MHC Diversity in Bottleneck Ed Populations-A Simulation Model

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R E S E A R C H A R T I C L E

MHC diversity in bottlenecked populations: a simulation model

Maciej Jan Ejsmond•

Jacek Radwan

Received: 3 February 2009/ Accepted: 25 September 2009

Ó Springer Science+Business Media B.V. 2009

Abstract The depletion of variation at MHC loci, which

play a crucial role in pathogen recognition, has been pos-tulated to be one of important extinction risk factors for

endangered populations. Thus, it is important to understand

how selection affects the level of polymorphism in these

genes when populations undergo a reduction in size. We

followed MHC diversity in computer simulations of pop-

ulation bottlenecks. The fates of MHC alleles in the

simulations were determined either by drift, or by balanc-

ing selection resulting from host–parasite coevolution. We

found that the impact of selection on MHC polymorphism

in bottlenecked populations was dependent upon the

timescales involved. Initially, selection maintained lower

number of alleles than drift, but after *40 generations of

hosts selection maintained higher MHC diversity, as

compared to drift. The adverse effects of decreased MHC

polymorphism on population viability may be, to some

extent, compensated for if selection helps to retain MHC

alleles which show high functional diversity, which should

allow protection against a broader range of pathogens. Our

simulation shows, however, that the mean divergence of

alleles retained under selection in bottlenecked populations

is not, on average, significantly higher than the divergence

due to drift.

Keywords Major histocompatibility complex Á

Balancing selectionÁ

ConservationÁ

ExtinctionÁ

Bottleneck

Introduction

The MHC genes code for peptides that present antigens to

lymphocytes, thus initiating the adaptive immune response.

This function seems to be the reason that the MHC genes

are the most polymorphic vertebrate genes (Garrigan and

Hedrick 2003; Sommer 2005; Piertney and Oliver 2006).

Quickly evolving parasites may adapt to the most common

host genotypes and escape detection of their antigens by the

adaptive immune system of the host. Rare allelic variants of

MHC genes, to which parasites are unlikely to adapt, should

thus be favoured by negative frequency-dependent selection

(Snell 1968; Borghans et al. 2004). Indeed, there is some

evidence that rare alleles may confer resistance to parasites

(de Campos-Lima et al. 1997; Westerdahl et al. 2004).

Additionally, heterozygote advantage in resistance to para-

sites can contribute to polymorphism at MHC loci, as MHC

heterozygosity allows a broader range of antigens to be

presented (Doherty and Zinkernagel 1975), a theory which

has also gained some empirical support (McClelland et al.

2003; Froeschke and Sommer 2005).

In bottlenecked species, MHC variation is often severely

reduced (e.g. Ellegren et al. 1993; Radwan et al. 2007; Siddle

et al. 2007). O’Brien and Evermann (1988) and Hughes

(1991) have argued that species in which MHC variation

becomes depleted are more susceptible to disease and thus

more prone to extinction. Therefore, understanding the role

of selection in maintaining MHC variation in bottlenecked

populations has implications for the conservation of endan-

gered species (see Radwan et al. 2009 for recent review).

M. J. Ejsmond (&)

Institute of Environmental Sciences, Jagiellonian University,

Krakow, Poland

e-mail: [email protected]

J. Radwan

Institute of Nature Conservation, Polish Academy of Sciences,

Krakow, Poland

123

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DOI 10.1007/s10592-009-9998-6



The higher number of MHC alleles, as compared to

neutral markers (Aguilar et al. 2004), and the high dis-

similarity between MHC allele sequences (Hedrick 2003)

have been interpreted as evidence for the role of balancing

selection in maintaining MHC diversity in bottlenecked

populations. However, the ability of balancing selection to

maintain polymorphism may depend on equilibrium allele

frequencies (Robertson 1962) and population size (Hedrick 1972). Here we investigate the role of selection in main-

taining MHC polymorphism in simulated bottlenecked

populations, allowing for the simultaneous action of het-

erozygote advantage and frequency-dependent selection.

We also investigate whether selection can be expected to

maintain more divergence between alleles than drift. Based

on observations of several endangered species, Hedrick

(2003) argued that this may often happen, as heterozygote

advantage would be more pronounced if alleles substan-

tially differ in the range of antigens they bind. Under such a

scenario, an endangered species might be able to cope with

pathogen assault better than could be expected based on thenumber of alleles retained in the population.

