Defining the Functional Network of Epigenetic Regulators in Arabidopsis thaliana

Molecular Plant

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Volume 2

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Number 4

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Pages 661–674

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July 2009

RESEARCH ARTICLE

Defining the Functional Network of Epigenetic Regulators in Arabidopsis thaliana Chongyuan Luoa,b,2, Brittany G. Durgina,2, Naohide Watanabea,2 and Eric Lama,b,1 a Biotechnology Center for Agriculture and the Environment, Rutgers The State University of New Jersey, 59 Dudley Road, New Brunswick, NJ 08901, USA b Department of Plant Biology and Pathology, Rutgers The State University of New Jersey, 59 Dudley Road, New Brunswick, NJ 08901, USA

ABSTRACT Development of ChIP-chip and ChIP-seq technologies has allowed genome-wide high-resolution profiling of chromatin-associated marks and binding sites for epigenetic regulators. However, signals for directing epigenetic modifiers to their target sites are not understood. In this paper, we tested the hypothesis that genome location can affect the involvement of epigenetic regulators using Chromatin Charting (CC) Lines, which have an identical transgene construct inserted at different locations in the Arabidopsis genome. Four CC lines that showed evidence for epigenetic silencing of the luciferase reporter gene were transformed with RNAi vectors individually targeting epigenetic regulators LHP1, MOM1, CMT3, DRD1, DRM2, SUVH2, CLF, and HD1. Involvement of a particular epigenetic regulator in silencing the transgene locus in a CC line was determined by significant alterations in luciferase expression after suppression of the regulator’s expression. Our results suggest that the targeting of epigenetic regulators can be influenced by genome location as well as sequence context. In addition, the relative importance of an epigenetic regulator can be influenced by tissue identity. We also report a novel approach to predict interactions between epigenetic regulators through clustering analysis of the regulators using alterations in gene expression of putative downstream targets, including endogenous loci and transgenes, in epigenetic mutants or RNAi lines. Our data support the existence of a complex and dynamic network of epigenetic regulators that serves to coordinate and control global gene expression in higher plants. Key words: Cell differentiation; specialization; chromatin structure and remodeling; chromosome organization; epigenetics; gene silencing; Arabidopsis.

INTRODUCTION Epigenetic regulation is indispensable for plant development, reproduction, and response to environmental stimuli (Pien and Grossniklaus, 2006; Sung and Amasino, 2004; Kinoshita et al., 2004). Thousands of genes that control various biological processes have been identified as possible targets of epigenetic regulation (Schubert et al., 2006; Zhang et al., 2007b; Turck et al., 2007). In contrast to transcription factors that recognize promoters or enhancers via sequence-specific interactions with cis-elements, the targeting of epigenetic regulators (epiregulators) involves complex interactions between DNA, RNA, histones, and regulatory proteins (Lindroth et al., 2004; Zhang et al., 2007b; Turck et al., 2007; Chan et al., 2005). For example, in-vitro binding assays showed that Arabidopsis CHROMOMETHYLASE 3 (CMT3) can interact with histone H3 N-terminal tails that are methylated at both the K9 and K27 positions (Lindroth et al., 2004). In addition, the Arabidopsis DOMAIN REARRANGED METHYLTRANSFERASE 2 (DRM2) protein was shown to be guided by small RNAs to different locations in the genome to catalyze de-novo cytosine methylation at CHG (H = A,T,C,G) sites (Cao and Jacobson, 2002; Cao et al., 2003).

Two complementary high-throughput approaches have been used to study the targeting of epi-regulators in vivo. First, physical binding sites of a particular regulator can be identified via chromatin immunoprecipitation (ChIP) or DNA adenine methyltransferase identification (DamID) followed by hybridization with whole-genome tiling microarrays (ChIPchip). Alternatively, enriched DNA from ChIP can be directly sequenced by high-throughput sequencing technologies (ChIP-seq) (Zhang et al., 2007b; Turck et al., 2007). Using this type of approach, genome-wide DNA methylation and histone modifications can be determined at single-nucleotide resolution, while small RNAs (sRNAs) can be identified by Massively

1 To whom correspondence should be addressed. E-mail [email protected]. edu, fax +1-732-932-6535, tel. +1-732-932-8165. 2

These authors contributed equally to this work.

ª The Author 2009. Published by the Molecular Plant Shanghai Editorial Office in association with Oxford University Press on behalf of CSPP and IPPE, SIBS, CAS. doi: 10.1093/mp/ssp017, Advance Access publication 3 April 2009 Received 7 December 2008; accepted 24 February 2009

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Parallel Signature Sequencing (MPSS) in order to reveal their correlated genomic regions (Zhang et al., 2006; Zilberman et al., 2007; Lu et al., 2005; Zhang et al., 2007a; Bernatavichute et al., 2008; Cokus et al., 2008; Lister et al., 2008). Second, identification and characterization of mis-expressed genes in epigenetic regulator mutants, such as met1 and the drm1/drm2/ cmt3 triple mutant, have provided insights into which parts of the genome depend on the particular epigenetic factor for maintenance of normal expression behavior (Zhang et al., 2006; Lister et al., 2008). Using these high-throughput methods, some important questions regarding the targeting of epi-regulators have been readily answered. For example, it has been shown that Arabidopsis LIKE HETEROCHROMATIN PROTEIN 1 (LHP1) co-localizes with H3K27me3 in vivo (Zhang et al., 2007b; Turck et al., 2007). In another study, ChIP-chip analysis of Arabidopsis H3K9me2 revealed that H3K9me2 significantly associates with DNA methylation at CHG (H = A,T,C,G) sites (Bernatavichute et al., 2008). However, the targeting mechanisms for many epigenetic marks (e.g. DNA methylation and histone modifications) have yet to be elucidated. For instance, gene body methylation was found in about a third of the expressed genes in Arabidopsis, but only 9% of the known gene body methylated regions associate with sRNAs (Zhang et al., 2006). How DNA methylation is directed to these regions that do not correlate with detectable sRNAs remains obscure. In addition, H3K27me3 was shown to be associated with ;4400 genes in Arabidopsis. The distribution of H3K27me3, however, is largely independent of DNA methylation and sRNAs (Zhang et al., 2007a). Further study is necessary to identify the signals that guide histone methyltransferases to H3K27me3-associated loci. In Arabidopsis, loci with considerable or complete sequence identity can acquire different combinations of epi-regulators for gene silencing (Rangwala and Richards, 2007; Lewis et al., 2007). This suggests that genome position-related factors may play an important role in directing epi-regulators. For example, within the Sadhu retrotransposon family (;70% similarity in nucleotide sequence among family members), individual retrotransposons located at different genome locations display variations in requiring DECREASED DNA METHYALTION 1 (DDM1), METHYLTRANSFERASE 1 (MET1), HISTONE DEACETYLASE 6 (HDA6), and SU(VAR)3–9 HOMOLOG 4 (SUVH4) for the maintenance of silencing (Rangwala and Richards, 2007). In a recent study using the nucleolar dominance system as an epigenetic model, ectopically integrated Arabidopsis thaliana rDNA was shown to be transcriptionally active in F1 progeny from Arabidopsis thaliana crossed with Arabidopsis lyrata. Interestingly, Arabidopsis thaliana rDNA located in the NORs were normally transcriptionally silenced via nucleolar dominance in this heterozygous genetic background (Lewis et al., 2007). These results suggest that for some epigenetic phenomena genome location may be a critical determinant for the establishment of epigenetic regulations. It is worth noting, however, that a 6-kb genomic fragment of the Arabidopsis FLOWER LOCUS C (FLC) gene can mediate mitotically heritable

