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The life aquatic: advances in marine vertebrate genomics Joanna L. Kelley1, Anthony P. Brown1, Nina Overgaard Therkildsen2 and Andrew D. Foote3

Abstract | The ocean is hypothesized to be where life on earth originated, and subsequent evolutionary transitions between marine and terrestrial environments have been key events in the origin of contemporary biodiversity. Here, we review how comparative genomic approaches are an increasingly important aspect of understanding evolutionary processes, such as physiological and morphological adaptation to the diverse habitats within the marine environment. In addition, we highlight how population genomics has provided unprecedented resolution for population structuring, speciation and adaptation in marine environments, which can have a low cost of dispersal and few physical barriers to gene flow, and can thus support large populations. Building upon this work, we outline the applications of genomics tools to conservation and their relevance to assessing the wide-ranging impact of fisheries and climate change on marine species. Estuarine An environment that is situated in the transition zone where the ocean meets rivers. One special challenge in this environment is that salt water from the ocean mixes with fresh water from a river, making this a unique environment in terms of salinity.

School of Biological Sciences, Washington State University, PO Box 644236, Pullman, Washington 99164, USA. 2 Department of Natural Resources, Cornell University, 208 Fernow Hall, Ithaca, New York 14853, USA. 3 Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, Bern CH‑3012, Switzerland. 1

Correspondence to A.D.F. [email protected] doi:10.1038/nrg.2016.66 Published online 4 Jul 2016

The ocean comprises 70% of the planet and contains diverse habitats ranging from the estuarine and coastal to the abyssal (FIG. 1). Life on earth is hypothesized to have originated in the oceans1,2, and evolutionary transitions between marine and terrestrial environments have been essential to the origin of contemporary biodiversity. An estimated 2.2 million eukaryotic species, more than one-quarter of the global total, are marine3. However, the breadth of marine life has been largely understudied at the genomic level. Marine habitats are rapidly changing owing to anthropogenic forces, the consequences of which are unknown. Marine carnivores are, on average, at higher trophic levels than terrestrial carnivores, owing to the complexity of marine food webs4. Moreover, marine vertebrates are a major source of protein for human populations and are an especially important source of protein for coastal communities; for example, in 2010, fish comprised ~16.7% of the animal protein consumed worldwide5. Overfishing, the continuation of whaling practices, bycatch mortality and habitat loss all contribute to the rapidly changing population dynamics of marine vertebrates. It is therefore imperative to understand these species before additional large-scale population declines occur. Progress in marine genomics has lagged behind genomic studies on terrestrial species, potentially owing to the paucity of available reference genomes for marine species in relation to terrestrial species (FIG. 2). For example, a search of the Ensembl genome browser identified that the number of marine species for which

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genomes have been sequenced only reached double figures in 2015, almost a decade after genome sequences for terrestrial species reached such a total (see FIG. 2 for key species). The growing number of genomic resources available for marine species has facilitated genomic investigations in a broad array of marine biota to answer questions about the processes of both macroevolution and microevolution. Emerging genomic investigations have highlighted key themes and over-arching questions that are broadly relevant to marine vertebrates. Comparative genomic studies between sister marine and terrestrial s pecies have provided insights into candidate functional genomic changes underpinning adaptation to the locomotory, sensory, thermal, osmoregulatory and pathogenic challenges associated with life in the sea6–9. At the population level, novel genomic approaches are emer ging that can tease apart the complexity of the confounding effects of population structuring, large effective population size and high connectivity on population-level genetic inference10. Although not unique to (or ubiqui tous in) marine taxa, the low cost of movement and the few physical barriers to geographical dispersal in the marine environment 11,12 mean that these genomic tools are more broadly applicable to marine than terrestrial taxa. Moreover, advances in genome technology now facilitate genome assembly for comparative and population genomics (BOX 1). Given these recent advances, it is therefore timely to review the progress made in the field of marine genomics and to highlight how genomics approaches can benefit future studies: VOLUME 17 | SEPTEMBER 2016 | 523

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Abyssal Coastal An environment that is found near a shoreline and is shallower than most other marine environments; the substrates of the coast can vary considerably (sandy, rocky and so on).

Abyssal An environment that is found in the deepest parts of the ocean. There is very little light and primary production, which makes it difficult for large predators to survive.

Macroevolution Evolutionary patterns at or above the species level.

Microevolution Evolutionary patterns at the population or subpopulation level.

Adaptation The process by which populations become better at reproducing and surviving within a particular environment; this is a population-level process that typically involves changes in allele frequencies.

Effective population size The number of breeding individuals within a population that contribute offspring to the next generation.

Clines Gradients of environmental differences.

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Figure 1 | Vast diversity in the marine environment. Marine habitats range from estuarine (at sea level at the transition zone between the rivers and ocean) to abyssal, which can be over 10,000 metres below sea level at their deepest. Because Nature Reviews | Genetics the ocean is a three-dimensional environment, perhaps analogous to mountain ranges in terrestrial ecosystems, adaptation can also be driven by vertical and horizontal spatial clines, and ecosystems range from coastal to open sea zones. Light levels affect primary productivity. The range of species that inhabit different marine zones are very different and face distinct challenges, including — but not limited to — varying salinity, light and pressure due to depth. For example, rockfishes of the genus Sebastes have radiated to inhabit a range of depths113, and within some species (for example, the beaked redfish, S. mentella, in the North Atlantic) these populations have diverged into shallow (250–500 m) and deep (550–800 m) ecotypes114. The shifts in light levels that occur with increasing depth are also associated with repeated independent parallel occurrence of the same putatively functional amino acid replacements in the rhodopsin (RHO) gene, at the interspecific level among different Sebastes species113 and at the intraspecific level within S. mentella115. Rhodopsin is a photoreceptor that is required for image-forming vision at low light intensity, and differently charged amino acid residues in the rhodopsin protein are expected to result in slightly different light absorbance by the photoreceptor cells.

for example, in the fields of conservation and management of marine vertebrates. In this Review, we define genomics as the study of the structure, function and patterns of variation in genomes or large-scale sequencing data that allow genome-wide inference of evolutionary processes. First, we focus on how comparative genomics of single representative genome assemblies for key marine species has provided new insights into macroevolutionary processes, including the transition from land to sea. Then we highlight how challenges faced by biologists working with marine populations can be addressed with emerging population genomic theory, methods and high-resolution genomic data sets. We finish by discussing resource management and conservation applications of genomics for marine populations and species.

Transitions between land and sea. A key focus of several recent comparative genomics studies on single genomes of marine species has been the genomic underpinning


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Insights from comparative genomics The recent increase in de novo genome assemblies of marine vertebrates highlighted above has provided new opportunities for the inference of functional adaptation to the marine environment and the different ecosystems within the oceans. Comparative genomics identifies differences in genome sequences (for example, in regulatory regions and protein-coding genes) and structural variation (for example, deletions, insertions, copy- number variations and inversions) between a s ingle representative genome of the species of interest and a database of existing genomic data.

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Figure 2 | Genome assemblies through the years. The accumulation of marine and terrestrial genomes assembled Nature Reviews | Genetics from 1996 to 2015 are shown, highlighting the dearth of reference genomes for marine species relative to terrestrial species. Genomes assembled from 1996 to 2014 include organisms found in the Ensembl genome browser (as of September 2015). Genomes assembled in 2015 reflect the results from a Web of Science literature search (as of April 2016).

Cetaceans A group that encompasses the fully aquatic marine mammals (including whales, dolphins and porpoises). The closest living terrestrial relative is the hippopotamus.

Pinniped An organism that belongs to the group Pinnepedia, which encompasses all types of seals (including walruses, sea lions and fur seals). The closest living terrestrial relatives are bears.

