Molecular Ecology (2009)
doi: 10.1111/j.1365-294X.2009.04121.x
Pedigrees and microsatellites among endangered ungulates:
what do they tell us?
Blackwell Publishing Ltd
M A R Í A J O S É R U I Z - L Ó P E Z ,* E D U A R D O R . S . R O L D Á N ,*‡ G E R A R D O E S P E S O † and
M O N T S E R R AT G O M E N D I O *§
*Reproductive Ecology and Biology Group, Museo Nacional de Ciencias Naturales (CSIC), José Gutierrez Abascal 2, 28006-Madrid,
Spain, †Estación Experimental de Zonas Áridas (CSIC), General Segura 1, 04001-Almería, Spain, ‡Department of Veterinary Basic
Sciences, The Royal Veterinary College, London NW1 0TU, UK, §Department of Zoology, University of Cambridge, Downing Street,
Cambridge CB2 3EJ, UK
Abstract
Relationships between pedigree coefficients of inbreeding and molecular metrics are generally weak, suggesting that measures of heterozygosity estimated using microsatellites may
be poor surrogates of genome-wide inbreeding. We compare three endangered species of
gazelles (Gazella) with different degrees of threat in their natural habitats, for which captive
breeding programmes exist. For G. dorcas, the species with the largest founding population,
the highest and most recent number of founding events, the correlation between pedigree
coefficient of inbreeding and molecular metrics was higher than for outbred populations
of mammals, probably because it has both higher mean f and variance. For the two species
with smaller founding populations, conventional assumptions about founders, i.e. outbred
and unrelated, are unrealistic. When realistic assumptions about the founders were made,
clear relationships between pedigree coefficients of inbreeding and molecular metrics were
revealed for G. cuvieri. This population had a small founding population, but it did experience
admixture years later; thus, the relationship between inbreeding and molecular metrics in
G. cuvieri is very similar to the expected values but lower than in G. dorcas. In contrast, no
relationship was found for G. dama mhorr which had a much smaller founding population
than had been previously assumed, which probably had high levels of inbreeding and low
levels of genetic variability, and no admixture. In conclusion, the strength of the association
between pedigree coefficient of inbreeding and molecular metrics among endangered species
depends on the level of inbreeding and genetic variability present in the founding population, its size and its history.
Keywords: endangered species, inbreeding, microsatellite, pedigree
Received 14 May 2008; revision received 14 January 2009; accepted 23 January 2009
Introduction
Inbreeding is a main issue in evolutionary and conservation
biology because of its detrimental effects on fitness and its
consequences upon population viability (Frankham 1995).
Mating between relatives leads to a reduction in individual
fitness known as inbreeding depression, which is thought
to be the consequence of the increased homozygosity through
identity by descent at all loci across the genome (Wright
1921; Charlesworth & Charlesworth 1987; Thornhill 1993;
Correspondence: M. Gomendio, Fax: +34-91-5645078, E-mail:
[email protected]
© 2009 Blackwell Publishing Ltd
Ballou et al. 1995). Inbreeding depression could be the result
of two different mechanisms. First, inbreeding can lead to
the expression of recessive deleterious alleles when homozygosity increases (dominance hypothesis). Alternatively,
heterozygotes may be fitter than either homozygote (overdominance hypothesis). Expression of deleterious recessive
alleles is thought to be the main cause of inbreeding depression (Charlesworth & Charlesworth 1999).
The traditional way of analysing inbreeding depression
has been to use the inbreeding coefficient f (Wright 1922).
This represents the expected homozygosity across the whole
genome of an individual, and is defined as the probability
that two alleles sampled at random at a locus are identical
2 M. J. RUIZ-LÓPEZ ET AL.
by descent (Falconer & Mackay 1996). When genealogies
are known, f can be calculated for each individual in the
population, and analysed in relation to fitness components
(Ralls et al. 1979, 1980, 1988; Crnokrak & Roff 1999; Kalinowski
et al. 2000; Marshall & Spalton 2000; Keller & Waller 2002).
However, imperfect pedigree information may lead to miscalculations of the inbreeding coefficient (Marshall et al.
2002; Markert et al. 2004; Pemberton 2004, 2008). A common
problem both in captive and wild populations is that the
assignment of paternity on the basis of behavioural observations (copulations) may lead to mistakes when females
mate promiscuously; extra-pair copulations are more difficult to detect because they tend to be less conspicuous, leading to errors when constructing pedigrees unless paternity
is determined by molecular methods (O’Connor et al. 2006).
Incomplete information may also make the pedigree inaccurate because unknown individuals are assumed to be
unrelated (Marshall et al. 2002). These imprecisions in the
construction of pedigrees have been recognized, but little
attention has been paid to the fact that pedigree analyses
commonly assume that individuals in the founding population are non-inbred and unrelated. While this assumption
may not be unrealistic in large outbred populations, it is
certainly almost never the case among endangered species
which suffer from small population sizes and lack of gene
flow. Furthermore, when captive breeding programmes are
established for critically endangered species which have
experienced marked population declines, the founding population will necessarily be small, and the founding individuals are likely to be related, inbred, or both. Under such
conditions, calculating inbreeding coefficients under the
assumption that the founders are outbred and unrelated may
lead to considerable biases. In addition, if new individuals
are incorporated into the breeding programmes later on,
whether they are related or not to the first founders, whether
they have the same geographical origin, and the timing of
their arrival, may have profound implications for the way
the coefficient of inbreeding should be calculated and its
relationship with molecular metrics.
Constructing pedigrees requires detailed information
which is not always available, and in these cases inbreeding
coefficients cannot be calculated. An alternative approach
has been developed to test for inbreeding depression indirectly. If inbreeding causes heterozygosity depletion, then
measuring heterozygosity levels with molecular markers,
may provide a good indication of inbreeding levels. Currently, microsatellites are frequently the markers of choice
to estimate heterozygosity and different measures have been
developed. These include: multilocus heterozygosity (MLH)
and standardized heterozygosity (sMLH) (Coltman et al.
1999), internal relatedness (IR) (Amos et al. 2001), and heterozygosity by locus (HL) (Aparicio et al. 2006), mean d2 (Coulson et al. 1998) and standardized mean d2 (Coltman et al. 1999).
