GENE-39993; No. of pages: 9; 4C: Gene xxx (2014) xxx–xxx
Contents lists available at ScienceDirect
Gene journal homepage: www.elsevier.com/locate/gene
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Methods paper
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Hua Li a,b, Lei Wang a, Zhi Min Yang a,⁎ a
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Article history: Received 18 August 2014 Received in revised form 1 October 2014 Accepted 3 October 2014 Available online xxxx
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Keywords: Arabidopsis thaliana Iron deficiency Co-expression analysis PYE IRT1
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Department of Biochemistry and Molecular Biology, College of Life Science, Nanjing Agricultural University, Nanjing 210095, China Department of Plant Science, College of Life Science, Henan Agricultural University, Henan 450002, China
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Iron (Fe) is an essential element for plant growth and development. Iron deficiency results in abnormal metabolisms from respiration to photosynthesis. Exploration of Fe-deficient responsive genes and their networks is critically important to understand molecular mechanisms leading to the plant adaptation to soil Fe-limitation. Co-expression genes are a cluster of genes that have a similar expression pattern to execute relatively biological functions at a stage of development or under a certain environmental condition. They may share a common regulatory mechanism. In this study, we investigated Fe-starved-related co-expression genes from Arabidopsis. From the biological process GO annotation of TAIR (The Arabidopsis Information Resource), 180 iron-deficient responsive genes were detected. Using ATTED-II database, we generated six gene co-expression networks. Among these, two modules of PYE and IRT1 were successfully constructed. There are 30 co-expression genes that are incorporated in the two modules (12 in PYE-module and 18 in IRT1-module). Sixteen of the co-expression genes were well characterized. The remaining genes (14) are poorly or not functionally identified with iron stress. Validation of the 14 genes using real-time PCR showed differential expression under iron-deficiency. Most of the co-expression genes (23/30) could be validated in pye and fit mutant plants with iron-deficiency. We further identified iron-responsive cis-elements upstream of the co-expression genes and found that 22 out of 30 genes contain the iron-responsive motif IDE1. Furthermore, some auxin and ethylene-responsive elements were detected in the promoters of the co-expression genes. These results suggest that some of the genes can be also involved in iron stress response through the phytohormone-responsive pathways. © 2014 Published by Elsevier B.V.
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Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency
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Iron is an essential inorganic nutrient required for numerous metabolic and developmental processes in plants. However, its availability in many types of soil is limited because iron is usually present in fixed forms that are unavailable to plants (Marschner, 1995). Iron deficiency results in modification of many biological processes such as imbalanced redox reaction, abnormal respiration and photosynthesis, and altered root architecture. When plants encounter iron limitation, they may trigger various strategies to improve iron mobilization in soil and uptake into plants (Hindt and Guerinot, 2012). Iron abundance in plant tissues is regulated through uptake, translocation and recycling. In Arabidopsis (Strategy I plant species), iron is absorbed in three steps including rhizosphere acidification through H+-ATPases, ferric reductase oxidase 2
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1. Introduction
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Abbreviations: TAIR, The Arabidopsis Information Resource; FRO2, ferric reductase oxidase 2; IRT1, iron regulated transporter 1; ACOECIS, Arabidopsis co-expression associated with cis-regulatorymotifs;MR, mutual rank; ABRE,abscisic acidresponse element; ERE, ethylene responsive element; ARF, auxin response factor responsive; W-box, WRKY binding site. ⁎ Corresponding author at: College of Life Science, Nanjing Agricultural University, Nanjing, 210095, China. E-mail address: [email protected] (Z.M. Yang).
(FRO2)-meditated reduction of Fe (III) to Fe (II), and Fe (II) intake by iron regulated transporter 1 (IRT1); in contrast to Arabidopsis plants, the graminaceous species (Strategy II plants such as rice and wheat) acquire iron from soil through secretion of high-affinity Fe (III) chelator phytosiderophores (Hindt and Guerinot, 2012). Thus, exploration of mechanisms for iron uptake and accumulation is of great importance to understand the adaptation of plants to Fe limitation. At the molecular level, iron limitation induces a number of genes responsible for Fe uptake and translocation. Arabidopsis AtIRT1 coding for an iron transporter was identified as a major route for root iron acquisition (Vert et al., 2002). FIT was found to be required for transcription of FRO2/IRT1 (Colangelo and Guerinot, 2004). Recently, the genome-wide transcriptome analysis have unraveled many genes involved in iron uptake and homeostasis in plants (Kong and Yang, 2010; Schmidt and Buckhout, 2011; Schuler et al., 2011; Stein and Waters, 2011). To date, two major genes FIT (encoding FER-like iron-deficiency-induced bHLH transcription factor) and PYE (encoding bHLH transcription factor) are at the forefront of the research area (Hindt and Guerinot, 2012). Several other genes such as IRT1, FRO2, and AHA2 are under the control of FIT, which can interact with bHLH38 and bHLH39 to induce IRT1 and FRO2 expressions (Colangelo and Guerinot, 2004; Yuan et al., 2008). PYE-mediated system includes BTS (putative E3 ubiquitin ligase) that
http://dx.doi.org/10.1016/j.gene.2014.10.004 0378-1119/© 2014 Published by Elsevier B.V.
Please cite this article as: Li, H., et al., Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency, Gene (2014), http://dx.doi.org/10.1016/j.gene.2014.10.004
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Two independent datasets related to iron-responsive genes in plants were extracted and analyzed. One is from the Arabidopsis database (The Arabidopsis Information Resource, TAIR, http://www.arabidopsis.org/) and the other is from ATTED-II (Obayashi et al., 2007). ATTEDII provides gene-to-gene mutual ranks, correlation coefficients from 58 experiments,
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2.1. Extraction of genes related to iron stress response
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2. Materials and methods
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ATTED-II and ATCOECIS are available for gene co-expression and motif analysis (Obayashi et al., 2007; Vandepoele et al., 2009), but no report is available on analyzing gene co-expression networks with irondeficiency. In this paper, we report identification of co-expressed genes associated with iron uptake, allocation, homeostasis and regulatory networks in Arabidopsis. Two major modules, PYE-module and IRT1-module for iron-deficient response were constructed, from which, 14 poorly or functionally uncharacterized genes with irondeficiency have been identified. Validation analysis revealed that a vast majority of them responds to iron deficiency. Expression of most of the genes was confirmed in the pye and fit mutant plants. These genes will be potentially used for further genetic characterization as putative genes involved in Fe-deficient responses.
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forms a regulatory cascade to maintain iron homeostasis (Long et al., 2010). Moreover, there are many genes that are strongly induced by iron deficiency but unidentified (Schuler et al., 2011). These uncharacterized genes may have potential roles in iron uptake and accumulation through different pathways related to auxin, ethylene, nitric oxide or carbon monoxide (García et al., 2010, 2011; Kong et al., 2010; Li et al., 2013; Romera et al., 2011). Some genes under a certain environmental condition usually have a similar expression pattern to execute correlatively biological functions (Eison et al., 1998). These co-expression genes may share a common regulatory mechanism (e.g. motifs in their promoters) (Wang et al., 2009; Zheng et al., 2011). By extraction of tightly co-expressed genes, one may find some important or even novel genes associated with their special biological processes. For example, using co-expression approach, Han et al. (2012) identified 63 candidate genes of fatty acid biosynthesis and two transcription factors (TFs) AP1 and CRC. Information from gene co-expression may help to understand special molecular events. The model plants such as Arabidopsis and rice provides priority to construct and analyze gene co-expression networks (Fu and Xue, 2010; Han et al., 2012). Importantly, many different approaches have been developed recently to model the gene regulatory networks (Aoki et al., 2007; Schlitt and Brazma, 2007). Excellent databases such as
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Fig. 1. An outline of the analytical processes in this study.
Please cite this article as: Li, H., et al., Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency, Gene (2014), http://dx.doi.org/10.1016/j.gene.2014.10.004
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2.2. Construction of Arabidopsis gene co-expression networks relevant to iron stress
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2.3. RT-PCR analysis
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Real time-PCR and semi-quantitative PCR were performed to analyze gene transcripts based on the methods described previously (Guo et al., 2008). Briefly, total RNA was isolated by the method indicated above, and 1.0 μg RNA was used as templates for cDNA synthesis. Quantitative RT-PCR (qRT-PCR) was conducted on CFX96 Real-Time PCR Detection System (Bio-Rad). Amplification reaction was performed in a 25 μL mixture containing 5 ng template, 12.5 μL SYBR-Green PCR Mastermix (Toyoba, Japan) and 10 pmol primers. The temperature
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All experiments in the study were independently performed three times. Each result shown in the figures was the mean of at least three replicated treatments and each treatment contained at least 30–60 seedlings. The significant differences between treatments were
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2.5. Statistical analysis
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The corresponding gene sequences were obtained from TAIR (The Arabidopsis Information Resource, TAIR, http://www.arabidopsis.org/). Because cis-elements of higher plants are usually located in 500– 1000 bp upstream of the translation start site (TSS) of gene. The TSS and TATA-box were analyzed based on the method of Cui et al. (2009). We retrieved the promoter sequences of the co-expression genes with 1000 bp. The specific iron-responsive motifs IDE1 and IDE2 were obtained using the element sequences described previously (Kobayashi et al., 2003). Occurrence of known plant motifs of co-expression genes was located using a command-line version of Arabidopsis co-expression associated with cis-regulatory motifs (ACOECIS) (http://bioinformatics.psb.ugent.be/ATCOECIS/) (Vandepoele et al., 2009). ATCOECIS uses motifs enlisted in the PLACE and AGRIS motif databases to annotate promoters and computes for a set of genes the enrichment values for all mapped motifs together with statistical significance values. Only motifs with a frequency of at least 50% in one module and enrichment fold greater than 1.5 were regarded to be authentic. This frequency threshold level was set to filter out motifs that were not concentrated enough in co-expression genes.
