Article
Epigenetic and Genetic Variability in Contrasting Latitudinal
Fagus sylvatica L. Provenances
María Ángeles Guevara 1,2 , David Sánchez-Gómez 1 , María Dolores Vélez 1,2 , Nuria de María 1,2 ,
Luis Miguel Díaz 1,2 , José Alberto Ramírez-Valiente 3 , José Antonio Mancha 1 , Ismael Aranda 1
and María Teresa Cervera 1,2, *
1
2
3
*
Citation: Guevara, M.Á.;
Sánchez-Gómez, D.; Vélez, M.D.;
de María, N.; Díaz, L.M.;
Ramírez-Valiente, J.A.; Mancha, J.A.;
Aranda, I.; Cervera, M.T. Epigenetic
and Genetic Variability in
Instituto de Ciencias Forestales ICIFOR (INIA-CSIC), Carretera de la Coruña Km 7.5, 28040 Madrid, Spain
Unidad Mixta de Genómica y Ecofisiología Forestal, INIA/UPM, 28040 Madrid, Spain
Ecological and Forestry Applications Research Centre (CREAF), Campus de Bellaterra, Edifici C,
08193 Cerdanyola del Vallès, Spain
Correspondence: cervera@inia.csic.es; Tel.: +34-913-476-798
Abstract: The adaptive capacity of a species and its population is determined by both genetic and
epigenetic variation, which defines the potential for adaptive evolution and plastic response to
environmental changes. In this study, we used Methylation Sensitive Amplified Polymorphism
(MSAP) and Amplified Fragment Length Polymorphism (AFLP), similar genome-wide profiling
techniques, to analyze the epigenetic and genetic variability in European beech provenances from
Germany (DE), Spain (ES) and Sweden (SE), representing the latitudinal distribution of the species.
In addition, we evaluated the effect of moderate water stress on cytosine methylation dynamics by
comparing two latitudinal contrasting provenances. Our analysis revealed that trees from ES showed
lower values of epigenetic and genetic diversity than those from DE and SE. Analyses of molecular
variance for MSAPs and AFLPs showed that 16% and 15% of the among population variations
were associated with epigenetic and genetic variation, respectively. The study of the effect of water
stress on cytosine methylation dynamics in seedlings from ES and SE revealed no significant levels
of epigenetic differentiation between well-watered and stressed plants. Only 2% of the epigenetic
variation was explained by the watering regime in ES without changes in SE. The results support that
DNA methylation may play a role in the local adaptation of Fagus sylvatica to environmental variation.
Contrasting Latitudinal Fagus
sylvatica L. Provenances. Forests 2022,
13, 1971. https://doi.org/10.3390/
f13121971
Keywords: epigenetic variability; genetic variability; Fagus sylvatica L.; DNA methylation; drought;
local adaptation
Academic Editor: Cristina Vettori
Received: 28 October 2022
Accepted: 17 November 2022
Published: 22 November 2022
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4.0/).
1. Introduction
Expectations of an environmental harshening as a consequence of the increase recurrence and intensity of droughts in many parts of Europe have been reinforced in recent
years [1,2], especially at the southern rear edge margins of some forest tree species [3,4].
These expected harsher conditions might affect the current area of distribution northward
for some species with local extinctions in the south, or bring about altitudinal displacements [5,6]. However, due to habitat fragmentation, limited dispersal ability or low migration rates, population migration to new areas might not be possible for many species [7].
Considering the expected accelerated changes worldwide in local climate, a high degree
of within-population genetic diversity is advanced as one of the prerequisites suggested
to buffer the negative impacts on adaptability of forest tree populations [8,9]. Epigenetic
variability has been suggested to play a relevant role in promoting the adaptation of
widespread species [10,11] since underpinning phenotypic plasticity occurs at the molecular level [12–14], mediating, among others, their responses to multiple abiotic and biotic
stresses [15,16]. Epigenetic mechanisms are of a reversible nature as they do not alter the
DNA sequence; thus, enabling these sessile organisms to cope with environmental changes
over their long lives [17,18].
Forests 2022, 13, 1971. https://doi.org/10.3390/f13121971
https://www.mdpi.com/journal/forests
Forests 2022, 13, 1971
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Epigenetic marks, which largely determine the phenotypic plasticity of plant species,
allow them to regulate their interaction with the environment, and to respond rapidly
to changes that may compromise their development and even their survival [19,20]. The
onset of a stressful condition triggers changes in gene expression, in just a few minutes [21].
However, it is the duration and frequency of the environmental stimulus, as well as the
ontogenetic state in the life cycle of the plant, that determines whether the epigenetic
marks are maintained as a molecular memory and even transmitted to subsequent generations [22]. In addition, epigenetic regulation plays a key role in how gene expression
changes during developmental transitions [23,24] and cell differentiation at broader stages
of plant development [25]. The impact of epigenome changes on the ecology and evolution
of plants is now beginning to be elucidated [12,26–31].
In forest trees, preliminary studies on natural variation in epigenetic marks have been
restricted to a few species, mostly to examine the extent of the epigenetic variability in
natural populations, yet only a few of them also explore their functional consequences [32].
