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Article

Grafting with Different Rootstocks Induced DNA Methylation Alterations in Pecan [Carya illinoinensis (Wangenh.) K. Koch]

by
Zhuangzhuang Liu
1,2,
Pengpeng Tan
1,
Youwang Liang
1,
Yangjuan Shang
3,
Kaikai Zhu
1,
Fangren Peng
1,* and
Yongrong Li
4
1
College of Forestry, Nanjing Forestry University, Nanjing 210037, China
2
Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences (Nanjing Botanical Garden Mem. Sun Yat-Sen), Nanjing 210014, China
3
College of Life and Environment Sciences, Huangshan University, Huangshan 245021, China
4
Green Universe Pecan Science and Technology Co., Ltd., Nanjing 210007, China
*
Author to whom correspondence should be addressed.
Forests 2023, 14(1), 4; https://doi.org/10.3390/f14010004
Submission received: 27 October 2022 / Revised: 16 December 2022 / Accepted: 16 December 2022 / Published: 20 December 2022
(This article belongs to the Special Issue Strategies for Tree Improvement under Stress Conditions)
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Abstract

:
Rootstocks are well known to have important effects on scion growth performance. However, the involved mechanisms remain unclear. Recent studies provided some clues on the potential involvement of DNA methylation in grafting, which open up new horizons for exploring how rootstocks induce the growth changes. To better understand the involvement of DNA methylation in rootstock-induced growth alterations, whole-genome bisulfite sequencing (WGBS) was used to evaluate the methylation profiles of two sets of pecan grafts with different growth performances on different sizes of rootstocks. The results showed that methylated cytosines accounted for 24.52%–25.60% of all cytosines in pecan. Methylation levels in CG were the highest, with the lowest levels being in CHH (C= cytosine; G= guanine; H = adenine, thymine, or cytosine). Rootstocks induced extensive methylation alterations in scions with 934, 2864, and 15,789 differentially methylated regions (DMRs) determined in CG, CHG, and CHH contexts, respectively. DMR-related genes (DMGs) were found to participate in various processes associated with plant growth, among which 17 DMGs were found, most likely related to hormone response, that may play particularly important roles in graft growth regulation. This study revealed DNA methylomes throughout the pecan genome for the first time, and obtained abundant genes with methylation alterations that were potentially involved in rootstock-induced growth changes in pecan scions, which lays a good basis for further epigenetic studies on pecan and deeper understanding of grafting mechanisms in pecan grafts.

1. Introduction

Grafting is the process of connecting two plant parts with the root piece known as “rootstock” and the shoot part called “scion” [1]. Plants with desirable characteristics can be produced by combining the favorable traits of these two graft segments. As an ancient, clonal propagation technique, grafting is widely used for reproducing horticultural crops, such as fruit trees, vegetables, and flowers. For crops harvested from aboveground parts, attention is usually paid to the effects of rootstocks on their scions. Various studies have revealed that rootstocks can regulate scion growth vigor, tree architecture, mineral element composition, fruit quality and yield, and stress tolerance [2,3,4].
Although grafting has been applied for a long time, the mechanisms on how rootstocks influence the growth vigor of scions remain elusive. Previous studies on the effects of dwarfing rootstocks have put forth various hypotheses from physiological aspects to explain rootstock-conferred differences in vigor. In summary, the rootstocks can regulate scion growth, through their effects on anatomy of graft union, water and solutes supply to the scion, and synthesis and transportation of hormones [5,6]. Compared with much attention on the physiological mechanisms involved in rootstocks-induced growth differences, there are few studies to reveal the molecular mechanisms.
Previous studies have revealed the movement of mRNA, microRNA and siRNAs (small interfering RNAs) in grafts [7]. As a type of non-coding RNAs, siRNAs are known to direct transcriptional gene silencing (TGS) by RNA-directed DNA methylation (RdDM) [8]. Recent studies in A. thaliana and tobacco (Nicotiana tabacum L.) suggested the small interfering RNAs (siRNAs), a type of non-coding RNAs, can move from across the graft union and direct DNA methylation in the genome of scion recipient cells [9,10]. On the basis that DNA methylation is an important epigenetic modification and plays critical roles in regulation of plant development [11], it is possible that DNA methylation may be involved in the regulatory roles of rootstocks in scions. Several studies using methylation-sensitive amplified polymorphism (MSAP) technique suggested that rootstocks can induce different extent of DNA methylation changes in amplified sites of scions [12,13,14], and the sites with different methylation patterns were sequenced to analyze their potential functions [12,14]. By grafting eggplant (Solanum melongena L.) on Solanum torvum Swartz rootstock or tomato F1 commercial hybrid Emperador RZ rootstock, Cerruti et al. investigated the epigenetic bases of the grafting-induced vigor and found that CHH (C= cytosine; H = adenine, thymine, or cytosine) methylation levels decreased significantly in eggplant scions on the two rootstocks compared to that of self-grafted plants, which was associated with enhanced vigor in hetero-grafted eggplant scions [15]. Although these studies provided some clues on the involvement of DNA methylation in grafting process [12,13,14,15], the mechanisms on mediation of DNA methylation in rootstock-induced vigor changes in scions remain largely unknown, and systematic studies are urgently needed regarding this issue.
Pecan [Carya illinoinensis (Wangenh.) K. Koch] is an important nut tree native to North America [16]. Besides delicious and nutritious nuts, it can also produce fine timber or can be planted for afforestation. With significant economic, social, and ecological benefits, it has been planted widely throughout the world. As the main clonal propagation method of pecan, grafting plays important roles in the maintenance of excellent characteristics of cultivars, early flowering and fruit-bearing, and improvement of stress resistance. With the development of pecan industry, the directional cultivation of fine pecan grafts is required to suit multiple purposes. For example, in addition to the requirement of dwarfing trees for fruits in areas where land resources are scarce, there is also an increasing demand for the timber forests with fast vegetative growth. As an important part of the graft, rootstocks are known to have important effects on performance of scions. Thus, studies on the cultivation of rootstock resources and rootstocks-conferred effects on scions are critical to the directional cultivation of fine pecan grafts. In production, no clonal rootstock of pecan is available, and the rootstocks for grafting are mainly originated from the open-pollinated seeds of pecan trees. The limited breeding works on pecan rootstock mainly focus on the selection of the seedling rootstocks of different pecan cultivars, and their resistances to pests and diseases are regarded as important characteristics to test [17,18]. Currently, there is a still lack of rootstock resources to meet the requirements of pecan graft production, and little is known on the effects of rootstocks on scion performance and the involved mechanisms in pecan. In our previous study, we observed that rootstocks with small height can significantly reduce growth vigor in pecan scions. Using deep sequencing technology, we identified 24 significantly differentially expressed miRNAs between the two groups of pecan grafts with different growth vigor and further revealed their potential roles in growth regulation [19]. However, nothing is currently known regarding how DNA methylation changes in response to grafting with different rootstocks in this fruit tree, nor its involvement in regulation of pecan graft. Studies on the DNA methylation in grafts will help us fully understand the roles of epigenetic factors in grafting process.
Different methods have been developed for detecting DNA methylation, such as high-performance liquid chromatography (HPLC), MSAP method, immunoprecipitation technology, and whole-genome bisulfite sequencing (WGBS). Among these, MSAP has been more widely used because of its low cost and lack of need for genomic information. We previously used the MSAP method to successfully detect methylation in different pecan cultivars and tissues at different stages [20,21]. However, unlike MSAP technology, which covers preselected CCGG sites using a limited number of primer pairs (G= guanine), WGBS allows DNA methylation to be detected on a genome-wide scale with single-base resolution and is considered the “gold standard” [22]. Recently, the pecan genome was revealed [23], and it is now feasible for the first time to reveal DNA methylomes throughout the pecan genome using WGBS, which can provide comprehensive methylation information for epigenetic studies in pecan. In the current study, WGBS was performed to detect the DNA methylation profiles in pecan grafts with different growth vigor on tall and short rootstocks. Differentially methylated regions (DMRs) and DMR-related genes (DMGs) in the two sets of grafts were then identified. Finally, the DMGs were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to reveal gene functions.