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Gene co-expression networks were constructed with the analytical tool of ATTED-II (http://atted.jp/), from which the relationship of genes from Arabidopsis was analyzed based on all microarray datasets. Distance relationship was defined by MR (mutual rank) value. The co-expression gene was analyzed with CoExSearch in ATTED-II. Usually, when MR is b50, the correlation of genes is considered as “close”; however, when MR is N1000, the relationship between two genes is very “weak”. In this study, genes with MR b 1000 were considered as co-expression genes.
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2.4. Promoter analysis
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profile was 98 °C for 30 s, followed by 40 cycles at 98 °C for 2 s, 60 °C for 5 s and melt curve at 65 °C for 5 s. Data were analyzed using CFX Data Analysis Manager Software. The relative expression level was normalized to ACTIN2, which was used as the internal control, with the 2−△ CT method representing the relative quantification of gene expression.
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1388 GeneChips collected by AtGenExpress, and more than 20,000 publicly available files. For each file from ATTED-II, an anchor gene was denoted, with its Pearson's correlation coefficients with other genes being established. Thus, all genes co-expressed with the anchor gene can be considered as a co-expression group. To construct co-expression networks, genes corresponding to iron nutrition were retrieved from ATTED-II based on the GO annotations with the biological process. The genes included are those relevant to iron homeostasis, iron transport, response to iron, regulation of iron transport, and cellular response to iron starvation. For a single gene, it may be included in several GO annotations. The redundant genes in the collection were removed.
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Fig. 2. Co-expression analysis of 180 iron deficiency-associated genes. Yellow: flavonoid biosynthesis; green: amino sugar and nucleotide sugar; blue: starch and sucrose metabolism; white: non-annotation in KEGG; diamond: transcription factor; circle: non transcription factor. Each module contains at least four genes. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Please cite this article as: Li, H., et al., Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency, Gene (2014), http://dx.doi.org/10.1016/j.gene.2014.10.004
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An integrative framework was designed to illustrate the protocol of modeling the gene networks responsible for iron homeostasis in this study (Fig. 1). To analyze the gene co-expression networks, we first searched all iron-responsive genes based on the GO biological process annotation in the Arabidopsis database (The Arabidopsis Information Resource, TAIR, http://www.arabidopsis.org/). Following this step, a total of 180 genes were retrieved (Table S1), including those related to iron ion homeostasis, response to Fe deficiency, Fe transport, factors relevant to regulation of Fe transport and cellular response to Fe stress. We next analyzed the connection of these genes using the database ATTEDII (Obayashi and Kinoshita, 2009), and found that some genes are more closely related to one another. The highly inter-connected genes were clustered. Finally, the closely-related genes were grouped into six categories (Fig. 2). Among these, three were highlighted because they contained the genes PYE, IRT1 and FER1, which have been well characterized as regulators of iron homeostasis (Vert et al., 2002; Ravet et al., 2009; Long et al., 2010). As PYE, IRT1 and FER1 play crucial roles in regulating their downstream genes under iron-deficiency, each group with PYE, IRT1 and FER1 was named as PYE-module, IRT1-module and FER1module, respectively. All genes in these modules were named as “guide genes”. PYE, BTS, FRO3 and NRAMP4 were the guide genes in PYEmodule; IRT1, MTPA2, CYP82C4, At5g38820, At3g12900 and At1g74770 belonged to IRT1-module, and FER1, FER3, FER4 and ABC1 fell into FER1-module. FIT is also a critical transcription factor mediating genes for low-iron acclimation (Colangelo and Guerinot, 2004). Unexpectedly, it was not detected in any of the modules. This could be the result of no genes detected in the microarray dataset to co-express with FIT. However, as FIT is a direct regulator of IRT1 and FRO2, we also analyzed FIT further through the IRT1 module.
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3.2. Identification of genes co-expressing with guide genes
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ATTED-II is one of the excellent gene co-expression databases and provides two different ways to examine co-expression gene information including a gene list and a gene network view (Obayashi et al., 2007). The former is used for the “guide gene” approach to find relevant genes with one or more guide genes, while the latter is used for the “narrow-down” approach to examine internal relationships and identify the core gene among a set of genes (Obayashi and Kinoshita, 2009). To draw gene networks from a list of co-expressed genes, a threshold must be determined to define the co-expressed gene pairs. ATTED-II database uses a unique co-expression measure, namely mutual rank (MR) of the Pearson's correlation coefficient, which performs well to compare the co-expression strength for various guide genes under different conditions (Obayashi and Kinoshita, 2009). Based on the statistical MR value, genes with MR b 50 usually display a tight co-expression relationship, whereas those with MR N 1000 usually show a weak co-expressive correlation (Obayashi and Kinoshita, 2009). In this study, we used MR b 1000 to search for co-expression genes and each time was run with a single guide gene. It is shown that numerous co-expression genes were detected (Supplementary Table S2). Some relevant coexpression genes were incorporated into their respective modules. After strict screening, 9, 43 and 2 co-expression genes were finally identified and integrated into the PYE-module, IRT1-module and FER1-module, respectively (Supplementary Table S3). Because the co-expression genes generated from ATTED-II database occurred under conditions of normal growth and development, other
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3.3. Analysis of iron-responsive cis-elements in co-expression genes
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The difference in gene expression caused by iron starvation can be attributed to specific signals in plants (Hindt and Guerinot, 2012). Gene co-expression under Fe deficiency suggests that these genes may have similar responsive elements in their promoters. To investigate the possibility, two iron-deficient responsive elements IDE1 and IDE2 (Kobayashi et al., 2003) in the co-expression genes were analyzed. In PYE-module, ten co-expression genes were found to have IDE1 elements, while 12 out of 18 co-expression genes in IRT1-module were detected with IDE1 elements (Table 2). No IDE2 was found in any promoter of the co-expression genes. As not all co-expression genes from the two modules have IDE motifs, we then searched other elements in the promoters relevant to iron-deficient response. Using ATCOECIS tool, elements such as ABRE (abscisic acid response element), ERE (ethylene responsive element),
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than iron-deficiency, these genes were matched to the microarray datasets with iron deficiency (Dinneny et al., 2008). Only genes matched to those on microarray with two fold up- or down-regulated changes were considered as authentic iron-responsive co-expression genes. Finally, twelve and eighteen of the co-expression genes were detected and incorporated into the PYE-module and IRT1-module, respectively (Table 1). Unexpectedly, no gene was identified as members in FER1-module. Therefore, the PYE-module and IRT1-module were subject to further analysis.
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Table 1 t1:1 Co-expression genes in PYE-module and IRT1-module. Y: genes experimentally identified t1:2 to regulate iron homeostasis. N: genes remain to be characterized. t1:3
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statistically evaluated by standard deviation and one-way analysis of variance (ANOVA). The data between differently treated groups were compared statistically by ANOVA, followed by the least significant difference (LSD) test if the ANOVA result was significant at P b 0.05.
