Biotechnol Lett DOI 10.1007/s10529-015-1789-1
ORIGINAL RESEARCH PAPER
Gene chip analysis of Arabidopsis thaliana genomic DNA methylation and gene expression in response to carbendazim Zhongai Li • Zicheng Wang • Suoping Li
Received: 23 December 2014 / Accepted: 4 February 2015 Ó Springer Science+Business Media Dordrecht 2015
Abstract Objectives To examine the effects of carbendazim on Arabidopsis genomic DNA methylation and gene expression. Results Carbendazim caused widespread changes in gene loci methylation and gene expression. With 0.1 mM (D2) and 0.2 mM (D3) carbendazim, there were, respectively, 1522 and 2278 demethylated sites and 1541 and 2790 methylated sites. A total of 279 and 505 genes were up-regulated by more than 300 % and 175 and 609 genes were down-regulated by 67 % in D2 and D3 treatments, respectively, compared with the control. Conjoint analysis showed that 20 and 39 demethylated genes were up-regulated[300 % and 21 and 24 methylated genes were down-regulated\67 % in D2 and D3, respectively. Conclusions Carbendazim causes methylation or demethylation of certain genes and changes the expression of these genes. These findings provide a theoretical basis for novel epigenetics-based methods
Zhongai Li and Zicheng Wang have contributed equally.
Electronic supplementary material The online version of this article (doi:10.1007/s10529-015-1789-1) contains supplementary material, which is available to authorized users. Z. Li Z. Wang S. Li (&) Plant Germplasm Resources and Genetic Laboratory, College of Life Science, Henan University, Jinming Road, Kaifeng 475004, Henan, China e-mail: [email protected]
to detect organic food and a new interpretation for the degradation of crop varieties. Keywords Carbendazim DNA chip DNA methylation Epigenetics Farm chemicals Gene expression Microarray
Introduction Pesticides are the main means of controlling plant diseases and insect pests but are one of the risks in agriculture (Thompson 2010). The scatter and residues from these pesticides can cause serious pollution (Ghimire and Woodward 2013) and great harm (Wang et al. 2013), including many diseases to humans (Jaga and Dharmani 2005; Koutros et al. 2010) Pesticides can affect human and animal genome epigenetic status (Collotta et al. 2013) thereby causing high incidences of a variety of cancers (Zhang et al. 2012a, b; Weichenthal et al. 2010). Some exogenous chemicals can cause methylation changes in plant genomic DNA (Karan 2012; Tyunin et al. 2012). However, there are still no reports about the effects of pesticides on the genetics and gene expression in crops. Epigenetics is the study of heritable changes in gene activity that are not caused by changes in the DNA sequence and has become a new field of genetic research (Matladi et al. 2011; McCarthy 2013). Epigenetic information plays an important role in
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regulation of gene expression (Feng et al. 2010) and biological genetic diversity (Klironomos et al. 2013). DNA methylation is one of the important forms of epigenetic modification. Many studies have shown that DNA methylation is affected by the environment and that changes of DNA methylation can cause phenotype genetic variations (Henderson and Jacobsen 2007; Becker and Weigel 2012). Microarray technologies allow a large number of DNA/RNA fragments to be tested in a highly parallel fashion (Schumacher et al. 2006). These technologies have been used widely in DNA methylation analysis of human and animal diseases (Mansego-Talavera et al. 2013; Sandoval et al. 2011; Mori et al. 2011; Aryee et al. 2011; Triche et al. 2013; Sabaouni et al. 2013). In this study, the impact of a pesticide (carbendazim) widely used in agriculture, on the genomic DNA and gene expression of Arabidopsis thaliana was examined. The results provide an important reference for the response of vegetables and crops to chemicals used in farming.
Materials and methods Materials The wild ecotype of Arabidopsis thaliana Columbia (Col-0) was provided by the Shanghai Institute of Plant Physiology, China. Carbendazim (99.9 %) was purchased from the Solarbio Company, China.The NimbleGen A. thaliana DNA Methylation 385K Minimal Promoter Array (2006-11-01_ATH6_min_promoter; Roche, Switzerland) and the Arabidopsis (V4) Gene Expression Microarray, 4 9 44K (Agilent Technologies, California) were used to analyze whole genome DNA methylation and gene expression. Arabidopsis cultivation Murashige and Skoog (MS) medium with a carbendazim at 0, 0.1, and 0.2 mM was prepared and labeled as CK (control), D2, and D3 respectively. Arabidopsis seeds were disinfected and sterilized as follows: 75 % (v/v) ethanol soak for 30 s, then a 0.1 % HgCl2 disinfection for 7–10 min, followed by a wash 3–4 times in sterile water. The washed seeds were sown in the MS culture medium, and subjected to vernalization
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at 4 °C for 3 days. After vernalization, the seeds were placed in a culture room at 22 ± 2 °C and grown with an illumination time of 16 h d-1 at a relative humidity of 70 %. Twenty days after sowing, 100 Arabidopsis seedlings (without roots) from the same treatment groups were sheared and mixed. Analysis using the A. thaliana genome DNA methylation chip and gene expression microarray methylated DNA immunoprecipitation Total DNA was isolated using the DNeasy Blood & Tissue Kit (QIAGEN). DNA was sheared by a Bioruptor sonicator (Diagenode; 10 cycles of 30 s with a 30 s break between cycles) and 5 lg sonicated genomic DNA fragments (300–1000 bp) was used as starting material. DNA fragments were denatured for 10 min at 94 °C and immunoprecipitated overnight at 4 °C with 5 lg mouse anti-5-methyl-cytidine antibody (Diagenode, Belgium). Mouse IgG (5 lg) (Jackson) was added to a tube containing mock immunoprecipitation (mock IP) solution (0.5 % NP40; 1.1 % Triton X-100; 1.5 mM EDTA; 50 mM Tris/HCl, 150 mM NaCl). The sample was then placed on a rotating wheel at 4 °C for 4 h. Magnetic beads (50 ll) (Bangs Laboratories Inc.) coupled with antimouse IgG was added to the sample, which was mixed for 2 h at 4 °C by end-over-end rotation. The magnetic beads were then pelleted by a Magnetic Separation Rack for 2 min at 4 °C and the supernatant was discarded. The magnetic beads were washed at 4 °C for 5 min with rotation with 500 ul of each of the following buffers in the order listed: Wash Buffer 1: 0.1 % SDS; 1 % Triton X-100; 2 mM EDTA; 20 mM Tris/HCl, pH 8.0; 150 mM NaCl; Wash Buffer 2: 0.1 % SDS; 1 % Triton X-100; 2 mM EDTA; 20 mM Tris/HCl, pH 8.0; 500 mM NaCl; and Wash Buffer 3: 10 mM Tris/HCl, 1 mM EDTA, pH 8.0. The beads were washed once in Wash Buffer 1, twice in Wash Buffer 2, and twice in Wash Buffer 3. Between each wash, the beads were pelleted as before and the supernatant was carefully removed to avoid disturbing the beads. To each methylated DNA immunoprecipitation ‘‘MeDIP’’ or ‘‘mock IP’’ tube, 200 ul of Elution Buffer (1 mM Tris/HCl, pH 8.0; 0.5 mM EDTA, pH 8.0; 10 % SDS) was added. Elution proceeded at 65 °C for 15 min. Beads were separated from the solution using a magnet and the supernatant was transferred to a new
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tube. Immunoprecipitated and reference DNA were extracted with phenol/chloroform. MeDIP-CHIP A genome library was prepared using the GenomePlex Whole Genome Amplification Kit (Sigma-Aldrich) and a thermal cycler. The DNA was purified using a QIAquick PCR purification kit (Qiagen) and then labeled with Cy3/Cy5 dye-labeled random primers (TriLink Biotechnologies) and a Klenow Fragment (New England Biolabs). Hybridization was achieved using Hybridization Kit 40 (NimbleGen). Mixers were prepared with the NimbleChip Mixer (NimbleGen). Sample loading and hybridization were accomplished using the Hybridization System (NimbleGen). Hybridized arrays were washed using Hybridization Kit 40 (NimbleGen). Two-color array scans were completed using GenePix 4000B. Data were extracted using GenePix Pro 6.0 and exported into a spreadsheet. Agilent whole genome oligo microarrays (onecolor) Total RNA was extracted using TRIzol and purified by the RNeasy Mini kit (Qiagen). RNA was labeled by the Quick Amp Labeling Kit, One-Color (Agilent) and purified with the RNeasy Mini kit. Hybridization of the purified RNA was performed using the Gene Expression Hybridization kit (Agilent). Samples were washed with Gene Expression Wash Buffer 1 (Agilent) and Gene Expression Wash Buffer 2 (Agilent). The prepared microarrays were then scanned with the Microarray Scanner (Agilent) and the data were extracted using Feature Extraction Software (Agilent).
Hypergeometric-P value) denotes the significance of the pathway correlated to the conditions. The lower the P-value, the more significant the pathway. The recommend P value cut-off is 0.05.
Results Twenty days after carbendazim treatment, the seedlings in D2 (0.1 mM) and D3 (0.2 mM) showed no significant differences with the seedlings in the control (CK), except that the root length was shorter and the lateral root was longer in the treated seedlings compared with the control (Fig. 1, see also Supplementary Figs. 1, 2). Genomic DNA methylation in response to carbendazim treatment The gene chip data revealed 6671 methylation sites in the DNA from the seedlings in the control group, and 6690 and 7193 methylation sites in the DNA from D2 and D3, respectively. The genome methylation analysis detected 1541 methylation loci and 1522 demethylation sites in the D2 treatment group that were different than those in CK. In the D3 treatment group, there were 2790
Data analysis The Gene Ontology (GO) project provides a controlled vocabulary to describe gene and gene product attributes in any organism (http://www.geneontology. org). The P value denotes the significance of the enrichment of GO terms in the DE genes. The lower the P value, the more significant the GO term. A P value B0.05 is recommended. Pathway analysis is a functional analysis that maps genes to KEGG (the Kyoto Encyclopedia of Genes and Genomes; http://www.genome.jp/kegg/) pathways. The P-value (EASE-score, Fisher-P value or
Fig. 1 Seedlings of Arabidopsis after treatment with carbendazim showing thicker leaves and more lateral roots as compared to the control. CK control, D2 0.1 mM carbendazim treatment, D3 0.2 mM carbendazim treatment
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Biotechnol Lett Fig. 2 Numbers of methylated/demethylated sites in genomic DNA of Arabidopsis after treatment with carbendazim as compared to the control. D2 0.1 mM carbendazim treatment, D3 0.2 mM carbendazim treatment
methylation loci and 2278 demethylation sites that were different than those in CK. There were 472 methylation loci and 872 demethylation loci common to both carbendazim treatment groups (Fig. 2). The results showed that 11 transcription factors were among the methylated genes and 16 transcription factors were among the demethylated genes in the two carbendazim treatment groups (Tables 1, 2). Gene expression microarray analysis The microarray results showed that in the D2 treatment group, 279 genes were up-regulated 300 %, while 175 genes were down-regulated 67 % compared with those genes in CK. This accounted for 2.8 and 1.8 % of the
total genes. (The total number of genes in the microarray was 9999.) In the D3 group, 505 genes were up-regulated 300 % (accounting for 5 %), while 609 genes were down-regulated 67 % (accounting for 6 %) compared with those genes in CK (Fig. 3). GO analysis showed that the changes in gene expression after carbendazim treatment involved a wide range of biological processes, including several stress stimulation processes such as chemical stimulation and abiotic stress response (Figs. 4, 5). Metabolic pathway gene expression changes The microarray results were analyzed using the KEGG pathway database. The differentially expressed genes
Table 1 Transcription factors showing increased methylation levels both in 0.1 mM and 0.2 mM carbendazim treatments as compared to the control Gene name (NCBI accession)
Gene description
AT1G19000
myb family transcription factor, similar to MybSt1 GI:7705206 from (Solanum tuberosum)
AT1G27490
Similar to MYB transcription factor isolog (AC002335)
AT2G03500
myb family transcription factor, contains Pfam profile: PF00249
AT2G22850
bZIP transcription factor family protein, contains a bZIP domain
AT3G09370
myb family transcription factor (MYB3R3), contains Pfam profile
AT1G58100
TCP family transcription factor, putative
AT3G45150
TCP family transcription factor, putative
AT4G34590
bZIP transcription factor family protein
AT5G06950 AT5G28770
Similar to bZIP family transcription factor [Arabidopsis thaliana] Similar to bZIP transcription factor family protein [Arabidopsis thaliana]
AT1G46480
Homeobox-leucine zipper transcription factor family protein
AT5G45710
Heat shock transcription factor family protein, contains Pfam profile
AT5G67000
Encodes a member of the ERF (ethylene response factor) subfamily B-6 of ERF/AP2 transcription factor family
AT1G58330
Transcription factor-related
AT1G59453
Transcription factor-related, weak similarity to TFIIIC Box B-binding subunit (Homo sapiens) GI:442362
AT1G68150
Protein_coding_gene:WRKY family transcription factor, similar to DNA-binding protein ABF2 GI:1159879 from Avena fatua
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Biotechnol Lett Table 2 Transcription factors showing decreased methylation levels both in 0.1 mM and 0.2 mM carbendazim treatments as compared to the control Gene name (NCBI accession)
Gene description
AT1G35490
bZIP family transcription factor
AT1G55600
WRKY family transcription factor, similar to SPF1 protein GI:484261 from Ipomoea batatas
AT1G62990
Homeodomain transcription factor (KNAT7), contains Pfam profiles
AT2G40140
Similar to zinc finger (CCCH-type) family protein [Arabidopsis thaliana] (TAIR:At3g55980.1)
AT4G04580
Protein coding gene: myb family transcription factor, contains Pfam profile: PF00249 myb-like DNA-binding domain
AT4G04800
Low similarity to pilin-like transcription factor (Homo sapiens) GI:5059062, SP:P14930
AT4G20400
Similar to transcription factor jumonji (jmj) family protein/zinc finger (C5HC2 type) family protein [Arabidopsis thaliana] (TAIR:At2g34880.1)
AT5G17490
Putative member of the VHIID domain transcription factor family RGAL—Arabidopsis thaliana, EMBL:AJ224957
AT5G38800 AT5G39230
bZIP transcription factor family protein, similar to bZIP transcription factor GI:1769891 from Arabidopsis thaliana Transcription initiation factor-related, contains weak similarity to Transcription initiation factor IIB (General transcription factor TFIIB)
AT5G45420
myb family transcription factor, contains Pfam profile: PF00249
were predicted to be involved in 32 signaling pathways; in the D2 group, 21 pathways were involved and in the D3 group, 25 pathways were involved (Tables 3, 4). Expression profiles associated with methylation analysis A conjoint analysis of the methylation and expression microarray chip data showed that 20 and 39 genes were both demethylated and up-regulated 3-fold, and 21 and 24 genes were both methylated and downregulated 3-fold in D2 and D3, respectively. A further 21 genes were both demethylated and up-regulated 2-fold, and three genes were both methylated and down-regulated 2-fold in D2 and D3, respectively (Tables 4, 5, 6; Fig. 6).
Discussion Epigenetic information is one of the basic forms of plant genetic diversity. For example, it is involved in the regulation of gene expression (McCarthy 2013; Li et al. 2012), adaptation to stress conditions (Karan et al. 2012; Wang et al. 2011), and the formation of heterosis (Chen 2013; He et al. 2013). DNA methylation is a relatively stable epigenetic form and DNA
methylation changes could cause changes in biological traits, which could be inherited through somatic or germ cells (Henderson and Jacobsen 2007). Previous studies often have been focused on the epigenetic effects of environmental pollution on animals and humans, and many of these studies have indicated that pollution may have an important influence on the genome (Collotta et al. 2013). Methoxychlor (Mori et al. 2011; Sciandrello et al. 2004), vinclozolin (Chanda et al. 2006; Pilsner et al. 2007), organochlorine pesticides (Pilsner et al. 2009), DDE, BHC, oxychlordane, chlordane, Mirex, PCBs (Stouder and Paoloni-Giacobino 2011),and DDT (Zama and Uzumcu 2009) can all trigger DNA methylation changes in human cells and rat organs. The epigenetic impact of environmental pollution (Guerrero-Bosagna et al. 2010), especially pesticides, has not been reported so far. To our knowledge, this is the first study to look at epigenetics in response to pesticide exposure in plants. The results showed that carbendazim application could change genomic DNA methylation in A. thaliana, and that this caused significant changes in the gene expression profile of the treated plants. Some up- and down-regulated genes that may be associated with these changes were identified in the carbendazim-treated plants. Recently, gene chips have been used widely to determine changes in DNA methylation sites in
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Fig. 3 Numbers of differentially expressed genes in groups treated with carbendazim. D2 versus CK UP up-regulation of gene expression in D2 compared with the control, D3 versus CK UP up-regulation of gene expression in D3 compared with the control, D2 versus CK down down-regulation of gene expression in D2 compared with the control, D3 versus CK down down-regulation of gene expression in D3 compared with the control. (D2 0.1 mM carbendazim treatment, D3 0.2 mM carbendazim treatment)
mammalian genomes. Exposing pregnant rats to vinclozolin was found to cause DNA methylation changes in the promoter regions of the sperm epigenome in the F3 generation using gene chip Fig. 4 Enrichment scores of down-regulated biological processes following carbendazim treatment. D2 0.1 mM carbendazim treatment, D3 0.2 mM carbendazim treatment
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technology, and some of the genes were identified as candidate markers (Chanda et al. 2006). Zhang et al. (2012a) identified 1069 CpG sites in 984 genes with significant methylation changes in diazinon-treated human K562 cells using a microarray, and some of these genes were predicted to be associated with cancer development or involved in related biological pathways. In the present study, we detected 1522 and 2278 demethylated sites and 1541 and 2790 methylated sites in D2 and D3 carbendazim-treated A. thaliana, respectively, using a DNA chip. Compared with the control, there were 279 and 505 genes that were upregulated 3-fold, and 175 and 609 genes that were down-regulated 3-fold in D2 and D3, respectively. Genes associated with stress and chemical stimulation may also participate in interactions between bacteria and plants (Timmusk et al. 1999). We propose that such genes may be used as candidate markers to decide whether carbendazim treatment is required during the course of plant development. MEK1 (AT4G26070) is a possible example of a marker gene but many more experiments are required to verify this. Many of these genes have been reported to participate in important physiological and biochemical processes
Biotechnol Lett Fig. 5 Enrichment scores of up-regulated biological processes following carbendazim treatment. D2 0.1 mM carbendazim treatment, D3 0.2 mM carbendazim treatment
Table 3 The enrichment score and the down-regulated genes of metabolic pathways which have changed both in the 0.1 mM and 0.2 mM carbendazim treatments as compared to the control Pathway identification
Definition
Enrichment score
ath00460
Cyanoamino acid metabolism
3.5
bglu40//nit1//shm1//shm7//nit2
ath00910
Nitrogen metabolism
2.7
bca4//nit1//ca1//nit2//asn2
ath00450 ath00710
Selenocompound metabolism Carbon fixation in photosynthetic organisms
ath00670
One carbon pool by folate
2.1
mthfr1//shm1//shm7
ath00195
Photosynthesis
1.6
atfd1//atpc1//fed_a//npq4//psby
ath00630
Glyoxylate and dicarboxylate metabolism
1.5
cat1//pglp1//shm1//shm7
22 2.1
Genes
aps4//atms2//ntrb aoat2//gapb//pkp3//prk//sbpase//atppc3
Pathway identification is from the KEGG database
Table 4 The enrichment score and the up-regulated genes of metabolic pathways which have changed both in the 0.1 mM and 0.2 mM carbendazim treatments as compared to the control Pathway identification
Definition
Enrichment score
Genes
ath04626
Plant-pathogen interaction
7.0
atmpk3//cnbt1//cngc19//efr//fls2//frk1//jaz1//mek1// rin4//rps2//serk4/tch3//wrky25//rps4
ath00460
Cyanoamino acid metabolism
4.3
bglu15//bglu17//bglu44//bxl2//ggt4//nit4
ath00591
Linoleic acid metabolism
2.9
lox2//lox5//lox3
ath04075
Plant hormone signal transduction
2.7
abf1//erf1//erf2//ers1//ers2//etr2//gh3.3//jaz1// jaz5//pbs3//tga3//wes1//jaz10//ebf2
ath00940
Phenylpropanoid biosynthesis
2.2
bglu15//bglu17//bglu44//bxl2//ccr2//prxca//prxcb//rci3
ath00909
Sesquiterpenoid and triterpenoid biosynthesis
1.9
thas1//tps12//tps13
ath00910
Nitrogen metabolism
1.7
atgsr1//gdh1//gln1;4//bca3//bca4
ath00860
Porphyrin and chlorophyll metabolism
1.5
atfer1//atfer4//pora//porb
Pathway identification is from the KEGG database
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Biotechnol Lett Table 5 Both demethylation and up-regulation genes being detected both in the 0.1 mM and 0.2 mM carbendazim treatment groups as compared to the control Gene name (NCBI accession)
Fold change D2 versus CK
Fold change D3 versus CK
Gene description
AT1G35710
63.5
47.2
Putative leucine-rich repeat receptor-like protein kinase(Arabidopsis thaliana);
AT1G30900
11.3
12.6
Vacuolar sorting receptor 6
AT1G79700
3.4
5.3
AP2-like ethylene-responsive transcription factor.
AT3G42725
2.5
6.8
Putative membrane lipoprotein
AT2G20142
3.3
4.3
Toll-interleukin-resistance domain-containing protein
AT4G15120 AT4G25940
2.4 3.8
3.3 2.8
VQ motif-containing protein ENTH/ANTH/VHS superfamily protein
AT1G59960
2.9
5.5
NAD(P)-linked oxidoreductase superfamily protein
AT1G03850
6.3
7.8
Arabidopsis thaliana glutaredoxin family protein
AT3G62550
3.5
5.1
Drought responsive ATP-binding motif containing protein
AT5G05965
2.3
4.6
Hypothetical protein, uncharacterized protein.
AT1G72060
9.8
12.9
AT5G39240
2.2
4.9
Hypothetical protein uncharacterized protein
AT3G25400
2.2
3.1
Hypothetical protein uncharacterized protein
AT3G57700
4.3
4.2
Putative protein kinase
AT4G38550
5.7
5.3
Phospholipase like protein (PEARLI 4) family
AT5G44390
2.5
2.4
FAD-binding Berberine family protein
AT4G26070
3.9
4.3
AT2G40300
3.1
5.5
MEK1 (MAP KINASE/ERK KINASE 1); MAP kinase kinase/kinase/protein binding (MEK1) Arabidopsis thaliana ATFER4 (ferritin 4)
AT1G02065
2.8
3.2
Arabidopsis thaliana SPL8 (SQUAMOSA PROMOTER BINDING PROTEINLIKE 8)
AT5G28640
2.9
4.3
Arabidopsis thaliana AN3 (ANGUSTIFOLIA 3)
AT5G67480
3.0
4.6
Arabidopsis thaliana BT4 (BTB AND TAZ DOMAIN PROTEIN 4)
Serine-type endopeptidase inhibitor
D2 versus CK = 0.1 mM carbendazim treatment compared with the control; D3 versus CK = 0.2 mM carbendazim treatment compared with the control
Table 6 Both methylation and down-regulation genes being detected both in the 0.1 mM and 0.2 mM carbendazim treatment groups as compared to the control Gene name (NCBI accession)
Fold change D2 versus CK
Fold change D3 versus CK
Gene description
AT5G35460
-2.3
-5.8
Hypothetical protein uncharacterized protein
AT2G35130
-2.2
-2.7
Pentatricopeptide repeat-containing protein
AT4G09420
-4.3
-2.1
TIR-NBS class of disease resistance protein
D2 versus CK = 0.1 mM carbendazim treatment compared with the control; D3 versus CK = 0.2 mM carbendazim treatment compared with the control
but the specific mechanism of action of these genes requires further study. Additionally, the functions of AT5G35460, AT3G25400, and AT5G39240 are still unknown so further studies are required to elucidate their action mechanisms.
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This study showed that the application of carbendazim caused multiple gene alterations in DNA methylation in Arabidopsis, and also brought about changes in gene expression. This finding is of importance because in agricultural production, for example,
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Fig. 6 The number of genes in which the methylation status and expression levels having both changed in D2 and D3 treatments as compared to the control. A the number of both upregulation and demethylation genes; a the number of overlap
genes in D2 and D3. B the number of both down-regulation and methylation genes; b the number of overlap genes in D2 and D3 (D2 0.1 mM carbendazim treatment, D3 0.2 mM carbendazim treatment)
pesticides are commonly used. Therefore, if pesticide application can cause genetic changes in crops, it could affect the genetic stability of specie. In farming, the problem of degradation of crop varieties is encountered frequently, and whether the epigenetic impact of pesticide use might be one of the reasons for species degeneration, needs further study. The results of this study suggest that the use of pesticides could cause widespread DNA methylation in plants. It is possible that measuring DNA methylation could be used to determine whether pesticides have been used during agricultural production. Crops grown without the use of pesticides are the organic foods that have been widely praised by consumers. Traditional residue-detection methods used in organic vegetable production are not reliable because these methods cannot detect chemical application in the early stages of farming. However, if pesticides are applied during the plant growth process, they may cause variations in the DNA methylation status of a group of genes. Therefore, whether organic farming methods have been used to grow vegetables (for example) could be detected by measuring DNA methylation changes in target genes. Our results also indicate that carbendazim can have an impact on many important biological processes in Arabidopsis, including photosynthesis, amino acid metabolism, selenium and nitrogen metabolism, and nutrient accumulation. Such influences will lead inevitably to changes in some secondary metabolic processes, which will have an impact on plant functional ingredients. In medicinal plants, changes in secondary metabolic processes could directly affect the plant’s medicinal efficacy (Gershenzon 1984).
Direct and indirect relationships between selenium and 40 common diseases have been reported (Nogales et al. 2013; Hatfield et al. 2012) may affect plant nitrogen metabolism and nutritional ingredients (Zhang et al. 2012a; Taiwo and Oso 1997; Macedo et al.2013; Masakapalli et al.2013). Carbendazim treatment, therefore, may have a significant impact on the nutritional value of a crop and on the medicinal value of medicinal plants, resulting in unpredictable effects on the human body. Because only one pesticide, carbendazim, was studied in this research, further work is needed to determine if other pesticides also alter DNA methylation, and whether the variations are specific to each pesticide. In addition, whether different plants exhibit specific DNA methylation patterns to a given pesticide also requires further investigation. It is possible that each farm chemical produces a specific methylation pattern, which could be used to detect whether pesticides have been applied during crop production. Clearly, broader and more in-depth studies are required to determine the effects of pesticides on plant DNA methylation and gene expression. Acknowledgments Financial support from the National Science Foundation of China(no. 31171982, no. 31372090)and the Foundation of Henan University (China) (no. 0000A40448). Conflict of interests conflict of interests.
The authors declare that they have no
Supporting information Supplementary Fig. 1—The length of roots was significantly decreased with the carbendazim added. Supplementary Fig. 2—The number of fibrous roots was significantly increased with the carbendazim added.
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Mansego-Talavera ML, Milagro FI, Campion J, Martinez A (2013) Techniques of DNA methylation analysis with nutritional applications. J Nutrig Nutrigen 6:83–96 Masakapalli SK, Kruger NJ, Ratcliffe RG (2013) The metabolic flux phenotype of heterotrophic Arabidopsis cells reveals a complex response to changes in nitrogen supply. Plant J 74:56–582 Matladi NN, He´ le‘ne D, Fuks F (2011) Exposing the DNA methylome iceberg. Trends in Biochem Sci 36:381–387 McCarthy N (2013) Epigenetics: the long view. Nature Rev Cancer 13(2):76 Mori Y, Olaru AV, Cheng Y, Agarwal R, Yang J (2011) Novel candidate colorectal cancer biomarkers identified by methylation microarray-based scanning. Endocr Relat Cancer 18:465–478 Nogales F, Ojeda ML, Fenutrı´a M, Murillo ML, Carreras O (2013) Role of selenium and glutathione peroxidase on development, growth, and oxidative balance in rat offspring. Reproduction 146(6):659–667 Pilsner JR, Liu X, Ahsan H, Ilievski V (2007) Genomic methylation of peripheral bloodleukocyte DNA: influencs of arsenic and folate in Bangladeshi adults. Am J Clin Nutr 86:1179–1186 Pilsner JR, Liu X, Ahsan H, Ilievski V (2009) Folate deficiency, hyperhomocysteinemia, low urinary creatinine and hypomethylation of leukocyte DNA are risk factors for arsenic-induced skin lesions. Environ Health Perspect 117:254–260 Sabaouni I, Moussa A, Vannier B, Semlali O, Pietka TA et al (2013) The whole genome expression analysis using two microarray technologies to identify gene networks that mediate the myocardial phenotype of CD36 deficiency. Bioinformation 9:849 Sandoval J, Heyn H, Moran S, Serra-Musach J, Pujana MA et al (2011) Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome. Epigenetics 6:692–702 Schumacher A, Kapranov P, Kaminsky Z, Flanagan J, Assadzadeh A (2006) Microarray-based DNA methylation profiling: technology and applications. Nucleic Acid Res 34:528–542 Sciandrello G, Caradonna F, Mauro M, Barbata G (2004) Arsenic-induced DNAhypomethylation affects chromosomal instability in mammalian cells. Carcinogenesis 25:413–417 Stouder C, Paoloni-Giacobino A (2011) Specific transgenerational imprintingeffects of the endocrine disruptor methoxychlor on male gametes. Reproduction 141:207–216 Taiwo LB, Oso BA (1997) The influence of some pesticides on soil microbial flora in relation to changes in nutrient level, rock phosphate solubilization and P release under laboratory conditions. Agric Ecosyst Environ 65:59–68 Thompson A (2010) Pests and diseases. In: Carroll M, Wilford S (eds) Controlled atmosphere storage of fruits and vegetables. MPG Books Group, Preston, pp 71–80 Timmusk S, Gerhart E, Wagner H (1999) The plant-growthpromoting Rhizobacterium Paenibacillus polymyxa induces changes in Arabidopsis thaliana gene expression: a possible connection between biotic and abiotic stress responses. Mol Plant microb Interact 12:951–959
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Weichenthal S, Moase C, Chan P (2010) A review of pesticide exposure and cancer incidence in the agricultural health study cohort. Environ Health Persp 118:1117–1125 Zama AM, Uzumcu M (2009) Fetal and neonatal exposure to the endocrinedisruptor methoxychlor causes epigenetic alterations in adult ovarian genes. Endocrinology 150:4681– 4691 Zhang X, Andrew DW, Du P, Kibbe WA (2012a) DNA methylation alterations in response to pesticide exposure in vitro. Environ Mol Mut 53:542–549 Zhang X, BreksaIII AP, Mishchuk DO, Fake CE, O’Mahony MA (2012b) Fertilisation and pesticides affect mandarin orange nutrient composition. Food Chem 134:1020–1024
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ORIGINAL RESEARCH PAPER
Gene chip analysis of Arabidopsis thaliana genomic DNA methylation and gene expression in response to carbendazim Zhongai Li • Zicheng Wang • Suoping Li
Received: 23 December 2014 / Accepted: 4 February 2015 Ó Springer Science+Business Media Dordrecht 2015
Abstract Objectives To examine the effects of carbendazim on Arabidopsis genomic DNA methylation and gene expression. Results Carbendazim caused widespread changes in gene loci methylation and gene expression. With 0.1 mM (D2) and 0.2 mM (D3) carbendazim, there were, respectively, 1522 and 2278 demethylated sites and 1541 and 2790 methylated sites. A total of 279 and 505 genes were up-regulated by more than 300 % and 175 and 609 genes were down-regulated by 67 % in D2 and D3 treatments, respectively, compared with the control. Conjoint analysis showed that 20 and 39 demethylated genes were up-regulated[300 % and 21 and 24 methylated genes were down-regulated\67 % in D2 and D3, respectively. Conclusions Carbendazim causes methylation or demethylation of certain genes and changes the expression of these genes. These findings provide a theoretical basis for novel epigenetics-based methods
Zhongai Li and Zicheng Wang have contributed equally.
Electronic supplementary material The online version of this article (doi:10.1007/s10529-015-1789-1) contains supplementary material, which is available to authorized users. Z. Li Z. Wang S. Li (&) Plant Germplasm Resources and Genetic Laboratory, College of Life Science, Henan University, Jinming Road, Kaifeng 475004, Henan, China e-mail: [email protected]
to detect organic food and a new interpretation for the degradation of crop varieties. Keywords Carbendazim DNA chip DNA methylation Epigenetics Farm chemicals Gene expression Microarray
Introduction Pesticides are the main means of controlling plant diseases and insect pests but are one of the risks in agriculture (Thompson 2010). The scatter and residues from these pesticides can cause serious pollution (Ghimire and Woodward 2013) and great harm (Wang et al. 2013), including many diseases to humans (Jaga and Dharmani 2005; Koutros et al. 2010) Pesticides can affect human and animal genome epigenetic status (Collotta et al. 2013) thereby causing high incidences of a variety of cancers (Zhang et al. 2012a, b; Weichenthal et al. 2010). Some exogenous chemicals can cause methylation changes in plant genomic DNA (Karan 2012; Tyunin et al. 2012). However, there are still no reports about the effects of pesticides on the genetics and gene expression in crops. Epigenetics is the study of heritable changes in gene activity that are not caused by changes in the DNA sequence and has become a new field of genetic research (Matladi et al. 2011; McCarthy 2013). Epigenetic information plays an important role in
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regulation of gene expression (Feng et al. 2010) and biological genetic diversity (Klironomos et al. 2013). DNA methylation is one of the important forms of epigenetic modification. Many studies have shown that DNA methylation is affected by the environment and that changes of DNA methylation can cause phenotype genetic variations (Henderson and Jacobsen 2007; Becker and Weigel 2012). Microarray technologies allow a large number of DNA/RNA fragments to be tested in a highly parallel fashion (Schumacher et al. 2006). These technologies have been used widely in DNA methylation analysis of human and animal diseases (Mansego-Talavera et al. 2013; Sandoval et al. 2011; Mori et al. 2011; Aryee et al. 2011; Triche et al. 2013; Sabaouni et al. 2013). In this study, the impact of a pesticide (carbendazim) widely used in agriculture, on the genomic DNA and gene expression of Arabidopsis thaliana was examined. The results provide an important reference for the response of vegetables and crops to chemicals used in farming.
Materials and methods Materials The wild ecotype of Arabidopsis thaliana Columbia (Col-0) was provided by the Shanghai Institute of Plant Physiology, China. Carbendazim (99.9 %) was purchased from the Solarbio Company, China.The NimbleGen A. thaliana DNA Methylation 385K Minimal Promoter Array (2006-11-01_ATH6_min_promoter; Roche, Switzerland) and the Arabidopsis (V4) Gene Expression Microarray, 4 9 44K (Agilent Technologies, California) were used to analyze whole genome DNA methylation and gene expression. Arabidopsis cultivation Murashige and Skoog (MS) medium with a carbendazim at 0, 0.1, and 0.2 mM was prepared and labeled as CK (control), D2, and D3 respectively. Arabidopsis seeds were disinfected and sterilized as follows: 75 % (v/v) ethanol soak for 30 s, then a 0.1 % HgCl2 disinfection for 7–10 min, followed by a wash 3–4 times in sterile water. The washed seeds were sown in the MS culture medium, and subjected to vernalization
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at 4 °C for 3 days. After vernalization, the seeds were placed in a culture room at 22 ± 2 °C and grown with an illumination time of 16 h d-1 at a relative humidity of 70 %. Twenty days after sowing, 100 Arabidopsis seedlings (without roots) from the same treatment groups were sheared and mixed. Analysis using the A. thaliana genome DNA methylation chip and gene expression microarray methylated DNA immunoprecipitation Total DNA was isolated using the DNeasy Blood & Tissue Kit (QIAGEN). DNA was sheared by a Bioruptor sonicator (Diagenode; 10 cycles of 30 s with a 30 s break between cycles) and 5 lg sonicated genomic DNA fragments (300–1000 bp) was used as starting material. DNA fragments were denatured for 10 min at 94 °C and immunoprecipitated overnight at 4 °C with 5 lg mouse anti-5-methyl-cytidine antibody (Diagenode, Belgium). Mouse IgG (5 lg) (Jackson) was added to a tube containing mock immunoprecipitation (mock IP) solution (0.5 % NP40; 1.1 % Triton X-100; 1.5 mM EDTA; 50 mM Tris/HCl, 150 mM NaCl). The sample was then placed on a rotating wheel at 4 °C for 4 h. Magnetic beads (50 ll) (Bangs Laboratories Inc.) coupled with antimouse IgG was added to the sample, which was mixed for 2 h at 4 °C by end-over-end rotation. The magnetic beads were then pelleted by a Magnetic Separation Rack for 2 min at 4 °C and the supernatant was discarded. The magnetic beads were washed at 4 °C for 5 min with rotation with 500 ul of each of the following buffers in the order listed: Wash Buffer 1: 0.1 % SDS; 1 % Triton X-100; 2 mM EDTA; 20 mM Tris/HCl, pH 8.0; 150 mM NaCl; Wash Buffer 2: 0.1 % SDS; 1 % Triton X-100; 2 mM EDTA; 20 mM Tris/HCl, pH 8.0; 500 mM NaCl; and Wash Buffer 3: 10 mM Tris/HCl, 1 mM EDTA, pH 8.0. The beads were washed once in Wash Buffer 1, twice in Wash Buffer 2, and twice in Wash Buffer 3. Between each wash, the beads were pelleted as before and the supernatant was carefully removed to avoid disturbing the beads. To each methylated DNA immunoprecipitation ‘‘MeDIP’’ or ‘‘mock IP’’ tube, 200 ul of Elution Buffer (1 mM Tris/HCl, pH 8.0; 0.5 mM EDTA, pH 8.0; 10 % SDS) was added. Elution proceeded at 65 °C for 15 min. Beads were separated from the solution using a magnet and the supernatant was transferred to a new
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tube. Immunoprecipitated and reference DNA were extracted with phenol/chloroform. MeDIP-CHIP A genome library was prepared using the GenomePlex Whole Genome Amplification Kit (Sigma-Aldrich) and a thermal cycler. The DNA was purified using a QIAquick PCR purification kit (Qiagen) and then labeled with Cy3/Cy5 dye-labeled random primers (TriLink Biotechnologies) and a Klenow Fragment (New England Biolabs). Hybridization was achieved using Hybridization Kit 40 (NimbleGen). Mixers were prepared with the NimbleChip Mixer (NimbleGen). Sample loading and hybridization were accomplished using the Hybridization System (NimbleGen). Hybridized arrays were washed using Hybridization Kit 40 (NimbleGen). Two-color array scans were completed using GenePix 4000B. Data were extracted using GenePix Pro 6.0 and exported into a spreadsheet. Agilent whole genome oligo microarrays (onecolor) Total RNA was extracted using TRIzol and purified by the RNeasy Mini kit (Qiagen). RNA was labeled by the Quick Amp Labeling Kit, One-Color (Agilent) and purified with the RNeasy Mini kit. Hybridization of the purified RNA was performed using the Gene Expression Hybridization kit (Agilent). Samples were washed with Gene Expression Wash Buffer 1 (Agilent) and Gene Expression Wash Buffer 2 (Agilent). The prepared microarrays were then scanned with the Microarray Scanner (Agilent) and the data were extracted using Feature Extraction Software (Agilent).
Hypergeometric-P value) denotes the significance of the pathway correlated to the conditions. The lower the P-value, the more significant the pathway. The recommend P value cut-off is 0.05.
Results Twenty days after carbendazim treatment, the seedlings in D2 (0.1 mM) and D3 (0.2 mM) showed no significant differences with the seedlings in the control (CK), except that the root length was shorter and the lateral root was longer in the treated seedlings compared with the control (Fig. 1, see also Supplementary Figs. 1, 2). Genomic DNA methylation in response to carbendazim treatment The gene chip data revealed 6671 methylation sites in the DNA from the seedlings in the control group, and 6690 and 7193 methylation sites in the DNA from D2 and D3, respectively. The genome methylation analysis detected 1541 methylation loci and 1522 demethylation sites in the D2 treatment group that were different than those in CK. In the D3 treatment group, there were 2790
Data analysis The Gene Ontology (GO) project provides a controlled vocabulary to describe gene and gene product attributes in any organism (http://www.geneontology. org). The P value denotes the significance of the enrichment of GO terms in the DE genes. The lower the P value, the more significant the GO term. A P value B0.05 is recommended. Pathway analysis is a functional analysis that maps genes to KEGG (the Kyoto Encyclopedia of Genes and Genomes; http://www.genome.jp/kegg/) pathways. The P-value (EASE-score, Fisher-P value or
Fig. 1 Seedlings of Arabidopsis after treatment with carbendazim showing thicker leaves and more lateral roots as compared to the control. CK control, D2 0.1 mM carbendazim treatment, D3 0.2 mM carbendazim treatment
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Biotechnol Lett Fig. 2 Numbers of methylated/demethylated sites in genomic DNA of Arabidopsis after treatment with carbendazim as compared to the control. D2 0.1 mM carbendazim treatment, D3 0.2 mM carbendazim treatment
methylation loci and 2278 demethylation sites that were different than those in CK. There were 472 methylation loci and 872 demethylation loci common to both carbendazim treatment groups (Fig. 2). The results showed that 11 transcription factors were among the methylated genes and 16 transcription factors were among the demethylated genes in the two carbendazim treatment groups (Tables 1, 2). Gene expression microarray analysis The microarray results showed that in the D2 treatment group, 279 genes were up-regulated 300 %, while 175 genes were down-regulated 67 % compared with those genes in CK. This accounted for 2.8 and 1.8 % of the
total genes. (The total number of genes in the microarray was 9999.) In the D3 group, 505 genes were up-regulated 300 % (accounting for 5 %), while 609 genes were down-regulated 67 % (accounting for 6 %) compared with those genes in CK (Fig. 3). GO analysis showed that the changes in gene expression after carbendazim treatment involved a wide range of biological processes, including several stress stimulation processes such as chemical stimulation and abiotic stress response (Figs. 4, 5). Metabolic pathway gene expression changes The microarray results were analyzed using the KEGG pathway database. The differentially expressed genes
Table 1 Transcription factors showing increased methylation levels both in 0.1 mM and 0.2 mM carbendazim treatments as compared to the control Gene name (NCBI accession)
Gene description
AT1G19000
myb family transcription factor, similar to MybSt1 GI:7705206 from (Solanum tuberosum)
AT1G27490
Similar to MYB transcription factor isolog (AC002335)
AT2G03500
myb family transcription factor, contains Pfam profile: PF00249
AT2G22850
bZIP transcription factor family protein, contains a bZIP domain
AT3G09370
myb family transcription factor (MYB3R3), contains Pfam profile
AT1G58100
TCP family transcription factor, putative
AT3G45150
TCP family transcription factor, putative
AT4G34590
bZIP transcription factor family protein
AT5G06950 AT5G28770
Similar to bZIP family transcription factor [Arabidopsis thaliana] Similar to bZIP transcription factor family protein [Arabidopsis thaliana]
AT1G46480
Homeobox-leucine zipper transcription factor family protein
AT5G45710
Heat shock transcription factor family protein, contains Pfam profile
AT5G67000
Encodes a member of the ERF (ethylene response factor) subfamily B-6 of ERF/AP2 transcription factor family
AT1G58330
Transcription factor-related
AT1G59453
Transcription factor-related, weak similarity to TFIIIC Box B-binding subunit (Homo sapiens) GI:442362
AT1G68150
Protein_coding_gene:WRKY family transcription factor, similar to DNA-binding protein ABF2 GI:1159879 from Avena fatua
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Biotechnol Lett Table 2 Transcription factors showing decreased methylation levels both in 0.1 mM and 0.2 mM carbendazim treatments as compared to the control Gene name (NCBI accession)
Gene description
AT1G35490
bZIP family transcription factor
AT1G55600
WRKY family transcription factor, similar to SPF1 protein GI:484261 from Ipomoea batatas
AT1G62990
Homeodomain transcription factor (KNAT7), contains Pfam profiles
AT2G40140
Similar to zinc finger (CCCH-type) family protein [Arabidopsis thaliana] (TAIR:At3g55980.1)
AT4G04580
Protein coding gene: myb family transcription factor, contains Pfam profile: PF00249 myb-like DNA-binding domain
AT4G04800
Low similarity to pilin-like transcription factor (Homo sapiens) GI:5059062, SP:P14930
AT4G20400
Similar to transcription factor jumonji (jmj) family protein/zinc finger (C5HC2 type) family protein [Arabidopsis thaliana] (TAIR:At2g34880.1)
AT5G17490
Putative member of the VHIID domain transcription factor family RGAL—Arabidopsis thaliana, EMBL:AJ224957
AT5G38800 AT5G39230
bZIP transcription factor family protein, similar to bZIP transcription factor GI:1769891 from Arabidopsis thaliana Transcription initiation factor-related, contains weak similarity to Transcription initiation factor IIB (General transcription factor TFIIB)
AT5G45420
myb family transcription factor, contains Pfam profile: PF00249
were predicted to be involved in 32 signaling pathways; in the D2 group, 21 pathways were involved and in the D3 group, 25 pathways were involved (Tables 3, 4). Expression profiles associated with methylation analysis A conjoint analysis of the methylation and expression microarray chip data showed that 20 and 39 genes were both demethylated and up-regulated 3-fold, and 21 and 24 genes were both methylated and downregulated 3-fold in D2 and D3, respectively. A further 21 genes were both demethylated and up-regulated 2-fold, and three genes were both methylated and down-regulated 2-fold in D2 and D3, respectively (Tables 4, 5, 6; Fig. 6).
Discussion Epigenetic information is one of the basic forms of plant genetic diversity. For example, it is involved in the regulation of gene expression (McCarthy 2013; Li et al. 2012), adaptation to stress conditions (Karan et al. 2012; Wang et al. 2011), and the formation of heterosis (Chen 2013; He et al. 2013). DNA methylation is a relatively stable epigenetic form and DNA
methylation changes could cause changes in biological traits, which could be inherited through somatic or germ cells (Henderson and Jacobsen 2007). Previous studies often have been focused on the epigenetic effects of environmental pollution on animals and humans, and many of these studies have indicated that pollution may have an important influence on the genome (Collotta et al. 2013). Methoxychlor (Mori et al. 2011; Sciandrello et al. 2004), vinclozolin (Chanda et al. 2006; Pilsner et al. 2007), organochlorine pesticides (Pilsner et al. 2009), DDE, BHC, oxychlordane, chlordane, Mirex, PCBs (Stouder and Paoloni-Giacobino 2011),and DDT (Zama and Uzumcu 2009) can all trigger DNA methylation changes in human cells and rat organs. The epigenetic impact of environmental pollution (Guerrero-Bosagna et al. 2010), especially pesticides, has not been reported so far. To our knowledge, this is the first study to look at epigenetics in response to pesticide exposure in plants. The results showed that carbendazim application could change genomic DNA methylation in A. thaliana, and that this caused significant changes in the gene expression profile of the treated plants. Some up- and down-regulated genes that may be associated with these changes were identified in the carbendazim-treated plants. Recently, gene chips have been used widely to determine changes in DNA methylation sites in
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Fig. 3 Numbers of differentially expressed genes in groups treated with carbendazim. D2 versus CK UP up-regulation of gene expression in D2 compared with the control, D3 versus CK UP up-regulation of gene expression in D3 compared with the control, D2 versus CK down down-regulation of gene expression in D2 compared with the control, D3 versus CK down down-regulation of gene expression in D3 compared with the control. (D2 0.1 mM carbendazim treatment, D3 0.2 mM carbendazim treatment)
mammalian genomes. Exposing pregnant rats to vinclozolin was found to cause DNA methylation changes in the promoter regions of the sperm epigenome in the F3 generation using gene chip Fig. 4 Enrichment scores of down-regulated biological processes following carbendazim treatment. D2 0.1 mM carbendazim treatment, D3 0.2 mM carbendazim treatment
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technology, and some of the genes were identified as candidate markers (Chanda et al. 2006). Zhang et al. (2012a) identified 1069 CpG sites in 984 genes with significant methylation changes in diazinon-treated human K562 cells using a microarray, and some of these genes were predicted to be associated with cancer development or involved in related biological pathways. In the present study, we detected 1522 and 2278 demethylated sites and 1541 and 2790 methylated sites in D2 and D3 carbendazim-treated A. thaliana, respectively, using a DNA chip. Compared with the control, there were 279 and 505 genes that were upregulated 3-fold, and 175 and 609 genes that were down-regulated 3-fold in D2 and D3, respectively. Genes associated with stress and chemical stimulation may also participate in interactions between bacteria and plants (Timmusk et al. 1999). We propose that such genes may be used as candidate markers to decide whether carbendazim treatment is required during the course of plant development. MEK1 (AT4G26070) is a possible example of a marker gene but many more experiments are required to verify this. Many of these genes have been reported to participate in important physiological and biochemical processes
Biotechnol Lett Fig. 5 Enrichment scores of up-regulated biological processes following carbendazim treatment. D2 0.1 mM carbendazim treatment, D3 0.2 mM carbendazim treatment
Table 3 The enrichment score and the down-regulated genes of metabolic pathways which have changed both in the 0.1 mM and 0.2 mM carbendazim treatments as compared to the control Pathway identification
Definition
Enrichment score
ath00460
Cyanoamino acid metabolism
3.5
bglu40//nit1//shm1//shm7//nit2
ath00910
Nitrogen metabolism
2.7
bca4//nit1//ca1//nit2//asn2
ath00450 ath00710
Selenocompound metabolism Carbon fixation in photosynthetic organisms
ath00670
One carbon pool by folate
2.1
mthfr1//shm1//shm7
ath00195
Photosynthesis
1.6
atfd1//atpc1//fed_a//npq4//psby
ath00630
Glyoxylate and dicarboxylate metabolism
1.5
cat1//pglp1//shm1//shm7
22 2.1
Genes
aps4//atms2//ntrb aoat2//gapb//pkp3//prk//sbpase//atppc3
Pathway identification is from the KEGG database
Table 4 The enrichment score and the up-regulated genes of metabolic pathways which have changed both in the 0.1 mM and 0.2 mM carbendazim treatments as compared to the control Pathway identification
Definition
Enrichment score
Genes
ath04626
Plant-pathogen interaction
7.0
atmpk3//cnbt1//cngc19//efr//fls2//frk1//jaz1//mek1// rin4//rps2//serk4/tch3//wrky25//rps4
ath00460
Cyanoamino acid metabolism
4.3
bglu15//bglu17//bglu44//bxl2//ggt4//nit4
ath00591
Linoleic acid metabolism
2.9
lox2//lox5//lox3
ath04075
Plant hormone signal transduction
2.7
abf1//erf1//erf2//ers1//ers2//etr2//gh3.3//jaz1// jaz5//pbs3//tga3//wes1//jaz10//ebf2
ath00940
Phenylpropanoid biosynthesis
2.2
bglu15//bglu17//bglu44//bxl2//ccr2//prxca//prxcb//rci3
ath00909
Sesquiterpenoid and triterpenoid biosynthesis
1.9
thas1//tps12//tps13
ath00910
Nitrogen metabolism
1.7
atgsr1//gdh1//gln1;4//bca3//bca4
ath00860
Porphyrin and chlorophyll metabolism
1.5
atfer1//atfer4//pora//porb
Pathway identification is from the KEGG database
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Biotechnol Lett Table 5 Both demethylation and up-regulation genes being detected both in the 0.1 mM and 0.2 mM carbendazim treatment groups as compared to the control Gene name (NCBI accession)
Fold change D2 versus CK
Fold change D3 versus CK
Gene description
AT1G35710
63.5
47.2
Putative leucine-rich repeat receptor-like protein kinase(Arabidopsis thaliana);
AT1G30900
11.3
12.6
Vacuolar sorting receptor 6
AT1G79700
3.4
5.3
AP2-like ethylene-responsive transcription factor.
AT3G42725
2.5
6.8
Putative membrane lipoprotein
AT2G20142
3.3
4.3
Toll-interleukin-resistance domain-containing protein
AT4G15120 AT4G25940
2.4 3.8
3.3 2.8
VQ motif-containing protein ENTH/ANTH/VHS superfamily protein
AT1G59960
2.9
5.5
NAD(P)-linked oxidoreductase superfamily protein
AT1G03850
6.3
7.8
Arabidopsis thaliana glutaredoxin family protein
AT3G62550
3.5
5.1
Drought responsive ATP-binding motif containing protein
AT5G05965
2.3
4.6
Hypothetical protein, uncharacterized protein.
AT1G72060
9.8
12.9
AT5G39240
2.2
4.9
Hypothetical protein uncharacterized protein
AT3G25400
2.2
3.1
Hypothetical protein uncharacterized protein
AT3G57700
4.3
4.2
Putative protein kinase
AT4G38550
5.7
5.3
Phospholipase like protein (PEARLI 4) family
AT5G44390
2.5
2.4
FAD-binding Berberine family protein
AT4G26070
3.9
4.3
AT2G40300
3.1
5.5
MEK1 (MAP KINASE/ERK KINASE 1); MAP kinase kinase/kinase/protein binding (MEK1) Arabidopsis thaliana ATFER4 (ferritin 4)
AT1G02065
2.8
3.2
Arabidopsis thaliana SPL8 (SQUAMOSA PROMOTER BINDING PROTEINLIKE 8)
AT5G28640
2.9
4.3
Arabidopsis thaliana AN3 (ANGUSTIFOLIA 3)
AT5G67480
3.0
4.6
Arabidopsis thaliana BT4 (BTB AND TAZ DOMAIN PROTEIN 4)
Serine-type endopeptidase inhibitor
D2 versus CK = 0.1 mM carbendazim treatment compared with the control; D3 versus CK = 0.2 mM carbendazim treatment compared with the control
Table 6 Both methylation and down-regulation genes being detected both in the 0.1 mM and 0.2 mM carbendazim treatment groups as compared to the control Gene name (NCBI accession)
Fold change D2 versus CK
Fold change D3 versus CK
Gene description
AT5G35460
-2.3
-5.8
Hypothetical protein uncharacterized protein
AT2G35130
-2.2
-2.7
Pentatricopeptide repeat-containing protein
AT4G09420
-4.3
-2.1
TIR-NBS class of disease resistance protein
D2 versus CK = 0.1 mM carbendazim treatment compared with the control; D3 versus CK = 0.2 mM carbendazim treatment compared with the control
but the specific mechanism of action of these genes requires further study. Additionally, the functions of AT5G35460, AT3G25400, and AT5G39240 are still unknown so further studies are required to elucidate their action mechanisms.
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This study showed that the application of carbendazim caused multiple gene alterations in DNA methylation in Arabidopsis, and also brought about changes in gene expression. This finding is of importance because in agricultural production, for example,
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Fig. 6 The number of genes in which the methylation status and expression levels having both changed in D2 and D3 treatments as compared to the control. A the number of both upregulation and demethylation genes; a the number of overlap
genes in D2 and D3. B the number of both down-regulation and methylation genes; b the number of overlap genes in D2 and D3 (D2 0.1 mM carbendazim treatment, D3 0.2 mM carbendazim treatment)
pesticides are commonly used. Therefore, if pesticide application can cause genetic changes in crops, it could affect the genetic stability of specie. In farming, the problem of degradation of crop varieties is encountered frequently, and whether the epigenetic impact of pesticide use might be one of the reasons for species degeneration, needs further study. The results of this study suggest that the use of pesticides could cause widespread DNA methylation in plants. It is possible that measuring DNA methylation could be used to determine whether pesticides have been used during agricultural production. Crops grown without the use of pesticides are the organic foods that have been widely praised by consumers. Traditional residue-detection methods used in organic vegetable production are not reliable because these methods cannot detect chemical application in the early stages of farming. However, if pesticides are applied during the plant growth process, they may cause variations in the DNA methylation status of a group of genes. Therefore, whether organic farming methods have been used to grow vegetables (for example) could be detected by measuring DNA methylation changes in target genes. Our results also indicate that carbendazim can have an impact on many important biological processes in Arabidopsis, including photosynthesis, amino acid metabolism, selenium and nitrogen metabolism, and nutrient accumulation. Such influences will lead inevitably to changes in some secondary metabolic processes, which will have an impact on plant functional ingredients. In medicinal plants, changes in secondary metabolic processes could directly affect the plant’s medicinal efficacy (Gershenzon 1984).
Direct and indirect relationships between selenium and 40 common diseases have been reported (Nogales et al. 2013; Hatfield et al. 2012) may affect plant nitrogen metabolism and nutritional ingredients (Zhang et al. 2012a; Taiwo and Oso 1997; Macedo et al.2013; Masakapalli et al.2013). Carbendazim treatment, therefore, may have a significant impact on the nutritional value of a crop and on the medicinal value of medicinal plants, resulting in unpredictable effects on the human body. Because only one pesticide, carbendazim, was studied in this research, further work is needed to determine if other pesticides also alter DNA methylation, and whether the variations are specific to each pesticide. In addition, whether different plants exhibit specific DNA methylation patterns to a given pesticide also requires further investigation. It is possible that each farm chemical produces a specific methylation pattern, which could be used to detect whether pesticides have been applied during crop production. Clearly, broader and more in-depth studies are required to determine the effects of pesticides on plant DNA methylation and gene expression. Acknowledgments Financial support from the National Science Foundation of China(no. 31171982, no. 31372090)and the Foundation of Henan University (China) (no. 0000A40448). Conflict of interests conflict of interests.
The authors declare that they have no
Supporting information Supplementary Fig. 1—The length of roots was significantly decreased with the carbendazim added. Supplementary Fig. 2—The number of fibrous roots was significantly increased with the carbendazim added.
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