Appendix S1 – Chemical Methodology
One to two fully expanded leaves were collected from each plant on July 8, 2014. One
flower bud and one fruit were collected from each plant throughout the season as the
tissue became available. Flower buds were collected 1-3 days before emergence. Fruit
tissues were collected less than one week after anthesis. These times correspond to when
these tissues are most vulnerable to herbivore attack. All tissues were immediately placed
into a chilled cooler, transferred to a -80oC freezer within three hours and subsequently
freeze-dried. We pooled equal amounts of tissue from each replicate plant within a
genotype. The samples were ground to a fine powder within 1.5 ml microcentrifuge tubes
containing 2mm diameter stainless steel beads in a cryogrinder (mixer mill cryomill,
Retsch, Newtown, PA, USA) for 1 min. 20 mg  0.5mg of each sample were transferred
to a new microcentrifuge tube, to which we added 1.4 ml of acetone/water (80:20 V/V).
Samples were then vortexed for 5 min and macerated at 4oC overnight. Each
microcentrifuge tube was then placed on a plenary shaker for 3 h (280 rotations/min),
followed by centrifugation for 10 min at 16000 g. The supernatant was transferred to a
new microcentrifuge tube and acetone was removed in an Eppendorf concentrator (5301,
Eppendorf AG). The plant pellet was then re-extracted with 1.4 ml of acetone/water
solution (80:20, V/V). With the exception of overnight maceration, all other steps were
repeated once. Samples were then frozen at –20 oC and lyophilized. The freeze-dried
phenolic extract was re-suspended in 1 ml of distilled water, vortexed for 5 min, and
centrifuged for 10 min at 16000 g. The supernatant was then pipetted and placed into a
new 1.5 ml microcentrifuge tube.
1
Measurements of total phenolics and oxidative capacity were carried out using a
modified protocol from Salminen & Karonen (2011). Total phenolics and oxidative
capacity were measured spectrophotometrically. Gallic acid standards of 0, 10, 25, and
100 μg/ml were used for calibrations, while 20 μl of extract was used from each sample,
with all measurements replicated in triplicate. Next, 180 μl of pH 10 carbonate buffer
(Buffer A, J.T. Baker, Deventer, Holland) was placed in the oxidized samples, while 280
μl of Buffer C (9/5 Buffer A/Buffer B) was placed in non-oxidized samples (Buffer B
consists of 0.6% formic acid, J.T.Baker, Deventer, Holland). The 96-well plate was then
incubated for 30 min, shaking every 10 min. We added 100 μl of Buffer B to each
oxidized sample to stop the oxidation; each sample volume was 300 μl at this stage. 50 μl
of the samples was mixed with 50 μl of 1 M Folin-Ciocalteau reagent. 100 μl of 20%
sodium carbonate was added and the plate with both normal and oxidized samples was
then placed into a plate reader (Multiskan GO Microplate Spectrophotometer, Thermo,
Mississauga, Canada) for 60 minutes and absorbance was measured at 730 nm in 1 min
intervals. Total phenolics were quantified as gallic acid equivalents in μg/ml and results
were converted to mg/g dry weight. Oxidative capacity of each plant sample was
measured as the concentration of phenolics present in the non-oxidized samples minus
the concentrations present in the oxidized samples.
Concentrations of oenothein A and B and the oxidized form of oenothein A were
measured using UPLC-DAD (Waters Acquity UPLC; Waters Corporation, Milford, MA,
USA) as per Johnson et al. (Johnson et al. 2014). These compounds are ellagitannins
produced by the hydrolysable tannin pathway (Salminen & Karonen 2011). Oenothein B
is a dimer composed of two tellimagrandin I subunits, while oenothein A is a
2
corresponding trimmer (Karonen et al. 2010). The oxidized form of oenothein A is a
partially characterized ellagitannin with 14 Da higher molecular weight than the trimeric
oenothein A (McArt et al. 2013). Samples were thawed for 1-2 h and vortexed for 5 min.
