Beta vulgaris - Save Our Seeds

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Received 6 March 2003
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Accepted 19 March 2003
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50 Evidence for gene flow via seed dispersal from crop
51 to wild relatives in Beta vulgaris (Chenopodiaceae):
52 consequences for the release of genetically modified
53 crop species with weedy lineages
54 J.-F. Arnaud * , F. Viard†, M. Delescluse and J. Cuguen
55 UMR CNRS 8016, Laboratoire de Génétique et Evolution des Populations Végétales, Bâtiment SN2, Université de Lille 1,
56 59655 Villeneuve d’Ascq cedex, France
57 Gene flow and introgression from cultivated to wild plant populations have important evolutionary and
58 ecological consequences and require detailed investigations for risk assessments of transgene escape into
59 natural ecosystems. Sugar beets (Beta vulgaris ssp. vulgaris) are of particular concern because: (i) they are
60 cross-compatible with their wild relatives (the sea beet, B. vulgaris ssp. maritima); (ii) crop-to-wild gene
61 flow is likely to occur via weedy lineages resulting from hybridization events and locally infesting fields.
62 Using a chloroplastic marker and a set of nuclear microsatellite loci, the occurrence of crop-to-wild gene
63 flow was investigated in the French sugar beet production area within a ‘contact-zone’ in between coastal
64 wild populations and sugar beet fields. The results did not reveal large pollen dispersal from weed to wild
65 beets. However, several pieces of evidence clearly show an escape of weedy lineages from fields via seed
66 flow. Since most studies involving the assessment of transgene escape from crops to wild outcrossing
67 relatives generally focused only on pollen dispersal, this last result was unexpected: it points out the key
68 role of a long-lived seed bank and highlights support for transgene escape via man-mediated long-distance
69 dispersal events.
70 Keywords: Beta vulgaris; contact zone; cpDNA; crop–wild hybrids; GMO; microsatellites;
71 risk assessment; weed beets1
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73
74 1. INTRODUCTION
75 Over the last decade, the development of transgenic plants
76 has heightened concerns about the potential negative
77 effects of the wide-scale commercial release of genetically
78 engineered crops (Darmency 1994; Raybould & Gray
79 1994; Gray & Raybould 1998; Hails 2000). Among the
80 commonly listed risks associated with environmental
81 release of genetically engineered cultivars is the hybridiz-
82 ation of transgenic plants with wild relatives, and the sub-
83 sequent introgression of transgenic traits into the gene
84 pool of wild plant populations in natural ecosystems
85 (Ellstrand et al. 1999). Furthermore, the risk of a trans-
86 genic crop escaping cultivation is likely to be higher in
87 crops where non-transgenic varieties have weedy tend-
88 encies (Raybould & Gray 1994; Bartsch et al. 1999). Even
89 if gene flow between wild and cultivated relatives results
90 in a transgene escape, its spread will obviously depend on
91 the relative fitness enhancement attributable to the nature
92 of the engineered trait, as well as on other factors such as
93 hybrid fertility, particularly during seedling establishment
94 (Van Raamsdonk & Schouten 1997; Bartsch et al. 1999;
95 Hails 2000).
96 With regard to crop/wild gene flow and its potential
97 consequences, the Beta vulgaris complex is of particular
98 interest as crop, wild and weedy forms can be found in
99 parapatry or sympatry in Europe with overlapping flower-
1
*
28 Author for correspondence (jean-francois.arnaud@univ-lille1.fr).
29 † Present address: UMR 7127, EGPM, Station Biologique, Place
30 Georges-Teissier, BP 74, 29682 Roscoff cedex, France.
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2 Proc. R. Soc. Lond. B 03PB0216.1 © 2003 The Royal Society
3 DOI 10.1098/rspb.2003.2407
6
ing periods, are wind-pollinated and all appear to be interfertile
(Bartsch et al. 1999; Saeglitz et al. 2000). In
northern France, the sugar beet (Beta vulgaris ssp.
vulgaris) is an extensively cultivated plant. Numerous
fields can be found close to the coastline where the common
wild form (B. vulgaris ssp. maritima) also occurs.