Sirenian An organism that belongs to the order Sirenia, which includes herbivorous marine mammals (such as dugongs and manatees). The closest living terrestrial relatives are elephants.

to the life aquatic — as compared with life on land. One hypothesis for the origin of life on earth is that it started in the submarine hydrothermal vents of the deep oceans1 and then diversified within the oceans1,2. This was followed by subsequent evolutionary transitions from the marine to the terrestrial environment 13 (and vice versa)14,15 (FIG. 3a), and there are now genomic data for taxa from either side of these transitions. Organisms undergoing evolutionary transitions between terrestrial and marine environments face many challenges associated with the different physical and biological properties of the two environments. The anaerobic, locomotory, pathogenic, salinity, sensory and thermal challenges of inhabiting the marine environment place intense selection pressure on the genomes of colonizing species13,16. The signature of this selection is observed in the shared phenotypic adaptations that have independently arisen through convergent evolution in highly divergent taxa; for example, fin-like limbs adapted for swimming have evolved independently in separate marine mammal lineages, which themselves have emerged from different terrestrial tetrapod ancestors17,18 (FIG. 3a,b). Such independent examples of adaptation to the marine environment provide an opportunity to study convergent evolution at both the phenotypic and the genomic level. Several mammalian species, from different (primarily terrestrial) clades, have recolonized the marine environment. Fossil evidence suggests there have been



at least seven recolonizations of the marine realm15. The recently sequenced genomes of cetaceans (whales and dolphins)6–9, a pinniped (the walrus, Odobenus rosmarus)7 and a sirenian (the Florida manatee, Trichechus manatus latirostris)7 highlight the genomic underpinning of secondary colonization of the marine environment. Conversely, comparative genomics of the African coelacanth, Latimeria chalumnae (a lobe-finned fish), have provided insights into the genomic changes that occurred in vertebrates during the transition from the marine to the terrestrial environment 13. Strikingly simi lar functional categories of protein-coding genes and regulatory regions — associated with the immune system, nitrogen excretion, limb formation and sensory adaptation — have undergone rapid evolution along the phylogenetic lineages to marine mammals, compared with their respective terrestrial ancestors16, and along the lineage to the tetrapods from the shared coelacanth– tetrapod ancestor 13. For example, the most enriched gene ontology categories for inferred regulatory elements that originated in tetrapods after their divergence from the coelacanth lineage were those associated with the sense of airborne smells13,19. By contrast, the gene family involved in olfactory receptor activity was the most decreased gene orthologue cluster in the genome of the Yangtze River dolphin, Lipotes vexillifer (known as the Baiji)9, and olfactory and taste receptors were under-represented in the genome of the minke whale, VOLUME 17 | SEPTEMBER 2016 | 525

REVIEWS Box 1 | Genomics tools and techniques for marine genomics De novo genome assembly Logistical difficulties in obtaining high-quality tissue samples from organisms in habitats with limited accessibility are likely to have contributed to the relatively slow pace at which genome data have been generated for marine species compared with terrestrial species. High-quality de novo genome assemblies require large amounts of high-molecular-weight DNA. New long-read technologies and long-insert library preparation protocols that require lower DNA input both facilitate and improve contiguity of de novo genome assemblies and enable the generation of genome-scale data from marine organisms. However, computational approaches lag behind improvements in molecular techniques and numerous computational challenges remain for the de novo assembly of genomes95. Genome assembly is also hindered by the higher level of polymorphisms found in some marine vertebrate species, especially fish, relative to terrestrial vertebrate species, by the fact that many marine organisms cannot be kept in captivity to create individuals with lower levels of heterozygosity and by the occurrence of the whole-genome duplication in teleosts31. Population genomics The recent increase in the number of reference genome assemblies means that there are more genomes available for mapping, which increases the potential for using genomics approaches to answer questions in marine biology. These approaches include whole-genome, reduced-representation96 and transcriptome sequencing. Reducedrepresentation techniques, which involve sequencing the same fraction of the genome among individuals, are used to assess population-level processes by surveying many markers at a fraction of the cost of whole-genome resequencing. Transcriptome studies, which quantify patterns of gene expression, allow questions to be answered regarding transcriptional responses to the environment.

Pseudogenized The process by which a functional gene becomes dysfunctional (a pseudogene) owing to sequence alterations such as premature stop codons. Pseudogenization during evolution often results in one species lineage harbouring the defective gene, whereas other species retain the functional homologue.

Otolith A structure in the inner ear that helps marine vertebrates with balance and sound detection.

Pleiotropic A phenomenon in which one gene has an effect on several, often seemingly unrelated, traits.

Benthic The zone at the bottom of a body of water.

Euryhaline Able to tolerate a wide range of salinity.

Synteny The preserved order of genes on chromosomes of related species.

Balaenoptera acutorostrata, in relation to the genomes of terrestrial mammals8. Most taste receptors have been pseudogenized in cetaceans owing to multiple insertions and deletions that disrupt the open reading frame. The only exception is members of the epithelial sodium channel (ENaC) protein complex, which are thought to have a crucial role in the perception of salt taste and are therefore potentially important in sodium ion reabsorption and osmoregulation20,21. Similarly, the gene SMPX (small muscle protein, X-linked), which has a role in inner ear development 22, was inferred to be evolving under positive selection along the branches to the cetaceans, pinnipeds and sirenians (from their respective terrestrial ancestors)7. Remodelling of the inner ear is an important macroevolutionary process of morphological change during transitions between environments. For example, a gene that is essential for otolith formation in the zebrafish, otomp (which encodes otolith matrix protein), has been lost in tetrapods13. These findings indicate that similar pathways underlie adaptation during transitions (in v ertebrates) between terrestrial and marine environments. Morphological adaptation and homeobox genes. Genomic data have increased our understanding of the molecular basis of morphological adaptation in marine vertebrates. Surprisingly, the homeobox (HOX) genes, which are known to have a role in the developmental stages of the body plan and limb formation23,24, remain largely conserved between the coelacanth and the tetrap ods, as well as in comparisons of marine and terrestrial mammals7–9. However, candidate regulatory elements that are absent in teleosts are shared between the coelacanth and the tetrapods19, including a known

Adaptation to diverse marine habitats. In addition to transitions between sea and land, marine organisms have undergone evolutionary adaptations to occupy the vast range of ecological niches within the marine environment (FIG. 1). Each habitat has its own ecological and physiological challenges — for example, extreme pressures associated with living in the deep ocean and b enthic habitat 28, or the variation in salinity between estuaries and the open sea29 — and the recent characterization of the genomes of marine organisms has shed new light on the molecular basis of adaptation to these diverse marine ecosystems. The salinity gradient found in some of the major marginal seas drives genetic adaptation30. Generation of the high-quality genome assembly of a euryhaline species, the European sea bass Dicentrarchus labrax, and its subsequent comparison with the genomes of teleost fish that have a more narrow range of tolerance to salinity (stenohaline species), has revealed the expansion of gene families associated with ion and water regulation, implying that they have a role in developing tolerance to rapid changes in salinity 29. Comparison of genome synteny among teleosts, tetrapods and the coelacanth indicates that the retention of these gene families in the European sea bass29 (and their loss in other teleosts) followed the whole-genome duplication event that took place in the common ancestor of all extant teleosts31,32. Within the marine environment, temperatures vary from the warm, shallow waters of tropical regions to the freezing polar waters where winter temperatures hover around –1.9 °C. The recently sequenced genome of the Atlantic cod, Gadus morhua, has shed light on genomic



cis-regulatory region proximal to the HoxD cluster 13. Expression of the coelacanth HoxD cis-regulatory region in a transgenic mouse resulted in the expression of a reporter gene in forming limb buds, strongly indicating that this developmental enhancer region had a role in lobe-fin formation that may have been co‑opted as a distal limb enhancer in tetrapods13 (FIG. 3c). Similarly, polyalanine-repeat tracts encoded in the cetacean HoxD13 gene sequence align with an insertion of seven alanine residues that is found in humans and mice with synpolydactyly (the production and fusion of supernumerary digits)25 (FIG. 3d). These results suggest that the HoxD cluster has a role in the evolution of finlike forelimbs in at least some marine mammals during secondary colonization of the marine environment 16. These findings also support predictions that morphological traits are more likely to evolve through less- constrained cis-regulatory mutations due to the higher rate of pleiotropic effects of mutations in protein-coding sequences, and because of the many morphological developmental genes that are central to gene regulatory networks (further increasing the probability of pleio tropy)26,27. The recent release of single de novo genome assemblies of marine species has therefore provided valuable insights into the genomic underpinning of key adaptations associated with the morphological and physiological t ransformations that are widely found in marine vertebrates.