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t1:4
PYE-module Gene ID
Gene name
Guide gene At1g23020 At3g18290 At3g47640 At5g67330
FRO3 BTS PYE NRAMP4
Co-expression gene At2g42750 At3g56980 BHLH039 At4g16370 OPT3 At5g04150 BHLH101 At5g05250 At5g13740 ZIF1 At5g53450 ORG1 At5g67370 CGLD27
Fold
Identified
References
5.12 8.38 3.71 6.60
Y Y Y Y
Mukherjee et al. (2006) Long et al. (2010) Long et al. (2010) Lanquar et al. (2005)
4.13 5.56 10.28 6.74 4.71 8.24 6.85 12.09
N Y Y Y N Y N Y
Fold
Identified
3.89 36.57 4.32 2.34 10.84 5.99
N N Y Y Y N
0.42 2.42 0.42 0.49 6.58 5.56 2.62 13.20 2.43 11.35 6.80 5.85
N N N N N Y N N Y N Y N
Yuan et al. (2008) Stacey et al. (2008) Wang et al. (2013) Haydon et al. (2012) Urzica et al. (2012)
IRT1-module Gene ID Guide gene At1g74770 At3g12900 At3g58810 At4g19690 At4g31940 At5g38820
Gene name
MTPA2 IRT1 CYP82C4
Co-expression gene At1g22880 CEL5 At1g73120 At2g39040 At3g12540 At3g12820 MYB10 At3g56980 BHLH039 At3g61410 At3g61930 At4g30120 HMA3 At5g02780 GSTL1 At5g03570 IREG2 At5g13910 LEP
References
Arrivault et al. (2006) Vert et al. (2002) Murgia et al. (2011)
Yuan et al. (2008)
Morel et al. (2009) Schaaf et al. (2006)
Please cite this article as: Li, H., et al., Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency, Gene (2014), http://dx.doi.org/10.1016/j.gene.2014.10.004
t1:5 t1:6 t1:7 t1:8 t1:9 t1:10 t1:11 t1:12 t1:13 t1:14 t1:15 t1:16 t1:17 t1:18 t1:19 t1:20 t1:21 t1:22 t1:23 t1:24 t1:25 t1:26 t1:27 t1:28 t1:29 t1:30 t1:31 t1:32 t1:33 t1:34 t1:35 t1:36 t1:37 t1:38 t1:39 t1:40 t1:41 t1:42 t1:43 t1:44
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deficiency for 5 days, whereas five genes (At1g22880, At1g73120, At2g39040, At3g12540 and At5g13910) were shown to be depressed (Fig. 3). Among the genes up-regulated, gene At5g53450 was induced by 4.5 fold compared to the control. Other genes were moderately induced. Gene At3g12900 was not significantly induced in plants after a 5 day iron treatment. This was the case for gene At3g12540 that was slightly depressed but not significantly.
3.4. Experimental validation of extracted unidentified co-regulated genes under iron deficiency
3.5. Expression of co-regulated genes in pye and fit mutants under iron 287 deficiency 288
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To confirm the co-expressed genes identified here, the fourteen genes that have not been functionally characterized were analyzed using a quantitative real-time PCR. Nine genes (At1g74770, At2g42750, At3g12900, At3g61410, At3g61930, At5g05250, At5g38820, At5g53450 and At5g02780) were found to be induced in plants under iron-
Both PYE and FIT directly or indirectly regulate their downstream gene expression under iron deficiency. To understand the coexpression genes in PYE-module under iron-deficiency, we used publicly available data to examine the differentially expressed genes in pye mutants from the iron-starved microarray (Long et al., 2010). As shown
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Table 2 Iron-responsive cis-element IDE in the promoter regions of co-expression genes.
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t2:3
ID
Name
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PYE-module At3g47640
PYE
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At2g42750
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−236/−220
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At5g05250
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−200/−183
t2:8
At1g23020
FRO3
5.1
−494/−477
t2:9
At3g56980
BHLH039
5.6
t2:10
At5g67330
NRAMP4
6.6
t2:11
At5g04150
BHLH101
6.7
t2:12
At5g53450
ORG1
6.8
t2:15
At4g16370
OPT3
t2:16 t2:17 t2:18
IRT1-module At1g22880
CEL5
t2:19
At3g12540
t2:20
At4g19690
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At3g58810
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IRT1
MTPA2
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−291/−274 −26/−8 −318/−302
−988/−970 −442/−428
10.3
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−57/−38
2.3
−247/−230 −604/−586
4.3
−419/−410 −108/−90
BHLH039
5.6
−260/−242
At5g13910
LEP
5.9
−331/−313
t2:26
At3g12820
MYB10
6.6
−944/−926
t2:27
At5g03570
IREG2
6.8
−486/−470
t2:28
At4g31940
CYP82C4
10.8
−411/−394
t2:29
At5g02780
GSTL1
11.4
−156/−139
t2:30
At3g61930
13.2
−530/−513
t2:31
At3g12900
36.6
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At3g56980
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ARF (auxin response factor responsive), and W-box (WRKY binding site) were identified in the upstream of the co-expression genes (Supplementary Table S4). We further analyzed transcription factors (TFs) from microarray that bind to these elements under irondeficiency (Dinneny et al., 2008). It is shown that many of the TFs can be differentially regulated by iron deficiency (Supplementary Table S5).
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Alignment
Stand
ATCAAGCATGCTTCTTGC ATT AATCAT–CTTATGTC ATCAAGCATGCTTCTTGC GCTAAGCACGCTT–TCGC ATCAAGCATGCTTCTTGC ATTAAGCCATCTTCTTAC ATCAAGCATGCTTCTTGC ATACAACAAGCTTCATGC ATC–AAGCATGCTTCTTGC ATCCAAACATTCTTCTTTA ATCAAGCATGCTTCTTGC ATCGAGTCTTCTTCTTGG ATCAAGCATGCTTCT–TGC AGCAAGAATGGTACTCTGC ATCAAGCATGCTTCTTGC GTGAAGT–TGCTTCTTTC ATCAAGCATGCT–TCTTGC ATTAAGCCTCCTCTCTCTC ATCAAGCATGCTTCTTGC ATCA–GCATCCGACGTGG ATCA–AGCATGCTTCTTGC TTCAGAGCTTGGTTCTTGG
+
ATCAAGCATGCTTCTTGC ATCCATAAT–CTTCTTAC ATCAAG–CATGCTTCT–TGC ATCAAATCATTCTTCTCTTC ATCAAGCATGCTTCTTGC ATCTAGCTAGGTACTTTC ATCAA–GCATGCTTCTTGC TTGAATGCATTGTTCATGC ATCAA——GCATGCTTCTTGC ATCAAAAGCATAATGCTTTC ATCAAG–CATGCTTCTTGC AGAAAGTCATGATACATGC ATCAAGCATGCT–TCTTGC ATGAAACATGCTATCAAGT ATC–AAGCATGCTTCTTGC ATCCAAACATTCTTCTTTA ATCAAGCATGCTTCTT–GC ATTATGCATTATTCTACGT ATCAAGCATGCTTCTTGC ATAATGAAT–CTTCTTGA ATCAAGCATGCTTCTTGC CTTATGCATGGATCTTGC ATCAAGCATGCTTCTTGC ATGAACCAAGCCTCTTCC ATCAAGCATGCTTCTTGC ACCTCGCATGCCCCATGC ATCAAGCATGCTTCTTGC CACAAGCGTGCATAATGC
−
+ + − + − + + − + +
− + − + − + + + − + + + +
Please cite this article as: Li, H., et al., Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency, Gene (2014), http://dx.doi.org/10.1016/j.gene.2014.10.004
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Fig. 3. Validation of unidentified co-expression genes using quantitative real-time PCR. Two week-old Arabidopsis seedlings were subjected to iron-deficiency for 5 days. After that, total RNA was extracted and transcripts were analyzed. Vertical bars represent the standard deviation of the mean. Asterisks indicate that mean values are of significant difference of gene transcripts between the iron sufficient and deficient treatments (p b 0.05).
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in Supplementary Table S6, 16 co-expression genes were presented. Of these, 11 were shown in PYE-module, and the other 5 genes (IRT1, MTPA2, At3g12900, MYB10, and IREG2) were recovered in IRT1-module. Examination of genes in fit mutants from the iron-starved microarray (Colangelo and Guerinot, 2004) revealed 12 co-expression genes belonging to IRT1-module.
