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A GENOTYPING ANALYSIS OF THE MAJOR HISTOCOMPATIBILITY COMPLEX IN TWO POLAR SPECIES: GENET IC DIVERSITY IN THE ARCTIC FOX AND SOUTHERN ELEPHANT SEAL BY KRYSTAAL MOONCHYLD MCCLAIN A Thesis Submitted to the Division of Natural Sciences New College of Florida In partial fulfillment of the requirements for the degree Bachelor of Arts in Conservation Biology Under the sponsorship of Diana Weber, Ph.D. Sarasota, Florida May, 2013
ii ACKNOWLEDGEMENTS First and foremost I would like to thank my committee. To Dr. Diana Weber, my thesis sponsor, your support and direction led to me Conservation Biology, and aided tremendously in the completion of this thesis. A special thank you to my committee members, Dr. Suzanne Sherman and Dr. Alfred Beulig, as well. I would like to thank Deborah Perez and Jennifer Shelton for the lab work they did on the arctic fox; without th ose sequences, I would have had to study a much less cute species (like the muskox). Additionally, I would like to thank John Scheinman and Matt Leslie for the lab work they did on the southern elephant seal; while not exactly cute, it was definitely an interesting species to study. Ha nnah E. Brown, thank you so very much for sticking by my side these past four years. What would we have done without each other? Through the ups and downs, I know I can always count on you, to be both supportive and childish. Seriously, LYLAS. Rachel Weis three semesters, and managed to have a wonderful time. Imagine all the hangovers and Maria Phillips, not sure if I should thank my big mouth or your crooked bangs for our nearly as fun. Thank you for being in the same boat as me all of fourth year, and for remind ing me that we can get through this. To Rachael Haensly, Kenny Lee, Madelaine Verbeek, Ben Reinhold, Tait Mandler, and I surely would have exploded. Finally, a huge thank you to my family, without whom I would not be here. Your support saying when I talk to you about my thesis. I love you.
iii TABLE OF CONTENTS Chapter Page ACKNOWLEDGEMENTS................................................................................................ii LIST OF TABLES............................................................................... ................................ v LIS T OF FIGURES............................................................................. ............................ ... v i ABBREVIATIONS & COMMON TERMS..................................... ............................... .v i i ABSTRACT........................ ........................................................................................ ... .. vii i CHAPTER 1 INTRODUCTION.............................................. .............................. ...... ... ....1 The Major Histocompatibility Complex ........ ................ ............................... ............2 Climate Change and the Immune System ....................... ............................... ......... 6 MHC and Disease in Polar Environments .............................. ....................... ..... ....7 The Arctic Fox ..................................................................................................... ..10 The Southern Elephant Seal ...................................................................................1 3 Thi s Study ..........................................................................................................1 6 References................................................................................................................... .1 8 CHAP TER 2 MAJOR HISTOCOMPATIBILITY COMPLEX DIVERSITY IN THE ARCTIC FOX................................................................................. ..........3 4 Introduction .................................................................................. ..........................3 5 Methods ..................................................................................................................3 7 Results .............................................................................................. ......................3 9 Discussion .............................................................................................................. 41 References........................................................................................... .........................4 3 CHAPTER 3 MAJOR HISTOCOMPATIBILITY COMPLEX DIVERSITY IN THE SOUTHERN ELEPHANT SEAL..................................................... .. ....... 63 Introduction .................................................................... ........................................ 64 Methods .................................................................................................................. 67 Results ..................................................................................... ...............................68 Discussion .............................................................................................................. 70 Referen ces..................................................................................... ...............................73
iv CHAPTER 4 CONCLUSIONS......................................................... ...............................96 References..... ............................................................................... ..............................101 APPENDIX A: NUCLEOTIDE SEQUENCES..............................................................105
v LIST OF TABLES CHAPTER 2 Table 1: Genetic Diversity Indices for DRB and DQB ............................ .........4 7 CHAPTER 3 Table 1: Locus Examined by Individuals ............................... .......................... 79 Table 2: Genetic Diversity Indices ........... ............................... ............................ 80
vi LIST OF FIGURES CHAPTER 1 Figure 1: MHC Diagram .....................................................................................2 6 Figure 2: Canid Phylogenetic Tree ...................... ...............................................2 7 Figure 3: Arctic Fox .............................................................................................2 8 Figure 4: Map of Arctic Fox Range ....................................................... .............2 9 Figure 5: Arctic Sea Ice Extent in 1979 versus 2012 ......................................... 30 Figure 6: Competition with Red Fox ...................................................... ............31 Figure 7: Southern Elephant Seal ....... ...............................................................3 2 Figure 8: Map of Southern Elephant Seal Range ... ............................... ...........3 3 CHAPTER 2 Figure 1: Maps of Arctic Fox Range .................................................. ................4 8 Figure 2: Sequence Chromatogram of Data ...................................................... 50 Figure 3: Amino Acid Variation in DRB and DQB ............ ..............................51 Figure 4: Nucleotide Variation in DRB and DQB ............................................. 54 CHAPTER 3 Figure 1: Male Southern Elephant Seal .............................. ...............................82 Figure 2: Southern Elephant Seal Range Map .......... ............................... ........83 Figure 3: Sequence Chromatogram of Data ....................... ...............................84 Figure 4: Nucleotide Variation in DQA DQB and DRB .................................. 85 CHAPTER 4 Figure 1: Simplified Arctic Food Web .................... ............................... ..........103 Figure 2: Simplified Antarctic Marine Food Web ..... ............................... ......104
vii ABBREVIATIONS AND COMMON TERMS Allele Different form of a gene Locus (loci) Place where a particular gene resides in a genome Genotype T he alleles at linked genes on a given copy of a chromosome Heterozygosity T wo alleles at a locus that are different Homozygosity T wo alleles at a locus that are identical Linkage Disequilibrium T he statistical association of genes at different loci Allozyme E nzyme coded for by a gene that has different allelic forms Microsatellite Highly variable locus composed of short, tandem repeats of two to six nucleotides Mitochondrial DNA D NA in the mitchondrion, inherited maternally Single nucleotide polymorphism (SNP) A nucleotide position that is variable in a population Dispersal Active or passive movement of an organism from an ancestral center of origin into new areas Emigration Movement of individuals out of a pop ulation Immigration Movement of individuals into a population Intraspecific Within species (arctic fox vs arctic fox) Interspecific Between species (arctic fox vs red fox) Disease Abnormal condition that affects the body of an organism Pathogen Infective microorganism that causes disease in its host Parasite Microorganism that benefits at the expense of its host DRB Specific locus in class II of the MHC DQB Specific locus in class II of the MHC DQA Specific locus in class II of the MHC ACC Antarctic Circumpolar Current APF Antarctic Polar Front CNV Copy Number Variation ENSO El Ni o Southern Oscillation MHC Major Histocompatibility Complex PBR Peptide Binding Region SAF Sub Antarctic Front SES Southern Elephant Seal Definitions from: PW Hedrick. (2011). Genetics of Populations Sudbury, Massachusetts: Jones and Bartlett Publishers.
viii A GENOTYPING ANALYSIS OF THE MAJOR HISTCOMPATIBILITY COMPLEX IN TWO POLAR SEPCIES: GENETIC DIVERSITY IN THE ARCTIC FOX AND SOUTHERN ELEP HANT SEAL Krystaal Moonchyld McClain New College of Florida, 2013 ABSTRACT The major histocompatibility complex (MHC) is part of the immune system in all vertebrates, potentially providing protection from a wide range of pathogens, and thus increasing in dividual fitness. The insight into species ability for long term survi val is key for conservation as populations with high diversity in the immune system may have increased survival to novel pathogens and changing environments. Conversely, when diversity i s lost, the ability of a species to cope with new diseases and parasites could be reduced resulting in lower survival rates and increased infection. Historically, extreme cold temperatures in polar environments have prevented an influx of pathogens, and th us species in thes e regions have maintained a low pathogen prevalence and load. Currently, both polar environments are warming and the environme nt is changing at record levels, a phenomena especially pronounced in the Arctic. To assess potential vulnerabil ity of polar species to disease exposure I examined genetic variation in the MHC from two polar carnivore species, the arctic fox and t he southern elephant seal, and found both had moderate levels of genetic diversity. The arctic fox showed high genotypic diversity, high heterozygosity, and a large number of polymorphic sites for both loci, DRB and DQB In contrast, the southern elephant seal had low to mod erate nucleotide diversity and all loci had l ower observed heterozygosity tha n expected though the n umber of alleles was high
ix especially for DRB This is notable when compared with its sister taxa, the northern elephant seal, which has almost no genetic variability. As the climate changes, a healthy immune system may increase population viability of the se two polar species. It is important to understand the genetic dynamics of a species to infer its possible response to climate change and shifts in the environment, as this will increase the effectiveness of conservation efforts in a changing world. ____ ___________________ Diana Weber, Ph. D.
1 CHAPTER 1: Introduction
2 The Major Histocompatibility Complex Genetics is a very important tool in conservation biology, providing different types of genetic data to investigate a variety of questions. Markers such as single nucleotide polymorph isms (SNPs), microsatellites, and mitochondrial DNA (mtDNA) allow for the examination of population structure, paternity or identity analysis, inter and intra species relationships, forensic analysis in wild and captive populations. In contrast, non neutr al genes can provide insight into the evolutionary and adaptive potential of a species or population (Sommer 2005). As an example, the major histocompatibility complex (MHC) has been used in conservation efforts (Acevedo Whitehouse & Cunningham 2006) becau se of its important role in the immune system in all vertebrates (Kumanovics et al. 2003; Piertney & Oliver 2006). The MHC is a multi gene complex, divided into three sections: Class I, II, and III (Fig. 1a). Classes I and II process and destroy peptides, while the function of Class III is less understood, although it may have immunological importance (Kumanovics et al. 2003). Class III, generally, is between classes I and II. For class I and II, peptides are generated from pathogenic fragments inside anti gen presenting cells (Klein & Sato 2000). These peptides are displayed to T cells that process and mount an immune response in response to the peptides (Klein & Sato 2000; Kumanovics et al. 2003) (Fig. 1b). CD4+ helper T cells recognize the Class II molecu le with its associated antigenic peptide so that when a foreign peptide is presented, the T cells initiate a response and regulate other lymphocytes (Fig. 1b) (Rammensee et al. 1995). The manner in which class I molecules present peptides is indicative of a response to viruses (Sommer 2005; Piertney & Oliver 2006). In contrast, class II molecules function in a way to indicate defenses against
3 extracellular parasites and pathogens (Sommer 2005; Piertney & Oliver 2006). MHC is conserved in all mammals and has the highest levels of variation found in any mammalian gene (Parham & Ohta 1996, Hughes & Yeager 1998; Trowsdale 2011), potentially providing protection from a wide range of pathogens (Piertney & Oliver 2006; Kamath & Getz 2011; Lenz 2011). This is import ant because when diversity is lost, the ability of a species to cope with new diseases and parasites may be reduced (Sommer 2005; Goda et al. 2010) potentially resulting in lower survival rates and increased severity of infection (Acevedo Whitehouse & Duf fus 2009). Investigating levels of diversity in these genes can provide insight into the immunological fitness of a species and thus indicate the potential ability for long term survival (Acevedo Whitehouse & Cunningham 2006; Ujvari & Belov 2011) an impo rtant consequence for conservation implications. The conservation benefit would be that a population with high diversity in the immune system might have increased survival to novel pathogens and possibly to changing environments (Sommer 2005; Ujvari & Belo v 2011). The MHC is under heavy selective pressures, probably to maintain immune function (Hedrick & Kim 2000). Pathogen prevalence may heighten selection pressure in the MHC, thereby increasing genetic variability in the MHC (Paterson et al. 1998; Dionne et al. 2007; Axtner & Sommer 2007). Balancing selection has been suggested as a mechanism to maintain high MHC variation, but which type(s) involved is under debate (Hedrick & Kim 2000; Sommer 2005; Piertney & Oliver 2006; Kamath & Getz 2011; Ujvari & Bel ov 2011). Three main types of balancing selection are important for MHC in parasite resistance: heterozygote advantage, frequency dependent selection, and variable selection in time and space
4 (Hedrick & Kim 2000). The heterozygote advantage hypothesis prop oses that because heterozygous individuals have two different alleles, they can identify multiple suites of parasites, i.e., one per each type of allele, and thus, are potentially more fit than their homozygous counterparts. This is overdominant selection and two types have been proposed: i ) symmetric overdominance, where all heterozygotes have essentially equal advantage over homozygotes and ii ) divergent allele advantage (Sommer 2005). This latter overdominance model argues that the more differences betwe en the alleles in heterozygotes, the greater the advantage those heterozygotes have over homozygotes and other, more similar, heterozygotes. The second type of balancing selection, frequency dependent selection, suggests that an allele is favored at one fr equency, but not another (Hedrick & Kim 2000; Sommer 2005). For example, a rare allele that is more resistant to a common parasite will sweep through the population, but as the rare allele becomes common, it loses its advantage as the parasite adapts, pote ntially causing a new rare allele to repeat the process. A third type of selection is variable selection in time and space, which has one allele being advantageous to one population or generation but not another based on the parasite and environmental dyna mics of the specific habitat (Hedrick & Kim 2000). None of these hypotheses is mutually exclusive, and the use of models, which have a predominant role in a particular instance or situation, makes it difficult to determine which process is key (Hedrick & K im 2000; Sommer 2005; cf Arkush et al. 2002 and Bryja et al. 2007). Field studies are beginning to focus on the causes of balancing selection and high levels of MHC diversity in wild populations (review in Sommer 2005). Arkush et al. (2002) determined th at levels of heterozygosity and outbreeding could be used to indicate
5 resistance to certain pathogens, with higher levels of either conferring greater protection, providing support for the heterozygote advantage hypothesis. Heterozygotes had reduced parasi te burden and lower chances of co infection in water voles ( Arvicola terrestris) (Oliver et al. 2009). In support of these studies, MHC diversity increased with pathogen presence in three spined sticklebacks ( Gasterosteus aculeatus ) (Wegner et al. 2003). I n Soay sheep (Ovies aries), specific alleles were associated with survivorship and resistance to nematodes as opposed to heterozygosity (Paterson et al. 1998), potentially showing frequency dependent selection. The same conclusion was drawn in a study of b ank voles ( Clethrionomys glareolus) and nematode resistance (Axtner & Sommer 2007), and in a study of nematodes in the yellow necked mouse ( Apodemus flavicollis ) (Meyer Lucht & Sommer 2005). In the Malagasy mouse lemur ( Microcebus murinus ) a common allele was often associated with infection (Schad et al. 2005). Although the mechanism that maintains MHC diversity is still unknown, these studies show that disease is one factor that influences the levels of variability witnessed in the MHC. These studies direc tly and indirectly show that some form of MHC diversity in the population assisted in higher levels of resistance to specific pathogens. The Tasmanian devil ( Sarcophilus harrisii) may face extinction as a result of Devil Facial Tumor Disease (DFTD), a tra nsmissible cancer that emerged 16 years ago (Siddle et al. 2013). One hundred percent of infected individuals die from the disease, as the tumors are not rejected from the host. A recent study found that down regulation of genes that assist in the function ing of class I of the MHC aid in the spread of this disease, but MHC positive DFTD cells may provide a vaccine.
