Next Article in Journal
Automated In Situ Seed Variety Identification via Deep Learning: A Case Study in Chickpea
Next Article in Special Issue
OMICs, Epigenetics, and Genome Editing Techniques for Food and Nutritional Security
Previous Article in Journal
Identifying SSR Markers Related to Seed Fatty Acid Content in Perilla Crop (Perilla frutescens L.)
Previous Article in Special Issue
Effect of Drought Stress on Capsaicin and Antioxidant Contents in Pepper Genotypes at Reproductive Stage
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Plants
Volume 10
Issue 7
10.3390/plants10071405
plants-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Genome Wide MeDIP-Seq Profiling of Wild and Cultivated Olives Trees Suggests DNA Methylation Fingerprint on the Sensory Quality of Olive Oil

by
Oussama Badad
1,2,
Naoufal Lakhssassi
1,
Nabil Zaid
2,
Abdelhalim El Baze
1,
Younes Zaid
2,3,
Jonas Meksem
4,
David A Lightfoot
1,
Huseyin Tombuloglu
5,
El Houcine Zaid
2,
Turgay Unver
6,* and
Khalid Meksem
1,*
1
Department of Plant, Soil and Agricultural Systems, Southern Illinois University, Carbondale, IL 62901, USA
2
Department of Biology, Faculty of Sciences, Mohammed V University, Rabat 10000, Morocco
3
Research Center, Abulcasis University of Health Sciences, Rabat 10000, Morocco
4
Trinity College of Arts and Sciences, Duke University, Durham, NC 27708, USA
5
Department of Genetics Research, Institute for Research and Medical Consultations (IRMC), Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
6
Ficus Biotechnology, Ostim OSB Mah, 100. Yil Blv, No:55, Yenimahalle, Ankara 06000, Turkey
*
Authors to whom correspondence should be addressed.
Plants 2021, 10(7), 1405; https://doi.org/10.3390/plants10071405
Submission received: 1 May 2021 / Revised: 3 July 2021 / Accepted: 5 July 2021 / Published: 9 July 2021
(This article belongs to the Collection OMICs, Epigenetics and Genome Editing Techniques for Food and Nutritional Security)
Browse Figures
Versions Notes

Abstract

:
Secondary metabolites are particularly important to humans due to their pharmaceutical properties. Moreover, secondary metabolites are key compounds in climate change adaptation in long-living trees. Recently, it has been described that the domestication of Olea subspecies had no major selection signature on coding variants and was mainly related to changes in gene expression. In addition, the phenotypic plasticity in Olea subspecies was linked to the activation of transposable elements in the genes neighboring. Here, we investigated the imprint of DNA methylation in the unassigned fraction of the phenotypic plasticity of the Olea subspecies, using methylated DNA immuno-precipitation sequencing (MeDIP-seq) for a high-resolution genome-wide DNA methylation profiling of leaves and fruits during fruit development in wild and cultivated olives from Turkey. Notably, the methylation profiling showed a differential DNA methylation in secondary metabolism responsible for the sensory quality of olive oil. Here, we highlight for the first time the imprint of DNA methylation in modulating the activity of the Linoleate 9S lipoxygenase in the biosynthesis of volatile aromatic compounds. Unprecedently, the current study reveals the methylation status of the olive genome during fruit ripening.

1. Introduction

Olive (Olea europaea) oil is a major component of the Mediterranean diet and is associated with multiple health benefits. Although extra virgin olive oil (EVOO) is primarily made of triacylglycerols, an abundance of phenolic and volatile compounds are also present [1]. Phenolic compounds are secondary plant metabolites, a major group of plant compounds chemically characterized by the presence of one or more aromatic rings [2]. The olive tree (O. europaea) produces a large arsenal of polyphenols that includes phenylpropanoids, terpenoids, and the most important and abundant subclass of phenolic compounds in olive oil: the secoiridoids such as oleuropein and its derivatives. The polyphenols in olive oil have multiple pharmaceutical properties such as fighting inflammation, coronary heart diseases, and several types of cancers [3]. In Turkish groves, particularly in the Aegean coast, Ayvalik cv is the most grown cultivar and is used mainly for oil production for its sensory qualities. Ayvalik cv olive oil has been extensively characterized and is appreciated for its mild fruity flavor due to low phenolic content varying from 106 to 296 mg/kg [4,5]. In contrast, oil extracted from wild olives is less encountered because of the bitterness and peppery taste caused by its high volatile aromatic and phenolic content. The analysis of wild olive oil from Tunisia, Algeria, Portugal, and Spain showed that their total phenolic content varies from 340 to 870 mg/kg [6,7,8,9]. In a genetic diversity study on wild olives and Ayvalik cv from the Aegean region of Izmir, Ayvalik cv showed a similarity of 97% with the wild olives [10]. The results from this study raised the question about the process by which genetically close subspecies can have a significant difference in their phenotypes, mainly, their observed phenolic composition in this case.
After the release of the first assembled and annotated chromosome level wild olive (Olea europaea ssp. europaea var. sylvestris) genome sequence [11], which uncovered the genetic code behind the health benefits of olive oil. The importance of the olive tree in the Mediterranean diet and economy raised the interest to explore beyond the boundaries of the DNA code. Interestingly, due to the siRNA extraordinary regulation of the fatty acid desaturase-2 (FAD2) gene family expression in favor of the accumulation of the oleic acid in the olive oil [11], several questions were raised about the possible existence of another type of epigenetic regulation: DNA methylation for instance. Notably, epigenetic regulation is important for environmental adaptation by modulating gene expression as it has been suggested to accelerate adaptive responses to selection process [12,13,14].
The genetic diversity of olive has been extensively investigated. In earlier studies, olive cultivars were mainly clustered based on agronomical traits such as size, the shape of fruits, pits, leaves, general stature of the tree, oil, and polyphenolic content. With the current advance in molecular biology and sequencing technologies, the scientific community dug deeper to understand other aspects of the genetic diversity using molecular markers, beginning with random amplified polymorphic DNA (RAPD) [15], chloroplastic DNA markers [16], mitochondrial DNA and RAPD [17], allozyme variation [18], amplified fragment length polymorphism (AFLP) [19], and simple-sequence repeats (SSR) [20]. Recently, Besnard et al. have revealed the presence of three main lineages of pre-Quaternary origin by performing the phylogeographic and Bayesian molecular dating analyses based on plastid genome profiling of wild and cultivated genotypes [21]. Moreover, an evolutionary transcriptomic study on wild and cultivated olive trees showed no major signatures of selection on coding variants in addition to weak signals that are primarily affected by transcription factors. Interestingly the phylogenetic analysis based on gene expression could not discriminate the wild and cultivated accessions from the eastern part of the Mediterranean including the Turkish accessions [22]. Furthermore, the transposable elements activity in the olive genome was shown to be involved in generating genetic variability in cultivated olives [23].
Epigenetics is a word coined by Waddington in 1942, defined by the inherited somatic changes that are not associated with changes in DNA sequences [24]. DNA methylation is one of the most studied epigenetic marks that can be inherited during cell division [25], and can mediate epigenetic regulation of gene expression. This regulation is due to the recruitment of proteins involved in gene repression or inhibition of the binding of transcription factors to DNA [26]. Methylation of cytosine residues in DNA is enzymatically catalyzed by DNA methyltransferases, which transfer a methyl group from S-adenosyl-L-methionine to the 5-position [27]. DNA methylation occurs in different genomic features including CpG islands, intergenic regions, gene bodies, and gene promoters for different functionalities. For instance, methylation of transcription binding sites leading to a suppression of gene expression can lead to a higher level of gene expression when the methylation is located in the gene body [28]. The evolution of NGS based technologies such as endonuclease digestion and bisulfite conversion made genome-wide DNA methylation mapping pretty feasible, but it remains relatively expensive. Affinity enrichment analysis such as MeDIP-seq Generates unbiased, cost-effective, and full-genome methylation levels without the limitations of restriction sites or CpG islands. To date, DNA methylation has been studied in many plant species, including algae [29], cereal crops [30], vegetables [31,32,33]; however, no studies were conducted on olive trees.
Prominent evidence suggests that DNA methylation plays an important role in the ripening of climacteric fruits. In tomatoes (Solanum lycopersicum), the genome undergoes a global decrease in methylation levels during ripening due to the increased expression of DNA demethylases [34]. The downregulation of the RdDM gene during fruit ripening in non-climacteric strawberries (Fragaria ananassa) resulted in ripe fruits with a lower DNA methylation level than immature fruits, suggesting a decrease in DNA methylation during ripening of non-climacteric fruits [35]. Recently, a study on DNA methylation in orange (Citrus sinensis) a non-climacteric fruit showed a global increase of DNA methylation with fruit ripening. These previous studies raised the question about whether or not the DNA methylation behavior during fruit ripening is related to the fruit ripening mechanism.
In addition to DNA methylation, phenolic and aromatic volatile compounds have been involved in ripening. In apple (Malus x domestica), 6 out of 22 putative LOX genes are expressed in a ripening dependent manner. The previous study showed that the activity of 9-LOX gene was related to linoleic and linolenic acids hydroperoxidation: a crucial step in the biogenesis of six-carbon volatile aldehydes, which are major constituents of the aroma in extra virgin olive oil (EVOO) [36]. In pepper (Capsicum annuum), 9-LOX (CaLOX1) gene, encodes a 9-specific lipoxygenase that catalyzes the hydroperoxidation of linoleic acid [37]. In olive, two lipoxygenases are characterized and at least three copies of Oep1LOX2 and one copy of Oep2LOX2 are present in the olive genome [38]. Besides volatile compounds, polyphenols play a major role in fruit defense during early ripening and also provide characteristic color (anthocyanins) to ripened fruits [39]. Phenolic content in olive fruits is high during early maturation stage and decreases to reach the lowest when fruits are ripe and ready to be harvested. The phenolic content is modulated by the activity of Peroxidase (POX), β-glucosidase (GLU) gene families [40]. Interestingly the beta glucosidase gene family gene expression has been described as high in early maturation stage and decrease with fruit ripening [41].
The current study aims to elucidate and bring more insight into DNA methylation dynamic and its fingerprint on the important properties of olives and their by-product by comparing the landscape between wild and cultivated olive trees.

