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Folia Geobotanica

, Volume 52, Issue 3–4, pp 443–449 | Cite as

Epigenetic variation in clonal stands of aspen

  • Jehwoo Ahn
  • Scott B. Franklin
  • Vladimir Douhovnikoff
Article

Abstract

Epigenetic mechanisms can affect ecologically important traits, even in the absence of genetic variation. Environmental factors can influence gene regulation through chemical modifications, such as DNA methylation, resulting in acclimation that can be transferred to subsequent cell generations both mitotically and meiotically. Clonal plants such as Populus tremuloides (aspen) show considerable promise as model species for the long-term in situ study of ecological epigenetics. The common replication of identical genotypes across heterogeneous environments permits within- and between-genotype comparisons while controlling for genetic makeup. With a long lifespan and limited natural selection resulting from sexual recombination, it is conceivable that epigenetic acclimation plays an important role in the long-term ecological success of aspen. This case study is the first in a series investigating the role of epigenetics in aspen ecology. We have established long-term permanent plots of aspen, identified (genotyped) clones and established the baseline epigenetic structure. Here we report the in situ epigenetic structure of two aspen stands. We find considerable epigenetic variation and significant differences within and among genotypes and sites, suggesting both genotype and environment influence the epigenotype.

Keywords

Aspen Clonal Epigenetics 

Introduction

There is growing evidence that epigenetic mechanisms can affect ecologically important traits, even in the absence of genetic variation (Kilvitis et al. 2014). Environmental factors can influence gene regulation through chemical modifications of DNA, such as methylation, resulting in acclimation that can be transferred to subsequent cell generations both mitotically and meiotically (Richards 2011). Because some epigenetic responses are conserved but more immediate and potentially more reversible than adaptation driven by DNA sequence variation, this plasticity might be key to long-lived plants maintaining productivity and reproduction as the environment changes through time. The potential ecological and evolutionary implications of epigenetic mechanisms are thus far-reaching (Richards 2011; Geng et al. 2012; Douhovnikoff and Dodd 2015).

Clonal plants represent ideal model systems for the long term in situ study of ecological epigenetics (Douhovnikoff and Dodd 2015). The common replication of identical genotypes across heterogeneous environments permits within- and between-genotype comparisons while controlling for genetic makeup. Yet, to date, we are only just seeing the first reports of in situ plant epigenetic ecology studies (Laguncularia racemosa – Lira-Medeiros et al. 2010; Viola cazorlensis – Herrera and Bazaga 2011; Betula ermanii – Wu et al. 2013) and even fewer in situ clonal plant epigenetics studies (Fallopia japonica – Richards et al. 2012; Helleborus foetidus – Herrera et al. 2014). None of these studies have been conducted over long time periods.

Populus tremuloides (quaking aspen) shows particular promise as a model species for the long-term in situ study of ecological epigenetics (Mock et al. 2013). Aspen is one of the best-studied clonal tree species, providing an excellent foundation on which to build future research. Aspen are distributed across diverse environments permitting the comparative study of a range of environmental conditions. With a long lifespan and limited natural selection resulting from sexual recombination, it is possible that epigenetic acclimation plays an important role in the long-term ecological success of aspen (Mock et al. 2013). Recent observations in other species suggest that epigenetic diversity may have as great an impact on population performance and stability as genetic diversity (Latzel et al. 2013).

Together, European aspen (Populus tremula) and quaking aspen span a circumboreal distribution and are of high conservation concern (Kouki et al. 2004; Edenius and Ericsson 2007; Kuhn et al. 2011). Quaking aspen is the most widely distributed deciduous tree species in North America, spanning from northern Alaska/Canada to central New Mexico and coast to coast in the northern US and Canada (Little 1971). Its wide distribution suggests adaptation to different environmental conditions and/or tolerance to a broad range of environmental conditions, i.e. strong phenotypic plasticity. Large scale studies involving several clones of P. tremuloides indicate high levels of variation in physiology and growth traits within a single growing season (Mock et al. 2008). However, despite its adaptability, researchers have suggested since the 1940s that aspen stands are declining, especially in the western United States (Packard 1942; Krebill 1972). This decline is spatially and temporally variable and depends on site characteristics, disturbance, succession from aspen to conifer forests, extreme climatic events and herbivory (St. Clair et al. 2010; Sankey 2012; Rogers et al. 2013). Thus, there is an emerging need to study the ability of aspens to respond to different environmental factors to better understand this recent reduction in aspen populations.