However, the validity of mean d2 has been recently
questioned (Hedrick et al. 2001; Tsitrone et al. 2001; Balloux
et al. 2004) and will therefore not be included in this study.
Correlations between the different molecular metrics and
individual fitness components have been widely reported
in the literature including: survival (Coltman et al. 1998;
Coulson et al. 1999), fecundity (Amos et al. 2001), disease
resistance (Coltman et al. 1999; Acevedo-Whitehouse et al.
2003), and lifetime reproductive success (Slate et al. 2000).
Most of the populations in which heterozygosity-fitness
correlations have been studied are large natural populations in which most individuals are outbred and levels of
genetic variability are high. Inbreeding has been usually
proposed as the mechanism underlying the association
between individual heterozygosity and fitness. However,
recent work has questioned this idea because the reported
correlations between pedigree inbreeding coefficients and
molecular metrics are often weak (Slate et al. 2004). Alternative explanations for the association between measures
of heterozygosity and fitness have been proposed such as
associative overdominance through linkage disequilibrium
between the markers and fitness genes (local effect) (David
1998; Hansson et al. 2004).
The main question is whether heterozygosity measured
over a small group of molecular markers does indeed reflect
genome-wide inbreeding (Balloux et al. 2004; Pemberton
2004; Slate et al. 2004). So far, few studies have directly analysed the correlation between pedigree inbreeding coefficient
and different measures of heterozygosity, and the populations studied are very different, including domestic species
under artificial selection (Slate et al. 2004), natural populations (Markert et al. 2004; Overall et al. 2005; Jensen et al. 2007),
and endangered species (Hedrick et al. 2001; Bensch et al.
2006). The available evidence shows that the association
between pedigree inbreeding coefficients and molecular metrics at the individual level is weak among some natural
populations (Markert et al. 2004; Slate et al. 2004; Overall et al.
2005; Jensen et al. 2007), although studies on endangered
species have found strong correlations (Hedrick et al. 2001).
The extent of the association between inbreeding and heterozygosity seems to depend strongly on the degree of inbreeding and on its variance, so that weak relationships tend to
be found in populations with low levels of inbreeding and
low variance (Balloux et al. 2004; Pemberton 2004; Slate et al.
2004). Using stochastic, individual-based simulations, Balloux
et al. (2004), showed that the range under which inbreeding
and heterozygosity are linked is narrow, and requires
strong population subdivision, small population sizes or
extreme mating systems (polygyny or selfing). The strength
of the associations may also vary depending on the molecular metric employed (Hedrick et al. 2001; Balloux et al. 2004).
To understand under which circumstances is the pedigree
inbreeding coefficient associated with molecular metrics, it
is necessary to measure both using the same methodology
(including the same panel of markers) in populations from
© 2009 Blackwell Publishing Ltd
INBREEDING AND HETEROZYGOSITY IN GAZELLES 3
species with different histories. In this study, we examine
the relationship between coefficient of inbreeding and different marker-based metrics, in captive populations of three
endangered ungulates with founding populations of different sizes and histories. In addition, we explore how such
relationship varies when assumptions about the founders
are modified to make them more realistic.
The three species included in our study, Gazella cuvieri,
Gazella dama mhorr and Gazella dorcas neglecta, are part of
captive breeding programmes at the Parque de Rescate de
Fauna Sahariana (CSIC-Spain) and detailed information on
genealogies is available in published studbooks. These three
populations had different founding histories, with different
founding sizes (4 individuals in G. cuvieri, 11 individuals in
G. dama mhorr and 20 individuals in G. dorcas neglecta), different timing of founding events, and different degrees of
admixture due to the geographical origin of the founders.
Since the captive breeding programmes were established,
the populations of all three species have grown markedly.
In 2005 the number of individuals born from the founding
populations was 1120 for G. cuvieri, 1460 individuals for G.
dama mhorr, and 1200 individuals for G. dorcas neglecta. This
rapid population growth has allowed the transfer of animals
to different institutions around the world making the population at the Parque de Rescate de la Fauna Sahariana (CSIC)
the main captive stock for these species. Currently, the size
of the captive population at the Parque de Rescate de Fauna
Sahariana for each of the three species is approximately 100
individuals. In the captive breeding programmes there are
three types of social groups: (i) breeding groups, (ii) all-male
groups and (iii) solitary males. The first type of group consists of a single mature male and several females. Because
there is only one reproductively mature male with each group
of females, paternity assignment is likely to be accurate.
Inbreeding depression has been reported in these populations (Roldan et al. 1998; Gomendio et al. 2000; Cassinello
et al. 2001).
Materials and methods
Study populations
This study was carried out in three species of endangered
gazelles, Gazella cuvieri (Ogilby, 1841), Gazella dorcas neglecta
(Lavauden, 1926) and Gazella dama mhorr (Bennett, 1833), for
which captive breeding programmes have been established
at the Parque de Rescate de Fauna Sahariana (CSIC-Spain).
The pedigree information was obtained from the international studbooks of the species (Barbosa & Espeso 2005;
T. Abaigar, personal communication; Espeso & Moreno 2006).
The size of the founding populations differed [number of
individuals (male:female)]: four (1:3) in G. cuvieri, eleven (2:9)
in G. dama mhorr and 20 (6:14) in G. dorcas neglecta. Details
of the founding populations are shown in Table 1.
© 2009 Blackwell Publishing Ltd
Microsatellite analyses
A total of 284 blood and muscle samples from the gazelles
were obtained at the Parque de Rescate de Fauna Sahariana,
including 91 different individuals of G. cuvieri, 112 G. dama
mhorr and 89 of G. dorcas neglecta all accurately identified.
Animals sampled for G. cuvieri were born between 1988
and 2004, for G. dama mhorr between 1987 and 2006, and for
G. dorcas neglecta between 1982 and 2003. Blood samples were
taken during routine veterinary procedures and collected
in a 5-mL EDTA tubes and preserved frozen at –80 °C. Tissue
samples were obtained during necropsies, placed in 96%
ethanol and shipped refrigerated.
