Supporting information
A metabolomic study in oats (Avena sativa) highlights a drought tolerance
mechanism based on salicylate signalling pathways and the modulation
of carbon, antioxidant and photo-oxidative metabolism.
Javier Sánchez-Martín1, Jim Heald2, Alison Kingston Smith2, Ana Winters2, Diego
Rubiales1 ,Mariluz Sanz3, Luis A. J. Mur2, Elena Prats1*.
1
CSIC, Institute of Sustainable Agriculture, Apdo. 4084, E-14080 Córdoba, Spain.
2
Institute of Biological, Environmental and Rural Sciences, University of Aberystwyth,
UK.
3
CSIC, Instituto de Química Orgánica General, Juan de la Cierva, 3. 28006 Madrid,
Spain.
Supporting information Table S1. Significant compounds highlighted by the general
model (modelled with all residuals) and related metabolic pathways.
Supporting information Table S2. Significant compounds from the analysis of each of
the specific pathways arisen from the general analysis but that did not appeared
significant in the general analysis.
Supporting information Figure S1. Pictures of Flega a Patones plants at key time points
of the water deficit time course experiment.
Supporting information Figure S2. Analysis Pipeline.
Supporting information Figure S3. PCA loadings.
Supporting information Figure S4. Example sequential analyses of Mass Spectrometry
profiles from a single experimental time point.
Supporting information Figure S5. Principal Component analysis of pathways.
Supporting information Figure S6. Exemplary metabolic changes in susceptible oat
Flega and tolerant Patones under drought.
Supporting information Table S1: Significant compounds highlighted by the general
model (modelled with all residuals) and related metabolic pathways
m/z
Pathwaya
Compound
Also significant
Codeb from individual
pathway
analysis
109 Catechol
Phenylp
a
YES
110 Pyrrole-2-carboxylate
Arg-Pro
a
YES
111 Uracil
β-alanine
a
YES
112 1-Pyrroline-5-carboxylate
Ala-Asp-Glu / Arg-Pro
a
YES
Thiosulfate
Cys-Met
a
YES
Creatinine / 1-Pyrroline-2-carboxylate/ 1Pyrroline-5-carboxylate
Arg-Pro
a
YES
Asc-Ald
a*
YES
Pentoses
a*
YES
Ribulose / Xylulose
Pentoses
a*
YES
Xylose
Starch / Pentoses
a*
YES
Guanidinobutanoate
Arg-Pro
a*
NO
Tartrate / Mesotartrate
Glyox-dicarb
a*
YES
Glyox-dicarb
a*
YES
Tryptoph
a*
YES
Galact
a
YES
Gly-Glu
a
YES
Fruct-Mann
a
YES
Pentoses
a
YES
Phenylp
a
YES
Galact
a
YES
Gly-Glu
a
YES
Fruct-Mann
a
YES
Pentoses
a
YES
Arg-Pro
a
YES
Phenylp
a
YES
Arg-Pro
a
YES
Asc-Ald
a
YES
Glutathione
a
YES
Indol-3-acetamide / Indol-3-acetaldoxime
Tryptoph
a
YES
N-Acetylornithine
Arg-Pro
a
YES
Shikimic acid
Phenylp
a
YES
Cis-aconitate
Phenylp
a
YES
TCA
a
YES
Glyox-dicarb
a
YES
149 Arabinose
155 2-Phosphoglycolate
Indole-3-acetonitrile
169 Glyceraldehyde 3-phosphate
Dihydroxyacetone phosphate
171 Acetylagmatine
3-Dehydroshikimate
173 Arginine
Dehydroascorbate
175 N-Carbamoyl-aspartate
Ala-Asp-Glu
a
YES