Methylation of the 5′ cytosines in DNA strands is one of the epigenetic mechanisms related
to modulation of the expression or silencing of genes in plants [33,34]. Studies of the
variability in DNA methylation marks have allowed researchers to identify polymorphisms
associated with climatic conditions of the population origins and with phenotypic traits
such as budburst phenology or wood quality [35,36]. Significant correlations between
DNA methylation and changes in gene expression patterns of different plant species grown
under water stress have been described. Drought-tolerant plants of rice [37], maize [38]
and mulberry [39] have a more stable methylome under drought. Comparative analysis
of methylation patterns between drought-sensitive and drought-tolerant apple varieties
showed different dynamics when grown under contrasting hydric conditions [40]. Citrus
grafted plants exposed to recurrent water deficit revealed epigenetic variation was not only
associated with a scion and rootstock combination but also with a progressive tolerance
to water stress [41]. In Eucalyptus globulus, although global DNA methylation increased
during dehydration, the analysis of specific DNA sequences showed an induction of redox
and methylation changes during stress imposition and recovery [42]. Populus, considered a
model genus in forest tree genomics, has concentrated most of the efforts geared towards
unravelling the role of DNA methylation in response to drought [14,43]. The analysis
of black cottonwood (P. trichocarpa) response to drought showed an association between
DNA methylation and variable splicing, with non-methylated cis-splicing sites versus a
high level of methylated trans-splicing sites. The identification of methylated transposable
elements (TEs) in promoters and the gene body of transcription factors involved in drought
signal transduction pathways demonstrated the role of DNA methylation in the regulation of stress-responsive genes [44]. The analysis of differentially expressed genes and
differentially methylated regions in the shoot apical meristems of Populus × euramericana
(P. deltoides × P. nigra) grown under different water regimes, revealed a significant enrichment in the genes related to phytohormone metabolism and signaling [45]. Sow et al. [46]
observed that RNAi-ddm1 lines (undermethylated) were more tolerant to drought-induced
cavitation than control P. tremula × P. alba plants. Mapping of differentially methylated
regions revealed colocalization with differentially expressed genes, mainly involved in
hormone-related stress responses, as well as with active TEs. This highlights the role of
DNA methylation in the repression of TEs, and therefore, in the maintenance of genome
integrity. The impact of environmental history on the capacity of a tree to respond to an
environmental stimulus was observed in poplar clonal material harvested from different
geographical locations and grown under common environmental conditions [47]. In this
study, transcriptomic profiles associated with the response to drought were correlated,
with differences in DNA methylation as well as with the geographical origin of the clones
with the longest time since establishment. The usefulness of global DNA methylation as a
potential marker for population differentiation, performance, and selection under stressful
conditions was validated by the estimation of heritability and phenotypic differentiation for
Forests 2022, 13, 1971
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global DNA methylation in P. nigra trees from natural populations grown under different
soil water availability [48].
The present study aims to compare the epigenetic and genetic variability of European
beech (Fagus sylvatica L.); a widespread tree species in Europe of high economic and
ecological value. Its distribution in the Mediterranean basin is limited by drought sensitivity
since this species needs moist soils, abundant rain and atmospheric humidity. The high
sensitivity of beech to water stress [49–51] was clearly observed in the main core range of
distribution in central Europe after the acute dry period in the summer of 2003 [52,53], and
more recently after the severe drought of 2018 and its dire consequences on beechwood
health [54]. On the other hand, the species has a complex recent history of recolonization
after the last glacial period from different refugees in the Holocene, and with extant
populations that, in the case of the Iberian Peninsula at the trailing edge in the south, could
probably have its origin from even more antique refugia dating back to the Pleistocene [55].
This would add complexity to the understanding of the current genetic population structure
of the species [56–58]. In this study, we explored the epigenetic and genetic divergence
among three provenances of European beech spanning along the latitudinal gradient of
the species [59]. This includes one of the southern-most populations of the range, which
is highly threatened by intense recurrent droughts. In addition, we explored to what
extent drought stress modified DNA cytosine methylation comparing two latitudinal
contrasting provenances. We used Amplified Fragment Length Polymorphism (AFLP) and
Methylation-Sensitive Amplified Polymorphism (MSAP) techniques to analyze the genetic
and cytosine methylation of specific anonymous CG and CCG sequences, respectively.
Specifically, we have tested two hypotheses: (i) epigenetic variability is as important as
genetic variability in molecular differentiation of beech provenances; and (ii) the change in
cytosine methylation status of some loci is related to a drought response.
2. Materials and Methods
2.1. Plant Material and Experimental Layout
Seeds from three beech provenances from Spain, Germany and Sweden representing
the latitudinal distribution range of the species were collected (Table 1). After a chilling
treatment for 8 weeks at 4 ◦ C, most of the seeds began to germinate. Between 25 and
30 seedlings with 1–2 cm long radicle per provenance were transplanted into 2 L pots filled
with a 3:1 volume mixture of peat: sand. The substrate was supplemented with 2 kg m−3 of
Osmocote Plus fertilizer (16-9-12 NPK+2 micronutrients, Scotts, Heerlen, The Netherlands).
Table 1. Location and climatic details of the provenances studied in the diversity (1) and water
treatment (2) assays.
Provenance
Code
Assay
Country
Location
DE
ES
SE
SE
1
1, 2
1
2
Germany
Spain
Sweden
Sweden
Kempten
Montejo de la Sierra
Blaviksliarna
Falkenberg
Latitude
47◦
42◦
57◦
56◦
44′
01′
90′
52′
Longitude
Altitude
(m. a. s. l)
Rainfall
(mm)
Average
Temperature
(◦ C)
10◦ 23′
3◦ 05′
13◦ 14′
12◦ 51′
860–900
1250–1400
75
150
1316
950–1100
860
900
6.9
8.1
6.5
7
Two-year old seedlings were transplanted into 25 L pots and watered regularly to
field capacity. The plants were maintained in a greenhouse under controlled conditions
with a photosynthetic photon flux density (PPFD) of 353 to 454 µmol m−2 s−1 , minimum
and maximum temperatures of 18.8 ± 3.1 ◦ C and 32.5 ± 4.0 ◦ C, respectively, a minimum
relative humidity throughout the experiment of 66.6% ± 3.8%, and natural lighting.
2.2. Watering Treatment and Water Potential Measurements Layout
In order to study the effects of drought stress, the experimental layout of seedlings
from the Spanish (ES) and additional Swedish (SE) provenances (Table 1, assay 2), represent-
Forests 2022, 13, 1971
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ing the latitudinal extremes of the range of distribution of the species, followed a random
factorial design with two main factors: provenance and watering. During the establishment
phase of one month, the ES and SE seedlings were grown under the conditions previously
described and watered to field capacity. In a second phase, half of the seedlings of each
provenance (12–14 seedlings per each combination of provenance and watering regime)
were randomly assigned to the water-stress (WS) or well-water (WW) treatments, respectively. WW seedlings were watered to field capacity during the whole experiment. At the
beginning of the experiment, seedlings were watered every 5 days, increasing the frequency
of the watering according to plant growth. By the second month of the experiment and
afterward, the WW seedlings were watered every two days. In contrast, the WS seedlings
were progressively subjected to drought by watering withdrawal. Drought peaked after
50 days when the soil water content reached a soil volumetric water content (VWC vol%)
of 13. The watering protocol resulted in a moderated water stress that was maintained for
almost two months. The VWC was individually monitored throughout the experiment
with time domain reflectometry, TDR (TRIME-FM, Imko Micromodultechnik GMBH, Ettlingen, Germany). A similar level of water deficit across the provenances was ensured
by an intensive (three–four times a week) individualized control of the soil moisture and
watering according to the individual differences in water consumption. The water potential
at predawn (Ψpd ) and midday (Ψmd ) was measured with a Scholander pressure chamber
using one leaf per seedling (PMS Instrument Co. 7000, Corvallis, OR, USA). More detailed
experimental protocols are reported in Sánchez-Gómez et al. [59].