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The genome-wide profiling of transcriptome in iron-starved plants provides valuable information on hundreds of genes involved in plant response to iron-deficiency (Buckhout et al., 2009; O' Rourke et al., 2009; Zamboni et al., 2012). These iron stress-responsive genes are of
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great importance to understand iron uptake and metabolism at the level of molecular biology and systematic biology. However, the differential gene expression in iron-stress plants does not mean that all genes participate in the regulation of iron-deficient response. Possibly, only some of the genes are directly involved in the process, and most of them are likely related to the secondary or subsequent responses. The analytical method of gene co-expression networks provides a useful approach that allows us to screen some co-regulated genes from bulk genes under a certain environmental stress. Indeed, the data from the co-expression analysis can be used in a variety of experimental designs for further gene identification (Aoki et al., 2007; Usadel et al., 2009). From the biological process GO annotation of TAIR (The Arabidopsis Information Resource), 180 iron-deficient responsive genes were
Please cite this article as: Li, H., et al., Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency, Gene (2014), http://dx.doi.org/10.1016/j.gene.2014.10.004
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specifically regulated by brassinolide (Goda et al., 2004); and CEL5 involves carbohydrate metabolic process (Land et al., 2012). At2g39040 responds to oxidative stress and could be induced by IAA (Goda et al., 2004). Recent studies have shown that regulation of plant adaptation to iron deficiency can be achieved by gaseous molecules such as ethylene and nitric oxide (García et al., 2010, 2011; Meiser et al., 2011) and carbon monoxide (Kong et al., 2010; Li et al., 2013). At3g12540 is differentially expressed in root epidermis of hairy versus hairless mutant lines (Bruex et al., 2012). Several other genes such as At5g05250, At5g38820, At3g12900, At1g74770, At1g73120, At3g61410, and At3g61930 genes are yet to be characterized and are involved in iron stress response. FIT is one of the critical transcription factors that directly or indirectly regulates plant iron-deficient response through controlling transcription of iron-responsive genes (Colangelo and Guerinot, 2004; Meiser et al., 2011). In this study, however, no gene was found to be accompanied by FIT. This result is consistent with the recent report of a coexpression network of ferrome (Schmidt and Buckhout, 2011). As FIT directly regulates IRT1 expression under iron deficiency, the coexpression genes in IRT1-module could be considered to be closely related to the FIT-responsive network. The assumption was supported by the gene expression in fit mutants, as it is shown that most of the co-expression genes in IRT1-module were detected, and their expression was altered in the mutant compared to wild-type (Colangelo and Guerinot, 2004; Table S6). In the case of iron deficiency, all genes in the IRT1-module had lower expressions in fit mutant compared to wild type, while the expression level of all genes in PYE-module were higher in pye mutant than the wild type. It is shown that FIT and PYE
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retrieved. Using ATTED-II database, six gene co-expression networks were constructed. Three modules, namely PYE-module, IRT1-module and FER1-module were highlighted, because the core (or guide) genes PYE, IRT1 and FER1 have been well functionally characterized (Vert et al., 2002; Ravet et al., 2009; Long et al., 2010). Unfortunately, we did not detect any co-expression gene for FER1-module. Nevertheless, no guide gene could be found in modules IV and V, although module IV is the largest group with 46 genes. Therefore, we focused on analyzing the co-expression genes in PYE-module and IRT1-module. A total of thirty co-expression genes (including PYE and IRT1) were detected in the modules. Twelve genes were found to co-express with PYE and eighteen genes co-express with IRT1. We further examined the coexpression genes in the two modules. Sixteen genes including PYE, BTS, FRO3, NRAMP4, BHLH039, BHLH101, ZIF1, OPT3, and CGLD27 in PYE-module and IRT1, MTPA2, CYP82C4, HMA3, BHLH039, IREG2, and MYB10 in IRT1-module have been well characterized (Vert et al., 2002; Lanquar et al., 2005; Arrivault et al., 2006; Stacey et al., 2008; Yuan et al., 2008; Morel et al., 2009; Long et al., 2010; Murgia et al., 2011). The remaining genes (At2g42750, At5g05250 and ORG1 in PYEmodule and At5g38820, At3g12900, At1g74770, CEL5, At2g39040, At3g12540, At1g73120, At3g61410, LEP, GSTL1 and At3g61930 in IRT1module) are poorly or not functionally identified. However, all these genes were experimentally analyzed and most of them were found to be induced in response to iron deficiency (Fig. 3). These genes can be considered as potential genes used to further identify their involvement in iron deficient response, although their functional responses to iron deficiency are not or poorly understood. For example, At2g42750 is
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Fig. 4. The hypothetic network under iron deficiency. Diamond: transcription factor (TF); ellipse: non TF; red graph: related to iron deficiency by genetic experiments; black graph: related to iron deficiency by co-expression analysis; arrows from A to B: A gene changes expression of B gene; a line between A and B: A interacted with B.
Please cite this article as: Li, H., et al., Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency, Gene (2014), http://dx.doi.org/10.1016/j.gene.2014.10.004
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Z. M. Yang designed and carried out the study, and drafted the manuscript. Hua Li carried out gene extraction and analysis. Lei Wang participated in seedling culture and analysis of gene expression. All authors read and approved the final manuscript. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gene.2014.10.004.
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The present study demonstrated a new approach on how to identify the functional modules or genes in iron-deficient plants by construction of gene co-expression networks. The ATTED-II database was employed to examine the correlation of complex regulation of iron-stress responsive genes. Importantly, a group of putative genes were found to be enriched in the PYE-module and IRT1-module but have not been well characterized in response to iron-deficiency. Further characterization of these genes will provide insights into the biological functions and interaction of genes under iron-deficiency and help in the understanding of the mechanism for plant adaptation to iron limitation.
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García, M.J., Suárez, V., Romera, R.J., Alcántara, E., Pérez-Vicente, R., 2011. A new model involving ethylene, nitric oxide and Fe to explain the regulation of Fe-acquisition genes in strategy I plants. Plant Physiol. Biochem. 49, 537–544. Goda, H., Sawa, S., Asami, T., Fujioka, S., Shimada, Y., Yoshida, S., 2004. Comprehensive comparison of auxin-regulated and brassinosteroid-regulated genes in Arabidopsis. Plant Physiol. 134, 1555–1573. Guo, K., Xia, K., Yang, Z.M., 2008. Regulation of tomato lateral root development by carbon monoxide and involvement in auxin and nitric oxide. J. Exp. Bot. 59, 3443–3452. Han, X., Yin, L., Xue, H., 2012. Co-expression analysis identifies CRC and AP1 the regulator of Arabidopsis fatty acid biosynthesis. J. Integr. Plant Biol. 54, 486–499. Haydon, M.J., Kawachi, M., Wirtz, M., Hillmer, S., Hell, R., Krämer, U., 2012. Vacuolar nicotianamine has critical and distinct roles under iron deficiency and for zinc sequestration in Arabidopsis. Plant Cell 24, 724–737. Hindt, M.N., Guerinot, M.L., 2012. Getting a sense for signals: regulation of the plant iron deficiency response. Biochim. Biophys. Acta 1823, 1521–1530. Huang, Y.C., Chang, Y.L., Hsu, J.J., Chuang, H.W., 2008. Transcriptome analysis of auxinregulated genes of Arabidopsis thaliana. Gene 420, 118–124. Kobayashi, T., Nakayama, Y., Itai, R.N., Nakanishi, H., Yoshihara, T., Mori, S., Nishizawa, N.K., 2003. Identification of novel cis-acting elements, IDE1 and IDE2, of the barley IDS2 gene promoter conferring iron deficiency-inducible, root-specific expression in heterogeneous tobacco plants. Plant J. 36, 780–793. Kong, W.W., Yang, Z.M., 2010. Identification of iron-deficiency responsive microRNA genes and cis-elements in Arabidopsis. Plant Physiol. Biochem. 48, 153–159. Kong, W.W., Zhang, L.P., Guo, K., Lui, Z.P., Yang, Z.M., 2010. Carbon monoxide improves adaptation of Arabidopsis to iron deficiency. Plant Biotechnol. J. 7, 1–12. Land, P., Li, W., Wen, T.N., Schmidt, W., 2012. Quantitative phosphoproteome profiling of iron-deficienct Arabidopsis roots. Plant Physiol. 159, 403–417. Lanquar, V., Lelievre, F., Bolte, S., Hames, C., Alcon, C., Neumann, D., Vansuyt, G., Curie, C., Schroder, A., Kramer, U., Barbier-Brygoo, H., Thomine, S., 2005. Mobilization of vacuolar iron by AtNRAMP3 and AtNRAMP4 is essential for seed germination on low iron. EMBO J. 24, 4041–4051. Li, H., Song, J.B., Zhao, W.T., Yang, Z.M., 2013. AtHO1 is involved in iron homeostasis in a NO-dependent manner. Plant Cell Physiol. 54, 1105–1117. Long, T.A., Tsukagoshi, H., Busch, W., Lahner, B., Salt, D.E., Benfey, P.N., 2010. The bHLH transcription factor POPEYE regulates response to iron deficiency in Arabidopsis roots. Plant Cell 22, 2219–2236. Marschner, H., 1995. Mineral Nutrition of Higher Plants. Academic Press, London. Meiser, J., Lingam, S., Bauer, P., 2011. Posttranslational regulation of the iron deficiency basic helix–loop–helix transcription factor FIT is affected by iron and nitric oxide. Plant Physiol. 157, 2154–2166. Morel, M., Crouzet, J., Gravot, A., Auroy, P., Leonhardt, N., Vavasseu, A., Richaud, P., 2009. AtHMA3, a P1B-ATPase allowing Cd/Zn/Co/Pb vacuolar storage in Arabidopsis. Plant Physiol. 