also found evidence for population structuring, with four main Antarctic island groups being resolved. Finally, appreciable variance in individual inbreeding could be detected, reflecting the strong polygyny and site fidelity of the species. Overall, our study contributes important resources for future genomic studies of fur seals and other pinnipeds while also providing a clear example of how high throughput sequencing can generate diverse biological insights at multiple levels of organization.

The genomic revolution has provided researchers with the opportunity to address broadreaching questions in ecology, evolution and conservation with greater power and precision than ever before. It is nowpossible to sequence genomes and produce high-resolution genomic marker datasets for practically any species for which high quality DNA can be collected. There are a vast and expanding number of ways in which to develop genomic resources, but the gold standard is to create a permanent and diverse toolkit, as this is likely to provide the greatest power for addressing outstanding and timely questions long into the future. The Antarctic fur seal (Arctocephalus gazella) is an important polar predator and arguably one of the most intensely monitored pinniped species in the world. During the 18th and 19th century it was the target of large-scale commercial exploitation and despite having rebounded, worsening environmental conditions in the South Atlantic have meant that many fur seal populations are in decline again. Nevertheless, the Antarctic fur seal is yet to benefit from the genomic revolution and as such, many fundamental aspects of its biology remain poorly understood. In my dissertation, I developed a permanent genomic toolkit for the Antarctic fur seal and used this to investigate a broad range of phenomena including inbreeding, population structure and demography. In the first chapters of my thesis, I lay the genomic and methodological foundation for many of the subsequent elements of my PhD. In Chapter 2, I present the first genome assembly for the Antarctic fur seal and use this to explore the genomic characteristics of 144 SNP probe sequences in order to optimize the development of a custom genotyping array. I found that probes mapping uniquely and completely to the fur seal genome were more likely to successfully validate, a pattern that holds up across a variety of species. In Chapter 3, I describe a hybrid transcriptome assembly comprising information from

Heterozygosity-fitness correlations (HFCs) have been widely used to explore the impact of inbreeding on individual fitness. Initially, most studies used small panels of microsatellites, but more recently with the advent of next-generation sequencing, large SNP datasets are becoming increasingly available and these provide greater power and precision to quantify the impact of inbreeding on fitness. Despite the popularity of HFC studies, effect sizes tend to be rather small. One reason for this may be low variation in inbreeding levels among individuals. Using genetic markers, it is possible to measure variance in inbreeding through the strength of correlation in heterozygosity across marker loci, termed identity disequilibrium (ID). ID can be quantified using the measure g2, which is also a central parameter in HFC theory that can be used within a wider framework to estimate the direct impact of inbreeding on both marker heterozygosity and fitness. However, no software exists to calculate g2 for large SNP datasets nor to implement this framework. inbreedR is an R package that provides functions to calculate g2 based on microsatellite and SNP markers with associated P-values and confidence intervals. Within the framework of HFC theory, inbreedR also estimates the impact of inbreeding on marker heterozygosity and fitness. Finally, inbreedR implements user-friendly simulations to explore the precision and magnitude of estimates based on different numbers of genetic markers. We hope this package will facilitate good practice in the analysis of HFCs and help to deepen our understanding of inbreeding effects in natural populations.

Summary 1.Heterozygosity–fitness correlations (HFCs) have been widely used to explore the impact of inbreeding on individual fitness. Initially, most studies used small panels of microsatellites, but more recently with the advent of next-generation sequencing, large SNP datasets are becoming increasingly available and these provide greater power and precision to quantify the impact of inbreeding on fitness. 2.Despite the popularity of HFC studies, effect sizes tend to be rather small. One reason for this may be low variation in inbreeding levels among individuals. Using genetic markers, it is possible to measure variance in inbreeding through the strength of correlation in heterozygosity across marker loci, termed identity disequilibrium (ID). 3.ID can be quantified using the measure inline image, which is also a central parameter in HFC theory that can be used within a wider framework to estimate the direct impact of inbreeding on both marker heterozygosity and fitness. However, no software exists to calculate inline image for large SNP datasets nor to implement this framework. 4.inbreedR is an R package that provides functions to calculate inline image based on microsatellite and SNP markers with associated P-values and confidence intervals. Within the framework of HFC theory, inbreedR also estimates the impact of inbreeding on marker heterozygosity and fitness. Finally, inbreedR implements user-friendly simulations to explore the precision and magnitude of estimates based on different numbers of genetic markers. We hope this package will facilitate good practice in the analysis of HFCs and help to deepen our understanding of inbreeding effects in natural populations.

