New insights into aluminum tolerance in rice: the ASR5 protein binds the STAR1 promoter and other aluminum-responsive genes

Rafael Augusto Arenhart1, Yang Bai2,3, Luiz Felipe Valter de Oliveira1, Lauro

Bucker Neto1, Mariana Schunemann1, Felipe dos Santos Maraschin4, Jorge

Mariath4, Adriano Silverio4, Gilberto Sachetto-Martins5, Rogerio Margis1,6, Zhi-Yong

Wang2, *Marcia Margis-Pinheiro1,.

Institutions:

1 Programa de Pós-Graduação em Genética e Biologia Molecular – Departamento de Genética - Universidade Federal do Rio Grande do Sul. 2 Department of Plant Biology - Carnegie Institution for Science, Stanford, CA 94305.3 School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.4 Departamento de Botânica - Universidade Federal do Rio Grande do Sul.5 Departamento de Genética - Universidade Federal do Rio de Janeiro.6 Centro de Biotecnologia - Universidade Federal do Rio Grande do Sul.

*Corresponding address:

Dr. Marcia Margis-Pinheiro

Avenida Bento Gonçalves 9500, Departamento de Genética, sala 207, prédio

43312, Universidade Federal do Rio Grande do Sul, 91501-970, Porto Alegre,

Brasil. Phone: 55 (51) 3308-9814. E-mail: marcia.margis@ufrgs.br

SummaryAcidic soils comprise a large portion of earth’s crust. In this environment,

aluminum becomes soluble to plants affecting directly plant development. Among

crops, rice is the most Al-resistant but the base of this tolerance is far from being

elucidated. In this work, we showed a large-scale profile of Al-responsive genes in

rice. Besides, we extended the study in relation to ASR5, a protein previously

found by our group as having an important function in Al resistance.

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Abstract

Aluminum (Al) toxicity in plants is one of the primary constraints in crop production.

Al3+, the most toxic form of Al, is released into soil under acidic conditions and

causes extensive damage to plants, especially in the roots. In rice, Al tolerance

requires the ASR5 gene, but the molecular function of ASR5 has remained

unknown. Here, we perform genome-wide analyses to identify ASR5-dependent

Al-responsive genes in rice. Based on ASR5_RNAi silencing in plants, a global

transcriptome analysis identified a total of 961 genes that were responsive to Al

treatment in wild type rice roots. Of these genes, 909 did not respond to Al in the

ASR5_RNAi plants, indicating a central role for ASR5 in Al-responsive gene

expression. Under normal conditions, without Al treatment, the ASR5_RNAi plants

expressed 1.756 genes differentially compared to the wild type plants, and 446 of

these genes responded to Al treatment in the wild type plants. Chromatin

immunoprecipitation followed by deep sequencing identified 104 putative target

genes that were directly regulated by ASR5 binding to their promoters, including

the STAR1 gene, which encodes an ABC transporter required for Al tolerance.

Motif analysis of the binding peak sequences revealed the binding motif for ASR5,

which was confirmed via in vitro DNA binding assays using the STAR1 promoter.

These results demonstrate that ASR5 acts as a key transcription factor that is

essential for Al-responsive gene expression and Al tolerance in rice.

Keywords: Aluminum, ChIP-Seq, RNA-Seq, Rice, ASR

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Introduction

Abiotic stress is a major cause of crop failure worldwide, leading to reduced

crop productivity, which threatens agricultural sustainability (Mahajan and Tuteja,

2005). Aluminum (Al), an abundant metal in the earth’s crust, is a component of

clay soils. However, under acidic conditions, the trivalent form, Al3+, is solubilized

in soil solutions and is highly toxic to plants (Famoso et al., 2010). Because

approximately 30 - 50% of the world’s arable land shows acidic conditions, Al

toxicity is the primary limiting factor in crop productivity (Von Uexkull and Mutert,

1995). The major effect of Al toxicity is inhibition of root elongation, leading to poor

ion and water uptake (Barcelo and Poschenrieder, 2002).

Over the course of evolutionary history, many plants have developed

mechanisms that permit them to tolerate Al toxicity. These mechanisms are

classified as either external or internal tolerance mechanisms (Kochian et al.,

2004). External mechanisms, such as root exudation of organic acids (OAs) that

bind to Al and prevent its entrance into cells, have been well characterized in

several species, such as wheat, sorghum and maize (Kochian et al., 2004).

Internal mechanisms, such as compartmentalization of Al in the vacuole, have also

been demonstrated in some species (Ma et al., 1997; Zheng et al., 1998; Wenzl et

al., 2002).

Different species exhibit different levels of Al tolerance, and rice (Oryza

sativa) is one of the most Al-resistant crops under field conditions (Foy, 1988). In

general, rice is approximately two to five times more Al tolerant than wheat,

sorghum, or maize (Famoso et al., 2010). Al tolerance is mediated by Al-

responsive gene expression (Tsutsui et al., 2012). For example, the Al-induced

genes STAR1 and STAR2 encode an ATP-binding protein and a transmembrane

domain protein, respectively. The STAR1-STAR2 complex transports UDP-

glucose, a substrate used to modify the cell wall and mask Al binding sites (Huang

et al., 2009). Nrat1, a natural resistance-associated macrophage protein (Nramp),

encodes an Al transporter (Xia et al., 2010), whereas FRDL4, a multidrug and

toxic compound extrusion (MATE) protein, encodes an Al-induced citrate

transporter that is involved in citrate secretion (Yokosho et al., 2011). These

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studies indicate that rice may display both external and internal Al detoxification

mechanisms as well as additional unknown mechanisms to manage Al toxicity. Al-

responsive genes have also been identified in other species such as Arabidopsis

(Goodwin and Sutter, 2009; Kumari et al., 2008), Aspen (Grisel et al., 2010),

Medicago truncatula (Chandran et al., 2008), common bean (Eticha et al., 2010),

maize (Maron et al., 2008; Mattiello et al., 2010) and soybean (Duressa et al.,

2010; You et al., 2011; Guo et al., 2007; Houde and Diallo, 2008). Nevertheless,

little is known about the mechanisms of Al signal transduction that mediate Al-

responsive gene expression. In rice, the transcription factor ART1 has been

identified as an essential component of Al-responsive gene expression (Yamaji et

al., 2009). However, the level and localization of ART1 are not affected by Al

treatment, and it was therefore suggested that additional Al-regulated factors

might be required for ART1 activation and Al-responsive gene expression (Yamaji

et al., 2009).

The Abscisic Acid, Stress and Ripening (ASR) proteins constitute a low-

molecular weight, highly hydrophilic plant-specific protein family. Members of this

family have been shown to be involved in processes such as fruit development

(Çakir et al., 2003; Chen et al., 2011), abiotic stress (Kim et al., 2009; Sugiharto et

al., 2002; Vaidyanathan et al., 1999; Yang et al., 2004) and biotic stress (Liu et al.,

2010). Some ASR proteins present chaperone activity (Konrad and Bar-Zvi, 2008)

and also may participate in transcriptional regulation (Çakir et al., 2003; Kim et al.,

2009; Yang et al., 2008; Hsu et al., 2011).

