markers
We note one marker in particular and place emphasis on it throughout this paper. The microsatellite OLADRB lies within an intron 30 bp downstream from the 3′ splice site of exon 2 in Ovar-DRB1 (40), the major expressed class II DRB gene of sheep (41, 42). Class II genes are believed to play a major role in immune defense against macroparasites (43) and commonly show extensive polymorphism (3), the vast majority of this polymorphism being located in the antigen presenting site encoded by exon 2 (44). This pattern of polymorphism at DRB also is found in domestic sheep flocks (45, 46). High correlation is observed between microsatellite variation at OLADRB and adjacent, expressed sequence polymorphism, with all sequence variants distinguishable on the basis of microsatellite variation (55).
Statistical Treatment. Generalized linear models (47) were used in both analyses of juvenile survival and parasite resistance. Such models are commonly used to describe complex traits where many factors contribute toward a character (48). In this way we were able to control for many of the confounding variables present in the St. Kilda population that otherwise might obscure subtle genetic associations with the MHC. Minimal nongenetic models were constructed by using standard techniques (48) and the computer program splus (Mathsoft, Cambridge, MA). A binomial error distribution was assumed for survivorship data, and a negative binomial error distribution was assumed for FEC data. In the case of lamb survival, only lambs that survived to 4 months of age were included in the analysis. This analysis excluded neonatal mortality, which may largely reflect maternal condition, and allowed measurements taken during August to be included in the model. Terms were deletion tested, with significance levels determined by comparing the resulting change in deviance against a χ2 distribution with degrees of freedom equal to the number of terms (or levels of a factor) dropped (47).
After the construction of minimal nongenetic models, significance of genetic terms were calculated by deletion testing as before. Genetic terms were fitted either (i) under an additive model where, for a particular allele, the value of the heterozygote class lies midway between the two homozygote classes (i.e., given an allele Ai compared against all other alleles, denoted Am, the genotypes AmAm, AiAm and AiAi have genotypic values 0, αi and 2αi respectively), or (ii) under a symmetrical overdominance model where values of heterozygotes are compared against homozygotes (i.e., for all i, j≠i, the genotypes AiAi, AiAj, and AjAj have genotypic values 1-d, 1 and 1− d, respectively, where d denotes the change in the value of a trait because of overdominance). Alleles with a frequency of less than 2% were pooled with their closest length variant at that locus to prevent comparisons being made on small sample sizes. In all models, all comparisons made involved a minimum cell size of at least 30 data points (48).
Juvenile Survival. Mortality in Soay sheep is highest in lambs and yearlings (24), hence survivorship within these age classes is likely to be a strong predictor of fitness. Separate generalized linear models were constructed for lamb and yearling survival to avoid pseudo-replication. Mean lamb survivorship was found to be 0.471, and mean yearling survivorship was found to be 0.636. Significant nongenetic terms are shown in Table 3. In common with previous studies (21, 24), cohort, sex, and August weight were found to be important factors associated with juvenile survivorship. | Table 3 Nongenetic terms significantly associated with juvenile survivorship |
Genetic terms were tested at each of the five loci. Given the alternate hypotheses of frequency-dependent selection or heterozygote advantage proposed to maintain MHC diversity, genetic terms were fitted under either an additive model or a symmetrical overdominance model. As shown in Tables 4 and 5, associations were observed at all three of the MHC loci when genetic terms were fitted simultaneously under an additive model but, with the exception of one marginally significant association (Table 5), not under an overdominance model. No significant associations were observed at either of the flanking marker controls (with one marginally significant exception, Table 5). Significant associations were observed in lambs as weight interactions and in yearlings as simple terms. Genetic terms also were fitted under a dominant model (i.e., given an allele Ai compared against all other alleles, denoted Am, the genotypes AmAm, AiAm, and AiAi have genotypic values 0, αi and αi, respectively); for both lambs and yearlings the results from dominant models followed closely those produced under an additive model (results not shown). | Table 4Genetic associations with lambsurvivorship |