2.3. DNA Extraction
The leaf tissues of well-watered and water-stressed seedlings were harvested and
immediately frozen in liquid nitrogen and stored at −80 ◦ C. Samples were maintained at
−80 ◦ C in a freezer until molecular analysis.
DNA was extracted from frozen leaves ground in a Retsch MM300 mixer mill (Retsch
GmbH & Co. KG, Hann, Germany) using a DNeasy Plant Mini Kit (Qiagen, Hilden, Germany), according to the manufacturer’s instructions. Extracted DNAs were quantified
using a Nanodrop 1000 Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA).
2.4. MSAP Analysis and Scoring
The Methylation-Sensitive Amplified Polymorphism (MSAP) technique, a modification of the AFLPs, was used to study anonymous methylation sensitive restriction sites
at the wide genome [60]. The isoschizomers MspI and HpaII endonucleases, that show
different sensitivity to 5′ -cytosine methylation, were used, each in combination with the
rare-cutting restriction enzyme EcoRI. Both isoschizomers recognize the tetranucleotide
5′ -CCGG but their cutting ability depends on the methylation status of one (internal or
external) of the cytosines [61–64]. MspI cleaves sites whose internal cytosines (5′ -CmCGG)
are hemi- (one strand) or fully- (both strands) methylated, but does not cut when the
external cytosines are methylated (5′ -mCCGG); whereas, HpaII only cleaves sites whose
external cytosines are hemi-methylated (5′ -hmCCGG).
For the MSAP analysis, 250 ng of total DNA was digested with each restriction
enzyme combination EcoRI/HpaII and EcoRI/MspI as described by Cervera et al. [62].
Following the ligation of adaptors, the resulting fragments were used as a template for
pre-amplification using an EcoRI + A//HpaII/MspI + A primer combination followed by
EcoRI + 2 or +3//HpaII/MspI + 3 selective nucleotides in the selective amplification. A total
of 30 different EcoRI + 2 or +3//HpaII/MspI + 3 primer combinations were tested initially
using a subset of 8 samples to identify the most informative combinations (data not shown).
Four primer combinations were finally selected and used: EcoRI + AAC//HpaII/MspI
+ AAT, EcoRI + AAC//HpaII/MspI +ATC, EcoRI + AAC//HpaII/MspI + ACT and EcoRI
ACG//HpaII/MspI + ACT. The sequences of adaptors and primers used are listed in
Supplementary Table S1. EcoRI + 3 selective primers were labeled at their 5′ end with
fluorescent dye 800 IRDye to allow visualization of the fragments on a Li-Cor 4300 DNA
Forests 2022, 13, 1971
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Analyzer (Li-Cor Biosciences, Lincoln, NE, USA). Electrophoresis was performed using
25 cm denaturing polyacrylamide gels [16% Long Ranger® 50% Gel Solution (Lonza,
Rockland ME, USA), 7 M urea, 1 × TBE] and run at 1500 V. Before loading, the samples
were denatured by adding an equal volume of formamide buffer (98% formamide, 10 mM
EDTA, pH 8.0, and 0.06% bromophenol blue) and heated at 94 ◦ C for 2 min.
Comparative analysis between EcoRI/HpaII and EcoRI/MspI profiles revealed information about the methylation status of each targeted restriction site and were used to infer the
genetic variability associated with “Methylation-insensitive polymorphisms” (MIP) and the
epigenetic variability associated with “Methylation-sensitive polymorphisms” (MSP). The
MIPs were polymorphic fragments that showed a common EcoRI/HpaII and EcoRI/MspI
pattern, MSP were polymorphic fragments that differed in their presence or absence, or
in their intensity between EcoRI/HpaII and EcoRI/MspI profiles for one or more samples
(Supplementary Figure S1). Thus, methylation of the internal cytosine would lead to the
presence of amplified fragments in EcoRI/MspI but not in EcoRI/HpaII profiles. Indeed,
hemi-methylation of the CCGG site, in which the external cytosine is methylated only
in one strand, would lead to the appearance of fragments in EcoRI/HpaII but not in the
EcoRI/MspI profile (reviewed by Schulz et al. [63,65]).
The MSAP fragment presence or absence was visually determined by two independent
observers. For the methylation-sensitive loci, we adopted a methylation scoring described
by Salmon et al. [66] and the review by Schulz et al. [63]. Four score-types could be
distinguished for a given sample and MSAP fragment: class 1, which included fragments
present in both EcoRI/HpaII and EcoRI/MspI profiles, was scored as 0; class 2, which
included fragments present in EcoRI/MspI and absent in EcoRI/HpaII profiles, was scored
as 1; class 3, which included fragments present in EcoRI/HpaII and absent in the EcoRI/MspI
profiles, was scored as 1; and finally, class 4, which included fragments absent in both
profiles, was scored as 0.
2.5. AFLP Analysis and Scoring
Samples were also analyzed using the Amplified Fragment Length Polymorphism
(AFLP) technique. A total of 250 ng DNA was digested with EcoRI/MseI restriction enzymes
according to Cervera et al. [67]. Following the ligation of adaptors, the resulting fragments
were used as a template for the pre-amplification, using an EcoRI + A/MseI + C primer
combination followed by a selective amplification using EcoRI + 3/MseI + 3 selection. Five
primer combinations were used: EcoRI + ATC/MseI + CAT, EcoRI + ATA/MseI + CAT, EcoRI
+ ACC/MseI + CAT, EcoRI + AAT/MseI + CCA, and EcoRI + ACA/MseI + CCA, (Sequences
of adapters and primers are listed in Supplementary Table S1). EcoRI + 3 selective primers
were labeled at their 5′ ends with fluorescent dye 800 IRDye to allow visualization of
the fragments on a Li-Cor 4300 DNA Analyzer as previously described for MSAP. The
data matrix was developed by scoring the presence (1) or absence (0) of each fragment in
each sample.
2.6. Statistical Analysis
Epigenetic and genetic differentiation was assessed using GenAlEx version 6.503
(Australian National University, Canberra, Australia) [68,69]. The Analysis of Molecular
Variance (AMOVA) allowed a hierarchical partitioning of the total epigenetic or genetic
variation estimated among the provenances or treatments, using a PhiP index, an analogue
of FST, (where PhiPT = VAP /(VWP + VAP ), VAP = Variance among the provenances or
treatments and VWP = Variance within the provenances or treatments), using 9999 random
permutations to test its significance. Locus-by-locus analyses were performed to determine
the significant and informative markers in terms of variability between the watering
regimes. Additionally, Principal Coordinate Analysis (PCoA) was carried out on a pairwise
genetic distance matrix to identify the main patterns within the epigenetic or genetic data.
