genetic components of root architecture remodeling … · 2 genetic components of root architecture...
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RESEARCH ARTICLE 1
Genetic Components of Root Architecture Remodeling in Response to 2
Salt Stress 3 Magdalena M. Julkowska
#1,2, Iko T. Koevoets
2^, Selena Mol
1,2, Huub Hoefsloot
3, Richard 4
Feron5, Mark A. Tester
6, Joost J.B. Keurentjes
4,7, Arthur Korte
8, Michel A. Haring
1, Gert-5
Jan de Boer5, Christa Testerink*^
2 6
7 University of Amsterdam, 1Plant Physiology, 2Plant Cell Biology, 3Biosystems Data Analysis, 8 4Applied Quantitative Genetics, Swammerdam Institute for Life Sciences, 1090GE Amsterdam, 9 the Netherlands 10 5ENZA Zaden Research and Development B.V., 1602DB Enkhuizen, the Netherlands 11 6Department of Biological and Environmental Sciences and Engineering, King Abdullah 12 University of Science and Technology, 23955-6900 Thuwal-Jeddah, Kingdom of Saudi Arabia 13 7Laboratory of Genetics, 6708PB Wageningen University & Research, Wageningen, the 14 Netherlands 15 8 Center for Computational and Theoretical Biology, Wuerzburg Universitat, 97074 Wuerzburg, 16 Germany 17 # MMJ Current address: Department of Biological and Environmental Sciences and 18 Engineering, King Abdullah University of Science and Technology, 23955-6900 Thuwal-19 Jeddah, Kingdom of Saudi Arabia 20 *Corresponding author: [email protected] ^ITK and CT Current address: Laboratory of Plant Physiology, 6708PB Wageningen University22 & Research, Wageningen, the Netherlands23
24 Short title: Natural variation in plasticity of roots in salt 25 One-sentence summary: Natural variation in 347 Arabidopsis accessions reveals differential 26 root plasticity responses to salinity, associated with 100 genetic loci, and roles for HKT1 and 27 CYP79B2 in lateral root development. 28
29 The author responsible for distribution of materials integral to the findings presented in this 30 article in accordance with the policy described in the Instructions for Authors 31 (www.plantcell.org) is Christa Testerink ([email protected]). 32
33 ABSTRACT 34 Salinity of the soil is highly detrimental to plant growth. Plants respond by a redistribution of root 35 mass between main and lateral roots, yet the genetic machinery underlying this process is still 36 largely unknown. Here, we describe the natural variation among 347 Arabidopsis thaliana 37 accessions in root system architecture (RSA) and identify the traits with highest natural variation 38 in their response to salt. Salt-induced changes in RSA were associated with 100 genetic loci using 39 genome-wide association studies (GWAS). Two candidate loci associated with lateral root 40 development were validated and further investigated. Changes in CYP79B2 expression in salt 41 stress positively correlated with lateral root development in accessions, and cyp79b2 cyp79b3 42 double mutants developed fewer and shorter lateral roots under salt stress, but not in control 43 conditions. By contrast, high HKT1 expression in the root repressed lateral root development, 44 which could be partially rescued by addition of potassium. The collected data and Multi-Variate 45 analysis of multiple RSA traits, available through the Salt_NV_Root App, capture root responses 46 to salinity. Together, our results provide a better understanding of effective RSA remodeling 47 responses, and the genetic components involved, for plant performance in stress conditions. 48
Plant Cell Advance Publication. Published on November 7, 2017, doi:10.1105/tpc.16.00680
©2017 American Society of Plant Biologists. All Rights Reserved
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INTRODUCTION 50
Salt stress is a major threat in modern agriculture, affecting 20% of the cultivated area 51
worldwide and half of the irrigated farmlands (OECD, 2012). Plants can adopt multiple 52
strategies to increase their salinity tolerance, such as reduced growth rate, 53
compartmentalization of ions or synthesis of compatible solutes (Munns and Tester, 54
2008; Munns and Gilliham, 2015). One of the most robust phenotypes used for screening 55
salinity tolerance is accumulation of sodium in shoot tissue. Exclusion of sodium from 56
the shoot is correlated with maintenance of high rates of photosynthesis, growth, and 57
yield (Munns and Tester, 2008). Allelic variation affecting transcription of HKT1 and 58
CIPK13 was previously established to play a major role in sodium exclusion and 59
therefore salinity tolerance (Rus et al., 2006; Munns et al., 2012; Roy et al., 2012). 60
Another trait broadly used for identification of salt stress-related mechanisms is 61
elongation of the main root (Wu et al., 1996; Ding and Zhu, 1997; Liu and Zhu, 1997). 62
While main root elongation is instrumental for seedling establishment, the distribution of 63
the root mass between main and lateral roots is also affected by salt, yet the genetic 64
machinery underlying this process as well as its significance in salt stress tolerance are 65
only now starting to be unraveled (Duan et al., 2013; Geng et al., 2013; Julkowska et al., 66
2014; Julkowska and Testerink, 2015; Kobayashi et al., 2016; Kawa et al., 2016). 67
The root is the first plant organ exposed to salinity stress and plays an important 68
role in salt sensing (Galvan-Ampudia et al., 2013; Robbins et al., 2014) as well as signal 69
transduction to the shoot tissue (Choi et al., 2014; Jiang et al., 2013). Salt stress reduces 70
the cell cycle activity at the root meristems, resulting in growth reduction (West et al., 71
2004). Quiescence of lateral roots is initiated by endodermal ABA signaling, which 72
interestingly is also involved in recovery of lateral root growth (Duan et al., 2013). In the 73
long term, salt stress reduces main root growth more severely than lateral root elongation 74
in the Arabidopsis thaliana accession Col-0 (Julkowska et al., 2014), causing remodeling 75
of Root System Architecture (RSA) compared to control conditions. Interestingly, other 76
Arabidopsis accessions show different RSA remodeling response to salt stress, indicating 77
natural variation that can be exploited for candidate gene identification by means of 78
Genome Wide Association Studies (GWAS). Since the root system is important for 79
efficient water uptake and ion exclusion (Faiyue et al., 2010; Ristova and Busch, 2014), 80
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changes in RSA are likely to contribute to plant performance under salt stress conditions 81
(Julkowska and Testerink, 2015). 82
In this study we explore natural variation in RSA development under control and 83
salt stress conditions by screening 347 Arabidopsis accessions of the HapMap population 84
(Horton et al., 2012; Li et al., 2010). Our results indicate increased phenotypic variation 85
in main and lateral root length in salt stress conditions compared to control conditions. 86
By performing GWAS, we identified several candidate genetic loci to be associated with 87
the remodeling of root architecture in response to salt. Further analysis of HKT1 and 88
CYP79B2/B3 candidate genes supports a role for them in modulation of lateral root 89
development under salt stress conditions, increasing our understanding of root responses 90
in contributing to plant performance under stress. To optimally exploit our complex RSA 91
phenotyping dataset beyond the analysis described in this scientific publication, we also 92
make our data available through the Salt_NV_Root App (http://genseq-93
h0.science.uva.nl/shiny/App/Salt_NV_Root/). This tool will facilitate other researchers in 94
exploring our dataset, and finding new leads for further research on RSA remodeling. 95
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RESULTS 97
Salt-induced remodeling of RSA relies on altered lateral root development 98
To examine natural variation in root architecture under salt stress conditions, 347 99
Arabidopsis accessions of the HapMap population (Weigel and Mott, 2009; 100
Supplemental Dataset 1) were grown on agar plates under control and two salt stress 101
conditions (75 and 125 mM NaCl). Using EZ-Rhizo software, 17 RSA traits (Figure 1A, 102
Supplemental Dataset 2) were extracted from the images of 8-day-old plants grown under 103
control condition and 12-day-old plants for both salt stress conditions. Col-0 was used as 104
the reference accession across individual experimental batches, validating the 105
reproducibility of the experiment (Supplemental Figure 1). Using ANOVA, we identified 106
significant effects of medium and genotype on all RSA traits except for lateral root 107
patterning (lateral root density per branched zone) (Supplemental Dataset 2). 108
Additionally, using two-way ANOVA we identified significant interactions between 109
medium and genotype in root angle traits (main root vector angle and straightness) and 110
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distribution of mass between main and lateral root (for example lateral root density per 111
main root length) (Supplemental Dataset 2). 112
Substantial natural variation was observed for all recorded RSA traits, and 113
accessions identified as outliers differed among traits and conditions (Figure 1B, 114
Supplemental Figure 2). The variance within the population differed between individual 115
traits: straightness showing the smallest, and main root vector angle the largest, variance 116
(Figure 1C). Salt stress increased the observed variance in traits related to main and 117
lateral root length, but not in lateral root density, indicating that observed natural 118
variation in response to salt stress is mainly due to differences between accessions in 119
maintenance of main and lateral root growth rather than root patterning. 120
Individual components of RSA were strongly correlated under control conditions 121
(Figure 2A-B, Supplemental Dataset 3). Several of these correlations, including the 122
number of lateral roots with main root length, were significant across all conditions, 123
indicating again that salt does not alter lateral root patterning or that the natural variation 124
therein is limited (Supplemental Dataset 3). However, a significant correlation between 125
the length of the apical zone and lateral root length was observed only under control 126
conditions (Figure 2A), indicating that salt stress increased the variation in the distance 127
from the root tip to the point at which lateral roots start to emerge and elongate, which 128
might be related to different rates of lateral root emergence upon salt stress. The 129
correlation between lateral root length and lateral root number was maintained in 130
seedlings grown under salt stress conditions (Figure 2B), although a decrease in 131
correlation strength was observed. Thus, lateral root emergence had a significant 132