6 Climate Change and the Immune System Climatic change will result in ecosystem changes, and as parasites are part of the ecosystem, their distr ibutions and patterns will change (Polley & Thompson 2009), because changing temperature and moisture levels have a large influence on pathogens (ACIA 2005; Bradley et al. 2005; Parkinson & Butler 2005; Kutz et al. 2009). Higher temperatures benefit many p arasites by shortening development time, providing sufficient time to progress through the life cycle, and increasing survival and transmission (Bradley et al. 2005; Kutz et al. 2009; Hueffer et al. 2011). Insect borne diseases can be temperature limited a nd therefore will potentially increase with global warming (ACIA 2005; Bradley et al. 2005). Thus, warming temperatures caused by climate change can indirectly increase susceptibility to disease. As temperatures are increasing, range expansions are occurri ng and are expected to continue at a greatly increased rate. This influx of new species brings both free living agents of disease as well as disease hosts into areas not inhabited before or at minimal levels (ACIA 2005; Bradley et al. 2005; Acevedo Whiteho use & Duffus 2009; Kutz et al. 2009). Precipitation patterns are expected to change with climate change by showing more extremes, i.e., more severe droughts during part of the year and increased precipitation at other times (Polley & Thompson 2009; Hueffer et al. 2011). Droughts will decrease survival of some pathogens, while increased precipitation will benefit some disease populations (Bradley et al. 2005; Kutz et al. 2009). The exact patterns of the spread of disease and it s prevalence are unpredictable; but overall disease diversity, density, and transmission is expected to increase in polar environments as they warm (Bradley et al. 2005; Kutz et al. 2009).
7 A diverse and functional immune system for a species is important with the emergence and spread o f new diseases from climate change and the increase of new stressors, which could negatively affect the species (Acevedo Whitehouse & Duffus 2009). Direct and indirect consequences of climate change include habitat loss and alteration, invasion by new spec ies, increased competitive interactions, and loss of prey species (Crowl et al. 2008; Acevedo Whitehouse & Duffus 2009). These changes can increase stress levels, in turn reducing immune system function and thus potentially decrease reproductive success an d survival (Acevedo Whitehouse & Duffus 2009). Loss of prey species can lead to malnutrition (Henden et al. 2009), which is a major cause of immune deficiency in the world (Katona & Katona Apte 2008). While the direct effects of climate change on the healt h of species are often obvious, indirect effects can work in conjunction with other factors to reduce the health of the immune system. For example, a loss of habitat may reduce gene flow of a population, causing a loss of alleles and potentially affect imm une system function at a later date (Radwan et al. 2009). MHC and Disease in Polar Environments Species richness has been shown to negatively associate with latitude, in that the diversity and abundance of species decreases toward the poles (Pianka 1966 ; Guernier et al. 2004). Arctic pathogens, such as helminth parasites and vector borne diseases, have been limited in the past by short summers and cold temperatures that reduce the life cycle and transmission time for the pathogen (Halvorsen & Bye 1999; H arvell et al. 2002; Kutz et al. 2004; Kutz et al. 2005; Hueffer et al. 2011). It has been shown that in salmon, MHC diversity can increase with increasing environmental temperatures, a possible response to
8 pathogen pressures (Dionne et al. 2007). These gra dients suggest that over evolutionarily time polar parasite diversity may have been minimal (Halvorsen & Bye 1999), along with host MHC variation. However, climate change appears to be driving the emergence of Arctic disease by increasing the length of the growing season, expanding ranges of hosts and parasites, and creating opportunities for human exploration (Kutz et al. 2004; Polley & Thompson 2009; Hueffer et al. 2011). Increased contact with humans could be problematic for polar wildlife because they c an be exposed to an increasing number and diversity of pathogens (Eberhardt et al. 1982; Kutz et al. 2004; Acevedo Whitehouse & Duffus 2009; Hueffer et al. 2011). A sentinel location is one that can provide warning for the future of other habitats (Stroev e et al. 2007) The Ar ctic can be considered a sentinel location for studies on the effect of climate change and disease because the area is remote and already experiencing the impacts of climate change (White et al. 2013). Unfortunately, limited studies h ave been conducted on MHC diversity in Arctic species ( cf. Olsen et al. 1998; Ploshnitsa et al. 2012; Weber et al. in press). Studies of subpolar species may provide insight as to expected levels of diversity in their polar counterparts. Diversity in the M HC of the gray wolf ( Canis lupus ), a subpolar canid species, is rather high, although populations with higher hunting pressures have less diversity (Seddon & Ellegren 2002; Kennedy et al. 2007). Brown bears ( Ursos arctos ) from Japan, Siberia, and the Alask an Kodiak showed high levels of polymorphism (Goda et al. 2010), while Canadian polar bears ( Ursus maritimus ) showed low levels of genetic diversity (Weber et al. in press). MHC studies have been conducted on the Arctic charr ( Salvelinus alpinus ), but did not focus on genetic diversity, although it was found that kin discrimination occurred, a potential mechanism
9 to increase diversity (Olsen et al. 1998). Only one study has been published on MHC in the arctic fox ( Vulpes lagopus ) (Ploshnitsa et al. 2012); however, canid MHC has been well studied (Seddon & Ellegren 2002; Aguilar et al. 2004; Kennedy et al. 2007), and the species can be compared (Fig. 2). Ploshnitsa et al. (2012) examined the genetic diversity in MHC loci, DRB and DQB from island [Bering and Mednyi Islands, part of the Commander Islands] and mainland [Siberia and Alaska] subpopulations of the arctic fox and found minimal allelic and gene diversity in the island subpopulations, but much higher levels in the mainland subpopulations, e.g., 27 of the 47 mainland foxes sampled were different. In comparison, the temperate Channel Island fox ( Urocyon littoralis ) found on the Channel Islands off California, USA was monomorphic in all other areas of the genome studied but demonstrated variability in th e MHC (Aguilar et al. 2004). Antarctic seals have been previously studied in DOA and DQA in the MHC. Lehman et al. (2004) found that heterozygosity and allelic diversity were extremely high in Crabeater seals ( Lobodon carcinophagus ), while diversity was m oderately high in Weddell (89% observed heterozygosity) ( Leptonychotes weddellii ) and Ross (21% observed heterozygosity) ( Ommatophoca rossii ) seals, and monomorphic in the Leopard seal ( Hydurga leptonyx ). Single samples from Ross, Weddell, and Leopard seal s were analyzed at DOA with each species conferring different alleles (Decker et al. 2002). Later analysis of the DOA compared Leopard, Weddell, northern elephant ( Mirounga angustirostris NES) and southern elephant ( Mirounga leonina SES) seals and found low levels of interspecific diversity, indicating the importance of the locus in the immune system (Soll et al. 2005). A study of the sister taxa, the NES, showed very low to no
10 genetic diversity in the different genomic marker studies (Bonnell & Selander 1974; Hoelzel et al. 1993; Garza 1998; Lehman et al. 1998, Weber et al. 2000; Lehman & Stewart 2002; Weber 2003; Weber et al. 2004) with low variation in the MHC loci surveyed (Weber et al. 2004). Low diversity found in the NES was caused by multiple hist orical bottlenecks both from commercial sealing and indigenous hunting (Weber et al. 2000). Initial studies of the MHC in the southern elephant seal showed low levels of diversity (Slade 1992), while later studies indicate high levels of allelic diversity in DQB (Hoelzel et al. 1999). The Arctic Fox The arctic fox (Fig. 3) is a circumpolar species found in the northern latitudes of North America and Eurasia (Fig. 4) (Geffen et al. 2007). It has close relatives with other foxes in the region, e.g., red ( Vu lpes vulpes ), swift ( Vulpes velox ), and kit ( Vulpes macrotis ) (Geffen et al. 2007; Szuma 2011). Eight subspecies of the arctic fox have been recognized based on geographic location, but a lack of genetic differentiation between the subpopulations puts this delineation into contention (Dalen et al. 2005; Szuma 2011). Tundra and pack ice are the typical habitat for the Arctic fox and ice connects many subpopulations (Carmichael et al. 2007; Geffen et al. 2007) facilitating gene flow. Studies on gene flow in t he arctic fox have used the mtDNA control region and microsatellites (Dalen et al. 2006; Geffen et al. 2007; Noren et al. 2011). Geffen et al. (2007) used mitochondrial DNA and microsatellites from 20 different populations to determine that sea ice distrib ution provided a better explanation for the minimal genetic differentiation between subpopulations than ecotype differences (Dalen et al. 2005). Using
11 microsatellites in seven loci for 1834 individuals, Noren et al. (2011) found that ecotype designation ha d no impact on genetic differences and that differentiation increased with distance. Arctic foxes in Iceland and Scandinavia, two relatively ice free islands, were genetically distinct from the rest of the Arctic (Noren et al. 2011). Gene flow is likely me diated by long distance movements, which are presumably triggered by prey population crashes, notably lemmings ( Lemmus lemmus ) (Carmichael et al. 2007; Noren et al. 2011). Threats to Arctic Fox Survival Arctic fox populations are now globally stable desp ite intense fur hunting in the early twentieth century (Elmhagen et al. 2000; Dalen et al. 2006; Nystrom et al. 2006). However, climate warming is expected to alter sea ice levels (Fig. 5) impacting the arctic species in a myriad of ways (ACIA 2005; Kutz e t al. 2009; Hof et al. 2012) and as temperatures rise, so do threats to the arctic fox (Hof et al. 2012). Temperature has been shown to i) limit arctic fox distribution, ii ) increase interspecific competition and predation by the red fox (Fig. 6), and iii ) reduce lemming abundance (Hof et al. 2012). Increasing environmental temperatures are expected to shift spring break up earlier in the season and cause the ice freeze up to occur later, thus shortening the length of time ice connects the arctic fox subp opulations (Hueffer et al. 2011) and ultimately limiting its distribution. Arctic foxes utilize sea ice as bridges to other populations (Henttonen et al. 2001; Geffen et al. 2007; Noren et al. 2011), with areas that lack pack ice being more genetically dis tinct than the rest of the population (Geffen et al. 2007; Noren et al. 2011). Though reductions in sea ice will isolate some high Arctic islands
12 from invading species; it will also prevent movement between Arctic fox subpopulations with possible genetic c onsequences. Red foxes are expected to expand their range northward as temperatures rise (Hof et al. 2012) potentially limiting the range of the arctic fox, as it is an inferior competitor to the red fox for common prey, e.g. lemmings and voles ( Microtus rossiaemeridionalis ) (Hersteinsson & MacDonald 1992; Tannerfeldt et al. 2002; Killengreen et al. 2007). Competition between the two fox species limits the range of the arctic fox (Hersteinsson & MacDonald 1992). Interspecific competition between the two fo x species is a serious threat because the red fox is a larger more powerful competitor and predator (Tannerfeldt et al. 2002; Pamperin et al. 2006; cf. Gallant et al. 2012). Aggressive interactions culminating in the chasing and killing of arctic foxes occ urred in Scandinavia (Fig. 6) (Frafjord et al. 1989). Arctic foxes are divided into two ecotypes: coastal and inland, with different sources of food. The major prey for inland arctic foxes, i.e., lemmings and voles, need cold stable winters to survive T herefore, prey population sizes could decrease with increasing environmental temperatures (Killengreen et al. 2007). This will act as an additional stressor for inland arctic foxes that depend primarily on small mammals for survival (Killengreen et al. 200 7). A decline in lemming populations has already been observed in some areas, with a consequent reduction in arctic fox reproduction (Schmidt et al. 2012). The distribution and residency period of seabirds, a major source of food for the coastal arctic fox is expected to change as the climate warms (ACIA 2005). Unpredictable shifts and loss of food source may result in lower pup survival and reduced fitness (Roth 2003).
13 Unlike temperate species, arctic species experience range expansions during glacial p eriods, and contractions during interglacials (Dalen et al. 2007). Studies of ancient samples indicate that the Icelandic arctic fox subpopulation had minimal genetic diversity before the Little Ice Age sea ice expansion (Mellows et al. 2012). After the La st Glacial Maximum [approximately 26,000 20,000 years ago], southern populations went extinct, as the arctic fox seemed unable to track its habitat (Dalen et al. 2007). Threatened by predator invasion, the arctic fox may become an imperiled species as los s of connectivity increases from sea ice reduction and potential fluctuations in prey abundance occur. The arctic fox is finely adjusted to a very specific habitat, which climate warming is putting at risk. The Southern Elephant Seal The southern elepha nt seal (Fig. 7) is found circumpolar on most of the sub Antarctic islands (King 1983) (Fig. 8) with hauling out colonies for breeding and molting on the islands of Heard, Kerguelen, South Georgia, and Macquarie and on the Peninsula Valdes, Argentina (McMahon et al. 2005). The total population is estimated at 739,000; South Georgia accounts for over fifty percent of the population, followed by Isles Kerguelen with 29% and Macquarie Island with 10%. Marion Island is a small part of the Isles Kergue len stock. The five stocks listed above are genetically differentiated, with limited gene flow between subpopulations (Slade 1998; Hoelzel et al. 2001; Fabiani et al. 2003). Genetic variability within the southern elephant seal is consistent with levels f ound in other large mammal populations (Hoelzel et al. 1993; Slade et al. 1998). Nuclear
14 levels of diversity are high in the South Georgia stock (Hoelzel et al. 2001), with population diversity levels similar to those found in model species, such as the hu man and mouse (Slade et al. 1998). Mitochondrial DNA sequences show adequate levels of variation in the South Georgia and Heard Island stocks, also in part of the Isles Kerguelen stock, but much lower diversity in the Peninsula Valdes stock (Hoelzel et al. 1993; Slade et al. 1998; Hoelzel et al. 2001). Harem breeding in conjunction with site fidelity, as observed in the southern elephant seal can result in non random mating (Fabiani et al. 2006). Studies of female kinship (Fabiani et al. 2006), nuclear gen e flow (Fabiani et al. 2003), and mtDNA (Hoelzel et al. 2001) detect a structure indicative of male mediated dispersal. Data shows that, as a species, levels of diversity are indicative of a healthy population (Slade et al. 1998). Threats to Southern Elep hant Seal Survival The southern elephant seal population has rebounded since hunting pressures t hroughout the 18 th and 19 th centuries, with the exception of Marion and Macquarie Islands (McCann 1980; McMahon et al. 2005). Southern elephant seals were hunt ed for their blubber (McCann 1980; Laws 1994). Genetic data collected from Heard Island indicate that the Isle Kerguelen stock may have sufficient genetic diversity (Slade et al. 1998; Hoelzel et al. 2001). However, the drastic decline [from 3850 before th e 1970s to 2131 in the 2000s, a 45% decline] witnessed on Marion Island (McMahon et al. 2005) may indicate that genetic diversity in this subpopulation is reduced, especially considering the lack of genetic diversity in the NES following a similar bottlene ck [a severe reduction in population size] (Weber et al. 2004). There are many hypotheses to
15 explain the regional variation in population success [lack of males, pandemic disease, loss of prey species, predation on juveniles, competition with fisheries and other species], but the most likely explanation is environmental change (McMahon et al. 2005). Southern elephant seals show fidelity to feeding sites, causing seasonal variability in diet, primarily due to prey distribution (Bradshaw 2003). This fidelity to feeding sites could prove problematic if fish move out of seal feeding sites, particularly as female seals have more specific prey choices than males (Lewis et al. 2006). Lack of prey will likely result in lower levels of pup survival because not only pups will not have food, but also mothers will be unable to provide as much energy to pups before they are born or during the nursing time (McMahon & Burton 2005). Continual levels of low pup survival will eventually cause population declines. Sea ice play s a major role in the Southern Ocean ecosystem, and is expected to decline as the climate warms (McMahon & Burton 2005; Parmesan 2006). Primary production will decline because abundance of ice obligate algae will decline, reducing a vital food source to kr ill, which itself is an important food source (Parmesan 2006). As top predators, southern elephant seals consume enormous amounts of fish and squid, both in the open ocean and on the continental shelf (Boyd & Arnbom 1991; Bradshaw et al. 2003). Santos et a l. (2001) estimate that the y consume at least 4.5 million tons of cephalopods per year. Being a global phenomenon, t he El Ni o Southern Oscillation (ENSO) can affect food sources becaus e changes in the vertical water temperature gradient can determine wher e prey is located (McMahon & Burton 2005; McMahon et al. 2005; Learmonth et al. 2006; Parmesan 2006). Shifts in fish communities have already been documented (Parmesan 2006) and temperature is one determinant of prey
16 assemblage, which could result in the s outhern elephant seal being out of synchrony with its prey ( cf Parmesan 2006). Climate change will further add to the physiological stress of the Marion Island population as it already has lost genetic variability needed for potential changes in the envi ronment. Shifts in sea ice and ENSO that result in the movement of prey species and/or the reduction in prey population size will only increase risk for this species. The additional consideration of a potentially reduced immune system places the survival o f the population, in light of these climatic changes, in jeopardy. This Study As the basis of all life, genetics plays a role that is often minimized in conservation. Examination of the genetic diversity in populations provides copious information that cannot always be observed through other methods of study (Frankham 2003). The MHC has an important role in conservation because of its functional importance for the immune system (Acevedo Whitehouse & Cunningham 2006). Functionally important regions of the genome have significance for the evolutionary potential of a species (Acevedo Whitehouse & Cunningham 2006). Genetic studies and the subsequent responses by a species can provide insight into their potential survival as the climate changes. Not only can polar environments act as sentinels, but also species higher up in the trophic pyramid are often used as sentinels because they require more resources [habitat, food, etc.] from the ecosystem (Aguirre 2004). The arctic fox and southern elephant seal are tw o carnivorous polar species at the top of their respective food chains. Both face
17 impending threats from climate change, such as loss of habitat, prey, and the increase in pathogen prevalence. Studying the diversity of the MHC in these two species adds to the genetic background information, which is lacking and needed for conservation efforts to protect these species in the face of global warming. This thesis examines MHC class II loci ( DQA DQB DRB ) for two polar species, the Svalbard population of the ar ctic fox and the Marion Island population of the southern elephant seal to investigate the levels of genetic diversity in two species that have experienced human caused impacts historically and habitat/prey degradation currently.
