Molecular Plant Plant • • Volume Pages 1–14, 2012 Molecular 5 • Number 5 • Pages 1068–1081 • September 2012
RESEARCH ARTICLE ARTICLE RESEARCH
Comparative Transcriptomic Analysis of Salt Adaptation in Roots of Contrasting Medicago truncatula Genotypes Ons Zahafa,2, Sandrine Blancheta,2, Axel de Ze´licourta,b,2, Benoıˆt Alunnia,b, Julie Pleta, Carole Laffonta, Laura de Lorenzoa,c,d, Sandrine Imbeaude,f, Jean-Laurent Ichante´e, Anouck Dieta,b, Mounawer Badrig, Ana Zabalzah, Esther M. Gonza´lezh, Herve´ Delacroixe, Ve´ronique Grubera,b, Florian Frugiera and Martin Crespia,1 a Institut des Sciences du Ve´ge´tal (ISV), CNRS, 91198 Gif-sur-Yvette, France b Universite´ Paris Diderot Paris 7, 75205 Paris Cedex 13, France c Departamento de Microbiologı´a y Parasitologı´a, Universidad de Sevilla, 41012 Sevilla, Spain d Present address: Centro Nacional de Biotecnologı´a (CNB), CSIC, 28049 Madrid, Spain e Centre de Ge´ne´tique Mole´culaire (CGM), CNRS, Gif/Orsay DNA Microarray Platform (GODMAP), Universite´ Paris-Sud 11, 91190 Gif-sur-Yvette, France f Present address: Ge´nomique Fonctionnelle des tumeurs solides, INSERM, IUH, Universite´ Paris Descartes, 75010 Paris, France g Laboratory of Legumes, Centre of Biotechnology of Borj Cedria, BP 901, 2050 Hammam-Lif, Tunisia h Departamento de Ciencias del Medio Natural, Universidad Pu´blica de Navarra, 31006 Pamplona, Spain
ABSTRACT Evolutionary diversity can be driven by the interaction of plants with different environments. Molecular bases involved in ecological adaptations to abiotic constraints can be explored using genomic tools. Legumes are major crops worldwide and soil salinity is a main stress affecting yield in these plants. We analyzed in the Medicago truncatula legume the root transcriptome of two genotypes having contrasting responses to salt stress: TN1.11, sampled in a salty Tunisian soil, and the reference Jemalong A17 genotype. TN1.11 plants show increased root growth under salt stress as well as a differential accumulation of sodium ions when compared to A17. Transcriptomic analysis revealed specific gene clusters preferentially regulated by salt in root apices of TN1.11, notably those related to the auxin pathway and to changes in histone variant isoforms. Many genes encoding transcription factors (TFs) were also differentially regulated between the two genotypes in response to salt. Among those selected for functional studies, overexpression in roots of the A17 genotype of the bHLH-type TF most differentially regulated between genotypes improved significantly root growth under salt stress. Despite the global complexity of the differential transcriptional responses, we propose that an increase in this bHLH TF expression may be linked to the adaptation of M. truncatula to saline soil environments. Key words:
root architecture; abiotic stress; legume; transcriptome; bHLH.
INTRODUCTION Environmental variations can alter plant growth and development and severely impact crop productivity. Salinity is one of the major agricultural constraints affecting 20% of the world’s irrigated cropland (Munns and Tester, 2008). Salt stress induces both osmotic (cell dehydration) and toxic (ion accumulation) effects on plants, impairing growth, ion homeostasis and photosynthesis among other key physiological processes. By influencing hormone levels and response, plants can rapidly adjust organ growth to changing environments (Wolters and Ju¨rgens, 2009). Among several strategies, plants can cope with salt and osmotic stresses by modifying their root architecture in order to minimize the areas exposed to salt stress (Malamy, 2005).
The diversity of stress responses can be analyzed at a genomewide scale using transcriptomic approaches. Microarray-based transcriptional profiling has been broadly used in various plants to identify genes whose expression levels change in response to saline conditions (e.g. Jiang and Deyholos, 2006; and in
1
To whom correspondence should be addressed. E-mail
[email protected]. fr, tel. 331-6982-3703, fax 33-1-6982-3695. 2
These authors have contributed equally to this work.
ª The Author 2012. Published by the Molecular Plant Shanghai Editorial Office in association with Oxford University Press on behalf of CSPB and IPPE, SIBS, CAS. doi: 10.1093/mp/sss009, Advance access publication 14 March 2012 Received 6 November 2011; accepted 15 January 2012
2
|
Zahaf et al.
d
Salt Adaptation of Medicago Genotypes
Medicago truncatula, Gruber et al., 2009; Li et al., 2009). However, relatively fewer reports analyzed differences in gene expression between intra-species genotypes showing contrasting responses to salt stress (Taji et al., 2004; Walia et al., 2005; de Lorenzo et al., 2007; Ouyang et al., 2007; Sanchez et al., 2010; Cotsaftis et al., 2011; Kang et al., 2011). Using alfalfa varieties showing contrasting responses to long-term drought and re-watering, several differential regulatory genes and physiological responses were identified (Kang et al., 2011). Analysis of transcriptional changes between these genotypes may reveal specific genes linked to adaptive traits. Among legumes, the model M. truncatula is native to the Mediterranean basin and is found in a wide range of habitats with varying environmental constraints, notably soil salinity (Badri et al., 2007). This high level of variation among and within natural populations offers thus a large diversity of genotypes to explore environmental adaptation mechanisms (Badri et al., 2007; Lazrek et al., 2009; www.noble.org/medicago/ecotypes. html). Legumes could be indeed interesting pioneer crops to incorporate salty soils in agriculture due to their ability to interact with soil symbiotic microorganisms to form root nodules and fix atmospheric nitrogen (Crespi and Frugier, 2008). The numerous genomic and genetic tools available for the M. truncatula model legume (Young et al., 2009) may then serve to identify genes that could improve agronomic performances such as abiotic stress tolerance. Several legume transcription factor (TF) genes were recently implicated in abiotic stress tolerance based on heterologous functional analyses in Arabidopsis or tobacco. Among the WRKY gene family, overexpression of the soybean WRKY21 and WRKY54 TFs in Arabidopsis increased tolerance to various abiotic stresses (Zhou et al., 2008). Using transgenic tobacco plants, overexpression of two soybean AP2/ERF TF genes, GmERF057 and GmERF089, as well as the chickpea AP2-type TF CAP2, led to an increased abiotic stress tolerance (Shukla et al., 2006; Zhang et al., 2008). Similarly, two soybean NAC TFs promote abiotic stress tolerance and lateral root formation in Arabidopsis transgenic plants (Hao et al., 2011). To our knowledge, few TFs linked to abiotic stresses were functionally analyzed in a homologous legume context. Overexpression of the C2H2 zinc-finger TF Alfin1 enhanced M. sativa (alfalfa) growth and tolerance to salt whereas expression of this gene in antisense orientation caused defective root growth, supporting a link between root development and salt tolerance (Winicov and Bastola, 1999). In addition, the M. truncatula MtZpt2-1 gene, another C2H2 zinc-finger-type TF, is required for both symbiotic nodule development and root growth recovery after salt stress (Merchan et al., 2007). This gene and the related MtZpt2-2 TF showed a differential expression in response to salt between the M. truncatula Jemalong A17 and the salt-sensitive 108-R genotypes (de Lorenzo et al., 2007). Overexpression of MtZpt2-1 or MtZpt2-2 in the sensitive genotype allowed significant increase in root growth under salt stress, suggesting a role for this pathway in the adaptive response to salt stress. More recently, a detailed transcriptomic
Zahaf et al. • Salt Adaptation of Medicago Genotypes
1069
analysis of the salt stress response of M. truncatula Jemalong A17 roots led to the identification of an AP2–EREBP TF able to enhance salt tolerance in Arabidopsis and M. truncatula roots (Li et al., 2011). In this work, we analyzed transcriptional networks involved in salt stress adaptation by comparing two genotypes of the M. truncatula model legume: the Jemalong A17 reference and a salt-adapted genotype, TN1.11, sampled from a salty Tunisian soil (containing around 150 mM NaCl; Lazrek et al., 2009). Physiological and large-scale transcriptomic analyses revealed specific pathways regulated in root apices of the TN1.11 genotype in response to salt stress, including downregulation of many histone variants and changes in expression of auxin-related genes. In addition, several TFs differentially regulated between the two genotypes were identified. Among those functionally tested, overexpression of the most differentially expressed TF, MtbHLH–658, allowed M. truncatula A17 composite plants to maintain their root growth under salt stress when compared to control plants. This suggests that differential salt-regulation of a specific bHLH-type TF may play a role in the adaptation of M. truncatula to salinity.