Methods

Deriving host populations before bottleneck

To derive source host populations evolving in the presence

of pathogens prior a bottleneck, we adopted a modification

of the simulation model proposed by Borghans et al.

(2004).The model simulates diploid hosts, with a constant

population size, coevolving with populations of 25 haploid

pathogen species. To investigate the effect of the number

of pathogen species on MHC polymorphism we also run a

few exploratory simulations of coevolution with 12 path-

ogen species. The scenario of coevolution between hosts

and parasites we simulated included both frequency-

dependence and heterozygote advantage, as fitness of a

heterozygote bearing an allele capable of pathogen recog-

nition was set to be equal to that of a homozygote bearing

the same allele. The heterozygote was thus twice as likely

to respond to a random parasite. In our simulations, we

represented each of the two host MHC molecules being

carried by a diploid host as binary strings of 16 bits. Each

bit may be thought of as a representation of an amino acid

crucial for binding the antigens (e.g., those forming pockets

implicated in the specificity of binding; Stern et al. 1994)

that subsequently get presented to T-cell receptors. We

assumed that each haploid pathogen can produce 20 anti-

gens, each 16-bits long. As in Borghans et al. (2004), we

assume that a random MHC molecule has a probability

equal to 0.043 of presenting one randomly generated

antigen. Thus, the probability that a randomly generated

pathogen with 20 antigens will be immuno-dominantly

presented by a heterozygous host with a particular pair of

MHC molecules is 0.88. Such parameters have been shown

to maintain realistic levels of polymorphism in simulated

populations (Borghans et al. 2004). If at least seven bits of

the antigen sequences matched a MHC molecule, the

pathogen was immunodominantly presented. The number

of antigens presented simultaneously was assumed to haveno effect on the strength of immune response or on host

fitness.

In our simulations, hosts interacted with 25 species of

haploid pathogens, for 10 pathogen generations per one

host generation, with all pathogens species having the same

mutation rate. All 25 pathogen species had population sizes

equal to the sizes of host populations. Each new generation

of pathogens was created with haplotype frequencies pro-

portional to the fitness gained by each haplotype in the

parental generation. The fitness of a particular pathogen

haplotype was proportional to the number of hosts it

infected. During each generation, each host was exposed toall parasite species. Each host was attacked by one parasite

of each species. Parasite haplotypes attacking individual

host, were drawn at random in each pathogen generation,

with a probability equal to their proportion in the popula-

tion. As in Borghans et al. (2004), the fitness of hosts was

calculated as the square of the proportion of recognized

pathogens during a given generation. Consequently, hosts

that presented the same number of pathogens from differ-

ent species had the same fitness.

After every 10 pathogen generations, a new generation

of hosts was recruited, based on host fitness. During host

recruitment, each descendant inherited one MHC haplotype

from each of two different individuals drawn at random

from the parental generation with the probability propor-

tional to the fitness of an individual. Mutations in host

MHC molecules were simulated by generating new bit

strings to account for the fact that MHC variation often

arises by micro-recombination rather than by point muta-

tion. In our simulations, we assume a rate of 10-5 muta-

tions per allele, per host generation.

Haploid pathogens reproduce asexually, such that the

genotypes of the offspring and parents are identical, except

for mutations. We simulated mutations stochastically,

where each bit of the antigen could change to the reverse.

Based on the work of Borghans et al. (2004), we assumed

the mutation rates for parasites are generally higher than

they are for hosts, to allow for a higher rate of evolution of

parasites. These somewhat oversimplified assumptions

about mutational processes in parasites and hosts appear

not to influence general features of the derived populations

(Borghans et al. 2004).

We originally derived populations under four different

mutation rates: 10-2, 5 9 10-3, 2 9 10-3, or 10-3 per

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antigen, per pathogen generation. However, 10-2 proved

too high a mutation rate, effectively precluding adaptation

of parasites to host genotypes by disrupting coevolved

haplotypes of parasites. This was evident by the very high

host fitness compared to other mutation rates (not shown)

and little variance in fitness between hosts, similar to what

occurs under drift (Fig. 3). Consequently, this mutation

rate was not considered below in most of analyses. We alsovaried the pre-bottleneck host population size (1,000, 3,000

and 5,000).

Coevolution was started at the point at which a popu-

lation of hosts was randomly generated, such that host

polymorphism was maximal at the outset, and then evolved

to the level set by natural selection. This method shortened

the time necessary to derive host populations and gave the

same results as evolution starting from two host alleles.