contribution to lateral root size in all conditions despite the increased variability in lateral 133
root length (Figure 1C). The 17 RSA traits, together with the length of the individual 134
zones relative to the main root length, were used for Principal Component Analysis, 135
reducing the data dimensionality to three Principal Components (PC1–3) (Figure 2C, 136
Supplemental Figure 3, Supplemental Dataset 4). Traits corresponding to lateral root 137
development, such as number of lateral roots per main root, lateral root length, and size 138
of the branched zone significantly contributed to PC1, explaining 41% of the variance. 139
PC2, explaining 18.8% of the variance, corresponded to the main root-related traits, such 140
as main root path length, vector length, and depth. The traits related to lateral root 141
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elongation, such as average lateral root length, significantly contributed to PC3, 142
explaining 11.2% of the observed variance. Thus, the majority of the natural variation in 143
RSA is harbored in the distribution of the root mass between main and lateral roots 144
(PC1), maintenance of main root growth (PC2) and lateral root emergence and elongation 145
(PC3). Summarizing the RSA results in three PCs allowed identification of the RSA traits 146
exhibiting most natural variation and reveals phenotypic plasticity in response to salt 147
stress, as the differences between the accessions grown under different conditions are 148
evident even when the dimensionality of the RSA is reduced to three PCs (Supplemental 149
Figure 3). 150
151
GWAS reveals HKT1 and CYP79B2 as candidate genes explaining natural variation 152
in the response of lateral roots to salt 153
Natural variation in 17 RSA traits and three PCs (Supplemental Dataset 5) was used as an 154
input for genome-wide association study (GWAS) using the scan_GLS algorithm 155
(Kruijer et al., 2015). After applying correction for population structure (Kang et al., 156
2008) and exclusion of traits with low narrow heritability (h2 < 0.2, Supplemental Dataset 157
6) GWAS identified 150, 132 and 254 significantly [–log10(p-value) above 5.6] 158
associated SNPs for RSA traits in 0, 75, and 125 mM NaCl respectively (Supplemental 159
Dataset 7). Most SNPs were associated with the average lateral root length per main root 160
length. The largest variation observed in the relative distribution of root mass from main 161
root length to lateral root length corresponds with the high number of associations found 162
for PC3 and average lateral root length measured under salt stress conditions. Identified 163
associations were examined in detail considering their association with multiple traits, 164
using both individual replicates and average value per accession. As the majority of the 165
associations was mapped using the SNP set with Minor Allele Frequency above 0.01, we 166
selected for the associations mapped with MAF of at least 0.01 or with the –log10(p-167
value) score above strict Bonferroni threshold, based on the collection of SNPs including 168
the rare alleles, corresponding to the score of 6.6. We further explored the associations 169
identified with multiple RSA traits and different conditions (Supplemental Figure 4, 170
Supplemental Datasets 8–10). Our selection yielded 100 candidate loci for RSA traits 171
under salt stress conditions, and we subsequently compared their transcriptional changes 172
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in tissue-specific expression in response to salt (Dinneny et al. 2008), revealing 10 genes 173
directly underlying the associated SNPs and 60 genes within the 10-kb window of the 174
mapped SNPs to be significantly altered in the cell type-specific expression dataset in 175
response to salt (Supplemental Dataset 11). The candidate genes that were either directly 176
underlying the associated SNP, or located within the linkage disequilibrium of the 177
identified SNP, were found to be significantly enriched in the genes with tissue specific 178
alterations in response to salt stress as tested per hyper-geometric test. Since natural 179
variation in salt stress response was mostly found in traits related to the relative 180
distribution of root mass between lateral and main roots, we selected six loci associated 181
with average lateral root length, average lateral root length per main root length and PC3 182
in salt stress (Figure 3A, Supplemental Dataset 12) for further analysis. 183
To fine-map the selected loci, the RSA phenotypes were associated with the SNPs 184
based on the whole-genome sequencing data of the accessions (Alonso-Blanco et al., 185
2016), to identify additional SNPs and increase the mapping resolution. We identified 186
between 2 and 26 additional SNPs for loci 1, 2, 5, and 6 (Supplemental Dataset 13). For 187
the chosen loci, the regions surrounding the identified SNPs were further examined for 188
sequence variation (Figure 3B-C, Supplemental Figures 5-8A). Genes located in the 10-189
kb window of the associated SNPs were examined for natural variation in their 190
expression in root and shoot tissue under control and salt stress conditions using 48 191
accessions, chosen based on the SNP diversity of the candidate loci and the pronounced 192
differences between their RSA under all conditions studied (Supplemental Figures 5-8b-193
c, Supplemental Figure 9a, Supplemental Figure 10, Supplemental Dataset 14). For four 194
loci (1,2,3, and 6), we were not able to validate candidate genes due to lack of available 195
mutant lines and/or limited phenotypic changes in response to salt in Col-0 background 196
(Supplemental Figure 7e). Nevertheless, the natural variation in the expression observed 197
among 48 accessions identified candidate background lines for future studies on these 198
loci and can be accessed in the supplemental data (Supplemental Dataset 14). 199
The genomic region surrounding the 4th locus, associated with average lateral 200
root length and the ratio of average lateral root length and main root length at 75 mM 201
NaCl (Figure 3A-B, Supplemental Data set 12), was found to contain only one gene, 202
At4g10310, also known as Arabidopsis HIGH AFFINITY K+ TRANSPORTER 1 203
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(AtHKT1). This gene was previously identified for its role in salinity tolerance (Rus et al., 204
2001; Munns et al., 2012), although no role in the regulation of root system architecture 205
was noted. The genomic region around the associated SNP contained a high number of 206
SNPs and a number of insertions / deletions in the promoter and intron regions of HKT1 207
(Figure 3B). We re-sequenced the locus in 6 accessions varying in HKT1 expression 208
(Supplemental Figure 9B-C, Supplemental Datasets 15-17), and identified 33 cis-209
regulatory elements (Higo et al., 1999) that were specific for two accessions, N4 and Gr-210
5, showing high HKT1 expression. The location of those cis-regulatory elements was 211
widespread between 1330 to 3530 bp upstream of the HKT1 start codon (Supplemental 212
Datasets 16). The coding regions of HKT1 were found to carry 11 polymorphisms 213
compared to Col-0, of which 5 lead to non-synonymous mutations and none were located 214
in the trans-membrane domains (Supplemental Dataset 17). 215
Locus 5 contains six SNPs, spanning from the coding region of At4g39940 up to 216
the coding region of At4g39955 (Figure 3C, Supplemental Datasets 12-13). The SNPs 217
were associated with variation in average lateral root length in 125 mM of NaCl, average 218
lateral root length per main root length in both salt stress conditions, and PC3 in 75 mM 219
of NaCl. Interestingly, the expression of At4g39950, also known as CYTOCHROME 220
P450 FAMILY 79 SUBFAMILY B2 (CYP79B2), was reported to exhibit zone-specific 221
expression changes in response to salt (Dinneny et al., 2008) (Supplemental Dataset 11). 222
CYP79B2 is known to convert tryptophan (Trp) to indole-3-acetaldoxime (IAOx) in the 223
biosynthesis pathway of camalexin, indole glucosinolates and auxin (Hull et al., 2000; 224
Mikkelsen et al., 2000; Zhao et al., 2002; Glawischnig et al., 2004; Sugawara et al. 2009) 225
and its expression was reported at the sites of lateral root development and in the 226
quiescent center, but no role for CYP79B2 in root development has been reported (Ljung 227
et al., 2005). The promoter region of CYP79B2 showed extensive sequence divergence 228
among the accessions and three SNPs were mapped to the promoter of this gene (Figure 229
3C), but the region was too diverse to conduct haplotype analysis. No non-synonymous 230
SNPs were identified in the protein coding sequence of CYP79B2. 231
232
Salt-induced changes in CYP79B2 expression correlate with maintenance of lateral 233
root development 234
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We further investigated the natural variation in transcriptional changes of 235
CYP79B2, and other genes at the same locus, in response to salt stress. CYP79B2 236
expression significantly increased upon salt stress in both root and shoot tissue in most of 237
the 48 accessions studied, but much variation was observed (Figure 4A, Supplemental 238
Dataset 14). A three-way ANOVA showed that the response was the same in both tissues 239
as no interaction effect was found, although expression in the root was significantly 240
higher. While At4g39960 also showed significant induction of expression in salt stress in 241
both root and shoot, the effect was more pronounced in the shoot. At4g39940 showed 242
reduced expression in the root and induced expression in the shoot and At4g39955 243
showed no change upon salt stress (Supplemental Figure 9, Supplemental Dataset 14). 244
For At4g39952 only very recently transcripts were found, and it likely has very low 245
expression (Liu et al., 2016). We have thus decided to focus on CYP79B2 for further 246
analysis. 247
The effect of salt on CYP79B2 expression in the root showed much variation 248
between accessions. The log2 fold change in gene expression in the root upon salt stress 249
ranged from -2.2 in MNF-Pot-4 to 7.2 in Brö1-6 (Supplemental Dataset 14). To 250
investigate whether the change in CYP79B2 expression upon salt stress would correspond 251
with lateral root development, we examined the correlations between the log2 fold 252
change in expression of CYP79B2 and associated RSA traits. The average lateral root 253
length at 75 mM of NaCl significantly correlated with the log2 fold change in CYP79B2 254
expression upon salt stress (Figure 4B). In addition, the log2 fold change showed a 255
significant positive correlation with the lateral root density in salt stress conditions 256
(Figure 4C). 257
As the function of CYP79B2 is known to partially overlap with that of CYP79B3 258