2. Materials and Methods

2.1. Plant Materials

At the end of 2015, 180 tall and 180 short 1-year-old pecan seedlings were selected from Nanjing Green Universe Pecan Science and Technology Co., Nanjing, China. In January of 2016, they were transferred and cultivated in the test site of Nanjing Forestry University, Zhenjiang, Jiangsu Province (height data collected after seedling transplantation: mean height of 68.3 cm for tall seedlings, 16.7 cm for short seedlings). In September of 2016, the seedlings were reselected, and short seedlings of 30.0 cm height and tall seedlings of 94.6 cm height were obtained. Then, Pawnee and Shaoxing scions from the same trees of respective cultivars were grafted on the two types of seedling rootstocks (tall rootstocks: TR; short rootstocks: SR) using patch budding. After observation and selection of the grafts in 2017 and 2018, three grafts with significantly strong growth vigor (SV) on TR and three grafts with poor growth vigor (PV) on SR were obtained for each cultivar. The graft height and stem diameter of SV grafts were significantly higher than those of PV grafts, respectively (p < 0.05; the growth indexes of ‘Pawnee’ grafts are shown in Figure S1). Phloem samples from selected ‘Pawnee’ grafts were subjected to WGBS. The experimental plants were arranged in three blocks in a split-plot design with rootstock types set as main plots and cultivars as secondary plots. The detailed experimental design and selection method of the rootstocks and experimental grafts were previously described [19].

2.2. WGBS Library Construction and Sequencing

Genomic DNA was extracted from each pecan sample using the cetyltrimethylammonium bromide (CTAB) method and the DNA quality was measured using 1% agarose gel electrophoresis, a K5500 micro-spectrophotometer (Beijing Kaiao Technology Development Co., Ltd., Beijing, China), and a Qubit fluorometer 2.0 (Invitrogen, Carlsbad, CA, USA). The qualified DNA was segmented firstly by ultrasound, and the DNA fragments were purified, end-repaired, adenylated at the 3′ end, and ligated with methylated adapters. The targeted fragments were obtained from 2% agarose gel electrophoresis, treated with bisulfite, and amplified by PCR to generate the WGBS library. The prepared library was sequenced on an Illumina HiSeq PE125/PE150 platform (Biomarker Technologies, Beijing, China).

