Genetics and Genomics

Genetics and Genomics

400 G Genetics and Genomics 1969). Bile acids play a major role in lipid absorption in the small intestine, and their absence in sirenians is in li...

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Genetics and Genomics

1969). Bile acids play a major role in lipid absorption in the small intestine, and their absence in sirenians is in line with a shift to nutrient absorption in the large intestine. The large intestinal length of sirenians is massive (~6–7 times body length compared with 2 times body length in elephants; Reynolds and Rommel, 1996) with a large diameter (~15 cm in manatees), and when filled, the large intestine can account for 10% of the body mass. The small intestine empties into the cecum (also called the midgut cecum), consisting of the body (corpus ceci) separated by an externally visible fold from the ampulla ceci. The corpus also features paired cecal horns (manatee) or a single horn in the dugong. The midgut cecum contains goblet cells for mucous secretion covered by either keratinized or unkeratinized stratified squamous epithelium to protect underlying cells from abrasion. Absorptive cells that were absent in the small intestine are common in the cecum and colon. VFAs are produced in the cecum and large intestine as a result of microbial breakdown of cellulose at a higher rate than reported for other hindgut fermenters (Murray et al., 1977), and probably corresponds to the slow gut passage rate and high digestive efficiency of sirenians. Similar to the small intestine, the colon shows many ridges running perpendicular to food movement, but serves here to slow passage. Other than being the main site of nutrient absorption, the colon may have important osmoregulatory function in sirenians.

References Amstrup, S.C., and Nielsen, C.A. (1989). Acute gastric dilatation and volvulus in a free-living polar bear. J. Wildl. Dis. 25, 601–604. Bauermeister, A., and Sargent, J.R. (1979). Wax esters: Major metabolites in the marine environment. Trends Biochem. Sci. 4, 209–211. Best, R.C. (1985). Digestibility of ringed seals by the polar bear. Can. J. Zool. 63, 1033–1036. Caldwell, F.T., Sherman, E.B., and Levitsky, K. (1969). The composition of bladder bile and the histological pattern of the gallbladder and liver of the sea cow. Comp. Biochem. Physiol. 28, 437–441. Forsten, A., and Youngman, P.M. (1982). Hydrodamalis gigas. Mamm. Species. 165, 1–3. Gray, R., Canfield, P., and Rogers, T. (2006). Histology of selected tissues of the leopard seal and implications for functional adaptations to an aquatic lifestyle. J. Anat. 209, 179–199. Helm, R.C. (1983). Intestinal length of three California pinniped species. J. Zool. Lond. 199, 277–304. Helm, R.C. (1984). Rate of digestion in three species of pinnipeds. Can. J. Zool. 62, 1751–1756. Jeuniaux, C., and Cornelius, C. (1997). Distribution and activity of chitinolytic enzymes in the digestive tract of birds and mammals. First International Conference on Chitin/Chitosan, pp. 542–549. Krockenberger, M.B., and Bryden, M.M. (1994). Rate of passage of digesta through the alimentary tract of southern elephant seals (Mirounga leonine) (Carnivora: Phocidae). J. Zool. Lond. 234, 229–237. Lanyon, J.M., and Sanson, G.D. (2006). Mechanical disruption of seagrass in the digestive tract of the dugong. J. Zool. 270, 277–289. Lawson, J.W., Hare, J.A., Noseworthy, E., and Friel, J.K. (1997). Assimilation efficiency of captive ringed seals (Phoca hispida) fed different diets. Polar Biol. 18, 107–111. Mårtensson, P.-E., Nordøy, E.S., and Blix, A.S. (1994). Digestibility of krill (Euphausia superba and Thysanoessa sp.) in minke whales (Balaenoptera acutorostrata) and crabeater seals (Lobodon carcinophagus). Br. J. Nutr. 72, 713–716. Mårtensson, P.-E., Nordøy, E.S., Messelt, E.B., and Blix, A.S. (1998). Gut length, food transit time and diving habit in phocid seals. Polar Biol. 20, 213–217. Mead, J.G. (2007). Stomach anatomy and use in defining systemic relationships of the cetacean family Ziphiidae (beaked whales). Anat. Rec. 290, 581–595.