RESULTS Impact of Salt Stress on Growth of a Salt-Adapted Genotype The TN1.11 genotype was identified in Enfidha Tunisian salty soils (Lazrek et al., 2009) and its behavior was compared with the reference M. truncatula Jemalong A17 genotype under laboratory conditions (Figure 1). Root growth and dry weight biomass of both M. truncatula genotypes were analyzed after 4 d of NaCl treatment at different concentrations. The root lengths of the two genotypes (expressed as percentage against the value without salt to avoid intrinsic growth differences) were significantly reduced after 90–150 mM NaCl treatments in comparison to non-treated plants (Figure 1A, left panel). Whereas the various salt concentrations had similar effects on root growth in both genotypes, the 150-mM NaCl concentration affected more drastically A17 than TN1.11 (Figure 1A and Supplemental Figure 1A). Similarly, this salt treatment significantly reduced the root dry weight of A17 but not of TN1.11 (Figure 1A, right panel). This was correlated with increased lateral root length of this salt-adapted genotype (Figure 1B) even though lateral root density was not affected (Supplemental Figure 2). In contrast, no major difference in shoot dry weight biomass was found between genotypes after such a short-term salt treatment (10 d), suggesting an increased effect of salt in the root relative to the aerial part in these conditions (Supplemental Figure 1B). The ratio of root to shoot dry weights recapitulates the relative effects of increasing salt concentration for each genotype (Figure 1C) and the differential growth response observed at high salt concentration (150 mM) for the TN1.11 genotype. As legumes interact with rhizobial bacteria to form symbiotic root
120
Roott length (%)
100
a
a
a a
a
a
Jemalong A17 TN1.11
b b
80
c
60
Zahaf et al.
c
c
40 20
d
0
0
30
60
90
120
150
NaCl (mM) Lateral root Length (cm) (
B 4
a
3.5
a
3
C
2.5
b
2 1.5 1
Salt Adaptation of Medicago Genotypes
a
a
a a
0
1.4
30
ab a
60
a a
a
ab
a
a b
90
120
150
Jemalong A17 TN1.11
a a a
1 0.8
bc
bc
bc
b
bc c
0.6 0.4
0
100
0
150
60
30
0
NaCl (mM)
D Ion concentration (mg g-1 DW)
3
0.2
0.5 0
a ab bb
120 100
c
a ab
ab
80 60
c
CHLORIDE abc
bc c
40
Shoot
a
100
b b
bc
60
TN1.11
Root
6
80
ab ab
a
b
b
150
c
c
A17
TN1.11
Shoot
No NaCl NaCl 50 mM NaCl 100 mM
14
a
4
ab a
a
c
40 20
1
0
0
A17
TN1.11
Root
ab
2
a
12
5
3
60
0
A17
120 100
80
20
0
TN1.11
120
CITRATE
140
120
40
20
A17
90
NaCl (mM)
SODIUM 90 80 70 60 50 40 30 20 10 0
|
a a
1,2
a
d
NaCl (mM)
Jemalong A17 TN1.11
a
a
180 160 140 120 100 80 60 40 20 0
o Root/Shoot ratio
A
Zahaf et al. • Salt Adaptation of Medicago Genotypes
Root drry weight (%)
1070
b
a
10 8 6 4
a
ab b
b
2 0
A17
TN1.11
Shoot
A17
TN1.11
Root
Figure 1. Differential Responses to Salt Stress of Jemalong A17 and TN1.11 M. truncatula Genotypes. (A) Root length and dry weight of both genotypes under salt stress. Root length was measured 4 d after treatment with different NaCl concentrations (0, 30, 60, 90, 120, or 150 mM). Relative root length of each genotype is shown as a percentage to the control condition (without salt). Root dry weight of the two genotypes was measured 10 d after the different salt treatments, and results are shown as percentage relatively to the non-treated control. A representative example out of two biological replicates is shown, and error bars represent confidence interval (a = 0.01). Values indicated with different letters indicate significant differences based on a Kruskal and Wallis test (a , 0.01; n . 30). (B) Lateral root length of both genotypes 2 weeks after treatment with different NaCl concentrations (0, 100, or 150 mM). Error bars represents confidence interval (a = 0.05) and values labeled with different letters indicate significant differences based on a Kruskal and Wallis test (a , 0.05; n . 8 plants). (C) Root to shoot dry weights ratio of both genotypes after a salt stress (identical to those in (A)), to evaluate the effect of salinity on plant biomass. A representative example out of two biological replicates is shown, and error bars represent confidence interval (a = 0.01). Values indicated with different letters indicate significant differences based on a Kruskal and Wallis test (a , 0.01; n . 30). (D) Ion accumulation in the two genotypes exposed to salt stress. Sodium, chloride, and citrate concentrations (ion mg g 1 of dry weight (DW), for all graphs) were determined in shoots and roots of A17 and TN1.11 genotypes exposed to different NaCl concentrations (0, 50, or 100 mM) for 15 d. Error bars represent standard errors of three averaged biological replicates, and values labeled with different letters indicate significant differences between genotypes and salt treatments based on Kruskal and Wallis tests for each ion and organ (a , 0.05; n . 20).
4
|
Zahaf et al.
d
Salt Adaptation of Medicago Genotypes
nodules, plants grown under different NaCl concentrations were inoculated with the Sinorhizobium meliloti strain Sm1021, which is able to grow in up to 300 mM NaCl (Ru¨berg et al., 2003). Three weeks after inoculation, the difference observed on the number of nodules at 150 mM NaCl between the two genotypes (Supplemental Figure 3A) correlate with their differences in root and shoot dry weight (Supplemental Figure 3B). This suggests that the increased growth of TN1.11 is responsible for the increased nodulation trend observed in these conditions. We then analyzed the differential accumulation of ions between both genotypes in response to increasing NaCl concentrations (Figure 1D). TN1.11 shoots and roots continuously accumulate sodium and chloride ions (respectively shown in left and middle graphs) until the 100-mM NaCl treatment. In contrast, A17 shoots reach a maximum of accumulation at 50 mM that correlates with citrate levels, used as an indicator of active cell metabolism (Sienkiewicz-Porzucek et al., 2008; Figure 1D, right graphs). This suggests that A17 plants may suffer some metabolic damage at 100 mM NaCl even though there is no significant difference on root growth at this salt concentration between the two genotypes (Figure 1A). Interestingly, TN1.11 plants accumulate more of both ions in the shoot at the 100-mM treatment whereas no significant difference is observed in roots (Figure 1D). This suggests that the TN1.11-adapted genotype may be taking up more NaCl than A17 and store it in shoots. Hence, the TN1.11 genotype differentially accumulates sodium and chloride ions and showed increased root growth under salt stress in controlled laboratory conditions—a trait likely linked with its adaptation to salty soils in natural environments.
Analysis of Differential Gene Expression Profiles in Roots of A17 and TN1.11 M. truncatula Genotypes In order to identify regulatory networks linked to the contrasting salt stress responses of roots from both genotypes, a comparative transcriptomic analysis using Mt16K+ microarrays (containing 16086 probes; www.ebi.ac.uk/arrayexpress) was performed. As TN1.11 root meristems are able to maintain their activity under salt stress conditions, we focused our analysis in root apices. Furthermore, we used a NaCl concentration (100 mM) that does not drastically affect root growth in the sensitive A17 genotype (Figure 1) to avoid a bias in gene expression due to the activation of cell death pathways. The experimental design, based on circular hybridizations, included four conditions (root tips from A17 and TN1.11 genotypes, submitted or not to a NaCl 100-mM treatment for 1 h; Figure 2A), and four independent biological replicates for each of these conditions. This allowed us to distinguish the genotype effect on root apex transcriptomes from the salt treatment influence. These results revealed that an important proportion of genes were differentially expressed in the comparisons analyzed, including between both genotypes under control conditions (see Table 1 and Supplemental Table 1 for details).