Studies on the persistence of aspen root systems show that root connections among ramets of the same genet are maintained throughout the life of a ramet (DeRocher and Lieffers 2001), that grafting can occur among roots of different genets (Jelínková et al. 2009), that roots remain functional even under dead ramets (Jelínková et al. 2009) and that resources are shared among ramets (Tew et al. 1969; Peltzer, 2002; Jelínková et al. 2012; Bretfeld 2017). Regeneration from these root systems allows expansion into prairies (Peltzer, 2002), prolific sucker production following fires (Romme et al. 2005) and a generally positive response to most disturbances (Bartos and Mueggler 1981; Hanberry et al. 2013).

It has been hypothesized elsewhere that epigenetic mechanisms may be a key factor in the success of a clonal growth strategy at an ecological (Douhovnikoff and Dodd 2015) and evolutionary scale (Verhoeven and Preite 2013). This study is the first in a series investigating the role of epigenetics in aspen. In it we establish long-term permanent plots of aspen, genotype and identify clones, and establish the baseline epigenetic structure. Here, we report on the in situ epigenetic structure within and among two natural stands of aspen, as well as within and among different genotypes within these sites.

Material and methods

In June 2013 we mapped and sampled two Coastal Maine stands of Populus tremuloides (Table 1) at the Brunswick Naval Air Station (BNAS) located at 43°53′54.2″ N, 69°56′03.5″ W. The stands are separated by approximately one kilometer and are similar in slope (0%), elevation (~ 23 m a.s.l.) and soil type. While there is little difference in macroscale site characteristics, both sites harbor substantial microsite environmental heterogeneity in light and nutrient availability due to neighbor shading and local competitive interactions (Fig. 1). In each site, we sampled 50% of the stems by selecting every other ramet across the site. On each stem, the leaf material was collected from the uppermost south-facing branch and frozen for storage. We extracted DNA from one leaf per ramet using the method described by Doyle and Doyle (1987).
Table 1

Site genotyping results

Stand

Number of genotyped samples

Number of different genotypes

Percentage of each ramets within each stand

Number epigenotyped

A

74

2

A1

59%

20

   

A2

41%

19

C

30

2

C1

63%

13

   

C2

37%

7

Total

104

4

  

59

Fig. 1

Site C. Photographs depicting heterogeneous conditions (from open grassland to forest cover) found at site C. Taken in fall to maximize visibility of aspen ramets (white defoliated stems)

Determination of genotypes

Seven microsatellite markers (single sequence repeats [SSRs]) developed for P. tremuloides by Smulders et al. (2001 – WPMS14, WPMS17, WPMS18, WPMS 19, WMPS20), Dayanandan et al. (1998 – PTR2) and Rahman et al. (2000 – PTR14) were used to genotype all samples. The PCR reaction included 5 ng DNA, 25 ng forward primer, 25 ng reverse primer, 200 μmol·L−1 of each dNTP (Promega, Madison, Wisconsin, USA), 0.5 U Taq DNA polymerase (GibcoBRL, Grand Island, New York, USA), 20 mmol·L−1 Tris-HCl pH 8.4, 50 mmol·L−1 KCl and 1.5 mmol·L−1 MgCl2. The cycling conditions were 94°C for 2 min, 35 cycles of 94°C for 40 s, 54°C for 1 min, 72°C for 2 min, and 72°C for 20 min. Fragment analysis of the amplified DNA was performed on an ABI Prism 3100 DNA Sequencing System, using the Genemapper software (Applied Biosystems, Foster City, California, USA). We used PAUP* 4.0b10 (Swofford, 2003) and GENODIVE (Meirmans and van Tienderen, 2004) to compare genetic fingerprints and assign clonal identities as in Douhovnikoff and Dodd (2003) based on matching of genotypes.

Analysis of epigenetic variation

Methylation-sensitive amplified fragment length polymorphism (MS-AFLPs)