Conspecific weed beets, which germinate from the seed
bank, are also present within the sugar beet fields. Previous
studies demonstrated that these weeds result, primarily,
from hybridization events between cultivated and
wild inland beets within seed production areas for sugar
beet (Boudry et al. 1993; Bartsch et al. 1999; Van Dijk &
Desplanque 1999). Various concepts coexist as to which
plants are weeds (Baker 1974). In the present study, the
term ‘weed’ is used to define: (i) the in-row and out-row
bolters found within crops and resulting from hybridization
events; and (ii) beets encountered within man-disturbed
habitats in the close vicinity of the agrosystem,
such as roadsides, recently built slopes, etc. (Baker 1974;
Hornsey & Arnold 1979; Desplanque et al. 2002). Sugar
beets are biennial, in contrast to weed beets which
inherited the possibility of first-year flowering from wild
forms and bolt late in the growing season without the
requirement of vernalization (dominant B allele; see Boudry
et al. 1993). Sugar beet seed grown for commercial
purposes in northern France contains a fraction of hybrid
seeds and the resulting crop–wild F 1 hybrid plants are
annuals, bolting, flowering and setting large amounts of
seeds. These contaminant hybrids have given rise to
weedy lineages; their crucial character ‘earliness of flowering’
preadapts them for invasive success in cultivated beet
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131 fields (Van Dijk & Desplanque 1999). Therefore, these
132 characteristics place beets in a high-risk category in terms
133 of the likelihood of transgene escape, since herbicide-
134 resistant transgenic sugar beet lines already exist (Boudry
135 et al. 1993; Van Raamsdonk & Schouten 1997;
136 Desplanque et al. 2002; Viard et al. 2002).
137 However, at the current time, there is no evidence for
138 gene exchange between weedy lineages and wild coastal
139 relatives in sugar beet production areas. Hybridizations
140 are not necessarily confined to narrow zones of close para-
141 patry, and long-distance pollen dispersal up to hundreds
142 of metres away from the cultivated source could be sus-
143 pected in this outcrossing species (Lavigne et al. 2002). In
144 this context, we attempted to evaluate the genetic features
145 of nearby populations located within the French area of
146 sugar beet production (northern France) by analysing: (i)
147 a typical wild coastal population; (ii) a neighbouring weed
148 population situated within a sugar beet field; and (iii) an
149 intermediate population located between the two latter.
150 Such a linear sampling scheme reflects the geography of
151 a potential contact zone and provides a unique opport-
152 unity to evaluate gene exchange from sugar beet crops to
153 coastal wild sea beet populations, and the distance at
154 which pollen and seed dispersal occurs. In this study, the
155 likelihood of weed seed migration was traced back using
156 a maternally inherited chloroplastic marker diagnostic of
157 cultivated lines (Ran & Michaelis 1995). Possible introgr-
158 ession via pollen and/or seed flow was also investigated
159 using nuclear microsatellite markers (Mörchen et al. 1996;
160 Viard et al. 2002).
161 2. MATERIAL AND METHODS
162 (a) Sampling
163 To investigate fine-scale crop–wild gene flow, three locations
164 were sampled: (i) a natural coastal population of wild beets
165 (named COAST); (ii) a weed population (named FIELD)
166 located within a sugar beet field situated 1.5 km apart; and (iii)
167 a contact zone with a possible mixture of wild and weedy beets,
168 located along the river of Wimereux (named RIVER) (figure 1).
169 The present studied area is characterized by the high incidence
170 of sugar beet farming for more than 100 years and is typical of
171 what can be found in northern France where sugar beet crops
172 border the coast. From an intensive field survey, this study site
173 was chosen as representative of a case of close contact between
174 coastal sea beet populations (together with individuals sampled
175 in the river embankments) and sugar beet fields found in close
176 proximity.