DNA extractions were performed either using phenolchloroform (Sambrook et al. 1989) or QIAGEN blood and
tissue kit (QIAGEN) to avoid haemo group contamination.
Samples were typed using a panel of microsatellites that had
already been successfully used in several ungulate species
(red deer: Coulson et al. 1998; Slate & Pemberton 2002; roe
deer: Galan et al. 2003; dorcas gazelle and barbarian sheep:
Beja-Pereira et al. 2004) and proved to be adequate for the
species under study (M.J. Ruiz-Lopez, M. Gomendio, G.
Espeso and E.R.S. Roldan, unpublished). Microsatellites
were chosen to be evenly distributed across the genome of
each species. The panel consisted of 16 polymorphic microsatellite loci in G. cuvieri and G. dorcas neglecta and 17 loci in
G. dama mhorr. Loci used were the following: BM302, BM415,
BM4505, BMC1009, CELJP15, CSSM41, CSSM43, HUJ1177,
INRA005, MAF70, OARFCB193, OARFCB304 (typed in the
three species), BM848 and INRA040 (typed in G. cuvieri and
G. dorcas neglecta), MAF109 and TGLA94 (typed in G. cuvieri
and G. dama mhorr), IDVGA29 (typed in G. dama mhorr and
G. dorcas neglecta), BM1706 and MAF35 (typed in G. dama
mhorr), and CSSM39 (typed in G. dorcas neglecta). Microsatellites were amplified by fluorescent genotyping on an ABI
PRISM 3700 (Applied Biosystems). Alleles were scored using
GeneMapper 3.1 (ABI 3700, Applied Biosystems), and when
uncertain genotypes appeared (unclear or low peaks) those
were repeated. Additionally, 10% of all the samples were
also repeated to estimate the error rate. The percentage of
coincident genotypes was higher than 95%; therefore we
considered our results to be highly consistent.
Genetic variability
Population level analyses. These genotypes were tested for
deviations from Hardy–Weinberg equilibrium (HWE) and
mean number of alleles, and mean expected and observed
heterozygosity were calculated for each species with the
program Arlequin 3.1 (Excoffier et al. 2005). Some loci showed
significant deviations from HWE that may be related to
both the overlapping of generations and the strong founder
event and subsequent inbreeding. Future analyses were
performed both including the microsatellites that deviated
4 M. J. RUIZ-LÓPEZ ET AL.
Table 1 Founding events in the captive breeding programmes of the three Gazella species, G. cuvieri, G. dama mhorr, and G. dorcas neglecta,
at the Parque de Rescate de Fauna Sahariana
Founding events
N
Year
Origin
Group
Nind.
G. cuvieri
1975
1975
1981
Algeria
Algeria
Morocco
Gcuv1
—
Gcuv2
G. dama mhorr
1970
1970
1975
Western Sahara
Western Sahara
Western Sahara
Gdam1A
Gdam2
Gdam1B
7 (1:6)
2 (0:2)
10 (4:6)
G. dorcas neglecta
1970
1971
1973
1975
1993
1994
Western Sahara
Western Sahara
Western Sahara
Western Sahara
Captive population (Fuerteventura)
Captive population (Duyos)
Gdor1
Gdor2
Gdor3
Gdor4
Gdor5
Gdor6
2 (1:1)
17 (6:11)
1 (1:0)
54 (29:25)
6 (2:4)
2 (1:1)
3 (1:2)
1 (1:0)
1 (0:1)
3 (1:2)
0
1 (0:1)
4 (1:3)
6 (1:5)
1 (0:1)
4 (1:3)
11 (2:9)
0
1 (0:1)
0
13 (4:9)
4 (1:3)
2 (1:1)
20 (6:14)
Ne
3
6.55
16.8
Year is the year of entry to the population according to the studbook information; Origin is the geographical origin of the group according
to the studbook information; Group is the label given in this study to each founding event; Nind. is the number of individuals that entered
the population each time showing the total number and in parentheses the sex ratio (males:females); N is the number of founders for each
event, i.e. animals with descendants up to the present day, including the total and the sex ratio (males:females), the numbers in bold are the
total number of founders; Ne is the effective number of founders calculated following the formula Ne = (4 * Nm * Nh)/Nm + Nh (Falconer
& Mackay 1996).
from Hardy–Weinberg equilibrium and excluding them.
These results were very similar, and the correlations between
the different genetic variability measures were highly significant. Therefore, we decided to include here the results
obtained using all loci (16 in both G. cuvieri and G. dorcas
neglecta and 17 in G. dama mhorr).
Individual molecular metrics. The following multilocus molecular metrics were calculated for each individual:
1 Individual heterozygosity (MLH): proportion of genotyped
loci that are heterozygotes for an individual (Mitton 1993;
Coulson et al. 1998; Coltman et al. 1999).
2 Standardized individual heterozygosity (sMLH): proportion
of loci genotyped that are heterozygotes for an individual,
divided by the average heterozygosity of the genotyped
loci (Coltman et al. 1999). This metric controls for different
loci having different expected heterozygosities.
3 Internal relatedness (IR): IR = (2H – ∑ fi)/(2N – ∑ fi), where H
is the number of loci that are homozygous, N is the number
of loci and fi is the frequency of the ith allele contained in
the genotype (Amos et al. 2001). In this measure, the frequency of each allele counts towards the final score,
allowing the sharing of rare alleles to be weighted more
than the sharing of common alleles.
4 Homozygosity by loci (HL): HL = ∑ Eh/(∑ Eh + ∑ Ej), where
Eh and Ej are the expected heterozygosities of the loci that
an individual carries in homozygosis (h) and heterozygosis
(j), and the expected heterozygosities are E = 1 – ∑ fi2
being fi the frequency of the ith allele in the population
(Aparicio et al. 2006). The weight given to each locus is
proportional to the expected heterozygosity, and therefore
makes a locus more important in HL index when their alleles
are more frequent, and there are more alleles in the locus.
All these variables were calculated for each individual
as described, using the Excel Macro ‘IRmacroN4’
(www.zoo.cam.ac.uk/zoostaff/amos).