The dramatic increase in the application of genomic techniques to non-model organisms (NMOs) over the past decade has yielded numerous valuable contributions to evolutionary biology and ecology, many of which would not have been possible with traditional genetic markers. We review this recent progression with a particular focus on genomic studies of marine mammals, a group of taxa that represent key macroevolutionary transitions from terrestrial to marine environments and for which available genomic resources have recently undergone notable rapid growth. Genomic studies of NMOs utilize an expanding range of approaches, including whole genome sequencing, restriction site-associated DNA sequencing, array-based sequencing of single nucleotide polymorphisms and target sequence probes (e.g., exomes), and transcriptome sequencing. These approaches generate different types and quantities of data, and many can be applied with limited or no prior genomic resources, thus overcoming one traditional limitation of research on NMOs. Within marine mammals, such studies have thus far yielded significant contributions to the fields of phylogenomics and comparative genomics, as well as enabled investigations of fitness, demography, and population structure. Here we review the primary options for generating genomic data, introduce several emerging techniques, and discuss the suitability of each approach for different applications in the study of NMOs.

Background Single nucleotide polymorphism (SNP) discovery is an important goal of many studies. However, the number of ‘putative’ SNPs discovered from a sequence resource may not provide a reliable indication of the number that will successfully validate with a given genotyping technology. For this it may be necessary to account for factors such as the method used for SNP discovery and the type of sequence data from which it originates, suitability of the SNP flanking sequences for probe design, and genomic context. To explore the relative importance of these and other factors, we used Illumina sequencing to augment an existing Roche 454 transcriptome assembly for the Antarctic fur seal (Arctocephalus gazella). We then mapped the raw Illumina reads to the new hybrid transcriptome using BWA and BOWTIE2 before calling SNPs with GATK. The resulting markers were pooled with two existing sets of SNPs called from the original 454 assembly using NEWBLER and SWAP454. Finally, we explored the extent to which SNPs discovered using these four methods overlapped and predicted the corresponding validation outcomes for both Illumina Infinium iSelect HD and Affymetrix Axiom arrays. Results Collating markers across all discovery methods resulted in a global list of 34,718 SNPs. However, concordance between the methods was surprisingly poor, with only 51.0 % of SNPs being discovered by more than one method and 13.5 % being called from both the 454 and Illumina datasets. Using a predictive modeling approach, we could also show that SNPs called from the Illumina data were on average more likely to successfully validate, as were SNPs called by more than one method. Above and beyond this pattern, predicted validation outcomes were also consistently better for Affymetrix Axiom arrays. Conclusions Our results suggest that focusing on SNPs called by more than one method could potentially improve validation outcomes. They also highlight possible differences between alternative genotyping te

Although the genetic basis of color variation has been extensively studied in humans and domestic animals, the genetic polymorphisms responsible for different color morphs remain to be elucidated in many wild vertebrate species. For example, hypopigmentation has been observed in numerous marine mammal species but the underlying mutations have not been identified. A particularly compelling candidate gene for explaining color polymorphism is the melanocortin 1 receptor (MC1R), which plays a key role in the regulation of pigment production. We therefore used Antarctic fur seals (Arctocephalus gazella) as a highly tractable marine mammal system with which to test for an association between nucleotide variation at the MC1R and melanin-based coat color phenotypes. By sequencing 70 wild-type individuals with dark-colored coats and 26 hypopigmented individuals with cream-colored coats, we identified a nonsynonymous mutation that results in the substitution of serine with phenylalanine at an evolutionarily highly conserved structural domain. All of the hypopigmented individuals were homozygous for the allele coding for phenylalanine, consistent with a recessive loss-of-function allele. In order to test for cryptic population structure, which can generate artefactual associations, and to evaluate whether homozygosity at the MC1R could be indicative of low genome-wide heterozygosity, we also genotyped all of the individuals at 50 polymorphic microsatellite loci. We were unable to detect any population structure and also found that wild-type and hypopigmented individuals did not differ significantly in their standardized multilocus heterozygosity. Such a lack of association implies that hypopigmented individuals are unlikely to suffer disproportionately from inbreeding depression, and hence, we have no reason to believe that they are at a selective disadvantage in the wider population.