149, 894–904. Mukherjee, I., Campbell, N.H., Ash, J.S., Connolly, E.L., 2006. Expression profiling of the Arabidopsis ferric chelate reductase (FRO) gene family reveals differential regulation by iron and copper. Planta 223, 1178–1190. Murgia, I., Tarantino, D., Soave, C., Morandini, P., 2011. Arabidopsis CYP82C4 expression is dependent on Fe availability and circadian rhythm, and correlates with genes involved in the early Fe deficiency response. J. Plant Physiol. 168, 894–902. Obayashi, T., Kinoshita, K., 2009. Rank of correlation coefficient as a comparable measure for biological significance of gene coexpression. DNA Res. 16, 249–260. Obayashi, T., Kinoshita, K., Nakai, K., Shibaoka, M., Hayashi, S., Saeki, M., Shibata, D., Saito, K., Ohta, H., 2007. ATTED-II: a database of coexpressed genes and cis-elements for identifying co-regulated gene groups in Arabidopsis. Nucleic Acids Res. 35, D863–D869. Palmer, C.M., Hindt, M.N., Schmidt, H., Clemens, S., Guerinot, M.L., 2013. MYB10 and MYB72 are required for growth under iron-limiting conditions. PLoS Genet. 9, e1003953. Ravet, K., Touraine, B., Boucherez, J., Briat, J.F., Gaymard, F., Cellier, F., 2009. Ferritins control interaction between iron homeostasis and oxidative stress in Arabidopsis. Plant J. 57, 400–412. Romera, F.J., García, M.J., Alcántara, E., Pérez-Vicente, R., 2011. Latest findings about the interplay of auxin, ethylene and nitric oxide in the regulation of Fe deficiency responses by strategy I plants. Plant Signal. Behav. 6, 167–170. Schaaf, G., Honsbein, A., Meda, A.R., Kirchner, S., Wipf, D., von Wirén, N., 2006. AtIREG2 encodes a tonoplast transport protein involved in iron-dependent nickel detoxification in Arabidopsis thaliana roots. J. Biol. Chem. 281, 25532–25540. Schlitt, T., Brazma, A., 2007. Current approaches to gene regulatory network modeling. BMC Bioinforma. 8, S9. Schmidt, W., Buckhout, T.J., 2011. A hitchhiker's guide to the Arabidopsis ferrome. Plant Physiol. Biochem. 49, 462–470. Schuler, M., Keller, A., Backes, C., Philippar, K., Lenhof, H.P., Bauer, P., 2011. Transcriptome analysis by GeneTrail revealed regulation of functional categories in response to alterations of iron homeostasis in Arabidopsis thaliana. BMC Plant Biol. 11, 87. Sivitz, A.B., Hermand, V., Curie, C., Vert, G., 2012. Arabidopsis bHLH100 and bHLH101 control iron homeostasis via a FIT-independent pathway. PLoS ONE 7, e44843. Stacey, M.G., Patel, A., McClain, W.E., Mathieu, M., Remley, M., Rogers, E.E., Gassmann, W., Blevins, D.G., Stacey, G., 2008. The Arabidopsis AtOPT3 protein functions in metal homeostasis and movement of iron to developing seeds. Plant Physiol. 146, 589–601. Stein, R.J., Waters, B.M., 2011. Use of natural variation reveals core genes in the transcriptome of iron-deficient Arabidopsis thaliana roots. J. Exp. Bot. 63, 1039–1055. Urzica, E.I., Casero, D., Yamasaki, H., Hsieh, S.I., Adler, L.N., Karpowicz, S.J., Blaby-Haas, C.E., Clarke, S.G., Loo, J.A., Pellegrini, M., Merchant, S.S., 2012. Systems and trans-system level analysis identifies conserved iron deficiency responses in the plant lineage. Plant Cell 24, 3921–3948.
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positively and negatively control their own co-expression genes respectively. Notably, PYE also regulates the expression of five genes in IRT1module (IRT1, MTPA2, At3g12900, MYB10 and IREG2), but the transcriptional level of IRT1, MTPA2 and IREG2 were lower in pye mutant than in the wild type when exposed to iron-deficiency. This result can be explained by the fact that IRT1, MTPA2 and IREG2, located in IRT1module, are also controlled by FIT. Our analysis has demonstrated that BHLH039 is an overlapping gene between PYE-module and IRT1module (Table 1). Because BHLH039 with BHLH101 can interact with FIT (Sivitz et al., 2012), there is a link between PYE-module and IRT1module. Based on these observations, two independent but connected iron-responsive networks have been summarized (Fig. 4). In PYEmodule, the central component is PYE transcription factor, which connects and regulates 11 co-expression genes, while in IRT1-module there are 18 co-expression genes that are linked to and regulated by the central gene FIT. Notably, BHLH039 is shared by the two modules. Because many of the co-expression genes in their promoter regions contain several other elements such as ARF-binding motif and ethylene responsive elements (ERE), it is possible that the co-expression genes participate in the response to iron-deficiency through auxin- or ethylene-responsive pathway (Romera et al., 2011).
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Methods paper
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Article history: Received 18 August 2014 Received in revised form 1 October 2014 Accepted 3 October 2014 Available online xxxx
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Keywords: Arabidopsis thaliana Iron deficiency Co-expression analysis PYE IRT1
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Department of Biochemistry and Molecular Biology, College of Life Science, Nanjing Agricultural University, Nanjing 210095, China Department of Plant Science, College of Life Science, Henan Agricultural University, Henan 450002, China
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Iron (Fe) is an essential element for plant growth and development. Iron deficiency results in abnormal metabolisms from respiration to photosynthesis. Exploration of Fe-deficient responsive genes and their networks is critically important to understand molecular mechanisms leading to the plant adaptation to soil Fe-limitation. Co-expression genes are a cluster of genes that have a similar expression pattern to execute relatively biological functions at a stage of development or under a certain environmental condition. They may share a common regulatory mechanism. In this study, we investigated Fe-starved-related co-expression genes from Arabidopsis. From the biological process GO annotation of TAIR (The Arabidopsis Information Resource), 180 iron-deficient responsive genes were detected. Using ATTED-II database, we generated six gene co-expression networks. Among these, two modules of PYE and IRT1 were successfully constructed. There are 30 co-expression genes that are incorporated in the two modules (12 in PYE-module and 18 in IRT1-module). Sixteen of the co-expression genes were well characterized. The remaining genes (14) are poorly or not functionally identified with iron stress. Validation of the 14 genes using real-time PCR showed differential expression under iron-deficiency. Most of the co-expression genes (23/30) could be validated in pye and fit mutant plants with iron-deficiency. We further identified iron-responsive cis-elements upstream of the co-expression genes and found that 22 out of 30 genes contain the iron-responsive motif IDE1. Furthermore, some auxin and ethylene-responsive elements were detected in the promoters of the co-expression genes. These results suggest that some of the genes can be also involved in iron stress response through the phytohormone-responsive pathways. © 2014 Published by Elsevier B.V.
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Iron is an essential inorganic nutrient required for numerous metabolic and developmental processes in plants. However, its availability in many types of soil is limited because iron is usually present in fixed forms that are unavailable to plants (Marschner, 1995). Iron deficiency results in modification of many biological processes such as imbalanced redox reaction, abnormal respiration and photosynthesis, and altered root architecture. When plants encounter iron limitation, they may trigger various strategies to improve iron mobilization in soil and uptake into plants (Hindt and Guerinot, 2012). Iron abundance in plant tissues is regulated through uptake, translocation and recycling. In Arabidopsis (Strategy I plant species), iron is absorbed in three steps including rhizosphere acidification through H+-ATPases, ferric reductase oxidase 2
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Abbreviations: TAIR, The Arabidopsis Information Resource; FRO2, ferric reductase oxidase 2; IRT1, iron regulated transporter 1; ACOECIS, Arabidopsis co-expression associated with cis-regulatorymotifs;MR, mutual rank; ABRE,abscisic acidresponse element; ERE, ethylene responsive element; ARF, auxin response factor responsive; W-box, WRKY binding site. ⁎ Corresponding author at: College of Life Science, Nanjing Agricultural University, Nanjing, 210095, China. E-mail address: [email protected] (Z.M. Yang).
(FRO2)-meditated reduction of Fe (III) to Fe (II), and Fe (II) intake by iron regulated transporter 1 (IRT1); in contrast to Arabidopsis plants, the graminaceous species (Strategy II plants such as rice and wheat) acquire iron from soil through secretion of high-affinity Fe (III) chelator phytosiderophores (Hindt and Guerinot, 2012). Thus, exploration of mechanisms for iron uptake and accumulation is of great importance to understand the adaptation of plants to Fe limitation. At the molecular level, iron limitation induces a number of genes responsible for Fe uptake and translocation. Arabidopsis AtIRT1 coding for an iron transporter was identified as a major route for root iron acquisition (Vert et al., 2002). FIT was found to be required for transcription of FRO2/IRT1 (Colangelo and Guerinot, 2004). Recently, the genome-wide transcriptome analysis have unraveled many genes involved in iron uptake and homeostasis in plants (Kong and Yang, 2010; Schmidt and Buckhout, 2011; Schuler et al., 2011; Stein and Waters, 2011). To date, two major genes FIT (encoding FER-like iron-deficiency-induced bHLH transcription factor) and PYE (encoding bHLH transcription factor) are at the forefront of the research area (Hindt and Guerinot, 2012). Several other genes such as IRT1, FRO2, and AHA2 are under the control of FIT, which can interact with bHLH38 and bHLH39 to induce IRT1 and FRO2 expressions (Colangelo and Guerinot, 2004; Yuan et al., 2008). PYE-mediated system includes BTS (putative E3 ubiquitin ligase) that
http://dx.doi.org/10.1016/j.gene.2014.10.004 0378-1119/© 2014 Published by Elsevier B.V.