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TCCGGACGAGCGGCAGCGGCGGCGGCGGCGGCGGCAGCGGCAGCGGCGGCGGCGGCGGCGGCCTCGGGCTTC S G R A A A A A A A A A A A A A A A A A A S G F TCTGGGCGCGCTGCGGCCGCGGCGGCGGCAGCGGCC---------GCGGCCGCGGCGGCGGCCTCAGGCTTC S G R A A A A A A A A A A A A A A A S G F TCCGGACGCGCGGCGGCGGCGGCCGCAGCAGCGGCG---------GCGGCAGCGGCGGCAGCATCCAGCTTC S G R A A A A A A A A A A A A A A A S S F TCGGGGCGGGCGGCGGCGGCGGCAGCGGCGGCTGCG---------GCGGCGGCAGCGGCAGCCTCCGGCTTT S G R A A A A A A A A A A A A A A A S G F

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TCGGGGCGGGCGGCGGCGGCGGCAGCGGCGGCTGCGGCGGCGGCGGCGGCGGCTGCGGCGGCGGCAGCGGCAGCCTCCGGCTTT 22 S G R A A A A A A A A A A A A A A A A A A A A A A S G F TCCGGACGCGCGGCGGCGGCGGCCGCAGCAGCGGCGGCGGCGGCCGCAGCAGCGGCGGCGGCAGCGGCGGCAGCATCCAGCTTC 22 S G R A A A A A A A A A A A A A A A A A A A A A A S S F

Figure 3 | Genomic insights into macroevolutionary transitions. a | A simplified phylogeny highlighting the relationships among key taxa for which new genomic data have provided insights into the molecular underpinning of transitions between the terrestrial and marine environment. The change from blue to brown coloured branches indicates a transition from the sea to the land, and a change from brown to blue indicates a transition from land to sea. b | Transformations occurred from the bony ray-fins of the teleost fish (such as the zebrafish) to the lobe-fin of the coelacanth, which then evolved into the forelimbs of the tetrapods following the colonization of land; however, they subsequently reverted to a more fin-like structure in marine mammals (such as whales) upon secondary colonization of the oceans. Such transitions demonstrate that morphological adaptations to the marine environment have been recurrent, and we can now investigate these adaptations at the genomic level. The colours indicate homologous structures. c | Sequence homology of a limb regulatory enhancer found upstream of the homeobox D (HoxD) locus using the mouse (Mus musculus) genome as a reference. The alignment highlights regions of homology (peaks indicate the percentage of sequence homology) between



the coelacanth and each of the tetrapods indicated; these homologies are not shared with the teleost fish, suggesting that these sequences were derived in the lobe-finned fish. A transgenic assay that used the coelacanth Nature Reviews | Genetics enhancer region in a mouse resulted in the expression of a reporter gene in the developing limb bud (lower panel), suggesting a role for the coelacanth sequence in this region during distal limb formation. d | The alignment of polyalanine repeat tracts encoded by the HoxD13 gene highlights the additional polyalanine repeats in the minke whale (Balaenoptera acutorostrata) as well as in alleles isolated from both a human (Homo sapiens) and a mouse (M. musculus) exhibiting the morphological defect synpolydactyly (identified as ‘mutant’ in the figure). This suggests that the HoxD locus also had a role in fin evolution in the secondary colonization of the oceans by cetaceans. Part a is adapted from REFS 7,13, Nature Publishing Group. Part b is adapted with permission from REF. 116, Elsevier. Part c is adapted from REF. 13, Nature Publishing Group. Part d is adapted from Wang, Z. et al. Adaptive evolution of 5ʹHoxD genes in the origin and diversification of the cetacean flipper. Mol. Biol. Evol. (2009) 26(3), 613–622, by permission of Oxford University Press.

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REVIEWS Box 2 | Marine microbiomes The marine environment poses unique challenges that affect not only vertebrates but also the microbes that are associated with them. It has been argued that genomic analyses are incomplete if they do not account for the interactions between host genomes and the genomes of the associated microorganisms: together, these genomes form the ‘hologenome’ (REF. 94). Although there are still major gaps in our knowledge of how microorganisms interact with and affect marine vertebrates, recent studies on the microbiota from marine mammals have improved our understanding of the diversity of microorganisms found in larger marine species. Specifically, it has been shown that there are significant differences in bacterial communities in marine mammals compared with those found in terrestrial mammals97,98, which indicates that microorganisms may be important during the transition from land to sea and vice versa. Despite this land-versus-sea dichotomy, there are still significant differences in microbiota found in marine mammals, exemplified by the finding that dolphins and sea lions that have highly similar diets and that were caught in the same area (San Diego Bay, California, USA) harboured substantially different microbial communities98. This discovery suggests that marine mammal microbiomes are, to some degree, host-specific. This notion is also supported by the unique gut microbiome of baleen whales: baleen whales have a carnivorous diet, yet their gut microbiome is overall more similar to terrestrial herbivores than to terrestrial carnivores99. However, in genes associated with certain functional pathways (including essential amino acid synthesis and protein catabolism) the baleen whale microbiome parallels terrestrial carnivores more closely than terrestrial herbivores99. These studies indicate that various factors, including diet, evolutionary history and environmental variables, influence the microbial communities found in marine organisms. Future studies will probably focus not only on the differences between marine and terrestrial microbiota, but also on how these unique communities of microorganisms are affecting their marine hosts.

Panmixia Random mating within a population.

Population structure Differences in allele frequencies among subpopulations within a larger population, possibly due to different ancestry, inbreeding and so on.

Allozyme Allelic variants of proteins detected by protein electrophoresis.

Standing genetic variation Allelic variation that is currently segregating within a species, as opposed to alleles that arise through new mutations.

adaptation to thermal variation within an ocean basin33. Star et al.33 examined the haemoglobin gene cluster and found a 73 bp insertion–deletion polymorphism within an intergenic promoter region located between the α1- and β1-globin genes, in linkage with two amino acid substitutions in the β1 gene. The 73 bp insertion was experimentally shown to significantly increase the transcriptional activity of the allele that confers lower oxygen affinity at higher temperatures33. Moreover, in relation to cold temperature, although antifreeze glycoproteins have been well characterized and studied before the availability of genome assemblies 34, the de novo genome assembly of the Antarctic bullhead notothen, Notothenia coriiceps, also revealed that the evolution of haemoglobin is critical for survival in cold temperatures35. Thus, these genome assemblies illustrate how complex interactions among environmental vari ables, regulatory regions and protein-coding sequences can facilitate adaptation to the differing environments within the oceans. More broadly, the examples discussed above demonstrate the power of comparative genomics to infer the differential expansion, loss and retention of genes and gene families during the evolutionary history of major taxonomic groups. In particular, comparative genomics of marine vertebrates have highlighted structural changes associated with adaptation to the marine environment and the different habitats within the oceans. It is important to recognize that genomic changes associated with environmental adaptation are not only occurring in the vertebrate genomes, they are also occurring in their microbiomes (BOX 2).

