transcriptional dynamics of bread wheat in response to nitrate … · 129 nitrate or phosphate from...

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Title: Transcriptional dynamics of bread wheat in response to 1 nitrate and phosphate supply reveal functional divergence of 2 genetic factors involved in nitrate and phosphate signaling 3

Running title: Wheat transcriptional responses to nitrate and 4 phosphate 5 6 7 Authors: Indeewari Dissanayake1, Joel Rodriguez-Medina2, Siobhan M. Brady2, Miloš 8 Tanurdžić1* 9 10 11 Affiliations: 12 1School of Biological Sciences, The University of Queensland, QLD 4072, Australia 13 14 2 Department of Plant Biology and Genome Center, University of California Davis, 15 CA95616, USA 16 17 *Corresponding author 18 19 Contact information: 20 Email of corresponding author [email protected] 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41

author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was not peer-reviewed) is the. https://doi.org/10.1101/551069doi: bioRxiv preprint

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Abstract 42

43

Nitrate (N) and phosphate (P) levels are sensed by plant cells and signaled via local and 44

systemic signaling pathways to modulate plant growth and development. Understanding the 45

genetic basis of these signaling mechanisms is key to future improvement of nutrient use 46

efficiency. While major progress has been made in understanding N and P signaling 47

pathways and their interaction in the model plant Arabidopsis, understanding of 48

transcriptional responses to N and P in a major monocot crop wheat is lacking. Therefore, 49

we investigated gene expression dynamics of wheat roots in response to N and/or P provision 50

using RNA-Seq. We found that nitrate presence is the major trigger for most of the 51

transcriptional response to occur within 24 h, however, we also identified a large array of 52

synergistic transcriptional responses to concomitant supply of N and P. Through gene co-53

expression analysis, we identified gene co-expression modules prominent in nitrate signaling 54

and metabolism in wheat. Importantly, we identified likely instances of functional 55

divergence in major N-responsive transcription factors families HRS1/HHO and TGA of 56

wheat from their rice/Arabidopsis homologues. Our work broadens the understanding of 57

wheat N and P transcriptional responses and aids in prioritizing gene candidates for 58

production of wheat varieties that are efficient in nitrogen usage. 59

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Key words: Nitrate, phosphate, wheat, transcriptomics, gene co-expression networks, 62

HRS1/HHO, TGA 63

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Introduction 72

73

Plant development is a highly plastic process, necessitated by the plants’ need to cope with 74

changes in the environment. Availability of nutrients in the soil, for example, modulates 75

plant form and function by changing the root system architecture or shifting the plant’s 76

metabolism. Nitrogen and phosphorus are plant macronutrients absorbed in the form of 77

nitrates (Crawford and Glass 1998) and orthophosphates (Pi) (Schachtman et al. 1998; 78

Marschner 2011) respectively. Many soil types lack in both available nitrate (Schlesinger, 79

1994; Vance 2001) and phosphate (Beadle 1953; Bieleski 1973). Therefore, nitrogen and 80

phosphorus fertilizers are applied to arable lands in large amounts globally where the excess 81

fertilizer usage contributes to environmental pollution (X. Zhang et al. 2015; Tilman et al. 82

2002). Hence, understanding the mechanisms mediating plant responses to nutrient supply 83

as well as to nutrient deficiency is critical for the production of new resilient and productive 84

crops that are efficient in nitrogen and phosphorus usage. 85

86

Studies on the dicotyledonous model plant Arabidopsis thaliana have been key to unraveling 87

the effects of nitrate and phosphate supply/starvation on plant biology and showed that 88

changes in levels of available nitrate and phosphate trigger signaling pathways that modulate 89

root development (Forde 2014; Chiou and Lin 2011). Transcription factors such as NLP7 90

(Castaings et al. 2009; Marchive et al. 2013), PHR1 (Rubio et al. 2001, Nilsson et al. 2007) 91

and HRS1 (Medici et al. 2015) and their downstream targets play crucial roles in nitrate and 92

phosphate signaling. For example, NLP7 regulates genes involved in nitrate signaling and 93

nitrate assimilation upon nitrate resupply (Castaings et al. 2009; Marchive et al. 2013) while 94

PHR1 regulates phosphate starvation responses (Rubio et al. 2001, Nilsson et al. 2007). 95

Importantly, these studies have shown that nitrate and phosphate signaling are intricately 96

regulated at the transcriptional, post-transcriptional and post-translational levels (reviewed 97

in Krapp et al. 2014; Briat et al. 2015). Moreover, plant hormones such as auxin, cytokinin 98

and strigolactone are implicated in nitrate and phosphate signaling pathways (reviewed in 99

Krouk 2017; Kapulnik and Koltai 2016; Guan 2017). For example, auxin plays a major role 100

in the lateral root development in response to local nitrate availability through nitrate-101

mediated regulation of components in the auxin signaling pathway such as auxin receptor 102

AFB3 (Vidal et al. 2010) and auxin response factor ARF8 (Lavenus et al. 2013). 103

104


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Several lines of evidence suggest nitrate and phosphate signaling pathways connect through 105

the ubiquitin E3 ligase NLA (NITRATE LIMITATION ADAPTATION) and GARP family 106

transcription factor HRS1 (HYPERSENSITIVE TO LOW PI-ELICITED PRIMARY ROOT 107

SHORTENING 1) (Kant et al. 2011; Medici et al. 2015). For example, Arabidopsis 108

HRS1/HHO gene family contains seven members and these genes are orthologous to rice 109

NIGT1 (Nitrate-Inducible, GARP-type Transcriptional Repressor 1) (Sawaki et al. 2013). 110

The Arabidopsis HRS1/HHO gene family and rice NIGT1 are MYB-related transcription 111

factors from the GOLDEN2-like subgroup of GARP family transcription factors (H. Liu et 112

al. 2009; Sawaki et al. 2013). Arabidopsis, HRS1 and HHO1 are up-regulated in response to 113

nitrate supply within 6 minutes (Krouk et al. 2010), while in rice NIGT1 is induced within 1 114

h (Sawaki et al. 2013). HRS1/HHO gene family members have been identified as 115

transcriptional repressors regulating nitrate starvation responses (Maeda et al. 2018; Kiba, 116

et al, 2018). AtHHO2 and AtHHO3 are transcriptionally induced by nitrate albeit to a lesser 117

extent than AtHRS1/HHO1 (Maeda et al. 2018) while AtHHO5 and AtHHO6 were validated 118

as nitrate responsive transcription factors (Varala et al. 2018). 119

120

While Arabidopsis HRS1 was first characterized by its mutant root phenotype in response to 121

phosphate starvation (H. Liu et al. 2009), later studies reported Arabidopsis HRS1 and its 122

close paralogue HHO1 (Krouk et al. 2010) as well as rice NIGT1 (Sawaki et al. 2013) as 123

being rapidly and specifically transcriptionally induced by nitrate. This was the first 124

evidence that N and P signaling pathways may, in effect, crosstalk, and recently AtHRS1 125

was, indeed, shown to be at the nexus of nitrate and phosphate signaling (Medici et al. 2015; 126

Maeda et al. 2018; Kiba et al., 2018) whereby HRS1 is regulated transcriptionally by nitrate 127

and post-transcriptionally by phosphate. Therefore, delineating exclusive responses to 128

nitrate or phosphate from the responses to the concomitant supply of nitrate and phosphate 129

will facilitate better understanding on the coordination of plant nitrate and phosphate 130

signaling and homeostasis. 131

132

Interestingly, it has been reported that the phenotypic changes in root system architecture in 133

response to nitrate and phosphate are different in Arabidopsis relative to monocot species 134

such as rice and maize (Smith and I. De Smet 2012; Niu et al. 2013; Shahzad and Amtmann 135

2017). These phenotypically different responses could be due to underlying gene regulatory 136

mechanisms. Indeed, compelling evidence shows orthologues of a gene performing opposite 137

functions in Arabidopsis and rice. For example, SPX-Major Facility Superfamily3 proteins 138


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are implicated in vacuolar transport of phosphate and behave as phosphate influx 139

transporters in Arabidopsis (J. Liu et al. 2015) while they are phosphate efflux transporters 140

in rice (C. Wang et al. 2015). 141

142

Wheat is a major cereal crop accounting for an annual production of 749 million metric tons 143

in 2016 (Food and Agriculture Organization statistics), being second in production to maize 144

(1 billion metric tons in 2016). The hexaploid genetic structure of bread wheat renders it an 145

interesting, yet complex genetic system to study due to its two recent duplication events 146

(Marcussen et al. 2014). Evidence for independent regulation of three subgenomes in 147

hexaploid wheat (Pfeifer et al. 2014; Powell et al. 2017) have been reported. Here, we aim 148

to determine the effects of nitrate and/or phosphate supply on transcriptional dynamics in 149

wheat. Our results show transcriptional reprogramming by nitrate and phosphate provision 150

and delineate the transcriptional responses to nitrate provision that are dependent or 151

independent of phosphate. Moreover, we could also identify instances where wheat gene 152

families of transcription factors involved in nitrate and phosphate signaling such as TGA 153

(TGACG SEQUENCE-SPECIFIC BINDING PROTEIN) and HRS1/HHO 154

(HYPERSENSITIVE TO LOW PI-ELICITED PRIMARY ROOT SHORTENING 1/HRS1-155

HOMOLOG) have functionally diverged from their rice or Arabidopsis homologues. 156

Altogether, our results may contribute to prioritizing gene candidates for future wheat 157

nutrient use efficiency breeding efforts. 158

159

Results and discussion 160

Nitrate and/or phosphate provision affects wheat root system 161

architecture 162

163

To investigate transcriptome dynamics in response to N and P supply, we first determined if 164

growth under N and/or P deplete or replete conditions had any effect on wheat root system 165

architecture. To this end, we measured root system parameters and in planta N and P content. 166

To maximize root responses to N and/or P supply, we grew Triticum aestivum (cultivar 167

Chinese spring) plants in water for 11 days. This led to a two-fold and four-fold decrease in 168

nitrogen and phosphorus content in the roots, respectively, relative to plants grown in full 169

strength nutrient solution (see materials and methods) (Figure S1). We then supplied the 170


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plants with nutrient solutions which differed in nitrate and phosphate concentrations (0.5 171

mM or 0 mM phosphate, and/or 2 mM or 0 mM nitrate). We therefore used four treatment 172

combinations (-P-N, -P+N, +P-N and +P+N), here denoted as pn, pN, Pn and PN, 173

respectively. After further growing the plants under these four conditions for seven days we 174

were able to detect changes in root system architecture (Figure 1A). 175

176

Following N and/or P supply for 7 days, we measured N and P content in roots and shoots 177

of 18 days old plants (Figure 1E-F). As expected, N content was significantly higher in roots 178

and shoots of plants grown in pN and PN conditions than in Pn and pn (Figure 1E). 179

Phosphorus content was significantly higher in roots and shoots of plants grown in Pn and 180

PN conditions, than in the plants grown in pN and pn conditions. Interestingly, the 181

phosphorus content was also significantly lower in Pn treated plants than in PN treated plants 182

(Figure 1F). This result first suggested that presence of nitrogen may facilitate phosphorus 183

uptake/redistribution because an equal amount of phosphate was supplied in Pn and PN 184

treatments. 185

186

Plant root system architecture is modulated by nutrient resources available through nutrient 187

sensing and signaling (Kellermeier et al. 2014; Shahzad and Amtmann 2017). We measured 188

three root system parameters (primary root length, the number of lateral roots and lateral 189

root density on the primary root) of 18 day old plants, as described above. The three root 190

system parameters were significantly different among treatments (Figure 1A-D): single (pN, 191

Pn) or combined (pn) nutrient deficiency led to increased primary root length (Figure 1B) 192

and increased number of lateral roots on the primary root (Figure 1C), relative to the nutrient 193

replete (PN) condition. Single nutrient deficiency also led to increased lateral root density, 194

suggestive of root foraging for nitrate and phosphate. However, both PN and pn treatments 195

resulted in similar lateral root densities (Figure 1D). These results showed that wheat roots 196

under single P/N deficient conditions employ strategies for increasing root mass by both 197

increasing main root length and the number of lateral roots. They also suggest that N 198

availability supersedes the effect of P availability. 199

200

Previous studies of Arabidopsis root responses to phosphate deficiency reported shorter 201

primary roots and increased lateral root density. This is thought to be a mechanism for 202

efficient top-soil foraging (Péret et al. 2014), although the responses may vary depending on 203

the severity and the exposure time to the phosphate deficiency (Niu et al. 2013; Tian et al. 204


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2014) and the genetic background since some natural accessions of Arabidopsis thaliana 205

show difference in P response (Chevalier et al. 2003; Shahzad et al. 2018). Similarly, root 206

responses to nitrate deficiency vary depending on the severity of deficiency as well as the 207

distribution of nitrate (homogeneous vs local distribution in soil) (Gruber et al. 2013, 208

reviewed in Giehl et al. 2013). Under severe nitrate deficiency conditions, both primary and 209

lateral root growth were retarded in Arabidopsis (Giehl et al. 2013; Gruber et al. 2013; Giehl 210

and Wirén 2014). Studies on rice reported increased seminal root length and decreased 211

lateral root density (Sun et al. 2014) due to nitrate or phosphate deficiency. Our results on 212

wheat primary root length under single nutrient deficiency are in agreement with those 213

reported in the study on rice (Sun et al. 2014; Yu et al. 2016), however they differ in lateral 214

root density where nitrate or phosphate deficiency caused increased lateral root density in 215

wheat. This could be due to the differences in the nitrogen and phosphorus concentrations 216

used in our experiment and the study by Sun et al. 2014. 217

218 219


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220

221

Analysis of differential gene expression reveals major combinatorial 222

effects of nitrate and phosphate provision on transcriptional dynamics 223

224 Since rapid transcriptomic changes have been observed in response to nitrate (Krouk et al. 225

2010; K.-H. Liu et al. 2017), and phosphate supply (Gutiérrez-Alanís et al. 2017; Secco et 226

al. 2013), we focused on exploring the dynamics of wheat root transcriptional responses 227

within the first 24 h of nitrate and/or phosphate supply. Moreover, considering the emerging 228

evidence of a connection between nitrate and phosphate signaling pathways (Maeda et al. 229

2018; Kiba et al., 2018) as well as our results on root system architecture changes in wheat 230

2 cm

PN pN pnPn

PN pN Pn pn0

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2

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Nitr

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[% d

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eigh

t]

a ab b

a a

b b

Root Shoot

A B

C

D

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F

Figure 1. The wheat root responses to nitrate and/or phosphate supply. (A) Root system architecture of wheat plants treated with nitrate and/or phosphate. Comparison of wheat root system parameters (B) primary root length, (C) number of lateral roots (LR) on the primary root, (D) lateral root (LR) density on the primary root (n=15, error bars indicate standard error of mean). Comparison of (E) Nitrogen content, (F) Phosphorus content of total root and total shoot tissue (n=3, error bars indicate standard error of mean). Figures 1A-F are results from 18-day old wheat plants that were grown in indicated nutrient regimes for seven days, letters denote significance based on two-way ANOVA followed by Tukey HSD (P<0.05) in Figures 1B-F.