We have previously shown that the ASR5 (LOC_Os11g06720) protein is

localized in the chloroplast (Arenhart et al., 2012), cytoplasm and nucleus

(Arenhart et al., 2013). ASR5 transcript levels increase in response to Al in the

roots and shoots, and ASR5-silenced plants are extremely sensitive to Al

(Arenhart et al., 2013). To understand the mechanisms by which rice tolerates

toxic Al concentrations, it is important to determine how ASR5 acts in the Al

response pathway. In this study, we performed genome-wide transcriptome and

protein-DNA interaction analyses of ASR5-mediated Al responses using

ASR5_RNAi in plants. We show that ASR5 regulates a large number of Al-

responsive genes, including STAR1.

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Results

Promoter analysis reveals a correlation between ASR5 expression and its role in the Al tolerance mechanisms.

Previous analysis has showed that the ASR5 transcript level increases in

response to Al (Arenhart et al., 2013). To characterize the tissue-specific

expression conferred by the ASR5 promoter, a construct containing the 2060 base

pairs upstream of the rice ASR5 start codon fused with GUS was transformed into

rice. Regenerated plants from non-transformed calli were used as negative

controls. GUS activity was detected in the vascular tissue of the root (Figures 1A

and 1B), root cap (Figures 1C and 1D), lateral root cap (Figures 1E and1F) and

cells detaching from the root cap (root border cells) (Figure 1G). Transverse

sections revealed that GUS was also expressed in the cells of the exodermal layer

and the cortex and in the parenchymatous cells of the xylem and the companion

cells of the phloem in the vascular tissue (Figure 1H). Lateral root emergence

mechanically damages the cortical cells adjacent to the apical zone, and GUS

expression was stronger in the cortical cells in the apical zone than in other

cortical cells (Figure 1F). Under Al stress, there was a slight increase in GUS

expression in the roots (Figure S1).

In the leaves, expression of ASR5prom:GUS was detected in vascular

tissues (Supplementary Figure S2A) and in response to mechanical damage

(Supplementary Figure S2B). In floral tissues, GUS was expressed in the vascular

tissues of the anther (Supplementary Figure S2C), stigma (Supplementary Figure

S2D), palea and lemma (Supplementary Figure S2E), and it was also detected in

the trichomes of the palea and lemma (Supplementary Figure S2F).

Global transcriptome analysis reveals a central role for ASR5 in Al-responsive gene expression in rice

In a previous study, we showed that ASR5-silenced plants (ASR5_RNAi)

present high sensitivity to Al (Arenhart et al., 2013) (Supplementary Figure S3A).

Furthermore, the function of ASR5 was found to be specific to Al, as cadmium

treatment did not trigger different responses in wild type non-transformed (NT)

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versus ASR5_RNAi plants (Arenhart et al., 2013). To understand the molecular

function of ASR5, we performed transcriptome analysis of the ASR5_RNAi plants.

NT and ASR5_RNAi transgenic plants were cultivated under control conditions for

12 days and then treated with a control solution (Cnt) or AlCl3 (Al, 450 µM) for 8 h.

The plant roots were harvested to generate four RNA libraries for RNA-Seq

analysis. Illumina RNA-Seq generated a total of 9,497,649 reads mapped to the

Rice Genome Annotation, version 7.0 for the NT_Cnt sample; 11,257,398 for the

NT_Al sample; 2,013,886 for the ASR5_RNAi_Cnt sample; and 1,831,659 for the

ASR5_RNAi_Al sample. Digital gene expression (DGE) determined from the

counted reads was normalized via a statistical analysis performed using edgeR

(Robinson et al., 2010) for the four libraries and was employed to perform three

comparisons, as follows: i) NT_Cnt vs. NT_Al, ii) ASR5_RNAi_Cnt vs.

ASR5_RNAi_Al and iii) NT_Cnt vs. ASR5_RNAi_Cnt. Using this statistical method,

we normalized the data, despite the variation in the number of uniquely mapped

reads (Supplementary Figures S3B, S3C and S3D). The ASR5 gene was up-

regulated in response to Al in the NT plants and was silenced in the ASR5_RNAi

plants (Table S1). The raw data from these experiments are provided in the

Supplementary Information (S1).

A total of 961 genes were differentially expressed in rice roots in response

to Al treatment in the NT plants (475 up-regulated and 486 down-regulated).

These included 72 genes (51 up- and 21 down-regulated) previously shown to be

affected by a low concentration of Al (20 µM) in wild type rice (Tsutsui et al., 2012)

(Supplementary information S1). In contrast, in the ASR5_RNAi plants, only 309

genes showed Al-induced differential expression (234 up-regulated and 75 down-

regulated) (Figure 2A). Only 48 genes were up-regulated and 4 genes were down-

regulated by Al treatment in both the NT and ASR5_RNAi plants (Figure 2A).

Thus, approximately 95% of the rice genes regulated by Al in the NT plants did not

respond similarly to Al treatment in the ASR5_RNAi plants (Figure 2A). A set of 23

known Al-responsive genes showed similar Al response patterns in the NT plants,

as previously reported (Table 1) (Zhang et al., 2007; Zhang et al., 2010; Yamaji et

al., 2009; Xia et al., 2010; Huang et al., 2009; Dong et al., 2010; Krill et al., 2010;

Yokosho et al., 2011). However, 22 (95%) of these 23 genes did not respond to

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the Al treatment, or they responded in an opposite manner in the ASR5_RNAi

plants. Therefore, the RNA-seq data demonstrate an essential role of ASR5 in Al-

responsive gene expression.

Under normal growth conditions, without Al treatment, the ASR5_RNAi

plants expressed 1.756 genes differentially (632 up-regulated and 1.124 down-

regulated) compared to the NT plants, 446 of which responded to Al treatment in

the wild type plants, suggesting that ASR5 plays additional roles, independent of

Al stress (Figure 2B and Supplementary Figure S3D). A hierarchical clustering and

heatmap analysis showed that the expression patterns observed in the NT and

ASR5_RNAi plants in the presence of Al clustered separately and revealed that

hundreds of genes were affected by ASR5 silencing and showed clear opposite

patterns when Al-responsive genes were compared in the NT and ASR5_RNAi

plants (Supplementary Figure S3E).

Because basipetal transport of exogenous [3H] indole-3-acetic acid applied

to the meristematic zone is significantly inhibited by Al application in the root apex

DTZ (Distal Transition Zone) in the Al-sensitive maize cv Lixis (Kollmeier et al.,

2000), we searched our RNA-Seq data for auxin-related genes in the NT and

RNAi plants that were responsive to Al (Supplementary Figure S4). We found one

auxin response factor and an auxin-repressed protein gene showing increased

transcript levels in response to Al only in NT plants (LOC_Os02g06910 and

LOC_Os03g22270). Another auxin-repressed protein (LOC_Os11g44810) was

increased in NT but down-regulated in RNAi plants. Furthermore, three auxin-

induced proteins (LOC_Os05g01570, LOC_Os08g44750 and LOC_Os01g58910)

and one auxin efflux carrier (LOC_Os02g50960) did not respond to Al but were

down-regulated in the ASR5_RNAi plants,

A gene ontology (GO) search for biological processes within the RNA-Seq

dataset using the website software programs AgriGO (Du et al., 2010) and

ReviGO (Supek et al., 2011) revealed several enriched terms. A total of 83 GO

terms were found for genes that were up-regulated by Al in the NT plants. Some of

the enriched GOs included programmed-cell-death (PCD)-like apoptotic

processes, response to stress, signaling and ion transport (Supplementary Figure

S5A). Among the down-regulated genes, 131 GO terms were enriched, covering a

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wide range within the classes including primary metabolism, sugar pathways,

cellulose biosynthesis (including glucan and carbohydrate biosynthetic processes

and glucose and hexose metabolic processes) and cellular macromolecule

complex assembly (including chromatin assembly, chromosome organization and

DNA packing) (Supplementary Figure S5B). The GO terms for the genes that were

up-regulated in the ASR5_RNAi plants in response to Al treatment were enriched

in classes including carbohydrate metabolic processes, molecule catabolic

processes, signal transduction and amine biosynthetic processes. All of the GO

terms are included in the Supplementary Information (S2). Under the same

experimental conditions, no significant terms were found for the 75 genes that

were down-regulated by Al in the ASR5_RNAi plants when using the same

threshold.

