Animal Genetics 1990,21,221-232
The relationship between bovine major histocompatibility complex class I1 polymorphism and disease studied by use of bull breeding values A. LUNDCN, S. SIGURDARD6TTIR, I. EDFORS-LILJA, B. DANELL, J. RENDEL & L. ANDERSSON
Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
Summary. The predictive value of class I1 DQ and DYA polymorphisms of the bovine major histocompatibility (MHC) complex (BoLA) for the incidence of disease in dairy cattle was estimated in a sample of 196progeny-tested A1 bulls of the Swedish Red and White breed. The BoLA DQ and DYA types of the bulls were determined by analysing restriction fragment length polymorphisms (RFLPs). Breeding values of bulls for clinical mastitis, all diseases including clinical mastitis and diseases other than clinical mastitis were used as measures of disease resistance or susceptibility. The relationship between MHC polymorphism and bull breeding values for disease resistance was evaluated statistically by linear regression analysis. A significant association between the haplotype DQ'* and susceptibility to clinical mastitis was revealed. No other DQ haplotype nor the DYA locus had a significant effect on any of the disease traits studied. Keywords: major histocompatibility complex, disease resistance, mastitis, cattle
Introduction
The incidence of disease in farm animals is of major concern both from an ethical and economical point of view. In cattle, mastitis is an infectious disease with a major influence on the economic outcome in dairy production. The economic loss due to mastitis has recently been estimated in Sweden to exceed 100 million US dollars per year (Emanuelson 1987). It is clear that resistance to many infectious diseases is partly genetically determined (Gavora & Spencer 1983). Consequently, there has been an increasing interest in recent years in studying the genetic basis for disease resistance and also to identify genetic and immunological markers which could be used in breeding programmes to improve disease resistance. Major histocompatibility complex (MHC) genes are candidate markers for disease resistance due to their important role in the immune system. Two classes of
Correspondence: Dr A. LundCn, Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, S-750 07 Uppsala, Sweden. Accepted 18 January 1990
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222 A. LundCn et al.
integral cell-surface glycoproteins, denoted class I and class 11, are encoded in the MHC (Klein 1986). The important role of the MHC molecules in the regulation of the immune response is due to the fact that T cells recognize foreign antigens in association with self MHC molecules (Zinkernagel & Doherty 1979). A salient feature of MHC molecules is their extreme genetic polymorphism, which has been found in most species studied so far. There is accumulating evidence supporting the concept that the polymorphism is maintained by natural selection (for review see Klein 1986; Andersson et al. 1987; Nagy et al. 1989). Moreover, it has recently been shown that there is selection for replacement substitutions in the nucleotide sequence corresponding to the antigen binding site of both class I (Hughes & Nei 1988) and class I1 molecules (Hughes & Nei 1989;Jonsson etal. 1989). The selection mechanism favouring extensive MHC polymorphism is still not clearly understood. The most common view is that this phenomenon is related to significant differences between allelic MHC molecules in their influence on the immune response and thereby on the resistance to pathogens. A number of reports on significant associations between MHC polymorphism and various diseases have been published (for review see Klein 1986). However, most of the well-documented MHC-associated diseases are rare and non-infectious, having little effect on fertility and viability during reproductive years. Few clear associations between MHC and infectious diseases have been reported so far, one of the most striking examples being the association with Marek’s disease in chickens (Hansen er al. 1967; Longenecker et al. 1976; Briles et al. 1977). A possible explanation for this lack of associations could be that it should be easier to carry out genetic studies on chronic diseases than on infectious diseases as the incidence of infectious diseases tends to be more influenced by non-genetic factors such as the presence and degree of pathogen exposure, general health conditions, etc. We have previously studied the organization and genetic polymorphism of class I1genes in the bovine MHC, which is called BOLA. Using human probes in Southern blot analysis, the existence of bovine DQA, DQB, DRA, DRB, DOB, DNA, DYA and DYB genes was documented (Andersson et al. 1986a, b, 1988; Andersson & Rask 1988; Sigurdard6ttir et al. 1988). Furthermore, restriction fragment length polymorphism (RFLP) was found for all these genes. Linkage analysis revealed that the bovine class I1 region is divided into two subregions, one consisting of DQA, DQB, DRA and DRB genes, and the other including DOB, DYA, DYB and, most likely, DNA (Anderson er al. 1988). The recombination distance between these two subregions was estimated to about 1 7 ~It ~should . be noted that the previously used gene symbols for bovine class 11 genes have been changed to conform with the new nomenclature for HLA genes (Anon. 1988). Thus, class I1 a genes are denoted A (e.g. DQA) and class I1 p genes are denoted B (e.g. DOB). Furthermore, DZcl has been changed to DNA. The objective of this study was to examine the importance of MHC class I1 polymorphism in resistance to diseases as registered in commercial dairy herds in Sweden. In the present study, class I1 polymorphism of breeding bulls was examined by DQA, DQB and DYA RFLP typing as previously described by Sigurdard6ttir et
MHC and disease resistance in cattle 223
al. (1988). thereby representing both class I1 subregions. Bull breedingvalues, based on large progeny groups, were used as estimates of disease resistance.
Material and methods Animals. The analysis included 197 bulls, used for artificial insemination (AI), of the Swedish Red and White breed (SRB). Some genetic material from Finnish Ayrshire and Norwegian Red Cattle are continuously being imported into the SRB breed. The young bulls were born between 1976 and 1981 and they were sampled from the yearly batches of bulls undergoing progeny testing. They had previously been selected, based on pedigree records and growth rate up to one year of age in a performance test. Thereafter they also had to pass selection on conformation, especially against weak and short legs, and semen was tested for sperm motility after thawing. Chromosomal defects and unfavourable new information on the mother regarding production and fertility are other criteria for discarding potential breeding bulls before progeny testing. For the progeny testing, semen from the bulls was used for insemination of randomly chosen cows within the regions for the two A1 societies, ‘Seminavel’ and ‘Elitsemin’. The number of bulls was reduced to 196 due to one case of uncertain DQ typing. The 196 bulls were the offspring of 41 sires.
