Associations between MHC class II variation and phenotypic traits in a
free-living sheep population
“MHC effects on phenotypic traits”
Wei Huang11These authors contributed equally to this work,1,
Kara L Dicks*,1, Keith T
Ballingall2, Susan E Johnston1,
Alexandra M Sparks1,3, Kathryn
Watt1, Jill G. Pilkington1,
Josephine M Pemberton1
1 Institute of Evolutionary Biology, The University of Edinburgh,
Edinburgh, UK
2 Moredun Research Institute, Penicuik, UK
3 School of Biology, University of Leeds, West Yorkshire, UK
Correspondence author:
wei.huang@ed.ac.uk
Keywords: major histocompatibility complex, Soay sheep, selection,
phenotypic trait, parasite, immune response
Abstract
Pathogen-mediated selection (PMS) is thought to maintain the high level
of allelic diversity observed in the major histocompatibility complex
(MHC) class II genes. A comprehensive way to demonstrate contemporary
selection is to examine associations between MHC variation and
individual fitness. As individual fitness is hard to measure, many
studies examine associations between MHC diversity and phenotypic traits
which include direct or indirect measures of adaptive immunity thought
to contribute to fitness. Here, we tested associations between MHC class
II variation and five representative phenotypic traits measured in
August: weight, strongyle faecal egg count, and plasma IgA, IgE and IgG
immunoglobulin titres against the gastrointestinal nematode parasiteTeladorsagia circumcincta in a free-living population of Soay
sheep. We found no association between MHC class II variation and August
weight or strongyle faecal egg count. We did however find associations
between MHC class II variation and immunoglobulin levels which varied
with age, isotype and sex. Our results suggest associations between MHC
and phenotypic traits are more likely to be found for traits more
closely associated with pathogen defence than integrative traits such as
body weight and highlight a useful role of MHC-antibody associations in
examining selection on MHC genes.
Introduction
The immune system provides a variety of mechanisms to protect the host
from infection by rapidly evolving and highly variable pathogens. The
diversity of immune-related proteins and their associated genes are
believed to have evolved in response to such pathogen diversity via the
process of coevolution (Eizaguirre, Lenz et al. 2012, Pilosof, Fortuna
et al. 2014). Among the proteins directly involved in the initiation of
adaptive immunity, major histocompatibility complex (MHC) molecules,
encoded by MHC class I and class II gene families, are the most variable
and have been intensively researched in many species (Edwards and
Hedrick 1998, Bernatchez and Landry 2003, Piertney and Oliver 2006). MHC
genes encode heterodimeric MHC molecules which bind and present short
peptides derived from pathogens to T cells to invoke and coordinate the
adaptive immune response. Classical MHC class I genes are primarily
responsible for presenting peptides derived from intracellular pathogens
such as viruses, while classical MHC class II genes typically present
peptides derived from extracellular pathogens such as bacteria and
parasites (Bernatchez and Landry 2003).The tight mechanistic link
between pathogen infection and MHC molecules leads to the expectation
that selection pressure imposed by pathogens, known as pathogen-mediated
selection (PMS), is the major force driving high levels of diversity at
the MHC (Bernatchez and Landry 2003, Piertney and Oliver 2006, Spurgin
and Richardson 2010).
Substantial effort has been made to investigate how pathogen-mediated
selection (PMS) can maintain high levels of MHC diversity across a wide
variety of vertebrate taxa (reviewed by (Bernatchez and Landry 2003,
Piertney and Oliver 2006, Spurgin and Richardson 2010)). There are
several non-mutually-exclusive mechanisms by which pathogen-mediated
selection may occur. 1) Heterozygote advantage (HA): The HA occurs when
heterozygotes have greater fitness than either homozygote (Hughes and
Nei 1988, Takahata and Nei 1990, Penn, Damjanovich et al. 2002). 2)
Divergent allele advantage (DAA): DAA is an extension of HA. Under DAA,
individuals with high levels of functional divergence between MHC
alleles have a selective advantage over individuals with lower levels of
allelic divergence (Wakeland, Boehme et al. 1990). 3) Negative
frequency-dependent selection (NFDS): NFDS occurs due to rare allele
advantage; pathogens are predicted to be under selection to evade the
most common MHC alleles, resulting in rare MHC alleles having a
selective advantage, and creating a cyclical co-evolutionary arms race
(Takahata and Nei 1990, Slade and Mccallum 1992). 4) Fluctuating
selection (FS): Under FS, directional selection due to variation in
pathogen pressure varies in time and space such that it maintains
diversity (Hedrick 2002). Several studies have used experimental methods
to examine PMS on MHC genes (Bolnick and Stutz 2017, Phillips, Cable et
al. 2018). However, experimental studies are rarely capable of
replicating the wide array of pathogens and parasites that occur within
a wild host and are limited in the conclusions that they can draw about
natural processes. Therefore, testing these hypotheses within wild
systems is valuable (Piertney and Oliver 2006, Spurgin and Richardson
2010).