(Hull et al., 2000; Zhao et al., 2002; Glawischnig et al., 2004), we investigated the root 259
system architecture of T-DNA insertion lines (Supplemental Figure 11A) for both genes 260
and the cyp79b2 cyp79b3 double mutant at different salt concentrations. The cyp79b2-1 261
and cyp79b2-2 lines as well as the double mutant cyp79b2-2 cyp79b3-2 showed a slight, 262
but significant, longer main root independent of the conditions (Supplemental Figure 263
11B), but no lateral root-related differences were observed under control conditions. 264
Interestingly, cyp79b2-2 cyp79b3-2 mutant seedlings grown on 125 mM NaCl 265
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supplemented medium, developed significantly fewer lateral roots per cm of main root at 266
10 days after germination (Figure 5A). This is consistent with the observed positive 267
correlation between fold change in CYP79B2 expression upon salt stress and lateral root 268
density (Figure 4C). Double mutant seedlings also developed shorter lateral roots at 12 269
days after germination, consistent with the mapped traits in the GWAS (Figure 5B-C, 270
Supplemental Figure 11B). In summary, our results show that loss-of-function of 271
CYP79B2, together with the partially overlapping CYP79B3, leads to reduced 272
development of lateral root growth under salt stress, but not in control conditions. 273
274
High HKT1 expression reduces lateral root development in saline conditions 275
Extensive natural variation in HKT1 expression in the set of 48 accessions was observed 276
in the root tissue of seedlings exposed to salt stress (Figure 6a, Supplemental Figure 9A), 277
with Gr-5, Hs-0, N4, Ga-2 and Jl-3 showing the highest and LDV-58, CUR-3 and Tsu-0 278
the lowest expression. Although only few accessions exhibited high HKT1 expression, all 279
of these tended to develop shorter lateral roots under salt stress conditions (Figure 6B). 280
By contrast, T-DNA insertion lines with reduced HKT1 expression in the Col-0 281
background did not exhibit any differences in RSA development compared to wild type 282
Col-0 (Supplemental Figure 12), consistent with the natural variation expression data. 283
Since ubiquitous overexpression of HKT1 was previously observed to have a detrimental 284
effect on plant development (Moller et al., 2009), we studied the phenotypes of two 285
available lines with enhanced HKT1 expression at the native expression site, the root 286
pericycle (Mäser et al., 2002; Moller et al., 2009): E2586 UAS-HKT1 in Col-0 287
background and J2731 UAS-HKT1 in C24 background, (Moller et al., 2009). No 288
significant differences between the background lines and lines with enhanced HKT1 289
expression were observed under our control conditions. Interestingly though, under salt 290
stress conditions lines with enhanced HKT1 expression developed fewer and shorter 291
lateral roots in both Col-0 and C24 backgrounds (Figure 6C-D), while the high HKT1 292
expression caused severe reduction in main root length only in Col-0 background (E2586 293
UAS-HKT1) (Figure 6C-D). Thus, while low expression levels of HKT1, either in 294
Arabidopsis accessions or T-DNA lines, seem to have no obvious effects on root 295
morphology, enhanced expression can cause severe alterations in root architecture under 296
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salt stress, possibly due to toxic effects of high Na+ concentrations or changes in osmotic 297
potential of root cells. 298
To investigate whether the severe reduction of lateral root development is caused 299
by osmotic stress, the lines with and without enhanced HKT1 expression in both 300
backgrounds were examined for their lateral root development when grown on media 301
supplemented with 150 mM mannitol. No differences between the background lines and 302
lines with enhanced HKT1 expression were observed (Figure 7A), indicating that the 303
reduced lateral root development is due to the ionic rather than the osmotic component of 304
salinity stress. Salt stress results in imbalance between sodium and potassium ions, and 305
phenotypes of some salt overly sensitive (sos) mutants are known to be rescued by 306
supplementing K+
(Zhu et al., 1998). Therefore, we examined the effect of additional K+ 307
on the UAS-HKT1 lines. For the background lines (E2586 and J2731), extra K+ further 308
reduced lateral root development under salt stress conditions (Figure 7B-C, Supplemental 309
Figure 13). However, for the UAS-HKT1 lines addition of potassium to the salt 310
containing medium resulted in partial rescue of lateral root development. In conditions in 311
which 75 mM NaCl was supplemented by 30 mM KCl, the average lateral root length of 312
the UAS-HKT1 lines was comparable to that of the background lines (Figure 7B), while 313
lateral root emergence was partially rescued (Supplemental Figure 13). Reduction of 314
main root length in the Col-0 UAS-HKT1 line was not affected by additional potassium. 315
These results indicate that potassium supplementation alleviates the effect of enhanced 316
HKT1 expression on lateral root growth specifically in salt stress conditions, suggesting 317
that reduced lateral root growth observed in Arabidopsis accessions and UAS-HKT1 318
lines with high HKT1 expression might be due to an imbalance between sodium and 319
potassium ions. 320
321
High HKT1 expression reduces salt tolerance of Col-0 during early development 322
Interestingly, UAS-HKT1 lines were previously described to exhibit enhanced salt stress 323
tolerance in hydroponic cultures (Moller et al., 2009), but the salt stress was applied at a 324
different developmental stage than in our study. To examine the role of UAS-HKT1 325
expression mediated altered RSA in salt stress tolerance under more natural conditions, 326
UAS-HKT1 and their background lines were grown in soil and were stressed at 1, 2 or 3 327
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weeks after germination by watering with 75 mM NaCl (Figure 8). The UAS-HKT1 line 328
in Col-0 background (E2586 UAS-HKT1) was observed to develop smaller rosettes than 329
its background line (E2586) when plants were stressed one week after germination 330
(Figure 8B). This difference between the Col-0 and UAS-HKT1 lines was less 331
pronounced when plants were treated 2 weeks after germination or later. Consistent with 332
a previous report (Moller et al., 2009), the UAS-HKT1 line in C24 background developed 333
larger rosettes than the background line (J2731) independent of the timing of stress 334
treatment. Interestingly, the rosettes of C24 background line plants grown in control 335
conditions showed no significant difference with plants stressed for 3 or 4 weeks with salt 336
(Figure 8B). Two-way ANOVA analysis (Supplemental Figure 14) showed a 337
background-specific effect, where enhanced HKT1 expression is detrimental for plant 338
development in Col-0 background but not in C24 background when salt stress is applied 339
shortly after germination. Therefore, the correlation between high HKT1 expression and 340
salinity tolerance is dependent on genotype by environment (GxE) effects and the 341
developmental stage at which plants are exposed to salinity stress. 342
343
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DISCUSSION 344
Salt stress not only reduces the development and growth of roots (West et al., 2004; Liu 345
and Zhu, 1997; Kobayashi et al., 2016; Shelden et al., 2013; Tu et al., 2014), but also 346
causes reprogramming and re-distribution of the root mass between main and lateral roots 347
(Julkowska et al., 2014). By studying natural variation for root architecture in 348
Arabidopsis, we observed that the natural variation in RSA responses to salt stress is 349
exhibited mainly through the emergence and elongation, rather than patterning, of lateral 350
roots. The variance observed in traits related to root mass distribution between main and 351
lateral root increased with salt stress exposure (Figure 1D), while the correlations 352
between main root length and number of lateral roots remained unaltered by salt stress 353
(Supplemental Dataset 3). Those trends are in agreement with the data on dynamic 354
changes in RSA performed on a smaller number of Arabidopsis accessions (Julkowska et 355
al., 2014) and with the reduction of lateral root development under salt stress conditions 356
observed in an earlier study (Kawa et al., 2016). In this study, we describe the traits with 357
the most pronounced phenotypic plasticity in response to salt stress to be related to main 358
root length, number of lateral roots, size of the apical zone and average lateral root 359
length, as they make most significant contributions to Principal Components describing 360
natural variation observed (Supplemental Dataset 4) and are subjected to G x E 361
interactions (Supplemental Dataset 2). Collecting multi-trait phenotypes and performing 362
multi-variate analysis, as presented in this work, will improve our understanding of how 363
plant development affects performance under stress conditions. The data presented in this 364
study are available through the Salt_NV_Root App for the user to explore in more detail, 365
compare individual accessions and also perform cluster analysis on the RSA traits of 366
interest. This tool can thus provide additional insight for further exploration of natural 367
variation in complex RSA traits and their relationship to plant performance. 368
While many GWAS studies published to date focus on single traits, such as ion 369
accumulation, main root growth or compatible solute accumulation (Strauch et al., 2015; 370
Baxter et al., 2010; Lachowiec et al., 2015; Slovak et al., 2014; Verslues et al., 2014), 371
there is an increasing focus on multi-trait response phenotypes, including RSA response 372
to stress (Rosas et al., 2013; Kawa et al., 2016). An advantage of performing GWAS on 373
multi-trait phenotypes, also apparent in our study, is that additional confidence can be 374
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gained when the same candidate loci are mapped using different traits and / or different 375
stress conditions, or when the multi-trait phenotypes are reduced to Principle 376
Components that map to the overlapping loci (Figure 3A). Interestingly, 100 candidate 377
loci identified by GWAS in this study contain genes involved in ethylene and ABA 378
signaling, such as EIN2 and SnRK2.7 (Supplemental Dataset 11), indicating natural 379
variation in hormonal control pathways that were earlier described to play a role in RSA 380
responses to salt stress (Duan et al., 2013; Geng et al., 2013). The significant overlap 381
between the identified candidate genes and salt stress-induced changes in gene expression 382