Murray, R.M., Marsh, H., Heinsohn, G.E., and Spain, A.V. (1977). The role of the midgut caecum and large intestine in the digestion of sea grasses by the dugong (Mammalia: Sirenia). Comp. Biochem. Physiol. 56, 7–10. Olsen, M.A., Nordøy, E.S., Blix, A.S., and Mathiesen, S.D. (1994). Functional anatomy of the gastrointestinal system of Northeastern Atlantic minke whales (Balaenoptera acutorostrata). J. Zool., Lond. 234, 55–74. Olsen, M.A., and Mathiesen, S.D. (1996). Production rates of volatile fatty acids in the minke whale (Balaenoptera acutorostrata) forestomach. Br. J. Nutr. 75, 21–31. Olsen, M.A., Nilssen, K.T., and Mathiesen, S.D. (1996). Gross anatomy of the gastrointestinal system of harp seals (Phoca groenlandica). J. Zool. Lond. 238, 581–589. Ortiz, R.M. (2001). Osmoregulation in marine mammals. J. Exp. Biol. 204, 1831–1844. Place, A.R. (1992). Comparative aspects of lipid digestion and absorption: physiological correlates of wax ester digestion. Am. J. Physiol. 263, R464–471. Reynolds, J.E., and Rommel, S.A. (1996). Structure and function of the gastrointestinal tract of the Florida manatee, Trichechus manatus latirostris. Anat. Rec. 245, 539–558. Sanders, J.G., Beichman, A.C., Roman, J., Scott, J.J., Emerson, D., McCarthy, J.J., and Girguis, P.R. (2015). Baleen whales host a unique gut microbiome with similarities to both carnivores and herbivores. Nature Comm. 6 doi:10.1038/ncomms9285. Shurin, J.B., Gruner, D.S., and Hillebrand, H. (2006). All wet or dried up? Real differences between aquatic and terrestrial food webs. Proc. R. Soc. B 273, 1–9. Simmonds, M.P. (2012). Cetaceans and marine debris: the great unknown. J. Mar. Bio. 2012, 1–8. Stevens, C.E., and Hume, I.D. (1995). Microbial fermentation and synthesis of nutrients and the absorption of end products. In “Comparative Physiology of the Vertebrate Digestive System” (C.E. Stevens, and I.D. Hume, Eds), pp. 188–228. Cambridge University Press. Swaim, Z.T., Westgate, A.J., Koopman, H.N., Rolland, R.M., and Kraus, S.D. (2009). Metabolism of ingested lipids by North Atlantic right whales. Endanger. Species Res. 6, 259–271. Takahashi, K., and Yamasaki, F. (1972). Digestive tract of Ganges dolphin, Platanista gangetica. II. Small and large intestine. Okajimas Fol. Anat. Jap. 48, 427–452. Tarpley, R.J., Sis, R.F., Albert, T.F., Dalton, L.M., and George, J.C. (1987). Observations on the anatomy of the stomach and duodenum of the bowhead whale, Balaena mysticetus. Am. J. Anat. 180, 295–322. Trumble, S.J., Barboza, P.S., and Castellini, M.A. (2003). Digestive constraints on an aquatic carnivore: Effects of feeding frequency and prey composition on harbor seals. J. Comp. Physiol. B 173, 501–509. Warner, A.C.I. (1981). Rate of passage of digesta through the gut of mammals and birds. Nutr. Abstr. Rev. 51, 789–820. Williams, T.M., Haun, J., Davis, R.W., Fuiman, L.A., and Kohin, S. (2001). A killer appetite: Metabolic consequences of carnivory in marine mammals. Comp. Biochem. Phys. A 129, 785–796.

GENETICS AND GENOMICS Per J. Palsbøll, Andrea A. Cabrera and Martine Bérubé Genetics has undergone several significant technological advances since the early 1960s, which have dramatically expanded the application of genetics across life sciences, most recently into the field of genomics, which is a subarea of genetics. Consequently, genetic methods are employed not only to study genetics per se, but