To estimate the epigenetic and genetic diversity, we calculated the percentage of
polymorphic bands (P%), number of alleles (Na), number of effective alleles (Ne), Shannon’s
Forests 2022, 13, 1971
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diversity index (I) and expected heterozygosity (He) for the epigenetic (MSAP-MSP) and
genetic (MSAP-MIP and AFLPs) markers using GenAlEx version 6.503.
Additionally, Bayesian clustering analyses using Structure v.2.3.4 software (Pritchard
Lab, Stanford University, Stanford, CA, USA) [70,71] were performed to infer the epigenetic
and genetic structure of the analyzed individuals. We applied a burning time of 10,000 and
100,000 Markov Chain Monte Carlo repetitions with K values (number of populations) from
1 to 7. The best K was estimated using the delta k method [72] using Structure Harvester
software (CA University, Berkeley, CA, USA).
Mantel tests were applied to the distance matrices for MSP-MSAP and AFLP loci or
MIP-MSAP loci in order to establish the statistical correlations between the epigenetic and
genetic variability and, to the distance matrices for MIP-MSAP loci and AFLP loci to test
for a correlation between the genetic markers.
The effect of water stress was assessed from the water potential at sampling time.
ANOVA was applied to evaluate the effect of the population and watering regimes as
main factors.
3. Results
3.1. Epigenetic and Genetic Variability among Provenances
MSAP analysis of 60 beeches from Spanish (ES), German (DE) and Swedish (SE)
provenances, 20 beech per provenance that represent the latitudinal distribution of the
species, was performed in order to analyze the epigenetic and genetic variability.
3.1.1. Epigenetic Variability
MSAP analysis was performed to infer the variability of cytosine methylation throughout the genome, analyzing specific anonymous CCGG motifs. Three out of the 30 primer
combinations initially tested were selected based on the number of polymorphic markers and easy scoring. The selected MSAP primer combinations rendered 205 amplified
fragments (Table 2), of which 144 could be scored. A total of 83 markers out of 144
were classified as methylation-sensitive (MS), 97.59% and 2.41% of them identified as
methylation-sensitive polymorphic (MSP) and methylation-sensitive monomorphic (MSM)
markers, respectively. The remaining 61 markers were classified as methylation-insensitive
(MI), 55.74% and 44.26% identified as methylation-insensitive polymorphic (MIP), and
methylation-insensitive monomorphic (MIM) markers, respectively (Table 2).
Table 2. Number of MSAPs detected with the primer combinations used to analyze the seedlings
from Spanish, German and Swedish Fagus sylvatica provenances.
No. total markers
No. scorable markers
Methylation-insensitive markers (MI)
No. polymorphic markers (MIP)
No. monomorphic markers (MIM)
Methylation-sensitive fragments (MS)
No. polymorphic markers (MSP)
No. monomorphic markers (MSM)
HpaII/MspI-ATC
EcoRI-AAC
HpaII/MspI-ACT
EcoRI-ACG
HpaII/MspI-AAT
EcoRI-AAC
Total
64
49
72
47
69
48
205
144
13
9
10
10
11
8
34
27
27
0
25
2
29
0
81
2
The overall percentage of analyzed methylated restriction sites was estimated, ranging
from 32.0% of the total fragments in the Swedish provenance (SE) to 32.3% in the Spanish
provenance (ES) (Table 3). The percentage of full or hemi-methylated internal C, markers
present in EcoRI/MspI and absent in EcoRI/HpaII, was also very similar ranging from
30.7% of the total fragments in the ES to 31.1% in the German provenance (DE), while the
percentage of hemi-methylated external C, markers present in EcoRI/HpaII and absent in
EcoRI/MspI, was much lower, ranging from 0.9% in DE to 1.5% in ES.
Forests 2022, 13, 1971
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Table 3. Percentage of analyzed methylated restriction sites (mean values ± SD) in German (DE),
Spanish (ES), and Swedish (SE) provenances.
Full or hemi-methylated internal C
Hemi-methylated external C
Total
DE
ES
SE
31.1% ± 2.9%
0.9% ± 1.0%
32.1% ± 2.7%
30.7% ± 2.4%
1.5% ± 0.7%
32.3% ± 2.7%
30.8% ± 2.5%
1.2% ± 1.1%
32.0% ± 2.7%
Epigenetic diversity parameters, such as the average number of observed alleles (Na),
number of effective alleles (Ne), Shannon’s diversity index (I) and expected heterozygosity
(He), were lower in the ES than in the DE and SE provenances (Table 4a), with the DE and
SE showing similar values for all of them (Table 4a).
Table 4. Epigenetic (a) and genetic (b,c) diversity parameters estimated for individuals of three
provenances of Fagus sylvatica, Germany (DE), Spain (ES) and Sweden (SE), using MSAP-MSP (a),
MSAP-MIP (b) and AFLP (c) markers. No. loci = Number of loci, P% = Percentage of polymorphic
fragments, I = Shannon’s diversity index, Na = Number of alleles, Ne = Number of effective alleles,
He = Expected Heterozygosity, (mean values ± SD).
a)
Provenance
Sample size
No. loci
P%
Na
Ne
I
He
DE
ES
SE
20
19
20
81
81
81
75.31
67.90
75.31
1.519 ± 0.095
1.432 ± 0.096
1.543 ± 0.091
1.324 ± 0.038
1.268 ± 0.035
1.337 ± 0.038
0.313 ± 0.028
0.273 ± 0.027
0.322 ±0.028
0.200 ± 0.020
0.171 ± 0.019
0.207 ± 0.020
Provenance
Sample size
No. loci
P%
Na
Ne
I
He
DE
ES
SE
20
20
20
34
34
34
85.29
61.76
67.65
1.735 ± 0.114
1.235 ± 0.096
1.412 ± 0.153
1.355 ± 0.065
1.326 ± 0.064
1.319 ± 0.062
0.327 ± 0.045
0.289 ± 0.049
0.297 ±0.046
0.210 ± 0.033
0.191 ± 0.035
0.192 ± 0.033
Provenance
Sample size
No. loci
P%
Na
Ne
I
He
DE
ES
SE
20
19
20
105
105
105
87.62
65.71
74.29
1.810 ± 0.053
1.419 ± 0.083
1.562 ± 0.076
1.428 ± 0.034
1.369 ± 0.036
1.374 ± 0.033
0.397 ± 0.023
0.326 ± 0.027
0.353 ± 0.025
0.258 ± 0.017
0.216 ± 0.019
0.229 ± 0.018
b)
c)
An analysis of molecular variance (AMOVA) was carried out to explore the differentiation between the provenances. The analysis revealed a moderate–high epigenetic
differentiation among the provenances with an estimated PhiPT value of 0.156 (p = 0.0001):
Most (84%) of total epigenetic variation resided within the provenances, while 16% resided
among the analyzed provenances.
