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Review

Major Histocompatibility Complex (MHC) Markers in Conservation Biology

by
Beata Ujvari
and
Katherine Belov
*
Faculty of Veterinary Science, University of Sydney, RMC Gunn Bldg, Sydney, NSW 2006, Australia
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2011, 12(8), 5168-5186; https://doi.org/10.3390/ijms12085168
Submission received: 11 May 2011 / Revised: 27 June 2011 / Accepted: 5 August 2011 / Published: 15 August 2011
(This article belongs to the Special Issue Advances in Molecular Ecology)
Versions Notes

Abstract

:
Human impacts through habitat destruction, introduction of invasive species and climate change are increasing the number of species threatened with extinction. Decreases in population size simultaneously lead to reductions in genetic diversity, ultimately reducing the ability of populations to adapt to a changing environment. In this way, loss of genetic polymorphism is linked with extinction risk. Recent advances in sequencing technologies mean that obtaining measures of genetic diversity at functionally important genes is within reach for conservation programs. A key region of the genome that should be targeted for population genetic studies is the Major Histocompatibility Complex (MHC). MHC genes, found in all jawed vertebrates, are the most polymorphic genes in vertebrate genomes. They play key roles in immune function via immune-recognition and -surveillance and host-parasite interaction. Therefore, measuring levels of polymorphism at these genes can provide indirect measures of the immunological fitness of populations. The MHC has also been linked with mate-choice and pregnancy outcomes and has application for improving mating success in captive breeding programs. The recent discovery that genetic diversity at MHC genes may protect against the spread of contagious cancers provides an added impetus for managing and protecting MHC diversity in wild populations. Here we review the field and focus on the successful applications of MHC-typing for conservation management. We emphasize the importance of using MHC markers when planning and executing wildlife rescue and conservation programs but stress that this should not be done to the detriment of genome-wide diversity.

1. Introduction

Ever since the development of protein electrophoresis in the 1970s, biologists have realized that most natural populations exhibit high levels of genetic diversity [1]. Genetic diversity is the base material for selective processes. High levels of diversity enable populations to respond to threats such as pathogens, predators, and to long term effects such as environmental change [2]. Conversely, low levels of genetic diversity may limit a population’s ability to respond to these threats in both the long and short term [3]. The level of genetic diversity within a population represents a balance between gene flow, mutation, drift (random changes in allele frequencies), and natural selection. Habitat fragmentation can result in decreased effective population size and concurrent increase in the rate of inbreeding. The diminishing gene flow among fragmented populations may further exacerbate the loss of polymorphism. Genetic diversity is generated by mutation, and in small populations it may be eroded by drift. Natural selection may either reduce genetic diversity by fixation of alleles or promote diversity as a result of balancing or diversifying selection [4].
Genetic diversity may be reduced as a consequence of periods of fragmentation and decreased population size (bottlenecks). At first, it may seem that such loss of genetic diversity is only of concern for long-term evolutionary adaptation. However, there are immediate short-term implications as well. Loss of genetic diversity is intimately related to an increased risk of inbreeding depression resulting in decreased growth rate, fertility, fecundity and offspring viability [5–12]. Although the negative effects of inbreeding may be reduced, or purged, by selection against deleterious alleles, it is highly unlikely to completely eliminate its impact on organismal fitness [2,13]. Populations that have lost genetic diversity may also suffer from an increased probability of extinction as a consequence of increased vulnerability to novel pathogens [14,15]. Hence, the maintenance of genetic diversity is of fundamental importance in conservation biology [4,6–8,11,16–21].
During the last two decades, microsatellites (sections of DNA consisting of very short repeated nucleotide sequences) have frequently been employed in quantifying population genetic diversity and the results from such studies have often provided the basis for management recommendations (reviewed in [22]). The frequent use of microsatellites in conservation genetics is commonly based on the assumption that these markers are neutral i.e., not directly targeted by selection. However, emerging evidence shows that patterns of variation and divergence in adaptive traits are not always associated with concomitant variation in neutral markers and several studies have questioned the validity of using only neutral markers for development of conservation strategies [22–30].
Two central questions in conservation genetics are: (1) the degree to which genetic bottlenecks and low effective population size will reduce genetic diversity within a population; and (2) the impact of this reduction on the population’s long-term viability. In particular, will genetic diversity be reduced to a similar degree throughout the genome, or will some loci be affected more than others? The strength of the relationship between genetic variation and effective population size varies for different categories of markers which are subject to different intensities of selection [4,21,22,31]. Selection is likely to retain higher levels of genetic diversity at some functionally important loci, despite reductions in variation at other parts of the genome. Therefore, the use of genetic markers linked to adaptive traits, including genes involved in immune defense, reproduction and some physiological functions, is important [32,33]. Recent studies suggest that the Major Histocompatibility Complex (MHC) loci are particularly suited to this role [7,11,21,31,34–40]. These studies are reviewed below.

2. Results and Discussion

2.1. An Overview of the Major Histocompatibility Complex

The Major Histocompatibility Complex (MHC) plays a crucial role in the vertebrate immune system by encoding a collection of immune and non-immune related molecules [41,42]. The term MHC was derived from early transplant studies in humans and mice that revealed the role of glycoproteins encoded by MHC in self-identification (or histocompatibility) [43,44]. In 1975, Doherty and Zinkernagel linked the role of the MHC molecules to antigen presentation [45,46]. Since then MHC class I and class II loci have been shown to exhibit an extraordinarily high degree of polymorphism and over 1000 HLA-A, HLA-B and HLA-C MHC Class I molecules as well as hundreds of DRB alleles of Class II loci have been characterized in human populations [47]. Based on their structure and function MHC genes generally cluster into three groups, called Class I, II and III. The main function of the ubiquitously expressed classical Class Ia molecules is to present foreign cytosolic peptides to CD8+ cytotoxic T cells [48,49]. Non-classical MHC Class I molecules (Ib) accomplish a variety of cellular tasks commonly performed by epithelial cells, specifically in areas of cellular transport and regulation of lymphocyte responses to altered epithelial cells and possibly bacterial antigens [50]. In humans, MHC Class II molecules are only expressed on the surface of professional antigen presenting cells, such as macrophages, dendritic- and B-cells [51]. In dogs and some other species, they are expressed on both B- and T-cells [52]. Class II molecules present exogenously derived antigens to CD4+ T helper cells triggering an immune response, such as activation of antibody production by B-cells, resulting in the destruction of the invaded cell [51]. The MHC Class II molecules are also classified into classical (IIa) and non-classical (IIb) categories, respectively, based on their ability or inability to present antigens.
MHC Class III contains a variety of genes that do not have antigen presenting capacity, but code for other immune functions, such as complement components (e.g., C2, C4, factor B) and cytokines (e.g., TNF-α [53]).

2.2. Evolution of MHC Polymorphism

Two, not mutually exclusive, hypotheses have been suggested to explain the high level of MHC polymorphism: (i) pathogen-driven selection [54–57]; and (ii) MHC-based mate choice [58–60]. Given the central role of MHC in the vertebrate immune system, the pathogen-driven selection may be a more likely candidate for explaining the high MHC diversity observed in most vertebrates, and may serve as the underlying reason for MHC-based mate choice.
It is generally believed that some form of pathogen-driven balancing selection, a broad term that identifies any kind of natural selection where no single allele is absolutely most fit, is responsible for the high polymorphism of the MHC genes, but the exact nature of the selection continues to be a topic of debate [37,61]. A recent study, however, shows that different modes of MHC selection are operating in different systems and during different times, suggesting that the mechanisms for maintenance of MHC polymorphism in natural populations are likely to be far more complex than previously envisioned [37].