A direct way to demonstrate contemporary selection on MHC genes in a
wild population is to examine associations between MHC heterozygosity or
genotypes and fitness. As fitness measurements are not always available,
we could alternatively examine associations between MHC variation and
pathogen load (Spurgin and Richardson 2010) and other fitness-related
phenotypic traits, e.g. body weight. However, examining phenotypic
traits is a less direct approach than examining fitness components and,
in the quest to understand selection mechanisms, it is of interest to
know how consistent results from these two approaches are. Only a few
studies have analysed both MHC-fitness associations and MHC-phenotypic
trait associations in the wild (summarized in Table 1). Of these, some
studies found coherent results between MHC-fitness and MHC-phenotypic
trait associations (Paterson, Wilson et al. 1998, Kloch, Baran et al.
2012, Sepil, Lachish et al. 2013), while other studies did not (Dunn,
Bollmer et al. 2013). These mixed results could be due to some
MHC-fitness associations not acting through the phenotypic traits
examined. Therefore, it is of interest to determine which types of
traits MHC-based selection is most likely to be acting through.
Another possible explanation for variation between MHC-fitness and
MHC-phenotype studies may lie in analysis methods. First,
MHC–phenotypic trait associations may vary due to heterogeneity in
exposure or response to pathogens due to host age and sex. For example,
in a recent study of black-legged kittiwake (Rissa tridactyla ),
MHC class II diversity was positively associated with growth and tick
clearance in female but not in male chicks (Pineaux, Merkling et al.
2020). Therefore it is important to investigate whether MHC- phenotypic
traits associations vary with age and sex. In addition, there is
additive genetic variation for most phenotypic traits. When examining
MHC-phenotypic trait associations in datasets including many related
individuals, animal models should be used. The animal model framework
includes phenotypic information from individuals of varying relatedness
to estimate the additive genetic component of the trait by including the
breeding value as a random effect within a mixed effect model such that
variation in the trait that is due to additive genetic effects located
throughout the genome could be controlled (Wilson, Reale et al. 2010).
This will reduce risk of generating false positive associations
MHC–trait associations.
The unmanaged Soay sheep (Ovis aries ) population on Hirta, St
Kilda, UK has been intensively studied for more than three decades
(Clutton-Brock and Pemberton 2004). Since 1985, nearly all individuals
living in the Village Bay study area have been followed from birth,
through all breeding attempts, to death. These data, combined with a
genetically-inferred multigenerational pedigree and phenotypic data for
body weight, parasite load and plasma antibodies (Hayward, Wilson et al.
2011, Hayward, Nussey et al. 2014, Nussey, Watt et al. 2014, Berenos,
Ellis et al. 2015, Sparks, Watt et al. 2018), enable us to investigate
the interplay between MHC variation, fitness and phenotypic traits. A
previous study of Soay sheep alive between 1985 and 1994 found negative
associations between two alleles at an MHC-linked microsatellite and a
key parasite measurement, strongyle faecal egg count (FEC), and these
two alleles were also positively associated with juvenile survival
(Paterson, Wilson et al. 1998). Recently, we reported associations
between Soay sheep MHC class II variation and fitness measurements
(Huang, Dicks et al. 2020). These new findings were enabled by major
advances in the characterisation of MHC variation in Soay sheep. A total
of eight MHC class II haplotypes (named A-H) were identified through
sequence-based genotyping of a subset of the population (Dicks,
Pemberton et al. 2019) and imputed successfully for 5349 sheep sampled
from 1985 to 2012 using 13 SNPs (Dicks 2017, Dicks, Pemberton et al.
2019). We found haplotype C and D are associated with decreased and
increased male total fitness (measured as the number of offspring that
an individual had throughout its life span) respectively. In term of
fitness components, we found MHC divergence (measured as the proportion
of the amino acid sequence that differed between the two MHC haplotypes
of each individual) was positively associated with juvenile survival. We
also found that a haplotype (C) is associated with decreased adult male
breeding success while another haplotype (F) is associated with
decreased adult female life span. In addition, the frequency of
haplotype D has increased significantly through the study period more
than expected by drift (Huang, Dicks et al. 2020). These results
indicate that there is contemporary selection on MHC class II variation
in Soay sheep.