Zahaf et al. • Salt Adaptation of Medicago Genotypes
1071
To evaluate the main expression patterns found across the four conditions tested, we used a K-means clustering analysis that revealed six transcriptional clusters (Figure 2B and Supplemental Figure 4). Clusters 2 and 5 corresponded to genes differentially expressed between genotypes independently of the salt treatment (respectively showing a higher expression in TN1.11 or in A17), whereas clusters 4 and 6 corresponded to transcripts regulated by salt stress in both genotypes (respectively up-regulated or down-regulated). The two other clusters identified (clusters 1 and 3) were of particular interest, as they included transcripts showing increased regulation by salt stress preferentially in the TN1.11 salt-adapted genotype. Interestingly, clusters corresponding to genes preferentially regulated by salt in the A17 genotype could not be identified based on K-means clustering. Cluster 1 (798 genes) and cluster 3 (578 genes) corresponded to transcripts showing respectively a stronger up-regulation or down-regulation by salt in TN1.11 compared to Jemalong A17 (Figure 2B; Supplemental Table 2 for detailed gene lists from clusters 1 and 3). Genes from these two clusters were functionally assigned using the GeneBin database of the MapMan software (Tellstro¨m et al., 2007). Clusters 1 and 3 showed a global enrichment for abiotic stress-related genes (Fisher’s exact test, P , 0.0005; Supplemental Table 3), supporting that these clusters are relevant for further analysis. Among the various functional classes, we focused on regulatory pathways that may be the basis of the differential developmental adaptation of A17 and TN1.11 root meristems in response to salt (Supplemental Table 3 and Supplemental Figure 5). Analysis of cluster 1 genes assigned to MapMan ‘Regulatory Pathways’ (Figure 3A) revealed that 64 TFs (representing about 6% of the total number of differentially expressed TFs) were present. Detailed analysis of the TF families (Supplemental Figure 5A) revealed a significant enrichment for bHLH and bZIP (using respectively a Wilcoxon rank sum test, P = 0.03 and a Fisher’s exact test, P = 0.01). In addition, the redox pathways, notably linked to ascorbate/glutathione and glutathione-S-transferases, are significantly enriched in cluster 1 (Figure 3A; Fisher’s exact test, P = 0.006 and 0.02, respectively). Furthermore, among phytohormonal pathways, a significant enrichment was found for genes related to auxin metabolism and response (Fisher’s exact test, P = 0.02). As auxin transport is a major determinant of auxin distribution in root apices in Arabidopsis (Potters et al., 2009), we analyzed the changes of PIN gene expression in response to salt in both genotypes (Figure 4). Among the different PIN genes tested, we found that only MtPIN9 was differentially up-regulated between both genotypes whereas MtPIN10 (the closest homolog to AtPIN1 from Arabidopsis; Schnabel and Frugoli, 2004) is similarly induced in both of them. Examination of cluster 3 genes showing a higher down-regulation by salt in TN1.11 versus A17 and linked to MapMan ‘Regulatory Pathways’ (Figure 3B) revealed 27 TFs, but no enrichment for any specific TF family. Interestingly, histone variants were very significantly enriched (Fisher’s exact test, P = 4 E 16, representing 22 genes/54
1072
Zahaf et al. • Salt Adaptation of Medicago Genotypes
Zahaf et al.
d
Salt Adaptation of Medicago Genotypes
|
5
Table 1. Number of Differentially Expressed Genes between Jemalong A17 and TN1.11 Root Apices in Response to Salt. TN1.11 salt versus TN1.11 control
P , 0.001
Fold change .1.5 Fold change .1.8
2032 1049
A17 salt versus A17 control
P , 0.001
Fold change .1.5 Fold change .1.8
1278 675
A17 control versus TN1.11 control
P , 0.001
Fold change .1.5 Fold change .1.8
1561 944
A17 salt versus TN1.11 salt
P , 0.001
Fold change .1.5 Fold change .1.8
2302 1184
Differentially expressed genes were defined using the following thresholds: Fold change . 1.5 or 1.8, A-mean . 7, and Adjusted P-value , 0.001.
present in the array; Supplemental Figure 5B). Among the different isoforms, three H2A, six H2B, five H3, and eight H4 were found, but no H1 linker histone. Regarding hormonal regulations, brassinosteroids and gibberellin-related genes were significantly enriched in cluster 3 (Figure 3B; Fisher’s exact test, P , 0.05). These results indicate overall that major differences in gene expression can be detected in the salt-adapted genotype in response to salt stress, and highlight specific functional pathways regulated differentially under salt stress conditions in these naturally diverging genotypes.
Figure 2. Analysis of Gene Expression Using M. truncatula Microarrays. (A) Experimental design of Mt16kOLI1+ microarray circular hybridizations. Each arrow represents four hybridizations. Per condition, four independent biological samples were labeled with both Cy5 and Cy3 dyes (two arrays for each dye labeling orientation). (B) K-means clusters derived from the transcriptomic analysis shown in (A). T: TN1.11 and A: Jemalong A17 genotypes, under control or salt (1 h, NaCl 100 mM) conditions. Clusters 2 and 5 correspond to genes differentially expressed between root apices of both genotypes, clusters 4 and 6 correspond to genes regulated by salt stress in both genotypes, and clusters 1 and 3 represent genes preferentially regulated by salt stress in TN1.11. Centroid expression views of the clusters are shown. According to the experimental design, each condition provides eight expression values per gene, which are shown on the x-axes. On the y-axes, each dot represents the mean normalized intensity value for all the genes within that cluster, and the error bar indicates normalized standard deviation. As a result, the line can be viewed as the mean expression profile of the genes within that cluster, and the shape of the curve emphasizes the differential expression between the experimental conditions.
Identification of a bHLH Transcription Factor Controlling Root Growth under Salt Stress in M. truncatula To investigate the putative roles of TFs in the regulation of M. truncatula root architecture under salt stress, an overexpression approach was performed using Jemalong A17 genotype composite plants (Boisson-Dernier et al., 2001). These plants contain wild-type shoots and transgenic roots induced by A. rhizogenes transformation and each plant corresponds to an independent transformation event. We then evaluated whether roots overexpressing different TFs may mimic phenotypes of the roots from the TN1.11 genotype. We concentrated on TFs from cluster 1 grouping transcripts preferentially induced by salt in TN1.11 and that may be linked to regulatory networks differentially activated in root apices of the saltadapted genotype (Supplemental Figure 5A). Among others, we choose a basic Helix-Loop-Helix (MtbHLH–658), showing the maximal level of differential regulation between genotypes, and two basic leucine ZIPper TFs (MtbZIP-102 and MtbZIP-627 also highlighted) having different expression levels among genotypes (Table 2 and Supplemental Table 2). We also included in our functional analysis a previously characterized C2H2 zinc finger, MtZpt2-1, linked to root
6
|
Zahaf et al.
d
Salt Adaptation of Medicago Genotypes
Zahaf et al. • Salt Adaptation of Medicago Genotypes
1073
Figure 3. Regulatory Pathways Differentially Regulated between A17 and TN1.11 Root Apices in Response to Salt. Genes from cluster 1 (A) and cluster 3 (B), respectively, were functionally assigned to regulatory pathways based on the MapMan ‘regulatory pathways overview’ display. Auxin is symbolized by IAA, abscissic acid by ABA, brassinosteroids by BA, salicylic acid by SA, and gibberellic acid by GA.
1074
Zahaf et al. • Salt Adaptation of Medicago Genotypes
Zahaf et al.