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26 (a) (b) Figure 1. Diagrams of the major histocompatibility complex in humans. The region is called the HLA in humans even though it is the same as the M HC. (b) Antigen processing in class II of the major histocompa tibility complex. (Taken from K l e in & Sato 2000).
27 Figure 2. Phylogenetic tree of canid species created from ~15kb of exon and intron sequence. The arctic fox is at the very top, NES, the sister taxa of the southern elephant seal, is the second to last species listed on the tree. The southern elephant seal is closely related to canids as shown above (Taken from Lindblad Toh et al. 2005).
28 Figure 3. Photo of arctic fox pups in both color morphs inland foxes are usually white, coastal foxes brown to aid in camouflage with the environment. (Taken from Seth Gordon http://www.zooborns.com/zooborns/2010/06/arctic fox pup pileon.html)
29 Figure 4. Map of arctic fox range, highlighted in yellow. Svalba rd circled in red. (Taken from IUCN http://maps.iucnredlist.org/map.html?id=899 ).
30 Figure 5. Arctic sea ice extent in September 1979 and September 2012. Sea ice has declined 7.8% per decade bet ween 1953 & 2006 (Stroeve et al. 2007). (Taken from http://epa.gov/climatechange/science/indicators/snow ice/sea ice.html )
31 Figure 6. Evidence of interspecific competiti on, red fox carrying away the arctic fox it killed (Taken from Pamperin et al. 2006).
32 Figure 7. Southern elephant seal pup sitting on its mother, surrounded by other lounging seals. (Taken from Des & Jen Bartlett via National Geographic http://travel.nationalgeographic.com/travel/countries/argentina photos/#/elephant seal pup_6611_600x450.jpg )
33 Figure 8. Map of islands use d by the southern elephant seal A larger black circle indicates a larger stock. Marion Island is circled. (Taken from: http://www.wildlifeextra.com/go/news/seal migration009.html#cr)
34 CHAPTER 2: Major Histocompatibility Complex Diversity in the Arctic Fox Abstract The major histocompatibility complex (MHC) plays an important role in immune function, with higher levels of diversity increasing the ability of an individual to initiate an immune response to novel pathogens. Warming in the Arct ic will increase the hospitability of the environment to dise ase and competitors, as well as reducing the amount of usable habitat for Arctic species. The arctic fox is a circumpolar species with little genetic differentiation as a result of the continenta l connectivity provided by sea ice. Climate change threatens the arctic fox, but high levels of MHC diversity could mediate some of the stress. This study examines genotypic diversity of the Svalbard arctic fox in two MHC class II loci, DRB and DQB The en tire sampled population was heterozygous at both loci, with some individuals showing copy number variation (CNV), implying a potential large pathogenic repertoire.
35 Introduction Arctic foxes ( Vulpes lagopus ) are opportunists (generalists) with two distinct ecotypes: coastal and inland (Fuglei & Ims 2008; Noren et al. 2011). Coastal foxes are found in Greenland, Svalbard, and Iceland, along with smaller High Arctic islands [Jan Mayen Island, Aleutian Islands, and the numerous islands off the northern coast of Canada] (Fig. 1a). Coastal subpopulations express the blue color morph and inland foxes express the white color morph (Noren et al. 2011). Inland foxes are established primarily in North America, eastern Greenland, Fennoscandia, and Siberia. Coastal areas are able to support a higher number of arctic foxes because food, e.g., seabirds, seal carcasses, and marine invertebrates, are more plentiful and reliable than food (e.g., lemmings and carrion) used by inland foxes. This food disparity results in a lowe r number of inland dens (Eide et al. 2012; Dalen et al. 2005; Noren et al. 2011). Though inland arctic fox adults sometimes remain in areas when food availability is low (Strand et al. 2000), this group of foxes tend to disperse long distances if food reso urces become too scarce for extended time periods (Noren et al. 2011). The two ecotypes have different reproductive strategies based on food availability (Angerbjorn et al. 2004). Coastal foxes reproduce once annually, with five pups per litter, because they have more stable and consistent food resources. In comparison, during surplus years the inland ecotype has large litters, up to 19 pups, but will forego reproduction when there is greater food insecurity. Juvenile foxes leave the den during the fall o r winter of their first year and show dispersal that is slightly male biased (Strand et al. 2000; Ehrich et al. 2012). Svalbard is a high Arctic island (Fig. 1b) located north of the Barents Sea and
36 south of the Arctic Ocean (Fig. 1c) and is part of Norwa y. Svalbard has an important connectivity role for arctic foxes during the winter, allowing immigration from both Russia and North America (Figure 1) (Noren et al. 2011). The Svalbard foxes show less emigration suggesting local adaptation to the coastal en vironment has an important role and is being maintained for this subpopulation (Noren et al. 2011). If immigration is more prominent in this subpopulation, as is suggested by the larger than average litter sizes (Prestrud & Nilssen 1992 in Noren et al. 201 1) and higher proportion of white foxes compared to other coastal populations (Vibe 1967 in Noren et al. 2011), then the corresponding influx of new individuals may introduce and increase the prevalence of pathogens (Noren et al. 2011). A taeniid tapeworm ( Echinococcus multilocularis ) was reported for the first time in Svalbard in 2001, and was likely introduced through the natural migratory movements of the arctic fox from Siberia (Henttonen et al. 2001). Arctic foxes from Russia, Alaska, Canada and Greenl and have been infected with rabies (Mansfield et al. 2006). When the rabies isolates were sequenced and analyzed, it was found that Greenland, Canada, and Alaska rabies grouped together, indicating movement across borders. Loss of breeding individuals, whe ther through disease or other factors, can alter gene flow. Harvest by humans is still permitted on the island, and may have a disrupting effect on the spread of genes, as indicated by genetic differentiation between the un harvested region of Svalbard [Ho rnsund] and the rest of the harvested island (Ehrich et al. 2012). Previous genetic studies of the arctic fox indicate a well connected population with little genetic differentiation except on ice free islands (Geffen et al. 2007; Noren et al. 2011). A stu dy of ancient DNA reveals that southern populations went extinct as the
37 climate warmed after the Last Glacial Maximum [~20,000 years ago], and haplotype diversity declined (Dalen et al. 2007). The major histocompatibility complex (MHC) is a multi gene comp lex involved in the immune system, showing the highest levels of variation of any mammalian gene (Parham & Ohta 1996; Hughes & Yeager 1998). High variability in the MHC could increase the pathogenic repertoire of a species, and possibly increase fitness (P iertney & Oliver 2006; Kamath & Getz 2011). Ploshnitsa et al. (2012) surveyed 47 mainland foxes from Siberia and the North Shore of Alaska in two MHC loci, DQB and DRB and found nine alleles in DRB and 11 in DQB Levels of observed heterozygosity were hig her than expected in all instances except Siberian DRB which was only 2% lower than expected. Here, I present levels of genetic diversity found in DRB and DQB genotypes of the Svalbard arctic fox, and discuss potential impacts of MHC diversity in the face of impending Arctic warming. Methods Arctic fox tissue samples from Svalbard were provided by the Norwegian Polar Institute, Troms, Norway ( E. Fuglei) and all subsequent lab work was performed by Dr. Diana Weber and her team ( cf. Weber et al. 2013) in the following protocols. DNA was extracted (DNeasy tissue kit, Qiagen) and the resulting template was processed for all individuals and both loci with puRe Taq Ready To Go PCR beads (GE Healthcare) [25 l PCR reaction volume: 1 l of genomic DNA, 10 pmol o f each primer] [each PCR bead concentration reconstituted for a 25 l bead reaction: 200 M dNTP, 10 mMTris HCl, 50mM KCL, 1.5 mM MgCl 2 2.5 U Taq DNA polymerase]. The PCR program profile used for direct sequencing the DQB and DRB loci were 96 C
38 68 C per cycle, followed by [98 temperatures for each locus were: DQB [X1 = 70 C; X2 = 63 C] and DRB [X1 = 67 C; X2 = 60 C]. For genotyping PCR (direct sequencing) the primers used for the DRB locus: PBDRB1 GCCATTTCACCAACGGGACGGAGCGGG ) / PBDRB2 CACCCCGTAGTTGTGTC ) (164 bases) (Weber et al. 2013), which were designed for another carnivore, the polar bear ( Ursus maritimus ). For the DQB locus the primers [ DQB1 5' CWGGTAGTTGTGTCTGCACAC ) / DQB2 5' CATGTGCTACTTCACCAACGG ) (172 bases)] ( Scharf et al. 1986) used were a modified version of GH28 and GH29 and have been used with other carnivores (Webe r et al. 2004; Weber et al. 2013) and non carnivores ( Baker et al. 2006 ) The team obtained bidirectional nucleotide sequences of purified PCR products (QIAquick PCR purification kit, Qiagen or Biomek FX Automated Workstation, PCR Purification System Agenc ourt Ampure) on an Applied Biosystems 3730XL (modified for BigDye Terminator (V.1.1)). I edited the DNA sequences (Fig. 2) from both loci with SEQUENCHER 5.1 (Gene Codes) and obtained 191 base pairs for DRB in 75 individuals and 194 base pairs for DQB i n 67 individuals, of which I had sequences for the same individual in both loci for 64 foxes. I aligned the edited data with Clustal X (Larkin et al. 2007) and analyzed it using Arlequin 3.5 (Excoffier & Lischer 2010) and MEGA 4 (Tamura et al. 2007). Nucle otide sequences were converted to amino acids using previously published alleles (Ploshnitsa et al. 2012) and the northern elephant seal ( Mirounga angustirostris ) (Weber et al. 2004). For each locus, I determined the following diversity indices using Arleq uin 3.5 (Excoffier & Lischer 2010): number of expected alleles, nucleotide diversity, gene
39 diversity, expected heterozygosity, observed heterozygosity, Tajima's D (Tajima 1993), Fu's Fs (Fu 1997), Fu's expected number of alleles (Fu 1997), Chakraborty's ex pected number of alleles (Chakraborty 1990), and Ewens Watterson's observed and expected F valu es (Ewens 1972; Watterson 1978). Tajima's D (Tajima 1993) and synonymous to non synonymous substitutions (Nei & Gojobori 1986) were calculated using MEGA 4 (Tamu ra et al. 2007). Results The Svalbard arctic fox showed high genetic variation in the peptide binding region (PBR) in exon 2 for both of the MHC class II loci, DRB and DQB surveyed in this study. DRB provided 25 different genotypes, of which fifteen wer e singletons, meaning that particular genotype was only found in one individual (Fig. 3a and Xa). DQB had 23 genotypes in the arctic foxes and 15 of these were singletons (Fig. 3b and Xb). There were 50 ambiguous sites [21 in the PBR] in DRB and 55 in DQB [20 in PBR]. There were no homozygous individuals in either DRB or DQB and none of the sites that were analyzed resulted in stop codons (Fig. 3). In DRB fourteen individuals showed copy number variation (CNV), where at least two sites had three bases ind icating more than one gene in those individuals, and three individuals had CNV for DQB Ambiguous sites were in line with those found in previously published NES and arctic fox alleles in both loci, as well as a sampling of Canis lupus alleles in DRB and C anis familiaris alleles in DQB (Figure 3). Codons with only one ambiguous site were recorded by hand, and compared for synonymous to non synonymous substitutions. Of the eleven codons examined in DRB nine conferred non synonymous changes, while there are 10 non
40 synonymous substitutions in the 17 examined codons of DQB Nucleotide diversity was greater for DRB [ =0.010] than DQB [ =0.002], but gene diversity was higher in DQB [0.8988] than DRB [0.8714] (Table 1). Tajima's D was negative at both loci, indic ating a population that has experienced growth (Table 1) (Rogers et al. 1996; Schneider & Excoffier 1999; Schneider et al. 2000; Tajima 1993). In DRB Fu's Fs confirms this finding, while in DQB Fu's Fs value may suggest a historical bottleneck (Table 1) ( Fu 1997; Schneider et al. 2000). Observed levels of homozygosity were lower in DRB than expected, but higher in DQB (Ewens 1972; Watterson 1978) (Table 1). However, given the genotypic data, it is known that no individuals were homozygous at either locus. Forty four DRB/DQB haplotypes were found in the 64 individuals sampled at both loci. Both Chakraborty and Fu expected 5.2754 alleles (Table 1); conceivably there are more than six alleles given the genotypic diversity. Nucleotide diversity is low [0.002], while gene diversity is very high [0.9790]. Expected heterozygosity is 97.9 % but all individuals are heterozygous. The Ewens Watterson test values say that the population is more homozygous than expected bu t, knowing the problems with these data and Arle quin 3.5, this can be discounted (Table 1). The data used in this study were genotypic data only as individual alleles were indeterminable. The high levels of diversity and the large number of singletons for both loci in combination with the paucity of pre viously published data makes it difficult to determine with certainty the exact allele sequences for each genotype.