2.3. Quantifying MHC Diversity

The primary use of MHC genes in conservation to date has been for quantifying genetic diversity of natural populations, without specific conservation management implications (Table 1). The extraordinary polymorphism of MHC genes observed in vertebrates [62] prompted biologists to focus on the most variable regions of MHC molecules, the peptide binding region (PBR) of either the MHC Class I or Class II molecules. Most of the allelic variation in the peptide-binding regions is maintained by selection processes, but MHC diversity is also generated through gene duplications and copy number variation [63]. Due to the complex genomic organization and high sequence variation of MHC loci, accurate genotyping of MHC variation can prove to be rather challenging and cumbersome. Several assays including mixed lymphocyte response assay (MLR), PCR and non-PCR based molecular methods have been developed to measure MHC polymorphism between individuals and within populations. The most frequently used techniques, such as Restriction Fragment Length Polymorphism (RFLP), Single Strand Conformation Polymorphism (SSCP), Denaturing Gradient Gel Electrophoresis (DGGE), Reference Strand-mediated Conformational Analysis (RSCA) and cloning followed by sequence-based typing of PCR products, have recently been reviewed in detail [64], we therefore do not expand further on the use of these methods. Instead we will briefly review the use of the most recently developed Next-Generation Sequencing (NGS) technologies. The rapid progress of high-throughput sequencing technologies has facilitated the development of so-called “-omics” (genomics, transcriptomics, metagenomics and proteomics) and revolutionized the scale and dimensions of accessible molecular information for evolutionary and conservation biology studies. Given the increasing capacity and speed of genome sequencing, and the shrinking cost of high-throughput sequencing, hundreds of vertebrate and invertebrate genomes and transcriptomes have been sequenced (reviewed in [65], c.f. GOLD, the Genomes OnLine Database v 3.0 [66]). The genome of the endangered Giant panda (Ailuropoda melanoleuc) has recently been sequenced and the number of endangered species targeted for genome sequencing is rapidly increasing [67]. The ability to use genomic sequences from closely related species also helps with design of genetic markers in endangered species [65,68,69]. Additionally, the genomes of thousands of pathogens and microorganisms have been sequenced, allowing the study of the co-evolutionary arms race of hosts and parasites, and the selection forces driving species extinctions (e.g., Amphibian Chytridiomycosis [70]). A key factor in conservation is to understand the spatiotemporal changes in host resistance to pathogens in natural populations, particularly for populations at high risk of disease outbreaks or pathogen introductions, such as in the Tasmanian devil (Sarcophilus harrisii) [71]. The use of NGS technology will enable conservation biologists to elucidate the immunogenetic status of small or endangered populations, and hence facilitate appropriate risk assessments and design management strategies.
The rapid evolution of NGS technologies will enable such a multi-gene approach. The latest ultra high-throughput Next-Generation Sequencing (NGS) technologies are relatively low cost, quick and easy to scale up or down (reviewed in [72,73]). A few studies on non-model animals already exist using these latest technologies to characterize and quantify MHC polymorphism in various species, for example in bank voles (Myodes glareolus) [74] and the collared flycatcher (Ficedula albicollis) [75], and it will not be long before next-generation sequencing becomes the accepted tool in conservation genetics [76]. A software package has been developed to assist in the analysis of next-generation data to identify multilocus gene families [75,77,78]. It is clear that NGS will facilitate the real-time monitoring of microevolutionary processes of host-parasite interactions and the co-analysis of genotypic and phenotypic evolutionary processes on a multigene level.

2.4. MHC in Conservation Biology

Maintenance of high levels of MHC polymorphism is crucial to counteract novel pathogenic challenges and to ensure organismal long-term survival [36,63,79–81]. In spite of its unambiguous fitness significance, a dispute between Hughes [32] and peers in the early ‘90s highlighted a major apprehension about the sole use of MHC markers in conservation genetics. Opponents argued that maximizing allele diversity at MHC loci would lead to the loss of genetic diversity at many other, equally important loci [82–84]. Acevedo-Whitehouse and Cunningham [85] recently suggested a broader approach by incorporating other candidate immune genes to understand wildlife immunogenetics. We support this notion and suggest that conservation programs should take into account as many genetic markers as possible, including MHC genes.
As mentioned previously, MHC markers have been used on endangered species (a selection of these studies is summarized in Table 1) [7,38–40,86–90]. MHC genes have been shown to be associated with individual variation in parasite load [57,91] local adaptations [92], maternal-foetal interactions [93,94] and life-time reproductive success [95]. Individual variation in MHC genes has been shown to be a major component in mate choice [96–98] by providing offspring with an optimal MHC repertoire [98,99]. MHC genes have also been used to plan captive breeding programs [24,38–40,86,88–109] (Table 1). We argue that MHC typing has an important place in conservation genetics, and should be used alongside other measures of genetic variability.

2.5. The Role of MHC in Captive Breeding

In order to minimize kinship, and reduce the deleterious effects of inbreeding in captive breeding programs, zoos rely on studbooks [110–112]. Studbooks have been employed successfully in many species. In 2009, the World Association of Zoos and Aquariums counted 118 active international studbooks, including 159 species and/or sub-species [113], including the red panda (Ailurus fulgens) [114], okapi (Okapia johnstoni) and the lowland gorilla (Gorilla gorilla gorilla) [110]. Captive management could benefit from the addition of genetic management, including MHC data, to the studbook process [112]. By measuring MHC diversity in captive populations, zoo staff would be forewarned about the resilience of the population to pathogen challenges. Populations with low MHC diversity should be managed with caution, and additional MHC alleles introduced into the population if at all possible.

2.6. The Role of MHC in Genetic Rescue Programs

Translocation of individuals from genetically and demographically healthy population to populations suffering from significantly reduced genetic diversity (reviewed in [115,116]) allows genetic rescue. Several recent studies have shown that inbred populations can be ‘rescued’ by the introduction of migrants, either naturally [117], or as part of a management program [7,8,12,118–120]. Only one study so far has monitored MHC during a genetic rescue program. Madsen et al. [7] showed that the introduction of new genes into a severely inbred and isolated population of Swedish adders (Vipera berus) halted the population’s decline. The genetic polymorphism of MHC genes in the population increased following the introduction of new snakes. The once severely inbred and isolated population of Swedish vipers continues to thrive and expand [8].

2.7. The Role of MHC in Transmissible Cancer

The emergence of virus-associated, carcinogen-related wildlife cancers [121] and transmissible tumors [71] raises novel and important conservation concerns. Cancers can directly or indirectly affect conservation outcomes by severely reducing individual fitness, ultimately resulting in altered population dynamics and population declines. The existence of two naturally occurring clonally transmissible cancers, Tasmanian Devil Facial Tumor Disease (DFTD) and Canine Transmissible Venereal Tumor (CTVT) further highlights the importance of MHC variation in conservation biology. Both of these diseases are transmitted by physical contact. CTVT is a sexually transmitted tumor of canines, while DFTD affects the largest marsupial carnivore, the Tasmanian devil (reviewed in [71]). Both cancers are believed to have emerged and spread due to genetic bottlenecks and low MHC diversity in dog and devil populations [71,107,122]. Siddle et al. [107,122] found that the rapid spread of DFTD and decline in devil populations by over 80% was due to a lack of MHC Class I diversity in inbred devils [71]. Devils in the infected areas have functionally identical MHC genes which they share with DFTD cells [107,108]. Consequently, the devils’ immune system does not recognize the DFTD cells as non-self and hence does not mount an immune response. The canine disease is also believed to have emerged in inbred wolf populations with low MHC diversity, and then spread to MHC-disparate hosts when the tumor evolved the ability to evade the host immune response [71]. A third transmissible cancer has been observed in inbred populations of captive-bred golden hamsters [123,124] further emphasizing that MHC diversity not only increases the immunological fitness of populations by providing protection against pathogens, but also helps to shield individuals from transmissible cancers [71,125–127].
DFTD provides a powerful example of how the loss of genetic diversity within populations, together with an infectious disease with frequency-dependent transmission, can cause extinction and presents a cautionary tale and a warning for conservation biologists to be aware of unusual diseases in inbred populations [127]. In conclusion, we emphasize, that maintenance of maximal genetic diversity across the genome should be the ultimate goal in conservation.