gene silencing that is induced by vernalization when introduced as a stably integrated transgene. This observation indicates that the establishment of the Polycomb-like complex at the FLC locus is largely determined by specific recognition of DNA sequences (Sheldon et al., 2002; Sung and Amasino, 2004; Wood et al., 2006; De Lucia et al., 2008). The existence of numerous known epi-regulators and diverse ways that they may be targeted raises the question of how these different regulators may be orchestrated genome-wide to regulate gene expressions. Indeed, many endogenous and transgenic loci are controlled by more than one epi-regulator (Elmayan et al., 2005; Vaillant et al., 2006). Various genetic relations among regulators that control a particular locus have been described. For example, MOM1 appears to function downstream or independent of DNA methylation (Mittelsten Scheid et al., 2002), whereas DDM1 functions upstream of global DNA methylation as well as deposition of H3K9me2 and H3K4me2 marks (Gendrel et al., 2002). However, analyzing genetic interactions of epi-regulators by assaying molecular phenotypes (e.g. chromatin modifications or transcript accumulation) of a single target (tester) or a small set of target loci (tester sets) can generate ambiguous conclusions. One example presented by a recent study (Ba¨urle et al., 2007) showed that FCA and FPA are redundant in silencing AtMu1 but not AtSN1. Similarly, the de-repression of AtMu1 requires simultaneous loss of NUCLEAR RNA POLYMERASE D 1A (NRPD 1A) and FCA, or NRPD IA and FPA, whereas nrpd Ia single mutation is sufficient to activate the IG/LINE locus (Ba¨urle et al., 2007). In this case, analyzing a single tester for involvement of FCA, FPA, and NRPD IA will generate different conclusions from the result of analyzing all three testers (AtSN1, AtMu1, and IG/LINE). The observation that the function of epi-regulators can be redundant at one locus but distinct at others suggests that multiple chromatin modifiers may be used in a combinatorial fashion to exert different types of epigenetic control in various loci of the Arabidopsis genome. The Chromatin Charting Lines (CC Lines), which have an identical transgene construct inserted at different locations of the Arabidopsis genome (Rosin et al., 2008), can serve as valuable testers in studying interactions of epi-regulators. A luciferase (LUC) gene cassette included in the common CC transgene of these characterized lines can facilitate rapid quantification of changes in gene expression as a function of developmental stage or tissue type. In addition to using these CC lines for studying interactions of epi-regulators, the fact that each CC line has a single copy of a common transgene distributed at different locations of the genome allows direct testing of the hypothesis that genome location can affect targeting of epi-regulators. This hypothesis is strongly supported by locus-specific silencing observed in the nucleolar dominance system (Lewis et al., 2007), but has never been explicitly shown with any genes transcribed by RNA polymerase II. Recent work from our laboratory suggested that, for one particular CC line, CCP4.211, which has the transgene

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cassette flanked by the NOR of Chr. 2 from one side and by a 50-kbp region rich in retrotransposons on the other side, displays severe transgene silencing. In-vivo imaging analysis of CCP4.211 revealed that the transgene silencing of CCP4.211 was correlated with tethering of this transgene locus to the nucleolus and decreased mobility (Rosin et al., 2008). These results suggest that large-scale chromatin structure can be involved in regulating gene expressions at some genome locations, such as that tagged in the CC line, CCP4.211. To test the hypothesis that targeting of epi-regulators can be affected by genomic location, we set out to compare the mechanism of epigenetic silencing of four selected CC lines that have insertions mapped to different positions within a 100-kbp region of Chr. 2. We compared the contribution of eight epi-regulators (LHP1, MOM1, CMT3, DEFECTIVE IN RNA-DIRECTED DNA METHYLATION 1 (DRD1), DRM2, Su(VAR)3-9 HOMOLOG 2 (SUVH2), CURLY LEAF (CLF), and HISTONE DEACETYLASE 1 (HD1)) by transforming each of the four selected CC lines with RNAi vectors individually targeting these epi-regulators. Effects of RNAi-mediated silencing of these epiregulators on LUC gene and NPTII gene expression were measured and compared among the four CC line backgrounds and between two tissue types (shoot and root). We found that the reporter gene cassette in the four CC lines are differentially targeted by these eight regulators, and differences in the role of epi-regulators can also be observed between shoot and root tissues in some cases. In addition to analyzing the effects of gene silencing on our CC cassette, we also examined the effects of gene suppression of these eight epi-regulators on seven other genomic loci that are known to be epigenetically regulated. Our clustering analysis of these eight epi-regulators using the gene expression dataset generated in this study reveals predicted and novel interactions between them.

RESULTS CC Transgene Cassettes Integrated at Different Genome Locations Exhibit Different Gene Expression Levels and Tissue-Specific Expression Patterns Chromatin Charting lines used in this study include one line, CCP4.211, having a T-DNA insertion and three lines, CCT383, CCT396, and CCT431, having a Ds element derived from CCP4 launchpad lines. These four selected CC lines have transgene construct inserted within the first 100-kbp region of Chromosome 2. Transgene cassette in CCP4.211 is flanked by the NOR from one side and by a 50-kbp region rich in Gypsy-like retrotransposons from the other side (Rosin et al., 2008). Insertion site of the transgene construct in CCP4.211 maps to a rDNA spacer and is about 300 bp away from the coding region of a Ty3/Gypsy retrotransposon (Figure 1D). In contrast to CCP4.211, transgene constructs in CC lines CCT431, CCT396, and CCT383 are inserted in euchromatic regions populated with expressed genes (Figure 1D).