40 μl of each extract was diluted in 450 μl of water: acetonitrile (8:1, v/v), and filtered
through a 0.20 μm polytetrafluoroethylene (PTFE) filter. We used a Waters Acquity
UPLC BEH Phenyl (1.7 µm, 2.1 x 100 mm) column with Acetonitrile (CH3CN) (A) and
0.1% aq. HCOOH (B) as eluents. The gradient was as follows: 0–0.5 min, 0.1% A
(isocratic); 0.5–5 min, 0.1–30% A in B (linear gradient); the flow rate was 0.5 ml min-1.
UV spectra were recorded for each peak between 195 and 500 nm. For quantitative
analysis, 5 μl the dilute extract was injected into the UPLC column, and compounds were
quantified as oenothein B equivalents.
3
Appendix S2 – Phylogeography
Introduction
Glaciation history has had profound impacts on the present-day distribution of plant
genetic diversity (Soltis et al. 1997; Comes & Kadereit 1998; Hewitt 2004). During
glaciation, plants survive in glacial refugia from where they colonize northern regions
during interglacial periods (Hewitt 2000). Yet this dispersal might not occur uniformly.
Within species variation in dispersal ability might lead to founder effects and lower levels
of genetic variation in previously glaciated regions (Ibrahim et al. 1996; Soltis et al.
1997). The diversity of other ecologically relevant traits, such as traits protecting against
herbivory, could be negatively impacted by these demographic events. For example, fast
dispersers might also be genetically correlated with lower levels of plant defence.
Therefore, having information on the distribution of genetic variation is a useful
complement to studying the biogeography of plant defence traits as such information
could help disentangle the effects of selection through biotic interactions with those of
dispersal history.
Here we focus on the geographical distribution of haplotype diversity in
Oenothera biennis. A considerable amount of work has already been conducted on the
population genetics of this system due to interests in the effects of the functionally
asexual breeding system, Permanent Translocation Heterozygosity (PTH) (Johnson 2011).
Early work on O. biennis population genetics utilized allozymes to show considerable
evidence for population differentiation even within a single region (Levin 1975). As well,
a decrease in allozyme diversity was found in populations in the Northern part of the O.
biennis range (Levin 1975), suggesting a latitudinal gradient in genetic diversity within
4
this system. Overall, a relatively large amount of genetic diversity has been discovered at
the regional level (Levy & Levin 1975, Johnson 2009, Godfrey 2014). Yet within
individual populations, most consist of either one or two genotypes (Levin 1975; Godfrey
2014), allowing the sampling of one individual per population to adequately describe the
genetic identity of that immediate area.
Taxonomic work on the Oenothera biennis complex has found evidence for
several distinct races within O. biennis (Levy & Levin 1975; Dietrich et al. 1997).
Specifically, O. biennis I is expected to be found in much of the eastern USA, except
New England, while O. biennis II should be found in New England and parts of Eastern
and Central Canada (Levy & Levin 1975). However it is unclear how genetic diversity is
distributed across the full range and within each race. To increase our understanding of
this system we ask the following questions: (1) Is there are latitudinal gradient in
haplotype diversity in O. biennis? (2) Is there a difference in haplotype diversity between
glaciated and unglaciated regions?
Methods
Population sampling and DNA extraction
We designed our sampling to cover the majority of the range of O. biennis. In total we
sampled 119 individuals from 70 distinct populations (62 of these populations are shared
with the common garden). The numbers of samples per population ranged from one to
nine (mean = 1.7). Most samples were collected as newly expanding leaves dried in
silica-gel from natural populations, and the remaining samples were obtained from
seedlings germinated in the lab from seed. Seeds were obtained directly from natural
populations, the Ornamental Plant Germplasm Center at Ohio State University and S.
5
Greiner’s collection at the Max Planck Institute for Molecular Plant Physiology (Golm,
Germany). We germinated 5-10 seeds from each maternal genotype on moistened filter
paper in sealed petri dishes for 10–40 days. Seedlings were transplanted into pots
containing potting soil and cultivated in the greenhouse for 40–60 days; one seedling per
maternal haplotype was harvested for DNA extraction. Dried and fresh samples were
ground into a fine powder and genomic DNA was extracted using a cetyl-trimethyl
ammonium bromide (CTAB) protocol (Doyle 1987), and stored at -20°C until further
analysis.