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roots in response to combinatorial nitrate and phosphate treatment, we used an experimental 231

setup that enabled delineating combinatorial effects of nitrate and phosphate on the root 232

transcriptome from the effects due to nitrate- or phosphate-only. 233

234 To characterize transcriptomic responses to P and N provision, we collected root samples at 235

1 h, 2 h, 4 h and 24 h following nutrient supply and quantified gene expression using RNA-236

Seq. Out of 110790 wheat high confidence genes in IWGSC RefSeq version 1.0 annotation, 237

94253 (85.03%) had non-zero total read count across samples. We herein denote these 94253 238

genes as “expressed” under at least one of the conditions. 239

240

We considered the numbers of differentially expressed genes (FDR < 0.05) between a 241

treatment (PN or Pn or pN) and reference (pn) at four time points (Figure 2A). Only 25 genes 242

(0.02% of expressed genes) responded to phosphate supply in the absence of nitrate (Pn) 243

within the first 24 h (Table S8). These 25 genes included the SPX domain containing gene 244

most similar to SPX DOMAIN GENE 3 in Arabidopsis (TraesCS2D01G177100, orthologous 245

to ATSPX3 (AT2G45130)) down-regulated at 1 h; three phosphate transporter genes 246

(TraesCS4B01G317200, TraesCS4A01G416500 and TraesCSU01G070800 (orthologous to 247

ATPT1 (PHOSPHATE TRANSPORTER 1, AT5G43350)) down-regulated at 2 h, and CLE 248

gene family members (TraesCS1D01G401200 and TraesCS1B01G421600, up-regulated at 249

24 h). Transcriptional repression of both ATSPX3 (Duan et al. 2008) and ATPT1 (Puga et al. 250

2014) by PHR1 under P sufficient conditions has been reported in Arabidopsis (reviewed in 251

Gu et al. 2016). This result suggests that despite few wheat genes are regulated by phosphate 252

in the absence of nitrate, at least some components of the PHR1 signaling module are 253

conserved in function between wheat and Arabidopsis and respond rapidly to phosphate 254

supply independent of nitrate. Even though IPS1 and miR399 are also well known targets of 255

PHR1, these genes could not be assessed using RNA-Seq since these ncRNA loci are not 256

present in the current wheat high confidence gene annotation. 257

258

Following N supply in the absence of P (pN treatment) for 1 h, 16 genes (0.01% of expressed 259

genes) were differentially expressed (Figure 2A, Table S8), only two of which were up-260

regulated (Table S2). This changed dramatically at later time points with thousands of genes 261

being differentially expressed under pN treatment (Figure 2A, Table S2), starting with the 262

the 2 h time point. These results show the progression of a transcriptional cascade related to 263

nitrate signaling and metabolism (further discussed below). 264


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265

Strikingly, when nitrate and phosphate were supplied concomitantly (PN), massive 266

transcriptome changes occur as early as 1 h, with 3372 genes (3.5% of expressed genes) 267

differentially expressed (1514 up-regulated, 1858 down-regulated) (Figure 2A, Table S2). 268

This transcriptional response subsides at 2 h and 4 h with 1350 (1.4% of expressed genes) 269

and 1581 (1.6% of expressed genes) genes differentially expressed, respectively. Another 270

wave of transcriptional response could then be detected at 24 h, with 4618 genes (4.8% of 271

expressed genes) differentially expressed (2080 up-regulated and 2538 down-regulated) in 272

response to PN treatment (Figure 2A, Table S2, Table S8). Altogether, by considering gene 273

expression across the three treatments (pN, Pn and PN relative to pn) and the four time 274

points, 10229 genes (10.8% of expressed genes) (Table S8) were identified as differentially 275

expressed at least in one treatment-time point combination. 276

277

To identify sub-groups within 10229 differentially expressed genes based on the similarity 278

in expression profiles in an unsupervised manner, we carried out a hierarchical clustering 279

analysis (Figure 2B). Intriguingly, Pearson correlation-based clustering of variance-280

stabilized read counts showed that treatments at 1 h induce gene expression changes forming 281

a separate cluster from rest of the treatment-time combinations. This observation implies 282

that early responses to P and N are distinct from the transcriptomic responses at later time 283

points. Furthermore, if P and N signaling pathways were mutually independent, we would 284

expect to see the clustering based on treatment, regardless of the time points. However, the 285

clustering pattern suggests that wheat root responses to P supply are dependent on the supply 286

of N. Our results indicate the combinatorial effects of nitrate and phosphate provision in 287

modulating gene expression and validate our approach that took into account the interaction 288

effects in response to P and N supply. 289

290

To identify the contribution from time factor and treatment to the variation in expression 291

profiles we analyzed multi-dimensional scaling (MDS) plots (Figure 2C, 2D, Figure S2A). 292

The first four dimensions explain 85.7% of the variance (Figure S2A) where first two 293

dimensions essentially recapitulate the patterns observed with hierarchical clustering (Figure 294

2C). While dimension 3 accounts for variance due to time factor, dimension 4 explains 295

variance due to presence or absence of nitrate (Figure 2D). Considering both the overlap of 296

differentially expressed genes (Figure 2A) and the clustering pattern of the treatment 297

comparisons (Figure 2B-2D) we conclude that while concomitant supply of nitrate and 298


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phosphate have a synergistic effect on the transcriptomic dynamics occurring at 1 h, at later 299

time points, the presence of nitrate is required for most of the transcriptional response to 300

occur. 301

302

While the bulk of gene expression changes that require supply of both P and N (PN 303

treatment) happen by 1 h (Figure 2A), the number of genes that respond to N supply 304

regardless of P status (the overlap between pN and PN treatments) gradually increases over 305

time from 9 to 3069 genes (Figure 2A). If a gene is differentially expressed in more than one 306

treatment, directionality of fold change (up- or down-regulation) could indicate whether the 307

gene is transcriptionally regulated the same way by the different treatments. To this end, 308

directionality of fold change (up/down regulation with respect to pn condition) remained the 309

same in all the genes that were differentially expressed in both pN and PN conditions at a 310

given time point (the overlap between pN and PN treatments), except for 311

TraesCS6A01G165100, which was transcriptionally upregulated by N (PN and pN), 312

however the supply of P in the absence of N (Pn) led to its down-regulation at 4 h after 313

treatment (Table S8). This gene is annotated as a nicotianamine synthase in wheat. 314

Congruent with our observations, previous studies have reported up-regulation of 315

nicotianamine synthase genes in response to nitrate supply in Arabidopsis (R. Wang et al. 316

2000; R. Wang et al. 2003). However, in the study by (Shukla et al. 2017), they reported up-317

regulation of NICOTIANAMINE SYNTHASE 2 in response to excess phosphate levels (20 318

mM phosphate and 3.9 mM nitrate) in Arabidopsis. Our results show that wheat 319

nicotianamine synthase TraesCS6A01G165100 is regulated similarly only in the presence 320

of N. This suggests that TraesCS6A01G165100 is regulated by phosphate in a nitrate 321

dependent manner. Since nicotianamine synthase is involved in iron transport (Schuler et al. 322

2012), our results suggest nitrate and phosphate-dependent effects on iron distribution 323

through nicotianamine synthase. 324


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325 326

327

The majority of the studies characterizing nitrate-induced transcriptional responses in 328

Arabidopsis have been carried out in the presence of sufficient phosphate. Considering the 329

emerging evidence of crosstalk between nitrate and phosphate signaling (Kant et al. 2011; 330

Medici et al. 2015, Maeda et al. 2018), our approach enables delineation of the responses to 331

nitrate that are dependent or independent of presence of phosphate. To that end, we 332

performed GO term enrichment analysis using genes that were differentially expressed 333

exclusively in pN vs pn or in PN vs pn treatments at each of the four time points (Table 1, 334

Table S3). 335

336

Z-score normalized expression

PN

pN

3357

7

9 6

Pn4

1 h

PN

pN

322

874

1024 4

Pn2

2 h

PN

pN

553

582

10271

Pn2

4 h

PN

pN

1549

1867

30654

Pn5

24 h

1

A

B C

D

pn_1hpN_1hPn_1h

PN_1h

pn_24h

pN_24h

Pn_24h

PN_24h

pn_2h

pN_2h

Pn_2h

PN_2h

pn_4h

pN_4h

Pn_4h

PN_4h

Dimension_1

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ensi

on_2

time

aaaa

1h

2h

4h

24h

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pn_1h

pN_1hPn_1h

PN_1h

pn_24h

pN_24h

Pn_24hPN_24h

pn_2h

pN_2h

Pn_2hPN_2hpn_4h

pN_4h

Pn_4h

PN_4h

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Dim

ensi

on_6

time

aaaa

1h

2h

4h

24h

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pn_1h

pN_1h

Pn_1h

PN_1h

pn_24h

pN_24h

Pn_24h

PN_24h

pn_2h

pN_2h

Pn_2h

PN_2h

pn_4h

pN_4h

Pn_4h

PN_4h

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on_4

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aaaa

1h

2h

4h

24h

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pn_1h

pN_1h

Pn_1h

PN_1hpn_24hpN_24h

Pn_24h

PN_24hpn_2h

pN_2h

Pn_2h

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N-absent

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pn_1hpN_1hPn_1h

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pn_1h

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PN_1h

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pn_2h

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pn_1h

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Pn_1h

PN_1hpn_24hpN_24h

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pn_4h pN_4h

Pn_4hPN_4h

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aaaa

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24h

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on 4

Dimension 3

N- present

N-absent

Figure 2. Combinatorial effects of nitrate and phosphate provision in modulating gene expression. (A)Venn diagrams showing the overlap of differentially expressed (DE) genes among different treatment comparisons with respect to pn treatment within a time point. (B) Hierarchical clustering of the DE genes based on z-score normalized expression values. Multi-dimensional scaling plots representing variance as vectors in the first four dimensions (C) dimensions 1 and 2; (D) dimensions 3 and 4.


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After 2 h of N supply in the absence of P (pN treatment at 2 h), the over-represented GO 337

terms in the differentially expressed gene set were related to hormonal regulation (“cytokinin 338

metabolism”, “response to auxin stimulus”) (Table 1, Table S3). Specifically, the genes that 339

were up-regulated and assigned to “cytokinin metabolism” GO category at 2 h in response 340

to pN treatment were identified as cytokinin oxidase in wheat (Table S3). This observation 341

is of interest, since cytokinin has been identified as a key hormone in systemic nitrate 342

signaling (Sakakibara et al. 2006) in Arabidopsis. Cytokinin is involved in lateral root 343

development in response to systemic nitrate status by acting as a reporter of nitrate demand 344

of the whole plant (Ruffel et al. 2011; Ruffel et al. 2016). Nitrate is capable of inducing 345

cytokinin oxidases (R. Wang et al. 2003; Scheible et al. 2004), which in turn regulates 346

cytokinin levels by negative feedback mechanisms (Kieber and Schaller 2018). A recent 347

study suggested a role for cytokinin oxidases in modulating shoot meristem growth triggered 348

by nitrate supply (Landrein et al. 2018). Therefore, up-regulation of cytokinin oxidases 349

indicates that by two hours after N supply (in the absence of phosphate) N signaling already 350

is likely to affect cytokinin levels in the roots and, consequently, cytokinin signals moving 351

to the shoot. The genes that were up-regulated in pN treatment and assigned “response to 352

auxin stimulus” GO term are homologous to SAUR-like auxin responsive family genes in 353

Arabidopsis (Table S3). Up-regulation of SAUR-like auxin responsive family members may 354

suggest that by two hours of nitrate supply, auxin levels are also changing in the roots as 355

SAUR gene family members are rapidly induced by auxin (McClure et al. 1989; Abel and 356

Theologis 1996). At 4 h, biological processes related to amino acid biosynthesis are enriched 357

in the pN up-regulated gene set (Table 1) and these results are in agreement with previous 358

reports on transcriptomic responses to nitrate in the presence of phosphate (R. Wang et al. 359

2003; Scheible et al. 2004). However, our results show that in wheat, these processes occur 360

independent of P status. 361

362

Interestingly, cell wall structure related processes such as “cellulose biosynthesis” and 363

“microfibril organization” were enriched in the down-regulated gene sets in response to pN, 364

specially at 24 h (Table1, Table S3). This may suggest that upon nitrate supply, cell division 365

and expansion which ensures longer roots in the search for nitrate is reduced. Five genes 366

(TraesCS5D01G401900, TraesCS5A01G095200, TraesCS5A01G392000, 367

TraesCS5B01G396900 and TraesCS5D01G107900) specifically down-regulated in 368

response to nitrate supply at 24 h were assigned GO terms of “cellulose microfibril 369

organization” and “cell growth” (Table S3) and have been annotated as COBRA-like 370


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14

proteins in wheat. COBRA is a plant-specific glycosylphosphatidylinositol-anchored protein 371

and is upregulated in cells entering the zone of elongation (Roudier 2002) in Arabidopsis. 372

The involvement of COBRA gene family members in shaping up plant root system 373

architecture has been studied in Arabidopsis (Brady et al. 2006; Schindelman et al., 2001; 374

Benfey and Scheres 2000). The five COBRA-like wheat genes that are specifically down-375

regulated at 24 h of nitrate supply are orthologous to COBRA and COBRA-Like 4 in 376

Arabidopsis and BRITTLE STALK-2 (Bk2), BRITTLE STALK-LIKE-3 (Bk2L3) and 377

BRITTLE STALK-LIKE-4 (Bk2L4) in maize (Figure S2B). Bk2L4 is down-regulated within 378

2 h of nitrate starvation, while Bk2L3 remained unresponsive to nitrate starvation (Brady et 379

al. 2006). While both wheat and maize COBRA gene orthologues respond to nitrate (supply 380

or starvation), it is intriguing that the down-regulation of wheat Bk2L3/4 orthologues in 381

response to nitrate supply happens only in the absence of phosphate at 24 h. 382

383

The biological processes enriched in the up-regulated gene category at 1 h in response to PN 384

include carbon metabolism and transport of ions such as nitrate and calcium (Table 1, Table 385

S3). Some of the processes, such as “RNA processing” and “pentose phosphate shunt”, were 386

previously reported to be enriched among the genes up-regulated in response to nitrate 387

supply in the presence of phosphate (R. Wang et al. 2003; Scheible et al. 2004; Krouk et al. 388

2010). Interestingly all the genes that were assigned GO term “malate transport” were 389

annotated as aluminum activated malate transporter family members in wheat (Table S3). 390

Some of these genes (TraesCS7B01G127200, TraesCS7B01G116000, 391

TraesCS7A01G208700, TraesCS7D01G211100) were up-regulated while some 392

(TraesCS6B01G270300, TraesCS6D01G236500, TraesCS2D01G399700, 393

TraesCS2B01G420600) were down-regulated as early as 1 h (Table 1, Table S3). Later in 394

the time course, aluminum activated malate transporter genes were found up-regulated by 395

PN treatment at 2 h and 24 h. Interestingly, wheat aluminum activated malate transporters 396

have been found to be permeable not only to malate, but also to nitrate and chloride (Piñeros 397

et al. 2008; W.-H. Zhang et al. 2008). Moreover, AtALMT1 (ALUMINUM ACTIVATED 398

MALATE TRANSPORTER 1) is a key regulator in modulating root development under 399

phosphate deficiency (Mora-Macías et al. 2017; Balzergue et al. 2017). Therefore, our 400

results suggest involvement of aluminum activated malate transporters in response to nitrate 401

and phosphate, although their precise function (as nitrate transporter or functioning in P 402

starvation induced root development) remains unresolved. 403

404


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15

Moreover, wheat genes annotated as ubiquitin carboxyl-terminal hydrolases were enriched 405

in GO term categories “ubiquitin dependent protein catabolic process” and “protein 406

deubiquitination” (Table 1, Table S3). The Arabidopsis homologues of these genes are 407

members of ubiquitin specific protease (UBP) family (Table S3). While UBP14 is involved 408

in the adaptation of root development to local phosphate availability (W.-F. Li et al. 2010), 409

none of the Arabidopsis homologs in these GO categories were UBP14 (Table S3). 410