Disease records. Since 1984, all veterinary treatments of dairy cows in Sweden have been registered by the Swedish Association for Livestock Breeding and Production (SHS). These disease records are used for estimating bull breeding values for (1) clinical mastitis, (2) all diseases including clinical mastitis and (3) diseases other than clinical mastitis. The two latter traits include diagnoses such as: ketosis, retained placenta, milk fever, injured teats, leg and hoof lesions, infections, cysts and various gynaecological and metabolic malfunctions. The pooling of diseases is considered necessary because of low disease incidences and low heritabilities, mainly due to large environmental variation and difficulties in diagnosing the various disorders. In estimating the breeding values, disease data recorded from lodays before the onset of first lactation to 150 days after calving were used. During this period about 75% of the veterinary treatments in the first lactation are performed. The number of daughters per progeny-tested bull vaned between 104 and 330, with a mean of 175. The breeding values were taken from the routine evaluation system, adapted at SHS. A BLUP procedure was used and the model included the effect of sire together with the relationship matrix and fixed effects of herd-year-season, month and age of calving and breed of dam (Nordens Bondeorganisationers Centralrid 1987).
Typing for BOLA class II RFLPs. Genomic DNA was isolated from doses of frozen semen and Southern blot analysis was carried out as previously described (Andersson et al. 1986a; Andersson 1988). DNA samples were digested with two alternative restriction enzymes, TaqI and PvuII. Human MHC class I1 cDNA probes were used (Sigurdard6ttir et al. 1988). They were labelled to high specific activity with u ( - ~ * P ) ~ C TbyP nick translation (Rigby et al. 1977). The hybridization
224 A. Lundkn et al.
Table 1. Observed class I1 DQ haplotypes in cattle of the SRB breed and the representation of the various DQ haplotypes among 41 paternal half-sib families ~
DQ haplotype
1A
1B 2 3 4 5
6 7 8 9 10 rare'
Frequency
No of paternal half-sib families
0.16 0.10 0.19 0.03 0.09 0.07 0.08 0.04
0.03 0.12 0.04
0.05
27 19 23 8 12 11 11 9 12 17 4 13
' DQ haplotypes assigned 'rare' have frequencies below 0.03.
membranes were hybridized overnight in 40% formamide, 0 . 5 NaCl ~ at 42°C and subsequently washed in 0.7 x SSC at 60°C. The interpretation and nomenclature of DQ and DYA RFLPs have been described previously (Anderson er al. 1986a,b; 1988; Sigurdard6ttir er al. 1988). Two DYA alleles designated DYA' and DYA', with the frequencies of 0.642 and 0-3.58respectively, were present in this material. The different DQ haplotypes and their frequencies are given in Table 1; DQA and DQB polymorphism have been analysed as DQ haplotypes due to the extreme linkage disequilibrium between these genes. Srarisricalanalysis. The effect of DQ haplotype and DYA alleles on the breeding values of disease were studied using least square analysis. Rare DQ haplotypes, with frequencies below 0.03, were pooled (Table 1) to avoid extremely small classes in the statistical analyses. A multiple regression model in accordance with 0stergArd er al. (1989) was used as follows:
Y; = a where
Y;
= breeding value of the ith breeding bull for one of three alternative disease
a
traits: clinical mastitis, all diseases including clinical mastitis, or diseases other than clinical mastitis = intercept = regression coefficient of the bull breeding values for disease trait (see above) on the corresponding breeding values of their sires
bl
MHC and disease resisiance in cattle 225
x l i = sire breeding value for the corresponding disease trait of the ithbreeding bull b 2 = regression coefficient of the bull breeding values for disease traits (see above)
on the number of copies of the rchDQ haplotype ( r = 1,2. . .12) x t , = 0 , l or 2 depending on the number of copies of the rthDO haplotype for the
i'h bull b 3 = regression coefficient of the bull breeding values for the disease traits (see above) on the number of copies of the sthDYA allele (s = 1,2) x3ir = 0, 1 o r 2 depending on the number of copies of the slh DYA allele for the ith bull ei = residual random term N(O,c?) There are dependencies in the data as the value of the last allelelhaplotype is known given the values of the previous n-1 haplotypes. This dependency was solved by imposing a restriction on the regression coefficients so that Zbz, = ?b3r = 0 (see r above). In this model, the separate effects of the various DQ haplotypes and DYA alleles were simultaneously estimated and tested for significance. All effects in the model, except the residuals, were considered as futed. It should be noted that this model tests exclusively for additive effects of the various MHC alleles present in the bulls. Such a model was chosen since the MIIC typings were made on breeding bulls while the disease records were collected on their daughters. Therefore, the number of copies of a certain BOLA class I1 haplotype of a bull merely reflects the approximate proportion of daughters that will inherit the particular haplotype. The dams' contribution to their daughters' genotypes is not known and therefore it has to be assumed that the gene frequencies among dams are the same in all progeny groups. The GLM procedure of the Statistical Analysis System (SAS) was used for the statistical analyses (SAS Institute Inc. 1985). As the 196 bulls used in the study belonged to 41 paternal half-sib families, it was considered necessary to correct for effects of the genetic background formed by non-MHCgenes that influence the actual trait and the fact that observations were not independent due to resemblance between half-sibs. The preferred method to adjust for these effects would be to include random effects of sire in the model. One condition for that model is that the ratio (A) between the error variance and the sire variance is known. However, when analysing genotypic values, which constitute the breeding values in this analysis, A is not equal to the variance ratio used with phenotypic values, since with breeding values the error variance is decreasing with increasing accuracy of the breeding value. Thus, with a high accuracy A will approach zero and the random model becomes a fixed model. Therefore, there are two practicable ways t o account for the resemblance between half-sibs and the background genes: either by treating sire as a fixed effect or alternatively to use the corresponding breeding value of sire as a covariate in the model for each of the three disease traits in the analysis. By using the sire breeding values instead of treating sire as a fixed effect, the effective number of bulls increases because those bulls which had no half-sibs in the material can be included. Also, the breeding values of sires, which are estimated with high accuracy based on large daughter groups, should constitute better estimates of the effects of the genetic background than the mean value based
226 A. Lundkn et al.
on the breeding values of the limited number of bulls of each sire that are included in this investigation. Therefore, in this study the covariate model was chosen for the statistical analysis.