3. Perspectives

Anthropogenic activities have resulted in the extinction of numerous species and massive reductions in the population numbers of others. A consequence of this is loss of genetic diversity and a primary focus of conservation biologists has been quantifying genetic diversity of endangered and threatened species. A wide range of different genetic markers have been employed in conservation studies. We argue that with increasing accessibility to next-generation sequencing technologies, MHC and other immune-related genes should be used in addition to other markers, to provide indirect measures of the immunological fitness of populations as well as the evolutionary and adaptive potential of populations—especially those threatened by disease. We emphasize that there is still scope to increase the use of MHC and other adaptive markers for management of captive-bred populations and for genetic rescue programs. Both of these conservation measures require understanding of complex evolutionary, genetic and non-genetic (environmental, behavioral and demographic) factors, and therefore it is crucial to monitor genetic diversity pre- and post-management. Future studies should also focus on the spatiotemporal changes in host resistance to pathogens in natural populations. We envisage that NGS technologies will soon become the main tool for conservation geneticists, and will enable the real-time monitoring of microevolutionary processes, including host-parasite evolution across populations and entire species.

Acknowledgments

We are grateful to Thomas Madsen for endless discussions on the subject and for comments on the manuscript. The ideas conferred in this review have been influenced and inspired by our collaborators Menna Jones and Anne-Maree Pearse. We thank Paul Hohenlohe and two anonymous reviewers for their helpful criticism and useful suggestions. The research conducted by the authors is funded by the Australian Research Council, the University of Sydney, the Eric Guiler Fund and the Save the Tasmanian Devil Appeal.