* 4
*
2
0 0
MtPIN10 Fold induction
MtPIN9 Fold induction
Jemalong A17
100
TN1.11
4 3 2 1 0
0
NaCl (mM)
Salt Adaptation of Medicago Genotypes
|
7
A change in root architecture may allow the MtbHLH–658 composite plants to cope with the stress condition. On the other hand, the MtbHLH–658-overexpressing roots did not show any improved nodulation after inoculation with S. meliloti under salt stress conditions (unpublished results). The overexpression of the MtbHLH–658 gene was confirmed using semiquantitative RT–PCR (Supplemental Figure 7). A phylogenetic tree analysis showed that MtbHLH–658 is divergent from other legume bHLHs functionally characterized so far (Supplemental Figure 8), among which none was previously linked to abiotic stress responses to our knowledge. To analyze the MtbHLH–658 expression pattern under a variety of conditions, we used the M. truncatula Gene Expression Atlas (MtGEA) performed in the A17 reference genotype (http://bioinfo.noble.org/gene-atlas/: Benedito et al., 2008; Supplemental Figure 9). MtbHLH–658 showed high expression in roots, although at much lower levels in root tips (asterisk), compared to other organs present in the database. Expression is lower during nodulation and mycorrhization compared to un-inoculated roots. Interestingly, although MtbHLH–658 expression is detected in salt-treated roots, there is no upregulation of this gene in the A17 genotype (used for these transcriptomic studies; Supplemental Figure 9). A positive link between MtbHLH–658 and salt stress responses only became apparent in our comparative analysis that used the TN1.11 salt-adapted genotype. We additionally searched for genes co-regulated with MtbHLH–658 using the co-expression analysis tool provided in the MtGEA (Benedito et al., 2008). Out of several candidate genes retrieved as co-regulated with MtbHLH–658 among all the conditions present in the database (using a correlation threshold of 0.89), two also belonged to cluster 1 and then have a similar regulation between genotypes to MtbHLH– 658 (Table 2 and Supplemental Table 2). One codes for a KELCH-related protein whereas the second one encodes a plasma-membrane ATPase transporter (MtKELCH and MtPM-ATPase, respectively; Supplemental Figure 10). A possible role of the PM-ATPases in leaf expansion and ion exclusion
growth responses to salt in the M. truncatula 108-R genotype (de Lorenzo et al., 2007; Table 2). Independent composite plants obtained for each construct were grown for 7 d under control and salt conditions (NaCl 100 mM) in order to test the impact of this stress on root dry weight (Figure 5). We used this salt concentration because, under the greenhouse growing conditions used to analyze the phenotypes of composite plants, a 150-mM NaCl concentration leads to a drastic inhibition of root growth as well as fast shoot senescence. Except for MtbHLH–658, root dry weight of composite plants overexpressing the other TFs was negatively affected by the salt treatment, similarly to GUS-overexpressing controls (Figure 5A). In contrast, MtbHLH–658-overexpressing roots showed a similar dry weight density (root dry weight per primary root length) in control and salt stress conditions (Figure 5B), suggesting that no significant inhibitory effect of salt on root growth was observed in these composite plants (Supplemental Figure 6). To avoid fluctuations on primary root growth among composite plants, we considered the root density (root dry weight per primary root length) to further show the significant differences between these plants (Figure 5B). 6
d
100
NaCl (mM)
Figure 4. Expression Analysis of MtPIN Genes between M. truncatula Genotypes. Real-time RT–PCR of two MtPIN genes differentially regulated between genotypes or in response to salt stress (1 h, 100 mM NaCl). A representative example out of two biological replicates is shown and error bars represent confidence interval (a = 0.05) of two technical replicates and stars indicate statistical significant differences between genotypes.
Table 2. List of Transcription Factors Preferentially Regulated by Salt in Root Apices of the Salt-Adapted TN1.11 Genotype (Cluster 1) Selected for Functional Analyses and bHLH–658 Co-Regulated Genes. A17 salt/A17 control
Name
MtGI9 (TIGR Mt ID (16K+ database) microarray) FC
TF preferentially MtbHLH–658 TC 126500 regulated by MtbZIP-627 TC 120540 salt in TN1.11 TC 132781 roots (cluster 1) MtbZIP-102 MtZpt2-1 TC 114184 MtbHLH–658 co-regulated genes (cluster 1)
P
A
TN1.11 salt/TN1.11 control
A17 control/TN1.11 control
A17 salt/TN1.11 salt
FC
P
FC
P
FC
P
A
A
A
MT015658
2.1
1.7 E-02
7.6
13.5
8.7 E-11
7.6
1.0
9.8 E-01
7.6
–6.4
8.0 E-08
7.6
MT002627
1.1
3.6 E-01
10.2
3.2
9.3 E-14
10.2
1.3
1.1 E-02
10.2
–2.2
3.0 E-10
10.2
MT016102
4.3
6.0 E-15
8.5
2.6
8.9 E-11
8.5
–2.5
1.9 E-10
8.5
–1.5
2.8 E-04
8.5
MT007470
1.3
5.2 E-04
10.2
1.5
1.3 E-07
10.2
1.5
3.0 E-07
10.2
1.3
5.1 E-04
10.2
MtPM-ATPase TC 121827 MT009389
1.5
3.8 E-02
13.3
5.5
8.2 E-11
13.3
–1.6
1.4 E-02
13.3
–5.8
2.9 E-11
13.3
MtKELCH
2.0
2.1 E-03
10.4
6.2
1.8 E-10
10
–1.2
2.7 E-01
10.4
–4.0
4.0 E-08
10.4
TC 121791 MT007396
FC, fold change; P, adjusted p-value; A, A-mean. For each gene, a Tentative Consensus (TC) number is given according to the M. truncatula TIGR database (MtGI9), as well as an Mt ID corresponding to the 16K+ microarray gene probe-set based on M. truncatula sequences.
8
|
Zahaf et al.
d
Salt Adaptation of Medicago Genotypes
in salt-stressed plants was proposed in forage Medicago (M. citrina and M. arborea; Sibole et al., 2005). These genes may be linked to the same pathway activated in the TN1.11 genotype. Hence, we tested the effects of MtbHLH–658 ectopic expression on the accumulation of ions in shoots and roots after a long-term salt treatment (NaCl 100 mM for 1 month). Interestingly, increasing expression of MtbHLH–658 in roots resulted in an enhanced accumulation of sodium and chloride ions in the shoots (Figure 5C). These results suggest a role for the differential regulation by salt of a bHLH TF in ion accumulation and in the control of Medicago root growth under salt stress. Despite the complex differential transcriptional response observed between genotypes, we propose that the bHLH-dependent pathway identified may contribute to the adaptation of M. truncatula to saline soils.
DISCUSSION Using a salt-adapted M. truncatula genotype, TN1.11, and the reference model Jemalong A17, we analyzed their differential physiological and molecular behavior in response to this abiotic constraint with regard to root growth. We then developed a functional assay in the A17 genotype that allowed us to propose a role for a bHLH-dependent pathway in an adaptive M. truncatula root growth trait under salt stress. A salt-adapted genotype was retrieved from Tunisian soils (Lazrek et al., 2009) and showed an enhanced root growth capacity under controlled salt stress conditions, in correlation with the influence of the natural salty environment from which this legume genotype was originating. In legumes, root growth also determines the capacity of the plants to form nodules able to fix atmospheric nitrogen. No significant difference between TN1.11 and A17 genotypes in nodule numbers per root dry weight is observed under salt stress, despite the increased root growth of TN1.11. Nevertheless, the ability to maintain root growth under salt stress is a pre-requisite for symbiosis, as no rhizobial infections could occur in growtharrested roots. Cell-based mechanisms of ion homeostasis are essential determinants of salt stress adaptation (Munns and Tester, 2008). At 100 mM NaCl, TN1.11 accumulates more ions in shoots than A17, suggesting that transport between shoot and roots may also contribute to enhance TN1.11 growth. Since high cytosolic sodium concentrations have a perturbing action on cell metabolism, TN1.11 may sequester these ions in another compartment or alternatively may alter their transport between shoots and roots (Munns and Tester, 2008). On the other hand, the difference in tolerance observed between genotypes at the root growth level seems to be linked to the response to NaCl and not directly to a differential ion accumulation, further reinforcing the interest of analyzing salt stress transcriptional responses in roots. We developed a comparative transcriptomic analysis based on the salt-adapted TN1.11 and A17 genotypes to reveal the
Zahaf et al. • Salt Adaptation of Medicago Genotypes
1075
large differences existing in their expression patterns in response to salt. Comparative studies of related genotypes or species responding differentially to saline stress, including the highly salt-tolerant Thellungiella halophila, a relative of the glycophyte Arabidopsis, were achieved in several nonlegumes (Taji et al., 2004; Gong et al., 2005; Walia et al., 2005; Ouyang et al., 2007). In legumes, using gradual salt acclimation of different L. japonicus genotypes, genes specifically associated with salt differential stress responses and leaf traits were identified (Sanchez et al., 2009). Further analyses to establish robust correlations between transcriptional and metabolic responses suggest that many salinity-induced transcripts may be genotype-specific, highlighting the interest of comparing related genotypes to understand ecological adaptation to particular environments (Sanchez et al., 2010). We focused our studies on root apices of contrasting saltresponding genotypes. There may be large variations in the response of different cell types to stress conditions and efforts have been made to link changes of gene expression to developmental stages using cell-specific analysis (e.g. Dinneny et al., 2008). Indeed, salt regulation of many regulatory genes such as TFs is different in root apices compared to whole roots (Gruber et al., 2009). The action of salt in meristems affects the whole architecture of the root system, including lateral root initiation and emergence (Osmont et al., 2007). In Arabidopsis, salt stress induces elongation of existing lateral roots and this effect was linked to an increased progression of pre-emergent primordia to emergence (Wang et al., 2009; Zolla et al., 2010). In M. truncatula, an HD-ZIP I (HomeoDomain-leucine ZIPper) TF regulated by salt stress was recently shown to control lateral root emergence through repression of an auxin-related TF (Ariel et al., 2010). TN1.11 showed an increased lateral root elongation that may also be linked to an increased emergence. Accordingly, our transcriptomic study pointed out that, in Medicago roots, the most significant hormonal pathway differentially regulated between A17 and TN1.11 in response to salt corresponded to auxin and this correlated with a change in the expression of a particular PIN gene between genotypes. In addition, the gene family showing the most striking differential expression between the two genotypes encoded core histone variants. Specific histone isoforms have been recently linked to changes in nucleosomal distribution in plant cells during phosphate starvation and thermal responses (Kumar and Wigge, 2010; Smith et al., 2010). Such regulation at chromatin level may allow the coordinated regulation of a large number of stress-responsive genes. Changes in histone variant patterns in TN1.11 roots exposed to salt may therefore condition the accessibility to different chromatin regions in order to regulate gene expression. Modulation of TFs has been correlated to the salt adaptation status of specific genotypes (Munns and Tester, 2008). In M. truncatula, we previously linked a differential root response of the A17 and 108-R genotypes to the de-regulation of an MtZpt2-1-dependent pathway (de Lorenzo et al., 2007). In Lotus japonicus, many TFs belonging to the AP2/ERF
1076
Zahaf et al. • Salt Adaptation of Medicago Genotypes
A
140
Zahaf et al.