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Previously, in-vitro enzyme assay was used to quantify LUC activity in CC lines (Rosin et al., 2008). In the current study, quantitative measurements of LUC activity were performed with in-vivo bioluminescence imaging with live plants (Figure 1A). Relative Luciferase Activities (RLA) of wild-type Col-0, CCP4.20, CCP4.80, CCP4.211, CCT383, CCT396, and CCT431 plants were measured through in-vivo imaging and compared with previous results. Results acquired with the two methods are largely similar except that we found the in-vitro enzyme assay gives a significantly higher RLA in root tissue of CCT431 plants than that from in-vivo imaging (data not shown). One plausible reason for this discrepancy is that these two techniques utilize different normalization methods. For in-vitro enzyme assays, protein concentration of tissue homogenate was used to normalize luciferase activity for each sample whereas, for in-vivo imaging assays, luciferase activity was normalized with the size of viewing areas for the plant tissues used in chemiluminescence imaging. Protein extraction from root tissues is not very efficient due to the low content of proteins compared to that of shoot tissues; therefore, large volumes of samples are needed in some cases for protein determination of root extracts that may lead to more systematic errors. Transcript accumulation of LUC gene and NPTII gene in shoots was measured by RT–PCR and RNA gel blot, respectively. Levels of LUC transcripts in all tested lines apparently correlated with RLA from in-vivo imaging very well (Figure 1A and 1C), which validates that RLA indeed represents the relative abundance of LUC transcripts. Notably, expression levels of LUC gene and NPTII gene are highly correlated in CCP4.20, CCP4.80, CCP4.211, CCT431, and CCT396 plants. For line CCP4.211, consistent with the heterochromatic nature of where the transgene construct has inserted into, both LUC and NPTII genes are highly suppressed. On the other hand, the insert in line CCT383 exhibits a similar NPTII expression level as in CCP4.20, a representative CC line with ‘average’ transgene expression levels, even though the expression level of LUC is about 10-fold lower than in CCP4.20 (Figure 1B and 1C). As reported in Rosin et al. (2008), expression of LUC in lines CCT431 and CCT 396 are specifically suppressed in roots but not in shoots (Figure 1A). This tissue-specific expression pattern is not a common behavior of the CaMV 35S promoter that drives LUC gene expression in the CC transgene cassette, because both CCP4.20 and CCP4.80 show comparable RLA in shoots and roots (Figure 1A). Thus, the root-specific suppression of LUC expression is likely mediated by epigenetic mechanisms. Treating CCT431 and CCT396 plants with 5-aza-2#-deoxycytidine (AZA), which inhibits maintenance cytosine methylation, resulted in enhancement of RLA in roots. This suggests that DNA methylation is involved in root-specific silencing of the LUC gene at the insertion sites tagged in these CC lines (Rosin et al., 2008). Interestingly, integration sites of transgene constructs in lines CCT431 (Chr2: 75361, within AT2G01060) and CCT396 (Chr2: 77442, within AT2G01070) are physically close

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Figure 1. Differential Expressions of Luciferase and NPTII Transcripts in Chromatin Charting Lines. (A) Luciferase imaging of Chromatin Charting lines. Bright-field (BF) and bioluminescence (BL) images were separately acquired from an MS agar plate containing wild-type Arabidopsis, CCP4.20, CCP4.80, CCP4.211, CCT 383, CCT 396, and CCT 431 plants, which were vertically grown for 12 d before imaging. Merged image of BF and BL is also shown. The color scale of luminescence, from the lowest of 4.8 3 106 photons s 1 (dark blue) to the highest of 9.0 3 107 photons s 1 (light red), is shown in the BL image. (B) Northern blot analysis of NPTII transcripts in CC lines. Ten micrograms of total RNA isolated from shoots of 14-day-old plants were blotted and hybridized with 32P-labeled NPTII probe. A methylene blue-stained membrane was shown as a loading control. (C) RT–PCR analysis of Luc and Actin2 transcripts. RNA samples used in (B) were subjected to this analysis. Relative expression levels of Luc and Actin2 (Act2) transcripts were estimated by agarose gel electrophoresis followed by ethidium bromide staining. RT–PCR for Luc was carried out with three different cycles (28, 30, 32) under specific conditions. An Act2 cDNA fragment was amplified under specific conditions and used as a positive control. Inverted images of ethidium bromide-stained gels were shown. (D) Integration sites of transgene constructs in lines CCP4.211, CCT431, CCT396, and CCT383. The x-axis represents the first 100 kbp of chromosome 2. Positions of red bars indicate the integration site of each CC line and the lengths of red bars represent RLA (y-axis) in shoots from 12–14-day-old plants. Horizontal bars indicate regions of rDNA (green), Ty3/Gypsy Retrotransposons (blue) and expressed genes (gray).

to each other (Figure 1D). Consistent with the physical proximity of transgene integration sites of these transposant lines, they exhibit similar RLA in shoots and share the specific suppression of LUC gene in roots.

Evaluation of Epigenetic Regulator Involvement Using Reverse Genetics with RNAi We selected four CC lines, CCP4.211, CCT383, CCT396, and CCT431, to test the hypothesis that distinct combinations of epi-regulators can be involved in silencing an identical gene cassette located in a different location of the genome. Although the LUC gene cassette is silenced in both shoots and roots in the CC lines CCP4.211 and CCT383, the former is located within a region that is likely heterochromatic in nature while the latter is situated in euchromatin. In contrast, CCT396 and CCT431 lines exhibited root-specific silencing of LUC ex-

pression (Figure 1A). These different characteristics can be explained if distinct sets of epi-regulators are recruited to the four tagged locations in this region of Chr. 2 where these CC lines have been mapped (Figure 1D). To test this hypothesis, we took a candidate gene approach and set out to determine the involvement of eight different known epi-regulators in LUC gene silencing observed in these four CC lines. We chose to suppress the candidate epi-regulators by RNAi rather than crossing genetic mutants of these genes with the four CC lines because of the following considerations: (1) Crossing eight mutants with four CC lines and then identifying homozygous mutants in F2 progeny sets for all combinations via genotyping is more laborious and tedious. (2) Well characterized mutants in the Col-0 background are not readily available for some of these genes, such as MOM1, DRM2, CMT3, and CLF. (3) RNAi has been broadly used for and proved to be an efficient