4,6-Dihydroxy-2,5-dioxohexanoate / 5dehydro-4-deoxy-glucuronate
Pentoses
a
YES
Ascorbate
Glutathione
a
YES
Asc-Ald
a
NO
N-Hydroxyl-tryptamine / Serotonin
Tryptoph
a
YES
Glucuronolactone
Asc-Ald
a
NO
Pentoses
a*
NO
Galact
a*
YES
Asc-Ald
a*
NO
186 Acetylspermidine
Arg-Pro
a*
YES
195 Altronate
Pentoses
a*
NO
Galactonate
Galact
a*
YES
Gulonate
Asc-Ald / Pentoses
a*
NO
Ala-Asp-Glu /Arg-Pro /
Phenylp / TCA
Arg-Pro
b
YES
b
YES
Asc-Ald / Arg-Pro
b
YES
Pentoses
b
NO
Asc-Ald
b
YES
TCA
b
NO
Glyox-dicarb
b
NO
Phenylp
b
YES
137 Salicylate
Phenylp
b
YES
167
137 Phosphoenolpyruvate
Gly-Glu
b
YES
Phenylp
b
YES
TCA
b
YES
168 3-Sulfo-acetate / Cysteate
Cyst-Met
b
YES
181 Sorbitol
Fruct-Mann / Galact
b*
YES
Galactitol
Galact
b*
YES
Mannitol
Fruct-Mann
b*
YES
b*
NO
b*
YES
b
YES
Arg-Pro
b
NO
440 Folate
Phenylp
b*
YES
119 3-Methythiopropionate
Cys-Met
c
YES
130 Creatine
Arg-Pro
c
YES
2-Oxosuccinamate
Ala-Asp-Glu
c
YES
N-Acetyl-beta-alanine
β-alanine
c
YES
Glutamate 5-semialdehyde
Arg-Pro
c
YES
177 2-Dehydro-3-deoxy-gluconate
Galactono-1,4-lactone / 2-Dehydro-3deoxy-galactonate
Gulono-1,4-lactone / Galactone- 1,4
lactone
115 Fumarate
129 Agmatine
2,5-dioxo-pentanoate
133 3-Dehydro-threonate
Malate
210 5-(2'-Formylethyl)-4,6-dihydroxypicolinate Tryptoph
Creatine phosphate
Arg-Pro
226 5-(2'-Formylethyl)-4,6-dihydroxypicolinate Tryptoph
Glutamyl 5-phosphate
5-Amino-2-oxopentanoic acid /
Norspermidine / N-carbamoylputrescine
Arg-Pro
c
YES
c
NO
Acetylserine
Arg-Pro / Glutathione /
Ala-Asp-Glu / Glyoxdicarb/
Cyst-Met
c
YES
2-Oxo-4-hydroxy-5-aminovalerate
Arg-Pro
c
YES
156 2-Aminomuconate
Tryptoph
c*
YES
185 3-Phospho-glycerate
Glyox-dicarb
c
YES
Gly-Glu
c
YES
Glyox-dicarb
c
Phenylp
c
YES
YES
YES
NO
Gly-Glu
c
YES
Pentoses
c
NO
Phenylp
c
Tryptoph
c
YES
NO
YES
Arg-Pro
c
NO
196 Carbamoyl phosphate
Ala-Asp-Glu / Asc-Ald
c
YES
198 Phosphoserine
Cys-Met
c
NO
201 Spermine
β-alanine / Glutathione
c
YES
Arg-Pro
c
NO
Tryptoph
c
NO
206 4-(2-aminophenyl)-2,4-dioxobutanoate / 2- Tryptoph
Formaminobenzoylacetate
c
YES
221 Cystathionine
Cys-Met
c
YES
244 beta-Alanyl-arginine
β-alanine
c
YES
116 Indole
Tryptoph
d
YES
Aspartate-4-semialdehyde
Arg-Pro / Cys-Met
d
YES
Guanidinoacetate
Arg-Pro
d
YES
134 Homocysteine
Cys-Met
d
YES
136 Anthranilate
Tryptoph
d
YES
Phenylp
d
YES
Pentoses
d
YES
4-Methylthio-2-oxobutanoate
Cys-Met
4-Methylthio-2-oxobutanoate
2-Dehydro-3-deoxyarabinonate/Arabinono- Asc-Ald
1,4-lactone
d
YES
d
YES
Oxaloglycolate
Glyox-dicarb
d
YES
Fruct-Mann
d
YES
Fruct-Mann
d
YES
564 CDP-glucose
Starch
d
YES
565 UDP-glucose
Asc-Ald
d
YES
Galact
d
Pentoses
d
YES
YES
YES
Starch
d
NO
146 Glutamate
Glycerate-2-phosphate
188 1-Acetylisatin
N-Acetyl-glutamate
204 6-hydroxy-kynurenate / Xanthurenate /
Indolelactate
Xylonolactone
147
163 Fucose / Fuculose
Rhamnofuranose / Rhamnose
UDP-galactose
Galact
d
YES
Asc-Ald
d
YES
Pentoses
d
YES