Summary 1.Heterozygosity–fitness correlations (HFCs) have been widely used to explore the impact of inbreeding on individual fitness. Initially, most studies used small panels of microsatellites, but more recently with the advent of next-generation sequencing, large SNP datasets are becoming increasingly available and these provide greater power and precision to quantify the impact of inbreeding on fitness. 2.Despite the popularity of HFC studies, effect sizes tend to be rather small. One reason for this may be low variation in inbreeding levels among individuals. Using genetic markers, it is possible to measure variance in inbreeding through the strength of correlation in heterozygosity across marker loci, termed identity disequilibrium (ID). 3.ID can be quantified using the measure inline image, which is also a central parameter in HFC theory that can be used within a wider framework to estimate the direct impact of inbreeding on both marker heterozygosity and fitness. However, no software exists to calculate inline image for large SNP datasets nor to implement this framework. 4.inbreedR is an R package that provides functions to calculate inline image based on microsatellite and SNP markers with associated P-values and confidence intervals. Within the framework of HFC theory, inbreedR also estimates the impact of inbreeding on marker heterozygosity and fitness. Finally, inbreedR implements user-friendly simulations to explore the precision and magnitude of estimates based on different numbers of genetic markers. We hope this package will facilitate good practice in the analysis of HFCs and help to deepen our understanding of inbreeding effects in natural populations.

Background Single nucleotide polymorphism (SNP) discovery is an important goal of many studies. However, the number of ‘putative’ SNPs discovered from a sequence resource may not provide a reliable indication of the number that will successfully validate with a given genotyping technology. For this it may be necessary to account for factors such as the method used for SNP discovery and the type of sequence data from which it originates, suitability of the SNP flanking sequences for probe design, and genomic context. To explore the relative importance of these and other factors, we used Illumina sequencing to augment an existing Roche 454 transcriptome assembly for the Antarctic fur seal (Arctocephalus gazella). We then mapped the raw Illumina reads to the new hybrid transcriptome using BWA and BOWTIE2 before calling SNPs with GATK. The resulting markers were pooled with two existing sets of SNPs called from the original 454 assembly using NEWBLER and SWAP454. Finally, we explored the extent to which SNPs discovered using these four methods overlapped and predicted the corresponding validation outcomes for both Illumina Infinium iSelect HD and Affymetrix Axiom arrays. Results Collating markers across all discovery methods resulted in a global list of 34,718 SNPs. However, concordance between the methods was surprisingly poor, with only 51.0 % of SNPs being discovered by more than one method and 13.5 % being called from both the 454 and Illumina datasets. Using a predictive modeling approach, we could also show that SNPs called from the Illumina data were on average more likely to successfully validate, as were SNPs called by more than one method. Above and beyond this pattern, predicted validation outcomes were also consistently better for Affymetrix Axiom arrays. Conclusions Our results suggest that focusing on SNPs called by more than one method could potentially improve validation outcomes. They also highlight possible differences between alternative genotyping te

The dramatic increase in the application of genomic techniques to non-model organisms (NMOs) over the past decade has yielded numerous valuable contributions to evolutionary biology and ecology, many of which would not have been possible with traditional genetic markers. We review this recent progression with a particular focus on genomic studies of marine mammals, a group of taxa that represent key macroevolutionary transitions from terrestrial to marine environments and for which available genomic resources have recently undergone notable rapid growth. Genomic studies of NMOs utilize an expanding range of approaches, including whole genome sequencing, restriction site-associated DNA sequencing, array-based sequencing of single nucleotide polymorphisms and target sequence probes (e.g., exomes), and transcriptome sequencing. These approaches generate different types and quantities of data, and many can be applied with limited or no prior genomic resources, thus overcoming one traditional limitation of research on NMOs. Within marine mammals, such studies have thus far yielded significant contributions to the fields of phylogenomics and comparative genomics, as well as enabled investigations of fitness, demography, and population structure. Here we review the primary options for generating genomic data, introduce several emerging techniques, and discuss the suitability of each approach for different applications in the study of NMOs.

