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First published online December 23, 2005; 10.1104/pp.105.067868 Plant Physiology 140:349-364 (2006) © 2006 American Society of Plant Biologists Proteomic Analysis of Different Mutant Genotypes of Arabidopsis Led to the Identification of 11 Proteins Correlating with Adventitious Root Development1,[W]Laboratoire de Biologie Cellulaire, Institut National de la Recherche Agronomique, 78026 Versailles cedex, France (C.S., C.B.); Umeå Plant Science Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, 90183 Umea, Sweden (C.S., G.S., C.B.); and Unité Mixte de Recherche de Génétique Végétale, Institut National de la Recherche Scientifique/Centre National de la Recherche Scientifique/Université Paris-Sud/Institut National Agronomique Paris-Grignon, 91190 Gif-sur-Yvette, France (L.N., T.B., H.C., M.-P.J., M.D., M.Z.)
A lack of competence to form adventitious roots by cuttings or explants in vitro occurs routinely and is an obstacle for the clonal propagation and rapid fixation of elite genotypes. Adventitious rooting is known to be a quantitative genetic trait. We performed a proteomic analysis of Arabidopsis (Arabidopsis thaliana) mutants affected in their ability to develop adventitious roots in order to identify associated molecular markers that could be used to select genotypes for their rooting ability and/or to get further insight into the molecular mechanisms controlling adventitious rooting. Comparison of two-dimensional gel electrophoresis protein profiles resulted in the identification of 11 proteins whose abundance could be either positively or negatively correlated with endogenous auxin content, the number of adventitious root primordia, and/or the number of mature adventitious roots. One protein was negatively correlated only to the number of root primordia and two were negatively correlated to the number of mature adventitious roots. Two putative chaperone proteins were positively correlated only to the number of primordia, and, interestingly, three auxin-inducible GH3-like proteins were positively correlated with the number of mature adventitious roots. The others were correlated with more than one parameter. The 11 proteins are predicted to be involved in different biological processes, including the regulation of auxin homeostasis and light-associated metabolic pathways. The results identify regulatory pathways associated with adventitious root formation and represent valuable markers that might be used for the future identification of genotypes with better rooting abilities.
In dicotyledonous plants, adventitious roots can be defined as roots that develop from organs such as leaves and stems under unusual circumstances. Adventitious root formation is a key step in vegetative propagation of woody or horticultural species, and problems associated with rooting of cuttings frequently result in significant economic losses (De Klerk et al., 1999
While the physiology of adventitious root formation is reasonably well known, the genetic and molecular mechanisms involved are still poorly understood. The few genetic and molecular studies of adventitious rooting that have been undertaken have shown that it is a heritable character, and quantitative trait loci analyses of adventitious rooting in trees (Han et al., 1994
The argonaute1 (ago1) mutant was first characterized as a leaf developmental mutant (Bohmert et al., 1998
This approach has already been successfully used for the characterization of Arabidopsis developmental mutants (Santoni et al., 1994 In this article, we describe the analysis and comparison of 2-D protein profiles of hypocotyls of ago1-3, sur1-3, sur2-1, and sur2-1ago1-3 Arabidopsis mutants during initiation of adventitious roots. This showed that, although AGO1 is involved in the regulation of gene expression through the miRNA pathway, its mutation does not induce more variations in hypocotyls than a mutation in SUR1 or SUR2. We also showed significant differences between the sur1 and sur2 protein profiles, although the two genes act in the same biosynthesis pathway. Finally, we identified 11 proteins, including three auxin-inducible GH3-like proteins, whose content correlated either positively or negatively with early and/or late phases of adventitious root development.
Analysis of 2-D Protein Patterns of the Different Genotypes
This work describes proteomic variations between the ago1-3, sur1-3, and sur2-1 Arabidopsis mutants and the sur2-1ago1-3 double mutant, with particular reference to the early developmental events associated with adventitious root initiation in the hypocotyl. All four genotypes behave differently in terms of adventitious root development. The auxin overproducers sur1-3 and sur2-1 spontaneously develop adventitious roots on the hypocotyl either in the light (Boerjan et al., 1995
Seeds were germinated in the dark and young seedlings were etiolated until they were about 5 mm and then transferred to the light for 48 h, as described previously (Sorin et al., 2005
We first estimated the number of proteins that varied significantly between genotypes (Table I). After spot detection, 2-D gels were aligned and matched to a reference gel created by Progenesis software, where 1,147 reproducible spots were identified. Out of a total of 1,147 spots analyzed, a similar percentage was significantly affected by the sur1-3 or the sur2-1 mutation, 6.6% in sur1-3 (Columbia [Col]-0) and 7.4% in sur2-1 (Wassilewskija [Ws]), compared to their corresponding wild types, Col-0 and Ws, respectively.