Starch
d
YES
135 Threonate
Asc-Ald
e
YES
148 Methionine
Cys-Met
e
NO
Tryptoph
e
YES
153 Protocatechuate / 2,3-Dihydroxybenzoate
Phenylp
e
YES
154 Histidine
β-alanine
e
YES
165
154 Arabinonate
Xylonate
155
Lyxonate
155
174 Monodehydroascorbate
Asc-Ald
e
YES
Pentonses
e
YES
Asc-Ald / Pentoses
e
YES
Asc-Ald
e
YES
156 Carboxy-norspermidine
Arg-Pro
e
YES
Citrulline
Arg-Pro
e
YES
N-acetylaspartate
Ala-Asp-Glu
e
YES
Asc-Ald
e
NO
Pentoses
e
YES
YES
Starch
e
NO
211 Isophenoxazine
Tryptoph
e
YES
216 gamma-glutamylputrescine
Arg-Pro
e
YES
β-alanine
e
YES
229 Ribulose-5-phosphate
Glyox-dicarb
e
YES
261 Mannitol 1-phosphate / Sorbitol 6phosphate
Fruct-Mann
e
YES
338 Fructose 1,6-bisphosphate
Fruct-Mann
e
YES
343 Melibiitol
Galact
e
YES
579 UDP-glucuronate
Dihydroxyindole / 2formylaminobenzaldehyde
193 Glucuronate / Galacturonate
Pinitol/ononitol
beta-Alanyl-lysine
Pathways refer to; Gly-Glu: Glycolysis/Gluconeogenesis (Ko00010); TCA: TCA Cycle (Ko00020); Pentoses: Pentose
phosphate pathway and Pentoses and glucuronate interconversions (Ko00030 / Ko00040); Fruct-Mann: Fructose
and Mannose metabolism (Ko00051); Galact: Galactose metabolism (Ko00052); Asc-Ald: Ascorbate and aldarate
metabolism (Ko00053); Ala-Asp-Glu: Alanine, Aspartate and Glutamate metabolism (Ko00250); Gly-Ser: Glycine,
serine and threonine metabolism (Ko00260); Cys-Met: Cysteine and Methionine metabolism (Ko00270); Arg-Pro:
Arginine and Proline metabolism (Ko00330); Tryptoph: Thryptophane metabolism (Ko00380); β-alanine: β-alanine
metabolism (Ko00410); Glutathione: Glutathione metabolism (Ko00480); Starch: Starch and sucrose metabolism
(Ko00500); Glyox-dicarb: Glyoxylate-dicarboxylate metabolism (Ko00630); Phenylp: Main core phenylpropanoid
metabolism (Map01061); according to KEEG database.
b) Code legend
a -> Significant in discriminating between susceptible and resistant genotypes subjected to drought stress
but not in watered controls, in at least three sampling times .
b -> Significant discriminating susceptible and resistant genotypes subjected to drought stress but not in
watered controls, in two sampling times
c -> Significant discriminating susceptible and resistant genotypes subjected to drought stress but not in
watered controls, in one sampling time
d -> Significant discriminating susceptible and resistant genotypes subjected to drought stress but also
watered controls, in at least 4 of the 5 sampling times
e -> Significant only in specific time points and/or comparisons
*Significant discriminating susceptible and resistant genotypes subjected to drought stress but not in
watered controls also in the general model (all time points)
Supporting information Table S2: Significant compounds from the analysis of each of
the specific pathways arisen from the general analysis but that did not appeared
significant in the general analysis.