41 Discussion In the Svalbard arctic fox, none of the individuals surveyed were homozygous at either locus, demonstrating a high level of h eterozygosity. The genotypic results from this study were consistent with Ploshnitsa et al. (2012), who found 27 different DRB/DQB genotypes in 47 mainland foxes. This high number of genotypes may add protection for this population from a wide range of pat hogens ( Arkush et al. 2002; Oliver et al. 2009; Wegner et al. 2003), and is consistent with previous findings of at least 8 singleton haplotypes in the 47 individuals studied (Ploshnitsa et al. 2012) The large number of unique genotypes may provide evolut ionary potential in an unpredictably changing environment; however, evolution is not always adaptive, and thus high diversity does not necessarily increase adaptive potential as models show highly diverse populations are more likely to go extinct than the ir moderately diverse counterparts (Lande & Shannon 1996). CNV may be a means to increase diversity (Siddle et al. 2010), and was observed in both loci in this study and the study done by Ploshnitsa et al. (2012). Although the population dynamics of the Sv D suggests a growing population, which is not unreasonable given the immigration into the population. In DQB Fs indicates a historical bottleneck, somewhat confirmed by the history of the Svalbard arctic fox, which was, and is still, being hunted (Ehrich et al. 2012). Climate warming is modifying innumerable aspects of the Arctic environment to which the arctic fox must adjust. Apart from alterations of sea ice levels and the provision of suitable habitat for predators, the composition and health of one of the coastal arctic fox's prey, seabirds, is changing as a result of pollution. Chemical pollutants can
42 negatively impact the health of marine animals (Vos et al. 2000; Jenssen 2006; Burek et al. 2 008). Bioaccumulation of toxins from prey species has been recorded in the Svalbard arctic fox, which could impact their health (Fuglei et al. 2007). Ability to cope with climate change and other environmen tal factors may be affected by toxin load, impair the immune system, and alter the breeding and migration events in sea birds (Jenssen 2006), an important food source for the Svalbard arctic fox. Changes in prey phenology i.e. timing of biological events such as reproduction or migration, can affect pred ators by reducing their energy source and changing their reproductive success (Aceveedo Whitehouse & Duffus 2009). The Svalbard population, while genetically diverse in the MHC, may be irreversibly stressed by Arctic warming. Svalbard, a high Arctic islan d, may experience climate change differently from Arctic continents and the Svalbard arctic fox may face different stressors than mainland foxes. For example, a loss of sea ice would prevent the movement of both the arctic and red foxes to Svalbard, while warming temperatures on the mainland will provide suitable habitat for the competitor. Immunologically impaired individuals are more susceptible to disease. Stress caused by higher temperatures, invasion of predators, loss of prey, and pollution may work t ogether to reduce the health of arctic fox individuals ( Reeder & Kramer 2005; Wingfield & Sapolsky 2003)
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47 Table 1. Genetic Diversity Indices for DRB and DQB DRB DQB DRB & DQB Nucleotide Diversity 0.010492 +/ 0.006585 0.001976 +/ 0.002079 0.002614 +/ 0.001965 Gene Diversity 0.8714 +/ 0.0174 0.8988 +/ 0.0115 0.9769 +/ 0.0038 Expected Heterozygosity 0.8714 0.8988 0.9769 # Alleles 1 5.83829 [p = 0.733] 1.47208 [p = 0.001] 5.42754 2 9.15516 2.95069 5.42754 Fs 3.68243 p = 0.925] 1.93762 [p = 0.168] 0.68038 Ewens Watterson Expected F 3 0.50912 [p = 0.290] 0.51288 [p = 0.958] 0.51122 Ewens Watterson Observed F 0.4164 0.89689 0.8 7988 D (Arlequin 3.5) 4 2.15288 [p = 0.002] 1.13728 [p = 0/126] 2.04920 D (MEGA 4) 1.157528 1.159335 -1 Chakraborty 1990 2 Fu 1997 3 Ewens 1972; Watterson 1978 4 Tajima 1993
48 Figure 1. (a) Map of current arctic fox range, highlighted in yellow. Svalbard is circled in red. (Taken from IUCN http://maps.iucnredlist.org/map.html?id=899 ). (b) Detailed map of Svalbard Islands (Take from http://www.fairbankmusic.c a/AC svalbard.html). (c) Svalbard, highlighted in orange, in relation to Arctic Ocean (Taken from http://svalbard.travelize.se/reiser/uk/About Svalbard 1 14/Maps 7 356.html). (a) Current arctic fox range (b) Svalbard Islands
49 (c) Svalbard in relation to the Arctic Ocean
5 0 Figure 2. Sequence chromatogram of part of the DRB genotype for two different arctic fox individuals. The sequence chromatogram shown here has peaks of varying colors depending on the base called [A: green, T: red, C: blue, and G: black]. The chromatogram is edited using SEQUENCHER (Gene Codes) verifying that the bases were called complementary directions; the bottom line is a different i individual. The yellow box highlights a site that is polymorphic, i.e., varies between alleles. A blue and red peak can both be seen at the first site in the box, followed by a green and red peak.
51 Figure 3. Amino acid variation in class II of the MHC in (a) DRB and (b) DQB genotypes of the arctic fox. Dots mark identity with top sequence. Question marks indicate sites with base ambiguity. Dashes indicate lack of data. Shaded regions indi cate the peptide binding region as determined by Ploshnitsa et al. (2012). (a) DRB genotypes in the arctic fox AFdrb## indicates shared genotype. 6 7 digit numbers ending in 102 and 304 indicate individual names, and singleton genotypes. VulaDRB*## are the alleles previously published by Ploshnitsa et al. (2012). DLA_DRB1*## are Canis lupus alleles [DLA_DRB*D13 Accession Number U44778; DLA_DRB*D2A Accession Number U44777; DLA_DRB*D24 Accession Number AF016912; taken from GenBank]. MianDRB#*## are northern e lephant seal alleles published in Weber et al. (2004). PBDRB1*01 is a polar bear allele taken from Weber et al. (2013). (b) Shared DQB genotypes are identified by genoA H. Six to seven digit numbers ending in 102 and 304 indicate individual names, and sing leton genotypes. VulaDQB*## are the alleles previously published by Ploshnitsa et al. (2012). MianDQB*## are northern elephant seal alleles, MianDQB*01 was accessed from GenBank using accession number AF111031; MianDQB*02 was accessed from GenBank using ac cession number AF111030. CafaDQB*## are Canis familiaris alleles [CafaDQB1*02301 Accession Number AF016909; CafaDQB1*00701 Accession Number AF016907; CafaDQB1*00101 Accession Number AF016905].
52 (a) DRB
53 (b) DQB
54 Figure 4. Nucleotide variation in class II of the M HC in (a) DRB and (b) DQB genotypes of the arctic fox. Dots mark identity with top sequence. (a) DRB genotypes in the arctic fox AFdrb## indicates shared genotype. 6 7 digit numbers ending in 102 and 304 indicate individual names, and singleton genotypes. (b) DQB genotypes in the arctic fox AFdrb## indicates shared genotype. 6 7 digit numbers ending in 102 and 304 indicate individual names, and singleton genotypes.
63 CHAPTER 3: Major Histocompati bility Complex Diversity in the Southern Elephant Seal Abstract The major histocompatibility complex (MHC) plays an important role in immune system response, is one of the most diverse regions in the mammalian genome, and provides protection from pat hogens. Marine and polar environments are suggested to have lower pathogen presence, which could reduce the MHC variability of species in these habitats. The southern elephant seal, a top predator in the Antarctic food chain, was hunted to near extinction, and while some populations have recovered, the population on Marion Island is declining. Initial studies of DQB (a class II MHC locus) showed low levels of diversity in the southern elephant seal, however a preliminary study on DRB had high levels of dive rsity. This study found moderate levels of diversity in three class II MHC loci ( DQA DQB and DRB ) in the Marion Island population of the southern elephant seal. Despite historical hunting pressures and a current declining population, the Marion Island so uthern elephant seal has more MHC diversity than its sister taxa, the northern elephant seal, which has since recovered from similar hunting pressures.
64 Introduction The southern elephant seal ( Mirounga leonina ) (Fig. 1) is a circumpolar pinniped that haul s out on islands around Antarctica, and islands south of the southern tip of South America and Africa in the S outhern ocean (Fig. 2) to molt, breed, and give birth. It is the largest pinniped and shows drastic sexual dimorphism, as males weigh 1,500 3,700 kg and females 350 800 kg (Le Boeuf & Laws 1994), resulting in large quantities of oil from their blubber that was considered superior to whale oil (Weber 2003). This resulted in the southern elephant seal being hunted severely for its oil during the eight eenth and nineteenth centuries, such that an estimated over one million seals were harvested (Laws 1994). Sealing decreased in 1909 and thereafter seals were taken primarily at South Georgia Island (Fig. 2), but by then hunting pressures had drastically re duced all populations of the southern elephant seal Once hunting pressures had ceased, most populations began to increase and became stable. The Marion Island population, the s to the rebound (Laws 1994; McMahon et al. 2005). Despite the large numbers of southern elephant seals taken, it had refuge from hunting pressures during the winter mon ths because of the hostile sea conditions and the remoteness of their island habitats, unlike its sister taxa in the temperate northern hemisphere, t he northern elephant seal ( Mirounga angustirostris ) The northern elephant seal suffered multiple severe bo ttlenecks from commercial harvest and from hunting by indigenous Indians before the sealing and was declared extinct three separate times (Weber et al. 2000; Weber 2003). As a result of hunting, t he NES lost genetic diversity
65 (Weber et al. 2000) and extant individuals show minimal variation in mitochondrial and nuclear DNA [allozymes, minisatellites, microsatellites, and major histocompatibility complex (MHC)] (Bonnell & Selander 1974 ; Lehman et al. 1993; Garza 1998; Hoelzel et al. 1993; Hoelzel 1999; Weber et al. 2000; Weber et al. 2004). In comparison, m itochondrial DNA (mtDNA) from the South Georgia and Peninsula Valdez southern elephant seal stocks showed 23 haplotypes in 48 individuals (Hoelzel et al. 1993) levels of mitochondrial DNA diversity in the small King George Island molting population were higher than other modern colonies (Bogdanowicz et al. 2013) and nucleotide diversity levels from South Georgia and Peninsula Valdez were high (Hoelzel et al. 2001). In spite of hunting, nuclear and mitochon drial levels of diversity in the southern elephant seal are consistent with those found in model species, such as the human and mouse (Slade et al. 1998; Hoelzel et al. 1993; Hoelzel et al. 2001). The southern elephant seal is listed as a species of least concern by the International Union for Conservation of Nature (IUCN) but in the future with climate warming may face impending challenges, e.g., loss of sea ice (McMahon & Burton 2005; Parmesan 2006), changes in prey species (Parmesan 2006) and the influx of new diseases (ACIA 2005; Kutz et al. 2009; Parkinson & Butler 2005). In particular, populations possibly at risk are those that have yet to rebound from hunting pressures or have been demonstrating a constant rate of decline, such as the Marion Island population (Laws 1994; McMahon et al. 2005). Seals from Marion Island must contend with the variable conditions caused by the Antarctic Circumpolar Current (ACC), which is associated with intense salinity, temperature, and density gradients (Tosh et al. 20 12). Warming of 1.2 o C near Marion Island was documented between 1969 and 1999 (Smith 2002). Depending
66 on where they haul out to breed and molt (Tosh et al. 2012), the southern elephant seal will show fidelity to a feeding site (Bradshaw 2003), and can tra vel long distances to reach them (McConnell et al. 1992). Marion Island southern elephant seal switched feeding sites from the Antarctic Polar Front (APF) to the Sub Antarctic Front (SAF), when the SAF was close to Marion Island (Tosh et al. 2012). Temper ature could change the location of these two fronts, potentially affecting the diet and energy expenditure of Marion Island southern elephant seal if the fronts move away from the island. Climate change will also alter levels of pollution and disease in th e marine environment (Aguirre & Tabor 2004; Harvell et al. 2002). Levels of persistent organic pollutants are expected to rise in Antarctica, increasing the susceptibility of individuals to disease and reducing reproductive success in Antarctic seals (Goer ke et al. 2004; McFarlane et al. 2009). Marine degradation through increased pollution has assisted in increasing rates of disease among marine mammals (Aquirre & Tabor 2004). In recent decades, disease prevalence in marine mammals has expanded (Ward & Laf ferty 2004). Resistance to pathogens may come as a result of high genetic diversity in the MHC, which plays an important role in immune system function (Piertney & Oliver 2006). MHC diversity in the southern elephant seal has been examined for DQB (Hoelze l et al. 1999) along with preliminary studies of DRB (Weber et al. 2004). Levels of diversity in DQB are comparable to those found in humans, a well studied species with high levels of MHC diversity (Hoelzel et al. 1999). Weber et al. (2004) found five all eles in DRB when sampling two southern elephant seal individuals. Although the first study of the MHC in the southern elephant seal found low levels of diversity (Slade et al. 19992), these newer studies indicate a population with high diversity. This stud y will examine the
67 MHC diversity in three class II loci of the MHC [ DRB, DQB, and DQA ] in the Marion Island population of the southern elephant seal. Methods The southern elephant seal s amples for the Marion Island subpopulation were provided by Marthan Bester and Brent Stewart, and all subsequent lab work was performed by Dr. Diana Weber and her team ( cf Weber et al. 2004). From the obtained sequence data, I edited the sequence chromatograms (Fig. 3) of clones and/or direct nucleotide sequences from 11 individuals for DQB 13 individuals for DRB and 15 individuals in DQA using SEQUENCHER (Gene Codes); six individuals had data for all three loci (Table 1). A total of 19 individuals were examined for at least one locus. The edited data was aligned (Clust al X, Larkin et al. 2007) and analyzed to obtain statistical measures using the programs DnaSP (Librado & Rozas 2009), MEGA 4 (Tamura et al. 2007), and Arlequin 3.5 (Excoffier & Lischer 2010). Nucleotide sequences were translated to amino acids starting wi th the second nucleotide site based on previously published alleles of the northern and southern elephant seal (Weber et al. 2004). From Arlequin 3.5 (Excoffier & Lischer 2010), I obtained the n umber of expected alleles (Chakraborty 1990; Fu 1997), nucleo tide diversity, expected heterozygosity, observed heterozygosity, Tajima's D (Tajima 1993), and Fu's Fs (Fu 1997), and the Ewens Watterson test for neutrality (Ewens 1972; Watterson 1978). DnaSP 5.0 (Librado & Rozas 2009) provided the diversity indices [n u cleotide diversity, gene diversity, raggedness (Harpending 1994), R2 D* F*
68 S D (Tajima 1993)] for each locus. MEGA 4 (Tamura et al. 2007) gave the statistical measure for Tajima's D (Tajima 1997) and synonymous to non synonymous substitutions (Nei & Gojobori 1986). Results The southern elephant seal showed low nucleotide diversity ( ) (Table 2), high gene diversity (Table 2), low number of alleles for DQA (4 alleles in 15 seals) but high allelic number for DQB ( 8 alleles in 11 individuals ) and DRB (31 alleles in 13 individuals). I found all individuals surveyed in DQA to be homozygou s at that locus, eight were homozygous in DQB and none in DRB (Table 2 S values were less than one for DQA [0.728] and DQB [0.893], but equal to one in DRB indicating more alleles than expected in DRB (Table 2) (Venkatesan et al. 2007). DQA h ad approximately the expected number of alleles observed in the data by both Fu (1997) and Chakraborty (1990) measures (Table 2). DQB also had very similar expected to observed number of alleles (Table 2). In contrast, DRB demonstrated a large difference i n observed [obs: 31] alleles to expected between the two statistical measures, Chakraborty (1990) [exp: 32] and Fu (1997) [exp: 18] (Table 2) These two values possibly differ because Chakraborty (1990) estimates the number of expected alleles based on obs erved homozygosity while Fu (1997) bases it on the number of pairwise differences (Excoffier & Lischer 2011). Arlequin overestimated the homozygosity in DRB as a result of the n the value found by Chakraborty. Observed heterozygosity was much lower than expected for all loci (Table 2). However, observed levels of homozygosity from the Ewens Watterson
