Cultivation shapes genetic novelty in a globally important invader
GENEVIEVE D. THOMPSON, DIRK U. BELLSTEDT, MARGARET BYRNE, MELISSA A.
MILLAR, DAVID M. RICHARDSON, JOHN R.U. WILSON, JOHANNES J. LE ROUX
SUPPORTING INFORMATION
Molecular Ecology · DOI TO BE CONFIRMED
Appendix A METHODS FOR AMPLIFICATION OF GENE REGIONS.
Appendix B BAYESIAN CLUSTERING METHODS.
Appendix C ADDITIONAL TABLES AND FIGURES FROM RESULTS
Figure S1 Isolation by distance analysis for native and introduced populations of A.
saligna.
Figure S2 Principal Component analysis of microsatellite data
Figure S3 Bayesian clustering of native populations using GENELAND and TESS.
Figure S4 Identification of the number of clusters in the native and introduced range
using TESS.
Figure S5 Hierarchical clustering in the native range using STRUCTURE.
Figure S6 Native and introduced allelic frequencies.
Figure S7 nDNA statistical parsimony network of native and introduced A. saligna
accessions.
Figure S8 Multi-dimensional scaling of ETS and trnQ data.
Figure S9 Hierarchical clustering in the native and introduced range using
STRUCTURE.
Table S1 Population genetic structure in the native and introduced range.
Table S2 Genetic distances between species and subspecies of acacias.
References
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Appendix A AMPLIFICATION OF NUCLEAR AND CHLOROPLAST GENE REGIONS
The nuclear ETS region was amplified using the primers described in Brown et al. (2008),
and the PCR setup and conditions described in Le Roux et al. (2011). Accessions that did
not produce clean sequences were cloned using the PGEM® -T Easy Vector System
(Promega, Anatech, Johannesburg, South Africa), and had a number of inserts sequenced.
The chloroplast region (trnQ - 5’rps16) was amplified using the primers described in Shaw et
al. (2007), and the following PCR conditions: each 50 µL reaction contained approximately
30 ng of genomic DNA, 200 µM of each dNTP (AB gene; Southern Cross Biotechnologies,
Cape Town, South Africa), 25 pmol of each primer, 0.5 U Taq DNA polymerase (SuperTherm JMR-801; Southern Cross Biotechnologies), 10 X PCR reaction buffer, 3 mM MgCl2.
The reaction was held at 95 °C for 5 minutes prior to the addition of Taq. Thermocycling
consisted of initial denaturation at 95 °C for 2 min, 35 cycles of 95 °C for 15 s, 56 °C for 30 s,
72 °C for 10 s; and a final extension of 72 °C for 10 min. Amplified DNA fragments were
purified using the QIAquick PCR Purification kit (Qiagen, Cape Town, South Africa, Southern
Cross Biotechnologies), sequenced using the ABI PRISM BigDye Terminator Cycle
Sequencing Ready Reaction kit (forward only) and an automated ABI PRISM 377XL DNA
sequencer (PE Applied Biosystems, Foster City, CA, USA).
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Appendix B BAYESIAN CLUSTERING METHODS
First we used a hierarchical clustering approach (Le Roux et al. 2010) implemented in
STRUCTURE (Falush et al. 2007) and the ΔK method of Evanno et al. (2005) to determine all
levels of population structure in the native range (Knative). This approach was repeated for the
native and invasive range (Kcombined). We followed the methods of Rollins et al. (2009),
simulating K values from one upwards until either K exceeded the total number of
populations, or the number of individuals per population was insufficient to allow for further
analyses of population structure. Individuals that could not be assigned with more than 60%
of their scored loci to a particular group were not included in subsequent analyses.
Furthermore, individuals within a single population that were assigned to a genetic group
outside of their population of origin were separated into their respective genetic groups for
the next level of the analysis.
Second, we conducted an analysis using the spatial model in GENELAND (Guillot et al.
2005), implemented in R (Ihaka & Gentleman 1996, R Development Core Team 2004).
GENELAND produces results that are robust when fine scale population structure is present
(see Guillot 2008). GENELAND uses spatial co-ordinates as artificial centres around which the
genetic groups are clustered. In this way it is able to incorporate spatial information without
actually using the physical location of the sampled populations. We conducted ten
independent runs using correlated allele frequencies, and 1 million iterations of the Markov
chain Monte Carlo procedure, saving every 1 000th iteration.