References

  1. Clark, BC. The cause for biological diversity. Sci. Am 1975, 2, 50–60. [Google Scholar]
  2. Frankham, R; Ballou, JD; Briscoe, DA. Introduction to Conservation Genetics; Cambridge University Press: Cambridge, UK, 2002; p. 617. [Google Scholar]
  3. Willi, Y; van Buskirk, J; Hoffman, AA. Limits to the adaptive potential of small populations. Ann. Rev. Ecol. Syst 2006, 37, 433–458. [Google Scholar]
  4. Frankham, R. Relationship of genetic variation to population size in wildlife. Conserv. Biol 1996, 10, 1500–1508. [Google Scholar]
  5. Keller, LF. Inbreeding and its fitness effects in an insular population of song sparrows (Melospiza melodia). Evolution 1998, 52, 240–250. [Google Scholar]
  6. Madsen, T; Stille, B; Shine, R. Inbreeding depression in an isolated population of adders (Vipera berus). Biol. Conserv 1996, 75, 113–118. [Google Scholar]
  7. Madsen, T; Olsson, M; Shine, R; Wittzell, H. Restoration of an inbred adder population. Nature 1999, 402, 34–35. [Google Scholar]
  8. Madsen, T; Ujvari, B; Olsson, M. Novel genes continue to enhance population growth in adders (Vipera berus). Biol. Conserv 2004, 120, 145–147. [Google Scholar]
  9. Saccheri, I; Kuussari, M; Kankare, M; Vikman, P; Fortelius, W; Hanski, I. Inbreeding and extinction in a butterfly metapopulation. Nature 1998, 92, 91–99. [Google Scholar]
  10. Slate, J; Kruuk, LEB; Marshall, TC; Pemberton, JM; Clutton-Brock, TH. Inbreeding depression influences lifetime breeding success in a wild population of red deer (Cervus elaphus). Proc. R. Soc. Lond. B 2000, 267, 1657–1662. [Google Scholar]
  11. Ujvari, B; Madsen, T; Kotenko, T; Olsson, M; Shine, R; Wittzell, H. Low genetic diversity threatens imminent extinction for the Hungarian meadow viper (Vipera ursinii rakosiensis). Biol. Conserv 2002, 105, 127–130. [Google Scholar]
  12. Westemeier, RL; Brawn, JD; Simpson, SA; Esker, TL; Jansen, RW; Walk, JW; Kershner, EL; Bouzat, JL; Paige, KN. Tracking the long-term decline and recovery of an isolated population. Science 1998, 282, 1695–1698. [Google Scholar]
  13. Frankham, R; Gilligan, DM; Morris, D; Briscoe, DA. Inbreeding and extinction: Effects of purging. Conserv. Genet 2001, 2, 279–284. [Google Scholar]
  14. O’Brien, SJ; Roelke, ME; Marker, L; Newman, A; Winkler, CA; Meltzer, D; Colly, L; Evermann, JF; Bush, M; Wildt, DE. Genetic basis for species vulnerability in the cheetah. Science 1985, 227, 1428–1434. [Google Scholar]
  15. O’Brien, SJ; Evermann, JF. Interactive influence of infectious disease and genetic diversity in natural populations. Trends Ecol. Evol 1988, 3, 254–259. [Google Scholar]
  16. Frankham, R. Inbreeding and extinction: A threshold effect. Conserv. Biol 1995, 9, 792–799. [Google Scholar]
  17. Frankham, R. Inbreeding and extinction: Island populations. Conserv. Biol 1998, 12, 665–675. [Google Scholar]
  18. Frankham, R. Genetics and extinction. Biol. Conserv 2005, 126, 131–140. [Google Scholar]
  19. Frankham, R; Ralls, K. Conservation biology—Inbreeding leads to extinction. Nature 1998, 92, 1–2. [Google Scholar]
  20. Frankham, R; Lee, K; Montgomery, ME; England, PR; Lowe, E; Briscoe, DA. Do population size bottlenecks reduce evolutionary potential? Anim. Conserv 1999, 2, 255–260. [Google Scholar]
  21. Ujvari, B; Madsen, T; Olsson, M. Discrepancy in mitochondrial and nuclear polymorphism in meadow vipers (Vipera ursinii) questions the unambiguous use of mtDNA in conservation studies. Amphibia–Reptilia 2005, 26, 287–292. [Google Scholar]
  22. Madsen, T; Olsson, M; Wittzell, H; Stille, B; Gullberg, A; Shine, R; Andersson, S; Tegelström, H. Population size and genetic diversity in sand lizards (Lacerta agilis) and adders (Vipera berus). Biol. Conserv 2000, 9, 257–262. [Google Scholar]
  23. Gomez-Mestre, I; Tejedo, M. Contrasting patterns of quantitative and neutral genetic variation in locally adapted populations of the natterjack toad, Bufo calamita. Evolution 2004, 58, 2343–2352. [Google Scholar]
  24. Hedrick, PW. Conservation genetics: Where are we now? Trends Ecol. Evol 2001, 16, 629–636. [Google Scholar]
  25. Luikart, G; England, PR; Tallmon, D; Jordan, S; Taberlet, P. The power and promise of population genomics: From genotyping to genome typing. Nat. Rev. Genet 2003, 4, 981–999. [Google Scholar]
  26. Lynch, M. A Quantitative Genetic Perspective on Conservation Issues. In Conservation Genetics: Case Histories From Nature; Avise, JC, Hamrick, JL, Eds.; Chapman and Hall: New York, NY, USA, 1996; pp. 471–490. [Google Scholar]
  27. McKay, JK; Latta, RG. Adaptive population divergence: Markers, QTL, and traits. Trends Ecol. Evol 2002, 17, 285–291. [Google Scholar]
  28. Palo, JU; O’Hara, RB; Laugen, AT; Laurila, A; Primmer, CR; Merila, J. Latitudinal divergence of common frog (Rana temporaria) life history traits by natural selection: Evidence from a comparison of molecular and quantitative genetic data. Mol. Ecol 2003, 12, 1963–1978. [Google Scholar]
  29. Pfrender, ME; Spitze, K; Hicks, J; Morgan, K; Latta, L; Lynch, M. Lack of concordance between genetic diversity estimates at the molecular and quantitative-trait levels. Conserv. Genet 2000, 1, 263–269. [Google Scholar]
  30. Reed, DH; Frankham, R. How closely correlated are molecular and quantitative measures of genetic variation? A meta-analysis. Evolution 2001, 55, 1095–1110. [Google Scholar]
  31. Aguilar, A; Roemer, G; Debenham, S; Binns, M; Garcelon, D; Wayne, RK. High MHC diversity maintained by balancing selection in an otherwise genetically monomorphic mammal. Proc. Natl. Acad. Sci. USA 2004, 101, 3490–3494. [Google Scholar]
  32. Hughes, AL. MHC polymorphism and the design of captive breeding programs. Conserv. Biol 1991, 5, 249–251. [Google Scholar]
  33. O’Brien, SJ. A role for molecular genetics in biological conservation. Proc. Natl. Acad. Sci. USA 1994, 91, 5748–5755. [Google Scholar]
  34. Hedrick, PW; Parker, KM. MHC variation in the endangered gila topminnow. Evolution 1998, 52, 194–199. [Google Scholar]
  35. Paterson, S; Wilson, K; Pemberton, JM. Major histocompatibility complex variation associated with juvenile survival and parasite resistance in a large unmanaged ungulate population. Proc. Natl. Acad. Sci. USA 1998, 95, 3714–3719. [Google Scholar]
  36. Sommer, S. The importance of immune gene variability (MHC) in evolutionary ecology and conservation. Front Zool 2005, 2, 16:1–16:18. [Google Scholar]
  37. Ekblom, R; Sæther, SA; Fiske, P; Kålås, JA; Höglund, J. Balancing selection, sexual selection and geographic structure in MHC genes of Great Snipe. Genetica 2010, 18, 453–461. [Google Scholar]
  38. Miller, HC; Miller, KA; Daugherty, CH. Reduced MHC variation in a threatened tuatara species. Animal Conserv 2008, 11, 206–214. [Google Scholar]
  39. Miller, HC; Allendorf, F; Daugherty, CH. Genetic diversity and differentiation at MHC genes in island populations of tuatara (Sphenodon spp.). Mol. Ecol 2010, 19, 3894–3908. [Google Scholar]
  40. Becker, L; Nieberg, C; Jahreis, K; Peters, E. MHC class II variation in the endangered European mink Mustela lutreola (L. 1761)—Consequences for species conservation. Immunogenetics 2009, 61, 281–288. [Google Scholar]
  41. Benacerraf, B. Role of MHC gene products in immune regulation. Science 1981, 212, 1229–1238. [Google Scholar]
  42. Snell, GD. Studies in histocompatibility. Science 1981, 213, 172–178. [Google Scholar]
  43. Gorer, PA; Lyman, S; Snell, GD. Studies on the genetic and antigenic basis of tumour transplantation. Linkage between a histocompatibility gene and ‘fused’ in mice. Proc. R. Soc. London Ser. B 1948, 135, 499–505. [Google Scholar]
  44. Dausset, J. Iso–leuco–anticorps. Acta Haematol 1959, 20, 156. [Google Scholar]