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approach to suppressing gene expression in reverse genetic screens (Crane and Gelvin, 2007). In our case, this approach was also aided by the fact that the Plant Genome Chromatin Group at the University of Arizona has already generated RNAi vectors targeting more than 170 Arabidopsis genes predicted to have chromatin related functions (www.chromdb.org). Many of these RNAi vectors have been transformed into Arabidopsis plants and suppression efficiencies were tested by gene-specific RT–PCR. This public resource thus provides us with a set of tested vectors for suppressing epi-regulators in CC lines. Using RNAi vectors obtained from the Arabidopsis Stock Center, we successfully generated T1 transformants for all 32 combinations (four CC lines each transformed with eight different RNAi vectors). We tested suppression efficiency in independent T1 plants for all 32 combinations (Supplemental Figure 1). In most cases, effective suppression of 80% or more of the target transcripts can be achieved as assayed by RT–PCR with total RNA isolated from leaf tissues. In some combinations such as CCT383-MOM1, however, significant increase in LUC expression can be observed in transgenic lines with lower levels of suppression of MOM1 transcripts (Supplemental Figure 1). There are three possible explanations for this observation: (1) MOM1 protein synthesis may be efficiently repressed by siRNA (Brodersen et al., 2008), although the suppression of MOM1 transcripts is incomplete. (2) The expression of LUC gene in line CCT383 is highly sensitive to the suppression of MOM1 expression. This dosage-dependent sensitivity could be a result of limiting amounts of MOM1 protein in the nucleus and/or low affinity of the particular genome location to MOM1 relative to other MOM1 target sites in the genome. (3) The activation of LUC gene expression may be due to accidental silencing of off-target regulatory genes affected by the particular RNAi vector.

Tissue Identity Affects Observed Dependence on Epigenetic Regulators RLA in shoots and roots of T1 plants from all 32 combinations were measured by in-vivo bioluminescence imaging together with their parental CC lines. For each combination, 15–25 independent T1 lines were analyzed. A schematic overview of the approach is shown in Figure 2A. Data from the 32 combinations can be categorized into two types, based on the distribution of RLA within their T1 population: (1) All T1 plants show similar RLA to their parental line, indicating that the epigenetic regulator being suppressed does not contribute to the regulation of LUC gene. (2) A majority of plants within the T1 population display significant changes in RLA compared to their parental CC line, while the remaining plant lines exhibited similar RLA to the corresponding parental background. RLA in the T1 population of all 32 combinations showed either bimodal distribution or simply no significant change is observed. Continuous distribution of RLA in T1 population is not observed in any of the 32 combinations. For combinations belonging to type 1, mean RLA were calculated from a randomly selected pool of six plants,

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since all T1 plants display similar RLA. For combinations belonging to type 2, six representative plants, which show significant changes of RLA compared to the parental background, were used to calculate mean RLA. Mean RLA from all 32 combinations are summarized and shown in Figure 2B (data for shoots) and Figure 3 (data for roots). Based on the levels of variations that we observed among individual plants with identical genotypes, we set a threshold of three-fold (3X) from the RLA in the parental CC line background to be the significance cut-off for our analyses. One prevalent feature that can be readily discerned from our data is that LUC gene expression in shoots and roots from the same CC lines can be regulated by different sets of epiregulators (Figures 2B and 3). Among the eight regulators included in this study, only MOM1 was found to be involved in silencing the LUC gene cassette in shoot tissues of CCP4.211 (Figure 2B). In root of line CCP4.211, however, the suppression of LUC expression appears not to be mediated by MOM1 (Figure 3). Therefore, the regulators that contribute to transcription repression are not identical in these tissues, although LUC gene is silenced to comparable levels in shoot and root tissues of CCP4.211. In the shoots of lines CCT431 and CCT396, LUC expression could not be significantly enhanced by suppressing any tested regulators (Figure 2B), suggesting that the LUC gene is not repressed by any of these eight regulators in shoots of both CCT431 and CCT396 lines. These data also suggest that the enhancement of RLA observed in CCP4.211 transformants is specific to the reversal of epigenetic silencing at that locus and not due to a general increase in transcription activity. In the root tissues of line CCT431, however, MOM1, DRD1, DRM2, and CLF all appear to individually contribute to silencing of the LUC gene cassette (Figure 3). Similarly, in roots of line CCT 396, a tagged locus close to that of line CCT431, LUC expression is negatively regulated by MOM1, CLF, and LHP1 (Figure 3). These results suggested that the LUC gene is specifically silenced in roots but not shoots of lines CCT431 and CCT396 via common (MOM1 and CLF) as well as different (DRD1, DRM2, and LHP1) epi-regulators. Epi-regulators that only repress the LUC gene cassette in roots of both CCT 431 and CCT 396 lines are either specifically directed to the LUC gene during root development or they may be actively removed from the LUC cassette in shoot tissues. More careful analyses of LUC expression in the early embryo from these transformed lines may help to resolve this question. In contrast to the specificity of MOM1 suppression displayed by line CCP4.211, all eight epi-regulators tested are apparently involved in silencing of the LUC gene cassette in shoot tissues of CCT383 (Figure 2B). This is correlated with the exceptionally low RLA of CCT 383. However, in root tissues of both CCP4.211 and CCT383 lines, only minor increases in RLA were observed in some cases (Figure 3). To validate these minor activations, luciferase activity will need to be detected by more sensitive approaches, since the luciferase activity in root tissues of the parental lines is very close to the detection limit for the CCD camera being used.

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Figure 2. Effects of RNAi-Mediated Gene Silencing of Eight Chromatin Modifiers on Luciferase Expression in Shoot Tissues of CC Lines. (A) Schematic overview of screening of T1 plants transformed with dsRNA constructs in CC lines. (B) Detection of relative Luc activity in shoots of 2-week-old T1 seedlings. The relative Luc activity (RLA) was measured in vivo for T1 seedlings of four CC lines transformed with RNAi constructs that could suppress LHP1, MOM1, CMT3, DRD1, DRM2, SUVH2, CLF, or HD1. Each value represents the mean and standard error of six representative T1 seedlings for each RNAi construct. RLA of non-transformants of CCP4.211, CCT383, CCT396, and CCT431 lines was shown as control. More than three-fold higher (line marked with 3X) or less than three-fold lower (line marked with 0.3X) RLA in comparison with untransformed CC plants were considered as significant changes in RLA for each.