Third, we determined the optimal number of K clusters for A. saligna using TESS (Chen et
al. 2007) so we could compare our results to Millar et al. (2011). We used spatial information
when determining Knative, but not for Kcombined. We followed the methods of Millar et al. (2011)
for all parameters, except that we used an admixture model for the reason outlined in
François and Durand (2010). For each value of Kmax, we computed the Deviance Information
Criterion (DIC), and averaged the estimated admixture coefficients over 20 % of the runs with
the lowest DIC values plotted against K for all runs. We then selected the minimum value of
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
K for which DICK was not significantly different from the mean of all values of DIC greater
than K based on a one-sample t-test.
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Appendix C ADDITIONAL RESULTS (TABLES AND FIGURES)
Figure S1 Relationship between genetic and geographic distance for Acacia saligna populations in the native range in Western Australia (A) and the
introduced range in South Africa (B) based on 10 nuclear microsatellite loci. Population pairwise genetic (FST calculated in ARLEQUIN) and geographic
(Euclidean) distance was correlated using a Mantel test and the online “isolation by distance” service (http://ibdws.sdsu.edu/~ibdws).
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Figure S2 Genetic correlation between native lineages of Acacia saligna (circles, diamonds, triangles) and introduced populations from South Africa (crosses)
using a principle co-ordinate analysis of microsatellite data. Native lineages include A. saligna subspecies ‘lindleyi’ (Group 1), and subspecies ‘stolonifera’ and
subspecies ‘saligna’ (Group 2). Group 3 comprised of invasive South African populations and two native populations (Tua and Bus), and clustered separately
from the two major native Groups. Co-ordinate 1 explained 34.6% of the variation, and Co-ordinate 2 explained 22.6% of the variation.
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Figure S3 Bayesian clustering of native populations of Acacia saligna based on 10 nuclear microsatellite loci in the software GENELAND and TESS
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Figure S4 Identification of the optimal number of clusters in the native range (A), as well as
the native and introduced range (B) of Acacia saligna. The data sets contain a total of A) 202
and B) 365 individuals for 10 diploid, nuclear microsatellite loci. For each region (native and
introduced), we performed 1000 independent runs of 10 000 sweeps using an admixture
parameter α = 0.6 in TESS. We kept 20% of runs that had the lowest DIC or lnP(D|K) values,
averaged their outputs per K value, and plotted these averages against K.
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Figure S5 – see legend on next page.
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Figure S5 Identification of the optimal number of clusters (Knative) for Acacia saligna in the native range in Western Australia using hierarchical
Bayesian clustering in the software STRUCTURE. The data set contains a total of 14 populations containing 202 individuals genotyped at 10 nuclear
microsatellite loci that were clustered at 3 hierarchical levels: Level 1 (A), Level 2 (B, C, D) and Level 3 (E, F, G). The estimated proportional
membership is represented by bar plots, where each bar is an individual that is divided into K-coloured segments representing the proportional
membership of each individual’s genome (qi) to a particular K cluster. The optimal K for each level of clustering was identified using the ΔK method
(Evanno et al. 2005) and is graphed with each plot. Sampling site labels are indicated below each plot.
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Figure S6 Distribution of microsatellite allelic frequencies that differed by at least 10 %between the native and introduced ranges of Acacia saligna.
Loci and alleles presented were selected to display the maximum variation between the native and introduced range.
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Figure S7- see legend on next page.
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Figure S7 Spatial distribution of sequence variation (external transcribed spacer region) for Acacia saligna accessions in (A) native Western Australia and (B)
introduced South African populations. Statistical parsimony networks were constructed in TCS for Acacia saligna accessions in (C and D), where each circle
represents a sampled haplotype (size proportional to frequency) and each link between haplotypes indicates one mutational event. The pie slices of a circle
indicate the proportion of localities at which that haplotype was collected. Angle of bifurcation and length of link between haplotypes have no significance.
Number of haplotypes (NH), haplotype diversity (h) and nucleotide diversity (p) are presented in bottom left corner for Western Australia (A) and South Africa
(B).