We screened 59 samples (Table 1) for variation in DNA methylation using MS-AFLP, a modified AFLP analysis based on restriction enzymes that are differentially methylation-sensitive. Each sample was analyzed using two different protocols, once using HpaII and once using MspI as common cutter. HpaII and MspI recognize the same restriction site, 5’-CCGG, but cut differentially based on the degree of methylation at either cytosine. HpaII is blocked when either or both cytosines are fully or hemi-methylated, and MspI is blocked when the inner C is methylated (Richards et al. 2012). The combination of the two cutters thus allows the identification of DNA methylation polymorphisms among samples. Briefly, each sample was digested in a solution containing 1× NEBuffer 3.1, nanopure water, 7 U EcoRI, and 14 U HpaII or MspI at 37°C for 2–3 hours. Enzymes were inactivated at 67°C for 20 minutes. Adapters were ligated to sample fragment ends by incubation overnight (14–18 hours) at 16°C in a master mix composed of 1 μL of 5 μM EcoRI MM solution (100 μM EcoRI Adapter 1, 100 μM EcoRI Adapter 2, 1 M TrisHCL, 5 M NaCl, 0.5 M EDTA, nanopure water), 1 μL of 50 μM HpaII/MspI MM solution (100 μM HpaII/MspI Adapter 1, 100 μM HpaII/MspI Adapter 2, 1M TrisHCL, 5M NaCl and 0.5M EDTA), 200U T4 Ligase, 2 μL of 10× Ligation Buffer, and 0.5 μL of nanopure H2O per sample.

All samples were pre-amplified with universal primers to ensure sufficient DNA concentration before selective amplification with three pairs of enzyme-specific primers. Pre-selective and selective primers were designed following Greco et al. (2012) according to their amplification efficiency (number of bands reliably produced). PCR cycling conditions were as follows: 2 min at 94°C, then 35 cycles of 30 sec at 94°C, 1 min at 56°C, and 1 min at 72°C; followed by 15 min at 72°C and storage at 4°C as necessary. NEBuffer 3.1, Ligation Buffer, T4 Ligase, and EcoRI/HpaII/MspI restriction enzymes were obtained from New England Biolabs (Ipswich, Massachusetts).

Fragment analysis

The fragment analysis returned chromatograph data, which were scored by hand, using a binary code where ‘1’ represented the presence of a particular fragment size in a sample and ‘0’ marked its absence. Samples were run twice to test whether different scoring styles were producing consistent results. We determined a scoring error rate of less than 5% which is consistent with Perez-Figueroa (2013). Abnormally shaped peaks or peaks smaller than 100 bp were not scored, and markers encountered fewer than five times across all samples were omitted.

We used the R package msap (Perez-Figueroa 2013) to analyze 283 loci across three primer pairs. For each of these primer pairs, markers were classified as methylation-susceptible loci (MSL) or non-methylation-susceptible loci (NML) according to whether they were epigenetically polymorphic. A total of 59 individuals returned scoreable chromatographs for both restriction enzyme pairs; data from the five individuals that produced a chromatograph for only one enzyme pair were not processed further.

Statistics

We compared both genetic (AFLP) and epigenetic (MS-AFLP) data for the aspen ramets to identify DNA methylation-based epigenetic variation (Perez-Figueroa 2013). To understand patterns of epigenetic similarity among the different ramets, we used principal component analysis (PCA) where polymorphic markers from the MSL/NML groups are used to creates PC axes and ellipses are drawn around group centroid to visualize the dispersion of samples around their parent group centroid. We also calculated hierarchical AMOVAs to compare variances among sites, genotypes and ramets using the GenAlEx add-on for Microsoft Excel (Peakall and Smouse, 2006, 2012).

Results

Microsatellite analysis identified four distinct multi-ramet aspen genotypes, two at each site (Table 1), and AFLP derived non-methylation-susceptible loci confirmed the genotyping results. At each site the genotypes were of comparable size based on percent of ramets genotyped. The clonal genotypes were broadly distributed across each site, in some cases with large distances between the nearest ramets (≅ 20 m).

Using 283 polymorphic loci AMOVA hierarchical analysis of epigenetic profiles identified significant differences among sites (Phi ST = 0.449, P > 0.001), among genotypes within sites (Phi ST = 0.260, P > 0.001) and within clonal genotypes (Phi ST = 0.592, P > 0.001). The greatest level of variation was among sites (45%) and within genotypes (41%; Table 2).
Table 2

AMOVA hierarchical analysis of epigenetic profiles

Source

D.f.

SS

MS

Est. Var.