Target Specificity of Epi-Regulator Suppression via RNAi: Analysis of Cognate Genomic Loci In order to test the specificity of RNAi as well as to confirm that RNAi-mediated suppression of eight epi-regulators can recapitulate known molecular phenotypes (e.g. activation of transposable elements) associated with the corresponding genetic mutants, we compared expression of several genomic loci between untransformed CCP4.211 plants and those transformed with the eight RNAi vectors (Figure 4). Testing seven different genomic targets that are known to be epigenetically silenced showed that one can phenocopy known deregulated expression observed in genetic mutants with our CCP4.211-RNAi lines. For example, the expression of AGAMOUS (AG) in somatic tissue is up-regulated in lhp1 or clf mutant backgrounds (Nakahigashi et al., 2005; Schubert et al., 2006). We were able to detect the up-regulation of AG in CCP4.211-RNAi lines that suppressed LHP1 or CLF expression effectively (Figure 4). Also,

silencing of centromeric 180-bps repeats and CYCLOPHILIN 40 (CyP40, AT2G15790) was released in mom1 background (Habu et al., 2006; Vaillant et al., 2006). Correspondingly, increased transcripts from both of these loci can be shown in our CCP4.211-MOM1 lines (Figure 4). Importantly, transcripts of AtMu1 and Athila LTR were not detectable in any of the CCP4.211-RNAi plant lines (Figure 4), but can be easily detected in ddm1-2, when they were analyzed using the same PCR conditions (data not shown). These results suggest that RNAimediated gene silencing of the eight epi-regulators can specifically relieve gene silencing at some genomic targets but not others. In addition to confirming the efficacy and specificity of our RNAi strategy, we also extended our knowledge on target specificity of the eight epi-regulators in this work. Some misregulations of genomic loci we found with CCP4.211-RNAi lines upon RNAi suppression of these eight

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Figure 3. Effects of RNAi-Mediated Gene Silencing of Eight Chromatin Modifiers on Luciferase Expression in Root Tissues of CC Lines. Detection of relative Luc activity in roots of 2-week-old T1 seedlings. The relative Luc activity (RLA) was measured in vivo for roots of T1 seedlings from four CC lines transformed with RNAi constructs that could suppress LHP1, MOM1, CMT3, DRD1, DRM2, SUVH2, CLF, or HD1. Each value represents the mean and standard error of six representative T1 seedlings for each RNAi construct. RLA of non-transformants of lines CCP4.211, CCT383, CCT396, and CCT431 was shown as control. More than three-fold higher (line marked with 3X) or less than threefold lower (line marked with 0.3X) RLA in comparison with untransformed CC plants were considered as significant changes in RLA for each.

Figure 4. Effects of RNAi-Mediated Silencing of Eight Epigenetic Regulators on Expression of Endogenous Loci. Expression of endogenous genes AGAMOUS (AG), FLOWER LOCUS C (FLC), AT2G15790 (CyP40), centromeric satellite repeats (180 bps) and transposable elements Arabidopsis Mutator Like Element 1 (AtMu1), SINE retroelement AtSN1 and Athila LTR were analyzed by RT– PCR in line CCP4.211 and two representative T1 plants in the CCP4.211 background for each construct. Rosette leaves of 30day-old CCP4.211 and T1 plants were used for RNA isolation. An Act2 cDNA fragment was amplified to serve as control. Inverted images of ethidium bromidestained gels are shown.

genes were not previously reported. For instance, FLC appears to depend on two histone H3 modifiers, SUVH2 and HD1, for epigenetic silencing in somatic tissue of Columbia accession; AG was up-regulated when CMT3, DRM2, and HD1 were individually suppressed in addition to LHP1 and CLF. Also,

suppression of DRD1 and DRM2 can relieve silencing of the AtSN1 locus. Interestingly, NRPD 1A and RDR2, which are involved in siRNA biogenesis (Matzke et al., 2007), were also shown to be involved in silencing the AtSN1 locus (Ba¨urle et al., 2007).

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Transgenes Inserted into Different Genomic Locations Are Regulated by Distinct Sets of Epigenetic Regulators When changes of RLA caused by suppressing the eight epi-regulators are compared between the four selected CC lines, we found that similar LUC expression does not necessarily mean the LUC genes are regulated by identical mechanisms. In both shoots and roots, both CCP4.211 and CCT383 lines exhibited similar expression of the LUC gene (Figure 1A and 1C). However, repression of LUC expression in CCT383 shoot involves cooperative contribution from all eight tested regulators whereas only MOM1 was shown to suppress LUC expression in the CCP4.211 background (Figure 2B). This apparent difference in epi-regulator involvement may be due to the consequence of different genome locations of the LUC gene cassette, although another more complex explanation is possible at this point. Nevertheless, the observation that LUC expression in line CCT383 is regulated by LHP1 correlates with the euchromatin property of the insertion locus in this CC line (Libault et al., 2005). In fact, high-resolution ChIP-chip and DamID-chip studies indicated that LHP1 does not localize to heterochromatin of the Arabidopsis genome (Zhang et al., 2007b; Turck et al., 2007). In contrast, regulators that are identified to regulate LUC expression in line CCP4.211, including DDM1, MET1, and MOM1, have all been shown to have heterochromatic targets (Gendrel et al., 2002; Vaillant et al., 2006; Rosin et al., 2008). More differences between lines CCP4.211 and CCT383 regarding the dependence of epiregulators can be found by comparing regulation of the NPTII gene. In line CCP4.211, NPTII expression is similarly repressed to that of the LUC gene cassette—suppressed by MOM1 but not any other tested regulators in shoot tissues (Supplemental Figure 1). In contrast, none of the tested regulators is found to influence expression of the NPTII gene in CCT383, although all of them appeared to be involved in LUC gene silencing (Figure 2B and Supplemental Figure 1). LUC expression in shoots of both CCT431 and CCT396 lines are not significantly enhanced by suppressing any of the eight tested epi-regulators (Figure 2B). In fact, suppressing LHPI, CMT3, HD1, and SUVH2 in line CCT431 was observed to cause a significant down-regulation of RLA (< 0.3X) in the shoots (Figure 2B). The reason for this observation is unclear at present, since there are no previous results indicating that these epi-regulators can positively regulate transcription. These could be indirect effects through deregulation of other factors that are controlled by these epi-regulators.