(Dinneny et al., 2008, Supplemental Dataset 11) implies that the allelic variation might 383
accumulate in the regions important for transcriptional regulation of genes involved in 384
root remodeling in response to salt. Also, a meta-analysis on genetic architecture of 385
abiotic and biotic stress responses, which included a selection of our salt stress response 386
data, implied genetic correlations with other abiotic stress responses (Thoen et al., 2017). 387
Our genetic and physiological data confirm two identified candidate genes, 388
CYP79B2 and HKT1, to be involved in lateral root development under salinity stress, 389
which suggests that genes identified in our GWAS are indeed involved in reshaping RSA 390
under salt stress conditions. Significant correlations were found between salt-induced 391
expression of CYP79B2 and lateral root development under salinity stress (Figure 4). 392
Further analysis of CYP79B2 and CYP79B3, which are known to have partially 393
overlapping functions, showed that these genes are required for the maintenance of lateral 394
root growth under salt stress conditions, but not in control conditions (Figure 5). As both 395
CYP79B2 and CYP79B3 convert tryptophan to indole-3-acetaldoxime (IAOx), these data 396
suggest the involvement of the IAOx pathway in shifting investments from main to 397
lateral roots during salt stress. Both CYP79B2 and CYP79B3 were previously observed to 398
be expressed at the site of newly developing lateral roots (Ljung et al., 2005). The IAOx 399
pathway is Brassica-specific and can produce three types of active compounds: 400
camalexin, indole glucosinolates and IAA (Hull et al., 2000; Zhao et al., 2002; Mikkelsen 401
et al., 2000; Glawischnig et al., 2004; Sugawara et al., 2009). Both camalexin and indole 402
glucosinolates act as defense compounds induced in both shoot and root upon pathogen 403
attack (Glawischnig, 2007; Halkier and Gershenzon, 2006; Brown et al., 2003; Lemarié 404
et al., 2015), but no clear link to root development has been found. The IAOx pathway 405
14
has been shown to contribute to auxin production under heat stress conditions (Zhao et 406
al., 2002). NITRILASE 1 (NIT1), proposed to catalyze the last step of the IAOx pathway 407
leading to auxin biosynthesis, was previously described to be involved in maintenance of 408
lateral root development (Lehmann et al., 2017), and the expression of NIT1 and NIT2 409
was observed to be upregulated in response to salt stress (Bao and Li, 2002). We propose 410
that the natural variation in promoter region of CYP79B2 results in altered expression 411
induction by salt stress, and that IAOx-pathway is necessary for maintenance of lateral 412
root development under salt stress, most likely through production of auxin, although a 413
role for other IAOx-pathway generated compounds cannot be excluded. 414
The association found in the promoter region of HKT1 provides a link between 415
ion sequestration and lateral root development. Our results suggest that some accessions 416
with high HKT1 expression develop shorter lateral roots under salt stress conditions 417
(Figure 6B). Using transgenic lines with enhanced expression at the native root 418
expression site (UAS-HKT1 lines), we confirmed that high HKT1 expression indeed 419
reduces lateral root formation under salt stress in Col-0 and C24 background (Figure 6C-420
D). Potassium uptake was previously described to repress lateral root formation under 421
control and drought conditions, as kup268 and gork mutants showed enhanced root 422
development (Osakabe et al., 2013). Our results suggest that the effect of potassium is 423
stress dependent, as additional potassium enhanced lateral root development only in lines 424
with enhanced HKT1 expression, but not in the background lines (Figure 7B-C). 425
Although sodium accumulation in the root stele is important for ion exclusion from shoot 426
tissue (Moller et al., 2009; Kotula et al., 2015; Munns et al., 2012), in the young 427
seedlings the high stelar sodium accumulation could potentially result in ABA-dependent 428
lateral root quiescence (Duan et al., 2013) or even damage to the lateral root primordia. 429
The exact mechanisms underlying the reduced lateral root development in lines 430
overexpressing HKT1 remain to be verified in future studies. 431
The salinity tolerance of the C24 UAS-HKT1 line was reported before to be 432
enhanced when 3-week-old plants were exposed to salinity (Moller et al., 2009), and high 433
HKT1 expression was previously found to cause sodium exclusion from leaf tissue and 434
therefore higher salt stress tolerance (Rus et al., 2006; Baxter et al., 2010; Munns et al., 435
2012). Previously, natural accessions that exhibited reduced lateral root emergence were 436
15
associated with increased sensitivity to salt stress, while those with many, but shorter 437
later roots showed better maintenance of Na+/K
+ ratio under salt stress (Julkowska et al., 438
2014). Here, we found that enhanced HKT1 expression reduced RSA development when 439
4-day-old seedlings were exposed to salt on agar plates and while also negatively 440
affecting salinity tolerance in the Col-0 background when these plants were exposed to 441
salt in soil early in their development (Figure 8), which might be ascribed to differences 442
in sodium-storage capacity of 4-day-old roots versus 3-week-old roots. On the other 443
hand, enhanced stelar expression of HKT1 in the C24 line was associated with increased 444
salinity tolerance in soil independent of the developmental stage at the application of salt 445
stress (Figure 8), in agreement with previously published hydroponics data (Moller et al., 446
2009). These results imply that the benefit of tissue-specific sodium 447
compartmentalization depends on maintenance of the ion balance between sodium and 448
potassium as well as genetic background and the developmental stage at which plants are 449
exposed to salinity. 450
The allelic variation responsible for high HKT1 expression was widespread across 451
the promoter region, with 33 predicted cis-regulatory elements shared between accessions 452
with high HKT1 expression (Supplemental Figure 9, Supplemental Dataset 16). The 33 453
predicted cis-regulatory elements did not overlap with either the minimal promoter of 454
HKT1 (Mäser et al., 2002), or ABI4 binding sites (Shkolnik-Inbar et al., 2013). 455
Identification of a promoter region responsible for enhanced HKT1 expression will 456
require identification of transcription factors regulating HKT1 expression and their 457
binding sites, rather than examining extensive and widespread allelic variation. Although 458
high HKT1 expression was earlier associated with increased salt stress tolerance (Moller 459
et al., 2009; Munns et al., 2012), the plants used in those studies were much further along 460
in their development at the time of salt stress exposure. Our results suggest that this 461
strategy is not advantageous when plants are exposed to salinity early in their 462
development (Figure 8), in accordance with several coastal accessions carrying a low-463
expression HKT1 allele (Baxter et al., 2010). The complex relationship between high 464
HKT1 expression and plant tolerance to salinity shown in this study provides a rationale 465
for high variation of the HKT1 promoter region in natural accessions of Arabidopsis as 466
well as other plant species (Munns et al., 2012; Negrão et al., 2012), and fine-tuning of 467
16
HKT1 expression levels depending on local soil conditions and timing of exposure to salt 468
stress. Correlations between RSA and plant survival (Katori et al., 2010) and sodium 469
exclusion (Baxter et al., 2010) are very weak (Supplemental Figure 15), which might be 470
partially due to different experimental set-ups used. Additionally, the relationship 471
between RSA and salt tolerance depends on the developmental and the genetic context, as 472
we have shown in this study using UAS-HKT1 lines. Further investigation of the other 473
candidate genes identified in this study and examining their contribution to RSA 474
development and salt stress tolerance in a uniform genetic background will provide more 475
insight in how salt stress affects root morphology and how those changes would increase 476
salt stress tolerance of crops. 477
478
17
MATERIALS & METHODS 479
480
Plant material and growth conditions 481
The Arabidopsis HapMap collection (Weigel and Mott, 2009) was obtained from the 482
Arabidopsis Biological Resource Centre (www.abrc.osu.edu). The 360 accessions were 483
propagated under long day conditions (21°C, 70% humidity, 16/8h light/dark cycle, 125 484
mol/m2/s, Sylvania Britegrow F58W 1084 lamps), with 8 weeks vernalization (between 485
4 and 8°C, 70% humidity, 16/8h light/dark cycle) starting at the 3rd
week after 486
germination to ensure flowering of all the accessions. Accessions that failed to germinate 487
or flower were excluded from the screen, resulting in 347 accessions in total 488
(Supplemental Dataset 1). Seeds used for the experiments were between 2 months and 1 489
year old. 490
Seeds were surface sterilized in a desiccator of 1.6 L volume using 20 mL 491
household bleach and 600 µL 40% HCl for 3 h and were put in the laminar flow for 1.5 h 492
to remove toxic vapors. The seeds were stratified in 0.1% agar at 4°C in the dark for 72 h 493
and sown on square petri dishes (12 x 12 cm) containing 50 mL of control growth 494
medium consisting of ½ Murashige-Skoog, 0.5% sucrose, 0.1% M.E.S. monohydrate and 495
1% Daishin agar, pH 5.8 (KOH), dried for 1 h in a laminar flow. Plates were placed 496
vertically at a 70° angle under long day conditions (21°C, 70% humidity, 16/8h light/dark 497
cycle). Four-day-old seedlings were transferred to square petri dishes containing basic 498
medium supplemented with 0, 75 or 125 mM NaCl. Each plate contained four seedlings 499
of two genotypes (two seedlings per genotype). Plates were placed in the growth chamber 500
following a random design. The plates were scanned with Epson perfection V700 scanner 501
at 200 dpi every other day until 8th
day post transfer. The 8-day-old seedlings grown in 0 502
mM NaCl were used for phenotyping of RSA in control conditions while for both salt 503
stress conditions (75 and 125 mM NaCl) phenotypes of 12-day-old seedlings were 504
scored. The pictures were analyzed with EZ-Rhizo software (Armengaud et al., 2009). 505
The entire population of 347 accessions was screened over six individual experiments 506
with Col-0 as internal reference (Supplemental Figure 1). The RSA phenotypes of 507
individual accessions were calculated from four biological replicates, except for Nd-1, 508
18
Tommegap and Tottarp, where the RSA phenotype in control conditions was measured 509
only for 2 biological replicates. 510