Genetics and Genomics


also as an indirect means for inquiries into the evolution, ecology, behavior, and conservation of natural populations. This chapter focuses on the current, most commonly applied methodologies. The analysis of changes in the DNA sequence itself took a giant leap forward by the development of the polymerase chain reaction (PCR) in the late 1980s (Mullis and Faloona, 1987). PCR-based analyses require minute amounts of genetic material which, in turn, facilitated the use of nonlethal methods to obtain the required tissue for DNA extraction, such as skin biopsies (e.g., Palsbøll et  al., 1991), as well as noninvasive tissue samples, such as feces and even “exhalent breath” (e.g., Acevedo-Whitehouse et  al., 2010). The high sensitivity and specificity of PCR-based analyses mean that DNA obtained from ancient/historic samples (e.g., Sremba et  al., 2015) or environmental samples, such as filtered sea water (Foote et al., 2012) can be analyzed to determine species and assess genetic diversity. The human genome project initiated the subsequent development of so-called massive “parallelized” sequencing technologies which was applied to nonmodel species from 2010 and onwards (Davey et  al., 2011) thereby facilitating the adoption and application of genomic approaches to the study of marine mammals (Foote et al., 2015; Keane et al., 2015; Yim et al., 2014; Zhou et al., 2013). Current genomic approaches can be tailored to target different kinds of hereditary variation, such as the nucleotide sequence in DNA and RNA sequences, proteins as well as epigenetic modifications, such as methylation. Most studies that generate genomic data sets from marine mammal species and populations take advantage of the vast amounts of data generated to obtain more precise estimates of aspects, such as gene flow, past demographic events as well as the detection of genes under past or current selection (Allendorf et al., 2010), providing novel, key insights into the ecology and evolution of marine mammals. Here, we provide a brief overview of the key applications of genetics and genomics (which is a subdiscipline of genetics) to the study of marine mammals. The range of questions addressed by genetic techniques applied to marine mammals is very broad ranging - from the origin of marine mammal lineages, taxonomy, and adaptation to the identification of individuals, their sex and pathogens. Herein, we highlight a few illustrative examples (for a broad overview see Cammen et al., 2016).

individuals for tooth extraction is not feasible. In long-term studies based upon individual photo-identification (or tagging), individuals identified as pups/calves will be of known age. Such long-term individual-based studies require a nontrivial and sustained effort to accumulate sufficient observations and are limited to relatively few uniquely studied populations (e.g., Northeast Pacific killer whales, Orcinus orca; Gulf of Maine humpback whales, Megaptera novaeangliae; and Bird Island Antarctic fur seals, Arctocephalus gazella). Two kinds of genetic aging assays have been applied to cetaceans. Initial attempts were based upon telomeres (Olsen et al., 2012, 2014), which, in humans and other vertebrates, decrease in average length during an individual’s lifespan. This approach performs poorly in mysticetes despite some age-related telomere changes. In addition, telomere shortening likely reflects biological age but not necessarily chronological age, and hence telomeres are probably better suited to assess cumulative stress exposure of individuals rather than age per se (Jarman et al., 2015). Another “short-term” change in the DNA of an individual is so-called epigenetic modifications. Many epigenetic modifications appear to correlate consistently with chronological age in humans. Polanowski and colleagues (2014) characterized several such age-related human epigenetic markers in humpback whales of known age. The degree of methylation at three epigenetic markers was found to correlate tightly with age in humpback whales (Polanowski et  al., 2014). Unfortunately, the same epigenetic markers did not appear to correlate with age across a wider range of species (Polanowski et  al., 2014), likely implying that specific age-correlated epigenetic markers must be identified separately in each marine mammal species. However, the more recent genomewide epigenetic screening methods should make it relatively straight forward to identify species-specific age-correlated epigenetic markers (Bossdorf et  al., 2008). The age distribution within and among con-specific populations differs substantially between shrinking, expanding and recovering populations. Accordingly, reliable and cost-efficient ageing methods that are applicable to noninvasive samples will facilitate the assessment of the current population status and recent history, which would make epigenetic aging a key tool to inform and guide the management and conservation of marine mammal populations (Jarman et  al., 2015; Polanowski et al., 2014).