In the present study, with larger sample sizes and improved genetic
resolution of haplotypes compared with the previous study (Paterson,
Wilson et al. 1998), we examine the associations between MHC variation
and five representative phenotypic traits in Soay sheep. These traits
are August weight, a fitness-related non-immune trait, strongyle faecal
egg count, FEC, a fitness-related trait with a strong link to the immune
system and three immune traits, Teladorsagia
circumcincta -specific immunoglobulin isotypes IgA, IgE and IgG
(henceforth, ‘anti-T.circ antibodies’). August weight is an
important measure of body condition in Soay sheep and high weight is
advantageous for both survival and fecundity in Soay sheep (Coltman,
Pilkington et al. 2001, Clutton-Brock and Pemberton 2004).
Gastrointestinal nematodes (GIN) are common in Soay sheep throughout
life, with virtually 100 % prevalence in lambs, and immunity to GIN
develops with age (Craig, Pilkington et al. 2006). GIN are a major
selective force on the Soay sheep (Gulland and Fox 1992, Craig,
Pilkington et al. 2006, Hayward, Wilson et al. 2011) and GIN burden,
measured as FEC, is negatively associated with body weight (Coltman,
Pilkington et al. 2001) and over-winter survival (Gulland and Fox 1992,
Hayward, Wilson et al. 2011). Immunoglobulin isotypes IgA, IgE and IgG
are involved in the acquired immune response to GIN in sheep (Stear,
Strain et al. 1999, Lee, Munyard et al. 2011, Hayward 2013).
Parasite-specific IgA acts at mucosal surfaces and is known to reduce
worm growth and fecundity (Stear, Strain et al. 1999, Gutierrez-Gil,
Perez et al. 2010, Lee, Munyard et al. 2011). Parasite-specific IgE also
acts predominantly at mucosal surfaces and is involved in the
degranulation of mast cells, which are white blood cells involved in
parasite expulsion (McNeilly, Devaney et al. 2009, Murphy, Eckersall et
al. 2010). IgG is the primary plasma antibody that can interact directly
with the parasite. In Soay sheep, anti-T. circ IgG is positively
associated with increased survival in adult females (Nussey, Watt et al.
2014, Watson, McNeilly et al. 2016, Sparks, Watt et al. 2018). However,
a recent study decomposed the association between IgG and female
survival into within-individual and between-individual effects and found
the association was driven by within-individual variation late in life
linked to senescence rather than by between-individual differences
determined by genetics or early-life conditions (Froy, Sparks et al.
2019). We aim to determine whether MHC-phenotypic trait associations can
indicate contemporary selection on MHC genes in Soay sheep by answering
the following questions: 1) which phenotypic traits are associated with
MHC class II variation? 2) Does the association between MHC variation
and phenotypic traits vary with age and sex? 3) If there are
associations which selection mechanism can be inferred from such
associations? 4) Are there coherent patterns between MHC-phenotypic
trait associations and MHC-fitness associations?
Materials and methods
MHC data
The genetic data used in this study was obtained from a previous study
(Dicks, Pemberton et al. 2019, Dicks, Pemberton et al. 2020). Seven
expressed loci (DRB1 , DQA1 , DQA2 , DQA2-like ,DQB1 , DQB2 and DQB2-like ) within the MHC class IIa
region were characterised in 118 Soay sheep using sequence-based
genotyping. A total of eight MHC haplotypes were identified (named A to
H) and confirmed in an additional 94 Soays selected from the pedigree to
maximise diversity. A panel of 13 SNPs located in the region of MHC
class IIa haplotypes, including 11 SNPs from the Ovine Infinium HD chip
and two other SNPs located within the DQA1 gene, were selected
and genotyped in 5951 Soay sheep using Kompetitive Allele-specific PCR
(KASP) to impute the eight haplotypes. After quality control, which
included pedigree checking, the diplotypes of 5349 individuals sampled
between 1985 and 2012 were identified. For each individual successfully
diplotyped, the functional divergence between an individual’s two
haplotypes (MHC divergence) was measured as the proportion of the amino
acid sequence that differed between the two MHC haplotypes
(p-distance)(Henikoff 1996, Huang, Dicks et al. 2020).