Adaptation to divergent habitats. Owing to their high genetic diversity, large oceanic populations can retain large amounts of potentially adaptive standing genetic variation. The large effective population sizes found in many marine populations allow beneficial alleles with relatively weak selection coefficients to increase in frequency 54. However, high gene flow is expected to constrain the segregation of both neutral and adaptive alleles, which limits the opportunities for local adaptation and speciation between populations in divergent habitats. Divergent taxon pairs of marine and freshwater threespine stickleback, Gasterosteus aculeatus, are an important system for the study of ecological speci ation55,56. The marine form spends most of its adult life in the sea but returns to freshwater to breed, whereas



Insights from population genomics The low energetic cost of movement in water (compared with movement on land)11,12,36 along with the relative absence of geographical barriers to dispersal across oceans37,38 facilitate long-distance (including inter-hemispheric and inter-oceanic) movement in many marine species39–42. This high dispersal potential can result in panmixia or high connectivity between subpopulations, which results in limited or weak p opulation structure and large effective population sizes 38,43–46. Consistent with this expectation, previous studies based on small numbers of traditional markers, such as microsatellites and mitochondrial DNA, often failed to find structure in marine populations of fish47,48, whales49 and dolphins50 even across large spatial scales. However, a rapidly growing body of population genomic studies are making it increasingly clear that population divergence can occur over relatively small temporal and geographical scales in marine organisms. This is either because behaviour or local oceanographical features limit dispersal or because ecological variables, rather than physical obstruction to movement, may become barriers to gene flow and drive local adaptation. Genome-wide analyses, which are now possible for almost any species, are revealing previously cryptic popu lation structuring as a result of a general improvement in the statistical power to detect small genetic differences between populations with larger marker sets and also because of the ability to detect genomic regions that are affected by selection (BOX 3). For example, in the Atlantic herring Clupea harengus, early allozyme studies detected almost no genetic differentiation between geographically distant and morphologically distinct forms of the species47. More recent microsatellite and single-nucleotide polymorphism (SNP) studies have confirmed the pattern of generally very low genetic differentiation, but have detected statistically significant differences between some major regions, although not among all suspected subpopulations51,52. Now, whole-exome sequencing has identified several thousand SNPs that show striking differences among populations, in some cases approaching fixation for different alleles53 (FIG. 4). These results show how genome-scale data can improve our understanding of population dynamics in marine populations.

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REVIEWS Box 3 | Detecting natural selection in the genome An emerging pattern suggests that marine populations often show strong divergence at particular genomic regions while the genome-wide level of differentiation is very low (for examples, see Lamichhaney53 and Hemmer-Hansen100). This pattern has typically been interpreted as evidence of divergent selection in the face of gene flow, but recent work has indicated that alternative explanations must be carefully considered101,102. Another consideration for marine species is the possible skew in offspring distributions, which is a violation of the currently used coalescent approaches for studying genomic processes (for a review, see Eldon and Wakeley103). The increasing resolution in marine genomic data sets should help to support more refined coalescent simulations and robust interpretations about the drivers of heterogeneous genomic divergence in different systems. Many forces shape genomic variation, including demographic history and natural selection. Natural selection may be identified using divergence data104, polymorphism data105 or a combination of the two106 (see below). Divergence data are used to identify natural selection between species, whereas polymorphism data are used to identify natural selection within a species: within, between or among populations. Methods to detect natural selection operate on different time scales. Divergence data identify older selective events, whereas polymorphism data can be used to identify recent selective events (reviewed in Vitte et al.107).

Divergence-based methods In protein-coding loci, the ratio of the number of non-synonymous (amino acid altering) substitutions per possible non-synonymous site (dN) to the number of synonymous (silent) substitutions per possible synonymous site (dS) is often used as a measure of natural selection. A dN/dS ratio equal to one is indicative of neutrality and a lack of functional constraint, a ratio less than one implies purifying selection and a ratio significantly greater than one is indicative of positive selection104. To detect positive selection, these divergence-based methods rely on having an excess of non-synonymous substitutions in the same gene. Polymorphism-based methods Natural selection can skew the shape of the local site frequency spectrum108,109. As the frequency of a positively selected allele increases in a population, the frequency of neutral-linked alleles also increases. A reduction in the variation around a positively selected site leads to a change in the local site frequency spectrum109. The process of hitch-hiking by neutral alleles also leads to unusually long haplotypes as compared with regions that have not been affected by recent positive selection. The length of time since the selected allele increased in frequency, the strength of the selection and the recombination rate in the region all play a part in the length of the haplotype around a selected allele. Site frequency spectra or linkage-disequilibrium-based data may be used to detect natural selection in a population; however, a recent review cautions that alternative forces, including background selection and demography, may obscure signatures of positive selection110. It is possible to detect local adaptation between two or more populations using genetic–environment association analyses111 or differentiation outlier approaches112.

Selective sweeps Processes by which new favourable mutations and physically linked alleles increase in frequency within a population owing to selection on the adaptive mutation, thereby reducing variation within a genomic region.

the freshwater form has evolved to spend its entire life in freshwater ecosystems55. The two forms consistently differ in the amount of body armour they have owing to differences in predation pressure55. The ectodysplasin (Eda) signalling pathway has been shown, through mapping and transgenic studies, to play a key part in the changes to bony plate formation in threespine stickleback populations. Repeated selection of these Eda alleles has resulted in parallel evolution of stickleback lowplated phenotypes at many different freshwater locations throughout the world57. These alleles are derived from an ancestral low-plated haplotype estimated to have first appeared more than two million years ago57. Reuse of standing genetic variation, at multiple markers across the stickleback genome, has been shown to be an important component of rapid parallel evolution of divergent species pairs56–60. This standing genetic vari ation remains at low frequency in marine populations57–59,

Resource management and conservation Adaptive variants as population markers. Given that genomic data from marine vertebrates are improving our understanding of microevolutionary processes in the oceans, they also have important practical applications for the management and conservation of marine biodiversity. The unprecedented power to detect previously cryptic population structure and adaptive divergence in commercially important species, such as the Atlantic cod62,63 and Atlantic herring 51,53, is improving our ability to target management efforts to biologically relevant population units, which is crucial for protecting the broadest evolutionary potential within species and maximizing long-term sustainable yields from fisheries resources64. Genome-scale data are also revolutionizing our ability to use forensic techniques to enforce fisheries regulations and to ensure the traceability of fish products to a local scale. Sequencing of the mitochondrial cytochrome c oxidase I (COI) gene has proved effective for identifying mislabelled seafood to the species level65. However, genomic analysis is often required to detect diagnostic markers that allow individuals to be assigned to specific populations or geographical regions. This level of detail can be important when fisheries regulations allow the harvesting of a species in certain areas but not in others (for example, marine protected areas) or when only certain regional fisheries for a particular species are eco-labelled by consumer organizations63.



suggesting that only a small number of founders contribute these adaptive alleles to freshwater populations. Many genome-wide comparisons between freshwater and marine populations, sampled across the globe, have identified genomic regions in which alternative alleles were fixed in either form58,59. These differentiated regions of the genome stand out against a background of mainly low differentiation58,59. Therefore, although most of the genome can be homogeneous in pairwise comparisons between populations that have recently diverged (or for which there are low levels of on‑going gene flow), selection on loci associated with ecological variables drives shifts in allele frequencies at particular genomic regions. Selective sweeps reduce variation at linked sites that are adjacent to adaptive loci, increasing the rate of lineage sorting within these genomic regions between populations under divergent selective regimes10. Thus, when previously panmictic populations become isolated and gene flow among them diminishes, adaptive alleles (and those alleles in tight linkage) are often the first markers to segregate between populations and become strongly differentiated. The genomic regions thought to be important for adaptation to varying environmental conditions in the European sea bass and the Atlantic cod, as discussed above, show strong differentiation (sometimes reaching near fixation of alternative alleles in functionally relevant genomic regions) between populations from habitats with different salinity 29 and temperature regimes33, respectively. These examples highlight the increasing importance of adaptive loci identified by genomewide scans61 for identifying both cryptic structure and differences in local adaptation among populations.