We also performed GO searches for the 632 genes that were up-regulated

and the 1.124 genes that were down-regulated by ASR silencing. Due the large

number of genes, we performed these analyses using only the GO terms that

presented a p-value, Log10 of lower than 0.0009. We retrieved 33 and 99 GO

terms for the up- and down-regulated genes, respectively. The genes that were

up-regulated due to ASR silencing were enriched in programmed-cell-death

(apoptosis) compared to the reference genome (Supplementary Figure S5C). The

down-regulated genes belong to categories including cell wall macromolecule

catabolism, response to stress, oxidative stress, chemical stimulus, and

antioxidant activity.

ASR5 silencing affects STAR1 expressionTo identify downstream genes responsible for ASR5-mediated Al tolerance,

we searched the RNA-seq dataset for rice Al-specific up-regulated genes with

orthologues and homologues reported in the literature. We first searched for gene

families whose transcript levels were increased in response to Al treatment in the

NT plants, but not in the ASR5_RNAi plants. The genes that fit these criteria and

were repressed in the ASR5_RNAi plants were also included. Using this approach,

we found four ABC transporter genes showing Al-induced expression only in the

NT plants (LOC_Os01g50100, LOC_Os03g54790, LOC_Os04g49900, and

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STAR1/LOC_Os06g48060). STAR1 was the only ABC gene whose transcript level

was increased in the Al-treated NT plants but decreased in the ASR5_RNAi plants

compared to the untreated NT plants (Supplementary Figure S6). To confirm the

RNA-Seq results, real time RT-qPCR experiments were performed to validate the

expression patterns of 19 genes (including genes responsive to Al described in the

literature, such as ASR5, STAR1, MATE and a metallothionein) in NT and

ASR5_RNAi plants that were treated with AlCl3 (450 µM) for 8 h (Figure 3 and

Supplementary Figure S7).

Identification of in vivo ASR5-binding sitesBecause ASR5_RNAi plants are hypersensitive to Al (Arenhart et al., 2013)

and an ASR protein was shown to act as a transcription factor in grape (Çakir et

al., 2003), we searched for in vivo DNA-binding sites for ASR5. To accomplish this

task, multiple chromatin-immunoprecipitation (ChIP) experiments (biological

triplicates) were performed using an anti-ASR5 antibody in the roots of NT rice

plants (12 days old) that were treated with AlCl3 (450 µM) for 8 h at pH 4.5. The

obtained DNA samples were then combined to perform ChIP-Seq analysis. The

control ChIP experiments were performed using pre-immune serum. The anti-

ASR5 antibody specifically detected increased ASR5 protein levels in response to

Al treatment (Figure 4A). Sequencing of the anti-ASR5 ChIP DNA libraries

generated 6.0 million reads, and the control ChIP experiments generated 1.74

million reads that mapped to the Rice Genome Annotation Version 7.0 (35 bp/read

with unique and up to 2 mismatches) using the MACS software program (Zhang et

al., 2008). A total of 649 binding peaks led to the identification of 1.087 loci in the

ChIP-Seq binding peak analyses, which were proposed as potential ASR5 target

genes, including 421 loci (38.7%) that contained binding peaks in the promoter

region (5000-bp upstream region), 148 loci (13.62%) in the transcribed region

(5’UTR, CDS or 3’UTR) and 518 loci (47.69%) outside of genes (Figure 4B and

Supplementary Information S3). Consistent with a transcription factor function,

most of the binding peaks were distributed near transcription start sites (Figure

4C). When a binding site was located in the gene body region (5 kb upstream of

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the 5’UTR and 1 kb downstream of the 3’UTR), the gene was designated as a

potential ASR5 target gene. If the binding site was not located inside a gene body

region, the nearest upstream gene and the nearest downstream gene to this

binding site were included as potential ASR5 target genes.

The list of ASR5 target genes was compared to the genes that responded

to Al in the NT plants but not in the ASR5_RNAi plants in the RNA-Seq

experiments (Figure 2A). This comparison identified 36 genes that were Al-

responsive in an ASR5-dependent manner and that were bound by ASR5 in vivo

(Figure 5A). Among these genes, 21 were unaffected, and 15 were affected in the

ASR5_RNAi plants without Al treatment, including STAR1 (Supplementary

Information S4). In addition, 68 ASR5 target genes were affected by ASR5_RNAi

but were not responsive to Al treatment (Figure 5B and Supplementary Information

S4). Together, these results identified 104 genes that were bound by ASR5 in vivo

and were affected by Al treatment and/or silencing of ASR5. We consider these

genes to be functional targets of ASR5.

Identification of the ASR5 DNA-binding motif and binding sites in the STAR1 promoter region

To identify potential ASR5-binding motifs, we used the DREME

(Discriminative DNA Motif Discovery) tool (Bailey, 2011) to search for statistically

overrepresented motifs in ASR5-binding regions base on the ChIP-Seq data. First,

649 binding sequences were used, which included all of the binding sites from the

ChIP-Seq dataset. The DREME analysis identified 10 potential enriched motif

sequences (Supplementary Figure S8). The analysis was then repeated using only

the binding peaks found in the promoter region (5 kb, 322 sequences). This

strategy allowed the identification of a consensus sequence GGCCCA(T/A)

(Figure 6A). The sequences GGCCCA, AGCCCAT and GGCCCAT were enriched

in the ChIP-seq dataset compared to the rice genome (Figure 6B). However, the

CACCG motif, which serves as the binding site for the ABI4 transcription factor in

Arabidopsis (Shkolnik and Bar-zvi, 2008), was not enriched in the ASR5-bound

sequences (Figure 6B).

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ChIP-qPCR experiments confirmed the in vivo binding of ASR5 to the

STAR1 promoter region (Figure 7A). This region contains two ASR5-binding motifs

(AGCCCAT) separated by 58 bp. We further analyzed the binding of ASR5 to the

STAR1 promoter through an in vitro DNA pull-down assay (Wu, 2006). A

biotinylated DNA fragment containing the 442 base pairs of the STAR1 promoter

region centered on the ASR5 ChIP-seq peak was incubated with the GST-ASR5

protein or GST itself. The DNA-bound proteins were pulled down using

Streptavidin-agarose beads. The results showed that GST-ASR5 bound to the

biotinylated DNA fragment, whereas GST did not. The ASR5-DNA binding was

competed away by the inclusion of a 25x concentrated non-biotinylated STAR1

fragment but not by Di-DC or DNA fragments harboring deletions of the putative

ASR5-binding motif (AGCCCAT) (Figure 7B-C). Moreover, transient gene

expression assays demonstrated the regulation of STAR1 by ASR5 (Figure 7D).