As the sur1-3 and sur2-1 mutants are in two different genetic backgrounds (Col-0 and Ws, respectively), spots displaying significant ecotype variation were removed prior to comparison of the 2-D profiles (Table I). Nineteen spots were shown to be variable in both sur1-3 and sur2-1, which represents 32% and 31% of the variable spots in sur1-3 and sur2-1, respectively. Analysis of the ago1-3 (Col-0) versus wild-type (Col-0) 2-D profiles showed that 7.1% of the spots were affected by the mutation (Table I). Thus, although the AGO1 gene is involved in the regulation of many genes, including various transcription factors, the variability observed in the 2-D profile of soluble proteins of the ago1-3 hypocotyl remained in the same range as that observed in the hypocotyls of the two superroot mutants. We also compared variations observed in ago1-3 versus wild type (Col-0) to those in sur1-3 versus wild type (Col-0) and in sur2-1 versus wild type (Ws) after removal of the spots variable between the two wild-type ecotypes Ws and Col-0 (Table I). Interestingly, we could see that 37 spots were commonly affected by the ago1-3 and sur1-3 mutations, which represents on average 50% of the variable spots in ago1-3 and sur1-3 compared to their wild types. Three spots were absent in the wild type (Col-0) and appeared in both sur1-3 and ago1-3, and one spot varied in opposite ways in sur1-3 and ago1-3. In the comparison between ago1-3/wild type (Col-0) and sur2-1/wild type (Ws), 14 spots were commonly affected by sur2-1 and ago1-3 mutations. This indicates that there are more than 50% less common variable spots in ago1-3/wild type (Col-0) and sur2-1/wild type (Ws) than in ago1-3/wild type (Col-0) and sur1-3/wild type (Col-0). Three of them varied in opposite ways in sur2-1 and ago1-3 compared to their respective wild types.
The sur2-1ago1-3 double mutant derived from a cross between a homozygote sur2-1 plant in a Ws ecotype and a plant heterozygote for the ago1-3 mutation in a Col-0 background. This recombinant genetic background will be referred to as recombinant genotype (RG) in the remainder of the article. The characterization of the double mutant sur2-1ago1-3 (RG) showed that they produced more auxin than the wild type and the single ago1-3 mutant, but less than sur2-1 (RG) and developed no, or very few, adventitious roots (Table II; Sorin et al., 2005
Correlation of Spot Intensity with the Auxin Content and/or the Adventitious Rooting Process
To identify proteins associated with adventitious root formation, we computed Pearson correlations of spot intensities with free IAA content, number of adventitious root primordia 2 d after seedling transfer to light, and number of adventitious roots 7 d after transfer to light. These different parameters are reported in Table II and were defined either based on a previous characterization of the mutants (Sorin et al., 2005 Because sur1-3 and ago1-3 are sterile, the double mutant sur1-3ago1-3 could only be unambiguously identified in the 2-week-old progeny of double heterozygotes grown in light (Camus, 1999). It was impossible to distinguish the phenotype of the double mutant sur1-3ago1-3 from the single mutant ago1-3 at the young stages of development used for proteomic analysis (data not shown). In addition, as a consequence of the strong phenotype of sur1-3, it was impossible to determine the number of adventitious roots 7 d after transfer to light because there were too many. Therefore, we preferred to eliminate sur1-3 from the correlation analysis. We are in the process of creating an inducible sur1 mutant that hopefully should allow easier identification of double mutants and completion of this analysis. Only the spots that were shown to be significantly variable after variance analysis were used for correlation analysis. Pearson correlation coefficients were computed between the mean of the relative intensity in the six genotypes and the different parameters. The results of the correlations are reported in Table III. Among the variable proteins that were affected by at least one mutation, 18 showed a significant correlation (P < 0.01) with at least one parameter. Positively or negatively correlated spots were in approximately the same amount for each parameter.