All molecular metrics were highly correlated in the three
species (r > 0.95 in all cases). In this study, we will use sMLH
and IR because they are the most frequently used so this will
facilitate comparison with other studies, and HL which is a
recent measure which has never been tested in this context.
Pedigree analyses
Inbreeding coefficients were calculated from the pedigrees
constructed using studbook information following Stevens–
Boyce algorithm (Boyce 1983) implemented in PEDSYS
software (Southwest Foundation for Biomedical Research,
San Antonio, Texas). The pedigree analyses performed consider a starting population, the founders, to be outbred and
unrelated, and all subsequent calculations of genetic relatedness trace common ancestries back to this founder stock
© 2009 Blackwell Publishing Ltd
INBREEDING AND HETEROZYGOSITY IN GAZELLES 5
(Lacy et al. 1995). Individuals with unknown parentage are
also treated as founders in these kinds of analyses, which can
lead to underestimation of inbreeding coefficients. However,
our studbook information is complete and in recent generations, there are no gaps in parentage assignment. For each
species, mean f and its variance were also calculated.
In those cases in which two or more loci genotyped did
not match those of one or both parents, we could not rule
out that there had been an error in assigning parentage,
and these individuals were excluded from the analyses. In
the three species, the animals excluded from the analyses
are both real and inferred errors. Inferred errors are those
in which parent and offspring genotypes do not match but
in which the parents of the typed individuals have not been
directly genotyped but its genotype inferred from other
animals. We used a conservative approach and excluded
these animals from future analyses. This increased the
number of excluded animals in G. dorcas greatly, where
most of the errors were inferred errors due to three males
(accounting for 12 of the 22 mismatches). The final percentage of animals excluded were G. cuvieri: 10 (10%), G. dama
mhorr: 3 (2.67%), G. dorcas neglecta: 22 (24.7%).
For the two species with the smallest founding populations (G. cuvieri and G. dama mhorr), the coefficient of inbreeding was also recalculated, changing the assumptions about
the founders. At the beginning of the captive breeding programme, these two species had already suffered marked
declines, and in the case of G. dama mhorr, historical evidence
suggests that founders of this population were probably
related (Valverde 2004). Thus, the assumption that the founders were outbred and unrelated seems unlikely. To perform
the recalculations, fake ancestors of the founders were added
to the studbook information to construct new pedigrees. The
basic scenarios reconstructed assumed different degrees of
relatedness among founders (unrelated, all related or related
according to the date of entrance in the population and geographical origin) and different levels of inbreeding (none,
moderate or high).
Statistical analyses
It has been proposed that the main drivers of the relationship
between heterozygosity and f are the variance of f and the
number and heterozygosity of loci. To relate these parameters
Slate et al. (2004), proposed a model to calculate the expected
correlation among inbreeding coefficient and heterozygosity
based on the mean and variance of both measures, assuming
that all loci have the same expected heterozygosity in the
absence of inbreeding, all are equally affected by inbreeding
and are unlinked. The formula employed is: r(H, f) = –σ(f)/
[(1 – E(f))(σ(H))]. Where σ(f) is the standard deviation of the
inbreeding coefficient (f), E(f) is the mean of the inbreeding
coefficient and σ(H) is the standard deviation of the standardized heterozygosity (sMLH) following Slate et al. (2004).
© 2009 Blackwell Publishing Ltd
For the three species under study, we calculated mean and
variance of f and sMLH and the expected correlations among
inbreeding coefficient and standardized heterozygosity.
In order to test the relationship between the inbreeding
coefficients and the three molecular metrics, we performed
Pearson correlations generating our own distribution table
by means of Monte-Carlo simulations (Gotelli & Ellison 2004).
We used Matlab 7.0 software to simulate 1000 times the
relationship between the two variables. With these values,
we calculated 1000 times the correlation coefficient and
ordered the values to create a new distribution of the test
statistic that would be expected under the null hypothesis.
Then, the correlation coefficient performed with the real data
was compared to the distribution of the simulated values
and the P value was estimated as a tail probability, i.e the
unbiased probability value obtained was the one corresponding to the location of the correlation coefficient in the distribution. Any other correlation in the study (among molecular
metrics or among different inbreeding coefficients) was performed using Monte-Carlo simulations.
Results
Inbreeding coefficients and levels of genetic variability
Mean f was different in the three Gazella species, being higher
in G. cuvieri, intermediate in G. dama mhorr, and lower in G.
dorcas neglecta (Table 2). Thus, as the size of the founding
populations decreased, mean f seemed to increase. In contrast, genetic variability seemed unrelated to the size of the
founding population for each species. Expected heterozygosities (HE) were lowest for G. dama mhorr, intermediate in
G. cuvieri, and highest in G. dorcas neglecta (HE = 0.552 in
G. cuvieri, HE = 0.476 in G. dama mhorr and HE = 0.718 in G. dorcas
neglecta). Finally, mean number of alleles was different in the
three species being lowest for G. dama mhorr, slightly higher
for G. cuvieri, and much higher for G. dorcas neglecta (3.94 in
G. cuvieri, 3.30 in G. dama mhorr and 8 in G. dorcas neglecta).
Relationship between molecular metrics and inbreeding
coefficient
When testing the relationship between pedigree inbreeding
coefficient and molecular metrics, there was no significant
Table 2 Mean and variance of the pedigree coefficient of inbreeding
(f), and heterozygosity (HE) for the three Gazella species: G. cuvieri,
G. dama mhorr and G. dorcas neglecta
G. cuvieri
G. dama
G. dorcas
Mean f
Variance (f)
Mean (HE)
Variance (HE)
0.178275
0.100502
0.052614
0.001050
0.001116
0.003593
0.551726
0.476350
0.718096
0.013035
0.012087
0.011552
6 M. J. RUIZ-LÓPEZ ET AL.
Table 3 Correlation coefficients (r) between the pedigree coefficients of inbreeding (f) and three molecular metrics for the three
Gazella species under study (G. cuvieri, G. dama mhorr, and G. dorcas
neglecta)
G. cuvieri (f)
r
sMLH –0.2320
IR
0.2214
HL
0.1831
G.dama (f)
G.dorcas (f)
P value r
P value r
P value
< 0.05
n.s.
n.s.
n.s.
n.s.
n.s.
