How multilocus genotypic pattern helps to
understand the history of selfing populations:
a case study in Medicago truncatula
M Siol1, JM Prosperi1, I Bonnin2and J Ronfort1
1UMR 1097 Diversite ´ et Adaptations des Plantes Cultive ´es, INRA Montpellier, Domaine de Melgueil, Mauguio, France
and2UMR (INRA-CNRS-UPS-INAPG) de Ge ´ne ´tique Ve ´ge ´tale, Ferme du Moulon, Gif/Yvette, France
The occurrence of populations exhibiting high genetic
diversity in predominantly selfing species remains a puzzling
question, since under regular selfing genetic diversity is
expected to be depleted at a faster rate than under
outcrossing. Fine-scale population genetics approaches
may help to answer this question. Here we study a natural
population of the legume Medicago truncatula in which both
the fine-scale spatial structure and the selfing rate are
characterized using three different methods. Selfing rate
estimates were very high (B99%) irrespective of the method
used. A clear pattern of isolation by distance reflecting
small seed dispersal distances was detected. Combining
genotypic data over loci, we could define 34 multilocus
genotypes. Among those, six highly inbred genotypes (lines)
represented more than 75% of the individuals studied and
harboured all the allelic variation present in the population.
We also detected a large set of multilocus genotypes
resembling recombinant inbred lines between the most
frequent lines occurring in the population. This finding
illustrates the importance of rare recombination in redis-
tributing available allelic diversity into new genotypic combi-
nations. This study shows how multilocus and fine-scale
spatial analyses may help to understand the population
history of self-fertilizing species, especially to make infer-
ences about the relative role of foundation/migration and
recombination events in such populations.
published online 20 February 2008
Keywords: Medicago truncatula; microsatellite; allozyme; genetic diversity; population structure; selfing rate
Understanding how mating system affects plant genetic
diversity is a major theme in evolutionary genetics.
Selfing is known to reduce within-population diversity at
equilibrium by a factor (2?S)/2, where S is the selfing
rate (Pollak, 1987; Nordborg and Donnelly, 1997).
Because inbreeding also reduces the efficiency of
recombination (Nordborg, 2000), a further reduction in
neutral polymorphism is expected from hitchhiking
associated with selective sweeps (Maynard Smith and
Haigh, 1974; Barton, 2000) and from background selec-
tion against deleterious mutations (Charlesworth et al.,
1993). Self-fertilization may also increase between-popu-
lation differentiation due to reduced pollen dispersal—
one of the two forms of gene flow among plant
populations. Consistently, empirical surveys of allozyme
and molecular variation among species have shown that
high levels of self-fertilization are associated with lower
within-population diversity and higher between-popula-
tions differentiation, as compared to outcrossing species
(Hamrick and Godt, 1990, 1996; Schoen and Brown, 1991;
Charlesworth and Yang, 1998; Vitalis et al., 2002; Meunier
et al., 2004; see also Charbonnel et al., 2005). However, as
noted by Schoen and Brown (1991) in a seminal paper,
there is a higher population-to-population variation in
the level of diversity in preferentially inbreeding species
than in outcrossing ones. This means that although the
mean level of genetic diversity is on average lower in
inbreeders, some populations exhibit high genetic
diversity. Since then, this result has been confirmed, for
example, in several studies on Arabidopsis thaliana
(Bergelson et al., 1998; Kuittinen et al., 2002; Jorgensen
and Mauricio, 2004; Bakker et al., 2006) in which some
populations exhibited a rather high polymorphism
whereas other populations were monomorphic (com-
posed of a single multilocus homozygous genotype).
This particular feature is not fully understood and no
satisfying explanations have been given to date. It has
been proposed that inbreeding species should be
composed of ancient populations exhibiting high levels
of polymorphism and of recent marginal populations
derived from small samples of individuals from these
large ‘source’ populations (Schoen and Brown, 1991).
However this explanation depends critically on the
dispersive abilities of the species and other explanations
can be proposed. Variation in the level of selfing
experienced by different populations of the same species
may also explain the different levels of genetic diversity
observed between populations. Finally, population sub-
division is often invoked to explain the maintenance of
Received 19 June 2007; revised 29 September 2007; accepted
3 January 2008; published online 20 February 2008
Correspondence: Dr M Siol, UMR1097 Diversite ´ et Adaptations des
Plantes Cultive ´es, INRA Montpellier, Domaine de Melgueil, Mauguio,
Heredity (2008) 100, 517–525
& 2008 Nature Publishing Group All rights reserved 0018-067X/08 $30.00
genetic diversity. Under rather simplistic assumptions it
can be shown that population subdivision reduces
genetic drift at the global scale compared to an
unsubdivided population and therefore allows main-
taining higher amounts of genetic diversity at the
population level (Wang and Caballero, 1999).