From the 192 spots that were significantly variable, only 110 were identifiable on preparative gels stained with SYPRO ruby protein gel stain (see "Materials and Methods") for identification via liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Among these 110, several did not give enough protein for proper sequencing or were degraded. After LC-MS/MS analysis, only 50 could be unambiguously identified (Table IV). For several spots, several proteins matched the sequence data and were not reported in Table IV. Nevertheless, they can be found in Supplemental Table I, where detailed sequence data are provided. These data will be made available together with quantitative data on the freely accessible database PROTICdb (Ferry-Dumazet et al., 2005
Seventeen proteins were related to metabolism, 10 of which were putatively involved in energy/carbon metabolism and five linked to nitrogen metabolism. Nine proteins were putatively involved in stress responses, four related to oxidative stress, and another four to the glucosinolate metabolism and biosynthesis. Four proteins associated with hormone metabolism were identified as well as proteins involved in protein folding, protein degradation, protein glycosylation, cytoskeleton, cell wall biosynthesis, and few proteins of unknown function. Four (At3g01500, ATCG00490, At2g21330, and At1g53240) out of the 10 proteins related to energy and carbon metabolism were up-regulated in ago1-3, and one (At2g21330) was up-regulated in sur2-1ago1-3. At1g31390, a putative fructokinase, was also found up-regulated in sur2-1ago1-3, but since the induction level (1.45) was just below the cutoff level of 1.5, it appears in Table IV as nonsignificantly variable. In contrast, five proteins (At1g06680, At1g32060, At2g21330, At2g38970, and At1g31390) of the same category were down-regulated in sur2-1.
Twelve proteins were significantly variable in sur1-3 compared to Col-0 but were not affected by the sur2-1 mutation, whereas 18 proteins were significantly variable in sur2-1 compared to Ws but were not affected by the sur1-3 mutation. Seven proteins were affected by both mutations and were always modified in the same way (i.e. either up-regulated or down-regulated) in both mutant genotypes. At1g62380 and At3g11830 (a putative 1-aminocyclopropane-1-carboxylic acid oxidase and a putative T-complex protein 1 Interestingly, two lectins (At3g16450 and At3g16470) similar to myrosinase-binding proteins were identified. One of them (At3g16470) may have been posttranslationally modified as it was found in two different locations (see spots 1,871 and 1,875 in Fig. 1). They were both significantly variable in ago1-3, but only At3g16450 was significantly down-regulated in sur2-1ago1-3 (RG). At3g16450 was significantly down-regulated in sur1-3 compared to Col-0, but no significant variation was observed in sur2-1 compared to Ws. Both putative At3g16470 isoforms were down-regulated in ago1-3 compared to Col-0. Interestingly, the isoform corresponding to spot 1,875 was down-regulated in sur1-3 compared to Col-0 but not in sur2-1 compared to Ws, and it was the opposite for spot 1,871. Three different auxin-inducible GH3-like proteins (GH3-3/At2g23170, GH3-5/AtGH3a/At4g27260, and GH3-6/DFL1/At5g54510) were up-regulated in sur2-1 and down-regulated in sur2-1ago1-3 (RG; Table IV; Figs. 2A and 3B ). Surprisingly, only one of these GH3-like proteins appeared to significantly accumulate in sur1-3 (Table IV).
The behavior of the two lectin proteins and two GH3-like proteins again highlighted differences between the sur1-3 and sur2-1 mutants, although both mutations affect genes sequentially involved in the same biosynthesis pathway and induce auxin overproduction. Out of the 18 correlated spots, 11 could be identified (Tables III and IV; Fig. 2). Five of these were negatively correlated with at least one parameter (Table III). Two proteins from the energy/carbon metabolism group (At1g32060 and At4g38970) were negatively correlated to adventitious root number. At4g38970 was also negatively correlated to the free IAA content. This was also the case for one protein related to protein degradation (At3g18490), also annotated as a putative chloroplast nucleoid DNA-binding protein. At1g32060 was negatively correlated to the three parameters as it correlated also with free IAA content and the number of adventitious root primordia. Two proteins related to stress responses were negatively correlated, the first one (At4g25100) to the number of primordia 2 d after transfer to light and the second (At5g20630) to the number of adventitious roots 7 d after transfer to light. Among the identified proteins, six were positively correlated with one or more parameters. One protein related to glucosinolate metabolism (CORI-7/AtST5a/At1g74100), which was up-regulated in both sur1-3 and sur2-1, was positively correlated with both free IAA content and adventitious root primordia 2 d after transfer to light. Two putative chaperone proteins were positively correlated to the number of primordia 48 h after transfer to light. The three GH3-like proteins were all positively correlated with the number of adventitious roots 7 d after germination but were surprisingly not correlated with free IAA content, although they are known to be auxin-inducible proteins.