< 0.001
< 0.001
< 0.001
–0.1484
0.1237
0.1267
–0.5024
0.4951
0.5207
P values are shown as n.s. (nonsignificant), P < 0.05, P < 0.01,
P < 0.001.
relationship between them for G. dama mhorr (Table 3).
In the case of G. cuvieri, sMLH was the only metric that
was significantly correlated with pedigree inbreeding
coefficient, but the relationship was weak (Table 3). In
contrast, in G. dorcas neglecta every molecular metric was
strongly correlated with pedigree inbreeding coefficient
(Table 3 and Fig. 1).
Simulations of different scenarios for the founding
populations
To analyse how the initial assumptions about the founders
may have affected our estimates of pedigree coefficient of
inbreeding for the species with the smallest founding populations, we recreated different scenarios for G. cuvieri and
G. dama mhorr. We did not carry out any recalculation for G.
dorcas because the size of the founding population was larger,
the degree of threat among natural populations was lower
at the time the captive breeding programme started, and
new individuals have entered the population at different
times and from different origins, and thus, the assumptions
of non-inbreeding and non-relatedness are likely to be more
realistic. Recalculations were performed adding fake ancestors to the founders, and re-analysing the inbreeding coefficients using the new pedigrees.
Different scenarios were recreated for G. cuvieri assuming
different degrees of relatedness and inbreeding for the founders and the results are shown in Table 4 and Fig. 2. In this
population, there were two founding events of different geographical origin, which were separated by a period of 6 years,
and thus, they were considered as distinct groups (Gcuv1
and Gcuv2) (Table 1). The first scenario (F0) assumed that
founders were not inbred and unrelated following common
practice when calculating coefficient of inbreeding from
pedigrees. As already stated, in this scenario coefficient of
inbreeding was significantly correlated only with sMLH
(Table 4B). When different scenarios of inbreeding and relatedness were recreated, we found that coefficient of inbreed-
Fig. 1 Relationships between pedigree coefficient of inbreeding
and three molecular metrics in G. dorcas neglecta: (A) Standardized
Individual Heterozygosity (sMLH), (B) Internal Relatedness (IR),
and (C) Homozygosity by Loci (HL).
ing and all the molecular metrics were associated whenever
it was assumed that individuals within each founding group
were related, but were unrelated between the two founding
groups, independently of the inbreeding coefficient assigned
to founders (F1, F3, F5). In all those cases, estimated levels
of inbreeding increased and so did the variance of f (which
in some cases doubled, e.g. F1), therefore improving the
relationship between f and molecular metrics which became
© 2009 Blackwell Publishing Ltd
INBREEDING AND HETEROZYGOSITY IN GAZELLES 7
Table 4 Recreated scenarios for Gazella cuvieri assuming different degrees of relatedness and inbreeding among founders
(A) Mean pedigree coefficient of inbreeding and variance in the recreated scenarios
Founder population
Present population
Scenarios
Relatedness
f
Mean f
Variance (f)
F0
F1
F2
F3
F4
F5
F6
unrelated
Gcuv1/Gcuv2
Gcuv1 + Gcuv2
Gcuv1/Gcuv2
Gcuv1 + Gcuv2
Gcuv1/Gcuv2
Gcuv1 + Gcuv2
0
0.25
0.25
0.125
0.125
0
0
0.178275
0.375230
0.472523
0.333412
0.414216
0.291594
0.355909
0.001050
0.002027
0.000380
0.001711
0.000449
0.001450
0.000525
In the founder population, three levels of relatedness were considered: unrelated (all individuals were unrelated); Gcuv1/Gcuv2 (the
animals of the two founder groups were related within each group but not between groups); Gcuv1 + Gcuv2 (all the founders were related).
Levels of inbreeding (f) considered were three: f = 0; f = 0.125 (cross of paternal half-brother–paternal half-sister); f = 0.25 (cross of full
brother–full sister).
(B) Correlation coefficients (r) between the pedigree coefficients of inbreeding (f) and the six molecular metrics for the recreated scenarios
F0
sMLH
IR
HL
F1
F2
F3
F4
r
P value
r
P value
r
P value
r
P value
–0.232
0.221
0.183
< 0.05
n.s.
n.s.
–0.309
0.286
0.242
< 0.05
< 0.05
< 0.05
–0.215
0.208
0.172
n.s.
n.s.
n.s.
–0.302
0.281
0.237
< 0.05
< 0.05
< 0.05
F5
P value
–0.208
0.203
0.167
n.s.
n.s.
n.s.
F6
P value
–0.290
0.272
0.228
< 0.01
< 0.05
< 0.05
P value
–0.202 n.s.
0.198 n.s.
0.162 n.s.
P values are shown as n.s (nonsignificant), P < 0.05, P < 0.01, P < 0.001.
significant in all cases. Those scenarios where it was assumed
that the animals in the two founding groups were related
(F2, F4, F6) resulted in higher levels of inbreeding but a
reduced inbreeding variance, and no relationship between
pedigree coefficient of inbreeding and molecular metrics was
detected. It seems, therefore, that the factor that is affecting
the most the relationship between inbreeding coefficients and
levels of genetic variability is the assumption of relatedness
within and between the two founding groups through its
strong effect upon f variance.
Different scenarios were recreated for G. dama mhorr following the same logic than in G. cuvieri, and in this case,
historical records provided detailed information about the
founding events (Valverde 2004). Seven scenarios were considered for this species (see Table 5). According to Valverde
(2004), the founding groups of G. dama mhorr in Almería
originated mainly from a captive group kept by the Spanish
Army facilities in Daora (Morocco), that was brought to Spain
sub-divided in two groups which arrived in different years
(Gdam1A and Gdam1B in Table 1). The fact that the military kept captive groups of this species is not surprising since
it was almost extinct in the wild at the time and they were
aware that it was a rare and precious species. Thus, these
two groups are considered as one founding group although
they arrived at different times. The second founding group
© 2009 Blackwell Publishing Ltd
consisted of two females of unknown origin (Gdam2). Thus,
we recreated scenarios in which individuals in Gdam1A and
Gdam1B are always related, but the relatedness with the
second founding group varies as does the level of inbreeding of founders. In the founder population, seven possible
scenarios were considered. F0 is the conventional scenario
considered in the studbook and assumes no relatedness
among founders and no inbreeding and, as already shown,
pedigree inbreeding coefficient calculated this way and
molecular metrics were not associated. The other six scenarios considered three possible levels of inbreeding [f = 0;
f = 0.25 (cross of full brother-full sister); f = 0.125 (cross of
paternal half-brother-paternal half sister)] and two possible
relationships among the founders: (i) Gdam1A and Gdam1B
were related among them but not with Gdam2, and
(ii) Gdam1A and Gdam1B were both related with Gdam2. No
correlation was found between inbreeding coefficient and
any molecular metric in any of the scenarios considered
(see Table 5B).