511
Analysis of natural variation in RSA phenotypes 512
The collected data on RSA phenotypes was cleared of outliers by removing the 513
accessions of which the standard deviation within the genotype was larger than the 514
standard deviation within the HapMap population, and RSA phenotyping was repeated 515
for these accessions in the next experimental batch. The natural variation in the studied 516
population was further explored by using average values per accessions as an input for 517
notched boxplots and calculating coefficient of variance per condition studied. The 518
correlations among different RSA traits at different conditions are presented in 519
Supplemental Dataset 3. 17 RSA parameters and three additional parameters consisting 520
of the length of apical, branched, and basal zone represented as the portion of main root 521
length (Apical / MRL, branched / MRL and basal / MRL respectively), were reduced to 522
three PC by performing PCA (Supplemental Figures 2C, 3). The raw data was first 523
normalized per trait by applying Z-score normalization in individual phenotypes. The 524
Principal Components were calculated using Mat Lab. The importance of individual RSA 525
traits for each PC is presented in Supplemental Dataset 4. Individual PCs as well as the 526
raw phenotypic data were used as input for Genome Wide Association Study 527
(Supplemental Dataset 5). 528
The entire dataset and the Multi-Variate analysis was integrated into Shiny App 529
based “Salt_NV_Root App”, available at http://genseq-530
h0.science.uva.nl/shiny/App/Salt_NV_Root/. The user guide for the App is available at 531
https://mmjulkowska.github.io/Salt_NV_RootApp/. The code for the App is available at 532
https://github.com/mmjulkowska/Salt_NV_RootApp. 533
534
GWAS on RSA phenotypes 535
The RSA phenotypes were linked to published genomic data on accessions from a 250k 536
SNP chip with average SNP density of one SNP in 500 bp (Horton et al., 2012). The 537
narrow sense heritability of individual traits at different conditions was determined 538
(Supplemental Dataset 6). Apart from one trait (excluded from further analysis), the 539
19
estimated heritability for all traits was above 0.2. We performed GWAS using the entire 540
SNP data set as well as excluding the SNPs with minor allele frequency of 0.01, 0.05 and 541
0.10 to avoid misleading associations. The associations between each SNP and individual 542
RSA phenotypes were tested using a scan_GLS program (Kruijer et al., 2015), based on 543
EMMA-X (Kang et al., 2008). The method implements Gao and Bonferroni corrections 544
for multiple testing to minimize the false discovery rates. Both methods were applied on 545
phenotypic values per accession with α of 0.01 and 0.05 and Minor Allele Frequency 546
(MAF) of 0.00, 0.01, 0.05 and 0.10. We used 5.6 as the threshold value, as there were 547
around 20000 SNPs with MAF > 0.01 and the threshold was therefore -548
log10(0.05/20000) = 5.6. The overview of numbers of associated loci identified with 549
individual traits with LOD > 5.6, including all rare alleles is presented in Supplemental 550
Dataset 7. 551
The list of putative loci was selected using metrics considering the association 552
when the individual values of each replica were mapped and when average values per 553
genotype were used for GWAS. Furthermore, we selected for the associations mapped 554
using only the SNP subset with MAF > 0.01, as the majority of the associations were 555
identified with this SNP set, while excluding the rare alleles, represented by less than 3 556
accessions, that could skew the associations found. For the loci that were mapped with a 557
SNP set including rare alleles, we used the more stringent Bonferroni threshold for 558
further selection of associations, based on all SNPs used (including the rare SNPs), 559
determined as log10(0.05/200 000) = 6.6 (Supplemental Datasets 8 – 10). We selected the 560
SNPs that were mapped with both average and individual replica trait values and –561
log10(p-value) above the Bonferroni threshold or mapped with the SNP subset of MAF > 562
0.01 (Supplemental Figure 4). Our selection yielded 49 associations with traits measured 563
under control conditions and 154 associations specific to RSA traits measured under salt 564
stress conditions (Supplemental Figure 4, Supplemental Datasets 8, 9 and 10). The 565
candidates from all conditions studied were compared and the associations overlapping 566
between individual traits and conditions were identified. 567
The enrichment analysis of the 100 candidate loci identified under salt stress 568
conditions was performed with the hyper-geometrical test, using the phyper() function in 569
R. We used 27,655 protein-coding genes as the “population size” parameter, with 1632 570
20
genes identified by Dinneny (et al., 2008) as responsive to salt stress. For testing the 571
genes directly underlying the associated SNP, we used 10 genes that we identified to be 572
altered in their expression, among 100 possible genes. For testing the genes in linkage 573
disequilibrium with the identified SNP, we calculated the average number of genes per 10 574
kb upstream and downstream from identified SNP (27,655 genes per 119,146,348 bp 575
resulting in 0.0002321095 gene per bp, and 4.64219 genes per 20 kbp – 10kb upstream 576
and 10 kb downstream from the identified SNP). Subsequently, we used the average gene 577
density to determine the number of possible candidate genes for 100 identified loci, 578
ending up with 464,219 possible candidate genes. Therefore, the hyper-geometric test for 579
the neighboring candidate genes was run with 70 genes that we identified to be altered in 580
their expression among 464,219 possible genes. 581
The associations with average lateral root length and the ratio between average 582
lateral root length were studied in greater detail (Supplemental Data set 12). To further 583
fine-map the chosen loci, the RSA phenotypes were linked to the genotypic data based on 584
whole-genome sequencing data of the different accessions (Alonso-Blanco et al., 2016) 585
and covered 4,000,000 SNPs. For the accessions that were not sequenced, genome 586
information was imputed based on the 250-k SNP chip data (Horton et al., 2012). Those 587
imputations are known to have negligible effect on the GWAS outcomes (Cao et al., 588
2011). The GWAS was performed on the average trait value per genotype and the SNPs 589
corresponding to the 6 loci that we identified (Supplemental Dataset 12) are presented in 590
Supplemental Dataset 13. 591
For the selected associations (Supplemental Dataset 12) sequence information of 592
147 accessions belonging to the HapMap population was downloaded from the 1001 593
genomes project website (1001genomes.org) and aligned with ClustalO as described in 594
Julkowska et al. (2016). 595
596
Expression analysis of accessions 597
48 Arabidopsis accessions were selected based on different haplotypes of selected 598
candidate loci as determined from SNP data and the pronounced differences between 599
their RSA under all conditions studied (Supplemental Dataset 14). The accessions were 600
used for studying the natural variation in the expression of candidate genes 601
21
(Supplemental Dataset 14). The 4-day-old seedlings of 48 different accessions were 602
transferred to plates supplemented with 0 or 75 mM NaCl. After 24 h, the seedlings were 603
harvested, snap-frozen in liquid nitrogen and divided into root and shoot fraction. RNA 604
extraction was performed with TRI-reagents (Sigma) with additional chloroform cleaning 605
step, followed by TURBO DNase treatment (Ambion). The RNA was checked for the 606
integrity on 2% agarose gel. The cDNA was synthesized from 1 µg total RNA using 607
reverse transcriptase (Fermentas). The cDNA was diluted to approximately 10ng/µl. The 608
diluted cDNA was used in a specific target amplification (STA) reaction and subjected to 609
PCR on a Biomark genetic analysis system on a 96 x 96 Dynamic array, according to 610
manufacturer’s instructions (Fluidigm). The primer sequence for qPCR was designed 611
focusing on the 3ʹ end and targeting the conserved sites with no / little natural variation in 612
the sequence as found out in 1001 sequence browser. The sequences of the primers used 613
are to be found in Supplemental Data set 18. For the loci 1, 2, 3, 4, and 6 the transcript 614
levels of At1G07920, At1G13320, At3G04120, At5G12240, and At5G46630 were used 615
for normalization of expression. Expression of the genes in the locus 5 was measured in a 616
separate experiment, using At1G07920, At1G13320, At5G12240, and At5G46630 as 617
reference transcripts for normalization, without At3G04120. 618
Samples of low quality were removed and Ct-values ≥ 30 were set to 30 to reduce 619
the background noise. The expression levels of target genes were calculated by ΔCt = 620
2-Ct-value target
⁄ 2-Ct-value reference
. To normalize the expression for all five / four reference 621
genes used; geometrical mean was calculated from delta-Ct normalized expression for 622
each reference gene and the average expression per accession, tissue, and conditions were 623
calculated for each putative candidate gene. For regression analysis between traits and 624
expression, highly influential observations were not considered based on Cook’s distance 625
(if > 0.5). 626
T-DNA insertion lines genotyping and phenotyping 627
The lines were ordered from the European Arabidopsis stock center (nasc.org.uk), except 628
for the cyp79b2-2 cyp79b3-2 line (Sugawara et al., 2009), which was kindly provided by 629
Dr. Hiroyushi Kasahara (RIKEN Center for Sustainable Resource Science, Yokohama, 630
Japan). The full list of T-DNA insertion lines used is to be found in Supplemental Dataset 631
19. The T-DNA insertion lines were genotyped by extracting DNA from leaf material 632
22
ground in liquid nitrogen using 10% Chelex (Bio-rad) in MiliQ followed by 15 min 633
incubation at 95°C and 15 min centrifugation at maximum speed in the standard tabletop 634
centrifuge. The supernatant was used as an input for the PCR reaction. The primers used 635
for T-DNA insertion lines identification are listed in Supplemental Dataset 19. The RSA 636
phenotypes of HKT1 T-DNA insertion lines were studied as described above for the 637
phenotyping of Arabidopsis accessions (n=16). A one-way ANOVA was used to analyze 638
these data, as the control plants and salt treatment plants were not the same age. A Tukey 639
post-hoc test was used to analyze differences between genotypes within treatments. The 640
RSA phenotypes of CYP79B2 and CYP79B3 T-DNA insertion lines were studied as 641
described above, but no sucrose was added in the medium (n=20) and RSA traits were 642
