SDG8-mediated histone methylation and RNA processing ... · 49 SDG8 is required for canonical RNA processing, and that RNA isoform switching is 50 more prominent in the sdg8-5 deletion

1

Short title: A H3K36 methyltransferase in nitrate signaling 1

Authors for contact: Dr. Gloria Coruzzi and Dr. Ying Li 2

3

SDG8-mediated histone methylation and RNA processing function in the 4

response to nitrate signaling 5

6

Ying Li1,2,3,*, Matthew Brooks1, Jenny Yeoh-Wang1, Rachel M McCoy2,3, Tara M Rock1, 7

Angelo Pasquino1, Chang In Moon2,3, Ryan M Patrick2,3, Milos Tanurdzic4, Sandrine 8

Ruffel5, Joshua R. Widhalm2,3, W Richard McCombie6, Gloria M Coruzzi1,* 9

10

1. Center for Genomics and Systems Biology, Department of Biology, New York 11

University, New York, NY 10003, USA 12

2. Department of Horticulture and Landscape Architecture, Purdue University, West 13

Lafayette, IN 47907, USA 14

3. Center for Plant Biology, Purdue University, West Lafayette, IN 47907, USA 15

4. School of Biological Sciences, The University of Queensland, St Lucia, QLD 16

4072, AUSTRALIA 17

5. BPMP, INRA, CNRS, Universite de Montpellier, Montpellier SupAgro, 34090 18

Montpellier, France 19

6. Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA 20

*Corresponding authors 21

22

ONE-SENTENCE SUMMARY: Nitrogen nutrient can trigger changes in chromatin 23

modifications, thus affecting RNA processing, metabolism and growth in plants. 24

25

AUTHOR CONTRIBUTIONS 26

The work was designed by GMC and YL. YL, MB, JYW, RMM, TR, AP, RMP, and SR 27

performed experiments. YL, MB, JYW, RMM, CIM, MT, SR, JRW, and GMC contributed 28

to the data analysis. WRM performed the sequencing. YL, MB, JYW, RMM, SR, and 29

GMC wrote the manuscript. GMC and MT critically revised the manuscript. All authors 30

edited and approved the manuscript. 31

Plant Physiology Preview. Published on October 22, 2019, as DOI:10.1104/pp.19.00682

Copyright 2019 by the American Society of Plant Biologists

www.plantphysiol.orgon June 11, 2020 - Published by Downloaded from Copyright © 2019 American Society of Plant Biologists. All rights reserved.

http://www.plantphysiol.org

2

32

Funding information: This work is supported by Department of Energy (DE-FG02-33

92ER20071 to GMC), National Science Foundation (MCB 1412232 to GMC), USDA 34

National Institute of Food and Agriculture (Hatch project numbers 1013620 to YL, and 35

177845 to JRW), and start-up funds from Purdue University to YL and JRW. 36

37

Email address of Author for Contact: Dr. Gloria Coruzzi, [email protected] and Dr. 38

Ying Li, [email protected]. 39

40

41

ABSTRACT 42

Chromatin modification has gained increased attention for its role in the regulation of 43

plant responses to environmental changes, but the specific mechanisms and molecular 44

players remain elusive. Here, we show that the Arabidopsis (Arabidopsis thaliana) 45

histone methyltransferase SET DOMAIN GROUP 8 (SDG8) mediates genome-wide 46

changes in H3K36 methylation at specific genomic loci functionally relevant to nitrate 47

treatments. Moreover, we show that the specific H3K36 methyltransferase encoded by 48

SDG8 is required for canonical RNA processing, and that RNA isoform switching is 49

more prominent in the sdg8-5 deletion mutant than in the wild type. To demonstrate that 50

SDG8-mediated regulation of RNA isoform expression is functionally relevant, we 51

examined a putative regulatory gene, CONSTANS, CO-like and TOC1 101 (CCT101), 52

whose nitrogen-responsive isoform-specific RNA expression is mediated by SDG8. We 53

show by functional expression in shoot cells that the different RNA isoforms of CCT101 54

encode distinct regulatory proteins with different effects on genome-wide transcription. 55

We conclude that SDG8 is involved in plant responses to environmental nitrogen 56

supply, affecting multiple gene regulatory processes including genome-wide histone 57

modification, transcriptional regulation, and RNA processing, and thereby mediating 58

developmental and metabolic processes related to nitrogen use. 59

60

61


mailto:[email protected]

mailto:[email protected]


3

INTRODUCTION 62

Chromatin modifications have gained increasing attention for their roles in modulating 63

developmental and environmental responses across plant and animal kingdoms (Greer 64

and Shi, 2012; Khan and Zinta, 2016; Sirohi et al., 2016). In plants, environmental 65

signals such as light (Charron et al., 2009), drought (Chinnusamy and Zhu, 2009) and 66

temperature (Lamke et al., 2016) have been shown to affect histone modifications or 67

DNA methylation at functionally-relevant gene loci. While it is well known that nitrogen 68

(N) - especially nitrate - acts as a nutrient signal to trigger global reprogramming of 69

gene expression to optimize N uptake and assimilation (Vidal et al., 2015; Varala et al., 70

2018), little is known about the role of epigenetic regulation in N signaling. One report in 71

Arabidopsis (Arabidopsis thaliana) showed that high levels of nitrogen increased the 72

level of H3K27me3 at the Nitrate Transporter 2.1 (NRT2.1) gene locus, and this 73

increase was dependent on a Pol II complex protein HIGH NITROGEN INSENSTIVE 9 74

(HNI9) (Widiez et al., 2011). However, at the genome scale, our knowledge of the role 75

of chromatin modifications in nitrate or N signaling is limited. Here, we present data 76

which implicates the SET DOMAIN GROUP 8 (SDG8) protein as a specific histone 77

methyltransferase involved in mediating genome-wide responses to a changing nitrate 78

environment. 79

We initially uncovered genes involved in regulation of the N-assimilatory pathway 80

in Arabidopsis using a positive genetic selection for mutants impaired in the regulation 81

of the promoter of Asparagine synthetase 1 (ASN1), a key gene involved in the 82

assimilation of N into asparagine (Thum et al., 2008). This genetic selection uncovered 83

a mutant called sdg8-5 (formerly known as cli186 e.g. in Thum et al 2008), which we 84

later showed was deleted in a gene encoding the histone methyltransferase SDG8 (Li et 85

al., 2015). Despite the existence of 32 SDG proteins encoded in the Arabidopsis 86

genome (Springer et al., 2003), genetic studies show that SDG8 plays a non-redundant 87

role in histone methylation. Specifically, mutant analysis has associated SDG8 with 88

pleiotropic effects on plant growth and development, including early flowering (Soppe et 89

al., 1999; Kim et al., 2005; Zhao et al., 2005; Xu et al., 2008), impaired pigment 90

synthesis (Cazzonelli et al., 2009), enhanced shoot branching (Dong et al., 2008; 91



4

Cazzonelli et al., 2009), defects in pathogen defense (Berr et al., 2012; Lee et al., 92

2016), and an impaired touch response (Cazzonelli et al., 2014). Our previous study of 93

the sdg8-5 deletion mutant revealed that SDG8 is also associated with gene responses 94

to carbon and light signals (Li et al., 2015). Our genome-wide transcriptome and 95

epigenome profiling revealed that only a subset of genes lose H3K36me3 modification 96

in the sdg8-5 mutant, and this set of hypomethylated genes are enriched in specific 97

functional categories (photosynthesis, defense, N metabolism, development, etc) (Li et 98

al., 2015). Therefore, SDG8 is likely involved in regulating multiple processes with a 99

certain level of target specificity. Mechanistically, we showed that SDG8 is required for 100

depositing the H3K36me3 histone mark on the gene body, which is required to maintain 101

active expression of its target genes (Li et al., 2015). 102

In addition, several lines of evidence have linked SDG8 with N uptake and 103

assimilation: (i) SDG8 was identified as a regulator of a key N assimilation gene, ASN1, 104

in a mutant screen (aka the cli186 mutant) (Thum et al., 2008); (ii) N metabolism genes 105

are significantly over-represented among the validated genome-wide targets of SDG8 106

(Li et al., 2015); (iii) SDG8 is required to maintain the high expression level of genes in 107

the N uptake and assimilation pathways including the nitrate transporter (NRT1.5) and 108

glutamine synthetase genes (GLN1;1, GLN1;3, GLN1;4) (Li et al., 2015); (iv) SDG8 109

physically binds to the glutamine synthetase GLN1;1 gene locus (Li et al., 2015); (v) 110

SDG8 is required to maintain wild-type H3K36me3 levels at gene loci encoding nitrate 111

and nitrite reductases (NIA1; NIA2; NIR1) (Li et al., 2015); and (vi) the mRNA level of 112

SDG8 is induced by nitrate treatment, specifically in the lateral root cap and pericycle in 113

roots (Gifford et al., 2008). Despite this supportive evidence, it still remains unclear 114

whether SDG8 has a direct role in mediating genome-wide changes in response to 115

fluctuations in environmental N supply. Moreover, how and whether the H3K36me3 116

marks made by SDG8 in the gene body regulate gene expression remain unclear. 117

We previously showed that SDG8 has a preference for H3K36me3 in the gene 118

body, suggesting its role in histone methylation that mediates transcriptional elongation 119

or co-transcriptional RNA processing (Li et al., 2015). This is consistent with the role of 120

SETD2, the Arabidopsis SDG8 homolog in mammals, which prevents transcripts from 121



5

starting in the middle of the gene body (Simon et al., 2014). In Arabidopsis, H3K36me3 122

and SDG8 were reported to affect RNA splicing of genes during responses to 123

temperature (Pajoro et al., 2017). Alternative splicing of RNAs promotes the diversity of 124

the transcriptome, which was recently shown to be involved in mineral nutrient signaling 125

such as phosphate signaling (Dong et al., 2018). Therefore, these findings beg the 126

questions whether and how SDG8 mediates RNA processing during nitrate signaling. 127

In this study, we investigated whether the response to nitrate treatment at a 128

genome-wide scale is mediated through chromatin modifications, especially through 129

histone H3K36me3 modification by SDG8, and what impacts this may have on gene 130

expression, especially RNA processing. We hypothesized that SDG8, and the 131

H3K36me3 marks it makes on histones associated with specific N-related genes, play a 132

role in regulating gene responses to N signals, thus affecting physiological responses to 133

N treatment. To test this hypothesis, we compared the N-induced genome-wide 134

H3K36me3 patterns, transcriptome responses including RNA isoform specific gene 135

expression, and physiological responses, between the sdg8-5 deletion mutant (Thum et 136

al., 2008; Li et al., 2015) and its corresponding wild type (WT), in the presence or 137

absence of a N-treatment. Our results show that the sdg8-5 mutant displays impaired 138

H3K36me3 responses at genomic loci functionally relevant to nitrate uptake and 139

assimilation, as well as reduced metabolic and developmental responses to N 140

treatments. We also show that N-responsive transcriptional reprogramming and RNA 141

isoform switching (i.e. differential production of distinct transcript isoforms under 142

different N conditions) are altered in the sdg8-5 mutant. Finally, we investigated the 143

relevance of SDG8-mediated RNA isoform switching of CCT101, a putative CCT motif 144

regulatory gene, which we functionally validated in shoot cells. We also demonstrated 145

physiological relevance of SDG8 to N responses in planta. Overall, our results support 146

the idea that the histone methyltransferase encoded by SDG8 is required for plants to 147

respond to N signals, affecting genome-wide histone modification, transcriptomic 148

response, and RNA isoform processing, as well as modulating root development, nitrate 149

uptake, and primary metabolism. 150

RESULTS 151



6

152

SDG8 mediates changes in histone modifications in response to N treatments 153

SDG8, a histone methyltransferase required for deposition of the histone mark 154

H3K36me3 (Li et al., 2015), was initially uncovered in a screen for mutants impared in 155

the regulation of ASN1, a key gene involved in N-assimilation (Thum et al., 2008). We 156

thus tested the hypothesis that SDG8 mediates genome-wide changes of H3K36me3 in 157

genes functionally relevant to response to nitrate treatments. To do this, we exposed 158

the sdg8-5 mutant and its WT control to nitrate treatments, as previously described 159

(Wang et al., 2001; Wang et al., 2003). Briefly, seeds were sown on nitrate-free media 160

(0.5 mM NH4 succinate) for two weeks, followed by nitrogen starvation for 24 hours, 161

before transferring to either 5 mM KNO3 or 5 mM KCl treatments. After 5-hr of nitrate vs. 162

control treatments, the shoots were harvested for histone ChIP-Seq to profile the global 163

pattern of H3K36me3 (Supplemental Fig. S1). Two independent biological replicates 164

were performed for ChIP-Seq. The raw sequencing reads were first trimmed and 165

mapped to the Arabidopsis genome using Bowtie (Langmead et al., 2009). The mapped 166

reads were used to call significant H3K36me3 islands and significantly differentially 167

methylated islands using SICER (Zang et al., 2009). To synthesize the output from the 168

two biological replicates, a nitrate-responsive differentially-methylated gene had to be 169

identified as significantly different (FDR <0.05) in both replicates, and the mean fold 170

change of enrichment of the two replicates had to be greater than 1.2, a cutoff that was 171

chosen based on our previous study (Li et al., 2015) to reflect the dynamic range and 172

stability of the H3K36me3 mark (see methods for details). 173

174

Our results showed that nitrate treatment caused changes in the H3K36me3 175

levels of 196 genes in WT, but only 26 genes in the sdg8-5 mutant (Fig. 1). In detail, in 176

WT, 143 genes show increased H3K36me3 in the N starvation group compared to the N 177

supply group (Fig. 1; Supplemental Table S1). These 143 genes are significantly 178

enriched for GO terms “response to nitrogen starvation”, “defense response”, and 179

“response to stress”, (FDR<0.05; Supplemental Table S2). This group of genes includes 180

WRKY transcription factors and a nuclear transcription factor Y family gene, which were 181

previously reported to control N starvation (Krapp et al., 2011) and stress responses 182



7

(Phukan et al., 2016). In WT, we also identified 53 genes with increased H3K36me3 in 183

the N supply group compared to the N starvation group (Fig. 1; Supplemental Table 184

S1). This group includes genes involved in nitrate reduction (G6PD3 and UPM1), 185

nitrogen assimilation (Asparagine synthetase ASN2), regulators of N signaling including 186

HHO2 (Medici et al., 2015) and CIPK3 (Canales et al., 2014), and genes responsive to 187

cytokinin (Arabidopsis Response Regulator ARR7, ARR8, and ARR9) – a downstream 188

signal in the N response (Sakakibara et al., 2006). Significantly enriched GO terms 189

identified among this group of genes include “response to circadian rhythm”, “cytokinin 190

stimulus”, “phosphorelay”, and “sulfate assimilation” (FDR<0.05; Supplemental Table 191

S3). These GO terms have functional relevance to N responses in plants, as cytokinin 192

(Sakakibara et al., 2006) and phosphorelay signaling (Engelsberger and Schulze, 2012) 193

are known to mediate N signaling, and N was previously reported to regulate circadian 194

rhythm (Gutiérrez et al., 2008) and sulfate assimilation (Wang et al., 2003). Overall, 195

these results support that genes relevant to N signaling, reduction, and assimilation are 196

regulated at the chromatin level through H3K36me3 modification in response to 197

changes of N levels in WT plants. In contrast, the N-mediated modification of these N-198

relevant target genes in WT are abrogated in the sdg8-5 mutant. Instead, in the sdg8-5 199

mutant the changes of H3K36me3 occur at a different set of genes in response to N 200

starvation (3 genes) or N supply (23 genes), respectively (Fig. 1; Supplemental Table 201

S4), with no significant enrichment of GO terms. 202

203

In summary, our comparative analyses identified 143 genes whose H3K36me3 204

levels are increased by N starvation in WT, and this response is abrogated in the sdg8-205