Results The results from the statistical analyses of the effect of DQ haplotypes and DYA alleles on disease resistance are presented in Table 2. The most pronounced and consistent association of BOLA D Q with diseases was found with DQIA, one of the most frequent D Q haplotypes in this material. Bulls carrying the DQIA haplotype had significantly lower breeding values for the disease traits compared to bulls with other DQ haplotypes. The effect was most pronounced for the breeding values in which clinical mastitis was included. In the present analysis the DQ'* haplotype was present in the sons of 28 of the 41 sires (see Table 1)and among 23 of the 28 sires with more than two sons in the investigation. Out of 40 DQIA-positiveanimals for which it was possible to deduce the origin of the haplotype to either parent, 34 animals inherited DQIA from the dam. Furthermore, the DQIA-positive bulls were evenly
Table 2. Coefficients of regression and their standard errors for DQ haplotypes and DYA alleles on breeding values for various disease traits
Trait All diseases including clinical mastitis
Diseases other than clinical mastitis
-1.3 +- 0-5** -0.2 +0:5 0.4 k 0.4 -0.5 f 0.9 -0.3 f 0.6 -0-0 f 0.6 0.6 f 0.6 -0.4 f 0.8 0.0 f 0.9 -0.1 f 0.5 1.0 f 0.9 0.7 f 0.7
-1-3 f 0-5 ** -0.2 f 0.5 -0.2 f 0.4 1.0 f 0.9 -0.1 f 0.6 0.4 f 0.6 1.0 f 0.6 (*) -0.6 f 0.8 -0.5 f 0.9
-0.7 5 0.4 (*)
0.1 k 0-2 -0.1 5 0.2
-0.1 L 0-2
Clinical mastitis D Q haplotype 1A
1B 2 3 4
5 6 7 8 9 10
rare' DYA allele 1 2 a
-0.3 f 0.5 0.5 f 0.8 0.4 f 0.6
0.1
* 0.2
D Q haplotypes assigned 'rare' have frequencies below 0.03. P < 0.1.
(8)
* * P c 0.01.
-0.2 k 0.4 -0.6 & 0.4 (*) 1.3 k 0.8 -0.1 f 0.5 0.6 f 0.5 0.8 k 0-5 -0.4 f 0.7 -0.4 f 0.8 -0.2 f 0.5 0.2 f 0.8
-0.2 f 0.7 -0.1 k 0-2 0.1 f 0.2
MHC and disease resistance in cattle 227
distributed among maternal grandsires. This implies that the observed association was not merely caused by family relationships. No other DQ haplotypes, nor the DYA locus belonging to the other linkage subgroup, had a significant effect on any of the disease traits studied. When comparing the covariate model with a more conventional model where the sire effect is treated as fixed, the two methods turned out to give almost identical estimates with significant F-tests for DQIA,although the power of the tests was somewhat strengthened by the increased number of observations and the reduced number of degrees of freedom used up by the sire effect when using the covariate model. The statistical models in Table 3 were used in an attempt to estimate the relative importance of the effects of sire breeding value and the DQ1* haplotype on the variation in breeding values for clinical mastitis among bulls. A comparison of the adjusted coefficient of determination shows that the major proportion of the variance is explained by the breeding value of sire. However, an additional 2.2% of the variance in the bull breeding value for clinical mastitis is explained when the effect of the DQIA haplotype is added to the model.
Tabie 3. Contribution of the effect of the DQIA haplotype and breeding value of sire to the total variance in breeding value of bulls for clinical mastitis'
Clinical mastitis
Y,= P + b 6 4 , + e, Y,= p + b l x l , + e, Y,= IL + blxl, + b d 4 , + e,
6.57 31.08 33.27
The elements in the models have the same meaning as before and in addition: b 4 = regression coefficient of the bull breeding values for clinical mastitis (see above) on the number of copies of the DQIA haplotype. x4, = 0.1 or 2 depending on the number of copies of the DQIA haplotype. bAdjusted for the number of independent variables N - 1 SS Residual in the model: R 2 = 1 - - X dj N - p SS Corr. tot where N = no. of observations, p = d.f. for the model and SS Corr. tot. = total sums of squares corrected for the mean.