many but not all cases, suppression of regulators that are predicted to function in the same pathway can give rise to similar molecular phenotypes. For example, transcription from AG, 180 bps repeats, AtSN1, and LUC genes in roots of CCT431 plants can be activated by suppressing either DRD1 or DRM2 (Figure 4), both of which are involved in RNA-directed DNA Methylation (RdDM) pathway (Cao et al., 2003). Also, suppression of either LHP1 or CLF can induce AG, FLC, and RLA in roots of CCT396 plants. CLF is responsible for the deposition of some of the H3K27me3 marks in the Arabidopsis genome and LHP1 has been shown to be closely associated with this particular histone modification in vivo (Schubert et al., 2006; Zhang et al., 2007b; Turck et al., 2007). Therefore, it may be possible to predict functional interactions between epi-regulators by scoring the similarities between multiple molecular phenotypes upon their suppression. Regulators that belong to the same pathway, or are involved in the formation of a common complex, would be likely to share a majority of their target loci. To test the feasibility of this approach, we attempt to predict interactions between the eight epi-regulators examined in this study (LHP1, MOM1, CMT3, DRD1, DRM2, SUVH2, CLF, and HD1). Changes in RLA (Figures 2B and 3) of the four selected CC lines and expression of the seven different cognate genomic loci (Figure 4), as compared to that of the parental CC lines, served as molecular phenotypes. The eight epi-regulators were subjected to hierarchical clustering based on the similarities observed between molecular phenotypes caused by RNAimediated gene suppression. Two stringency cut-offs (three-fold or two-fold up/down-regulation in RLA) for significant changes in LUC expression were applied and the results are shown in Figure 5A and 5B3, respectively. As expected, DRD1 and DRM2 were clustered together at both stringency levels. Five regulators—LHP1, CMT3, HD1, SUVH2, and CLF—grouped together and are separated from DRM2 and DRD1 regardless of the stringency, although the resultant tree topology varies when using these two different cut-offs. Interestingly, these five regulators all have known functions relating to histone H3 modification. Functions of CLF and LHP1 have been described earlier; CMT3 cytosine methyltransferase has been shown to interact with histone H3 with methylation at both K9 and K27 positions (Lindroth et al., 2004); HD1 gene codes for a histone deacetylase (Fong et al., 2006) and SUVH2 is one of the Arabidopsis homologs for SU(VAR)3-9 like histone methyltransferase (Naumann et al., 2005). This functional relationship between them suggests a possible interaction network that gives rise to the similarity of their molecular phenotypes and targets.

Inference of Epi-Regulator Interactions via Clustering Analysis Suppression of epi-regulators can result in visible (e.g. early flowering) and molecular (e.g. deregulated gene expression) phenotypes. In this study, we refer to changes of RLA (Figures 2B and 3) and gene expression of endogenous loci (Figure 4) as molecular phenotypes caused by suppressing epi-regulators. By assaying these molecular phenotypes, we found that in

DISCUSSION Epigenetic Mechanisms Contribute to Dynamic Regulation of Gene Expression in Plants Intense studies of Arabidopsis development have demonstrated the capacity of epigenetic mechanisms to dynamically

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Figure 5. Hierarchical Clustering of Chromatin Modifiers Using Molecular Phenotypes Resulting from RNAi-Mediated Silencing of Epigenetic Regulators. Heat maps representing qualitative changes of RLA caused by RNAi-mediated silencing of epigenetic regulators (listed to the right of the heat maps) in four CC lines and two tissue types (listed on the top of heat maps). In (A), more than three-fold higher or less than three-fold lower than the RLA of untransformed CC lines is considered significant up-regulation (red in heat maps) or down-regulation (green in heat maps). In (B), more than two-fold higher or less than two-fold lower than RLA of untransformed CC lines is considered significant changes. Changes in expression of endogenous loci were estimated by RT–PCR results shown in Figure 4 and are also represented in the heat maps. Black blocks indicate insignificant changes of RLA and expression levels of endogenous loci, while missing data are shown as gray blocks. The gene tree at the left of the heat maps represents the similarity between effects (change of RLA and endogenous loci expression) of RNAi-mediated silencing of different epigenetic regulators. Longer internode distance indicates less similarity while shorter internode distance indicates higher similarity.

regulate gene expression in different phases of the plant life cycle (Kinoshita et al., 2004; Wood et al., 2006; De Lucia et al., 2008; Pien and Grossniklaus, 2006). In many cases, disruption of epigenetic regulators (e.g. CLF, MEDEA (MEA), VERNALIZATION RESPONSE 2 (VRN2)) that control genes important for reproduction give rise to visible morphological and/or growth phenotypes (Goodrich et al., 1997; Grossniklaus et al., 1998; Gendall et al., 2001) and can facilitate identification of these regulators through forward genetic screens. In vegetative tissues or vegetative growth stages, however, the role of epigenetic mechanisms in dynamically regulating gene expression is less characterized. This may be partially due to the lack of phenotypes that can be easily scored when epigenetic regulators are mutated in somatic tissues. Chromatin Charting lines provide a large collection of genetic materials in which expression of an identical LUC gene inserted at different locations within the genome can be easily quantified in various tissues and developmental stages. In addition, our initial characterization of CC lines revealed evidence for extensive tissue-specific epigenetic

regulation (e.g. root-specific silencing of LUC expression), thus illustrating the use of the CC lines as unique resources for studying dynamic control of gene expression by epigenetic mechanisms with high spatial and temporal resolution (Rosin et al., 2008). In the current study, we showed that several independent pathways are involved in tissue-specific regulation of LUC expression in selected CC lines. MOM1, DRD1, DRM2, and CLF work together to suppress LUC expression in root tissues of line CCT431; LHP1, MOM1, and CLF are responsible for LUC silencing in root tissues in line CCT396 (Figure 3). In addition, MOM1 is required to suppress LUC expression in shoot but not root tissues of line CCP4.211 (Figure 2B). The role of the plant Polycomb complex, which includes CLF and probably also LHP1, in the dynamic control of gene expression has been proposed from studies on regulation of the FLC locus. In this case, vernalization induces transcriptional repression associated with an increase in H3K27me3 at the FLC locus (Finnegan and Dennis, 2007). LHP1 then binds to H3K27me3 at this locus and mediates subsequent transcriptional repression (Sung et al., 2006; Mylne et al., 2006;