177 The COAST population is a typical sea beet population found
178 along the seashore, with individuals located at the upper level
179 of the high tide. The FIELD population is characteristic of the
180 infestation of sugar beet fields by weed beets. Only weed plants
181 bolting outside the sowing lines (‘out-row weeds’ following the
182 terminology of Viard et al. (2002)) were sampled. Weedy forms
183 found outside the rows of cultivation, were derived from crosses
184 of either physiological bolters or in-row weeds found in the
185 vicinity (Desplanque et al. 2002; Viard et al. 2002). The RIVER
186 population represents a situation analogous to an estuarial zone,
187 as there is an inland tide stream that can explain the colonization
188 of the river embankments. Although cultivated and wild forms
189 are often difficult to distinguish, the RIVER population was
190 chosen to test for possible introgression because several individ-
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ual beets displayed conspicuous morphological characters specific
to cultivated lines.
Approximately 20% of the individuals belonging to the
COAST and FIELD populations were randomly sampled in
order to achieve the best representation of the whole population.
The sampling of the RIVER population was exhaustive (i.e. all
individuals were collected). Altogether, 154 individuals were
collected (see figure 1) and fresh leaves were desiccated using
silica gels (Prolabo Inc.) prior to DNA extraction.
(b) Genetic data collection
Extraction and purification of total DNA was performed using
a DNeasy 96 Plant Kit following the standard protocol for isolation
of DNA from plant leaf tissue outlined in the DNeasy 96
Plant protocol handbook (Qiagen Inc.).
The maternal cultivated origin was assessed by means of a
diagnostic chloroplastic PCR–RFLP marker. Weed beets carry
the Owen cytoplasmic male sterility (CMS) (Boudry et al.
1993), a trait maternally inherited and characterized by the
inability of the plant to produce functional pollen. This CMS is
typical of sugar beet cultivars because of its worldwide use in
breeding. The Owen CMS cytoplasm is associated with one
additional polymorphic HindIII site on chloroplast DNA (Ran &
Michaelis 1995). Primers used, PCR conditions, and DNA
digestion were applied as described by Ran & Michaelis (1995).
HindIII-digested cpDNA products were separated using 0.8%
agarose gel electrophoresis and visualized after ethidium bromide
staining under UV light.
Individuals were genotyped at six microsatellite loci (CT4,
GTT1, GCC1, GAA1, BVM3 and CAA1) according to protocols
previously described in Mörchen et al. (1996) and Viard et
al. (2002). One additional unpublished microsatellite locus
(CA2) was used with CCTTGCTAGTTGCTGCTGTG and
GCATATGTACAAGAGAGCCGTTT as 5-3 primer
sequences. CA2 is an imperfect and interrupted locus composed
of TG repeats, allelic sizes range between 225 and 229 bp, and
PCR conditions are identical to those described in Viard et al.
(2002) except for the annealing temperature (55 °C). Electrophoresis
and genotyping were performed on a LI-COR automated
DNA sequencer model 4200s (LI-COR Inc., NB, USA).
(c) Statistical treatments
Allele frequencies, departures from Hardy–Weinberg equilibrium,
linkage disequilibrium, allelic richness following the
rarefaction procedure of El Mousadik & Petit (1996), gene
diversity, and unbiased intrapopulation fixation index (Fis, a
measure of departures from panmixia within populations) were
calculated for each population using Fstat (Goudet 1995). Global
differentiation among populations (Fst) was quantified following
Weir & Cockerham (1984) and tested for significant
departure from zero by randomly permuting multilocus genotypes
among samples.
The high number of alleles segregating at hypervariable
microsatellite markers is likely to achieve a differentiation of all
individuals that are uniquely defined, even with a small number
of loci (e.g. Beaumont et al. 2001). To depict fine-scaled introgression
from crop to wild relatives, and to test individual admixture
proportions and the correspondence of genetic clusters with
geographically labelled groups, we applied a model-based clustering
algorithm introduced by Pritchard et al. (2000). Using the
software Structure (Pritchard et al. 2000), this Bayesian
method enables identification of clusters of genetically similar
individuals from multilocus genotypes without prior knowledge
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1 Weed–wild interactions in Beta vulgaris J.-F. Arnaud and others 03PB0216.3
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3580
581
sugar beet production area
100 m
500 m
1500 m
FIELD
FIELD
n = 40
the Channel
COAST
RIVER
n = 38 n = 76
river of Wimereux
River 31
river of Wimereux
bridge
River 62
582
583
584 Figure 1. Map of the sampled area. The three B. vulgaris populations are located within (COAST and RIVER) and in the
585 vicinity (FIELD) of Wimereux city (northern France, 50°46 N; 1°37 W). n: sample size. The spatial distribution of the
586 individuals sampled within the RIVER population is also given. Individuals characterized by the Owen cytoplasmic male
587 sterility are indicated with a grey triangle, whereas individuals carrying a non-Owen cytoplasmic type are represented by a
588 white circle. Scale bar, 50 m.