These results indicated that rice ASR5 acts as a transcription factor that activates

STAR1 expression through direct interaction with cis elements in the STAR1

promoter. Under Al stress, the ASR5 protein binds to the STAR1 promoter and

other target genes to modulate their expression (Figure 7E).

A previous study showed that Al-responsive expression of STAR1 requires

the transcription factor ART1 (Yamaji et al., 2009). To test whether ASR5 can form

homodimers and/or heterodimers with ART1 (a regulator of STAR1), a yeast two-

hybrid assay was performed. The assay showed that ASR5 was unable to form

homodimers or heterodimers with ART1 in the presence or absence of Al and Zinc

(Supplementary Figure S9).

Discussion

In previous studies, we have demonstrated an essential role for ASR5 in Al

tolerance in rice. However, the molecular mechanism of ASR5 function has

remained unknown. Here, through genome-wide gene expression and protein-

DNA interaction analyses, we show that ASR5 is a DNA-binding protein that

directly regulates a number of Al-responsive genes, including several genes

previously shown to be required for full Al tolerance.

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ASR5 is expressed in tissues that are important for Al tolerance in plantsThe expression of GUS driven by the ASR5 promoter in the root apex

(more specifically, in the root border cells) (Figure 1A-G) provides new insights

regarding Al resistance in rice. The root border cells (RBCs) are a population of

mucilage-secreting cells that surround the root cap (Hawes et al., 2003). The

expression of ASR5 in border cells is consistent with previous observations that

physical removal of RBCs from the root tips results in higher Al accumulation in

the root tips and more severe inhibition of root elongation, which indicates that

these cells protect the root tip from Al toxicity (Miyasaka and Hawes, 2001).

Therefore, the tissue-specific expression pattern of ASR5 and its increased level in

the roots under Al treatment (Figure S1) are consistent with the role of ASR5 in Al

tolerance.

GUS expression was also observed in the trichomes of leaves

(Supplementary Figure S2A) and of the palea and lemma (Supplementary Figure

S2F). In tobacco, trichomes have been shown to secrete metals complexed with

calcium crystals when the plants are grown in a medium with toxic levels of zinc

(Sarret et al., 2006). Additionally, ASR5_RNAi plants display a reduced number of

trichomes in the leaves, palea and lemma (Arenhart et al., 2013). Together these

observations suggest that ASR5 acts on trichome development and may

contribute to the management of toxic Al levels in leaf and inflorescence tissues in

rice.

ASR5 is required for Al-responsive gene expression in rice.Our RNA-seq experiments demonstrated that approximately 95% of the 961

identified Al-responsive genes depend on ASR5 for normal Al-responsive

expression. The robustness of the applied statistical approach is supported by the

fact that the ASR5 gene was up-regulated in response to Al in the NT plants and

was silenced in the ASR5_RNAi plants (Table S1 and Supplementary Figure 3). In

addition, our RNA-seq data were consistent with previous reports indicating 72

genes that respond to a low concentration of Al in wild type rice (Tsutsui et al.,

2012) (Supplementary information S1) and a set of 23 other known Al-responsive

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genes (Table S1). The observation that 95% of the genes that responded to Al in

NT plants did not show a similar Al response in the ASR_RNAi plants

demonstrates a central role for ASR5 in Al-responsive gene expression.

Among these ASR5-dependent Al-responsive genes, STAR1 (Huang et al.,

2009), Nrat1 (Xia et al., 2010) and FRDL4 (Yokosho et al., 2011) were previously

shown to play important roles in the rice response to Al. STAR1 belongs to the

ABC family of genes, and in rice, the STAR1 protein, together with STAR2,

mediates the transport of UDP-glucose to the cell wall, participating in masking Al-

binding sites (Huang et al., 2009). An Arabidopsis homolog of STAR1, ALS3, has

been documented to be essential for Al resistance (Kumari et al., 2008; Larsen et

al., 2005). Nrat1 transports trivalent Al ions but not other divalent ions, such as

manganese, iron, and cadmium, or the Al–citrate complex (Xia et al., 2010).

FRDL4, another Al-induced protein, participates in external Al detoxification

(organic acid release) via citrate transport (Yokosho et al., 2011).

Several gene classes described previously as being Al-responsive were

also detected in our RNA-Seq experiments. For example, nine genes encoding

metallothionein and metal transporters (LOC_Os05g39540, LOC_Os03g38970,

LOC_Os02g50730, LOC_Os12g38290, LOC_Os12g38270, LOC_Os12g38010,

LOC_Os12g38040, LOC_Os12g38051 and LOC_Os12g38300) were up-regulated

by Al in the NT plants (Supplementary Information S1). LOC_Os12g38051 and

LOC_Os12g38300 were repressed in the ASR5_RNAi plants. These

metallothioneins may have evolved for the detoxification of heavy metals by

chelating metals and buffering their cytosolic concentration (Cobbett and

Goldsbrough, 2002). Six glycosyl hydrolases (LOC_Os01g71820,

LOC_Os10g28080, LOC_Os10g28120, LOC_Os01g47070, LOC_Os04g40490

and LOC_Os01g71350) were up-regulated by Al only in the NT plants

(Supplementary Information S1); all of these genes except for LOC_Os01g71820

were repressed in the ASR5_RNAi plants. Glycosyl hydrolases have also been

shown to be up-regulated by Al in Arabidopsis and Populus (Kumari et al., 2008;

Grisel et al., 2010). Al-induced root growth inhibition is the earliest symptom of Al

toxicity and occurs as a result of the rapid inhibition of cell elongation (Kochian et

al., 2005). Plants employ a set of different mechanisms to loosen the cell wall

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during cell extension. Glycosyl hydrolases may play a crucial role in this loosening

process by negating the Al-induced cell wall-stiffening effect. ASR5 also regulates

many genes with potential functions in the auxin response (Supplementary Figure

S4), including an auxin response factor homolog (LOC_Os02g06910), a putative

auxin efflux carrier (LOC_Os02g50960), two auxin repressed proteins

(LOC_Os03g22270 and LOC_Os11g44810) and three auxin-induced proteins

(LOC_Os05g01570, LOC_Os08g44750 and LOC_Os01g58910), suggesting a

role of ASR5 in regulating plant growth by modulating the auxin pathway.

A gene ontology search for genes that were differentially expressed in NT

plants in response to Al (Supplementary Figure S5A,B) found that many classes of

stress-responsive genes were up-regulated, while primary metabolism and cell

cycle genes were down-regulated in response to Al. The down-regulation of

primary metabolism may be required to manage stressful conditions (Chandran et

al., 2008). These findings are consistent with a previous report in Medicago

truncatula (Chandran et al., 2008).

Although the ASR5_RNAi plants exhibited a reduced overall transcriptional

response to Al, a number of genes responded to Al in the ASR5_RNAi plants that

did not respond in the NT control plants (Figure 2A). These genes may have been

affected by Al damage in the absence of ASR5-mediated adaptive protection.

Consistent with this notion, the star1 mutant, which exhibits a defect in Al

detoxification, showed a much broader Al-induced gene expression response than

wild type plants (Tsutsui et al., 2012).