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Figure 4 | Genomic regions linked to local adaptation and associated with high population differentiation. Allele frequencies (part a) at a genomic region corresponding to chromosome XIV in the stickleback genome assembly that included 50 individual Atlantic herring, Clupea harengus, that were sampled from different locations the Baltic Sea NatureinReviews | Genetics (sample codes starting with BH) and the North Atlantic (sample codes starting with AH)53. The herring sampled from the Baltic Sea are highly differentiated from those sampled from the Atlantic in this genomic region. This is in contrast to most of the genome. For example, a phylogenetic tree based on all loci (part b) with a star-like phylogeny illustrates that most of the genome is only weakly differentiated, even between herring from the Baltic Sea and the North Atlantic. However, some genomic regions containing genes that may be locally adaptive along a salinity gradient are highly differentiated, hence a phylogenetic tree based on these regions (part c) linked to candidate adaptive loci provides a high resolution of population structuring53. bcl7a, B cell CLL/lymphoma 7A; clip1, CAP–GLY domain containing linker protein 1; ddx55, DEAD box helicase 55; denr, density-regulated protein; enoph1, enolase–phosphatase 1; hip1r, huntingtin interacting protein 1 related; hnrpdl, heterogeneous nuclear ribonucleoprotein D-like; ptpn11, protein tyrosine phosphatase, non-receptor type 11; sbno1, strawberry notch homolog 1; setd8, SET domain containing 2; tmed, transmembrane emp24 domain trafficking protein 2. Figure is adapted with permission from REF. 53, National Academy of Science.



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REVIEWS The ability to genetically assign individuals back to their population of origin is also creating new opportunities for assessing the levels of connectivity among commercially harvested populations. Classic equilibrium-b ased methods of population genetics used to estimate gene flow have limited power for most marine species. This is because it is often difficult to decipher whether low genome-wide levels of neutral differentiation result from extensive inter-mixing or whether populations are actually demographically independent but genetically similar because population sizes are large and divergence through genetic drift is therefore very slow 10,66. Model-based methods that can jointly estimate population size and migration rates can help resolve this problem67, but they typically integrate signals accumulated over relatively long timescales. For conservation purposes and fisheries management, however, it is primarily the contemporary rates of demographic and reproductive exchange that are relevant — for example, for predicting overspill effects from protected areas68 and understanding whether an area depleted by overfishing is likely to be repopulated by fish from neighbouring regions69. Fisheries management therefore needs estimates of current dispersal patterns, which have been inferred by reconstructing parentage and kinship relationships using genetic markers in many marine organisms with modest population sizes, such as reef fish70,71. However, these approaches probably have limited utility for most commercially important species with large population sizes, for which it will only be logistically feasible to sample an exceedingly small proportion of the population. For such species, the increased power of assignment tests afforded through initial genome scans to identify diagnostic markers can be very valu able63. New methods that use patterns of haplotype sharing (that is, segments of chromosomes that are identical-by‑descent between individuals) to infer recent migrations that have occurred over the past tens to hundreds of generations72,73 also offer a promising complementary approach as dense genotype data become available for c ommercially important species.

Genetic drift A change in allele frequency due to random chance; small populations are especially susceptible to large changes in allele frequency resulting from genetic drift.

Identical-by‑descent Segments of DNA in multiple individuals that are derived from the same common ancestor.

Monitoring the effects of fishing. Genomics can also play an important part in monitoring how fishing affects the genetic variation of the exploited populations. A recent meta-analysis showed that the current levels of genetic diversity, on average, are lower in overfished populations than in populations that have not suffered from fisheries collapse74. However, several studies based on DNA extracted from archived samples that were collected before the intensification of industrial fishing (for example, in Atlantic cod) have found no evidence of diversity loss despite population size reductions down to 1% of the historical maximum75,76. Future work with genome-scale data and ancient samples that cover longer time scales should provide more comprehensive insights into the circumstances under which fisheries are likely to erode genetic diversity 77. Genomic analysis should also help to test the hypothesis that the strong selection pressures imposed by intensive fishing have caused rapid evolution in several

Applications to conservation. A better understanding of the ways by which marine organisms respond to stressors as well as the variations in resilience to common threats seen among populations and individuals can be important for setting conservation priorities and designing restoration efforts. For example, genomic and transcriptional responses are important for understanding how organisms respond to major climatic shifts, as well as how organisms cope with pollution. Genomics can be an important diagnostic tool in elucidating the nature of threats to marine organisms and the selective pressures those threats place on the genome. Several recent studies have examined the genomic response to pollutant exposure 87–89. Populations of the mummichog killifish, Fundulus heteroclitus, on the Atlantic Coast of North America experience varying degrees of exposure to toxic aromatic hydrocarbon pollutants, such as dioxins and polychlorinated biphenyl (PCB), and have correspondingly variable sensitivity to specific PCBs88. Populations of mummichog that inhabit highly polluted areas show transcriptional changes that are indicative of an adaptive resistance to pollutant toxi city 87. In addition to a transcriptomic response, comparisons of divergent genomic loci between pairs of polluted sites and reference clean sites have revealed a small percentage of highly differentiated alleles that are indicative of adaptation to the pollutants89. These findings may have important conservation applications in restoration, transplantation, predicting how species will respond to new environments and identifying threats endangering those species at risk. Beyond characterizing organismal responses to threats, genomics is also revolutionizing our ability to rapidly and directly characterize biological threats such as disease agents. By comparing shared and unique mechanisms of resistance and sensitivity to harmful algal blooms, it is possible to identify genomic responses to this strong selective pressure90,91. A comparison of genome-wide differences in allele frequencies between survivors and victims of harmful algal blooms indicates



traits (including growth rates and timing of maturation), potentially reducing fish stock productivity and resilience to overfishing. Extensive phenotypic studies have suggested that such fisheries-induced evolution is widespread among the world’s fish stocks78,79, but the extent to which the observed changes truly are genetic and occur over timescales that are relevant for fisheries managers remains controversial80,81. Recent experimental studies have started to identify specific genomic regions associated with fisheries-induced evolution and have found evidence for selection effects on genes previously linked to body size variation82, embryological metabolism, stress response and immune function83. Moreover, heritable changes in the expression of hundreds of genes can happen in a generation84. In combination with temporal genome scans using archived samples collected directly from wild populations85,86, these types of studies provide a promising avenue for increasing our understanding of how fishing pressure affects functional genomic variation.


REVIEWS Metagenomic analyses Studies of DNA from multiple organisms that are found in environmental samples.

Hologenomes The collective genomes of a host plus all of its symbiotic microbes.

strong genomic signatures of ongoing selection for toxin resistance in the common bottlenose dolphin, Tursiops truncatus 90. Live populations of bottlenose dolphins off the coast of the Florida panhandle and central-west Florida were compared with those that died in the same regions during unusual mortality events. There were many alleles that changed in frequency between the live and dead dolphins, which helped identify candidate genes for brevetoxin resistance. These types of studies can shed light on the ability of populations to respond to biological threats.