Interestingly, nicotianamine synthase genes and Yellow Stripe like (YSL) genes were 411

present in the over-represented GO categories “nicotianamine biosynthetic process” and 412

“transmembrane transport”. Considering nicotianamine synthase (Koen et al. 2013) and 413

YSL genes (Waters et al. 2006; Kumar et al. 2017) are involved in plant iron homeostasis, 414

these results may suggest the changes in the iron homeostasis are affected by concomitant 415

supply of N and P. Moreover, wheat phosphate transporters which are homologous to AtPT1 416

and AtPT1;4 were down-regulated at 4 h, suggesting that plants experience phosphate 417

sufficient conditions by this time, thereby repressing the phosphate transporters. While four 418

cytokinin oxidase genes were present in the “cytokinin metabolic process” category for 419

genes up-regulated at 24 h (Table S3), these genes were not present in the cytokinin oxidase 420

gene set that were responding to pN, suggesting the activity of some wheat cytokinin 421

oxidases may depend on the presence of phosphate. 422

423

Table 1. Lowest level GO terms enriched in pN vs pn and PN vs pn treatment comparisons, 424

along with the fold enrichment (All GO terms shown were enriched with FDR P<0.05). 425

426

Treatment-time combination

GO category Fold enrichment

pN_1 h down phosphatidylcholine biosynthetic process

1151.16

pN_2 h up glutamate biosynthetic process 138.48 nitrate transport 69.24 histidine biosynthetic process 39.57 NAD biosynthetic process 27.70 chloride transport 24.44 cytokinin metabolic process 15.39 zinc ion transmembrane transport 14.58 regulation of cyclin-dependent protein kinase

activity 14.20

response to auxin stimulus 4.48 pN_2 h down L-phenylalanine catabolic process 30.15 fatty acid beta-oxidation 29.61


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16

glutathione catabolic process 23.69 amino acid transmembrane transport 7.05 response to wounding 4.51 oxidation reduction 1.59 pN_4 h up maturation of SSU-rRNA from tricistronic

rRNA transcript (SSU-rRNA, 5.8S rRNA, LSU-rRNA)

121.57

intracellular distribution of mitochondria 91.18 glutamate biosynthetic process 60.79 negative regulation of ethylene mediated

signaling pathway 45.59

isoleucine biosynthetic process 40.52 proline biosynthetic process 39.08 glutathione catabolic process 24.31 histidine biosynthetic process 17.37 defense response to fungus 17.37 response to desiccation 15.20 arginine biosynthetic process 14.59 tricarboxylic acid cycle 14.25 glycolysis 10.80 trehalose metabolic process 9.27 protein amino acid dephosphorylation 8.82 oligosaccharide biosynthetic process 8.05 sulfur amino acid biosynthetic process 6.59 pN_4 h down mitochondrial pyruvate transport 74.42 cell proliferation 62.02 heparan sulfate proteoglycan biosynthetic

process 62.02

glycosaminoglycan biosynthetic process 53.16 response to wounding 20.52 pN_24 h up photosystem II stabilization 34.20 pyrimidine nucleotide biosynthetic process 25.65 glycolipid biosynthetic process 25.65 response to nitrate 25.65 cellular iron ion homeostasis 20.52 nitrate transport 20.52 phosphatidylcholine biosynthetic process 11.40 galactose metabolic process 8.02 pN_24 h down S-adenosylmethionine biosynthetic process 27.18 L-serine biosynthetic process 16.56 L-phenylalanine catabolic process 14.46 galactose metabolic process 13.09 cell growth 11.62 cellulose microfibril organization 11.62 aromatic amino acid family biosynthetic

process 11.36

activation of protein kinase C activity by G-protein coupled receptor protein signaling pathway

11.04


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17

cellulose biosynthetic process 8.76 zinc ion transmembrane transport 6.97 chitin catabolic process 5.74 nicotinamide nucleotide metabolic process 5.27 hemicellulose metabolic process 3.51 cellular cell wall macromolecule metabolic

process 3.46

PN_1 h up protein sumoylation 55.90 glutamate biosynthetic process 55.90 intracellular distribution of mitochondria 55.90 ribosomal large subunit assembly 37.27 phosphatidylserine biosynthetic process 27.95 nitrate transport 20.96 glutamyl-tRNA aminoacylation 15.24 gluconeogenesis 13.97 threonyl-tRNA aminoacylation 12.42 pentose-phosphate shunt 9.58 malate transport 9.32 NAD biosynthetic process 8.38 chloride transport 8.22 histidine biosynthetic process 7.99 protein deubiquitination 6.82 fructose 6-phosphate metabolic process 6.78 glycolysis 6.25 calcium ion transmembrane transport 6.21 trehalose biosynthetic process 5.99 sodium ion transport 5.59 ubiquitin-dependent protein catabolic process 2.01 RNA processing 1.93 PN_1 h down L-serine biosynthetic process 8.77 glucosylceramide catabolic process 8.77 malate transport 7.79 regulation of cyclin-dependent protein kinase

activity 5.99 L-phenylalanine catabolic process 5.10 oligopeptide transport 4.73 xyloglucan metabolic process 4.11 plant-type cell wall organization 3.51 response to oxidative stress 3.36 PN_2 h up malate transport 47.96 zinc ion transmembrane transport 30.29 regulation of response to stimulus 25.03 plant-type cell wall organization 14.39 PN_2 h down transmembrane transport 3.07 PN_4 h up rRNA methylation 98.23 nitrogen compound transport 42.10 pseudouridine synthesis 12.63 metal ion transport 5.59 ammonium transport 28.07


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PN_4 h down abscisic acid biosynthetic process 87.09 allantoin catabolic process 87.09 phosphate transport 38.42 valyl-tRNA aminoacylation 34.83 sulfate transport 15.83 L-phenylalanine catabolic process 14.25 respiratory electron transport chain 9.11 ATP synthesis coupled proton transport 7.46 recognition of pollen 3.61 PN_24 h up glutamate biosynthetic process 71.39 threonine biosynthetic process 42.83 acetyl-CoA biosynthetic process from

pyruvate 21.42 phosphatidylcholine biosynthetic process 21.42 isoleucine biosynthetic process 19.04 L-methionine salvage from

methylthioadenosine 17.13 trehalose biosynthetic process 13.77 nicotianamine biosynthetic process 12.24 malate transport 10.71 tricarboxylic acid cycle 10.71 cytokinin metabolic process 9.52 sulfate transport 7.79 glycolysis 7.33 nucleoside metabolic process 5.91 lipid transport 4.56 PN_24 h down cellular iron ion homeostasis 35.08 mitochondrial pyruvate transport 21.05 oligopeptide transport 7.10 amino acid transmembrane transport 6.26 drug transmembrane transport 3.76 lipid metabolic process 2.04 oxidation reduction 1.38

427

Gene co-expression network analysis reveals gene modules involved 428 in nitrate signaling in wheat 429 430

Correlation based methods using similarity of gene expression profiles to infer functions of 431

the genes through guilt-by-association principle have been widely employed in systems 432

biology research (Wolfe et al. 2005; Lee et al. 2010; Usadel et al. 2009; R. De Smet and 433

Marchal 2010; Banf and Rhee 2017). To perform gene co-expression analysis using 434

WGCNA (Langfelder and Horvath 2008), we selected 8300 genes with the highest variance 435

in gene expression across the entire dataset (top 10%). The gene co-expression module-436


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19

treatment (“module-trait”) relationships that resulted from weighted gene co-expression 437

analysis are shown in Figure 3A and were used to identify modules for further analyses. 438

439

To delineate the independent effects of nitrate or phosphate on gene co-expression from 440

those due to combined nutrients, we selected the modules that showed significant correlation 441

coefficient values in a treatment-dependent pattern. This resulted in a sub-network with ten 442

modules (tan, lightcyan, brown, midnightblue, black, cyan, salmon, red, green and 443

greenyellow modules) (Figure 3A). We identified the top 5 hub genes in each module based 444

on intramodular connectivity. In three of the modules in the sub-network, homeologues of a 445

gene were among the hub genes where black module contained homeologue triad of a 446

dirigent protein, salmon module contained a homeologue triad of a putative LOB domain 447

containing protein and brown module contained homeologue duplet of a high affinity nitrate 448

transporter (Table S4). The functional annotation for these hub genes identified based on 449

intramodular connectivity are shown in Figure 3B. Moreover, to identify the biological 450

processes enriched in each module we carried out a GO term enrichment analysis on the 451

modules. The top 5 GO terms enriched in each module are listed in Table S4. According to 452

this analysis, the brown module contains genes with a function related to nitrate signaling 453

and/or transport (Figure 3B, Table S4). The genes in the brown module also showed 454

expression profiles with higher expression under pN and PN treatments throughout the time 455

course (Figure 3C). 456

457

Based on the principle of guilt-by-association, we predicted the transcription factors co-458

expressed with the genes in the brown module could play a regulatory role in nitrate 459

signaling/metabolism. According to the annotation available for the wheat genome 460

(International Wheat Genome Sequencing Consortium (IWGSC) et al. 2018), the brown 461

module contained 23 transcription factors/transcription factor-like proteins which included 462

homeologue triads of MYB transcription factors (TraesCS2A01G488200, 463

TraesCS2B01G515800, TraesCS2D01G488500 and TraesCS5A01G401600, 464

TraesCS5B01G406300, TraesCS5D01G411800), transcription factor-like proteins 465

(TraesCS1A01G276600, TraesCS1B01G285800, TraesCS1D01G276100) (Table S5). Out 466

of these 23 transcription factors, the two homeologue triads TraesCS5A01G401600, 467

TraesCS5B01G406300, TraesCS5D01G411800 and TraesCS1A01G276600, 468

TraesCS1B01G285800, TraesCS1D01G276100 have Arabidopsis orthologues that are 469

members of HRS1/HHO and TGA gene families, respectively. Since some HRS1/HHO 470


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20

(Medici et al. 2015) and TGA (Álvarez et al. 2014) family members are involved in nitrate 471

signaling and metabolism, we decided to further probe the role of these two homeologue 472

triads in the context of nitrate signaling in wheat. 473

474

475

Module−trait relationships

−1

−0.5

0

0.5

1

PN_1hPN_2hPN_4h

PN_24h

pN_1hpN_2hpN_4h

pN_24h

Pn_1h

Pn_2h

Pn_4h

Pn_24h

pn_1h

pn_2h

pn_4h

pn_24h

MEturquoise

MEpurple

MEtan

MEblue

MEblack

MEmagenta

MEbrown

MEcyan

MEsalmon

MElightcyan

MEred

MEgreen

MEgreenyellow

MEpink

MEmidnightblue

MEyellow

MEgrey

−0.46(9e−04)

0.099(0.5)

0.14(0.4)

0.13(0.4)

−0.41(0.004)

0.063(0.7)

0.13(0.4)

0.1(0.5)

−0.42(0.003)

0.2(0.2)

0.15(0.3)

0.15(0.3)

−0.33(0.02)

0.16(0.3)

0.19(0.2)

0.1(0.5)

−0.2(0.2)

0.031(0.8)

−0.059(0.7)

−0.015(0.9)

−0.15(0.3)

−0.1(0.5)

−0.16(0.3)

−0.05(0.7)

−0.21(0.1)

0.037(0.8)

−0.13(0.4)

0.65(6e−07)

−0.12(0.4)

−0.017(0.9)

−0.086(0.6)

0.59(9e−06)

−0.35(0.01)

−0.14(0.3)

−0.22(0.1)

−0.25(0.08)

0.0021(1)

−0.19(0.2)

−0.3(0.04)

−0.13(0.4)

−0.11(0.4)

0.3(0.04)

0.16(0.3)

0.39(0.007)

0.011(0.9)

0.25(0.08)

0.2(0.2)

0.38(0.008)

−0.12(0.4)

0.029(0.8)

−0.027(0.9)

−0.00054(1)

0.092(0.5)

−0.055(0.7)

−0.18(0.2)

0.11(0.5)

−0.027(0.9)

0.049(0.7)

−0.12(0.4)

0.013(0.9)

0.24(0.1)

−0.074(0.6)

0.00079(1)

0.068(0.6)

−0.18(0.2)

−0.065(0.7)

0.03(0.8)

0.64(1e−06)

−0.17(0.2)

−0.049(0.7)

−0.011(0.9)

0.65(6e−07)

−0.2(0.2)

−0.14(0.4)

−0.14(0.4)

0.042(0.8)

−0.16(0.3)

−0.13(0.4)

−0.13(0.4)

0.013(0.9)

−0.25(0.09)

−0.19(0.2)

−0.12(0.4)

0.39(0.006)

−0.19(0.2)

−0.2(0.2)

−0.18(0.2)

0.42(0.003)

−0.21(0.1)

−0.062(0.7)

−0.031(0.8)

0.45(0.001)

−0.17(0.2)

−0.098(0.5)

0.0076(1)

0.44(0.002)

0.034(0.8)

0.28(0.06)

0.36(0.01)

0.28(0.05)

−0.32(0.03)

0.29(0.04)

0.36(0.01)

0.2(0.2)

−0.33(0.02)

−0.081(0.6)

−0.055(0.7)

−0.26(0.07)

−0.26(0.07)

−0.12(0.4)

−0.09(0.5)

−0.3(0.04)

−0.069(0.6)

0.21(0.1)

0.14(0.3)

0.6(6e−06)

−0.29(0.05)

0.18(0.2)

0.11(0.5)

0.22(0.1)

−0.026(0.9)

−0.22(0.1)

−0.17(0.2)

−0.034(0.8)

−0.18(0.2)

−0.22(0.1)

−0.19(0.2)

−0.07(0.6)

−0.024(0.9)

0.18(0.2)

0.16(0.3)

0.33(0.02)

−0.15(0.3)

0.13(0.4)

0.047(0.8)

0.36(0.01)

−0.21(0.1)

−0.1(0.5)

−0.18(0.2)

−0.13(0.4)

−0.015(0.9)

−0.15(0.3)

−0.14(0.3)

−0.12(0.4)

0.31(0.04)

0.37(0.009)

0.28(0.05)

−0.21(0.2)

−0.0052(1)

0.39(0.007)

0.22(0.1)

−0.29(0.05)

−0.12(0.4)

0.078(0.6)

−0.071(0.6)

−0.37(0.01)

0.021(0.9)

−0.05(0.7)

−0.18(0.2)

−0.38(0.008)

0.23(0.1)

0.14(0.3)

−0.17(0.3)

−0.43(0.002)

0.38(0.008)

0.062(0.7)

−0.19(0.2)

−0.44(0.002)

0.25(0.09)

0.15(0.3)

−0.12(0.4)

−0.2(0.2)

0.41(0.004)

0.18(0.2)

−0.098(0.5)

−0.16(0.3)

−0.21(0.1)

0.19(0.2)

0.076(0.6)

−0.6(7e−06)

0.0047(1)

0.16(0.3)

0.031(0.8)

−0.52(2e−04)

0.0016(1)

0.22(0.1)

0.17(0.2)

−0.0094(0.9)

0.18(0.2)

0.15(0.3)

0.097(0.5)

0.06(0.7)

0.021(0.9)

0.29(0.05)

0.018(0.9)

−0.36(0.01)

0.023(0.9)

0.18(0.2)

0.023(0.9)

−0.46(9e−04)

−0.086(0.6)

0.38(0.007)

0.061(0.7)

−0.26(0.08)

0.0078(1)

0.38(0.008)

0.052(0.7)

−0.26(0.07)

0.31(0.03)

−0.14(0.3)

−0.27(0.06)

−0.11(0.4)

0.29(0.05)

−0.15(0.3)

0.048(0.7)

−0.15(0.3)