Expected and observed correlations between pedigree
coefficient of inbreeding and standardized heterozygosity
Following formula 4 in Slate et al. (2004), we estimated the
expected correlation among inbreeding coefficient and
8 M. J. RUIZ-LÓPEZ ET AL.
G. dama mhorr the expected and observed correlations between
f and sMLH are much lower, although both values are very
similar which means that no strong relationship between
inbreeding and genetic variability should be expected for
G. dama mhorr.
Discussion
Fig. 2 Relationships between pedigree coefficient of inbreeding and
standardized individual heterozygosity (sMLH) under two different
scenarios in G. cuvieri. (A) F0: founders assumed to be non-inbred
and unrelated. (B) F1: Founders assumed to be highly inbred (f = 0.25)
and individuals from the two founding groups assumed to be related
within each group but unrelated between groups.
standardized individual heterozygosity (sMLH). Given the
mean and variance of these two parameters in the three
species, we found that the expected correlation was different
for each species (see Table 6). The f variance in G. dorcas
neglecta was almost three times that of G. cuvieri and G. dama
mhorr when inbreeding was calculated the conventional
way in all three species, and thus, in G. dorcas neglecta a higher
correlation between sMLH and f would be expected. This
expectation fits well with the observed correlation values
found G. dorcas neglecta which were high and in fact exceeded
the expected values. Thus, in G. dorcas neglecta, the observed
correlation between f and sMLH is much higher than in the
other two species (when the conventional coefficients of
inbreeding are calculated). In the case of G. cuvieri in the
recreated scenarios considered more realistic, the correlation between f and sMLH increases considerably, and the
match between expected and observed correlations is very
close (in the F3 scenario, the values are identical). Finally, in
Our findings show that the relationship between pedigree
coefficient of inbreeding and molecular metrics is stronger
among endangered species with high levels of inbreeding
and high variance than among large outbred populations.
However, the strength of the association differs depending
on the history of the founding populations (size, number and
timing of founding events, and geographical origin of the
founders) and the degree of genetic depletion suffered before
the captive breeding started. Assumptions about founders
have a profound influence on coefficients of inbreeding,
particularly when founding populations are small. The conventional assumptions made when calculating coefficients
of inbreeding from pedigrees, i.e. that the founders are unrelated and non-inbred, are unrealistic for endangered species.
We show that when we adjust assumptions about founders
to the information available about the founding population,
the relationship between pedigree coefficient of inbreeding
and molecular metrics improved in those scenarios likely
to be more realistic. In addition, the occurrence of admixture
between populations and the degree of genetic variability
present in the founding populations, also affect the relationship between coefficient of inbreeding and molecular
metrics, through its effect on variance of both inbreeding
and heterozygosity.
The captive breeding programme for G. dorcas neglecta
started with the largest founding population of the three
species studied, and incorporated new animals several times
until recently. In addition, this species had not suffered a
marked decline in its natural habitat at the time the captive
breeding programme started. As a consequence, in this species levels of inbreeding are comparatively low, and levels
of genetic variability are high since both its expected heterozygosity and mean number of alleles are similar to those
found among nonbottlenecked populations (Bradshaw et al.
2007). For this population, there was a clear association
between pedigree coefficient of inbreeding calculated in
the conventional way and all the molecular metrics used.
The highest correlation found was between HL and coefficient of inbreeding, probably because this measure is
particularly well suited to cases in which rare alleles are carried
by immigrants (Aparicio et al. 2006), and in the dorcas population, there have been multiple founding events with different geographical origins which have probably introduced
new alleles to the original gene pool. Furthermore, the correlation between sMLH and f was higher than that estimated
following Slate et al. (2004) probably due to high levels of
© 2009 Blackwell Publishing Ltd
INBREEDING AND HETEROZYGOSITY IN GAZELLES 9
Table 5 Recreated scenarios for Gazella dama mhorr assuming different degrees of relatedness and inbreeding among founders
(A) Mean pedigree coefficient of inbreeding and variance in the recreated scenarios
Founder population
Present population
Scenarios
Relatedness
f
Mean f
Variance (f)
F0
F1
F2
F3
F4
F5
F6
Unrelated
Gdam1A + Gdam1B/Gdam2
Gdam1A + Gdam1B + Gdam2
Gdam1A + Gdam1B/Gdam2
Gdam1A + Gdam1B + Gdam2
Gdam1A + Gdam1B/Gdam2
Gdam1A + Gdam1B + Gdam2
0
0.25
0.25
0.125
0.125
0
0
0.100502
0.347532
0.432272
0.302811
0.373427
0.258089
0.314582
0.001116
0.000813
0.000412
0.000769
0.000498
0.000759
0.000593
In the founder population, three levels of relatedness were considered: unrelated (all individuals were unrelated); Gdam1A + Gdam1B/
Gdam2 (Gdam1A and Gdam1B were related within them and among them but not related with Gdam2); Gdam1A + Gdam1B/Gdam2 (all
the founders were related). Levels of inbreeding (f) considered were three: f = 0; f = 0.125 (cross of paternal half-brother–paternal half-sister);
f = 0.25 (cross of full brother–full sister).
(B) Correlation coefficients (r) between the pedigree coefficients of inbreeding (f) and the six molecular metrics for the recreated scenarios
F0
sMLH
IR
HL
F1
F2
F3
F4
F5
F6
r
P value
r
P value
r
P value
r
P value
r
P value
r
P value
r
P value
–0.148
0.124
0.127
n.s.
n.s.
n.s.