5 mutant (Fig. 1). Similarly, we identified 53 genes whose H3K36me3 levels are 206

increased by N supply in WT, but this response is abrogated in the sdg8-5 mutant (Fig. 207

1). We collectively call this group of 196 genes (143 and 53 genes, Fig. 1) “SDG8-208

dependent Differentially Methylated Genes (DMGs)”. 209

210

To determine whether these SDG8-dependent DMGs are directly or indirectly 211

regulated by SDG8, we compared the list of 196 SDG8-dependent DMGs with the set of 212

genes shown to be directly bound targets of SDG8, as previously determined under 213



8

highly comparable experimental conditions (Li et al., 2015). This analysis showed that a 214

modest, but statistically significant portion of the 196 SDG8-dependent DMGs were 215

indeed directly bound by SDG8 (Li et al., 2015), (28/196, 14% overlap with an 216

enrichment p-val < 0.001, Supplemental Fig. S2). This significant enrichment provides 217

support that the differential H3K36me3 in response to nitrogen is at least partially 218

attributed to a direct role of SDG8. It is likely that some of the “unbound” DMGs may 219

also be direct targets of SDG8, but they could not be identified by the SDG8 binding 220

assay, which requires stable binding. These false negatives may occur, as the ChIP-221

Seq assay - performed at a given timepoint - identifies only a subset of the bona fide 222

targets, because the interaction of a regulatory protein (in this case an HMT enzyme) to 223

its target genes is a dynamic process (Swift and Coruzzi, 2016). Lastly, a portion of the 224

SDG8-dependent DMGs could be regulated by SDG8 indirectly, i.e. through an 225

intermediate partner. Moreover, we also observed a significant overlap between the 196 226

SDG8-dependent DMGs and a list of 4,058 genes that display significantly less 227

H3K36me3 in the sdg8-5 mutant compared to WT (overlap p <0.001; Fig. 1; 228

Supplemental Results; Supplemental Table S5). In summary, our results suggest that 229

SDG8 controls N-responsive changes in H3K36me3 at a set of functionally relevant 230

genomic loci. 231

232

SDG8 affects transcriptomic responses to N treatments 233

To determine whether and how histone methylation mediated by SDG8 affects the 234

transcription of N-responsive genes, we performed RNA-Seq to compare these 235

responses in the sdg8-5 mutant and WT exposed to nitrate treatments (Supplemental 236

Fig. S1). Specifically, we identified two types of SDG8-mediated regulation of gene 237

transcription: (i) differentially expressed genes (DEGs) that are regulated by SDG8 in 238

the context of nitrate treatment (i.e. genotype x treatment); and (ii) genes whose RNA 239

isoform switching is affected by the deletion of SDG8 in the sdg8-5 mutant. 240

241

Overall, our RNA-Seq analysis supports the notion that SDG8 mediates N-242

triggered reprogramming of gene expression. Specifically, the RNA-Seq reads were first 243

trimmed and mapped to the Arabidopsis TAIR10 genome using the TopHat suite 244



9

(Trapnell et al., 2012). The gene counts were generated by HTSeq (Anders et al., 245

2015), and then processed by DESeq2 (Love et al., 2014) with the design 246

(~Genotype+Treatment+Genotype:Treatment) to detect differentially expressed genes. 247

Genes that are regulated by the interaction of nitrogen and genotype were determined 248

based on p-value for Genotype:Treatment interaction, which was adjusted for multi-249

testing error using false discovery rate (FDR) and controlled at 5%. In total, we identified 250

215 DEGs regulated by the interaction of SDG8 genotype and N treatment using the 251

two-factor design by DESeq2 (FDR<0.05; Fig. 2; Supplemental Table S6). This analysis 252

identified genes whose regulation by nitrate is different in WT compared to the sdg8-5 253

deletion mutant. Among this group of misregulated genes are Asparagine Synthase 1 254

(ASN1) – whose promoter was used to isolate the original sdg8-5 mutant (aka cli186) 255

(Thum et al., 2008), as well as genes encoding nitrate transporters (NRT2.1 and 256

NRT1.5) and glutamine synthetase (GLN1;4). Next, using hierarchical clustering, we 257

identified two major clusters of the 215 DEGs. Cluster 1 comprised 126 genes that are 258

highly induced by N starvation in WT, but not in the sdg8-5 mutant (Fig. 2; 259

Supplemental Table S6). The enriched GO terms for this group include “cellular amino 260

acid derivative metabolic process” (FDR<0.0019), “response to nutrient level” 261

(FDR<0.039), and “cellular nitrogen compound metabolic process” (FDR<0.047) 262

(Supplemental Table S7). These Cluster 1 genes whose N-response is misregulated in 263

sdg8-5 share a significant overlap (p<0.001, 6 genes) with the genes that display higher 264

H3K36me3 under the N-starved condition than the N-supplied condition (Fig. 2). This 265

finding for the 126 cluster 1 genes suggests that SDG8 affects the expression of these 266

N-responsive genes through regulating the histone mark H3K36me3, which is known to 267

be associated with actively transcribed genes (Bannister et al, 2005). Cluster 2 contains 268

89 genes induced by N supply in WT, which is abolished or attenuated in the sdg8-5 269

mutant (Fig. 2; Supplemental Table S6). Over-represented GO terms in cluster 2 270

include “cellular amine metabolic process” (FDR<0.0056) and “amino acid transport” 271

(FDR<0.016) (Supplemental Table S8). Similarly, the cluster 2 genes share a significant 272

overlap (p<0.001, 5 genes) with genes that exhibit higher H3K36me3 under N-supplied 273

conditions than N-starved conditions (Fig. 2). Overall, the 215 DEGs have a significant 274

overlap with genes directly bound by SDG8 (Li et al., 2015) (30/215, overlap p < 0.024), 275



10

supporting a direct role of SDG8 in regulating this set of SDG8-dependent DEGs. The 276

215 DEGs also have a significant overlap with the 4,058 H3K36 hypomethylated genes 277

(74/215, overlap p < 0.001). Together, these results support that histone methylation by 278

SDG8 regulates transcriptional reprogramming of functionally relevant genes during 279

nitrate treatments. 280

281

SDG8 affects RNA isoform switching in response to N-treatments. 282

Next, because SDG8 mediates H3K36me3 preferentially in the gene body (Li et al., 283

2015), we investigated the role that SDG8 might play in regulating the preferential 284

expression of transcript isoforms in responses to nitrate treatments. To do this, we first 285

tested whether nitrate treatments preferentially regulate expression of specific RNA 286

isoforms in WT plants. We found 26 genes that switched isoform preference between N-287

supplied and N-starved samples (Fig. 3; Supplemental Table S9). Notably, under the N-288

starved condition, the AT3G54830 gene locus is transcribed as a shorter transcript 289

isoform that skips the first four exons, while the longer transcript isoform (with 12 exons) 290

is produced in response to N supply (Fig. 4). This longer isoform encodes a protein that 291

shares high structural similarity with an amino acid/polyamine/organocation 292

transmembrane transporter with ten transmembrane α-helices (Shaffer et al., 2009) 293

(Fig. 4; confidence level 99.9% determined by Phyre2 (Kelley et al., 2015)). Under the 294

N-starved condition, the shorter RNA isoform encodes a truncated putative 295

transmembrane protein that is missing the four N-terminal exons, and the predicted 296

protein structure contains only seven transmembrane α-helices (Fig. 4). Further studies 297

are required to elucidate if there is any functional difference between the putative 298

transmembrane proteins encoded by these two mRNA isoforms of a putative amino acid 299

transporter. 300

301

Interestingly, deletion of SDG8 greatly increases the number of genes with N-302

triggered isoform switches, from 26 in WT to 144 in the sdg8-5 deletion mutant (Fig. 3; 303

Supplemental Table S9). This suggests that SDG8 normally plays a role in maintaining 304

the stability of RNA isoform expression from specific gene loci when plants experience a 305

change in the N environment. In contrast, in the sdg8-5 mutant, the RNA isoform 306



11

expression is more likely to alter when plants experience a change in the N 307

environment. Comparison of these two gene lists leads to the identification of 137 genes 308

with RNA isoform switches in the sdg8-5 mutant, but not in WT in response to N supply 309

(Fig. 3; Supplemental Table S9). Overall, we refer to this group of 137 genes as “sdg8-310

dependent isoform-switched genes”. As a group, the sdg8-dependent isoform-switched 311

genes are enriched with functional annotations such as “nucleotide binding” (FDR< 312

0.0011 determined by AgriGO (Tian et al., 2017)) and “membrane/transmembrane” 313

(determined by GeneCloud (Krouk et al., 2015)) (Fig. 3). Transmembrane transport and 314

nucleotide metabolism were also identified as enriched functional groups among 315

alternatively spliced genes involved in maintaining nutrient homeostasis in rice (Dong et 316

al., 2018). In summary, our results indicate that the histone methyltransferase SDG8 317

affects differential RNA isoform production in response to changes in nutrient levels. 318

319

The histone methyltransferase SDG8 affects RNA isoform switching of CCT101 320

which influences its regulatory function 321

We next investigated whether sdg8-dependent RNA isoform switching is related to 322

SDG8-dependent H3K36 methylation. To do this, we compared the gene list of sdg8-323

dependent isoform-switched genes with H3K36 hypomethylated genes in the sdg8-5 324

deletion mutant (Supplemental Table S5). We found a significant overlap between these 325

SDG8 dependent genes (overlap p < 0.002, 32/137 genes), which suggests that SDG8-326

mediated H3K36me3 in the gene body is associated with the RNA isoform switch of its 327

target genes. An example downstream target gene, which encodes a CCT motif protein 328

(CONSTANS, CO-like and TOC1 motif; AT5G53420) (Brambilla and Fornara, 2017), is 329

referred to as CCT101 hereinafter. To study the functional relevance of RNA isoform 330

switches associated with SDG8 targets, we performed functional studies on the 331

CCT101 RNA isoforms as a case study example. 332

333

CCT101 belongs to the ASML2 family of CCT domain proteins (Brambilla and 334

Fornara, 2017). The best studied member of this family is ASML2 (Activator of 335

Spomin::LUC2), which is a regulatory protein that activates expression of sugar-336

responsive genes (Masaki et al., 2005). In the sdg8-5 mutant, the H3K36me3 marks 337



12

associated with the CCT101 locus are significantly lower, compared to WT (FDR<0.05; 338

Fig. 5). Moreover, the H3K36me3 level associated with the CCT101 gene locus which 339

increases in response to N starvation in the WT, is abrogated in the sdg8-5 mutant 340

(FDR<0.05; Fig. 5). CCT101 has three isoforms based on the TAIR10 annotation 341

(www.arabidopsis.org) (Fig. 5). In our RNA-Seq analysis, we captured all three CCT101 342

RNA isoforms and also found support for an additional isoform that is expressed at very 343

low levels (Fig. 5). CCT101.1, the longest transcript isoform, is the dominantly 344

expressed isoform, while the RNA isoform CCT101.2 is truncated at the 5’ end and is 345

expressed at a lower level (Fig. 5). Interestingly, in the sdg8-5 mutant, the proportions of 346

CCT101.1 and CCT101.2 RNA isoforms change significantly in response to nitrate 347

treatment (FDR=0.02; Fig. 5). In WT, the change in the proportions of CCT101.1 and 348

CCT101.2 RNA isoform due to N treatment is not statistically significant. These data 349

support the notion that SDG8 affects the preferential accumulation of RNA isoforms 350

CCT101.1 and CCT101.2 in response to N-treatment. 351

352

To understand the functional implications of RNA isoform switching of CCT101, 353

we analyzed the regulatory role of the proteins encoded by the two RNA isoforms 354

CCT101.1 and CCT101.2. To do this, we tested their functionality using a plant cell-355

based transient over-expression system called TARGET (Bargmann et al., 2013). In 356

detail, the CCT protein encoded by each of the RNA isoforms was transiently over-357

expressed in Arabidopsis shoot protoplasts, and following controlled nuclear import, the 358

resulting effect of the CCT protein on genome-wide expression was assayed by RNA-359

Seq in three treatment replicates (see Methods). The experiments were performed on 360

the same day using the same batch of protoplasts to ensure that the effect of different 361

CCT isoforms can be directly compared. The overexpression of the protein encoded by 362

the CCT101.1 RNA isoform led to the up-regulation of 341 genes and down-regulation 363

of 122 genes in shoot protoplasts (FDR<0.05, fold-change>2) (Fig. 5; Supplemental 364

Table S10). By contrast, the protein encoded by the CCT101.2 RNA isoform up-365

regulates 414 genes and down-regulates 105 genes (FDR<0.05, fold-change>2) (Fig. 5; 366

Supplemental Table S10). Comparisons of these gene lists indicate that the two 367

CCT101 RNA isoforms encode proteins that regulate overlapping, yet distinct gene 368



13

targets (Fig. 5; Supplemental Table S10). Moreover, genes regulated by one CCT 369

isoform but not by the other isoform have different enriched GO terms compared to the 370

genes regulated by both isoforms (Fig. 5; Supplemental Table S10), suggesting that the 371

proteins encoded by the two CCT isoforms perform related, yet different, functions. 372

373

Physiological responses to nitrate are abrogated in the histone methyltransferase 374

mutant sdg8-5 375

We next set out to test whether the SDG8-mediated changes in histone methylation and 376

RNA isoforms in response to N-treatment have an impact on nitrogen-related 377

phenotypic responses in planta. To do this, we first examined whether the sdg8-5 378

deletion mutant shows altered physiological responses to nitrate treatments. The sdg8-5 379

mutant and its corresponding WT strain (Li et al., 2015) were grown on ammonium 380

succinate for ten days and then transferred to either low N (0.5 mM KNO3) or high N (5 381

mM KNO3) medium (see Methods). Five to six days after the transfer, we measured 382

chlorophyll content, root architecture, N uptake, and free amino acids. We found that 383

WT plants grown under high N conditions showed significantly enhanced lateral root 384

growth on the nascent primary root (Fig. 6), as well as elevated chlorophyll levels in the 385

shoots (Fig. 6), compared to low N treatment conditions. By contrast, these responses 386

to high N seen in WT were abrogated in the sdg8-5 deletion mutant (Fig.6). The sdg8-5 387

mutant also showed altered N acquisition and free amino acids compared to WT 388

(Supplemental Fig. S3). The sdg8-5 mutant had lower nitrate acquisition than WT plants 389

under the high N condition (Supplemental Fig. S3). Although the total amount of free 390

amino acids was comparabe between WT and the sdg8-5 deletion mutant 391

(Supplemental Fig. S3), free leucine was significantly higher in the sdg8-5 mutant 392

compared to WT under the low N condition (Supplemental Fig. S3), and gamma-393

aminobutyric acid (GABA), a non-proteinogenic amino acid, was significantly induced by 394

N supply in the sdg8-5 mutant but not in WT (Supplemental Fig. S3). In summary, our 395

data support the idea that deletion of the specific histone methyltransferase encoded by 396

SDG8 affects plant physiological responses to nitrate at many different levels. 397

398

DISCUSSION 399



14

Chromatin modifications including histone modifications have been reported as an 400

additional regulatory layer of plant responses to environmental fluctuations (Charron et 401

al., 2009; Kim et al., 2010). However, the mechanisms through which a specific histone 402

modifying protein affects gene transcription and/or RNA processing in response to 403

environmental change is largely unknown. In this study, we addressed the role of 404

epigenetics in the regulation of RNA isoforms in response to the nutrient environment by 405

demonstrating that the sdg8-5 mutant, with a deletion of a specific histone 406

methyltransferase, displays alterations in the genome-wide H3K36me3 landscape, 407

transcriptome, and RNA isoform expression in response to nitrate treatments, as well as 408

impaired physiological and metabolic responses to N nutrient treatments. Overall, our 409

study links a specific chromatin modification and histone methyltransferase with RNA 410

processing and nitrate responses in plants. 411

412

Our previous studies showed that loss of H3K36 methylation in the gene body of 413