0.18(0.2)

−0.17(0.2)

0.1(0.5)

−0.084(0.6)

0.32(0.03)

−0.15(0.3)

0.078(0.6)

−0.081(0.6)

0.28(0.05)

−0.1(0.5)

−0.19(0.2)

0.3(0.04)

0.25(0.09)

−0.1(0.5)

−0.37(0.01)

0.34(0.02)

0.13(0.4)

−0.22(0.1)

−0.26(0.08)

0.084(0.6)

0.22(0.1)

−0.26(0.08)

−0.26(0.07)

0.16(0.3)

0.46(9e−04)

−0.12(0.4)

−0.2(0.2)

−0.049(0.7)

0.46(0.001)

−0.13(0.4)

−0.23(0.1)

−0.032(0.8)

0.36(0.01)

−0.16(0.3)

−0.18(0.2)

−0.042(0.8)

0.34(0.02)

−0.2(0.2)

−0.23(0.1)

−0.046(0.8)

−0.24(0.1)

−0.19(0.2)

0.094(0.5)

0.13(0.4)

−0.15(0.3)

−0.13(0.4)

0.22(0.1)

0.037(0.8)

0.077(0.6)

−0.068(0.6)

0.087(0.6)

0.18(0.2)

0.11(0.5)

−0.27(0.06)

0.0095(0.9)

0.12(0.4)

TurquoisePurpleTanBlueBlack

MagentaBrownCyan

SalmonLightcyan

RedGreen

GreenyellowPink

MidnightblueYellowGrey

A

B C

Glutathione S-transferase

GDSL esteraseGermin-like protein

High affinitynitrate transporter

Aldose-1 epimerase

Protein kinaseWound responsivefamily protein

Ammonium transporter

LOB domain containing protein

Dirigent protein Nor

mal

ized

logF

C

Pn pN PN

10.0

0.0

-10.0


https://doi.org/10.1101/551069

21

476

Wheat HRS1/HHO and TGA family members show functional 477

divergence from Arabidopsis orthologues in response to nitrate 478

479 Given the role of the HRS1/HHO gene family in response to N and P in Arabidopsis and rice 480

(Medici et al. 2015; Maeda et al. 2018; Kiba et al., 2018), we explored gene expression 481

dynamics of the wheat HRS1/HHO gene family in response to nitrate and phosphate supply. 482

Firstly, we identified putative wheat HRS1/HHO orthologues by protein sequence alignment 483

using reciprocal BLAST. This confirmed that all the wheat HRS1/HHO sequences contain 484

the conserved G2-like DNA binding domain (Figure S3A). A maximum likelihood-built 485

gene tree showed that a single wheat homeologue triad falls within the AtHRS1 and 486

OsNIGT1 clade, another homeologue triad groups within the AtHHO4 clade, while three 487

homeologue triads cluster within the AtHHO5/HHO6 clade (Figure 4A). Of those 15 wheat 488

HRS1/HHO orthologues, only 10 genes were found to be differentially expressed in at least 489

one treatment-time combination in our dataset (Figure 4A). 490

Interestingly, the three wheat HRS1 (TaHRS1) genes (TraesCS2A01G116100, 491

TraesCS2B01G135600, TraesCS2D01G119100) showed up-regulation only at 24 h in 492

response to nitrate supply in the absence of phosphate. This delayed transcriptional response 493

was unexpected of TaHRS1, as previous studies on rice (Sawaki et al. 2013) and Arabidopsis 494

(Krouk et al. 2010) have reported HRS1/NIGT1 to be up-regulated within 1 h of nitrate 495

supply. However, the seven wheat genes that are closely related to AtHHO5/HHO6 496

(TaHHO5/6 genes) (TraesCS5B01G075300, TraesCS2D01G259200, 497

TraesCS2B01G277300, TraesCS2A01G264800, TraesCS5D01G411800, 498

Figure 3. Weighted gene co-expression network (WGCNA) analysis identified gene modules involved in nitrate signaling in wheat. (A) Heatmap showing expression between network modules and the treatments (traits). Module eigengenes were calculated using WGCNA package and each cell shows the corresponding correlation value and its P-value. Color scale corresponds to the correlation values. Cells outlined in black represent the module-trait relationships selected for further analysis. (B) The hub genes were identified based on intramodular connectivity. (C) Gene expression profile for the Brown module; Y axis represents the normalized log fold change (logFC) values where expression was measured as treatment/reference (i.e. pn) for a given time point; mean (black or gold or orange line) is shown for all the genes (shaded lines) in the module.


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TraesCS5B01G406300, TraesCS5A01G401600) showed up-regulation upon nitrate supply 499

at early time points, and remained induced for the rest of the 24 h of treatment (Figure 4A). 500

Specifically, all TaHHO5/6 genes but TraesCS5B01G075300, were up-regulated by PN 501

treatment at 1 h, and remained up-regulated in PN and pN conditions at later time points. 502

TraesCS5B01G075300 was up-regulated in PN and pN treatments from 2-24 h (Table S8). 503

This pattern of gene expression indicated that N regulation of the wheat HRS1/HHO gene 504

family may have functionally diverged from that of Arabidopsis and rice, and, consequently, 505

the downstream genetic targets of TaHRS1 and TaHHO5/6 may also be regulated in a 506

different manner. 507

It has been estimated that a plant gene can be directly regulated by 6-40 transcription factors 508

(Pal et al. 2017). We therefore tested the hypothesis that TaHRS1 and TaHHO5/6 differ in 509

their transcriptional responses to N at least in partly due to having different transcription 510

factor binding motifs (TFBM) present within their promoters. We used MEME (Bailey et 511

al. 2009) to identify enriched promoter motifs followed by TOMTOM (Khan et al. 2018) 512

TFBM comparison analysis of DNA regions 1 kb upstream from transcription start site and 513

identified 11 plant TFBM within the promoter of TaHRS1 genes (TraesCS2A01G116100, 514

TraesCS2B01G135600, TraesCS2D01G119100) (Table S7). These 11 TFBM included 515

KANADI, ERF10, homeodomain-like superfamily proteins and Myb-like transcription 516

factors. Except ERF10, the 10 transcription factors predicted to bind to TaHRS1 promoters 517

all belong to the G2-like transcription factor family (Table S7). On the other hand, the same 518

analysis of the nine TaHHO5/6 gene promoters (TraesCS5B01G075300, 519

TraesCS2D01G259200, TraesCS2B01G277300, TraesCS2A01G264800, 520


TraesCS5D01G081000, TraesCS5A01G068900) identified 118 plant TFBM (Table S7). 522

Among these 118 TFBM, Dof, MADS box and G2-like TFBMs were the most abundant 523

types (Figure S5C, Table S7). All but two G2-like TFBM identified in TaHRS1 promoters 524

were also present in TaHHO5/6 promoters (Table S7). The larger diversity of TFBM within 525

the promoters of the TaHHO5/6 genes may result in increased responsiveness to a wider 526

array of signals. On the other hand, apparent lack of similar level of TFBM diversity within 527

TaHRS1 promoters may also be due to failure to properly identify wheat-specific TFBM 528

using currently available tools and database of plant TFBM. 529

In order to identify the regulators of TaHRS1 and TaHHO6 we used a different approach 530

where we attempted to infer regulatory networks from gene expression data as implemented 531


https://doi.org/10.1101/551069

23

in GENIE3 (Huynh-Thu et al. 2010). Using this tree-based ensemble approach on the gene 532

expression matrix containing 8300 genes (top 10% genes by expression variance, see above) 533

and the 389 transcription factors (as annotated by the (International Wheat Genome 534

Sequencing Consortium (IWGSC) et al. 2018)) present within the 8300 genes, 22 predicted 535

regulators were found to be regulating both members of the homeologue duplet of TaHRS1 536

(TraesCS2A01G116100, TraesCS2D01G119100) (Table S6). Similarly, 29 regulators were 537

commonly predicted for the homeologue triad of TaHHO5/6 (TraesCS5D01G411800, 538

TraesCS5B01G406300 and TraesCS5A01G401600 ) (Table S6). These genes we refer to as 539

“common regulators” herein. While the majority (10 regulators, Fisher’s exact test P = 1.7e-540

31) of the predicted common regulators were shared between homeologues for TaHRS1 or 541

TaHHO6 (Table S6), there were genes that regulated one of the TaHRS1 or TaHHO6 542

homeologues, but not all (Figure 6). Interestingly, the predicted common regulators of 543

TaHRS1 and TaHHO6 included wheat homologues of AtNLP7 and AtLBD37. In 544

Arabidopsis, NLP7 is a direct transcriptional regulator of HRS1/HHO family members in 545

response to nitrate (Medici et al. 2015; Marchive et al. 2013) while the role of LBD37 in 546

HRS1/HHO regulation remains unclear (Kiba et al., 2018; Rubin et al. 2009), even though 547

its involvement in regulation of early nitrate responses has been confirmed (Rubin et al. 548

2009; Varala et al. 2018), suggesting that LBD37 may act upstream of at least some 549

HRS1/HHO family members. Altogether, our results suggest that TaHRS1/HHO also 550

require NLP7 and LBD37, while the unique regulators of TaHRS1 and TaHHO5/6 possibly 551

contribute to differences in the downstream activity of TaHRS1 and TaHHO5/6. 552

553

We further investigated this apparent functional divergence within the wheat HRS1/HHO 554

gene family using co-expression network analysis. Out of the 15 TaHRS1/HHO homologues, 555

only five genes (TraesCS2A01G116100, TraesCS2D01G119100, TraesCS5D01G411800, 556

TraesCS5B01G406300 and TraesCS5A01G401600) showed significant co-expression 557

correlation and were assigned to gene co-expression modules (Figure 4A). 558

TraesCS2A01G116100 and TraesCS2D01G119100, which are closely related to OsNIGT1 559

(AtHRS1), were assigned to turquoise and black modules respectively. The TaHHO5/6 genes 560

(TraesCS5D01G411800, TraesCS5B01G406300 and TraesCS5A01G401600) were 561

assigned to the brown co-expression module. Since TraesCS2A01G116100 was assigned to 562

the turquoise module, we included the turquoise module in our co-expression sub-network. 563

The GO term enrichment analysis identified nicotianamine metabolism and biogenic amine 564

metabolism processes enriched in the black module (containing the TaHRS1 gene 565


https://doi.org/10.1101/551069

24

TraesCS2D01G119100), while processes related to oxidative stress were enriched in the 566

turquoise module (containing the TaHRS1 gene TraesCS2A01G116100) (Table S4). As 567

noted above, the brown module, containing the three TaHHO5/6 homeologues, showed 568

statistically significant enrichment of the GO terms of nitrogen signaling and/or transport 569

(Figure 3B, Table S4). 570

571

Furthermore, when we compared the wheat HRS1 and HHO5/6 co-expressed genes to the 572

list of differentially expressed genes, 612 out of 699 HHO5/6 co-expressed genes (88%) 573

were found differentially expressed in response to N/P treatments. The GO term enrichment 574

analysis of these 612 genes identified over-represented processes related to nitrate signaling 575

and metabolism (Figure 4B). On the other hand, the 126 (40%) genes at the intersect of genes 576

co-expressed with TaHRS1 and the differentially expressed genes do not show any 577

enrichment for processes related to nitrate signaling and metabolism (Figure 4B). These 578

results together with our gene expression profiling results support our hypothesis that the 579

N/P responses in wheat are more likely to be mediated by the TaHHO5/6 gene regulatory 580

network(s) than the TaHRS1 one(s). 581

582

In order to identify candidate direct TaHRS1- or TaHHO5/6-target gene interactions, we 583

considered the GENIE3 predictions. We then considered the putative common targets of 584

TraesCS2A01G116100 and TraesCS2D01G119100 (TaHRS1) predicted by the GENIE3 585

analysis, and found that a significant portion of 205 predicted targets (65%, 133 targets, 586

Fisher’s exact test P = 3.6e-85) were also differentially expressed, while only a small 587

proportion of them (14 genes, 7%, Fisher’s exact test P = 1.7e-15) were shared with the 588

TaHRS1 co-expressed genes (Table S6, Figure S5A). Moreover, most of the predicted 589

targets of TaHRS1 showed similar expression dynamics as TaHRS1, whose marked up-590

regulation was observed only at 24 h in response to pN treatment. Despite this, the GO terms 591

enrichment analysis of the 205 predicted HRS1 target genes also showed enrichment for GO 592

terms “nicotianamine metabolism” and “cellular amine metabolic process”. This further 593

supports the notion that TaHRS1 genes may be regulating a class of genes which are 594

functionally different from their counterparts in Arabidopsis. Nicotianamine metabolism 595

plays a crucial role in metal ions transport (Fe and Zn) in plants (Schuler et al. 2012; 596

Takahashi et al. 2003; Hofmann 2012). Nicotianamine has been considered a metal ion 597

chelator that enables proper distribution of metal ions among source and sink tissues 598

(Schuler et al. 2012; Conte and Walker 2011), while contributing to prevent metal ion 599


https://doi.org/10.1101/551069

25

toxicity (Wiren N et al. 1999). Up-regulation of nicotianamine synthase genes have been 600

reported in response to nitrate supply which has been thought to be a response to facilitate 601

transport of Fe required for synthesis of nitrate assimilatory enzymes such as nitrate 602

reductase and nitrite reductase (R. Wang et al. 2003). While nicotianamine synthase gene 603

NAS3 was induced under P starvation (Bournier et al. 2013), NAS2 was up-regulated under 604

excess P condition (Shukla et al. 2017). Therefore, nitrate or phosphate treatments trigger 605

changes in the nicotianamine levels which may lead to precise regulation of metal ion 606

transport. Considering the gene expression dynamics of TaHRS1 homeologue triad, the 607

GENIE3-predicted targets of TraesCS2A01G116100, TraesCS2D01G119100 , the 608

biological processes enriched in the black and turquoise co-expression modules, and the 609

biological processes enriched in the predicted targets of TaHRS1, we propose that TaHRS1 610

may be regulating nitrate-dependent metal ion transport in the absence of phosphate. 611

612

Similar to the results of the WGCNA analysis, GENIE3 identified a larger set of predicted 613

common gene targets of TraesCS5D01G411800, TraesCS5B01G406300 and 614

TraesCS5A01G401600 (TaHHO5/6) than TaHRS1 (Table S6) with 754 predicted 615

TaHHO5/6 targets. While 644 out of 754 predicted targets (85%, Fisher’s exact test P = 0) 616

were differentially expressed in at least one treatment-time combination, a much larger 617

proportion (537 genes) of the TaHHO5/6 predicted targets were also co-expressed with 618

TaHHO5/6 genes (71%, Fisher’s exact test P = 0) (Figure S5B, Table S6). GO term 619

enrichment analysis on these 754 predicted TaHHO5/6 targets revealed that processes such 620

as “response to nitrate”, “nitrate transport”, “glutamate biosynthetic process” were enriched. 621

622

This result corroborates our hypothesis of the possible functional convergence in the 623

background of genetic divergence of some of the TaHRS1/HHO family members in 624

mediating nitrate transcriptional responses and the regulatory roles these two transcription 625

factors play in wheat P/N responses. Altogether our results suggest that, TaHRS1 and 626

AtHRS1 are functionally divergent, while TaHHO5 and AtHRS1 show functional 627

convergence while being genetically divergent. These differences may be due to TaHHO5/6 628

rapid induction by nitrate that initiates a transcriptional response cascade as a primary 629

response to nitrate supply. Meanwhile, TaHRS1 is induced later in the time course and 630

regulates secondary processes, such as metal ion transport. However, it should also be noted 631

that these putative transcription factor – target relationships are predicted based on gene 632


https://doi.org/10.1101/551069

26

expression dynamics and the post-transcriptional level regulation by TaHRS1/HHO 633

members may be different. 634

635

In line with their divergent regulation and predicted function as transcription factors, the set 636

of genes that are co-expressed with either the two TaHRS1 or the three TaHHO5/6 637

homeoalleles are different, despite their homeologue relationships. For example, 638