PCR amplification and sequencing
To identify variable regions suitable for phylogeographic analysis, we screened 10-13
individuals for the amplification and polymorphisms at six non-coding intergenic
chloroplast (cp) DNA regions. These regions included atpI-atpH, psbA-trnH, rpl32-trnL,
rps16-trnQ, trnL-trnF, and trnS-trnG. We successfully amplified and sequenced each
region using universal primer pairs (Taberlet et al. 1991). Only the rpl32-trnL intergenic
spacer showed evidence of sufficient polymorphism for phylogeographic analysis. We
therefore selected this locus for further sampling and analysis of haplotype variation.
Specifically, we amplified a ~600 bp region where the primers occurred in the 3’ coding
sequence of rpl32 and the 5’ coding sequencing of trnL.
Amplification and sequencing followed standard protocols. We
performed polymerase chain reaction (PCR) at a volume of 20 μL containing 10–50 ng
genomic DNA, 1xTaq buffer with 2 mmol/L MgCl2, 200 μmol/L of each dNTP, 0.2
μmol/L of each primer, 0.5 U Dream Taq DNA polymerase (Burlington, ON, Canada),
and ddH2O. PCR was carried out in an Eppendorf Thermocycler (AG22331, Hamburg,
6
Germany) using the following program: initial denaturation at 94°C for 3 min; 35 cycles
of denaturation at 94°C for 30 s, annealing at 52°C for 45 s, extension at 72°C for 45 s;
and a final extension at 72°C for 5 min. Successful PCR amplification was assessed by
electrophoresis on a 1% agarose gel dyed with SYBR Green (ThermoFisher, Burlington,
Canada) and visualized under UV. Positive PCR products were sequenced using the
BigDye Terminator Cycle Sequencing Kit (ThermoFisher, Burlington, Canada).
Sequencing reactions were run at a volume of 5 μL, containing 1 μL PCR product, 0.5μL
BigDye, 1 μL buffer (1x), 0.5 uL primer (10 μmol/L), and 2 μL ddH2O. The sequencing
reaction involved 25 cycles of denaturing at 96°C for 30 s, annealing at 50°C for 15s,
extension at 60°C for 4 min. Products were analyzed on an ABI 3730 automated
sequencer (Applied Biosystems, Foster City, CA, USA) in University of Toronto’s
Center for the Analysis of Genome Evolution and Function (CAGEF).
DNA sequence editing and alignment
We manually checked and aligned rpl32-trnL sequences to a reference sequence of
Oenothera biennis rpl32-trnL locus using Geneious R8 version (Biomatters, Gene Codes
Corp., San Francisco, CA, USA). Sequences that were less than 200 nucleotides long
were removed from further analyses as reliable polymorphisms could not be detected in
them. We conservatively removed a poly-adenelated repeat region in each species
because it was difficult to distinguish polymorphisms from sequencing error. We used the
sequence variation in rpl32-trnL to identify haplotypes present in our populations. A
minimum variant frequency of 0.01 and an alpha value of 0.0001 were used to align all the
sequences to display the range of polymorphisms that were present. Nine polymorphic sites
were found which included both SNPs and indel mutations. These polymorphisms were
manually analyzed to identify distinct haplotypes present in the sample populations. Single
7
polymorphisms detected in only a single individual with considerable uncertainty were
disregarded and considered to be sequencing errors.
The polymorphisms were used to classify each sequence into a distinct haplotype.
Genetic distances between haplotype, as calculated by the number of mutational steps
separating each haplotype were used to generate a haplotype relatedness map (unrooted tree).
GPS coordinates associated with each haplotype were used to generate a map of haplotype
distributions in ArcMap (ver. 10.3). Each haplotype was assigned an identity as either being
from a glaciated or unglaciated region, measured by the extent of the Wisconsin glacier.