SDG8 targets in the sdg8-5 mutant is associated with down-regulation of gene 414

expression (Li et al., 2015). Our current study has now tested the hypothesis that the 415

histone methylation marks made by SDG8 in the gene body are also able to impact 416

qualitative transcriptomic changes via affecting RNA isoform switches. This hypothesis 417

was inspired by our previous observation that SDG8 is associated with H3K36me3 in 418

the gene body (Li et al., 2015), indicating a potential role for SDG8 in transcriptional 419

elongation or co-transcriptional splicing. This notion was also supported by a recent 420

study showing that H3K36me3 alters alternative RNA splicing of genes in the 421

temperature response (Pajoro et al., 2017), and by findings that the yeast SET2 protein, 422

a homolog of Arabidopsis SDG8, prevents spurious transcripts from starting in the 423

middle of a gene (Carrozza et al., 2005). Moreover, SETD2, the mammalian homolog of 424

Arabidopsis SDG8, is associated with proper RNA processing including the choice of 425

transcription start site and exon-intron splicing (Simon et al., 2014). We thus tested the 426

hypothesis that SDG8 plays a role in RNA processing in nutrient signaling in 427

Arabidopsis. Our results indeed suggest that the Arabidopsis SDG8 protein affects RNA 428

processing in transcriptional responses to N treatments. 429

430



15

How do SDG8 and H3K36me3 affect the production of RNA isoforms? In yeast, 431

the H3K36 methylation deposited in the gene body by SET2 (homolog of SDG8) 432

suppresses histone acetylation in the middle of a gene, thus preventing transcription 433

from alternative start sites (Carrozza et al., 2005). It is possible that Arabidopsis SDG8 434

functions similarly to its yeast homolog, and this hypothesis could be tested by 435

performing ChIP-Seq for histone acetylation in the sdg8-5 mutant. Alternatively, 436

H3K36me3 might differentially “mark” histones associated with exons and introns, thus 437

guiding spliceosome machinery for proper splicing. In line with this hypothesis, we found 438

that there is a minor, but significant, enrichment of H3K36me3 deposited by SDG8 in 439

the exons compared to the introns (p-value <0.005), based on our epigenome data (Li 440

et al., 2015). In addition, we speculate that the H3K36me3 marks mediated by SDG8 441

could change the rate of Pol-II mediated transcription, which was shown to affect the 442

fidelity of splicing in yeast (Aslanzadeh et al., 2018). 443

444

To further investigate how SDG8-mediated RNA isoform preference can affect 445

protein function, we focused our functional validation on one putative regulatory protein, 446

CCT101. We found that SDG8 affects the level of H3K36me3 associated with the 447

CCT101 locus. Specifically, a reduced H3K36me3 mark at the CCT101 locus favors the 448

transcription of the short RNA isoform (CCT101.2), while high levels of H3K36me3 are 449

associated with the transcription of the long RNA isoform (CCT101.1). The missing N-450

terminal polypeptide in the short RNA isoform CCT101.2 - relative to the longer isoform 451

CCT101.1 - is not predicted as a signal peptide by SignalP (Nielsen, 2017). Therefore, 452

the biochemical function of the missing N-terminal polypeptide requires further 453

investigation. To this end, we tested whether the protein encoded by the two CCT101 454

RNA isoforms have different regulated genome-wide targets using a transient 455

overexpression system in plant cells called TARGET (Bargmann et al., 2013). Our 456

TARGET studies show that both CCT101 isoforms can regulate hundreds of genes. 457

Specifically, the proteins encoded by the CCT101.1 and CCT101.2 RNA isoforms 458

regulate overlapping, as well as distinct downstream genes. Therefore, the RNA isoform 459

switch between CCT101.1 and CCT101.2 that is affected by SDG8 results in two 460



16

distinct functional CCT regulatory proteins that appear to regulate different sets of 461

downstream genes. 462

463

How do the genome-wide changes of histone marks that we attribute to SDG8 464

affect the nitrate response in plants at a physiological level? Previous studies showed 465

that levels of SDG8 mRNA are specifically induced in the root pericycle cells by a 466

supply of nitrate (Gifford et al., 2008). Since lateral root initiation occurs in the pericycle, 467

we tested if SDG8 is required for lateral root growth in response to a nitrate signal. We 468

observed that WT plants display an enhanced lateral root growth in the newly grown 469

primary root under high N relative to low N, and this morphological response to N 470

treatments is abolished in the sdg8-5 mutant (Fig. 6). Therefore, SDG8 indeed has a 471

role in mediating lateral root growth in response to N level changes. However, since the 472

H3K36me3 and transcriptome data in our current study were collected from the shoots, 473

an examination of H3K36 status of genes in roots could thus help to elucidate the role of 474

SDG8-mediated histone methylation in sensing and foraging for nitrate. 475

476

One of the many possible roles for SDG8 is that it might serve as an integration 477

point across inputs from photosynthesis, carbon metabolism, and nitrogen metabolism 478

(Thum et al., 2008; Li et al., 2015). Indeed, among the mis-regulated N-responsive 479

genes in the sdg8-5 mutant, GO terms related to response to sugar stimulus are 480

significantly enriched (Supplemental Table S7). In agreement with this role in nutrient 481

crosstalk, we observed that the chlorophyll level is increased by N supply in WT, but not 482

in the sdg8-5 mutant (Fig. 6). Therefore, the sdg8-5 mutant might not be able to provide 483

enough carbon skeletons and reducing power for nitrate assimilation when nitrate level 484

increases. This is supported by the observation that the sdg8-5 mutant has lower nitrate 485

acquisition than WT plants under the high nitrate condition (Supplemental Fig. S3). 486

Another piece of evidence comes from the free amino acid measurements comparing 487

the sdg8-5 mutant and WT plants. GABA, a non-proteinogenic amino acid, has a central 488

position in the interface between carbon and nitrogen metabolism, and is reported to 489

regulate genes involved in nitrogen metabolism and carbon metabolism (Barbosa et al., 490

2010). GABA is synthesized from the nitrogen donor glutamate and degraded into 491



17

succinate to enter the citric acid cycle to generate carbon molecules (Michaeli and 492

Fromm, 2015). In our study, GABA is significantly induced by N supply in the sdg8-5 493

mutant, but not in WT (Supplemental Fig. S3). Collectively, our results support the 494

notion of altered carbon/nitrogen balance in the sdg8-5 mutant deleted in the H3K36 495

methyltransferase, with impacts on gene expression, RNA processing, and 496

physiological responses to N treatment. 497

498

Conclusions 499

500

Our study shows that nitrate treatments induce genome-wide changes in the histone 501

mark H3K36me3 mediated by SDG8, with impacts on gene expression, RNA 502

processing, and physiological responses. This has revealed a previously overlooked 503

layer of chromatin regulation involved in nutrient signaling. To develop a comprehensive 504

understanding of the scope and function of chromatin regulation in nutrient signaling, it 505

is important that future studies expand to include more epigenetic marks, such as other 506

histone modifications (e.g. histone acetylation), chromatin landscape, and DNA 507

methylation. Such knowledge will reveal how chromatin modifiers could be harnessed 508

and engineered to enable a holistic N response in plants to increase nutrient use 509

efficiency. 510

511

MATERIALS AND METHODS 512

Plant growth for ChIP-Seq and RNA-Seq 513

Arabidopsis (Arabidopsis thaliana) sdg8-5 mutant (aka cli186) and corresponding wild 514

type (WT) (Li et al., 2015) seeds were surface sterilized and grown hydroponically in 515

phytatrays. In detail, approximately 200 seeds were sown onto a nylon mesh supported 516

by a plastic platform in a sterile phytatray filled with 200 ml plant growth media (1× basal 517

MS medium (GIBCO Formula# 97-5068EC), 3 mM sucrose, 0.5 mM NH4 succinate, 0.5 518

g/L MES hydrate, pH 5.8). The phytatrays were kept under white light (50µM•s-1•m-2) in 519

long-day cycle (16h Light/8h Dark) at 22ºC for 16 days. Next, plants were starved for 520

nitrogen for 24 hours in media which is identical to the growth media except for that the 521



18

0.5 mM NH4 succinate was removed. Next, half of the plants were exposed to nitrate-522

supplied condition (5 mM KNO3 added to the starvation solution). As controls, the other 523

half plants were exposed to the starvation medium with 5 mM KCl added. After 5 hours, 524

the plants were harvested for ChIP-Seq or RNA-Seq (Supplemental Fig. S1). 525

526

ChIP-Seq experiment 527

The H3K36me3 ChIP-Seq was performed as previously described (Li et al., 2015). Two 528

independent biological replicates were collected from shoot tissues. The ChIP-Seq 529

libraries for the first biological replicate were prepared as described in (Li et al., 2015) 530

and sequenced on an Illumina GAII platform with paired-end 75bp format at Cold Spring 531

Harbor Lab (Cold Spring Harbor, NY). The ChIP-Seq libraries for the second replicate 532

were barcoded with NEXTflex DNA Barcodes (Bioo Scientific, Austin, TX) and pooled to 533

sequence on an Illumina HiSeq platform with paired-end 100 bp format at Cold Spring 534

Harbor Lab. 535

536

ChIP-Seq analysis 537

For the first replicate of H3K36me3 ChIP-seq, 20-34 million raw reads were generated 538

for each sample. The raw reads were trimmed for adaptors and low quality using in-539

house Python and Perl scripts, and then mapped to the Arabidopsis genome (TAIR10) 540

using Bowtie (Langmead et al., 2009). On average, 89% of raw reads were mapped to 541

genome, while 78% raw reads mapped to chromosomes. The chromosome mapped 542

reads were used to call significant H3K36me3 islands and significantly differentially 543

methylated islands with H3K36me3 using SICER (Zang et al., 2009) as previously 544

described (Li et al., 2015). For the second replicate, 40-47 million raw reads were 545

generated for each library and 65% were mapped to the genome, while 57% were 546

mapped to chromosomes. The data analysis was performed in the same way as a 547

replicate one. The ChIP-Seq signal of the two replicates share a high similarity 548

(correlation coefficient=0.9 across all the identified islands). To combine the results from 549

the two replicates, a nitrate responsive DMG (differentially methylated gene) has to 550

pass the following criteria: i) identified as significantly different (FDR <0.05) for both 551

replicates, and ii) the mean fold change (N-supplied vs. N-starved) of Enrichment 552



19

(Enrichment=ChIP/Input) of the two replicates has to be greater than 1.2 for the 553

transient N treatment. We used a relatively low cutoff for fold change that is similar to a 554

previous study (Li et al., 2015) to detect H3K36me3 changes caused by N, because: (1) 555

compared to RNA-Seq analysis that samples multiple copies of a transcript in a cell, 556

histone ChIP-Seq samples only one copy of genomic DNA from a cell, therefore a 557

smaller dynamic range is expected; (2) the nitrate treatment is a transient treatment that 558

lasts for only a few hours; and (3) histone methylation compared to histone acetylation 559

is relatively stable during the time frame of our treatment (in hours) (Barth and Imhof, 560

2010). Nonetheless, changing the fold change cutoff from 1.0 to 2 revealed the same 561

trend, which is that WT shows more H3K36me3 changes in response to nitrate 562

treatment compared to the sdg8-5 mutant (Supplemental Fig. S4). 563

To identify hypomethylated genes, WT and sdg8-5 mutants were compared for 564

N-supplied and N-starved conditions separately, and then the overlap (approximately 565

90% overlap) between two conditions was identified. The analysis regarding biological 566

replicates and statistical cutoff was similar to determining the nitrate-responsive DMGs 567

described above, with fold change of enrichment greater than 2 as the cutoff, because 568

the difference between WT and mutant is a long-term effect compared to the transient N 569

treatment. 570

571

Gene overlap analysis 572

The significance level of overlap between two gene lists was calculated by Genesect 573

tool within the VirtualPlant platform (Katari et al., 2010). Genesect is a non-parametric 574

randomization test to determine whether an overlap between two gene lists is 575

significantly higher or lower than by chance. 576

577

RNA-Seq experiments 578

Three biological replicates of plant shoot tissues were harvested for each genotype and 579

treatment, while each biological replicate is a pool of approximately 200 seedlings. Total 580

RNA samples were extracted using RNeasy Plant Mini kit (Qiagen, Hilden, Germany) 581

following the manufacturer's instruction. The quality and quantity of RNA were 582

determined using a Bioanalyzer (Agilent Genomics, Santa Clara, CA). 9 µg total RNA of 583



20

each sample was used to prepare an RNA-Seq library using a home-made protocol 584

(Wang et al., 2011). The RNA-Seq libraries were barcoded with the NEXTflex DNA 585

Barcodes. 12 libraries were pooled and sequenced in one lane of the Illumina Hi-Seq 586

platform with the paired-end 100bp format at Cold Spring Harbor Lab. 587

588

RNA-Seq analysis 589

15 million to 20 million read pairs were generated for each RNA-Seq library. The reads 590

were trimmed for quality and adaptor using an in-house Python script. The trimmed 591

reads were then mapped to the Arabidopsis TAIR10 genome using the TopHat suite 592

(Trapnell et al., 2012). On average, 81% of the raw read pairs were mapped to the 593

genome concordantly. Next, two analysis pipelines were performed to answer two 594

different questions: i) to identify differentially expressed genes (DEG) using DESeq2 595

(Love et al., 2014); and ii) to identify alternative splicing genes (ASG) using the cuffdiff 596

function in the Cufflinks package (Trapnell et al., 2012). For the first pipeline, the gene 597

counts were generated by HTSeq (Anders et al., 2015). The raw gene counts were then 598

processed by DESeq2 with the design (~Genotype+Treatment+Genotype:Treatment). 599

Note that DESeq2 deals with normalization and low counts filtering internally (Love et 600

al., 2014). To identify genes that are regulated by the interaction of nitrogen and 601

genotype, p-value for NxG interaction was adjusted for multi-testing with false discovery 602

rate (FDR) controlled at 5%. For the second pipeline to detect alternative spliced 603

isoforms, the mapped reads were assembled into transcriptome (to detect new splicing 604

events), and gene counts were generated using Cufflinks (Trapnell et al., 2012). The 605

cuffdiff function in the Cufflinks package was used to call genes with alternative splicing 606

between N-supplied groups and N-starved groups, in three categories (alternative 607

promoter use, alternative splicing from the same primary transcript, and alternative 608

coding sequence (CDS)) with significance cutoff FDR < 0.1 (Trapnell et al., 2012). The 609

conclusion remains the same if a different statistical cutoff such as FDR 5% is used. 610

Note that cuffdiff only considers genes with high read counts for the alternative splicing 611

analysis, therefore, the number of genes considered for the alternative splicing analysis 612

is ~2000 for alternative promoter use, ~5800 for alternative splicing from the same 613

primary transcript, and ~1800 for alternative CDS output. Therefore, the actual number 614



21

of significant alternative splicing events is likely to be higher. To confirm the alternative 615

splicing analysis by Cufflinks, we also analyzed the same RNA-Seq data with DEXSeq 616

(Anders et al., 2012) for differential exon usage. The conclusion was also supported by 617

DEXSeq analysis. 618

619

Plant growth for N response phenotyping 620

The sdg8-5 mutant and the corresponding wild type (WT) were surface sterilized and 621

planted on growth medium as below (unless indicated otherwise): 1× nitrate-free 622

Murashige and Skoog medium [Caisson MSP10], 3 mM sucrose, 0.5 mM ammonium 623

succinate, 0.5 g/L sodium MES (sodium 2-(N-Morpholino)ethanesulfonic acid), 100 624

mg/L I-inositol, 0.5 mg/L niacin, 0.5 mg/L pyridoxine HCl, 0.1 mg/L thiamine HCl, and 625