228 A. Lundkn et al.
Discussion This study has revealed a significant association between the DQIA haplotype and susceptibility to clinical mastitis in cattle of the SRB breed. To our knowledge, this is the first study on MHC-disease association based on class I1 polymorphism and also the first such study where the RFLP method has been utilized for MHC typing. The use of a DNA method was in fact a prerequisite for the present study, since all breeding bulls had been slaughtered when the study started. Thus, the MHC typings had to be made using frozen semen previously collected for AI. Previous MHC-disease association studies have been based on serological typing of class I polymorphism (e.g. Solbu et al. 1982; Lewin & Bernoco 1986; Lewin et al. 1988; Stear et al. 1988; Templeton ef al. 1988). The observed association between DQIA and clinical mastitis is of particular interest since mastitis is the most economically important disease among dairy cows in the Western world. Statistics on veterinary treatments in Sweden show that more than 20% of the dairy cows are treated against mastitis each year (Swedish Association for Livestock Breeding and Production 1989). Our results indicate that bulls heterozygous for DQIA on average have breeding values 1.3 index units lower than bulls not having DQIA (Table 2). This figure corresponds approximately to an increased incidence of clinical mastitis in first lactation cows from 8.0% to 8.3% for daughters of bulls heterozygous for DQ’*. Since the dams’ haplotypes are not known, the analyses only measure the change in haplotype frequency among daughters due to the haplotypes of their sires. If the contrast between cows with and without DQIA could have been measured, the expected difference would have been twice as large, thus from 8-0 to 8.6%. There was one single DQIA homozygous bull in the material. Interestingly, he had the second lowest breeding value for clinical mastitis (87.9) among all 196 bulls in this study. The association of DQIA remains significant even when this single DQIA homozygote is removed from the analysis. However, the observed association between DQIA and susceptibility to clinical mastitis needs to be confirmed in independent materials. In an attempt to estimate the practical significance of the observed association, the relative importance of the effects of sire breeding values and DQIAin explaining the variation in bull breeding values for clinical mastitis was compared using the models described in Table 3. The analysis showed that the determination coefficient for clinical mastitis increased from 31.1% to 33.3% when DQIA was added to a model including breeding value of sire. The figure of about 2% should be considered as a minimum estimate since a part of the DQIA effect is confounded with the effect of sire breeding value when DQ’* is not included in the model. Ways to overcome the problem with confounding are suggested by Bentsen & Klemetsdal (1990). A maximum estimate of about 6% is obtained by a model including DQIA but not breeding value of sire. This figure is comparable to the amount of variation accounted for by the breeding value of the maternal grand-grand-grandsire, if included in the model. The inference drawn from these figures is that the effect of DQIA on the variation in disease suceptibility is small, but nonetheless statistically
M H C and disease resistance in cattle 229
significant. Before selecting sires for reduced mastitis frequency, the correlated response on other production traits must be evaluated. The association between DQIA and clinical mastitis may not be a direct one. It is quite possible that DQIA confers an increased susceptibility to other disease conditions which in turn causes an increased incidence of clinical mastitis. There is evidence, for instance, for immunosuppressive effects in cattle infected by Bovine virus diarrhoea virus (Larsson et al. 1988). In this context it is also worth noting that breeding values for diseases other than clinical mastitis were lower (of borderline significance) for DQIA bulls (Table 2). The observed effects could also be caused by linked genes. An extremely close linkage disequilibrium has been found in the bovine DQ-DR class I1 region (Anderson et al. 1986b, 1988; Sigurdard6ttir et al. 1988). Due to this close association, only DQ haplotypes were used in this study. DQIA has, in all 63 animals studied so far, been found together with a single DRB RFLP type (DRBIA) as well as a single DRB type (DF4) identified by iso-electric focusing (Joostens et al., 1990). Thus, the association with clinical mastitis may equally well be caused by DRBIA or any other gene in linkage disequilibrium with DQ’~. Previous studies have indicated a tentative association between the class I specificity (BOLA-A) w16 and mastitis. Firstly, Solbu et al. (1982) reported on this association. Subsequently, an association between the blood group factor M’ and mastitis was reported (Larsen et al. 1985) where M’ is extremely closely associated with the w16 specificity (Leveziel & Hines 1984; Lindberg & Anderson 1988). M‘ and w16 are both very closely associated with the DQ haplotype DQ” in the SRB breed (Lindberg & Anderson 1988; Sigurdard6ttir et al. 1988). DQ” was not significantly associated with the incidence of clinical mastitis in the present material. Thus, the previous results by Solbu etal. (1982) and Larsen et al. (1985) could not be supported in this study, nor in an analysis on the association between the blood group factor M’ and clinical mastitis performed on a large sample of SRB breeding bulls (L. Andersson-Eklund, in preparation). However, such discrepancies could be due to differences between countries in the genetic backgrounds of the populations studied. Mastitis has proved to be a disease with a complex aetiology with several different pathogens involved. In Sweden the main pathogens are Staphylococcus aureus, Streptococcus dysgalactiae and Escherichia coli, which together account for more than half of all veterinary treatments against clinical mastitis (Swedish Association of Livestock Breeding and Production 1989). It is clear that an MHC-association study based on detailed clinical diagnosis of mastitis may give a quite different result than the present study, which is based on the overall incidence of clinical mastitis. Thus, it may well be that the moderate effect of DQIA observed in this analysis is due to a marked susceptibility among animals with this haplotype towards a specific pathogen. Such a detailed study is an obvious topic for future studies. However, studieson the influence of the MHC on the overall incidence may be more informative from a breeding point of view, since such studies make it possible to evaluate the usefulness of the MHC for improving disease resistance in a broader perspective. In this study bull breeding values with regard to disease susceptibility, based on disease records from large progeny groups, have been related to the MHC type of the
230 A. Lundkn et al.
individual bulls. Thus we have asked the question if the MHC genotype of breeding bulls has any predictive value for the incidence of disease among their daughters. There is an obvious advantage with this approach, as the number of individuals to be typed can be kept at a manageable level. The breeding value of a bull based on progeny testing, at least under the present circumstances, has a high accuracy. Thus, the size of the random variation is low compared to a situation with single observations on individual animals. This is especially evident for traits like mastitis and other diseases which have low heritabilities. Therefore a data set of the same size but with typings and registrations on individual cows would be less informative. A limitation of using breeding values is that only additive effects of the genetic marker will be detected, since MHC typings and disease observations are not derived from the same animal. Thus, associations present in certain combinations of haplotypes only will not be detected. However, from a breeding point of view it is difficult to utilize such non-additive genetic variation, particularly in a complex genetic system like the MHC. Therefore, it is our view that the use of bull breeding values is useful as an initial approach to study the relationship between a genetic marker and a complex disease trait.
Acknowledgements Sincere thanks are due to U. Emanuelson and L. Anderson-Eklund for statistical assistance, to G. Malmberg, Malmens husdjurstjanst and B. Lindht, Seminavel for kindly providing semen samples of breeding bulls, to the Swedish Association for Livestock Breeding and Production for generously providing bull breeding values and to C. Borsch for linguistic comments on the paper. The work was supported by a grant from the Swedish Council for Forestry and Agricultural Research.