|
9
0 mM NaCl 100 mM NaCl
120
120
100
100 80
Dry weight density (%)
Root dry weight (%)
Salt Adaptation of Medicago Genotypes
B
0 mM NaCl 100 mM NaCl
*
* *
60
*
40 20
80
*
60 40 20
0
0
C
80
60
Chloride content (mg/gDW)
70
Sodium content (mg/gDW)
d
*
50 40 30 20 10 0
Shoot
Root
70
*
60
1 month NaCl 100 mM 35S::GUS 35S::MtbHLH-658
50 40 30 20 10 0
Shoot
Root
Figure 5. Functional Analysis of Four Selected Transcription Factors by Overexpression in M. truncatula A17 Roots. (A) Root dry weight of transgenic roots overexpressing several transcription factors (MtbHLH–658, MtbZIP–102, MtbZIP–627, and MtZpt2-1) or a control GUS construct was determined with or without a salt treatment (7 d, 100 mM NaCl). Relative root dry weight was expressed as percentage of that of untreated plants. A representative example out of two biological experiments is shown (n . 20). Error bars represent confidence interval (a = 0.05) and asterisks indicate significant differences against non-salt-treated conditions for the same construct based on a Mann and Whitney test (a , 0.05). (B) Root dry weight density (root dry weight per centimeter of primary root) of transgenic roots overexpressing MtbHLH–658 or a control GUS construct was quantified with or without a salt treatment (7 d, 100 mM NaCl). Error bars represent confidence interval (a = 0.05) and asterisks indicate significant differences against non-salt-treated conditions for the same construct based on a Mann and Whitney test (a , 0.05). (C) Ion accumulation in composite plants exposed to salt stress. Sodium and chloride contents (mg g 1 dry weight (DW)) were determined in shoots and roots of 1-month-old composite plants overexpressing MtbHLH–658 or GUS exposed to a salt treatment (NaCl 100 mM). Error bars represent confidence intervals (a = 0.05) and asterisks indicate significant differences between 35S::MtbHLH–658 and 35S::GUS plants for each condition based on a Mann and Whitney test (a , 0.05; n = 10).
DREB, WRKY, and MYB families were pinpointed as potential global coordinators of transcriptional changes during a saltacclimatization response (Sanchez et al., 2009). Very recently, a specific AP2–EREBP TF, CBF4, was shown to play a significant role in most abiotic stresses, including drought, cold, and salt using overexpression both in Arabidopsis and M. truncatula roots (Li et al., 2011). The bHLH gene identified in our study
could not be retrieved using a transcriptomic analysis on a single genotype, however, as this gene is not induced by salt in Jemalong A17 (Supplemental Figure 9), underlining the interest of comparative transcriptomics strategies. To link the differences detected between genotypes to a particular phenotype, we devised a functional assay to overexpress in the A17-sensitive genotype, different TFs showing preferential
10
|
Zahaf et al.
d
Salt Adaptation of Medicago Genotypes
up-regulation by salt in the TN1.11 genotype. Indeed, among the TFs functionally analyzed, MtbHLH–658 permitted the strongest improvement of root growth under salt stress to Jemalong A17. This gene is not induced in A17 whereas it is the strongest salt up-regulated TF in the TN1.11 genotype from cluster 1. The lack of functional approaches in TN1.11, however, prevented us from analyzing in more detail the role of MtbHLH–658 in this genotype. On the other hand, comparisons of gene expression between plant genotypes or related species may hide genes involved in stress tolerance due to genotype specificities (Sanchez et al., 2011). Accordingly, only one out of four tested TFs led to a detectable stress response phenotype when overexpressed, demonstrating that not all differentially expressed TFs can be linked to the adaptation of TN1.11 to salty soils. The bHLH-type TFs play important roles in root growth and development and several genes in this family have been linked to abiotic stress responses (Jiang et al., 2009; Cheng et al., 2011). In non-legumes, overexpression of bHLH genes improved tolerance to cold (Wang et al., 2003), salt, and osmotic stresses (Jiang et al., 2009; Zhou et al., 2009). In legume plants, a role of bHLH TFs in the root development and nodulation process has been recently identified (Karas et al., 2009; Godiard et al., 2011). However, no functional data so far have involved legume bHLH TFs in stress responses. Interestingly, one of the genes co-regulated with MtbHLH–658 in the Affymetrix arrays and between genotypes (our study) codes for a PMATPase. These genes are involved in the regulation of intracellular pH, turgor maintenance, and electrochemical gradients that drive cellular secondary transport functions, suggesting an involvement in plant responses to salinity (Morsomme and Boutry, 2000). By comparing M. citrina and M. arborea, PM-ATPases were proposed to modulate ion exclusion in aerial tissues and contribute to the differential salt stress responses between these forage legumes (Sibole et al., 2005). As MtbHLH–658 overexpression leads to a differential ion accumulation in shoot tissues, we can speculate that this TF may act through this co-regulated MtPM-ATPase gene to improve salt stress adaptation between the M. truncatula genotypes. Nevertheless, the adaptation of TN1.11 to saline soils likely requires many different pathways as shown by the complex transcriptional responses observed between genotypes. Altogether, our results indicate that de-regulation of the MtbHLH–658 TF allows the Medicago A17 genotype to maintain root growth in high salinity environments. We propose that activation of a MtbHLH–658-dependent network, among other regulatory pathways, may have played a role in the evolution of the adaptation of M. truncatula to salty environments.
METHODS Plant Material and Growth Conditions Two genotypes of Medicago truncatula, the Jemalong A17 reference (Young et al., 2009) and TN1.11 issued from the Enfidha population (Lazrek et al., 2009), were used in this work. Seeds
Zahaf et al. • Salt Adaptation of Medicago Genotypes
1077
were stratified at 4 C for 3 d and sterilized. Germinated seedlings were transferred to square plates or pots containing appropriate medium with or without salt and grown vertically at 24 C on a 16-h light/8-h dark cycle, in a growth chamber or in a greenhouse, respectively (de Lorenzo et al., 2007). For root growth (primary root length and root dry weight), germinated seedlings were grown in vitro on paper in a nitrogen-containing medium for 3 d (Fahraeu¨s medium) and then transferred to different NaCl concentrations (0, 30, 60, 90, 120, and 150 mM; de Lorenzo et al., 2007). The position of primary root tips was marked at the time of transfer and root growth was measured after 4 d using ImageJ (http:// rsb.info.nih.gov/ij/). Root growth was evaluated as percentage to untreated roots. Two biological experiments with 30 roots per genotype and treatment were analyzed. Seedlings from both genotypes were grown in the same in vitro plates to randomize eventual position or environmental effects. Lateral root length and number were analyzed in vitro on ‘i’ medium (Gonzalez-Rizzo et al., 2006) with different NaCl concentrations (0, 100, or 150 mM). After 2 weeks, primary root length as well as number and length of lateral roots were measured using ImageJ (n . 8 plants/genotype/condition). For nodulation, M. truncatula genotypes and composite plants were grown on nitrogen-poor ‘i’ medium in greenhouse conditions and infected by Sinorhizobium meliloti Sm1021 as described in de Lorenzo et al. (2007). Two biological replicates per salinity treatment were performed (n . 20 plants/genotype/condition). Root length, dry weight, lateral root, and nodule number in the various treatments were tested for significant differences using the XLSTAT software (Addinsoft, Paris, France) and tests indicated in figure legends.