TraesCS2A01G116100 and TraesCS2D01G119100, the TaHRS1 homeoalleles, share 85 co-639

expressed genes (85/315 or only 27%) (Figure 4D). Meanwhile, the TaHHO5/6 homeoallele 640

triad (TraesCS5D01G411800, TraesCS5B01G406300 and TraesCS5A01G401600) shares 641

470 co-expressed genes (66% of genes co-expressed with the entire TaHHO5/6 triad) while 642

another 92 genes (13%) are co-expressed with either two of the three TaHHO5/6 643

homeoalleles (Figure 4C). This suggests that presence of active homeoalleles may increase 644

the complexity of wheat gene regulatory networks. 645

646

Altogether, these results suggest that TaHHO5/6 orthologues are functionally more related 647

to AtHRS1 and OsNIGT1(Figure 4B), while TaHRS1 may have a different role in mediating 648

N/P responses in wheat, in line with its delayed transcriptional responses (Figure 4A). 649

650


https://doi.org/10.1101/551069

27

651

Wheat DEG

10103126

TaHRS1 co-expressed

189

Wheat DEG9617

612TaHHO5/6 co-

expressed87

Co-expressed with HRS1 Co-expressed with HHO5/6response to oxidative stress nitrate transportresponse to chemical stimulus response to nitrateresponse to stress glutamine amino acid biosynthesis

C4-dicarboxylate transport nitric oxide metabolismmalate transport nitric oxide biosynthesisdicarboxylic acid transport glutamate biosynthesisoxidation reduction inorganic anion transportresponse to stimulus nitrate metabolismcarboxylic acid transport nitrate assimilationorganic acid transport transmembrane transportmetal ion transport carbon utilization

A

B C

D

A25

88B D1547057 24

20

A D200

8530

TraesCS2A01G116100 TraesCS2D01G119100 TraesCS2B01G135600 Os02g0325600 OsNIGT1 At1G13300 HRS1 At3G25790 HHO1 At1G25550 HHO3 At1G68670 HHO2 At2G03500 HHO4 EFM TraesCS3A01G123700 TraesCS3B01G144100 TraesCS3D01G125300 At4G37180 HHO5 At1G49560 HHO6 TraesCS5D01G081000 TraesCS5B01G075300 TraesCS5A01G068900 TraesCS2D01G259200 TraesCS2B01G277300 TraesCS2A01G264800 TraesCS5D01G411800 TraesCS5B01G406300 TraesCS5A01G401600 At2G01060 Myb-like

100

7999

73

72100

87

6299

98

62

99

4899

72

48

81

52

83

38100

PN_1h

pN_1h

Pn_1h

pn_1h

PN_2h

pN_2h

PN_4h

pN_4h

PN_24h

pN_24h

Pn_2h

pn_2h

Pn_4h

pn_4h

Pn_24h

pn_24h

TaHRS1

TaHHO5/6

Figure 4. Functional divergence of HRS1/HHO gene family members in wheat. (A) Maximum likelihood-based (JTT matrix-based model) gene tree for the HRS1/HHO gene family members from rice, Arabidopsis and wheat along with gene expression patterns of the wheat HRS1/HHO genes; genes in red boxes were assigned to co-expressed modules in the co-expression network. The percentage of trees in which the associated genes clustered together is shown next to the branches. (B) Functional differences, determined by GO term enrichment, between genes that are co-expressed with TaHRS1 or TaHHO5/6 and are also differentially expressed in response to N/P. (C) The overlap of the genes that are co-expressed with wheat TaHHO5/6 orthologues in a homeologue-specific context - the 699 genes that were co-expressed with TaHHO5/6 were further grouped based on which homeologue of TaHHO5/6 they were co-expressed with; 470 (67%) of co-expressed genes were shared by the TaHHO5/6 triad, (D) The overlap of the genes that are co-expressed with wheat TaHRS1 orthologues in a homeologue-specific context: of the 315 genes that were co-expressed with TaHRS1 only 27% of co-expressed genes were shared between TaHRS1_2A and TaHRS1_2D.


https://doi.org/10.1101/551069

28

The TGA gene family members are transcription factors characterized by the presence of 652

bZIP_1 signature DNA binding domain and their ability to bind to the TGAGC promoter 653

motif (Lebel et al. 1998; Gatz 2013). In Arabidopsis, 10 TGA gene family members have 654

been identified (Jakoby et al. 2002). TGA family members were first identified to be 655

involved in pathogenesis related processes (Subramaniam et al. 2001; Fan and Dong 2002), 656

however, TGA1 and TGA4 have been shown to regulate root development in response to 657

nitrate (Álvarez et al. 2014). None of the other Arabidopsis TGA family members have been 658

found to be involved in nitrate signaling/metabolism (Álvarez et al. 2014). Our analysis 659

showed that the TGA gene family in wheat consists of at least 38 members (as identified 660

through reciprocal BLAST), all of which possess the conserved bZIP_1 DNA binding 661

domain (Figure S3B-C). Out of 9 wheat TGA genes (TraesCS3A01G372400, 662


TraesCS1B01G285800, TraesCS1D01G276100, TraesCS4A01G183400, 664

TraesCS4B01G135000 and TraesCS4D01G129900) that form a separate clade with three 665

members of the rice TGA family, 8 genes were differentially expressed in at least one 666

treatment-time combination (Figure 5A). Since only TraesCS1A01G276600, 667

TraesCS1B01G285800 and TraesCS1D01G276100 were assigned to modules in WGCNA 668

analysis and differentially expressed, we focused more on these three genes. Based on 669

sequence homology, TraesCS1A01G276600, TraesCS1B01G285800 and 670

TraesCS1D01G276100, (constituting a homeologue triad) were found to be most closely 671

related to Os05g0443900 (Liguleless2), through a reciprocal BLAST (Figure 5A, Figure S4). 672

Since AtTGA9/10 are the closest Arabidopsis TGA family members to 673

TraesCS1A01G276600, TraesCS1B01G285800 and TraesCS1D01G276100 on the gene tree 674

(Figure 5A, Figure S4), we refer to TraesCS1A01G276600, TraesCS1B01G285800 and 675

TraesCS1D01G276100 triad as TaTGA9/10 herein. In contrast to Arabidopsis, we did not 676

detect differential expression of wheat TGA1/4 homologues (TraesCS2A01G526300, 677

TraesCS2B01G556600, TraesCS2D01G529000), and they were not assigned to modules in 678

the WGCNA network. However, we detected TaTGA9/10 orthologues as differentially 679

expressed (up-regulated under PN condition throughout the time course and under pN 680

condition 2-24 h (Table S8)) and co-expressed with nitrate signaling/metabolism related 681

genes in the brown module (Figure 4C). This may suggest possible sub-functionalization of 682

wheat TGA members in regulating nitrate signaling/metabolism. Similar to the TaHHO5/6 683

homeologue triad, when the TaTGA9/10 co-expressed genes were considered in a 684

homeologue-specific context, 454 genes out of 517 genes (88% of co-expressed genes with 685


https://doi.org/10.1101/551069

29

TaTGA9/10 triad) were co-expressed with all three TaTGA9/10 genes (Figure 5B). Since the 686

TaTGA9/10 triad was loosely annotated as “transcription factor like proteins”, our gene co-687

expression analysis identified putative functions of this homeologue triad in the context of 688

nitrate signaling/metabolism. And our results suggest that in wheat, TaTGA9/10 triad is 689

functionally convergent with AtTGA1/4 despite being genetically divergent. 690

Moreover, our GENIE3 analysis predicted 1107 common putative target genes downstream 691

of TaTGA9/10 genes (Table S6). These are enriched for processes such as “nitrate 692

assimilation”, “malate transport” and “glutamate biosynthetic processes”, with 850 of the 693

1107 (76.7%, Fisher’s exact P = 0) targets also differentially expressed in at least one of the 694

treatment-time combinations, while 447 targets (40.3%, Fisher’s exact P = 0) were co-695

expressed with TaTGA9/10. Intriguingly, phosphate transporters (12 genes homologous to 696

AtPT1 and AtPHO1) and SPX domain containing proteins (8 genes homologous to 697

AtSPX2/3, AtPHT5;1) were also among the predicted TaTGA9/10 targets (Table S6), out of 698

which 4 phosphate transporter genes and 3 SPX domain containing genes were co-expressed 699

as well. Indeed it has been reported that most phosphate transporters and phosphate 700

starvation induced genes, including SPX1/3/4 and PHO1, possess TGAGC motif (Baek et 701

al. 2017). Our results suggest that TaTGA9/10 participates in the nitrate dependent regulation 702

of phosphate starvation responses and transport, and as such, likely plays a role in integrating 703

nitrate and phosphate signals. 704

705

706


https://doi.org/10.1101/551069

30

707

708

Considering the evidence for possible functional divergence of TaHRS1/HHO and TaTGA 709

gene family members, with TaHHO5/6 and TaTGA9/10 being prominent in wheat nitrate 710

signaling/metabolism by regulating hundreds of target genes, we expected that a 711

transcriptional network of TaHRS1/HHO and TaTG9/10 members and their regulators 712

would be important in identifying regulatory mechanisms underpinning TaHRS1/HHO and 713

TaTGA9/10 transcriptional responses to N and P provision. To this end, we used the GENIE3 714

TraesCS5B01G265300 TraesCS5D01G273500 TraesCS5A01G265600 Os09g0489500 AT5G06839 AtTGA10 Os09g0280500 TraesCS5A01G174200 TraesCS5D01G178800 Os06g0614100 Os02g0194900 TraesCS6D01G154400 TraesCS6A01G165800 TraesCS6B01G193200 AT1G08320 AtTGA9 TraesCS3A01G372400 TraesCS3D01G365200 TraesCS3B01G404800 Os01g0859500 TraesCS1B01G285800 TraesCS1D01G276100 TraesCS1A01G276600 Os05g0443900 Os11g0152700 Os12g0152900 TraesCS4A01G183400 TraesCS4B01G135000 TraesCS4D01G129900 AT5G65210 AtTGA1 AT5G10030 AtTGA4 AT1G22070 AtTGA3 AT1G77920 AtTGA7 Os04g0637000 Os08g0176900 TraesCS2D01G529000 TraesCS2A01G526300 TraesCS2B01G556600 Os05g0492000 TraesCS1D01G105300 TraesCS1A01G096300 TraesCS1B01G127400 AT5G06950 AtTGA2 AT3G12250 AtTGA6 AT5G06960 AtTGA5 Os03g0318600 Os07g0687700 TraesCS4A01G126300 TraesCS4D01G180200 TraesCS4B01G178600 TraesCS2B01G113200 TraesCS2D01G096800 TraesCS2A01G097500 Os01g0279900 TraesCS3A01G190700 TraesCS3B01G220400 TraesCS3D01G194800 TraesCS3B01G365100 TraesCS3D01G327600 TraesCS3A01G334100 Os01g0808100 AT1G68640 AtTGA8 PAN Os01g0882200 Os10g0566200 Os06g0265400 TraesCS7B01G114300 TraesCS7D01G209800 TraesCS7A01G207100 SELMODRAFT 231689 EFJ28227

99

98

9697

89

80

7791

7377

6999

82

6980

9879

61

5995

69

55

53

5087

98

39

3942

58

36

48

3596

91

35

3499

68

86

3398

76

30

30

1929

18

18

17

17

41

43

39

27

16

1553

19

13

15

8

6

7

PN_1h

pN_1h

Pn_1h

pn_1h

PN_2h

pN_2h

PN_4h

pN_4h

PN_24h

pN_24h

Pn_2h

pn_2h

Pn_4h

pn_4h

Pn_24h

pn_24h

TaTGA9/10

A2

12B D2045417 7

5

Wheat DEG9746

483TaTGA9/10

co-expressed34

Co-expressed with TaTGA9/10nitric oxide metabolismnitric oxide biosynthesistransmembrane transport

nitrate metabolismnitrate assimilationcarbon utilizationglucose metabolisminorganic anion transport

A B

C

Figure 5. Functional divergence of TGA gene family members in wheat. (A) Segment of the maximum likelihood based (JTT matrix-based model) gene tree for the TGA family members from rice, Arabidopsis and wheat along with gene expression patterns of wheat TGA orthologues; genes in red boxes were assigned to co-expressed modules in the coexpression network. The percentage of trees in which the associated genes clustered together is shown next to the branches; full gene tree is in Figure S4. (B) The overlap of the genes that are co-expressed with TaTGA9/10 orthologues in a homeologue-specific context; the 517 genes that were co-expressed with TaTGA9/10 were further grouped based on which homeologue of TaTGA9/10 they were co-expressed with; 88% of co-expressed genes were shared by TaTGA9/10 triad. (C) Genes that are both co-expressed with TaTGA9/10 and differentially expressed are involved in nitrate signaling and metabolism.


https://doi.org/10.1101/551069

31

predictions to identify putative regulatory relationships between transcriptional regulators of 715

TaHRS1 homeologue duplet, TaHHO5/6 homeologue triad, TaTGA9/10 homeologue triad 716

(Figure 6, Table S9). Indeed, we found that wheat NLP7 genes (TraesCS6A01G102400, 717

TraesCS6B01G130800 and TraesCS6D01G091000) were among regulators shared between 718

TaHRS1, TaHHO5/6 and TaTGA9/10 highlighting the central regulatory role played by 719

NLP7 genes in wheat nitrate responses. In addition to wheat NLP7 genes, 720

TraesCS6A01G287700 (Dof zinc finger protein homologous to AT2G37590) and a 721

homeologue triad (TraesCS2A01G488200, TraesCS2B01G515800 and 722

TraesCS2D01G488500) of a MYB-like transcription family protein homologous to 723

AT5G06800, a MYB-HTH transcriptional regulator family protein, were also shared 724

regulators of TaHRS1, TaHHO5/6 and TaTGA9/10 (Figure 6, Table S9), suggesting that 725

these transcription factors play a role in regulating wheat nitrate responses. While 726

AT2G37590 and AT5G06800 have not been characterized in the context of nitrate regulation, 727

gene co-expression data from Arabidopsis suggest that AT5G06800 is co-expressed with 728

AtHRS1 (Obayashi et al. 2018). Moreover, the targets of wheat LBD37 genes 729

(TraesCS4B01G078800, TraesCS2B01G212400, TraesCS4D01G077600 and 730

TraesCS4A01G236200) also included TaHRS1, TaHHO5/6 and TaTGA9/10 (Figure 6, 731

Table S9). These results are consistent with observations made about NLP7 (Medici et al. 732

2015; Marchive et al. 2013) and LBD37 (Rubin et al. 2009; Varala et al. 2018) regulatory 733

roles in Arabidopsis. TaHHO5/6 and TaTGA9/10 expression dynamics were also consistent 734

with their being regulated by each other, as predicted by the GENIE3 analysis. However, the 735

exact nature of this cross-regulation remains unresolved due to a lack of fine scale temporal 736

resolution in our dataset. 737

In our transcriptional regulatory network, we could also identify regulators that were 738

predicted to be regulating only TaHRS1 or TaHHO5/6 or TaTGA9/10 (Figure 6, Table S9). 739

For example, wheat genes homologous to AtLBD41 and AtRAV2 were predicted to be 740

specifically regulating only the TaHHO5/6 triad, while genes homologous to AtNAC058 and 741