Many genes were also affected by ASR5 silencing but not by Al treatment

(Figure 2B). The genes that were up-regulated due to ASR5 silencing were

enriched for genes involved in programmed cell death (PCD) compared to the

reference genome (Supplementary Figure S5C). Under normal growth conditions

in WT rice plants, PCD may be a mechanism for managing Al toxicity, as PCD can

occur as a result of an oxidative burst due to various stresses. ROS production

due to Al toxicity induces cell death in wheat (Delisle et al., 2001) and barley

(Simonovicova et al., 2004), and this process has been proposed to remove cells

that accumulate Al and therefore serve as a mechanism of Al resistance

(Chandran et al., 2008). However, the ASR5_RNAi plants displayed this pattern

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under normal conditions (without Al treatment), suggesting that the basal level of

ASR5 expression plays a role in protecting cells from apoptosis under normal

conditions (or when plants were stressed by an unknown factor under our normal

growth conditions). The genes that were down-regulated due to ASR5 silencing

belonged to categories including the response to stress, oxidative stress, chemical

stimulus and antioxidant activity, among others, and showed a positive correlation

with the genes that were up-regulated by Al in the NT plants (Supplementary

Figure S5D and Supplementary Information S2), consistent with Al activation of

ASR5.

These results indicate that ASR5 is required for the Al-responsive

expression of large numbers of genes, and the lack of Al induction of these genes

may contribute to the high Al sensitivity displayed in the ASR5_RNAi plants. In the

absence of ASR5-mediated protection, such as when ASR5 is silenced, plants

experience greater intracellular damage induced by Al. Under non-Al-stress

conditions, ASR5 appears to also play a role in protecting plant cells from

programmed cell death, although this phenotype is only detectable at gene

expression level.

ASR5 directly activates Al-responsive genes, including STAR1 Our RNA-seq and ChIP-seq experiments identified STAR1 as a direct

target gene of ASR5. STAR1 transcript levels were increased in the Al-treated NT

plants but decreased in the ASR5_RNAi plants compared to the untreated NT

plants (Table S1, Figure 3 and Supplementary Figure S6). STAR1 was one of the

ASR5 target genes identified in the ChIP-Seq analysis (Figure 7A), and ASR5

binding to the STAR1 promoter region was confirmed via in vitro DNA-binding

assays (Figure 7C). Furthermore, transient reporter gene assays showed that

ASR5 activates STAR1 expression in protoplasts (Figure 7D).

A previous study (Kalifa et al., 2004) suggested that tomato ASR1 binds to

a specific DNA sequence (C2-3 (C/G) A). Using the DREME tool, we identified

four putative ASR5-binding sequences from the ChIP_seq data,

(A(C/A)(G/A)GCCCA, (G/A)GCCCAT), GGCCCA(A/C) and (GGCCCA(T/A)

(Supplementary Figure S8 and Figure 6A), which showed high similarity to the

15

tomato ASR1-binding site identified in a SELEX-binding experiment (Kalifa et al.,

2004). The STAR1 promoter region used for ChIP-qPCR contains two ASR5-

binding motifs (AGCCCAT) separated by 58 bp. We propose that the consensus

sequence (AGCCCAT) represents a novel motif for the binding of the ASR5

protein.

ASR1 from tomato forms homodimers via zinc-dependent DNA-binding

activity (Goldgur et al., 2007), though ASR1 monomers can also bind DNA

(Maskin et al., 2007). In the same study (Maskin et al., 2007), ASR1 was only

found as homodimers in specific organs. Although ASR5 homodimerization could

not be demonstrated in our yeast two-hybrid assays (Supplementary Figure S9),

this possibility cannot be discarded because ASR proteins are able to form dimers

in tomato (Rom et al., 2006; Goldgur et al., 2007; Konrad and Bar-Zvi, 2008) in the

nucleus and even in the cytoplasm (Ricardi et al., 2012). Our results suggest that

rice ASR5 can show activity as a monomer, or ASR5 might require another protein

for its function, as grape ASR forms heterodimers with drought response element-

binding (DREB) proteins (Saumonneau et al., 2008).

Al-responsive gene expression also requires the transcription factor ART1

(Yamaji et al., 2009). However, the ART1 gene is not affected by Al treatment, and

Yamaji et al. suggested that other Al-regulated factors may be required for ART1

to activate its target genes in response to Al stress. Our results suggest that ASR5

is the Al-activated factor that binds to the STAR1 promoter to enhance its

expression. The requirement of both ASR5 and ART1 for Al-induced STAR1

expression suggests that ASR5 and ART1 may interact with each other directly

and function cooperatively. ASR5-binding sites (AGCCCAT) are found in STAR1

promoter 218 and 282 nucleotides upstream of the ART1-binding motif (Tsutsui et

al., 2011). However, we did not detect any ASR5-ART1 interaction in our yeast

two-hybrid assay, even in the presence of Al and Zinc (Supplementary Figure S9).

Further research will be required to understand the mechanism underlying the

transcriptional activities of these two proteins.

No Al receptors have been found in rice, and our results have shown that

ASR5 likely does not serve as the receptor for Al, as IMAC (immobilized-metal

affinity chromatography) experiments indicated no Al binding (data not shown).

16

However, similar to ASR1 from tomato (Goldgur et al., 2007), ASR5 was able to

bind zinc ions in IMAC assays (data not shown). Interestingly, ART1, a putative

C2H2 zinc finger protein, was unable to bind zinc ions in IMAC assays (data not

shown).

This study demonstrates that ASR5 is a key transcription factor that

mediates Al-responsive gene expression to provide Al tolerance in rice. Under Al

stress, the ASR5 protein binds to promoter DNA sequences to mediate the Al-

responsive expression of large number of genes, many of which play important

roles in Al detoxification and stress adaptation. Taken together, our results provide

new insights into the molecular mechanisms of Al resistance in rice. Furthermore,

the large number of both ASR5-dependent and ASR5-independent Al-responsive

genes identified defines a structured transcriptome that mediates Al tolerance in

rice. Our findings not only shed light on the molecular mechanisms of Al resistance

in rice but also provide important information for future research on improving Al

tolerance in other crops.

METHODS

Aluminum Treatment and Sample Preparation for Transcriptome Sequencing Rice seeds were germinated on filter paper for 4 d in the dark at 28 °C. The

seedlings were grown in hydroponic Baier’s solution (Baier et al., 1995) for 12 d in

a growth chamber at 28 °C under 12 h of light. The hydroponic solution was

replaced every 4 d. After 12 days, root samples from non-transformed (NT) and

ASR5-silenced (ASR5_RNAi) rice plants (ssp. Japonica cv. Nipponbare) grown

under control conditions or subjected to Al treatment (8 h with 450 µM AlCl3 at pH

4.5) were collected and immediately frozen in liquid nitrogen. The total RNA was

then extracted with TRIzol (Invitrogen, Carlsbad, CA, USA) according to the

manufacturer’s instructions. The total RNA (> 10 μg) was then sent to Fasteris Life

Sciences SA (Plan-les-Ouates, Switzerland) for sample preparation (conversion to

cDNA) and shotgun sequencing using Illumina HiSeq 2000 (Illumina, San Diego,

CA, USA). Polyadenylated transcript sequencing (mRNA-seq) was performed

using the following successive steps: poly-A purification, cDNA synthesis using the

17

poly-T primer shotgun to generate inserts of 300 to 500 nucleotides, 3p and 5p

adapter ligations, pre-amplification, colony generation and sequencing. The cDNA

sequencing reaction was performed using a single-end and a 100 nucleotide read

length.