Conclusions There has been rapid growth in marine genomics, fuelled by concurrent improvements in sequencing technologies and data analytics, and these have made a large impact on our understanding of evolution within the oceans, even though the number of reference genomes for marine organisms is still lagging behind that of terrestrial species. Comparative genomics studies have identi fied major genomic regions underlying developmental and morphological changes that are relevant for the evolutionary transitions to and from land and sea13–15,92. The many environments within the ocean provide ample opportunity for population differentiation, adaptation and, ultimately, speciation. By studying marine popu lations, we gain novel insights into adaptation and

Martin, W., Baross, J., Kelley, D. & Russell, M. J. Hydrothermal vents and the origin of life. Nat. Rev. Microbiol. 6, 805–814 (2008). 2. Nisbet, E. G. & Sleep, N. H. The habitat and nature of early life. Nature 409, 1083–1091 (2001). 3. Mora, C., Tittensor, D. P., Adl, S., Simpson, A. G. B. & Worm, B. How many species are there on earth and in the ocean? PLoS Biol. 9, e1001127 (2011). 4. Tucker, M. A. & Rogers, T. L. Examining predator–prey body size, trophic level and body mass across marine and terrestrial mammals. Proc. R. Soc. B 281, 20142103 (2014). 5. Food and Agriculture Organization of the United Nations. The state of food and agriculture: innovation in family farming (FAO, 2014). 6. McGowen, M. R., Grossman, L. I. & Wildman, D. E. Dolphin genome provides evidence for adaptive evolution of nervous system genes and a molecular rate slowdown. Proc. R. Soc. B 279, 3643–3651 (2012). This was the first comparative genomics study to use whole annotated genomes of terrestrial and marine sister taxa (in this case, the cow and dolphin) to elucidate the genomic underpinnings of adaptation associated with secondary colonization of the marine environment. 7. Foote, A. D. et al. Convergent evolution of the genomes of marine mammals. Nat. Genet. 47, 272–275 (2015). 8. Yim, H. S. et al. Minke whale genome and aquatic adaptation in cetaceans. Nat. Genet. 46, 88–92 (2014). 9. Zhou, X. et al. Baiji genomes reveal low genetic variability and new insights into secondary aquatic adaptations. Nat. Commun. 4, 2708 (2013). 10. Gagnaire, P. ‑A. et al. Using neutral, selected, and hitchhiker loci to assess connectivity of marine populations in the genomic era. Evol. Appl. 8, 769–786 (2015). This paper provides a comprehensive overview of how genomic data can be harnessed to improve estimates of dispersal and population connectivity. 11. Williams, T. M. The evolution of cost efficient swimming in marine mammals: limits to energetic 1.

optimization. Phil. Trans. R. Soc. Lond. B 354, 193–201 (1999). 12. Tucker, V. A. The energetic cost of moving about. Am. Sci. 63, 413–419 (1975). 13. Amemiya, C. T. et al. The African coelacanth genome provides insights into tetrapod evolution. Nature 496, 311–316 (2013). This article presents the sequencing and subsequent analysis of the coelacanth genome and reveals key insights into transitions from the marine to the terrestrial environment. 14. Thewissen, J. G. M. & Bajpai, S. Whale origins as a poster child for macroevolution: fossils collected in the last decade document the ways in which Cetacea (whales, dolphins, and porpoises) became aquatic, a transition that is one of the best documented examples of macroevolution in mammals. BioScience 51, 1037–1049 (2001). 15. Uhen, M. D. Evolution of marine mammals: back to the sea after 300 million years. Anat. Rec. 290, 514–522 (2007). 16. McGowen, M. R., Gatesy, J. & Wildman, D. E. Molecular evolution tracks macroevolutionary transitions in Cetacea. Trends Ecol. Evol. 29, 336–346 (2014). 17. Perrin, W. F., Würsig, B. & Thewissen, J. G. M. (eds) Encyclopedia of Marine Mammals Vol. 47 (Elsevier, 2008). 18. Berta, A., Sumich, J. L. & Kovacs, K. M. Marine Mammals: Evolutionary Biology 2nd edn (Academic Press, 2006). 19. Nikaido, M. et al. Coelacanth genomes reveal signatures for evolutionary transition from water to land. Genome Res. 23, 1740–1748 (2013). 20. Zhu, K. et al. The loss of taste genes in cetaceans. BMC Evol. Biol. 14, 218 (2014). 21. Feng, P., Zheng, J., Rossiter, S. J., Wang, D. & Zhao, H. Massive losses of taste receptor genes in toothed and baleen whales. Genome Biol. Evol. 6, 1254–1265 (2014). 22. Huebner, A. K. et al. Nonsense mutations in SMPX, encoding a protein responsive to physical force, result in X‑chromosomal hearing loss. Am. J. Hum. Genet. 88, 621–627 (2011). 23. Lopez-Rios, J. et al. Attenuated sensing of SHH by Ptch1 underlies evolution of bovine limbs. Nature 511, 46–51 (2014).

24. Carroll, S. B. Evo-devo and an expanding evolutionary synthesis: a genetic theory of morphological evolution. Cell 134, 25–36 (2008). 25. Wang, Z. et al. Adaptive evolution of 5ʹHoxD genes in the origin and diversification of the cetacean flipper. Mol. Biol. Evol. 26, 613–622 (2009). 26. Seehausen, O. et al. Genomics and the origin of species. Nat. Rev. Genet. 15, 176–192 (2014). 27. Stern, D. L. & Orgogozo, V. The loci of evolution: how predictable is genetic evolution? Evolution 62, 2155–2177 (2008). 28. Chen, S. et al. Whole-genome sequence of a flatfish provides insights into ZW sex chromosome evolution and adaptation to a benthic lifestyle. Nat. Genet. 46, 253–260 (2014). 29. Tine, M. et al. European sea bass genome and its variation provide insights into adaptation to euryhalinity and speciation. Nat. Commun. 5, 5770 (2014). 30. Schultz, E. T. & McCormick, S. D. in Fish Physiology: Euryhaline Fishes 1st edn (ed. McCormick, S. D.) (Elsevier, 2013). 31. Taylor, J. S., Braasch, I., Frickey, T., Meyer, A. & Van de Peer, Y. Genome duplication, a trait shared by 22,000 species of ray-finned fish. Genome Res. 13, 382–390 (2003). 32. Jaillon, O. et al. Genome duplication in the teleost fish Tetraodon nigroviridis reveals the early vertebrate proto-karyotype. Nature 431, 946–957 (2004). 33. Star, B. et al. The genome sequence of Atlantic cod reveals a unique immune system. Nature 477, 207–210 (2011). This paper presents the first annotated genome sequence for a commercially important fish species, revealing complex thermal adaptation and an unusual genome architecture. 34. Fletcher, G. L., Hew, C. L. & Davies, P. L. Antifreeze proteins of teleost fishes. Annu. Rev. Physiol. 63, 359–390 (2001). 35. Shin, S. C. et al. The genome sequence of the Antarctic bullhead notothen reveals evolutionary adaptations to a cold environment. Genome Biol. 15, 468 (2014). 36. Williams, T. M. et al. Travel at low energetic cost by swimming and wave-riding bottlenose dolphins. Nature 355, 821–823 (1992).



evolutionary processes. In addition, genomic studies have practical applications in fisheries and conservation and for the management of marine populations. We anticipate an increase in palaeogenomic s tudies on marine fauna within the next few years, which will provide greater insights into ancestral states and population structuring. By looking back at genomic responses during periods of intense harvesting 86, or past climate change during the end of the Last Glacial Maximum93, we may be better able to forecast responses, adaptive potential and genomic and/or phenotypic consequences to on‑going and future change. Finally, the world is becoming increasingly inter-connected; for example, as fishing vessels move around the oceans and circumnavigate the globe, the interactions between organisms, the environment and humans that take place within the marine (and terrestrial) environment become more intertwined. Marine ecosystems are composed of interacting organisms, and their survival is often inter-dependent on that of the other species with which they interact. Recent marine metagenomic analyses have revealed insights into microbiomes (BOX 2), and we anticipate that hologenomes94 will soon provide new insights into how selection pressures and evolutionary forces are acting on the collective community of organisms within a marine ecosystem, thus providing a better understanding of this connectivity.