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The relationship between bovine major histocompatibility complex class I1 polymorphism and disease studied by use of bull breeding values A. LUNDCN, S. SIGURDARD6TTIR, I. EDFORS-LILJA, B. DANELL, J. RENDEL & L. ANDERSSON
Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
Summary. The predictive value of class I1 DQ and DYA polymorphisms of the bovine major histocompatibility (MHC) complex (BoLA) for the incidence of disease in dairy cattle was estimated in a sample of 196progeny-tested A1 bulls of the Swedish Red and White breed. The BoLA DQ and DYA types of the bulls were determined by analysing restriction fragment length polymorphisms (RFLPs). Breeding values of bulls for clinical mastitis, all diseases including clinical mastitis and diseases other than clinical mastitis were used as measures of disease resistance or susceptibility. The relationship between MHC polymorphism and bull breeding values for disease resistance was evaluated statistically by linear regression analysis. A significant association between the haplotype DQ'* and susceptibility to clinical mastitis was revealed. No other DQ haplotype nor the DYA locus had a significant effect on any of the disease traits studied. Keywords: major histocompatibility complex, disease resistance, mastitis, cattle
Introduction
The incidence of disease in farm animals is of major concern both from an ethical and economical point of view. In cattle, mastitis is an infectious disease with a major influence on the economic outcome in dairy production. The economic loss due to mastitis has recently been estimated in Sweden to exceed 100 million US dollars per year (Emanuelson 1987). It is clear that resistance to many infectious diseases is partly genetically determined (Gavora & Spencer 1983). Consequently, there has been an increasing interest in recent years in studying the genetic basis for disease resistance and also to identify genetic and immunological markers which could be used in breeding programmes to improve disease resistance. Major histocompatibility complex (MHC) genes are candidate markers for disease resistance due to their important role in the immune system. Two classes of
Correspondence: Dr A. LundCn, Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, S-750 07 Uppsala, Sweden. Accepted 18 January 1990
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222 A. LundCn et al.
integral cell-surface glycoproteins, denoted class I and class 11, are encoded in the MHC (Klein 1986). The important role of the MHC molecules in the regulation of the immune response is due to the fact that T cells recognize foreign antigens in association with self MHC molecules (Zinkernagel & Doherty 1979). A salient feature of MHC molecules is their extreme genetic polymorphism, which has been found in most species studied so far. There is accumulating evidence supporting the concept that the polymorphism is maintained by natural selection (for review see Klein 1986; Andersson et al. 1987; Nagy et al. 1989). Moreover, it has recently been shown that there is selection for replacement substitutions in the nucleotide sequence corresponding to the antigen binding site of both class I (Hughes & Nei 1988) and class I1 molecules (Hughes & Nei 1989;Jonsson etal. 1989). The selection mechanism favouring extensive MHC polymorphism is still not clearly understood. The most common view is that this phenomenon is related to significant differences between allelic MHC molecules in their influence on the immune response and thereby on the resistance to pathogens. A number of reports on significant associations between MHC polymorphism and various diseases have been published (for review see Klein 1986). However, most of the well-documented MHC-associated diseases are rare and non-infectious, having little effect on fertility and viability during reproductive years. Few clear associations between MHC and infectious diseases have been reported so far, one of the most striking examples being the association with Marek’s disease in chickens (Hansen er al. 1967; Longenecker et al. 1976; Briles et al. 1977). A possible explanation for this lack of associations could be that it should be easier to carry out genetic studies on chronic diseases than on infectious diseases as the incidence of infectious diseases tends to be more influenced by non-genetic factors such as the presence and degree of pathogen exposure, general health conditions, etc. We have previously studied the organization and genetic polymorphism of class I1genes in the bovine MHC, which is called BOLA. Using human probes in Southern blot analysis, the existence of bovine DQA, DQB, DRA, DRB, DOB, DNA, DYA and DYB genes was documented (Andersson et al. 1986a, b, 1988; Andersson & Rask 1988; Sigurdard6ttir et al. 1988). Furthermore, restriction fragment length polymorphism (RFLP) was found for all these genes. Linkage analysis revealed that the bovine class I1 region is divided into two subregions, one consisting of DQA, DQB, DRA and DRB genes, and the other including DOB, DYA, DYB and, most likely, DNA (Anderson er al. 1988). The recombination distance between these two subregions was estimated to about 1 7 ~It ~should . be noted that the previously used gene symbols for bovine class 11 genes have been changed to conform with the new nomenclature for HLA genes (Anon. 1988). Thus, class I1 a genes are denoted A (e.g. DQA) and class I1 p genes are denoted B (e.g. DOB). Furthermore, DZcl has been changed to DNA. The objective of this study was to examine the importance of MHC class I1 polymorphism in resistance to diseases as registered in commercial dairy herds in Sweden. In the present study, class I1 polymorphism of breeding bulls was examined by DQA, DQB and DYA RFLP typing as previously described by Sigurdard6ttir et
MHC and disease resistance in cattle 223
al. (1988). thereby representing both class I1 subregions. Bull breedingvalues, based on large progeny groups, were used as estimates of disease resistance.
Material and methods Animals. The analysis included 197 bulls, used for artificial insemination (AI), of the Swedish Red and White breed (SRB). Some genetic material from Finnish Ayrshire and Norwegian Red Cattle are continuously being imported into the SRB breed. The young bulls were born between 1976 and 1981 and they were sampled from the yearly batches of bulls undergoing progeny testing. They had previously been selected, based on pedigree records and growth rate up to one year of age in a performance test. Thereafter they also had to pass selection on conformation, especially against weak and short legs, and semen was tested for sperm motility after thawing. Chromosomal defects and unfavourable new information on the mother regarding production and fertility are other criteria for discarding potential breeding bulls before progeny testing. For the progeny testing, semen from the bulls was used for insemination of randomly chosen cows within the regions for the two A1 societies, ‘Seminavel’ and ‘Elitsemin’. The number of bulls was reduced to 196 due to one case of uncertain DQ typing. The 196 bulls were the offspring of 41 sires.