2.3. Sequence Data Processing and Analysis

Raw image files were produced by high-throughput sequencing and converted into sequenced reads, known as raw reads. Clean reads were obtained from the raw reads for subsequent analysis by removing the reads with adapters and excluding reads with more than 10% N content or more than 50% low quality bases (quality value < 10). Clean reads need to be aligned with a reference genome to conduct the analysis of DNA methylation. We used Bismark software to blast align the clean reads with the pecan genome to determine the uniquely mapped reads and calculate mapping efficiency (the number of uniquely mapped reads per number of total clean reads). Under bisulfite treatment and PCR amplification of the treated fragments, unmethylated cytosines were converted into thymine (T), while methylated cytosines (mC) remained unchanged. Therefore, the blast information on cytosine throughout the genome was extracted according to the alignment of clean reads with the pecan genome, and the reads supporting methylated and unmethylated cytosines were counted. Detailed steps of alignment analysis using Bismark are shown on the following website: https://github.com/FelixKrueger/Bismark/blob/master/Docs/README.md (accessed on 15 December 2022). To determine if each individual cytosine site (C site) was methylated, a binomial distribution test was conducted. With a coverage depth ≥ 4× and false discovery rate (FDR) < 0.05, methylation status of the C sites was confirmed.
In the current study, methylation level of a single C site was calculated using the following formula:
  Methylation   level   of   C   site = Ci / ( Ci + Ti )
The methylation level in regions was counted as follows:
Weighted   methylation   level = ∑ i = 1 n Ci / ∑ i = 1 n ( Ci + Ti )
where C represented the number of reads supporting methylated cytosine, T represented the number of reads supporting unmethylated cytosine, i was the position of cytosine, and n was the summation of cytosine positions [24].
Model-based analysis of bisulfite sequencing data (MOABS) [25] was used to determine DMRs in SV and PV grafts in which the coverage depth was no less than 10×. There were at least three different methylation sites, the minimum difference in methylation levels was 0.2 (0.3 for CG type), and p-value from Fisher’s exact test was less than 0.05. Annotation of the DMGs was obtained through the comparison of DMGs with functional databases of GO and KEGG using BLAST to analyze gene functions. Fisher’s exact test with p < 0.05 was used to determine the significantly enriched GO annotations and KEGG pathways.

3. Results

3.1. Pecan DNA Methylomes

Using WGBS, a total of 66,502,614 to 84,008,102 clean reads and 19,950,784,200 to 25,202,430,600 clean bases were generated from the pecan grafts, including the grafts with strong growth vigor on TR (SV1, SV2, and SV3) and grafts with poor growth vigor on SR (PV1, PV2, and PV3). Guanine and cytosine accounted for 21.53%–22.42% of all the bases. Through mapping analysis, 75.50%–77.95% of the clean reads could be uniquely mapped to the pecan genome for subsequent analysis, and all of the bisulfite conversion rates for the six samples were over 99% (Table 1).
Methylation in pecan was shown to occur in all cytosine sequence contexts, CG, CHG, and CHH. Based on the methylation status of each individual C site and statistics of mC, total methylated cytosines (mCG + mCHG + mCHH) accounted for 24.52%–25.60% of all cytosines (total methylation levels) in the six pecan samples (Table S1). The methylation levels were highest in CG (66.77%–67.85%), with methylation levels of 54.16%–55.31% in CHG and 14.21%–15.37% in CHH (Methylation level in C context was determined based the number of mC of each context/the number of all C sites of the same C context) (Figure 1a). Among the methylated cytosine sites, mCHH contexts accounted for 44.85%–46.41% (relative methylation levels), which was the highest percentages, followed by 27.98%–28.70% mCHG contexts and 25.61%–26.45% mCG context (Figure 1b). Through student’s t-tests, there were no significant differences in the methylation levels (including total methylation levels, methylation levels in different C contexts, and relative methylation levels) between VG and PG grafts (p > 0.05).
Violin graphs demonstrate the distribution of methylation levels at single C sites (Figure 2). Overall, mCG and mCHG, with methylation levels more than 75%, had higher density in pecan, while mCHH with levels lower than 25% possessed higher density. Analysis was then conducted on the characteristics of 9-base pair (bp) sequences in which mC was in the fifth position. Based on the results of all pecan samples, the frequencies of adenine (A) and T were higher than those of C in the sixth position of the CHG sequences. In addition, A and T were also found to occur at higher frequencies than C in the sixth and seventh positions of the CHH sequences (Figure 3; Figure S2).
Chromosome methylation maps were plotted to visually demonstrate the distribution of mC throughout pecan chromosomes (Figure 4a; Figure S3). The maps showed that methylation levels were highest in CG in the whole, with the lowest methylation levels detected in the CHH context. We also analyzed methylation in different gene regions of pecan genome, including the upstream regions [2 kilobase (kb)], first intron, inner intron, first exon, inner exon, last exon, and downstream regions (2 kb). Methylation levels in the three contexts, especially CG, exhibited an obvious drop between the gene bodies and flanking regions near the transcription start site (TSS) and transcription termination site (TTS). In the CG context, highest methylation levels were found in the inner introns compared to those in other regions, while methylation levels were highest in the upstream and downstream regions for the CHG and CHH contexts (Figure 4b; Figure S4). In the gene bodies, methylation levels in the introns appeared higher than those in the exons. We also investigated methylation levels in different regions of repeats and found that methylation levels in repeats were higher than those in gene regions, and repeat bodies had higher methylation levels than those in the upstream (1.5 kb) and downstream (1.5 kb) regions of repeats (Figure 4c; Figure S5).
Hypermethylation CG island (CGI) regions were defined as CGI regions with methylation levels greater than 70%. We also excluded those in which the rates of C sites with coverage depth > 5× were less than 0.1, and annotated the remaining hypermethylation CGI regions. The results showed that distal intergenic regions had the highest proportions of hypermethylation CGI regions, ranging from 81.35% to 84.26% in the six pecan samples. Hypermethylation CGI regions in ≤ 1 kb promoter, 1–2 kb promoter and 2–3 kb promoter accounted for 3.03%–4.52%, 5.74%–6.61% and 3.65%–4.45%, respectively. The lowest percentages of hypermethylation CGI were found in untranslated regions (UTRs) and exons (≤ 0.3%; Figure 5).