AtWRKY24 were predicted to be specifically regulating TaTGA9/10 triad (Figure 6, Table 742

S9). Although these regulatory relationships are predicted based on gene expression and 743

therefore any post-transcriptional/translational effects are likely missed, our results suggest 744

that the regulatory roles played by genes such as NLP7 and LBD37 are conserved in wheat, 745

while identifying candidate genes, such as TraesCS2A01G488200, TraesCS2B01G515800 746

and TraesCS2D01G488500, which may play a central role in regulating wheat nitrate 747


https://doi.org/10.1101/551069

32

responses. 748

749

750

751 752

753

Plants sense multiple nutritional signals and show coordinated responses to these signals as 754

suggested by the emerging evidence for crosstalk between nutrient signaling mechanisms 755

such as those between nitrate and phosphate signaling (Kellermeier et al. 2014; Medici et 756

al. 2015). Hence, studying the combined effects exerted by nitrate and phosphate on the 757

transcriptional response within wheat roots identified the synergistic effects of N and P 758

supply on gene expression as early as 1 h post-treatment, while also identifying other, 759

mutually independent transcriptional responses in wheat. Using recent wheat genome 760

annotation, we identified instances of likely functional divergence in transcription factor 761

gene families prominent in nitrate signaling and metabolism. Analysis of gene co-expression 762

HB7_5A

HRA1_3A

OBP1_2A

HB5_4B

LBD37_4A

HRA1_3D

bZIP48_5A

WRKY35_1D

ERF71_5B

WRKY22_7B

HB1_5B

MYBS1_7A

ERF72_1D

MYB111_3A

bZIP25_5A

TaHRS1_2A

bHLH39_3D

LBD37_4D

bHLH39_3A CSP1_2D

NAC058_4D

HB5_4ATaHRS1_2D

EMB3114_4D

ERF_3A

HSFA6B_1A bHLH100_3B

TaHHO5/6_5A

LBD41_2D

Dof_2B

MYB20_5ALBD37_4B

WRKY62_2B

ERF73_4A

NLP7_6ANLP7_6B

LBD40_3B

TaHHO5/6_5B LBD41_2A

RL3_4D

RAV2_3B

NLP7_6D

TaHHO5/6_5D

NAC1L_2A

WRKY62_2D

bZIP48_5D

HRA1_3B

Dof_2D

WRKY35_1B

RVE1_6A

LBD37_2B

TaTGA9/10_1B

ERF74_4A

WRKY50_3A

DREB1A_5D

TaTGA9/10_1D

TaTGA9/10_1A RL6_5B

MYB_HTH_2D

Dof_6AMYB_HTH_2A

WRKY72_7D

MYB_HTH_2B

MYB111_3BERF71_1A

ERF_1B

NAC058_4B

WRKY24_3D

NAC058_4A

bZIP14_2B

bHLH_4B

WRKY72_7D MYBS1_4A

Figure 6. Predicted relationships between TaHRS1, TaHHO5/6, TaTGA9/10 and their regulators. The node colors correspond to the module color on WGCNA network, except genes belonging to black module are represented in light purple for clarity. Edges represent a weight measure >0.005 as calculated by GENIE3. The nodes are named based on their sequence homology to Arabidopsis.


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33

networks identified gene modules that are involved in wheat nitrate signaling and 763

metabolism which begins to unravel the complex and intricate nutrient signaling components 764

in wheat and will be helpful in prioritizing candidate genes to increase nutrient use efficiency 765

in wheat. 766

767

Materials and methods 768

769

Plant growth and treatment 770

Surface sterilized wheat seeds (variety Chinese spring) were pre-imbibed at 4 0C overnight 771

and transferred on to moistened rock wool plugs in a hydroponics system and the plants were 772

grown at 24 0C in a growth chamber at 16 h photoperiod. The seedlings were grown in water 773

for 11 days before treating them with nutrients. After 11 days, water was replaced with 774

nutrient solutions of varying nitrate and phosphate concentrations. Composition of the 775

nutrient solutions is available in Table S10. Briefly, the plants were subjected to 0.5 mM (P-776

sufficient) or 0 mM (P-deficient) phosphate in the form of KH2PO4 and 2 mM (N-sufficient) 777

or 0 mM (N-deficient) nitrate in the form of Ca(NO3)2. The nutrient solution was changed 778

once in every three days and for RNA extraction, total roots were harvested after 1 h, 2 h, 4 779

h and 24 h of transferring to the nutrient solution, snap-frozen in liquid nitrogen and stored 780

at -80 0C. The plant root measurements were taken after 7 days of treatment. Four – six of 781

18-da old wheat seedlings that were grown in nutrient solutions were used for in planta 782

nutrient content measurements. Nitrogen content was analyzed by combustion. Phosphorus 783

content was analyzed by ICPOES on samples open-vessel digested using 5:1 mixture of 784

nitric and perchloric acids. 785

786

RNA extraction and library preparation 787 788 Samples were collected in triplicate per treatment-time point combination and each sample 789

contained root tissue from four - six plants. Total RNA was extracted from 48 samples using 790

TRI-reagent (SIGMA-ALDRICH) according to manufacturer’s instruction. The RNA 791

samples were treated with DNase I (NEW ENGLAND BIOLABS) and poly-A RNA 792

selection was carried out using Dynabeads mRNA purification kit (THERMOFISHER 793

SCIENTIFIC) according to manufacturer’s instructions. RNA-Seq library preparation was 794

carried out using NEBNext Ultra RNAlibrary prep kit for Illumina (NEW ENGLAND 795


https://doi.org/10.1101/551069

34

BIOLABS) and 48 RNA-Seq libraries were sequenced using 75x2 setting on Illumina 796

HiSeq2500 platform to obtain at least 20 million 75 bp paired end reads per sample (Table 797

S1). 798

799

RNA-Seq data analysis 800 801 Data pre-processing: 802

Each RNA-Seq library had more than 20 million reads and initial quality control was carried 803

out using FastQC package (Andrews, 2010). The libraries were pre-processed to remove 804

adapter sequences and low quality reads using Trimmomatic (Bolger et al. 2014). Wheat 805

transcript file was generated through RSEM (B. Li and Dewey 2011) using IWGSC wheat 806

RefSeqv1.0 genome assembly (161010_Chinese_Spring_v1.0_pseudomolecules.fasta) and 807

annotation (iwgsc_refseqv1.0_HighConf_2017Mar13.gff3) (International Wheat Genome 808

Sequencing Consortium (IWGSC) et al. 2018). Next, the transcripts were used to take the 809

read counts for each transcript/gene using Salmon – a quasi-mapping based algorithm (Patro 810

et al. 2017). The samples had average mapping percentage of 68% (Table S1). 811

812

Differential gene expression analysis: 813

Differential gene expression analysis was performed using DESeq2 version 1.18.1 (Love et 814

al. 2014) using a design formula (~time + treatment + treatment:time) that takes into account 815

the contrast between two treatment levels throughout the time course as well at a FDR<0.05. 816

A complete list of differentially expressed genes at each treatment-time point along with the 817

log fold change and adjusted P values is available in Table S8. The differentially expressed 818

gene lists were compared using BioVenn (Hulsen et al. 2008). For the non-redundant list of 819

differentially expressed genes, the z-score normalized variance stabilized expression values 820

were used to generate hierarchical clustering based heat map using pheatmap R package 821

(Kolde, 2013). 822

823

GO term enrichment analysis: 824

GO term analysis was carried out using BinGO app for Cytoscape (Maere et al. 2005) for a 825

custom made wheat GO term annotation database for IWGSCRefseqv1.0 (International 826

Wheat Genome Sequencing Consortium (IWGSC) et al. 2018). The most terminal GO terms 827

that are enriched in the hierarchy were considered for further analyses. Fold enrichment was 828

calculated as (x/X)/(n/N) where x is the number of genes (from the list) assigned to a GO 829


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35

category, X is the total number of genes (in the gene list) that were assigned to any GO 830

category, n is the number of genes (in the genome) assigned to the considered GO category 831

and N is the total number of genes (in the genome) that were assigned to GO categories. 832

Over-represented GO terms at FDR < 0.05 were considered for further analyses. 833

834

Gene co-expression network analysis: 835

Variance stabilized count data of the expressed genes were considered and the genes were 836

ranked by variance of gene expression across all conditions. The top 8300 (top 10%) genes 837

were selected for gene co-expression network analysis using WGCNA package version 838

1.64.1 (Langfelder and Horvath 2008). Signed network with soft-thresholding power of 12 839

was generated. The co-expression network was visualized in Cytoscape version 3.5.1 840

(Shannon et al. 2003). GO term enrichment analysis for the selected modules was carried 841

out using BinGO app for Cytoscape (Maere et al. 2005). 842

843

Gene tree construction 844

The wheat orthologues for HRS1/HHO and TGA gene family members were identified by a 845

reciprocal tBLASTx search with a E value cutoff of 10-5.The amino acid sequences of the 846

HRS1/HHO and TGA gene family orthologues from Arabidopsis, rice and wheat were 847

aligned using ClustalW (Thompson et al. 1994) and phylogenetic tree construction was done 848

using maximum likelihood method (JTT matrix-based model) (Jones et al. 1992) for 1000 849

bootstrap replicates using the MEGA6.06 (Tamura et al. 2013). 850

851

Promoter motif analysis 852

For the considered genes in wheat, 1000 bp upstream region nucleotide sequences were 853

extracted and used for MEME algorithm for motif discovery (version 5.0.1) (Bailey et al. 854

2009) with default parameters and -nmotifs 30. The results from MEME motif search were 855

then used to run TOMTOM algorithm for motif comparison (version 5.0.1) (Bailey et al. 856

2009) against JASPAR non-redundant core plant PFM database (release 7, 2018) (Khan et 857

al. 2018). 858

To search for the conserved domains in putative wheat TGA family members, the amino 859

acid sequences were extracted for the TGA family members and these sequences were used 860

to perform MEME algorithm for motif discovery (version 5.0.1) (Bailey et al. 2009) with 861

protein sequence alphabet. 862

863


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36

GENIE3 analysis 864

Variance stabilized count data of the expressed genes were considered and the genes were 865

ranked by variance of gene expression across all conditions. The top 8300 (top 10%) genes 866

were selected for GENIE3 analysis using GENIE3 version 1.4.0 (Huynh-Thu et al. 2010). 867

There were 389 genes that were annotated as transcription factors or transcription factor like 868

proteins with evidence from GO-, Pfam- or Interpro-IDs among the selected 8300 genes. 869

Random forest method was used to infer the network with default paramaters with gene 870

expression matrix for 8300 genes and a list of transcription factor genes as the input. The 871

regulatory relationships that had a weight measure >0.005 were considered for downstream 872

analyses which included GO term enrichment analysis (as described above) for predicted 873

target genes of TaHRS1, TaHHO5/6 and TaTGA9/10 and gene regulatory network 874

visualization using Cytoscape version 3.5.1 (Shannon et al. 2003). 875

876

Gene list overlaps 877

Fisher’s exact test for overlap between gene lists was performed through GeneOverlap R 878

package (Shen and Senai, 2013). Overlap was considered significant if the adjusted P value 879

< 0.05. 880

881

Author Contributions: M.T. and I.D. conceived the project. I.D. carried out the 882

experiments, collected the samples and prepared the RNA-Seq libraries. I.D. carried out data 883

analyses with contributions from J.R-M. I.D., J.R-M., S.B. and M.T. interpreted the data. 884

I.D. and M.T. wrote the manuscript with input from S.B. and J.R-M. 885

886

References 887

888 Abel, S. and Theologis, A. (1996). Early genes and auxin action. PLANT PHYSIOLOGY 889 111:9–17. 890

Álvarez, J.M., Riveras, E., Vidal, E.A., Gras, D.E., Contreras-López, O., Tamayo, K.P., 891 Aceituno, F., et al. (2014). Systems approach identifies TGA1 and TGA4 transcription 892 factors as important regulatory components of the nitrate response of Arabidopsis 893 thalianaroots. The Plant Journal 80:1–13. 894

Baek, D., Chun, H.J., Yun, D.-J. and Kim, M.C. (2017). Cross-talk between Phosphate 895 Starvation and Other Environmental Stress Signaling Pathways in Plants. Molecules and 896 cells 40:697–705. 897

Bailey, T.L., Boden, M., Buske, F.A., Frith, M., Grant, C.E., Clementi, L., Ren, J., et al. 898


https://doi.org/10.1101/551069

37

(2009). MEME SUITE: tools for motif discovery and searching. Nucleic acids research 899 37:W202–8. 900

Balzergue, C., Dartevelle, T., Godon, C., Laugier, E., Meisrimler, C., Teulon, J.-M., Creff, 901 A., et al. (2017). Low phosphate activates STOP1-ALMT1 to rapidly inhibit root cell 902 elongation. Nature Communications 8:15300. 903

Banf, M. and Rhee, S.Y. (2017). Computational inference of gene regulatory networks: 904 Approaches, limitations and opportunities. BBA - Gene Regulatory Mechanisms 1860:41–905 52. 906

Beadle, N.C.W. (1953). The Edaphic Factor in Plant Ecology With a Special Note on Soil 907 Phosphates. Ecology 34:426–428. 908

Benfey, P.N. and Scheres, B. (2000). Root development. Current Biology 10:R813–5. 909

Bieleski, R.L. (1973). Phosphate Pools, Phosphate Transport, and Phosphate Availability. 910 Annual Review of Plant Physiology 24:225–252. 911

Bolger, A.M., Lohse, M. and Usadel, B. (2014). Trimmomatic: a flexible trimmer for 912 Illumina sequence data. Bioinformatics (Oxford, England) 30:2114–2120. 913

Bournier, M., Tissot, N., Mari, S., Boucherez, J., Lacombe, E., Briat, J.-F. and Gaymard, 914 F. (2013). Arabidopsis ferritin 1 (AtFer1) gene regulation by the phosphate starvation 915 response 1 (AtPHR1) transcription factor reveals a direct molecular link between iron and 916 phosphate homeostasis. The Journal of biological chemistry 288:22670–22680. 917

Brady, S.M., Song, S., Dhugga, K.S., Rafalski, J.A. and Benfey, P.N. (2006). Combining 918 Expression and Comparative Evolutionary Analysis. The COBRA Gene Family. PLANT 919 PHYSIOLOGY 143:172–187. 920

Briat, J.-F., Rouached, H., Tissot, N., Gaymard, F. and Dubos, C. (2015). Integration of P, 921 S, Fe, and Zn nutrition signals in Arabidopsis thaliana: potential involvement of 922 PHOSPHATE STARVATION RESPONSE 1 (PHR1). Frontiers in Plant Science 6:290–923 16. 924

Castaings, L., Camargo, A., Pocholle, D., Gaudon, V., Texier, Y., Boutet-Mercey, S., 925 Taconnat, L., et al. (2009). The nodule inception-like protein 7 modulates nitrate sensing 926 and metabolism in Arabidopsis. The Plant Journal 57:426–435. 927

Chevalier, F., Pata, M., Nacry, P., Doumas, P. and Rossignol, M. (2003). Effects of 928 phosphate availability on the root system architecture: large-scale analysis of the natural 929 variation between Arabidopsis accessions. Plant, Cell & Environment 26:1839–1850. 930

Chiou, T.-J. and Lin, S.-I. (2011). Signaling network in sensing phosphate availability in 931 plants. Annual review of plant biology 62:185–206. 932

Conte, S.S. and Walker, E.L. (2011). Transporters contributing to iron trafficking in plants. 933 Molecular Plant 4:464–476. 934