Hosts and parasites were allowed to co-evolve for 2,000

host generations, i.e. 20,000 pathogen generations, which

was enough for the number of MHC alleles to stabilize for

all mutation rates studied (Fig. 1). We derived 15 replicatehost populations for each combination of parameters.

MHC polymorphism under a bottleneck

The populations to be bottlenecked were derived under four

pathogen mutation rates: 10-2, 5 9 10-3, 2 9 10-3,or10-3

and three pre-bottleneck host population sizes (1,000, 3,000,

5,000). For each set of parameters, 15 populations were

independently derived. Each such population was

bottlenecked to five different population sizes, as described

below, and followed under the same pathogen mutation rates

as before bottleneck. We compared two scenarios: coevo-

lution between host and pathogens (including simultaneous

action of frequency dependence and heterozygote advan-

tage) and genetic drift of host alleles. Additionally, for a

limited set of parameters, we estimated effects of frequency

dependence and heterozygote advantage separately.To simulate the effect of a prolonged bottleneck, a small

number of hosts (12, 25, 50, 100, 200) was randomly

chosen from a large population derived under host–parasite

coevolution as described above. Simultaneously, each

pathogen species suffered the same reduction in population

size as host population. After this step, for the next 100

host generations we analyzed MHC polymorphism, fre-

quency and fitness of all alleles under two scenarios—

coevolution and genetic drift. In the coevolution scenario,

fitness functions of hosts and parasites were constructed as

described above for populations before bottleneck. In the

drift scenario, hosts that passed to the next generation weredrawn at random. Population size was constant in time.

For each of 15 independently derived source populations

for a given set of parameters, we simulated 20 independent

bottleneck events, consisting of an appropriate number of

randomly chosen host genotypes. Each of 20 events was

treated as a replicate nested in one derived population and

run 20 times to assess the mean trajectory of the studied

parameters under coevolution and under drift. In this way

we derived 400 replicates (20 9 20) for each indepen-

dently originated pre-bottleneck population (which gives

15 9 400 = 6,000 runs for each scenario studied). We

then calculated the averages of those mean trajectories over

each of the 400 replicates for each of 15 independently

derived source populations.

In order to investigate separately effects on MHC

polymorphism in bottlenecked populations of each of the

two forms of balancing selection studied: heterozygote

advantage and frequency-dependence, we run simulations

where only one form was operating following the bottle-

neck. Excluding frequency-dependence was achieved by

drawing parasites to the next generation at random, such

that they could not adapt to the most common host geno-

types. In simulations where frequency-dependence was

retained, but heterozygote advantage eliminated, the hosts

were set as haploids. This eliminates heterozygote advan-

tage (Borghans et al. 2004), but causes a decrease in the

number of gene copies segregating in a population.

Therefore, we additionally simulated haploid hosts with

population sizes twice as high as those of diploid hosts. We

used population sizes of 50 and 100 individuals and path-

ogen mutation rates 5 9 10-3 and 2 9 10-3. Because all

sets of parameters yielded similar conclusions, below we

only present a scenario with 2 9 10-3 mutation rate.

0 200 400 600 800 1000 1200 1400 1600 1800 20000

20

40

60

80

100

120

140

Time [generations]

N u m b e r o f a l l e l e s

0.010

0.005

0.005

0.002

0.001

Fig. 1 The mean number of alleles during coevolution in source host

populations of 3,000 individuals, at different pathogen mutation rates

(shown above each trajectory). Solid lines indicate mean trajectories

of coevolution with 25 pathogen species (as used in all subsequent

simulations); a dotted line indicates coevolution with 12 pathogen

species. Error bars indicate standard deviation calculated for 15

replicates

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Sequence divergence

We also studied the divergence of the alleles which were

retained in a population. The level of divergence between a

particular pair of alleles was assessed in two ways. First,

we computed the similarity between bit sequences, by

calculating the number of identical bits in a pair of alleles.

Second, we considered the differences between retainedalleles with respect to the pathogen genotypes they bind to.