The distance matrix by provenances evidenced strong epigenetic differences among
them with all pairwise distances being statistically significant (p < 0.001). ES was the
provenance more epigenetically differentiated with pairwise epigenetic distances of 0.165
and 0.191 relative to the DE and SE populations, respectively. The pairwise epigenetic
distance between DE and SE was 0.112. The distance matrix between individuals was
subjected to a PCoA, where the first and second axes explained 29.18% and 20.03% of the
variance, respectively, and the individuals were clustered into three groups corresponding
with the DE, ES and SE provenances (Figure 1a).
Forests 2022, 13, 1971
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Figure 1. Principal Component Analyses (PCoA) of German (blue diamond), Spanish (red circles)
and Swedish (green triangles) provenances based on MSAP-MSP (a), MSAP-MIP (b) or AFLP (c). The
explained variance percentages for each coordinate are shown in brackets.
Epigenetic structure analysis of the three provenances using Structure software showed
that the best K using the delta K method was K = 2 (Figure 2a). For this K value, the individuals were clustered into two main groups: SE and DE provenances, and ES provenance.
For K = 3, the program sorted individuals into three groups which corresponded to the
three provenances sampled in the study (Figure 2a).
Forests 2022, 13, 1971
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Figure 2. Plot of delta K values and the population structure diagram of the Spanish (ES), Swedish (SE)
and German (DE) provenances using MSAP-MSP (a), MSAP-MIP (b), or AFLP (c).
3.1.2. Genetic Variability
MIP markers were uninformative with regard to sensitivity to methylation, but informative with respect to the degree of potential genetic polymorphism. MIP markers
allowed for the construction of a second binary matrix that was used to establish a proxy of
putative genetic differentiation between the individuals and provenances. The presence of
a fragment in both the EcoRI/HpaII and EcoRI/MspI profiles is associated with unmethylated cytosines at these CCGG site, and therefore, this type of fragment could be treated
as genetic. However, the analysis of MIP fragments must be interpreted carefully since
this class of fragments may contain not only true genetic fragments but also fully methylated mCmCGG sequences. To avoid this type of bias, the Amplified Fragment Length
Polymorphism technique (AFLP) was also used to analyze the differentiation between
provenances. The same 60 trees from DE, ES, and SE provenances were analyzed using two
primer combinations that revealed a total of 227 makers. From them, 180 markers were
finally scored, 105 of them (58.33%) were polymorphic (Table 5).
Table 5. Number of AFLPs detected with the primer combinations used to analyze the three
Fagus sylvatica provenances.
No.
No.
No.
No.
total markers
scorable markers
polymorphic markers
monomorphic markers
EcoRI + ATC
MseI + CAT
EcoRI + ATA
MseI + CAT
Total
121
90
51
39
106
90
54
36
227
180
105
75
The average number of observed alleles (Na), number of effective alleles (Ne), Shan36for provenances were consistent for
non’s (I), and expected heterozygosity (He), calculated
both genetic markers (MIPs and AFLPs) (Table 4b,c). ES presented the lowest values for all
parameters of genetic diversity except for the Ne for MIP markers (Table 4b,c). DE exhibited
Forests 2022, 13, 1971
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the highest values for all genetic diversity parameters indicating a higher genetic diversity
of this provenance originating from the core distribution of Fagus sylvatica (Table 4b,c).
The AMOVA revealed that genetic variation mainly occurred within provenances (86%
and 85% for MIP and AFLP markers, respectively), while the variation among the provenances was 14% and 15%, respectively. The estimated PhiPT value was 0.136 (p = 0.0001)
and 0.152 (p = 0.001) using MIPs and AFLPs, indicating a moderate differentiation.
The distance matrix by provenances shows significant genetic differences among them
for both MIP and AFLP markers. Similar to the epigenetic analysis (based on MSAP-MSPs),
ES was the provenance more differentiated using genetic markers (MIP and AFLP). The
PCoA analysis did not group the individuals in three separated clusters corresponding to
the three provenances (Figure 1b, 1c) but the ES provenance could be differentiated from
DE and SE provenances with AFLP markers. The first and second axes explained 24.27
and 19.22% of the variance using MIP markers, and 30.27 and 18.44% of the variance using
AFLP markers.
A structure analysis of the AFLP markers showed that the best K was K = 2 (Figure 2c).
As with the MSP markers, the individuals were clustered into two groups: SE and DE
provenances, and ES provenance. For K = 3, most individuals were grouped mainly into
three groups corresponding to the three studied provenances (Figure 2c). With the MIP
markers, the individuals could not be clustered into different groups (Figure 2b).
3.1.3. Mantel Test
A positive correlation was detected between the epigenetic distance (based on MSPs)
and the genetic distance estimated with MIPs or AFLPs (R = 0.172, p = 0.010 or R = 0.253,
p = 0.010, respectively). Additionally, a lower but significant correlation was found between
the genetic distances calculated with MIPs and AFLPs (R = 0.102, p = 0.020) (Supplementary
Figure S2).
3.2. Water Stress Response
In order to study the response to drought, we analyzed 54 seedlings from the Spanish
(ES) and an additional Swedish (SE) provenance, representing the latitudinal extremes of
the distribution range of the species.
3.2.1. Water Status of Seedlings
The watering effect was significant for the predawn water potential, Ψpd (p < 0.0001)
but not for the midday water potential, Ψmd (p >0.05 after ANOVA). The provenance
effect was not significant for either the water potential at predawn (Ψpd ), or for the water
potential at midday (Ψmd ) (p >0.05 after ANOVA). Specifically, after almost two months
of progressive withdrawal of watering, the WS seedlings showed a significant decrease in
Ψpd in comparison with the WW seedlings (Figure 3). There were no significant differences
between the two provenances, and seedlings from both provenances had a similar decrease
in Ψpd in response to water stress. In general, WS seedlings had slightly lower values of
Ψmd than the WW seedlings, but the differences were not statistically significant (Figure 3).
