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DNA methylation changes in fusarium wilt resistant and sensitive chickpea genotypes (Cicer arietinum L.)
Accepted Manuscript DNA methylation changes in fusarium wilt resistant and sensitive chickpea genotypes (Cicer arietinum L.) Parvin Mohammadi, Bahman Bahramnejad, Dr., Hedieh Badakhshan, Homayoun Kanouni PII:
S0885-5765(15)30006-0
DOI:
10.1016/j.pmpp.2015.06.001
Reference:
YPMPP 1117
To appear in:
Physiological and Molecular Plant Pathology
Received Date: 28 January 2015 Revised Date:
26 May 2015
Accepted Date: 2 June 2015
Please cite this article as: Mohammadi P, Bahramnejad B, Badakhshan H, Kanouni H, DNA methylation changes in fusarium wilt resistant and sensitive chickpea genotypes (Cicer arietinum L.), Physiological and Molecular Plant Pathology (2015), doi: 10.1016/j.pmpp.2015.06.001. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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DNA methylation changes in fusarium wilt resistant and sensitive chickpea genotypes (Cicer arietinum L.) Parvin Mohammadi1, Bahman Bahramnejad1, Hedieh Badakhshan1, Homayoun Kanouni2 Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Kurdistan,
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1
Sanandaj, Iran
Research Center for Agriculture and Natural Resources, Sanandaj, Iran
Corresponding author: Dr. Bahman Bahramnejad Department of Agricultural Biotechnology
P. O. Box: 416, Sanandaj, Iran
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Tel: 0098 871 6620552
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University of Kurdistan
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2
Fax: 0098 871 6620553
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E-mail: [email protected]
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Abstract DNA methylation plays an important role in the regulation of gene expression in biotic and abiotic stresses. In the present study, a methylation-sensitive amplified polymorphism (MSAP)
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analysis was performed to profile DNA methylation changes in seven resistant and sensitive chickpea genotypes following inoculation with Fusarium oxysporum f. sp. ciceris. In all, 27468 DNA fragments, each representing a recognition site cleaved by either or both of two isoschizomers,
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were amplified using nine selective primer pairs. DNA methylation was evaluated in leaves, stems and roots in control and inoculated plants. Extensive cytosine methylation alterations were found in pathogen-treated
genotypes
compared
with
the
corresponding
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the
control,
including
hypermethylation and demethylation as well as the potential conversion of methylation types. For all genotypes, the percentage of demethylated sites were more than methylated sites in infected plants compared with the corresponding control. No significant differences were observed for
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banding patterns in infected and control leaf tissues, while the differences between percentage of unchanged, methylated and demethylated sites were significant in stem and root tissues. The total numbers of methylated polymorphic bands ranged from 137 to 154 bands in Sel95th1716and
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Arman, accounting for 36.81% to 44.64% of all bands, respectively. Ten fragments that were differentially amplified between infected and control plants were isolated and sequenced in three
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tissues separately. Most of sequenced fragments showed homology with disease related genes in GenBank. The results suggest that significant differences in cytosine methylation exist between resistant and sensitive chickpea genotypes, and that hypermethylation or hypomethylation of specific genes may be involved in the chickpea resistance to Fusarium wilt. Keywords DNA methylation, chickpea, fusarium wilt, MSAP marker
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List of abbreviations AFLP
Amplified Fragment Length Polymorphism
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AUDPC Area under the Disease Progress Curve IDD Disease Intensity Index Fusarium oxysporum f. sp. ciceris
MSAP
Methylation Sensitive Amplified Polymorphism
SAUDPC
Standardize Area under the Disease Progress Curve
Introduction
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1.
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FOC
Plants usually adapt to complex and changeable environmental stresses through reversible epigenetic modifications. DNA in most eukaryotic genomes is modified by methylation of cytosine residues (5mC) within the di-nucleotide CpG and the tri-nucleotide CpNpG sequences.
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DNA methyl-transferases, a group of enzymes, catalyze the transfer of methyl group from the pyrimidine ring of cytosine residues. DNA methylation is implicated in gene regulation, genomic imprinting [12], the timing of DNA replication [26], determination of chromatin
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structure [47] and the control of parasitic DNA elements in plants and response to stresses [59]. Levels of methylation vary greatly in different organisms. The percentage of methylated
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cytosines in genome ranges from 0-3% in insects, 2-7% in vertebrates, 10% in fish and amphibians, to more than 30% in some plants [1] The methylation of cytosine in plant nuclear DNA usually occurs in both CpG and CpNG sequences, whereas in vertebrates it is located almost exclusively in CpG [19]. Mainly three types of assays have been developed for the detection of DNA methylation. In the first method, methylated DNA fragments can be isolated by affinity purification using
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proteins that preferentially bind methylated DNA, or by immuno-precipitation using anti-mC antibodies (mCIP) [13]. A second method involves treating genomic DNA with sodium bi-sulfite, a process that converts unmethylated cytosines to uracils. Following PCR amplification and
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sequencing of bisulfite-treated DNA, methylated cytosines can be identified as those that remains as cytosines whereas unmethylated cytosines appear as thymines [23]. The third method is methylation-sensitive amplified polymorphisms (MSAP) that involves digestion of genomic DNA
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by methylation-sensitive restriction enzymes such as MspI and HpaII for which digestion is blocked by methylation [40]. It is a modification of the AFLP (Amplified Fragment Length Polymorphism)
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technique in which the isoschizomers HpaII and MspI are employed as ‘frequent-cutter’ enzymes. Both HpaII and MspI recognize 5’-CCGG-3’ but display differential sensitivity to DNA methylation (Fig. 1).
Previous studies showed that the DNA methylation level in plant changes dynamically in
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response to environmental stimuli. Environmental stimuli, such as cold [55], drought [32; 56; 58], salt [56; 58; 63], and metals [2; 30] are known to alter cytosine methylation throughout the genome and at specific loci. Plants have evolved the DNA methylation approach as a major defense strategy
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against biotic stress. Upon exposure to biotic stresses, plants 'immunecomponents', such as recognition of pathogen-associated molecular patterns (PAMPs) and the basal defense machinery,
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are activated as a process of defense priming [42]. Clear evidence of dynamic changes in DNA methylation following pathogen attack, as well as the functional consequences of differential methylation in regulating defense-related genes has been reported [15]. The MSAP technique has been applied to evaluate the level and pattern of cytosine methylation in plants upon biotic stresses. DNA methylation analysis by MSAP showed the induction of post-transcriptional gene silencing in tomato infected with the tomato yellow leaf curl Sardinia virus [39]. Significant differences in
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cytosine methylation were observed between seedlings and adult rice plants after inoculation with the pathogen Xanthomonas oryzae pv. oryzae [51]. Furthermore, analysis of DNA methylation in potato showed change in the transcript levels of genes in response to
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Burkholderia phytofirmans strain PsJN in infected plants [14].
Chickpea production is limited worldwide by fusarium wilt caused by Fusarium oxysporum. f. sp. ciceris [33]. Fusarium wilt is one of the most important and destructive vascular disease of
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chickpea [31]. After infection, the fungus enters roots and spreads systemically through the host’s vascular system and blocks the plant's transport system. Disease symptoms such as
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yellowing and wilting appear after disease progress. Vascular discoloration occurs from the roots to the young stems, followed by a yellowing and wilting of the leaves before final necrosis [35]. Transcriptomic analysis revealed that a large set of genes is differentially expressed during fusarium wilt infections in chickpea [6]. In addition, previous works show that chickpea
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genotypes have very different reactions to fusarium wilt, ranging from very sensitive to resistant [22, 7].
To date, little is known about the mechanism of resistance and epigenetic control of gene
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expression in chickpea. Seven chickpea cultivars that showed different response to fusarium wilt were selected. To investigate whether changes in DNA methylation might be involved in gene
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expression during infection in resistant and susceptible cultivars, MSAP was used to assay the methylation status of genomic DNA in leaves, roots, and stems of plants that had been inoculated with Fusarium oxysporum f. sp. ciceris and control plants. 2.
Materials and methods
2.1.
Disease Evaluation
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Seven genotypes of chickpea were used in the present study. The genotypes were provided by the Agricultural and Natural Resources Center of Kurdistan, Sanandaj, Iran. The code number,
ciceris (FOC) strain used in this study was previously described [28].
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name and origin of these genotypes are shown in table 1. Isolation of the Fusarium oxysporum f. sp.
The resistant/susceptible reaction of genotypes to pathogen was evaluated under greenhouse conditions. Each pot represented an experimental unit, and treatments were replicated three times,
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each pot containing three chickpea plants. Seeds of each genotype were sown in sterilized soil infested with 10 cfu/g of pathogen isolate. The symptoms of disease were recorded daily from one
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to three weeks after planting. Disease severity was assessed for each plant on a 0 to 4 rating scale according to the percentage of chlorosis, necrosis and wilt, as follows: 0= healthy, 1=1-33%, 2=33%-66%, 3= 66%- 100%, 4= dead plant [10]. The occurrence of vascular infection was determined in symptomless plants in order to validate the experiment. Stems were cut into 5-10 mm
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large pieces, surface disinfected in 0.2% NaCLO for two min, then plated on potato dextrose agar (PDA) and incubated at room temperature [43]. A disease intensity index (DII) was determined based on wilt incidence and severity of symptoms data by the following equation: DII = (∑Si Ni). 4× Nt, where Si = symptoms severity; Ni = number of plants with Si symptom severity; and Nt =
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total number of plants. DII was used as a representative of the mean value of disease intensity at any
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given moment. The standardized area under the disease progress curve (SAUDPC) was calculated based on the plots of DII values over time (days) [10]. Differences among the genotypes for disease severity were evaluated using analysis of variance (ANOVA). Squared Euclidean distance matrix among genotypes was calculated based on the SAUDPC. The grouping of genotypes was conducted by XLSTAT software, a statistical analysis add- Ins for Microsoft Excel.
2.2.
Genomic DNA extraction
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Total genomic DNA was extracted from leaf, root and stem tissues of infected and control chickpea genotypes. For infected plants samples were taken when disease symptoms were appeared and for control plant at the same time. Total DNA was isolated from leaf samples using
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CTAB [49]. The DNA of root and stem tissues was extracted by using SDS method [27]. Quantity and quality of the isolated DNA was evaluated by spectrophotometer (Eppendorf, Germany) and 0.8% agarose gel electrophoresis respectively. Methylation-sensitive amplification polymorphism analysis
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2.3.
MSAP analyses were conducted in accordance with Cervera et al (2002) method by minor
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modification. Two enzyme combinations EcoRI/MspI and EcoRI/ HpaII were used for analysis. Digestion and ligation of DNA was performed as following [11]: DNA digestion was conducted at 37˚C with 5 U each of EcoRI and HpaII (Thermo Scientific) in 25µl of Tango (MBI) buffer. One adapter for EcoRI sticky ends and another for HpaII/MspI sticky ends were designed. The
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sequence information of the adapters and primers are provided in Table 2. After digestion, a 5µl mixture was used containing 5 pmol of EcoRI adapter, 50 pmol of HpaII/MspI adapter, 8 mM ATP, 10 mM TRIS-acetate pH 7.5, 10 mM magnesium acetate, 50 mM DTT, and 1.4 U of T4
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DNA ligase (Thermo Scientific). The mixture was incubated for 3 h at 37˚C and overnight at 4˚C. For the first amplification reaction, ligated DNA fragments were diluted fivefold and used
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as template. The applied primers in the first amplification step were complementary to EcoRI and HpaII/MspI adapters with addition of 3 selective nucleotides (table 2). Preamplification was carried out with 2 µl of diluted ligated product and 10 pmol of preselective primers. The PCR reaction used the following program: 25 cycles of 94˚C for 30 s, 56˚C for 30 s, 72˚C for 1 min, and finally, 10 min at 72˚C. The product was diluted to 250µl and used for selective amplification. Selective amplification was carried out using 2µl of diluted pre-
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amplification product and 4 pmol of each selective primer (Table 2). The PCR program for amplification was conducted as follows: 1 cycle of 94˚C for 5 min, 1 cycle of 94˚C for 30 s, 56˚C for 30 s, and 72˚C for 1 min, followed by 12 cycles with a 0.7˚C decrease in annealing temperature
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per cycle, and 23 cycles of 94˚C for 30 s, 56˚C for 30 s, and 72˚C for 1 min, and a final extension of 72 ˚C for 7 min. The final products were denatured at 95˚C for 5 min and separated on 4.5% polyacrylamide gels. The staining of the gels was performed based on silver-nitrate staining [8].
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Scoring followed a previously published methylation method [50]. The frequencies of methylation changes were compared between different genotypes using G tests, as implemented in PROC
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FREQ, SAS 9.1 for Windows (SAS Institute Inc., Cary, NC, USA).
Amplified fragments were separated from gel and PCR was conducted with the primer combinations which were used in selective amplification [11]. After purification of amplified products, DNA fragments were sequenced at commercial sequencing service (Bioneer Inc. Bioneer
3.
Results
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Corporation).
One way analysis of variance (ANOVA) was performed to compare of the chickpea genotypes
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for average AUDPC. The average AUDPC was calculated based on two weeks rates. Significant differences were observed among genotypes (Fig. 2). Sel95th1716 and Kaka were the most resistant
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and sensitive chickpea genotype to fusarium wilt, respectively. Cluster analysis was conducted based on the average of AUDPC using squared Euclidean distance and UPGMA algorithm. The genotypes were divided into three main groups. Kaka, Biovenig, Pirooz and Arman were grouped in the first cluster into two sub-clusters that were evaluated as sensitive. Sel95th1716 was individually evaluated resistant. The third cluster included FLIP02-50C and Azad that evaluated are showing partial resistance (Fig. 3).
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3.1.
Repeatability of MSAP
In a preliminary experiment, two primer combinations were selected randomly to determine
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the repeatability of MSAP markers. Two different chickpea genotypes including Kaka and Sel95th1916 were selected for this purpose. The MSAP test was performed for leaf, stem and root tissues of both infected and control plants separately. The banding patterns of the above mentioned separate experiments were compared on the same gel. More than 95% (96 and 96.5%
3.2.
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degree of reliability of this marker technique.
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Kaka and Sel95th1916, respectively) banding patterns were the same, implying a reasonable
Pathogen-induced methylation and demethylation changes
The changes in cytosine methylation patterns under pathogen infection stress were determined by comparing all possible banding patterns among control and infected samples. This comparison was
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performed for seven chickpea genotypes and three tissues separately. Three different banding patterns were observed on the gels (Table 3; Fig. 5). In class I, there were no distinguishable different banding patterns among control and infected genotypes. II represents cases where a band is
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missing as a result of demethylation in inoculated plants, whereas, possible induced cytosine methylation events were classified as class III. The three classes I, II and III were compared using G
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tests. The results of this test revealed that there were no significant differences for banding patterns in leaf tissues among genotypes. However, the cultivars (genotypes) did show significant differences between percentage of unchanged, methylated and demethylated sites in stem and root tissues (Table 4).
Approximately 77.98% to 83.79% of the CCGG sites remained unchanged under pathogen stress in leave tissue (Table 3) but the percent of demethylated and methylated bands in this tissue of different genotypes was estimated from 7.65 to 12.23 and 4.59 to 11.92, respectively.
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In root tissue, the percentage of unchanged, demethylated and methylated sites was 76.76 to 80.12, 9.78 to 13.15 and 8.56 to 11.02, respectively. In stem tissue, the estimated unchanged, demethylated and methylated sites were 78.9 to 83.79, 8.87 to 12.83 and 5.2 to 12.23 percent respectively. In
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general, the percent of demethylated sites were higher than methylated sites for all seven genotypes after infection. The lowest and highest methylated sites were in leaf tissues of resistant genotype (Sel95th1716) and in stem tissues of semi-resistant genotype (Arman). The lowest and highest
root tissues of resistant genotype (Azad). Pattern of DNA Methylation in different genotypes
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3.3.
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demethylated sites were detected in the leaf tissues of semi-resistant genotype (Arman) and in the
In this study, cytosine methylation at CCGG sites was assessed in three tissues of seven chickpea genotypes under stress (FOC infection) and control conditions using nine MSAP primer combinations. A total of 27468 clear and reproducible fragments were amplified. Each of the
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fragments is assumed to have at least one CG overhang terminus derived from the common CCGG recognition site and cleaved by one or both isoschizomers. To compare DNA methylation
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polymorphism in different chickpea genotype, the levels of DNA methylation in the healthy leaf tissues were analyzed (Table5). Based on the digestions with the isoschizomers, bands were divided
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into the following four types: Type I bands, present for both enzyme combinations; Type II and III bands respectively represented amplified products after digestion with EcoRI/HpaII or EcoRI/MspI enzymes, and Type IV bands, absent from both enzyme combinations. The hemi-methylated state of 5’-CCGG-3’ sites due to methylation in one DNA strand but not in its complementary strand is classified as Type II bands and the internal cytosine of 5’-CCGG-3’ methylation represented as Type III bands. Type IV bands are absent from both enzyme combinations but present in the other
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genotype. Type IV implies full methylation of both cytosine in the 5’-CCGG-3’ sequence in one sample but no methylation at the same site in the other. The total number of polymorphic methylated (hemi-methylated and fully methylated) bands
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were 137 to 154 (Type II+TypeIII+Type IV bands), accounting for 36.81% to 44.64% of all bands. Full-methylation (Type III) occurred more frequently than hemi-methylation (Type II), but the total number of these two kinds of methylated fragments was stable in each sample in all
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genotypes. The type IV bands were the main source of the DNA methylation changes that induced in different chickpea genotypes.
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Dendrograms based on methylation contents in leaf, root and stem tissues of seven chickpea genotypes in control and infected plants were prepared using UPGMA algorithm (Fig. 4). In all tissues except roots in control plants the clustering of genotypes was similar to grouping of genotypes based on AUDPC. The genotypes Sel95th1716, FLIP02-50C and Azad, which are
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resistant and semi-resistant genotypes were grouped in one cluster and the other genotypes were divided in a separate cluster with two sub-clusters. The genotype Sel95th1716 clustered with sensitive genotype Arman in the roots of control plants.
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The first group included susceptible genotypes Kaka and Biovenig. The second group contained semi-resistant genotypes Arman and Pirooz. Resistant genotypes Azad, FLIP02-50C,
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Sel95th1716were classified in the third group. The classification of genotypes based on methylation
content
was
consistent
with
grouping
of
genotypes
according
to
susceptible/resistance response to pathogen attack. Based on methylation contents of the different three tissues (leaf, stem and root) principal coordinate analysis (PCoA) was carried out and each tissue differentiated into three discrete groups (Fig. 6).
3.4.
Analysis of the Differentially Methylated DNA Sequences
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To obtain more information about the results of MSAP analysis, some fragments that were differentially amplified between infected and control plants were isolated and sequenced consistent. Distinct homology was detected in GenBank for 10 fragments (Table 6). Of these 10 fragments,
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eight fragments showed homology to genes with known functions and two had homology to a genomic DNA clone or predicted protein (Table 6). ST14 and KL18 fragments showed similarities to ribosomal protein S3 in chickpea and KL4 fragment was similar to 30S ribosomal protein S14 in
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Medicago truncatula. KL3 fragment had homology with Acetyl-CoA carboxylase beta in alfalfa. Sequence KL2 displayed very high similarity to salinity-stressed chickpea root (Cicer arietinum)
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cDNA. KR9 sequence displayed similarity to GTPase activating protein in chickpea. A fragment of KR10 matched a sequence in the cDNA library from Cajanus cajan roots exposed to fusarium wilt.
4.
Discussion
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In this study we have applied the MSAP technique to investigate the methylation pattern of chickpea DNA during infection by FOC. Our data demonstrate that fusarium wilt changes the methylation status of the chickpea genome and that MSAP is a powerful tool for identifying genes
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involved in plant fungi interactions. More than 95% of sites were repeatable for the same samples in two separate MSAP tests, demonstrating that the obtained results using the MSAP technique is
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fairly repeatable. Several previous studies have demonstrated that the MSAP technique is highly efficient for large-scale detection of cytosine methylation in plant genomes [60; 5; 36; 52; 11; 53; 63].
Cluster analysis of seven genotypes based on AUDPC and MSAP bands on infected plants produced similar groups. Resistant and susceptible cultivars were completely separated. AUDPC analysis classified genotypes in three groups resistant, semi resistant and sensitive. HajiAllahverdipoor et al (2011) evaluated Kaka, Biovenig, Pirooz and Arman genotypes as sensitive
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genotypes and Mahdieh (2005) evaluated Sel 95 th1716 as a resistant genotype [22; 37]. Evidence from proteins generating epigenetic marks showed their crucial roles in the plant defense against pathogens [4]. Demethylation of R gene Xa21G in rice caused heritable
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resistance to Xanthomonas oryzae pv. oryzae [3]. Arabidopsis mutants met1 and ddc were resistant to Pseudomonas syringae pv. tomato DC3000 infection due to cytosine demethylation[15]. In soybean resistant to yellow mosaic India virus, a higher level of intergenic
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region specific DNA methylation was reported [61]. Therefore, it is possible that methylation or demethylation of such genes may be involved in resistance or sensitivity of chickpea genotypes
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to FOC.
Some studies have demonstrated that biotic stress can alter cytosine methylation patterns throughout the genome. Arabidopsis exposed to Pseudomonas syringae exhibited extensive genomic DNA hypo-methylation [46]. The significance of DNA hypo-methylation in the
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activation of plant stress-responsive genes was demonstrated in tobacco upon TMV infection [57]. Also in rice, the level of cytosine methylation during the development of adult plant at 13leaf stage exposed to Xanthomonas oryzae was increased. These results suggest that an increase
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in the level of cytosine methylation during disease development may have contributed to adult plant resistance [51]. Comparison of DNA methylation of powdery mildew susceptible and
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resistant near-isogenic lines in common wheat showed that the DNA methylation level in infected plants of the resistant NILs was reduced compared to that of susceptible NILs [45]. They concluded that variation of DNA methylation plays a potential role in the resistance responses to powdery mildew. These results inferred that responses of plants were mediated through active alteration of the DNA methylation status, and the change in DNA methylation
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level upon exposure to biotic and abiotic stresses may globally regulate the expression of stress responsive genes. Comparing between classes I, II and III methylation in leaf tissue by G-test did not reveal any
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significant difference among genotypes, while in root significant difference between resistant and susceptible genotypes (Kaka and Sel95th1716) was observed. Confocal microscopic studies highlighted pathogen invasion and colonization accompanied by tissue damage and deposition of
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callose degraded products in the xylem vessels of infected roots of chickpea plants [20]. Deposition of callose led to the clogging of xylem vessels in compatible hosts while the resistant plants were
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devoid of such obstructions [20]. Infection by FOC race 5 caused a significant change in the root expression of lipoxygenase and actin genes. This up-regulation was earlier (lipoxygenase) or higher (actin) in the incompatible than in the compatible interaction. Thus, changes in oxidative metabolism differ in compatible and incompatible interactions in fusarium wilt of chickpea [20; 18].
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Defense related transcription factors, NBS-LRR resistant genes and retrotransposons accumulated in FOC infected chickpea resistant cultivar roots of seven days old plants as determined using by employing transcript-profiling techniques [44]. Therefore, it is possible that the methylation
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difference in resistant and susceptible cultivars affect defense related activation. Typically,
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demethylation in a promoter is associated with an increase of gene expression. Methylation patterns of DNA in leaf, stem and root differed in chickpea cultivars. Differences in the level of cytosine methylation among different organs or between different developmental stages have also been found in several other plants. In tomato, the level of DNA methylation was found to be higher in seeds than in mature leaves [41], and in rice a higher level of DNA methylation was detected in seedlings than in flag leaves [60]. In maize, the Mu transposable element normally undergoes hypermethylation in adult plants [9]. Profiling of DNA methylation in different organs of
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soybean revealed 2162 differentially methylated regions among organs, and showed that a portion of hypomethylated regions were correlated with high expression of neighboring genes [54]. All of these studies showed an association of tissue-specific differentially methylated
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regions with differential gene expression.
In this study, we analyzed the diversity of cytosine methylation at CCGG sites for seven
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genotypes of chickpea. The results showed that methylation polymorphism is widespread in Cicer arietinum. In the current study, the polymorphism of methylation patterns varied from
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36.81% to 44.64% of all bands. High methylation polymorphism has been observed in Gossypium arboretum L. (67%) [29] and Brassica oleracea (95%) [50], while low methylation polymorphism has been reported in navel orange (max. 22.2%) [25], wild soybean (34.65%), and cultivated soybean (47.05%) [64].
To further investigate whether methylation of functional genes is correlated with resistance
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to fusarium wilt, some polymorphic fragments were sequenced, and ten fragments were found to be homologous to functionally characterized genes. Ribosomal protein S3 (ST14, KL18, KL4 fragments) has been directly and indirectly implicated in host-pathogen interactions and a
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multifunctional target of attaching/effacing bacterial pathogens [17]. Ribosomal protein S3
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covalently binds to chaperon/oxidoreductase protein through a cysteine bond [34]. Higher expression level of a ribosomal protein was detected in FOC Race I infected resistant than infected in a sensitive variety [21]. Acetyl-CoA carboxylase (ACCase) mRNA (KL3 fragment) was induced by wounding and pathogen attack in common bean. Pathogen attack induced expression of ACCase through jasmonic acid pathway [16]. KL2 fragment was similar to a gene that is induced by high salinity stress and a fungal pathogen as detected in a chickpea in microarray analysis [38]. KR9 sequence displayed similarity to GTPase activating protein in
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chickpea. RabGTPases have been demonstrated to play a crucial role in regulating multiple responses in plants. In barley, a member of the RHO plant family of GTPases functions as a susceptibility factor in the interaction of barley with the barley powdery mildew fungus Blumeria
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graminis f. sp. hordei [24]. Also, in Arabidopsis RabGTPase-activating protein RabGAP22 acts as an activator of multiple components in the immune responses to Verticillium longisporum [48]. KR10 showed homology with one of the ESTs identified from a susceptible genotype of fusarium
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wilt ('ICP 2376') in pigeon-pea.
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To our knowledge, this is the first study attempting to assess whether DNA methylation changes are associated with a chickpea response to FOC. Our data showed that different organs; roots, stems and leaves show epigenetic response to FOC that differ and also that resistant and sensitive genotypes show different epigenetic response. Author contribution
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P. Mohammadi wrote the manuscript and performed the green house and laboratory assays. H. Badakhshan assisted in manuscript preparation and MSAP experiment and data analysis. H. Kanouni provided the genotypes used in this study. B. Bahramnejad assisted in manuscript
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Acknowledgements
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preparation, designed experiments and provided financial support for the project.
The authors wish to acknowledge the Faculty of Agriculture, University of Kurdistan, for providing the funds and research facilities.
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Canadian Journal of Plant Science 2009;89:851-63.
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Name Kaka Pirooz Biovenig Arman Azad FLIP02-50C Sel 95 th 1716
Origin Esfahan, Iran Ahar, Iran kermanshah, Iran Maragheh, Iran ICARDA ICARDA ICARDA
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Genotype code 1 2 3 4 5 6 7
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Table 1 Genotype code, cultivar name and cultivar origin of 7 chickpea genotypes
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Table 2 Sequences of adapters and pre-selective and selective primers used for MSAP analysis. Primers/adapters EcoRI adapter
Sequence (5ʹ-3ʹ) CTCGTAGACTGCGTACC AATTGGTACGCAGTCTAC GACTGCGTACCAATTC+A + ACC + ACG + AGT GATCATGAGTCCTGCT CGAGCAGGACTCATGA + TAA + TCC + TTC
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E+ 1 primer E+ 3 primer
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HpaII/MspI adapter
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Table 3 MSAP analysis of DNA methylation content of Fusarium oxysporum. f. sp. ciceris infected and control plants in leave, roots and stems tissue in seven genotypes. Leaf CClass I Class II
Root Class III
Class I
Class II
Stem
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Genotypes
Class III
Class I
Class II
Class III
259
32
36
261
32
34
274
29
24
Pirooz
262
32
33
274
28
25
263
35
29
Biovenig
251
37
39
270
30
27
260
42
25
Arman
256
42
29
263
25
Azad
256
43
28
272
40
FLIP02-50C
254
43
30
Sel 95 th 1716
256
43
28
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Kaka
258
29
40
15
274
40
13
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39
266
33
28
271
39
17
255
40
32
274
34
19
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Class I: no change; class II: demethylation group; class III: methylation group
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Table 4 Methylation change by Fusarium wilt in different genotypes of chickpea Comparison group Contrast ' Sel 95 th 1716 vs. kaka' Contrast ' Sel 95 th 1716 vs. Arman Contrast ' Sel 95 th 1716 vs. Arman Contrast ' FLIP-2-50c vs. Arman ' Contrast 'Arman vs. Azad
df 2 2 2 2 2
*
ᵡ2* 8.4833 4.2796 15.9895 11.0807 8.3526
P valuea 0.0144 0.0008 0.0003 0.0039 0.0154
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Tissue Root Root Stem Stem Stem
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G test calculated based on frequency in no change, methylation and demethylation classes shown in Table3.
a
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Only significant comparision are showed.
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Table 5 MSAP-based cytosine methylation levels in different genotypes.
Pirooz
I
204
205
198
II
35
39
45
III
73
70
73
IV
33
31
total sites
345
MSAP (%)a Fully methylated ratio (%)b Hemi-methylated ratio (%)c Non-methylated ratio (%)d
Arman
191
201
FLIP0 2-50C
Sel 95 th 1716
208
208
55
61
53
51
73
79
82
81
26
4
2
5
345
345
345
345
345
345
40.78
40.87
42.61
44.64
39.13
36.81
36.18
30.72
29.27
29.57
28.7
24.05
24.35
24.93
10.14
11.3
13.04
15.94
17.68
15.36
14.78
59.14
59.13
57.39
55.36
60.87
63.18
63.18
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MSAP (%) = [(II + III + IV)/(I + II + III + IV)] × 100 Fully methylated ratio (%) = [(III + IV)/(I + II + III + IV)] × 100 c Hemi-methylated ratio (%) = [(II)/(I + II + III + IV)] × 100 d Non-methylated ratio (%) = [(I)/(I + II + III + IV)] × 100 b
Azad
29
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a
Biovenig
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Kaka
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Genotypes
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MSAP Banding Type
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Table 6 BLAST result of the DNA methylation polymorphic sequences
fragme nts
size methylation state
EST or DNA or protein homology Accession
description
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S: Sel 95 th 1716 and K: kaka genotype; L: leave, R: root and T: stem tissue
ident ity
E value
99
0
402
Demethylation
XM_004514 750.1
Cicer arietinum 30S ribosomal protein S3, chloroplastic-like, mRNA
KL2
710
Methylation
GR408216.1
3e-127
KL3
473
Demethylation
XM_003605 553.1
KL4
284
Demethylation
XM_003605 567.1
Salinity-stressed chickpea root 99 cDNA library Cicer arietinum cDNA clone, mRNA Medicago truncatula Acetyl-CoA 72 carboxylase beta subunit, mRNA, complete cds Medicago truncatula 30S ribosomal 95 protein S14 mRNA, complete cds
SR8
409
Methylation
JG784703.1
81
5e-78
KR9
608
Demethylation
XM_004504 009
73
2e-36
KR10
405
Demethylation
GR467945.1
CFNT Panicum virgatum AP13 normalized full root Panicum virgatum cDNA clone, mRNA sequence PREDICTED: Cicer arietinum mental retardation GTPase activating protein homolog 3-like, mRNA Fusarium wilt challenged (10 DAI) pigeonpea genotype ICP2376 root cDNA library Cajanus cajan cDNA clone, mRNA hypothetical protein MTR [Medicago truncatula]
72
2e-21
93
5e-29
Cicer arietinum strain WR-315, cultivar clone cpchlor map chloroplast, complete sequence PREDICTED: Cicer arietinum 30S ribosomal protein S3, chloroplasticlike, mRNA
68
8e-28
98
0
KL17
KL18
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KL16
SC
ST14
565
Methylation
XP_0035995 74.1
547
methylation
AC145820.2 0
458
Demethylation
XM_004514 750.1
3e-20
5e-26
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G C
Types
+
+
no methylation; type I fragment
_
+
CpCpG methylated; type II fragment
+
_
G C
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_
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C G
HpaII
CpG methylation; type III fragment
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C G
MspI
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Methylation pattern of CCGG sites
_
hyper methylation; type IV fragment
Fig. 1. MspI and HpaII sensitivities to 5-CCGG-3 methylation status
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(‘‘+’’: enzyme cuts; ‘‘_’’: enzyme does not cut)
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0.6
e
e d
0.4
0.3
c b
0.2
0
Kaka
Pirooz
Biovenig
Arman
Azad
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Genotypes
b
SC
0.1
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Avarage AUDPC
0.5
FLIP02-50C
a
Sel95th 1716
Fig. 2. Response of seven chickpea genotypes to Fusarium oxysporum. f. sp ciceris.
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Values are the average area under the disease progress curve (AUDPC) of two weekly ratings (0–5 rating scale). The means followed by different letters are significantly different at P ≤ 0.05, according to least significant difference (LSD) test.
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FLIP02-50C
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Azad Sel95 th 1716 Biovenig Kaka
SC
Arman
0.97
0.77
0.57
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Pirooz
0.37
0.17
-0.03
-0.23
-0.43
Similarity
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Fig. 3. Dendrogram using the EUCLIDSQ (squared Euclidean) coefficient and UPGMA method based on disease severity in chickpea genotypes after inoculation by Fusarium oxysporum f.sp ciceris
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b
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a
d
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c
f
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e
Fig. 4. Dendrogram showing DNA methylation pattern in different organ before and after inoculation with FOC . a; stems in control plants b: infected stems c: roots in control plants d: roots in infected plants e; leave in control plants f: leave in infected plants
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Stem
treatment Control
Leave
treatment
Control
treatment
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Control
Root
SC
Class I
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Class III
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Class II
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Fig. 5. Example of cytosine methylation patterns in the leave, root and stem in the control and pathogen infected plants.
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Coord. 2
Leaf
Root
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Coord. 1
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Stem
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Fig6. Results from Principal Coordinates Analysis (PCoA) to comparison three tissues based on methylation pattern.
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Highlights •
We assessed the response of seven chickpea genotype to Fusarium oxysporum f. sp. ciceris Cytosine methylation and demethylation differences occurred in different genotypes.
•
Cytosine methylation and demethylation differences occurred in different tissues after
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•
pathogen infection.
More DNA demethylation events occurred in the resistant genotypes.
•
Genomic regions with changed methylation status in sensitive and resistant genotypes were disease related genes.
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•
S0885-5765(15)30006-0
DOI:
10.1016/j.pmpp.2015.06.001
Reference:
YPMPP 1117
To appear in:
Physiological and Molecular Plant Pathology
Received Date: 28 January 2015 Revised Date:
26 May 2015
Accepted Date: 2 June 2015
Please cite this article as: Mohammadi P, Bahramnejad B, Badakhshan H, Kanouni H, DNA methylation changes in fusarium wilt resistant and sensitive chickpea genotypes (Cicer arietinum L.), Physiological and Molecular Plant Pathology (2015), doi: 10.1016/j.pmpp.2015.06.001. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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DNA methylation changes in fusarium wilt resistant and sensitive chickpea genotypes (Cicer arietinum L.) Parvin Mohammadi1, Bahman Bahramnejad1, Hedieh Badakhshan1, Homayoun Kanouni2 Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Kurdistan,
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1
Sanandaj, Iran
Research Center for Agriculture and Natural Resources, Sanandaj, Iran
Corresponding author: Dr. Bahman Bahramnejad Department of Agricultural Biotechnology
P. O. Box: 416, Sanandaj, Iran
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Tel: 0098 871 6620552
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University of Kurdistan
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2
Fax: 0098 871 6620553
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E-mail: [email protected]
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Abstract DNA methylation plays an important role in the regulation of gene expression in biotic and abiotic stresses. In the present study, a methylation-sensitive amplified polymorphism (MSAP)
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analysis was performed to profile DNA methylation changes in seven resistant and sensitive chickpea genotypes following inoculation with Fusarium oxysporum f. sp. ciceris. In all, 27468 DNA fragments, each representing a recognition site cleaved by either or both of two isoschizomers,
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were amplified using nine selective primer pairs. DNA methylation was evaluated in leaves, stems and roots in control and inoculated plants. Extensive cytosine methylation alterations were found in pathogen-treated
genotypes
compared
with
the
corresponding
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the
control,
including
hypermethylation and demethylation as well as the potential conversion of methylation types. For all genotypes, the percentage of demethylated sites were more than methylated sites in infected plants compared with the corresponding control. No significant differences were observed for
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banding patterns in infected and control leaf tissues, while the differences between percentage of unchanged, methylated and demethylated sites were significant in stem and root tissues. The total numbers of methylated polymorphic bands ranged from 137 to 154 bands in Sel95th1716and
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Arman, accounting for 36.81% to 44.64% of all bands, respectively. Ten fragments that were differentially amplified between infected and control plants were isolated and sequenced in three
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tissues separately. Most of sequenced fragments showed homology with disease related genes in GenBank. The results suggest that significant differences in cytosine methylation exist between resistant and sensitive chickpea genotypes, and that hypermethylation or hypomethylation of specific genes may be involved in the chickpea resistance to Fusarium wilt. Keywords DNA methylation, chickpea, fusarium wilt, MSAP marker
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List of abbreviations AFLP
Amplified Fragment Length Polymorphism
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AUDPC Area under the Disease Progress Curve IDD Disease Intensity Index Fusarium oxysporum f. sp. ciceris
MSAP
Methylation Sensitive Amplified Polymorphism
SAUDPC
Standardize Area under the Disease Progress Curve
Introduction
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1.
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FOC
Plants usually adapt to complex and changeable environmental stresses through reversible epigenetic modifications. DNA in most eukaryotic genomes is modified by methylation of cytosine residues (5mC) within the di-nucleotide CpG and the tri-nucleotide CpNpG sequences.
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DNA methyl-transferases, a group of enzymes, catalyze the transfer of methyl group from the pyrimidine ring of cytosine residues. DNA methylation is implicated in gene regulation, genomic imprinting [12], the timing of DNA replication [26], determination of chromatin
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structure [47] and the control of parasitic DNA elements in plants and response to stresses [59]. Levels of methylation vary greatly in different organisms. The percentage of methylated
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cytosines in genome ranges from 0-3% in insects, 2-7% in vertebrates, 10% in fish and amphibians, to more than 30% in some plants [1] The methylation of cytosine in plant nuclear DNA usually occurs in both CpG and CpNG sequences, whereas in vertebrates it is located almost exclusively in CpG [19]. Mainly three types of assays have been developed for the detection of DNA methylation. In the first method, methylated DNA fragments can be isolated by affinity purification using
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proteins that preferentially bind methylated DNA, or by immuno-precipitation using anti-mC antibodies (mCIP) [13]. A second method involves treating genomic DNA with sodium bi-sulfite, a process that converts unmethylated cytosines to uracils. Following PCR amplification and
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sequencing of bisulfite-treated DNA, methylated cytosines can be identified as those that remains as cytosines whereas unmethylated cytosines appear as thymines [23]. The third method is methylation-sensitive amplified polymorphisms (MSAP) that involves digestion of genomic DNA
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by methylation-sensitive restriction enzymes such as MspI and HpaII for which digestion is blocked by methylation [40]. It is a modification of the AFLP (Amplified Fragment Length Polymorphism)
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technique in which the isoschizomers HpaII and MspI are employed as ‘frequent-cutter’ enzymes. Both HpaII and MspI recognize 5’-CCGG-3’ but display differential sensitivity to DNA methylation (Fig. 1).
Previous studies showed that the DNA methylation level in plant changes dynamically in
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response to environmental stimuli. Environmental stimuli, such as cold [55], drought [32; 56; 58], salt [56; 58; 63], and metals [2; 30] are known to alter cytosine methylation throughout the genome and at specific loci. Plants have evolved the DNA methylation approach as a major defense strategy
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against biotic stress. Upon exposure to biotic stresses, plants 'immunecomponents', such as recognition of pathogen-associated molecular patterns (PAMPs) and the basal defense machinery,
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are activated as a process of defense priming [42]. Clear evidence of dynamic changes in DNA methylation following pathogen attack, as well as the functional consequences of differential methylation in regulating defense-related genes has been reported [15]. The MSAP technique has been applied to evaluate the level and pattern of cytosine methylation in plants upon biotic stresses. DNA methylation analysis by MSAP showed the induction of post-transcriptional gene silencing in tomato infected with the tomato yellow leaf curl Sardinia virus [39]. Significant differences in
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cytosine methylation were observed between seedlings and adult rice plants after inoculation with the pathogen Xanthomonas oryzae pv. oryzae [51]. Furthermore, analysis of DNA methylation in potato showed change in the transcript levels of genes in response to
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Burkholderia phytofirmans strain PsJN in infected plants [14].
Chickpea production is limited worldwide by fusarium wilt caused by Fusarium oxysporum. f. sp. ciceris [33]. Fusarium wilt is one of the most important and destructive vascular disease of
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chickpea [31]. After infection, the fungus enters roots and spreads systemically through the host’s vascular system and blocks the plant's transport system. Disease symptoms such as
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yellowing and wilting appear after disease progress. Vascular discoloration occurs from the roots to the young stems, followed by a yellowing and wilting of the leaves before final necrosis [35]. Transcriptomic analysis revealed that a large set of genes is differentially expressed during fusarium wilt infections in chickpea [6]. In addition, previous works show that chickpea
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genotypes have very different reactions to fusarium wilt, ranging from very sensitive to resistant [22, 7].
To date, little is known about the mechanism of resistance and epigenetic control of gene
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expression in chickpea. Seven chickpea cultivars that showed different response to fusarium wilt were selected. To investigate whether changes in DNA methylation might be involved in gene
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expression during infection in resistant and susceptible cultivars, MSAP was used to assay the methylation status of genomic DNA in leaves, roots, and stems of plants that had been inoculated with Fusarium oxysporum f. sp. ciceris and control plants. 2.
Materials and methods
2.1.
Disease Evaluation
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Seven genotypes of chickpea were used in the present study. The genotypes were provided by the Agricultural and Natural Resources Center of Kurdistan, Sanandaj, Iran. The code number,
ciceris (FOC) strain used in this study was previously described [28].
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name and origin of these genotypes are shown in table 1. Isolation of the Fusarium oxysporum f. sp.
The resistant/susceptible reaction of genotypes to pathogen was evaluated under greenhouse conditions. Each pot represented an experimental unit, and treatments were replicated three times,
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each pot containing three chickpea plants. Seeds of each genotype were sown in sterilized soil infested with 10 cfu/g of pathogen isolate. The symptoms of disease were recorded daily from one
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to three weeks after planting. Disease severity was assessed for each plant on a 0 to 4 rating scale according to the percentage of chlorosis, necrosis and wilt, as follows: 0= healthy, 1=1-33%, 2=33%-66%, 3= 66%- 100%, 4= dead plant [10]. The occurrence of vascular infection was determined in symptomless plants in order to validate the experiment. Stems were cut into 5-10 mm
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large pieces, surface disinfected in 0.2% NaCLO for two min, then plated on potato dextrose agar (PDA) and incubated at room temperature [43]. A disease intensity index (DII) was determined based on wilt incidence and severity of symptoms data by the following equation: DII = (∑Si Ni). 4× Nt, where Si = symptoms severity; Ni = number of plants with Si symptom severity; and Nt =
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1
total number of plants. DII was used as a representative of the mean value of disease intensity at any
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given moment. The standardized area under the disease progress curve (SAUDPC) was calculated based on the plots of DII values over time (days) [10]. Differences among the genotypes for disease severity were evaluated using analysis of variance (ANOVA). Squared Euclidean distance matrix among genotypes was calculated based on the SAUDPC. The grouping of genotypes was conducted by XLSTAT software, a statistical analysis add- Ins for Microsoft Excel.
2.2.
Genomic DNA extraction
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Total genomic DNA was extracted from leaf, root and stem tissues of infected and control chickpea genotypes. For infected plants samples were taken when disease symptoms were appeared and for control plant at the same time. Total DNA was isolated from leaf samples using
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CTAB [49]. The DNA of root and stem tissues was extracted by using SDS method [27]. Quantity and quality of the isolated DNA was evaluated by spectrophotometer (Eppendorf, Germany) and 0.8% agarose gel electrophoresis respectively. Methylation-sensitive amplification polymorphism analysis
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2.3.
MSAP analyses were conducted in accordance with Cervera et al (2002) method by minor
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modification. Two enzyme combinations EcoRI/MspI and EcoRI/ HpaII were used for analysis. Digestion and ligation of DNA was performed as following [11]: DNA digestion was conducted at 37˚C with 5 U each of EcoRI and HpaII (Thermo Scientific) in 25µl of Tango (MBI) buffer. One adapter for EcoRI sticky ends and another for HpaII/MspI sticky ends were designed. The
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sequence information of the adapters and primers are provided in Table 2. After digestion, a 5µl mixture was used containing 5 pmol of EcoRI adapter, 50 pmol of HpaII/MspI adapter, 8 mM ATP, 10 mM TRIS-acetate pH 7.5, 10 mM magnesium acetate, 50 mM DTT, and 1.4 U of T4
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DNA ligase (Thermo Scientific). The mixture was incubated for 3 h at 37˚C and overnight at 4˚C. For the first amplification reaction, ligated DNA fragments were diluted fivefold and used
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as template. The applied primers in the first amplification step were complementary to EcoRI and HpaII/MspI adapters with addition of 3 selective nucleotides (table 2). Preamplification was carried out with 2 µl of diluted ligated product and 10 pmol of preselective primers. The PCR reaction used the following program: 25 cycles of 94˚C for 30 s, 56˚C for 30 s, 72˚C for 1 min, and finally, 10 min at 72˚C. The product was diluted to 250µl and used for selective amplification. Selective amplification was carried out using 2µl of diluted pre-
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amplification product and 4 pmol of each selective primer (Table 2). The PCR program for amplification was conducted as follows: 1 cycle of 94˚C for 5 min, 1 cycle of 94˚C for 30 s, 56˚C for 30 s, and 72˚C for 1 min, followed by 12 cycles with a 0.7˚C decrease in annealing temperature
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per cycle, and 23 cycles of 94˚C for 30 s, 56˚C for 30 s, and 72˚C for 1 min, and a final extension of 72 ˚C for 7 min. The final products were denatured at 95˚C for 5 min and separated on 4.5% polyacrylamide gels. The staining of the gels was performed based on silver-nitrate staining [8].
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Scoring followed a previously published methylation method [50]. The frequencies of methylation changes were compared between different genotypes using G tests, as implemented in PROC
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FREQ, SAS 9.1 for Windows (SAS Institute Inc., Cary, NC, USA).
Amplified fragments were separated from gel and PCR was conducted with the primer combinations which were used in selective amplification [11]. After purification of amplified products, DNA fragments were sequenced at commercial sequencing service (Bioneer Inc. Bioneer
3.
Results
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Corporation).
One way analysis of variance (ANOVA) was performed to compare of the chickpea genotypes
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for average AUDPC. The average AUDPC was calculated based on two weeks rates. Significant differences were observed among genotypes (Fig. 2). Sel95th1716 and Kaka were the most resistant
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and sensitive chickpea genotype to fusarium wilt, respectively. Cluster analysis was conducted based on the average of AUDPC using squared Euclidean distance and UPGMA algorithm. The genotypes were divided into three main groups. Kaka, Biovenig, Pirooz and Arman were grouped in the first cluster into two sub-clusters that were evaluated as sensitive. Sel95th1716 was individually evaluated resistant. The third cluster included FLIP02-50C and Azad that evaluated are showing partial resistance (Fig. 3).
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3.1.
Repeatability of MSAP
In a preliminary experiment, two primer combinations were selected randomly to determine
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the repeatability of MSAP markers. Two different chickpea genotypes including Kaka and Sel95th1916 were selected for this purpose. The MSAP test was performed for leaf, stem and root tissues of both infected and control plants separately. The banding patterns of the above mentioned separate experiments were compared on the same gel. More than 95% (96 and 96.5%
3.2.
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degree of reliability of this marker technique.
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Kaka and Sel95th1916, respectively) banding patterns were the same, implying a reasonable
Pathogen-induced methylation and demethylation changes
The changes in cytosine methylation patterns under pathogen infection stress were determined by comparing all possible banding patterns among control and infected samples. This comparison was
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performed for seven chickpea genotypes and three tissues separately. Three different banding patterns were observed on the gels (Table 3; Fig. 5). In class I, there were no distinguishable different banding patterns among control and infected genotypes. II represents cases where a band is
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missing as a result of demethylation in inoculated plants, whereas, possible induced cytosine methylation events were classified as class III. The three classes I, II and III were compared using G
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tests. The results of this test revealed that there were no significant differences for banding patterns in leaf tissues among genotypes. However, the cultivars (genotypes) did show significant differences between percentage of unchanged, methylated and demethylated sites in stem and root tissues (Table 4).
Approximately 77.98% to 83.79% of the CCGG sites remained unchanged under pathogen stress in leave tissue (Table 3) but the percent of demethylated and methylated bands in this tissue of different genotypes was estimated from 7.65 to 12.23 and 4.59 to 11.92, respectively.
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In root tissue, the percentage of unchanged, demethylated and methylated sites was 76.76 to 80.12, 9.78 to 13.15 and 8.56 to 11.02, respectively. In stem tissue, the estimated unchanged, demethylated and methylated sites were 78.9 to 83.79, 8.87 to 12.83 and 5.2 to 12.23 percent respectively. In
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general, the percent of demethylated sites were higher than methylated sites for all seven genotypes after infection. The lowest and highest methylated sites were in leaf tissues of resistant genotype (Sel95th1716) and in stem tissues of semi-resistant genotype (Arman). The lowest and highest
root tissues of resistant genotype (Azad). Pattern of DNA Methylation in different genotypes
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3.3.
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demethylated sites were detected in the leaf tissues of semi-resistant genotype (Arman) and in the
In this study, cytosine methylation at CCGG sites was assessed in three tissues of seven chickpea genotypes under stress (FOC infection) and control conditions using nine MSAP primer combinations. A total of 27468 clear and reproducible fragments were amplified. Each of the
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fragments is assumed to have at least one CG overhang terminus derived from the common CCGG recognition site and cleaved by one or both isoschizomers. To compare DNA methylation
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polymorphism in different chickpea genotype, the levels of DNA methylation in the healthy leaf tissues were analyzed (Table5). Based on the digestions with the isoschizomers, bands were divided
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into the following four types: Type I bands, present for both enzyme combinations; Type II and III bands respectively represented amplified products after digestion with EcoRI/HpaII or EcoRI/MspI enzymes, and Type IV bands, absent from both enzyme combinations. The hemi-methylated state of 5’-CCGG-3’ sites due to methylation in one DNA strand but not in its complementary strand is classified as Type II bands and the internal cytosine of 5’-CCGG-3’ methylation represented as Type III bands. Type IV bands are absent from both enzyme combinations but present in the other
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genotype. Type IV implies full methylation of both cytosine in the 5’-CCGG-3’ sequence in one sample but no methylation at the same site in the other. The total number of polymorphic methylated (hemi-methylated and fully methylated) bands
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were 137 to 154 (Type II+TypeIII+Type IV bands), accounting for 36.81% to 44.64% of all bands. Full-methylation (Type III) occurred more frequently than hemi-methylation (Type II), but the total number of these two kinds of methylated fragments was stable in each sample in all
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genotypes. The type IV bands were the main source of the DNA methylation changes that induced in different chickpea genotypes.
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Dendrograms based on methylation contents in leaf, root and stem tissues of seven chickpea genotypes in control and infected plants were prepared using UPGMA algorithm (Fig. 4). In all tissues except roots in control plants the clustering of genotypes was similar to grouping of genotypes based on AUDPC. The genotypes Sel95th1716, FLIP02-50C and Azad, which are
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resistant and semi-resistant genotypes were grouped in one cluster and the other genotypes were divided in a separate cluster with two sub-clusters. The genotype Sel95th1716 clustered with sensitive genotype Arman in the roots of control plants.
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The first group included susceptible genotypes Kaka and Biovenig. The second group contained semi-resistant genotypes Arman and Pirooz. Resistant genotypes Azad, FLIP02-50C,
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Sel95th1716were classified in the third group. The classification of genotypes based on methylation
content
was
consistent
with
grouping
of
genotypes
according
to
susceptible/resistance response to pathogen attack. Based on methylation contents of the different three tissues (leaf, stem and root) principal coordinate analysis (PCoA) was carried out and each tissue differentiated into three discrete groups (Fig. 6).
3.4.
Analysis of the Differentially Methylated DNA Sequences
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To obtain more information about the results of MSAP analysis, some fragments that were differentially amplified between infected and control plants were isolated and sequenced consistent. Distinct homology was detected in GenBank for 10 fragments (Table 6). Of these 10 fragments,
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eight fragments showed homology to genes with known functions and two had homology to a genomic DNA clone or predicted protein (Table 6). ST14 and KL18 fragments showed similarities to ribosomal protein S3 in chickpea and KL4 fragment was similar to 30S ribosomal protein S14 in
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Medicago truncatula. KL3 fragment had homology with Acetyl-CoA carboxylase beta in alfalfa. Sequence KL2 displayed very high similarity to salinity-stressed chickpea root (Cicer arietinum)
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cDNA. KR9 sequence displayed similarity to GTPase activating protein in chickpea. A fragment of KR10 matched a sequence in the cDNA library from Cajanus cajan roots exposed to fusarium wilt.
4.
Discussion
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In this study we have applied the MSAP technique to investigate the methylation pattern of chickpea DNA during infection by FOC. Our data demonstrate that fusarium wilt changes the methylation status of the chickpea genome and that MSAP is a powerful tool for identifying genes
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involved in plant fungi interactions. More than 95% of sites were repeatable for the same samples in two separate MSAP tests, demonstrating that the obtained results using the MSAP technique is
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fairly repeatable. Several previous studies have demonstrated that the MSAP technique is highly efficient for large-scale detection of cytosine methylation in plant genomes [60; 5; 36; 52; 11; 53; 63].
Cluster analysis of seven genotypes based on AUDPC and MSAP bands on infected plants produced similar groups. Resistant and susceptible cultivars were completely separated. AUDPC analysis classified genotypes in three groups resistant, semi resistant and sensitive. HajiAllahverdipoor et al (2011) evaluated Kaka, Biovenig, Pirooz and Arman genotypes as sensitive
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genotypes and Mahdieh (2005) evaluated Sel 95 th1716 as a resistant genotype [22; 37]. Evidence from proteins generating epigenetic marks showed their crucial roles in the plant defense against pathogens [4]. Demethylation of R gene Xa21G in rice caused heritable
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resistance to Xanthomonas oryzae pv. oryzae [3]. Arabidopsis mutants met1 and ddc were resistant to Pseudomonas syringae pv. tomato DC3000 infection due to cytosine demethylation[15]. In soybean resistant to yellow mosaic India virus, a higher level of intergenic
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region specific DNA methylation was reported [61]. Therefore, it is possible that methylation or demethylation of such genes may be involved in resistance or sensitivity of chickpea genotypes
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to FOC.
Some studies have demonstrated that biotic stress can alter cytosine methylation patterns throughout the genome. Arabidopsis exposed to Pseudomonas syringae exhibited extensive genomic DNA hypo-methylation [46]. The significance of DNA hypo-methylation in the
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activation of plant stress-responsive genes was demonstrated in tobacco upon TMV infection [57]. Also in rice, the level of cytosine methylation during the development of adult plant at 13leaf stage exposed to Xanthomonas oryzae was increased. These results suggest that an increase
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in the level of cytosine methylation during disease development may have contributed to adult plant resistance [51]. Comparison of DNA methylation of powdery mildew susceptible and
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resistant near-isogenic lines in common wheat showed that the DNA methylation level in infected plants of the resistant NILs was reduced compared to that of susceptible NILs [45]. They concluded that variation of DNA methylation plays a potential role in the resistance responses to powdery mildew. These results inferred that responses of plants were mediated through active alteration of the DNA methylation status, and the change in DNA methylation
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level upon exposure to biotic and abiotic stresses may globally regulate the expression of stress responsive genes. Comparing between classes I, II and III methylation in leaf tissue by G-test did not reveal any
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significant difference among genotypes, while in root significant difference between resistant and susceptible genotypes (Kaka and Sel95th1716) was observed. Confocal microscopic studies highlighted pathogen invasion and colonization accompanied by tissue damage and deposition of
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callose degraded products in the xylem vessels of infected roots of chickpea plants [20]. Deposition of callose led to the clogging of xylem vessels in compatible hosts while the resistant plants were
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devoid of such obstructions [20]. Infection by FOC race 5 caused a significant change in the root expression of lipoxygenase and actin genes. This up-regulation was earlier (lipoxygenase) or higher (actin) in the incompatible than in the compatible interaction. Thus, changes in oxidative metabolism differ in compatible and incompatible interactions in fusarium wilt of chickpea [20; 18].
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Defense related transcription factors, NBS-LRR resistant genes and retrotransposons accumulated in FOC infected chickpea resistant cultivar roots of seven days old plants as determined using by employing transcript-profiling techniques [44]. Therefore, it is possible that the methylation
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difference in resistant and susceptible cultivars affect defense related activation. Typically,
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demethylation in a promoter is associated with an increase of gene expression. Methylation patterns of DNA in leaf, stem and root differed in chickpea cultivars. Differences in the level of cytosine methylation among different organs or between different developmental stages have also been found in several other plants. In tomato, the level of DNA methylation was found to be higher in seeds than in mature leaves [41], and in rice a higher level of DNA methylation was detected in seedlings than in flag leaves [60]. In maize, the Mu transposable element normally undergoes hypermethylation in adult plants [9]. Profiling of DNA methylation in different organs of
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soybean revealed 2162 differentially methylated regions among organs, and showed that a portion of hypomethylated regions were correlated with high expression of neighboring genes [54]. All of these studies showed an association of tissue-specific differentially methylated
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regions with differential gene expression.
In this study, we analyzed the diversity of cytosine methylation at CCGG sites for seven
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genotypes of chickpea. The results showed that methylation polymorphism is widespread in Cicer arietinum. In the current study, the polymorphism of methylation patterns varied from
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36.81% to 44.64% of all bands. High methylation polymorphism has been observed in Gossypium arboretum L. (67%) [29] and Brassica oleracea (95%) [50], while low methylation polymorphism has been reported in navel orange (max. 22.2%) [25], wild soybean (34.65%), and cultivated soybean (47.05%) [64].
To further investigate whether methylation of functional genes is correlated with resistance
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to fusarium wilt, some polymorphic fragments were sequenced, and ten fragments were found to be homologous to functionally characterized genes. Ribosomal protein S3 (ST14, KL18, KL4 fragments) has been directly and indirectly implicated in host-pathogen interactions and a
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multifunctional target of attaching/effacing bacterial pathogens [17]. Ribosomal protein S3
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covalently binds to chaperon/oxidoreductase protein through a cysteine bond [34]. Higher expression level of a ribosomal protein was detected in FOC Race I infected resistant than infected in a sensitive variety [21]. Acetyl-CoA carboxylase (ACCase) mRNA (KL3 fragment) was induced by wounding and pathogen attack in common bean. Pathogen attack induced expression of ACCase through jasmonic acid pathway [16]. KL2 fragment was similar to a gene that is induced by high salinity stress and a fungal pathogen as detected in a chickpea in microarray analysis [38]. KR9 sequence displayed similarity to GTPase activating protein in
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chickpea. RabGTPases have been demonstrated to play a crucial role in regulating multiple responses in plants. In barley, a member of the RHO plant family of GTPases functions as a susceptibility factor in the interaction of barley with the barley powdery mildew fungus Blumeria
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graminis f. sp. hordei [24]. Also, in Arabidopsis RabGTPase-activating protein RabGAP22 acts as an activator of multiple components in the immune responses to Verticillium longisporum [48]. KR10 showed homology with one of the ESTs identified from a susceptible genotype of fusarium
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wilt ('ICP 2376') in pigeon-pea.
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To our knowledge, this is the first study attempting to assess whether DNA methylation changes are associated with a chickpea response to FOC. Our data showed that different organs; roots, stems and leaves show epigenetic response to FOC that differ and also that resistant and sensitive genotypes show different epigenetic response. Author contribution
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P. Mohammadi wrote the manuscript and performed the green house and laboratory assays. H. Badakhshan assisted in manuscript preparation and MSAP experiment and data analysis. H. Kanouni provided the genotypes used in this study. B. Bahramnejad assisted in manuscript
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Acknowledgements
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preparation, designed experiments and provided financial support for the project.
The authors wish to acknowledge the Faculty of Agriculture, University of Kurdistan, for providing the funds and research facilities.
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Canadian Journal of Plant Science 2009;89:851-63.
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Name Kaka Pirooz Biovenig Arman Azad FLIP02-50C Sel 95 th 1716
Origin Esfahan, Iran Ahar, Iran kermanshah, Iran Maragheh, Iran ICARDA ICARDA ICARDA
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Genotype code 1 2 3 4 5 6 7
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Table 1 Genotype code, cultivar name and cultivar origin of 7 chickpea genotypes
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Table 2 Sequences of adapters and pre-selective and selective primers used for MSAP analysis. Primers/adapters EcoRI adapter
Sequence (5ʹ-3ʹ) CTCGTAGACTGCGTACC AATTGGTACGCAGTCTAC GACTGCGTACCAATTC+A + ACC + ACG + AGT GATCATGAGTCCTGCT CGAGCAGGACTCATGA + TAA + TCC + TTC
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E+ 1 primer E+ 3 primer
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HpaII/MspI adapter
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Table 3 MSAP analysis of DNA methylation content of Fusarium oxysporum. f. sp. ciceris infected and control plants in leave, roots and stems tissue in seven genotypes. Leaf CClass I Class II
Root Class III
Class I
Class II
Stem
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Genotypes
Class III
Class I
Class II
Class III
259
32
36
261
32
34
274
29
24
Pirooz
262
32
33
274
28
25
263
35
29
Biovenig
251
37
39
270
30
27
260
42
25
Arman
256
42
29
263
25
Azad
256
43
28
272
40
FLIP02-50C
254
43
30
Sel 95 th 1716
256
43
28
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Kaka
258
29
40
15
274
40
13
M AN U
39
266
33
28
271
39
17
255
40
32
274
34
19
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Class I: no change; class II: demethylation group; class III: methylation group
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Table 4 Methylation change by Fusarium wilt in different genotypes of chickpea Comparison group Contrast ' Sel 95 th 1716 vs. kaka' Contrast ' Sel 95 th 1716 vs. Arman Contrast ' Sel 95 th 1716 vs. Arman Contrast ' FLIP-2-50c vs. Arman ' Contrast 'Arman vs. Azad
df 2 2 2 2 2
*
ᵡ2* 8.4833 4.2796 15.9895 11.0807 8.3526
P valuea 0.0144 0.0008 0.0003 0.0039 0.0154
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Tissue Root Root Stem Stem Stem
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G test calculated based on frequency in no change, methylation and demethylation classes shown in Table3.
a
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Only significant comparision are showed.
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Table 5 MSAP-based cytosine methylation levels in different genotypes.
Pirooz
I
204
205
198
II
35
39
45
III
73
70
73
IV
33
31
total sites
345
MSAP (%)a Fully methylated ratio (%)b Hemi-methylated ratio (%)c Non-methylated ratio (%)d
Arman
191
201
FLIP0 2-50C
Sel 95 th 1716
208
208
55
61
53
51
73
79
82
81
26
4
2
5
345
345
345
345
345
345
40.78
40.87
42.61
44.64
39.13
36.81
36.18
30.72
29.27
29.57
28.7
24.05
24.35
24.93
10.14
11.3
13.04
15.94
17.68
15.36
14.78
59.14
59.13
57.39
55.36
60.87
63.18
63.18
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MSAP (%) = [(II + III + IV)/(I + II + III + IV)] × 100 Fully methylated ratio (%) = [(III + IV)/(I + II + III + IV)] × 100 c Hemi-methylated ratio (%) = [(II)/(I + II + III + IV)] × 100 d Non-methylated ratio (%) = [(I)/(I + II + III + IV)] × 100 b
Azad
29
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a
Biovenig
M AN U
Kaka
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Genotypes
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MSAP Banding Type
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Table 6 BLAST result of the DNA methylation polymorphic sequences
fragme nts
size methylation state
EST or DNA or protein homology Accession
description
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S: Sel 95 th 1716 and K: kaka genotype; L: leave, R: root and T: stem tissue
ident ity
E value
99
0
402
Demethylation
XM_004514 750.1
Cicer arietinum 30S ribosomal protein S3, chloroplastic-like, mRNA
KL2
710
Methylation
GR408216.1
3e-127
KL3
473
Demethylation
XM_003605 553.1
KL4
284
Demethylation
XM_003605 567.1
Salinity-stressed chickpea root 99 cDNA library Cicer arietinum cDNA clone, mRNA Medicago truncatula Acetyl-CoA 72 carboxylase beta subunit, mRNA, complete cds Medicago truncatula 30S ribosomal 95 protein S14 mRNA, complete cds
SR8
409
Methylation
JG784703.1
81
5e-78
KR9
608
Demethylation
XM_004504 009
73
2e-36
KR10
405
Demethylation
GR467945.1
CFNT Panicum virgatum AP13 normalized full root Panicum virgatum cDNA clone, mRNA sequence PREDICTED: Cicer arietinum mental retardation GTPase activating protein homolog 3-like, mRNA Fusarium wilt challenged (10 DAI) pigeonpea genotype ICP2376 root cDNA library Cajanus cajan cDNA clone, mRNA hypothetical protein MTR [Medicago truncatula]
72
2e-21
93
5e-29
Cicer arietinum strain WR-315, cultivar clone cpchlor map chloroplast, complete sequence PREDICTED: Cicer arietinum 30S ribosomal protein S3, chloroplasticlike, mRNA
68
8e-28
98
0
KL17
KL18
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AC C
KL16
SC
ST14
565
Methylation
XP_0035995 74.1
547
methylation
AC145820.2 0
458
Demethylation
XM_004514 750.1
3e-20
5e-26
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G C
Types
+
+
no methylation; type I fragment
_
+
CpCpG methylated; type II fragment
+
_
G C
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_
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C G
HpaII
CpG methylation; type III fragment
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C G
MspI
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Methylation pattern of CCGG sites
_
hyper methylation; type IV fragment
Fig. 1. MspI and HpaII sensitivities to 5-CCGG-3 methylation status
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(‘‘+’’: enzyme cuts; ‘‘_’’: enzyme does not cut)
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0.6
e
e d
0.4
0.3
c b
0.2
0
Kaka
Pirooz
Biovenig
Arman
Azad
M AN U
Genotypes
b
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0.1
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Avarage AUDPC
0.5
FLIP02-50C
a
Sel95th 1716
Fig. 2. Response of seven chickpea genotypes to Fusarium oxysporum. f. sp ciceris.
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Values are the average area under the disease progress curve (AUDPC) of two weekly ratings (0–5 rating scale). The means followed by different letters are significantly different at P ≤ 0.05, according to least significant difference (LSD) test.
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FLIP02-50C
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Azad Sel95 th 1716 Biovenig Kaka
SC
Arman
0.97
0.77
0.57
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Pirooz
0.37
0.17
-0.03
-0.23
-0.43
Similarity
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Fig. 3. Dendrogram using the EUCLIDSQ (squared Euclidean) coefficient and UPGMA method based on disease severity in chickpea genotypes after inoculation by Fusarium oxysporum f.sp ciceris
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b
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a
d
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c
f
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e
Fig. 4. Dendrogram showing DNA methylation pattern in different organ before and after inoculation with FOC . a; stems in control plants b: infected stems c: roots in control plants d: roots in infected plants e; leave in control plants f: leave in infected plants
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Stem
treatment Control
Leave
treatment
Control
treatment
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Control
Root
SC
Class I
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Class III
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Class II
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Fig. 5. Example of cytosine methylation patterns in the leave, root and stem in the control and pathogen infected plants.
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Coord. 2
Leaf
Root
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Coord. 1
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Stem
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Fig6. Results from Principal Coordinates Analysis (PCoA) to comparison three tissues based on methylation pattern.
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Highlights •
We assessed the response of seven chickpea genotype to Fusarium oxysporum f. sp. ciceris Cytosine methylation and demethylation differences occurred in different genotypes.
•
Cytosine methylation and demethylation differences occurred in different tissues after
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•
pathogen infection.
More DNA demethylation events occurred in the resistant genotypes.
•
Genomic regions with changed methylation status in sensitive and resistant genotypes were disease related genes.
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•