1% (w/v) agar, pH 5.8. The seeds were stratified at 4˚C in dark for four days and then 626

moved to a Percival growth chamber at 22˚C, with a light cycle of 16h light / 8h dark 627

with 50 µM•s-1•m-2 light. The plants were grown vertically on plates. After 10 days, the 628

plants were transferred to two groups of vertical plates, with high N and low N 629

treatments, separately. The high N and low N plates are identical to the growth plates, 630

except for that the 0.5 mM ammonium succinate was replaced by either 5 mM (for high 631

N) or 0.5 mM KNO3 (for low N, with an additional 4.5 mM KCl to balance). For the 15N 632

analysis, the KNO3 was spiked with 1% (v/v) K15NO3 to allow analysis of N uptake. The 633

roots were scanned 5 days after the treatment for root architecture analysis, while the 634

chlorophyll measurement (N=6, individual plants), 15N measurement (N=6, individual 635

plants), and amino acid profiling (N= 3-5, pooled 150 seedlings) were performed 6 days 636

after the treatment. For the amino acid profiling experiment, the plants were first grown 637

with the following nutrients: 1× nitrate-free Murashige and Skoog medium [Caisson 638

MSP10], 3 mM sucrose, 0.5 mM ammonium succinate, 0.5 g/L NaMES, and 1% (w/v) 639

agar, with pH 5.8, and then transferred to high N or low N plates where 0.5 mM 640

ammonium succinate was replaced by either 5 mM KNO3 or 0.5 mM KNO3 641

supplemented with 4.5 mM KCl. 642

643

15N analysis 644



22

After 6 days of N treatments (with 5 or 0.5 mM KNO3 spiked with 1% v/v K15NO3), plants 645

were analyzed for net 15NO3- uptake. Individual seedlings were first rinsed in 0.1 mM 646

CaSO4, and then placed in pre-weighed tin capsules (CE Elantech, NJ), left at 70˚C 647

oven for 48 hrs. Dry weight was determined and the total nitrogen and atom % 15N were 648

analyzed by continuous-flow isotope ratio mass spectrometer, using a Euro-EA Euro 649

Vector elemental analyzer coupled with an IsoPrime mass spectrometer (GV 650

Instruments). 651

652

Chlorophyll analysis 653

Individual seedling was weighed, flash frozen in 1.5 ml tubes and ground to powder 654

using tissuelyzer (Qiagen). Next, 300 µl methanol was added to each sample and tubes 655

were rotated for 10 min at room temperature. The lysate was then centrifuged at 14,000 656

rpm for 5 minutes, and 200 µl supernatant was transferred and measured with an 657

Infinite M200 plate reader for Absorbance at 750nm, 665nm and 652nm, with methanol 658

as the background controls. The chlorophyll content was calculated as previously 659

described (Porra, 2002). For the high N vs low N experiment, six individual seedlings 660

were analyzed for each genotype/condition. 661

662

Root architecture analysis 663

After transferring the seedlings to high N and low N plates, the end of each primary root 664

was marked with a permanent marker on the plate, to allow measurement of newly 665

grown roots. After 5 days in high N vs low N condition, the roots were scanned, and the 666

resulting images were analyzed using ImageJ (imagej.nih.gov/ij/). The root 667

measurements generated by ImageJ were summarized and analyzed using in-house 668

Perl and R scripts. 669

670

Amino acid profiling 671

Approximately 150 seedlings were pooled for each replicate per genotype and per N 672

condition. In total, three to five replicates were analyzed per genotype and per condition. 673

Amino acid profiling was performed as previously described (McCoy et al., 2018). 674

Briefly, shoots were extracted in 10 ml of methanol. The neutral and basic amino acids 675



23

were separated from acidic amino acids in order to measure glutamate and aspartate 676

separately from glutamine and asparagine. Free amino acids were then derivatized with 677

heptafluorobutyric acid and analyzed via GC-MS. Pools were quantified in reference to 678

external standards using ⍺-amino-butyrate for neutral and basic amino acids and ⍺-679

amino-adipate for glutamate and aspartate. Pyroglutamate was identified and added to 680

the glutamine abundance. B-cyanoalanine was also identified and added to the 681

asparagine abundance. The resulting measurements were normalized to fresh weights. 682

The significance of difference between nitrate treatments and genotypes was 683

determined by t-test as well as two-way ANOVA (genotype * nitrate). Only amino acids 684

that show significant p-value for genotype difference in both t-test and ANOVA are 685

reported (p<0.05). 686

687

Determining the genome-wide targets of isoforms of CCT 101 688

The cell-based TARGET system for transcription factor perturbation (Bargmann et al., 689

2013) was used to identify the genome-wide targets of different isoforms of CCT101. 690

Plants were grown on vertical petri plates containing ½ MS media with 1 mM KNO3 for 691

10 days prior to the experiment. The shoot protoplast preparation, transient 692

transformation, and cell-sorting were performed as described previously (Bargmann et 693

al., 2013). Protoplasts isolated from shoots were treated with 20 mM KNO3 and 20 mM 694

NH4NO3 prior to the nuclear import of transcription factor induced by dexamethasone. 695

Cells over-expressing either CCT101 isoforms or empty vector controls were collected 696

in triplicate in the same batch of experiment and RNA-Seq libraries were prepared from 697

mRNA using the NEBNext® Ultra™ RNA Library Prep Kit for Illumina. All three isoforms 698

are stably expressed at comparable levels based on RNA-Seq readout. The libraries 699

were pooled and sequenced on the Illumina NextSeq 500 platform for 75 cycles. The 700

RNA-Seq reads were aligned to the TAIR10 genome assembly using TopHat and gene 701

expression was estimated using the GenomicFeatures/GenomicAlignments packages 702

(Lawrence et al., 2013). Genes showing differential expression between the samples 703

with an overexpressed isoform and the samples with empty vector were identified using 704

DESeq2 package (Love et al., 2014) at a significance level of FDR<0.05 and fold 705

change >2. 706



24

707

Accession numbers 708

The ChIP-Seq and RNA-Seq data for this study can be accessed in NCBI SRA 709

(Accession number SRP149810). SDG8 is encoded by AT1G77300. 710

711

Supplemental Data 712

Supplemental Figure S1. Experimental design for the ChIP-Seq and RNA-Seq 713

experiments. 714

Supplemental Figure S2. Overlaps of the two groups of differentially methylated genes 715

with the SDG8 bound genes. 716

Supplemental Figure S3. Nitrogen uptake and assimilation in WT and the sdg8-5 717

mutant. 718

Supplemental Figure S4. The number of differentially methylated genes between N-719

supplied and N-starved conditions identified using different fold change cutoffs. 720

Supplemental Table S1. Genes with increased H3K36me3 level in N-supplied group 721

compared to N-starved group (A), or vice versa (B), in wild-type plants 722

Supplemental Table S2. Significantly enriched GO terms (Biological process) among 723

the 143 genes whose H3K36me3 increases in response to N-starvation in wild-type, 724

determined by Biomaps tool in VirtualPlant platform. 725

Supplemental Table S3. Significantly enriched GO terms (Biological process) among 726

the 53 genes whose H3K36me3 increases in response to N-supply in wild-type, 727

determined by Biomaps tool in VirtualPlant platform. 728

Supplemental Table S4. Genes with increased H3K36me3 level in N-supplied group 729

compared to N-starved group (A), or vice versa (B), in the sdg8-5 mutant. 730

Supplemental Table S5. 4,058 H3K36 hypomethylated genes that show significantly 731

higher H3K36me3 in WT compared to the sdg8-5 mutant in N-supplied and N-732

starved groups. 733

Supplemental Table S6. Genes that are regulated by the interaction of genotype and 734

nitrogen. 735

Supplemental Table S7. Significantly enriched GO terms among the cluster 1 genes 736

regulated by the interaction of genotype and nitrogen, determined by AgriGO. 737



25

Supplemental Table S8. Significantly enriched GO terms of cluster 2 genes that are 738

regulated by the interaction of genotype and nitrogen, determined by AgriGO. 739

Supplemental Table S9. Genes with isoform switch between N and KCl in WT and 740

sdg8-5, determined by cuffdiff in Cufflinks. 741

Supplemental Table S10. The target genes of CCT101 and their functional 742

enrichments. 743

744

ACKNOWLEDGEMENTS 745

We thank Dr. David Rhodes for insightful discussion about amino acid analysis. We also 746

thank two undergraduates Ellen Cho and Teresa Qi at New York University for their 747

help in root analysis, and Pascal Tillard in INRA (Montpellier, France) for 15N 748

measurements. This work is supported by Department of Energy (DE-FG02-749

92ER20071 to GMC), National Science Foundation (MCB 1412232) to GMC, USDA 750

National Institute of Food and Agriculture Hatch project numbers 1013620 to YL, and 751

177845 to JRW, and start-up funds from Purdue University to YL and JRW. 752

753

FIGURE LEGENDS 754

755

Figure 1. Nitrogen-responsive H3K36 methylation is attenuated in the sdg8-5 756

deletion mutant. (A) The comparison of genome-wide H3K36me3 patterns between N-757

supplied (+N) and N-depleted (-N) WT plants identified 196 genes with differentially 758

methylated H3K36, including 143 genes that have higher H3K36me3 in -N than in +N, 759

and 53 genes that have higher H3K36me3 in +N than in -N. In the sdg8-5 mutant, only 760

three genes were identified to have higher H3K36me3 in -N than in +N, and 23 genes 761

were identified to have higher H3K36me3 in +N than in -N. There is no overlap between 762

the genes identified in WT and that identified in the sdg8-5 mutant. Therefore, we 763

identified 143 genes that gain H3K36me3 in N starvation condition in WT but not in the 764

sdg8-5 mutant, and 53 genes that gain H3K36me3 in N-supplied condition in WT but in 765

the sdg8-5 mutant. (B) Overlaps of the two groups of differentially methylated genes 766

with the H3K36 hypomethylated genes (i.e. genes with less H3K36me3 in the sdg8-5 767

mutant compared to WT) are shown in the Venn diagram. Asterisks indicate a 768



26

significant overlap: *** p<0.001 determined by Genesect. (C) Exemplary genes show 769

H3K36me3 responses to nitrate level change in WT but not in the sdg8-5 mutant. 770

771

Figure 2. N-responsive reprogramming of gene expression is altered in the sdg8-5 772

deletion mutant. Expression levels of 215 genes significantly regulated by the 773

interaction of nitrate and SDG8 genotype are shown as a heatmap. Two major clusters 774

of the 215 DEGs were identified: (i) Cluster 1 comprises 126 genes that are more highly 775

induced by N starvation in WT, compared to the sdg8-5 mutant. The Cluster 1 genes 776

share a significant overlap with the genes that display higher H3K36me3 under N-777

starved condition than N-supplied condition. (ii) Cluster 2 contains 89 genes induced by 778

N supply in WT, which is abolished or attenuated in the sdg8-5 mutant. The Cluster 2 779

genes share a significant overlap with genes that exhibit higher H3K36me3 under N-780

supplied condition than N-starved condition. 781

782

Figure 3. Deletion of the histone methyltransferase SDG8 increases N-responsive 783

RNA isoform switching. We identified 144 genes that show N-responsive isoform 784

switching in the sdg8-5 mutant, and only 26 genes that show isoform switching in WT. 785

The comparison between the two gene lists identified 137 genes that are dependent on 786

SDG8 for WT-like RNA processing. The functional enrichment within these 137 genes 787

were determined and visualized using GeneCloud. 788

789

Figure 4. A putative transporter displays RNA isoform switching in response to N. 790

(A) Expression profile of AT3G54830 (encoding a putative transmembrane transporter) 791

shows distinct preference for RNA isoforms under N-supplied condition (+N, green, long 792

RNA isoform) compared to N-starved condition (-N, blue, short RNA isoform). 793

Specifically, a gene-centric view of RNA-Seq sequencing depth is shown with three 794

biological replicates for each condition. (B) Predicted structure of proteins encoded by 795

the long or short mRNA isoform suggested that the encoded protein is likely a putative 796

transmembrane transporter, with distinct structures under N-supplied vs. N-starved 797

conditions. Structures were predicted using Phyre2. 798

799



27

Figure 5. Histone methylation by SDG8 regulates RNA isoform preference of 800

CCT101 (AT5G53420), which impacts transcriptional regulation. (A) H3K36me3 801

levels at the CCT101 locus are affected by the sdg8-5 deletion and nitrate levels. In WT, 802

the H3K36me3 mark at the CCT101 locus is induced by N starvation. By contrast, in the 803

sdg8-5 mutant, the H3K36me3 mark at the CCT101 locus is greatly reduced and not 804

responsive to nitrate level changes. Two biological replicates of histone ChIP-Seq, each 805

sampled a pool of 200 to 400 seedlings, were used to calculate the H3K36me3 levels. 806

The error bars represent standard error of the mean. ****: p<0.001. The p-values were 807

determined using SICER. (B) CCT101 has four isoforms identified by Cufflinks. Three of 808

them are also annotated by TAIR10 (CCT101.1, CCT101.2, and CCT101.3, as 809

displayed in panel A). The proportion of transcripts for each CCT101 mRNA isoform is 810

shown as pie chart for the genotype and condition tested. In the sdg8-5 mutant but not 811

in the WT, the change of nitrate level induces a significant isoform switch. (C) 812

Overlapping yet different genes are regulated by proteins encoded by isoforms 813

CCT101.1 and CCT101.2. Numbers of genes regulated by each isoform are shown 814

within parentheses. Significantly enriched GO terms are displayed for shared targets 815

between the two isoforms, or unique targets of either isoform. 816

817

Figure 6. Physiological N responses are attenuated in the histone 818

methyltransferase deletion mutant sdg8-5. Root architecture, specifically nascent 819

lateral root growth (A) and chlorophyll content (B), is regulated by nitrogen in the WT 820

plants but not in the sdg8-5 mutant. The sdg8-5 mutants and the corresponding WT 821

seedlings were first grown on ammonium succinate for ten days and then transferred to 822

either low N (0.5 mM KNO3) or high N (5 mM KNO3) medium. Chlorophyll content (N=6, 823

individual plants) and root architecture (N=12-18, individual plants) were measured five 824

to six days after the transfer. The p-values were calculated by Student’s t-test, and the 825

error bars represent standard error of the mean. LR: lateral roots. PR: primary roots. 826

827

Literature Cited 828

Anders S, Pyl PT, Huber W (2015) HTSeq—a Python framework to work with high-829

throughput sequencing data. Bioinformatics 31: 166–169 830



28

Anders S, Reyes A, Huber W (2012) Detecting differential usage of exons from RNA-831

seq data. Genome Res 22: 2008–2017 832

Aslanzadeh V, Huang Y, Sanguinetti G, Beggs JD (2018) Transcription rate strongly 833

affects splicing fidelity and cotranscriptionality in budding yeast. Genome Res 28: 834

203–213 835

Bannister AJ, Schneider R, Myers FA, Thorne AW, Crane-Robinson C, Kouzarides 836

T (2005) Spatial distribution of di- and tri-methyl lysine 36 of histone H3 at active 837

genes. J Biol Chem 280: 17732–17736 838

Barbosa JM, Singh NK, Cherry JH, Locy RD (2010) Nitrate uptake and utilization is 839

modulated by exogenous gamma-aminobutyric acid in Arabidopsis thaliana 840

seedlings. Plant Physiol Biochem PPB 48: 443–450 841

Bargmann BOR, Marshall-Colon A, Efroni I, Ruffel S, Birnbaum KD, Coruzzi GM, 842

Krouk G (2013) TARGET: A Transient Transformation System for Genome-Wide 843

Transcription Factor Target Discovery. Mol Plant 6: 978–980 844

Barth TK, Imhof A (2010) Fast signals and slow marks: the dynamics of histone 845

modifications. Trends Biochem Sci 35: 618–626 846

Berr A, Ménard R, Heitz T, Shen W-H (2012) Chromatin modification and remodelling: 847

a regulatory landscape for the control of Arabidopsis defence responses upon 848

pathogen attack: Chromatin regulation of plant defence. Cell Microbiol 14: 829–849