Phenotypic traits
During an annual August catch when we try to catch as many individuals
as possible, all sheep were weighed to the nearest 0.1 kg.
In our study, faecal samples were collected from as many individuals as
possible at capture in August, and counts of nematode worm eggs were
performed using a modified McMaster technique (MAFF 1986). This protocol
enumerates Strongyle-type eggs per gram of wet weight faeces but does
not differentiate between several morphologically indistinguishable
species. Of the species contributing to FEC on St Kilda,Trichostrongylus axei , Trichostrongylus vitrinus andTeladorsagia circumcincta eggs are the most abundant, but eggs
from Chabertia ovina , Bunostomum trigonocephalus andStrongyloides papillosus may also be present (Craig, Pilkington
et al. 2006). This measure of FEC is correlated with adult worm count
within the abomasum in Soay sheep on St. Kilda and on Lundy (Grenfell,
Wilson et al. 1995).
IgA, IgE and IgG activity against antigens of the third larval stage of
T. circ were measured using ELISA from blood samples obtained from sheep
caught in the August catches. Full laboratory details and quality
control measures were described in the previous study (Sparks, Watt et
al. 2018). Of 3189 individuals assayed, 13 individuals failed quality
control for IgA, 8 individuals for IgE and 27 individuals for IgG. Due
to the lack of standard solutions, all results were measured as optical
density (OD) values. The OD ratio of each sample was calculated as
(sample OD – blank OD) / (positive control OD –blank OD). If the blank
OD was greater than the sample OD, the OD ratio was set to zero to
prevent negative OD ratios. The mean OD ratio was then calculated for
each duplicated sample, and these values were used in all subsequent
analyses.
For all the phenotypic traits used in this study, we only included
individuals which were successfully genotyped for MHC class II
diplotype, and we excluded individuals which had received an
experimental treatment prior to sampling, for example, an anthelminthic
bolus. The number of records that we used for each analysis is shown in
Table 2.
Statistical analysis
We used animal models (AMs) to study the associations between MHC
haplotypes and phenotypic traits. An AM was built for each phenotypic
trait by fitting an additive genetic effect with a covariance structure
proportional to the pedigree relatedness matrix in addition to the
generalized linear mixed models. Each null model included fixed and
random effects relevant to the studied phenotypic trait and age-group
based on the findings of previous studies (Hayward, Wilson et al. 2011,
Berenos, Ellis et al. 2016, Sparks, Watt et al. 2018) (Table 3).
Genome-wide inbreeding, Fgrm (Fhat3 from (Yang, Lee et
al. 2011) based on 38K genome wide SNPs (Berenos et al 2016), was
included in all models as a fixed effect to ensure any MHC
heterozygosity associations did not simply reflect inbreeding
depression. First, for each null model, we added MHC effects as MHC
heterozygosity (0 for homozygote, 1 for heterozygote) and each MHC
haplotype as dosage (0, 1 or 2) to test whether there are non-additive
dominance effects (Hu, Deutsch et al. 2015, Lenz, Deutsch et al. 2015).
In order to test any sex-dependent association between MHC diversity and
phenotypic traits, we also fitted MHC by sex interactions including
heterozygosity by sex and haplotype by sex interactions for each model.
In all models, haplotype H was treated as a reference haplotype so any
differences between individual haplotypes were relative to haplotype H.
In another sets of models, we also tested the association between MHC
divergence and phenotypic traits by adding MHC divergence and divergence
by sex interaction into each null model.
We used a conservative statistical framework to determine the
significance of MHC effects on phenotypic traits in Soay sheep. For
models including MHC heterozygosity and haplotypes, the significance of
MHC heterozygosity and MHC heterozygosity by sex interactions can be
directly determined by whether the 95% credibility interval overlapped
with zero. The significance of specific haplotypes was first determined
using Wald tests for models with or without all MHC haplotypes fitted in
the same model. When the Wald test was significant (p<0.05) we examined the significance of specific MHC haplotypes
by conducting an additional analysis comparing the estimated effect of
each haplotype against the mean of the effect estimates of all the other
haplotypes (see Supplementary 1 for detailed methods). Similarly, Wald
tests for each model with and without haplotype by sex interactions in
the same model were used to determine the significance of haplotype by
sex interactions. If the Wald test was significant, we conducted an
additional analysis comparing the estimated effect of each haplotype by
sex interaction with the mean of the effect estimates of all the other
haplotype by sex interactions (see Supplementary 1 for detailed method).