–0.101
0.081
0.110
n.s.
n.s.
n.s.
–0.163
0.132
0.141
n.s.
n.s.
n.s.
–0.119
0.094
0.121
n.s.
n.s.
n.s.
–0.163
0.131
0.140
n.s.
n.s.
n.s.
–0.134
0.106
0.130
n.s.
n.s.
n.s.
–0.163 n.s.
0.131 n.s.
0.139 n.s.
P values are shown as n.s. (nonsignificant), P < 0.05, P < 0.01, P < 0.001.
Table 6 Observed and expected correlation coefficients between coefficient of inbreeding (f) and H (H is calculated using sMLH following
Slate et al. 2004) for Gazella cuvieri (F0 and recreated scenarios with the most significant correlations, F1 and F3), G. dama mhorr and G. dorcas
neglecta
G. cuvieri
G. dama
G. dorcas
F0
F1
F3
F0
Mean f
Variance
(f)
Mean
MLH
Mean
sMLH
Variance
(sMLH)
Expected
r(H,f)
Observed
r(H,f)
0.1783
0.3752
0.4725
0.1005
0.0526
0.0010
0.0020
0.0017
0.0011
0.0036
0.5517
0.5517
0.5517
0.4764
0.7181
1.0037
1.0037
1.0037
1.0042
0.9954
0.0421
0.0421
0.0421
0.0540
0.0221
–0. 1922
–0.3512
–0.3025
–0.1598
–0.4259
–0.2320
–0.3090
–0.3020
–0.1484
–0.5024
admixture. The arrival of founders from different geographical origins is likely to have led to drastic changes in both f
(decrease) and heterozygosity (increase). The extent of these
associated changes in both variables may not be captured
entirely when expected values are calculated. We did not
recreate other scenarios for this species since the assumption
that founders were outbred and nonrelated seems realistic.
Thus, in this population the association between pedigree
coefficient of inbreeding and molecular metrics is stronger
than that found among natural outbred populations of mammals, probably because it has higher mean f and higher varia© 2009 Blackwell Publishing Ltd
nce (Soay sheep: Overall et al. 2005, bighorn sheep: Coltman
in Slate et al. 2004). In fact, our population of G. dorcas has
similar mean f to the domestic sheep studied by Slate et al.
(2004) but higher variance in f, and this may be the reason
why the correlation between pedigree coefficient of inbreeding and molecular metrics is much higher in G. dorcas. The
reason why G. dorcas has higher variance in f may be related
to the fact that different founding events have occurred since
1970 until recently, generating a wide scatter of inbreeding
coefficients which result in a good match between inbreeding
and genetic variability. There is only one population of
10 M . J . R U I Z - L Ó P E Z E T A L .
mammals in which a higher correlation has been found
between pedigree coefficient of inbreeding and molecular
metrics: the population of captive wolves studied by Hedrick
et al. (2001) which had both higher average f and higher
variance in f than our population of G. dorcas. In this case, the
founders in the breeding programme also had different
geographical origins, and therefore, the situation would be
similar to the one in G. dorcas. Thus, the correlation between
pedigree coefficient of inbreeding and molecular metrics is
higher when mean f and its variance are higher, which is more
likely to be the case among endangered species than among
large outbred populations.
In the case of G. cuvieri, the founding population was
extremely small, and consisted of two groups which arrived
6 years apart and from different geographical origins (different countries in fact). As a result, levels of inbreeding in
the captive population are the highest of the three species
studied and levels of genetic variability are low. Compared
with other vertebrate populations studied, its inbreeding
coefficient is one of the highest ever reported (Slate et al. 2004;
Bensch et al. 2006), but its genetic variability is one of the
highest found for bottlenecked populations (Bradshaw et al.
2007). When the coefficient of inbreeding was calculated
following the conventional assumption that all founders
were outbred and unrelated, no significant correlations were
found between this variable and molecular metrics, with
the exception of sMLH which showed a weak association,
although still higher than that expected. We recreated a
number of scenarios in which we modified assumptions
about (i) the relatedness between founders, and (ii) the
coefficient of inbreeding of founders. We found that when
founders were considered to be related within-groups but
unrelated between-groups, significant associations emerged
between the new coefficients of inbreeding and all the
molecular metrics, which were very similar to their expected
values. In fact, one of the scenarios (F3) yielded a correlation
coefficient between inbreeding and standardized heterozygosity that was identical to the expected value. Thus, the
strength of these associations was influenced mainly by
whether admixture had been considered in the recreated
scenario. In contrast, correlations between coefficient between
inbreeding and standardized heterozygosity did not seem
to be influenced by the degree of inbreeding assigned to
founders. Because natural populations of G. cuvieri had
already experienced a marked decline when the captive
breeding programme was started, and all individuals in
the first founding group had the same origin, it is likely that
individuals in the first founding event were related. Since
the second founding event took place several years later, and
had a very different geographical origin (individuals came
from different countries), it is unlikely that individuals from
the two groups were related. Thus, the relationship between
pedigree coefficient of inbreeding and molecular metrics
improved when the coefficient of inbreeding was calculated,
changing the assumptions about the degree of relatedness
between founders to make them more realistic, given the
information available about the founding populations (i.e.
recognizing that there had been admixture). However, the
relationship between coefficient of inbreeding and molecular metrics was less strong than in the case of G. dorcas probably because in G. cuvieri, there were fewer founding events
and these took place during the first years of the captive
breeding programme. In contrast, in G. dorcas, new founding
events have continued until recently, and thus, they probably
have a much greater impact on our study sample (Ballou
1997; Balloux et al. 2004).
Finally, G. dama mhorr had a founding population of ‘apparent’ intermediate size, thus having a mean coefficient of
inbreeding intermediate between the other two species. However, levels of genetic variability (expected heterozygosity
and mean number of alleles) were the lowest, being similar
to those of a highly bottlenecked population (Bradshaw et al.
