Supporting experimental procedures
Methods S1: Yeast two-hybrid
Qualitative yeast two-hybrid assays were performed using yeast strain
MaV203 (Vidal et al., 1996) and gateway vectors pDEST22 for GAL4-AD fusion and
a modified pDEST32 (carrying a Kanamycin Resistant gene) for GAL-BD fusion
(Invitrogen). Cells were co-transformed with the two two-hybrid plasmids using a
classical Li/PEG/Heat chock (Schiestl and Gietz, 1989) and selected on medium
lacking tryptophan and leucine (SC with 0.2% Drop out -T-L, US Biological) at 30°C
for 2 days. Colonies were grown overnight in the same medium without agar, then
diluted 200 times and 5 µL were spotted on SC plate (SC with 0.2% Drop out -T-L-H,
US Biological) containing indicated concentrations of 3-Amino-1,2,4-triazole (3AT).
Methods S2: BiFC experiment
LR recombinations of appropriated ORFs in pDONR207 were done with splitYFP destination vectors, pBiFC2 and pBiFC3, that allow N-terminal fusion with the Nand C-terminal YFP moieties, respectively (Azimzadeh et al., 2008). Recombined
vectors were transformed in Agrobacterium C58C1 strain. Nicotiana benthamiana
leaves were agro-infiltrated as previously described (Colcombet et al., 2013). After 3
days, the YFP fluorescence was visualized using a TCS SP2-AOBS static confocal
microscope (Leica, Germany).
Methods S3: Relative Water Content measurements
Water deficit was evaluated as described previously (Barrs and Weatherley,
1962, Elhaddad et al., 2014). Briefly, plants were grown in Jiffy pots for 3 weeks in
long-day conditions (16 h light, 8 h night, 70% humidity, 22°C) before lowering the
humidity to 35%. The watering was stopped for half of the plants during 10 days, the
other half being used as control. Detached leaves of the different genotypes were
weighted (Fresh Weight, FW) and then submitted to water saturation overnight to
measure Turgid Weight (TW). The samples were then placed for 24h at 65°C and
Dry Weight (DW) was measured. Relative water content (RWC) can be calculated in
percentage as:
RWC = (FW – DW)/(TW – DW) x 100.
Methods S4: CATMAv7 microarray design, hybridization and Statistical
Analysis
The CATMAv7 design of Arabidopsis thaliana genome have been made with
gene annotations include in FLAGdb++, an integrative database around plant genome
(http://urgv.evry.inra.fr/FLAGdb (Derozier et al., 2011)). The single high density
CATMAv7 microarray slide contains four chambers, each containing 149 916
primers. Each 60 bp primer is triplicate in each chamber for robust analysis and in
both strand. As part of all probes, 35 754 in triplicate correspond to gene TAIRv8
(among which 476 probes corresponding to mitochondrial and chloroplast genes) +
1289 probes corresponding to EUGENE software predictions + 658 probes for
miRNA/MIR, and finally 240 controls. All the details of the experiment design and
differential analyses are accessible in the CATdb (Project RA14-02_mkk3-ABA), a
database to manage transcriptomic data (http://urgv.evry.inra.fr/CATdb (Gagnot et
al., 2008)).
RNA were extracted using RNeasy plant mini kit and RNase-Free DNAse Set
following manufacturer’s recommendations (QIAgen). For each comparison, one
technical replicate with fluorochrome reversal was performed for each biological
replicate (i.e. four hybridizations per comparison). The labeling of cRNAs with Cy3dUTP or Cy5-dUTP was performed as described in Two-Color Microarray-Based
Gene Expression Analysis Low Input Quick Amp Labeling manual (© Agilent
Technologies, Inc.). The hybridization and washing were performed according to
Agilent Microarray Hybridization Chamber User Guide instructions ((© Agilent
Technologies, Inc.). Two micron scanning was performed with InnoScan900 scanner
(InnopsysR, Carbonne, FRANCE) and raw data were extracted using MapixR
software (InnopsysR, Carbonne, FRANCE).
Experiments were designed with the statistics group of the Unité de
Recherche en Génomique Végétale. For each array, the raw data comprised the
logarithm of median feature pixel intensity at wavelengths 635 nm (red) and 532 nm
(green). For each array, a global intensity-dependent normalization using the loess
procedure (Yang et al., 2002) was performed to correct the dye bias. The differential
analysis is based on the log-ratios averaging over the duplicate probes and over the
technical replicates. Hence the numbers of available data for each gene equals the
number of biological replicats and are used to calculate the moderated t-test (Smyth,
2004).
Under, the null hypothesis, no evidence that the specific variances vary
between probes is highlighted by Limma and consequently the moderated t-statistic
is assumed to follow a standard normal distribution.
To control the false discovery rate, adjusted p-values found using the
optimized FDR approach of (Storey and Tibshirani, 2003) are calculated. We
considered as being differentially expressed the probes with an adjusted p-value ≤
0.05.
Analysis was done with the R software. The function SqueezeVar of the library
limma has been used to smooth the specific variances by computing empirical Bayes
posterior means. The library kerfdr has been used to calculate the adjusted p-values.
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