Please cite this article as: Li, H., et al., Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency, Gene (2014), http://dx.doi.org/10.1016/j.gene.2014.10.004
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Two independent datasets related to iron-responsive genes in plants were extracted and analyzed. One is from the Arabidopsis database (The Arabidopsis Information Resource, TAIR, http://www.arabidopsis.org/) and the other is from ATTED-II (Obayashi et al., 2007). ATTEDII provides gene-to-gene mutual ranks, correlation coefficients from 58 experiments,
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ATTED-II and ATCOECIS are available for gene co-expression and motif analysis (Obayashi et al., 2007; Vandepoele et al., 2009), but no report is available on analyzing gene co-expression networks with irondeficiency. In this paper, we report identification of co-expressed genes associated with iron uptake, allocation, homeostasis and regulatory networks in Arabidopsis. Two major modules, PYE-module and IRT1-module for iron-deficient response were constructed, from which, 14 poorly or functionally uncharacterized genes with irondeficiency have been identified. Validation analysis revealed that a vast majority of them responds to iron deficiency. Expression of most of the genes was confirmed in the pye and fit mutant plants. These genes will be potentially used for further genetic characterization as putative genes involved in Fe-deficient responses.
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forms a regulatory cascade to maintain iron homeostasis (Long et al., 2010). Moreover, there are many genes that are strongly induced by iron deficiency but unidentified (Schuler et al., 2011). These uncharacterized genes may have potential roles in iron uptake and accumulation through different pathways related to auxin, ethylene, nitric oxide or carbon monoxide (García et al., 2010, 2011; Kong et al., 2010; Li et al., 2013; Romera et al., 2011). Some genes under a certain environmental condition usually have a similar expression pattern to execute correlatively biological functions (Eison et al., 1998). These co-expression genes may share a common regulatory mechanism (e.g. motifs in their promoters) (Wang et al., 2009; Zheng et al., 2011). By extraction of tightly co-expressed genes, one may find some important or even novel genes associated with their special biological processes. For example, using co-expression approach, Han et al. (2012) identified 63 candidate genes of fatty acid biosynthesis and two transcription factors (TFs) AP1 and CRC. Information from gene co-expression may help to understand special molecular events. The model plants such as Arabidopsis and rice provides priority to construct and analyze gene co-expression networks (Fu and Xue, 2010; Han et al., 2012). Importantly, many different approaches have been developed recently to model the gene regulatory networks (Aoki et al., 2007; Schlitt and Brazma, 2007). Excellent databases such as
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Fig. 1. An outline of the analytical processes in this study.
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Real time-PCR and semi-quantitative PCR were performed to analyze gene transcripts based on the methods described previously (Guo et al., 2008). Briefly, total RNA was isolated by the method indicated above, and 1.0 μg RNA was used as templates for cDNA synthesis. Quantitative RT-PCR (qRT-PCR) was conducted on CFX96 Real-Time PCR Detection System (Bio-Rad). Amplification reaction was performed in a 25 μL mixture containing 5 ng template, 12.5 μL SYBR-Green PCR Mastermix (Toyoba, Japan) and 10 pmol primers. The temperature
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All experiments in the study were independently performed three times. Each result shown in the figures was the mean of at least three replicated treatments and each treatment contained at least 30–60 seedlings. The significant differences between treatments were
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The corresponding gene sequences were obtained from TAIR (The Arabidopsis Information Resource, TAIR, http://www.arabidopsis.org/). Because cis-elements of higher plants are usually located in 500– 1000 bp upstream of the translation start site (TSS) of gene. The TSS and TATA-box were analyzed based on the method of Cui et al. (2009). We retrieved the promoter sequences of the co-expression genes with 1000 bp. The specific iron-responsive motifs IDE1 and IDE2 were obtained using the element sequences described previously (Kobayashi et al., 2003). Occurrence of known plant motifs of co-expression genes was located using a command-line version of Arabidopsis co-expression associated with cis-regulatory motifs (ACOECIS) (http://bioinformatics.psb.ugent.be/ATCOECIS/) (Vandepoele et al., 2009). ATCOECIS uses motifs enlisted in the PLACE and AGRIS motif databases to annotate promoters and computes for a set of genes the enrichment values for all mapped motifs together with statistical significance values. Only motifs with a frequency of at least 50% in one module and enrichment fold greater than 1.5 were regarded to be authentic. This frequency threshold level was set to filter out motifs that were not concentrated enough in co-expression genes.
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Gene co-expression networks were constructed with the analytical tool of ATTED-II (http://atted.jp/), from which the relationship of genes from Arabidopsis was analyzed based on all microarray datasets. Distance relationship was defined by MR (mutual rank) value. The co-expression gene was analyzed with CoExSearch in ATTED-II. Usually, when MR is b50, the correlation of genes is considered as “close”; however, when MR is N1000, the relationship between two genes is very “weak”. In this study, genes with MR b 1000 were considered as co-expression genes.
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profile was 98 °C for 30 s, followed by 40 cycles at 98 °C for 2 s, 60 °C for 5 s and melt curve at 65 °C for 5 s. Data were analyzed using CFX Data Analysis Manager Software. The relative expression level was normalized to ACTIN2, which was used as the internal control, with the 2−△ CT method representing the relative quantification of gene expression.
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1388 GeneChips collected by AtGenExpress, and more than 20,000 publicly available files. For each file from ATTED-II, an anchor gene was denoted, with its Pearson's correlation coefficients with other genes being established. Thus, all genes co-expressed with the anchor gene can be considered as a co-expression group. To construct co-expression networks, genes corresponding to iron nutrition were retrieved from ATTED-II based on the GO annotations with the biological process. The genes included are those relevant to iron homeostasis, iron transport, response to iron, regulation of iron transport, and cellular response to iron starvation. For a single gene, it may be included in several GO annotations. The redundant genes in the collection were removed.
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Fig. 2. Co-expression analysis of 180 iron deficiency-associated genes. Yellow: flavonoid biosynthesis; green: amino sugar and nucleotide sugar; blue: starch and sucrose metabolism; white: non-annotation in KEGG; diamond: transcription factor; circle: non transcription factor. Each module contains at least four genes. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Please cite this article as: Li, H., et al., Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency, Gene (2014), http://dx.doi.org/10.1016/j.gene.2014.10.004
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An integrative framework was designed to illustrate the protocol of modeling the gene networks responsible for iron homeostasis in this study (Fig. 1). To analyze the gene co-expression networks, we first searched all iron-responsive genes based on the GO biological process annotation in the Arabidopsis database (The Arabidopsis Information Resource, TAIR, http://www.arabidopsis.org/). Following this step, a total of 180 genes were retrieved (Table S1), including those related to iron ion homeostasis, response to Fe deficiency, Fe transport, factors relevant to regulation of Fe transport and cellular response to Fe stress. We next analyzed the connection of these genes using the database ATTEDII (Obayashi and Kinoshita, 2009), and found that some genes are more closely related to one another. The highly inter-connected genes were clustered. Finally, the closely-related genes were grouped into six categories (Fig. 2). Among these, three were highlighted because they contained the genes PYE, IRT1 and FER1, which have been well characterized as regulators of iron homeostasis (Vert et al., 2002; Ravet et al., 2009; Long et al., 2010). As PYE, IRT1 and FER1 play crucial roles in regulating their downstream genes under iron-deficiency, each group with PYE, IRT1 and FER1 was named as PYE-module, IRT1-module and FER1module, respectively. All genes in these modules were named as “guide genes”. PYE, BTS, FRO3 and NRAMP4 were the guide genes in PYEmodule; IRT1, MTPA2, CYP82C4, At5g38820, At3g12900 and At1g74770 belonged to IRT1-module, and FER1, FER3, FER4 and ABC1 fell into FER1-module. FIT is also a critical transcription factor mediating genes for low-iron acclimation (Colangelo and Guerinot, 2004). Unexpectedly, it was not detected in any of the modules. This could be the result of no genes detected in the microarray dataset to co-express with FIT. However, as FIT is a direct regulator of IRT1 and FRO2, we also analyzed FIT further through the IRT1 module.