Because GH3-like proteins (GH3-3/At2g23170, GH3-5/AtGH3-a/At4g27260, and GH3-6/DFL1/At5g54510) that were positively correlated with adventitious root number belong to an auxin-inducible protein family and were recently shown to be auxin-conjugating enzymes (Staswick et al., 2002
The objectives of the proteomic analysis presented here were to identify gene markers regulating adventitious rooting in Arabidopsis. We analyzed 2-D patterns of soluble proteins of Arabidopsis mutants differing in their auxin content and/or their adventitious rooting ability. The statistical analysis allowed us to restrict the initial 1,147 spots to 50 that showed significant variation and that could be identified by LC-MS/MS. Eleven of them were correlated to either the endogenous free IAA content, the number of adventitious root primordia after 2 d in light, and/or the number of adventitious roots 7 d after transfer to light.
The protein pattern of the different mutants was first compared to their respective wild types, and this led to interesting observations regarding the effect of their mutations. Comparing 2-D gels, the ago1-3 mutant and its wild type (Col-0) revealed that less than 10% of the spots varied. Since AGO1 is involved in the regulation of gene expression through the miRNA pathway (Vaucheret et al., 2004
Identification of variable proteins showed that several cellular functions were affected by ago1-3. One of the interesting features was the up-regulation of several proteins involved in energy and carbon metabolism. Up-regulation of some of the proteins linked directly or indirectly to photosynthesis in the ago1-3 mutant is in agreement with the ago1-3 mutant being hypersensitive to light (Sorin et al., 2005
The analysis of the sur1-3 and sur2-1 mutants interestingly showed that, although both mutants were altered in the same biosynthesis pathway and displayed very similar phenotypes in young seedlings (Boerjan et al., 1995 The proteins that varied significantly were submitted to correlation analysis in order to find those that were related to adventitious root formation. A Pearson correlation analysis of spot intensity with the three physiological parameters (free IAA content, mean number of adventitious root primordia after 2 d of light, and mean number of adventitious roots after 7 d of light) was performed. Eleven proteins were correlated with at least one parameter.
As one could expect in the case of a developmental process regulated by auxin, proteins involved in the control of auxin homeostasis were identified. The three GH3 proteins, GH3-3/At2g23170, GH3-5/AtGH3-a/At4g27260, and GH3-6/DFL1/At5g54510, were significantly positively correlated with adventitious root number 7 d after transfer to light. Expression of these GH3 genes was lower in the ago1-3 mutant compared to Col-0 and in the sur2-1ago1-3 (RG) mutant compared to sur2-1 (RG). The lower level of expression in the ago1-3 background could be explained by the lower level of endogenous free IAA (Table II; Sorin et al., 2005
Among the other correlated proteins, two were related to energy and carbon metabolism and they were both negatively correlated to adventitious rooting. This is in agreement with data obtained by microarray analyses from Brinker et al. (2004)
Finally, several proteins either positively or negatively correlated were putative chaperones or stress-related proteins. Although it is difficult at this point to discuss the potential role of these proteins in adventitious root development, our results confirm at the protein level the observations made at the transcriptional level by Brinker et al. (2004)
Interestingly, and although these proteins were not correlated to adventitious rooting, we could find some overlap among the protein identified here and the genes described to be potentially associated with adventitious root formation in P. contorta (Brinker et al., 2004
In conclusion, the proteomic analysis of ago1-3, sur1-3, sur2-1, and the sur2-1ago1-3 double mutant allowed us to identify proteins whose expression was altered by the mutations, particularly in regard to the adventitious rooting process. We identified auxin-related proteins and light-related proteins positively or negatively correlated to adventitious root formation. Several other proteins related to stress responses, protein degradation, or cytoskeleton function were correlated to at least one of the studied parameters. As similar functions were affected during adventitious root formation in P. contorta (Brinker et al., 2004
Plant Material
ago1-3, sur1-3, and sur2-1 mutants were identified in Col-0 and Ws Arabidopsis (Arabidopsis thaliana L. Heyhn.) ecotypes, respectively (Boerjan et al., 1995 ago1-3 and sur1-3 mutants, which are sterile and kept as heterozygotes, were compared to their wild-type siblings, Col-0; sur2-1 was compared to the Ws wild-type ecotype. ago1-3sur2-1 double mutants were compared to their sur2-1 siblings in the recombinant Ws/Col-0 background (RG). For simplification, the background (Col-0, Ws, or RG) will always be indicated in parentheses after the genotype.