During the drought period, the soil moisture content was similar for both provenances in
each watering treatment according to the water potential measurements (see more details
on Sanchez-Gómez et al. [59]).
3.2.2. Epigenetic Analysis
MSAP analysis was performed in order to analyze the methylation status of the
cytosine residues in response to drought. With the aim of increasing the number of
polymorphic markers, a total of four MSAP primer combinations were selected based on
the number of polymorphic markers and easy scoring. Among the selected combinations,
EcoRI-ACG HpaII-ACT and EcoRI-AAC HpaII-AAT were the most and less informative
primer combinations, respectively. The four selected MSAP primer combinations rendered
tial at midday (Ψ
Forests 2022, 13, 1971
Ψ
crease in Ψ
ues of Ψ
11 of 21
a total number of 235 markers, of which 188 could be scored (Table 6): 109 markers were
classified as MS (105 MSPs and 4 MSMs) and 79 as MI (29 MIPs and 50 MIMs).
Figure 3. Predawn (top) and midday (bottom) water potential measured in well-watered (WW) and
water-stressed (WS) seedlings from Spanish (ES) and Swedish (SE) provenances.
Table 6. Number of MSAPs detected with the primer combinations used to analyze seedlings from
Spanish (ES) and Swedish (SE) Fagus sylvatica provenances subjected to different hydric regimes.
No. total markers
No. scorable markers
Methylation-insensitive markers (MI)
No. polymorphic markers (MIP)
No. monomorphic markers (MIM)
Methylation-sensitive fragments (MS)
No. polymorphic markers (MSP)
No. monomorphic markers (MSM)
HpaII/MspIAAT
EcoRI-AAC
HpaII/MspIACT
EcoRI-ACG
HpaII/MspIATC
EcoRI-AAC
HpaII/MspIACT
EcoRI-AAC
Total
48
30
63
59
60
54
64
45
235
188
2
7
10
16
16
12
1
15
29
50
21
0
29
4
26
0
29
0
105
4
The percentage of analyzed methylated restriction sites ranged between 31.7% of the
total fragments in ES-WS and 32.5% in both SE-WW and SE-WS (Table 7). The percentage
of full or hemi-methylated internal C ranged from 29.5% to 31% in ES-WW and SE-WS,
respectively, while the percentage of hemi-methylated external C ranged from 1.2% to 2.4%
in ES-WS and ES-WW, respectively. No significant differentiation between the WS and WW
plants was observed in the Spanish or Swedish provenance nor between the provenances.
The average number of observed alleles (Na), number of effective alleles (Ne), Shannon’s (I), and expected heterozygosity (He), for epigenetic markers (MSAP-MSP) was
similar for both the provenances and experimental treatments (Table 8a).
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Table 7. Percentage of analyzed methylated restriction sites (mean values ± SD) of well-watered
(WW) and water-stressed (WS) seedlings from Spanish (ES) and Swedish (SE) provenances.
Full or hemi-methylated internal C
Hemi-methylated external C
Total
SE-WW
SE-WS
ES-WW
ES-WS
30.9% ± 2.7%
1.6% ±1.4%
32.5% ± 2.9%
31.0% ± 2.7%
1.5% ± 1.1%
32.5% ± 2.7%
29.5% ± 2.1%
2.4% ± 1.7%
32.0% ± 2.8%
30.5% ± 2.6%
1.2% ± 1.1%
31.7% ± 2.8%
Table 8. Epigenetic (a) and genetic (b,c) diversity parameters estimated for well-watered (WW) and
water-stressed (WS) seedlings of Spanish (ES) and Swedish (SE) provenances using MSAP-MSP (a),
MSAP-MIP (b) and AFLP (c) markers. No. loci = Number of loci; P% = Percentage of polymorphics
fragments; I = Shannon’s diversity index; Na = Number of alleles; Ne = Number of effective alleles;
He = Expected Heterozygosity, (mean values ± SD).
a)
Provenance
Treatment
Sample
size
No. loci
P%
Na
Ne
I
He
SE
SE
ES
ES
WS
WW
WS
WW
13
13
14
11
104
104
104
104
74.04
65.38
66.35
75.00
1.519 ± 0.082
1.356 ± 0.090
1.346 ± 0.091
1.529 ± 0.082
1.335 ± 0.033
1.335 ± 0.036
1.331 ± 0.033
1.353 ± 0.035
0.321 ± 0.025
0.304 ± 0.027
0.311 ±0.026
0.331 ± 0.025
0.206 ± 0.018
0.199 ± 0.019
0.202 ± 0.018
0.214 ± 0.018
Provenance
Treatment
Sample
size
N loci
P%
Na
Ne
I
He
SE
SE
ES
ES
WS
WW
WS
WW
14
14
15
12
29
29
29
29
58.62
79.31
65.52
65.52
1.207 ± 0.182
1.586 ± 0.153
1.379 ± 0.168
1.379 ± 0.168
1.348 ± 0.066
1.413 ± 0.070
1.328 ± 0.069
1.369 ± 0.072
0.313 ± 0.053
0.370 ± 0.049
0.297 ± 0.051
0.322 ± 0.053
0.208 ± 0.037
0.243 ± 0.036
0.195 ± 0.037
0.214 ± 0.038
Provenance
Treatment
Sample
size
N loci
P%
Na
Ne
I
He
SE
SE
ES
ES
WS
WW
WS
WW
14
14
15
12
232
232
232
232
78.02
77.16
68.97
69.83
1.621 ± 0.049
1.603 ± 0.050
1.453 ± 0.056
1.487 ± 0.054
1.394 ± 0.023
1.359 ± 0.022
1.390 ± 0.024
1.373 ± 0.024
0.364 ± 0.017
0.346 ± 0.016
0.349 ± 0.018
0.339 ± 0.018
0.237 ± 0.012
0.222 ± 0.011
0.231 ± 0.013
0.223 ± 0.012
b)
c)
AMOVA based on PhiPT values indicated that most of the epigenetic diversity occurred within the provenances (82%), while the variability among the provenances contributed 18% when the ES-WW and SE-WW plants were compared. A PhiPT value of 0.180
revealed a significant differentiation between the provenances (p = 0.0001). The analysis of
the SE provenance showed that the total epigenetic variation occurred within treatments,
whereas 2% of the epigenetic variation was attributed to treatment in the ES provenance. A
total of 4 out of 105 MSPs were associated with water stress response in the ES provenance
(PhiPT per locus > 0.150, p < 0.05), and responsible for the 34% differentiation detected by
AMOVA between the WW and WS plants (PhiPT = 0.345, p = 0.0001).