Crawford, N.M. and Glass, A.D.M. (1998). Molecular and physiological aspects of nitrate 935 uptake in plants. Trends in plant science 3:389–395. 936


https://doi.org/10.1101/551069

38

De Smet, R. and Marchal, K. (2010). Advantages and limitations of current network 937 inference methods. Nature reviews. Microbiology 8:717–729. 938

Duan, K., Yi, K., Dang, L., Huang, H., Wu, W. and Wu, P. (2008). Characterization of a 939 sub-family of Arabidopsis genes with the SPX domain reveals their diverse functions in 940 plant tolerance to phosphorus starvation. The Plant Journal 54:965–975. 941

Fan, W. and Dong, X. (2002). In vivo interaction between NPR1 and transcription factor 942 TGA2 leads to salicylic acid-mediated gene activation in Arabidopsis. The Plant Cell 943 14:1377–1389. 944

Food and Agriculture Organization Statistics. Available at: 945 http://faostat3.fao.org/download/Q/QC/E. 946

Forde, B.G. (2014). Nitrogen signalling pathways shaping root system architecture: an 947 update. Current Opinion in Plant Biology 21:30–36. 948

Gatz, C. (2013). From Pioneers to Team Players: TGA Transcription Factors Provide a 949 Molecular Link Between Different Stress Pathways. Molecular plant-microbe interactions 950 : MPMI 26:151–159. 951

Giehl, R.F.H. and Wirén, von, N. (2014). Root nutrient foraging. PLANT PHYSIOLOGY 952 166:509–517. 953

Giehl, R.F.H., Gruber, B.D. and Wirén, von, N. (2013). It’s time to make changes: 954 modulation of root system architecture by nutrient signals. Journal of Experimental Botany 955 65:769–778. 956

Gruber, B.D., Giehl, R.F.H., Friedel, S. and Wirén, von, N. (2013). Plasticity of the 957 Arabidopsis root system under nutrient deficiencies. PLANT PHYSIOLOGY 163:161–179. 958

Gu, M., Chen, A., Sun, S. and Xu, G. (2016). Complex Regulation of Plant Phosphate 959 Transporters and the Gap between Molecular Mechanisms and Practical Application: What 960 Is Missing? Molecular Plant 9:396–416. 961

Guan, P. (2017). Dancing with Hormones: A Current Perspective of Nitrate Signaling and 962 Regulation in Arabidopsis. Frontiers in Plant Science 8:1697. 963

Gutiérrez-Alanís, D., Yong-Villalobos, L., Jiménez-Sandoval, P., Alatorre-Cobos, F., 964 Oropeza-Aburto, A., Mora-Macías, J., Sánchez-Rodríguez, F., et al. (2017). Phosphate 965 Starvation-Dependent Iron Mobilization Induces CLE14 Expression to Trigger Root 966 Meristem Differentiation through CLV2/PEPR2 Signaling. Developmental Cell 41:555–967 570.e3. 968

Hofmann, N.R. (2012). Nicotianamine in zinc and iron homeostasis. The Plant Cell 969 24:373–373. 970

Hulsen, T., de Vlieg, J. and Alkema, W. (2008). BioVenn - a web application for the 971 comparison and visualization of biological lists using area-proportional Venn diagrams. 972 BMC Genomics 9:488. 973

Huynh-Thu, V.A., Irrthum, A., Wehenkel, L. and Geurts, P. (2010). Inferring regulatory 974


https://doi.org/10.1101/551069

39

networks from expression data using tree-based methods. Isalan, M. (ed.). PLoS ONE 975 5:e12776. 976

International Wheat Genome Sequencing Consortium (IWGSC), IWGSC RefSeq principal 977 investigators:, Keller, B., IWGSC whole-genome assembly principal investigators:, 978 Distelfeld, A., Eversole, K., Whole-genome sequencing and assembly:, et al. (2018). 979 Shifting the limits in wheat research and breeding using a fully annotated reference 980 genome. Science (New York, N.Y.) 361:eaar7191. 981

Jakoby, M., Weisshaar, B., Dröge-Laser, W., Vicente-Carbajosa, J., Tiedemann, J., Kroj, 982 T. and Parcy, F. (2002). bZIP transcription factors in Arabidopsis. Trends in plant science 983 7:106–111. 984

Jones, D.T., Taylor, W.R. and Thornton, J.M. (1992). The rapid generation of mutation 985 data matrices from protein sequences. Bioinformatics (Oxford, England) 8:275–282. 986

Kant, S., Peng, M. and Rothstein, S.J. (2011). Genetic regulation by NLA and 987 microRNA827 for maintaining nitrate-dependent phosphate homeostasis in arabidopsis. 988 PLoS Genetics 7:e1002021–11. 989

Kapulnik, Y. and Koltai, H. (2016). Fine-tuning by strigolactones of root response to low 990 phosphate. Journal of Integrative Plant Biology 58:203–212. 991

Kellermeier, F., Armengaud, P., Seditas, T.J., Danku, J., Salt, D.E. and Amtmann, A. 992 (2014). Analysis of the Root System Architecture of Arabidopsis Provides a Quantitative 993 Readout of Crosstalk between Nutritional Signals. The Plant Cell 26:1480–1496. 994

Khan, A., Fornes, O., Stigliani, A., Gheorghe, M., Castro-Mondragon, J.A., van der Lee, 995 R., Bessy, A., et al. (2018). JASPAR 2018: update of the open-access database of 996 transcription factor binding profiles and its web framework. Nucleic acids research 997 46:D1284–D1284. 998

Kiba, T., Inaba, J., Kudo, T., Ueda, N., Konishi, M., Mitsuda, N., Takiguchi, Y., Kondou, 999 Y., Yoshizumi, T., Ohme-Takagi, M., Matsui, M., Yano, K., Yanagisawa, S. and 1000 Sakakibara, H. (2018). Repression of Nitrogen Starvation Responses by Members of the 1001 Arabidopsis GARP-Type Transcription Factor NIGT1/HRS1 Subfamily. The Plant Cell 1002 30:925–945. 1003

Kieber, J.J. and Schaller, G.E. (2018). Cytokinin signaling in plant development. 1004 Development (Cambridge, England) 145:dev149344. 1005

Koen, E., Besson-Bard, A., Duc, C., Astier, J., Gravot, A., Richaud, P., Lamotte, O., et al. 1006 (2013). Arabidopsis thaliana nicotianamine synthase 4 is required for proper response to 1007 iron deficiency and to cadmium exposure. Plant science : an international journal of 1008 experimental plant biology 209:1–11. 1009

Krapp, A., David, L.C., Chardin, C., Girin, T., Marmagne, A., Leprince, A.-S., Chaillou, 1010 S., et al. (2014). Nitrate transport and signalling in Arabidopsis. Journal of Experimental 1011 Botany 65:789–798. 1012

Krouk, G. (2017). Hormones and nitrate: a two-way connection. Plant Molecular Biology 1013 91:599–606. 1014


https://doi.org/10.1101/551069

40

Krouk, G., Mirowski, P., LeCun, Y., Shasha, D.E. and Coruzzi, G.M. (2010). Predictive 1015 network modeling of the high-resolution dynamic plant transcriptome in response to 1016 nitrate. Genome biology 11:R123. 1017

Kumar, R.K., Chu, H.-H., Abundis, C., Vasques, K., Rodriguez, D.C., Chia, J.-C., Huang, 1018 R., et al. (2017). Iron-Nicotianamine Transporters Are Required for Proper Long Distance 1019 Iron Signaling. PLANT PHYSIOLOGY 175:1254–1268. 1020

Landrein, B., Formosa-Jordan, P., Malivert, A., Schuster, C., Melnyk, C.W., Yang, W., 1021 Turnbull, C., et al. (2018). Nitrate modulates stem cell dynamics in Arabidopsis shoot 1022 meristems through cytokinins. Proceedings of the National Academy of Sciences of the 1023 United States of America 115:1382–1387. 1024

Langfelder, P. and Horvath, S. (2008). WGCNA: an R package for weighted correlation 1025 network analysis. BMC bioinformatics 9:559. 1026

Lavenus, J., Goh, T., Roberts, I., Guyomarc’h, S., Lucas, M., De Smet, I., Fukaki, H., et al. 1027 (2013). Lateral root development in Arabidopsis: fifty shades of auxin. Trends in plant 1028 science 18:450–458. 1029

Lebel, E., Heifetz, P., Thorne, L., Uknes, S., Ryals, J. and Ward, E. (1998). Functional 1030 analysis of regulatory sequences controlling PR-1 gene expression in Arabidopsis. The 1031 Plant Journal 16:223–233. 1032

Lee, I., Ambaru, B., Thakkar, P., Marcotte, E.M. and Rhee, S.Y. (2010). Rational 1033 association of genes with traits using a genome-scale gene network for Arabidopsis 1034 thaliana. Nature biotechnology 28:149–156. 1035

Li, B. and Dewey, C.N. (2011). RSEM: accurate transcript quantification from RNA-Seq 1036 data with or without a reference genome. BMC bioinformatics 12:323. 1037

Li, W.-F., Perry, P.J., Prafulla, N.N. and Schmidt, W. (2010). Ubiquitin-specific protease 1038 14 (UBP14) is involved in root responses to phosphate deficiency in Arabidopsis. 1039 Molecular Plant 3:212–223. 1040

Liu, H., Yang, H., Wu, C., Feng, J., Liu, X., Qin, H. and Wang, D. (2009). Overexpressing 1041 HRS1 confers hypersensitivity to low phosphate-elicited inhibition of primary root growth 1042 in Arabidopsis thaliana. Journal of Integrative Plant Biology 51:382–392. 1043

Liu, J., Yang, L., Luan, M., Wang, Y., Zhang, C., Zhang, B., Shi, J., et al. (2015). A 1044 vacuolar phosphate transporter essential for phosphate homeostasis in Arabidopsis. 1045 Proceedings of the National Academy of Sciences of the United States of America 1046 112:E6571–8. 1047

Liu, K.-H., Niu, Y., Konishi, M., Wu, Y., Du, H., Chung, H.S., Li, L., et al. (2017). 1048 Discovery of nitrate–CPK–NLP signalling in central nutrient–growth networks. Nature 1049 Publishing Group 545:311–316. 1050

Love, M.I., Huber, W. and Anders, S. (2014). Moderated estimation of fold change and 1051 dispersion for RNA-seq data with DESeq2. Genome biology 15:550. 1052

Maeda, Y., Konishi, M., Kiba, T., Sakuraba, Y., Sawaki, N., Kurai, T., Ueda, Y., et al. 1053


https://doi.org/10.1101/551069

41

(2018). A NIGT1-centred transcriptional cascade regulates nitrate signalling and 1054 incorporates phosphorus starvation signals in Arabidopsis. Nature Communications:1–14. 1055

Maere, S., Heymans, K. and Kuiper, M. (2005). BiNGO: a Cytoscape plugin to assess 1056 overrepresentation of gene ontology categories in biological networks. Bioinformatics 1057 (Oxford, England) 21:3448–3449. 1058

Marchive, C., Roudier, F., Castaings, L., Bréhaut, V., Blondet, E., Colot, V., Meyer, C., et 1059 al. (2013). Nuclear retention of the transcription factor NLP7 orchestrates the early 1060 response to nitrate in plants. Nature Communications 4:1713–9. 1061

Marcussen, T., Sandve, S.R., Heier, L., Spannagl, M., Pfeifer, M., International Wheat 1062 Genome Sequencing Consortium,, Jakobsen, K.S., et al. (2014). Ancient hybridizations 1063 among the ancestral genomes of bread wheat. Science (New York, N.Y.) 345:1250092–1064 1250092. 1065

Marschner, H. (2011). Marschner's Mineral Nutrition of Higher Plants. 3rd ed. Academic 1066 Press. 1067

McClure, B.A., Hagen, G., Brown, C.S., Gee, M.A. and Guilfoyle, T.J. (1989). 1068 Transcription, organization, and sequence of an auxin-regulated gene cluster in soybean. 1069 The Plant Cell 1:229–239. 1070

Medici, A., Marshall-Colon, A., Ronzier, E., Szponarski, W., Wang, R., Gojon, A., 1071 Crawford, N.M., et al. (2015). AtNIGT1/HRS1 integrates nitrate and phosphate signals at 1072 the Arabidopsis root tip. Nature Communications 6:1–11. 1073

Mora-Macías, J., Ojeda-Rivera, J.O., Gutiérrez-Alanís, D., Yong-Villalobos, L., Oropeza-1074 Aburto, A., Raya-González, J., Jiménez-Domínguez, G., et al. (2017). Malate-dependent 1075 Fe accumulation is a critical checkpoint in the root developmental response to low 1076 phosphate. Proceedings of the National Academy of Sciences 114:E3563–E3572. 1077

Nilsson, L., Müller, R. and Nielsen, T.H. (2007). Increased expression of the MYB-related 1078 transcription factor, PHR1, leads to enhanced phosphate uptake in Arabidopsis thaliana. 1079 Plant, Cell & Environment 30:1499–1512. 1080 1081

Niu, Y.F., Chai, R.S., Jin, G.L., Wang, H., Tang, C.X. and Zhang, Y.S. (2013). Responses 1082 of root architecture development to low phosphorus availability: a review. Annals of 1083 botany 112:391–408. 1084

Obayashi, T., Aoki, Y., Tadaka, S., Kagaya, Y. and Kinoshita, K. (2018). ATTED-II in 1085 2018: A Plant Coexpression Database Based on Investigation of the Statistical Property of 1086 the Mutual Rank Index. Plant and Cell Physiology 59:440–440. 1087

Pal, S., Kisko, M., Dubos, C., Lacombe, B., Berthomieu, P., Krouk, G. and Rouached, H. 1088 (2017). TransDetect identifies a new regulatory module controlling phosphate 1089 accumulation. PLANT PHYSIOLOGY:pp.00568.2017–11. 1090

Patro, R., Duggal, G., Love, M.I., Irizarry, R.A. and Kingsford, C. (2017). Salmon 1091 provides fast and bias-aware quantification of transcript expression. Nature methods 1092 14:417–419. 1093


https://doi.org/10.1101/551069

42

Péret, B., Desnos, T., Jost, R., Kanno, S., Berkowitz, O. and Nussaume, L. (2014). Root 1094 architecture responses: in search of phosphate. PLANT PHYSIOLOGY 166:1713–1723. 1095

Pfeifer, M., Kugler, K.G., Sandve, S.R., Zhan, B., Rudi, H., Hvidsten, T.R., International 1096 Wheat Genome Sequencing Consortium,, et al. (2014). Genome interplay in the grain 1097 transcriptome of hexaploid bread wheat. Science (New York, N.Y.) 345:1250091–1250091. 1098

Piñeros, M.A., Cançado, G.M.A. and Kochian, L.V. (2008). Novel properties of the wheat 1099 aluminum tolerance organic acid transporter (TaALMT1) revealed by electrophysiological 1100 characterization in Xenopus Oocytes: functional and structural implications. PLANT 1101 PHYSIOLOGY 147:2131–2146. 1102

Powell, J.J., Fitzgerald, T.L., Stiller, J., Berkman, P.J., Gardiner, D.M., Manners, J.M., 1103 Henry, R.J., et al. (2017). The defence-associated transcriptome of hexaploid wheat 1104 displays homoeolog expression and induction bias. Plant biotechnology journal 15:533–1105 543. 1106

Puga, M.I., Mateos, I., Charukesi, R., Wang, Z., Franco-Zorrilla, J.M., de Lorenzo, L., 1107 Irigoyen, M.L., et al. (2014). SPX1 is a phosphate-dependent inhibitor of PHOSPHATE 1108 STARVATION RESPONSE 1 in Arabidopsis. Proceedings of the National Academy of 1109 Sciences 111:14947–14952. 1110