Disease records. Since 1984, all veterinary treatments of dairy cows in Sweden have been registered by the Swedish Association for Livestock Breeding and Production (SHS). These disease records are used for estimating bull breeding values for (1) clinical mastitis, (2) all diseases including clinical mastitis and (3) diseases other than clinical mastitis. The two latter traits include diagnoses such as: ketosis, retained placenta, milk fever, injured teats, leg and hoof lesions, infections, cysts and various gynaecological and metabolic malfunctions. The pooling of diseases is considered necessary because of low disease incidences and low heritabilities, mainly due to large environmental variation and difficulties in diagnosing the various disorders. In estimating the breeding values, disease data recorded from lodays before the onset of first lactation to 150 days after calving were used. During this period about 75% of the veterinary treatments in the first lactation are performed. The number of daughters per progeny-tested bull vaned between 104 and 330, with a mean of 175. The breeding values were taken from the routine evaluation system, adapted at SHS. A BLUP procedure was used and the model included the effect of sire together with the relationship matrix and fixed effects of herd-year-season, month and age of calving and breed of dam (Nordens Bondeorganisationers Centralrid 1987).
Typing for BOLA class II RFLPs. Genomic DNA was isolated from doses of frozen semen and Southern blot analysis was carried out as previously described (Andersson et al. 1986a; Andersson 1988). DNA samples were digested with two alternative restriction enzymes, TaqI and PvuII. Human MHC class I1 cDNA probes were used (Sigurdard6ttir et al. 1988). They were labelled to high specific activity with u ( - ~ * P ) ~ C TbyP nick translation (Rigby et al. 1977). The hybridization
224 A. Lundkn et al.
Table 1. Observed class I1 DQ haplotypes in cattle of the SRB breed and the representation of the various DQ haplotypes among 41 paternal half-sib families ~
DQ haplotype
1A
1B 2 3 4 5
6 7 8 9 10 rare'
Frequency
No of paternal half-sib families
0.16 0.10 0.19 0.03 0.09 0.07 0.08 0.04
0.03 0.12 0.04
0.05
27 19 23 8 12 11 11 9 12 17 4 13
' DQ haplotypes assigned 'rare' have frequencies below 0.03.
membranes were hybridized overnight in 40% formamide, 0 . 5 NaCl ~ at 42°C and subsequently washed in 0.7 x SSC at 60°C. The interpretation and nomenclature of DQ and DYA RFLPs have been described previously (Anderson er al. 1986a,b; 1988; Sigurdard6ttir er al. 1988). Two DYA alleles designated DYA' and DYA', with the frequencies of 0.642 and 0-3.58respectively, were present in this material. The different DQ haplotypes and their frequencies are given in Table 1; DQA and DQB polymorphism have been analysed as DQ haplotypes due to the extreme linkage disequilibrium between these genes. Srarisricalanalysis. The effect of DQ haplotype and DYA alleles on the breeding values of disease were studied using least square analysis. Rare DQ haplotypes, with frequencies below 0.03, were pooled (Table 1) to avoid extremely small classes in the statistical analyses. A multiple regression model in accordance with 0stergArd er al. (1989) was used as follows:
Y; = a where
Y;
= breeding value of the ith breeding bull for one of three alternative disease
a
traits: clinical mastitis, all diseases including clinical mastitis, or diseases other than clinical mastitis = intercept = regression coefficient of the bull breeding values for disease trait (see above) on the corresponding breeding values of their sires
bl
MHC and disease resisiance in cattle 225
x l i = sire breeding value for the corresponding disease trait of the ithbreeding bull b 2 = regression coefficient of the bull breeding values for disease traits (see above)
on the number of copies of the rchDQ haplotype ( r = 1,2. . .12) x t , = 0 , l or 2 depending on the number of copies of the rthDO haplotype for the
i'h bull b 3 = regression coefficient of the bull breeding values for the disease traits (see above) on the number of copies of the sthDYA allele (s = 1,2) x3ir = 0, 1 o r 2 depending on the number of copies of the slh DYA allele for the ith bull ei = residual random term N(O,c?) There are dependencies in the data as the value of the last allelelhaplotype is known given the values of the previous n-1 haplotypes. This dependency was solved by imposing a restriction on the regression coefficients so that Zbz, = ?b3r = 0 (see r above). In this model, the separate effects of the various DQ haplotypes and DYA alleles were simultaneously estimated and tested for significance. All effects in the model, except the residuals, were considered as futed. It should be noted that this model tests exclusively for additive effects of the various MHC alleles present in the bulls. Such a model was chosen since the MIIC typings were made on breeding bulls while the disease records were collected on their daughters. Therefore, the number of copies of a certain BOLA class I1 haplotype of a bull merely reflects the approximate proportion of daughters that will inherit the particular haplotype. The dams' contribution to their daughters' genotypes is not known and therefore it has to be assumed that the gene frequencies among dams are the same in all progeny groups. The GLM procedure of the Statistical Analysis System (SAS) was used for the statistical analyses (SAS Institute Inc. 1985). As the 196 bulls used in the study belonged to 41 paternal half-sib families, it was considered necessary to correct for effects of the genetic background formed by non-MHCgenes that influence the actual trait and the fact that observations were not independent due to resemblance between half-sibs. The preferred method to adjust for these effects would be to include random effects of sire in the model. One condition for that model is that the ratio (A) between the error variance and the sire variance is known. However, when analysing genotypic values, which constitute the breeding values in this analysis, A is not equal to the variance ratio used with phenotypic values, since with breeding values the error variance is decreasing with increasing accuracy of the breeding value. Thus, with a high accuracy A will approach zero and the random model becomes a fixed model. Therefore, there are two practicable ways t o account for the resemblance between half-sibs and the background genes: either by treating sire as a fixed effect or alternatively to use the corresponding breeding value of sire as a covariate in the model for each of the three disease traits in the analysis. By using the sire breeding values instead of treating sire as a fixed effect, the effective number of bulls increases because those bulls which had no half-sibs in the material can be included. Also, the breeding values of sires, which are estimated with high accuracy based on large daughter groups, should constitute better estimates of the effects of the genetic background than the mean value based
226 A. Lundkn et al.
on the breeding values of the limited number of bulls of each sire that are included in this investigation. Therefore, in this study the covariate model was chosen for the statistical analysis.