252 of their population affiliation. In this approach, it is assumed
253 that there are K populations contributing to the gene pool of
254 the sampled populations. Individuals can have membership in
255 multiple clusters, with membership coefficients summing to 1
256 across clusters. Each run consisted of a burn-in period of
257 200 000 steps followed by 106 MCMC (Monte Carlo Markov
258 Chain) replicates, with the number K of specified clusters being
259 from one to six and assuming that allele frequencies are uncorre-
260 lated. Repeated runs of Structure produced identical results to
261 those shown.
262 3. RESULTS
263 Chloroplastic DNA markers allowed us to distinguish
264 the cytoplasm associated with Owen’s male sterility (found
265 in cultivated sugar beets and their weedy relatives resulting
266 from a crossing with a maternal cultivated plant) from
267 other cytoplasms. All individuals from FIELD and
268 COAST populations were characterized by the OwenCms
269 and non-OwenCms haplotypes, respectively. This demon-
270 strates that extensive seed dispersal does not occur from
271 the fields into the coastal population of the area under
272 study. However, the RIVER population was clearly par-
273 titioned into two groups according to the cytoplasm
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2 Proc. R. Soc. Lond. B
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(figure 1). Twenty-five individuals out of 76, spatially
clustered in the upstream part of the RIVER population,
exhibited the OwenCms haplotype, indicating that one of
their maternal ancestors was a cultivated individual.
Therefore, in the further nuclear microsatellite analyses
the RIVER population was partitioned into two subpopulations
according to OwenCms and non-OwenCms lineages.
No linkage disequilibrium occurred for microsatellite
loci, except for pair CT4/CAA1 within the FIELD population
( p 0.05, after Bonferroni adjustment). Multiple
probability tests across all population samples yielded no
significant p-adjusted values, showing the independence of
each locus. Summary statistics about the genetic diversity
within the four populations are given in table 1. Allele frequencies
are available upon request. Allelic richness
(Arich.) ranged from 2 to 16.95 across loci and populations,
and amounts of gene diversity (He) were relatively
high whatever the lineages considered (table 1). In contrast
to OwenCms lineages (FIELD and OwenCms
RIVER populations), no significant departures from
Hardy–Weinberg equilibrium were detected for wild beet
populations (COAST and non-OwenCms RIVER), as
suggested by Fis values closed to zero (table 1). The
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619 Table 1. Genetic diversity within the FIELD, COAST and RIVER populations.
620 (The RIVER population was divided into two subpopulations according to the individual chloroplastic haplotypes (OwenCms
621 versus non-OwenCms). A rich. : allelic richness estimated following the rarefaction method developed by El Mousadik & Petit
622 (1996); He: expected heterozygosity (gene diversity); Fis: intrapopulation fixation index and its associated significance ( ∗ p
623 624 0.05, ∗∗ p 0.01, ∗∗∗ p 0.001 after Bonferroni correction).)