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REVIEWS 37. Palumbi, S. R. Genetic divergence, reproductive isolation, and marine speciation. Annu. Rev. Ecol. Syst. 25, 547–572 (1994). 38. Palumbi, S. R. Population genetics, demographic connectivity, and the design of marine reserves. Ecol. Appl. 13, 146–158 (2003). 39. Block, B. A. et al. Electronic tagging and population structure of Atlantic bluefin tuna. Nature 434, 1121–1127 (2005). 40. Shillinger, G. L. et al. Persistent leatherback turtle migrations present opportunities for conservation. PLoS Biol. 6, e171 (2008). 41. Stone, G., Florez-Gonzalez, L. & Katona, S. Whale migration record. Nature 346, 705 (1990). 42. Bonfil, R. et al. Transoceanic migration, spatial dynamics, and population linkages of white sharks. Science 310, 100–103 (2005). 43. Waples, R. Separating the wheat from the chaff: patterns of genetic differentiation in high gene flow species. J. Hered. 89, 438–450 (1998). 44. Ward, R. D., Woodwark, M. & Skibinski, D. O. F. A comparison of genetic diversity levels in marine, freshwater, and anadromous fishes. J. Fish Biol. 44, 213–232 (1994). 45. Hedgecock, D., Barber, P. H. & Edmands, S. Genetic approaches to measuring connectivity. Oceanography 20, 70–79 (2007). 46. Cowen, R. K. & Sponaugle, S. Larval dispersal and marine population connectivity. Annu. Rev. Mar. Sci. 1, 443–466 (2009). 47. Ryman, N., Lagercrantz, U., Andersson, L., Chakraborty, R. & Rosenberg, R. Lack of correspondence between genetic and morphologic variability patterns in Atlantic herring (Clupea harengus). Heredity 53, 687–704 (1984). 48. Gaither, M. R., Toonen, R. J., Robertson, D. R., Planes, S. & Bowen, B. W. Genetic evaluation of marine biogeographical barriers: perspectives from two widespread Indo-Pacific snappers (Lutjanus kasmira and Lutjanus fulvus). J. Biogeog. 37, 133–147 (2010). 49. Thompson, K. F., Patel, S., Baker, C. S., Constantine, R. & Millar, C. D. Bucking the trend: genetic analysis reveals high diversity, large population size and low differentiation in a deep ocean cetacean. Heredity 116, 277–285 (2016). 50. Quérouil, S. et al. High gene flow in oceanic bottlenose dolphins (Tursiops truncatus) of the North Atlantic. Conserv. Genet. 8, 1405–1419 (2007). 51. Limborg, M. T. et al. Environmental selection on transcriptome-derived SNPs in a high gene flow marine fish, the Atlantic herring (Clupea harengus). Mol. Ecol. 21, 3686–3703 (2012). 52. Mariani, S. et al. North Sea herring population structure revealed by microsatellite analysis. Mar. Ecol. Progr. Ser. 303, 245–257 (2005). 53. Lamichhaney, S. et al. Population-scale sequencing reveals genetic differentiation due to local adaptation in Atlantic herring. Proc. Natl Acad. Sci. USA 109, 19345–19350 (2012). This study was one of the first to harness and convincingly demonstrate the potential of genomic sequencing to detect both cryptic population structure and local adaptation in a pelagic fish stock with high effective population size, which had been largely undetected by previous studies that used traditional molecular markers. 54. Kimura, M. & Ohta, T. The average number of generations until fixation of a mutant gene in a finite population. Genetics 61, 763–771 (1969). 55. McKinnon, J. S. & Rundle, H. D. Speciation in nature: the threespine stickleback model systems. Trends Ecol. Evol. 17, 480–488 (2002). 56. Lescak, E. A. et al. Evolution of stickleback in 50 years on earthquake-uplifted islands. Proc. Natl Acad. Sci. USA 112, E7204– E7212 (2015). 57. Colosimo, P. F. et al. Widespread parallel evolution in sticklebacks by repeated fixation of Ectodysplasin alleles. Science 307, 1928–1933 (2005). 58. Jones, F. C. et al. A genome-wide SNP genotyping array reveals patterns of global and repeated speciespair divergence in sticklebacks. Curr. Biol. 22, 83–90 (2012). 59. Jones, F. C. et al. The genomic basis of adaptive evolution in threespine sticklebacks. Nature 484, 55–61 (2012). This landmark paper is an exemplary application of how high-quality reference genomes combined with population genomic data can provide novel insights and resolution into key genomic changes during adaptive divergence.

82. van Wijk, S. J. et al. Experimental harvesting of fish populations drives genetically based shifts in body size and maturation. Front. Ecol. Environ. 11, 181–187 (2013). 83. Uusi-Heikkila, S. et al. The evolutionary legacy of size-selective harvesting extends from genes to populations. Evol. Appl. 8, 597–620 (2015). 84. Christie, M. R., Marine, M. L., Fox, S. E., French, R. A. & Blouin, M. S. A single generation of domestication heritably alters the expression of hundreds of genes. Nat. Commun. 7, 10676 (2016). 85. Hansen, M. M., Olivieri, I., Waller, D. M., Nielsen, E. E. & The GeM Working Group. Monitoring adaptive genetic responses to environmental change. Mol. Ecol. 21, 1311–1329 (2012). 86. Therkildsen, N. O. et al. Microevolution in time and space: SNP analysis of historical DNA reveals dynamic signatures of selection in Atlantic cod. Mol. Ecol. 22, 2424–2440 (2013). 87. Fisher, M. A. & Oleksiak, M. F. Convergence and divergence in gene expression among natural populations exposed to pollution. BMC Genomics 8, 1–10 (2007). 88. Nacci, D. E., Champlin, D. & Jayaraman, S. Adaptation of the estuarine fish Fundulus heteroclitus (Atlantic killifish) to polychlorinated biphenyls (PCBs). Estuar. Coasts 33, 853–864 (2010). 89. Williams, L. M. & Oleksiak, M. F. Signatures of selection in natural populations adapted to chronic pollution. BMC Evol. Biol. 8, 1–12 (2008). 90. Cammen, K. M., Schultz, T. F., Rosel, P. E., Wells, R. S. & Read, A. J. Genomewide investigation of adaptation to harmful algal blooms in common bottlenose dolphins (Tursiops truncatus). Mol. Ecol. 24, 4697–4710 (2015). 91. Cammen, K. M., Wilcox, L. A., Rosel, P. E., Wells, R. S. & Read, A. J. From genome-wide to candidate gene: an investigation of variation at the major histocompatibility complex in common bottlenose dolphins exposed to harmful algal blooms. Immunogenetics 67, 125–133 (2015). 92. Olsen, J. L. et al. The genome of the seagrass Zostera marina reveals angiosperm adaptation to the sea. Nature 530, 331–335 (2016). 93. Foote, A. D. et al. Ancient DNA reveals that bowhead whale lineages survived Late Pleistocene climate change and habitat shifts. Nat. Commun. 4, 1677 (2013). 94. Bordenstein, S. R. & Theis, K. R. Host biology in light of the microbiome: ten principles of holobionts and hologenomes. PLoS Biol. 13, e1002226 (2015). 95. El‑Metwally, S., Hamza, T., Zakaria, M. & Helmy, M. Next-generation sequence assembly: four stages of data processing and computational challenges. PLoS Comput. Biol. 9, e1003345 (2013). 96. Narum, S. R., Buerkle, C. A., Davey, J. W., Miller, M. R. & Hohenlohe, P. A. Genotyping-by‑sequencing in ecological and conservation genomics. Mol. Ecol. 22, 2841–2847 (2013). 97. Nelson, T. M., Rogers, T. L. & Brown, M. V. The gut bacterial community of mammals from marine and terrestrial habitats. PLoS ONE 8, e83655 (2013). 98. Bik, E. M. et al. Marine mammals harbor unique microbiotas shaped by and yet distinct from the sea. Nat. Commun. 7, 10516 (2016). 99. Sanders, J. G. et al. Baleen whales host a unique gut microbiome with similarities to both carnivores and herbivores. Nat. Commun. 6, 8285 (2015). This study was one of the first to highlight that genomics can shed light on adaptations to the marine environment through shifts in the composition of the gut microbiota. 100. Hemmer-Hansen, J. et al. A genomic island linked to ecotype divergence in Atlantic cod. Mol. Ecol. 22, 2653–2667 (2013). 101. Cruickshank, T. E. & Hahn, M. W. Reanalysis suggests that genomic islands of speciation are due to reduced diversity, not reduced gene flow. Mol. Ecol. 23, 3133–3157 (2014). 102. Bierne, N., Welch, J., Loire, E., Bonhomme, F. & David, P. The coupling hypothesis: why genome scans may fail to map local adaptation genes. Mol. Ecol. 20, 2044–2072 (2011). 103. Eldon, B. & Wakeley, J. Coalescent processes when the distribution of offspring number among individuals is highly skewed. Genetics 172, 2621–2633 (2006). 104. Yang, Z. & Bielawski, J. P. Statistical methods for detecting molecular adaptation. Trends Ecol. Evol. 15, 496–503 (2000).