69 F test were approximately equal to expected under neutrality for all three loc i (Table 2) (Ewens 1972; Watterson 1978). D was slightly positive [though deemed insignificant by DnaSP] in DRB [DnaSP p > 0.10; Arlequin p=0.99] and DQB [DnaSP p > 0.10; Arlequin p=0.972] indicative of a lack of growth (Table 2) ( Rogers et al. 1 996; Schneider & Excoffier 1999; Schneider et al. 2000; Tajima 1993). In DRB Fs [p=0.01] confirms this with negative values suggestive of a historical bottleneck. In DQB Fs calculated by DnaSP provided a slightly negative number [ 1.1] while Ar lequin had a positive number [0.8, p=0.633], though this appears conflicting, the results are not drastically different (Table 2) (Fu 1997; Schneider et al. 2000). In DQA D [DnaSP p > 0.10; Fs [p= 0.705] slightly positive potentially indicating population growth (Table 2) (Rogers et al. 1996; Schneider & Excoffier 1999; Schneider et al. 2000; Tajima 1993; Fu 1997). All three programs utilized D found positive values for DRB and D QB and negative values for DQA (Table 2). Rates of synonymous to non synonymous substitutions were only significant in DRB [0.031] (Table 2). Copy number variation (CNV) was found in 76.92% (10 individuals) of individuals in DRB and in 18.18% (2 individua ls) individuals in DQB meaning these individuals showed more than two alleles at a locus. Unfortunately, separating out the exact gene ( DRB1 or DRB2 ; DQB1 or DQB2 ) was not possible at this time. Looking at the three loci together, the southern elephant se al population has more alleles than expected by both Fu (1997) and Chakraborty (1990), also indicated by a Fs value (Table 2 ). Expected heterozygosity was much higher than
70 observed [exp: 0.9855; obs: 0.667], while observed homozygosity was lo wer than D was positive (Table 2 ). Minimal clone data for DQB may have reduced the observed diversity in this locus. Alternatively, the minimal number of clones may increase the chance of false alleles as s everal alleles were seen in a single clone. No stop codons were found in any alleles for any of the loci, indicating the sequences were from the coding region and not pseudogenes. Discussion Though the Marion Island southern elephant seal population ha s remained small after historical intense hunting pressure (McCann 1980; Laws 1994), these seals demonstrated higher genetic diversity at the MHC loci surveyed than found in the sister taxa, the NES (Weber et al. 2004). A previous study found a much lower level of DQB alleles [8 alleles] in 109 southern elephant seal individuals (Hoelzel et al. 1999) compared with 14 alleles in 11 seals in this study; neither of the other loci ( DQA and DRB ) were surveyed in their study. At DRB Weber et al. (2004) found 5 a lleles in 2 southern elephant seal individuals. Those individuals that were surveyed in this study for DQA DQB and DRB had higher than expected allelic diversity, suggesting the species may have expanded pathogen recognition repertoire ( Piertney & Oliv er 2006; Kamath & Getz 2011) However, the sample size was very small, which limits the reliability of the results. Surveying all individuals obtained per locus, only DRB showed higher levels of diversity than expected, as shown by more alleles observed th an expected by Fu (1997), lower
71 levels of homozygosity than expected (Ewens 1972; Watterson 1978), CNV in most S value of one, as well as high gene and nucleotide diversity (Table 2). For DRB DQB and individuals examined at all t Fs D values indicate that the population has not grown ( Rogers et al. 1996; Schneider & Excoffier 1999; Schneider et al. 2000; Tajima 1993; Fu 1997) which is known to be the case (McMahon et al. 2005). Additionally, small valu es for the raggedness index at all loci (Table 2) imply an unstable demographic (Rocha Olivares et al. 2000). Low levels of observed heterozygosity [compared to expected heterozygosity] for DQA and DQB could mean that individuals are less able to initiate an immune response to novel pathogens (Arkush et al. 2002; Oliver et al. 2009; Wegner et al. 2003). CNV occurs in a number of species (Trowsdale 2011; Bowen et al. 2004; Doxiadis et al. 2006; Mayer & Brunner 2007), including the southern elephant seal whi ch may increase allelic diversity (Axtner & Sommer 2007), possibly providing the species additional pathogen protection (Siddle et al. 2010). CNV was observed in both DRB and DQB. Although allelic diversity was high in DRB it was only moderate in DQB and CNV may have added allelic diversity to the locus. CNV may increase the functional effectiveness of the MHC, even in the face of varying environmental challenges (Saxena et al. 2009). The diversity indices suggest two conclusions: i ) genetic diversity in the MHC is high in DRB moderate in DQB and low in DQA and ii ) the Marion Island southern elephant seal population size has not increased in recent history. Regarding the first conclusion, levels of diversity found in DRB and DQB are similar to those prev iously published (Hoelzel et al. 1999; Weber et al. 2004); however, there have been no previous
72 studies conducted on DQA in the southern elephant seal The Scandinavian wolf ( Canis lupus lupus ) experienced population declines as a result of hunting (Seddon & Ellegren 2004). The population has since recovered slightly but DQA diversity is still low, as demonstrated by 2 alleles in 90 individuals. The giant panda ( Ailutopoda melanoleuca ), one of the most endangered species with a global population around 1000 individuals, showed six DQA alleles in 61 individuals (Zhu et al. 2007). In contrast, the thriving California sea lion ( Zalophus califorianus ) had five alleles in two individuals (Bowen et al. 2002). DQA diversity is often low (Weber et al. 2004) The pat terns of diversity in the MHC appear to coincide with published studies (McMahon et al. 2005; Bradshaw et al. 2002) and suggest that the Marion Island southern elephant seal population may have an increased risk. Expansion of disease, shifts in prey avail ability, and loss of habitat are all potential threats to the southern elephant seal with climate change (Parmesan 2006). Extended exposure to such stressors can impact reproductive and feeding success, which can reduce immune system function ( Reeder & Kra mer 2005; Wingfield & Sapolsky 2003) This can decrease fitness at the individual level, which could eventually reduce population fitness. Although levels of diversity were not high in all loci, the Marion Island southern elephant seal appears to have acce ptable levels of diversity and may have the capacity to withstand the influx of novel pathogens. As this study examined only one of the islands used by the species, extrapolation to the rest of the population should be viewed with caution. However, since t his population is small and declining, the MHC diversity of the southern elephant seal population as a whole may be higher than presented, potentially increasing the viability of th e species in the face of warming.
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79 Table 1. Locus Examined by Individual DRB DQB DQA BB193 BB193 BB193 B277 B277 B277 OO305 OO305 OO305 RG017 RG017 RG017 YY191 YY191 YY191 YY302 YY302 YY302 BB018 BB018 -BB045 -BB045 BB073 BB073 --BB125 --BB304 BB304 --OO263 TO345 -TO345 --TO349 TO356 -TO356 TO361 -TO361 WW336 ---Y428 Y428 --YY232 13 inds 11 inds 15 inds
80 Table 2. Genetic Diversity Indices DQA DQB DRB 3 loci # I ndividuals 15 11 13 6 # of Alleles 4 8 31 20 Nuc Diversity 1 0.002 0.008 0.027 0.016 0.060 0.031 0.016 0.008 Gene Diversity 1 0.579 0.077 0.772 0.077 0.981 0.009 0.986 0.016 Observed Heterozygosity 1 0.000 0.308 0.652 0.667 Expected Heter ozygosity 1 0.579 0.932 0.981 0.986 D 4 0.986 p=0.166] 1 ; 1.516 [p>0.10] 2 ; 1.516 3 1.738 [p=0.972] 1 ; 0.666 [p>0.10] 2 ; 1.110 3 2.053 [p=0.99] 1 ; 0.929 [p>0.10] 2 ; 2.034 3 1.817 1 Fs 5 0.823 [p=0.705] 1 ; 0.154 2 0.185 [p=0.633] 1 ; 1.143 2 9.485 [p=0.01] 1 ; 13.989 2 3.723 1 S 2, 6 0.728 0.893 1 Mean # Pairwise Differences 1 1.177 0.778 3.431 1.799 11.340 5.240 16.946 0.008 Exp # Alleles 1, 7 4.074 6.780 32.667 15.247 Alleles 1, 8 4.405 7.805 18.787 15.257 E wens Watterson expected F 1, 9 0.480 0.257 0.045 0.058 Ewens Watterson Observed F 1 0.440 0.234 0.041 0.056 Raggedness 2, 10 0.1746 0.0864 0.004 R2 Statistics 2, 11 0.1875 0.1868 0.1803 D* 2, 12 2.039 0.406 0.848 F* 2.170 0.551 1.038
81 d N >d S 3, 13 0.426 1.000 0.031 Table 2. Continued 1 The measures nucleotide diversity, gene diversity, observed heterozygosity, expected D Fs mean # pairwise differences, ted # of alleles, and Ewens Watterson expected and observed F were obtained using 718 bases for DQA 117 bases for DQB and 189 bases for DRB with Arlequin 3.5 (Excoffier & Lischer 2010) 2 D Fs S raggedness, R2 stat istics, Fu D* and F* were obtained using 718 bases for DQA 116 bases for DQB and 189 bases for DRB with DnaSP (Librado & Rozas 2009) 3 D and d N >d S were obtained using MEGA (Tamura et al. 2007) 4 Tajima 1993 5 Fu 1997 6 Stro beck 1987 7 Chakraborty 1990 8 Fu 1997 9 Ewens 1972; Watterson 1978 10 Harpending 1994 11 Hill & Robertson 1968 12 Fu & Li 1993 13 Nei & Gojobori 1986
82 Figure 1. Male southern elephant seal. (Taken from http://true wildlife.blogspot.com/2011/02/elephant seal.html )
83 Figure 2. Southern elephant seal range (shown in green) in Antarctic and SubAntarctic waters. (Taken from http://commons.wikimedia.org/wiki/File:Southern_Elepha nt_Seal_area.png )
84 Figure 3 Sequence chromatogram of two DRB alleles found in individual B277 from SEQUENCHER (Gene Codes). The sequence chromatogram shown here has peaks of varying colors depending on the base called [A: green, T: red, C: blue, and G: b lack]. The chromatogram is edited using SEQUENCHER (Gene Codes) verifying that the bases were called correctly. The top two lines show a DNA clone sequence from one individual l polymorphic, i.e., varies between alleles. As an example, C11 shows GGA, while D11 has CTC at these sites.
85 Figure 4. Nucleotide sequence variation in the southern el ephant seal. Dots mark identity with top sequence. marks every 10 bases. (a) Southern elephant seal DQA intron sequence. MileDQA*## indicates allele found in this study. LeweDQA*W6 is a previously published Weddell seal ( Leptonychotes weddellii ) allele, AY283565. OmroDQA*R1 is a previously published Ross seal ( Ommatophoca rossii ) allele, AY283567. LocaDQA*C10 is a previously published Crabeater seal ( Lobodon carcinophagus ) alleles, AY283568. HyleDQA*L1 is a previously published Leopard seal ( Hydrurga lept onyx ) allele, AY283566. MoscDQA is a previously published Hawaiian monk seal ( Monachus schauinslandi ) allele, AF093799 (b) Southern elephant seal DQB sequence. Top sequences, letter###*## indicate sequences found in this study. MileDQB*## identify previou sly published southern elephant seal alleles [Accession Numbers AF111032 111038] MianDQB*## identify previously published northern elephant seal alleles (Weber et al. 2004). ArgaDRB*K# identify Galapagos fur seal ( Arctocephalus galapagoensis ) alleles [Acc ession Numbers K3: HE663130; K4: HE663131]. MoscDQB*HMS# identify Hawaiian monk seal ( Monachus schauinslandi) alleles [Accession Numbers HMS1: AY007203; HMS2: AY007204] ArfoDQB*NFS3 identifies a New Zealand fur seal ( Arctocephalus forsteri ) alleles [Acces sion Number AF111044] ArgaDQB*AFS4 identifies an Antarctic fur seal ( Arctocephalus gazella ) allele [Accession Number AF111042]. (c) Southern elephant seal DRB sequences, all shown are from this study.
86 (a) DQA
87 (b) DQB
88 (b2) DQB
89 (b3) DQB
90 (b4) DQB
91 (b5) DQB
92 (c) DRB
93 (c2) DRB
94 (c3) DRB
95 (c4) DRB
96 Chapter 4: Conclusions
97 Conclusions Studies of the immune system can provide valuable information about the potential viability of a population (Acevedo Whitehouse & Duffus 2009) and i ts evolutionary and adaptive potential (Lande & Shannon 1996). Analysis of the genetic diversity of the major histocompatibility complex (MHC) pertains to both of these concerns, providing conservation efforts with valuable and needed information, regardin g inbreeding, outbreeding, adaptive potential to new environments, fragmentation, taxonomy, and etc. (Frankham 1995), all of which affect population and ecosystem dynamics. The MHC has been well studied in model organisms, such as the human, mouse, and rat (Kumanovics et al. 2003), but less so in non model species. Various studies (Parham & Ohta 1996; Hughes & Yeager 1998; Klein 1986; Vandiedonck & Knight 2009) indicate that the MHC is the most diverse area in the mammalian genome and has provided ample bac kground information on the region. Data from model species has given a means to make conclusions about wildlife MHC analyses more substantiated (Ujvari & Belov 2011). The arctic fox ( Vulpes lagopus ) and southern elephant seal ( Mirounga leonina ), two polar predators at opposite poles of the planet, were found to have reasonable levels of genetic diversity, based on heterozygosity and allelic diversity in the MHC class II loci examined. Though sampled individuals from each species were from a single populati on, they had characteristics that pertain to the species as a whole ; however different parts of the population may feel different environmental effects The Svalbard arctic fox subpopulation was centrally located to the other fox subpopulations and probabl y served as a bridge between North America n and Russia n subpopulations (Noren et al. 2011); this
98 would have facilitated gene flow between these fox subpopulations. Svalbard has more immigration than emigration (Noren et al. 2011), which would theoretically increase the gene pool assuming other fox subpopulations are genetically diverse and distinct. The southern elephant seal population on Marion Island is smaller than other populations (Laws 1994; McMahon et al. 2005) and may have experienced a possible lo ss of alleles (Frankham 1995). Neither of these populations are perfect extrapolations for the species in question, and analysis of the viability of the arctic fox and southern elephant seal could be enhanced by further genetic studies. An expansion of thi s study, with both more individuals and more populations represented, would be the first step to in creasing the reliability of these data. In addition, examination of other genes involved in immune system function would allow for more confident conclusions to be drawn (Acevedo Whitehouse & Duffus 2009). In addition to immune system complexity, comes the dynamic quality of the environment and the ability of species to respond to climate change. Species higher in the trophic level, such as the arctic fox (Fi gure 1) and southern elephant seal (Figure 2), may provide an indication of potential problems for the future of the ecosystem (Bossart 2006). Food web interactions in the Arctic tundra (Fig. 1) are largely determined by climate, and have already shown cha nges consistent with warming (Ims & Fuglei 2005). If the Arctic tundra food web is controlled by top down forcings, wherein predators control prey populations which in turn control primary productivity (Hairston et al. 1960), then declines in the arctic fo x subpopulations could have devastating consequences. Even without top down control, removal of a deeply embedded species in the food chain would reduce ecosystem stability (Paine 1969). It has been suggested that marine communities
99 show top down forcings more frequently than terrestrial environments (Heithaus et al. 2007). If true, ecosystem function would be dramatically affected if these key species serve as top marine predators and are subsequently lost (Heithaus et al. 2007). The likelihood of ecosyste m changes and possible degradation is high if either of these two species is lost. Knowing potential patterns of response by a species and it s role in the trophic food web will greatly aid conservation efforts; especially as current information regarding s pecies response focuses on a small number of species (Parmesan 2006). Not all ecosystems are created equal in the face of climate change nor do all species respond similarly; some species may expand their range, while others lose all or a considerable por tion of their habitat (Parmesan 2006). Island populations may respond differently than mainland ones, especially to climate change (Kier et al. 2009). For example, the survival of island populations may be in a more precarious position from species invasio n than r ange expansion by other species Smaller subpopulations have a greate r risk for loss of diversity and potential local extinction from stochastic events (Frankham 1995); however they may gain some benefit in lower density if it decreases the potenti al for the spread of disease (Smith & Wilkinson 2002). Studies of the changes in polar islands are crucial if species viability in the face of climate change is to be reported with any certainty. Lack of information regarding effective population sizes, sp ecies management units, and genetic diversity can result in unintentional mismanagement (Frankham 1995). Loss of alleles, regardless of cause, can reduce adaptive potential and increase extinction risk (Frankham 1995). Loss of species decreases the stabili ty of the food web (Paine 1969), with the capacity to drastically alter ecosystem functioning. For example, Paine
100 (1966) found that intertidal communities with a top predator [a starfish, Pisaster ] had more complex food webs and more species diversity than similar communities without a top predator. It is important to understand the genetic dynamics of a species to infer its possible response to climate change and shifts in the environment, as this will increase the effectiveness of conservation efforts in a changing world.