Statistics
Diversity of haplotypes was assessed by considering haplotype richness, diversity and
evenness. Diversity was calculated by using the reciprocal of Simpson’s index (Simpson
1949). Evenness was calculated by dividing Simpson’s index by species richness.
Differences between latitudes were assessed by binning populations into four regions (3034°N, 35-40°N, 41-44°N, and 45-50°N) and by comparing between the glaciated and
unglaciated areas.
Results
A total of 14 haplotypes were found, which clustered into two main groups that are
separated by 8 mutational steps (Fig. S2). One cluster was considerably more diverse
than the other. These two lineages are largely separated by the extent of the Wisconsin
glacier (Fig. S3), suggesting that haplotypes 2, 3 and 12 are associated with post
glaciation dispersal events. Populations were found to have only 1 or 2 haplotypes.
Haplotype richness, diversity and evenness are all greater in unglaciated regions (Table
S12). When compared across binned latitude classes, richness and diversity were greater
8
in 35-40°N (Fig. S4). These metrics were lower for more northern latitudes and for
isolated populations found in Alabama (30-34 ON).
Discussion
Overall, we find strong evidence for increased genetic diversity in unglaciated regions, at
mid-latitudes. This finding matches previous predictions of lower plant genetic diversity
in glaciated regions (Comes & Kadereit 1998; Hewitt 2000) and suggests that lower
latitude regions acted as a glacial refugia. This also matches previous work in O. biennis
which suggested a lower amount of diversity in more northern sites (Levin 1975). In this
section we will discuss how these findings match previous work on the population
genetics of O. biennis and how this data has possible implications for the study of
latitudinal gradients in plant herbivory and defence.
Phylogeography of O. biennis
The findings of this study matches the results of previous work in O. biennis and provides
an interesting species-wide geographic context to what is already a well studied plant.
Previous work found that O. biennis populations are genetically depauperate, usually
containing one or two genotypes (Levin 1975; Godfrey 2014). We extend these findings
to larger geographic areas, also finding that most populations where multiple individuals
were sampled have only one or two haplotypes. Oenothera biennis has been found to be
geographically separated into several races (Levy & Levin 1975). Here we find two
widely separated linages with clear geographic separation, which could constitute the
biennis I and biennis II races.
Implications for latitudinal gradients in defence
9
The utilization of genetic data to confirm claims made with trait-based genetics can only
serve to strengthen those claims. Here we have found evidence of poor haplotype
diversity within populations, but significant haplotype diversity across populations and
especially along a latitudinal gradient (Fig S3-S4). This provides justification for the
sampling design in our common garden, since a single sample is likely to adequately
describe the genetics of a population, but has a reasonable chance of remaining distinct
compared to other genotypes in the region (Johnson et al. 2009). It also shows that there
really are significant genetic differences between Northern and Southern O. biennis
populations. We have shown that Oenothein A, a major hydrolysable tannin believed to
be involved in defence against herbivores, correlates negatively with herbivory (Agrawal
et al. 2012; Table S8) and is found in much higher levels in previously glaciated regions
which have lower diversity (Fig. S1). Given the observed gradient in haplotype diversity,
there may have been a trade-off between distance and dispersal traits during
recolonization after the Wisconsin glaciation. This raises another possible explanation for
why genotypes from higher latitudes experience more herbivory in both a common
garden and in latitudinal surveys (Anstett et al. 2014).
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Appendix S4 – Trait Correlations
There are strong correlations between total phenolics and oxidative capacity within each
tissue (Table S9). Correlations between the chemistry of different tissues were sometimes
present, but are much weaker. For example, fruit total phenolics and fruit oxidative
capacity were strongly correlated (r=0.9, P<0.0001), while fruit total phenolics and leaf
total phenolics were only moderately correlated (r=0.37, P<0.0001). There were mostly
moderate correlations between total measures of chemistry and major compounds.
Oenothein A correlated positively with total phenolics and oenothein A concentrations
within other tissues; oenothein B showed negative correlations with total phenolics, but
positive correlations with oenothein B in other tissues. A variety of strong and weak
correlations occurred between plant traits (Table S9).
13