2. Results

2.1. Evolution of DNA Methylation Landscape across Olive Tree Tissues

To investigate the evolution of DNA methylation landscape during fruit ripening across tissues (leaves and fruits) in the wild and cultivated olive trees, the differential methylation in different genomic features including 1 KB promoter, untranslated regions (UTRs), introns, and exons were analyzed. The results show that the global levels of methylation in the leaves were higher for all studied genomic features when compared to the fruit in both cultivated and wild olives during fruit ripening (Figure S1A–D).
To further explore the relationship between DNA methylation behavior and ripening in both cultivated and wild olives. The difference in methylation status in leaves and fruits between different maturity stages was called using MACS2. The results showed a global decrease in methylation level in the fruit with ripening for both wild and cultivated olives including all 23 olive chromosomes. Interestingly the hypomethylation was uniform in the wild Olea europaea ssp. europaea var. sylvestris chromosomes where all the 23 pairs manifested a decrease in methylation level unlike the cultivated Ayvalik cv (Figure S2). Intriguingly, the hypomethylation with fruit ripening was significant in the wild Olea europaea ssp. europaea var. sylvestris when compared to the cultivated Ayvalik cv (Figure S3A,B). However, DNA methylation manifested a different trend in the leaves, where a global increase in methylation level was observed in the wild and cultivated leaf samples (Figure S3C,D).

2.2. Domestication Fingerprint on DNA Methylation Landscape

In order to bring insight into the domestication fingerprint on DNA methylation in Olea subspecies in the Aegean region, the methylomes of the cultivated and wild olives were compared for both leaves and fruits in July (early maturity phase) and November (advanced maturity phase). When comparing the methylation profiles of the fruits in early maturation stage, the global methylation level was shown to be relatively higher in the cultivated Ayvalik cv for all the genomic features except around the transcription termination site (Figure S4A). During advanced fruit maturation stage, the methylation manifested an opposite behavior and became higher in the wild olives in all genomic features (Figure S4B). In the early maturation phase, no major significant difference in global levels of methylation were observed in the leaves. However, differences were observed in the distribution of methylated regions across the genomic features. Interestingly, in July, the level of methylation was higher in the transcription regulatory regions (promoter, TSS, and TTS) of the wild Olea europaea ssp. europaea var. sylvestris, while the methylation of gene body (intron and exon) was higher in the cultivated Ayvalik cv (Figure S4C). In November, the methylation level in the leaves of the wild olives was significantly higher in all genomic features (including TSS, TTS, intron, and exon) when compared to the cultivated Ayvalik cv (Figure S4D).

2.3. Functional Enrichment Analysis for Genes Associated with Differentially Methylated Regions

To examine the potential functionality of genes associated with methylated regions in the cultivated Ayvalik cv and Olea europaea ssp. europaea var. Sylvestris genomes, enrichment analysis for gene ontology terms (molecular function, cellular component, and biological process) and KEGG enriched pathways were performed using HOMER (Table S4).
In the fruit samples, the results showed that genes associated with methylated regions were mostly enriched in gene ontology terms related to the following molecular function and biological processes: ripening of non-climacteric fruit (methyl jasmonate methylesterase activity, jasmonate O–methyltransferase activity), binding (nucleic acid binding, ATP binding, U3 snoRNA binding), and transport activity (mRNA transport, mitochondrial pyruvate transmembrane transport). To gain more insights into DNA methylation’s role in modulating important metabolic activity, KEGG enrichment analysis revealed the potential involvement of genes associated with methylated regions in six major categories of metabolism pathways, including amino acid metabolism, secondary metabolite metabolism (steroid, and phenylpropanoid), carbohydrate metabolism, energy metabolism (photosynthesis), lipid metabolism (alpha–Linolenic acid metabolism, Linoleic acid metabolism, arachidonic acid metabolism, glycerolipids, and sphingolipid), and metabolism of co-factors and vitamins (Figure 1). Due to the high number of entities, only the fifteen most enriched pathways are shown in the GO bar charts and KEGG enrichment scatter plots.
In the leaf samples, the majority of genes associated with methylated regions were enriched in gene ontology terms related to transcriptional activity, amino acid metabolism, and transport activity (Figure 2A,C). The KEGG enrichment analysis (Figure 2B,D) showed the potential involvement of the majority of genes associated with methylated regions in secondary metabolic pathways especially in some of the most important secondary metabolisms in olives including phenylpropanoid, flavonoid, Stilbenoid, and sesquiterpenoid and triterpenoid biosynthesis. We observed an increase of differentially methylated genes number with the fruit maturity as well as the significance of the test.

2.4. Comparative Methylated Promoter Analysis between Wild and Cultivated Olives

Putative genes involved in fatty acid and volatile aromatic compounds metabolism were retrieved from the literature [11,36] and mapped against the wild olive genome annotation database to extract methylated gene IDs.
The alignment of the wild Olea europaea ssp. europaea var. sylvestris methylated genes (1K promoter) against the cultivated Ayvalik cv assembly provided by the international olive genome consortium resulted in alignment identities ranging from 95% for a putative fatty acid desaturase-3 (Genbank ID MZ361724) to 99% for putative linoleate 9S-lipoxygenase (Genbank ID MZ361723). Pairwise alignment available in (Additional file S1). The results showed a conserved sequence of the methylation window including 24 bp flanking the summit of the peak for linoleate 9S-lipoxygenase and therefore, the conservation of the 1 kb promoter cis-elements between wild and cultivated Turkish olives (Figure 3A) (cis-elements available in the (Table S5).
In the other hand, the putative FAD3 promoter sequence pairwise alignment showed the presence of multiple SNPs in addition to an insertion of a 12 nucleotides “TACTCTCTAACC” sequence in the Ayvalik cv FAD3 promoter (Figure 3B) causing gain of new and loss of ancestral cis-elements (Table S6).

2.5. Metabolic Profiling of Ayvalik Cv and Wild Olea europaea ssp. europaea var. sylvestris

The gas chromatography analysis revealed a slight difference in the most important fatty acids including oleic acid (C18:1), linoleic acid (C18:2), and linolenic acid (C18:3) content. On the other hand, the HPLC-UV and the NMR analysis showed a significant difference in the total phenolic content between Ayvalik cv and the wild olive oil due to the high amount of oleuropein derivatives in the wild EVOO (Table 1).

3. Discussion

DNA methylation and secondary metabolites are key components in constantly changing environment adaption for long-living trees and play an eminent role in fleshy fruit ripening. It has been reported that the genome of non-climacteric fruits undergoes a global decrease of methylation levels during fruit ripening, such as in strawberries [35], while an opposite global increase of DNA methylation was observed in ripened orange fruits [42]. To bring more insight into the evolutionary landscape of DNA methylation in non-climacteric fruits ripening, we studied and compared the genome wide methylation profiling of wild and cultivated olives from turkey in two fruit maturation stages (Figure 4).

3.1. Differential Methylation across Tissues

To date, most available studies on methylation focus on comparing different vegetative tissues like leaves, shoots, roots, cotyledons, and inflorescence, but little is known about fruit’s comparative methylation. Previous studies have only reported high levels of methylation in vegetative organs in a small set of plants including the plant model Arabidopsis thaliana, tomatoes, and Silene latifolia [43,44,45]. The results showed a higher methylation level in the leaves compared to the fruit in both wild Olea europaea ssp. europaea var. sylvestris and cultivated olive (Figure S2).
Since the wild Olea europaea ssp. europaea var. sylvestris and Ayvalik cv manifested the same methylation behavior with ripening, DNA methyltransferase and demethylases gene expressions between July and November were extracted from the wild Olea europaea ssp. europaea var. sylvestris differential gene expression data in fruit and leaves between July and November [11]. The results showed the induction of 269 methyltransferases in the leaves (Figure S5, Additional file S2), compared to only 164 upregulated methyltransferases in the fruits (Figure S6, Additional file S3). This is consistent with previous studies showing that the global methylation levels are higher in vegetative tissues [46].