629 634
639
644
648 652
656
666
669 672
675
689
703 717
731
745
759
773
787
801
815
829
843
857
FIELD (n = 40) RIVER (n = 76) COAST (n = 38)
OwenCms (n = 25) non-OwenCms (n = 51)
locus A rich. He Fis A rich. He Fis A rich. He Fis A rich. He Fis
CT4 6.62 0.82 0.33 ∗∗∗ 6.00 0.79 0.24 ∗ 5.34 0.60 0.07 8.49 0.62 0.05
GTT1 3.00 0.66 0.28 ∗ 3.00 0.40 0.11 3.46 0.41 0.04 3.54 0.40 0.06
GCC1 2.00 0.49 0.75 ∗∗∗ 2.00 0.37 0.07 2.00 0.49 0.04 2.00 0.50 0.00
GAA1 2.62 0.33 0.09 2.00 0.39 0.085 2.97 0.38 0.13 3.00 0.45 0.04
BVM3 9.52 0.67 0.52 ∗∗∗ 10.00 0.76 0.63 ∗∗∗ 15.39 0.91 0.20 ∗∗∗ 16.95 0.93 0.04
CAA1 7.36 0.72 0.24 ∗ 9.00 0.74 0.46 ∗∗∗ 12.73 0.83 0.17 ∗∗ 12.21 0.85 0.08
CA2 3.00 0.62 0.36 ∗ 4.00 0.59 0.46 ∗∗ 2.98 0.45 0.097 2.99 0.52 0.24
mean 4.87 0.62 0.37 ∗∗∗ 5.14 0.57 0.33 ∗∗∗ 6.41 0.58 0.04 7.02 0.61 0.01
873
874 Table 2. Pairwise estimates of genetic differentiation (below diagonal) and their associate significance (above diagonal).
875 876 ( ∗∗ p 0.01, n.s.: not significant, after Bonferroni correction.)
882 888
894
900
902 904
906
913
920 927
934
941
948
955
962
969
RIVER
FIELD OwenCms non-OwenCms COAST
FIELD —
∗∗ ∗∗ ∗∗
RIVER OwenCms 0.0536 —
∗∗ ∗∗
non-OwenCms 0.1726 0.2259 — n.s.
COAST 0.1702 0.2257 0.0021 —
298 observed heterozygote deficiencies in weeds (OwenCms
299 lineages) could not be attributed to a particular locus, so
300 that both selective effects and potential presence of null
301 alleles can be neglected. Using permutation procedures
302 implemented in Fstat, neither Arich., nor He showed sig-
303 nificant differences between non-OwenCms and
304 OwenCms lineages. Fis values were, however, significantly
305 higher for OwenCms lineages ( p 0.001 after 10 000
306 permutations).
307 Although there were strong frequency oppositions, we
308 did not find any diagnostic microsatellite alleles to dis-
309 tinguish between cultivated–weed lineages and wild forms
310 of B. vulgaris (data not shown). However, even at this
311 microgeographical scale, noticeable significant genetic dif-
312 ferentiation ( p 0.01) occurred between all pairwise
313 population comparisons, with the clear exception of the
314 COAST population and non-OwenCms individuals of the
315 RIVER population (table 2). Such a lack of differentiation
316 strongly suggests that all non-OwenCms individuals
317 belong to the same breeding group. By assuming unin-
318 formative priors on all the K inferred clusters, the Baye-
319 sian clustering approach strongly strengthened this
320 hypothesis. Genetic admixture analysis clearly indicated
321 that the posterior probability for the proper number of
322 clusters was maximum for K = 3 populations
323 (LnP = 2794.7). By incorporating prior population
324 information to assist the clustering, figure 2 revealed three
325 clusters that: (i) discriminated well COAST/non-
326 OwenCms RIVER beets (i.e. wild lineages) and
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cluster 1
River 31
FIELD
RIVER OwenCms
RIVER non-OwenCms
COAST
River 62
cluster 2 cluster 3
Figure 2. Diagram of three inferred clusters of individuals
assuming K = 3 populations using Structure (Pritchard et
al. 2000). Each point shows the mean ancestry for an
individual in the sample. The values of the three coefficients
in the ancestry vector q(i) are given by the distances to each
of the three sides of the equilateral triangle. After the
clustering was performed, the points were labelled according
to sampling location and cytoplasmic type, i.e. COAST
(dark blue), FIELD (red), RIVER OwenCms (pink) and
RIVER non-OwenCms (light blue).