Results The results from the statistical analyses of the effect of DQ haplotypes and DYA alleles on disease resistance are presented in Table 2. The most pronounced and consistent association of BOLA D Q with diseases was found with DQIA, one of the most frequent D Q haplotypes in this material. Bulls carrying the DQIA haplotype had significantly lower breeding values for the disease traits compared to bulls with other DQ haplotypes. The effect was most pronounced for the breeding values in which clinical mastitis was included. In the present analysis the DQ'* haplotype was present in the sons of 28 of the 41 sires (see Table 1)and among 23 of the 28 sires with more than two sons in the investigation. Out of 40 DQIA-positiveanimals for which it was possible to deduce the origin of the haplotype to either parent, 34 animals inherited DQIA from the dam. Furthermore, the DQIA-positive bulls were evenly
Table 2. Coefficients of regression and their standard errors for DQ haplotypes and DYA alleles on breeding values for various disease traits
Trait All diseases including clinical mastitis
Diseases other than clinical mastitis
-1.3 +- 0-5** -0.2 +0:5 0.4 k 0.4 -0.5 f 0.9 -0.3 f 0.6 -0-0 f 0.6 0.6 f 0.6 -0.4 f 0.8 0.0 f 0.9 -0.1 f 0.5 1.0 f 0.9 0.7 f 0.7
-1-3 f 0-5 ** -0.2 f 0.5 -0.2 f 0.4 1.0 f 0.9 -0.1 f 0.6 0.4 f 0.6 1.0 f 0.6 (*) -0.6 f 0.8 -0.5 f 0.9
-0.7 5 0.4 (*)
0.1 k 0-2 -0.1 5 0.2
-0.1 L 0-2
Clinical mastitis D Q haplotype 1A
1B 2 3 4
5 6 7 8 9 10
rare' DYA allele 1 2 a
-0.3 f 0.5 0.5 f 0.8 0.4 f 0.6
0.1
* 0.2
D Q haplotypes assigned 'rare' have frequencies below 0.03. P < 0.1.
(8)
* * P c 0.01.
-0.2 k 0.4 -0.6 & 0.4 (*) 1.3 k 0.8 -0.1 f 0.5 0.6 f 0.5 0.8 k 0-5 -0.4 f 0.7 -0.4 f 0.8 -0.2 f 0.5 0.2 f 0.8
-0.2 f 0.7 -0.1 k 0-2 0.1 f 0.2
MHC and disease resistance in cattle 227
distributed among maternal grandsires. This implies that the observed association was not merely caused by family relationships. No other DQ haplotypes, nor the DYA locus belonging to the other linkage subgroup, had a significant effect on any of the disease traits studied. When comparing the covariate model with a more conventional model where the sire effect is treated as fixed, the two methods turned out to give almost identical estimates with significant F-tests for DQIA,although the power of the tests was somewhat strengthened by the increased number of observations and the reduced number of degrees of freedom used up by the sire effect when using the covariate model. The statistical models in Table 3 were used in an attempt to estimate the relative importance of the effects of sire breeding value and the DQ1* haplotype on the variation in breeding values for clinical mastitis among bulls. A comparison of the adjusted coefficient of determination shows that the major proportion of the variance is explained by the breeding value of sire. However, an additional 2.2% of the variance in the bull breeding value for clinical mastitis is explained when the effect of the DQIA haplotype is added to the model.
Tabie 3. Contribution of the effect of the DQIA haplotype and breeding value of sire to the total variance in breeding value of bulls for clinical mastitis'
Clinical mastitis
Y,= P + b 6 4 , + e, Y,= p + b l x l , + e, Y,= IL + blxl, + b d 4 , + e,
6.57 31.08 33.27
The elements in the models have the same meaning as before and in addition: b 4 = regression coefficient of the bull breeding values for clinical mastitis (see above) on the number of copies of the DQIA haplotype. x4, = 0.1 or 2 depending on the number of copies of the DQIA haplotype. bAdjusted for the number of independent variables N - 1 SS Residual in the model: R 2 = 1 - - X dj N - p SS Corr. tot where N = no. of observations, p = d.f. for the model and SS Corr. tot. = total sums of squares corrected for the mean.