839 850

Brambilla V, Fornara F (2017) Y flowering? Regulation and activity of CONSTANS and 851

CCT-domain proteins in Arabidopsis and crop species. Biochim Biophys Acta 852

BBA - Gene Regul Mech 1860: 655–660 853

Canales J, Moyano TC, Villarroel E, Gutiérrez RA (2014) Systems analysis of 854

transcriptome data provides new hypotheses about Arabidopsis root response to 855

nitrate treatments. Front Plant Sci. doi: 10.3389/fpls.2014.00022 856

Carrozza MJ, Li B, Florens L, Suganuma T, Swanson SK, Lee KK, Shia W-J, 857

Anderson S, Yates J, Washburn MP, et al (2005) Histone H3 methylation by 858

Set2 directs deacetylation of coding regions by Rpd3S to suppress spurious 859

intragenic transcription. Cell 123: 581–592 860

Cazzonelli CI, Cuttriss AJ, Cossetto SB, Pye W, Crisp P, Whelan J, Finnegan EJ, 861

Turnbull C, Pogson BJ (2009) Regulation of carotenoid composition and shoot 862

branching in Arabidopsis by a chromatin modifying histone methyltransferase, 863

SDG8. Plant Cell 21: 39–53 864

Cazzonelli CI, Nisar N, Roberts AC, Murray KD, Borevitz JO, Pogson BJ (2014) A 865

chromatin modifying enzyme, SDG8, is involved in morphological, gene 866



29

expression, and epigenetic responses to mechanical stimulation. Front Plant Sci. 867

doi: 10.3389/fpls.2014.00533 868

Charron J-BF, He H, Elling AA, Deng XW (2009) Dynamic Landscapes of Four 869

Histone Modifications during Deetiolation in Arabidopsis. Plant Cell Online 21: 870

3732–3748 871

Chinnusamy V, Zhu J-K (2009) Epigenetic regulation of stress responses in plants. 872

Curr Opin Plant Biol 12: 133–139 873

Dong C, He F, Berkowitz O, Liu J, Cao P, Tang M, Shi H, Wang W, Li Q, Shen Z, et 874

al (2018) Alternative Splicing Plays a Critical Role in Maintaining Mineral Nutrient 875

Homeostasis in Rice (Oryza sativa). Plant Cell 30: 2267–2285 876

Dong G, Ma D-P, Li J (2008) The histone methyltransferase SDG8 regulates shoot 877

branching in Arabidopsis. Biochem Biophys Res Commun 373: 659–664 878

Engelsberger WR, Schulze WX (2012) Nitrate and ammonium lead to distinct global 879

dynamic phosphorylation patterns when resupplied to nitrogen-starved 880

Arabidopsis seedlings. Plant J 69: 978–995 881

Gifford ML, Dean A, Gutierrez RA, Coruzzi GM, Birnbaum KD (2008) Cell-specific 882

nitrogen responses mediate developmental plasticity. Proc Natl Acad Sci U S A 883

105: 803–808 884

Greer EL, Shi Y (2012) Histone methylation: a dynamic mark in health, disease and 885

inheritance. Nat Rev Genet 13: 343–357 886

Gutiérrez RA, Stokes TL, Thum K, Xu X, Obertello M, Katari MS, Tanurdzic M, 887

Dean A, Nero DC, McClung CR, et al (2008) Systems approach identifies an 888

organic nitrogen-responsive gene network that is regulated by the master clock 889

control gene CCA1. Proc Natl Acad Sci 105: 4939–4944 890

Katari MS, Nowicki SD, Aceituno FF, Nero D, Kelfer J, Thompson LP, Cabello JM, 891

Davidson RS, Goldberg AP, Shasha DE, et al (2010) VirtualPlant: A Software 892

Platform to Support Systems Biology Research. Plant Physiol 152: 500–515 893

Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJE (2015) The Phyre2 web 894

portal for protein modeling, prediction and analysis. Nat Protoc 10: 845–858 895

Khan A, Zinta G (2016) Drought Stress and Chromatin: An Epigenetic Perspective. In 896

MA Hossain, SH Wani, S Bhattacharjee, DJ Burritt, L-SP Tran, eds, Drought 897

Stress Toler. Plants Vol 2. Springer International Publishing, Cham, pp 571–586 898

Kim J-M, To TK, Nishioka T, Seki M (2010) Chromatin regulation functions in plant 899

abiotic stress responses. Plant Cell Environ 33: 604–611 900



30

Kim SY, He Y, Jacob Y, Noh Y-S, Michaels S, Amasino R (2005) Establishment of 901

the vernalization-responsive, winter-annual habit in Arabidopsis requires a 902

putative histone H3 methyl transferase. Plant Cell 17: 3301–3310 903

Krapp A, Berthome R, Orsel M, Mercey-Boutet S, Yu A, Castaings L, Elftieh S, 904

Major H, Renou J-P, Daniel-Vedele F (2011) Arabidopsis Roots and Shoots 905

Show Distinct Temporal Adaptation Patterns toward Nitrogen Starvation. PLANT 906

Physiol 157: 1255–1282 907

Krouk G, Carré C, Fizames C, Gojon A, Ruffel S, Lacombe B (2015) GeneCloud 908

Reveals Semantic Enrichment in Lists of Gene Descriptions. Mol Plant 8: 971–909

973 910

La mke J, Brzezinka K, Altmann S, Ba urle I (2016) A hit-and-run heat shock factor 911

governs sustained histone methylation and transcriptional stress memory. EMBO 912

J 35: 162–175 913

Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient 914

alignment of short DNA sequences to the human genome. Genome Biol 10: R25 915

Lawrence M, Huber W, Pagès H, Aboyoun P, Carlson M, Gentleman R, Morgan 916

MT, Carey VJ (2013) Software for Computing and Annotating Genomic Ranges. 917

PLOS Comput Biol 9: e1003118 918

Lee S, Fu F, Xu S, Lee SY, Yun D-J, Mengiste T (2016) Global regulation of plant 919

immunity by histone lysine methyl transferases. Plant Cell 28: 1640-1661 920

Li Y, Mukherjee I, Thum KE, Tanurdzic M, Katari MS, Obertello M, Edwards MB, 921

McCombie WR, Martienssen RA, Coruzzi GM (2015) The histone 922

methyltransferase SDG8 mediates the epigenetic modification of light and carbon 923

responsive genes in plants. Genome Biol 16: 79 924

Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and 925

dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 926

Masaki T, Tsukagoshi H, Mitsui N, Nishii T, Hattori T, Morikami A, Nakamura K 927

(2005) Activation tagging of a gene for a protein with novel class of CCT-domain 928

activates expression of a subset of sugar-inducible genes in Arabidopsis 929

thaliana. Plant J Cell Mol Biol 43: 142–152 930

McCoy RM, Utturkar SM, Crook JW, Thimmapuram J, Widhalm JR (2018) The 931

origin and biosynthesis of the naphthalenoid moiety of juglone in black walnut. 932

Hortic Res. doi: 10.1038/s41438-018-0067-5 933

Medici A, Marshall-Colon A, Ronzier E, Szponarski W, Wang R, Gojon A, Crawford 934

NM, Ruffel S, Coruzzi GM, Krouk G (2015) AtNIGT1/HRS1 integrates nitrate 935

and phosphate signals at the Arabidopsis root tip. Nat Commun 6: 6274 936



31

Michaeli S, Fromm H (2015) Closing the Loop on the GABA Shunt in Plants: Are 937

GABA metabolism and signaling entwined? Front Plant Sci. doi: 938

10.3389/fpls.2015.00419 939

Nielsen H (2017) Predicting Secretory Proteins with SignalP. Methods Mol Biol Clifton 940

NJ 1611: 59–73 941

Pajoro A, Severing E, Angenent GC, Immink RGH (2017) Histone H3 lysine 36 942

methylation affects temperature-induced alternative splicing and flowering in 943

plants. Genome Biol 18: 102 944

Phukan UJ, Jeena GS, Shukla RK (2016) WRKY Transcription Factors: Molecular 945

Regulation and Stress Responses in Plants. Front Plant Sci. doi: 946

10.3389/fpls.2016.00760 947

Porra RJ (2002) The chequered history of the development and use of simultaneous 948

equations for the accurate determination of chlorophylls a and b. Photosynth Res 949

73: 149–156 950

Sakakibara H, Takei K, Hirose N (2006) Interactions between nitrogen and cytokinin in 951

the regulation of metabolism and development. Trends Plant Sci 11: 440–448 952

Shaffer PL, Goehring A, Shankaranarayanan A, Gouaux E (2009) Structure and 953

mechanism of a Na+independent amino acid transporter. Science 325: 1010–954

1014 955

Simon JM, Hacker KE, Singh D, Brannon AR, Parker JS, Weiser M, Ho TH, Kuan P-956

F, Jonasch E, Furey TS, et al (2014) Variation in chromatin accessibility in 957

human kidney cancer links H3K36 methyltransferase loss with widespread RNA 958

processing defects. Genome Res 24: 241–250 959

Sirohi G, Pandey BK, Deveshwar P, Giri J (2016) Emerging Trends in Epigenetic 960

Regulation of Nutrient Deficiency Response in Plants. Mol Biotechnol 58: 159–961

171 962

Soppe WJ, Bentsink L, Koornneef M (1999) The early-flowering mutant efs is 963

involved in the autonomous promotion pathway of Arabidopsis thaliana. 964

Development 126: 4763–4770 965

Springer NM, Napoli CA, Selinger DA, Pandey R, Cone KC, Chandler VL, Kaeppler 966

HF, Kaeppler SM (2003) Comparative Analysis of SET Domain Proteins in 967

Maize and Arabidopsis Reveals Multiple Duplications Preceding the Divergence 968

of Monocots and Dicots. Plant Physiol 132: 907–925 969

Swift J, Coruzzi GM (2016) A matter of time – How transient transcription factor 970

interactions create dynamic gene regulatory networks. Biochimica et Biophysica 971

Acta (BBA) – Gene regulatory mechanisms 1860 (1): 75-83 972

973



32

Thum KE, Shin MJ, Gutiérrez RA, Mukherjee I, Katari MS, Nero D, Shasha D, 974

Coruzzi GM (2008) An integrated genetic, genomic and systems approach 975

defines gene networks regulated by the interaction of light and carbon signaling 976

pathways in Arabidopsis. BMC Syst Biol 2: 31 977

Tian T, Liu Y, Yan H, You Q, Yi X, Du Z, Xu W, Su Z (2017) agriGO v2.0: a GO 978

analysis toolkit for the agricultural community, 2017 update. Nucleic Acids Res 979

45: W122–W129 980

Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, Pimentel H, Salzberg 981

SL, Rinn JL, Pachter L (2012) Differential gene and transcript expression 982

analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc 7: 562–983

578 984

Varala K, Marshall-Colón A, Cirrone J, Brooks MD, Pasquino AV, Léran S, Mittal S, 985

Rock TM, Edwards MB, Kim GJ, et al (2018) Temporal transcriptional logic of 986

dynamic regulatory networks underlying nitrogen signaling and use in plants. 987

Proc Natl Acad Sci 115: 6494–6499 988

Vidal E, Alvarez J, Moyano T, Gutierrez R (2015) Transcriptional networks in the 989

nitrate response of Arabidopsis thaliana. Curr Opin Plant Biol 27: 125–132 990

Wang L, Si Y, Dedow LK, Shao Y, Liu P, Brutnell TP (2011) A low-cost library 991

construction protocol and data analysis pipeline for Illumina-based strand-specific 992

multiplex RNA-seq. PloS One 6: e26426 993

Wang R, Okamoto M, Xing X, Crawford NM (2003) Microarray Analysis of the Nitrate 994

Response in Arabidopsis Roots and Shoots Reveals over 1,000 Rapidly 995

Responding Genes and New Linkages to Glucose, Trehalose-6-Phosphate, Iron, 996

and Sulfate Metabolism. Plant Physiol 132: 556–567 997

Wang Y-H, Garvin DF, Kochian LV (2001) Nitrate-Induced Genes in Tomato Roots. 998

Array Analysis Reveals Novel Genes That May Play a Role in Nitrogen Nutrition. 999

Plant Physiol 127: 345–359 1000

Widiez T, El Kafafi ES, Girin T, Berr A, Ruffel S, Krouk G, Vayssières A, Shen W-H, 1001

Coruzzi GM, Gojon A, et al (2011) High nitrogen insensitive 9 (HNI9)-mediated 1002

systemic repression of root NO3- uptake is associated with changes in histone 1003

methylation. Proc Natl Acad Sci U S A 108: 13329–13334 1004

Xu L, Zhao Z, Dong A, Soubigou-Taconnat L, Renou J-P, Steinmetz A, Shen W-H 1005

(2008) Di- and Tri- but Not Monomethylation on Histone H3 Lysine 36 Marks 1006

Active Transcription of Genes Involved in Flowering Time Regulation and Other 1007

Processes in Arabidopsis thaliana. Mol Cell Biol 28: 1348–1360 1008

Zang C, Schones DE, Zeng C, Cui K, Zhao K, Peng W (2009) A clustering approach 1009

for identification of enriched domains from histone modification ChIP-Seq data. 1010

Bioinformatics 25: 1952–1958 1011



33

Zhao Z, Yu Y, Meyer D, Wu C, Shen W-H (2005) Prevention of early flowering by 1012

expression of FLOWERING LOCUS C requires methylation of histone H3 K36. 1013

Nat Cell Biol 7: 1256–1260 1014

1015

1016



Figure 1.

Figure 1. Nitrogen-responsive H3K36 methylation is attenuated in the sdg8-5 deletion mutant. (A) The comparison of genome-wide H3K36me3 patterns between N-supplied (+N) and N-depleted (-N) WT plants identified 196 genes with differentially methylated H3K36, including 143 genes that have higher H3K36me3 in -N than in +N, and 53 genes that have higher H3K36me3 in +N than in -N. In the sdg8-5 mutant, only 3 genes were identified to have higher H3K36me3 in -N than in +N, and 23 genes were identified to have higher H3K36me3 in +N than in -N. There is no overlap between the genes identified in WT and that identified in the sdg8-5 mutant. Therefore, we identified 143 genes that gain H3K36me3 in N starvation condition in WT but not in the sdg8-5 mutant, and 53 genes that gain H3K36me3 in N-supplied condition in WT but in the sdg8-5 mutant. (B) Overlaps of the two groups of differentially methylated genes with the H3K36 hypomethylated genes (i.e. genes with less H3K36me3 in the sdg8-5 mutant compared to WT) are shown in venn diagram. Asterisks indicate a significant overlap: *** p<0.001 determined by Genesect. (C) Exemplary genes show H3K36me3 responses to nitrate level change in WT but not in the sdg8-5 mutant.



Figure 2

Figure 2. N-responsive reprogramming of gene expression is altered in the sdg8-5 deletion mutant. Expression levels of 215 genes significantly regulated by the interaction of nitrate and SDG8 genotype are shown as a heatmap. Two major clusters of the 215 DEGs were identified: (i) Cluster 1 comprises 126 genes that are more highly induced by N starvation in WT, compared to the sdg8-5 mutant. The cluster 1 genes share a significant overlap with the genes that display higher H3K36me3 under N-starved condition than N-supplied condition. (ii) Cluster 2 contains 89 genes induced by N supply in WT, which is abolished or attenuated in the sdg8-5 mutant. The cluster 2 genes share a significant overlap with genes that exhibit higher H3K36me3 under N-supplied condition than N-starved condition.



Figure 3

Figure 3. Deletion of SDG8 increases N-responsive RNA isoform switching. We identified 144 genes that show N-responsive isoform switching in the sdg8-5 mutant, and only 26 genes that show isoform switching in WT. The comparison between the two gene lists identified 137 genes that are dependent on SDG8 for WT-like RNA processing. The functional enrichment within these 137 genes were determined and visualized using GeneCloud.