3.2. Global Level of Methylation during Fruit Ripening

DNA methylation plays an important role in the ripening of fleshy fruit such as S. lycopersicum (tomatoes), F. ananassa (strawberries), and C. sinensis (oranges) [32,35,42]. The methylation landscape of non-climacteric fruit genomes however is still debatable. Data shown in (Figure S4) revealed a global decrease of DNA methylation during fruit ripening for both the cultivated and wild ancestor Olea europaea ssp. europaea var. sylvestris. The observed decrease of methylation levels is most likely due to the upregulation of 24 demethylase genes in the Olea europaea ssp. europaea var. sylvestris fruit (Figure S7 and Additional file S4). These results are in accordance with previous studies in S. lycopersicum [47] and F. ananassa [35]. Meanwhile, the C. sinensis genome manifested a global increase in DNA methylation during fruit ripening [42]. Unlike the fruit, the level of methylation in the leaves during ripening manifested a considerable global increase. This hypermethylation associated with ripening is most likely due to the upregulation of a large number of methyltransferases (up to 269) (Figure S5).

3.3. Differential DNA Methylation Potential Role in the Sensory and Organoleptic Properties of Olive Oil

3.3.1. Genes Involved in Polyunsaturated Fatty Acids Metabolism and Their Derivatives Volatile Compounds

The current study highlights the potential role of DNA methylation as an important component in phenotypic plasticity in olives trees. Oleic, linoleic, and linolenic acids are the major mono- and polyunsaturated fatty acids in extra virgin olive oil (EVOO). EVOO with higher levels of omega-9, omega-3, and lower levels of omega-6 are highly valued for their aroma and their health benefits to humans in fighting inflammation, cancer, and coronary heart conditions. To date, the characterization of FAD3 gene family activity in olive has not been described yet.
The DNA methylation of gene promoter’s rich in cis-regulatory elements and TF binding sites were strictly linked to gene expression repression. It has also been shown that DNA methylation surrounding the transcription starting site (TSS) is more closely linked to transcriptional silencing [48]. The functional analysis of methylated regions in the fruit samples showed a methylation in the promoter region (−313 bp) ahead of the transcription starting site (TSS) of a putative fatty acid desaturase (FAD3) in Ayvalik cv (Figure 3B, Additional file S5). This enzyme is responsible for the desaturation of linoleic acid into linolenic acid in the oil biosynthesis pathway. In fact, the absence of methylation the FAD3 gene promoter might explain the observed increase of linolenic acid content in the wild Olea europaea ssp. europaea var. sylvestris when compared to the cultivated Ayvalik cv (Table 1).
The sensory quality and aroma of EVOO depends on the biogenesis of volatile aromatic compounds, especially the fatty acid six-carbon aldehyde derivatives from linoleic and linolenic acids in the lipoxygenase pathway. Linoleate 9S-lipoxygenase (9-LOX; oxygen oxidoreductase) is a non-heme iron-containing enzyme that catalyzes the oxygenation of the 1,4-pentadiene sequence of polyunsaturated fatty acids to produce their corresponding hydroperoxides [36,49]. Linoleate 9S-lipoxygenase uses linoleic and linolenic acids as a substrate to form the ∆-9 hydroperoxide, which are the precursor of unsaturated six-carbon aldehydes including 2(E)-hexenal. The latter is the most prevalent constituent of olive oil aroma and responsible for the leafy green and peppery taste [50]. It has been described that the lipoxygenase activity is higher in early fruit maturation stages (15 weeks after anthesis) and decrease in advanced maturation stages (35 weeks) when the fruit are ripe and ready for harvest [51]. The methylation profiling of putative Linoleate 9S-lipoxygenase in both cultivated and wild olive fruits showed a methylation of the promoter of a putative linoleate 9S-lipoxygenase (−205 bp upstream) in early maturation stage for the cultivar Ayvalik cv (Additional file S5). Since the lipoxygenases are highly expressed in early maturation stages in the wild Olea europaea ssp. europaea var. sylvestris (Additional file S6), the potential silencing of one of Ayvalik cv lipoxygenase’s activity in early maturation due to its promoter methylation could potentially explain the observed difference in the hydroperoxidation of linoleic and linolenic acid to form their derivative volatile compounds, leading to differences in oil aroma between wild and cultivated olives. Moreover, the lower content of linoleic acid observed in the wild Olea europaea ssp. europaea var. sylvestris (9.08%), when compared to 10.8% in Ayvalik cv (Table 1), could be explained by the increased hydroperoxidation of linoleic acid as the substrate of preference to form its derivative 2(E)-hexenal. These results are consistent with previous studies on enzymatic oxidation of olive oil through the lipoxygenase pathway [51,52].

3.3.2. Differential Methylation in Putative Genes Involved in Phenolic Compound Metabolism in EVOO

The phenolic composition of olive fruits and derived EVOOs is affected by many factors including cultivar, fruit development, climate conditions, and cultural practices [53,54,55]. EVOO from wild Olea europaea ssp. europaea var. sylvestris is characterized by a pungent taste due to the higher phenolic content when compared to the oil extracted from cultivars [6,8,9,56,57]. Several studies have focused on changes in the phenolics composition and content during fruit development in cultivated olives [58,59,60]. The total phenolic content is higher in immature drupes and gradually decreases during fruit development to reach its lowest level when fruits are ripe and ready for harvest in November [61,62,63,64]. The GLU expression is strictly high in the early maturation stages and might be downregulated whenever a lower availability of oleuropein occurs with fruit ripening [60]. In olives the beta-glucosidase (OeGLU) was also shown to have a high affinity and substrate specificity to oleuropein and plays a major role in its degradation to the aglycone form [65]. In addition, (OeGLU) has been demonstrated to play a central role in determining the phenolic content of olive oil [41]. In attempt to bring insight into the potential involvement of DNA methylation in the phenolic content in olive oil, we investigated the methylation status of a well characterized OeGLU (GenBank: AY083162.1) a beta glucosidase gene involved in phenolic compounds metabolism [66,67]. The DNA methylation profiling during fruit maturation did not manifest any differential in the methylation status of the OeGLU gene between the wild and cultivated olives. These results join the hypothesis from a previous study on cultivated olives OeGLU transcriptional activity and Oleuropein content, where the low content of oleuropein in cultivated olives was linked to differences in the regulation of enzymes involved in its biosynthesis rather than in its degradation [60]. These results raise the question about the possibility of a copy number variation in genes involved in secoiroids biosynthesis pathway that could explain the significant difference in the phenolic content between wild and cultivated olives.

3.4. Domestication Fingerprint on Cis-Elements Modulating Genes Activity Involved in Sensory Quality of Olive Oil

To date, domestication studies focused mainly on coding regions of high interest to the olive industry. It has been shown that the domestication had a moderate consequence on the coding sequences, and the genetic diversity was mostly functional rather than structural due to the differential in gene expression [22]. The phenotypic plasticity was also linked to the transposable element’s activation around coding genes as a result of vegetative propagation over 5000 years on millions of acres across the Mediterranean coasts [23]. DNA methylation’s role as a regulator of secondary metabolites has been largely overlooked. The comparative promoter analysis showed a weak signal of domestication on the promoter sequences of the linoleate 9S-lipoxygenase with an identity of 99% between the wild and cultivated olives. The minor presence of SNPs has not affected the cis-regulatory elements surrounding the methylation site (Tables S5 and S6). Altogether, these results underline the potential role of DNA methylation in the observed difference in volatile compounds responsible for the sensory quality of EVOO between wild and cultivated olives. These results are supporting the studies on Lonicera japonica [68], Rorippa nasturtium var. aquaticum [69], and Salvia miltiorrhiza [70], where DNA methylation was first described as a regulator of phenolic acids biosynthesis.
In contrast, the domestication through selection and vegetative propagation of olives affected the putative FAD3 gene promoter, introducing multiple SNPs and a 12 nucleotides sequence insertion in the methylation site. This insertion led to the gain of new cis-elements and the loss of ancestral ones between the wild and cultivated olive trees (Table S6).
Therefore, the difference in linoleic and linolenic acids content between Olea europaea ssp. europaea var. sylvestris and Ayvalik cv are most likely due to the observed differences in cis-elements in the FAD3 promoter, in addition to the peroxidation of the linoleic and linolenic acids in the lipoxygenase pathway to form the six carbon volatile compounds.

4. Materials and Methods

4.1. Sample Preparation: DNA Extraction and Quantification

Wild Olea europaea ssp. europaea var. sylvestris “karadelice” in Turkish and Ayvalik cv were collected from the national germplasm collection, in Kayadibi-Izmir province Turkey. Leaves and fruits were collected in July (early maturity stage) and November (advance maturity stage) in 2014 and stored at −80 °C. The genomic DNA was isolated using a commercial kit (DNeasy Plant Maxi Kit; Qiagen Inc., Valencia, CA, USA). Following the manufacturer’s instructions. After DNA extraction, genomic DNA quantification was carried out by Qubit Fluorometer (Thermo Scientific). The DNA was fragmented by sonication using diagenode bioruptor to meet the BGI genomic DNA library preparation requirements: briefly, 10 μg/μL was used in 6 cycles of 15 s On and 90 s Off in cold water generating 300 bp fragments. The fragmented DNA was end-repaired into dA-tailed fragments using Taq polymerase (active at 72 °C for 20 min).