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Figure S8 Separation of native and introduced individuals of Acacia saligna based on pairwise genetic
distances for (A) cpDNA, the trnQ-5’rps16 region, and (B) nDNA, the ETS region. Genetic distances were
translated into proximity co-ordinates using a nonmetric multidimensional scaling analysis.
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Figure S9- see legend on next page.
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Figure S9 Identification of the optimal number of clusters (K) for Acacia saligna in the native (Western Australia) and introduced (South Africa)
range using hierarchical Bayesian clustering in the software STRUCTURE. The data sets contain a total of 21 populations containing 365
individuals genotyped at 10 nuclear microsatellite loci and clustered at 2 hierarchical levels: Level 1 (A) and Level 2 (B, C). The estimated
proportional membership is represented by bar plots, where each bar is an individual that is divided into K-coloured segments representing the
proportional membership of each individual’s genome (qi) to a particular K cluster. The optimal K for each level of clustering was identified
using the ΔK method (Evanno et al. 2005) and is graphed with each plot. Sampling sites are indicated below each plot.
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Table S1 Population pairwise genetic structure for the native (Western Australia) and introduced (South Africa) range of Acacia saligna.
Population pairwise FST values were calculated in ARLEQUIN using genotypic data generated from ten nuclear microsatellite loci
Western
Australia
Parkeyerring
Ravensthorpe
Wellesley
Busselton
Tuart Forest
Dinninup
Wanneroo
Leshnault Inlet
Mount Ney
Preston
Muntagin
Tweed River
Wickepin
Boyatup Hill
PAR
0.004
0.149
0.138
0.193
0.005
0.281
0.355
0.296
0.239
0.180
0.323
0.174
0.253
RAV
0.226
0.253
0.343
0.026
0.347
0.433
0.370
0.310
0.182
0.374
0.190
0.319
WEL
0.167
0.273
0.150
0.348
0.258
0.432
0.199
0.216
0.362
0.221
0.336
BUS
0.007
0.197
0.244
0.392
0.310
0.275
0.304
0.219
0.298
0.212
TUA
0.224
0.231
0.504
0.275
0.360
0.374
0.172
0.342
0.246
DIN
0.333
0.288
0.283
0.213
0.130
0.340
0.119
0.256
WAN
LEI
MTN
PRE
MUN
TWR
WIC
0.386
0.307
0.258
0.419
0.164
0.412
0.189
0.506
0.085
0.335
0.418
0.318
0.399
0.420
0.388
0.296
0.359
0.144
0.219
0.302
0.202
0.248
0.426
0.020
0.355
0.423
0.219
0.335
South Africa
CIN
EBE
BRE
PA
SED
JBAY
Cinsta
Ebenhaezer
0.130
Breede River
0.172 0.036
Port Alfred
0.237 0.130 0.083
Sedgefield
0.086 0.034 0.035 0.115
Jeffreys Bay
0.195 0.063 0.045 0.132 0.073
Albertinia
0.106 0.122 0.174 0.268 0.086 0.204
Note: Bold values indicate highest and lowest FST values
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Thompson et al. (2012) Cultivation shapes genetic novelty in a globally important invader. Molecular Ecology
Table S2 Pairwise comparisons of nuclear genetic distances (external transcribed spacer) between species and subspecies within the Acacia
genus.
Pairwise comparisons
Species - species
A. rostellifera1 vs. A. saligna subspecies ‘lindleyi’
A. rostellifera1 vs. introduced A. saligna (South African)
Subspecies - subspecies
A. longifolia subspecies longifolia2 vs. subspecies sophorae3
A. saligna subspecies ‘lindleyi’ vs. subspecies ‘saligna’
A. saligna subspecies ‘lindleyi’ vs. subspecies ‘stolonifera’
A. saligna subspecies ‘saligna’ vs. subspecies ‘stolonifera’
Native clade - Introduced clade
A. saligna subspecies ‘stolonifera’ vs. introduced A. saligna (South Africa)
A. saligna subspecies ‘lindleyi’ vs. introduced A. saligna (South Africa)
A. saligna subspecies ‘saligna’ vs. introduced A. saligna (South Africa)
GenBank numbers:
Genetic distance
0.091
0.161
0.003
0.016
0.012
0.021
0.085
0.061
0.089
1
JF420272
2
HM007639.1
3
HM007647
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