Ion Measurements Ion concentration was determined in 15-day-old plants growing vertically in Fahraeu¨s-agar square plates containing 0, 50, or 100 mM NaCl. Three biological experiments with 30 roots per genotype and treatment were analyzed. For composite plants, a salt treatment (100 mM NaCl) was applied during 1 month in four biological experiments. Frozen tissue was extracted in boiling 80% (v/v) ethanol and soluble extracts were dried in a Turbovap LV evaporator (Zymark Corp., Hopkinton, MA, USA). Soluble compounds were re-dissolved in distilled water and centrifuged at 20 000 g for 10 min. Ion concentration was determined by ion chromatography in a DX-500 system (Dionex, Voisins-le-Bretonneux, Paris). Chloride and citrate were analyzed by gradient separation with a Dionex IonPac AS11 column (2.5 mM NaOH/18% methanol to 45 mM NaOH/18% methanol in 13 min; Ga´lvez et al., 2005). Sodium concentration was analyzed by isocratic separation with a Dionex IonPac CS12A (20 mM metasulfuric acid).
RT–PCR Analysis For real-time RT–PCR, the same conditions and primers were used as described in Plet et al. (2011). For the MtbHLH–658
1078
Zahaf et al. • Salt Adaptation of Medicago Genotypes
gene, five different couples of primers were designed and none was useful for real-time RT–PCR, so we confirmed its overexpression using a semi-quantitative assay. For semiquantitative RT–PCR analysis, total RNA was extracted using the RNeasy Plant Mini Kit according to the manufacturer’s instructions (Qiagen, Paris, France). First-strand cDNAs were synthesized from 0.5 lg of total RNA from each sample using the Superscript II first-strand synthesis system (Invitrogen, Carlsbad, USA) and used as template for PCR analysis after normalization using the MtACT reference gene (Plet et al., 2011). The PCR products were analyzed on 1.5% agarose gels stained with ethidium bromide and visualized using a Gel Imaging System (Fisher Bioblock Scientific). Primer sequences (defined with a 55 C Tm) used for RT–PCR analysis are given in Supplemental Table 4.
Hybridization and Analysis of Mt16K+ Microarrays For microarray analysis of the response to salt stress in TN1.11 and A17 root apices, germinated seedlings were transferred to perlite:sand (3:1) pots without bottom on a grid as described in Gruber et al. (2009). The liquid plant growth media SN/2 imbibing the emerging root apices was replaced by fresh medium with or without salt (100 mM NaCl). Four biological replicates for each condition (saline and control) were performed (using at least nine plants per replicate). Root apices (1 cm) were harvested after the 1-h treatments, immediately frozen in liquid nitrogen, and stored at –80 C for RNA extraction. RNAs were extracted as described for RT–PCR and qualitychecked with an Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA, USA). Two micrograms of each sample were used to synthesize Cy5/Cy3-labeled cDNA using the Amino Allyl Message Amp II aRNA Amplification kit (Ambion, TX, USA) according to the manufacturer’s instructions. For each experimental condition, the four independent biological samples were labeled with both the Cy5 and Cy3 dyes, to ensure unbiased dyeinteractions. In total, 16 arrays were hybridized (two arrays for each dye labeling orientation), providing eight data points per probe and condition. Cy5/Cy3-labeled cDNA were hybridized with the 70-mer Mt16K+ oligonucleotide microarrays (www.ebi.ac.uk/microarray -as/ae/; accession number A-MEXP-138, ArrayExpress database) for 16 h at 60 C, in a rotating oven (6 rpm), using an Agilent hybridization chamber system. The hybridized slides were washed in SSC 1X, 0.2% SDS for 10 min at 50 C, SSC 0.1X for 10 min at room temperature, SSC 0.05X for 5 min, and then water at room temperature. Microarray slides were scanned with a GenePix 4000B two laser scanner (Molecular Devices, Sunnyvale, CA, USA) and the resulting images were analyzed with the GenePix Pro 6.0 image analysis software. Data transformation and normalization, performed with the MAnGO R script (version 1.0; Marisa et al., 2007), consisted of a local background correction, omitting flagged spots, and successively an intensity dependent print-tip lowess normalization and a scale between-array normalization
Zahaf et al.
d
Salt Adaptation of Medicago Genotypes
|
11
(Yang et al., 2002). MIAME-compliant data (Brazma et al., 2001) were deposited in the ArrayExpress database (www.ebi.ac.uk/ microarray-as/ae/) under the accession number E-MEXP-1255.
Statistical Analysis of Microarray Data The statistical analysis was conducted using the R environment and the R package BioConductor/Limma package (version 2.10.5; Smyth, 2005). The genotype effect was studied by comparing [A17_Control versus TN1.11_Control] and [A17_NaCl versus TN1.11_NaCl]. The same analysis was used to study the salt treatment effect, by comparing [A17_NaCl versus A17_Control] and [TN1.11_NaCl versus TN1.11_Control]. Differential analysis of the microarray data was based on an empirical Bayes moderated t-test adjusted with the false discovery rate (FDR; Benjamini and Hochberg, 1995) multiple test correction. For the four comparisons, an adjusted p-value (p), a fold change value (FC), and a mean intensity of the two channels (A-mean) were obtained. Differentially expressed genes were defined as those whose adjusted p-value was statistically significant at a level of P , 0.001, with jFCj . 1.5, and for which A-mean . 7 (on a log2 scale; threshold defined using negative controls available on the microarray). Genes considered as differentially expressed in at least one of the comparisons were subjected to classification analysis based on expression intensity measurements and Euclidian distance as similarity measure across the experimental conditions. A K-means clustering using a six-cluster limit (50 iterations) was computed using the Genesis software (version 1.7.2, http://genome.tugraz.at/genesisclient/genesisclient_description.shtml), an independent platform and user-friendly Java suite for large-scale gene expression analysis (Sturn et al., 2002). The FOM (Figure Of Merit) methodology (Yeung et al., 2001) was used for validating the number of gene expression clusters. Array data were visualized using functional annotations provided by the MapMan software for M. truncatula (http:// gabi.rzpd.de/projects/MapMan/; Tellstro¨m et al., 2007). To identify functional BINs that exhibit an enrichment in cluster 1 or 3, we used a Fisher’s exact test or alternatively the Benjamini and Hochberg corrected Wilcoxon rank sum test provided by the MapMan software (n . 7 genes as a BIN size to be considered and a , 0.05 in both cases).
Ectopic Overexpression of Transcription Factors For MtbHLH–658, MtbZIP-102, and MtbZIP-627 overexpression, constructs were generated using a Gateway-based system. The coding region of each gene was amplified by PCR with specific primers indicated in Supplemental Table 4. The PCR products were cloned into the entry vector pENTR/ D–TOPO (Invitrogen, Carlsbad, CA, USA) and then recombined into the binary plasmid pK7WG2D (Karimi et al., 2002) containing a 35S CaMV promoter. The Mt Zpt2-1 and GUS overexpression constructs were previously described (Merchan et al., 2007). Constructs were introduced into Agrobacterium rhizogenes and used for M. truncatula A17 root transformation (Boisson-
12
|
Zahaf et al.
d
Salt Adaptation of Medicago Genotypes
Dernier et al., 2001). The composite plants obtained consist of wild-type shoots and transgenic roots and each plant corresponds to an independent transformation event. This confers statistical robustness to conclude about growth phenotypes. Two weeks after inoculation with A. rhizogenes, plants developed transgenic roots and were transferred into the greenhouse to containers filled with perlite:sand (3:1, v/v) irrigated with ‘i’ medium. Ten control and 10 overexpressing plants were grown per container at 24 C on a 16-h light period in a growth chamber with 50% relative humidity. Five days after transfer, plants were irrigated with ‘i’ medium supplemented with or without salt (100 mM NaCl) for 1 week or 1 month. The primary root length was measured and the root system and aerial parts were separated individually, dried at 60 C for 48 h, used to determine their dry weight, and processed for ion measurements. Two biological replicates per treatment were performed (n . 20 plants).
Phylogenetic Analysis Full-length amino acid sequences of bHLH proteins functionally characterized in legumes or previously functionally linked to stress in Arabidopsis and rice were aligned using ClustalW (http://clustalw.genome.ad.jp) and analyzed with the MEGA 4 software (version 4.0.2) (www.megasoftware.net). Bootstrap values were obtained from 1000 replicates. Correspondence between different Medicago resources (different microarray, EST database, and the Medicago genome) was established using the LEGoo ‘nickname’ tool (www.legoo.org).