216
3.2. Identification of genes co-expressing with guide genes
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ATTED-II is one of the excellent gene co-expression databases and provides two different ways to examine co-expression gene information including a gene list and a gene network view (Obayashi et al., 2007). The former is used for the “guide gene” approach to find relevant genes with one or more guide genes, while the latter is used for the “narrow-down” approach to examine internal relationships and identify the core gene among a set of genes (Obayashi and Kinoshita, 2009). To draw gene networks from a list of co-expressed genes, a threshold must be determined to define the co-expressed gene pairs. ATTED-II database uses a unique co-expression measure, namely mutual rank (MR) of the Pearson's correlation coefficient, which performs well to compare the co-expression strength for various guide genes under different conditions (Obayashi and Kinoshita, 2009). Based on the statistical MR value, genes with MR b 50 usually display a tight co-expression relationship, whereas those with MR N 1000 usually show a weak co-expressive correlation (Obayashi and Kinoshita, 2009). In this study, we used MR b 1000 to search for co-expression genes and each time was run with a single guide gene. It is shown that numerous co-expression genes were detected (Supplementary Table S2). Some relevant coexpression genes were incorporated into their respective modules. After strict screening, 9, 43 and 2 co-expression genes were finally identified and integrated into the PYE-module, IRT1-module and FER1-module, respectively (Supplementary Table S3). Because the co-expression genes generated from ATTED-II database occurred under conditions of normal growth and development, other
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3.3. Analysis of iron-responsive cis-elements in co-expression genes
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The difference in gene expression caused by iron starvation can be attributed to specific signals in plants (Hindt and Guerinot, 2012). Gene co-expression under Fe deficiency suggests that these genes may have similar responsive elements in their promoters. To investigate the possibility, two iron-deficient responsive elements IDE1 and IDE2 (Kobayashi et al., 2003) in the co-expression genes were analyzed. In PYE-module, ten co-expression genes were found to have IDE1 elements, while 12 out of 18 co-expression genes in IRT1-module were detected with IDE1 elements (Table 2). No IDE2 was found in any promoter of the co-expression genes. As not all co-expression genes from the two modules have IDE motifs, we then searched other elements in the promoters relevant to iron-deficient response. Using ATCOECIS tool, elements such as ABRE (abscisic acid response element), ERE (ethylene responsive element),
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than iron-deficiency, these genes were matched to the microarray datasets with iron deficiency (Dinneny et al., 2008). Only genes matched to those on microarray with two fold up- or down-regulated changes were considered as authentic iron-responsive co-expression genes. Finally, twelve and eighteen of the co-expression genes were detected and incorporated into the PYE-module and IRT1-module, respectively (Table 1). Unexpectedly, no gene was identified as members in FER1-module. Therefore, the PYE-module and IRT1-module were subject to further analysis.
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Table 1 t1:1 Co-expression genes in PYE-module and IRT1-module. Y: genes experimentally identified t1:2 to regulate iron homeostasis. N: genes remain to be characterized. t1:3
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statistically evaluated by standard deviation and one-way analysis of variance (ANOVA). The data between differently treated groups were compared statistically by ANOVA, followed by the least significant difference (LSD) test if the ANOVA result was significant at P b 0.05.
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t1:4
PYE-module Gene ID
Gene name
Guide gene At1g23020 At3g18290 At3g47640 At5g67330
FRO3 BTS PYE NRAMP4
Co-expression gene At2g42750 At3g56980 BHLH039 At4g16370 OPT3 At5g04150 BHLH101 At5g05250 At5g13740 ZIF1 At5g53450 ORG1 At5g67370 CGLD27
Fold
Identified
References
5.12 8.38 3.71 6.60
Y Y Y Y
Mukherjee et al. (2006) Long et al. (2010) Long et al. (2010) Lanquar et al. (2005)
4.13 5.56 10.28 6.74 4.71 8.24 6.85 12.09
N Y Y Y N Y N Y
Fold
Identified
3.89 36.57 4.32 2.34 10.84 5.99
N N Y Y Y N
0.42 2.42 0.42 0.49 6.58 5.56 2.62 13.20 2.43 11.35 6.80 5.85
N N N N N Y N N Y N Y N
Yuan et al. (2008) Stacey et al. (2008) Wang et al. (2013) Haydon et al. (2012) Urzica et al. (2012)
IRT1-module Gene ID Guide gene At1g74770 At3g12900 At3g58810 At4g19690 At4g31940 At5g38820
Gene name
MTPA2 IRT1 CYP82C4
Co-expression gene At1g22880 CEL5 At1g73120 At2g39040 At3g12540 At3g12820 MYB10 At3g56980 BHLH039 At3g61410 At3g61930 At4g30120 HMA3 At5g02780 GSTL1 At5g03570 IREG2 At5g13910 LEP
References
Arrivault et al. (2006) Vert et al. (2002) Murgia et al. (2011)
Yuan et al. (2008)
Morel et al. (2009) Schaaf et al. (2006)
Please cite this article as: Li, H., et al., Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency, Gene (2014), http://dx.doi.org/10.1016/j.gene.2014.10.004
t1:5 t1:6 t1:7 t1:8 t1:9 t1:10 t1:11 t1:12 t1:13 t1:14 t1:15 t1:16 t1:17 t1:18 t1:19 t1:20 t1:21 t1:22 t1:23 t1:24 t1:25 t1:26 t1:27 t1:28 t1:29 t1:30 t1:31 t1:32 t1:33 t1:34 t1:35 t1:36 t1:37 t1:38 t1:39 t1:40 t1:41 t1:42 t1:43 t1:44
H. Li et al. / Gene xxx (2014) xxx–xxx
5
deficiency for 5 days, whereas five genes (At1g22880, At1g73120, At2g39040, At3g12540 and At5g13910) were shown to be depressed (Fig. 3). Among the genes up-regulated, gene At5g53450 was induced by 4.5 fold compared to the control. Other genes were moderately induced. Gene At3g12900 was not significantly induced in plants after a 5 day iron treatment. This was the case for gene At3g12540 that was slightly depressed but not significantly.
3.4. Experimental validation of extracted unidentified co-regulated genes under iron deficiency
3.5. Expression of co-regulated genes in pye and fit mutants under iron 287 deficiency 288
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To confirm the co-expressed genes identified here, the fourteen genes that have not been functionally characterized were analyzed using a quantitative real-time PCR. Nine genes (At1g74770, At2g42750, At3g12900, At3g61410, At3g61930, At5g05250, At5g38820, At5g53450 and At5g02780) were found to be induced in plants under iron-
Both PYE and FIT directly or indirectly regulate their downstream gene expression under iron deficiency. To understand the coexpression genes in PYE-module under iron-deficiency, we used publicly available data to examine the differentially expressed genes in pye mutants from the iron-starved microarray (Long et al., 2010). As shown
t2:1 t2:2
Table 2 Iron-responsive cis-element IDE in the promoter regions of co-expression genes.
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t2:3
ID
Name
t2:4 t2:5
PYE-module At3g47640
PYE
t2:6
O
272
Changed
Site
3.7
−67/−51
At2g42750
4.1
−236/−220
t2:7
At5g05250
4.7
−200/−183
t2:8
At1g23020
FRO3
5.1
−494/−477
t2:9
At3g56980
BHLH039
5.6
t2:10
At5g67330
NRAMP4
6.6
t2:11
At5g04150
BHLH101
6.7
t2:12
At5g53450
ORG1
6.8
t2:15
At4g16370
OPT3
t2:16 t2:17 t2:18
IRT1-module At1g22880
CEL5
t2:19
At3g12540
t2:20
At4g19690
t2:22
At3g58810
t2:23
IRT1
MTPA2
U
t2:21
8.4
R
BTS
R
At3g18290
N C O
t2:14
E C
T
−260/−242
E
t2:13
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Q1
−291/−274 −26/−8 −318/−302
−988/−970 −442/−428
10.3
−103/−85
0.4
−829/−813
0.5
−57/−38
2.3
−247/−230 −604/−586
4.3
−419/−410 −108/−90
BHLH039
5.6
−260/−242
At5g13910
LEP
5.9
−331/−313
t2:26
At3g12820
MYB10
6.6
−944/−926
t2:27
At5g03570
IREG2
6.8
−486/−470
t2:28
At4g31940
CYP82C4
10.8
−411/−394
t2:29
At5g02780
GSTL1
11.4
−156/−139
t2:30
At3g61930
13.2
−530/−513
t2:31
At3g12900
36.6
−225/−208
t2:24
At3g56980
t2:25
R O
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ARF (auxin response factor responsive), and W-box (WRKY binding site) were identified in the upstream of the co-expression genes (Supplementary Table S4). We further analyzed transcription factors (TFs) from microarray that bind to these elements under irondeficiency (Dinneny et al., 2008). It is shown that many of the TFs can be differentially regulated by iron deficiency (Supplementary Table S5).