To this end, we generated all 65,535 possible 16-bit path-

ogen antigens. For each pair of alleles we calculated the

number of antigens that could potentially be presented by

both alleles, where the higher this number, the higher the

functional similarity between alleles. The mean similarity

for all pairs of retained alleles was used as a measure of

sequence/functional divergence within a population. To

estimate the significance of the differences in sequence

resemblance and functional divergence between drift and

coevolution scenarios, we computed bootstrapped 95%

confidence intervals using 15 mean trajectories (i.e., aver-aged trajectories for 15 derived populations). Using means

guarantees the independence of measurements taken into

account during bootstrapping, as replicates derived from

the same pre-bottlenecked host population are nor inde-

pendent. The effects of a bottleneck on MHC polymor-

phism, and on allele divergence under coevolution, were

investigated using three different per antigen mutation

rates: 5 9 10-3, 2 9 10-3 and 10-3 and three different

pre-bottlenecked population sizes (1,000, 3,000 and 5,000).

Incidental bottleneck

We also investigated the effects of an incidental bottleneck

on the polymorphism anddivergence of MHCalleles. To this

end, a source population ( N = 3,000) of coevolving hosts

and each pathogen species was reduced to 50 individuals, as

during permanent bottleneck, but such a low population size

was maintained for only 10 host generations. After the bot-

tleneck, the population size was increased to the original

number ( N = 3,000), with genotype frequencies propor-

tional to their fitness,bothpathogens and hosts. As wedid for

the prolonged bottleneck, we compared the outcomes of

coevolution and genetic drift with three pathogen mutation

rates, same as in prolonged bottleneck scenario. For 1,000

host generations after the bottleneck, we traced MHC poly-

morphism and the divergence of alleles retained in the host

population, in the same manner as in the prolonged bottle-

neck simulation. The mean trajectory for the number and

divergence of alleles in the host population was a result of

averaging three replicates for each of 15 derived populations.

Confidence intervals for mean sequence resemblance and

functional divergence of alleles were computed, as in the

previous case, using 15 mean trajectories.

All of our simulations and analyses were performed in

MATLAB 7.5. (MathWorks).

Results

As in Borghans et al. (2004), the level MHC polymorphism

in our derived populations depended mainly on the path-ogen mutation rates, and on host and pathogen population

sizes (Fig. 2). Decreased parasite number resulted in a

lower level of polymorphism maintained. Variation in

fitness between host genotypes, which reflects selection

pressures exerted by pathogens, was the highest for the

lowest pathogen mutation rate we simulated (Fig. 3).

The initial number of alleles after a reduction in popu-

lation size (permanent bottleneck) depended on the number

present in the pre-bottleneck population, but this impact

decayed with time, both under drift (not shown) and under

coevolution (Fig. 4). The rate of the decrease in the number

of alleles was proportional to bottleneck severity, bothunder drift (not shown) and under coevolution (Fig. 5). The

levels of polymorphism for different parasite mutation

rates in bottlenecked populations under the coevolution

scenario, relative to the genetic drift scenario, are shown in

Fig. 6. The relative level of polymorphism initially

decreased, reaching a maximum of *20% fewer alleles

compared to drift. However, after 20–40 host generations

the level of polymorphism under coevolution exceeded that

maintained under drift and the excess continued to

increase, such that at generation 100 it was about 70%

higher than under the drift scenario. This was the case for

all post-bottleneck population sizes (Fig. 7), although the

0.001 0.002 0.005 0.010

20

40

60

80

100

Pathogen mutation rate


N = 5000

N = 3000

N = 1000

Fig. 2 The mean number of MHC alleles in host populations of three

different sizes. Error bars indicate standard deviation calculated

across 4,000 generations after allele number stabilized

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deficiency in the number of alleles initially maintained

under coevolution was more pronounced in more severely

bottlenecked populations. The propensity of coevolution

to maintain lower numbers of alleles, compared to drift, in

the initial phase of the bottleneck was the strongest for the

largest pre-bottleneck population size (Fig. 8). The same

pattern was observed when either heterozygote advantage

or frequency-dependence could not operate, although the

trajectories differed between these two forms of balancing

selection (Fig. 9). Interestingly, average host fitness

increased after bottleneck, but than decreased compared to

pre-bottleneck level (Fig. 10).

Although the average similarity between sequences was

usually lower under coevolution, the confidence intervals

calculated from 15 averaged trajectories for each set of

parameters overlapped with those calculated for drift (see

Fig. 11 for examples). We also found no significant dif-

ferences in functional similarity (Fig. 12). Both results

were robust for all tested parameters: mutation rate, size of

the source population and severity of the bottleneck.