3.2. Analysis of DMRs in Pecan Grafts with Different Growth Performances

DMRs were detected in the SV and PV grafts and the results showed that a total of 934 DMRs were identified in CG contexts (CG-DMRs), 2864 in CHG contexts (CHG-DMRs), and 15,789 in CHH contexts (CHH-DMRs) in the two types of grafts. Compared with the methylation status in SV grafts, 452 CG-DMRs, 1303 CHG-DMRs, and 7758 CHH-DMRs were hypermethylated in PV grafts, with 482 CG-DMRs, 1561 CHG-DMRs, and 8031 CHH-DMRs showing hypomethylation. The identified DMRs were annotated according to their position in the genome and the annotation information of the genome. Most DMRs were located in the distal intergenic regions with fewer DMRs in promoters, introns, and exons and very few DMRs in the 3′UTR and 5′UTR. In the distal intergenic regions and promoters, the number of hypomethylated DMRs for each C context was uniformly found to be more than that of hypermethylated DMRs. In addition, the number of hypermethylated or hypomethylated DMRs in the CHH context was the highest, followed by those of CHG-DMRs and CG-DMRs in the distal intergenic regions, promoters, and introns (Figure 6; Table S2).

3.3. GO and KEGG Analysis of DMGs

In the pecan grafts, a total of 849, 2114, and 6333 DMGs were detected for the CG, CHG, and CHH contexts, respectively (Table S2). GO and KEGG analyses were performed to analyze the gene functions of these DMGs. The GO annotation results were consistently found based on the analysis of CG-DMGs, CHG-DMGs, and CHH-DMGs contexts (Figure 7; Figure S6). In terms of biological processes, the largest number of DMGs were annotated with terms of metabolic process, cellular process, and single-organism process. In addition, the DMGs were involved in regulation activities with most genes enriched at three cellular components, cell, cell part, and membrane. In terms of molecular function, catalytic activity and binding enriched the most DMGs. Based on enrichment analysis using Fisher’s exact test, DMRs were significantly enriched in the biological processes that potentially affect graft growth (p < 0.05; Table S3). For example, the CG-DMGs were enriched in regulation of the ethylene-activated signaling pathway (GO:0010104) and jasmonic acid biosynthetic process (GO:0009695), the CHG-DMGs were enriched in defense response to virus (GO:0051607), and the CHH-DMGs were enriched in response to auxin (GO:0009733), abscisic acid (GO:0009737), cell wall macromolecule catabolic process (GO:0016998), cell differentiation (GO:0030154), asymmetric cell division (GO:0008356), and defense response (GO:0006952).
According to enrichment analysis of KEGG pathways, the CG-DMGs were significantly involved in phenylpropanoid biosynthesis, steroid biosynthesis, arginine biosynthesis, and alanine, aspartate and glutamate metabolism (p < 0.05). The CHG-DMGs were found to significantly correlate with the regulation of valine, leucine, and isoleucine biosynthesis, other glycan degradation, and glycosaminoglycan degradation (p < 0.05). For the CHH-DMGs, most (91 genes) were significantly assigned to plant hormone signal transduction (p < 0.05; Figure 8; Figure S7).
Based on analysis of GO and KEGG, a total of 17 genes were identified that were significantly enriched in the GO terms of response to hormones (15 for GO terms of response to auxin and 2 for the terms of response to abscisic acid) and the KEGG pathway of plant hormone signal transduction. The DMGs contained 31 DMRs, including 14 hypermethylated DMRs and 17 hypomethylated DMRs, all of which were located in the promoter and distal intergenic regions. Additional information regarding the selected genes is provided in Table S4.

4. Discussion

As an important research topic in horticultural crops, the mechanisms driving rootstock-induced changes in scion vigor remains poorly understood. DNA methylation is an important regulator of gene expression and plant developmental processes. Recent studies suggested that DNA methylation may be involved in the grafting process, but little is known about the involved mechanisms. As a reliable technology to detect DNA methylation on a genome-wide scale at single-base resolution, WGBS has been applied to some plants, such as A. thaliana, rice (Oryza sativa L.), soybean (Glycine max L. Merrill Cv. Jack), poplar (Populus trichocarpa Torr. and Gray), and white birch (Betula platyphylla Suk.) [26,27,28,29,30]. To date, there have been no reports on methylation sequencing in pecan. In this study, WGBS was conducted to detect DNA methylation in two sets of pecan grafts with different growth vigor (SV and PV) on tall and short rootstocks, revealing the DNA methylomes in pecan for the first time. Based on analysis of the methylation profiles, DMRs and DMGs were identified between SV and PV grafts. Furthermore, the DMGs were subjected to functional analysis to explore the potential involvement of DNA methylation in rootstock-induced growth alterations.