Accession Number MtbHLH–658 sequence data from this article can be found in the NCBI/Genbank data libraries under accession number JN833714.
SUPPLEMENTARY DATA Supplementary Data are available at Molecular Plant Online.
FUNDING This work was supported by the ‘Grain legumes’ FP6 EEC program (GLIP; FOOD-CT-2004–506223). O.Z. was supported by a grant from the Tunisian Government (Tunis), S.B. was the recipient of a fellowship from the ‘Grain legumes’ FP6 EEC project (GLIP; FOOD-CT2004–506223), and J.P. by a doctoral grant from the Ministe`re de la Recherche et de la Technologie (France).
ACKNOWLEDGMENTS We thank Dr Mohamed Elarbi Aouani (Technopole de Borj-Ce´dria, Hammam-Lif, Tunisia) and Dr Thierry Huguet (CNRS-INRA, Castanet Tolosan, France) for initial discussions about the TN1.11 M. truncatula genotype. We thank G. Garijo and X. Sanz-Corres for technical assistance and Cesar Arrese-Igor for advice (Universidad Publica de Navarra, Spain). We thank the two anonymous reviewers for their constructive comments. No conflict of interest declared.
Zahaf et al. • Salt Adaptation of Medicago Genotypes
1079
REFERENCES Ariel, F., Diet, A., Verdenaud, M., Gruber, V., Frugier, F., Chan, R., and Crespi, M. (2010). Environmental regulation of lateral root emergence in Medicago truncatula requires the HD-Zip I transcription factor HB1. Plant Cell. 22, 2171–2183. Badri, M., Ilahi, H., Huguet, T., and Aouani, M.E. (2007). Quantitative and molecular genetic variation in sympatric populations of Medicago laciniata and M. truncatula (Fabaceae): relationships with eco-geographical factors. Genet. Res. 89, 107–122. Benedito, V.A., et al. (2008). A gene expression atlas of the model legume Medicago truncatula. Plant J. 55, 504–513. Benjamini, Y., and Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B57, 289–300. Boisson-Dernier, A., Chabaud, M., Garcia, F., Becard, G., Rosenberg, C., and Barker, D.G. (2001). Agrobacterium rhizogenes transformed roots of Medicago truncatula for the study of nitrogen fixing and endomycorrhizal symbiotic associations. Mol. Plant Microbe Interact. 14, 695–700. Brazma, A., et al. (2001). Minimum information about a microarray experiment (MIAME): toward standards for microarray data. Nat. Genet. 29, 365–371. Cheng, Z., Sun, L., Qi, T., Zhang, B., Peng, W., Liu, Y., and Xie, D. (2011). The bHLH transcription factor MYC3 interacts with the jasmonate ZIM-domain proteins to mediate jasmonate response in Arabidopsis. Mol. Plant. 4, 279–288. Cotsaftis, O., Plett, D., Johnson, A.A.T., Walia, H., Wilson, C., Ismail, A.M., Close, T.J., Tester, M., and Baumann, U. (2011). Root-specific transcript profiling of contrasting rice genotypes in response to salinity stress. Mol. Plant. 4, 25–41. Crespi, M., and Frugier, F. (2008). De novo organ formation from differentiated cells: root nodule organogenesis. Sci. Signal. 2, er1. de Lorenzo, L., Merchan, F., Blanchet, S., Megia`s, M., Frugier, F., Crespi, M., and Sousa, C. (2007). Differential expression of the TFIIIA regulatory pathway in response to salt stress between Medicago truncatula genotypes. Plant Physiol. 145, 1521–1532. Dinneny, J.R., Long, T.A., Wang, J.Y., Jung, J.W., Mace, D., Pointer, S., Barron, C., Brady, S.M., Schiefelbein, J., and Benfey, P.N. (2008). Cell identity mediates the response of Arabidopsis roots to abiotic stress. Science. 320, 942–945. Ga´lvez, L., Gonzalez, E.M., and Arrese-Igor, C. (2005). Evidence for carbon flux shortage and strong carbon/nitrogen interactions in pea nodules at early stages of water stress. J. Exp. Bot. 56, 2551–2561. Godiard, L., Lepage, A., Moreau, S., Laporte, D., Verdenaud, M., Timmers, T., and Gamas, P. (2011). MtbHLH1, a bHLH transcription factor involved in Medicago truncatula nodule vascular patterning and nodule to plant metabolic exchanges. New Phytol. 191, 391–404. Gong, Q., Li, P., Ma, S., Indu Rupassara, S., and Bohnert, H.J. (2005). Salinity stress adaptation competence in the extremophile Thellungiella halophila in comparison with its relative Arabidopsis thaliana. Plant J. 44, 826–839. Gonzalez-Rizzo, S., Crespi, M., and Frugier, F. (2006). The Medicago truncatula CRE1 cytokinin receptor regulates lateral root
1080
Zahaf et al. • Salt Adaptation of Medicago Genotypes
Zahaf et al.
d
Salt Adaptation of Medicago Genotypes
|
13
development and early symbiotic interaction with Sinorhizobium meliloti. Plant Cell. 18, 2680–2693.
Munns, R., and Tester, M. (2008). Mechanisms of salinity tolerance. Annu. Rev. Plant Biol. 59, 651–681.
Gruber, V., Blanchet, S., Diet, A., Zahaf, O., Boualem, A., Kakar, K., Alunni, B., Udvardi, M., Frugier, F., and Crespi, M. (2009). Identification of transcription factors involved in root apex responses to salt stress in Medicago truncatula. Mol. Genet. Genomics. 281, 55–66.
Osmont, K.S., Sibout, R., and Hardtke, C.S. (2007). Hidden branches: developments in root system architecture. Annu. Rev. Plant Biol. 58, 93–113.
Hao, Y.J., et al. (2011). Soybean NAC transcription factors promote abiotic stress tolerance and lateral root formation in transgenic plants. Plant J. 68, 302–313. Jiang, Y., and Deyholos, M.K. (2006). Comprehensive transcriptional profiling of NaCl-stressed Arabidopsis roots reveals novel classes of responsive genes. BMC Plant Biol. 12, 6–25. Jiang, Y., Yang, B., and Deyholos, M.K. (2009). Functional characterization of the Arabidopsis bHLH92 transcription factor in abiotic stress. Mol. Genet. Genomics. 282, 503–516. Kang, Y., Han, Y., Torres-Jerez, I., Wang, M., Tang, Y., Monteros, M., and Udvardi, M. (2011). System responses to long-term drought and re-watering of two contrasting alfalfa varieties. Plant J. doi: 10.1111/j.1365–313X.2011.04738.x. Karas, B., Amyot, L., Johansen, C., Sato, S., Tabata, S., Kawaguchi, M., and Szczyglowski, K. (2009). Conservation of lotus and Arabidopsis basic helix-loop-helix proteins reveals new players in root hair development. Plant Physiol. 151, 1175–1185. Karimi, M., Inze´, D., and Depicker, A. (2002). GATEWAY vectors for Agrobacterium-mediated plant transformation. Trends Plant Sci. 7, 193–195. Kumar, S.V., and Wigge, P.A. (2010). H2A.Z-containing nucleosomes mediate the thermosensory response in Arabidopsis. Cell. 140, 136–147. Lazrek, F., Roussel, V., Ronfort, J., Cardinet, G., Chardon, F., Aouani, M.E., and Huguet, T. (2009). The use of neutral and non-neutral SSRs to analyse the genetic structure of a Tunisian collection of Medicago truncatula lines and to reveal associations with eco-environmental variables. Genetica. 135, 391–402. Li, D., Su, Z., Dong, J., and Wang, T. (2009). An expression database for roots of the model legume Medicago truncatula under salt stress. BMC Genomics. 10, 517. Li, D., Zhang, Y., Hu, X., Shen, X., Ma, L., Su, Z., Wang, T., and Dong, J. (2011). Transcriptional profiling of Medicago truncatula under salt stress identified a novel CBF transcription factor MtCBF4 that plays an important role in abiotic stress responses. BMC Plant Biol. 11, 109. Malamy, J.E. (2005). Intrinsic and environmental response pathways that regulate root system architecture. Plant Cell Environ. 28, 67–77. Marisa, L., Ichante´, J.L., Reymond, N., Aggerbeck, L., Delacroix, H., and Mucchielli-Giorgi, M.H. (2007). MAnGO: an interactive R-based tool for two-colour microarray analysis. Bioinformatics. 23, 2339–2341. Merchan, F., de Lorenzo, L., Gonzalez-Rizzo, S., Niebel, A., Manyani, H., Frugier, F., Sousa, C., and Crespi, M. (2007). Identification of regulatory pathways involved in the reacquisition of root growth after salt stress in Medicago truncatula. Plant J. 51, 1–17. Morsomme, P., and Boutry, M. (2000). The plant plasma membrane H+-ATPase: structure, function and regulation. Biochem. Biophys. Acta. 1465, 1–16.