4.2. Immunoprecipitated DNA Sequencing, Data Quality Control, and Read Alignment

The immunoprecipitation assay was conducted as previously described by [71]. Briefly, 10 μg/μL of sonicated DNA was diluted in TE buffer. The diluted DNA was denatured and immediately cooled on ice; after cooling, the DNA was incubated with an Isotype IgG1 monoclonal 5mC Antibody (Epigentek Group Inc., Farmingdale, NY, USA) for 2 h at 4 °C. Dynabeads were then added to the immunoprecipitation reaction tubes and incubated for 2 h at 4 °C. After digestion, the proteinase K was added, and the reaction tube was incubated one last time for 3 h at 50 °C. At the end, the immuno-precipitated fragments were extracted with phenol/chloroform, then precipitated with NaCl (20 μL NaCl 5 M), glycogen (1 μL), and 2 volumes 100% ethanol (500 μL), and finally resuspended in TE buffer and kept at –20 °C. The library preparation and sequencing were conducted at the Beijing genome institute (BGI) using Illumina HiSeq 2000 following the manufacturer guidelines and generating 63 to 65 M reads of raw data per sample with a Q20 between 97.64 and 98.80 (Table S1). The raw reads were subject to quality control using FASTQC v0.11.9, and the statistics of clean data after QC are available in Supplemental Table S2. After the quality control, reads were trimmed using Trimomatic V0.39 [72] to remove adapters and filter out the reads when N content greater than 5%. Low-quality raw reads were filtered before running quality control. The clean reads were then mapped to the wild Olea europaea ssp. europaea var. sylvestris genome sequence v1 [11] using BWA-0.7.17 [73] and resulting in a uniquely read mapping average rate of 94%. (Table S3). Samtools v1.10 [74] were used to sort, filter, index, and run statistics on the BAM files. Next, uniquely mapped read density distribution in chromosomes was visualized in a Manhattan plot using Circos v0.69.9 [75].

4.3. Methylated Regions Calling, Annotation, and Functional Analysis

To detect the methylated region in wild and cultivated olives, peaks related to genes, their count, width, significance, and distribution throughout genomic features including transcription starting site (TSS), transcription termination site (TTS), exons, and introns were called using MACS v2.2.7 software [76] with the following parameters (threshold -g 1.2e8-p 1e-5 -m 10,100). The width of the peak indicates the length of the DNA sequence to which the methylation-specific antibody protein binds. The significance of the peak (p-value) is an indication of the degree of confidence. The fold enrichment can also be called signal value, indicating a digital display of the peak signal during the peak calling. Larger values correspond to the number of enriched reads on the peak. Homer v4.10 annotate peak Python program [77] was used to annotate the genes associated with methylated regions in both cultivated and wild olive. HOMER first determines the distance to the nearest TSS and assigns the peak to that gene. Second, it determines the genomic annotation of the region occupied by the center of the peak using a gene transfer format (GTF) to retrieve structural annotation. In addition to associating peaks with nearby genes, HOMER was used to perform gene ontology and KEGG pathway analysis. The bar charts for different gene ontology terms (molecular function, cellular component, and biological process) and the scatter plots for the KEGG enrichment analysis were dressed using GO plot v1.0.2 [78]. To emphasize the role of DNA methylation in modulating the metabolic activity, differentially methylated gene IDs were extracted from the most enriched pathways in fatty acids and phenolic compounds metabolism. The gene IDs were mapped against the wild Olea europaea var. sylvestris annotation database hosted in the online resource for community annotation of eukaryotes [79] for further functional annotation. To explain the DNA methylation dynamic across tissues and maturation stages, DNA methyltransferases, and demethylases IDs were extracted from the Olea europaea var sylvestris annotation database and mapped against the published Olea europaea ssp. europaea var. sylvestris (July/November) differential gene expression matrix (Additional file S6).

4.4. Comparative Promoter Analysis

To explore the cis-regulatory elements of methylated gene between Ayvalik cv and wild Karadelice, a 1 kb promoter upstream the transcription starting site of two methylated genes: linoleate 9S lipoxugenase (9-LOX) and fatty acid desaturase (FAD3) were analyzed. The selected 1 Kb promoter sequences were extracted from the online resource for community annotation of eukaryotes genome browser using gene coordinates [79]. The three promoter sequences from the Olea europaea ssp. europaea var. sylvestris reference genome [11] were mapped against the Ayvalik assembly scaffolds provided by olive genome consortium using standalone BLASTN 2.6.0+ [80]. The homologous promoter sequences were subject to a cis-element analysis using Genomatix MatInspector v8.4.1 [81]. To avoid any discrepancies in methylation site calling, cis-elements screening windows were extended to the 24 bp flanking the predicted peak summit.

4.5. Metabolic Analysis, Fatty Acid and Total Polyphenol Profiling

The mono cultivar certified commercial olive oil sample from Olea europaea ssp. europaea var. sylvestris “karadelice” were kindly provided by Egeden Dogal Tarim Urunleri Ltd., Mugla, Turkey. To determine the fatty acid and total phenolic content, the gas chromatography flame ionization detector (GC-FID) and high-performance liquid chromatography (HPLC-UV) as described by [82,83] were performed in TARIM VE ORMAN BAKANLIĞI AYTB Hizmetleri Laboratory in turkey. The Nuclear Magnetic Resonance (NMR) analysis for detailed secoiridoids compounds was conducted in the laboratory of Natural Products Chemistry, Faculty of Pharmacy at the National and Kapodistrian University of Athens following the method described by [84]. Since the olive oil from Ayvalik cv is well and extensively characterized we used mean value from the previous studies [4,5].

5. Conclusions

The current study provides a base to understanding the DNA methylation landscape evolution throughout domestication of olive trees in the Aegean region of Turkey. DNA methylation could fill the gap in explaining the unassigned genetic variation responsible for the phenotypic plasticity in Olea europaea species. The genome-wide DNA methylation profiling of cultivated and wild olives from Turkey described the genome wide methylation status in olive fruit during ripening. The study also describes the potential role of DNA methylation in volatile aromatic compounds metabolism in the LOX pathway. The study provides a platform for epigenetic markers discovery, that could be used for early screening in olive trees breeding. It is recommended to carry out additional studies with larger samples of wild and cultivated olives from eastern and western Mediterranean regions, in addition to combining metabolomic, transcriptomic, and epigenomic data to elucidate the complexity of the biology and the evolution of this endemic tree.

Remarks and Future Perspectives

Exploring epigenetic diversity for plant breeding was widely studied in model plants and horticulture, but still rudimentary in sessile and long lived agro-forest trees [85,86]. This study is a gateway transition to explore epigenetics as a tool in agroforestry. Understanding the role of epigenetic variability in forest species and how it may contribute to their rapid adaptation to changing environments should be of high interest, especially with the current drastic climate change.
In the midst of the current climate change debate, food security has become of extreme concern to the food and agriculture sectors. Increasing crop production represents a great challenge in many countries. The food and agriculture organization (FAO), in partnership with local entities launched a variety of national programs for crop micro propagation and tissue culture of fruit trees in arid, semiarid, and tropical regions for conservation and restoration of damaged forests, groves, and orchards. For instance, to restore the date palm groves ravaged by Bayoud Fusarium wilt disease, efforts to produce clones resistant to the disease have been established in Saudi Arabia, the UAE, Morocco, and other North African and middle eastern countries since the 1980s. At this time, palm groves are still suffering from the lack of uniformity in established clones. In the southern coast of Europe, especially Italy, in an effort to contain the spread of Xylella fastidiosa in olive groves in the eastern Mediterranean and North Africa, the FAO is encouraging countries importing explants to produce their own through micropropagation and tissue culture. In Morocco, multiple efforts and resources are being deployed by the Kingdom in partnership with the FAO to restore the wild Moroccan Argan (Argania spinosa) tree groves in the Atlas Mountain valley, because of its high socioeconomic importance.
To avoid scenarios similar to the oil palm catastrophe in Indonesia [87], national programs on micro propagation and tissue culture should also take into consideration the recommendation from the scientific community. In addition to the socioeconomic recommendation, studying micropropagation effects on genome rearrangement and DNA methylation dynamics should be taken into utmost consideration.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/plants10071405/s1, Additional file S1: promoter alignment between wild and cultivated olives. Additional file S2: Leaves methyltransferases differential gene expression between July and November. Additional file S3: fruit methyltransferases differential gene expression between July and November. Additional file S4: fruit demethylases differential gene expression between July and November. Additional file S5: fruit differential methylation annotation between wild and cultivated olives. Additional file S6: wild oleaster fruit DGE between July and November. Additional file S7: phenolic compound analysis for Oleaster. Figure S1: Differential methylation between leaves and fruit in wild and cultivated olive trees, Figure S2: Differential methylated profile between the wild oleaster (Delice) and cultivated Ayvalik within the 23 olive chromosomes, Figure S3: Differential methylated region in fruits and leaves between July and November in wild and cultivated olive trees, Figure S4: Differential methylated region in fruits and leaves between wild and cultivated olive trees in different maturation stages, Figure S5: Heatmap of leaves DNA methyltransferases differential genes expression (DGE) between July and November (DGE data published in Turgay et al., 2017), Figure S6: Heatmap of fruit DNA methyltransferases differential genes expression between July and November (DGE data published in Turgay et al., 2017), Figure S7: Heatmap of fruits DNA demethylases differential genes expression between July and November, Table S1: Raw data statistic information, Table S2: Statistics of clean data after QC and trimming, Table S3: Statistics of reads alignments, Table S4: Summary of gene ontology and KEGG enrichment of DMR between wild Delice and cultivated Ayvalik for fruits and leaves in different fruit maturation phases (A: Ayvalik; D: Delice; J: July; N: November; L: leaf; F: fruit), Table S5: Identified cis-elements at the lipoxygenase 1 (Oeu003662.1) involved in the methylated peak/site, Table S6: Identified cis-elements at the methylation site for the fatty acid desaturase-3 (Oeu032520) promoter.