In the present study, the mechanisms underlying the
maintenance of large levels of genetic variability in
self-fertilizing populations are investigated in a natural
population of the selfing annual plant species, Medicago
truncatula (Lesins and Lesins, 1979). M. truncatula is
mainly studied as a model organism for the legume–
Rhizobium symbiosis (Cook, 1999). It is widespread all
around the Mediterranean basin and can be considered
an opportunistic species, common in open areas. It is
reported as a highly selfing species (Lesins and Lesins,
1979; Bataillon and Ronfort, 2006). Previous population
genetic analyses in this species have shown very high FIS
values and high within-population structure. Both
findings are consistent with a high selfing rate (Bonnin
et al., 1996, 2001; Bataillon and Ronfort, 2006). Indeed,
under such high selfing rates, populations are expected
to be composed of a number of nearly independent fully
homozygous sibships descended from founder indivi-
duals or from newly migrants. In order to disentangle
the relative contribution of population substructure
(Walhund effect) and selfing to the high observed FIS
values it is necessary to gather information on the spatial
distribution of individuals together with relatedness
information. To date, no direct assessment of selfing
rates have been conducted in this species and all
estimations have been obtained through the expected
relationship between heterozygote deficiency and selfing
rate at inbreeding equilibrium. However, the opportu-
nistic status of this species and the ephemeral nature of
its populations should violate the equilibrium assump-
tion and bias selfing rates estimated from FIS(Bataillon
and Ronfort, 2006). It is thus important to get new
estimate of selfing rates that do not assume that
populations are at inbreeding equilibrium. Following
this goal, we report here an analysis of the mating system
and of the fine-scale structure of a population of M.
truncatula that exhibits large levels of within-population
molecular variation. The mating system is investigated
using progeny arrays and selfing rate estimates are
compared to indirect measures based on deviation from
Hardy–Weinberg genotype frequencies (FIS). The study
of the multilocus composition of the population allowed
us to characterize the spatial distribution of inbred
sibships and to evaluate the possible impact of migration
and recombination on population genetic diversity.
Materials and methods
Seeds were collected in summer 1999 on a young fallow
(about 10 years old), located near Perpignan (Southern
France; 021550N, 421500E). The choice of this population
was motivated by its size (approximately 80?50m) and
the large number of pods available. Pods were sampled
at corners of a 50?50cm2space. We sampled two
pods per square, for a total of 100 mapped squares. Pods
were threshed and the extracted seeds were sown in a
greenhouse in order to obtain two different data sets: (1)
a first sample (hereafter referred to as Sample1) obtained
using one seed per pod (total of 200 seeds) was sown to
study the genetic structure of the population, (2) among
the 200 pods, 160 were randomly chosen for progeny
array analyses: for that purpose, two additional seeds
from each of these pods were sown, for a total of
180 individuals (that is, 60 sibships of three half-sib or
full-sib individuals, hereafter referred as Sample2).
Total DNA was extracted according to Tai and Tanksley
(1990) from 2g of young leaves previously frozen in
liquid nitrogen. Polymorphism was assayed on the first
sample (200 individuals) at seven loci previously devel-
oped by Baquerizot-Audiot et al. (2001): MAA660456,
MTR58, MTSA6, MTSA5 MTPG85C, MAA660749 and
(MAA660456, MTSA5, MTSA6, MTR58 and MTPG85C)
were used. As detailed in Table 1, this set of micro-
satellite loci includes dinucleotide, trinucleotide and
composed repeat loci. These loci are relatively well
dispersed over the eight linkage groups of M. truncatula
(Table 1). Amplification reactions were performed in a
final volume of 20ml as described in Baquerizot-Audiot
et al. (2001). PCR products were loaded on 6% denaturing
polyacrylamide gels and revealed through classical silver
staining. Allele sizes were determined with M13 as a size
Enzymatic polymorphism was assayed on Sample1.
Extracts were prepared from 80–100mg of young leaves.
Samples were ground in 1 M Tris-HCl buffer pH 7.2.