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Zhang et al., 2007b; Turck et al., 2007). Our results showed that some transgenic loci (i.e. the LUC gene cassette in lines CCT396 and CCT431, but not in lines CCP4.211 and CCT383) can also be targeted and regulated by the plant Polycomb complex in a tissue-specific manner. The requirement of CLF to suppress LUC expression in roots of both CCT431 and CCT396 suggests that root-specific deposition of H3K27me3 at the LUC locus of these two insertion locations is involved (Figure 3). Interestingly, CLF but not LHP1 is required for suppressing LUC in root of CCT431, indicating that LHP1 may be dispensable for H3K27me3associated transcriptional silencing in some cases (Figure 3). The requirement of DRD1 and DRM2 to suppress LUC expression in roots but not shoots of CCT431 suggests that the RdDM pathway can contribute to dynamic control of gene expression (Figure 3). This is consistent with previous results that show 5-AZA treatment of seedlings to inhibit cytosine methylation can reverse silencing in root tissues of these two CC lines (Rosin et al., 2008). RdDM includes multiple steps involving siRNA biogenesis, as well as catalyzing site-specific de-novo DNA methylation (Matzke et al., 2007). In comparison to the AtSN1 locus, which also depends on DRD1 and DRM2 for silencing, it will be interesting to test whether NRPD 1A and RDR2 are also required for the root silencing in line CCT431. To explain the root-specific silencing phenotype observed, one or several steps of RdDM at the LUC locus of line CCT431 may be more efficient in roots than in shoots. Future analysis of siRNA accumulation, DNA methylation, and histone modifications at the LUC gene cassette of CC lines will help to reveal the molecular basis of the observed root-specific silencing. In fact, seven out of eight epi-regulators tested in this work, except for MOM1, have been implicated to associate with certain epigenetic marks. The direct regulation of LUC locus by epiregulators can be confirmed by comparing the status of corresponding epigenetic marks between lines transformed with RNAi vectors and untransformed controls.

Does Genomic Location Affect Deposition of Epigenetic Regulators? The correlated expression levels between NPTII and LUC in CCP4.20, CCP4.80, CCP4.211, CCT431, and CCT396 suggest that these two linked transgenes are regulated similarly in these CC lines (Figure 1B and 1C). Thus, expression of both LUC and NPTII may be determined by the genomic environment surrounding the transgene constructs, perhaps through chromatin structure. In the case of line CCP4.211, where the transgene construct has been mapped to between the NOR and a large retrotransposon island that are likely heterochromatic in nature, the selection marker gene NPTII is silenced together with the LUC gene, resulting in a partial loss of Kanamycin resistance (data not shown). This is consistent with previous results that T-DNA integration into heterochromatic regions can be found under non-selective conditions but was disfavored when the selection condition was applied (Kim et al., 2007). Our results obtained in this study also showed that transgenes inserted into heterochromatic regions of Arabidopsis are more likely to be silenced.

If the hypothesis that genome locations can determine the deposition of epi-regulators is true in all cases, one prediction is that similar sets of epi-regulators will target linked transgenes such as the LUC and NPTII gene cassettes in the CC lines. In line CCP4.211, this is indeed observed in all the tested lines that we have preformed so far by epi-regulator suppression (Supplemental Figure 1). Sharing of epigenetic control mechanisms between the linked LUC and NPTII gene cassettes in these CC lines may partially explain their correlated expression levels. In addition to the proximity between LUC and NPTII that is predetermined by our CC construct design, the integration sites of transgene constructs in lines CCT431 and CCT396 are only ;2 kbp apart from each other (Figure 1D). The LUC gene expresses similarly in shoots of lines CCT431 and CCT396 and is silenced in roots of both lines (Figure 1A and 1C). Comparison of regulators that are responsible for root-specific silencing revealed that MOM1 and CLF, a component of the plant Polycomb complex, suppress LUC expression in the two CC lines, whereas the RdDM pathway is involved in silencing LUC expression in root tissues of CCT431 but not CCT396 (Figure 3). Thus, it appears that partial overlapping sets of regulators are targeted to the two transgenic loci that are spatially close together in the genome. Local sequence context in addition to genome location can thus dictate the particular types of epiregulators that may be targeted to a gene. The LUC gene cassette in line CCT383 is different from the other three CC lines, with respect to both transgene expression patterns and the underlying regulatory mechanisms. In contrast to the other tested CC lines showing correlated expression of LUC and NPTII genes, expression level of LUC in CCT383 is highly suppressed, which was similar to that in line CCP4.211, while expression level of NPTII gene is consistently higher in this line (Figure 1B and 1C). Consistent with the different relative expression levels between the two neighboring transgenes, the LUC gene cassette is suppressed by all tested regulators in shoots whereas none of them is shown to suppress NPTII expression (Figure 2B and Supplemental Figure 1). Therefore, the regulation of the LUC and NPTII gene cassettes in line CCT383 appears to be uncoupled. Our data thus suggest that, depending on the insert location in the genome, these two linked transgenes can be targeted by distinct sets of epigenetic regulators and controlled differentially. This can be explained by a combination of sequence-context-dependent and genome-location-directed epigenetic mechanisms that ultimately dictate the final patterns of epigenetic modifications at these two gene cassettes, as the two transgene cassettes are separated by about 2 kbp of LacO repeats.

Functional Interactome Studies as a Novel Approach to Predicting Protein Interactions between Epigenetic Regulators and Pathways Along with continuing discovery and characterization of epi-regulators in plants, interactions between some of these regulators have been reported, typically through biochemical or genetic approaches. For example, using co-immunoprecipitation,

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DDM1 was shown to bind Arabidopsis methyl-CpG binding domain proteins (Zemach et al., 2005). Also, two Polycomb-like complexes that may be involved in FLC regulation were identified by affinity purification (Wood et al., 2006; De Lucia et al., 2008). In parallel with these studies, interactions among DNA methyltransferases, histone modifiers, and components of the siRNA biogenesis pathway have been largely established by careful genetic analyses (Chan et al., 2005). Most of these traditional methods are time-consuming and require a substantial amount of knowledge about the biological functions for the protein of interest, which are difficult to scale up for genome-wide detection of protein interactions among epi-regulators. Here, we describe an approach for detecting interactions of epi-regulators that may be applied toward discovery of novel epigenetic networks. The approach is based on the notion that epi-regulators that function in the same pathway will generate similar molecular phenotypes when their levels are reduced by either forward or reverse genetic means. Molecular phenotypes can be any detectable molecular profile including transcriptome, sRNAome, methylome or histone modification profiles. Therefore, by subjecting epi-regulators to clustering analysis based on molecular phenotypes observed in loss-of-function mutants or RNAi suppressed lines, putative interacting regulators can be grouped together to predict a functional interactome. In the current study, using altered expression of cognate loci or selected transgenes as molecular phenotypes, we were able to detect the interaction between DRD1 and DRM2 and also a group of four histone H3 modifiers together with LHP1 (Figure 5). Although the clustering analysis is based on a relatively small dataset so far, this approach can be easily applied to larger profiling datasets generated by microarray and high-throughput sequencing technologies. In addition, a minimal amount of knowledge about the particular epiregulators being studied is required for this functional interactome method. With putative chromatin-associated regulators, for which physical binding sites in vivo can be identified at high resolution by ChIP-chip or ChIP-seq techniques, immediate downstream targets of regulators can also be used for clustering analysis. Thus, instead of grouping regulators based on phenotypes, coincidence of target sites can also be used to predict interactions of chromatin-associated proteins. Lastly, as shown in the present study, the CC lines that have been generated can also provide additional spatial and temporal resolution to the complex nature of epigenetic regulation genome-wide. Our results in this study illustrate that physiological processes such as differentiation and development play important roles in differentially modulating the epigenetic networks that are necessary to coordinate global gene regulation pathways.