  45. Doherty, PC; Zinkernagel, RM. Enhanced immunological surveillance in mice heterozygous at the H–2 gene complex. Nature 1975, 256, 50–52. [Google Scholar]
  46. Doherty, PC; Zinkernagel, RM. A biological role for the major histocompatibility antigens. Lancet 1975, 1, 1406–1409. [Google Scholar]
  47. IMGT/HLA Database. European Bioinformatics Institute: Cambridge, UK, 2011; Available online: http://www.ebi.ac.uk/imgt/hla/stats.html (accessed on 11 August 2011).
  48. Townsend, AR; Gotch, FM; Davey, J. Cytotoxic T cells recognize fragments of the influenza nucleoprotein. Cell 1985, 2, 57–67. [Google Scholar]
  49. Cresswell, P. Antigen processing and presentation. Immunol. Rev 2005, 207, 5–7. [Google Scholar]
  50. Blumberg, RS. Current concepts in mucosal immunity. II. One size fits all: Nonclassical MHC molecules fulfill multiple roles in epithelial cell function. Am. J. Physiol 1998, 274, 227–231. [Google Scholar]
  51. Cresswell, P; Ackerman, AL; Giodini, A; Peaper, DR; Wearsch, PA. Mechanisms of MHC class I–restricted antigen processing and crosspresentation. Immunol. Rev 2005, 207, 145–157. [Google Scholar]
  52. Huisinga, M; Failing, K; Reinacher, M. MHC class II expression by follicular keratinocytes in canine demodicosis—An immunohistochemical study. Vet. Immuno. Immunopath 2007, 118, 210–220. [Google Scholar]
  53. Aguado, B; Milner, CM; Campbell, RD. Genes of the MHC class III region and the functions of the proteins they encode. In HLA and MHC: Genes, Molecules and Function; Browning, M, McMichael, A, Eds.; Bios Scientific Publishers: Oxford, UK, 1996; pp. 9–76. [Google Scholar]
  54. Wegner, KM; Kalbe, M; Kurtz, J; Reusch, TBH; Milinski, M. Parasite selection for immunogenetic optimality. Science 2003, 301, 1343. [Google Scholar]
  55. Harf, R; Sommer, S. Association between major histocompatibility complex class II DRB alleles and parasite load in the hairy-footed gerbil, Gerbillurus paeba, in the southern Kalahari. Mol. Ecol 2005, 14, 85–91. [Google Scholar]
  56. Schad, J; Ganzhorn, JU; Sommer, S. Parasite burden and constitution of major histocompatibility complex in the Malagasy mouse lemur (Microcebus murinus). Evol 2005, 59, 439–450. [Google Scholar]
  57. Madsen, T; Ujvari, B. MHC Class I associates with parasite resistance and longevity in tropical pythons. J. Evol. Biol 2006, 19, 1973–1978. [Google Scholar]
  58. Potts, WK; Manning, CJ; Wakeland, EK. The role of infectious disease, inbreeding and mating preferences in maintaining MHC genetic diversity: An experimental test. Philos. Trans. R. Soc. London 1994, 346, 369–378. [Google Scholar]
  59. Wedekind, C; Seeback, T; Bettens, F; Paepke, AJ. MHC-dependent mate choice in humans. Proc. R. Soc. London Ser. B 1995, 260, 245–249. [Google Scholar]
  60. Olsson, M; Madsen, T; Nordby, J; Wapstra, E; Ujvari, B; Wittsell, H. Major histocompatibility complex and mate choice in sand lizards. Proc. R. Soc. London Ser. B 2003, 270, S254–S256. [Google Scholar]
  61. Hedrick, PW. Perspective: Highly variable loci and their interpretation in evolution and conservation. Evolution 1999, 53, 313–318. [Google Scholar]
  62. Kelley, J; Walter, L; Trowsdale, J. Comparative genomics of major histocompatibility complexes. Immunogenetics 2005, 56, 683–695. [Google Scholar]
  63. Bernatchez, L; Landry, C. MHC studies in nonmodel vertebrates: What have we learned about natural selection in 15 years? J. Evol. Biol 2003, 16, 363–377. [Google Scholar]
  64. Babik, W. Methods for MHC genotyping in non-model vertebrates. Mol. Ecol. Resour 2010, 10, 237–251. [Google Scholar]
  65. Kohn, MH; Murphy, WJ; Ostrander, EA; Wayne, RK. Genomics and conservation genetics. Trends Ecol. Evol 2006, 21, 629–637. [Google Scholar]
  66. GOLD, Genomes OnLine Database v 3.0. Nikos Kyrpides: Walnut Creek, CA, USA, 2011; Available online: http://www.genomesonline.org/members.htm (accessed on 11 August 2011).
  67. Li, R; Fan, W; Tian, G; Zhu, H; He, L; Cai, J; Huang, Q; Cai, Q; Li, B; Bai, Y; et al. The sequence and de novo assembly of the giant panda genome. Nature 2010, 6, 11–17. [Google Scholar]
  68. Lindblad-Toh, K; Lindblad-Toh, K; Wade, CM; Mikkelsen, TS; Karlsson, EK; Jaffe, DB; Kamal, M; Clamp, M; Chang, JL; Kulbokas, EJ, III; Zody, MC; et al. Genome sequence, comparative analysis and haplotype structure of the domestic dog. Nature 2005, 438, 803–819. [Google Scholar]
  69. O’Brien, SJ; Wienberg, J; Lyons, LA. Comparative genomics: Lessons from cats. Trends Genet 1997, 13, 393–399. [Google Scholar]
  70. Richmond, JQ; Savage, AE; Zamudio, KR; Rosenblum, EB. Toward immunogenetic studies of Amphibian Chytridiomycosis: Linking innate and acquired immunity. BioScience 2009, 59, 311–320. [Google Scholar]
  71. Belov, K. The role of the major histocompatibility complex in the spread of contagious cancers. Mamm. Genome 2011, 22, 83–90. [Google Scholar]
  72. Shendure, J; Ji, HL. Next-generation DNA sequencing. Nat. Biotechnol 2008, 26, 1135–1145. [Google Scholar]
  73. Babik, W; Taberlet, P; Ejsmond, MJ; Radwan, J. New generation sequencers as a tool for genotyping of highly polymorphic multilocus MHC system. Mol. Ecol. Resour 2009, 9, 713–719. [Google Scholar]
  74. Kloch, A; Babik, W; Bajer, A; Sinski, E; Radwan, J. Effects of an MHCDRB genotype and allele number on the load of gut parasites in the bank vole Myodes glareolus. Mol. Ecol 2010, 19, 255–265. [Google Scholar]
  75. Zagalska-Neubauer, M; Babik, W; Stuglik, M; Gustafsson, L; Cichoń, M; Radwan, J. 454 sequencing reveals extreme complexity of the class II major histocompatibility complex in the collared flycatcher. BMC Evol. Biol 2010, 10, 395–410. [Google Scholar]
  76. Ouborg, NJ; Pertoldi, C; Loeschcke, V; Bijlsma, RK; Hedrick, PW. Conservation genetics in transition to conservation genomics. Trends Genet 2010, 26, 177–187. [Google Scholar]
  77. Bentley, G; Higuchi, R; Hoglund, B; Goodridge, D; Sayer, D; Trachtenberg, EA; Erlich, HA. High-resolution, high-throughput HLA genotyping by next-generation sequencing. Tissue Antigens 2009, 74, 393–403. [Google Scholar]
  78. Stuglik, MT; Radwan, J; Babik, W. jMHC: Software assistant for multilocus genotyping of gene families using next-generation amplicon sequencing. Mol. Ecol. Resour 2011, 11, 739–742. [Google Scholar]
  79. Alcaide, M; Lemus, JA; Blanco, G; Tella, JL; Serrano, D; Negro, JJ; Rodriguez, A; Garcia-Montijano, M. MHC diversity and differential exposure to pathogens in kestrels (Aves: Falconidae). Mol. Ecol 2010, 19, 691–705. [Google Scholar]
  80. Piertney, SB; Oliver, MK. The evolutionary ecology of the major histocompatibility complex (MHC). Heredity 2006, 96, 7–21. [Google Scholar]
  81. Spurgin, LG; Richardson, DS. How pathogens drive genetic diversity: MHC, mechanisms and misunderstandings. Proc. R. Soc. London Ser. B 2010, 277, 979–988. [Google Scholar]
  82. Vrijenhoek, RC; Leberg, PL. Let’s not throw the baby out with the bathwater: A comment on management for MHC diversity in captive populations. Conser. Biol 1991, 5, 252–253. [Google Scholar]
  83. Gilpin, M; Wills, C. MHC and captive breeding: A rebuttal. Conserv. Biol 1991, 5, 554–555. [Google Scholar]
  84. Miller, PS; Hedrick, PW. MHC polymorphism and the design of captive breeding programs: Simple solutions are not the answer. Conserv. Biol 1991, 5, 556–558. [Google Scholar]
  85. Acevedo-Whitehouse, K; Cunningham, AA. Is MHC enough for understanding wildlife immunogenetics? Trend Ecol. Evol 2006, 21, 433–438. [Google Scholar]
  86. Zhu, L; Ruan, XD; Ge, YF; Wan, QH; Fang, SG. Low major histocompatibility complex class II DQA diversity in the giant panda (Ailuropoda melanoleuca). BMC Genet 2007, 8, 29. [Google Scholar]
  87. Wan, QH; Zhu, L; Wu, H; Fang, SG. Major histocompatibility complex class II variation in the giant panda (Ailuropoda melanoleuca). Mol. Ecol 2006, 15, 2441–2450. [Google Scholar]