I.  Sex and Age in an Era of Nonlethal Sampling

II.  Identification of Individuals and Their Close Relatives

The identification of the sex of individuals by observation alone is difficult, at best, for the vast majority of marine mammals. However, marine mammals have specific sex chromosomes in common with most other mammal species; males have one copy of the X-chromosome and one copy of the Y-chromosome, whereas females have two copies of the X-chromosome. Sex chromosome-specific DNA sequences can easily be targeted and amplified using PCR revealing the sex of the sampled individual (e.g., Bérubé and Palsbøll, 1996). Elucidating this very basic information has provided novel insights into group composition (Amos et  al., 1993; Pinela et al., 2009), mating strategies (Flatz et al., 2012) and sex-specific dispersal rates and patterns (e.g., Brown Gladden et al., 1997). The age of individuals represents another elusive characteristic in most marine mammal species. Pinnipeds and toothed whales can be aged from the number of dentine layers in their teeth (Hohn et al., 1989; Murphy et al., 2012). However, collecting teeth for aging is highly invasive and, when possible, requires a high degree of effort. In many species, in particular cetaceans, capturing

Genetic methods have also been applied to identify individuals and pairs of closely related individuals, which can be utilized to gain insights into many key ecological traits such as mating strategies and kin selection. Smaller marine mammal species can be captured and fitted with tags or branded, but such an approach is effort intensive and infeasible in most marine mammal species. In particular, attaching tags for long periods has proven challenging in large mysticetes. Alternatively, individuals can be identified from their permanent natural markings in some species; this has been applied with considerable success in species that have clear natural markings that differ among individuals in species such as gray seals (Halichoerus grypus; Hastings et  al., 2012), killer whales (Würsig and Jefferson, 1990), and humpback whales (Katona et al., 1979). The genetic equivalent to unique individual markings is so-called genetic fingerprinting, which has a long tradition in human forensics. Individual identification using genetic tagging has been applied to many natural populations of marine mammals (e.g., Hoelzel and Amos, 1988; Hoffman et al., 2006), in a few cases across entire ocean




Genetics and Genomics

basins (Baker et  al., 2013; Palsbøll et  al., 1997). Common applications of individual identification in natural populations are the estimation of abundance using capture-mark-recapture methods as well as assessing connectivity across the seascape. One example of the latter was the genetic (and photographic) identification of a female humpback whale off Gabon, Western Africa in the South Atlantic, which was reidentified the following year off Madagascar in the Indian Ocean (Pomilla and Rosenbaum, 2005), representing a transoceanic migration event. Several large oceanwide studies based upon the analysis of thousands of skin biopsies have utilized genetic tagging both to estimate abundance estimation and mapping seascape use, in particular in humpback whales (Palsbøll et al., 1997). The identification of closely related individuals enables insights into mating strategies, i.e., by paternity analysis (e.g., Wiszniewski et  al., 2012), pod structure (Pilot et  al., 2010) and even abundance (Palsbøll et  al., 2010). In general, it is assumed that most species evolve toward behaviors that prevent excessive inbreeding, which may lead to a reduction in average population fitness due to inbreeding depression. Long-term studies of several odontocete species, e.g., killer whales and common bottlenose dolphins, Tursiops truncatus (Amos et al., 1993; Gero et al., 2005; Pilot et al., 2010) revealed that most individuals, including mature males, stay within their natal pod during entire life. This kind of social structure could lead to excessive inbreeding if mature (and presumably closely related) individuals from the same pod were to mate with each other. Amos and colleagues (1991,1993) investigated this specific aspect in long-finned pilot whales, Globicephala melas. Employing genetic estimates of relatedness among aged (using the dentine layers in sectioned teeth) individuals from entire pods the authors affirmed that all individuals in a single pod were essentially part of the same extended matrilineal family (Amos et  al., 1993). In contrast, using paternity exclusion, none of the mature males in a pod sired other pod members (Amos et al., 1991). In addition, it appeared that pod members that were part of the same age cohort had been sired by a few, but closely related, males. Amos and colleagues (1993) concluded that the estrous females in a pod probably mate with a few males that were “visiting” from another pod. The males subsequently returned to their natal pod after mating. Since such visiting males would be related (i.e., part of the same maternal pod), the findings would explain why calves of the same age cohort appeared to be sired by a few closely related males. Later work in other species with similar pronounced matrilineal pod structure (e.g., killer whales) have yielded similar findings, i.e., that pods appear to represent extended matrilineal families, but mating appears to take place between individuals from different pods (Hoelzel et al., 1998). Several studies, particularly in pinnipeds, have suggested mate preference for individuals that are genetically diverse and/or dissimilar (Amos et al., 2001; Hoffman et al., 2007). All the above studies have reported findings that are consistent with the evolution of behaviors that presumably maximize outbreeding.