%

P

Among sites

1

812.704

812.704

25.586

45%

0.001

Among genotypes

2

280.110

140.055

8.172

14%

0.001

Within genotypes

55

1278.813

23.251

23.251

41%

0.001

Total

58

2371.627

 

57.009

100%

 
Principal coordinates analysis depicts the significant epigenetic variation among sites, among genotypes, and within genotypes. Relative to the genotypes at site C, site A has a greater overall epigenetic variation and the two genotypes have a greater overlap based upon the first two principle components which explain 40.5% of the variation (Fig. 2). Site C genotypes were found to spatially overlap in their distribution and this coincided with their overlap in epigenetic character. (Fig. 3).
Fig. 2

Principle component analysis (PCoA) showing the variation in DNA methylation profiles among genotypes at site A and C. Genotypes are distinguished by color, and each point represents a single ramet. Ellipses show the average dispersion of individuals around the centroid for their parent group

Fig. 3

Plot C spatial map in meters with inset PCoA. White and black circles represent aspen stems sampled from two different genotypes. Dashed black ovals show samples with spatial and epigenetic overlap

Discussion

Aspen is an extremely long-lived species with potentially vast spatial structure (~ 10,000 years, Mock et al. 2008), and its clones are likely exposed to spatially and temporally varying micro-environmental conditions. With limited opportunity for adaptation via sexual reproduction, epigenetic mechanisms may be a key factor in the ecological success of clonal plants (Douhovnikoff and Dodd 2015, Verhoeven and Preite 2013). Our results show high levels of epigenetic variation and significant differences at all three levels investigated, within genotypes, among genotypes and among sites.

Our finding of only two genotypes at each site represents a low genotypic diversity compared to other clonal plant systems, but it is consistent with observations in earlier aspen clonal studies (Myking et al. 2011, Mock et al. 2008). The high levels of epigenetic variance, however, suggest epigenetic sensitivity to small-scale spatial and micro-environmental conditions within aspen clones, and are consistent with other epigenetic studies in natural populations of other species (Lira-Medeiros et al. 2010, Richards et al. 2012). Epigenetic variation was greater than expected by genetic divergence alone. Although we did not systematically associate epigenetic variation with specific environmental factors, within-site environmental heterogeneity is likely influencing epigenetic variation. Aspen clones are broadly dispersed across the landscape with each ramet exposed to a range of conditions including edge effects, temperature, sunlight and water (Fig. 1). Future investigation will work to associate specific environmental factors with epigenetic responses while isolating any potential contributions of within ramet and developmental variation.

One potential indication of the strong influence of micro-environment on epigenotype is the spatial cluster of samples that were identified within the overlapping PCA distributions of Site C genotypes (Fig. 3). This case study may be an indication that within some range of conditions, different genotypes will exhibit very similar epigenotypes (i.e. epigenetic convergence) and by extension particular within-species epigenotypes may be optimally suited to particular conditions. Indications of this phenomenon have been observed in mangrove (Lira-Medeiros et al. 2010), spruce (Yakovlev et al. 2012) and Japanese knotweed (Richards et al. 2012). These results will be further investigated in planned common garden tests.

The capacity to epigenetically acclimate to varying conditions likely plays an important role in the ecology of clonal plants (Douhovnikoff and Dodd 2015, Latzel and Klimešová 2010). However, this acclimation is effective in adjusting to micro-environmental heterogeneity up to a limit defined by genotype as suggested by the between genotype differences observed here (Fig. 2). Epigenetic variation is an evolutionarily adaptive trait in clonal plants (Verhoeven and Preite 2013) and ecological conditions that test the limits of epigenetic capacity to acclimate would select for genotypes with greater epigenetic capacity. On the other hand, due to extensive clonality, at a stand scale, numbers of genotypes are low and potentially susceptible to drift. Therefore it is not clear at this stage if acclimation, adaptation, or drift explain the significant epigenetic variation identified among sites. This is an important area for future investigation.

It is also important to recognize that temporal heterogeneity can be a major factor controlling epigenetic variation (Douhovnikoff and Dodd 2015), which is why we are tracking epigenetic change over time within these permanent plots. Long-term observations of epigenetic variation and response to change will provide insights to the capacity for genotype acclimation. Recognizing the considerable epigenetic variation within the genome, broad spatial distribution and great longevity, these initial results support the selection of aspen as a model species for the long term study of ecological epigenetics. If epigenetic processes are important in matching organismal response to the environment, this may prove to be a mechanism that buffers aspen against the challenges of current variable conditions and future environmental change.

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Copyright information

© Institute of Botany, Academy of Sciences of the Czech Republic 2017

Authors and Affiliations

  • Jehwoo Ahn
    • 1
  • Scott B. Franklin
    • 2
  • Vladimir Douhovnikoff
    • 1
  1. 1.Bowdoin CollegeBrunswickUSA
  2. 2.University of Northern ColoradoGreeleyUSA

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