In simulations of a short-term bottleneck, the number of

alleles increased under coevolution for all pathogen

mutation rates studied, and decreased under genetic drift

(Fig. 13). As for the prolonged bottleneck, however, there

were no significant differences between coevolution and

drift when divergence, in sequence or functional similarity

1900 1920 1940 1960 1980 20000

1

2

3

4

5

Time [generations]

C V

i n

f i t n e s s

10−2 5⋅10

−32⋅10

−310

−3 Drift 2⋅10−3

Fig. 3 Example trajectories, showing the variation in host fitness

during coevolution and drift in populations of 3,000 individuals

before a bottleneck (numbers in the legend denote pathogen mutation

rates, CV denotes coefficient of variation)

20 40 60 80 1000

10

20

30

40

50

Time [generations after bottleneck]

N u m b e r o f a l l e l s

10−2

5⋅10−3

2⋅10−3

10−3

Fig. 4 Host polymorphism (mean trajectories) under coevolution,

after a bottleneck to 50 individuals at generation 0. The source

population size of hosts was 3,000 individuals for all four trajectories.

The post-bottleneck population size was maintained at 50 individuals

0 10 20 30 40 50 60 70 80 90 1000

2

4

6

8

10

12

14

16

18

20


N u m b e

r o f a l l e l e s

Nbot

= 12

Nbot

= 25

Nbot

= 50

Nbot

= 100

Nbot

= 200

Fig. 5 Host polymorphism under coevolution with a pathogen

mutation rate of 2 9 10-3 (mean trajectories). The source population

of hosts was 3,000 individuals for all five trajectories shown

0.001

0.002

0.005

0.01

−0.6

−0.4

−0.2

0

0.2

T i m e [ g e n e r

a t i o n s a f t e r b o t t l e n e c

k ]

P a t h o g e n m u t a t i o n r a t e

( d r i f t − c o e v o l u t i o n ) / d r i f t 020

4060

10080

Fig. 6 The relative difference in MHC allele number between

coevolution and drift for permanently bottlenecked populations, for

a gradient of pathogen mutation rates. Size of the host source

population was 3,000, and the bottlenecked population size was 50

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was compared between retained alleles (Figs. 14, 15 for

examples).

Discussion

While heterozygote advantage, and especially frequency

dependence resulting from host–parasite interaction have

been shown to be capable of maintaining high level of

MHC polymorphism in large populations (Borghans et al.

2004), their effect on MHC diversity in bottlenecked

population is underexplored. Here, we show that

heterozygote advantage and frequency dependence acting

alone or jointly in bottlenecked populations initially

deplete MHC polymorphism at a faster rate than drift. In

our simulations the initial negative effect of selection on

the level of MHC polymorphism was stronger under

12

25

50

100

200

−0.4

−0.3

−0.2

−0.1

0

0.1

0.2

0.3

Time [genera tions a f ter bo t tle

neck ]

S i z e o f b o t t l e n e c k e d

p o p u l a t i o n

( d r i f t

− c o e v o l u t i o n ) / d r i f t

20

80 60 40100

0

Fig. 7 The relative difference in MHC allele number between

coevolution and drift for permanently bottlenecked populations, for

a gradient of bottleneck severity. Size of the host source population

was 3,000 and the pathogen mutation rate was 2 9 10-3

0 10 20 30 40 50 60 70 80 90 100

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0

0.1

0.2

0.3


( d r i f t − c o e v o l u t i o n ) / d r i f t

N = 5000

N = 3000

N = 1000

Fig. 8 The relative difference in the number of MHC alleles between

coevolution and drift for permanently bottlenecked populations

originating from populations derived under three different sizes.

The bottlenecked population size was 50 individuals and the pathogen

mutation rate was 2 9 10-3

0 10 20 30 40 50 60 70 80 90 100

−0.4

−0.2

0

0.2

0.4

0.6


( d r i f t − s c e n a r i o ) / d r i f t

coevolution Nbot

= 50

drifting pathogenes Nbot

= 50

haploids Nbot

= 50

haploids Nbot

= 100

Fig. 9 The relative difference in the number of MHC alleles between

drift and different forms of balancing selection operating in perma-

nently bottlenecked populations. The pre-bottleneck population was

derived from 3,000 individuals coevolving with pathogens under

pathogen mutation rate equal to 2 9 10-3

. The thick solid line shows

scenario with both forms of balancing selection operating; thin solid

line—heterozygote advantage enabled, frequency dependence dis-

abled; dotted and dashed lines—frequency dependence enabled,

heterozygote advantage disabled, under two post-bottleneck popula-

tion sizes (given in the legend)