2013) and pinnipeds (Hoffman et  al., 2011) have been consistent with the notion of recent drastic declines due to human exploitation. In some cases, the historic abundance inferred from the amount of genetic variation in contemporary populations has been much higher than indicated by other approaches (e.g., demographic modeling). The discrepancies in inferred historic abundances may be due to a wide range of differences (and violations) of assumptions underlying each estimation approach. Perhaps the most common source of discrepancies lies with the time “point” that an estimate of historic abundance applies to, which for most genetic assessment is very wide, likely representing a mean across many hundreds to thousands of generations (depending on the approach used). Since there is a considerable temporal lag between a demographic change, and the corresponding change in genetic diversity, it is often challenging to assign a genetic-based historical abundance estimate to a specific, narrow timeframe (e.g., just prior to the onset of human exploitation). For similar reasons, it is also difficult to detect a very recent demographic change from the current degree and nature of genetic variation; unless the decline was very large (Fontaine et al., 2012).

IV.  Population Genetic Structure and Units of Conservation One key application of genetic analyses is for management and conservation, especially to delineate populations or management units (Dizon et  al., 1992). In other words, many genetic assessments have been aimed toward detecting a spatial and/or temporal heterogeneous structure in the genetic variation within species. Typically, heterogeneity in genetic variation among con-specific individuals across the seascape is inferred as evidence for reduced dispersal and consequently population substructuring, where each homogenous set of samples often is equated with a management unit (Dizon et al., 1992). The identification of management units is important in order to direct monitoring efforts at the proper temporal and spatial scale, thereby hopefully facilitating the early detection of possible endangerment and facilitate local recovery. The application of genetics and genomics toward delineating populations and/or management units has a long tradition in marine mammals (Banguera-Hinestroza et  al., 2002; Clapham et al., 2008; Bilgmann et al., 2014). However, translating what are essentially abstract population genetic concepts and entities into real-life ecological processes and management units is far from trivial (Palsbøll et  al., 2007). These applications of genetics and genomics, also outside marine mammals, are currently undergoing substantial debate and revision in order to develop concepts and analytical approaches where the underlying assumptions and estimates obtained from genetic and genomic data are better aligned with the general timeframes and effect sizes of relevance to ecology and conservation.

III.  Estimating Current and Past Abundance

V.  The Recent Application of Genomics to the Study of Marine Mammals

Given the intensive human overexploitation of many marine mammal species, it is perhaps not surprising that several studies have attempted to infer historic abundance and the rate of decline from genetic data. The degree and distribution of genetic variation within and among con-specific individuals is a product of past (and current) population sizes and migration rates, although such inferences require a number of highly simplistic assumptions (Palsbøll et al., 2013). In general, such genetic assessments of historic abundance in large whales (Roman and Palumbi, 2003; Ruegg et  al.,

Most of the examples above were based on studies that utilized relatively few genetic markers due to experimental restrictions in the methodologies employed available at the time. The development of massive parallel DNA sequencing methods during the last 1–2 decades has enabled the sequencing of entire genomes, i.e., the generation of several orders of magnitude more data. The vast amounts of unbiased, genome-wide data should, in principle, make inferences more robust to potential biases arising from a small, nonrepresentative “sample” of a genome (Hoffman et  al., 2014). The complete