m/z
Compound
Pathway
101
Cadaverine
Malonate
Hydroxy pyruvate
Succinate
Cysteine
Oxaloacetate
Ornithine
N-carbamoyl-β-alanine
N-carbamoylsarcosine
Glutathione
β-alanine
Glyox-dicarb
Ala-Asp-Glu / Glyox-dicarb
Glutathione
Gly-Glu / Glyox-dicarb
Arg-Pro/ Glutathione
β-alanine
Arg-Pro
140
2-Aminomuconate-semialdehyde
Tryptoph
179
180
212
239
Glucose
3-hydroxy-kyrenamine
4-Aspartyl-Phosphate
Anserine
Gly-Glu
Tryptoph
Cys-Met
β-alanine
247
5- Hydroxyindoleacetylglycine
Thryptoph
258
259
264
271
Galactosamine 6-phophate
Glucose 1-phosphate
3-Phospho-glyceroyl phosphate
Arbutin
Galact
Gly-Glu
Gly-Glu
Gly-Glu
300
N-Acetyl-Galactosamine-6P
Galact
309
365
Ribulose-1,5-bisphosphate
Salicin-6P
Glyox-dicarb
Gly-Glu
586
GDP-4-oxo-6-deoxy-mannose
Fruct-Mann
Weigh
103
t
(PYC
117
HEM)
120
hay
que
sumar
131
1
Pathways refer to; Gly-Glu: Glycolysis/Gluconeogenesis (Ko00010); Fruct-Mann: Fructose and Mannose metabolism
(Ko00051); Galact: Galactose metabolism (Ko00052); Ala-Asp-Glu: Alanine, Aspartate and Glutamate metabolism
(Ko00250); Arg-Pro: Arginine and Proline metabolism (Ko00330); Tryptoph: Thryptophane metabolism (Ko00380); βalanine: β-alanine metabolism (Ko00410); Glutathione: Glutathione metabolism (Ko00480); Glyox-dicarb:
Glyoxylate-dicarboxylate metabolism (Ko00630) according to KEEG database
Patones
Flega
SUPPORTING INFORMATION FIGURES
sRWC
daww
100%
0
55-60%
6
40-45%
9
30-35%
20-25%
15-20%
Controls
12
15
18
18
Supporting information Figure S1. Pictures of Flega a Patones plants at key time
points of the water deficit time course experiment.
A
DI-ESI-MS
Metabolite
Profiles
B
Multivariate
analyses
Analysis of all data
Separation according
to genotype and
treatment
(General model)
Separation
Analysis
of individual
timepoints
according to
Separation
according
genotype,
to genotype
treatmentand
and
treatment
time
Highlights m/z
discriminating
between genotype
and treatment
effects
Highlights m/z
changing with time
Identification of key m/z based on loading vectors
C
Tentative m/z identification from databases
Link with metabolic pathways (15
pathways selected)
D
Linked m/z to
biochemical
pathways
Confirmatory analysis on
each individual pathway
through PCA
E
Validation
Targeted
assays
Tandem
MS-MS
Supporting information Figure S2: Analysis Pipeline. A: Experimental samples
were profiled using Direct-Infusion-Electrospray Ionisation Mass Spectroscopy (DI-ESIMS). B: The multiple spectra were analysed using multivariate approaches. Data were
first interrogated using Principal Component Analysis (PCA; Causton 1987) followed by
Discriminant Function Analysis (DFA) which is a supervised projection method (Manly
1994) which attempts to designate groups on the basis of the retained PCs. PC-DFA
models were created to identify the key metabolites differentially produced in the
susceptible and tolerant cultivars based on deriving robust models where differences
between classes were separated along a particular PC-DF axis. This allowed plotting
the contributions of individual metabolites measured to the model (“loading vectors”).