0 20 40 60 80 100

0,004

0,008

0,012

0,016

0,02


H o s t f i t n e s s

10−3

10−3

5⋅10−3

5⋅10−3

Fig. 10 The mean host fitness (calculated as the square of the

proportion of recognized pathogens, see ‘‘Methods’’) after the

bottleneck, compared to host fitness prior to bottleneck (straight

lines, calculated as means from 15 independent simulations). Thebottlenecked population size was 50 individuals and the pre-

bottleneck population was derived from 3,000 individuals coevolving

with pathogens under two pathogen mutation rates (given in the

legend)

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frequency-dependence than under heterozygote advantage

(Fig. 9). When there was simultaneous action of hetero-

zygote advantage and frequency dependence, the initial

decline in polymorphism, although smaller than under each

of these two forms of balancing acting separately, was still

pronounced. Our results thus consistently show that, unlike

in large populations, balancing selection acting on parasite

resistance in a small population can deplete MHC variation

faster than expected under drift. While biological signifi-

cance of about 20% initial loss of MHC diversity, com-

pared to drift, may be debated, our results clearly indicate

that we cannot rely on selection to counteract drift from

depleting MHC polymorphism.

Our simulations reveal, however, that whether the fre-

quency of MHC polymorphisms is higher or lower than

expected under drift depends on the timescales considered.

For 20–60 host generations after the bottleneck, depending

8.6

9

9.4

S e q u e n c e

s i m i l a r i t y

8.6

9

9.4

0 10 20 30 40 50 60 70 80 90 100

8.6

9

9.4


Drift Coev. +/− CIDrift

+/− CICoev.

a

b

c

Fig. 11 The mean sequence similarity between MHC molecules

(mean number of identical bits) under drift and coevolution in

bottlenecked populations of 50 individuals originating from source

population of sizes: a N = 1,000; b N = 3,000; c N = 5,000;pathogen mutation rate was 2 9 10-3

50

70

90

110

130

50

70

90

110

0 20 40 60 80 10050

70

90

110


F u n c t i o n a l s i m i l a r i t y


+/− CICoev.

a

b

c

Fig. 12 The mean functional similarity between pairs of MHC

molecules (mean number of unique antigens presented by both

alleles) under drift and coevolution in bottlenecked populations of 50

individuals, originating from source population of size 3,000, under

three different pathogen mutation rates: a 10-3

; b 2 9 10-3

;

c 5 9 10-3

0 200 400 600 800 10000

10

20

30

40

50

60

70



10−2

Coev.

10−2

Drift

5⋅10−3

Coev.

5⋅10−3

Drift

2⋅10−3

Coev.

2⋅10−3

Drift

10−3

Coev.

10−3

Drift

Fig. 13 MHC polymorphism in a population of 3,000 individuals

after a bottleneck of 10 host generations (population size 50

individuals between generation -10 and 0), under drift and

coevolution

8.2

8.7

9.2

8.2

8.7

9.2

0 200 400 600 800 10008.7

8.9

9.1


S e q

u e n c e s i m i l a r i t y


+/− CICoev.

b

c

a

Fig. 14 The mean sequence similarity of MHC molecules (mean

number of identical bits) under drift and coevolution in a population

that has undergone a 10-generation bottleneck followed by an

increase to a size of 3,000, at three different pathogen mutation rates:

a 10-3

; b 2 9 10-3

; c 5 9 10-3

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on simulation parameters (compare Figs. 6–8), MHC

polymorphism was lower under selection than under drift,

the difference being most pronounced around the 10th–

20th host generation after the reduction in population size.

The disadvantageous effect of selection on MHC diversity

was the largest under the most severe bottleneck. Our

results suggest that a common observation of reduced

MHC variation in populations subject to recent population

bottlenecks (e.g. Babik et al. 2005; Hansson and Richard-

son 2005; Bollmer et al. 2007; Mainguy et al. 2007; Rad-

wan et al. 2007; Zhu et al. 2007; Biedrzycka and Radwan2008, but see Aguilar et al. 2004 for an exception) does not

need to imply that selection on MHC variation in these

populations is weak or non-existent. Indeed, our results

suggest a resolution of the apparent discrepancy between

the widespread evidence for historical positive selection

acting on MHC and inability of the same selection to

maintain MHC diversity during population bottlenecks

(reviewed in Radwan et al. 2009). Our simulations indicate

that even under joint action of heterozygote advantage and

negative-frequency dependence, selection in small popu-

lations should not be expected to maintain more MHC

variation than drift.