Roudier, F. (2002). The COBRA Family of Putative GPI-Anchored Proteins in 1111 Arabidopsis. A New Fellowship in Expansion. PLANT PHYSIOLOGY 130:538–548. 1112

Rubin, G., Tohge, T., Matsuda, F., Saito, K. and Scheible, W.-R. (2009). Members of the 1113 LBD family of transcription factors repress anthocyanin synthesis and affect additional 1114 nitrogen responses in Arabidopsis. The Plant Cell 21:3567–3584. 1115

Ruffel, S., Krouk, G., Ristova, D., Shasha, D., Birnbaum, K.D. and Coruzzi, G.M. (2011). 1116 Nitrogen economics of root foraging: transitive closure of the nitrate-cytokinin relay and 1117 distinct systemic signaling for N supply vs. demand. Proceedings of the National Academy 1118 of Sciences of the United States of America 108:18524–18529. 1119

Ruffel, S., Poitout, A., Krouk, G., Coruzzi, G.M. and Lacombe, B. (2016). Long-distance 1120 nitrate signaling displays cytokinin dependent and independent branches. Journal of 1121 Integrative Plant Biology 58:226–229. 1122

Sakakibara, H., Takei, K. and Hirose, N. (2006). Interactions between nitrogen and 1123 cytokinin in the regulation of metabolism and development. Trends in plant science 1124 11:440–448. 1125

Sawaki, N., Tsujimoto, R., Shigyo, M., Konishi, M., Toki, S., Fujiwara, T. and 1126 Yanagisawa, S. (2013). A Nitrate-Inducible GARP Family Gene Encodes an Auto-1127 Repressible Transcriptional Repressor in Rice. Plant and Cell Physiology 54:506–517. 1128

Schachtman, D., Reid, R. and Ayling, S. (1998). Phosphorus Uptake by Plants: From Soil 1129 to Cell. PLANT PHYSIOLOGY 116:447–453. 1130

Scheible, W.-R., Morcuende, R., Czechowski, T., Fritz, C., Osuna, D., Palacios-Rojas, N., 1131 Schindelasch, D., et al. (2004). Genome-wide reprogramming of primary and secondary 1132 metabolism, protein synthesis, cellular growth processes, and the regulatory infrastructure 1133


https://doi.org/10.1101/551069

43

of Arabidopsis in response to nitrogen. PLANT PHYSIOLOGY 136:2483–2499. 1134

Schindelman, G., Morikami, A., Jung, J., Baskin, T.I., Carpita, N.C., Derbyshire, P., 1135 McCann, M.C. and Benfey, P.N. (2001). COBRA encodes a putative GPI-anchored 1136 protein, which is polarly localized and necessary for oriented cell expansion in 1137 Arabidopsis. :1–14. 1138

Schuler, M., Rellán-Álvarez, R., Fink-Straube, C., Abadía, J. and Bauer, P. (2012). 1139 Nicotianamine Functions in the Phloem-Based Transport of Iron to Sink Organs, in Pollen 1140 Development and Pollen Tube Growth in Arabidopsis. The Plant Cell 24:2380–2400. 1141

Secco, D., Jabnoune, M., Walker, H., Shou, H., Wu, P., Poirier, Y. and Whelan, J. (2013). 1142 Spatio-Temporal Transcript Profiling of Rice Roots and Shoots in Response to Phosphate 1143 Starvation and Recovery. The Plant Cell 25:4285–4304. 1144

Shahzad, Z. and Amtmann, A. (2017). Food for thought: how nutrients regulate root 1145 system architecture. Current Opinion in Plant Biology 39:80–87. 1146

Shahzad, Z., Kellermeier, F., Armstrong, E.M., Rogers, S., Lobet, G., Amtmann, A. and 1147 Hills, A. (2018). EZ-Root-VIS: A Software Pipeline for the Rapid Analysis and Visual 1148 Reconstruction of Root System Architecture. PLANT PHYSIOLOGY 177:1368–1381. 1149

Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., et al. 1150 (2003). Cytoscape: a software environment for integrated models of biomolecular 1151 interaction networks. Genome Research 13:2498–2504. 1152

Li Shen and Mount Sinai (2013). GeneOverlap: Test and visualize gene overlaps. R 1153 package version 1.8.0. http://shenlab-sinai.github.io/shenlab-sinai/ 1154

Shukla, D., Rinehart, C.A. and Sahi, S.V. (2017). Comprehensive study of excess 1155 phosphate response reveals ethylene mediated signaling that negatively regulates plant 1156 growth and development. Nature Publishing Group 7:3074. 1157

Smith, S. and De Smet, I. (2012). Root system architecture: insights from Arabidopsis and 1158 cereal crops. Philosophical transactions of the Royal Society of London. Series B, 1159 Biological sciences 367:1441–1452. 1160

Subramaniam, R., Desveaux, D., Spickler, C., Michnick, S.W. and Brisson, N. (2001). 1161 Direct visualization of protein interactions in plant cells. Nature biotechnology 19:769–1162 772. 1163

Sun, H., Tao, J., Liu, S., Huang, S., Chen, S., Xie, X., Yoneyama, K., et al. (2014). 1164 Strigolactones are involved in phosphate- and nitrate-deficiency-induced root development 1165 and auxin transport in rice. Journal of Experimental Botany 65:6735–6746. 1166

Takahashi, M., Terada, Y., Nakai, I., Nakanishi, H., Yoshimura, E., Mori, S. and 1167 Nishizawa, N.K. (2003). Role of Nicotianamine in the Intracellular Delivery of Metals and 1168 Plant Reproductive Development. Plant Cell 15:1263. 1169

Tamura, K., Stecher, G., Peterson, D., Filipski, A. and Kumar, S. (2013). MEGA6: 1170 Molecular Evolutionary Genetics Analysis version 6.0. Molecular biology and evolution 1171 30:2725–2729. 1172


https://doi.org/10.1101/551069

44

Thompson, J.D., Higgins, D.G. and Gibson, T.J. (1994). CLUSTAL W: improving the 1173 sensitivity of progressive multiple sequence alignment through sequence weighting, 1174 position-specific gap penalties and weight matrix choice. Nucleic acids research 22:4673–1175 4680. 1176

Tian, H., De Smet, I. and Ding, Z. (2014). Shaping a root system: regulating lateral versus 1177 primary root growth. Trends in plant science 19:426–431. 1178

Tilman, D., Cassman, K.G., Matson, P.A., Naylor, R. and Polasky, S. (2002). Agricultural 1179 sustainability and intensive production practices. Nature 418:671–677. 1180

Usadel, B., Obayashi, T., Mutwil, M., Giorgi, F.M., Bassel, G.W., Tanimoto, M., Chow, 1181 A., et al. (2009). Co-expression tools for plant biology: opportunities for hypothesis 1182 generation and caveats. Plant, Cell & Environment 32:1633–1651. 1183

Vance, C.P. (2001). Symbiotic nitrogen fixation and phosphorus acquisition. Plant 1184 nutrition in a world of declining renewable resources. PLANT PHYSIOLOGY 127:390–1185 397. 1186

Wang, C., Yue, W., Ying, Y., Wang, S., Secco, D., Liu, Y., Whelan, J., et al. (2015). Rice 1187 SPX-Major Facility Superfamily3, a Vacuolar Phosphate Efflux Transporter, Is Involved 1188 in Maintaining Phosphate Homeostasis in Rice. PLANT PHYSIOLOGY 169:2822–2831. 1189

Wang, R., Guegler, K., LaBrie, S.T. and Crawford, N.M. (2000). Genomic analysis of a 1190 nutrient response in Arabidopsis reveals diverse expression patterns and novel metabolic 1191 and potential regulatory genes induced by nitrate. The Plant Cell 12:1491–1509. 1192

Wang, R., Okamoto, M., Xing, X. and Crawford, N.M. (2003). Microarray analysis of the 1193 nitrate response in Arabidopsis roots and shoots reveals over 1,000 rapidly responding 1194 genes and new linkages to glucose, trehalose-6-phosphate, iron, and sulfate metabolism. 1195 PLANT PHYSIOLOGY 132:556–567. 1196

Waters, B.M., Chu, H.-H., Didonato, R.J., Roberts, L.A., Eisley, R.B., Lahner, B., Salt, 1197 D.E., et al. (2006). Mutations in Arabidopsis yellow stripe-like1 and yellow stripe-like3 1198 reveal their roles in metal ion homeostasis and loading of metal ions in seeds. PLANT 1199 PHYSIOLOGY 141:1446–1458. 1200

Wiren N, von, Klair, S., Bansal, S., Briat, J., Khodr, H., Shioiri, T., Leigh, R., et al. (1999). 1201 Nicotianamine chelates both FeIII and FeII. Implications for metal transport in plants. 1202 PLANT PHYSIOLOGY 119:1107–1114. 1203

Wolfe, C.J., Kohane, I.S. and Butte, A.J. (2005). Systematic survey reveals general 1204 applicability of ‘guilt-by-association’ within gene coexpression networks. BMC 1205 bioinformatics 6:227. 1206

Yu, P., Gutjahr, C., Li, C. and Hochholdinger, F. (2016). Genetic Control of Lateral Root 1207 Formation in Cereals. Trends in plant science 21:951–961. 1208

Zhang, W.-H., Ryan, P.R., Sasaki, T., Yamamoto, Y., Sullivan, W. and Tyerman, S.D. 1209 (2008). Characterization of the TaALMT1 Protein as an Al3+-Activated Anion Channel in 1210 Transformed Tobacco (Nicotiana tabacum L.) Cells. Plant and Cell Physiology 49:1316–1211 1330. 1212


https://doi.org/10.1101/551069

45

Zhang, X., Davidson, E.A., Mauzerall, D.L., Searchinger, T.D., Dumas, P. and Shen, Y. 1213 (2015). Managing nitrogen for sustainable development. Nature 528:51–59. 1214

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Supplementary Figures 1216

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PN_Roo

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oot

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ogen

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Figure S1. (A) Nitrogen and (B) Phosphorus content (as a percentage of dry weight) in 11 days old wheat roots and shoots that were grown in deionized water (pn) or full strength nutrient solution (PN: 2 mM nitrate and 0.5 mM phosphate) (n=3, error bars indicate standard error of mean, significance P<0.05).


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1221

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Eigenvalues − Percentage Explained

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lained

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TraesCS5D01G401900.1

TraesCS5A01G392000.1

TraesCS5B01G396900.1

ZmBK2L4

ZmBK2L3

Os05t0386800-01 OsBC1L4

Os03t0754500-00


Os10t0497700-01 OsBC1L9

Os03t0416300-01 OsBC1L2

ZmBK2L6

Os07t0604300-01 OsBC1L6

AT3G02210(COBL1)

AT3G29810(COBL2/3)

AT5G60920(COB)

AT5G15630(COBL4)

ZmBK2L7

Os07t0604400-00 OsBC1L7

ZmBK2

Os03t0416200-01 OsBC1

TraesCS5A01G095200.1


AT5G60950(COBL5)

AT1G09790(COBL6)

ZmBK2L9

Os04t0540300-00 OsBC1LP1

ZmBK2L8

Os07t0690900-01

ZmBK2L1

Os03t0301200-01

AT4G16120(COBL7)

AT3G16860(COBL8)

AT5G49270(COBL9)

ZmBK2L5

AT3G20580(COBL10)

AT4G27110(COBL11)

100

96

96

95

9492

99

91

91

85

75

73

63

99

87

91

57

100

56

53

51

93

48

39100

49

37

6547

39

29

24

73

A

B

Figure S2. (A) Percentage of variance of the dataset explained by each dimension in multidimensional scaling plot (MDS plot) where number of dimensions was arbitrarily set to 16. (B) Maximum likelihood based (JTT matrix-based model) phylogenetic tree for the COBRA family members from rice, maize, Arabidopsis and wheat. The percentage of trees in which the associated taxa clustered together is shown next to the branches.


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1224

1225

1226

B

C

A

Figure S3. (A) The amino acid sequence alignment for AtHRS1, OsNIGT1 and members of wheat HRS1/HHO family; the conserved G2-like DNA binding domain is indicated with the black bar. (B) The amino acid sequence alignment for AtTGA1, AtTGA4, AtTGA9 and wheat orthologues for TGA1/4 and TGA9/10; the conserved bZIP_1 signature domain is indicated with the black bar. (C) The most enriched motif in putative TaTGA family members.


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1227

1228

1229

TraesCS5B01G265300 TraesCS5D01G273500 TraesCS5A01G265600 Os09g0489500 AT5G06839 AtTGA10 Os09g0280500 TraesCS5A01G174200 TraesCS5D01G178800 Os06g0614100 Os02g0194900 TraesCS6D01G154400 TraesCS6A01G165800 TraesCS6B01G193200 AT1G08320 AtTGA9 TraesCS3A01G372400 TraesCS3D01G365200 TraesCS3B01G404800 Os01g0859500 TraesCS1B01G285800 TraesCS1D01G276100 TraesCS1A01G276600 Os05g0443900 Os11g0152700 Os12g0152900 TraesCS4A01G183400 TraesCS4B01G135000 TraesCS4D01G129900 AT5G65210 AtTGA1 AT5G10030 AtTGA4 AT1G22070 AtTGA3 AT1G77920 AtTGA7 Os04g0637000 Os08g0176900 TraesCS2D01G529000 TraesCS2A01G526300 TraesCS2B01G556600 Os05g0492000 TraesCS1D01G105300 TraesCS1A01G096300 TraesCS1B01G127400 AT5G06950 AtTGA2 AT3G12250 AtTGA6 AT5G06960 AtTGA5 Os03g0318600 Os07g0687700 TraesCS4A01G126300 TraesCS4D01G180200 TraesCS4B01G178600 TraesCS2B01G113200 TraesCS2D01G096800 TraesCS2A01G097500 Os01g0279900 TraesCS3A01G190700 TraesCS3B01G220400 TraesCS3D01G194800 TraesCS3B01G365100 TraesCS3D01G327600 TraesCS3A01G334100 Os01g0808100 AT1G68640 AtTGA8 PAN Os01g0882200 Os10g0566200 Os06g0265400 TraesCS7B01G114300 TraesCS7D01G209800 TraesCS7A01G207100 SELMODRAFT 231689 EFJ28227

99

98

9697

89

80

7791

7377

6999

82

6980

9879

61

5995

69

55

53

5087

98

39

3942

58

36

48

3596

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68

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PN_24h

pN_24h

Pn_2h

pn_2h

Pn_4h

pn_4h

Pn_24h

pn_24h

TaTGA9/10

Figure S4. Maximum likelihood based (JTT matrix-based model) phylogenetic tree for the TGA family orthologues from rice, Arabidopsis and wheat along with gene expression patterns of wheat orthologues; genes in red boxes were assigned to brown module in WGCNA.


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1230

1231

1232

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Targets

19411

DEG & co-expressed

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Targets

251503

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TaHRS1 TaHHO5/6

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AP2-MBDlike

ARF

ARR-B

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BBR-BPC

bHLH

bZIP

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CPP

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G2-like

HD-ZIP

MADSbox

MYB

MYB-related

NAC

Trihelix

WRKY

ZF-HD

TFfamilydistribution amongTaHHO5/6TFBM

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C

B

Figure S5. The overlap between targets predicted by GENIE3 with genes that are both differentially expressed and co-expressed with, (A) TaHRS1 or (B) TaHHO5/6. (C) Distribution of TaHHO5/6 transcription factor binding motifs (TFBM) based on transcription factor (TF) family.


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transcriptional dynamics of bread wheat in response to nitrate … · 129 nitrate or phosphate from...

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