Figure 4

Figure 4. A putative transporter displays RNA isoform switching in response to N. (A) Expression profile of AT3G54830 (encoding a putative transmembrane transporter) shows distinct preference for RNA isoforms under N-supplied condition (+N, green, long RNA isoform) compared to N-starved condition (-N, blue, short RNA isoform). Specifically, a gene-centric view of RNA-Seq sequencing depth is shown with three biological replicates for each condition. (B) Predicted structure of proteins encoded by the long or short mRNA isoform suggested that the encoded protein is likely a putative transmembrane transporter, with distinct structures under N-supplied vs. N-starved conditions. Structures were predicted using Phyre2.



Figure 5.

Figure 5. Histone methylation by SDG8 regulates RNA isoform preference of CCT101 (AT5G53420), which impacts transcriptional regulation. (A) H3K36me3

levels at the CCT101 locus are affected by the sdg8-5 deletion and nitrate levels. In WT,



the H3K36me3 mark at the CCT101 locus is induced by N starvation. By contrast, in the

sdg8-5 mutant, the H3K36me3 mark at the CCT101 locus is greatly reduced and not

responsive to nitrate level changes. Two biological replicates of histone ChIP-Seq, each

sampled a pool of 200 to 400 seedlings, were used to calculate the H3K36me3 levels.

The error bars represent standard error of the mean. ****: p<0.0001. The p-values were

determined using SICER. (B) CCT101 has four isoforms identified by Cufflinks. Three of

them are also annotated by TAIR10 (CCT101.1, CCT101.2, and CCT101.3, as displayed

in panel A). The proportion of transcripts for each CCT101 mRNA isoform is shown as

pie chart for the genotype and condition tested. In the sdg8-5 mutant but not in the WT,

the change of nitrate level induces a significant isoform switch. (C) Overlapping yet

different genes are regulated by proteins encoded by isoforms CCT101.1 and CCT101.2.

Numbers of genes regulated by each isoform are shown within parentheses. Significantly

enriched GO terms are displayed for shared targets between the two isoforms, or unique

targets of either isoform.



Figure 6

Figure 6. Physiological N responses are attenuated in the histone methyltransferase deletion mutant sdg8-5. Root architecture, specifically nascent

lateral root growth (A) and chlorophyll content (B), is regulated by nitrogen in the WT

plants but not in the sdg8-5 mutant. The sdg8-5 mutants and the corresponding WT

seedlings were first grown on ammonium succinate for ten days and then transferred to

either low N (0.5 mM KNO3) or high N (5 mM KNO3) medium. Chlorophyll content (N=6,

individual plants) and root architecture (N=12-18, individual plants) were measured five

to six days after the transfer. The p-values were calculated by Student’s t-test, and the

error bars represent standard error of the mean. LR: lateral roots. PR: primary roots.



Parsed CitationsAnders S, Pyl PT, Huber W (2015) HTSeq-a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166–169

Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Anders S, Reyes A, Huber W (2012) Detecting differential usage of exons from RNA-seq data. Genome Res 22: 2008–2017Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Aslanzadeh V, Huang Y, Sanguinetti G, Beggs JD (2018) Transcription rate strongly affects splicing fidelity and cotranscriptionality inbudding yeast. Genome Res 28: 203–213


Bannister AJ, Schneider R, Myers FA, Thorne AW, Crane-Robinson C, Kouzarides T (2005) Spatial distribution of di- and tri-methyllysine 36 of histone H3 at active genes. J Biol Chem 280: 17732–17736


Barbosa JM, Singh NK, Cherry JH, Locy RD (2010) Nitrate uptake and utilization is modulated by exogenous gamma-aminobutyric acidin Arabidopsis thaliana seedlings. Plant Physiol Biochem PPB 48: 443–450


Bargmann BOR, Marshall-Colon A, Efroni I, Ruffel S, Birnbaum KD, Coruzzi GM, Krouk G (2013) TARGET: A Transient TransformationSystem for Genome-Wide Transcription Factor Target Discovery. Mol Plant 6: 978–980


Barth TK, Imhof A (2010) Fast signals and slow marks: the dynamics of histone modifications. Trends Biochem Sci 35: 618–626Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Berr A, Ménard R, Heitz T, Shen W-H (2012) Chromatin modification and remodelling: a regulatory landscape for the control ofArabidopsis defence responses upon pathogen attack: Chromatin regulation of plant defence. Cell Microbiol 14: 829–839


Brambilla V, Fornara F (2017) Y flowering? Regulation and activity of CONSTANS and CCT-domain proteins in Arabidopsis and cropspecies. Biochim Biophys Acta BBA - Gene Regul Mech 1860: 655–660


Canales J, Moyano TC, Villarroel E, Gutiérrez RA (2014) Systems analysis of transcriptome data provides new hypotheses aboutArabidopsis root response to nitrate treatments. Front Plant Sci. doi: 10.3389/fpls.2014.00022


Carrozza MJ, Li B, Florens L, Suganuma T, Swanson SK, Lee KK, Shia W-J, Anderson S, Yates J, Washburn MP, et al (2005) Histone H3methylation by Set2 directs deacetylation of coding regions by Rpd3S to suppress spurious intragenic transcription. Cell 123: 581–592


Cazzonelli CI, Cuttriss AJ, Cossetto SB, Pye W, Crisp P, Whelan J, Finnegan EJ, Turnbull C, Pogson BJ (2009) Regulation of carotenoidcomposition and shoot branching in Arabidopsis by a chromatin modifying histone methyltransferase, SDG8. Plant Cell 21: 39–53


Cazzonelli CI, Nisar N, Roberts AC, Murray KD, Borevitz JO, Pogson BJ (2014) A chromatin modifying enzyme, SDG8, is involved inmorphological, gene expression, and epigenetic responses to mechanical stimulation. Front Plant Sci. doi: 10.3389/fpls.2014.00533


Charron J-BF, He H, Elling AA, Deng XW (2009) Dynamic Landscapes of Four Histone Modifications during Deetiolation in Arabidopsis.Plant Cell Online 21: 3732–3748


Chinnusamy V, Zhu J-K (2009) Epigenetic regulation of stress responses in plants. Curr Opin Plant Biol 12: 133–139Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title


https://www.ncbi.nlm.nih.gov/pubmed?term=Anders S%2C Pyl PT%2C Huber W %282015%29 HTSeq%2Da Python framework to work with high%2Dthroughput sequencing data%2E Bioinformatics 31%3A 166%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Anders&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=HTSeq-a Python framework to work with high-throughput sequencing data.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=HTSeq-a Python framework to work with high-throughput sequencing data.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Anders&as_ylo=2015&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Anders S%2C Reyes A%2C Huber W %282012%29 Detecting differential usage of exons from RNA%2Dseq data%2E Genome Res 22%3A 2008%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Anders&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Detecting differential usage of exons from RNA-seq data.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Detecting differential usage of exons from RNA-seq data.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Anders&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Aslanzadeh V%2C Huang Y%2C Sanguinetti G%2C Beggs JD %282018%29 Transcription rate strongly affects splicing fidelity and cotranscriptionality in budding yeast%2E Genome Res 28%3A 203%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Aslanzadeh&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Transcription rate strongly affects splicing fidelity and cotranscriptionality in budding yeast.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Transcription rate strongly affects splicing fidelity and cotranscriptionality in budding yeast.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Aslanzadeh&as_ylo=2018&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Bannister AJ%2C Schneider R%2C Myers FA%2C Thorne AW%2C Crane%2DRobinson C%2C Kouzarides T %282005%29 Spatial distribution of di%2D and tri%2Dmethyl lysine 36 of histone H3 at active genes%2E J Biol Chem 280%3A 17732%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Bannister&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Spatial distribution of di- and tri-methyl lysine 36 of histone H3 at active genes.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Spatial distribution of di- and tri-methyl lysine 36 of histone H3 at active genes.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Bannister&as_ylo=2005&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Barbosa JM%2C Singh NK%2C Cherry JH%2C Locy RD %282010%29 Nitrate uptake and utilization is modulated by exogenous gamma%2Daminobutyric acid in Arabidopsis thaliana seedlings%2E Plant Physiol Biochem PPB 48%3A 443%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Barbosa&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Nitrate uptake and utilization is modulated by exogenous gamma-aminobutyric acid in Arabidopsis thaliana seedlings.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Nitrate uptake and utilization is modulated by exogenous gamma-aminobutyric acid in Arabidopsis thaliana seedlings.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Barbosa&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Bargmann BOR%2C Marshall%2DColon A%2C Efroni I%2C Ruffel S%2C Birnbaum KD%2C Coruzzi GM%2C Krouk G %282013%29 TARGET%3A A Transient Transformation System for Genome%2DWide Transcription Factor Target Discovery%2E Mol Plant 6%3A 978%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Bargmann&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=TARGET: A Transient Transformation System for Genome-Wide Transcription Factor Target Discovery.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=TARGET: A Transient Transformation System for Genome-Wide Transcription Factor Target Discovery.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Bargmann&as_ylo=2013&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Barth TK%2C Imhof A %282010%29 Fast signals and slow marks%3A the dynamics of histone modifications%2E Trends Biochem Sci 35%3A 618%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Barth&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Fast signals and slow marks: the dynamics of histone modifications.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Fast signals and slow marks: the dynamics of histone modifications.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Barth&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Berr A%2C M�nard R%2C Heitz T%2C Shen W%2DH %282012%29 Chromatin modification and remodelling%3A a regulatory landscape for the control of Arabidopsis defence responses upon pathogen attack%3A Chromatin regulation of plant defence%2E Cell Microbiol 14%3A 829%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Berr&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Chromatin modification and remodelling: a regulatory landscape for the control of Arabidopsis defence responses upon pathogen attack: Chromatin regulation of plant defence.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Chromatin modification and remodelling: a regulatory landscape for the control of Arabidopsis defence responses upon pathogen attack: Chromatin regulation of plant defence.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Berr&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Brambilla V%2C Fornara F %282017%29 Y flowering%3F Regulation and activity of CONSTANS and CCT%2Ddomain proteins in Arabidopsis and crop species%2E Biochim Biophys Acta BBA %2D Gene Regul Mech 1860%3A 655%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Brambilla&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Y flowering? Regulation and activity of CONSTANS and CCT-domain proteins in Arabidopsis and crop species.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Y flowering? Regulation and activity of CONSTANS and CCT-domain proteins in Arabidopsis and crop species.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Brambilla&as_ylo=2017&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Canales J%2C Moyano TC%2C Villarroel E%2C Guti�rrez RA %282014%29 Systems analysis of transcriptome data provides new hypotheses about Arabidopsis root response to nitrate treatments%2E Front Plant Sci%2E doi%3A 10%2E3389%2Ffpls&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Canales&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Systems analysis of transcriptome data provides new hypotheses about Arabidopsis root response to nitrate treatments.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Systems analysis of transcriptome data provides new hypotheses about Arabidopsis root response to nitrate treatments.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Canales&as_ylo=2014&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Carrozza MJ%2C Li B%2C Florens L%2C Suganuma T%2C Swanson SK%2C Lee KK%2C Shia W%2DJ%2C Anderson S%2C Yates J%2C Washburn MP%2C et al %282005%29 Histone H3 methylation by Set2 directs deacetylation of coding regions by Rpd3S to suppress spurious intragenic transcription%2E Cell 123%3A 581%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Carrozza&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Histone H3 methylation by Set2 directs deacetylation of coding regions by Rpd3S to suppress spurious intragenic transcription.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Histone H3 methylation by Set2 directs deacetylation of coding regions by Rpd3S to suppress spurious intragenic transcription.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Carrozza&as_ylo=2005&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Cazzonelli CI%2C Cuttriss AJ%2C Cossetto SB%2C Pye W%2C Crisp P%2C Whelan J%2C Finnegan EJ%2C Turnbull C%2C Pogson BJ %282009%29 Regulation of carotenoid composition and shoot branching in Arabidopsis by a chromatin modifying histone methyltransferase%2C SDG8%2E Plant Cell 21%3A 39%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Cazzonelli&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Regulation of carotenoid composition and shoot branching in Arabidopsis by a chromatin modifying histone methyltransferase, SDG8.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Regulation of carotenoid composition and shoot branching in Arabidopsis by a chromatin modifying histone methyltransferase, SDG8.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Cazzonelli&as_ylo=2009&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Cazzonelli CI%2C Nisar N%2C Roberts AC%2C Murray KD%2C Borevitz JO%2C Pogson BJ %282014%29 A chromatin modifying enzyme%2C SDG8%2C is involved in morphological%2C gene expression%2C and epigenetic responses to mechanical stimulation%2E Front Plant Sci%2E doi%3A 10%2E3389%2Ffpls&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Cazzonelli&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=A chromatin modifying enzyme, SDG8, is involved in morphological, gene expression, and epigenetic responses to mechanical stimulation.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=A chromatin modifying enzyme, SDG8, is involved in morphological, gene expression, and epigenetic responses to mechanical stimulation.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Cazzonelli&as_ylo=2014&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Charron J%2DBF%2C He H%2C Elling AA%2C Deng XW %282009%29 Dynamic Landscapes of Four Histone Modifications during Deetiolation in Arabidopsis%2E Plant Cell Online 21%3A 3732%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Charron&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Dynamic Landscapes of Four Histone Modifications during Deetiolation in Arabidopsis.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Dynamic Landscapes of Four Histone Modifications during Deetiolation in Arabidopsis.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Charron&as_ylo=2009&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Chinnusamy V%2C Zhu J%2DK %282009%29 Epigenetic regulation of stress responses in plants%2E Curr Opin Plant Biol 12%3A 133%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Chinnusamy&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Epigenetic regulation of stress responses in plants.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Epigenetic regulation of stress responses in plants.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Chinnusamy&as_ylo=2009&as_allsubj=all&hl=en&c2coff=1


Dong C, He F, Berkowitz O, Liu J, Cao P, Tang M, Shi H, Wang W, Li Q, Shen Z, et al (2018) Alternative Splicing Plays a Critical Role inMaintaining Mineral Nutrient Homeostasis in Rice (Oryza sativa). Plant Cell 30: 2267–2285


Dong G, Ma D-P, Li J (2008) The histone methyltransferase SDG8 regulates shoot branching in Arabidopsis. Biochem Biophys ResCommun 373: 659–664


Engelsberger WR, Schulze WX (2012) Nitrate and ammonium lead to distinct global dynamic phosphorylation patterns when resuppliedto nitrogen-starved Arabidopsis seedlings. Plant J 69: 978–995


Gifford ML, Dean A, Gutierrez RA, Coruzzi GM, Birnbaum KD (2008) Cell-specific nitrogen responses mediate developmental plasticity.Proc Natl Acad Sci U S A 105: 803–808


Greer EL, Shi Y (2012) Histone methylation: a dynamic mark in health, disease and inheritance. Nat Rev Genet 13: 343–357Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Gutiérrez RA, Stokes TL, Thum K, Xu X, Obertello M, Katari MS, Tanurdzic M, Dean A, Nero DC, McClung CR, et al (2008) Systemsapproach identifies an organic nitrogen-responsive gene network that is regulated by the master clock control gene CCA1. Proc NatlAcad Sci 105: 4939–4944


Katari MS, Nowicki SD, Aceituno FF, Nero D, Kelfer J, Thompson LP, Cabello JM, Davidson RS, Goldberg AP, Shasha DE, et al (2010)VirtualPlant: A Software Platform to Support Systems Biology Research. Plant Physiol 152: 500–515


Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJE (2015) The Phyre2 web portal for protein modeling, prediction and analysis.Nat Protoc 10: 845–858


Khan A, Zinta G (2016) Drought Stress and Chromatin: An Epigenetic Perspective. In MA Hossain, SH Wani, S Bhattacharjee, DJ Burritt,L-SP Tran, eds, Drought Stress Toler. Plants Vol 2. Springer International Publishing, Cham, pp 571–586