Ouyang, B., Yang, T., Li, H., Zhang, L., Zhang, Y., Zhang, J., Fei, Z., and Ye, Z. (2007). Identification of early salt stress response genes in tomato root by suppression substractive hybridization and microarray analysis. J. Exp. Bot. 58, 507–520. Plet, J., Wasson, A., Ariel, F., Le Signor, C., Baker, D., Mathesius, U., Crespi, M., and Frugier, F. (2011). MtCRE1-dependent cytokinin signaling integrates bacterial and plant cues to coordinate symbiotic nodule organogenesis in Medicago truncatula. Plant J. 65, 622–633. Potters, G., Pasternak, T.P., Guisez, Y., and Jansen, M.A.K. (2009). Different stresses, similar morphogenic responses: integrating a plethora of pathways. Plant Cell Environ. 32, 158–169. Ru¨berg, S., Tian, Z.X., Krol, E., Linke, B., Meyer, F., Wang, Y., Pu¨hler, A., Weidner, S., and Becker, A. (2003). Construction and validation of a Sinorhizobium meliloti whole genome DNA microarray: genome-wide profiling of osmoadaptive gene expression. J. Biotechnol. 106, 255–268. Sanchez, D.H., Lippold, F., Redestig, H., Hannah, M.A., Erban, A., Kra¨mer, U., Kopka, J., and Udvardi, M.K. (2009). Integrative functional genomics of salt acclimatization in the model legume Lotus japonicus. Plant J. 53, 973–987. Sanchez, D.H., Pieckenstain, F.L., Szymanski, J., Erban, A., Bromke, M., Hannah, M.A., Kraemer, U., Kopka, J., and Udvardi, M.K. (2011). Comparative functional genomics of salt stress in related model and cultivated plants identifies and overcomes limitations to translational genomics. PLoS One. 6, e17094. Sanchez, D.H., Szymanski, J., Erban, A., Udvardi, M.K., and Kopka, J. (2010). Mining for robust transcriptional and metabolic responses to long-term salt stress: a case study on the model legume Lotus japonicus. Plant Cell Environ. 33, 468–480. Schnabel, E.L., and Frugoli, J. (2004). The PIN and LAX families of auxin transport genes in Medicago truncatula. Mol. Genet. Genomics. 272, 420–432. Se´gue´la, M., Briat, J.F., Vert, G., and Curie, C. (2008). Cytokinins negatively regulate the root iron uptake machinery in Arabidopsis through a growth-dependent pathway. Plant J. 55, 289–300. Shukla, R.K., Raha, S., Tripathi, V., and Chattopadhyay, D. (2006). Expression of CAP2, an APETALA2-family transcription factor from chickpea, enhances growth and tolerance to dehydration and salt stress in transgenic tobacco. Plant Physiol. 142, 113–123. Sibole, J.V., Cabot, C., Michalke, W., Poschenrieder, C., and Barcelo´, J. (2005). Relationship between expression of the PM H+-ATPase, growth and ion partitioning in the leaves of salttreated Medicago species. Planta. 221, 557–566. Sienkiewicz-Porzucek, A., Nunes-Nesi, A., Sulpice, R., Lisec, J., Centeno, D.C., Carillo, P., Leisse, A., Urbanczyk-Wochniak, E., and Fernie, A.R. (2008). Mild reductions in mitochondrial citrate synthase activity result in a compromised nitrate assimilation and reduced leaf pigmentation but have no effect on photosynthetic performance or growth. Plant Physiol. 147, 115–127.
14
|
Zahaf et al.
d
Salt Adaptation of Medicago Genotypes
Smith, A.P., Jain, A., Deal, R.B., Nagarajan, V.K., Poling, M.D., Raghothama, K.G., and Meagher, R.B. (2010). Histone H2A.Z regulates the expression of several classes of phosphate starvation response genes but not as a transcriptional activator. Plant Physiol. 52, 217–225. Smyth, G.K. (2005). Limma: linear models for microarray data. In Bioinformatics and Computational Biology Solutions Using R and Bioconductor, Gentleman, R., Carey, V., Dudoit, S., Irizarry, R., Huber, W., eds. (New York, Springer), pp. 397–420. Sturn, A., Quackenbush, J., and Trajanoski, Z. (2002). Genesis: cluster analysis of microarray data. Bioinformatics. 18, 207–208. Swarbreck, D., et al. (2008). The Arabidopsis Information Resource (TAIR): gene structure and function annotation. Nucleic Acids Research. 36, 1009–1014. Taji, T., Seki, M., Satou, M., Sakurai, T., Kobayashi, M., Ishiyama, K., Narusaka, Y., Narusaka, M., Zhu, J.K., and Shinozaki, K. (2004). Comparative genomics in salt tolerance between Arabidopsis and Arabidopsis-related halophyte salt cress using Arabidopsis microarray. Plant Physiol. 135, 1697–1709. Tellstro¨m, V., Usadel, B., Thimm, O., Stitt, M., Ku¨ster, H., and Niehaus, K. (2007). The lipopolysaccharide of Sinorhizobium meliloti suppresses defense-associated gene expression in cell cultures of the host plant Medicago truncatula. Plant Physiol. 143, 825–837. Walia, H., et al. (2005). Comparative transcriptional profiling of two contrasting rice genotypes under salinity stress during the vegetative growth stage. Plant Physiol. 139, 822–835. Wang, Y., Li, K., and Li, X. (2009). Auxin redistribution modulates plastic development of root system architecture under salt stress in Arabidopsis thaliana. J. Plant Physiol. 166, 1637–1645. Wang, Y.J., Zhang, Z.G., He, X.J., Zhou, H.L., Wen, Y.X., Dai, J.X., Zhang, J.S., and Chen, S.Y. (2003). A rice transcription factor OsbHLH1 is involved in cold stress response. Theor. Appl. Genet. 107, 1402–1409.
Zahaf et al. • Salt Adaptation of Medicago Genotypes
1081
Winicov, I.I., and Bastola, D.R. (1999). Transgenic overexpression of the transcription factor alfin1 enhances expression of the endogenous MsPRP2 gene in alfalfa and improves salinity tolerance of the plants. Plant Physiol. 120, 473–480. Wolters, H., and Ju¨rgens, G. (2009). Survival of the flexible: hormonal growth control and adaptation in plant development. Nat. Rev. Genet. 10, 305–317. Yang, Y.H., Dudoit, S., Luu, P., Lin, D.M., Peng, V., Ngai, J., and Speed, T.P. (2002). Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res. 30, e15. Yeung, K.Y., Haynor, D.R., and Ruzzo, W.L. (2001). Validating clustering for gene expression data. Bioinformatics. 17, 309–318. Young, N.D., Cannon, S.B., Sato, S., Kim, D., Cook, D.R., Town, C.D., Roe, B.A., and Tabata, S. (2009). Sequencing the genespaces of Medicago truncatula and Lotus japonicus. Plant Physiol. 137, 1174–1181. Zhang, G., Chen, M., Chen, X., Xu, Z., Guan, S., Li, L., Li, A., Guo, J., Mao, L., and Ma, Y. (2008). Phylogeny, gene structures, and expression patterns of the ERF gene family in soybean (Glycine max L.). J. Exp. Bot. 59, 4095–4107. Zhou, J., Li, F., Wang, J.L., Ma, Y., Chong, K., and Xu, Y.Y. (2009). Basic helix-loop-helix transcription factor from wild rice (OrbHLH2) improves tolerance to salt- and osmotic stress in Arabidopsis. J. Plant Physiol. 166, 1296–1306. Zhou, Q.Y., Tian, A.G., Zou, H.F., Xie, Z.M., Lei, G., Huang, J., Wang, C.M., Wang, H.W., Zhang, J.S., and Chen, S.Y. (2008). Soybean WRKY-type transcription factor genes, GmWRKY13, GmWRKY21, and GmWRKY54, confer differential tolerance to abiotic stresses in transgenic Arabidopsis plants. Plant Biotech. J. 6, 486–503. Zolla, G., Heimer, Y.M., and Barak, S. (2010). Mild salinity stimulates a stress-induced morphogenic response in Arabidopsis thaliana roots. J. Exp. Bot. 61, 211–224.