Transcriptome Sequencing Data AnalysisMapping Method: The reads were aligned with the Bowtie v. 0.12.7

software program (Langmead et al., 2009) using the default parameters. The first

seed alignment was > 28 nucleotides in size, allowing zero mismatches and

unique mapped reads. The rice genome sequence RGAP v7

(http://rice.plantbiology.msu.edu/) was used as a reference. The SAM files from

Bowtie were then processed using Python scripts to assign the counted reads that

mapped to each gene region.

Statistical Methods: The scaling normalization method was employed to

normalize the data according to Robinson and Oshlack (Robinson and Oshlack,

2010). Quantification of differential gene expression was performed with the R

package EdgeR (Robinson et al., 2010). Briefly, EdgeR uses a negative binomial

model to estimate overdispersion from a gene count. The dispersion parameter for

each gene is estimated based on the tagwise dispersion. Finally, differential

expression is assessed for each gene using an adapted exact test for

overdispersed data.

Western Blot AnalysisTwelve-day-old roots from rice plants grown under control or Al-treated (8 h,

450 µM AlCl3) conditions were macerated and homogenized in 0.5 M Tris-HCl (pH

8.3), 2% Triton X-100, 20 mM MgCl2, 2% β-mercaptoethanol, 1 mM PMSF, 2.5%

PEG and 1 mM EDTA, followed by incubation at 4°C for 1 hour. Aliquots of each

sample were then loaded and separated via SDS-PAGE in 15% gels. The ASR5

protein was detected with a rabbit polyclonal ASR5 antibody (1:500 dilution). Goat

anti-rabbit IgG (1:1000) conjugated with alkaline phosphatase was used as the

secondary antibody. The resultant bands were detected with a premixed

18

BCIP/NBT substrate solution (Sigma, St. Louis, MO, USA) and recorded on X-ray

film.

ChIP-seq Data AnalysisMapping method: The ChIP-Seq libraries were sequenced using an

Illumina Genome Analyzer IIx. Thirty-six sequencing cycles were performed,

generating a total of more than 40 million sequence reads per sample. The

sequencing reads were then mapped to the Released RGAP v7 Rice Genome

Annotation using the SOAPaligner2.21 software program (Ruiqiang Li et al.,

2009), allowing up to two mismatched nucleotides and no gaps. Only unique

mapped reads were filtered out for further analyses.

Binding site detection method: The MACS software program (Zhang et al., 2008)

was employed to search for binding peaks with the default parameters. All binding

sites were detected under the following conditions: (1) binding site detection using

only our sample data (α-ASR5); (2) binding site detection adding our control (Pre-

Serum) dataset to the MACS software; and (3) comparison of these two conditions

to filter the binding sites that overlapped in the two conditions. Additionally, binding

sites that presented less than 50% overlap with the control binding sites were

included, and the resulting binding sites were considered to represent real

aluminum-binding sites in rice.

ChIP qPCRThe chromatin-immunoprecipitation (ChIP) experiments were performed as

previously described (He et al., 2005) using plants grown under the same

conditions as in the ChIP-Seq experiment in triplicate biological repeats. The ChIP

products were analyzed via quantitative real-time PCR (the primer sequences are

listed in Supplementary Information, S4), and enrichment was calculated as the

ratio between the control sample and the α-ASR5 sample. Ubiquitin

(LOC_Os04g57220) was used as a reference gene.

ASR5-binding Motif Identification

19

To perform motif searches, 200-bp sequences (100 bp upstream and 100

bp downstream) surrounding the peak of each binding site were extracted and

used to search for consensus transcription factor-binding motifs with the

bioinformatics tool DREME (Bailey, 2011). The enrichment of motifs found by

DREME was calculated based on the frequencies of these consensus binding

motifs per 1000 bp of sequence in the entire rice genome.

Yeast Two-Hybrid AssayTo investigate the interaction between the ASR5 and ART1 proteins, the

coding sequences of both genes were amplified via PCR using specific primers.

Sequential PCR was performed to amplify the ART1 gene (ART1 first step:

forward CACCATGGATCGCGACCAGATG and reverse

TCACTTGTCACCATTCTCCTCCT; ART1 second step: forward

AGTGATTCCCCCTGCTTGAT and reverse TCATATGCAACTCGCTACGC; ASR5

forward CACCATGGCGGAGGAGAAGCAC and ASR5 reverse

TCAGCCGAAGAGGTGGTG). Yeast strain AH109 was cotransformed with

pXDGATcy86 (GAL-4-binding domain) and pGADT7 (GAL-4 activation domain)

plasmids containing these genes. The lithium acetate yeast transformation method

was applied with some modifications to introduce the constructs into the cells

(Gietz and Woods, 2002). Different concentration of zinc and aluminum were used

to verify whether interactions could occur in the presence of metal ions (Zn = 0.01,

0.05, 0.1 mM; Al = 0.05, 0.1, 0.25, 0.5 mM).

Pull-down AssayPull-down assays were performed as previously described (Wu, 2006).

Biotin-labeled and non-labeled forward and reverse primers were used to amplify

fragments via PCR employing rice genomic DNA as a template. The amplified

products were bound to Streptavidin-agarose beads and used to precipitate the

ASR5 protein. A western blot assay was subsequently performed. The primers

used in these assays are described in the Supplementary Information (S4).

Transient Gene Expression Assays

20

Protoplast isolation and PEG transformation were performed using the tape

method (Wu et al., 2009). Plasmid DNAs were extracted using the QIAGEN

Plasmid Maxi Kit (Qiagen, Hilden, Germany) according to the manufacturer’s

instructions. Approximately 1x104 isolated mesophyll protoplasts were transfected

with 10 μg of each plasmid (35S::Renilla Luciferase and 35S::STAR1prom_GUS,

designated Gus518) plus 20 or 40 µg of 35S::ASR5 and incubated for 48 hours.

Protoplasts were harvested via centrifugation and lysed in 100 µl of CCLR buffer

(25 mM K-phosphate pH 7.5, 1 mM EDTA, 7 mM 2-mercaptoethanol, 1% triton X-

100, 1-% Glycerol). Renilla activity was measured using Coelenterazine (Sigma),

while GUS activity was measured using MUG (4-methylumbelliferyl-ß-D-

glucuronide) and MU (4-methylumbelliferone), and 35S:GUS was used as a

positive control.

Real Time RT-qPCRThe plant materials and Al conditions were the same as described in a

previous section (Aluminum Treatment and Sample preparation for Transcriptome

Sequencing). RNA was extracted with TRIzol (Invitrogen, Carlsbad, CA, USA)

according to the manufacturer’s instructions. cDNA was synthesized using M-MLV

RT reverse transcriptase (Promega, Madison, WI, USA). For the real-time RT-

qPCR assays, the stock solution was diluted 10x. The protocol applied for real

time RT-qPCR can be summarized as follows: an initial step of 5 minutes at 94ºC

was followed by 40 cycles of 10 seconds at 94ºC, 15 seconds at 60ºC and 15

seconds at 72ºC. The samples were incubated for 2 minutes at 40ºC to promote

re-annealing, and they were then warmed from 55ºC to 99ºC to generate relative

denaturing curve data for the amplification products. Relative changes in gene

expression levels were calculated using the 2-ΔΔCt method (Livak and Schmittgen,

2001). All of the reactions were performed in 4 technical replicates. Quantitative

PCR was conducted using the specific primer pairs listed in Supplementary

Information section S4. Real time RT-qPCR was performed in a StepOne Applied

Biosystems real-time cyclerTM. FDH (LOC_Os02g57040) and Actin2

(LOC_Os08g29650) were used as reference genes.