Kim J-M, To TK, Nishioka T, Seki M (2010) Chromatin regulation functions in plant abiotic stress responses. Plant Cell Environ 33: 604–611


Kim SY, He Y, Jacob Y, Noh Y-S, Michaels S, Amasino R (2005) Establishment of the vernalization-responsive, winter-annual habit inArabidopsis requires a putative histone H3 methyl transferase. Plant Cell 17: 3301–3310


Krapp A, Berthome R, Orsel M, Mercey-Boutet S, Yu A, Castaings L, Elftieh S, Major H, Renou J-P, Daniel-Vedele F (2011) ArabidopsisRoots and Shoots Show Distinct Temporal Adaptation Patterns toward Nitrogen Starvation. PLANT Physiol 157: 1255–1282


Krouk G, Carré C, Fizames C, Gojon A, Ruffel S, Lacombe B (2015) GeneCloud Reveals Semantic Enrichment in Lists of GeneDescriptions. Mol Plant 8: 971–973


La mke J, Brzezinka K, Altmann S, Ba urle I (2016) A hit-and-run heat shock factor governs sustained histone methylation andtranscriptional stress memory. EMBO J 35: 162–175


Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the humangenome. Genome Biol 10: R25



https://www.ncbi.nlm.nih.gov/pubmed?term=Dong C%2C He F%2C Berkowitz O%2C Liu J%2C Cao P%2C Tang M%2C Shi H%2C Wang W%2C Li Q%2C Shen Z%2C et al %282018%29 Alternative Splicing Plays a Critical Role in Maintaining Mineral Nutrient Homeostasis in Rice %28Oryza sativa%29%2E Plant Cell 30%3A 2267%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Dong&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Alternative Splicing Plays a Critical Role in Maintaining Mineral Nutrient Homeostasis in Rice (Oryza sativa).&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Alternative Splicing Plays a Critical Role in Maintaining Mineral Nutrient Homeostasis in Rice (Oryza sativa).&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Dong&as_ylo=2018&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Dong G%2C Ma D%2DP%2C Li J %282008%29 The histone methyltransferase SDG8 regulates shoot branching in Arabidopsis%2E Biochem Biophys Res Commun 373%3A 659%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Dong&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=The histone methyltransferase SDG8 regulates shoot branching in Arabidopsis.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=The histone methyltransferase SDG8 regulates shoot branching in Arabidopsis.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Dong&as_ylo=2008&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Engelsberger WR%2C Schulze WX %282012%29 Nitrate and ammonium lead to distinct global dynamic phosphorylation patterns when resupplied to nitrogen%2Dstarved Arabidopsis seedlings%2E Plant J 69%3A 978%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Engelsberger&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Nitrate and ammonium lead to distinct global dynamic phosphorylation patterns when resupplied to nitrogen-starved Arabidopsis seedlings.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Nitrate and ammonium lead to distinct global dynamic phosphorylation patterns when resupplied to nitrogen-starved Arabidopsis seedlings.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Engelsberger&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Gifford ML%2C Dean A%2C Gutierrez RA%2C Coruzzi GM%2C Birnbaum KD %282008%29 Cell%2Dspecific nitrogen responses mediate developmental plasticity%2E Proc Natl Acad Sci U S A 105%3A 803%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Gifford&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Cell-specific nitrogen responses mediate developmental plasticity.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Cell-specific nitrogen responses mediate developmental plasticity.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Gifford&as_ylo=2008&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Greer EL%2C Shi Y %282012%29 Histone methylation%3A a dynamic mark in health%2C disease and inheritance%2E Nat Rev Genet 13%3A 343%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Greer&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Histone methylation: a dynamic mark in health, disease and inheritance.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Histone methylation: a dynamic mark in health, disease and inheritance.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Greer&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Guti�rrez RA%2C Stokes TL%2C Thum K%2C Xu X%2C Obertello M%2C Katari MS%2C Tanurdzic M%2C Dean A%2C Nero DC%2C McClung CR%2C et al %282008%29 Systems approach identifies an organic nitrogen%2Dresponsive gene network that is regulated by the master clock control gene CCA1%2E Proc Natl Acad Sci 105%3A 4939%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Gutiérrez&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Systems approach identifies an organic nitrogen-responsive gene network that is regulated by the master clock control gene CCA1.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Systems approach identifies an organic nitrogen-responsive gene network that is regulated by the master clock control gene CCA1.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Gutiérrez&as_ylo=2008&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Katari MS%2C Nowicki SD%2C Aceituno FF%2C Nero D%2C Kelfer J%2C Thompson LP%2C Cabello JM%2C Davidson RS%2C Goldberg AP%2C Shasha DE%2C et al %282010%29 VirtualPlant%3A A Software Platform to Support Systems Biology Research%2E Plant Physiol 152%3A 500%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Katari&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=VirtualPlant: A Software Platform to Support Systems Biology Research.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=VirtualPlant: A Software Platform to Support Systems Biology Research.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Katari&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Kelley LA%2C Mezulis S%2C Yates CM%2C Wass MN%2C Sternberg MJE %282015%29 The Phyre2 web portal for protein modeling%2C prediction and analysis%2E Nat Protoc 10%3A 845%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Kelley&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=The Phyre2 web portal for protein modeling, prediction and analysis.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=The Phyre2 web portal for protein modeling, prediction and analysis.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Kelley&as_ylo=2015&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Khan A%2C Zinta G %282016%29 Drought Stress and Chromatin%3A An Epigenetic Perspective%2E In MA Hossain%2C SH Wani%2C S Bhattacharjee%2C DJ Burritt%2C L%2DSP Tran%2C eds%2C Drought Stress Toler%2E Plants Vol 2%2E Springer International Publishing%2C Cham%2C pp 571%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Khan&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Drought Stress and Chromatin: An Epigenetic Perspective.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Drought Stress and Chromatin: An Epigenetic Perspective.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Khan&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Kim J%2DM%2C To TK%2C Nishioka T%2C Seki M %282010%29 Chromatin regulation functions in plant abiotic stress responses%2E Plant Cell Environ 33%3A 604%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Kim&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Chromatin regulation functions in plant abiotic stress responses.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Chromatin regulation functions in plant abiotic stress responses.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Kim&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Kim SY%2C He Y%2C Jacob Y%2C Noh Y%2DS%2C Michaels S%2C Amasino R %282005%29 Establishment of the vernalization%2Dresponsive%2C winter%2Dannual habit in Arabidopsis requires a putative histone H3 methyl transferase%2E Plant Cell 17%3A 3301%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Kim&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Establishment of the vernalization-responsive, winter-annual habit in Arabidopsis requires a putative histone H3 methyl transferase.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Establishment of the vernalization-responsive, winter-annual habit in Arabidopsis requires a putative histone H3 methyl transferase.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Kim&as_ylo=2005&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Krapp A%2C Berthome R%2C Orsel M%2C Mercey%2DBoutet S%2C Yu A%2C Castaings L%2C Elftieh S%2C Major H%2C Renou J%2DP%2C Daniel%2DVedele F %282011%29 Arabidopsis Roots and Shoots Show Distinct Temporal Adaptation Patterns toward Nitrogen Starvation%2E PLANT Physiol 157%3A 1255%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Krapp&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Arabidopsis Roots and Shoots Show Distinct Temporal Adaptation Patterns toward Nitrogen Starvation.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Arabidopsis Roots and Shoots Show Distinct Temporal Adaptation Patterns toward Nitrogen Starvation.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Krapp&as_ylo=2011&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Krouk G%2C Carr� C%2C Fizames C%2C Gojon A%2C Ruffel S%2C Lacombe B %282015%29 GeneCloud Reveals Semantic Enrichment in Lists of Gene Descriptions%2E Mol Plant 8%3A 971%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Krouk&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=GeneCloud Reveals Semantic Enrichment in Lists of Gene Descriptions.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=GeneCloud Reveals Semantic Enrichment in Lists of Gene Descriptions.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Krouk&as_ylo=2015&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=La mke J%2C Brzezinka K%2C Altmann S%2C Ba urle I %282016%29 A hit%2Dand%2Drun heat shock factor governs sustained histone methylation and transcriptional stress memory%2E EMBO J 35%3A 162%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=La&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=A hit-and-run heat shock factor governs sustained histone methylation and transcriptional stress memory.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=A hit-and-run heat shock factor governs sustained histone methylation and transcriptional stress memory.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=La&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Langmead B%2C Trapnell C%2C Pop M%2C Salzberg SL %282009%29 Ultrafast and memory%2Defficient alignment of short DNA sequences to the human genome%2E Genome Biol 10%3A R&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Langmead&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Langmead&as_ylo=2009&as_allsubj=all&hl=en&c2coff=1


Lawrence M, Huber W, Pagès H, Aboyoun P, Carlson M, Gentleman R, Morgan MT, Carey VJ (2013) Software for Computing andAnnotating Genomic Ranges. PLOS Comput Biol 9: e1003118


Lee S, Fu F, Xu S, Lee SY, Yun D-J, Mengiste T (2016) Global regulation of plant immunity by histone lysine methyl transferases. PlantCell 28: 1640-1661


Li Y, Mukherjee I, Thum KE, Tanurdzic M, Katari MS, Obertello M, Edwards MB, McCombie WR, Martienssen RA, Coruzzi GM (2015)The histone methyltransferase SDG8 mediates the epigenetic modification of light and carbon responsive genes in plants. GenomeBiol 16: 79


Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol15: 550


Masaki T, Tsukagoshi H, Mitsui N, Nishii T, Hattori T, Morikami A, Nakamura K (2005) Activation tagging of a gene for a protein withnovel class of CCT-domain activates expression of a subset of sugar-inducible genes in Arabidopsis thaliana. Plant J Cell Mol Biol 43:142–152


McCoy RM, Utturkar SM, Crook JW, Thimmapuram J, Widhalm JR (2018) The origin and biosynthesis of the naphthalenoid moiety ofjuglone in black walnut. Hortic Res. doi: 10.1038/s41438-018-0067-5


Medici A, Marshall-Colon A, Ronzier E, Szponarski W, Wang R, Gojon A, Crawford NM, Ruffel S, Coruzzi GM, Krouk G (2015)AtNIGT1/HRS1 integrates nitrate and phosphate signals at the Arabidopsis root tip. Nat Commun 6: 6274


Michaeli S, Fromm H (2015) Closing the Loop on the GABA Shunt in Plants: Are GABA metabolism and signaling entwined? Front PlantSci. doi: 10.3389/fpls.2015.00419


Nielsen H (2017) Predicting Secretory Proteins with SignalP. Methods Mol Biol Clifton NJ 1611: 59–73Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Pajoro A, Severing E, Angenent GC, Immink RGH (2017) Histone H3 lysine 36 methylation affects temperature-induced alternativesplicing and flowering in plants. Genome Biol 18: 102


Phukan UJ, Jeena GS, Shukla RK (2016) WRKY Transcription Factors: Molecular Regulation and Stress Responses in Plants. FrontPlant Sci. doi: 10.3389/fpls.2016.00760


Porra RJ (2002) The chequered history of the development and use of simultaneous equations for the accurate determination ofchlorophylls a and b. Photosynth Res 73: 149–156


Sakakibara H, Takei K, Hirose N (2006) Interactions between nitrogen and cytokinin in the regulation of metabolism and development.Trends Plant Sci 11: 440–448


Shaffer PL, Goehring A, Shankaranarayanan A, Gouaux E (2009) Structure and mechanism of a Na+independent amino acid transporter.Science 325: 1010–1014


Simon JM, Hacker KE, Singh D, Brannon AR, Parker JS, Weiser M, Ho TH, Kuan P-F, Jonasch E, Furey TS, et al (2014) Variation inchromatin accessibility in human kidney cancer links H3K36 methyltransferase loss with widespread RNA processing defects. GenomeRes 24: 241–250


https://www.ncbi.nlm.nih.gov/pubmed?term=Lawrence M%2C Huber W%2C Pag�s H%2C Aboyoun P%2C Carlson M%2C Gentleman R%2C Morgan MT%2C Carey VJ %282013%29 Software for Computing and Annotating Genomic Ranges%2E PLOS Comput Biol 9%3A e&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Lawrence&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Software for Computing and Annotating Genomic Ranges.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Software for Computing and Annotating Genomic Ranges.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Lawrence&as_ylo=2013&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Lee S%2C Fu F%2C Xu S%2C Lee SY%2C Yun D%2DJ%2C Mengiste T %282016%29 Global regulation of plant immunity by histone lysine methyl transferases%2E Plant Cell&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Lee&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Global regulation of plant immunity by histone lysine methyl transferases&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Global regulation of plant immunity by histone lysine methyl transferases&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Lee&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Li Y%2C Mukherjee I%2C Thum KE%2C Tanurdzic M%2C Katari MS%2C Obertello M%2C Edwards MB%2C McCombie WR%2C Martienssen RA%2C Coruzzi GM %282015%29 The histone methyltransferase SDG8 mediates the epigenetic modification of light and carbon responsive genes in plants%2E Genome Biol&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Li&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=The histone methyltransferase SDG8 mediates the epigenetic modification of light and carbon responsive genes in plants.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=The histone methyltransferase SDG8 mediates the epigenetic modification of light and carbon responsive genes in plants.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Li&as_ylo=2015&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Love MI%2C Huber W%2C Anders S %282014%29 Moderated estimation of fold change and dispersion for RNA%2Dseq data with DESeq2%2E Genome Biol&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Love&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Love&as_ylo=2014&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Masaki T%2C Tsukagoshi H%2C Mitsui N%2C Nishii T%2C Hattori T%2C Morikami A%2C Nakamura K %282005%29 Activation tagging of a gene for a protein with novel class of CCT%2Ddomain activates expression of a subset of sugar%2Dinducible genes in Arabidopsis thaliana%2E Plant J Cell Mol Biol 43%3A 142%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Masaki&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Activation tagging of a gene for a protein with novel class of CCT-domain activates expression of a subset of sugar-inducible genes in Arabidopsis thaliana.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Activation tagging of a gene for a protein with novel class of CCT-domain activates expression of a subset of sugar-inducible genes in Arabidopsis thaliana.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Masaki&as_ylo=2005&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=McCoy RM%2C Utturkar SM%2C Crook JW%2C Thimmapuram J%2C Widhalm JR %282018%29 The origin and biosynthesis of the naphthalenoid moiety of juglone in black walnut%2E Hortic Res%2E doi%3A 10%2E1038%2Fs&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=McCoy&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=McCoy&as_ylo=2018&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Medici A%2C Marshall%2DColon A%2C Ronzier E%2C Szponarski W%2C Wang R%2C Gojon A%2C Crawford NM%2C Ruffel S%2C Coruzzi GM%2C Krouk G %282015%29 AtNIGT1%2FHRS1 integrates nitrate and phosphate signals at the Arabidopsis root tip%2E Nat Commun&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Medici&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=AtNIGT1/HRS1 integrates nitrate and phosphate signals at the Arabidopsis root tip.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=AtNIGT1/HRS1 integrates nitrate and phosphate signals at the Arabidopsis root tip.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Medici&as_ylo=2015&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Michaeli S%2C Fromm H %282015%29 Closing the Loop on the GABA Shunt in Plants%3A Are GABA metabolism and signaling entwined%3F Front Plant Sci%2E doi%3A 10%2E3389%2Ffpls&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Michaeli&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Closing the Loop on the GABA Shunt in Plants: Are GABA metabolism and signaling entwined? Front Plant Sci.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Closing the Loop on the GABA Shunt in Plants: Are GABA metabolism and signaling entwined? Front Plant Sci.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Michaeli&as_ylo=2015&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Nielsen H %282017%29 Predicting Secretory Proteins with SignalP%2E Methods Mol Biol Clifton NJ 1611%3A 59%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Nielsen&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Predicting Secretory Proteins with SignalP.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Predicting Secretory Proteins with SignalP.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Nielsen&as_ylo=2017&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Pajoro A%2C Severing E%2C Angenent GC%2C Immink RGH %282017%29 Histone H3 lysine 36 methylation affects temperature%2Dinduced alternative splicing and flowering in plants%2E Genome Biol&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Pajoro&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Histone H3 lysine 36 methylation affects temperature-induced alternative splicing and flowering in plants.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Histone H3 lysine 36 methylation affects temperature-induced alternative splicing and flowering in plants.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Pajoro&as_ylo=2017&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Phukan UJ%2C Jeena GS%2C Shukla RK %282016%29 WRKY Transcription Factors%3A Molecular Regulation and Stress Responses in Plants%2E Front Plant Sci%2E doi%3A 10%2E3389%2Ffpls&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Phukan&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=WRKY Transcription Factors: Molecular Regulation and Stress Responses in Plants.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=WRKY Transcription Factors: Molecular Regulation and Stress Responses in Plants.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Phukan&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Porra RJ %282002%29 The chequered history of the development and use of simultaneous equations for the accurate determination of chlorophylls a and b%2E Photosynth Res 73%3A 149%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Porra&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=The chequered history of the development and use of simultaneous equations for the accurate determination of chlorophylls a and b.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=The chequered history of the development and use of simultaneous equations for the accurate determination of chlorophylls a and b.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Porra&as_ylo=2002&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Sakakibara H%2C Takei K%2C Hirose N %282006%29 Interactions between nitrogen and cytokinin in the regulation of metabolism and development%2E Trends Plant Sci 11%3A 440%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Sakakibara&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Interactions between nitrogen and cytokinin in the regulation of metabolism and development.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Interactions between nitrogen and cytokinin in the regulation of metabolism and development.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Sakakibara&as_ylo=2006&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Shaffer PL%2C Goehring A%2C Shankaranarayanan A%2C Gouaux E %282009%29 Structure and mechanism of a Na%2Bindependent amino acid transporter%2E Science 325%3A 1010%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Shaffer&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Structure and mechanism of a Na+independent amino acid transporter.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Structure and mechanism of a Na+independent amino acid transporter.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Shaffer&as_ylo=2009&as_allsubj=all&hl=en&c2coff=1