Table 1 Microsatellite loci used for the analysis and summary of microsatellite data: observed number of alleles per locus (A, with range of
allele size), unbiased expected heterozygosity (HE), observed heterozygosity (HO) and FISvalues
A (size range in bp)
Overall value (s.d.)3.14 0.457 (0.217)0.011 (0.011)0.973 (0.003)
Abbreviation: LG, linkage group.
Population structure and selfing
M Siol et al
Filter paper wicks (Whatman) were dipped into super-
natant of centrifuged samples and these were inserted
into 12% horizontal starch gel prepared with the
appropriate buffer. Seven enzymatic systems (Wendel
and Weeden, 1989b) were studied using Tris-citrate gel
buffer pH 7 and lithium-borate buffer pH 8.3. Shikimate
dehydrogenase (SDH, E.C. 220.127.116.11), 6-phosphogluconate
dehydrogenase (PGD, E.C. 18.104.22.168) and phosphogluco-
mutase (PGM, E.C. 22.214.171.124) isozymes were resolved with
TC system. Glutamate oxaloacetate transaminase (GOT,
E.C. 126.96.36.199), endopeptidase (ENP, E.C. 3.4.-.-), leucine
amino peptidase (LAP, E.C. 188.8.131.52) and mannose
phosphate isomerase (MPI, E.C. 184.108.40.206) isozymes were
resolved using LB buffer. Recipes for electrophoresis and
staining procedures were adapted with minor modifica-
tions from Wendel and Weeden (1989a).
and gene diversity HEwere estimated (Nei, 1987). Both
values were compared
microsatellites using Mann–Whitney’s U-test with loci
as replicates. For each locus, departure from Hardy–
Weinberg expectations was tested through permutations
of alleles among individuals and Wright’s F-statistics FIS
estimated according to Weir and Cockerham (1984)
using GENETIX version 4.05 (Belkhir et al., 1996–2004).
Genotypic linkage disequilibrium was measured for
each pair of loci and tested through Fisher’s exact test
using GENEPOP version 3.2 (Raymond and Rousset,
1995) and applying sequential Bonferroni-type correc-
tions to test for significance.
For each individual, a multilocus genotype was
defined combining the genotypic information of the
polymorphic loci. Multilocus diversity was then mea-
sured using the Simpson index model corrected for finite
sample size (Pielou, 1969):
For each locus, the number of alleles
SI ¼ 1?
N N ? 1
where ni denotes the number of individuals with
multilocus genotype i and N the total sample size. The
term in brackets reflects the probability that two
randomly chosen individuals are identical (Nei, 1987).
Spatial autocorrelation analyses were used to describe
the spatial organization of the genetic diversity in this
population, using Spagedi version 1.2 (Hardy and
Vekemans, 1999, 2002). This software estimates condi-
tional kinship coefficients between individuals as a
function of their spatial distance. Kinship coefficients
were calculated as described in Loiselle et al. (1995) using
each individual multilocus genotype. To estimate the
level of within-population subdivision, we divided the
sampled area according to a grid of decreasing mesh
size. Seven grids were defined, dividing the population
in 4 (2?2) to 25 (5?5) squares. The genetic differentia-
tion between the subpopulations thus defined was
estimated by the overall FSTvalues among subpopula-
tions. FSTestimates were computed according to Weir
and Cockerham (1984) and their significance was tested
using 1000 permutations of individuals within the
population using GENETIX (Belkhir et al., 1996–2004).
Mating system analyses
Three different methods were used to assess the mean
selfing rate (S) of this population. S was first inferred
using the commonly used relationship between Wright’s
within-population inbreeding coefficient and the selfing
rate, FIS¼S/(2?S). This relation assumes that the selfing
rate has been constant for a sufficient number of
generations, that the population is at inbreeding equili-
brium, and that selfing is the major cause of departure
from Hardy–Weinberg genotypic frequencies (no spatial
structure, no fitness difference between selfing and
outcrossing progenies). A jacknife over loci was used to
obtain confidence intervals for S. As a second measure of
S, we used the maximum likelihood estimator developed
by Enjalbert and David (2000). This method uses multi-
locus individual heterozygosity and provides selfing rate
estimates and confidence intervals for the two or three last
generations assuming no selection, no allelic frequency
changes among generations, linkage equilibrium between
loci and that outcrossing gametes meet at random.