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103 Figure 1. Simplified version of the Arctic food web, showing the arctic fox (boxed in red) at the top. Thick black lines indicate direct relationship with lemmings, wqhile dotted lines show indirect lemming relationship. Thin lines show other population connections unrelated to lemmings. (Taken from Ims & Fuglei 2005).
104 Figure 2. Simplified version of the Antarctic food we b showing the elephant seal [boxed in yellow ] in a top trophic position (Taken from http://www.discoveringantarctica.org.uk/alevel_3_3.html confirmed by Stowasser et al. 2012).
105 Appendix A: Nucleotide Sequences of Arctic Fox and Southern Elephant Seal from Data in this study. Arctic Fox DRB nucleotide sequences genotype 1 CGGGTGCGGTWYCWGGMWARAYACATCTATAACCGGGAGGAGT TSGYGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACG GAGCTCGGGCGGCCCGAYGCTG AGTACTGGAACSGGCAGAAGGA GATCTTGGAGGASRMGCGGGCAGYGGTGGACMSSKWSTGCAGAC ACAACTACGGGGTGA genotype 2 CGGGTGCGGTWYCWGGMWARAYACATCTATAACCGGGAGGAGT TSGYGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACG GAGCTCGGGCGGCCCRWYGCTGAGTMCTGGAACSGGCAGAAGGA GATCTTGGAGGACRMGCGGGCMSHGGTGGAC MSSKWSTGCAGAC ACAACTACGGGGKGA genotype 3 CGGGTGCGGTAYCWGGMWARAYACATCTATAACCGGGAGGAGT WSGYGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACG GAGCTCGGGCGGCCCGAYGCTGAGTACTGGAACSGGCAGAAGGA GATCTTGGAGGASRMGCGGGCMGMGGTGGACMSSKWSTGCAGAC ACAACTACGGGG --genotype 4 CGGGTGCGGKTY CWGGAWARAYACATCTATAACCGGGAGGAGT WSGYGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACG GAGCTCGGGCGGCCCRWYGCTGAGTACTGGAACSGGCAGAAGGA GATCTTGGAGGASRMGCGGGCMSMGGTGGACMSSKWSTGCAGAC ACAACTACGGGG --genotype 5 CGGGTGCGGKYYCTGGMWARACACATCTATAACCGGGAGGAGT WSGTGCGCTTCGACAGCGACGT GGGGGAGTWCCGGGCGGTCACG GAGCTCGGGCGGCCCRWYGCTGAGTMCTGGAACCGGCAGAAGGA GATCTTGGAGGASRMGCGGGCCSAGGTGGACASSKWSTGCAGACA CAACTACGGGG --genotype 6 CGGGTGCGGTTYCTGGMWARACACATCTATAACCGGGAGGAGTT GGTGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACGG AGCTCGGGCGGCCCRWYGCTGAGTMCCGGA ACCGGCAGAAGGA GATCTTGGAGGASRMGCGGGCMSWGGTGGACMSSKWSTGCAGAC ACAACTACGGGG --genotype 7 CGGGTGCGGKYYCTGGMWARACACATCTATAACCGSGAGGAGTT SRTGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACGG AGCTCGGGCGGCCCRWYGCTGAGTMCTKGAACCGGCAGAAGGAS AWSKTGGASSRSRHRCGGGCMGWGGTGGACMSSKWSTGC AGACA CAACTACGGGGTGA genotype CGGGTGCGGKTYCTGGMHARACACATCTATAACCGGGAGGAGTT
106 8 SGTGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACGG AGCTCGGGCGGCCCRWYGCTGAGTMCTGGAACSGGCAGAAGGAG ATCTTGGAGSRSVVGCGGGCMSWGGTGGACMSSKWSTGCAGACA CAACTACGGGG --genotype 9 CGGGTGCGGKYYCWGGMHARA YACATCTATAACCGGGAGGAGY WVGTGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACG GAGCTCGGGCGGCCCKMSGCTGAGTMCTGGAACSGGCAGAAGGA GATCTTGGAGSRSMVGCGGGCMGMGGTGGACMSSKWSTGCAGAC ACAACTACGGGG --genotype 10 CGGGTGCGGKYYCTGGMHARACACATCTATAACCGGGAGGAGTW SGTGCGCTTCGACAGCGACGTGGGGGAGT WCCGGGCGGTCACGG AGCTCGGGCGGCCCRWYGCTGAGTMCTGGAACCGGCAGAAGGAG AWCTTGGAGSRSAAGCGGGCCSAGGTGGACASSKWSTGCAGACAC AACTACGGGGTGA 1010304 CGGGTGCGGKWYCWGGMWARAYACATCTATAACCGGGAGGAGT WSGYGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACG GAGCTCGGGCGGCCCGAYGCTGAGTACTGGAACSGGCAGAAG GA GATCTTGGAGGASRMGCGGGCAGYGGTGGACMSSKWSTGCAGAC ACAACTACGGGGTGA 1110102 CGGGTGCGGKHYCWGGMWARAYACATCTATAACCGGGAGGAGT WSGYGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACG GAGCTCGGGCGGCCCKMYGCTGAGTACTGGAACSSGCAGAAGGA SAWCKTGGASSRSRHRCGGGCMGHGGTGGACMSSKWSTGCAGAC ACAACTACGG GGTGA 140102 CGGGTGCGGKHYCWGGMWARAYACATCTATAACCGGGAGGAGT WSGYGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACG GAGCTCGGGCGGCCCRWYGCTGAGTMCTGGAACSGGCAGAAGGA GATCTTGGAGGASRMGCGGGCMSMGGTGGACASSKWSTGCAGAC ACAACTACGGGG --1490102 CGGGTGCGGTTCCTGSWSAGATACATCTATAACCGGSAGGAG AAC GYGCGCTTCGACAGCGACGTGGGGGAGTACCGGGCGGTGACGGA GCTGGGGCGGCCCATCGCTGAGTACTTCAACCAGCAGAAGGACAT CGTGGAGCAGASGCGGGCCSCGGTGGACASGTACTGCAGACACAA CTACGGGGTGA 150102 CGGGTGCGGTWYCWGGMWARAYACATCTATAACCGGGAGGAGT WSGTGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACG GAGCTCGGGCGG CCCRWYGCTGAGTMCTGGAACSGGCAGAAGGA GATCTTGGAGGASRMGCGGGCMSNGGTGGACMSSKWSTGCAGAC ACAACTACGGGG --
107 210102 CGGGTGCGGTWYCWGGAWARAYACATCTATAACCGGGAGGAGT TSGYGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACG GAGCTCGGGCGGCCCGAYGCTGAGTACTGGAACSGGCAGAAGGA GATCTTGGAGGASRMGCGGGCMGNG GTGGACMSSKWSTGCAGAC ACAACTACGGGG --240102 CGGGTGCGGTWYCWGGMWARAYACATCTATAACCGGGAGGAGY WSGYGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACG GAGCTCGGGCGGCCCKMBGCTGAGTMCTGGAACSGGCAGAAGGA GATCTTGGAGGASRMGCGGGCAGYGGTGGACMSSKWSTGCAGAC ACAACTACGGGG --420102 CGGGTGCGGTTYCT GGAWARACACATCTATAACCGGGAGGAGTT GGTGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACGG AGCTCGGGCGGCCCRWYGCTGAGTMCTGGAACCGGCAGAAGGAG ATCTTGGAGGASRMGCGGGCMSWGGTGGACMSSKWSTGCAGACA CAACTACGGGG --450304 CGGGTGCGGTTYMARGAAAAAYACATCTATAACCGGGAGGAGTT SGYGCGCTTCGACAGCGACGTGGGGGA GTWCCGGGCGGTCACGG AGCTCGGGCGGCCCGAYGCTGAGTACTGGAACSGGCAGAAGGAG ATCTTGGAGGASRMGCGGGCAGYGGTGGACMSSKWSTGCAGACA CAACTACGGGGTGA 460102 CGGGTGCGGTTYCTGGMWARACACATCTATAACCGGGAGGAGTT SGYGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACGG AGCTCGGGCGGCCCRWYGCTGAGTMCTGGAACSGGCAGAA GGAG ATCTTGGAGSRSVVGCGGGCMSNGGTGGACMSSKWSTGCAGACAC AACTACGGGG --540304 CGGGTGCGGKHYCWGGMHARAYACATCTATAACCGGGAGGAGT WSGTGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACG GAGCTCGGGCGGCCCRWYGCTGAGTMCTGGAACSGGCAGAAGGA GATCTTGGAGSRSVVGCGGGCMGMGGTGGACMSSKWSTGCAGAC ACAACTACGG GG --570102 CGGGTGCGGKTYCTGGAHARAYACATCTATAACCGGGAGGAGTW SGTGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACSG AGCTCGGGCGGCCCGAYGCTGAGTACTGGAACSGGCAGAAGGAG ATCTTGGAGSRSVVGCGGGCCGAGGTGGACMSSKWSTGCAGACAC AACTACGGGGTGA 620102 CGGGTGCGGTWYCWGGAHARAYACATCTATAACCGGGAGGAGY WRGTGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACG GAGCTCGGGCGGCCCDHBGCTGAGTMCTGGAACSGGCAGAAGGA GATCTTGGAGSRSVVGCGGGCMGNGGTGGACMSSKWSTGCAGAC ACAACTACGGGG --
108 850102 CGGGTGCGGKYYCTGGMYARAYACATCTATAACCGGGAGGAGTW SGTGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACGG AGCTCGGGCGGC CCDHBGCTGAGTMCTGGAACSSGCAGAAGGASR WSKTGGASSRSVDRCGGGCMGHGGTGGACMSSKWSTGCAGACAC AACTACGGGG --960102 CGGGTGCGGKYYCTGGMYARAYACATCTATAACCGGGAGGAGTA CGTGCGCTTCGACAGCGACGTGGGGGAGTWCCGGGCGGTCACGG AGCTCGGGCGGCCCGAYGCTGAGTACTGGAACSGGCAGAAGGAG ATCTTGGAGSRSMRGCGGGCCGAGG TGGACMSSKWSTGCAGACA CAACTACGGGG --Arctic Fox DQB nucleotide sequences genotype A TCATGTGCTACTTCACCAACGGGACRGAGCGGGTRCGGGGTSTGR MYARAYACATCTATAACCGGGAGGAGTWSGTGCGCTWCGACRRC GACGTGGGGGAGYWCCGGGCGGTSACGGAGCTSGGGCGGCCSRW YGCTGAGTACTKSAACCRGCAGAAGGASWTCWTGGAGC RGAMGC GGGCMGHGGTGGACACG genotype B TCATGTGCTACTTCACCAACGGGACRGAGCGGGTRCGGGGTGTGR MYARAYACATCTATAACCGGGAGGAGTACGTGCGCTWCGACRRC GACGTGGGGGAGYWCCGGGCGGTSACGGAGCTSGGGCGGCCSRW YGCTGAGTACTKSAACCAGCAGAAGGASWTCATGGAGCRGAMGC GGGCMGHGGTGGACACG genotype C TCATGTGCTACTT CACCAACGGGACRGAGCGGGTRCGGGGTGTGR MYARAYACATCTATAACCGGGAGGAGTACGTGCGCTTCGACRRCG ACGTGGGGGAGYWCCGGGCGGTSACGGAGCTSGGGCGGCCSRWY GCTGAGTACTKSAACCAGCAGAAGGACWTCATGGAGCRGAMGCG GGCCGMGGTGGACACG genotype D TCATGTGCTACTTCACCAACGGGACRGAGCGGGTRCGGGGTGTGR MCAGAYACATCTATAAC CGGGAGGAGTACGTGCGCTWCGACRRC GACGTGGGGGAGYWCCGGGCGGTGACGGAGCTGGGGCGGCCSRW CGCTGAGTACTKSAACCAGCAGAAGGACTTCATGGAGCRGAMGCG GGCMGHGGTGGACACG genotype E TCATGTGCTACTTCACCAACGGGACRGAGCGGGTRCGGGGTGTGR MCAGAYACATCTATAACCGGGAGGAGTACGTGCGCTWCGACRRC GACGTGGGGGAGCACCGGGCGG TGACGGAGCTGGGGCGGCCSRW CGCTGAGTACTKSAACCAGCAGAAGGACWTCATGGAGCRGAMGC GGGCCGMGGTGGACACG TCATGTGCTACTTCACCAACGGGACRGAGCGGGTRCGGGGTGTGG