quantified with Smartroot (Lobet et al., 2011). For analyses of the single and double 643
mutant lines on day 10 (Figure 5A, Supplemental Figure 11B), data of three experiments 644
was pooled to increase statistical power. To correct for this, Experiment was included as 645
random factor in a mixed linear model. For the analysis of double mutant lines on day 10 646
and day 12, data of one representative experiment is shown (Figure 6B and Supplemental 647
Figure 12C). Data was analyzed using a three-way ANOVA. For both, if a significant 648
interaction was found, a Bonferroni-corrected post-hoc within treatment (and day) 649
analysis was used to analyze differences between genotypes. 650
The expression levels of gene of interest in T-DNA insertion lines were studied 651
by qPCR analysis. RNA was extracted from whole seedlings grown on agar plates for 12 652
days in control conditions with TRI-reagents (Sigma Aldrich) with additional chloroform 653
cleaning step, followed by TURBO DNase treatment (Ambion). The RNA was examined 654
for the integrity on 2% agarose gel. The cDNA was synthesized from 1 µg total RNA 655
using reverse transcriptase (Fermentas), diluted to approximately 10 ng/µl and used for 656
qPCR using the Eva-Green kit (Solis Biodyne) and an Applied Biosystems sds7500 657
machine with three biological replicates and two technical replicates. The expression was 658
normalized using AT1G13320 transcript levels. The expression levels of putative 659
candidate genes were calculated by ΔCt = 2- (Ct-value target)
⁄ 2- (Ct-value reference)
. The sequences 660
of the primers used are listed in Supplemental Dataset S18. 661
662
Sequencing the HKT1 locus and parsimony calculations 663
23
The sequencing of HKT1 was performed on seven accessions. The accessions were 664
chosen based on their RSA phenotype and relative expression of HTK1. The primers used 665
are listed in Supplemental Dataset 15. The sequences of individual accessions were 666
aligned using MegAlign software and aligned to each other in MegAlign ClustalW 667
algorithm (Supplemental Figure 16). The sequences encoding exons are highlighted in 668
yellow, introns in purple and UTRs in red. The identified polymorphisms were 669
investigated by examining the patterns in the promoter region using the web-based 670
database for Plant Cis-acting Regulatory DNA Elements (PLACE) (Higo et al., 1999), by 671
examining the presence / absence of cis-regulatory element in the sequence flanking the 672
polymorphism. Translating exon sequences into the protein sequences in JalView was 673
performed to examine the non-synonymous changes in amino acid sequence. The 674
polymorphisms located in intron region were examined whether they interfere with the 675
splicing acceptor, donor or branching site. The polymorphisms found outside of those 676
areas were assumed to have no major effect. The polymorphisms identified in promoter 677
and exon regions were encoded with P-numbers and in exons with E-numbers for 678
individual locus separately and are listed in Supplemental Dataset 16 – 17. 679
The evolutionary history was inferred for each locus separately using the 680
Maximum Parsimony method. The most parsimonious tree with length is shown. The MP 681
tree was obtained using the Subtree-Pruning-Regrafting (SPR) algorithm with search 682
level 0 in which the initial trees were obtained by the random addition of sequences (10 683
replicates). The MP trees are drawn to scale; with branch lengths calculated using the 684
average pathway method and are in the units of the number of changes over the whole 685
sequence. The analysis involved 7 nucleotide sequences from different Arabidopsis 686
accessions. All positions containing gaps and missing data were eliminated. Evolutionary 687
analyses were conducted in MEGA5 (Tamura et al., 2011). 688
689
Salinity tolerance assessment in transpiring conditions (soil) 690
Seeds of UAS-HKT1 and the background lines to be tested were stratified for 48 h at 4°C 691
and sown in soil in pots. Seeds of four different lines were put in one pot (four plants per 692
pot) and were germinated under short day conditions (21°C, 70% humidity, 11/13h 693
light/dark cycle). After one, two or three weeks the seedlings were treated with 75 mM 694
24
NaCl applied from above every second day for 6 weeks. After 7 weeks of growth the 695
fresh weight of the rosette was measured. The statistical analysis was performed for one- 696
and two-way ANOVA with Scheffe’s post-hoc test for significance. 697
698
Accession Numbers 699
Sequence data from this article can be found in the Arabidopsis Genome Initiative or 700
GenBank/EMBL databases under the accession numbers listed in Supplemental Dataset 701
1. 702
703
Supplemental Data 704
Supplemental Figure 1. Experimental set up and internal reference accession data for 705
screening natural variation in RSA responses to salt stress. 706
Supplemental Figure 2. Natural variation in all RSA phenotypes studied. 707
Supplemental Figure 3. Principle Components used for GWAS. 708
Supplemental Figure 4. Selection of putative candidate loci from GWAS associations. 709
Supplemental Figure 5. Natural variation in Locus 1 associated with ratio of average 710
lateral root length to main root length and Principal Component 3 at 75 mM NaCl. 711
Supplemental Figure 6. Natural variation in Locus 2 associated with ratio of average 712
lateral root length to main root length and principal component 3 at 75 mM NaCl. 713
Supplemental Figure 7. Natural variation in Locus 3 associated with ratio of average 714
lateral root length to main root length and principal component 3 at 75 mM NaCl. 715
Supplemental Figure 8. Natural variation in Locus 6 on chromosome 5 associated with 716
average lateral root length, ratio of average lateral root length to main root length and 717
principal component 3 at 125 mM NaCl. 718
Supplemental Figure 9. Natural variation in HKT1 expression in root and shoot tissue in 719
control and salt stress conditions. 720
Supplemental Figure 10. Natural variation in CYP79B2 and surrounding genes in root 721
and shoot tissue in control and salt stress conditions. 722
Supplemental Figure 11. RSA phenotypes of knock-out mutants of CYP79B2 and 723
CYP79B3. 724
25
Supplemental Figure 12. Reduced expression of HKT1 does not result in changes in 725
RSA. 726
Supplemental Figure 13. RSA phenotype of UAS-HKT1 lines is partially rescued by 727
addition of K+ at 75 mM NaCl.728
Supplemental Figure 14 High HKT1 expression results in reduced salinity tolerance 729
during early exposure to salt stress and is dependent on the background. 730
Supplemental Figure 15. Correlation between salt induced changes in RSA and salt 731
tolerance. 732
Supplemental Figure 16. The alignment of HKT1 promoter and coding region sequence 733
in 7 sequenced accessions. 734
Supplemental Dataset 1. List of all Arabidopsis accessions screened for RSA in control 735
and salt stress conditions. 736
Supplemental Dataset 2. Overview of 17 Root System Architecture traits measured. 737
Supplemental Dataset 3. Correlations between RSA traits in different growth 738
conditions. 739
Supplemental Dataset 4. The scores of individual RSA traits for three Principal 740
Components used for GWAS. 741
Supplemental Dataset 5. The average of RSA traits for individual accessions of 742
Arabidopsis in three different conditions. 743
Supplemental Dataset 6. Heritability for individual RSA traits 744
Supplemental Dataset 7. Overview of number of significant associations identified. 745
Supplemental Dataset 8. List of significant associations with RSA traits at 0 mM NaCl. 746
Supplemental Dataset 9. List of significant associations with RSA traits at 75 mM 747
NaCl. 748
Supplemental Dataset 10. List of significant associations with RSA traits at 125 mM 749
NaCl 750
Supplemental Dataset 11. List of the candidate genes identified with RSA traits at 75 or 751
125 mM NaCl with significant alterations in the cell type-specific expression in response 752
to salt. 753
Supplemental Dataset 12. Overview of the candidate genes selected for examination in 754
Figure 4. 755
26
Supplemental Dataset 13. Fine-mapping of the 6 selected loci (table S12) by the use of a 756
10M SNP library. 757
Supplemental Dataset 14. The relative expression of accessions studied for natural 758
variation in candidate gene expression. 759
Supplemental Data set 15. List of primers used for sequencing the loci of putative 760
candidate genes. 761
Supplemental Data set 16. The list of polymorphisms found in the promoter region of 762
At4g10310 and predicted changes in cis-regulatory elements as analyzed with PLACE. 763
Supplemental Data set 17. The list of polymorphisms found in the exon regions of 764
At4g10310. 765
Supplemental Data set 18. List of primers used for expression study of candidate genes 766
Supplemental Data set 19. Overview of t-DNA insertion lines studied including the 767
primers used for genotyping t-DNA insertion lines. 768
769
Acknowledgements: 770
The authors would like to thank Willem Kruijer from Wageningen University for help 771
with GWAS, Dorota Kawa and Jessica Meyer from University of Amsterdam for their 772
technical support. We thank Dr. Hiroyushi Kasahara (RIKEN Center for Sustainable 773
Resource Science, Yokohama, Japan) for the provided materials. This work was 774
supported by the Netherlands Organisation for Scientific Research (NWO), STW 775
Learning from Nature project 10987 and ALW Graduate Program grant 831.15.004. 776
Author Contributions: 777
Conceptualization, CT; Methodology, JJBK, MMJ, HH, AK and CT; Validation, MMJ, 778
IK, SM and RF; Formal Analysis, MMJ and HH; Investigation, MMJ, IK, SM and 779
RF; Resources, JJBK, AK and MT; Data curation, MMJ, IK and CT; Writing Original 780
Draft, MMJ, and CT; Writing Review & Editing, MMJ, CT, IK, MT, MAH and JJBK; 781
Visualization, MMJ; App development, MMJ; Supervision, CT, MT, GJdB and MAH; 782
Project administration, CT; Funding Acquisition, CT and GJdB 783
784
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994
35
Figure Legends 995
Figure 1. Natural variation observed in RSA plasticity in response to salt stress. The 996
effect of salt stress on RSA was examined for 347 Arabidopsis accessions (Supplemental 997
Data set 1) on 8- and 12-day-old seedlings grown in control and salt stress conditions 998
respectively. (A) Overview of RSA parameters obtained from EZ-Rhizo quantification. 999
Additionally, lateral root length (LRL), average lateral root length (aLRL) as well as the 1000
ratios between main root (MRL), average lateral root length aLRL), and total root size 1001
(TRS) were calculated. All RSA traits are listed in Supplemental Dataset 2. (B) Natural 1002
variation in total root size (TRS), main root length (MRL), and average lateral root length 1003
(aLRL) is presented with notched box-plots. The accessions representing outliers in 1004