Genetics and Genomics genome has been published for several marine mammal species already (Foote et al., 2015; Humble et al., 2016; Keane et al., 2015; Liu et al., 2014; Yim et al., 2014; Zhou et al., 2013), and many more are underway, making marine mammals unique among mammals in terms of available, well-covered genome sequences. These genomic data have facilitated novel and detailed insights into the evolution and ecology of marine mammals (Liu et  al., 2014; Tsagkogeorga et al., 2015). Although genomic analyses have been applied to several different species of marine mammals, the killer whale is the species in which most genomic data have been generated and analyzed so far (Foote et al., 2016). Accordingly, the work in killer whales provides a nice illustration of the kind of inferences that may be drawn from genomic-level data. Most of the works in killer whales have been aimed at the timing and adaptations resulting in divergence into different ecotypes in this species. The division of killer whales into different ecotypes is largely based upon dietary differences (Ford et al., 1998). Some killer whale ecotypes prey exclusively upon fish, while others prey mainly on pinnipeds and/or large whales. In some cases, different ecotypes are morphologically distinguishable, such as in the Antarctic. Genetic studies have focused on whether the same ecotype arose independently in different ocean basins and whether the evolution into different ecotypes coincided with specific adaptations, i.e., as a consequences of the difference in diet (Ford et  al., 1998; Hoelzel et  al., 2007; Foote et  al., 2011). These studies have utilized the entire gamut of genetic data ranging from genotypes collected at a dozen microsatellite loci and mitochondrial control region DNA sequences (Hoelzel et  al., 1998; Chivers et  al., 2007), complete mitochondrial genome sequences (Morin et  al., 2010; Foote et  al., 2011) as well as complete and reduced genome data (Moura et  al., 2014; Foote et  al., 2016). The first kinds of “genomic” studies in killer whales were based upon sequencing the complete mitochondrial genome (~16,500 nucleotides), as opposed to the 300–500 nucleotides of the mitochondrial control region, which is common to most marine mammal genetic studies. Morin and colleagues (2010) presented an analysis of 139 complete mitochondrial genome sequences from different ecotypes in multiple in the North Pacific, Antarctic as well as the North Atlantic. These authors concluded that the mammal and fish-eating ecotypes had arisen multiple times, independently within each ocean basin. Subsequent analyses based upon reduced representation genome data (Moura et al., 2015), as well as an analysis of 50 complete, but low coverage, killer whale genome sequences (Foote et al., 2016), essentially confirmed the results inferred from previous data albeit with higher levels of precision as well as insights into the dynamics of past demographic changes. Foote and colleagues (2016) concluded that the radiations of killer whales leading to the present ecotypes occurred recently, during the past 250,000 years. The founding populations went through severe bottlenecks, presumably due to a small number of individuals that became the ancestors of novel ecotypes in new habitats. These initial small populations diverged rapidly genetically, presumably due to a combination of random effects (caused by the small ancestral populations), cultural cohesion of ecotypes and adaptations due to diet specialization (Foote et al., 2016). The analyses included an assessment of genes subjected to an above-genome-average rate of changes in key enzymes between mammal and fish-eating ecotypes. In the two mammal eating ecotypes, the candidate enzyme-coding genes and processes identified as under positive selection, were associated with the regulation of methionine metabolism. The observed changes in the inferred enzyme structure were interpreted by the authors as selection for


coping with infrequent rich sources of dietary methionine (i.e., from mammal predation), which, in turn, would result in an additional selective pressure on methionine metabolism compared to ecotypes that feed more regularly, i.e., upon fish (Foote et  al., 2016). Other genes under apparent selection were involved in lipid metabolism presumably due to preying on marine mammals which have substantial lipid stores. A similar finding was previously reported in an analysis of polar bear genome sequences (Liu et al., 2014), suggesting some degree of convergent adaptation driven by a diet mainly based upon marine mammals.

VI.  Convergent Evolution Among Marine Mammal Lineages The question of convergent evolution among marine mammal lineages (and even among echolocating mammals) has also been investigated by comparative genomics, in a manner similar to the killer whale analyses (Foote et al., 2015). The three main lineages of marine mammals, i.e., the cetaceans, pinnipeds and sirenians, each represents an independent “return” by a terrestrial mammal lineage into the marine environment resulting a triplicated evolutionary scale experiment of convergent evolution in mammals when subjected to a marine existence. Foote and coworkers (2015) sequenced and assembled the genome sequence from a killer whale, a bottlenose dolphin, a walrus (Odobenus rosmarus), and a West Indian manatee (Trichechus manatus latirostris). A comparative analysis of the protein-coding regions in these four genomes with terrestrial mammal genomes revealed a number of changes in the three marine mammal genomes that displayed signs consistent with positive selection. Approximately 1% of these changes were identified in two or more marine mammal lineages, suggesting convergent evolution among the three marine mammal lineages. It is worth noting that the analysis was conservative, i.e., very stringent in terms of what constituted a so-called convergent mutation. The inferred gene function of the regions that appeared subject to convergent positive selection included genes involved in bone formation, cardiac muscle development and blood coagulation; all traits which possibly could be important in terms of adapting to diving and a denser medium (i.e., water compared to air). An interesting outcome of the study was the observation that the rate of convergent positive selected substitutions was higher among the terrestrial mammal genomes relative to the rates observed among the marine mammal genomes. Our last example in this overview, will be of the apparent convergent evolution of echolocation in two very diverse and taxonomically divergent groups of mammals: bats and odontocetes. A fundamental question is whether such a complex trait could have evolved in a convergent manner due to similar selective pressures, i.e., a similar rationale for convergent evolution across different lineages of marine mammals as described above. In both bats and odontocetes, some species have evolved echolocation, which led Parker and colleagues (2013) to compare 2326 coding DNA sequences across 22 mammal species, including bats and odontocetes (the common bottlenose dolphin). The authors found strong support for convergence in the same genes and direction among echolocating bats and the dolphin, and to the exclusion of nonecholocating bats. The genes inferred as subjected to (negative and positive) selection included numerous genes linked to hearing or deafness, which were presumed to play a role in the evolution of echolocation. In addition, genes linked to vision also showed signs of convergent evolution. In general, the degree of convergence in many sensory genes was found to correlate with the inferred strength of natural selection.