Those metabolites that appeared > ± 1 standard deviation (STD) from the mean value
loading were recorded as significant metabolites associated with the differences
(Supporting information Table 1). To maximise the information obtained from these
analyses, PC-DFA were employed in a two-step manner 1) analysis of all data using
classes of genotype and treatment (4 classes) or by treatment grouped according to
the sampling times (10 groups per cultivar); 2) analysis of each specific sampling time
by genotype and treatment. This identified the key time points and m/z to discriminate
the susceptible and resistant cultivars. C: Each m/z was tentatively identified according
to predicted true mass (m/z + 1) and interrogation of ESI-MS metabolite libraries
constructed from the analysis of tomato plants and olive oils (Goodacre et al. 2002)
and of the Kyoto Encyclopaedia of Genes and Genomes (KEGG) metabolic pathways.
D Predicted metabolites (based on m/z) were grouped according to their biochemical
pathways and tested by ANOVA for significant differences between the experimental
groups. Analysis of each individually targeted pathway according to genotypes,
treatment and time point classes were performed to confirm the significance of
metabolites. E. The importance of the targeted metabolites and pathways in
discriminating between the experimental classes was validated through targeted
assays and tandem MS.
0.5
A
0.4
278.00
w[2]
92.00
280.00
34.00
16.00
0.0
-0.1
-0.4
C
305.00
478.00
465.00 63.00
47.00
12.00
479.00
80.00
243.00
340.00
541.00
279.00
36.00
416.00
306.00
466.00
110.00
480.00
68.00
29.00
74.00
440.00
10.00
332.00
1187.00
584.00
404.00
33.00
1188.00
542.00
556.00
281.00
442.00
467.00
513.00
527.00
566.00
414.00
602.00
244.00
434.00
1162.00
514.00
1160.00
38.00
3.00
116.00
454.00
20.00
376.00
216.00
362.00
528.00
1161.00
1203.00
1124.00
1190.00
1223.00
268.00
307.00
1189.00
341.00
557.00
62.00
225.00
438.00
585.00
56.00
417.00
486.00
502.00
44.00
260.00
264.00
352.00
354.00
441.00
456.00
487.00
512.00
516.00
1179.00
282.00
378.00
482.00
540.00
1073.00
1070.00
1094.00
1089.00
1079.00
1115.00
1105.00
1158.00
1157.00
1156.00
1154.00
1153.00
1152.00
1151.00
1149.00
1148.00
1147.00
1146.00
1144.00
1142.00
1141.00
1140.00
1139.00
1137.00
1132.00
1130.00
1128.00
1127.00
1126.00
1178.00
1177.00
1176.00
1175.00
1174.00
1172.00
1171.00
1170.00
1169.00
1168.00
1166.00
1165.00
1164.00
1163.00
1186.00
1185.00
1184.00
1183.00
1182.00
1181.00
1180.00
1222.00
1221.00
1220.00
1219.00
1218.00
1217.00
1216.00
1215.00
1214.00
1213.00
1212.00
1210.00
1209.00
1208.00
1207.00
1206.00
1205.00
1204.00
1202.00
1201.00
1200.00
1199.00
1197.00
1195.00
1193.00
1192.00
1191.00
1270.00
1269.00
1268.00
1267.00
1266.00
1265.00
1264.00
1263.00
1262.00
1261.00
1260.00
1259.00
1258.00
1257.00
1256.00
1255.00
1254.00
1253.00
1252.00
1251.00
1250.00
1249.00
1248.00
1247.00
1246.00
1245.00
1244.00
1243.00
1242.00
1241.00
1240.00
1239.00
1238.00
1237.00
1236.00
1235.00
1234.00
1233.00
1232.00
1231.00
1230.00
1229.00
1228.00
1227.00
1226.00
1225.00
1224.00
1286.00
1285.00
1284.00
1283.00
1282.00
1281.00
1280.00
1279.00
1278.00
1277.00
1276.00
1275.00
1274.00
1273.00
1272.00
1300.00
1299.00
1298.00
1297.00
1296.00
1295.00
1294.00
1293.00
1292.00
1291.00
1290.00
1308.00
1307.00
1306.00
1305.00
1304.00
1303.00
1302.00
1321.00
1320.00
1319.00
1318.00
1317.00
1315.00
1314.00
1313.00
1312.00
1310.00
1327.00