Seeds from the different genotypes were sterilized and sown in vitro as described previously (Santoni et al., 1994
The protein extraction method was derived from Damerval et al. (1986)
Thirty-five micrograms of protein were mixed together with R2D2 buffer (Mechin et al., 2003
For protein identification, a preparative gel containing 150 µg of protein was prepared and stained with SYPRO ruby protein gel stain (Bio-Rad). Staining visualization was performed with the use of a dark reader transilluminator DR190M (blue light source 400500 nm; Clare Chemical Research). Spots were picked out and the acrylamide pieces were collected in 96-well microplates. In-gel digestion was performed with the Progest system (Genomic Solution) according to a standard trypsin protocol. Briefly, gel pieces were washed and then subsequently digested with 125 ng of modified trypsin (Promega) during 5 h. The peptides were extracted with 30 µL of 5% trifluoroacetic acid (TFA), 10% acetonitrile (ACN), then 30 µL of 0.2% TFA, 83% ACN. Peptide extracts were dried in a vacuum centrifuge and resuspended in 20 µL of 0.1% TFA, 3% ACN. The peptides were separated on HPLC Famos-Switchos II-Ultimate (LC Packings-Dionex). Sample (5 µL) was loaded on a PEPMAP C18 column (5 µm, 75 µm x 15 cm; LC Packings-Dionex) after a 3-min preconcentration step at 5 µL min1 on a micro precolumn cartridge (300 µm x 5 mm). The separation was achieved with a linear gradient from 5% to 30% B for 25 min at 200 nL min1. Buffers were 0.1% HCOOH, 3% ACN (A) and 0.1% HCOOH, 0.95% ACN (B). The LCQ deca xp+ (Thermofinnigan) was used with a nanoelectrospray interface. Ionization (1.2- to 1.4-kV ionization potential) was performed with liquid junction and a noncoated capillary probe (New Objective). Peptide ions were analyzed by the nth-dependent method as follows: (1) full MS scan (m/z 5001500); (2) ZoomScan (scan of the two major ions with higher resolution); and (3) MS/MS of these two ions. Data were then analyzed with Bioworks 3.1 and the Arabidopsis protein sequences database downloaded from the National Center for Biotechnology Information (NCBI; http://www.ncbi.nlm.nih.gov) or the plant genome database (http://www.plantgdb.org). Identified tryptic peptides were filtered according to their cross-correlation (Xcorr) score and their charge state (Xcorr > 1.7 for +1 and Xcorr > 2.2 for +2 charge). Annotation of the identified proteins was obtained on http://www.arabidopsis.org/servlets/Search; http://www.tigr.org and http://www.genome.ad.jp/kegg were also used as a complement in protein function identification. Molecular weights were obtained from http://au.expasy.org/sprot and http://mips.gsf.de/proj/thal/db.
Statistical analysis was performed on 1,147 reproducible spots. ANOVA was performed for each of the 1,147 reproducible proteins. The factor was the combination between genetic background (Col-0, Ws, and RG) and the genotype at the locus of the different studied mutations. Thus, the different levels of the factor were wild type (Col-0), sur1-3 (Col-0), wild type (Ws), ago1 (Col-0), sur2-1 (Ws), sur2-1 (RG), and sur2-1ago1-3 (RG). This analysis allowed the computation of the residual variance of the spots over the complete dataset. For proteins showing a significant variation (P < 0.01), contrasts were computed between the following couples: sur1-3 (Col-0) versus wild type (Col-0), ago1 (Col-0) versus wild type (Col-0), sur2 (Ws) versus wild type (Ws), and sur2ago1 (RG) versus sur2 (RG). Contrasts were considered significant at P < 0.01. Thus, only proteins showing a significant quantitative difference at least between a mutant and its corresponding wild type were selected. Then spots showing an induction factor below 1.5 or above 0.66 were not considered further. The GLM procedure of the SAS software package (SAS Institute, version 8.1) was used for ANOVA and contrast analysis. Spots were described as showing qualitative variations when they were present (or absent) in all the gels of a mutant genotype and absent (or present) in all the gels of the corresponding wild type or sur2 (in the case of the sur2ago1 [RG] versus sur2 [RG] comparison).