The calculated distance by provenances evidenced a strong epigenetic differentiation
between the Swedish and Spanish provenances and a marginal differentiation between
treatments for the Spanish provenance (pairwise genetic distance = 0.022, p = 0.067). A
PCoA clustered the samples into two groups (Figure 4a), where the first and second axes
explained 17.52% and 7.48% of the variance, respectively. One group included the SEWW and SE-WD samples, while the other group integrated the ES samples with a higher
differentiation between the WW and WD plants. Similarly, Structure software also clustered
the individuals into two groups, the SE and ES provenances, regardless of the treatment
(data not shown).
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Figure 4. Principal Component Analyses (PCoA) of Spanish (red circles) and Swedish (green triangles)
provenances based on MSAP-MSP (a), MSAP-MIP (b), or AFLP (c). The explained variance percentages for each coordinate are shown in brackets. Well-watered (solid symbols) and water-stressed
(open symbols) seedlings.
3.2.3. Genetic Variation
To further explore the genetic relationships between the ES and SE provenances
subjected to drought, we increased the number of primer combinations. Both the MIPs and
AFLPs obtained with five primer combinations were used to assess the genetic variability
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of the samples. We identified 29 MIPs with MSAPs and 232 out of 352 scorable fragments
(66%) as polymorphic markers by AFLPs (Tables 6 and 9).
Table 9. Number of AFLPs detected with the primer combinations used to analyze the seedlings
from the Spanish and Swedish provenances subjected to different hydric regimes.
No.
No.
No.
No.
total markers
scorable markers
polymorphic markers
monomorphic markers
EcoRI + ATC
MseI + CAT
EcoRI + ATA
MseI + CAT
EcoRI-ACC
Mse-CAT
EcoRI-AAT
Mse-CCA
EcoRI-ACA
Mse-CCA
Total
124
101
78
23
136
84
57
27
46
41
26
15
65
61
31
30
81
66
41
25
452
352
232
120
The average number of observed alleles (Na), number of effective alleles (Ne), Shannon’s (I), and expected heterozygosity (He), were similar for both the provenances and
treatments within the provenances for both the MIP and AFLP markers (Table 8b,c). The
only exception was the Na estimated with the AFLPs that was slightly lower for the Spanish
provenances (Table 8c).
Although most genetic variation from AMOVA was attributed to being within provenances, a significant differentiation was observed between provenances. Thus, the value of
the differentiation index (PhiPT) between the SE and ES provenances was 0.208 (p = 0.0001)
for Ms and 0.162 (p = 0.001) for AFLPs.
A PCoA analysis using a genetic distance matrix based on the MIPs or AFLPs
grouped the individuals into two clusters corresponding with the ES and SE provenances
(Figure 4b,c). The first and second axes explained 20.88 and 11.68% of the variance using
MIPs, and 18.99 and 7.96% of the variance using AFLPs. These clearly differentiated groups
were confirmed using Structure software (data not shown).
3.2.4. Correlation between Genetic and Epigenetic Variability
Correlation between the genetic and epigenetic variability was explored using a Mantel test. There was a positive correlation (R = 0.252, p = 0.001) between the pairwise genetic
(AFLP) and epigenetic (MSAP-MSP) distance matrices while a marginally significant correlation (R = 0.126, p = 0.02) was detected between the genetic (MSAP-MIP) and epigenetic
(MSAP-MSP) distance matrices. Furthermore, we also detected a positive correlation between both genetic distance matrices assessed from the AFLPs and MSAP-MIPs (R = 0.384,
p = 0.001).
4. Discussion and Conclusions
During the last decades, patterns of genetic and epigenetic diversity in natural populations have been studied in different plant species [73,74]. Additional information is,
however, still required to disentangle their relative role in determining the adaptive capacity
of plants. Most epigenetic studies have focused on plant species of agronomic importance,
although in recent years studies have been carried out on forest species, which have important socio-economic and ecological value [10,13,14,17,35,43,75–80]. In this study, we
present the analysis of the genetic and epigenetic variation of three beech provenances that
represent the latitudinal range of distribution of the species, which have been previously
characterized at the metabolic and physiological levels [81,82]. Epigenetic variability of
Fagus sylvatica was previously assessed on provenances from North and Central Europe [35].
Our study revealed strong epigenetic differentiation among European beech populations
using MSAP markers, particularly separating central and northern populations from the
southern population. In contrast, the exposure to water withdrawn for 50 days did not
have a significant effect on epigenetic patterns in the studied provenances. Overall, these
results point to the role that DNA methylation may play in local adaptation of F. sylvatica
to environmental variation.
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The total percentage of methylated sites was approximately 32% considering the whole
data set, with very similar values across the provenances. Similar values have been found
in other forest tree species such as Populus tomentosa or P. simonii with 36.43% and 32.36%
of methylated sites, respectively. These two species also exhibited differences among populations [83,84]. In contrast, results for Fraxinus interspecific hybrids showed remarkably
lower values of percentage of methylated sites, from 20.12% to 24.61%, depending on the
genotype [85]. In conifers, differences between populations of Pinus sylvestris were not
significant when methylation levels were compared. Percentages depend on the organ
analyzed and the stage of development of the plant varying from 21.3% to 38.8% when
megagametophytes and embryos were studied [86]. In other species, total methylation
ranged from 13.50% to 44.70% in a full-sib family of Cupressus sempervirens L. [76], and
from 30.3% to 33.8% in Larix kaempferi intraspecific hybrids [87]. The methylation levels
were lower than in Pinus pinea populations (64.4%), a species characterized by very low
levels of genetic variation [77]. It is important to highlight that MSAP provides information
about cytosine methylation status at CCGG motives and different results may be obtained
using other massive techniques such as bisulfite sequencing. The percentages of full or
hemi-methylated internal C were much higher than percentages of hemi-methylated external C. This result, which supports Hrivnák et al. [35] observation in a previous work
with beech populations, has also been detected in other forest trees, such as Quercus lobata
and Q. ilex [88,89], Fraxinus mandshurica and F. americana [85], Ilex paraguariensis and
I. dumosaspecies [90] or Pinus pinea [77].
Diversity analyses revealed that the ES provenance showed lower values of epigenetic
and genetic diversity than the DE and SE provenances, which, despite their geographical
distance, showed similar values. Although the highest epigenetic variation was within the
provenances, the data showed that differences among populations explained 16% of the
epigenetic variation, a value similar to the among-population genetic variation observed
with AFLPs (15%) and MIPs (14%). Previous studies had already detected high levels of
genetic variation within populations, although lower levels were detected among beech
trees from different geographic origins [91]. This result is in line with the ecophysiological
studies focused on assessing intra-population variability in response to drought. Analysis
of half-siblings from different mother trees revealed a high degree of phenotypic differentiation among families for growth and functional traits [82,92]. Our analysis also revealed
significant epigenetic differentiation (PhiPT = 0.156), similar to the genetic differentiation
observed with AFLPs (PhiPT = 0.152) and slightly higher than with MIPs (PhiPT = 0.136).