Finally and in order to disentangle selfing effects and
population structure, we applied progeny arrays analysis
to the sib family dataset (Sample2). For this purpose, we
used the MLTR software, version 0.9 (Ritland, 2002) to
obtain maximum likelihood estimates of single (ts) and
multilocus (tm) outcrossing rates. This method relaxes
the assumption of hypothesis of inbreeding equilibrium
and differences between tsand tmallows inferring the
amount of inbreeding due to mating between relatives vs
selfing (Ritland and Jain, 1981). The MLTR program also
estimates the variance in selfing rates between maternal
individuals and correlation between mating parameters,
namely the correlation of selfing within progeny arrays.
A lack of correlation of selfing (rs¼0) indicates that the
selfing rate does not vary among families, whereas a
correlation suggests that sibships are either all selfed or
all outcrossed sibs. Between the two likelihood optimiza-
Newton–Raphton (NR) method, we chose the EM
method because it is more suitable for highly inbred
species (Ritland, 1986). In all our computations the
maximum number of iterations was used and sampling
variance estimates were obtained for each parameter
using 1000 bootstraps.
Monolocus genetic diversity
The number of alleles and the level of gene diversity
observed for each microsatellite locus and each allozyme
marker are reported in Tables 1 and 2, respectively.
Among the seven microsatellite loci, five showed
relatively high levels of diversity, displaying between
two and five alleles each, and gene diversities as
measured by HE ranging from 0.5 to 0.63. The two
remaining loci were less polymorphic with two alleles
segregating at unbalanced frequencies. Among the eight
enzymatic loci assayed, seven were polymorphic. All
loci, except ENP, displayed two alleles and HEvalues
lower than 0.5. Both the mean number of alleles and the
mean gene diversity were lower for allozymes compared
to microsatellites but these differences were not sig-
nificant (Mann–Whitney’s U-tests, P40.10 for both tests).
Population structure and selfing
M Siol et al
A significant departure from Hardy–Weinberg equili-
brium was detected for all the loci studied (Po0.0001).
The mean FIS value based on the whole set of
polymorphic loci was 0.978 (s.d.¼0.006) with a slightly
(but not significantly) lower value estimated using only
microsatellite markers (Table 1) as compared to the
average value obtained with allozymes (Table 2).
Spatial autocorrelation analyses using Loiselle’s coeffi-
cient (Loiselle et al., 1995; Hardy and Vekemans, 2002) as
a measure of the genetic relatedness between individuals
indicated a significant genetic relationship between
individuals located up to 8m apart (Figure 1). Similar
autocorrelograms were obtained when using microsatel-
lite loci or allozymes only (data not shown). When
subdividing arbitrarily the population into squared
units, FST values as large as 0.35–0.30 were obtained
especially when the number of subdivisions used was
large. When increasing the size of the subdivisions, the
level of differentiation progressively decreased (Figure2).
For instance, when the population was subdivided in
four squares of 25?25m2, the variation among sub-
populations accounted for approximately 15% of the
overall population variation (Figure 2).
Multilocus patterns of diversity
Over the 91 tests performed for linkage disequilibrium,
81 were found significant at the 5% level. When applying
Bonferroni correction, 74 tests were still significant.
Among those, 20 were pairs of microsatellite loci
(for 21 comparisons), 14 pairs of allozymes (21 compar-
isons) and 40 concerned pairs combining an allozyme
marker and a microsatellite locus (for 49 tests). Combin-
ing the genotypic data of the different microsatellite
markers (respectively, allozyme markers) allowed dis-
tinguishing 26 multilocus genotypes (respectively, 23).
Combining both types of markers yielded 34 multilocus
genotypes, among which 9 showed one or more
heterozygozous loci (Figure 3.). The relative frequency
of these different genotypes
(Figure 3), with 22 genotypes observed only once,
whereas 4 multilocus genotypes represented 76% of the
sample analysed (152 individuals in Sample1). This
pattern resulted in a Simpson index (computed over
the whole set of markers) of 0.805. Similar results were
(SI¼0.76) or microsatellite markers (SI¼0.74) to define
the multilocus genotypes. Interestingly, among the 34
multilocus genotypes detected, 6 were sufficient to
account for the total allelic variation of the population
(Figure 3 and see genotypes a7, b19, c14, d5, f22 and j4 in
Supplementary Table S1). A closer look at the genotypic
composition of the remaining multilocus genotypes
Table 2 Allele number (A), observed (HO) and expected (HE)
heterozygosity and FISvalues observed with eight allozyme loci
Overall value (s.d.)20.259 (0.219)0.005 (0.096) 0.981 (0.006)
0 1015 202530 3540 4550 5560 655
Figure 1 Results from the spatial autocorrelation analyses. The value of each point on the y axis represents the mean coefficient of relatedness
(here measured following Loiselle et al., 1995) between individuals located x metres apart (?): Po0.05; (J): P40.05.