2007). These results are probably due to a combination of
factors. On the one hand, considering that G. dama natural
populations are critically endangered (IUCN 2007 Red
List of Threatened Species, www.iucnredlist.org), and
for the subspecies G. dama mhorr, there are no reports of
animals seen in the wild after 1968, it is very likely that the
founding populations were already genetically impoverished due to decline and fragmentation of natural populations. On the other hand, due to this marked decline, the
captive breeding programme originated mainly from a
captive group of Dama gazelles kept by the Spanish army at
Daora (Morocco) (Valverde 2004). This group was captured
from the wild in 1958 from the Hagunia area (Morocco) and
kept in captivity by the military. In 1963, the group had a
male, two females and three calves. In 1970, the group consisted of 12 individuals and was divided into two. The first
subgroup (Gdam1A) consisted of eight animals (one died
during transport) brought to Almería in order to start the
breeding programme, while one sub-adult male, one adult
female, one sub-adult female, and a calve remained in
Morocco. Five years later this second subgroup had increased
in size to 10 animals and was integrated into the captive
breeding programme (Gdam1B) in Almería. In the same year
that the captive breeding programme started (1970), two
females from the same geographical area were also incorporated (Gdam2). Thus, the founding population of G. dama
mhorr descends from a small group kept in captivity in the
Sahara for years before the captive breeding started in
Almería, which presumably had high levels of inbreeding
and low levels of genetic variability. In addition, only one
female outside this captive group who left offspring up to the
present day joined the captive breeding programme in Almería
and it did so on the same year the captive breeding started.
Thus, the assumption of unrelatedness and non-inbreeding
in this species is particularly misleading. Based on this
historical information, we recreated several scenarios
© 2009 Blackwell Publishing Ltd
I N B R E E D I N G A N D H E T E R O Z Y G O S I T Y I N G A Z E L L E S 11
but, in contrast to G. cuvieri, no relationships were found
between inbreeding and the molecular metrics irrespective
of whether scenarios were more or less likely to be realistic.
The expected and observed values of the correlation between
f and sMLH were very similar, which indicates that no
association would be expected for G. dama mhorr. The reasons
why pedigree coefficients of inbreeding and molecular
metrics in this species show no association are probably
complex. First, natural populations were already extinct at
the time the captive breeding programme started and most
of the founders came from a small population which had
been held in captivity in the Sahara for many years and
consisted of related animals, and thus, the founding population probably already suffered from low levels of heterozygosity. Under these conditions, coefficient of inbreeding
may not be a good predictor of levels of homozygosity in
future generations, because these are already low in the
founding population and may not decrease much further.
Second, in contrast to the other two species, there is no admixture of different populations in this species, since the two
main founding events consisted of animals from the same
captive group, and the only female which did not belong to
this group joined the captive breeding programme at the
very beginning and had the same geographical origin. The
lack of admixture may have also contributed to the low levels
of heterozygosity found in this species.
When we consider the three species together, it becomes
clear that several factors influence the relationship between
coefficient of inbreeding and molecular metrics: (i) the size
of the founding populations, (ii) assumptions made about
founders' relatedness and inbreeding, (iii) the level of inbreeding and genetic variability present in the founding population, (iv) the occurrence of admixture, and (v) the timing of
founding events. G. dorcas neglecta had the largest founding
population, the largest number of founding events with
animals of different origins (leading to admixture), and the
most recent founding events; all these factors led to a strong
relationship between inbreeding and molecular metrics.
G. cuvieri had a small founding population, but it did experience
admixture years later, and thus, the relationship between
inbreeding and molecular metrics is lower than in G. dorcas
but very similar to the expected values. Finally, G. dama mhorr
had a much smaller founding population than had been
assumed, which probably had high levels of inbreeding
and low levels of genetic variability, and no admixture.
Thus, in this case inbreeding is not associated with molecular metrics because it is not a good predictor of levels of
homozygosity.
Recent studies have suggested that the correlation between
heterozygosity and f is likely to be weak among outbred
populations, mainly because the mean and the variance of
f are low (Balloux et al. 2004; Slate et al. 2004). This has led
some authors to conclude that heterozygosity is a weak signal for genome-wide inbreeding and that coefficients of
© 2009 Blackwell Publishing Ltd
inbreeding calculated the traditional way are the only reliable way of studying inbreeding depression (Pemberton
2004, 2008). Few studies have addressed these questions
among endangered species, where both the mean and the
variance of f are likely to be higher. By comparing three
species of gazelles which differ in the level of threat to natural populations, and in the size and history of the founding
populations, we have been able to show that the relationship between molecular metrics and pedigree coefficient of
inbreeding in endangered species is stronger than among
large outbred populations when the founding population
is large and levels of heterozygosity high (as is the case in
G. dorcas neglecta). In contrast, when founding populations are
small, there is apparently no relationship between molecular metrics and f. However, this seems to be the consequence
of common assumptions about founders (i.e. non-inbred
and unrelated) being particularly unrealistic in cases in which
species are critically endangered and founding populations
necessarily small in size. We have been able to show that
when more realistic assumptions about founders are used
to calculate f, its mean and its variance increase, and clear
relationships between molecular metrics and f are revealed.
Finally, when natural populations are on the brink of extinction and genetic variability is already greatly reduced,
inbreeding coefficient may not be an adequate measure of
subsequent reductions of genome-wide heterozygosity in
future generations.
In conclusion, founding populations for endangered species will tend to be small and will rarely consist of outbred
and unrelated individuals. In these cases, information about
the founding populations should be used to make realistic
assumptions about founders. In addition, the usefulness of
different molecular metrics as surrogate measures of pedigree coefficients of inbreeding will depend strongly on the
size of the founding population, history of the population and
on the degree of genetic erosion.
Acknowledgements
We thank Eulalia Moreno, Jesús Benzal and all the staff working at
the Parque de Rescate de la Fauna Sahariana (EEZA, CSIC). We also
thank Professor Lukas Keller for his valuable help with the programme PEDSYS and his constructive comments on a previous
version of the manuscript. The Spanish Ministry of Education and
Science provided funding (CGL2006-13340/BOS) and a PhD
studentship to MJRL. ERSR is the recipient of a Royal Society Wolfson
Research Merit Award.
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All authors are interested in understanding the deleterious
consequences of inbreeding and lack of genetic variation among
endangered species.