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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 Axiomarray for an intensively studied pinniped, the Antarctic fur seal (Arctocephalus gazella). SNPs were discovered from a combination of genomic and transcriptomic resources and filteredaccording 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 Bird26 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 ofhomozygosity being non-zero in all individuals. Furthermore, analysis of genomic relatedness coefficients identified previously unknown first-degree relatives and multiple second-degreerelatives 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.

Despite 400–450 million years of independent evolution, a strong phenotypic convergence has occurred between two groups of fish: tunas and lamnid sharks. This convergence is characterized by centralization of red muscle, a distinctive swimming style (stiffened body powered through tail movements) and elevated body temperature (endothermy). Furthermore, both groups demonstrate elevated white muscle metabolic capacities. All these traits are unusual in fish and more likely evolved to support their fast-swimming, pelagic, predatory behavior. Here, we tested the hypothesis that their convergent evolution was driven by selection on a set of metabolic genes. We sequenced white muscle transcriptomes of six tuna, one mackerel, and three shark species, and supplemented this data set with previously published RNA-seq data. Using 26 species in total (including 7,032 tuna genes plus 1,719 shark genes), we constructed phylogenetic trees and carried out maximum-likelihood analyses of gene selection. We inferred several genes relating to metabolism to be under selection. We also found that the same one gene, glycogenin-1, evolved under positive selection independently in tunas and lamnid sharks, providing evidence of convergent selective pressures at gene level possibly underlying shared physiology.

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.

Background All vertebrates initially feed their offspring using yolk reserves. In some live-bearing species these yolk reserves may be supplemented with extra nutrition via a placenta. Sharks belonging to the Carcharhinidae family are all live-bearing, and with the exception of the tiger shark (Galeocerdo cuvier), develop placental connections after exhausting yolk reserves. Phylogenetic relationships suggest the lack of placenta in tiger sharks is due to secondary loss. This represents a dramatic shift in reproductive strategy, and is likely to have left a molecular footprint of positive selection within the genome. Results We sequenced the transcriptome of the tiger shark and eight other live-bearing shark species. From this data we constructed a time-calibrated phylogenetic tree estimating the tiger shark lineage diverged from the placental carcharhinids approximately 94 million years ago. Along the tiger shark lineage, we identified five genes exhibiting a signature of positive selection. Four of these genes have functions likely associated with brain development (YWHAE and ARL6IP5) and sexual reproduction (VAMP4 and TCTEX1D2). Conclusions Our results indicate the loss of placenta in tiger sharks may be associated with subsequent adaptive changes in brain development and sperm production. Electronic supplementary material The online version of this article (doi:10.1186/s12862-016-0696-y) contains supplementary material, which is available to authorized users.

Phylogenetic tree of sharks. Based on analyses of 1,197 genes (1,101,288 bp per species). Species are named along with the orders and families they belong to. ‘Lam.’ refers to Lamniformes order and ‘Tri.’ refers to Triakidae family. The non-placental species are shown in red. Each node is supported with a bootstrap value of 100 %. (PDF 25 kb)