| Table 5Genetic associations with yearlingsurvivorship |
The biological significance of the MHC × weight interactions observed with lamb survival remains unclear. MHC × weight interactions may occur in this model either (i) because of an effect of the MHC on weight (possibly mediated by parasites or by energetic costs associated with immune function) and hence on survivorship or (ii) through a mechanism whereby effects of the MHC on survivorship are dependent on weight (48). The strongest associations with survivorship were observed with the locus OLADRB and are shown in Table 6. In lambs, allele 257 showed a significant weight interaction (P < 0.01), which appeared to decrease survivorship (estimated survivorship difference = −0.012), with the effect most pronounced in lambs below average weight; these underweight animals are most vulnerable to over-winter starvation (Table 3, refs. 21 and 24). In yearlings, allele 205 was associated with decreased survivorship (estimated survivorship difference = −0.089, P < 0.01), and allele 263 was associated with increased survivorship (estimated survivorship difference = +0.076, P < 0.05). Associations with alleles at OLADRBps and OMHC1 also were observed consistent with the linkage disequilibrium between alleles at these loci and alleles at OLADRB (not shown). Survival differences for alleles were estimated by comparing the mean fitted survival probability of animals carrying zero or one copy of the allele (numbers of animals homozygous for the allele generally were too small for robust analysis). This approach makes no assumptions as to the cause of any allele × weight interactions found and only looks at the overall difference between animals with zero or one copy of the allele. | Table 6Association between alleles at OLADRB andsurvivorship |
Parasite Resistance. Separate generalized linear models were constructed for lamb and yearling FEC. A negative binomial error distribution was assumed (49, 50). Significant nongenetic terms are shown in Table 7. Mean fitted lamb FEC was found to be 409 eggs/g; mean fitted yearling FEC was found to be 248 eggs/g. Genetic terms were tested as before. Strongest associations were observed at OLADRB under an additive model (shown in Table 8). For lambs, the 257 allele under an additive model showed a highly significant association (P < 0.01), which acted to increase FEC by an estimated 104 eggs/g (for animals carrying one copy versus animals carrying 0 copies of the 257 allele). In yearlings, allele 263 acted to decrease FEC (−76 eggs/g, P < 0.05) and allele 267 acted to increase FEC (+96 eggs/g, P < 0.05). No associations were observed under an overdominance model for either lambs or yearlings. Genetic terms also were fitted under a dominant model and followed closely the results produced from the additive model (results not shown). | Table 7Nongenetic terms significantly associated with parasiteresistance |
| Table 8Association between alleles at OLADRB and parasiteresistance |
Sire Effects. A possible criticism of the methodology used here is that the analysis may be influenced by family structure. In particular, if rams sire many offspring, any associations found may be caused by genome-wide, rather than MHC-specific, sire effects. This effect would not be expected to lead to any systematic bias but would lead to an increase in the frequency of type I errors. This effect, however, is expected to be slight because sibships are generally small (mean maternal sibship size 1.92, mean paternal sibship size 1.84; ref. 51). More importantly, the use of flanking markers in this study limits any associations found to the MHC region rather than to genome-wide sire effects. |
We previously have reported evidence of balancing selection on both allele frequency distributions and patterns of nucleotide substitution at the MHC (55). In this paper we present direct evidence of selection at the MHC. We examined MHC associations with survivorship in both lambs and yearlings—age classes in which highest mortality is observed (24). Associations with juvenile survival were observed at each of the three MHC loci when fitted under an additive model but not at either of the flanking markers, limiting associations to the MHC region. The general picture that emerges of selection at the MHC is that presence of individual alleles rather than heterozygosity is the critical factor determining mortality in lambs and yearlings with respect to MHC type. At OLADRB, the locus at which the strongest associations with juvenile survivorship are observed, alleles significantly associated with strongyle