Genetics and Genomics

VII.  A Final Note of Caution

See Also the Following Articles

The examples above have illustrated several uses of genetic and genomic analyses to elucidate the past and present status and evolution of marine mammals, both in terms of selection and subsequent adaptation as well as demographic changes in relation to diversification, climate change, and human exploitation. However, we would like to end on a note of caution. Genetic (including genomic) analysis has had a wide and fundamental effect upon the entire field of biology and medicine. The power of modern DNA-based analyses, coupled with genomic scale data and recently in silico inferences about gene function is truly impressive and has permeated biology and medicine over just a few decades. In the vast majority of studies, the reported results are essentially comprised of statistical significant correlations/signals detected using models of inference that are based upon highly simplistic assumptions about how populations, species and genes are structured and evolve. This is particularly true for difficult-to-study, nonmodel organisms such as marine mammals. The result is that most of the conclusions are more appropriately labeled as hypotheses, i.e., one (of several) possible explanations that are consistent with the findings of the particular study. Consequently, these hypotheses should ideally be subjected to subsequent rigorous and specific directed tests before the proposed explanation of the observed results is deemed to be correct. In many cases, such additional testing will require other experiments (e.g., controlled breeding or common garden experiments), which are difficult or impossible to conduct in marine mammals. In several cases, new experimental or analytical methods have significantly changed previous findings of earlier studies, which at the time of publication represented the state of the art. There are several notable examples, which were published in leading journals at the time. One older example was the finding that sperm whales were more closely related to baleen whales than other odontocetes (implying that baleen and not teeth is the ancestral character) which has since been proven incorrect (Cerchio and Tucker, 1998; Nikaido et  al., 2001). Another example is the estimation of prewhaling abundance of North Atlantic humpback whales at 265,000 humpback whales (Roman and Palumbi, 2003), which was vastly above the historic abundance at 25,000–40,000 inferred using other data sources and approaches. Subsequent data analyses and adjustments of mutation rates, by the same authors, yielded estimates at less than half the original estimate (Alter and Palumbi, 2009; Ruegg et al., 2013). The convergent evolution of echolocation among echolocating bats and the common bottlenose dolphin has been questioned by Thomas and Hahn (2015). Thomas and Hahn’s (2015) reanalysis revealed no excess convergence between the echolocating bats and the common bottlenose dolphin; they found that the degree of differentiation between these diverse taxa were well within expectations under a model of zero evolutionary convergence. In closing, the field of genetics (including genomics) has contributed substantially to our understanding and conservation of marine mammals. The extremely rapid advances of the field of genetics in general, and of genomics in particular, have brought several new and exciting hypotheses forward in terms of the ecology and evolution of marine mammals. However, living at the “cutting edge,” scientifically and experimentally, harbors the risk of prematurity—and only through the test of time with complementary data and analyses will we eventually be able to establish which of the new and exciting hypotheses emerging from the recent genomic studies are confirmed.