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Alignment
Stand
ATCAAGCATGCTTCTTGC ATT AATCAT–CTTATGTC ATCAAGCATGCTTCTTGC GCTAAGCACGCTT–TCGC ATCAAGCATGCTTCTTGC ATTAAGCCATCTTCTTAC ATCAAGCATGCTTCTTGC ATACAACAAGCTTCATGC ATC–AAGCATGCTTCTTGC ATCCAAACATTCTTCTTTA ATCAAGCATGCTTCTTGC ATCGAGTCTTCTTCTTGG ATCAAGCATGCTTCT–TGC AGCAAGAATGGTACTCTGC ATCAAGCATGCTTCTTGC GTGAAGT–TGCTTCTTTC ATCAAGCATGCT–TCTTGC ATTAAGCCTCCTCTCTCTC ATCAAGCATGCTTCTTGC ATCA–GCATCCGACGTGG ATCA–AGCATGCTTCTTGC TTCAGAGCTTGGTTCTTGG
+
ATCAAGCATGCTTCTTGC ATCCATAAT–CTTCTTAC ATCAAG–CATGCTTCT–TGC ATCAAATCATTCTTCTCTTC ATCAAGCATGCTTCTTGC ATCTAGCTAGGTACTTTC ATCAA–GCATGCTTCTTGC TTGAATGCATTGTTCATGC ATCAA——GCATGCTTCTTGC ATCAAAAGCATAATGCTTTC ATCAAG–CATGCTTCTTGC AGAAAGTCATGATACATGC ATCAAGCATGCT–TCTTGC ATGAAACATGCTATCAAGT ATC–AAGCATGCTTCTTGC ATCCAAACATTCTTCTTTA ATCAAGCATGCTTCTT–GC ATTATGCATTATTCTACGT ATCAAGCATGCTTCTTGC ATAATGAAT–CTTCTTGA ATCAAGCATGCTTCTTGC CTTATGCATGGATCTTGC ATCAAGCATGCTTCTTGC ATGAACCAAGCCTCTTCC ATCAAGCATGCTTCTTGC ACCTCGCATGCCCCATGC ATCAAGCATGCTTCTTGC CACAAGCGTGCATAATGC
−
+ + − + − + + − + +
− + − + − + + + − + + + +
Please cite this article as: Li, H., et al., Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency, Gene (2014), http://dx.doi.org/10.1016/j.gene.2014.10.004
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Fig. 3. Validation of unidentified co-expression genes using quantitative real-time PCR. Two week-old Arabidopsis seedlings were subjected to iron-deficiency for 5 days. After that, total RNA was extracted and transcripts were analyzed. Vertical bars represent the standard deviation of the mean. Asterisks indicate that mean values are of significant difference of gene transcripts between the iron sufficient and deficient treatments (p b 0.05).
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in Supplementary Table S6, 16 co-expression genes were presented. Of these, 11 were shown in PYE-module, and the other 5 genes (IRT1, MTPA2, At3g12900, MYB10, and IREG2) were recovered in IRT1-module. Examination of genes in fit mutants from the iron-starved microarray (Colangelo and Guerinot, 2004) revealed 12 co-expression genes belonging to IRT1-module.
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The genome-wide profiling of transcriptome in iron-starved plants provides valuable information on hundreds of genes involved in plant response to iron-deficiency (Buckhout et al., 2009; O' Rourke et al., 2009; Zamboni et al., 2012). These iron stress-responsive genes are of
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great importance to understand iron uptake and metabolism at the level of molecular biology and systematic biology. However, the differential gene expression in iron-stress plants does not mean that all genes participate in the regulation of iron-deficient response. Possibly, only some of the genes are directly involved in the process, and most of them are likely related to the secondary or subsequent responses. The analytical method of gene co-expression networks provides a useful approach that allows us to screen some co-regulated genes from bulk genes under a certain environmental stress. Indeed, the data from the co-expression analysis can be used in a variety of experimental designs for further gene identification (Aoki et al., 2007; Usadel et al., 2009). From the biological process GO annotation of TAIR (The Arabidopsis Information Resource), 180 iron-deficient responsive genes were
Please cite this article as: Li, H., et al., Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency, Gene (2014), http://dx.doi.org/10.1016/j.gene.2014.10.004
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specifically regulated by brassinolide (Goda et al., 2004); and CEL5 involves carbohydrate metabolic process (Land et al., 2012). At2g39040 responds to oxidative stress and could be induced by IAA (Goda et al., 2004). Recent studies have shown that regulation of plant adaptation to iron deficiency can be achieved by gaseous molecules such as ethylene and nitric oxide (García et al., 2010, 2011; Meiser et al., 2011) and carbon monoxide (Kong et al., 2010; Li et al., 2013). At3g12540 is differentially expressed in root epidermis of hairy versus hairless mutant lines (Bruex et al., 2012). Several other genes such as At5g05250, At5g38820, At3g12900, At1g74770, At1g73120, At3g61410, and At3g61930 genes are yet to be characterized and are involved in iron stress response. FIT is one of the critical transcription factors that directly or indirectly regulates plant iron-deficient response through controlling transcription of iron-responsive genes (Colangelo and Guerinot, 2004; Meiser et al., 2011). In this study, however, no gene was found to be accompanied by FIT. This result is consistent with the recent report of a coexpression network of ferrome (Schmidt and Buckhout, 2011). As FIT directly regulates IRT1 expression under iron deficiency, the coexpression genes in IRT1-module could be considered to be closely related to the FIT-responsive network. The assumption was supported by the gene expression in fit mutants, as it is shown that most of the co-expression genes in IRT1-module were detected, and their expression was altered in the mutant compared to wild-type (Colangelo and Guerinot, 2004; Table S6). In the case of iron deficiency, all genes in the IRT1-module had lower expressions in fit mutant compared to wild type, while the expression level of all genes in PYE-module were higher in pye mutant than the wild type. It is shown that FIT and PYE
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retrieved. Using ATTED-II database, six gene co-expression networks were constructed. Three modules, namely PYE-module, IRT1-module and FER1-module were highlighted, because the core (or guide) genes PYE, IRT1 and FER1 have been well functionally characterized (Vert et al., 2002; Ravet et al., 2009; Long et al., 2010). Unfortunately, we did not detect any co-expression gene for FER1-module. Nevertheless, no guide gene could be found in modules IV and V, although module IV is the largest group with 46 genes. Therefore, we focused on analyzing the co-expression genes in PYE-module and IRT1-module. A total of thirty co-expression genes (including PYE and IRT1) were detected in the modules. Twelve genes were found to co-express with PYE and eighteen genes co-express with IRT1. We further examined the coexpression genes in the two modules. Sixteen genes including PYE, BTS, FRO3, NRAMP4, BHLH039, BHLH101, ZIF1, OPT3, and CGLD27 in PYE-module and IRT1, MTPA2, CYP82C4, HMA3, BHLH039, IREG2, and MYB10 in IRT1-module have been well characterized (Vert et al., 2002; Lanquar et al., 2005; Arrivault et al., 2006; Stacey et al., 2008; Yuan et al., 2008; Morel et al., 2009; Long et al., 2010; Murgia et al., 2011). The remaining genes (At2g42750, At5g05250 and ORG1 in PYEmodule and At5g38820, At3g12900, At1g74770, CEL5, At2g39040, At3g12540, At1g73120, At3g61410, LEP, GSTL1 and At3g61930 in IRT1module) are poorly or not functionally identified. However, all these genes were experimentally analyzed and most of them were found to be induced in response to iron deficiency (Fig. 3). These genes can be considered as potential genes used to further identify their involvement in iron deficient response, although their functional responses to iron deficiency are not or poorly understood. For example, At2g42750 is
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Fig. 4. The hypothetic network under iron deficiency. Diamond: transcription factor (TF); ellipse: non TF; red graph: related to iron deficiency by genetic experiments; black graph: related to iron deficiency by co-expression analysis; arrows from A to B: A gene changes expression of B gene; a line between A and B: A interacted with B.
Please cite this article as: Li, H., et al., Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency, Gene (2014), http://dx.doi.org/10.1016/j.gene.2014.10.004
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Authors' contributions
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Z. M. Yang designed and carried out the study, and drafted the manuscript. Hua Li carried out gene extraction and analysis. Lei Wang participated in seedling culture and analysis of gene expression. All authors read and approved the final manuscript. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gene.2014.10.004.
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The present study demonstrated a new approach on how to identify the functional modules or genes in iron-deficient plants by construction of gene co-expression networks. The ATTED-II database was employed to examine the correlation of complex regulation of iron-stress responsive genes. Importantly, a group of putative genes were found to be enriched in the PYE-module and IRT1-module but have not been well characterized in response to iron-deficiency. Further characterization of these genes will provide insights into the biological functions and interaction of genes under iron-deficiency and help in the understanding of the mechanism for plant adaptation to iron limitation.
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positively and negatively control their own co-expression genes respectively. Notably, PYE also regulates the expression of five genes in IRT1module (IRT1, MTPA2, At3g12900, MYB10 and IREG2), but the transcriptional level of IRT1, MTPA2 and IREG2 were lower in pye mutant than in the wild type when exposed to iron-deficiency. This result can be explained by the fact that IRT1, MTPA2 and IREG2, located in IRT1module, are also controlled by FIT. Our analysis has demonstrated that BHLH039 is an overlapping gene between PYE-module and IRT1module (Table 1). Because BHLH039 with BHLH101 can interact with FIT (Sivitz et al., 2012), there is a link between PYE-module and IRT1module. Based on these observations, two independent but connected iron-responsive networks have been summarized (Fig. 4). In PYEmodule, the central component is PYE transcription factor, which connects and regulates 11 co-expression genes, while in IRT1-module there are 18 co-expression genes that are linked to and regulated by the central gene FIT. Notably, BHLH039 is shared by the two modules. Because many of the co-expression genes in their promoter regions contain several other elements such as ARF-binding motif and ethylene responsive elements (ERE), it is possible that the co-expression genes participate in the response to iron-deficiency through auxin- or ethylene-responsive pathway (Romera et al., 2011).
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Please cite this article as: Li, H., et al., Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency, Gene (2014), http://dx.doi.org/10.1016/j.gene.2014.10.004
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