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607
180
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rank
100
80
River 31
60
40
20
River 62
0 0.1
0.2 0.3 0.4 0.5
q
0.6 0.7 0.8 0.9 1
608
609
weeds
610 Figure 3. Distribution of the mean individual admixture coefficients q estimated using Structure (Pritchard et al. 2000)
611 without prior population information. In this analysis, K (the number of population contributing to the gene pool of all
612 sampled individuals) is assumed to be 2. Individuals were ranked from lowest to highest q-values and ranks were plotted
613 against q. Aq-value of 1 denotes a wild individual, whereas 0 denotes weedy individuals. Also displayed are lines giving the
614 95% posterior probability intervals of q for each individual. The cytoplasmic status of individuals is represented by a grey
615 diamond for a OwenCms cytoplasm and a white diamond for a non-OwenCms cytoplasm.
wilds
327 FIELD/OwenCms RIVER beets (i.e. weedy lineages); and
328 (ii) clustered almost all wild individuals into the same
329 cluster (i.e. cluster 1). Among the 89 individuals carrying
330 the non-OwenCms haplotype, 80 fell into cluster 1, while
331 no OwenCms individuals were assigned into this cluster.
332 Instead, OwenCms individuals split into clusters 2 and 3
333 in accordance with their spatial location, with, nonethe-
334 less, some intermediate individuals (figure 2). Does the
335 nuclear polymorphism mirror the cytoplasmic partitioning
336 of individuals? By assuming K = 2 (LnP = 2837.5), we
337 then reported the means for the individual admixture pro-
338 portion qi and their 95% probability intervals in figure 3,
339 as in Beaumont et al. (2001). It can be seen that there is
340 strong evidence for two distinct groups. These two clusters
341 were perfectly in accordance with the cytoplasmic classi-
342 fication, with only six non-OwenCms (wild) individuals
343 present in an intermediate position (0.2 q 0.8) with
344 very wide probability limits for q-values. However, within
345 the ‘wild part’ of the RIVER population (see figure 1),
346 individuals ‘River 31’ and ‘River 62’ have a large pro-
347 portion (0.912 and 0.976, respectively) of their nuclear
348 genome that comes from the weedy lineage although they
349 carry a non-OwenCms cytoplasm. Once again, no
350 OwenCms individuals were assigned into the bulk of wild
351 sea beets (figure 3).
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4. DISCUSSION
An increasing number of studies have documented gene
exchanges from crops into their wild or weedy relatives,
which can result in the long-term establishment of cultivar
alleles in wild populations (Darmency 1994; Ellstrand et
al. 1999). Lavigne et al. (2002) predicted the existence of
substantial pollen-mediated gene flow from cultivated to
wild beets, even in the case where wild beets are supposedly
destroyed within 1000 m outside the fields. None the
less, the use of nuclear microsatellite markers allowed us
to depict a clear genetic cleavage between wild individuals
and their weedy relatives. In addition to highlighting such
a genetic distinctiveness, admixture analysis also suggested
clustering in accordance with the maternal origin and very
rare introgression events with only, at best, two individuals
(1.29%) resulting from wild–weed hybridization events.
Based on these results, this study surprisingly demonstrates
that introgression via pollen dispersal into B. vulgaris
ssp. maritima populations occupying their natural
habitat may not be the most likely route for transgene
spread from agriculture (but see Gray & Raybould 1998).
In fact, the occurrence of such gene exchanges may be
limited because weedy beet populations usually suffer
from a rapid turnover owing to farming practices (crop
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376 rotation) and have a limited flowering overlap with wild
377 sea beets. The episodes of close parapatry between culti-
378 vated beets and coastal populations are therefore neither
379 continuous in time nor in space so that gene flow from
380 the ‘weedy pollen pool’ may be spatially and temporally
381 restricted. Weed plant species are indeed often distributed
382 in ephemeral patches (Baker 1974; Hodkinson & Thomp-
383 son 1997; McCauley 1997) and the location of the 25
384 weed beets collected along the ‘Wimereux’ river matched
385 well with recent dyke-building work and soil transport. In
386 fact, 2 years after the first sampling, this population of
387 weed beets was extinct, because of man-made disturb-
388 ances (building and cleaning, personal observation2).