individual traits are indicated. Boxplots of all RSA traits are presented in Supplemental 1005
Figure 2. (C) Coefficient of variation observed in all 17 RSA traits per salt stress 1006
condition for 347 Arabidopsis accessions studied. The significant differences in variation 1007
between control and salt stress are indicated with * for p-value < 0.05 and ** for p-value 1008
< 0.01, as calculated using f-tests. 1009
1010
Figure 2. Salt affects the relationship between RSA components, with lateral root 1011
development explaining the majority of observed variation. (A) The correlation 1012
between apical zone size and total lateral root length (LRL) and (B) lateral root number 1013
(#LR) and total lateral root length (LRL) for plants grown under 0, 75, and 125 mM NaCl 1014
are presented with red, green, and blue dots respectively. The lines in corresponding color 1015
represent the linear model fitting the correlation per condition. The Pearson correlation 1016
coefficients (r) are presented in the lower right corner of each correlation graph, with ** 1017
indicating p-value < 0.01 and * p-value < 0.05. (C) Principal Component Analysis 1018
revealed three PCs explaining 71.4% of variation. The contribution plots show how each 1019
RSA trait contributes to each PC, ranging from low contribution (dark-blue) to high 1020
contribution (light-blue). The contribution of individual traits to each PC is listed in 1021
Supplemental Data set 4. 1022
1023
Figure 3. GWAS identifies loci with high and low allele diversity. GWAS was 1024
performed on (A) average Lateral Root Length (aLRL), ratio of average Lateral and Main 1025
36
Root Length (aLRL/MRL), and Principle Component 3 (PC3) at low salt stress 1026
conditions (75 mM NaCl) and significant associations above LOD 5.6 with MAF > 0.01 1027
were identified. The dotted line represents the threshold of a LOD of 5.6. The 6 chosen 1028
loci (Supplemental Dataset 12) are marked. The validated loci containing HKT1 (locus 4) 1029
is marked with green and CYP79B2 (locus 5) with purple. Genetic variation in locus 4 1030
(B) and 5 (C) was studied in 147 HapMap population accessions. The purple graphs 1031
represent the portion of missing data, while the green graphs represent deletions present 1032
in accessions other than Col-0. The blue graphs represent the sequence similarity 1033
compared to Col-0. The Open Reading Frames are aligned in the lowest panel. The 1034
location of the associated SNPs from 250k SNP set is represented with highlighted 1035
dashed-lines, while the SNPs mapped using the 4M SNP set are represented with gray 1036
dashed-lines. 1037
1038
Figure 4. Change in CYP79B2 expression in response to salt stress correlates with 1039
lateral root development during salt stress. Natural variation in genes in locus 5 was 1040
studied in root and shoot tissue in 5-day-old seedlings treated with mock or 75 mM NaCl 1041
for 24 h. The boxplot (A) represents the median and extent of natural variation in 1042
CYP79B2 expression as observed for population of 48 accessions. Boxplots for the other 1043
genes in the same locus can be found in Supplemental Figure 10, together with heat plots 1044
of the expression per accession, while the normalized expression of all studied genes is 1045
presented in Supplemental Dataset 14. The relative log2 fold change in expression of 1046
CYP79B2 between control and salt stress positively correlated to several root architecture 1047
traits in the accessions, including (B) average lateral root length per main root length 1048
(aLRL/MRL) at 75 mM NaCl and (C) the lateral root density (LRD) at 75 mM NaCl. 1049
The Pearson correlation coefficients (r) are presented in the lower right corner of each 1050
correlation graph, with ** indicating p-value < 0.01 and * p-value < 0.05. 1051
1052
Figure 5. Loss-of-function of both CYP79B2 and CYP79B3 results in reduced lateral 1053
root development during salt stress. (A) 4-day-old seedlings of Col-0, cyp79b2, 1054
cyp79b3, and cyp79b2 cyp79b3 lines were transferred to 0, 75, and 125 mM NaCl and 1055
RSA of 10-day-old seedlings was quantified. The bar-plots represent the average lateral 1056
37
root density (LRD) of three experiments with each 20 replicates; error bars represent 1057
pooled SE. A mixed linear model was used to determine significant differences and a 1058
significant interaction between treatment and genotype was found. Letters represent 1059
significant differences (p < 0.05) following a manual-contrasts post-hoc comparison 1060
within treatment. (B) Average Lateral Root Length (aLRL/MRL) and average lateral root 1061
length (aLRL) for Col-0 and cyp79b2 cyp79b3 in 0 mM (10-day-old seedlings) and 125 1062
mM (10-day- and 12-day-old seedlings) NaCl. Other lateral root traits are presented in 1063
Supplemental Figure 11. Bar-plots represent the average trait value as observed in 20 1064
replicates and error bars represent SE. All traits were analyzed using two-way ANOVA 1065
and significant interactions were found for shown traits. Letters represent significant 1066
differences (p < 0.05) following a manual-contrasts post-hoc comparison within 1067
treatment. (C) Pictures of representative seedlings of Col-0 and the cyp79b2 cyp79b3 1068
double mutant at 125 mM NaCl (12-day-old seedlings). 1069
1070
Figure 6. High HKT1 expression reduces LR development in salt stress conditions. 1071
(A) Natural variation in the HKT1 expression was studied in root and shoot tissue in 5-1072
day-old seedlings treated with mock (C) or 75 mM NaCl (S) conditions for 24 h. The 1073
boxplots represent the median and extent of natural variation as observed for population 1074
of 48 accessions (Supplemental Figure 11A, Supplemental Dataset 14). (B) A trend 1075
between HKT1 expression and average lateral root length (aLRL) was observed, with 1076
accessions with high HKT1 expression developing short lateral roots. (C) Pictures of 1077
representative 12-day-old seedlings of UAS-HKT1 lines grown at 75 mM NaCl. (D) 1078
UAS-HKT1 lines, with enhanced HKT1 expression in the root pericycle in Col-0 (E2586) 1079
and C24 (J2731) backgrounds, were examined for salt induced changes in RSA. 4-day-1080
old seedlings were transferred to 0 and 75 mM NaCl and the RSA of 8- and 12-day-old 1081
seedlings respectively was quantified. The bar-plots represent the average trait value as 1082
observed in 16 replicates and error bars represent SE. Different letters are used to indicate 1083
the significant differences between the genotypes per condition as calculated using one-1084
way ANOVA with Tukey’s post-hoc test with significance levels of 0.05. 1085
1086
38
Figure 7. Reduction in lateral root development in UAS-HKT1 lines is due to the 1087
ionic component of salt stress. (A) Lines with enhanced HKT1 in root pericycle in Col-0 1088
(E2586) and C24 (J2731) backgrounds were studied for their main root length (MRL), 1089
average lateral root length (aLRL) and number of lateral roots (# LR) in control and 1090
osmotic stress condition (150 mM mannitol) (B) as well as media supplemented with 30 1091
mM KCl in addition to 75 mM NaCl. The RSA was quantified on 10-day-old seedlings 1092
and the relative decrease in average lateral root length (aLRL) and lateral root number (# 1093
LR) was calculated relative to 0 mM NaCl (75 mM NaCl) and 30 mM KCl (75 mM NaCl 1094
+ 30 mM KCl). The bar-plots represent the average value as observed in 16 replicates.1095
The error bars represent SE. Different letters are used to indicate the significant 1096
differences between the genotypes per condition as calculated using one-way ANOVA 1097
(in a) and two-way ANOVA (in b) with Tukey’s post-hoc test with significance levels of 1098
0.05. (C) Pictures of representative 12-day-old seedlings of UAS-HKT1 lines grown at 1099
30 mM KCl + 75 mM NaCl. 1100
1101
Figure 8. The effect of enhanced HKT1 expression on salinity tolerance is 1102
developmental-stage and genetic-background dependent. (A) E2586, E2586 UAS-1103
HKT1, J2731, and J2731 UAS-HKT1 lines were germinated in soil under short-day 1104
conditions and watered from above with 75 mM NaCl one, two or three weeks after 1105
germination. The pictures represent six-week-old plants and the scheme in the upper left 1106
panel shows the distribution of the genotypes in soil pots. (B) Fresh weight of the rosette 1107
was determined 6 weeks after germination. The bars represent average fresh weight 1108
observed over 15 biological replicates and error bars represent standard error. Different 1109
letters are used to indicate groups that are significantly different from each other as 1110
determined with two-way ANOVA using pairwise post-hoc Tukey’s test with 1111
significance levels of 0.05. 1112
B
C
A
TRS
0 0.2 0.4
MR
L
0 0.1 0.2
MR
VL
0 0.1 0.2
Depth
0 0.1 0.2
MR
VA
0 2 4S
traightness
0 0.02 0.04
# LR
0 0.2 0.4
LRD
/MR
L
0 0.2 0.4
LRD
/BZ
0 0.1 0.2 0.3
LRL
0 0.4 0.8
aLRL
0 0.4 0.8
Apical
0 0.2 0.4
Basal
0 0.3 0.6
Branched
0 0.2 0.4
MR
L/TRS
0 0.1 0.2
aLRL/M
RL
0 0.3 0.6 0.9
LRL/M
RL
0 0.4 0.8
Coefficient of Variation (StDev / mean)
Basal
Branched
Apical
Depth
MRVA(Main Root Vector Angle)
MRVL(Main Root Vector Length)
MRL(Main Root Length)
LRD / BZ(Lateral Root Density
per cm Branched Zone)
LRD / MR(Lateral Root Density
per cm Main Root)
Treatment0 mM NaCl75 mM NaCl125 mM NaCl
****
****
****
******
**
****
****
****
****
****
**
****
**
****
0 0.5 1.0 1.5aLRL (cm)
0 2 4 6 8MRL (cm)
0 5 10 15 20 25TRS (cm)
0
75
125
Est-0Kr-0
CIBC-17 Tscha-1
Omo2-1
Uk-1 C24
Uk-1No-0
CLE-6 C24Tscha-1
Est-0Kr-0
Sav-0
Trea
tnen
t (m
M N
aCl)
Trea
tnen
t (m
M N
aCl)
Trea
tnen
t (m
M N
aCl)
Figure 1. Natural variation observed in RSA plasticity in response to salt stress. The effect of salt stress on RSA was examined for 347 Arabidopsis accessions (Supplemental Dataset 1) on 8- and 12-day-old seedlings grown in control and salt stress conditions respectively. (A) Overview of RSA parameters obtained from EZ-Rhizo quantification. Additionally, lateral root length (LRL), average lateral root length (aLRL) as well as the ratios between main root (MRL), average lateral root length aLRL), and total root size (TRS) were calculated. All RSA traits are listed in Supplemental Dataset 2. (B) Natural variation in total root size (TRS), main root length (MRL), and average lateral root length (aLRL) is presented with notched box-plots. The accessions representing outliers in individual traits are indicated. Boxplots of all RSA traits are presented in Supplemental Figure 2. (C) Coefficient of variation observed in all 17 RSA traits per salt stress condition for 347 Arabidopsis accessions studied. The significant differences in variation between control and salt stress are indicated with * for p-value < 0.05 and ** for p-value < 0.01, as calculated using f-tests.