Although the genetic basis of color variation has been extensively studied in humans and domestic animals, the genetic polymorphisms responsible for different color morphs remain to be elucidated in many wild vertebrate species. For example, hypopigmentation has been observed in numerous marine mammal species but the underlying mutations have not been identified. A particularly compelling candidate gene for explaining color polymorphism is the melanocortin 1 receptor (MC1R), which plays a key role in the regulation of pigment production. We therefore used Antarctic fur seals (Arctocephalus gazella) as a highly tractable marine mammal system with which to test for an association between nucleotide variation at the MC1R and melanin-based coat color phenotypes. By sequencing 70 wild-type individuals with dark-colored coats and 26 hypopigmented individuals with cream-colored coats, we identified a nonsynonymous mutation that results in the substitution of serine with phenylalanine at an evolutionarily highly conserved structural domain. All of the hypopigmented individuals were homozygous for the allele coding for phenylalanine, consistent with a recessive loss-of-function allele. In order to test for cryptic population structure, which can generate artefactual associations, and to evaluate whether homozygosity at the MC1R could be indicative of low genome-wide heterozygosity, we also genotyped all of the individuals at 50 polymorphic microsatellite loci. We were unable to detect any population structure and also found that wild-type and hypopigmented individuals did not differ significantly in their standardized multilocus heterozygosity. Such a lack of association implies that hypopigmented individuals are unlikely to suffer disproportionately from inbreeding depression, and hence, we have no reason to believe that they are at a selective disadvantage in the wider population.

The dramatic increase in the application of genomic techniques to non-model organisms (NMOs) over the past decade has yielded numerous valuable contributions to evolutionary biology and ecology, many of which would not have been possible with traditional genetic markers. We review this recent progression with a particular focus on genomic studies of marine mammals, a group of taxa that represent key macroevolutionary transitions from terrestrial to marine environments and for which available genomic resources have recently undergone notable rapid growth. Genomic studies of NMOs utilize an expanding range of approaches, including whole genome sequencing, restriction site-associated DNA sequencing, array-based sequencing of single nucleotide polymorphisms and target sequence probes (e.g., exomes), and transcriptome sequencing. These approaches generate different types and quantities of data, and many can be applied with limited or no prior genomic resources, thus overcoming one traditional limitation of research on NMOs. Within marine mammals, such studies have thus far yielded significant contributions to the fields of phylogenomics and comparative genomics, as well as enabled investigations of fitness, demography, and population structure. Here we review the primary options for generating genomic data, introduce several emerging techniques, and discuss the suitability of each approach for different applications in the study of NMOs.

The dramatic increase in the application of genomic techniques to non-model organisms (NMOs) over the past decade has yielded numerous valuable contributions to evolutionary biology and ecology, many of which would not have been possible with traditional genetic markers. We review this recent progression with a particular focus on genomic studies of marine mammals, a group of taxa that represent key macroevolutionary transitions from terrestrial to marine environments and for which available genomic resources have recently undergone notable rapid growth. Genomic studies of NMOs utilize an expanding range of approaches, including whole genome sequencing, restriction site-associated DNA sequencing, array-based sequencing of single nucleotide polymorphisms and target sequence probes (e.g., exomes), and transcriptome sequencing. These approaches generate different types and quantities of data, and many can be applied with limited or no prior genomic resources, thus overcoming one traditional limitation of research on NMOs. Within marine mammals, such studies have thus far yielded significant contributions to the fields of phylogenomics and comparative genomics, as well as enabled investigations of fitness, demography, and population structure. Here we review the primary options for generating genomic data, introduce several emerging techniques, and discuss the suitability of each approach for different applications in the study of NMOs.

The dramatic increase in the application of genomic techniques to non-model organisms (NMOs) over the past decade has yielded numerous valuable contributions to evolutionary biology and ecology, many of which would not have been possible with traditional genetic markers. We review this recent progression with a particular focus on genomic studies of marine mammals, a group of taxa that represent key macroevolutionary transitions from terrestrial to marine environments and for which available genomic resources have recently undergone notable rapid growth. Genomic studies of NMOs utilize an expanding range of approaches, including whole genome sequencing, restriction site-associated DNA sequencing, array-based sequencing of single nucleotide polymorphisms and target sequence probes (e.g., exomes), and transcriptome sequencing. These approaches generate different types and quantities of data, and many can be applied with limited or no prior genomic resources, thus overcoming one traditional limitation of research on NMOs. Within marine mammals, such studies have thus far yielded significant contributions to the fields of phylogenomics and comparative genomics, as well as enabled investigations of fitness, demography, and population structure. Here we review the primary options for generating genomic data, introduce several emerging techniques, and discuss the suitability of each approach for different applications in the study of NMOs.