Previous studies have found contrasting patterns of epigenetic differentiation across species.
Low epigenetic population differentiation and high genetic differentiation were detected in
Prunus avium [75], while higher epigenetic differentiation was detected within and between
mangrove populations from contrasting environments [78] as well as in valley oaks from
climate gradients [93]. These results align with the idea that epigenetic variation in natural
populations plays an important role in the local adaptation to different environments.
The grouping analysis based on PCoA and Structure resulted in three groups that
corresponded to the DE, SE and ES provenances or in two groups, one of them including the DE and SE provenances. A similar differentiation between the DE and SE, and
the ES provenance had been previously observed in the relative concentration of several
metabolites [82]. DE and SE are two provenances located in Central and Northern Europe,
with a markedly lower annual temperature than the ES provenance. Gugger et al. [88],
using reduced-representation bisulphite sequencing data, identified 43 single-methylation
variants that were significantly associated with climate variables, most of them with mean
maximum temperature. These results also suggested that DNA methylation could be
involved in local adaptation of plant populations to their environments. In addition,
Hrivnák et al. [35] observed that the longitude of beech populations significantly correlated with cytosine methylation levels, identifying MSAPs correlating with environmental
variables, that may suggest that weather or the photoperiod during embryogenesis could
determine the methylation status of specific loci. In Norway spruce, a significant number
Forests 2022, 13, 1971
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of genes encoding epigenetic regulators involved in DNA and histone methylation, as well
as sRNAs were differentially expressed during embryogenesis, acting in the epigenetic
memory of temperature during this process [94]. Considering that the epigenetic marks
can be inherited across generations, they could be associated with maternal effects or with
lasting effects of exposure to environmental conditions. The analysis of progenies from
trees located in natural mangrove populations in a common garden experiment revealed
that, 25% of epigenetic differences could be explained by the maternal effect [95].
In this study, we also aimed to analyze the effect of moderate water stress on cytosine
methylation dynamics in beeches from two contrasting latitudinal provenances (SE and
ES). The Swedish provenance, from a region with a low evaporative demand, regular
rainfall distribution and higher availability of groundwater, is particularly sensitive to
water deficit [59]. In contrast, the Spanish provenance, which is located at the southern
limit of beech’s distribution, is subjected to frequent and severe multi-year and recurrent
droughts, combined with heatwaves leading to a high evaporative demand. The analyses
of the percentage of DNA methylation revealed no significant differentiation between
water-stressed and well-watered plants. This result is in contrast with the increase in DNA
methylation level reported in different plant species grown under water deficit, such as
in Quercus ilex [89], Populus trichocarpa [44], Fraxinus [85] and Hippophae rhamnoides [96]; or
decreased DNA methylation levels as found in Lolium perenne [97] and Vicia faba L [98]; or
genotype-dependent variations as observed in Populus euramericana [43]. The analyses of
epigenetic variation showed that most of the variation was attributed to the origin of the
provenances and only 2% of the variation was explained by the watering regime in the
ES population, mainly associated with 4 out of the 105 MSP loci. Although the number
of total loci analyzed is limited, given the genome-wide nature of the MSAPs, a higher
coverage would reveal additional loci whose methylation status is associated with the
water status of beech trees. This evidence for local adaptation to drought is in line with the
higher variation in stress-related genes expression observed among beech progenies from
different populations rather than in the drought response [91], which could be associated
to the development, in xeric populations, of different functional strategies to face the low
water availability than those from mesic populations.
Duration and intensity are important factors in plant stress response. It is possible that
longer intensities and/or periods of exposure may trigger longer-term responses, causing a
higher number of changes as observed when analyzing the MSAP patterns of Quercus ilex
subjected to drought for 12 years [89]. Additionally, recurrent exposure to extreme events,
such as drought, may also elicit a very different response compared to single sporadic
exposure [99].
This study provides new data about the genetic and epigenetic variability of beech
provenances from the latitudinal range of the species. The results on cytosine methylation
dynamics of contrasting provenances revealed that within the provenance, variation is
stronger than that associated with drought-induced responses. Further studies are required
to improve our understanding about how drought response can be modified by its intensity,
duration and recurrence. Additionally, our study focused on two-year-old seedlings, it
would be important to explore the response of adult trees as well as the response of
their progenies in order to acquire information not only about somatic memory but also
intergenerational memory.
Supplementary Materials: The following supporting information can be downloaded at: https:
//www.mdpi.com/article/10.3390/f13121971/s1, Table S1: Sequences of adapters and primers used
in the MSAP and AFLP assay; Figure S1: Scoring and interpretation of different banding patterns
obtained in the MSAP assay; Figure S2: Graphical representation of the Mantel test results between
epigenetic distance and genetic distance.
Forests 2022, 13, 1971
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Author Contributions: Conceptualization, M.Á.G., I.A. and M.T.C.; methodology, M.Á.G. and M.T.C.;
formal analysis, M.Á.G. and J.A.R.-V.; investigation, M.Á.G., N.d.M., M.D.V. and L.M.D.; resources,
D.S.-G., J.A.M. and I.A.; writing—original draft preparation, M.Á.G.; writing—review and editing,
M.Á.G., D.S.-G., J.A.R.-V., N.d.M., I.A. and M.T.C.; visualization, M.Á.G.; supervision, M.Á.G. and
M.T.C.; project administration, M.Á.G.; funding acquisition, I.A. and M.T.C. All authors have read
and agreed to the published version of the manuscript.
Funding: This research was funded by the Spanish Ministry of Science and Innovation (AGL201457762-R and AGl2011-25365).
Data Availability Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design
of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or
in the decision to publish the results.
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