Author Contributions

Conceptualization, O.B., D.A.L. and K.M.; Data curation, O.B. and N.Z.; Formal analysis, O.B., N.L., N.Z., A.E.B., Y.Z. and J.M.; Funding acquisition, D.A.L., H.T., E.H.Z., T.U. and K.M.; Investigation, E.H.Z., T.U. and K.M.; Methodology, O.B., T.U. and K.M.; Project administration, D.A.L., H.T., E.H.Z., T.U. and K.M.; Resources, K.M.; Software, O.B.; Supervision, D.A.L., E.H.Z. and K.M.; Writing—original draft, O.B., N.L. and K.M.; Writing—review and editing, O.B., N.L., Y.Z., J.M., D.A.L., H.T., E.H.Z., T.U. and K.M. All authors have read and agreed to the published version of the manuscript.

Funding

This project was funded by the Deanship of Scientific Research (DSR) fund of Imam Abdulrahman Bin Faisal University (IAU), Project number: 2017-609-IRMC. Oussama Badad (PhD candidate) was granted the Fulbright joint supervision doctoral grant to conduct the research at the plant biotechnology and genome core-facility at Southern Illinois University in Carbondale, IL, under supervision of Lightfoot and Meksem.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Acknowledgments

We would like to thank members of the international olive genome consortium for providing draft assembly of the cultivar Ayvalik. We also like to thank Chester Langin and Majid Memari from the Southern Illinois University research computing and cyber infrastructure (BIGDAWG) for providing and managing access to their high-performance computing cluster for Data analysis. We would like to extend our acknowledgment to Özlem Tok from the Karadeniz Technical University Trabzon, Turkey, for her effort to help with the olive oil samples acquisition and shipping logistics.

Conflicts of Interest

The authors declare that they have no competing interest.