228 A. Lundkn et al.
Discussion This study has revealed a significant association between the DQIA haplotype and susceptibility to clinical mastitis in cattle of the SRB breed. To our knowledge, this is the first study on MHC-disease association based on class I1 polymorphism and also the first such study where the RFLP method has been utilized for MHC typing. The use of a DNA method was in fact a prerequisite for the present study, since all breeding bulls had been slaughtered when the study started. Thus, the MHC typings had to be made using frozen semen previously collected for AI. Previous MHC-disease association studies have been based on serological typing of class I polymorphism (e.g. Solbu et al. 1982; Lewin & Bernoco 1986; Lewin et al. 1988; Stear et al. 1988; Templeton ef al. 1988). The observed association between DQIA and clinical mastitis is of particular interest since mastitis is the most economically important disease among dairy cows in the Western world. Statistics on veterinary treatments in Sweden show that more than 20% of the dairy cows are treated against mastitis each year (Swedish Association for Livestock Breeding and Production 1989). Our results indicate that bulls heterozygous for DQIA on average have breeding values 1.3 index units lower than bulls not having DQIA (Table 2). This figure corresponds approximately to an increased incidence of clinical mastitis in first lactation cows from 8.0% to 8.3% for daughters of bulls heterozygous for DQ’*. Since the dams’ haplotypes are not known, the analyses only measure the change in haplotype frequency among daughters due to the haplotypes of their sires. If the contrast between cows with and without DQIA could have been measured, the expected difference would have been twice as large, thus from 8-0 to 8.6%. There was one single DQIA homozygous bull in the material. Interestingly, he had the second lowest breeding value for clinical mastitis (87.9) among all 196 bulls in this study. The association of DQIA remains significant even when this single DQIA homozygote is removed from the analysis. However, the observed association between DQIA and susceptibility to clinical mastitis needs to be confirmed in independent materials. In an attempt to estimate the practical significance of the observed association, the relative importance of the effects of sire breeding values and DQIAin explaining the variation in bull breeding values for clinical mastitis was compared using the models described in Table 3. The analysis showed that the determination coefficient for clinical mastitis increased from 31.1% to 33.3% when DQIA was added to a model including breeding value of sire. The figure of about 2% should be considered as a minimum estimate since a part of the DQIA effect is confounded with the effect of sire breeding value when DQ’* is not included in the model. Ways to overcome the problem with confounding are suggested by Bentsen & Klemetsdal (1990). A maximum estimate of about 6% is obtained by a model including DQIA but not breeding value of sire. This figure is comparable to the amount of variation accounted for by the breeding value of the maternal grand-grand-grandsire, if included in the model. The inference drawn from these figures is that the effect of DQIA on the variation in disease suceptibility is small, but nonetheless statistically
M H C and disease resistance in cattle 229
significant. Before selecting sires for reduced mastitis frequency, the correlated response on other production traits must be evaluated. The association between DQIA and clinical mastitis may not be a direct one. It is quite possible that DQIA confers an increased susceptibility to other disease conditions which in turn causes an increased incidence of clinical mastitis. There is evidence, for instance, for immunosuppressive effects in cattle infected by Bovine virus diarrhoea virus (Larsson et al. 1988). In this context it is also worth noting that breeding values for diseases other than clinical mastitis were lower (of borderline significance) for DQIA bulls (Table 2). The observed effects could also be caused by linked genes. An extremely close linkage disequilibrium has been found in the bovine DQ-DR class I1 region (Anderson et al. 1986b, 1988; Sigurdard6ttir et al. 1988). Due to this close association, only DQ haplotypes were used in this study. DQIA has, in all 63 animals studied so far, been found together with a single DRB RFLP type (DRBIA) as well as a single DRB type (DF4) identified by iso-electric focusing (Joostens et al., 1990). Thus, the association with clinical mastitis may equally well be caused by DRBIA or any other gene in linkage disequilibrium with DQ’~. Previous studies have indicated a tentative association between the class I specificity (BOLA-A) w16 and mastitis. Firstly, Solbu et al. (1982) reported on this association. Subsequently, an association between the blood group factor M’ and mastitis was reported (Larsen et al. 1985) where M’ is extremely closely associated with the w16 specificity (Leveziel & Hines 1984; Lindberg & Anderson 1988). M‘ and w16 are both very closely associated with the DQ haplotype DQ” in the SRB breed (Lindberg & Anderson 1988; Sigurdard6ttir et al. 1988). DQ” was not significantly associated with the incidence of clinical mastitis in the present material. Thus, the previous results by Solbu etal. (1982) and Larsen et al. (1985) could not be supported in this study, nor in an analysis on the association between the blood group factor M’ and clinical mastitis performed on a large sample of SRB breeding bulls (L. Andersson-Eklund, in preparation). However, such discrepancies could be due to differences between countries in the genetic backgrounds of the populations studied. Mastitis has proved to be a disease with a complex aetiology with several different pathogens involved. In Sweden the main pathogens are Staphylococcus aureus, Streptococcus dysgalactiae and Escherichia coli, which together account for more than half of all veterinary treatments against clinical mastitis (Swedish Association of Livestock Breeding and Production 1989). It is clear that an MHC-association study based on detailed clinical diagnosis of mastitis may give a quite different result than the present study, which is based on the overall incidence of clinical mastitis. Thus, it may well be that the moderate effect of DQIA observed in this analysis is due to a marked susceptibility among animals with this haplotype towards a specific pathogen. Such a detailed study is an obvious topic for future studies. However, studieson the influence of the MHC on the overall incidence may be more informative from a breeding point of view, since such studies make it possible to evaluate the usefulness of the MHC for improving disease resistance in a broader perspective. In this study bull breeding values with regard to disease susceptibility, based on disease records from large progeny groups, have been related to the MHC type of the
230 A. Lundkn et al.
individual bulls. Thus we have asked the question if the MHC genotype of breeding bulls has any predictive value for the incidence of disease among their daughters. There is an obvious advantage with this approach, as the number of individuals to be typed can be kept at a manageable level. The breeding value of a bull based on progeny testing, at least under the present circumstances, has a high accuracy. Thus, the size of the random variation is low compared to a situation with single observations on individual animals. This is especially evident for traits like mastitis and other diseases which have low heritabilities. Therefore a data set of the same size but with typings and registrations on individual cows would be less informative. A limitation of using breeding values is that only additive effects of the genetic marker will be detected, since MHC typings and disease observations are not derived from the same animal. Thus, associations present in certain combinations of haplotypes only will not be detected. However, from a breeding point of view it is difficult to utilize such non-additive genetic variation, particularly in a complex genetic system like the MHC. Therefore, it is our view that the use of bull breeding values is useful as an initial approach to study the relationship between a genetic marker and a complex disease trait.
Acknowledgements Sincere thanks are due to U. Emanuelson and L. Anderson-Eklund for statistical assistance, to G. Malmberg, Malmens husdjurstjanst and B. Lindht, Seminavel for kindly providing semen samples of breeding bulls, to the Swedish Association for Livestock Breeding and Production for generously providing bull breeding values and to C. Borsch for linguistic comments on the paper. The work was supported by a grant from the Swedish Council for Forestry and Agricultural Research.
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