For models including only MHC divergence, the significance of MHC
divergence and MHC divergence by sex interactions can be directly
determined by whether the 95% credibility interval overlapped with
zero. Finally, if any MHC effect by sex interaction was significant, we
ran sex-specific models to determine whether there was a significant
association between the MHC effect and phenotypic trait within either
females or males.
Since the phenotypic traits have different distributions, we used
different transformations for each trait. For August weight, we used the
raw data as the distributions were normally distributed in all age
groups. However, as mean August weight is known to vary with age,
separate models were run for the different age classes (lambs, yearlings
and adults) (Supplementary Fig 2.1) (Wilson, Pemberton et al. 2007).
Strongyle FEC was not normally distributed so we carried out log
transformation as Log(FEC+50) by adding half the minimum detection limit
(100 eggs/g), and we again ran separate models for lambs, yearlings and
adults as means were different (Supplementary Fig 2.2). Distributions of
immunological traits were largely normal except lamb IgE. However, lamb
IgE was not transformed in this study as MCMCglmm takes a Bayesian
approach to mitigate the effect of non-Gaussian response variables. A
pronounced increase in antibody levels occurs between lambs and
yearlings (Sparks, Watt et al. 2018) but there was no difference in the
distributions between yearlings and adults (Supplementary Fig 2.3).
Thus, we fitted separate models for lambs and older sheep (including
yearlings and adults) All models were run in MCMCglmm in R v.3.5.2 for
60000 iterations with a sampling interval of 30 after 5000 iterations
(Hadfield 2010, R Core Team 2013).
Results
August weight
There was no significant association between MHC heterozygosity or
divergence and August weight in any age group (Figure 1, Supplementary 3
and 4). There was no significant heterozygosity by sex interaction.
However, there was an MHC divergence by sex interaction on lamb weight
where the effect of MHC divergence on male lamb weight was significantly
more positive than that on female lamb weight (Supplementary 3 and 4).
However, MHC divergence was not significant associated with lamb weight
in sex-specific models (Supplementary table 5.1).
The Wald test for haplotype differences was not significant in any age
group so no significant association was identified between specific MHC
haplotypes and August weight (Table 4, Figure 2). The result of Wald
test indicated that there was no significant haplotype by sex
interaction for August weight (Supplementary 6).
Strongyle FEC
There was no association between MHC heterozygosity or divergence and
strongyle FEC in any age group. Also, there was no significant MHC
heterozygosity by sex interaction and MHC divergence by sex interaction
(Figure 1, Supplementary 3 and 4). The Wald test for haplotype
differences was not significant in any age group, so no significant
association was identified between specific MHC haplotypes and strongyle
FEC (Table 4, Figure 3). Also, the Wald test indicated that there was no
significant haplotype by sex interaction for strongyle FEC
(Supplementary 6).
Immunoglobulins
Anti-T. circumcincta IgA
We found that both MHC heterozygosity and MHC divergence were positively
associated with IgA levels in lambs but not in older age groups (Figure
1, Supplementary 3 and 4). There was neither MHC heterozygosity by sex
interaction nor MHC divergence by sex interaction (Supplementary 3 and
4).
When testing for haplotype differences, Wald tests were significant in
both lambs and older sheep (Table 4). In lambs, haplotype C was
associated with increased IgA while haplotype G was associated with
decreased IgA (Figure 4A, Supplementary 7). In older sheep, both
haplotype A was associated with decreased IgA (Figure 4B, Supplementary
5). In addition, the Wald test for haplotype*sex interactions was
significant for lambs but not significant for older sheep. The effect of
haplotype E on IgA in male lambs was significantly more positive than
that on female lambs (Supplementary 6). When testing in sex-specific
models, haplotype E was positively significant with lamb IgA level in
males but not in females (Supplementary table 5.3).
Anti-T. circumcincta IgE
There was no association between MHC heterozygosity or divergence and
IgE levels, or significant heterozygosity by sex or divergence by sex
interaction, in any age group (Figure 1, Supplementary 3 and 4).
When testing for haplotype differences, Wald tests were only significant
in older sheep (Table 4). Haplotypes C and D were associated with
increased IgE while haplotypes G and H were associated with decreased
IgE (Figure 4B, Supplementary 7). The Wald tests for haplotype by sex
interactions were not significant for either lamb or older sheep, which
indicated there were no significant haplotype by sex interactions for
IgE (Supplementary 6).