Sirohi G, Pandey BK, Deveshwar P, Giri J (2016) Emerging Trends in Epigenetic Regulation of Nutrient Deficiency Response in Plants.Mol Biotechnol 58: 159–171


Soppe WJ, Bentsink L, Koornneef M (1999) The early-flowering mutant efs is involved in the autonomous promotion pathway ofArabidopsis thaliana. Development 126: 4763–4770


Springer NM, Napoli CA, Selinger DA, Pandey R, Cone KC, Chandler VL, Kaeppler HF, Kaeppler SM (2003) Comparative Analysis ofSET Domain Proteins in Maize and Arabidopsis Reveals Multiple Duplications Preceding the Divergence of Monocots and Dicots.Plant Physiol 132: 907–925


Swift J, Coruzzi GM (2016) A matter of time – How transient transcription factor interactions create dynamic gene regulatory networks.Biochimica et Biophysica Acta (BBA) – Gene regulatory mechanisms 1860 (1): 75-83


Thum KE, Shin MJ, Gutiérrez RA, Mukherjee I, Katari MS, Nero D, Shasha D, Coruzzi GM (2008) An integrated genetic, genomic andsystems approach defines gene networks regulated by the interaction of light and carbon signaling pathways in Arabidopsis. BMC SystBiol 2: 31


Tian T, Liu Y, Yan H, You Q, Yi X, Du Z, Xu W, Su Z (2017) agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update.Nucleic Acids Res 45: W122–W129


Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, Pimentel H, Salzberg SL, Rinn JL, Pachter L (2012) Differential gene andtranscript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc 7: 562–578


Varala K, Marshall-Colón A, Cirrone J, Brooks MD, Pasquino AV, Léran S, Mittal S, Rock TM, Edwards MB, Kim GJ, et al (2018)Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants. Proc Natl Acad Sci 115:6494–6499


Vidal E, Alvarez J, Moyano T, Gutierrez R (2015) Transcriptional networks in the nitrate response of Arabidopsis thaliana. Curr OpinPlant Biol 27: 125–132


Wang L, Si Y, Dedow LK, Shao Y, Liu P, Brutnell TP (2011) A low-cost library construction protocol and data analysis pipeline forIllumina-based strand-specific multiplex RNA-seq. PloS One 6: e26426


Wang R, Okamoto M, Xing X, Crawford NM (2003) Microarray Analysis of the Nitrate Response in Arabidopsis Roots and ShootsReveals over 1,000 Rapidly Responding Genes and New Linkages to Glucose, Trehalose-6-Phosphate, Iron, and Sulfate Metabolism.Plant Physiol 132: 556–567


Wang Y-H, Garvin DF, Kochian LV (2001) Nitrate-Induced Genes in Tomato Roots. Array Analysis Reveals Novel Genes That May Play aRole in Nitrogen Nutrition. Plant Physiol 127: 345–359


Widiez T, El Kafafi ES, Girin T, Berr A, Ruffel S, Krouk G, Vayssières A, Shen W-H, Coruzzi GM, Gojon A, et al (2011) High nitrogeninsensitive 9 (HNI9)-mediated systemic repression of root NO3- uptake is associated with changes in histone methylation. Proc NatlAcad Sci U S A 108: 13329–13334


Xu L, Zhao Z, Dong A, Soubigou-Taconnat L, Renou J-P, Steinmetz A, Shen W-H (2008) Di- and Tri- but Not Monomethylation on HistoneH3 Lysine 36 Marks Active Transcription of Genes Involved in Flowering Time Regulation and Other Processes in Arabidopsis www.plantphysiol.orgon June 11, 2020 - Published by Downloaded from

Copyright © 2019 American Society of Plant Biologists. All rights reserved.

https://www.ncbi.nlm.nih.gov/pubmed?term=Simon JM%2C Hacker KE%2C Singh D%2C Brannon AR%2C Parker JS%2C Weiser M%2C Ho TH%2C Kuan P%2DF%2C Jonasch E%2C Furey TS%2C et al %282014%29 Variation in chromatin accessibility in human kidney cancer links H3K36 methyltransferase loss with widespread RNA processing defects%2E Genome Res 24%3A 241%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Simon&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Variation in chromatin accessibility in human kidney cancer links H3K36 methyltransferase loss with widespread RNA processing defects.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Variation in chromatin accessibility in human kidney cancer links H3K36 methyltransferase loss with widespread RNA processing defects.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Simon&as_ylo=2014&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Sirohi G%2C Pandey BK%2C Deveshwar P%2C Giri J %282016%29 Emerging Trends in Epigenetic Regulation of Nutrient Deficiency Response in Plants%2E Mol Biotechnol 58%3A 159%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Sirohi&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Emerging Trends in Epigenetic Regulation of Nutrient Deficiency Response in Plants.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Emerging Trends in Epigenetic Regulation of Nutrient Deficiency Response in Plants.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Sirohi&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Soppe WJ%2C Bentsink L%2C Koornneef M %281999%29 The early%2Dflowering mutant efs is involved in the autonomous promotion pathway of Arabidopsis thaliana%2E Development 126%3A 4763%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Soppe&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=The early-flowering mutant efs is involved in the autonomous promotion pathway of Arabidopsis thaliana.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=The early-flowering mutant efs is involved in the autonomous promotion pathway of Arabidopsis thaliana.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Soppe&as_ylo=1999&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Springer NM%2C Napoli CA%2C Selinger DA%2C Pandey R%2C Cone KC%2C Chandler VL%2C Kaeppler HF%2C Kaeppler SM %282003%29 Comparative Analysis of SET Domain Proteins in Maize and Arabidopsis Reveals Multiple Duplications Preceding the Divergence of Monocots and Dicots%2E Plant Physiol 132%3A 907%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Springer&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Comparative Analysis of SET Domain Proteins in Maize and Arabidopsis Reveals Multiple Duplications Preceding the Divergence of Monocots and Dicots.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Comparative Analysis of SET Domain Proteins in Maize and Arabidopsis Reveals Multiple Duplications Preceding the Divergence of Monocots and Dicots.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Springer&as_ylo=2003&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Swift J%2C Coruzzi GM %282016%29 A matter of time %26%23x2013%3B How transient transcription factor interactions create dynamic gene regulatory networks%2E Biochimica et Biophysica Acta %28BBA%29 %26%23x2013%3B Gene regulatory mechanisms&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Swift&hl=en&c2coff=1


https://scholar.google.com/scholar?as_q=&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Swift&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Thum KE%2C Shin MJ%2C Guti�rrez RA%2C Mukherjee I%2C Katari MS%2C Nero D%2C Shasha D%2C Coruzzi GM %282008%29 An integrated genetic%2C genomic and systems approach defines gene networks regulated by the interaction of light and carbon signaling pathways in Arabidopsis%2E BMC Syst Biol&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Thum&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=An integrated genetic, genomic and systems approach defines gene networks regulated by the interaction of light and carbon signaling pathways in Arabidopsis.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=An integrated genetic, genomic and systems approach defines gene networks regulated by the interaction of light and carbon signaling pathways in Arabidopsis.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Thum&as_ylo=2008&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Tian T%2C Liu Y%2C Yan H%2C You Q%2C Yi X%2C Du Z%2C Xu W%2C Su Z %282017%29 agriGO v2%2E0%3A a GO analysis toolkit for the agricultural community%2C 2017 update%2E Nucleic Acids Res 45%3A W122%26%23x2013%3BW&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Tian&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Tian&as_ylo=2017&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Trapnell C%2C Roberts A%2C Goff L%2C Pertea G%2C Kim D%2C Kelley DR%2C Pimentel H%2C Salzberg SL%2C Rinn JL%2C Pachter L %282012%29 Differential gene and transcript expression analysis of RNA%2Dseq experiments with TopHat and Cufflinks%2E Nat Protoc 7%3A 562%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Trapnell&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Trapnell&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Varala K%2C Marshall%2DCol�n A%2C Cirrone J%2C Brooks MD%2C Pasquino AV%2C L�ran S%2C Mittal S%2C Rock TM%2C Edwards MB%2C Kim GJ%2C et al %282018%29 Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants%2E Proc Natl Acad Sci 115%3A 6494%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Varala&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Varala&as_ylo=2018&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Vidal E%2C Alvarez J%2C Moyano T%2C Gutierrez R %282015%29 Transcriptional networks in the nitrate response of Arabidopsis thaliana%2E Curr Opin Plant Biol 27%3A 125%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Vidal&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Transcriptional networks in the nitrate response of Arabidopsis thaliana.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Transcriptional networks in the nitrate response of Arabidopsis thaliana.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Vidal&as_ylo=2015&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Wang L%2C Si Y%2C Dedow LK%2C Shao Y%2C Liu P%2C Brutnell TP %282011%29 A low%2Dcost library construction protocol and data analysis pipeline for Illumina%2Dbased strand%2Dspecific multiplex RNA%2Dseq%2E PloS One 6%3A e&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Wang&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=A low-cost library construction protocol and data analysis pipeline for Illumina-based strand-specific multiplex RNA-seq.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=A low-cost library construction protocol and data analysis pipeline for Illumina-based strand-specific multiplex RNA-seq.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Wang&as_ylo=2011&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Wang R%2C Okamoto M%2C Xing X%2C Crawford NM %282003%29 Microarray Analysis of the Nitrate Response in Arabidopsis Roots and Shoots Reveals over 1%2C000 Rapidly Responding Genes and New Linkages to Glucose%2C Trehalose%2D6%2DPhosphate%2C Iron%2C and Sulfate Metabolism%2E Plant Physiol 132%3A 556%26%23x&dopt=abstract



https://scholar.google.com/scholar?as_q=&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Wang&as_ylo=2003&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Wang Y%2DH%2C Garvin DF%2C Kochian LV %282001%29 Nitrate%2DInduced Genes in Tomato Roots%2E Array Analysis Reveals Novel Genes That May Play a Role in Nitrogen Nutrition%2E Plant Physiol 127%3A 345%26%23x&dopt=abstract


https://scholar.google.com/scholar?as_q=Nitrate-Induced Genes in Tomato Roots.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Nitrate-Induced Genes in Tomato Roots.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Wang&as_ylo=2001&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Widiez T%2C El Kafafi ES%2C Girin T%2C Berr A%2C Ruffel S%2C Krouk G%2C Vayssi�res A%2C Shen W%2DH%2C Coruzzi GM%2C Gojon A%2C et al %282011%29 High nitrogen insensitive 9 %28HNI9%29%2Dmediated systemic repression of root NO3%2D uptake is associated with changes in histone methylation%2E Proc Natl Acad Sci U S A 108%3A 13329%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Widiez&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=High nitrogen insensitive 9 (HNI9)-mediated systemic repression of root NO3- uptake is associated with changes in histone methylation.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=High nitrogen insensitive 9 (HNI9)-mediated systemic repression of root NO3- uptake is associated with changes in histone methylation.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Widiez&as_ylo=2011&as_allsubj=all&hl=en&c2coff=1


H3 Lysine 36 Marks Active Transcription of Genes Involved in Flowering Time Regulation and Other Processes in Arabidopsisthaliana. Mol Cell Biol 28: 1348–1360


Zang C, Schones DE, Zeng C, Cui K, Zhao K, Peng W (2009) A clustering approach for identification of enriched domains from histonemodification ChIP-Seq data. Bioinformatics 25: 1952–1958


Zhao Z, Yu Y, Meyer D, Wu C, Shen W-H (2005) Prevention of early flowering by expression of FLOWERING LOCUS C requiresmethylation of histone H3 K36. Nat Cell Biol 7: 1256–1260



https://www.ncbi.nlm.nih.gov/pubmed?term=Xu L%2C Zhao Z%2C Dong A%2C Soubigou%2DTaconnat L%2C Renou J%2DP%2C Steinmetz A%2C Shen W%2DH %282008%29 Di%2D and Tri%2D but Not Monomethylation on Histone H3 Lysine 36 Marks Active Transcription of Genes Involved in Flowering Time Regulation and Other Processes in Arabidopsis thaliana%2E Mol Cell Biol 28%3A 1348%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Xu&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Di- and Tri- but Not Monomethylation on Histone H3 Lysine 36 Marks Active Transcription of Genes Involved in Flowering Time Regulation and Other Processes in Arabidopsis thaliana.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Di- and Tri- but Not Monomethylation on Histone H3 Lysine 36 Marks Active Transcription of Genes Involved in Flowering Time Regulation and Other Processes in Arabidopsis thaliana.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Xu&as_ylo=2008&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Zang C%2C Schones DE%2C Zeng C%2C Cui K%2C Zhao K%2C Peng W %282009%29 A clustering approach for identification of enriched domains from histone modification ChIP%2DSeq data%2E Bioinformatics 25%3A 1952%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Zang&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=A clustering approach for identification of enriched domains from histone modification ChIP-Seq data.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=A clustering approach for identification of enriched domains from histone modification ChIP-Seq data.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Zang&as_ylo=2009&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Zhao Z%2C Yu Y%2C Meyer D%2C Wu C%2C Shen W%2DH %282005%29 Prevention of early flowering by expression of FLOWERING LOCUS C requires methylation of histone H3 K36%2E Nat Cell Biol 7%3A 1256%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Zhao&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Prevention of early flowering by expression of FLOWERING LOCUS C requires methylation of histone H3 K36.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Prevention of early flowering by expression of FLOWERING LOCUS C requires methylation of histone H3 K36.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Zhao&as_ylo=2005&as_allsubj=all&hl=en&c2coff=1


Documents

SDG8-mediated histone methylation and RNA processing ... · 49 SDG8 is required for canonical RNA processing, and that RNA isoform switching is 50 more prominent in the sdg8-5 deletion