389 In contrast to pollen dispersal, seeds remain in the vicin-
390 ity of the seed source for the most part, and the long-
391 distance component of seed dispersal distribution is often
392 difficult to document (Levin 1981; Howe & Smallwood
393 1982; Cain et al. 2000; and references therein). Many
394 studies have reported that pollen dispersal is often the
395 major contributor to gene flow in populations of wind-
396 pollinated outcrossing plant species and that striking spa-
397 tial genetic structuring is mainly the result of restricted
398 seed dispersal (e.g. Hamrick & Nason 1996; McCauley
399 1997; Latta et al. 1998; Laporte et al. 2001). None the
400 less, we should bear in mind that dispersal occurs spatially
401 by seed and pollen movement, but also occurs in time via
402 the seed bank (Hodkinson & Thompson 1997; Raybould
403 1999). In the present study, several lines of evidence show
404 that seed migration can occur from fields to wild popu-
405 lations, through weedy lineages via human activities such
406 as soil transport. Individuals resulting from the emergence
407 of a weed seed bank (generally found within sugar beet
408 fields) were found only a few metres apart from typical
409 sea beet individuals. Since most studies involving the
410 assessment of transgene escape from crops to wild rela-
411 tives generally focus only on pollen dispersal (reviewed in
412 Lavigne et al. 2002) this last result was unexpected. It is
413 interesting with regard to the processes associated with
414 transgene escape in B. vulgaris (Gray & Raybould 1998),
415 as well as other key aspects of the biology of plants, such as
416 invasiveness or the evolution of metapopulation dynamics
417 (Cain et al. 2000). Because beets have a long-lived seed
418 bank and can shed thousands of seeds, this means that
419 weeds are likely to reappear each spring despite stochastic
420 disturbances (Desplanque et al. 2002). Together with
421 stochastic founder effects, occasional long-distance seed
422 dispersal, without regard to the extent of geographical sep-
423 aration, also means that gene flow would not necessarily
424 decline regularly as an exponential function of distance
425 from the genetically engineered crop (Raybould & Gray
426 1994; Van Raamsdonk & Schouten 1997).
427 Evaluation of the relative contribution of pollen and
428 seed movement using maternally (chloroplastic DNA) or
429 biparentally (microsatellites) inherited markers is also
430 especially interesting in weedy plant species (McCauley
431 1997). In human-dispersed species, such as weedy forms
432 of B. vulgaris, many colonization events may result from
433 long-distance dispersal of a relatively few seeds into
434 ephemeral vacant habitats, a situation in which extinction–
435 recolonization models of genetic differentiation would be
436 more adequate than classical models of gene flow
437 (Hamrick & Nason 1996; McCauley 1997). Indeed, weed
438 beets are adapted to man-disturbed habitats (e.g. very
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high seed output in favourable environmental
circumstances) and may display life histories equivalent to
the demography assumed in the so-called metapopulation
model (Hamrick & Nason 1996; Hanski 1999). Therefore,
seed movement should be relatively common in the
sugar beet production areas and may involve multiple
colonization events through either the seed bank and/or
human-mediated long-range dispersal. As (i) the weed
population located along the river embankments is clearly
differentiated from the neighbouring FIELD population;
and (ii) substantial departures from Hardy–Weinberg
equilibrium are found within both weed populations (
Fis 0; see table 1), these findings highlight the occurrence
of stochastic colonization events involving a mixture
of genetically distinct individuals coming from several
sources (Wahlund effect). Accordingly, an additional
subclustering analysis using Structure showed that
weedy individuals sampled within the sugar beet crop split
into seven distinct clusters with the highest probability
(results not shown). Hence, the evolution of B. vulgaris
weediness is likely to result from multiple exports of genetically
differentiated crop–wild hybrids from the seed production
areas, followed by secondary hybridization events
(see also Viard et al. 2002).
In conclusion, although pollen usually represents a significant
vector for the spread of genetically modified traits,
the present results suggest: (i) that seed flow may have
a deeper and longer impact in connecting wild and crop
relatives within the complex Beta; and (ii) point out the
key role of a long-lived seed bank, a factor often neglected.
The authors thank Jacqueline Bernard for technical advice and
support. They are grateful to Henk Van Dijk and two anonymous
referees for critical reading and helpful comments on
earlier versions of the manuscript. This work was funded by a
grant from the Bureau des Ressources Génétiques, the ACI
Impact des OGM from the French Ministry of Research, the
Contrat de Plan Etat/Région Nord-Pas-de-Calais. M.D. was
supported by an INRA/Région Nord-Pas-de-Calais fellowship.
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