60. Shapiro, M. D. et al. Genetic and developmental basis of evolutionary pelvic reduction in threespine sticklebacks. Nature 428, 717–723 (2004). 61. Manel, S. et al. Genomic resources and their influence on the detection of the signal of positive selection in genome scans. Mol. Ecol. 25, 170–184 (2016). 62. Bradbury, I. R. et al. Genomic islands of divergence and their consequences for the resolution of spatial structure in an exploited marine fish. Evol. Appl. 6, 450–461 (2013). 63. Nielsen, E. E. et al. Gene-associated markers provide tools for tackling illegal fishing and false ecocertification. Nat. Commun. 3, 851 (2012). This paper demonstrates how gene-associated markers allow the assignment of commercially important fish species to their population of origin, providing unprecedented resolution for using molecular forensics in marine fisheries management. 64. Reiss, H., Hoarau, G., Dickey-Collas, M. & Wolff, W. J. Genetic population structure of marine fish: mismatch between biological and fisheries management units. Fish Fish. 10, 361–395 (2009). 65. Ward, R. D., Hanner, R. & Hebert, P. D. The campaign to DNA barcode all fishes, FISH-BOL. J. Fish. Biol. 74, 329–356 (2009). 66. Waples, R. S. & Gaggiotti, O. What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity. Mol. Ecol. 15, 1419–1439 (2006). 67. Marko, P. B. & Hart, M. W. The complex analytical landscape of gene flow inference. Trends Ecol. Evol. 26, 448–456 (2011). 68. Harrison, Hugo, B. et al. Larval export from marine reserves and the recruitment benefit for fish and fisheries. Curr. Biol. 22, 1023–1028 (2012). 69. Goncalves da Silva, A., Appleyard, S. A. & Upston, J. Establishing the evolutionary compatibility of potential sources of colonizers for overfished stocks: a population genomics approach. Mol. Ecol. 24, 564–579 (2015). 70. Horne, J. B., van Herwerden, L., Abellana, S. & McIlwain, J. L. Observations of migrant exchange and mixing in a coral reef fish metapopulation link scales of marine population connectivity. J. Hered. 104, 532–546 (2013). 71. Planes, S., Jones, G. P. & Thorrold, S. R. Larval dispersal connects fish populations in a network of marine protected areas. Proc. Natl Acad. Sci. USA 106, 5693–5697 (2009). 72. Bowden, R. et al. Genomic tools for evolution and conservation in the chimpanzee: Pan troglodytes ellioti is a genetically distinct population. PLoS Genet. 8, e1002504 (2012). 73. Palamara, P. F. & Pe’er, I. Inference of historical migration rates via haplotype sharing. Bioinformatics 29, i180–i188 (2013). 74. Pinsky, M. L. & Palumbi, S. R. Meta-analysis reveals lower genetic diversity in overfished populations. Mol. Ecol. 23, 29–39 (2014). This article presents a meta-analysis of over 11,000 microsatellite loci across 140 species, and shows that allelic richness and heterozygosity are generally lower in overfished populations, which could hamper the evolutionary potential of these populations. 75. Ruzzante, D., Taggart, C., Doyle, R. & Cook, D. Stability in the historical pattern of genetic structure of Newfoundland cod (Gadus morhua) despite the catastrophic decline in population size from 1964 to 1994. Conserv. Genet. 2, 257–269 (2001). 76. Therkildsen, N. O., Nielsen, E. E., Swain, D. P. & Pedersen, J. S. Large effective population size and temporal genetic stability in Atlantic cod (Gadus morhua) in the southern Gulf of St. Lawrence. Can. J. Fish. Aquat. Sci. 67, 1585–1595 (2010). 77. Halffman, C. M. et al. Early human use of anadromous salmon in North America at 11,500 y ago. Proc. Natl Acad. Sci. USA 112, 12344–12348 (2015). 78. Allendorf, F. W. & Hard, J. J. Human-induced evolution caused by unnatural selection through harvest of wild animals. Proc. Natl Acad. Sci. USA 106, 9987–9994 (2009). 79. Jørgensen, C. et al. Ecology: managing evolving fish stocks. Science 318, 1247–1248 (2007). 80. Andersen, K. H. & Brander, K. Expected rate of fisheries-induced evolution is slow. Proc. Natl Acad. Sci. USA 106, 11657–11660 (2009). 81. Browman, H. I., Law, R. & Marshall, C. T. The role of fisheries-induced evolution. Science 320, 47–50 (2008).


REVIEWS 105. Tajima, F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123, 585–595 (1989). 106. Hudson, R. R., Kreitman, M. & Aguade, M. A test of neutral molecular evolution based on nucleotide data. Genetics 116, 153–159 (1987). 107. Vitti, J. J., Grossman, S. R. & Sabeti, P. C. Detecting natural selection in genomic data. Annu. Rev. Genet. 47, 97–120 (2013). 108. Cutter, A. D. & Payseur, B. A. Genomic signatures of selection at linked sites: unifying the disparity among species. Nat. Rev. Genet. 14, 262–274 (2013). 109. Maynard Smith, J. & Haigh, J. The hitch-hiking effect of a favourable gene. Genet. Res. 23, 23–35 (1974). 110. Bank, C., Ewing, G. B., Ferrer-Admettla, A., Foll, M. & Jensen, J. D. Thinking too positive? Revisiting current methods of population genetic selection inference. Trends Genet. 30, 540–546 (2014).

116. Schneider, I. & Shubin, N. H. The origin of the tetrapod limb: from expeditions to enhancers. Trends Genet. 29, 419–426 (2013).

Acknowledgements

J.L.K. and A.P.B. were supported in part by a grant from the US Army Research Office (W911NF‑15‑1‑0175). A.D.F. was supported by a short visit grant from the European Science Foundation–Research Networking Programme ConGenOmics and by a Swisss National Science Foundation grant (31003A‑143393) to L. Excoffier.

Competing interests statement

The authors declare no competing interests.

FURTHER INFORMATION Ensembl Genome Browser: http://www.ensembl.org/index.html ALL LINKS ARE ACTIVE IN THE ONLINE PDF



111. Rellstab, C., Gugerli, F., Eckert, A. J., Hancock, A. M. & Holderegger, R. A practical guide to environmental association analysis in landscape genomics. Mol. Ecol. 24, 4348–4370 (2015). 112. Whitlock, M. C. & Lotterhos, K. E. Reliable detection of loci responsible for local adaptation: inference of a null model through trimming the distribution of FST. Am. Nat. 186, S24–S36 (2015). 113. Sivasundar, A. & Palumbi, S. R. Parallel amino acid replacements in the rhodopsins of the rockfishes (Sebastes spp.) associated with shifts in habitat depth. J. Evol. Biol. 23, 1159–1169 (2010). 114. Shum, P., Pampoulie, C., Sacchi, C. & Mariani, S. Divergence by depth in an oceanic fish. Peer J. 2, e525 (2014). 115. Shum, P., Pampoulie, C., Kristinsson, K. & Mariani, S. Three-dimensional post-glacial expansion and diversification of an exploited oceanic fish. Mol. Ecol. 24, 3652–3667 (2015).

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