References

  1. Pedan, V.; Popp, M.; Rohn, S.; Nyfeler, M.; Bongartz, A. Characterization of Phenolic Compounds and Their Contribution to Sensory Properties of Olive Oil. Molecules 2019, 24, 2041. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Stefani, M.; Rigacci, S. Beneficial properties of natural phenols: Highlight on protection against pathological conditions associated with amyloid aggregation. BioFactors 2014, 40, 482–493. [Google Scholar] [CrossRef]
  3. Luque-Muñoz, A.; Tapia, R.; Haidour, A.; Justicia, J.; Cuerva, J.M. Direct determination of phenolic secoiridoids in olive oil by ultra-high performance liquid chromatography-triple quadruple mass spectrometry analysis. Sci. Rep. 2019, 9, 15545. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Andjelkovic, M.; Acun, S.; Hoed, V.; Verhé, R.; Camp, J. Chemical Composition of Turkish Olive Oil–Ayvalik. JAOCS J. Am. Oil Chem. Soc. 2009, 86, 135–140. [Google Scholar] [CrossRef]
  5. Kelebek, H.; Selli, S.; Kola, O. Quantitative determination of phenolic compounds using LC-DAD-ESI-MS/MS in cv. Ayvalik olive oils as affected by harvest time. J. Food Meas. Charact. 2017, 11. [Google Scholar] [CrossRef]
  6. Dabbou, S.; Dabbou, S.; Selvaggini, R.; Urbani, S.; Taticchi, A.; Servili, M.; Hammami, M. Comparison of the Chemical Composition and the Organoleptic Profile of Virgin Olive Oil from Two Wild and Two Cultivated Tunisian Olea europaea. Chem. Biodivers. 2011, 8, 189–202. [Google Scholar] [CrossRef]
  7. Bouarroudj, K.; Tamendjari, A.; Larbat, R. Quality, composition and antioxidant activity of Algerian wild olive (Olea europaea L. subsp. Oleaster) oil. Ind. Crops Prod. 2016, 83. [Google Scholar] [CrossRef]
  8. Rodrigues, N.; Pinho, T.; Casal, S.; Peres, A.; Baptista, P.; Pereira, J. Chemical Characterization of Oleaster, Olea europaea var. sylvestris (Mill.) Lehr., Oils from Different Locations of Northeast Portugal. Appl. Sci. 2020, 10, 6414. [Google Scholar] [CrossRef]
  9. Espínola, F.; Vidal Castro, A.; Espínola, J.; Moya, M. Processing Effect and Characterization of Olive Oils from Spanish Wild Olive Trees (Olea europaea var. sylvestris). Molecules 2021, 26, 1304. [Google Scholar] [CrossRef]
  10. Ozkaya, M.; ErgÜLen, E.; Ülger, S.; Özilbey, N. Molecular Characterization of Some Selected Wild Olive (Olea oleaster L.) Ecotypes Grown in Turkey. J. Agric. Sci. 2009, 15, 14–19. [Google Scholar] [CrossRef]
  11. Unver, T.; Wu, Z.; Sterck, L.; Turktas, M.; Lohaus, R.; Li, Z.; Yang, M.; He, L.; Deng, T.; Escalante, F.J.; et al. Genome of wild olive and the evolution of oil biosynthesis. Proc. Natl. Acad. Sci. USA 2017, 114, E9413. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Gugger, P.F.; Fitz-Gibbon, S.; PellEgrini, M.; Sork, V.L. Species-wide patterns of DNA methylation variation in Quercus lobata and their association with climate gradients. Mol. Ecol. 2016, 25, 1665–1680. [Google Scholar] [CrossRef] [PubMed]
  13. Artemov, A.V.; Mugue, N.S.; Rastorguev, S.M.; Zhenilo, S.; Mazur, A.M.; Tsygankova, S.V.; Boulygina, E.S.; Kaplun, D.; Nedoluzhko, A.V.; Medvedeva, Y.A.; et al. Genome-Wide DNA Methylation Profiling Reveals Epigenetic Adaptation of Stickleback to Marine and Freshwater Conditions. Mol. Biol. Evol. 2017, 34, 2203–2213. [Google Scholar] [CrossRef] [Green Version]
  14. Metzger, D.C.H.; Schulte, P.M. Persistent and plastic effects of temperature on DNA methylation across the genome of threespine stickleback (Gasterosteus aculeatus). Proc. Biol. Sci. 2017, 284, 20171667. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Angiolillo, A.; Mencuccini, M.; Baldoni, L. Olive genetic diversity assessed using amplified fragment length polymorphisms. Theor. Appl. Genet. 1999, 98, 411–421. [Google Scholar] [CrossRef]
  16. Besnard, G.; Bervillé, A. On chloroplast DNA variations in the olive (Olea europaea L.) complex: Comparison of RFLP and PCR polymorphisms. Theor. Appl. Genet. 2002, 104, 1157–1163. [Google Scholar] [CrossRef] [PubMed]
  17. Bronzini de Caraffa, V.; Giannettini, J.; Gambotti, C.; Maury, J. Genetic relationships between cultivated and wild olives of Corsica and Sardinia using RAPD markers. Euphytica 2002, 123, 263–271. [Google Scholar] [CrossRef]
  18. Lumaret, R.; Ouazzani, N.; Michaud, H.; Vivier, G.; Deguilloux, M.F.; Di Giusto, F. Allozyme variation of oleaster populations (wild olive tree) (Olea europaea L.) in the Mediterranean Basin. Heredity 2004, 92, 343–351. [Google Scholar] [CrossRef]
  19. Baldoni, L.; Tosti, N.; Ricciolini, C.; Belaj, A.; Arcioni, S.; Pannelli, G.; Germana, M.A.; Mulas, M.; Porceddu, A. Genetic Structure of Wild and Cultivated Olives in the Central Mediterranean Basin. Ann. Bot. 2006, 98, 935–942. [Google Scholar] [CrossRef]
  20. Breton, C.; Tersac, M.; Bervillé, A. Genetic diversity and gene flow between the wild olive (oleaster, Olea europaea L.) and the olive: Several Plio-Pleistocene refuge zones in the Mediterranean basin suggested by simple sequence repeats analysis. J. Biogeogr. 2006, 33, 1916–1928. [Google Scholar] [CrossRef]
  21. Besnard, G.; Khadari, B.; Navascués, M.; Fernández-Mazuecos, M.; El Bakkali, A.; Arrigo, N.; Baali-Cherif, D.; Brunini-Bronzini de Caraffa, V.; Santoni, S.; Vargas, P.; et al. The complex history of the olive tree: From Late Quaternary diversification of Mediterranean lineages to primary domestication in the northern Levant. Proc. Biol. Sci. 2013, 280, 20122833. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Gros-Balthazard, M.; Besnard, G.; Sarah, G.; Holtz, Y.; Leclercq, J.; Santoni, S.; Wegmann, D.; Glémin, S.; Khadari, B. Evolutionary transcriptomics reveals the origins of olives and the genomic changes associated with their domestication. Plant J. 2019, 100, 143–157. [Google Scholar] [CrossRef]
  23. Jiménez-Ruiz, J.; Ramírez-Tejero, J.A.; Fernández-Pozo, N.; Leyva-Pérez, M.d.l.O.; Yan, H.; Rosa, R.d.l.; Belaj, A.; Montes, E.; Rodríguez-Ariza, M.O.; Navarro, F.; et al. Transposon activation is a major driver in the genome evolution of cultivated olive trees (Olea europaea L.). Plant Genome 2020, 13, e20010. [Google Scholar] [CrossRef] [Green Version]
  24. Kelly, T.K.; De Carvalho, D.D.; Jones, P.A. Epigenetic modifications as therapeutic targets. Nat. Biotechnol. 2010, 28, 1069–1078. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Smith, Z.D.; Meissner, A. DNA methylation: Roles in mammalian development. Nat. Rev. Genet. 2013, 14, 204–220. [Google Scholar] [CrossRef] [PubMed]
  26. Moore, L.D.; Le, T.; Fan, G. DNA methylation and its basic function. Neuropsychopharmacology 2013, 38, 23–38. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Yoder, J.A.; Walsh, C.P.; Bestor, T.H. Cytosine methylation and the ecology of intragenomic parasites. Trends Genet. 1997, 13, 335–340. [Google Scholar] [CrossRef]
  28. Aran, D.; Toperoff, G.; Rosenberg, M.; Hellman, A. Replication timing-related and gene body-specific methylation of active human genes. Hum. Mol. Genet. 2011, 20, 670–680. [Google Scholar] [CrossRef]
  29. Dimond, J.L.; Nguyen, N.; Roberts, S.B. DNA methylation profiling of a cnidarian-algal symbiosis using nanopore sequencing. G3 Genes Genomes Genet. 2021. [Google Scholar] [CrossRef]
  30. Lu, Y.C.; Feng, S.J.; Zhang, J.J.; Luo, F.; Zhang, S.; Yang, H. Genome-wide identification of DNA methylation provides insights into the association of gene expression in rice exposed to pesticide atrazine. Sci. Rep. 2016, 6, 18985. [Google Scholar] [CrossRef] [Green Version]
  31. Zuo, J.; Wang, Y.; Zhu, B.; Luo, Y.; Wang, Q.; Gao, L. Comparative Analysis of DNA Methylation Reveals Specific Regulations on Ethylene Pathway in Tomato Fruit. Genes 2018, 9, 266. [Google Scholar] [CrossRef] [Green Version]
  32. Lang, Z.; Wang, Y.; Tang, K.; Tang, D.; Datsenka, T.; Cheng, J.; Zhang, Y.; Handa, A.K.; Zhu, J.-K. Critical roles of DNA demethylation in the activation of ripening-induced genes and inhibition of ripening-repressed genes in tomato fruit. Proc. Natl. Acad. Sci. USA 2017, 114, E4511–E4519. [Google Scholar] [CrossRef] [Green Version]
  33. Chen, X.; Ge, X.; Wang, J.; Tan, C.; King, G.J.; Liu, K. Genome-wide DNA methylation profiling by modified reduced representation bisulfite sequencing in Brassica rapa suggests that epigenetic modifications play a key role in polyploid genome evolution. Front. Plant Sci. 2015, 6, 836. [Google Scholar] [CrossRef] [Green Version]
  34. Manning, K.; Tör, M.; Poole, M.; Hong, Y.; Thompson, A.J.; King, G.J.; Giovannoni, J.J.; Seymour, G.B. A naturally occurring epigenetic mutation in a gene encoding an SBP-box transcription factor inhibits tomato fruit ripening. Nat. Genet. 2006, 38, 948–952. [Google Scholar] [CrossRef] [PubMed]
  35. Cheng, J.; Niu, Q.; Zhang, B.; Chen, K.; Yang, R.; Zhu, J.-K.; Zhang, Y.; Lang, Z. Downregulation of RdDM during strawberry fruit ripening. Genome Biol. 2018, 19, 212. [Google Scholar] [CrossRef] [PubMed]
  36. Schiller, D.; Contreras, C.; Vogt, J.; Dunemann, F.; Defilippi, B.G.; Beaudry, R.; Schwab, W. A dual positional specific lipoxygenase functions in the generation of flavor compounds during climacteric ripening of apple. Hortic. Res. 2015, 2, 15003. [Google Scholar] [CrossRef] [Green Version]