parasite resistance in lambs and yearlings show consistent associations in juvenile survival. In particular, the OLADRB 257 allele is significantly associated with both decreased parasite resistance and decreased survival in lambs; conversely, the OLADRB 263 allele is associated with both increased parasite resistance and increased survival in yearlings. No significant associations with parasite resistance are seen for the 205 allele that is associated with yearling survival. The mechanism behind these survivorship differences for this allele is unclear—possibly the 205 allele is associated with some other fitness trait as yet unidentified. The consistency between alleles associated with survivorship and resistance to strongyle parasites suggests that particular MHC types confer either increased or decreased levels of parasite resistance that are translated into survivorship differences. Given this, it is reasonable to suppose that parasites play a major role in the maintenance of MHC polymorphism in the Soay population. These results are similar to those found by Hill et al. (52) in a large study of human malaria in West Africa. There it was found that certain MHC alleles were associated with protection from severe cerebral malaria in children—a condition that untreated would be likely to cause death in these individuals. Our results, however, show parasite-associated selection at the MHC in an unmanaged, nonhuman population. It is tempting to draw conclusions with respect to the hypotheses of frequency-dependent selection and overdominance proposed to maintain MHC diversity. It was observed that particular MHC alleles, rather than heterozygosity, were associated with survivorship differences in both lambs and yearlings. Why then do favored alleles not rise to fixation in the population? In this respect, it is interesting to note that the most common alleles at OLADRB, 205 and 257, were associated with decreased survivorship, whereas the rarer 263 allele was associated with increased survivorship—as might be predicted under negative frequency-dependent selection. However, associations were not found to be consistent between lambs and yearlings. It may be the case that different MHC alleles exhibit different associations at different stages during the Soay sheep’s life, possibly reflecting the complex interplay between helminth parasites and the vertebrate immune system (53). This could lead to heterozygotes showing highest overall fitness. Despite this caveat, there is no evidence that alleles disadvantaged in lamb survivorship are advantageous in yearling survivorship or vice versa, but the possibility remains that MHC alleles may show associations with other, uncharacterized fitness traits, such as survivorship in older age classes or fecundity. Similarly, although the parasites considered here, strongyle nematodes, are thought to be the major parasites of both Soay and domestic flocks (29, 32), it is possible that other, perhaps uncharacterized parasite species exert strong selective effects on Soay sheep. Other MHC types therefore may confer protection against parasite species not considered in this study. The acid test of frequency-dependent selection would be to follow allele frequencies and selection coefficients through time and observe cycling of allele frequencies around a central mean. Unfortunately, the pace of change in allele frequencies and selection coefficients is likely to be limited by the average life span of Soay sheep (around 3 years), which is not much shorter than the number of cohorts available for this study (1985–1994). Parasites represent a major force in the natural environment and maintenance of MHC diversity by parasite selection may prove to be a widespread phenomenon in vertebrates. Large-scale studies of this kind will be essential to explore the potential of parasites in the maintenance of genetic diversity at the MHC and other loci. |
Acknowledgments We thank the numerous staff and volunteers who have helped collect samples and data on St. Kilda, especially A. Robertson, A. MacColl, F. Gulland, and J. Pilkington; Scottish Natural Heritage and the National Trust for Scotland for permission to work on St. Kilda; the Royal Artillery Range (Hebrides) and the Royal Corps of Transport for logistical assistance; and Andrew Read for comments during the preparation of this manuscript. This research was funded by the Biotechnology and Biological Sciences Research Council, the Natural Environment Research Council, and the Wellcome Trust. |
|