21

GUS ExpressionGUS histochemical assays were performed in different organs of the

transgenic rice plants as previously described (Jefferson et al., 1987). A region

2060 base pairs upstream of the start codon of the ASR5 gene was amplified

using specific primers (listed in Supplementary Information, S4). The amplified

product was cloned in the pENTR-D TOPO vector and recombined via an LR

reaction into the vector pHGWFS7 (Karimi et al., 2002). The resulting plasmid was

used to transform rice calli (Upadhyaya et al., 2000). The regenerated plants were

incubated in 1 mM X-Gluc, 100 mM phosphate buffer (pH 7.0), 2 mM KH2Fe and

0.5% Triton X-100. The samples were incubated for 16 h at 37º C. After the

reaction had completed, the green tissues were incubated in 70% ethanol to

remove any chlorophyll. The tissues were fixed in a solution of 4% formaldehyde

and 1% glutaraldehyde in sodium phosphate buffer (pH 7.2); they were then

dehydrated in increasingly concentrated ethanol solutions and treated with

hydroxyethylmethacrylate. Sections with a thickness of 10 µm were generated with

a rotative microtome, and the analysis was performed using a Leica DMR-HC

microscope equipped with a Leica DFC500 camera. Three independent lines were

used in this analysis.

AcknowledgmentsThis work was supported by the Coordenação de Aperfeiçoamento de

Pessoal de Nível Superior (CAPES: www.capes.gov.br), the Fundação de apoio a

Pesquisa do Rio Grande do Sul (FAPERGS), and the Brazilian National Council of

Technological and Scientific Development (CNPq). We thank the Stanford Center

for Genomics and Personalized Medicine (SCGPM) service center, which is led by

M. Snyder and A. Sidow, for providing sequencing services and Z. Wen for

performing the sequencing reactions. This research was partially supported by a

grant from the NIH (R01GM066258) to Z-Y.Wang.

Author ContributionsConceived and designed the experiments: MMP, Z-Y W, RM. Performed the

experiments: RAA, LBN, MS, AS. Wrote the paper: RAA. Performed some of the

22

data analysis: RAA, YB, LFVO, JM, GS-M. Revised the paper: MMP, FSM, Z-YW,

RM.

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Figure Legends

Figure 1. Expression pattern of ASR5 prom:GUS in rice roots. (A) View of the

root elongation zone. (B) Longitudinal section of the root elongation zone. (C)

Macroscopic view of the root cap. (D) Longitudinal section of the root cap. (E) Root

cap of the lateral root and (F) mechanical damage in the cortical cells. (G) Root

cap with unstructured cells (root border cells). (H) Transverse section of the root

elongation zone showing a GUS-positive reaction in the exodermal cells (arrow),

cortex, pericycle, parenchymatic cells of the xylem and companion cells of the

phloem. The bars in A=150 µm, B=50 µm, C=50 µm, D=50 µm, E=100 µm, F=100

µm and G=100 µm.

Figure 2. Al-responsive genes in non-transformed (NT) and ASR5_RNAi plants. (A) Venn diagram showing the overlap of the Al-responsive up- and down-

regulated genes between the NT and ASR5_RNAi plants. (B) Number of genes

affected by ASR5 silencing in the ASR5_RNAi plants.

Figure 3. Quantitative real-time RT-PCR of four selected genes from the RNA-Seq analysis. Total RNA was extracted from the roots and used to

synthesize cDNA. The relative expression was plotted using the expression levels

of the FDH and Actin 2 genes as a reference. The roots of the Nipponbare cultivar

were collected after 8 h of treatment with AlCl3 (450 µM). The bars with different

letters are significantly different (ANOVA, P < 0.05). Cnt = non-transformed plants

under control conditions; Al = non-transformed plants under aluminum treatment;

RNAi_Cnt = ASR5_RNAi plants under control conditions; RNAi_Al = ASR5_RNAi

plants under aluminum treatment. NQ = not quantified.

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Figure 4. ChIP-Seq analysis of ASR5 target genes in Al-treated rice plants. (A) Western blot showing increased ASR5 protein levels in rice plants in response

to Al. ASR5 was detected with anti-ASR5. (Cnt) indicates the control untreated

plants, whereas (Al) indicates the plants that were treated with 450 µM AlCl 3 for 8

h. (B) Number and percentage of loci found in each binding region. (C) Distribution

of the binding sites. The x-axis displays the relative distance; the promoter region

group is indicated in the top yellow bar; the coding region group is indicated by top

blue and black bars, and the downstream region group is indicated by the top red

bar. The y-axis displays the number of binding sites located in the different groups.

Figure 5. Overlap between the genes affected by ASR5_RNAi or Al treatment and the genes that bound to ASR5 (ChIP-seq loci). (A) Venn diagram showing

the overlap of the Al-responsive genes between the non-transformed (NT) and

ASR5_RNAi plants and the genes affected by ASR silencing. (B) Venn diagram

showing the overlap between the 469 Al-responsive genes found in the NT plants

and ChIP-Seq loci. Venn diagram showing the overlap between the 367 Al-

responsive genes found in the NT plants and those affected in the ASR5_RNAi

plants due to ASR silencing with ChIP-Seq loci. (C) Venn diagram showing the

overlap between the 1.204 genes that were affected by ASR5 silencing but were

unresponsive to Al.

Figure 6. Discriminative motif discovery in the ASR5 ChIP-Seq dataset. (A)

The most significant motif identified using only the promoter regions of the binding

peaks from the ChIP-Seq data identified by DREME. (B) Enrichment of possible

motifs identified by DREME compared to the reference rice genome.

Figure 7. ASR5 binds to the STAR1 promoter in vitro. (A) ChIP qPCR results

showing enrichment of the STAR1 promoter region using the α-ASR5 antibody. (B)

Scheme showing the amplification sites for the STAR1 promoter. (C) SAPA pull-

down system showing that ASR5-GST binds to an F1 biotinylated DNA fragment

(F1*). Fragments F1, F2, F3 and DiDc were used as competitors. GST alone was

32

used as a negative control. (D) Transient gene expression assays demonstrating

the regulation of STAR1 by ASR5 using GUS/luciferase assays. (E) A proposed model for the ASR5-STAR1 promoter interaction. ART1 does not respond to Al

in rice but maintains a housekeeping expression level of STAR1 under control

conditions. In response to Al, ASR5 binds to the STAR1 promoter to enhance its

expression. Adapted from Delhaize et al. (Delhaize et al., 2012).

Figure S1. Expression pattern of ASR5 prom:GUS in rice roots under Al stress.

Roots of one-month-old transgenic plants (Lines 01, 02 and 03) cultivated under

control conditions or Al treatment (450 µM) for 8 hours.

Figure S2. Expression pattern of ASR5 prom:GUS in rice shoots. (A) Leaf

vascular tissues. (B) Response to mechanical damage in leaves. (C) Anther. (D)

Stigma. (E) Vascular tissue of the palea and lemma. (F) Trichomes of the palea

and lemma.