Genetics, Forensics n Genetics, Management

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G GENETICS, FORENSICS C. Scott Baker and Debbie Steel I. Introduction Molecular genetics provide a powerful tool for the conservation and management of cetaceans and other marine mammals—via the identification of products derived from hunting, strandings and fisheries bycatch (Baker and Palumbi, 1994; Dalebout et al., 2002; Tzika et al., 2010). Such products include soft tissue such as meat, organs, blubber, skin and blood, as well as teeth, bone, baleen, and hair. Although the species origins of these products may be impossible to determine on the basis of their appearance, they contain DNA that can be amplified, sequenced and compared to sequences from known specimens. With advances in molecular methods over the last two decades, DNA can now be recovered from almost any biological source, even products that have been preserved, cooked or canned. With a comprehensive reference library of homologous sequences, such as the control region or cytochrome b gene of the mitochondrial DNA (mtDNA), a product of unknown origin can be attributed in most cases to one of the approximately 90 accepted or proposed species of cetaceans. If a comprehensive archive of tissue is maintained as part of a regulated hunt or documented fisheries bycatch, it is also possible to trace the origins of a product to a specific individual by matching of nuclear DNA genotypes (Baker et al., 2010; Cipriano and Palumbi, 1999; Palsbøll et al., 2006). Although many of the applications of these methods are not intended for criminal prosecution, they share the common methodology of wildlife forensic genetics and the broader objectives of improving controls over trade and illegal, unreported and unregulated (IUU) exploitation in fisheries and wildlife (Baker, 2008). The forensic use of molecular genetic methods is of particular interest to the International Whaling Commission (IWC), as it attempts to develop a revised management scheme (RMS) for the regulation of any future commercial whaling, and to the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), if it is to implement a verifiable system for controlling trade in cetacean products. An important application of

forensic genetics has been to identify the species and, in some cases, geographic origins of whale, dolphin, and porpoise products sold in two countries with active commercial markets: Japan and the Republic of (South) Korea. The sale of protected species or populations (stocks) derived from IUU exploitation has been of particular concern (Baker et  al., 2000). Other applications include identifying stranded individuals and fisheries bycatch, particularly for poorly described species such as beaked whales (Dalebout et al., 1998; Thompson et al., 2012), and monitoring of trade in pinniped penises sold as aphrodisiacs (Malik et  al., 1997). As an alternative to onboard observers or self-reporting, molecular identification of species and capture-recapture analysis of DNA genotyping from individual products can also be used to estimate the true level of bycatch for some species sold in commercial markets (Baker, 2008).

II.  Molecular Taxonomy and Identification of Cetacean Species The methods for molecular identification of species in trade developed initially from basic research on species-level phylogenetic relationships and the genetic structure of populations (Baker and Palumbi, 1994; DeSalle and Birstein, 1996; Malik et al., 1997). Over the last decade, there has been an explosion of interest in the systematic application of these techniques to basic organismal taxonomy (Hebert et  al., 2003), including cetaceans (Ross et  al., 2003; Dalebout et al., 2004). Now referred to as “molecular taxonomy” or “DNA taxonomy,” the objective of identifying known species from a designated homologous gene sequence differs from the usual goal of molecular phylogenetics, which is more concerned with hierarchical relationships above the species level. For species identification of cetaceans and other animals, the molecular marker of choice has usually been mtDNA. In general, mtDNA offers two important advantages over nuclear genetic markers. First, because of its maternal inheritance and absence of recombination, the phylogenetic relationship of mtDNA sequences reflects the history of maternal lineages within a population or species (if hybridization is encountered, nuclear markers are required to identify the paternal species; see below). Second, all else being equal, the effective population size of mtDNA genomes is one-fourth that of autosomal nuclear genes and its rate of random genetic drift is proportionately greater. This results in more rapid differentiation of mtDNA lineages among populations, compared to nuclear genes, and consequently greater sensitivity in the detection of recent historical demographic or speciation events. The ability to detect population differentiation is also enhanced by the rapid pace of mtDNA evolution, which is generally estimated to be 5–10 times faster than nuclear coding DNA in most species of mammals. Although one approach to molecular taxonomy has advocated a universal “DNA barcode of life” for all animal species based on the mtDNA cytochrome-c-oxidase I (COI) gene (Hebert et al., 2003), it is not clear that this locus is the most sensitive or reliable for identification of cetaceans (Amaral et  al., 2007). Instead, species-level identification of marine mammals has relied primarily on the phylogenetic reconstruction of sequences from the mtDNA control region (sometimes referred to as the D-loop) or the cytochrome b gene. The control region of the mtDNA does not code for a protein or RNA and, in the absence of these constraints, accumulates mutational substitutions more rapidly than other regions. For this reason, it has become the marker of choice for most studies of the population structure of cetaceans and pinnipeds. The cytochrome b gene, a protein region of the mtDNA, has also been used widely for species-level phylogenetics (May-Collado and Agnarsson, 2006).