Incidental bottlenecks can severely reduce MHC poly-

morphism, but as the population size increases, selection

and mutation restores variation to pre-bottleneck levels

(Fig. 13). Recovery of MHC diversity via mutation has

been documented in American moose, a species that

underwent a population bottleneck during the Pleistocene

glaciations (Mikko and Andersson 1995).

The initial higher rate of decline of MHC polymor-

phism, relative to drift, is likely to result from the fact that

while selection still affects allele frequencies in small

populations, frequency-dependence and heterozygote

advantage are becoming less effective in protecting poly-

morphism (Hedrick 1972). The increase in the frequency of

alleles conferring resistance to current parasites in small

populations would facilitate the loss of rare alleles due to

drift. In large populations, these rare alleles would have

been retained, and many of them can be temporarily (undercurrent composition of parasite genotypes) disadvanta-

geous, decreasing average population fitness. Thus, when

such rare disadvantageous alleles are lost due to drift,

population fitness should increase. Indeed, this is what we

observed (Fig. 10). However, as MHC alleles are lost and

parasites keep evolving, average fitness of hosts declines

below the pre-bottleneck level (Fig. 10), as the host

mutation is not effective enough in restoring the most

resistant alleles. This process is likely to make antigen-

binding abilities of alternative alleles more even, prevent-

ing extreme changes in allele frequencies and leaving

balancing selection more time to counteract allele loss dueto drift. This could explain the increased efficiency of

balancing selection in maintaining polymorphism we

observed in the late phase of the bottleneck.

Species whose genetic variation is reduced due to a

population bottleneck sometimes retain alleles which show

high levels of divergence. Hedrick (2003) hypothesized

that balancing selection can preferentially retain highly

divergent alleles if they are also very different functionally.

In the red wolf, only four allelic variants were found, but

their divergence is high. Simulations based on 27 sequen-

ces found in red wolves and in related Mexican wolves and

coyotes have shown that this level of divergence was

unlikely to have arisen by chance (Hedrick et al. 2002).

Our simulation, however, did not confirm the hypothesis

that selection will generally retain highly divergent alleles

in bottlenecked populations. Although the divergence ten-

ded to be higher under selection, in none of parameter sets

was the difference statistically significant. Thus, while

scenarios exemplified by the red wolf are possible, our

simulations suggest that this will not necessarily be the

rule, which may have important conservation genetic

consequences. Reduced MHC variation may increase the

susceptibility of endangered populations to disease: there

may simply be no alleles left which are capable of initi-

ating immune response to emergent diseases (e.g. (O’Brien

and Evermann 1988; Siddle et al. 2007). If highly divergent

alleles are retained, the ability of a population to respond to

pathogens might be substantially improved. Our simula-

tions suggest, however, that we cannot rely on selection

maintaining such functional diversity in endangered

species.

To summarize, our simulation showed that the impact of

selection on MHC diversity in bottlenecked populations

90

130

90

110

130

0 200 400 600 800 100090

110

130


F u n c t i o

n a l s i m i l a r i t y


+/− CICoev.

a

b

c

Fig. 15 The mean functional similarity of MHC molecules (mean

number of unique antigens presented by both alleles) under drift and

coevolution in post-bottlenecked populations of 3,000 individuals at

three different pathogen mutation rates: a 10

-3

; b 29

10

-3

;c 5 9 10-

3

Conserv Genet

123



depends on the timescales involved, but during the initial

stage of the bottleneck, selection should not be expected to

maintain higher levels of polymorphism than drift. On the

contrary, it may speed up its depletion. Furthermore,

selection does not tend to maintain appreciably higher

diversity of MHC alleles, and is thus unlikely to facilitate a

response by endangered populations to assaults form

emergent pathogens. However, if appropriate conservationmeasures are taken fast enough, a quick rebound in popu-

lation size may allow selection to maintain or restore MHC

variation.

Acknowledgements We thank Maciej Danko and Filip Kapustka

for advice, Wiesiek Babik for reading earlier version of the manu-

script, and Referees for their helpful comments.

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MHC Diversity in Bottleneck Ed Populations-A Simulation Model

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