10 9 genotype F MCAGAYACATCTATAACCGGGAGGAGTACGTGCGCTWCGACRRC GACGTGGGGGAGCACCGGGCGGTGACGGAGCTGGGGCGGCCSRW CGCTGAGTACTKSAACCAGCAGAAGG ACTTCATGGAGCRGAMGCG GGCCGMGGTGGACACG genotype G TCATGTGCTACTTCACCAACGGGACGGAGCGGGTGCGGKKTSTGG CYARACACATCTATAACCGGGAGGAGTWCGTGCGCTTCGACAGCG ACGTGGGGGAGYWCCGGGCGGTSACGGAGCTSGGGCGGCCSGWY GCTGAGTACTKSAACCGGCAGAAGGASWTCTTGGAGSAGAMGCGG GCMGHGGTGGACACG genotype H T CATGTGCTACTTCACCAACGGGACRGAGCGGGTRCGGGGTGTGG MYARAYACATCTATAACCGGGAGGAGTWCRTGCGCTWCGACARC GACGTGGGGGAGYWCCGGGCGGTSACGGAGCTSGGGCGGCCSRW YGCTGAGTMCTTSAACCRGCAGAAGGACTWCATGGASCRGAHRCG GGCMGHGGTGGACACG 1300102 TCATGTGCTACTTCACCAACGRGASRGAGCGGGTGCGGGGTGTGGC CAGACAC ATCTATAACCGGGAGGAGTACGTGCGCTWCGACRRCGA CGTGGGGGAGCWCCGGGCGGTGACGGAGCTGGGGCGGCCSAWCG CTGAGTACTTGAACCAGCAGAAGGACTTCWTGGAGCRGAMGCGG GCCGAGGTGGACACG 130102 TCATGTGYTACTTCACCAACGGGACRGAGCGGGTRCGGGGTGTGR MCAGAYACATCTATAACCGGGAGGAGTACGTGCGCTWCGACRRC GACGTGGGGGAGCACCG GGCGGTGACGGAGCTGGGGCGGCCSRW CGCTGAGTACTKSAACCAGCAGAAGGACTTCATGGAGCRGAMGCG GGCMGHGGTGGACACG 140102 TCATGTGCTACTTCACCAACGGGACGGAGCGGGTRCGGGGTGTGG CYARACACATCTATAACCGGGAGGAGTACGTGCGCTTCGACARCG ACGTGGGGGAGYWCCGRGCGGTSACGGAGCTSGGGCGGCCSRWY GCTGAGTACTKSAACCRGCAGAAGG ACWTCWTGGAGSRGAMGCG GGCCGMGGTGGACACG 1480102 TCATGTGYTACTTCACCAACGGGACRGAGCGGGTRCGGGGTGTGR MCAGAYACATCTATAACCGGGAGGAGTACGTGCGCTWCGACRRC GACGTGGGGGAGCACCGGGCGGTGACGGAGCTGGGGCGGCCSRW CGCTGAGTACTKSAACCAGCAGAAGGACTTCATGGAGCRGAMGCG GGCMGHGGTGGACACG 1500102 ---GTG CTACTTCACCAACGGGACRGAGCGGGTRCGGGGTGTGGMCAG AYACATCTATAACCGGGAGGAGTACGTGCGCTWCGACNRCGACGT GGGGGAGCACCGGGCGGTGACGGAGCTGGGGCGGCCSRWYGCTG AGTACTKSAACCAGCAGAAGGACTTCATGGAGCRGAMGCGGGCCG MGGTGGACACG
110 270102 TCATGTGCTACTTCACCAACGGGACRGAGCGGGTRCGGGGTGTGR MCAGAYACATCTATA ACCGGGAGGAGTACGTGCGCTWCGACRRC GACGTGGGGGAGCACCGGGCGGTGACGGAGCTGGGGCGGCCSRW CGCTGAGTACTKSAACCAGCAGAAGGACTTCATGGAGCRGAMGCG GGCMGHGGTGGACACG 320102 TCATGTGCTACTTCACCAACGGGACGGAGCGGGTGCGGGGTGTGA CCARAYACATCTATAACCGGGAGGAGTACGTGCGCTTCGACARCG ACGTGGGGGAGCACCGGGCGGTG ACGGAGCTGGGGCGGCCSRWY GCTGAGTACTKSAACCAGCAGAAGGACWTCATGGAGCGGAMGCG GGCCGMGGTGGACACG 360102 TCATGTGYTACTTCACCAACGGGACRGAGCGGGTRCGGGGTGKGR MCAGAYACATCTATAACCGGGAGGAGTACGTGCGCTTCGACARCG ACGTGGGGGAGYWCCGGGCGGTGACGGAGCTSGGGCGGCCSRWY GCTGAGTACTKSAACCRGCAGAAGGACWTCAT GGAGCRGAMGCG GGCMGHGGTGGACACG 430102 TCATGTGCTACTTCACCAACGGSACGGAGCGGGTGCGGGBWGTGG MSWGAYACATCTATAACCGGGAGGAGTWCGTGCGCTTCGACAGC GACGTGGGGGAGYWCCGGGCGGTGACGGAGCTGGGGCGGCCSDH CGCYGAGTACTKSAACMGCCAGAAGGACYTCCTGGAGCRGACRCG GGCCGHGGTGGACACG 480304 TCATGTGCTACTTCAC CAACGGGACGGAGCGGGTGCGGGGTSTGG CYARACACATCTATAACCGGGAGGAGTWCGTGCGCTTCGACARCG ACGTGGGGGAGYWCCGGGCGGTSACGGAGCTSGGGCGGCCSRWY GCTGAGTACTKSAACCGGCAGAAGGASWTCTTGGAGSAGAMGCGG GCMGHGGTGGACACG 510304 TCATGTGCTACTTCACCAACGGGACRGAGCGGGTRCGGGSTSTGRM YARAYACATCTATAACCGGGAGG AGTACGTGCGCTTCGACRGCGA CGTGGGGGAGYWCCGGGCGGTSACGGAGCTGGGGCGGCCCGCCG CTGAGTACTGCAACCAGCAGAAGGASWTCWTGGAGCRGAAGMGG GCCGMGGTGGACASG 530304 TCATGTGCTACTTCACCAACGGGACRGAGCGGGTRCGGKKTSTGR MYAGAYACATCTATAACCGGGAGGAGTACGTGCGCTTCGACRRCG ACGTGGGGGAGYWCCGGGCGGTGACGGAGCTG GGGCGGCCCRWC GCYGAGTACTKSAACCGGCAGAAGGACTTCWTGGARCRGAMGCG GGCMGGGGTGGACACG 700102 TCATGTGCTACTTCACCAACGGGACRGAGCGGGTRCGGGGTSTGR MYARAYACATCTATAACCGGGAGGAGTACGTGCGCTTCGACARCG ACGTGGGGGAGYWCCGGGCGGTSACGGAGCTGGGGCGGCCSRWY GCTGAGTACTKSAACCAGCAGAAGGACWTCWTGGAGCRGAM GCG GGCCGHGGTGGACACG
111 790102 TCATGTGCTACTTCACCAACGGGACGGAGCGGGTRCGGGGTGTGG CCAGAYACATCTATAACCGGGAGGAGTACGTGCGCTTCGACARCG ACGTGGGGGAGCACCGGGCGGTGACGGAGCTSGGGCGGCCSRWY GCTGAGTACTKSAACCRGCAGAAGGACWTCATGGAGCRGAMGCG GGCMGHGGTGGACACG 840102 TCATGTGYTACTTCACCAACGGGAC RGAGCGGGTRCGGGGTGTGR MCAGAYACATCTATAACCGGGAGGAGTACGTGCGCTWCGACRRC GACGTGGGGGAGCACCGGGCGGTGACGGAGCTGGGGCGGCCSRW CGCTGAGTACTKSAACCAGCAGAAGGACTTCATGGAGCRGAMGCG GGCMGHGGTGGACACG 850102 TCATGTGCTACTTCACCAACGGGACRGAGCGGGTRCGGGGTSTGGS YARAYACATCTATAACCGGGAGGAGTACGTGC GCTWCGACRRCGA CGTGGGGGAGYWCCGGGCGGTSACGGAGCTSGGGCGGCCSDHBGC TGAGTACTKSAACCVGCAGAAGGACWWCWTGGAGSRGAMGCGGG CMGHGGTGGACACG Southern Elephant Seal DQA nucleotide sequences Mile DQA *01 GTCTGGCAGCTGCCTATGTTTCAAACATACAGAAGATTTGACCCACA GGGCGCACTGACAAACTTGGCTACATTAA AACACAACTTGAACATCC TGACTGAACGGTCCAACTCCACCGCTGCTACCAATGGTATGTGTCCGC CACTCTGCCTCTCTTTACTGAACCTTCCTACACATCAGGTCTCATTCCC TTCCTCCCTACGATAGATACCCTTGACTAATTTCCAAGGATCTTTCCC CAGATCTTCTCATAGTAATTACTGAACACTCATCCTCTGCCATCTCAA AACTGAAATATTGCCATGTAGTACAAGGATCCTTACTCCCATACC ATG TTCCTTGAATCCCTCAAGGAGAAGTCCTATAGATCTGCTACTTTAATA AGCATGCCCACAGAGGGAAGGGCACAAGGATAAAGTATAGGCAGTG TATGTACACTTTCCCAAGCAGAAGGTAAGCAAGAACTCTTCTACCAT CAGATGGGGAACTGTTGATGGGAGGGCTCTTACAGGACACAATGCAG AACCTCAGGGCAGAGCTCTTTGCAATTCATATCAGTGCTGCTTCCTCA CCACAGAGGTTCCTGAG GTGACTGTGTTTCTAAAGTCTCCTGCGATGC TGGGTCAGCCCAACACCCTCATCTGTTTTGTCGACAACATCTTTCCTC CCGTGATCAATGTCACATGGTTGAAGAATAGGCACTCAGTCACAAAA GGTGTTTCTGAAACCAGCTTCCTCGCCAAGAGGGATCATTCCTTCTTA AAGATCAGTTACC Mile DQA *02 GTCTGGCAGCTGCCTATGTTTCAAACATACGGAAGATTTGACCCACA GGGCGCACT GACAAACTTGGCTACATTAAAACACAACTTGAACATCC TGACTGAACGGTCCAACTCCACCGCTGCTACCAATGGTATGTGTCCGC CACTCTGCCTCTCTTTACTGAACCTTCCTACACATCAGGTCTCATTCCC TTCCTCCCTACGATAGATACCCTTGACTAATTTCCAAGGATCTTTCCC CAGATCTTCTCATAGTAATTACTGAACACTCATCCTCTGCCATCTCAA AACTGAAATATTGCCATGTAGTACA AGGATCCTTACTCCCATACCATG
112 TTCCTTGAATCCCTCAAGGAGAAGTCCTATAGATCTGCTACTTTAATA AGCATGCCCACAGAGGGAAGGGCACAAGGATAAAGTATAGGCAGTG TATGTACACTTTCCCAAGCAGAAGGTAAGCAAGAACTCTTCTACCAT CAGATGGGGAACTGTTGATGGGAGGGCTCTTACAGGACACAATGCAG AACCTCAGGGCAGAGCTCTTTGCAATTCATATCAGTGCTGCTTCC TCA CCACAGAGGTTCCTGAGGTGACTGTGTTTCTAAAGTCTCCTGCGATGC TGGGTCAGCCCAACACCCTCATCTGTTTTGTCGACAACATCTTTCCTC CCGTGATCAATGTCACATGGTTGAAGAATAGGCACTCAGTCACAAAA GGTGTTTCTGAAACCAGCTTCCTCGCCAAGAGGGATCATTCCTTCTTA AAGATCAGTTACC Mile DQA *03 GTCTGGCAGCTGCCTATGTTTCAAACATACAGAAGA TTTGACCCACA GGGCGCACTGACAAACTTGGCTACATTAAAACACAACTTGAACATCC TGACTGAACGGTCCAACTCCACCGCTGCTACCAATGGTATGTGTCCGC CACTCTGCCTCTCTTTACTGAACCTTCCTACACATCAGGTCTCATTCCC TTCCTCCCTACGATAGATACCCTTGACTAATTTCCAAGGATCTTTCCC CAGATCTTCTCATAGTAATTACTGAACACTCATCCTCTGCCATCTCAA AACTG AGATATTGCCATGTAGTACAAGGATCCTTACTCCCATACCATG TTCCTTGAATCCCTCAAGGAGAAGTCCTATAGATCTGCTACTTTAATA AGCATGCCCACAGAGGGAAGGGCACAAGGATAAAGTATAGGCAGTG TATGTACACTTTCCCAAGCAGAAGGTAAGCAAGAACTCTTCTACCAT CAGATGGGGAACTGTTGATGGGAGGGCTCTTACAGGACACAATGCAG AACCTCAGGGCAGAGCTCTTTGCAA TTCATATCAGTGCTGCTTCCTCA CCACAGAGGTTCCTGAGGTGACTGTGTTTCTAAAGTCTCCTGCGATGC TGGGTCAGCCCAACACCCTCATCTGTTTTGTCGACAACATCTTTCCTC CCGTGATCAATGTCACATGGTTGAAGAATAGGCACTCAGTCACAAAA GGTGTTTCTGAAACCAGCTTCCTCGCCAAGAGGGATCATTCCTTCTTA AAGATCAGTTACC Mile DQA *04 GTCTGGCAGCTGCCTA TGTTTCAAACATACAGAAGATTTGACCCACA GGGCGCACTGACAAACTTGGCTACATTAAAACACAACTTGAACATCC TGACTGAACGGTCCAACTCCACCGCTGCTACCAATGGTATGTGTCCGC CACTCTGCCTCTCTTTACTGAACCTTCCTACACATCAGGTCTCATTCCC TTCCTCCCTACGATAGATACCCTTGACTAATTTCCAAGGATCTTTCCC CAGATCTTCTCATAGTAATTACTGAACACTCAT CCTCTGCCATCTCAA AACTGAAATATTGCCATGTAGTACAAGGATCCTTACTCCCATACCATG TTCCTTGAATCCCTCAAGGAGAAGTCCTATAGATCTGCTACTTTAATA AGCATGCCCACAGAGGGAAGGGCACAAGGATAAAGTATAGGCAGTG TATGTACACTTTCCCAAGCAGAAGGTAAGCAAGAACTCTTCTACCAT CAGATGGGGAACTGTTGATGGGAGGGCTCTTACAGGACACAATGCAG AACCT CAGGGCAGAGCTCTTTGCAATTCATATCAGTGCTGCTTCCTCA CCACAGAGGTTCCTGAGGTGACTGTGTTTCTAAAGTCTCCTGCGATAC TGGGTCAGGCCAACACCCTCATCTGTTTTGTCGACAACATCTTTCCTG GAGTGATCAATGTCACATGGTTGAAGAATAGGCACTCAGTCACAAAA GGTG?????????????????????????????????????????????????????????