References 1. Hedrick, P W. Am Nat. 1994;143:945–964. 2. Trowsdale, J. Trends Genet. 1993;9:117–122. [PubMed]3. Klein, J; Takahata, N; Ayala, F J. Sci Amer. 1993;269:78–83. [PubMed]4. Klein, J; Satta, Y; Ohuigin, C; Takahata, N. Annu Rev Immunol. 1993;11:269–295. [PubMed]5. Yuhki, N; O’Brien, S J. J Immunol. 1997;158:2822–2833. [PubMed]6. Hughes, A L; Nei, M. Nature (London). 1988;335:167–170. [PubMed]7. Hughes, A L; Nei, M. Proc Natl Acad Sci USA. 1989;86:958–962. [PubMed]8. Hughes, A L; Hughes, M K; Howell, C Y; Nei, M. Philos Trans R Soc London B. 1994;345:359–367. [PubMed]9. Hedrick, P W; Thomson, G. Genetics. 1983;104:449–456. [PubMed]10. Wedekind, C; Seebeck, T; Bettens, F; Paepke, J. Proc R Soc London B. 1995;260:245–249. 11. Wedekind, C; Chapuisat, M; Macas, E; Rulicke, T. Heredity. 1996;77:400–409. [PubMed]12. Potts, W K; Manning, C J; Wakeland, E K. Philos Trans R Soc London B. 1994;346:369–378. [PubMed]13. Potts, W K; Manning, C J; Wakeland, E K. Nature (London). 1991;352:619–621. [PubMed]14. Doherty, P C; Zinkernagel, R M. Nature (London). 1975;256:50–52. [PubMed]15. Hedrick, P W. Annu Rev Ecol Syst. 1986;17:535–566. 16. Ellner, S; Haiston, N G. Am Nat. 1994;143:403–417. 17. Hamilton, W D. Oikos. 1980;35:282–290. 18. Bodmer, W. Nature (London). 1972;237:139–145. [PubMed]19. Potts, W K; Wakeland, E K. Trends Genet. 1993;9:408–412. [PubMed]20. Gulland, F M D; Albon, S D; Pemberton, J M; Moorcroft, P R; Clutton-Brock, T H. Proc R Soc London B. 1993;254:7–13. 21. Illius, A W; Albon, S D; Pemberton, J M; Gordon, I J; Clutton-Brock, T H. J Anim Ecol. 1995;64:481–492. 22. Paterson, S; Pemberton, J. Proc R Soc London B. 1998;264:1813–1819. 23. Campbell, R N. Island Survivors. Jewell P A, Milner C, Morton Boyd J. , editors. London: Athlone; 1974. pp. 8–35. 24. Clutton-Brock, T H; Price, O F; Albon, S D; Jewell, P A. J Anim Ecol. 1992;61:381–396. 25. Clutton-Brock, T H; Price, O F; Albon, S D; Jewell, P A. J Anim Ecol. 1991;60:593–608. 26. Stevenson, I R; Bancroft, D R. Proc R Soc London B. 1995;262:267–275. 27. Gulland, F M D. Parasitology. 1992;105:493–503. [PubMed]28. Cheyne, I A; Foster, W M; Spence, J B. Island Survivors. Jewell P A, Milner C, Morton Boyd J. , editors. London: Athlone; 1974. pp. 338–359. 29. Urquhart, G M; Armour, J; Duncan, J L; Dunn, A M; Jennings, F W. Veterinary Parasitology. Avon: Longman; 1987. 30. Abbott, E M; Parkins, J J; Holmes, P H. Res Vet Sci. 1985;38:6–13. [PubMed]31. Coop, R L; Huntley, J F; Smith, W D. Res Vet Sci. 1995;59:24–29. [PubMed]32. Gulland, F M D; Fox, M. Parasitology. 1992;105:481–492. [PubMed]33. Stear, M J; Bishop, S C; Doligalska, M; Duncan, J L; Holmes, P H; Irvine, J; McCririe, L; McKellar, Q A; Sinski, E; Murray, M. Parasite Immunol. 1995;17:643–652. [PubMed]34. Trowsdale, J. Immunogenetics. 1995;41:1–17. [PubMed]35. Crawford, A M; Dodds, K G; Ede, A J; Pierson, C A; Montgomery, G W; Garmonsway, H G; Beattie, A E; Davies, K; Maddox, J F; Kappes, S W, et al. Genetics. 1995;140:703–724. [PubMed]36. Schwaiger, F W; Buitkamp, J; Weyers, E; Epplen, J T. Mol Ecol. 1993;2:55–59. [PubMed]37. Blattman, A N; Beh, K J. Anim Genet. 1992;23:392. [PubMed]38. Groth, D M; Wetherall, J D. Anim Genet. 1994;25:61. [PubMed]39. Bishop, M D; Kappes, S M; Keele, J W; Stone, R T; Sunden, S L F; Hawkins, G A; Toldo, S S; Fries, R; Grosz, M D; Yoo, J Y; Beattie, C W. Genetics. 1994;136:619–639. [PubMed]40. Schwaiger, F W; Epplen, J T. Immunol Rev. 1995;143:199–224. [PubMed]41. Ballingall, K T; Wright, H; Redmond, J; Dutia, B M; Hopkins, J; Lang, J; Deverson, E V; Howard, J C; Puri, N; Haig, D. Anim Genet. 1992;23:347–359. [PubMed]42. Dutia, B M; McConnell, I; Ballingall, K T; Keating, P; Hopkins, J. Anim Genet. 1994;25:235–241. [PubMed]43. Weir, D W; Stewart, J. Immunology. Edinburgh: Churchill Livingston; 1993. 44. Brown, J H; Jardetzky, T; Saper, M A; Samraoui, B; Bjorkman, P J; Wiley, D C. Nature (London). 1988;332:845–850. [PubMed]45. Schwaiger, F W; Weyers, E; Buitkamp, J; Ede, A J; Crawford, A; Epplen, J T. Mol Biol Evol. 1994;11:239–249. [PubMed]46. Schwaiger, F W; Weyers, E; Epplen, C; Brun, J; Ruff, G; Crawford, A; Epplen, J T. J Mol Evol. 1993;37:260–272. [PubMed]47. McCullagh, P; Nelder, J A. Generalized Linear Models. London: Chapman & Hall; 1989. 48. Crawley, M J. GLIM for Ecologists. Oxford: Blackwell; 1993. 49. Wilson, K; Grenfell, B T; Shaw, D J. Funct Ecol. 1996;10:592–601. 50. Wilson, K; Grenfell, B T. Parasitol Today. 1997;13:33–38. [PubMed]51. Smith, J A. Ph.D. thesis. University of Cambridge; 1996. 52. Hill, A V S; Allsopp, C E M; Kwiatkowski, D; Anstey, N M; Twumasi, P; Rowe, P A; Bennett, S; Brewster, D; McMichael, A J; Greenwood, B M. Nature (London). 1991;352:595–600. [PubMed]53. Maizels, R M; Bundy, D A P; Selkirk, M E; Smith, D F; Anderson, R M. Nature (London). 1993;365:797–805. [PubMed]54. Guo, S W; Thompson, E A. Biometrics. 1992;48:361–372. [PubMed]55. Paterson, S. (1998) J. Hered., in press. |
| |