For each protein that was significantly variable, Pearson correlation coefficients (correlation procedure of the SAS package) were computed between means of relative intensity in the six genotypes and IAA (IAA concentration), number of adventitious root primordia 2 d after transfer to light, and number of adventitious roots emerging from the hypocotyl 7 d after transfer to light. When the protein was not detected in a genotype, the genotype was excluded from the computation of the correlation with this protein. When the correlation was significant (P < 0.01), consistence of the correlation with the absence of the protein in this genotype was verified.
Endogenous free IAA levels (pg mg1 fresh weight) were previously measured in the apical part of seedlings, 48 h after transfer to light in wild type (Col-0), wild type (Ws), ago1-3 (Col-0), sur2-1 (RG), and sur2-1ago1-3 (RG) (Sorin et al., 2005
The average number of primordia 2 d after transfer to light was determined in sur2-1 (RG) mutants and sur2-1ago1-3 (RG) double mutants by analyzing the expression of the CyclinB1:uidA reporter gene as described by Sorin et al. (2005) Adventitious roots emerging from the hypocotyls were counted on seedlings 7 d after transfer to light using a stereomicroscope. An average of 40 seedlings was analyzed in three independent biological replicates.
Siblings from Col-0 and ago1-3 or sur2-1 (RG) and sur2-1ago1-3 (RG) were grown in the same conditions as for protein extraction. For auxin induction of GH3-like genes, the seedlings were transferred, after 44 h in the light, into liquid culture medium with or without 10 µM of 1-naphthylacetic acid for 4 h in the same environmental conditions. RNA was extracted from dissected frozen hypocotyls. For semiquantitative RT-PCR, total RNA was extracted using the RNAqueous kit (Ambion). Five hundred nanograms or 1 µg of RNA was transcribed into cDNA by using iScript reverse transcriptase (Bio-Rad). PCR amplification was carried out in triplicate with each cDNA and primer pairs 5'-CCTATGCTGGGCTTTACAGG-3' and 5'-ACCAGGGGACCATTTAGGAC-3' for GH3-6/DFL1/At5g54510; 5'-AAGTTTGTGCGGAGGAAGAA-3' and 5'-AAAGCGGGCTGAAGTGTGT-3' for GH3-3/At2g23170; 5'-AATGCCAACAATCGAAGAGG-3' and 5'-CTTGCACTCAAATTCCACGA-3' for GH3-5/AtGH3a/At4g27260; 5'-GAAATGACTCGGAACCCTGA-3' and 5'-GCAGAGGATGGCTTCGTTAG-3' for GH3-2/YDK1/At4g37390; and 5'-AGCCATCCTCTGCTGTGACT-3' and 5'-ACTCCTCCATCTCCATCGTG-3' for GH3-4/At1g59500. Quantum 18S RNA internal standard kit (Ambion) served as an internal control. PCR products were analyzed on a 1.5% agarose gel. The experiment was performed on two independent biological replicates.
We thank John D. Bussell, Brian Jones, Thomas Moritz, and Gunnar Wingsle for discussions and critical reading of the manuscript. Received July 1, 2005; returned for revision November 2, 2005; accepted November 2, 2005.
1 This work was supported by the Institut National de la Recherche Agronomique (C.B. and M.Z.) and the Swedish Foundation for Strategic Research (C.B.). C.S. received a Ph.D. fellowship from the Ministère de la Recherche et de l'Enseignement Supérieur and from the Swedish Foundation for Strategic Research.
2 Present address: Departament de Genètica Molecular, Institut de Biologia Molecular de Barcelona (Consejo Superior de Investigaciones Científicas), 08034 Barcelona, Spain. The authors responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) are: Michel Zivy (zivy{at}moulon.inra.fr) and Catherine Bellini (catherine.bellini{at}genfys.slu.se).
[W] The online version of this article contains Web-only data. Article, publication date, and citation information can be found at www.plantphysiol.org/cgi/doi/10.1104/pp.105.067868. * Corresponding author; e-mail catherine.bellini{at}genfys.slu.se; fax 46907868561.
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