113 Sout hern Elephant Seal DQB nucleotide sequences MileDQB*06 BB125*06 TCACCAACGGGACGGAGCGGGTGCGGGTCCTGACCAGATACA T CTATAACCGGGAGGAGTACGTGCGCTTCGACAGCGACGTGGG GGAGTACCGGCCGGTGACGGAGCTGGGGCGGCCGGACGCTGA GTAC?????????????????????????????????????????????????????????? ?? ?????????????????????????????????????????????????????????????????? ?? MileDQB*08 BB018 TCACCAACGGGACGGAGCGGGTGCGGCTCCTGACCAGATACA T CTATAACCGGGAGGAGTACGTGCGCTTCGACAGCGACGTGGG GGAGTACCGGCCGGTGACGGAGCTGGGGCGGCCGGACGCTGA GTAC????????????????????????????????? ??????????????????????????? ?????????????????????????????????????????????????????????????????? ?? MileDQB*09 B277*09 ???????????????AGCGGGTGCGGCTCCTGACCAGATACAT CTATAACCGGGAGGAGTACGTGCGCTTCGACAGCGACGTGGG GGAGTACCGGCCGGTGACGGAGCTGGGGCGGCCGGACGCTGA GTACTGGAAC CGCCAGAAGGACAT CTTGGAGCAGACGCGGGCCTAGGTGGACACGGTGTGCAGACA CAACTACCTGCAGCTCAAGGGCGAATTCCAGCACACTGGCGGC CGTTACTAGTGGATCCGAGCTA MileDQB*11 B277*11 TCACCAACGGGACGGAGCGGGTGCGGCTCCTGACCAGATACA T CTATAACCGGGAGGAGTACGTGCGCTTCGACAGCGACGTGGG GGAGTACCGGCCGGTGACGGAGCTG GGGCGGCCGGACGCTGA GTACTGGAACCGCCAGAAGGACAT CTTGGAGCAGACGCGGGCCTCGGTGGACACGGTGTGCAGACA CAACTACCTGCAGCTCAAGGGCGAATTCCAGCACACTGGCGGC CGTTACTAGTGGATCCGAGCTA MileDQB*12 BB125*12 ??????ACGGGACGGAGCGGGTGCGGCTCCTGACCAGATACAT CTATAACCGGGAGGAGTACGTGCGCTTCGACAGCGACGT GGG GGAGTACCGGCCGGTGACGGAGCTGGGGCGGCCGGACGCTGA GTACTGGAACCGCCAGAAGGACAT CTTGGAGCAGACGCGGGCCGAGGTGGACACGGTGTGCAGACA CAACTACCTGCAGCTCAAGGGCGAATTCCAGCACACT????????? ??????????????????? MileDQB*13 ??????ACGGGACGGAGCGGGTGCGGCTCCTGACCAGATACAT CTATAACCGGG AGGAGTACGTGCGCTTCGACAGCGACGTGGG
114 BB125*13 GGAGTACCGGCCGGTGACGGAGCTGGGGCGGCCGGACGCTGA GTACTGGAACCGCCAGAAGGACAT CTTGGAGCAGACGCGGGCCTCGGTGGACACGGTGTGCAGACA CAACTACCTGCAGCTCAAGGGCGAATTCCAGCACACT????????? ??????????????????? MileDQB*14 BB304 TCACCAACGGGACGGAGCGGGTGCGGCTCC TGACCAGATACA TTCTATAACCGGGAGGAGTACGTGCGCTTCGACAGCGACGTGG GGGAGTACCGGCCGGTGACGGAGCTGGGGCGGCCCTCCGCTG AGTACTGGAACCGCCAGAAGGACAT CTTGGAGCAGACGCGGGCCGAGGTGGACACGGTGTGCAGACA CAACTACCTGCAGCTCAAGGGCGAATTCCAGCACACT????????? ??????????????????? MileDQB*15 OO305 TCACC AACGGGACGGAGCGGGTGCGGCTCCTGACCAGAGACA T CTATAACCGGGAGGAGTTCGTGCGCTTCGACAGCGACGTGGG GGAGTTCCGGCCGGTGACGGAGCTGGGGCGGCCCTTCGCTGA GTACTGGAACCGCCAGAAAGACTT CATGGAGCAGACGCGGGCCGAGGTGGACACGGTGTGCAGACA CAACTACCTGCAGCTCAAGGGCGAATTCCAGCACACT????????? ??????????????????? MileDQB*16 RG017*16 TCACCAACGGGACGGAGCGGGTGCGGCTCCTGACCAGAGACA T CTATAACCGGGAGGAGTTCGTGCGCTTCGACAGCGACGTGGG GGAGTTCCGGCCGGTGACGGAGCTGGGGCGGCCCTTCGCTGA GTACTGGAACCGCCAGAAGGACTT CTTGGAGCGGACGCGGGCCGAGGTGGACACGGTGTGCAGACA CAACTACCTGCAGCTCAAGGGCGAATTCCAGCACACT? ???????? ??????????????????? MileDQB*17 RG017*17 TCACCAACGGGACGGAGCGGGTGCGGCTCCTGACCAGATACA T CTATAACCGGGAGGAGTTCGTGCGCTTCGACAGCGACGTGGG GGAGTACCGGCCGGTGACGGAGCTGGGGCGGCCCTTCGCTGA GTACTGGAACCGCCAGAAGGACAT CCTGGAGCGGACGCGGGCCGAGGTGGACACGGTGTGCAGACA CAACTACCTG CAGCTCAAGG??????????????????????????????????? ?????????? MileDQB*18 Y428 TCACCAACGGGACGGAGCGGGTGCGGGTCCTGACCAGAGACA T CTATAACCGGGAGGAGTTCGTGCGCTTCGACAGCGACGTGGG GGAGTACCGGCCGGTGACGGAGCTGGGGCGGCCCTTCGCTGA GTACTGGAACCGCCAGAAGGACAT CTTGGAGCGGACGCGGGCCGAGGTGGAC ACGGTGTGCAGACA
115 CAACTAC TGCAGTTCCAAGGG??????????????????????????????????????????? MileDQB*19 YY191 TCACCAACGGGA CGGAGCGGGTGCGGGTCCTGACCAGATACA T CTATAACCGGGAGGAGTTCGTGCGCTTCGACAGCGACGTGGG GGAGTACCGGCCGATGACGGAGCTGGGGCGGCCGGACGCTGA GTACTGGAACCGCCAGAAGGACATTCTT GGAGCAGACGCGGG CCTCGGTGGACACGGTGTGCAGACACAACTACCTGCAGCTCAA GGGCGAATTCCAGCACACT???????????????????????????? MileDQB*20 YY302 TCACCAACGGGACGGAGCGGGTGCGGGTCCTGACCAGATACA T CTATAACCGGGAGGAGTTCGTGCGCTTCGACAGCGACGTGGG GGAGTTCCGGCCGGTGACGGAGCTGGGGCGGCCCTTCGCTGA GTA CTGGAACCGCCAGAAGGACTT CATGGAGCAGACGCGGGCCGAGGTGGACACGGTGTGCAGACA CAACTAC TGCAGCTCAAGGGCGAATTCCAGCACACT????????????????????? ??????? Southern Elephant Seal DRB nucleotide sequences MileDRB*06 GGTACCTGGTCAGAGACATCTATAACGGGGAGGAGGTCACGC GCTTCGACAGCGACGTGGG GGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACA TCTTGGAGCAGACGCGGGCCGAGGTGGACACGGTGTGCAGAC ACAACTACCAGGTGGTTGAGA MileDRB*07 GGTACCTGGTCAGAGACATCTATAACGGGGAGGAGAACGTGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCCTTCGCTGAGTACTGGAACCG CCAGAAGGACTT CATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGACA CAACTACCGGGTGGGTGAGA MileDRB*08 GGCTCCTGACCAGATACATCTATAACCGGGAGGAGTTCGTGCG CTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGCT GGGGCGGCCCTCCGCTGAGTACTGGAACCGCCAGAAGGACAT CTTGGAGCGGACGCGGGCCGAGGTGGACAGGGTGTGCAGACA CAACTACCCGGTGGTTGAGA MileDRB*09 GGCTCCTGGATAGGTATTTCTATAACGGGGAGGAGTACGTGCG CTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGCT
116 GGGGCGGCCCTCCGCTGAGTACTGGAACCGCCAGAAGGACTT CATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGACA CAACTACCGGGTGGGTGAGA MileDRB*10 GGCTCCTGGATAGGTATTTCT ATAACGGGGAGGAGTACGTGCG CTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGCT GGGGCGGCCCTTCGCTGAGTACTGGAACCGCCAGAAGGACTTC ATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGACAC AACTACCGGGTGGGTGAGA MileDRN*11 GGCTCCTGGTCAGAAACATCTATAACGGGGAGGAGGTCTCGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGG TGACGGAGC TGGGGCGGCCCTTCGCTGAGTACTGGAACCGCCAGAAGGACA TCTTGGAGCGGAGGCGGGCCGAGGTGGACACGGTGTGCAGAC ACAACTACCCGGTGGGTGAGA MileDRB*12 GGCTCCTGGTCAGAAACTTCTATAACGGGGAGGAGAACGTGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACA TCT TGGAGCAGACGCGGGCCGAGGTGGACAGGGTGTGCAGAC ACAACTACCCGGTGGTTGAGA MileDRB*13 GGCTCCTGGTCAGAGACATCTATAACGGGGAGGAGGTCACGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACT TCATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGAC ACAACTACCGGGTGG GTGAGA MileDRB*14 GGTTCCTGGTCAGATACATCTATAACCGGGAGGAGTTCGTGCG CTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGCT GGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACTT CATGGAGCAGACGCGGGCCGAGGTGGACAGGGTGTGCAGACA CAACTACCCGGTGGTTGAGA MileDRB*15 GGCTCCTGGATAGGTATTTCTATAACGGGGAGGAG TACGTGCG CTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGCT GGGGCGGCCCTCCGCTGAGTACTGCAACCGCCAGAAGGACAT CTTGGAGCGGAGGCGGGCCGAGGTGGACACGGTGTGCAGACA CAACTACCGGGTGGGTGAGA MileDRB*16 GGCTCCTGGATAGGTATTTCTATAACGGGGAGGAGAACGTGCG CTTCGACAGCGACGGGGGGGAGTTCCGGCCGGTGACGGAGCT GGGG CGGCCCTTCGCTGAGTACTGGAACCGCCAGAAGGACTTC ATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGACAC AACTACCGGGTGGGTGAGA MileDRB*17 GGCTCCTGGATAGGTATATCTATAACGGGGAGGAGTACGTGCG
117 CTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGCT GGGGCGGCCCTCCGCTGAGTACTGGAACCGCCAGAAGGACTT CATGGAGCAGACGCGG GCCGCGGTGGACACGGTGTGCAGACA CAACTACCGGGTGGGTGAGA MileDRB*18 GGCTCCTGGTCAGAAACATCTATAACGGGGAGGAGGTCTCGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCCTTCGCTGAGTACTGGAACCGCCAGAAGGACA TCTTGGAGCGGAGGCGGGCCGAGGTGGACACGGTGTGCAGAC ACAACTACCCGGTGGGTGAGA MileDR B*19 GGCTCCTGGATAGGTATTTCTATAACGGGGAGGAGTACGTGCG CTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGCT GGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACAT CTTGGAGCGGACGCGGGCCGAGGTGGACAGGGTGTGCAGACA CAACTACCCGGTGGTTGAGA MileDRB*20 GGTACCTGGTCAGAGACATCTATAACGGGGAGGAGGACGTGC GCTTCGA CAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACT TCATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGAC ACAACTACCAGGTGGTTGAGA MileDRB*21 GGTTCCTGGTCAGAGACATCTATAACGGGGAGGAGGTCACGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCCTTCGCTGA GTACTGGAACCGCCAGAAGGACTT CATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGACA CAACTACCAGGTGGTTGAGA MileDRB*22 GGCTCCTGGTCAGAGACATCTATAACGGGGAGGAGGACGTGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACT TCATGGAGCAGACGCGGGCCGCGGTGGACAC GGTGTGCAGAC ACAACTACCAGGTGGTTGAGA MileDRB*23 GGTTCCTGGTCAGATACATCTATAACGGGGAGGAGAACGTGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCGGAAGCTGAGTACTGGAACCGCCAGAAGGACA TCTTGGAGCGGACGCGGGCCGCGGTGGACGCGGTGTGCAGAC ACAACTACCAGGTGGTTGAGA MileDRB*24 GGTACCTGG TCAGAGACATCTATAACGGGGAGGAGGTCACGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACT TCATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGAC ACAACTACCGGGTGGGTGAGA
118 MileDRB*25 GGCTCCTGGTCAGAGACATCTATAACGGGGAGGAGGACGTGC GCTTCGACAGCGACGTGGGGG AGTTCCGGCCGGTGACGGAGC TGGGGCGGCCCTTCGCTGAGTACTGGAACCGCCAGAAGGACTT CATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGACA CAACTACCAGGTGGTTGAGA MileDRB*26 GGCTCCTGGTCAGAGACATCTATAACGGGGAGGAGGACGTGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCGGACGCTGAGTACTGGAACCGCC AGAAGGACT TCATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGAC ACAACTACCAGGTGGTTGAGA MileDRB*27 GGTTCCTGGTCAGAGACATCTATAACGGGGAGGAGGACGTGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCCTTCGCTGAGTACTGGAACCGCCAGAAGGACTT CATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGACA CA ACTACCAGGTGGTTGAGA MileDRB*28 GGTTCCTGGTCAGAAACATCTATAACGGGGAGGAGGTCTCGCG CTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGCT GGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACAT CTTGGAGCGGACGCGGGCCGCGGTGGACACGGTGTGCAGACA CAACTACCCGGTGGTTGAGA MileDRB*29 GGTTCCTGGTCAGAAACATCTAT AACGGGGAGGAGTACGTGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCCTCCGCTGAGTACTGGAACCGCCAGAAGGACTT CTTGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGACA CAACTACCGGGTGGGTGAGA MileDRB*30 GGCTCCTGGTCAGAAACATCTATAACGGGGAGGAGGTCTCGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTG ACGGAGC TGGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACA TCTTGGAGCGGACGCGGGCCGCGGTGGACACGGTGTGCAGAC ACAACTACCCGGTGGTTGAGA MileDRB*31 GGCTCCTGACCAGATACATCTATAACCGGGAGGAGTTCGTGCG CTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGCT GGGGCGGCCCTCCGCTGAGTACTGGAACCGCCAGAAGGACAT CTTG GAGCGGACGCGGGCCGAGGTGGACAGGGTGTGCAGACA CAACTACCCGGTGGTTGAGA MileDRB*32 GGTACCTGGTCAGAGACATCTATAACGGGGAGGAGAACGTGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACA TCTTGGAGCAGACGCGGGCCGAGGTGGACACGGTGTGCAGAC ACAACTACCAGGTGGTT GAGA
119 MileDRB*33 GGCTCCTGGTCAGAGACTTCTATAACGGGGAGGAGGTCACGC GCTTCGACAGCGACGTGGGGGAGTACCGGCCGGTGACGGAGC TGGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACA TCTTGGAGCGGAGGCGGGCCGAGGTGGACACGATGTGCAGAC ACAACTACCGGGTGGGTGAGA MileDRB*34 GGCTCCTGACCAGATACATCTATAACCGGGAGGAGTT CGTGCG CTTCGACAGCGACGTGGGGGAGTACCGGCCGGTGACGGAGCT GGGGCGGCCCTCCGCTGAGTACTGGAACCGCCAGAAGGACTT CATGGAGCAGAAGCGGGCCGCGGTGGACACGGTGTGCAGACA CAACTACCGGGTGGGTGAGA MileDRB*35 GGTTCCTGGTCAGAGACATCTATAACCGGGAGGAGTACGTGCG CTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGCT GGGGCG GCCCTTCGCTGAGTACTGGAACCGCCAGAAGGACTTC ATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGACAC AACTACCGGGTGGGTGAGA MileDRB*36 GGTTCCTGGTCAGATACATCTATAACCGGGAGGAGAACGTGCG CTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGCT GGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACAT CATGGAGCAGACGCGGGC CGCGGTGGACACGGTGTGCAGACA CAACTACCGGGTGGGTGAGA MileDRB*37 GGTTCCTGGTCAGATACATCTATAACCGGGAGGAGAACGTGCG CTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGCT GGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACAT CATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGACA CAACTACCGGGTGGGTGAGA MileDRB*38 GGTACCTGGTCAGAGACATCTATAACGGGGAGGAGGTCACGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACA TCTTGGAGCAGACGCGGGCCGAGGTGGACACGGTGTGCAGAC ACAACTACCAGGTGGTTGAGA MileDRB*39 GGTACCTGGTCAGAGACATCTATAACGGGGAGGAGAACGTGC G CTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCCTTCGCTGAGTACTGGAACCGCCAGAAGGACTT CATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGACA CAACTACCGGGTGGGTGAGA MileDRB*40 GGCTCCTGGTCAGAGACATCTATAACGGGGAGGAGAACGTGC GCTTCGACAGCGACGTGGGGGAGTACCGGCCGGTGACGGAGC TGGGGCGGCCCTT CGCTGAGTACTGGAACCGCCAGAAGGACA TCTTGGAGCGGAGGCGGGCCGAGGTGGACACGGTGTGCAGAC ACAACTACCGGGTGGTTGAGA
120 MileDRB*41 GGCTCCTGGTCAGAAACATCTATAACGGGGAGGAGGTCTCGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCGTTCGCTGAGTACTGGAACCGCCAGAAGGACA TCTTGGAGCGGAGGCGGGCCGAGGT GGACACGGTGTGCAGAC ACAACTACCCGGTGGGTGAGA MileDRB*42 GGCTCCTGGTCAGAAACTTCTATAACGGGGAGGAGAACGTGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACA TCTTGGAGCAGACGCGGGCCGAGGTGGACAGGGTGTGCAGAC ACAACTACCCGGTGGTTGAGA MileDRB*43 GGT TCCTGGTCAGATACATCTATAACGGGGAGGAGAACGTGC GCTTCGACAGCGACGTGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCGGAAGCTGAGTACTGGAACCGCCAGAAGGACA TCTTGGAGCGGACGCGGGCCGCGGTGGACACGGTGTGCAGAC ACAACTACCAGGTGGTTGAGA MileDRB*44 GGCTCCTGGTCAGAGACATCTATAACGGGGAGGAGGTCACGC GCTTCGACAGCGACG TGGGGGAGTTCCGGCCGGTGACGGAGC TGGGGCGGCCGGACGCTGAGTACTGGAACCGCCAGAAGGACT TCATGGAGCAGACGCGGGCCGCGGTGGACACGGTGTGCAGAC ACAACTACCGGGTGGGTGAGA