  88. Mason, RA; Browning, TL; Eldridge, MDB. Reduced MHC class II diversity in island compared to mainland populations of the black-footed rock-wallaby (Petrogale lateralis lateralis). Conserv. Genet 2011, 12, 91–103. [Google Scholar]
  89. Smulders, MJM; Snoek, LB; Booy, G; Vosman, B. Complete loss of MHC genetic diversity in the common hamster (Cricetus cricetus) population in the Netherlands. Consequences for conservation strategies. Conserv. Genet 2003, 4, 441–451. [Google Scholar]
  90. Zhang, B; Fang, SG; Xi, YM. Major histocompatibility complex variation in the endangered crested ibis Nipponia nippon and implications for reintroduction. Biochem. Genet 2006, 44, 110–120. [Google Scholar]
  91. Schwensow, N; Fietz, J; Dausmann, KH; Sommer, S. Neutral versus adaptive genetic variation in parasite resistance: Importance of major histocompatibility complex supertypes in a freeranging primate. Heredity 2007, 99, 265–277. [Google Scholar]
  92. Evans, ML; Neff, BD; Heath, DD. MHC genetic structure and divergence across populations of Chinook salmon (Oncorhynchus tshawytscha). Heredity 2010, 104, 449–459. [Google Scholar]
  93. Thomas, ML; Harger, H; Wagenerd, K; Rabinb, S; Gill, TJ. Hla sharing and spontaneous-abortion in humans. Am. J. Obst. Gynecol 1985, 151, 1053–1058. [Google Scholar]
  94. Hedrick, PW; Thomson, G. Maternal-fetal interactions and the maintenance of HLA polymorphism. Genetics 1988, 119, 205–212. [Google Scholar]
  95. Kalbe, M; Eizaguirre, C; Dankert, I; Reusch, TBH; Sommerfeld, RD; Wegner, KM; Milinski, M. Lifetime reproductive success is maximized with optimal major histocompatibility complex diversity. Proc. R. Soc. B 2009, 276, 925–934. [Google Scholar] [Green Version]
  96. Penn, DJ; Potts, WK. The evolution of mating preferences and major histocompatibility complex genes. Am. Nat 1999, 153, 145–163. [Google Scholar]
  97. Penn, DJ. The scent of genetic compatibility: Sexual selection and the major histocompatibility complex. Ethology 2002, 108, 1–21. [Google Scholar]
  98. Eizaguirre, C; Yeates, SE; Lenz, TL; Kalbe, M; Milinski, M. MHC-based mate choice combines good genes and maintenance of MHC polymorphism. Mol. Ecol 2009, 15, 3316–3329. [Google Scholar]
  99. Milinski, M; Griffiths, S; Wegner, KM; Reusch, TBH; Haas-Assenbaum, A; Boehm, T. Mate choice decisions of stickleback females predictably modified by MHC peptide ligands. Proc. Natl Acad. Sci. USA 2005, 102, 4414–4418. [Google Scholar]
  100. Aguilar, A; Jessup, DA; Estes, J; Garza, JC. The distribution of nuclear genetic variation and historical demography of sea otters. Anim. Conserv 2008, 11, 35–45. [Google Scholar]
  101. Alcaide, M; Edwards, SV; Negro, JJ. Characterization, polymorphism, and evolution of MHC class II B genes in birds of prey. J. Mol. Evol 2007, 65, 541–554. [Google Scholar]
  102. Edwards, SV; Potts, WK. Polymorphism of genes in the major histocompatibility complex: Implications for conservation genetics of vertebrates. In Molecular Genetic Approaches in Conservation; Smith, TB, Wayne, RK, Eds.; Oxford University Press: New York, NY, USA, 1996; pp. 214–237. [Google Scholar]
  103. Fernandez De Mera, IG; Vicente, J; Perez de la Lastra, JM; Mangold, AJ; Naranjo, V; Fierro, Y; de la Fuente, J; Gortazar, C. Reduced major histocompatibility complex class II polymorphism in a hunter-managed isolated Iberian red deer population. J. Zool 2009, 277, 157–170. [Google Scholar]
  104. Hansen, MM; Skaala, O; Jensen, LF; Bekkevold, D; Mensberg, K-LD. Gene flow, effective population size and selection at major histocompatibility complex genes: Brown trout in the Hardanger Fjord, Norway. Mol. Ecol 2007, 16, 1413–1425. [Google Scholar]
  105. Peters, MB; Turner, TF. Genetic variation of the major histocompatibility complex (MHC class II b gene) in the threatened Gila trout, Oncorhynchus gilae gilae. Conserv. Genet 2008, 9, 257–270. [Google Scholar]
  106. Pokorny, I; Sharma, R; Goyal, SP; Mishra, S; Tiedemann, R. MHC class I and MHC class II DRB gene variability in wild and captive Bengal tigers (Panthera tigris tigris). Immunogenetics 2010, 62, 667–679. [Google Scholar]
  107. Siddle, HV; Kreiss, A; Eldridge, MDB; Noonan, E; Clarke, CJ; Pyecroft, S; Woods, GM; Belov, K. Transmission of a fatal clonal tumor by biting occurs due to depleted MHC diversity in a threatened carnivorous marsupial. Proc. Natl. Acad. Sci. USA 2007, 104, 16221–16226. [Google Scholar]
  108. Siddle, HV; Sanderson, C; Belov, K. Characterization of major histocompatibility complex class I and class II genes from the Tasmanian devil (Sarcophilus harrisii). Immunogenetics 2007, 59, 753–760. [Google Scholar]
  109. Smith, S; Belov, K; Hughes, J. MHC screening for marsupial conservation: Extremely low levels of class II diversity indicate population vulnerability for an endangered Australian marsupial. Conserv. Genet 2010, 11, 269–278. [Google Scholar]
  110. Rietkerk, F; Brouwer, K; Smits, S; Damen, M. EEP Yearbook, 1997/98. EAZA Executive Office: Amsterdam, The Netherlands, 1998. [Google Scholar]
  111. Glatston, AR. Studbooks the basis of breeding programmes. Int. Zoo Yb 1986, 24, 162–167. [Google Scholar]
  112. Glatston, AR. Relevance of studbook data to the successful captive management of grey mouse lemurs. Int. J. Primatol 2001, 22, 57–69. [Google Scholar]
  113. International Studbooks. World Association of Zoos and Aquariums: Gland, Switzerland, 2011; Available online: http://www.waza.org/en/site/conservation/international-studbooks (accessed on 11 August 2011).
  114. Glatston, AR. Ten years after: The history of the red panda studbook. In Proceedings of the 5th World Conference on Breeding Endangered Species in Captivity; Dresser, BL, Reece, RW, Maruska, EJ, Eds.; Cincinnati Zoo and Botanical Garden: Cincinnati, OH, USA, 9–12 October 1988; pp. 53–66. [Google Scholar]
  115. Tallmon, DA; Luikart, G; Waples, RS. The alluring simplicity and complex reality of genetic rescue. Trends Ecol. Evol 2004, 19, 489–496. [Google Scholar]
  116. Edmands, S. Between a rock and a hard place: Evaluating the relative risks of inbreeding and outbreeding for conservation and management. Mol. Ecol 2007, 16, 463–475. [Google Scholar]
  117. Vilà, C; Sundqvist, A-K; Flagstad, Ø; Seddon, J; Bjornerfeldt, S; Kojola, I; Casulli, A; Sand, H; Wabakken, P; Ellegren, H. Rescue of a severely bottlenecked wolf (Canis lupus) population by a single immigrant. Proc. R. Soc. London Ser. B 2003, 270, 91–97. [Google Scholar]
  118. Bouzat, JL; Johnson, JE; Toepfer, JE; Simpson, SA; Esker, TL; Westemeier, RL. Beyond the beneficial effects of translocations in an effective tool for the genetic restoration of isolated populations. Conserv. Genet 2009, 10, 191–201. [Google Scholar]
  119. Land, ED; Lacy, RC. Introgression level achieved through Florida panther genetic restoration. Endanger. Species Update 2000, 17, 100–105. [Google Scholar]
  120. Hedrick, PW; Fredrickson, R. Captive breeding and the reintroduction of Mexican and red wolves. Mol. Ecol 2008, 17, 344–350. [Google Scholar]
  121. McAloose, D; Newton, AL. Wildlife cancer: A conservation perspective. Nat. Rev. Cancer 2009, 9, 517–526. [Google Scholar]
  122. Siddle, HV; Marzec, J; Cheng, Y; Jones, M; Belov, K. MHC gene copy number variations in Tasmanian devils: Implications for the spread of a contagious cancer. Proc. Biol. Sci. London Ser. B 2010, 277, 2001–2006. [Google Scholar]
  123. Brindley, DC; Banfield, WG. Contagious tumor of hamster. J. Natl. Cancer Inst 1961, 26, 949–957. [Google Scholar]
  124. Fabrizio, AM. An induced transmissible sarcoma in hamsters—11-year observation through 288 passages. Cancer Res 1965, 25, 107–117. [Google Scholar]