Anti-T. circumcincta IgG
There was no association between MHC heterozygosity or divergence and
IgG in either lambs or older sheep (Figure 1, Supplementary 3 and 4). We
found no significant heterozygosity by sex interaction while the effect
of divergence on IgG in older sheep was significantly more negative in
males than that in females (Supplementary 3 and 4). However, MHC
heterozygosity was not significant associated with IgG in either older
females or males in sex-specific models (Supplementary table 5.2).
When testing for haplotype differences, the Wald test was significant
only in older sheep (Table 4). We found haplotype A was associated with
decreased IgG (Figure 4B, Supplementary 7). However, the Wald test for
haplotype by sex interactions was not significant in either lambs or
older sheep, which indicated there were no significant haplotype by sex
interactions for IgG (Supplementary 6).
Discussion
In this study, we tested for associations between MHC class II variation
(heterozygosity, specific haplotypes and divergence) and five
representative phenotypic traits in a large sample of Soay sheep using a
modelling approach that accounted for genome-wide additive genetic and
inbreeding effects. While we found no associations between MHC variation
and August weight or strongyle faecal egg count, we found a number of
associations with anti-T.circ. antibody levels. Specifically, we
found associations between MHC heterozygosity or divergence and
divergence and IgA levels in lambs and a number of associations between
specific MHC haplotypes and antibodies that vary with age, isotype and
sex.
Several previous studies have found evidence that MHC heterozygosity or
specific MHC alleles are associated with weight or body size in other
species (e.g. (Lenz, Wells et al. 2009, Lukasch, Westerdahl et al.
2017)). Although fitness is associated with body size in Soay sheep
(Coltman, Pilkington et al. 2001), we did not find any MHC associations
with August weight in our study. August weight is a polygenic trait with
modest heritability (Supplementary 9) (Berenos, Ellis et al. 2015). As a
non-immunological trait, there is also no direct connection between the
function of MHC genes and August weight. Thus, it may be not surprising
that we have not found any associations between MHC variation and August
weight.
MHC class II molecules are involved in the presentation of peptides from
gastrointestinal nematodes for recognition by the immune system
(Janeway, Travers et al. 1996). Variation in such responses to
gastrointestinal nematodes infection within a population has been
implicated in driving balancing selection which maintains MHC diversity
(Froeschke and Sommer 2005, Madsen and Ujvari 2006, Lenz, Wells et al.
2009, Kloch, Babik et al. 2010). Association between MHC class II
variation and FEC has been reported in a number of sheep breeds
(reviewed in (Valilou, Rafat et al. 2015)) and previous analyses have
demonstrated heritable variation in FEC as well as selection for
parasite resistance in Soay sheep (Coltman, Pilkington et al. 2001,
Coltman, Wilson et al. 2001, Beraldi, McRae et al. 2007, Hayward, Wilson
et al. 2011). However, in this study, we did not find any association
between MHC variation and strongyle FEC.
Several features of the FEC data may contribute to the lack of
association in Soay sheep. The measure of FEC used here is a crude
measure of parasite burden, both in terms of the way it was measured and
what the measure actually represents in terms of parasite species.
Because of the dilution factor used in the modified McMasters method
(MAFF 1986) for estimating FEC, the data are in multiples of 100, which
combined with overdispersion, makes modelling FEC challenging. Also,
individuals with 0 eggs per gram may have no strongyle worms or may have
a very low burden. There may also be a very complicated relationship
between FEC and the community composition of worm burden. For example in
naturally infected Scottish Blackface sheep, high FEC was associated
with a wider range of strongyle species (Stear, Bairden et al. 1996).
Therefore, increased FEC may be confounded with increased species
diversity. If there is variation among MHC haplotypes in their ability
to present peptides from different worm species, we may not expect to
detect a direct association between MHC haplotype and strongyle FEC.
Our results differ from an earlier study of MHC-FEC association in the
same population that used the DRB1-linked microsatellite OLADRB as a
marker of MHC class II haplotypes. In that study, a positive association
between FEC and OLADRB allele 257 in lambs, a positive association
between FEC and OLADRB allele 267 in yearlings and a negative
association between FEC and OLADRB allele 263 in adults were identified
(Paterson, Wilson et al. 1998). However, we did not recover such
associations in the current study. The previous study used 370
individuals, whereas in this study, we used FEC measures from 1183
lambs, 704 yearlings and 2205 FEC measures from 794 adults (Table 2).
Also, the MHC genotyping method used in the current study captures MHC
class II composition accurately, while some OLADRB alleles correspond to
multiple MHC class II haplotypes (Dicks, Pemberton et al. 2020). The
advances in sample size and genotyping method are likely to contribute
to this disparity in results.