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Figure 2. Salt affects the relationship between RSA components, with lateral root development explaining the majority of observed variation. (A) The correlation between apical zone size and total lateral root length (LRL) and (B) lateral root number (#LR) and total lateral root length (LRL) for plants grown under 0, 75, and 125 mM NaCl are presented with red, green, and blue dots respectively. The lines in corresponding color represent the linear model fitting the correlation per condition. The Pearson correlation coefficients (r) are presented in the lower right corner of each correlation graph, with ** indicating p-value < 0.01 and * p-value < 0.05. (C) Principal Component Analysis revealed three PCs explaining 71.4% of variation. The contribution plots show how each RSA trait contributes to each PC, ranging from low contribution (dark-blue) to high contribution (light-blue). The contribution of individual traits to each PC is listed in Supplemental Dataset 4.
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Figure 3. GWAS identifies loci with high and low allele diversity. GWAS was performed on (A) average Lateral Root Length (aLRL), ratio of average Lateral and Main Root Length (aLRL/MRL), and Principle Component 3 (PC3) at low salt stress conditions (75 mM NaCl) and significant associations above LOD 5.6 with MAF > 0.01 were identified. The dotted line represents the threshold of a LOD of 5.6. The 6 chosen loci (Supplemental Dataset 12) are marked. The validated loci containing HKT1 (locus 4) is marked with green and CYP79B2 (locus 5) with purple. Genetic variation in locus 4 (B) and 5 (C) was studied in 147 HapMap population accessions. The purple graphs represent the portion of missing data, while the green graphs represent deletions present in accessions other than Col-0. The blue graphs represent the sequence similarity compared to Col-0. The Open Reading Frames are aligned in the lowest panel. The location of the associated SNPs from 250k SNP set is represented with highlighted dashed-lines, while the SNPs mapped using the 4M SNP set are represented with gray dashed-lines.
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Figure 4. Change in CYP79B2 expression in response to salt stress correlates with lateral root development during salt stress. Natural variation in genes in locus 5 was studied in root and shoot tissue in 5-day-old seedlings treated with mock or 75 mM NaCl for 24 h. The boxplot (A) represents the median and extent of natural variation in CYP79B2 expression as observed for population of 48 accessions. Boxplots for the other genes in the same locus can be found in Supplemental Figure 10, together with heat plots of the expression per accession, while the normalized expression of all studied genes is presented in Supplemental Dataset 14. The relative log2 fold change in expression of CYP79B2 between control and salt stress positively correlated to several root architecture traits in the accessions, including (B) average lateral root length per main root length (aLRL/MRL) at 75 mM NaCl and (C) the lateral root density (LRD) at 75 mM NaCl. The Pearson correlation coefficients (r) are presented in the lower right corner of each correlation graph, with ** indicating p-value < 0.01 and * p-value < 0.05.
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Figure 5. Loss-of-function of both CYP79B2 and CYP79B3 results in reduced lateral root development during salt stress. (A) 4-day-old seedlings of Col-0, cyp79b2, cyp79b3, and cyp79b2 cyp79b3 lines were transferred to 0, 75, and 125 mM NaCl and RSA of 10-day-old seedlings was quantified. The bar-plots represent the average lateral root density (LRD) of three experiments with each 20 replicates; error bars represent pooled SE. A mixed linear model was used to determine significant differences and a significant interaction between treatment and genotype was found. Letters represent significant differences (p < 0.05) following a manual-contrasts post-hoc comparison within treatment. (B) Average lateral root length per main root (aLRL/MRL) and average lateral root length (aLRL) for Col-0 and cyp79b2 cyp79b3 in 0 mM (10-day-old seedlings) and 125 mM (10-day- and 12-day-old seedlings) NaCl. Other lateral root traits are presented in Supplemental Figure 11. Bar-plots represent the average trait value as observed in 20 replicates and error bars represent SE. All traits were analyzed using two-way ANOVA and significant interactions were found for shown traits. Letters represent significant differences (p < 0.05) following a manual-contrasts post-hoc comparison within treatment. (C) Pictures of representative seedlings of Col-0 and the cyp79b2 cyp79b3 double mutant at 125 mM NaCl (12-day-old seedlings).
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Figure 6. High HKT1 expression reduces LR development in salt stress conditions. (A) Natural variation in the HKT1 expression was studied in root and shoot tissue in 5-day-old seedlings treated with mock (C) or 75 mM NaCl (S) conditions for 24 h. The boxplots represent the median and extent of natural variation as observed for population of 48 accessions (Supplemental Figure 11A, Supplemental Dataset 14). (B) A trend between HKT1 expression and average lateral root length (aLRL) was observed, with accessions with high HKT1 expression developing short lateral roots. (C) Pictures of representative 12-day-old seedlings of UAS-HKT1 lines grown at 75 mM NaCl. (D) UAS-HKT1 lines, with enhancedHKT1 expression in the root pericycle in Col-0 (E2586) and C24 (J2731) backgrounds, were examined forsalt induced changes in RSA. 4-day-old seedlings were transferred to 0 and 75 mM NaCl and the RSA of8- and 12-day-old seedlings respectively was quantified. The bar-plots represent the average trait value asobserved in 16 replicates and error bars represent SE. Different letters are used to indicate the significantdifferences between the genotypes per condition as calculated using one-way ANOVA with Tukey’spost-hoc test with significance levels of 0.05.
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Figure 7. Reduction in lateral root development in UAS-HKT1 lines is due to the ionic component of salt stress. (A) Lines with enhanced HKT1 in root pericycle in Col-0 (E2586) and C24 (J2731) backgrounds were studied for their main root length (MRL), average lateral root length (aLRL) and number of lateral roots (# LR) in control and osmotic stress condition (150 mM mannitol) (B) as well as media supplemented with 30 mM KCl in addition to 75 mM NaCl. The RSA was quantified on 10-day-old seedlings and the relative decrease in average lateral root length (aLRL) and lateral root number (# LR) was calculated relative to 0 mM NaCl (75 mM NaCl) and 30 mM KCl (75 mM NaCl + 30 mM KCl). The bar-plots represent the average value as observed in 16 replicates. The error bars represent SE. Different letters are used to indicate the significant differences between the genotypes per condition as calculated using one-way ANOVA (in A) and two-way ANOVA (in B) with Tukey’s post-hoc test with significance levels of 0.05. (C) Pictures of representative 12-day-old seedlings of UAS-HKT1 lines grown at 30 mM KCl + 75 mM NaCl.
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Figure 8. The effect of enhanced HKT1 expression on salinity tolerance is developmental-stage and genetic-background dependent. (A) E2586, E2586 UAS-HKT1, J2731, and J2731 UAS-HKT1 lines were germinated in soil under short-day conditions and watered from above with 75 mM NaCl one, two or three weeks after germination. The pictures represent six-week-old plants and the scheme in the upper left panel shows the distribution of the genotypes in soil pots. (B) Fresh weight of the rosette was determined 6 weeks after germination. The bars represent average fresh weight observed over 15 biological replicates and error bars represent standard error. Different letters are used to indicate groups that are significantly different from each other as determined with two-way ANOVA using pairwise post-hoc Tukey’s test with significance levels of 0.05.
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DOI 10.1105/tpc.16.00680; originally published online November 7, 2017;Plant Cell
Joost J.B. Keurentjes, Arthur Korte, Michel A Haring, Gert-Jan de Boer and Christa TesterinkMagdalena Julkowska, Iko Tamar Koevoets, Selena Mol, Huub CJ Hoefsloot, Richard Feron, Mark Tester,
Genetic Components of Root Architecture Remodeling in Response to Salt Stress
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