1326.00
1325.00
1329.00
1334.00
1333.00
1332.00
1331.00
1338.00
1337.00
1336.00
1342.00
1341.00
1345.00
1344.00
1353.00
1352.00
1351.00
1360.00
1359.00
1358.00
1357.00
1363.00
1366.00
1368.00
1370.00
1374.00
1373.00
1376.00
1385.00
1388.00
1392.00
1391.00
1395.00
22.00
94.00
286.00
348.00
384.00
379.00
389.00
481.00
1125.00
1271.00
1289.00
1288.00
1287.00
1301.00
1309.00
1324.00
1323.00
1322.00
1328.00
1330.00
1335.00
1340.00
1339.00
1343.00
1347.00
1346.00
1350.00
1349.00
1355.00
1354.00
1362.00
1361.00
1364.00
1367.00
1369.00
1372.00
1371.00
1375.00
1380.00
1379.00
1378.00
1377.00
1382.00
1384.00
1387.00
1386.00
1389.00
1394.00
1393.00
1398.00
1397.00
1396.00
52.00
160.00
238.00
314.00
406.00
543.00
565.00
130.00
333.00
64.00
132.00
148.00
494.00
590.00
106.00
164.00
171.00
366.00
177.00
265.00
126.00
30.00
93.00
6.00
604.00
18.00
118.00
398.00
488.00
490.00
524.00
530.00
538.00
567.00
603.00
620.00
14.00
405.00
435.00
450.00
455.00
468.00
472.00
476.00
489.00
491.00
496.00
498.00
501.00
504.00
507.00
510.00
518.00
517.00
520.00
523.00
526.00
525.00
529.00
533.00
532.00
537.00
536.00
539.00
547.00
550.00
549.00
552.00
564.00
578.00
629.00
8.00
50.00
245.00
252.00
256.00
316.00
324.00
326.00
347.00
356.00
358.00
361.00
377.00
400.00
415.00
418.00
420.00
422.00
427.00
436.00
458.00
457.00
471.00
470.00
474.00
477.00
484.00
495.00
497.00
499.00
508.00
515.00
544.00
553.00
563.00
562.00
568.00
572.00
577.00
576.00
580.00
600.00
740.00
1056.00
1058.00
1072.00
1071.00
1069.00
1068.00
1067.00
1066.00
1065.00
1064.00
1095.00
1093.00
1092.00
1091.00
1090.00
1088.00
1087.00
1086.00
1085.00
1084.00
1083.00
1082.00
1081.00
1080.00
1078.00
1077.00
1076.00
1075.00
1123.00
1122.00
1121.00
1120.00
1119.00
1118.00
1117.00
1116.00
1114.00
1113.00
1112.00
1111.00
1110.00
1109.00
1108.00
1107.00
1106.00
1104.00
1103.00
1102.00
1101.00
1100.00
1099.00
1098.00
1097.00
1159.00
1155.00
1150.00
1145.00
1143.00
1138.00
1136.00
1135.00
1134.00
1133.00
1131.00
1129.00
1173.00
1167.00
1211.00
1198.00
1196.00
1194.00
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72.00
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252.00
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330.00
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514.00
542.00
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432.00
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486.00
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218.00
481.00
86.00
106.00
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332.00
31.00
32.00
350.00
28.00
300.00
314.00
56.00
17.00
50.00
322.00
541.00
48.00
104.00
144.00
465.00
30.00
110.00
430.00
479.00
480.00
15.0046.00
10.00
68.00
478.00
12.00
0.3
0.2
0.4
242.00
464.00
242.00
-0.0
0.2
0.4
0.6
0.8
1.0
1.2
-0.4
-0.2
0.0
-0.0
0.2
0.4
0.6
0.8
0.6
0.6
G
0.4
167
0.4
440
136
440
109
109
0.2
w[2]
167
136
-0.2
0.0
-0.4
0.0
0.1
0.2
0.3
w[1]
0.4
0.5
-0.2
169173
171
173
169
171
-0.1
0.2
164 185
137
339
442
203
259
121
153
199
225
265
164 185
137
339
442
203
121
259
225
265
199
153
0.0
H
-0.4
0.6
0.7 -0.1
0.0
0.1
0.2
0.3 0.4
w[1]
0.5
0.6
0.7
Supporting information Figure S3. PCA loadings of the variables on the first two
axes. A, B. PCA loadings corresponding to Figure 2A, for all samples and droughted
samples respectively. C,D. PCA loadings corresponding to Figure 3A,B. E,F. PCA
loadings corresponding to Figure 5A,B. G,H. PCA loadings corresponding to Figure
7A,B.