Previous studies have demonstrated associations between MHC variation
and antibody response in wild populations (summarized in (Gaigher, Burri
et al. 2019)). Some studies found significant associations (Bonneaud,
Richard et al. 2005, Charbonnel, Bryja et al. 2010, Cutrera, Zenuto et
al. 2011, Gaigher, Burri et al. 2019) while others did not (Ekblom,
Hasselquist et al. 2013, Cutrera, Zenuto et al. 2014). A recent study
suggested that the disparity of findings in previous studies examining
association between MHC variation and immunocompetence is likely caused
by insufficient sample size and recommended a minimum sample size of 200
individuals to achieve sufficient power for testing associations of
small effect size between MHC variation and immunocompetence (Gaigher,
Burri et al. 2019). From this perspective, our sample size was large
enough to have sufficient statistical power to test associations between
MHC variation and immune measures (Table 2). In addition, previous
studies investigating the association between MHC variation and antibody
response have mainly used non-specific challenge, such as sheep red
blood cell antigens (SRBC) and hemagglutinin, to elicit an antibody
response (Bonneaud, Richard et al. 2005, Cutrera, Zenuto et al. 2011,
Cutrera, Zenuto et al. 2014, Gaigher, Burri et al. 2019). An exception
is a study of Great snipe (Gallinago media ) that used diphtheria
and tetanus toxoid as antigens (Ekblom, Hasselquist et al. 2013).
Antibody against such challenges may be informative on the host’s
general immunocompetence, but may not reflect the host’s
immunocompetence in response to the actual pathogens imposing selection
in the host’s natural environment. By using the antigen ofTeladorsagia circumcincta , our study was able to test association
between MHC variation and a relevant pathogen-specific antibody
response. Although we did not find significant association between MHC
variation and FEC, we still expect to find significant associations
between MHC variation and anti T.circ antibodies because of the
functional link between MHC genes and adaptive immune response (Janeway,
Travers et al. 1996). Indeed, we found several associations between MHC
variation and anti-T.circ antibodies in Soay sheep, in contrast
to our results for weight and FEC. Such results suggest MHC class II
variation could contribute the inter-individual heterogeneity of immune
response to GIN in Soay sheep.
The associations between MHC class II variation and anti-T.circantibodies varied between different age classes and among different
isotypes. First, we only found association between MHC heterozygosity or
divergence and IgA level in lambs. This result is consistent with a
previous study of MHC-fitness associations which identified a positive
association between MHC divergence and juvenile survival (Huang, Dicks
et al. 2020) and indicates that there may be an age-dependent MHC
heterozygote advantage or MHC divergent allele advantage in Soay sheep
acting via IgA. However, the model including MHC heterozygosity,
individual MHC haplotypes and MHC divergence showed neither MHC
heterozygosity nor MHC divergence was significant (Supplementary 8).
Thus, we could not conclude the positive effect of MHC divergence on
lamb IgA was independent of MHC heterozygosity and vice versa .
Second, although we found associations between specific MHC haplotypes
and the IgA titre in both lambs and older sheep, IgE and IgG titres were
only associated with MHC haplotypes in older sheep. This is consistent
with a previous study in domestic sheep which found that associations
with specific MHC haplotypes were only present for lamb IgA but not for
lamb IgE (Ali, Murphy et al. 2019). Since the acquired immune response
develops over the first year of life (Stear, Strain et al. 1999), the
change in adaptive immune response may result in significant
associations with specific MHC haplotypes in older IgE and IgG.
Nevertheless, in terms of selection mechanism, our antibody results are
consistent with negative-frequency dependent selection or fluctuating
selection acting in both age classes.
The MHC-antibody associations are also partially consistent with the
genetic architecture of anti-T.circ antibodies described in a
recent genome-wide association study (GWAS) of Soay sheep. Lamb IgA and
older sheep IgE levels were both associated with the MHC class II region
on chromosome 20 (Sparks, Watt et al. 2019) and we recovered those
associations in this study. However, the associations with IgA and IgG
level in older sheep were not detected in the previous GWAS study. An
explanation for such difference probably lies in the different
approaches. Even with high density SNPs, a GWAS tests each SNP
independently, and each SNP has only two alleles. The ovine SNP arrays
have sparse coverage of the MHC and it requires ~13 SNPs
to define the eight haplotypes in this region as we have found (Dicks,
Pemberton et al. 2020). Therefore, it is not surprising that a GWAS
could miss MHC-antibody associations in this hypervariable region.