4.1. Pecan Methylation Patterns

Currently, we have obtained more knowledge on the genetic characteristics of pecan based on previous studies, such as the application of molecular markers [31,32] and recent revelation of pecan genome [23]. However, little is known on pecan epigenome. In present study, WGBS was applied for the first time to reveal methylome of pecan on a genome-wide scale, which is of great significant to full understanding of pecan epigenome and further epigenetic research on pecan.
According to detection of methylation status in the cytosines, methylated cytosines accounted for 24.52%–25.60% of all cytosines in the six pecan samples, which were similar to the cytosine percentage in rice (24.3%) [28], but were about four times higher than that in wild-type A. thaliana [26]. It was found that the methylation levels were highest in the CG context (66.77%–67.85%), followed by those in the CHG (54.16%–55.31%) and CHH (14.21%–15.37%) contexts, which was a common trend consistent with other plants [27,29]. However, obvious differences in methylation levels can be observed. For instance, methylation levels in poplar were reported to be 41.9%, 20.9%, and 3.25% in CG, CHG, and CHH, respectively [27], which were lower than those we observed in pecan. In all methylated cytosines in pecan, the percentages of mCG were found to be the lowest, while the largest percentages were found to be of mCHH. The opposite results were reported for rice and wild-type A. thaliana with the highest ratios being for mCG and the lowest ratios for mCHH [26,28]. In addition, a methylation study on soybean seed development suggested that methylation distribution levels can also change in the same species during different developmental stages, with the largest percentages being observed for mCHH during the middle and late seed maturation stages, but with the largest percentages for mCG being during early seed maturation stages [30]. It is known that the establishment, maintenance, and removal of methylation in CG, CHG, and CHH contexts are catalyzed by various enzymes, which results in a specific methylation state [33]. Therefore, in response to the different intrinsic environments of different species or developmental processes, the regulation activities of the enzymes related to methylation may be affected, which may induce alterations in methylation. In addition, a previous study suggested the higher methylation ratios for each context in Brassica rapa L. compared with those in A. thaliana may result from higher levels of repeat sequences [34]. Thus, the distinct genome composition in a species may also affect the methylation levels.
Genes contain different functional elements, and the distribution of methylation in different gene regions always attracts our attention for investigation. In this study, it was found that methylation levels in CG context tend to show a peak in the gene bodies and presented an obvious drop between the gene bodies and flanking regions. The similar characteristics in methylation distribution was also found in other plants, such as A. thaliana, soybean, and white birch [27,29,30], which may be attributed to their common evolutionary origin. To further explore gene body methylation, the methylation levels across introns and exons were compared. It was obtained herein that methylation levels in the introns were higher than those in the exons, which was consistent with the results from white birch [29]. However, as Feng et al. reported, the eight diverse plant and animals commonly showed the reverse trend, with the lower CG methylation levels in the introns relative to those in the exons [27]. It has been shown that nucleosome positioning affected the targeting of DNA methyltransferases in different DNA regions [35]. Therefore, there may be differences in nucleosome enrichment across exons and introns among diverse species, due to the distinct evolutional degrees where they are, which possibly influences the DNA methylation levels in exons and introns. Certainly, the reasons for the different distribution characteristics of methylation across exons and introns in diverse species are complicated, and need to be further explored. In addition, this study suggested that methylation levels in the repeats were higher than those in the gene regions, and the repeat bodies had higher methylation levels than those in the upstream and downstream of repeats. This was in agreement with the results from A. thaliana, rice, poplar and white birch [27,29]. Notably, methylation levels in CHG were found higher in the repeats of poplar and pecan than those of A. thaliana and rice. From this, it can be seen that there were certain methylation differences in the repeats between herbaceous and woody plants.

4.2. Methylation Alterations Induced by Grating with Different Rootstocks

The finding that siRNAs can move through grafts to direct DNA methylation in scions [9,10] prompted us to start being concerned about the involvement of methylation changes in grafting process. One hetero-grafting study demonstrated that cucumber (Cucumis sativus L.) and melon (Cucumis melo L.) scions grafted on pumpkin [Cucurbita moschata (Lam.) Poir.] presented significantly increased methylation levels compared to that of their respective seed-plant control [13]. The study on rubber [Hevea brasiliensis (Willd. ex A, Juss.) Muell. Arg.] trees obtained methylation levels ranging from 16.42% to 19.80% in the scions on different rootstocks [14]. Hetero-grafting experiments on eggplant also revealed that CHH methylation levels significantly decreased by 3.37% and 2.58% in eggplant scions grafted on S. torvum and ‘Emperador RZ’ rootstocks, respectively, compared to those of the self-grafted plants [15]. The detailed data provided in these studies reflected the overall methylation changes induced by rootstocks. Wu et al. found that the methylation levels were largely not affected by rootstocks, and mainly focused on the methylation changes in the amplified sites [12]. They revealed that more than 10% of the detected sites exhibited methylation changes in tomato scions grafted on eggplant, and eggplant scions on tomato, compared with their respective seed-plants. In the present study, by analysis of the methylation profiles in a genome-wide scale, no significant differences were found in the methylation levels between SV and PV grafts, while a total of 934, 2864, and 15,789 DMRs were identified in the CG, CHG, and CHH contexts, respectively. In the cytosine sites of SV and PV grafts, the reverse variation direction of methylation patterns may be one of the reasons for no significant differences in methylation levels. Furthermore, at the genome-wide level, the methylation variation in part of the sites may not significantly affect the overall methylation levels. The DMRs reflect more specifically the methylation changes, and the identification of so many DMRs in the three C contexts fully explained the extensive methylation alterations in pecan scions induced by different rootstocks. However, the exact mechanism is unknown on driving the methylation differences, even though it has been reported that the mobile siRNAs can direct DNA methylation [9,10]. Rootstocks are known to be able to change the physiological environments in scions, such as water potentials, concentrations of mineral elements, and hormones [36,37,38]. In view of the fact that DNA methylation can be alterated in response to various environment stresses [39,40,41], we speculate that the methylation alterations in scions may be responsive to the environmental changes induced by different rootstocks, in addition to being possibly directed by the siRNA transported from rootstocks.
According to the obtained results in the present study, although the methylation levels in CG were highest throughout genome, the methylation changes in CHG and CHH were more frequent. The similar results were also reported previously [15,30,42]. Apart from the significant decrease in CHH methylation found in grafted eggplants [15], CHH methylation was reported to change significantly and the CHH-DMRs account for most of the DMRs during the developmental processes of soybean seeds [30]. Domb et al. also found that specific elimination of CG methylation did not dysregulate genes or transposons, and, in contrast, exclusive removal of non-CG methylation massively up-regulated genes and transposons [42]. In the light of these results, it is speculated that CHH or CHG methylation may be more sensitive to plant growth signal and more closely related to growth regulation. This study mainly revealed the methylation alterations in pecan grafts induced by different rootstocks, and, on this basis, further research on their transcriptional roles could help elucidate the grafting mechanisms.
In this study, we also localized the identified DMRs and found that most DMRs were in the distal intergenic regions and promoters, with very few DMRs in the 3′UTR or 5′UTR. According to the existing reports, methylation of the promoter in the upstream region of a gene generally repressed gene expression, while different effects of methylation in the gene body have been revealed in previous studies [28,43]. However, little is known regarding the regulatory roles of methylation in distal intergenic regions. As is well known, the intergenic regions account for a large proportion of the genome in plants. These regions were previously thought to lack biological functions and were considered as “junk DNA”; however, their biological functions have started to be revealed in recent years. For example, a recent study on maize (Zea mays L.) demonstrated that KERNELROW NUMBER4 (KRN4), an intergenic quantitative trait locus (QTL) for kernel row number, can regulate the expression of UNBRANCHED3 (UB3) as a distal enhancer and mediate inflorescence development [44]. Therefore, it is necessary to further study the effects of methylation on the regulatory roles of intergenic regions based on the substantial methylation differences in distal intergenic regions.

4.3. Involvement of Methylation in Graft Growth Regulation

Given the many methylation alterations between SV and PV grafts and the important roles of methylation in biological processes, it was reasonable to believe that methylation changes may produce functional consequences. Functional analysis of the DMGs could enable us to understand the potential involvement of methylation in graft growth. In the current study, 849 CG-DMGs, 2114 CHG-DMGs, and 6333 CHH-DMGs were detected. According to GO enrichment analysis of the genes, the DMGs were found to be involved in various biological processes that potentially affect plant growth, such as cell activities, plant hormone synthesis and signal regulation, and defense response. It can be presumed that methylation may have regulated theses growth-related genes to influence growth vigor of the pecan grafts. There have been previous studies revealing gene expression changes in scions with different growth vigor induced by rootstocks [45,46,47]. However, little is known regarding the genes that are potentially regulated by methylation alterations induced by grafting. Through WGBS, this study provided abundant information on methylation variation and the related genes for a deep revelation regarding the molecular regulatory mechanisms of grafting-induced growth vigor.
Notably, this study identified 17 DMGs that were significantly enriched in both GO terms (15 genes enriched in response to auxin and two genes enriched in response to abscisic acid) and a KEGG pathway (plant hormone signal transduction). This implies that these genes may be closely associated with response to auxin and abscisic acid (ABA), which are generally regarded as plant growth promoter and inhibitor, respectively [48,49]. It has been known that hormone-responsive genes are activated or repressed under control of hormones, and play important roles in physiological effects through mediation of hormone signal transduction [50,51,52]. Therefore, we speculate that under the stimulus of hormones in grafts, the methylation alterations may be the important factor controlling the gene expression to influence the growth of pecan grafts.
This study located genes with methylation changes in SV and PV grafts that had different growth vigor, which lays a good foundation for revealing the molecular mechanisms driving grafting-induced growth alterations. To better understand the molecular mechanisms associated with grafting, the effects of methylation on gene expression need to be explored in the future, even though it seems difficult to reveal potential joint regulatory roles of methylation in the distinct C contexts of different gene regions and possible interference of other regulation factors, such as miRNAs. Further studies are also needed to validate the roles of DMGs in graft growth regulation.

5. Conclusions

In the current study, we used WGBS to develop a DNA methylation study on two sets of pecan grafts with different growth vigor (SV and PV) on tall and short rootstocks. The DNA methylomes throughout the pecan genome were revealed for the first time. Based on pecan methylation profiles, large amount of DMRs were identified in SV and PV grafts, reflecting extensive differences in methylation induced by different rootstocks. The functional analysis of DMGs showed that they were involved in the biological processes that likely affect graft growth, such as cell activities, plant hormone synthesis and signal regulation, and defense response. In particular, we identified 17 DMGs that were most likely related to response to auxin and ABA, which may have especially important roles in the regulation of graft growth. This study demonstrated the potential involvement of DNA methylation in rootstocks-induced growth changes in pecan scions.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f14010004/s1. Figure S1: Significantly different growth vigor in two groups of pecan grafts (SV and PV), Figure S2: Characteristics of 9-base pair sequences with methylated CG, CHG and CHH (SV2, SV3, PV1, PV2, and PV3), Figure S3: Circle plot of methylation distribution in pecan chromosomes (SV2, SV3, PV1, PV2, and PV3), Figure S4: Methylation distribution in different gene regions (SV2, SV3, PV1, PV2, and PV3), Figure S5: Methylation distribution in repeat regions (SV2, SV3, PV1, PV2, and PV3), Figure S6: GO annotation of DMGs in CG and CHG contexts, Figure S7: KEGG enrichment analysis of DMGs in CG and CHG contexts, Table S1: Statistics of methylated cytosines, Table S2: DMRs and DMGs, Table S3: GO enrichment analysis of DMGs, Table S4: The DMGs in CHH context potentially related with hormone regulation.

Author Contributions

F.P. and Z.L. conceived and designed the study. Z.L. collected experimental data, analyzed, and wrote the manuscript. P.T., Y.L. (Youwang Liang) and K.Z. provided help in data analysis and improving manuscript. Y.S. participated in collection of samples. Y.L. (Yongrong Li) provided the rootstocks. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by a grant from the National Key R&D Program of China (2021YFD1000403), the Promotion and Demonstration Project of Forestry Science and Technology of Central Government ([2022]TG04), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) and the Doctorate Fellowship Foundation of Nanjing Forestry University.