METHODS Plant Material and Growth Condition Chromatin Charting (CC) lines, including CCP4.211, CCT396, CCT431, and CCT383, were created as described previously

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(Rosin et al., 2008) and information for these materials is available on the Chromatin Charting Database (http://charting.cshl. org). RNAi construct targeting MOM1 (clone ID; CD3-528), DRM2 (CD3-557), HD1 (CD3-515), DRD1 (CD3-646), LHP1 (CD3-647), CMT3 (CD3-649), CLF (CD3-538), or SUVH2 (CD3-539), which were generated by the ChromDB Project (www.chromdb. org/index.html) (Kerschen et al., 2004; Gendler et al., 2008), were obtained from the Arabidopsis Biological Resource Center (www.arabidopsis.org). These RNAi constructs were introduced into Agrobacterium tumefaciens strain GV3101/pMP90 and four different CC lines were transformed by the floral dip method (Clough and Bent, 1998). Basta-resistant T1 plants were selected on 0.5X Murashige and Skoog (MS) media (Sigma-Aldrich) supplemented with 0.8% (w/v) agar (SigmaAldrich), 1% (w/v) sucrose (Fisher Scientific), 10 lg mL 1 basta (glufosinate ammonium; Sigma-Aldrich) and 200 lg mL 1 carbenicillin (Sigma-Aldrich) for up to 5–7 d and then transferred to 0.5X MS medium solidified with 1% (w/v) agar supplemented with 1% (w/v) sugar and grown vertically for 7 d. All plants were grown under constant illumination (100 lmol M 2 s 1) at 22
C in a walk-in growth chamber. T2 seeds were germinated on 0.5X MS solid medium with 1% sucrose and 10 lg mL 1 glufosinate ammonium (Basta) and grown under similar conditions as described above for further analyses.

In-Vivo Chemiluminescence Imaging For luciferase imaging, 12–14-day-old Arabidopsis seedlings grown on solid MS media were sprayed with the luciferin working solution (1 mM D-Luciferin sodium salt; Gold BioTechnology and 0.01% (w/v) Triton X-100 in distilled water) and then incubated at room temperature for 10 min to allow the uptake of luciferin. A bright-field image of each sample was taken for the recognition of plant outlines in the Lumazone Fluorescence Automated System (MAG Biosystems), which consists of a high-performance CCD camera, mounted in a dark chamber, camera and mount controllers, and a computer. Plants were further kept in the dark for 5 min in order to eliminate interference of delayed fluorescence from chlorophyll. Then, all luciferase images were acquired at room temperature in the dark with a 7-min exposure time through the chemiluminescence detection channel. All images were processed by MAG Biosystems Software Version 7.5.5.0 and then analyzed with MAG Biosystems Lumazone Analyzer 2.0. To quantitatively analyze luciferase activities of plant tissues, outlines of plants were recognized by the count/size tool of the Lumazone Analyzer 2.0 with manual adjustment. A measurement tool was then used to quantify average pixel intensities of selected areas. For each image, background was determined by measuring average pixel intensities of regions that were not covered with plants and then subtracted from the average pixel intensity of samples. The background subtracted average pixel intensities for each sample were normalized to that of line CCP4.20 with RLA set to 100.

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Northern Blot and RT–PCR Analyses For Northern blot analysis, total RNA was isolated from shoots of 12-day-old plants using the Plant RNA Purification Reagent (Invitrogen) according to the manufacturer’s instructions. 10 lg RNA were resolved by 1% (w/v) denaturing agarose gel electrophoresis, then transferred and UV cross-linked to Hybond N+ nylon membranes (GE Healthcare). A partial DNA fragment of NPTII gene was amplified by PCR using a set of oligonucleotide primers (EL1069 and EL1070; see Supplemental Table 1) and used as the hybridization probe. The DNA probe was labeled with [32P]dCTP (MP Biomedical) by the RadPrime DNA Labeling System (Invitrogen) according to the product manual. Hybridization was performed at 68
C using MiracleHyb Hybridization Solution (Strategene), as suggested by the manufacturer. For RT–PCR, total RNA was isolated from 30-day-old T1 transgenic plants with Tri-Reagent (Sigma-Aldrich). At least five rosette leaves were used from each plant. 400 ng of RNA treated with RQ1 RNase-Free DNase (Promega) was subjected to reverse transcription in a 20-lL reaction using Improm-II Reverse Transcription System (Promega). cDNAs were diluted into 150 lL with DNase-free water and 3 lL were used for each PCR reaction as template. PCRs were performed using GoTaq DNA Polymerase (Promega) in a 25-ll reaction with the following conditions: 2 min at 95
C, 28–37 cycles of 30 s at 95
C, 30 s at 55
C and 45 s at 72
C and a final elongation at 72
C for 5 min. Primers and PCR conditions used in this paper are listed in Supplemental Table 1.

Clustering Analysis Cluster analysis was applied to LHP1, MOM1, CMT3, DRD1, DRM2, SUVH2, CLF, and HD1 based on changes of RLA and endogenous loci expression causes by silencing these regulators. Significant changes of RLA or gene expression were determined as stated before. Euclidean distances between regulators were calculated to generate similarity metric. Hierarchical clustering was performed using centroid linkage with Cluster 3.0 (de Hoon et al., 2004). Results were visualized using Java Treeview 1.1.3 (Saldanha, 2004).

SUPPLEMENTARY DATA Supplementary Data are available at Molecular Plant Online.

FUNDING This work was supported in part by the PGRP program from the National Science Foundation (DBI-0077617) and funding from the Biotechnology Center for Agriculture and the Environment of Rutgers University to E.L. Support from the Douglass Project for Woman in Science, Technology, Engineering and Math program to B.D. and Christine Muglia and an Aresty Undergraduate Research grant at Rutgers University to B.D. is gratefully acknowledged. Support by the New Jersey Agricultural Experiment Station and the School of Environmental and Biological Sciences of Rutgers University is

gratefully acknowledged for contributing toward the purchase of the Lumazone FA imaging system used in this work.

ACKNOWLEDGMENTS We thank Christine Muglia for her involvement in the early phase of this work, participating in transformation of the CC lines with numerous Agrobacterium strains. We also thank the Arabidopsis Stock Center for their supply of constructs.

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