  37. Hwang, I.S.; Hwang, B.K. The pepper 9-lipoxygenase gene CaLOX1 functions in defense and cell death responses to microbial pathogens. Plant Physiol. 2010, 152, 948–967. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Padilla, M.N.; Hernández, M.L.; Sanz, C.; Martínez-Rivas, J.M. Functional Characterization of Two 13-Lipoxygenase Genes from Olive Fruit in Relation to the Biosynthesis of Volatile Compounds of Virgin Olive Oil. J. Agric. Food Chem. 2009, 57, 9097–9107. [Google Scholar] [CrossRef]
  39. Nagpala, E.G.; Guidarelli, M.; Gasperotti, M.; Masuero, D.; Bertolini, P.; Vrhovsek, U.; Baraldi, E. Polyphenols Variation in Fruits of the Susceptible Strawberry Cultivar Alba during Ripening and upon Fungal Pathogen Interaction and Possible Involvement in Unripe Fruit Tolerance. J. Agric. Food Chem. 2016, 64, 1869–1878. [Google Scholar] [CrossRef] [PubMed]
  40. Bertin, N.; Gomez-Caravaca, A.; Cirilli, M.; Caruso, G.; Gennai, C.; Urbani, S.; Frioni, E.; Ruzzi, M.; Servili, M.; Gucci, R.; et al. The Role of Polyphenoloxidase, Peroxidase, and β-Glucosidase in Phenolics Accumulation in Olea europaea L. Fruits under Different Water Regimes. Front. Plant Sci. 2017, 8, 717. [Google Scholar] [CrossRef] [Green Version]
  41. Velázquez-Palmero, D.; Romero-Segura, C.; García-Rodríguez, R.; Hernández, M.L.; Vaistij, F.E.; Graham, I.A.; Pérez, A.G.; Martínez-Rivas, J.M. An Oleuropein β-Glucosidase from Olive Fruit Is Involved in Determining the Phenolic Composition of Virgin Olive Oil. Front. Plant Sci. 2017, 8, 1902. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Huang, H.; Liu, R.; Niu, Q.; Tang, K.; Zhang, B.; Zhang, H.; Chen, K.; Zhu, J.-K.; Lang, Z. Global increase in DNA methylation during orange fruit development and ripening. Proc. Natl. Acad. Sci. USA 2019, 116, 1430–1436. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Messeguer, R.; Ganal, M.W.; Steffens, J.C.; Tanksley, S.D. Characterization of the level, target sites and inheritance of cytosine methylation in tomato nuclear DNA. Plant Mol. Biol. 1991, 16, 753–770. [Google Scholar] [CrossRef]
  44. Ruiz-García, L.; Cervera, M.T.; Martínez-Zapater, J.M. DNA methylation increases throughout Arabidopsis development. Planta 2005, 222, 301–306. [Google Scholar] [CrossRef]
  45. Zluvova, J.; Janousek, B.; Vyskot, B. Immunohistochemical study of DNA methylation dynamics during plant development. J. Exp. Bot. 2001, 52, 2265–2273. [Google Scholar] [CrossRef] [PubMed]
  46. Bartels, A.; Han, Q.; Nair, P.; Stacey, L.; Gaynier, H.; Mosley, M.; Huang, Q.Q.; Pearson, J.K.; Hsieh, T.-F.; An, Y.-Q.C.; et al. Dynamic DNA Methylation in Plant Growth and Development. Int. J. Mol. Sci. 2018, 19, 2144. [Google Scholar] [CrossRef] [Green Version]
  47. Fray, R.; Zhong, S. 11–Genome-wide DNA methylation in tomato. In Applied Plant Genomics and Biotechnology; Poltronieri, P., Hong, Y., Eds.; Woodhead Publishing: Oxford, UK, 2015; pp. 179–193. [Google Scholar]
  48. Brenet, F.; Moh, M.; Funk, P.; Feierstein, E.; Viale, A.J.; Socci, N.D.; Scandura, J.M. DNA methylation of the first exon is tightly linked to transcriptional silencing. PLoS ONE 2011, 6, e14524. [Google Scholar] [CrossRef]
  49. Siedow, J.N. Plant Lipoxygenase: Structure and Function. Annu. Rev. Plant Physiol. Plant Mol. Biol. 1991, 42, 145–188. [Google Scholar] [CrossRef]
  50. Morales, M.T.; Alonso, M.V.; Rios, J.J.; Aparicio, R. Virgin Olive Oil Aroma: Relationship between Volatile Compounds and Sensory Attributes by Chemometrics. J. Agric. Food Chem. 1995, 43, 2925–2931. [Google Scholar] [CrossRef]
  51. Angerosa, F.; Basti, C. Olive oil volatile compounds from the lipoxygenase pathway in relation to fruit ripeness. Ital. J. Food Sci. 2001, 13, 421–428. [Google Scholar]
  52. Kiritsakis, A.K. Flavor components of olive oil—A review. J. Am. Oil Chem. Soc. 1998, 75, 673–681. [Google Scholar] [CrossRef]
  53. Ryan, D.; Robards, K. Critical Review. Phenolic compounds in olives. Analyst 1998, 123, 31R–44R. [Google Scholar] [CrossRef]
  54. Servili, M.; Montedoro, G. Contribution of phenolic compounds to virgin olive oil. Eur. J. Lipid Sci. Technol. 2002, 104. [Google Scholar] [CrossRef]
  55. Tura, D.; Failla, O.; Pedò, S.; Gigliotti, C.; Bassi, D.; Serraiocco, A. Effects of Seasonal Weather Variability on Olive Oil Composition in Northern Italy. Acta Hortic. 2008, 791. [Google Scholar] [CrossRef] [Green Version]
  56. Boucheffa, S.; Tamendjari, A.; Rovellini, P.; Venturini, S. Composition and antioxidant activity of some Algerian wild extra virgin olive oils. Riv. Ital. Delle Sostanze Grasse 2014, 91, 177–185. [Google Scholar]
  57. Hannachi, H.; Nasri, N.; Elfalleh, W.; Tlili, N.; Ferchichi, A.; Msallem, M. Fatty Acids, Sterols, Polyphenols, and Chlorophylls of Olive Oils Obtained from Tunisian Wild Olive Trees (Olea europaea L. var. Sylvestris). Int. J. Food Prop. 2012, 16. [Google Scholar] [CrossRef]
  58. Amiot, M.J.; Fleuriet, A.; Macheix, J.J. Importance and evolution of phenolic compounds in olive during growth and maturation. J. Agric. Food Chem. 1986, 34, 823–826. [Google Scholar] [CrossRef]
  59. Ryan, D.; Robards, K.; Lavee, S. Changes in phenolic content of olive during maturation. Int. J. Food Sci. Technol. 1999, 34, 265–274. [Google Scholar] [CrossRef]
  60. Alagna, F.; Mariotti, R.; Panara, F.; Caporali, S.; Urbani, S.; Veneziani, G.; Esposto, S.; Taticchi, A.; Rosati, A.; Rao, R.; et al. Olive phenolic compounds: Metabolic and transcriptional profiling during fruit development. BMC Plant Biol. 2012, 12, 162. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  61. Monteleone, E.; Caporale, G.; Carlucci, A.; Pagliarini, E. Optimisation of extra virgin olive oil quality. J. Sci. Food Agric. 1998, 77, 31–37. [Google Scholar] [CrossRef]
  62. Romani, A.; Mulinacci, N.; Pinelli, P.; Vincieri, F.F.; Cimato, A. Polyphenolic Content in Five Tuscany Cultivars of Olea europaea L. J. Agric. Food Chem. 1999, 47, 964–967. [Google Scholar] [CrossRef]
  63. Rotondi, A.; Bendini, A.; Cerretani, L.; Mari, M.; Lercker, G.; Gallina Toschi, T. Effect of Olive Ripening Degree on the Oxidative Stability and Organoleptic Properties of Cv. Nostrana di Brisighella Extra Virgin Olive Oil. J. Agric. Food Chem. 2004, 52, 3649–3654. [Google Scholar] [CrossRef]
  64. Talhaoui, N.; Taamalli, A.; Caravaca, A.M.G.; Fernández-Gutiérrez, A.; Segura Carretero, A. Phenolic compounds in olive leaves: Analytical determination, biotic and abiotic influence, and health benefits. Food Res. Int. 2015, 77. [Google Scholar] [CrossRef]
  65. Gutierrez-Rosales, F.; Romero, M.P.; Casanovas, M.; Motilva, M.J.; Mínguez-Mosquera, M.I. Metabolites Involved in Oleuropein Accumulation and Degradation in Fruits of Olea europaea L.: Hojiblanca and Arbequina Varieties. J. Agric. Food Chem. 2010, 58, 12924–12933. [Google Scholar] [CrossRef] [PubMed]
  66. Koudounas, K.; Banilas, G.; Michaelidis, C.; Demoliou, C.; Rigas, S.; Hatzopoulos, P. A defence-related Olea europaea β-glucosidase hydrolyses and activates oleuropein into a potent protein cross-linking agent. J. Exp. Bot. 2015, 66, 2093–2106. [Google Scholar] [CrossRef] [Green Version]
  67. Koudounas, K.; Thomopoulou, M.; Michaelidis, C.; Zevgiti, E.; Papakostas, G.; Tserou, P.; Daras, G.; Hatzopoulos, P. The C-Domain of Oleuropein β-Glucosidase Assists in Protein Folding and Sequesters the Enzyme in Nucleus. Plant Physiol. 2017, 174, 1371–1383. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  68. Zha, L.; Liu, S.; Liu, J.; Jiang, C.; Yu, S.; Yuan, Y.; Yang, J.; Wang, Y.; Huang, L. DNA Methylation Influences Chlorogenic Acid Biosynthesis in Lonicera japonica by Mediating LjbZIP8 to Regulate Phenylalanine Ammonia-Lyase 2 Expression. Front. Plant Sci. 2017, 8, 1178. [Google Scholar] [CrossRef] [Green Version]
  69. Gutiérrez-Velázquez, M.V.; Almaraz-Abarca, N.; Herrera-Arrieta, Y.; Ávila-Reyes, J.A.; González-Valdez, L.S.; Torres-Ricario, R.; Uribe-Soto, J.N.; Monreal-García, H.M. Comparison of the phenolic contents and epigenetic and genetic variability of wild and cultivated watercress (Rorippa nasturtium var. aquaticum L.). Electron. J. Biotechnol. 2018, 34, 9–16. [Google Scholar] [CrossRef]
  70. Yang, D.; Huang, Z.; Jin, W.; Xia, P.; Jia, Q.; Yang, Z.; Hou, Z.; Zhang, H.; Ji, W.; Han, R. DNA methylation: A new regulator of phenolic acids biosynthesis in Salvia miltiorrhiza. Ind. Crops Prod. 2018, 124, 402–411. [Google Scholar] [CrossRef]
  71. Taiwo, O.; Wilson, G.A.; Morris, T.; Seisenberger, S.; Reik, W.; Pearce, D.; Beck, S.; Butcher, L.M. Methylome analysis using MeDIP-seq with low DNA concentrations. Nat. Protoc. 2012, 7, 617–636. [Google Scholar] [CrossRef]
  72. Bolger, A.M.; Lohse, M.; Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 2014, 30, 2114–2120. [Google Scholar] [CrossRef] [Green Version]
  73. Li, H.; Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009, 25, 1754–1760. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  74. Li, H.; Handsaker, B.; Wysoker, A.; Fennell, T.; Ruan, J.; Homer, N.; Marth, G.; Abecasis, G.; Durbin, R.; Genome Project Data Processing, S. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009, 25, 2078–2079. [Google Scholar] [CrossRef] [Green Version]
  75. Krzywinski, M.; Schein, J.; Birol, I.; Connors, J.; Gascoyne, R.; Horsman, D.; Jones, S.J.; Marra, M.A. Circos: An information aesthetic for comparative genomics. Genome Res. 2009, 19, 1639–1645. [Google Scholar] [CrossRef] [Green Version]