Figure S3. ASR5_RNAi phenotype in response to Al treatment; normalization plots and heatmap for the genes identified via RNA-Seq. (A) High-sensitivity

phenotype in ASR5_RNAi plants treated with 450 µM AlCl3 for 8 days and

comparison with NT plants. (B) Normalization plot for the Al-responsive genes in

the non-transformed plants. (C) Normalization plot for the Al-responsive genes in

the ASR5_RNAi plants. (D) Normalization plot for the ASR5_RNAi-affected genes.

(E) Heatmap showing the three analyzed groups. NT = non-transformed plants;

ASR5_RNAi = ASR5-silenced plants; Cnt = control conditions; Al = Aluminum

conditions.

Figure S4. Response of auxin-related genes in non-transformed (NT) and ASR5_RNAi plants. Venn diagrams showing comparisons between the genes in

the NT and ASR5_RNAi plants. NT = non-transformed plants; ASR5_RNAi =

silenced plants for ASR5 gene; Al_UP = Al up-regulated genes; Al_Down = Al

down-regulated genes; ASR5_RNAi_UP = up-regulated genes due to ASR5

silencing; ASR5_RNAi_Down = down-regulated genes due to ASR silencing.

33

Figure S5. Gene ontology analysis of the Al-responsive genes. The scatterplot

shows the cluster representatives (i.e., the terms that remained following

redundancy reduction) in a two-dimensional space derived by applying

multidimensional scaling to a matrix of the GO terms’ semantic similarities. The

bubble color indicates the AgriGO-provided p-value (see the legend in the upper

right-hand corner); the size indicates the frequency of the GO term in the

underlying GO analysis. The bubbles are larger for the more general terms.

Enriched terms for the Al-up-regulated genes in the non-transformed (NT) plants

(A); Al-down-regulated genes in the non-transformed plants (B); genes up-

regulated in the RNAi_ASR – ASR5_RNAi plants compared to the NT plants (C);

and genes down-regulated in the RNAi_ASR – ASR5_RNAi plants compared to

the NT plants (D).

Figure S6. Response of ABC transporter family genes in non-transformed (NT) and ASR5_RNAi plants. Venn diagrams showing comparisons between the

genes in the NT and ASR5_RNAi plants. NT = non-transformed plants;

ASR5_RNAi = silenced plants for ASR5 gene; Al_UP = Al up-regulated genes;

Al_Down = Al down-regulated genes; ASR5_RNAi_UP = up-regulated genes due

to ASR5 silencing; ASR5_RNAi_Down = down-regulated genes due to ASR

silencing.

Figure S7. Quantitative real-time RT-PCR analysis of fifteen selected genes from the RNA-Seq analysis. Total RNA was extracted from the roots and used to

synthesize cDNA. Relative expression was plotted using the FDH and Actin 2

gene expression levels as a reference. The roots of the Nipponbare cultivar were

collected after 8 h of treatment with AlCl3 (450 µM). The bars containing different

letters are significantly different (ANOVA, P < 0.05). Cnt = non-transformed plants

under control conditions; Al = non-transformed plants under aluminum treatment;

RNAi_Cnt = ASR5_RNAi plants under control conditions; RNAi_Al = ASR5_RNAi

plants under aluminum treatment. NQ = not quantified.

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Figure S8. The ten discriminative motifs discovered in the ASR5 ChIP-Seq dataset. The logo displays the binding motifs identified by DREME using the entire

ChIP-Seq binding peak dataset.

Figure S9. Yeast-two-hybrid analysis of ASR5 and ART1. The yeast strain

AH109 was cotransformed with pXDGATcy86 (GAL-4-binding domain) and

pGADT7 (GAL-4 activation domain) plasmids containing the ASR5 and ART1

genes. The lithium acetate yeast transformation method was used to introduce the

constructs into the cells. Different concentrations of zinc and aluminum were used

(Figure shows only strains treated with Zn 0.1 mM and Al 0.5 mM).

Supplementary Information S1. Raw RNA-Seq data.

Supplementary Information S2. Complete Gene Ontology (GO) retrieved from

the RNA-Seq data.

Supplementary Information S3. Raw ChIP-Seq data.

Supplementary Information S4. List of overlapping genes between the RNA-Seq and ChIP-Seq data, detailed materials and methods and list of primers.

(A) Overlapping data between the ChIP-Seq data and the 469 genes from the

RNA-Seq analysis that were responsive to Al only in the non-transformed plants.

(B) Overlapping data between the ChIP-Seq data and the 367 genes from the

RNA-Seq analysis that were responsive to Al in the non-transformed plants and

not responsive to Al in the ASR5_RNAi plants but that were affected by ASR5

silencing. (C) Overlap between the ChIP-Seq data and the 1204 genes from the

RNA-Seq analysis that were not responsive to Al but were affected by ASR

silencing. (D) List of primers used for PCR, real-time PCR, ChIP_qPCR, promoter

analyses and pull-down assays. Italics= Reference gene primers.

35

Table S1. List of genes described as being responsive to Al in rice compared to

their expression in the RNA-Seq experiment. ↓= Genes repressed under Al

treatment; ↑ genes induced under Al treatment; - = genes that were not responsive

or not detected under Al treatment.

(Annotation) Our data

Expression in reference

publicationsNT Al

RNAi Al

Expression in RNAi control

compared with NT control

(Zhang et al., 2007)LOC_Os01g49290 Guanine nucleotide binding protein ↓ ↓ - ↓LOC_Os12g01760 F-box/LRR domain containing

protein↑ ↑ - -

LOC_Os11g01780 F-box/LRR-repeat protein ↑ ↑ - -LOC_Os07g14270 Calreticulin precursor protein ↓ ↓ - -LOC_Os12g38290 Metallothionein ↑ ↑ ↓ -

(Zhang et al., 2010)LOC_Os03g13540 Ser/Thr protein phosphatase ↑ ↑ ↑ -LOC_Os03g05390 Citrate transporter protein ↑ ↑ - -

(Yamaji et al., 2009)LOC_Os03g55290 GASR3 - Gibberellin-regulated ↑ ↑ - -LOC_Os10g38080 Putative Subtilisin homologue ↑ ↑ - ↓LOC_Os03g54790 ABC transporter ↑ ↑ ↑ -LOC_Os10g13940 MATE efflux protein ↑ ↑ - -LOC_Os10g42780 LrgB-like family protein ↑ ↑ - -LOC_Os02g09390 Cytochrome P450 ↑ ↑ - -LOC_Os02g53130 Nitrate reductase ↑ ↑ - -LOC_Os04g41750 Expressed protein ↑ ↑ - -

(Yamaji et al., 2009)(Xia et al., 2010)(Xia et al., 2011)

LOC_Os02g03900 (Nrat1) Metal transporter Nramp6 ↑ ↑ - ↓(Yamaji et al., 2009)(Huang et al., 2009)

LOC_Os06g48060 ABC transporter, STAR1 ↑ ↑ - ↓(Dong et al., 2010)

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LOC_Os12g38051 Metallothionein ↑ ↑ - ↓(Krill et al., 2010)

LOC_Os05g09440 Malic enzyme ↑ ↑ - -(Yokosho et al., 2011)

LOC_Os01g69010 MATE or FDR4 ↑ ↑ - -(Arenhart et al., 2013)

LOC_Os02g33820 ASR1 ↑ ↑ - ↓LOC_Os01g72910 ASR4 ↑ ↑ - ↓LOC_Os01g06720 ASR5 ↑ ↑ - ↓

37