Size of the square's side (in meters)
Figure 2 Variation of FSTvalues calculated over all loci for different
spatial subdivisions. Black circles give estimated FSTvalues; thin
lines show the 95% limits of the distribution under the null
hypothesis of no differentiation, obtained after 100 permutations of
the multilocus genotypes.
Population structure and selfing
M Siol et al
revealed that 13 of them displayed genotypes corre-
sponding to recombinant inbred lines between two of
the most frequent genotypes, that is, either a7 ? b19 or
a7 ? b18 (Supplementary Table S1). Also 6 of the multi-
locus heterozygous genotypes could derive from a cross
between a7 and b19 (or b18) followed by several
generations of selfing (Supplementary Table S1). Map-
ping the different multilocus genotypes showed that (1)
the dominant genotype (a7) is broadly distributed over
the sampled area, (2) the other ones being more or less
confined to a particular region of the population.
Interestingly, small patches of identical genotypes were
located at the edge of the population (see for example
genotypes c14 and f22, Figure 4).
The selfing rate inferred using Wright’s inbreeding
coefficient (FIS) estimated over the entire population
andusingthe whole set
(s.d.¼10?3). Similar values were obtained when using
only the five microsatellite loci used for progeny array
analyses, that is, S¼0.987 (s.d.¼0.0016) or reducing the
sample to the 60 plants represented in Sample2, where
S¼0.985 (s.d.¼5?10?4). Multilocus estimates were also
consistent with these values. Indeed, the algorithm
developed by Enjalbert and David (2000) concluded to
a selfing rate of 0.987 into the last generation and of 0.989
for the preceding couple of generations (these two values
were not significantly different from one another).
Progeny array analyses also yielded high selfing rates.
Among the 60 families studied, 58 were composed of
identical and homozygous genotypes, as expected
following a selfing event on an inbred line. Overall,
of markerswas 0.989
outcrossing rate estimates obtained using MLT were
exceedingly small (tm¼0.006 (s.d.¼0.005) and tm¼0.017
(s.d.¼0.017)), whatever the assumption made concern-
ing the genotype of mother plants. Differences between
tmand tswere always very low (for instance, ts¼0.014
(s.d.¼0.014) when tm¼0.017), suggesting that mating
between relatives does not enhance the apparent
In this study, we report the first estimate of outcrossing
rate using maternal progenies and likelihood methods in
M. truncatula. Previous estimates were based on FISvalues,
and thus assumed (1) that the population under study was
at equilibrium for a fixed selfing rate and (2) that no
subdivision occurred within population (Bonnin et al.,
2001; Bataillon and Ronfort, 2006). To estimate the bias due
to deviation from these assumptions, we used two
independent datasets: one devoted to the estimation of
the selfing rate (that is, progeny arrays), the other
documenting the fine scale spatial structure of the
population and allowing two indirect measures of the
selfing rate based on patterns of individual heterozygosity.
Maternal progeny analyses confirmed the selfing status of
M. truncatula, yielding a mean selfing rate of approxi-
mately 99%. Although we detected a clear pattern of
within-population structure, which was expected to
upwardly bias indirect estimates of the selfing rate,
progeny array analyses yielded similar selfing rate
estimates as indirect measures. This result is however
consistent with the relationship linking F-statistics (Wright,
Number of individuals
Figure 3 Frequency distribution of the 34 multilocus genotypes. In black are the 6 genotypes that were sufficient to explain the total allelic
variation. Hatched bars represent ‘recombinant lines’ between the most frequent genotypes (see text). Black bars refer to genotypes with at
least one heterozygous locus. Grey bars indicate genotypes that do not fit the preceding categories. The name of each genotype is indicated
under each bar.
Population structure and selfing
M Siol et al
1969), that is, (1?FIS)¼(1?FIS
frequencies due to selfing and population subdivision
(that is, Wahlund effect), respectively. From this formula, it
appears that under high selfing rates (such as the one
detected in this population), population subdivision will
only have a reduced effect on the global FISvalue.
Progeny array analyses also concluded to very low
levels of mating between relatives. This result should
however be considered with caution. Indeed, given the
particular multilocus composition of the population
(with a small set of dominant inbred lines), outcrossing
events involving sister lines cannot be distinguished
from selfing events. This means that the proportion of
outcrossing events in the studied population is probably
slightly higher than estimated. A closer look at progeny
arrays showed that outcrossing events were not ran-
domly distributed among families but rather restricted to
two progenies, suggesting that outcrossing results from
the fertilization of a limited number of flowers. Never-
theless, in our sample, each family originated from a
single pod collected on the ground. It is thus not possible
to know whether outcrossing events are concentrated on
a small set of plants or they are randomly distributed
over the population. Further studies involving several
pods per plants are needed in order to clarify this issue.
subdivisionare departure from Hardy–Weinberg
Gene diversity and population structure
Despite the large self-fertilization rate estimated in this
population, the polymorphism revealed was relatively
high, especially when measured through Nei’s index of
gene diversity (HE). Indeed, both microsatellite markers
and allozyme loci displayed gene diversity approxi-
mately two times larger compared to mean HEvalues
reported for allozymes markers in self-fertilizing species
(Hamrick and Godt, 1990; Schoen and Brown, 1991).
Due to higher mutation rates (Jarne and Lagoda, 1996;
Goldstein and Schlo ¨tterer, 1998), we expected larger
polymorphism with microsatellites than with allozymes.
But, although both the number of alleles per loci (A) and
gene diversity (HE) were on average larger for micro-
satellites than for allozymes, these differences were not
significant, in contrast to other studies (Estoup et al.,
1995; Streiff et al., 1998; Freville et al., 2001). For the
number of alleles, this result may be due to the large
variance observed for microsatellite loci (s(A)
compared to allozymes (s(A)
large differences in mutation rates among loci. For gene
diversity, however, the variance among loci was large for
both allozymes and microsatellites. This reflects the
reduced number of multilocus genotypes occurring in
the Salses population, and the fact that the most common
genotypes are highly genetically differentiated. This also
suggests that HEvalues measured in this population may
reflect a short time period (that begins at population
foundation), probably too short to see the effect of
different mutation rates.
Previous population studies of M. truncatula have
shown that in this species, there is an important
population-to-population variation in gene diversity
(Bonnin et al., 2001; Bataillon and Ronfort, 2006). This
¼0.29), which could reflect
010 1520 2530 35 4045 505
Figure 4 Map showing the location of the individuals with the more common multilocus genotypes (combining microsatellite and allozyme
loci). Individuals with unique genotypes have been omitted for the sake of clarity.
Population structure and selfing
M Siol et al
observation is consistent with results found in other
selfing species, (Schoen and Brown, 1991; Green et al.,
2001; Bakker et al., 2006; see also Ramakrishnan et al.,
2006). The factors and mechanisms responsible for the
high level of genetic diversity maintained in such
populations remain unclear. Following different founda-
tion events, a self-fertilizing population is likely to be
subdivided into small neighbourhoods that consist of
single differentiated lineages. Such subdivision is ex-
pected to reduce the effect of drift and could thus play a
major role in the maintenance of genetic diversity at
the whole population level (Barton and Whitlock, 1997).
Another explanation could be that more variable
populations display higher outcrossing rates than classi-
cally thought in this species (Jorgensen and Mauricio,
2004). For the population of Salses, our study clearly
showed that large levels of genetic variation can be
observed at the population level despite a very high
selfing rate. Combining the different loci studied, we
could show that most of the allelic variation observed in
this population resulted from the co-occurrence of a
limited number of highly differentiated inbred lines.
Three of these lines were relatively dispersed over the
populations and are thus probably the initial founders of
this population. The remaining inbred lines were less
common and represented as small patches generally
confined around the edge of the population. These lines
are thus likely to result from recent migration events
followed by a few generations of reproduction through
self-fertilization. All together, our results suggest that the
allelic variation revealed in this population mostly
results from different founding and migration events,
and that the high levels of gene diversity observed seems
to be due to the maintenance in relatively high frequency
of the different founders (or recent immigrants). The
patchy spatial organization detected in this population
could then explain the persistence of these different
inbred lines (and the corresponding allelic variation).
Selection could act at the microhabitat level, favouring
different genotypes in different parts of the site. Even
without selection, reduced pollen dispersal among
subpopulations should lead to the maintenance of large
genetic variation at the whole population level because
genetic drift occurs at the subpopulation level, allowing
different alleles to be maintained in each deme (Barton
and Whitlock, 1997). As a conclusion, we thus suggest
that the history of foundation of a population and the
spatial structure plays an important role in the main-
tenance of allelic variation and gene diversity at the
population level. However, other factors like higher
outcrossing rates or dispersal in time via the seed bank
are possible additional sources of variation in other
populations of M. truncatula or in other self-fertilizing
plant and animal species (Bonnin et al., 2001; Chauvet
et al., 2004; Charbonnel et al., 2005).
Rare but observable recombination events
If a reduced set of well-represented and highly differ-
entiated inbred lines accounted for approximately 80% of
the population, we also revealed a large set of rare
multilocus genotypes, most of them being detected only
once. Interestingly, most of these unique genotypes can
be seen as naturally occurring recombinant inbred lines,
deriving from the segregation under self-fertilization of
outcrossing events between the most frequent lines.
Recombinant genotypes have already been observed in
other predominantly self-fertilizing species (see for
example Ramakrishnan et al., 2006). Such observations
suggest that although rare, pollen-mediated gene flow in
this self-fertilizing species might play a major role in the
organization of the genetic variation both within and
among populations. This also raises the question of the
possible role of outcrossing/recombination with regard
to natural selection and adaptation in self-fertilizing
species. Natural selection could favour outcrossed off-
springs following two different mechanisms. First,
hybrid progenies from crosses between differentiated
inbred lines could display a better fitness compared to
their parental lines because heterozygosity at individual
locus may hide recessive and partially recessive deleter-
ious mutations (Falconer and Mackay, 1996). Second,
outcrossing events followed by repeated self-fertiliza-
tions should result in a set of recombinant inbred lines
displaying a large panel of new allelic combinations
among loci. Some of these new combinations could result
in higher fitness value or in new adaptations to
environmental conditions. In order to determine if the
frequency of recombinant inbred lines observed in the
Salses population was consistent with a neutral model,
we ran deterministic simulations to obtain the expected
distribution of segregating genotypes derived from the
cross between two lines differing for 8 loci (as observed
between a7 and b19, see details in the supplementary
information S2 online). It shows that, assuming an
outcrossing rate of 1% as estimated in Salses and a large
effective population size, it is not necessary to invoke
selection to explain the observed frequency of recombi-
nant lines. However this model is overly simplifying
since it does not consider the effects of drift. A survey of
the temporal variation in allele frequencies in this
population has shown that genetic drift is not too strong
(NeB150, Siol et al., 2007). Further empirical studies
are however needed in order to assess the role of
recombination in the evolutionary dynamic of self-
Concluding remarks and implications for sampling
designs and conservation
In summary, our study show that even under very large
selfing rates, genetic and genotypic diversity can be high.
As could be expected, we observed different more or less
related inbred lines located throughout the population.
Our results suggest that the maintenance of these lines
may result from the peculiar structure and from the
colonization history of the population. Finally, outcross-
ing events, although rare, generate new genotypic
combinations that could have an important role in the
dynamic of genetic variation in self-fertilizing species.
From a more methodological perspective, our study
emphasizes that taking into account multilocus informa-
tion and fine-scale structure may help greatly to under-
stand how evolutionary factors shape genetic diversity in
selfing populations. M. truncatula is now recognized as
the model plant for the genetic and genomic of Legumes
(Cook, 1999). As for A. thaliana, there is thus a strong
interest for its reproductive biology as well as for the
natural genetic variation occurring in this species
(Ronfort et al., 2006). Due to the reduced level of
Population structure and selfing
M Siol et al
diversity expected within population under high selfing
rates, collections of naturally occurring variation in
selfers are generally composed of few inbred lines per
population (1 line per population in many cases). In
agreement with recent results in A. thaliana (Bakker et al.,
2006) and previous population genetic analyses in
M. truncatula (Bataillon and Ronfort, 2006), the present
study indicates that sampling strategies based on a single
individual per population or choosing populations at
random (for germplasm conservation purposes for
example) are likely to miss a large amount of diversity.
We are grateful to Sylvie Pistre for her participation to
the allozyme genotyping and Benoı ˆt Desplanques and
Se ´bastien Fournier for their participation to microsatellite
genotyping. We also thank Denis Tauzin and Marin
Vabre for technical assistance during sampling and for
monitoring plant growth in the greenhouse.
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