  76. Zhang, Y.; Liu, T.; Meyer, C.A.; Eeckhoute, J.; Johnson, D.S.; Bernstein, B.E.; Nusbaum, C.; Myers, R.M.; Brown, M.; Li, W.; et al. Model-based Analysis of ChIP-Seq (MACS). Genome Biol. 2008, 9, R137. [Google Scholar] [CrossRef] [Green Version]
  77. Heinz, S.; Benner, C.; Spann, N.; Bertolino, E.; Lin, Y.C.; Laslo, P.; Cheng, J.X.; Murre, C.; Singh, H.; Glass, C.K. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 2010, 38, 576–589. [Google Scholar] [CrossRef] [Green Version]
  78. Walter, W.; Sánchez-Cabo, F.; Ricote, M. GOplot: An R package for visually combining expression data with functional analysis. Bioinformatics 2015, 31, 2912–2914. [Google Scholar] [CrossRef] [PubMed]
  79. Sterck, L.; Billiau, K.; Abeel, T.; Rouzé, P.; Van de Peer, Y. ORCAE: Online resource for community annotation of eukaryotes. Nat. Methods 2012, 9, 1041. [Google Scholar] [CrossRef] [PubMed]
  80. Camacho, C.; Coulouris, G.; Avagyan, V.; Ma, N.; Papadopoulos, J.; Bealer, K.; Madden, T.L. BLAST+: Architecture and applications. BMC Bioinform. 2009, 10, 421. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  81. Cartharius, K.; Frech, K.; Grote, K.; Klocke, B.; Haltmeier, M.; Klingenhoff, A.; Frisch, M.; Bayerlein, M.; Werner, T. MatInspector and beyond: Promoter analysis based on transcription factor binding sites. Bioinformatics 2005, 21, 2933–2942. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  82. Wu, X.; Smith, J.S. A gas chromatography-flame ionization detection method for detection of fusaproliferin in corn. J. Agric. Food Chem. 2007, 55, 3211–3216. [Google Scholar] [CrossRef]
  83. Soman, A.; Qiu, Y.; Chan Li, Q. HPLC-UV method development and validation for the determination of low level formaldehyde in a drug substance. J. Chromatogr. Sci. 2008, 46, 461–465. [Google Scholar] [CrossRef] [Green Version]
  84. Karkoula, E.; Skantzari, A.; Melliou, E.; Magiatis, P. Direct Measurement of Oleocanthal and Oleacein Levels in Olive Oil by Quantitative 1H NMR. Establishment of a New Index for the Characterization of Extra Virgin Olive Oils. J. Agric. Food Chem. 2012, 60, 11696–11703. [Google Scholar] [CrossRef] [PubMed]
  85. Sáez-Laguna, E.; Guevara, M.-Á.; Díaz, L.-M.; Sánchez-Gómez, D.; Collada, C.; Aranda, I.; Cervera, M.-T. Epigenetic Variability in the Genetically Uniform Forest Tree Species Pinus pinea L. PLoS ONE 2014, 9, e103145. [Google Scholar] [CrossRef] [Green Version]
  86. Liang, L.; Chang, Y.; Lu, J.; Wu, X.; Liu, Q.; Zhang, W.; Su, X.; Zhang, B. Global Methylomic and Transcriptomic Analyses Reveal the Broad Participation of DNA Methylation in Daily Gene Expression Regulation of Populus trichocarpa. Front. Plant Sci. 2019, 10, 243. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  87. Lieben, L. Bad Karma reduces palm oil yields. Nat. Rev. Genet. 2015, 16, 625. [Google Scholar] [CrossRef]
Plants 10 01405 g001 550
Figure 1. Enrichment analysis of methylated regions in cultivated and wild olives. (A) Most enriched gene ontology terms in methylated regions in both cultivated and wild fruits in July. (B) Most enriched KEGG pathways in methylated region in both cultivated and wild fruits in July. (C) Most enriched gene ontology terms in methylated region in both cultivated and wild November fruits. (D) Most enriched KEGG pathways of methylated regions in both cultivated and wild November fruits. ANF: Ayvalik November fruit, DNF: wild November fruit. AJF: Ayvalik July fruit, DJF: wild July fruit, where Delice is the Turkish name of the wild oleaster.
Figure 1. Enrichment analysis of methylated regions in cultivated and wild olives. (A) Most enriched gene ontology terms in methylated regions in both cultivated and wild fruits in July. (B) Most enriched KEGG pathways in methylated region in both cultivated and wild fruits in July. (C) Most enriched gene ontology terms in methylated region in both cultivated and wild November fruits. (D) Most enriched KEGG pathways of methylated regions in both cultivated and wild November fruits. ANF: Ayvalik November fruit, DNF: wild November fruit. AJF: Ayvalik July fruit, DJF: wild July fruit, where Delice is the Turkish name of the wild oleaster.
Plants 10 01405 g001
Plants 10 01405 g002 550
Figure 2. Enrichment analysis of methylated regions in cultivated and wild olives. (A) Most enriched gene ontology terms in methylated regions in both cultivated and wild olives leaf samples in July. (B) Most enriched KEGG pathways in methylated region in both cultivated and wild olive leaf samples in July. (C) Most enriched gene ontology terms in methylated region in both cultivated and wild olives leaf samples in November. (D) Most enriched KEGG pathways of methylated regions in both cultivated and wild olives leaf samples in November. ANL: Ayvalik November fruit, DNL: wild November fruit. AJL: Ayvalik July fruit, DJL: wild July fruit, where Delice is the Turkish name of the wild Oleaster.
Figure 2. Enrichment analysis of methylated regions in cultivated and wild olives. (A) Most enriched gene ontology terms in methylated regions in both cultivated and wild olives leaf samples in July. (B) Most enriched KEGG pathways in methylated region in both cultivated and wild olive leaf samples in July. (C) Most enriched gene ontology terms in methylated region in both cultivated and wild olives leaf samples in November. (D) Most enriched KEGG pathways of methylated regions in both cultivated and wild olives leaf samples in November. ANL: Ayvalik November fruit, DNL: wild November fruit. AJL: Ayvalik July fruit, DJL: wild July fruit, where Delice is the Turkish name of the wild Oleaster.
Plants 10 01405 g002
Plants 10 01405 g003 550
Figure 3. Comparative promoter analysis of methylated putative genes responsible for the sensory and organoleptic qualities of olive oil between wild and cultivated olives. (A): linoleate 9S-Lipoxygenase. (B): Fatty acid desaturase FAD3. Colored boxes indicate the cis-elements in each promoter region. Zoomed parts show conserved, gained, and/or lost cis-elements at the methylation window between wild and cultivated olives. AJF: Ayvalik July fruit, ANF: Ayvalik November fruit, DNF: Delice November fruit sample and DJF: Delice July fruit sample.
Figure 3. Comparative promoter analysis of methylated putative genes responsible for the sensory and organoleptic qualities of olive oil between wild and cultivated olives. (A): linoleate 9S-Lipoxygenase. (B): Fatty acid desaturase FAD3. Colored boxes indicate the cis-elements in each promoter region. Zoomed parts show conserved, gained, and/or lost cis-elements at the methylation window between wild and cultivated olives. AJF: Ayvalik July fruit, ANF: Ayvalik November fruit, DNF: Delice November fruit sample and DJF: Delice July fruit sample.
Plants 10 01405 g003
Plants 10 01405 g004 550
Figure 4. Scheme summarizing the effect of DNA methylation during olive domestication on the sensory quality of olive oil.
Figure 4. Scheme summarizing the effect of DNA methylation during olive domestication on the sensory quality of olive oil.
Plants 10 01405 g004
Table
Table 1. Mean values of the major quantified fatty acids in (%), phenolic compounds (mg/kg). Values for Ayvalik cv EVOO represent the mean value of three replicate analyses data from [4,5]. Values for Olea europaea ssp. europaea var. sylvestris EVOO from the GC-FID HPLC-UV, and NMR represent the average of two replicates analysis. Abbreviations: ND not detected, diAOle agl dialdehyde form of oleuropein aglycone, AOle agl aldehydic form of oleuropein aglycone, Alig agl aldehydic form of ligstroside aglycon.
Table 1. Mean values of the major quantified fatty acids in (%), phenolic compounds (mg/kg). Values for Ayvalik cv EVOO represent the mean value of three replicate analyses data from [4,5]. Values for Olea europaea ssp. europaea var. sylvestris EVOO from the GC-FID HPLC-UV, and NMR represent the average of two replicates analysis. Abbreviations: ND not detected, diAOle agl dialdehyde form of oleuropein aglycone, AOle agl aldehydic form of oleuropein aglycone, Alig agl aldehydic form of ligstroside aglycon.
CompoundC18:1C18:2C183OleocanthalOleaceinAole agldiAOle aglAlig agldiALig aglTotal Polyphenol
Ayvalik cv EVOO69.310.80.74.94.23.10.82.7ND227
wild EVOO71.079.080.987476216462815211034
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Badad, O.; Lakhssassi, N.; Zaid, N.; El Baze, A.; Zaid, Y.; Meksem, J.; Lightfoot, D.A.; Tombuloglu, H.; Zaid, E.H.; Unver, T.; et al. Genome Wide MeDIP-Seq Profiling of Wild and Cultivated Olives Trees Suggests DNA Methylation Fingerprint on the Sensory Quality of Olive Oil. Plants 2021, 10, 1405. https://doi.org/10.3390/plants10071405

AMA Style

Badad O, Lakhssassi N, Zaid N, El Baze A, Zaid Y, Meksem J, Lightfoot DA, Tombuloglu H, Zaid EH, Unver T, et al. Genome Wide MeDIP-Seq Profiling of Wild and Cultivated Olives Trees Suggests DNA Methylation Fingerprint on the Sensory Quality of Olive Oil. Plants. 2021; 10(7):1405. https://doi.org/10.3390/plants10071405

Chicago/Turabian Style

Badad, Oussama, Naoufal Lakhssassi, Nabil Zaid, Abdelhalim El Baze, Younes Zaid, Jonas Meksem, David A Lightfoot, Huseyin Tombuloglu, El Houcine Zaid, Turgay Unver, and et al. 2021. "Genome Wide MeDIP-Seq Profiling of Wild and Cultivated Olives Trees Suggests DNA Methylation Fingerprint on the Sensory Quality of Olive Oil" Plants 10, no. 7: 1405. https://doi.org/10.3390/plants10071405

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop