Cyst Nematode Parasitism Induces Dynamic...(CH3) to the C5 position of the cytosine to generate...

Cyst Nematode Parasitism Induces DynamicChanges in the Root Epigenome1[OPEN]

Tarek Hewezi*, Thomas Lane, Sarbottam Piya, Aditi Rambani, J Hollis Rice, and Meg Staton

Department of Plant Sciences (T.H., S.P., A.R., J.H.R.), Department of Entomology and Plant Pathology (T.L.,M.S.), University of Tennessee, Knoxville, Tennessee 37996

ORCID IDs: 0000-0001-5256-8878 (T.H.); 0000-0003-4082-9502 (T.L.); 0000-0003-4046-1672 (J.H.R.).

A growing body of evidence indicates that epigenetic modifications can provide efficient, dynamic, and reversible cellularresponses to a wide range of environmental stimuli. However, the significance of epigenetic modifications in plant-pathogeninteractions remains largely unexplored. In this study, we provide a comprehensive analysis of epigenome changes during thecompatible interaction between the beet cyst nematode Heterodera schachtii and Arabidopsis (Arabidopsis thaliana). Whole-genomebisulfite sequencing was conducted to assess the dynamic changes in the methylome of Arabidopsis roots in response to H.schachtii infection. H. schachtii induced widespread hypomethylation of protein-coding genes and transposable elements (TEs),preferentially those adjacent to protein-coding genes. The abundance of 24-nt siRNAs was associated with hypermethylation ofTEs and gene promoters, with influence observed for methylation context and infection time points. mRNA sequencing revealeda significant enrichment for the differentially methylated genes among the differentially expressed genes, specifically those withfunctions corresponding to primary metabolic processes and responses to stimuli. The differentially methylated genes overlappedwith more than one-fourth of the syncytium differentially expressed genes and are of functional significance. Together, our resultsprovide intriguing insights into the potential regulatory role of differential DNA methylation in shaping the biological interplaybetween cyst nematodes and host plants.

Plant-parasitic cyst nematodes (Heterodera species) areamong the most devastating pathogens of plant roots.These obligate parasites initiate a long period of bioticinteractions with their host plants where formation of anoperative feeding structure, the syncytium, is vital fornematode survival and development. The nematodeprovokes differentially terminated cells in the vascularroot tissues to redifferentiate into a syncytium cell type, adynamic process that involves changes in the expressionof thousands of genes simultaneously (Hewezi andBaum, 2013; Kyndt et al., 2013; Hewezi, 2015). Thoughthe mechanisms controlling gene expression changes inthe syncytium remain ill defined, recent studies indicatethat epigenetic mechanisms including noncoding smallRNAs and DNA methylation may play fundamentalroles (Hewezi and Baum, 2015).

DNA methylation is a common epigenetic modifica-tion process that involves the addition of amethyl group(CH3) to the C5 position of the cytosine to generate5-methylcytosine. In plants, cytosine methylation occursin three DNA sequence contexts including CG, CHG,and CHH, where H represents any nucleotide except G.Although DNAmethylation can be stably inherited overseveral generations through both meiosis and mitosis(Becker et al., 2011; Schmitz et al., 2011), the establishment,maintenance, and removal of methylation patterns areoften subject to dynamic regulation during plant devel-opment, reproduction, and responses to biotic and abioticstresses (He et al., 2011; Sahu et al., 2013; Kim andZilberman, 2014; Matzke and Mosher, 2014; Deleris et al.,2016). In plants, de novo DNA methylation in CG, CHG,and CHH contexts is established through the activity ofDOMAINS REARRANGED METHYLTRANSFERASEs(DRMs) and the RNA-directed DNA methylation(RdDM) pathway (Cao and Jacobsen, 2002; Cao et al.,2003; Henderson and Jacobsen, 2007; Matzke et al.,2009; Law and Jacobsen, 2010). In the RdDM path-way, double-stranded RNAs (dsRNAs) generated byRNA-dependent RNA polymerase2 are cleaved into24-nucleotide (nt) short interfering RNAs (siRNAs) byDICER-LIKE3 (DCL3). Theseprocessed siRNAsare loadedinto a complex of proteins containing ARGONAUTE4(AGO4) and AGO6. This complex recruits and guidesDRM2 to the target loci in a sequence-dependentmannerto establish de novo DNA methylation in all sequencecontexts (Matzke et al., 2009; Matzke andMosher, 2014).In addition, a noncanonical RDR6-dependent RdDM

1 This work was supported by Hewezi Laboratory startup fundsfrom the University of Tennessee, Institute of Agriculture, and by agrant from TN-SCORE (Tennessee Solar Conversion and Storage us-ing Outreach, Research and Education) to T.H. and M.S.

* Address correspondence to [email protected] author responsible for distribution of materials integral to the

findings presented in this article in accordance with the policy de-scribed in the Instructions for Authors (www.plantphysiol.org) is:Tarek Hewezi ([email protected]).

T.H. conceived and designed the experiments; T.H., S.P., A.R., andJ.H.R. performed the experiments; T.H., T.L., and M.S. analyzed thedata; T.H. wrote the manuscript; all authors read and approved thefinal manuscript.

[OPEN] Articles can be viewed without a subscription.www.plantphysiol.org/cgi/doi/10.1104/pp.16.01948

Plant Physiology�, May 2017, Vol. 174, pp. 405–420, www.plantphysiol.org � 2017 American Society of Plant Biologists. All Rights Reserved. 405

Dow

nloaded from https://academ

ic.oup.com/plphys/article/174/1/405/6116697 by guest on 14 June 2021

http://orcid.org/0000-0001-5256-8878http://orcid.org/0000-0001-5256-8878http://orcid.org/0000-0001-5256-8878http://orcid.org/0000-0003-4082-9502http://orcid.org/0000-0003-4082-9502http://orcid.org/0000-0003-4046-1672http://orcid.org/0000-0003-4046-1672http://orcid.org/0000-0001-5256-8878http://orcid.org/0000-0003-4082-9502http://orcid.org/0000-0003-4046-1672http://crossmark.crossref.org/dialog/?doi=10.1104/pp.16.01948&domain=pdf&date_stamp=2017-04-20mailto:[email protected]://www.plantphysiol.orgmailto:[email protected]://www.plantphysiol.org/cgi/doi/10.1104/pp.16.01948

pathway that can initiate de novo DNA methylationhas been recently described (Matzke and Mosher,2014). In this pathway, some transcripts are copied byRDR6 to generate dsRNAs, which then are processedinto 21- to 22-nt siRNAs by DCL2 and DCL4. These 21-to 22-nt siRNAs can trigger low levels of de novo DNAmethylation when associated with DRM2 and AGO2(Matzke andMosher, 2014). In contrast to de novo DNAmethylation,maintenance of symmetricalmethylation inCG and CHG contexts during DNA replication is me-diated independently of the RdDM pathway throughthe activity of DNA METHYLTRANSFERASE1 andCHROMOMETHYLASE3, respectively. Both enzymesuse hemimethylated DNA as a template to copy themodifications to the other strand. Unlike symmetricalmethylation, asymmetric CHH methylation is estab-lished de novo during each cell cycle and requires theactivity of DRMs and the RdDM pathway (Cao andJacobsen, 2002; Cao et al., 2003; Law and Jacobsen, 2010).Recent findings suggest that the RdDM pathway maycontribute to more dynamic modifications that involveboth methylation and demethylation. DNA demeth-ylation is mediated by a small family of DNA glyco-sylases that includes REPRESSOR OF SILENCING1and DEMETERs (Zhu, 2009). The identification ofseveral components of the RdDM pathway in geneticscreens for ros1 suppressors pointed to an antagonisticrelationship between active DNAmethylation and theRdDM pathway (Zhang and Zhu, 2012).

DNA methylation can regulate the expression ofprotein-coding genes and the activity of transposableelements (TEs). CG methylation frequently occurs ingene body regions, whereas CHG and CHH methyla-tion are mostly found in TEs and other repetitive se-quences (Cokus et al., 2008; Lister et al., 2008; Schmitzet al., 2011; Rambani et al., 2015; Yong-Villalobos et al.,2015; Zhang et al., 2015; Kawakatsu et al., 2016). Whilethe functional role of gene bodymethylation is not fullyunderstood, it has been suggested that methylationin the gene body may fine-tune transcriptional activity,regulate alternative splicing efficiency, and inhibit aber-rant transcription of long transcripts (Zilberman et al.,2007; Luco et al., 2010; Maunakea et al., 2010; Regulskiet al., 2013; Rambani et al., 2015). DNA methylation ofTEs contributes to maintenance of the silent state of TEsand prevents their proliferation (Slotkin andMartienssen,2007; Hollister andGaut, 2009; Ito et al., 2011). Also, levelsand patterns of DNA methylation frequently impact theexpression of neighboring genes (Dowen et al., 2012;Wang et al., 2013; Le et al., 2014; Secco et al., 2015).

Recent studies have implicated DNA methylation inregulating plant gene expression in response to pathogeninfection. For example, infection by the bacterial pathogenPseudomonas syringae induced genome-wide DNA hypo-methylation in Arabidopsis (Arabidopsis thaliana) that im-pacted the expression of immune-response genes (Dowenet al., 2012; Yu et al., 2013). Also, a role of DNA demeth-ylation in modulating the interaction between the fungalpathogen Fusarium oxysporum and Arabidopsis has beenreported (Le et al., 2014). Recently, it has been shown that

gain or loss of DNA methylation antagonistically alteredplant basal resistance against the oomycete pathogenHyaloperonospora arabidopsidis (López Sánchez et al., 2016).In addition, our recent analysis of global DNA meth-ylation changes induced by the soybean cyst nematodeHeterodera glycines in soybean roots revealed substantialchanges in DNA methylation patterns, pointing to apotential association between differential DNA methyl-ation and transcriptome changes during cyst nematodeparasitism of host plants (Rambani et al., 2015).

In this study,we generatedmethylomemaps at single-base resolution, combined with mRNA and small RNAtranscriptomes of Arabidopsis roots infected with thebeet cyst nematode Heterodera schachtii. We found ex-tensive differences in the methylomes of Arabidopsisroots during the nematode infective stages correspond-ing to syncytium formation and maintenance phases.H. schachtii-induced methylome changes are character-ized by substantial increases in hypomethylation pat-terns that occurred predominantly in gene bodies andTEs in a context-specific fashion. Our results suggest thatdifferential methylation over differentially expressed geneschanges over the course of infection andmay contribute tothe steady-state expression levels at later stages of infection.Collectively, our data suggest that differential DNAmethylation associated with gene expression changesin the syncytium may determine the compatibility ofthe interaction between Arabidopsis and H. schachtii.

RESULTS

To identify changes in DNA methylation patternsassociated with the compatible interaction between thebeet cyst nematode H. schachtii and Arabidopsis, weused the bisulfite sequencing/MethylC-Seq approachto generate whole-genome, single-base resolution DNAmethylomes of Arabidopsis roots post-H. schachtii in-fection. Arabidopsis plants (ecotype Col-0) were inoc-ulated with H. schachtii, and three biological samples ofroot tissues were collected from both infected andnoninfected plants at 5 and 10 d postinfection (dpi). The5 and 10 dpi time points were selected to reflect thephases of syncytium formation and maintenance, re-spectively. Genomic DNA was extracted and used toprepare 12 MethylC-Seq libraries. Sequencing of theselibraries using the Illumina HiSeq platform resulted inmore than 378 million 100-basepair reads. After qualityfiltering, uniquely mapped reads to the Arabidopsisgenome (TAIR10) resulted in more than 233 genomecoverage per treatment (Supplemental Table S1). Usingthe nonmethylated l phage genome, we determinedthat the bisulfite conversion efficiency was higher than99.7%.

To identify regions of the Arabidopsis genome thatwere subjected to significant changes in DNA methyl-ation in response to H. schachtii infection, we identifieddifferentially methylated cytosines between infectedand control samples and the associated genomic re-gions using 200-basepair nonoverlapping windows.

406 Plant Physiol. Vol. 174, 2017

Hewezi et al.

Dow



http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1

Differentially methylated regions (DMRs) with a min-imum methylation difference of 25% were identified inCG, CHG, andCHH contextswith a false discovery rateof less than 1%. A total of 10,995 and 8622 unique DMRswere identified at 5 and 10 dpi, respectively (SupplementalData Set 1). These high numbers of DMRs indicate thatthe methylomes of Arabidopsis roots are significantlyaltered during the nematode infective stages corre-sponding to syncytium formation and maintenancephases. However, only 1042 DMRs overlapped be-tween the 5- and 10-d time points, suggesting that eachinfection stage is associated with distinct patterns ofDNAmethylation. TheDMRswere classified into hyper-and hypomethylated regions in CG, CHG, and CHHcontexts. At 5 dpi, 9499 differentially hypomethylatedregions (hypo-DMRs) and 728 differentially hyper-methylated regions (hyper-DMRs) were identified inCG context in the infected roots compared with thenoninfected control (Fig. 1A; Supplemental Data Sets1 and 2). Similarly, in the CHG context, 1264 hypo-DMRs and 221 hyper-DMRs were identified, whereasin the CHH context, 289 hypo-DMRs and 33 hyper-DMRs were identified (Fig. 1A; Supplemental DataSets 1 and 2). At 10 dpi, we identified 5702 hypo-DMRsand 1832 hyper-DMRs in the CpG context, 1325 hypo-DMRs and 112 hyper-DMRs in the CHG, and 578 hypo-DMRsand49hyper-DMRs inCHH(Fig. 1B; SupplementalData Sets 1 and 2). Finally, 428 regions were differentiallymethylated in more than one context (Supplemental DataSets 1 and 2). These results indicate that in all sequencecontexts H. schachtii induces hypomethylation to a muchhigher degree than hypermethylation.We next assigned DMRs in various sequence con-

texts to overlapping protein-coding genes and TEsbased on their genomic coordinates. At both time points,differential CG methylation was mostly associated withprotein-coding genes and to a lesser extentwith TEs (Fig.1, C and D). In contrast, differential methylation in theCHG and CHH contexts mainly overlapped with TEs(Fig. 1, C and D), consistent with the role of CHG andCHH methylation in regulating the activity of TEs. Aclear distinction between the two time points is the in-crease of CG hypermethylation at 10 dpi relative to5 dpi, specifically in protein-coding genes. At 10 dpi,the number of CG hyper-DMRs overlapping withprotein-coding genes was about 4-fold more than thatidentified at 5 dpi (1177 versus 298), whereas the numberof CG hypo-DMRs was 1.8 times less than the numberidentified at 5 dpi (3157 versus 5819; Fig. 1, C and D).Also, we uncovered an increase in the number of CHHhypo-DMRs overlapping with TEs at 10 dpi (Fig. 1D).These results imply dynamic changes in both methyla-tion patterns and activity during nematode parasitism ofArabidopsis.To determine if certain genic regions are associatedwith

a specific methylation context, we examined the distribu-tion ofDMRs at various annotated gene features, includingpromoters, 1000 basepairs upstream of the transcriptionstart site, exons, introns, and 59 and 39 untranslated regions(UTRs). The hyper- and hypomethylation in the CG

context occurred predominantly in gene bodies (exonsand introns), whereas hyper- and hypomethylation inthe CHG and CHH contexts were enriched in promoterregions (Fig. 1E; Supplemental Data Set 1). Though thedistributions of CHG and CHH methylation were verysimilar across the promoters and UTRs, the frequency ofCHGhypo-DMRs in exons and intronswasmuchhigherthan that of CHH hypo-DMRs at both 5- and 10-d timepoints (Fig. 1E; SupplementalData Set 1). Also,we foundthat the fraction of DMRs associated with the 39 UTRswas greater than those associated with 59 UTRs specifi-cally in the CG context (Fig. 1E; Supplemental Data Set1). These data indicate that each methylation context ispreferentially linked to specific genic regions.

H. schachtii Targets Various TE Classes forDifferential Methylation

To determine whether H. schachtii targets specific TEfamilies or classes during infection, we grouped theDMR-associated TEs (5930) into families and examinedtheir methylation patterns. We uncovered that CHHmethylation mainly targets Helitron and MuDR DNAtransposons, whereas CG and CHG methylation predom-inantly target the long terminal repeat retrotransposonsGypsy, Copia, and LINE/L1, in addition to the DNAtransposons Helitron, MuDR, and En-Spm (Fig. 2A;Supplemental Data Set 2). The distribution of the DMRsoverlapping with various TE families was strikingly sim-ilar at 5 and 10 dpi, with the exception of the absence ofCHG-hyperDMRs that target LINE/L1TEs at 10 dpi (Fig.2A; Supplemental Data Set 2). These analyses indicate thatH. schachtii preferentially targets specific TE families fordifferential DNAmethylation with influence observed formethylation sequence context.

Because DNAmethylation and demethylation of TEsimpact the expression of nearby genes (Hollister andGaut, 2009; Hollister et al., 2011; Hirsch and Springer,2017), we examined whether H. schachtii preferentiallyinduces differential methylation in the TEs that areproximal to genes in a context-dependent manner. Wemeasured the distance from the DMR-associated TEs tothe closest genes (transcriptional start or terminationsites), including both upstream and downstream genes,determined the percentages of DMR-associated TEs at1-kb bins and compared these percentages with thosecorresponding to all TEs in the genome. Strikingly, CHH-hypermethylation occurred preferentially in the TEs thatwere located within 1 kb upstream or downstream fromthe nearest genes (Fig. 2B). For example, while 23% of allTEs in the genome are locatedwithin 1 kb from the nearestgenes, 35.4% of all DMRs-associated TEs that werehypermethylated in the CHH context were locatedwithin1 kb downstream of the nearest genes. In contrast to theCHH context, hypermethylation of TEs in the CG or CHGoccurred preferentially when the TEs were located rela-tively far away from the genes. As shown in Figure 2B,63% and 54% of all hypermethylated TEs in CG or CHGcontexts, respectively, were located. 8 kb away from thenearest genes, whereas only 28% of all TEs in the genome

Plant Physiol. Vol. 174, 2017 407

Cyst Nematode-Induced Epigenome Changes

Dow



http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1

were located . 8 kb away from the flanking genes. Theassociation between CHH methylation of TEs and prox-imity to nearby genes was also evident for hypomethy-lated TEs located within 3 kb upstream or downstream ofthe nearby genes (Fig. 2C).

We refined this analysis to examine the tendency forDNA methylation of TEs nearby genes with respectto transposon types. We found that differential CHHmethylation occurred preferentially in retrotransposons

(class I) that were located within 1 kb upstream of thenearest genes (Fig. 3, A and B). For example, 42.1% of allhypomethylated retrotransposons in CHH context werelocated within 1 kb upstream of the adjacent genes(Fig. 3B). Similarly, about 70% of all differentially meth-ylated DNA transposons (class II) in the CHH contextwere located within 3 kb upstream or downstream of thenearest genes (Fig. 3, C and D). In contrast, CG and CHGhyper-/hypomethylation were abundant in class I and II

Figure 1. Classification of differential DNAmethylation induced byHeterodera schachtii in Arabidopsis roots. A and B, Numbersof hyper-DMRs and hypo-DMRs in CG, CHG, and CHH contexts induced byH. schachtii in Arabidopsis roots at 5 (A) and 10 (B)dpi. C and D, Numbers of hyper-DMRs and hypo-DMRs in CG, CHG, and CHH contexts overlapping with protein-coding genesand TEs at 5 (C) and 10 (D) dpi. E, Stacked bar graph showing the percentage of the DMRs overlapping with various annotatedgenic regions, including promoter, exon, intron, and UTRs, relative to the total numbers of DMRs associated with these genicfeatures in each methylation context at 5 or 10 dpi.


Hewezi et al.

Dow



transposons that were located . 8 kb away from theflanking genes (Fig. 3, A–D). These analyses indicate thatdifferential CHHmethylation of class I and II transposonswas abundant in the TEs that were relatively close togenes, whereas differential methylation in the CG andCHG contexts was abundant in the TEs that were rela-tively distant from genes.

DNA Methylation Contributes to Gene ExpressionChanges in Response to H. schachtii Infection

To determine the extent to which DNA methylationchanges influencedgene expression,we generatedRNA-seq data from the same tissue samples that were usedfor methylation analysis (Supplemental Table S2). Weidentified 1328 and 472 genes as differentially ex-pressed at 5 and 10 d post-H. schachtii infection, re-spectively, at a false discovery rate of less than 5%

(Fig. 4A; Supplemental Data Sets 3 and 4). Only 146 genesoverlapped between the two time points, resulting in atotal number of 1654 genes that significantly changedexpression in response to H. schachtii infection. We thencompared the differentially methylated genes (DMGs)having expression values (5952 genes) with the 1654genes to identify differentially expressed genes (DEGs)that were enriched for differential methylation. Wefound 262 genes overlapping between these two sets(Fig. 4B; Supplemental Data Set 5), indicating that therewas a significant enrichment for DMGs among theDEGs(15.84%, x2 = 993.99, P = 3.62E-215). Further classifica-tion of these 262 differentially methylated DEGsrevealed that 140 were related to 5 dpi and 31 relatedto 10 dpi, and only 7 genes were shared between the twotime points (Fig. 4C; Supplemental Data Set 5). Thisfinding suggests that DNA methylation of the DEGschanged over infection time but few genes maintained

Figure 2. H. schachtii targets various TE families for differential methylation. A, Scaled distribution of DMR-associated TEs over11 transposon families. B and C,H. schachtii preferentially induces differential DNAmethylation in TEs located nearby genes in acontext-dependent manner. CHH hyper-DMRs associate preferentially with TEs that are located within 1 kb upstream ordownstream from the nearest genes (B). CHH hypo-DMRs associate preferentially with TEs that are located within 3 kb upstreamor downstream from the nearest genes (C). Enrichment of DMR-associated TEs in eachmethylation context was calculated relativeto all TEs in the genome for each of the 1-kb nonoverlapping bins using Fisher’s exact test (*P , 0.05).



Dow



http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1

their methylation patterns during disease progression.Also, we found that 29 of the DMGs at 5 dpi were dif-ferentially expressed at 10 dpi, suggesting that DNAmethylation may precede transcriptional changes (Fig.4C). Moreover, we found that 69 of the DEGs at 5 dpiwere differentially methylated at 10 dpi (Fig. 4C), sug-gesting that DNA methylation might contribute to thesteady-state expression levels of these genes at 10 dpiand later stage of infection. The majority of these262 genes were hypomethylated (86%; Fig. 4D) andexhibited significantly higher expression than thehypermethylated genes (P value = 0.00027, Wilcoxonrank-sum test; Fig. 4E). Differential methylation ofthese genes occurred in gene body (171 genes, 65%),promoter (68 genes, 26%), or in both gene body andpromoter regions (23 genes, 9%), predominantly inthe CG context (84%), and to a much less extent in thenon-CG context (16%; Fig. 4D).

To explore the biological processes and molecularfunctions of the differentially methylated DEGs, geneontology (GO) enrichment analysis was performedusing the GO annotation from the AgriGO database

(Du et al., 2010) and Fisher’s exact test. Biological processcategories corresponding to “primary metabolicprocesses,” “response to other organism” and “responseto stimulus,” particularly those related to biotic, external,and chemical stimuli were significantly enriched amongthe differentially methylated DEGs (P value , 0.0001,false discovery rate (FDR) , 0.05; Fig. 4F). Also, thisgene list showed significant overrepresentation ofvarious molecular function groups associated withcatalytic activity, hydrolase activity, transferase activity,tetrapyrrole binding, oxidoreductase activity, andantioxidant activity (P value , 0.001, FDR , 0.05;Supplemental Fig. S1).

Differentially Methylated TEs Impact the Expression ofNearby Genes during H. schachtii Infection

To examine the association between differential meth-ylation of TEs and the expression of nearby genes duringH. schachtii infection, we identified DEGs located within5 kb upstream or downstream of the nearest differ-entially methylated TEs. At 5 dpi, 109 DEGs associated

Figure 3. H. schachtii preferentially induces differential CHH methylation in class I and II TEs located nearby genes. A and B,Distribution of class I TEs that overlapped with DMRs in CG, CHG, and CHH contexts with respect to their distance form closestgenes, showing that CHH hyper-DMRs (A) and CHH hypo-DMRs (B) associate preferentially with TEs that are located 1 kbupstream of the nearest genes. C and D, Distribution of class II TEs that overlapped with DMRs in CG, CHG, and CHH contextswith respect to their distance from closest genes, showing that CHH hyper-DMRs associate preferentially with TEs that are located1 kb upstream of the nearest genes (C), whereas CHH hypo-DMRs associate preferentially with TEs that are located within 3 kbupstream or downstream from the nearest genes (D). Enrichment of DMR-associated TEs in each methylation context was cal-culated relative to all TEs in the genome for each of the 1-kb nonoverlapping bins using Fisher’s exact test (*P , 0.05).


Hewezi et al.

Dow




with 125 TEs and 152 DMRs were identified (Fig. 5A;Supplemental Data Set 6). At 10 dpi, 31 DEGs associ-ated with 33 TEs and 37 DMRs were identified (Fig.5A). After eliminating duplicates, a total number of136 DEGs associated with 157 TEs and 189 DMRswereidentified (Fig. 5A; Supplemental Data Set 6). Con-sidering the 2064 genes identified as differentiallymethylated TE-flanking genes within 5 kb, there was asignificant enrichment for the TE-flanking genes amongthe DEGs (x2 = 707.68, P = 4.5432E-153). The differentialmethylation of the 157 differentially methylated TEsoccurred in CG (55%) and non-CG (45%) methylationcontexts, with the large majority being hypomethylated(87.5%; Fig. 5B). Of note is that 76% (120) of these TEsbelongs to class I DNA transposons, particularly those ofthe DNA/MuDR and RC/Helitron families (Fig. 5C).To test whether hypomethylation of TEs impacted

the expression of flanking genes, the expression levels

of 119 DEGs associated with the hypomethylated TEswere analyzed with respect to their distance from theTEs. As shown in Figure 5D, the DEGs located within 0 to1 kb of the hypomethylated TEs had lower expressionlevels compared to those located 1 to 2 kb away fromthe TEs (Wilcoxon rank-sum test, P, 0.001). Similarly,DEGs located within 1 to 2 kb of the hypomethylatedTEs showed lower expression levels compared tothose located 2 to 5 kb of the TEs (Wilcoxon rank-sumtest, P , 0.001), suggesting that H. schachtii-inducedhypomethylation in TEs is associated with low ex-pression of adjacent genes. GO term enrichmentanalysis of the 136 TE-associated DEGs indicated anoverrepresentation of the biological process cate-gories “development” and “secondary metabolicprocesses,” particularly isoprenoid and terpenoidmetabolic processes (Fig. 5E). Also, molecular func-tion categories corresponding to “catalytic activity”

Figure 4. H. schachtii-induced differential DNA methylation impacts transcript abundance. A, Overlap between DEGs identified inArabidopsis roots at 5 and 10 d post-H. schachtii infection usingmRNA-seq. B, Overlap between the total number of DEGs andDMGs. C,Comparisonsbetween thenumberofDEGsandDMGs identifiedat 5and10dpi.D,Cutoffs formethylationdirection,methylationcontexts,and genic features of the 262 genes overlapping betweenDEGs andDMGs. E,DEGs associatedwith hypo-DMRs exhibit higher expressionlevels than those associated with hyper-DMRs. The 262 genes overlapping between DEGs and DMGs were separated into hyper- andhypomethylated, and their expression levels were displayed as a box plot. Bottom and top boxes represent 25th and 75th percentiles, re-spectively, and whiskers range from the minimum to maximum expression values. Asterisks indicate statistically significant difference asdeterminedbyWilcoxon rank-sum test,P,0.001. F,GO termenrichment analysis of the biological processes of the262genesoverlappingbetween DEGs and DMGs. GO term enrichment analysis was determined using Fisher’s exact test and Bonferroni multitest adjustment.



Dow



http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1

and “hydrolase activity” were enriched among the136 TE-associated DEGs.

siRNAs Associate with Differentially Methylated Regions

To explore the association between siRNA abundanceand patterns of DNA methylation, we sequenced smallRNAs from the same12 root samplesused formethylC-seq

and RNA-seq analyses. We obtained between 11.1 and14.9 million reads per sample, with mapping efficiencyto the Arabidopsis genome being higher than 80%(Supplemental Table S3). Size distribution revealedthat the heterochromatic 24-nt siRNA class represents thelarge majority of the siRNA components (SupplementalFigure S2). The abundance of uniquely mapped siRNAreads (20–25 nt) were compared between hyper- and

Figure 5. Differential methylation of TEs impacts the expression of nearby genes. A, Numbers of DEGs located within 5 kbupstream or downstream of the nearest DMR-associated TEs at 5 and 10 dpi. At both time points, a total number of 136 DEGsassociated with 157 TEs and 189 DMRs were identified. B, Cutoffs for methylation contexts and methylation direction of the157 differentially methylated TEs flanking 136 DEGs. C, Distribution of the 157 differentially methylated TEs flanking DEGs overclass I and class II TE families. D, H. schachtii-induced hypomethylation in TE associates with low expression of nearby genes.DEGs locatedwithin 0 to 1 kb of the hypomethylated TEs showed statistically significant lower expression levels compared to theDEGs locatedwithin 1 to 5 kb of the TEs (Wilcoxon rank-sum test, P, 0.001). Two outlier values (33 IQR above the third quartileor below the first quartile) were suppressed. E, GO term enrichment analysis of the biological processes of the 136 TE-flankingDEGs. GO term enrichment analysis was determined using Fisher’s exact test and Bonferroni multitest adjustment.


Hewezi et al.

Dow



http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1

hypo-DMRs-associated TEs within 2-kb flanking re-gions. We observed higher abundance of siRNAs, spe-cifically the 24-nt class, targeting TEs overlapping withCHHhyper-DMRs and to a lesser extent with CG hyper-DMRs when compared with hypo-DMRs-associatedTEs at both 5 and 10 dpi time points (Fig. 6, A, B, E,and F). However, in the CHG context, a higher abun-dance of siRNAs targeting hyper-DMRs-associatedTEs relative to hypo-DMRs was noted only at 10 dpi(Fig. 6, C and D).Similarly, we compared the abundance of siRNAs

between hyper- and hypo-DMR-associated gene pro-moters, 2 kb upstream of the transcription start site. At5 dpi, siRNA levels in the gene promoters overlappingwith CG or CHG hyper-DMRs were similar to thoseassociated with CG or CHG hypo-DMRs (Fig. 6, Gand I). However, at 10 dpi, increases in siRNA levelsin the gene promoters overlapping with CG or CHGhyper-DMRs were observed compared with thoseassociated with CG or CHG hypo-DMRs (Fig. 6, H andJ). Notably, siRNAs were more abundant in the genepromoters overlapping with CHH hyper-DMRs com-pared to those overlapping with CHH hypo-DMRs atboth time points (Fig. 6, K and L).Because the large majority of gene body methylation

was found in the CG context, we compared the levelsof siRNAs between hyper- and hypo-CG-DMRs over-lappingwith gene body regions.While the abundance ofsiRNA reads in the gene bodywas generallymuch lowercompared with that in gene promoters and TEs, at 5 dpiwe noted about a 2-fold increase in siRNA levels in genebody-hypermethylated genes relative to gene body-hypomethylated genes (Fig. 6M). At 10 dpi, the levelsof siRNAs in hyper- and hypomethylated genes werecomparable (Fig. 6N). Taken together, these data suggestthat high abundance of the 24-nt siRNA class is associ-atedwith hypermethylation of TEs, gene promoters, andto a lesser extent gene body regions with influence ob-served for genomic features, methylation context, andinfection time points.

Differentially Methylated Genes Overlap with SyncytiumDifferentially Expressed Genes

A set of 7225 genes was previously identified aschanging the expression in the H. schachtii-inducedsyncytia (Szakasits et al., 2009). Thus, it was of interestto test the extent to which DMGs may contribute to theregulation of gene expression changes in the syncytium.To this end, we compared the lists of DMGs in thepromoters (2105 genes) and gene bodies (5691 genes)with the 7225 syncytium DEGs. Of the promoter DMGs511 genes (24.3%, x2 = 65.403,P= 4.113E-14; SupplementalData Set 7) and of the gene body DMGs 1465 genes(25.7%, x2 = 141.735, P = 1.597E-30; SupplementalData Set 8) were identified as overlapping with thesyncytium DEGs (Fig. 7A). Likewise, we comparedthe list of the differentially methylated TE-associatedgenes within 2-kb flanking regions (2624 genes) with

the syncytium DEGs. A significant overlap betweenthese two lists was also evident (20%, x2 = 198.356,P = 9.558E-43; Supplemental Data Set 9; Fig. 7A).When these gene lists were combined, a unique set of2,084 genes overlapped with the syncytium regulatedgenes (Fig. 7A; Supplemental Data Set 10).

Syncytium Differentially Methylated Genes Are ofFunctional Significance

To investigate whether syncytium genes overlappingwith DMGs are of functional significance, T-DNA in-sertional mutants for 10 of these DMGswere identifiedand used in nematode susceptibility assays. Interest-ingly, five mutant lines of body hypermethylated genesincluding, Glu synthase2 (AT2G41220, SALK_087050C),fatty acid reductase4 (AT3G44540, SALK_117623C),NRPD1a (AT1G63020, CS9920), beta-galactosidase3(AT4G36360, SALK_075361C), and starch branchingenzyme2.2 (AT5G03650, SALK_107255C) displayedenhanced susceptibility to H. schachtii (Fig. 7B). Similarly,five mutant lines of promoter hypomethylated genes,including a zinc finger family protein (AT1G28050,SALK_106851C), GRX480 (AT1G28480, SALK_031817C),OSB1 (AT1G47720, SALK_086929C), a Cys/His-rich C1domain family protein (AT5G54040, SALK_021867C),and a glycosyl hydrolase superfamily protein(AT3G60140, SALK_105913C) were assayed for nem-atode susceptibility. Three of these mutant lines dis-played increased or reduced nematode susceptibilitycompared with the wild-type Col-0 plants (Fig. 7C).These data suggest that differential methylation-mediatedgene expression changes in the syncytiummay contributeto the compatibility of the interaction between Arabi-dopsis and H. schachtii.

DISCUSSION

In this study, we show that H. schachtii inducessignificant changes in DNA methylation patterns,which involve both hypermethylation and hypo-methylation. This implies an intricate mechanism ofregulation that may involve the activity of both DNAmethyltransferases and DNA glycosylases. H. schachtii-induced methylome changes are characterized by in-creasing demethylation patterns in all sequence con-texts comparedwith hypermethylation. Thesemethylomechanges occurred predominantly in gene bodies andTEs and resemble those induced by the soybean cystnematode H. glycines in soybean (Rambani et al., 2015)and by biotic stress treatments in Arabidopsis (Dowenet al., 2012; Yu et al., 2013; Le et al., 2014; López Sánchezet al., 2016).

Remarkably, we found that 88% (1867 genes) of thepromoter DMGs (2105 genes)were hypomethylated. Ofthese, 31 genes were found to be significantly upregu-lated in our RNA-seq analysis. Demethylation of thesegene promoters may increase chromatin accessibility



Dow



http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1

and hence the recruitment of transcription factors andother components of the transcription machinery to theregulatory elements in the promoters, leading to geneactivation. Recently, it has been demonstrated that bind-ing sites for the tomato ripening inhibitor transcriptionfactors were commonly localized in hypomethylatedregions of the promoters of ripening-associated geneswhose expression was increased concurrently withgradual deceases in DNA methylation (Zhong et al.,2013). Also, we do not rule out the possibility that, insome cases, binding of transcription factors to specificpromoter regions may lead to active demethylation ofthese regions, as recently demonstrated in other sys-tems (Stadler et al., 2011; Pacis et al., 2015; Bogdanovi�cet al., 2016). In other words, DNA hypomethylation insome cases could be the consequence of gene up-regulation

and not the cause. In support of this possibility, ourdata also indicate that DNA methylation may beestablished following transcriptional changes but onlyin a small number of genes. Thus, transcription factorbinding may contribute to the observed widespreadpromoter demethylation but only to a small propor-tion since differential DNA methylation and gene ex-pression changes occur mostly concurrently under ourexperimental conditions.

Several recent studies indicated little association be-tween differential DNA methylation and gene expres-sion changes (Chodavarapu, et al., 2012; Secco et al.,2015; Kawakatsu et al., 2016; Hossain et al., 2017). Forexample, in soybean root hair, about 6% of the genesoverlapping with DMRs were differentially expressed(Hossain et al., 2017). Similarly, 3% of the DEGs

Figure 6. Association between siRNAs and DNA methylation. Distribution of siRNAs (20–25 nt) over hyper- and hypo-DMR-associated TEs within 2-kb flanking regions (A–F), gene prompters 2 kb upstream of the transcription start site (G–L), and genebodies (M and N) in CG, CHH, and CHG contexts at 5 and 10 d post H. schachtii infection.


Hewezi et al.

Dow



induced by phosphate starvation were associated withdifferential methylation (Secco et al., 2015). Consistentwith these findings, we found that approximately 5% ofthe DMR-overlapping genes associate with differentialgene expression, suggesting that DNAmethylation mayrequire additional epigenetic marks in order to impactgene expression. We also noted that demethylation ofgene promoters was not always accompanied with in-creased gene expression. In some cases, demethylationwas associated with gene down-regulation. Similar re-sults have been reported in a number of plant species,including soybean (Song et al., 2013; Rambani et al.,2015), maize (Gent et al., 2013), rice (Secco et al., 2015),and cotton (Song et al., 2015). This may be linked to theproperties of the DMRs including the presence of regu-latory elements, active chromatin marks, and proximityto differentially methylated TEs. For example, demeth-ylation may facilitate recruitment of transcriptionalrepressors to their binding sites, leading to gene down-regulation. Because of the mutual associations betweenhistone modifications and DNA methylation during

initiation and maintenance of repressed states of genes(Cedar and Bergman, 2009; To et al., 2011; Liu et al.,2012), it is conceivable that demethylation at specificpromoter regions may require active chromatin marksto activate gene expression. Nevertheless, association ofpromoter hypo-DMRs with repressive chromatin marksmay result in gene down-regulation. Another possibilityis that expression of promoter DMGs may be impactedby the activity of nearby TEs. Supporting this assump-tion is that about 50% (1047 genes) of the promoter DMGsare in fact locatedwithin 5 kb upstream or downstream ofdifferentially methylated TEs. The influence of methyla-tion status of TEs on the transcriptional activity of nearbygenes has been documented in a number of recent studies(Calarco et al., 2012; Secco et al., 2015; Yong-Villaloboset al., 2015; Zhang et al., 2015).

Our analysis provides compelling insights into theH. schachtii-induced widespread hypomethylation ofvarious TE families with influence observed for meth-ylation context and proximity to protein-coding genes.H. schachtii-induced hypomethylation was striking, as

Figure 7. One-fourth of the syncytium DEGs overlapped with DMGs. A, Overlaps between syncytium DEGs and DMGs. DMGsin gene body or gene promoters, in addition to those associated with differentially methylated TEs (MDTEs) within 2-kb flankingregions were compared with the 7225 syncytium DEGs and a set of 2084 genes were identified as syncytium DEGs overlappingwith the DMGs. B and C, T-DNA insertional mutants of syncytium genes overlapping with the DMGs altered plant susceptibilitytoH. schachtii. T-DNA insertional mutant lines of syncytium body hypermethylated genes (B) or promoter hypomethylated genes(C) were planted on modified Knop’s medium and assayed for H. schachtii susceptibility along with the wild-type Col-0 plants.Three weeks post-H. schachtii inoculation, the number of fourth-stage juveniles/females per root systemwas counted and used todetermine susceptibility levels comparedwith Col-0 plants. Data are shown asmeans of 20 replicates6 SE. Statistically significantdifferences between mutant lines and Col-0 plants were determined using unadjusted t tests. Asterisk indicates statistically sig-nificant differences at P value less than 0.05.



Dow



the large majority (86.5%) of TE-associated DMRswas demethylated. Also, we noted that CHH hypo-methylation was mostly associated with rolling circle(RC)/helitron TEs, whereas CG and CHG hypo-methylation preferentially associated with long ter-minal repeat/Gypsy type, consistent with the findingthat these TE families are targeted by demethylasesduring stress response (Le et al., 2014; Wibowo et al.,2016). Similarly, hypomethylation of microspores andsperm cells was found to occur in a context-specificfashion and associate with specific TE types (Calarcoet al., 2012). These results suggest that H. schachtii-induced hypomethylation of TEs may involve theactivity of various DNA demethylases that targetvarious types of TEs in a sequence context-specificmanner.

DNAmethylation of TEs, specifically at CHH sites, isguided by the 24-nt class siRNA through the RdDMpathway (Law and Jacobsen, 2010; Simon and Meyers,2011). Our results indicate that the 24-nt siRNAs con-tribute to the methylation of TEs specifically in theCHH context (Fig. 6, E and F). TEs associated with CHHhyper-DMRs showed higher abundance of 24-nt siRNAscomparedwith those associatedwith CHHhypo-DMRs.However, in the CG context the differences in 24-ntsiRNA abundance between hyper- and hypo-DMR-associated TEs was unsubstantial. This suggests thatCG-methylation of TEs is regulated through RdDM-dependent and -independent pathways duringH. schachtiiparasitism of Arabidopsis. Recently, SA-induced hypo-methylation of TEs was found to correlate with the bio-genesis of 21-nt siRNAs (Dowen et al., 2012).Weobservedonly a slight increase in 21-nt siRNAs in the TEs associ-ated with CHG hypo-DMRs at 5 dpi. Thus, the non-canonical RDR6-dependent RdDMpathway (Matzke andMosher, 2014) seems to play only a minor role in DNAmethylation changes during H. schachtii infection. In thiscontext, it may be important to mention that despite theimportance of siRNAs in mediating DNA methylation,siRNA abundance is not always associated with DNAmethylation, and other epigenetic marks such as histonemodifications could be involved in guiding DNA meth-ylation, especially in CG and CHG contexts (Lister et al.,2008; Li et al., 2014; Wibowo et al., 2016).

Recent experimental evidence has suggested thatpathogen-induced hypomethylationmay prime TEs andnearby genes through concomitant transcriptional acti-vation (Dowen et al., 2012; Yu et al., 2013). However, weobserved the opposite relationship, with hypo-DMR-associated TEs being associated with low expression ofnearby genes. Similarly, down-regulation of a number ofdefense-related genes was found to correlate withhypomethylation of flanking TEs (Le et al., 2014). Inaddition, a positive relationship between DNA methyl-ation of TEs and the expression of phosphate-starvation-induced genes was recently reported (Secco et al., 2015).However, it remains unknown how hypomethylation ofTEs can negatively impact the expression of flankinggenes. One assumption is that methylation may preventTE-originated cryptic transcripts from interfering with

the expression of neighboring genes (Barkan andMartienssen, 1991; Le et al., 2014). Hence, loss of DNAmethylation may activate the generation of aberranttranscripts that would impede the transcriptional ac-tivity of the neighboring genes, leading to gene down-regulation. Alternatively, hypomethylation of near-geneTEs may simply reflect transcriptional repression of TEsand the resultant dsRNA, generating 24-nt siRNAs thatguide DNA methylation (Hsieh et al., 2009; Bauer andFischer, 2011; Le et al., 2014). Whatever the underlyingmechanisms, our data suggest that hypomethylation ofTEs located nearby low-expressing genes may facilitatethe transcription of these genes once the syncytiumformation stage was completed. We noted a trend ofincreased expression of the large majority of thesegenes at 10 dpi compared to 5 dpi, specifically thosegenes located within 1 kb of the closest hypomethy-lated TEs. This finding sheds lights on a possible roleof hypomethylation of TEs located nearby nematode-responsive genes in shifting gene down-regulation,occurring during early stages of infection, into basalexpression level at later stages of infection.

The extent to which differential DNA methylationcontributes to gene expression changes in theH. schachtii-induced syncytium was determined by comparinglists of genes overlapping with or located near theDMRs with the 7225 syncytium DEGs previouslyreported (Szakasits et al., 2009). A set of 2084 geneswas identified, suggesting that levels and patterns ofDNA methylation may contribute to gene expressionchanges of more than one-fourth of syncytium DEGs.However, only 148 of these genes were identifiedas differentially expressed in our RNA-seq analysis(Supplemental Data Set 11). This small overlap can beexplained by the fact that the large majority of DEGsin the syncytia, a small portion of the root system,cannot be detected using mRNA isolated from thewhole roots. Consistent with the fact that syncytiumis a metabolically hyperactive structure, GO termscorresponding to primary metabolic pathways arethe most significantly enriched terms among these148 DMGs. Our results also provide interesting insightsinto a regulatory role of differential DNA methylation incontrolling phytohormone signaling in the syncytium.For example, AUXIN RESPONSE FACTOR9, the auxinefflux carrier family protein PIN-LIKES5, and theethylene response factor AP2/ERF59 were amongthese 148 DMGs. In addition, the cross talk betweenethylene signaling and auxin biosynthesis in the syncy-tium seems to be under methylation control. The alphasubunit of anthranilate synthase1-encoding gene,which isinvolved in auxin biosynthesis, was among syncytiumhypomethylated genes. Anthranilate synthase1 is posi-tively regulated by ethylene and constitutes a molecularlink between ethylene signaling and auxin biosynthesisduring root development (Mao et al., 2016).

Consistent with the recent findings that DNA meth-ylation contributes to the regulation of defense geneexpression (Dowen et al., 2012; Yu et al., 2013; Rambaniet al., 2015; López Sánchez et al., 2016), a set of syncytium


Hewezi et al.

Dow




genes overlapping with DMGs was found to functionin biotic stress responses. These genes included, forexample, two genes encoding pathogenesis-relatedproteins, lipoxygenase1 and glutaredoxin480, which func-tions as a negative regulator of the defensin gene PDF1.2(Ndamukong et al., 2007). This gene set also included theRECEPTOR-LIKE CYTOPLASMIC KINASE1, which isinvolved in pattern-triggered immunity (Sreekanta et al.,2015; Kong et al., 2016). Differential methylation mayalso contribute to lowering the level of myo-inositol inthe syncytium through down-regulation of myo-inositol-1-phosphate synthase2 and up-regulation of myo-inositoloxygenase2. The importance of myo-inositol for syncy-tium formation and function has been previously shown(Siddique et al., 2009; Siddique et al., 2014).Our data also point to a possible functional role of

gene bodymethylation in regulating gene expression inthe syncytium and therefore the disease phenotype.Several knockout mutants of body-methylated genesshowed increased susceptibility to H. schachtii infection(Fig. 7, B andC), suggesting that gene bodymethylationis of functional significance. Our results are in agreementwith the finding that body-methylated genes were morelikely to exhibit phenotypic consequences when mutatedcomparedwith nonmethylated genes (Takuno andGaut,2012). One of the syncytium body-methylated genes isNRPD1a, which encodes the largest subunit of RNApolymerase IV and is required for the biogenesis of 24-ntsiRNAs (Haag and Pikaard, 2011; Matzke and Mosher,2014). The increased susceptibility of nrpd1a-4 plants toH. schachtii again suggests that inactivation of siRNAs-guidedDNAmethylation pathwaymay contribute to thecompatibility of the interaction between H. schachtii andArabidopsis. This suggestion is consistent with ourfinding of widespread of hypomethylation in theH. schachtii-infected roots.In conclusion, we present detailed analyses of whole-

genome DNA methylation patterns coupled withmRNA and small RNA transcriptomes of Arabidopsisroots during the compatible interaction with the beetcyst nematode H. schachtii. Our analyses revealed thatH. schachtii induces extensive and dynamic changes inDNA methylation patterns that impact the transcrip-tional activity of genes involved in fundamental bio-logical processes required for nematode parasitism.Together, the results reported here provide strong evi-dence for potential essential roles of differential DNAmethylation in mediating Arabidopsis response to H.schachtii infection by regulating the expression of asignificant number of syncytial genes. A question thatmay arise in this context is how plant-parasitic nem-atodes trigger such changes in the epigenome of hostplants. One possibility is that nematode effector pro-teins may target and manipulate the activity of keycomponents of epigenetic mechanisms, leading toepigenome changes during parasitism. Identifyingnematode effectors that alter the epigenome of hostplants will be valuable for further understating themechanism of epigenetic control of nematode para-sitism of host plants.

MATERIALS AND METHODS

Nematode Inoculation, Tissue Collection, and MethylC-seq Library Construction

Arabidopsis (Arabidopsis thaliana) seeds (ecotype Columbia-0) were surface-sterilized and planted onmodifiedKnop’smedium (Sijmons et al., 1991) at 24°Cunder a photoperiod of 16 h of light and 8 h of dark. Ten-day-old seedlings wereinoculated with about 200 surface-sterilized second-stage juveniles of the beetcyst nematode Heterodera schachtii per seedling. Control and inoculated seed-lings were maintained under the same growth conditions. At 5 and 10 d post-inoculation, root tissues were collected from both infected and noninfectedcontrol plants. For each of these four treatments, three biological samples, eachfrom an independent experiment, were collected for a total of 12 samples. Ge-nomic DNA was extracted and used to prepare methylC-seq libraries as pre-viously described (Rambani et al., 2015). Paired-end sequencing of 100-basepairreads was performed using Illumina HiSEquation 2500 system.

Identification of DMRs and Mapping to AnnotatedGenomic Features

High-quality MethylC-seq reads were mapped to the Arabidopsis referencegenome (TAIR10) usingBismark (Krueger andAndrews, 2011), andmappingfileswere used to identify differentially methylated cytosines and regions using themethylKit package (Akalin et al., 2012). Cytosines were called if covered by aminimum of 10 reads. For each treatment, three methylation call files corre-sponding to the threemethylation sequence contexts were generated. Hyper- andhypo-DMRs inCG, CHG, andCHHcontextswere identified using a 200-basepairnonoverlapping windowwith a minimummethylation difference of 25% using afalse discovery rate cut-off of 0.01 as previously described (Rambani et al., 2015).DMRs were allocated to various annotated features of the Arabidopsis genomeincluding TEs, promoter regions (1 kb upstream of transcription start site), exons,introns, andUTRs, using the Bioconductor packages rtracklayers (Lawrence et al.,2009) and GenomicRanges (Lawrence et al., 2013).

RNA-seq Library Construction and Sequencing

mRNAwas isolated from20mgof ground root tissues using amagneticmRNAisolationkit (NewEnglandBiolabs)according to themanufacturer’s instruction.TheRNA-seq libraries were generated from 250 ng mRNA using the NEBnext mRNAlibrary prep master mix (New England Biolabs) according to the manufacturer’sinstruction. Single-end sequencing of 100-basepairp reads was performed usingIllumina HiSEquation 2500 platform. The quality of sequencing read was assessedin FastQCversion 0.11.4 and adapter trimmingwas performedusing Trimmomaticversion 0.35 (Bolger et al., 2014). High-quality, trimmed reads were aligned to theArabidopsis reference genome (TAIR10) using the splice-aware software packageSTAR version 2.5.1 (Dobin et al., 2013). Uniquely mapped reads assigned to eachgene were counted with HTSeq (Anders et al., 2015). DEGs between infected andnoninfected samples were determined using the edgeR package (Robinson et al.,2010), with a FDR less than 0.05. DEGs were assigned to GO terms using theAgriGO database (Du et al., 2010), and statistical significance of GO term enrich-mentwas determined using Fisher’s exact test and Bonferronimultitest adjustmentwith a FDR cut-off of 0.05.

Small RNA-seq Library Construction and Sequencing

Total RNA was isolated from 200 mg of ground root tissues using TRIzol(Invitrogen). Then, 1 mg of total RNA was used to prepare small RNA librariesaccording to Illumina TruSeq Small RNA library preparation protocol (Illumina).After purification and quality control analyses, small RNA-seq libraries were pooledformultiplexed sequencingusing the IlluminaHiSEquation 2500 Sequencing Systemin Rapid Read mode. Adapters were trimmed from raw reads using Trimmomaticversion 0.35 (Bolger et al., 2014). Quality assessment of raw and trimmed reads wasperformed using FastQC version 0.11.4 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). The adapter trimmed reads were aligned to the Arabidopsisreference genome (TAIR10) with bowtie2 version 2.2.8 (Langmead and Salzberg,2012). Alignmentfileswere sorted and indexedusing samtools version 1.3.1 (Li et al.,2009). Known tRNAs, miRNAs, ncRNAs, rRNAs, snoRNAs, and snRNAs wereremoved based on their alignment to the Arabidopsis reference genome usingHTSeq (Anders et al., 2015). The remaining siRNAswere further processed to assesstheir positions relative to DMRs overlapping with protein-coding genes and TEs.



Dow



http://www.bioinformatics.babraham.ac.uk/projects/fastqc/http://www.bioinformatics.babraham.ac.uk/projects/fastqc/

Nematode Infection Assay

Seeds of Arabidopsis wild-type (Col-0) and T-DNA insertional mutants of10 DMGs, including AT2G41220 (SALK_087050C), AT3G44540 (SALK_117623C),AT1G63020 (CS9920), AT4G36360 (SALK_075361C), AT5G03650 (SALK_107255C),AT1G28050 (SALK_106851C), AT1G28480 (SALK_031817C), AT1G47720(SALK_086929C), AT5G54040 (SALK_021867C), and T3G60140 (SALK_105913C)were planted in 12-well tissue culture plates (Biosciences) containing modifiedKnop’s medium using randomized complete block design with 20 replicates.Plates were incubated at 24°C under a photoperiod of 16 h of light and 8 h of darkin a plant growth chamber for 10 d before being inoculated with about250 surface-sterilized second-stage juvenile nematodes of H. schachtii per plant.Three weeks postinoculation, the number of fourth-stage juveniles/females perroot systemwas scored andused to determine susceptibility levels in eachmutantline compared to wild-type Col-0 plants using a modified t test on statisticalanalysis system (SAS) with a statistically significant P value cut-off of 0.05.

Accession Numbers

All sequencedatareported inthispaperhavebeensubmittedto the to theNCBIBioSample database under the following accession numbers: SAMN06017508 toSAMN06017511 for methylC-seq reads, SAMN06017512 to SAMN06017515 forsmall RNA reads, and SAMN06017516 to SAMN06017519 for mRNA reads.

Supplemental Data

The following supplemental materials are available.

Supplemental Figure S1. Enrichment analysis of GO terms associated withthe molecular functions of 262 genes overlapping between DEGs and DMGs.

Supplemental Figure S2. Size distribution of siRNAs obtained from con-trol and H. schachtii-infected root samples.

Supplemental Table S1. Description of methylC-seq libraries.

Supplemental Table S2. Description of RNA-seq libraries.

Supplemental Table S3. Description of small RNA-seq libraries.

Supplemental Data Set 1. DMRs overlapping with protein-coding genes.

Supplemental Data Set 2. DMRs overlapping with TEs.

Supplemental Data Set 3. List of 1328 genes identified as differentiallyexpressed at 5 d post-H. schachtii infection.

Supplemental Data Set 4. List of 472 genes identified as differentiallyexpressed at 10 d post-H. schachtii infection.

Supplemental Data Set 5. List of 262 genes overlapping between DMGsand DEGs.

Supplemental Data Set 6. List of 136 DEGs located within 5 kb upstreamor downstream of the nearest differentially methylated TEs.

Supplemental Data Set 7. List of 511 promoter DMGs overlapping withsyncytium DEGs.

Supplemental Data Set 8. List of 1465 body DMGs genes overlapping withsyncytium DEGs.

Supplemental Data Set 9. List of 526 differentially methylated TE-associatedgenes overlapping with syncytium DEGs.

Supplemental Data Set 10. List of 2084 syncytium genes overlapping withDMGs.

Supplemental Data Set 11. List of 148 genes common between DMGs,DEGs, and syncytium DEGs.

ACKNOWLEDGMENTS

We would like to thank Dr. Tessa Burch-Smith for insightful comments andsuggestions, and Sujata Agarwal at the UTIA Genomics Hub Lab for technicalassistance.

Received December 22, 2016; accepted March 12, 2017; published March 15,2017.

LITERATURE CITED

Akalin A, Kormaksson M, Li S, Garrett-Bakelman FE, Figueroa ME,Melnick A, Mason CE (2012) methylKit: A comprehensive R packagefor the analysis of genome-wide DNA methylation profiles. GenomeBiol 13: R87

Anders S, Pyl PT, Huber W (2015) HTSeq—a Python framework to workwith high-throughput sequencing data. Bioinformatics 31: 166–169

Barkan A, Martienssen RA (1991) Inactivation of maize transposon Musuppresses a mutant phenotype by activating an outward-reading pro-moter near the end of Mu1. Proc Natl Acad Sci USA 88: 3502–3506

Bauer MJ, Fischer RL (2011) Genome demethylation and imprinting in theendosperm. Curr Opin Plant Biol 14: 162–167

Becker C, Hagmann J, Müller J, Koenig D, Stegle O, Borgwardt K, WeigelD (2011) Spontaneous epigenetic variation in the Arabidopsis thalianamethylome. Nature 480: 245–249

Bogdanovi�c O, Smits AH, de la Calle Mustienes E, Tena JJ, Ford E, WilliamsR, Senanayake U, Schultz MD, Hontelez S, van Kruijsbergen I, et al (2016)Active DNA demethylation at enhancers during the vertebrate phylotypicperiod. Nat Genet 48: 417–426

Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: A flexible trimmer forIllumina sequence data. Bioinformatics 30: 2114–2120

Calarco JP, Borges F, Donoghue MT, Van Ex F, Jullien PE, Lopes T,Gardner R, Berger F, Feijó JA, Becker JD, et al (2012) Reprogrammingof DNA methylation in pollen guides epigenetic inheritance via smallRNA. Cell 151: 194–205

Cao X, Aufsatz W, Zilberman D, Mette MF, Huang MS, Matzke M, JacobsenSE (2003) Role of the DRM and CMT3 methyltransferases in RNA-directedDNA methylation. Curr Biol 13: 2212–2217

Cao X, Jacobsen SE (2002) Locus-specific control of asymmetric andCpNpG methylation by the DRM and CMT3 methyltransferase genes.Proc Natl Acad Sci USA 99(Suppl 4): 16491–16498

Cedar H, Bergman Y (2009) Linking DNA methylation and histone modi-fication: Patterns and paradigms. Nat Rev Genet 10: 295–304

Chodavarapu RK, Feng S, Ding B, Simon SA, Lopez D, Jia Y, Wang GL,Meyers BC, Jacobsen SE, Pellegrini M (2012) Transcriptome andmethylome interactions in rice hybrids. Proc Natl Acad Sci USA 109:12040–12045

Cokus SJ, Feng S, Zhang X, Chen Z, Merriman B, Haudenschild CD, PradhanS, Nelson SF, Pellegrini M, Jacobsen SE (2008) Shotgun bisulphite se-quencing of the Arabidopsis genome reveals DNA methylation patterning.Nature 452: 215–219

Deleris A, Halter T, Navarro L (2016) DNA methylation and demethylationin plant immunity. Annu Rev Phytopathol 54: 579–603

Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P,Chaisson M, Gingeras TR (2013) STAR: Ultrafast universal RNA-seqaligner. Bioinformatics 29: 15–21

Dowen RH, Pelizzola M, Schmitz RJ, Lister R, Dowen JM, Nery JR,Dixon JE, Ecker JR (2012) Widespread dynamic DNA methylation inresponse to biotic stress. Proc Natl Acad Sci USA 109: E2183–E2191

Du Z, Zhou X, Ling Y, Zhang Z, Su Z (2010) agriGO: A GO analysis toolkitfor the agricultural community. Nucleic Acids Res 38: W64–W70

Gent JI, Ellis NA, Guo L, Harkess AE, Yao Y, Zhang X, Dawe RK (2013)CHH islands: De novo DNA methylation in near-gene chromatin reg-ulation in maize. Genome Res 23: 628–637

Haag JR, Pikaard CS (2011) Multisubunit RNA polymerases IV and V:Purveyors of non-coding RNA for plant gene silencing. Nat Rev MolCell Biol 12: 483–492

He G, Elling AA, Deng XW (2011) The epigenome and plant development.Annu Rev Plant Biol 62: 411–435

Henderson IR, Jacobsen SE (2007) Epigenetic inheritance in plants. Nature447: 418–424

Hewezi T (2015) Cellular signaling pathways and posttranslational modi-fications mediated by nematode effector proteins. Plant Physiol 169:1018–1026

Hewezi T, Baum TJ (2013) Manipulation of plant cells by cyst and root-knot nematode effectors. Mol Plant Microbe Interact 26: 9–16

Hewezi T, Baum TJ (2015) Gene silencing in nematode feeding sites. In CEscobar, C Fenoll, eds, Plant-Nematode Interactions: A View on Compat-ible Interrelationships. Advances in Botanical Research, Vol. 73. Elsevier,Oxford, UK, pp 221–239

Hirsch CD, Springer NM (2017) Transposable element influences on geneexpression in plants. Biochim Biophys Acta 1860: 157–165


Hewezi et al.

Dow



http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1http://www.plantphysiol.org/cgi/content/full/pp.16.01948/DC1

Hollister JD, Gaut BS (2009) Epigenetic silencing of transposable elements:a trade-off between reduced transposition and deleterious effects onneighboring gene expression. Genome Res 19: 1419–1428

Hollister JD, Smith LM, Guo YL, Ott F, Weigel D, Gaut BS (2011)Transposable elements and small RNAs contribute to gene expressiondivergence between Arabidopsis thaliana and Arabidopsis lyrata. Proc NatlAcad Sci USA 108: 2322–2327

Hossain MS, Kawakatsu T, Kim KD, Zhang N, Nguyen CT, Khan SM,Batek JM, Joshi T, Schmutz J, Grimwood J, et al (2017) Divergent cy-tosine DNA methylation patterns in single-cell, soybean root hairs. NewPhytol 10.1111/nph.14421

Hsieh TF, Ibarra CA, Silva P, Zemach A, Eshed-Williams L, Fischer RL,Zilberman D (2009) Genome-wide demethylation of Arabidopsis en-dosperm. Science 324: 1451–1454

Ito H, Gaubert H, Bucher E, Mirouze M, Vaillant I, Paszkowski J (2011)An siRNA pathway prevents transgenerational retrotransposition inplants subjected to stress. Nature 472: 115–119

Kawakatsu T, Stuart T, Valdes M, Breakfield N, Schmitz RJ, Nery JR,Urich MA, Han X, Lister R, Benfey PN, et al (2016) Unique cell-type-specific patterns of DNA methylation in the root meristem. Nat Plants 2:16058

Kim MY, Zilberman D (2014) DNA methylation as a system of plant ge-nomic immunity. Trends Plant Sci 19: 320–326

Kong Q, Sun T, Qu N, Ma J, Li M, Cheng YT, Zhang Q, Wu D, Zhang Z,Zhang Y (2016) Two redundant receptor-like cytoplasmic kinases func-tion downstream of pattern recognition receptors to regulate activation ofSA biosynthesis. Plant Physiol 171: 1344–1354

Krueger F, Andrews SR (2011) Bismark: A flexible aligner and methylationcaller for Bisulfite-Seq applications. Bioinformatics 27: 1571–1572

Kyndt T, Vieira P, Gheysen G, de Almeida-Engler J (2013) Nematodefeeding sites: Unique organs in plant roots. Planta 238: 807–818

Langmead B, Salzberg SL (2012) Fast gapped-read alignment with Bowtie2. Nat Methods 9: 357–359

Law JA, Jacobsen SE (2010) Establishing, maintaining and modifying DNAmethylation patterns in plants and animals. Nat Rev Genet 11: 204–220

Lawrence M, Gentleman R, Carey V (2009) rtracklayer: An R package forinterfacing with genome browsers. Bioinformatics 25: 1841–1842

Lawrence M, Huber W, Pagès H, Aboyoun P, Carlson M, Gentleman R,Morgan MT, Carey VJ (2013) Software for computing and annotatinggenomic ranges. PLOS Comput Biol 9: e1003118

Le T-N, Schumann U, Smith NA, Tiwari S, Au PC, Zhu Q-H, Taylor JM,Kazan K, Llewellyn DJ, Zhang R, et al (2014) DNA demethylases targetpromoter transposable elements to positively regulate stress responsivegenes in Arabidopsis. Genome Biol 15: 458

Li Q, Eichten SR, Hermanson PJ, Springer NM (2014) Inheritance patternsand stability of DNA methylation variation in maize near-isogenic lines.Genetics 196: 667–676

Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G,Abecasis G, Durbin R; 1000 Genome Project Data Processing Subgroup(2009) The sequence alignment/map format and SAMtools. Bioinformatics25: 2078–2079

Lister R, O’Malley RC, Tonti-Filippini J, Gregory BD, Berry CC, MillarAH, Ecker JR (2008) Highly integrated single-base resolution maps ofthe epigenome in Arabidopsis. Cell 133: 523–536

Liu X, Yu CW, Duan J, Luo M, Wang K, Tian G, Cui Y, Wu K (2012) HDA6directly interacts with DNA methyltransferase MET1 and maintainstransposable element silencing in Arabidopsis. Plant Physiol 158: 119–129

López Sánchez A, Stassen JHM, Furci L, Smith LM, Ton J (2016) The roleof DNA (de)methylation in immune responsiveness of Arabidopsis.Plant J 88: 361–374 10.1111/nph.14421

Luco RF, Pan Q, Tominaga K, Blencowe BJ, Pereira-Smith OM, Misteli T(2010) Regulation of alternative splicing by histone modifications. Sci-ence 327: 996–1000

Mao J-L, Miao Z-Q, Wang Z, Yu L-H, Cai X-T, Xiang C-B (2016) Arabi-dopsis ERF1 mediates cross-talk between ethylene and auxin biosynthesisduring primary root elongation by regulating ASA1 expression. PLoSGenet 12: e1005760

Matzke M, Kanno T, Daxinger L, Huettel B, Matzke AJM (2009) RNA-mediated chromatin-based silencing in plants. Curr Opin Cell Biol 21:367–376

Matzke MA, Mosher RA (2014) RNA-directed DNA methylation: An epi-genetic pathway of increasing complexity. Nat Rev Genet 15: 394–408

Maunakea AK, Nagarajan RP, Bilenky M, Ballinger TJ, D’Souza C, FouseSD, Johnson BE, Hong C, Nielsen C, Zhao Y, et al (2010) Conservedrole of intragenic DNA methylation in regulating alternative promoters.Nature 466: 253–257

Ndamukong I, Abdallat AA, Thurow C, Fode B, Zander M, Weigel R,Gatz C (2007) SA-inducible Arabidopsis glutaredoxin interacts withTGA factors and suppresses JA-responsive PDF1.2 transcription. Plant J50: 128–139

Pacis A, Tailleux L, Morin AM, Lambourne J, MacIsaac JL, Yotova V,Dumaine A, Danckaert A, Luca F, Grenier J-C, et al (2015) Bacterialinfection remodels the DNA methylation landscape of human dendriticcells. Genome Res 25: 1801–1811

Rambani A, Rice JH, Liu J, Lane T, Ranjan P, Mazarei M, Pantalone V,Stewart CN, Jr., Staton M, Hewezi T (2015) The methylome of soybeanroots during the compatible interaction with the soybean cyst nematode.Plant Physiol 168: 1364–1377

Regulski M, Lu Z, Kendall J, Donoghue MTA, Reinders J, Llaca V,Deschamps S, Smith A, Levy D, McCombie WR, et al (2013) Themaize methylome influences mRNA splice sites and reveals wide-spread paramutation-like switches guided by small RNA. Genome Res23: 1651–1662

Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: A Bioconductorpackage for differential expression analysis of digital gene expressiondata. Bioinformatics 26: 139–140

Sahu PP, Pandey G, Sharma N, Puranik S, Muthamilarasan M, Prasad M(2013) Epigenetic mechanisms of plant stress responses and adaptation.Plant Cell Rep 32: 1151–1159

Schmitz RJ, Schultz MD, Lewsey MG, O’Malley RC, Urich MA, LibigerO, Schork NJ, Ecker JR (2011) Transgenerational epigenetic instability isa source of novel methylation variants. Science 334: 369–373

Secco D, Wang C, Shou H, Schultz MD, Chiarenza S, Nussaume L, EckerJR, Whelan J, Lister R (2015) Stress induced gene expression drivestransient DNA methylation changes at adjacent repetitive elements.eLife 4: e09343

Siddique S, Endres S, Atkins JM, Szakasits D, Wieczorek K, Hofmann J,Blaukopf C, Urwin PE, Tenhaken R, Grundler FMW, et al (2009) Myo-inositol oxygenase genes are involved in the development of syncytiainduced by Heterodera schachtii in Arabidopsis roots. New Phytol 184:457–472

Siddique S, Endres S, Sobczak M, Radakovic ZS, Fragner L, GrundlerFMW, Weckwerth W, Tenhaken R, Bohlmann H (2014) Myo-inositoloxygenase is important for the removal of excess myo-inositol fromsyncytia induced by Heterodera schachtii in Arabidopsis roots. NewPhytol 201: 476–485

Sijmons PC, Grundler FMW, von Mende N, Burrows PR, Wyss U (1991)Arabidopsis thaliana as a new model host for plant-parasitic nematodes.Plant J 1: 245–254

Simon SA, Meyers BC (2011) Small RNA-mediated epigenetic modifica-tions in plants. Curr Opin Plant Biol 14: 148–155

Slotkin RK, Martienssen R (2007) Transposable elements and the epige-netic regulation of the genome. Nat Rev Genet 8: 272–285

Song Q, Guan X, Chen ZJ (2015) Dynamic roles for small RNAs and DNAmethylation during ovule and fiber development in allotetraploid cot-ton. PLoS Genet 11: e1005724

Song Q-X, Lu X, Li Q-T, Chen H, Hu X-Y, Ma B, Zhang W-K, Chen S-Y,Zhang J-S (2013) Genome-wide analysis of DNA methylation in soy-bean. Mol Plant 6: 1961–1974

Sreekanta S, Bethke G, Hatsugai N, Tsuda K, Thao A, Wang L, Katagiri F,Glazebrook J (2015) The receptor-like cytoplasmic kinase PCRK1 con-tributes to pattern-triggered immunity against Pseudomonas syringae inArabidopsis thaliana. New Phytol 207: 78–90

Stadler MB, Murr R, Burger L, Ivanek R, Lienert F, Schöler A, vanNimwegen E, Wirbelauer C, Oakeley EJ, Gaidatzis D, et al (2011)DNA-binding factors shape the mouse methylome at distal regulatoryregions. Nature 480: 490–495

Szakasits D, Heinen P, Wieczorek K, Hofmann J, Wagner F, Kreil DP,Sykacek P, Grundler FMW, Bohlmann H (2009) The transcriptome ofsyncytia induced by the cyst nematode Heterodera schachtii in Arabi-dopsis roots. Plant J 57: 771–784

Takuno S, Gaut BS (2012) Body-methylated genes in Arabidopsis thalianaare functionally important and evolve slowly. Mol Biol Evol 29: 219–227

To TK, Kim J-M, Matsui A, Kurihara Y, Morosawa T, Ishida J, Tanaka M,Endo T, Kakutani T, Toyoda T, et al (2011) Arabidopsis HDA6



Dow



regulates locus-directed heterochromatin silencing in cooperation withMET1. PLoS Genet 7: e1002055

Wang X, Weigel D, Smith LM (2013) Transposon variants and their effectson gene expression in Arabidopsis. PLoS Genet 9: e1003255

Wibowo A, Becker C, Marconi G, Durr J, Price J, Hagmann J, PapareddyR, Putra H, Kageyama J, Becker J, et al (2016) Hyperosmotic stressmemory in Arabidopsis is mediated by distinct epigenetically labile sitesin the genome and is restricted in the male germline by DNA glycosylaseactivity. eLife 5: e13546

Yong-Villalobos L, González-Morales SI, Wrobel K, Gutiérrez-Alanis D,Cervantes-Peréz SA, Hayano-Kanashiro C, Oropeza-Aburto A, Cruz-Ramírez A, Martínez O, Herrera-Estrella L (2015) Methylome analysisreveals an important role for epigenetic changes in the regulation of theArabidopsis response to phosphate starvation. Proc Natl Acad Sci USA112: E7293–E7302

Yu A, Lepère G, Jay F, Wang J, Bapaume L, Wang Y, Abraham AL,Penterman J, Fischer RL, Voinnet O, et al (2013) Dynamics and

biological relevance of DNA demethylation in Arabidopsis antibacterialdefense. Proc Natl Acad Sci USA 110: 2389–2394

Zhang J, Liu Y, Xia E-H, Yao Q-Y, Liu X-D, Gao L-Z (2015) Autotetraploidrice methylome analysis reveals methylation variation of transposableelements and their effects on gene expression. Proc Natl Acad Sci USA112: E7022–E7029

Zhang H, Zhu JK (2012) Active DNA demethylation in plants and animals.Cold Spring Harb Symp Quant Biol 77: 161–173

Zhong S, Fei Z, Chen Y-R, Zheng Y, Huang M, Vrebalov J, McQuinn R,Gapper N, Liu B, Xiang J, et al (2013) Single-base resolution methyl-omes of tomato fruit development reveal epigenome modifications as-sociated with ripening. Nat Biotechnol 31: 154–159

Zhu J-K (2009) Active DNA demethylation mediated by DNA glycosylases.Annu Rev Genet 43: 143–166

Zilberman D, Gehring M, Tran RK, Ballinger T, Henikoff S (2007) Genome-wide analysis of Arabidopsis thaliana DNA methylation uncovers an interde-pendence between methylation and transcription. Nat Genet 39: 61–69


Hewezi et al.

Dow



Cyst Nematode Parasitism Induces Dynamic...(CH3) to the C5 position of the cytosine to generate...

Documents

Transcript of Cyst Nematode Parasitism Induces Dynamic...(CH3) to the C5 position of the cytosine to generate...