  125. Kurbel, S; Plestina, S; Vrbanec, D. Occurrence of the acquired immunity in early vertebrates due to danger of transmissible cancers similar to canine venereal tumors. Med. Hypotheses 2007, 68, 1185–1186. [Google Scholar]
  126. Murgia, C; Pritchard, JK; Kim, SY; Fassati, A; Weiss, RA. Clonal origin and evolution of a transmissible cancer. Cell 2006, 126, 477–487. [Google Scholar]
  127. McCallum, H. Tasmanian devil facial tumour disease: Lessons for conservation biology. Trends Ecol. Evol 2008, 23, 631–637. [Google Scholar]
  128. Oosterhout, CV; Smith, AM; Hanfling, B; Ramnarine, IW; Mohammed, RS; Cable, J. The guppy as a conservation model: Implications of parasitism and inbreeding for reintroduction success. Conserv. Biol 2007, 21, 1573–1583. [Google Scholar]
  129. Miller, HC; Lambert, DM. Genetic drift outweighs balancing selection in shaping post-bottleneck major histocompatibility complex variation in New Zealand robins (Petroicidae). Mol. Ecol 2004, 13, 3709–3721. [Google Scholar]
  130. Bollmer, JL; Vargas, FH; Parker, PG. Low MHC variation in the endangered Galapagos penguin (Spheniscus mendiculus). Immunogenetics 2007, 59, 593–602. [Google Scholar]
  131. Salas, ER. Molecular Ecology of the Endangered Gouldian Finch (Erythrura gouldiae). Ph.D. Thesis; James Cook University: Townsville, Australia, 2008. [Google Scholar]
  132. Richardson, DS; Westherdahl, H. MHC diversity in two Acrocephalus species: The outbred great reed warbler and the inbred Seychelles warbler. Mol. Ecol 2003, 12, 3523–3529. [Google Scholar]
  133. Hedrick, PW; Parker, KM; Lee, RN. Using microsatellite and MHC variation to identify species, ESUs, and MUs in the endangered Sonoran topminnow. Mol. Ecol 2001, 10, 1399–1412. [Google Scholar]
  134. Alcaide, M; Scott, VE; Cadahıa, L; Negro, JJ. MHC class I genes of birds of prey: Isolation, polymorphism and diversifying selection. Conserv. Genet 2009, 10, 1349–1355. [Google Scholar]
  135. Archie, EA; Henry, T; Maldonado, JE; Moss, CJ; Poole, JH; Pearson, VR; Murray, S; Alberts, SC; Fleischer, RC. Major histocompatibility complex variation and evolution at a single, expressed DQA locus in two genera of elephants. Immunogenetics 2010, 62, 85–100. [Google Scholar]
  136. Lekutis, C; Letvin, NL. MHC expression of African green monkeys of Barbados is limited in heterogeneity. J. Med. Primatol 1995, 24, 81–86. [Google Scholar]
  137. Marsden, CD; Mable, BK; Woodroffe, R; Rasmussen, GSA; Cleaveland, S; McNutt, JW; Emmanuel, M; Thomas, R; Kennedy, LJ. Highly endangered African wild dogs (Lycaon pictus) lack variation at the major histocompatibility complex. J. Hered 2009, 100, S54–S65. [Google Scholar]
  138. Mikko, S; Spencer, M; Morris, B; Stabile, S; Basu, T; Stormont, C; Andersson, L. A comparative analysis of Mhc DRB3 polymorphism in the American Bison (Bison bison). J. Hered 1997, 88, 499–503. [Google Scholar]
  139. Trau, DL; Li, H; Dasgupta, N; O’Toole, D; Eldridge, JA; Besser, TE; Davies, CJ. Resistance to malignant catarrhal fever in American bison (Bison bison) is associated with MHC class IIa polymorphisms. Anim. Genet 2007, 38, 141–146. [Google Scholar]
  140. Seddon, JM; Baverstock, PR. Variation on islands: Major histocompatibility complex (MHC) polymorphism in populations of the Australian bush rat. Mol. Ecol 1999, 8, 2071–2079. [Google Scholar]
  141. Go, Y; Rakotoarisoa, G; Kawamoto, Y; Shima, T; Koyama, N; Randrianjafy, A; Mora, R; Hirai, H. Characterization and evolution of major histocompatibility complex class II genes in the aye-aye, Daubentonia madagascariensis. Primates 2005, 46, 135–139. [Google Scholar]
  142. Yang, G; Yan, J; Zhou, K; Wei, F. Sequence variation and gene duplication at MHC DQB loci of baiji (Lipotes vexillifer), a Chinese river dolphin. J. Hered 2005, 96, 310–317. [Google Scholar]
  143. Goda, N; Mano, T; Kosintev, P; Vorobiev, A; Masuda, R. Allelic diversity of the MHC class II DRB genes in brown bears (Ursus arctos) and a comparison of DRB sequences within the family Ursidae. Tissue Antigens 2010, 76, 404–410. [Google Scholar]
  144. Bowen, L; Aldridge, BM; Stott, JL; Gulland, F; Woo, J; van Bonn, W; Johnson, ML. Molecular characterization of expressed DQA and DQB genes in the California sea lion (Zalophus californianus). Immunogenetics 2002, 54, 332–347. [Google Scholar]
  145. Bowen, L; Aldridge, BM; DeLong, R; Melin, S; Buckles, EL; Gulland, F; Lowenstine, LJ; Stott, JL; Johnson, ML. An immunogenetic basis for the high prevalence of urogenital cancer in a free-ranging population of California sea lions (Zalophus californianus). Immunogenetics 2004, 56, 846–848. [Google Scholar]
  146. Drake, GJ; Kennedy, LJ; Auty, HK; Ryvar, R; Ollier, WE; Kitchener, AC; Freeman, AR; Radford, AD. The use of reference strand-mediated conformational analysis for the study of cheetah (Acinonyx jubatus) feline leucocyte antigen class II DRB polymorphisms. Mol. Ecol 2004, 13, 221–229. [Google Scholar]
  147. De Groot, NG; Garcia, CA; Verschoor, EJ; Gaby, GM; Doxiadis, GGM; Marsh, SGE; Otting, N; Bontrop, RE. Reduced MIC gene repertoire variation in West African chimpanzees as compared to humans. Mol. Biol. Evol 2005, 22, 1375–1385. [Google Scholar]
  148. Gutierrez-Espleta, GA; Hedrick, PW; Kalinowski, ST; Garrigan, D; Boyce, WM. Is the decline of desert bighorn sheep from infectious disease the result of low MHC variation? Heredity 2001, 86, 439–450. [Google Scholar]
  149. Kennedy, LJ; Randall, DA; Knobel, D; Brown, JJ; Fooks, AR; Argaw, K; Shiferaw, F; Ollier, WER; Sillero-Zubiri, C; Macdonald, DW; Laurenson, MK. Major histocompatibility complex diversity in the endangered Ethiopian wolf (Canis simensis). Tissue Antigens 2011, 77, 118–125. [Google Scholar]
  150. Ellegren, H; Hartman, G; Johansson, M; Andersson, L. Major histocompatibility complex monomorphism and low-levels of DNA fingerprinting variability in a reintroduced and rapidly expanding population of beavers. Proc. Natl. Acad. Sci. USA 1993, 90, 8150–8153. [Google Scholar]
  151. Mikko, S; Andersson, L. Low major histocompatibility complex class II diversity in European and North American moose. Proc. Natl. Acad. Sci. USA 1995, 92, 4259–4263. [Google Scholar]
  152. Radwan, J; Aleksander, W; Demiaszkiewicz, AW; Kowalczyk, R; Lachowicz, J; Kawałko, JA; Wójcik, JM; Pyziel, AM; Babik, W. An evaluation of two potential risk factors, MHC diversity and host density, for infection by an invasive nematode Ashworthius sidemi in endangered European bison (Bison bonasus). Biol. Conserv 2010, 143, 2049–2053. [Google Scholar]
  153. Seddon, JM; Ellegren, H. MHC class II genes in European wolves: A comparison with dogs. Immunogenetics 2002, 54, 490–500. [Google Scholar]
  154. Schad, J; Sommer, S; Ganzhorn, JU. MHC variability of a small lemur in the littoral forest fragments of southeastern Madagascar. Conserv. Genet 2004, 5, 299–309. [Google Scholar]
  155. Aldridge, BM; Bowen, L; Smith, BR; Antonelis, GA; Gulland, F; Sott, JL. Paucity of class I MHC gene heterogeneity between individuals in the endangered Hawaiian monk seal population. Immunogenetics 2006, 58, 203–215. [Google Scholar]
  156. Blankenburg, A; Kaup, F-J; Sauermann, U. MHC class II DRB sequences of lion-tailed macaques (Macaca silenus). Tissue Antigens 2003, 62, 267–269. [Google Scholar]
  157. Sommer, S; Schwab, D; Ganzhorn, JU. MHC diversity of endemic Malagasy rodents in relation to geographic range and social system. Behav. Ecol. Sociobiol 2002, 51, 214–221. [Google Scholar]
  158. Sommer, S; Tichy, H. Major histocompatibility complex (MHC) class II polymorphism and paternity in the monogamous Hypogeomys antimena, the endangered, largest endemic Malagasy rodent. Mol. Ecol 1999, 8, 1259–1272. [Google Scholar]
  159. Hedrick, PW; Lee, RN; Parker, KM. Major histocompatibility complex (MHC) variation in the endangered Mexican wolf and related canids. Heredity 2000, 85, 617–624. [Google Scholar]
  160. Hedrick, PW; Lee, RN; Buchanan, C. Canine parvovirus enteritis, canine distemper, and major histocompatibility complex genetic variation in Mexican wolves. J. Wildl. Dis 2003, 39, 909–913. [Google Scholar]
  161. Kennedy, LJ; Angles, JM; Barnes, A; Carmichael, LE; Radford, AD; Ollier, WER; Happ, GM. DLA-DRB1, DQA1, and DQB1 alleles and haplotypes in North American gray wolves. J. Hered 2007, 98, 491–499. [Google Scholar]
  162. Weber, DS; Stewart, BS; Schienman, J; Lehman, N. Major histocompatibility complex variation at three class II loci in the northern elephant seal. Mol. Ecol 2004, 13, 711–718. [Google Scholar]
  163. Hedrick, PW; Parker, KM; Miller, EL; Miller, PS. Major histocompatibility complex variation in the endangered Przewalski’s horse. Genetics 1999, 152, 1701–1710. [Google Scholar]
  164. Kanthaswamy, S; Kou, A; Satkoski, J; Penedo, MCT; Ward, T; NG, J; Gill, L; Lerche, NW; Erickson, BJ-A; Smith, DG. Genetic characterization of specific pathogen-free rhesus macaque (Macaca mulatta) populations at the California National Primate Research Center (CNPRC). Am. J. Primatol 2010, 72, 587–599. [Google Scholar]
  165. Froeschke, G; Sommer, S. MHC Class II DRB Variability and parasite load in the striped mouse (Rhabdomys pumilio) in the Southern Kalahari. Mol. Biol. Evol 2005, 22, 1254–1259. [Google Scholar]
  166. Browning, TL. Inbreeding, the MHC and infectious disease susceptibility in the Tammar wallaby, Macropus eugenii. Ph.D. Thesis; Department of Biological Sciences, Faculty of Science, Macquarie University: Sydney, Australia, 2009. [Google Scholar]
Table
Table 1. A selection of studies using MHC markers in conservation biology.
Table 1. A selection of studies using MHC markers in conservation biology.
SpeciesPurpose of using MHCReference
Fish
Chinook salmon (Oncorhynchus tshawytscha)Understanding local adaptations[92]
Brown trout (Salmo trutta)Quantifying genetic diversity, disease susceptibility and human impact[104]
Gila trout (Oncorhynchus gilae gilae)Quantifying genetic diversity[105]
Guppy (Poecilia reticulate)Comparison of different conservation breeding regimes[128]
Birds
Chatham Island black robin (Petroica traversi)Monitoring genetic variation following bottleneck[129]
Crested ibis (Nipponia nippon)Quantifying genetic diversity and implications for reintroduction[90]
Galapagos penguin (Spheniscus mendiculus)Quantifying genetic diversity[130]
Gouldian finch (Erythrura gouldiae)Quantifying genetic diversity[131]
Great reed warbler (Acrocephalus arundinaceus)Comparison of genetic polymorphism of an outbred and an inbred species[132]
Seychelles warbler (Acrocephalus sechellensis)
Sonoran topminnow (Poeciliopsis occidentalis)Identify units for conservation[133]
Various birds of prey (for detailed list see references)Various conservation applications[101,134]
Reptiles
European adder (Vipera berus)Genetic rescue, monitoring the effect of translocation[6,7]
Hungarian meadow viper (Viper ursinii rakosiensis)Quantifying genetic diversity and level of inbreeding[11]
Sand lizard (Lacerta agilis)Quantifying the correlation between population size and genetic diversity[22]
Tuatara (Sphenodon punctatus)Quantifying genetic diversity[38,39]
Eutherian mammals
African elephant (Loxodonta africana)Quantifying genetic diversity[135]
Asian elephant (Elephas maximus)
African green monkey (Chlorocebus sabaeus)Quantifying gene expression[136]
African wild dog (Lycaon pictus)Quantifying genetic diversity[137]
American bison (Bison bison)Quantifying genetic diversity and resistance to malignant catarrhal fever[138,139]
Australian bush rat (Rattus fuscipes)Quantifying genetic diversity[140]
Aye-aye (Daubentonia madagascariensis)Quantifying genetic diversity[141]
Baiji the Chinese river dolphin (Lipotes vexillifer)Quantifying genetic diversity[142]
Bengal tiger (Panthera tigris tigris)Quantifying genetic diversity[106]
Brown bear (Ursus arctos)Quantifying genetic diversity[143]
California sea lion (Zalophus californianus)Quantifying genetic diversity and susceptibility to urogenital cancer[144,145]
California sea otter (Enhydra lutris nereis)Quantifying genetic diversity and bottleneck[100]
Cheetah (Acinonyx jubatus)Quantifying level of inbreeding and genetic diversity[146]
Chimpanzee (Pan troglodytes)Quantifying genetic diversity[147]
Common hamster (Cricetus cricetus)Consideration for breeding programs and genetic rescue[89]
Desert bighorn sheep (Ovis canadensis)Quantifying genetic diversity and disease susceptibility[148]
Ethiopian wolf (Canis simensis)Quantifying genetic diversity[149]
Eurasian beaver (Castor fiber)Quantifying genetic diversity following reintroduction[150]
European and North American moose (Alces alces)Quantifying genetic diversity[151]
European bison (Bison bonasus)Quantifying genetic diversity and pathogen resistance[152]
European mink (Mustela lutreola)Quantifying genetic diversity, genetic bottleneck, founder effect and captive breeding[40]
European wolf (Canis lupus lupus)Quantifying genetic diversity[153]
Giant panda (Ailuropoda melanoleuca)Quantifying genetic diversity and implications for the captive breeding program[87]
Gray mouse-lemur (Microcebus murinus)Quantifying genetic diversity[154]
Hawaiian monk seal (Monachus schauinslandi)Quantifying genetic variation[155]
Iberian red deer (Cervus elaphus hispanicus)Quantifying level of inbreeding and the effect of human impact[103]
Lion-tailed macaque (Macaca silenus)Quantifying genetic diversity[156]
Malagasy mouse lemur (Microcebus murinus)Quantifying genetic diversity and pathogen resistance[56]
Malagasy giant rat (Hypogeomys antimena)Quantifying genetic diversity in relation to geographic range and social system[157,158]
Mexican wolf (Canis lupus baileyi)Monitoring pathogen resistance following reintroduction[159,160]
North American gray wolf (Canis lupus)Quantifying MHC class II loci polymorphism in geographically separated regions[161]
Northern elephant seal (Mirounga angustirostris)Quantifying genetic diversity[162]
Przewalski’s horse (Equus ferus)Quantifying genetic diversity[163]
Rhesus macaque (Macaca mulatta)Monitoring intergenerational genetic changes, classifying the ancestry of research stocks[164]
Striped mouse (Rhabdomys pumilio)Quantifying genetic diversity[165]
Marsupials
Black-footed rock-wallaby (Petrogale lateralis lateralis)Quantifying genetic diversity of island and mainland populations[88]
Tammar wallaby (Macropus eugenii)Quantifying level of inbreeding and disease susceptibility[166]
Tasmanian devil (Sarcophilus harrisii)Quantifying genetic diversity and understanding the development of a contagious cancer[107,108,122]
Western barred bandicoot (Perameles bougainville)Quantifying genetic diversity[109]

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Ujvari, B.; Belov, K. Major Histocompatibility Complex (MHC) Markers in Conservation Biology. Int. J. Mol. Sci. 2011, 12, 5168-5186. https://doi.org/10.3390/ijms12085168

AMA Style

Ujvari B, Belov K. Major Histocompatibility Complex (MHC) Markers in Conservation Biology. International Journal of Molecular Sciences. 2011; 12(8):5168-5186. https://doi.org/10.3390/ijms12085168

Chicago/Turabian Style

Ujvari, Beata, and Katherine Belov. 2011. "Major Histocompatibility Complex (MHC) Markers in Conservation Biology" International Journal of Molecular Sciences 12, no. 8: 5168-5186. https://doi.org/10.3390/ijms12085168

APA Style

Ujvari, B., & Belov, K. (2011). Major Histocompatibility Complex (MHC) Markers in Conservation Biology. International Journal of Molecular Sciences, 12(8), 5168-5186. https://doi.org/10.3390/ijms12085168

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