PCA Scores
(B)
PC-DFA 2
PC2 (21.74%)
(A)
DFA Scores
PC-DFA 1
(D)
(C)
PC2 (15.93%)
PC2 (20.66%)
PC1 (51.33%)
PC1 (57.51%)
PC1 (64.24%)
Fw
Fd
Pw
Pd
Supporting information Figure S4. Example sequential analyses of Mass
Spectrometry profiles from a single experimental time point. A. Principal
Component Analysis (PCA) and B. Discriminant Functional Analysis (DFA) of
metabolite profiles from drought susceptible Flega (F) and tolerant Patones (P)
droughted (d) or control well watered plants at a given time point. In DFA crosses
indicate mean value for each class and the circles 90 and 95% confidence intervals; C.
PCA model based only on samples subjected to drought treatment. D. PCA model
based on control well watered samples. Significant metabolites explaining clustering
from these three different models were compared to determine the importance of these
metabolites at this specific sampling time and their constitutive or inducible condition
PC2 (18.09%)
PC2 (14.92%)
PC2 (9.77%)
PC2 (19.72%)
PC2 (13.73%)
PC2 (20.02%)
PC2 (13.30%)
Ascorbate Pathway
Photorrespiration
PC2 (12.98%)
PC2 (26.81%)
PC1 (78.04%)
PC1 (83.95%)
PC1 (85.34%)
Phenylpropanoids
PC1 (65.61%)
PC1 (68.57%)
PC1 (77.21%)
PC1 (42.77%)
Water/Drought (Patones)
Water/Drought (Flega)
Water/Water
PC1 (60.22%)
PC1 (77.81%)
Fw
Fd
Pw
Pd
Supporting information Figure S5. Principal Component analysis of pathways
profiles from oat cultivar Flega (triangles) and Patones (circles) well watered plants
(open symbols) and during a time course of water stress (solid symbols).
10
8
6
4
15
15
10
5
5
0
60
0
100
40
20
80
Rhamnose
Histidine
0
20
Methionine
2
20
10
Glutamate
Succinate
15
10
5
0
12
P-Serine
Fumarate
Threonate
Arginine
35
30
25
20
60
40
0
0
6
4
2
0
60
40
0
60
8
40
20
6
4
2
0
6
9
12 15 18
Days after treatment
6
4
2
0
80
10
Galactitol
UDP-Galactose
Arabinose
8
6
4
2
0
14
12
10
8
20
20
10
14
12
10
8
6
9
12 15 18
Days after treatment
0
6
9
12 15 18
Days after treatment
Supporting information Figure S6. Exemplary metabolic changes in susceptible
oat Flega and tolerant Patones under drought. Data represent normalized
responses of metabolite pools, that is, mass detector signals in arbitrary units
normalized to internal standard and sample dry weight in Flega (triangles) and Patones
(circles) under well-watered (open symbols) or drought conditions (solid symbols). Data
indicates mean + standard error of 6 replicates which were taken from four pooled
plants.