In order to test whether there are sex-dependent associations between
MHC variation and phenotypic traits, we fitted MHC by sex interactions
throughout our statistical models. We found the effect of MHC divergence
on lamb weight and older IgG level were significantly different between
males and females. However, MHC divergence was neither associated with
lamb weight nor older IgG level when testing in sex-specific models.
Regarding specific MHC haplotypes, we found that only the association
between haplotype E and lamb IgA was significantly different between
males and females. When testing in sex-specific models, haplotype E was
positively significant with lamb IgA level in males but not in females.
These results suggest sex-dependent effects of haplotype E on lamb IgA
level in Soay sheep which could result from the differences in ranging
behaviour and life history between males and females (Clutton-Brock and
Pemberton 2004).
In the present study, we have investigated MHC-phenotypic trait
associations for multiple phenotypic traits. Most of the traits have
been found to be associated with fitness or fitness components in
previous studies (Coltman, Pilkington et al. 2001, Hayward, Wilson et
al. 2011, Sparks, Watt et al. 2018). Thus, we hypothesised that we would
find links between MHC-phenotypic trait associations and MHC-fitness
associations. In this study, we only found associations between MHC
class II genes and antibody titres. Neither August weight nor FEC was
associated with MHC class II genes. When comparing MHC-antibody
associations with the associations between MHC variation and fitness
components identified in a previous study (Huang, Dicks et al. 2020), we
found MHC divergence were both positively associated with both lamb IgA
level and juvenile survival. In term of specific MHC haplotype,
haplotype C was positively associated with both older IgE level but
negatively associated with adult male breeding success (including both
yearling and adult sheep). However, haplotype F was associated with
decreased adult female life span but not associated with antibodies
(Huang, Dicks et al. 2020). Although lamb IgA level was not
significantly associated with juvenile survival, there is a coherent
pattern between lamb IgA level and FEC (Sparks, Watt et al. 2018). A
raised level of IgA is negatively associated with lamb FEC and lamb FEC
is negatively associated with annual fitness (Hayward, Wilson et al.
2011, Sparks, Watt et al. 2018). Thus, it is likely that lambs with
divergent MHC constitution have a survival advantage through raised
anti-T. circ IgA level. However, such a coherent pattern is not
observed in adults as older IgE level was not associated with adult
fitness component (Sparks, Watt et al. 2018). Therefore, it is not clear
whether selection on MHC variation could act through anti-T.circantibody response.
Overall, we can conclude three points from our study. First, we only
identified associations between MHC variation and immune traits,
suggesting that associations are more likely to be found as one moves
from highly integrative traits such as body weight to specific and more
molecular traits. Second, associations between antibody traits and MHC
variation varied with age, isotype and sex. Associations suggestive of
divergent allele advantage and divergent allele advantage were only
found in lambs, while associations suggestive of negative frequency
dependent selection or fluctuating selection were found in both lambs
and older sheep. Third, we found few MHC-phenotypic trait associations
that were coherent with MHC-fitness associations except an association
between MHC divergence and lamb IgA level. Overall, our results suggest
that examining the association between MHC variation and
pathogen-specific immune response is useful in the study of selection on
MHC variation in wild populations.
Acknowledgements
We thank the National Trust for Scotland for permission to work on St.
Kilda and QinetiQ, Eurest and Kilda Cruises for logistics and support.
We thank I. Stevenson and many volunteers who have collected samples and
all those who have contributed to keeping the project going. The MHC
diplotyping method and the diplotype dataset were developed and
generated by Kara Dicks and Susan Johnston. SNP genotyping was conducted
at the Wellcome Trust Clinical Research Facility Genetics Core. Field
data collection has been supported by NERC (NE/M002896/1) over many
years, the diplotyping was supported by the BBSRC and Royal Society and
most of the SNP genotyping was supported by the European Research
Council (AdG 250098). Wei Huang is supported by Edinburgh Global
research scholarship.
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Data Accessibility
All the data and R script pf this manuscript are available through the
following link: dx.doi.org/10.6084/m9.figshare.14401718
Author contribution
W.H and J.M.P designed the study. K.L.D conducted the MHC genotyping.
A.M.S and K.W generated the antibody data. J.G.P collected the data from
the field. W.H analysed the data and wrote the manuscript. All the
authors contributed to the final version of the manuscript.
Tables and Figures