Data Availability Statement

Not Applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The methylation levels in pecan grafts. SV1, SV2, SV3: grafts with strong growth vigor; PV1, PV2, PV3: grafts with poor growth vigor. (a) Methylation level was determined based the number of methylated cytosines (mC) of each context/the number of all C sites of the same C context; (b) Relative methylation level represented the percentage of methylated CG, CHG or CHH among all methylated cytosines (H = A, T, or C).
Figure 1. The methylation levels in pecan grafts. SV1, SV2, SV3: grafts with strong growth vigor; PV1, PV2, PV3: grafts with poor growth vigor. (a) Methylation level was determined based the number of methylated cytosines (mC) of each context/the number of all C sites of the same C context; (b) Relative methylation level represented the percentage of methylated CG, CHG or CHH among all methylated cytosines (H = A, T, or C).
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Figure 2. Distribution of methylation levels at single cytosine (C) sites of CG (a), CHG (b) and CHH (c) contexts in pecan grafts (H = A, T, or C). SV1, SV2, SV3: grafts with strong growth vigor; PV1, PV2, PV3: grafts with poor growth vigor. The ordinate represents the methylation level of C sites, and the width of each violin graph represents the density of C sites at that methylation level.
Figure 2. Distribution of methylation levels at single cytosine (C) sites of CG (a), CHG (b) and CHH (c) contexts in pecan grafts (H = A, T, or C). SV1, SV2, SV3: grafts with strong growth vigor; PV1, PV2, PV3: grafts with poor growth vigor. The ordinate represents the methylation level of C sites, and the width of each violin graph represents the density of C sites at that methylation level.
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Figure 3. Characteristics of 9-base pair sequences with methylated CG, CHG and CHH (H = A, T, or C) in pecan. (a–c) represent the sequence characteristics in the Watson strand, and (d–f) represent that in Crick strand. The abscissa refers to the position of bases at the methylation sites and the height of base signal at each position refers to the relative frequency of the bases at that position. The graphs were obtained based on the methylation data of SV1 pecan graft (One of the three pecan grafts with strong growth vigor).
Figure 3. Characteristics of 9-base pair sequences with methylated CG, CHG and CHH (H = A, T, or C) in pecan. (a–c) represent the sequence characteristics in the Watson strand, and (d–f) represent that in Crick strand. The abscissa refers to the position of bases at the methylation sites and the height of base signal at each position refers to the relative frequency of the bases at that position. The graphs were obtained based on the methylation data of SV1 pecan graft (One of the three pecan grafts with strong growth vigor).
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Figure 4. DNA methylation distribution in pecan genome. (a) Circle plot of methylation distribution in pecan chromosomes. The outermost circle refers to the chromosomes of the pecan. Light blue, blue and green bars represent the methylation levels in CG, CHG, and CHH contexts, respectively (H = A, T, or C). The innermost circle with color of gray represent the number of genes, and the darker the color is, the more genes there are. (b) Methylation levels in different gene regions (d: upstream; e: first exon; f: first intron; g: inner exon, h: inner intron; i: last exon; j: downstream). (c) Methylation levels in different repeat regions (k: upstream; l: repeat body; m: downstream). TSS: Transcription start site; TTS: Transcription termination site. The graphs were plotted based on the methylation data of SV1 pecan graft (one of the three pecan grafts with strong growth vigor).
Figure 4. DNA methylation distribution in pecan genome. (a) Circle plot of methylation distribution in pecan chromosomes. The outermost circle refers to the chromosomes of the pecan. Light blue, blue and green bars represent the methylation levels in CG, CHG, and CHH contexts, respectively (H = A, T, or C). The innermost circle with color of gray represent the number of genes, and the darker the color is, the more genes there are. (b) Methylation levels in different gene regions (d: upstream; e: first exon; f: first intron; g: inner exon, h: inner intron; i: last exon; j: downstream). (c) Methylation levels in different repeat regions (k: upstream; l: repeat body; m: downstream). TSS: Transcription start site; TTS: Transcription termination site. The graphs were plotted based on the methylation data of SV1 pecan graft (one of the three pecan grafts with strong growth vigor).
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Figure 5. The percentages of hypermethylation CG island (CGI) regions distributed in different gene regions of pecan genome. SV1, SV2, SV3: grafts with strong growth vigor; PV1, PV2, PV3: grafts with poor growth vigor. UTR: untranslated region.
Figure 5. The percentages of hypermethylation CG island (CGI) regions distributed in different gene regions of pecan genome. SV1, SV2, SV3: grafts with strong growth vigor; PV1, PV2, PV3: grafts with poor growth vigor. UTR: untranslated region.
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Figure 6. Statistics of differentially methylated regions (DMRs) in SV and PV grafts (SV: grafts with strong growth vigor; PV: grafts with poor growth vigor). (a) The number of DMRs in CG, CHG and CHH contexts. The number of DMRs in different gene regions in the CG (b), CHG (c) and CHH (d) contexts (H = A, T, or C). Hypermethylation and hypomethylation in DMRs represent the methylation changes in PV grafts relative to the methylation status in SV grafts. UTR: untranslated region.
Figure 6. Statistics of differentially methylated regions (DMRs) in SV and PV grafts (SV: grafts with strong growth vigor; PV: grafts with poor growth vigor). (a) The number of DMRs in CG, CHG and CHH contexts. The number of DMRs in different gene regions in the CG (b), CHG (c) and CHH (d) contexts (H = A, T, or C). Hypermethylation and hypomethylation in DMRs represent the methylation changes in PV grafts relative to the methylation status in SV grafts. UTR: untranslated region.
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Figure 7. Gene Ontology (GO) annotation of differentially methylated region (DMR)-related genes (DMGs) in CHH type (H =A, T, or C) in SV and PV grafts (SV: grafts with strong growth vigor; PV: grafts with poor growth vigor).
Figure 7. Gene Ontology (GO) annotation of differentially methylated region (DMR)-related genes (DMGs) in CHH type (H =A, T, or C) in SV and PV grafts (SV: grafts with strong growth vigor; PV: grafts with poor growth vigor).
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Figure 8. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of differentially methylated region (DMR)-related genes (DMGs) in CHH type (H = A, T, or C) in SV and PV grafts (SV: grafts with strong growth vigor; PV: grafts with poor growth vigor). The circle size represents the gene number. The coloring of circles represents p-value, indicating the enrichment significance of DMGs in KEGG pathways.
Figure 8. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of differentially methylated region (DMR)-related genes (DMGs) in CHH type (H = A, T, or C) in SV and PV grafts (SV: grafts with strong growth vigor; PV: grafts with poor growth vigor). The circle size represents the gene number. The coloring of circles represents p-value, indicating the enrichment significance of DMGs in KEGG pathways.
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Table
Table 1. Whole-genome bisulfite sequencing data in two sets of pecan grafts with different growth performances. SV: grafts with strong growth vigor on tall rootstocks; PV: grafts with poor growth vigor on short rootstocks.
Table 1. Whole-genome bisulfite sequencing data in two sets of pecan grafts with different growth performances. SV: grafts with strong growth vigor on tall rootstocks; PV: grafts with poor growth vigor on short rootstocks.
SampleClean BasesGC (%)Clean ReadsUnique ReadsMapped (%)Conversion Rate (%)
SV125,202,430,60022.4284,008,10265,482,39877.95 99.32
SV219,950,784,20021.9466,502,61451,044,26176.76 99.27
SV322,336,860,60021.5774,456,20256,215,23875.50 99.21
PV122,141,198,20021.5373,803,99456,631,16676.73 99.29
PV221,764,759,40021.7972,549,19855,861,16077.00 99.18
PV321,762,984,30021.7872,543,28154,898,02175.68 99.24
Note: GC (%): The number of guanines (G) and cytosines (C)/the number of all bases. Mapped (%): The number of unique reads/number of total clean reads. Conversion rate (%): Bisulfite conversion rate, the number of clean reads mapped to lambda DNA that support methylated cytosines/the number of total clean reads mapped to lambda DNA.
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Liu, Z.; Tan, P.; Liang, Y.; Shang, Y.; Zhu, K.; Peng, F.; Li, Y. Grafting with Different Rootstocks Induced DNA Methylation Alterations in Pecan [Carya illinoinensis (Wangenh.) K. Koch]. Forests 2023, 14, 4. https://doi.org/10.3390/f14010004

AMA Style

Liu Z, Tan P, Liang Y, Shang Y, Zhu K, Peng F, Li Y. Grafting with Different Rootstocks Induced DNA Methylation Alterations in Pecan [Carya illinoinensis (Wangenh.) K. Koch]. Forests. 2023; 14(1):4. https://doi.org/10.3390/f14010004

Chicago/Turabian Style

Liu, Zhuangzhuang, Pengpeng Tan, Youwang Liang, Yangjuan Shang, Kaikai Zhu, Fangren Peng, and Yongrong Li. 2023. "Grafting with Different Rootstocks Induced DNA Methylation Alterations in Pecan [Carya illinoinensis (Wangenh.) K. Koch]" Forests 14, no. 1: 4. https://doi.org/10.3390/f14010004

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