Supporting Information Fig. S1 Frequency distribution of leaf element concentration across
the 31 Arabidopsis accessions used in this study for (a) Ca, (b) Mg and (c) Zn. Weight
normalised leaf element concentration data for these accessions were obtained from the iHUB
consortium website (http://www.ionomicshub.org) and normalised using the REML method
proposed by Broadley et al. (2010). These values were partitioned across equal bins from
their minimum to maximum values for Ca (39,737-51,223 mg kg-1 DW), Mg (12,132–16,721
mg kg-1 DW) and Zn (24.9–111.2 mg kg-1 DW) and the number of accessions falling within
each
concentration
range
is
displayed
on
the
y-axis.
Fig. S2 Distribution of Pearson correlation coefficients (r values) for each transcript (with
log2 expression value ≥ 3.5 in at least one sample) each specific element (Ca, Mg and Zn).
Each correlation approaches a normal distribution, with no obvious skewed distribution.
Arrows indicate threshold applied to indicate significantly correlated transcripts (r < -0.3; r >
0.3). Note outermost bins represent values ≤ -0.5 and ≥ 0.5, respectively.
Calcium (Ca)
(a)
(b)
(c)
Magnesium (Mg)
r = 0.220
P = 0.234
r = -0.027
P = 0.884
Zinc (Zn)
r = -0.039
P = 0.833
r = 0.285
P = 0.120
r = 0.395
P = 0.028
r = 0.100
P = 0.594
r = -0.010
P = 0.957
r = 0.251
P = 0.173
r = -0.197
P = 0.288
r = -0.048
P = 0.797
r = -0.397
P = 0.027
r = 0.032
P = 0.863
r = -0.003
P = 0.989
r = 0.384
P = 0.033
r = 0.340
P = 0.061
(d)
r = -0.369
P = 0.041
(e)
(f)
(g)
(h)
(i)
(j)
(k)
r = 0.378
P = 0.036
r = -0.091
P = 0.628
r = 0.168
P = 0.367
r = 0.563
P = 0.001
r = 0.066
P = 0.724
r = -0.013
P = 0.945
r = -0.367
P = 0.042
r = -0.023
P = 0.903
r = -0.392
P = 0.029
r = 0.081
P = 0.666
r = -0.318
P = 0.081
r = -0.106
P = 0.569
r = -0.214
P = 0.248
r = 0.143
P = 0.444
r = 0.321
P = 0.023
Fig. S3 Scatter plots generated with the population correlation filter referred to in the main
text. Line of best fit, Pearson correlation coefficient (r) and P-value (P) shown for each graph
for the following genes: (a) AtCAX1 (At2g38170, 267093_at), (b) AtMRS2-1 (At1g16010,
261795_at), (c) AttDT (At5g47560, 248756_at), (d) AtVHA-a3 (At4g39080, 252932_at), (e)
AtKUP5 (At4g33530, 253330_at), (f) AtCCX4 (At1g54115, 263154_at), (g) AtTPC1
(At4g03560, 255380_at), (h) AtMTP5/AtMTPc2 (At3g12100, 256272_at), (i) AtKUP3
(At3g02050, 258860_at), (j) AtMCA1 (At4g35920, 253109_at), (k) AtMTP1 (At2g46800,
266718_at). Ca and Mg correlations for AtCAX1 and AtMRS2-1, respectively, are excluded
from this figure as they are presented in the main body.
Fig. S4 The expressed probesets (log2 expression value ≥ 3.5) from the microarrays where
used for average linkage clustering. The distance between two samples corresponds to 1Spearman correlation coefficient over the whole array. The divergence of the Frankfurt-2
accession (name highlighted in red), which was also seen in pairwise correlation plot
matrices, meant it was removed from all further correlation analyses. Accessions used in the
population correlation filter are: Achkarren-1, Bayreuth-0, Blanes-5, C24, Caen-0, Canary
Islands-0, Cape Verde Islands (Cvi-0), CIBC10, Columbia-0, Drahonin-1, Enkheim-T,
Erlangen-0, Estland, Frankfurt-2, HR-5, Isenburg-0, Kindalville-0, Landsberg erecta (Ler-1),
Limburg-2:1, Moscow-0, Neuweilnau-1, NFE1, Niederzenz-1, Noordwijk-1, Oldenburg-1,
Ovelgoenne-0, San Eleno-0, San Feliu-2e, Shahdara, Tabor-0, Umkirch-3, Vancouver-0.
Table S1 Studies incorporating natural Arabidopsis accessions to investigate elemental accumulation phenotypes or implicate genes in these
processes
Phenotype
Aluminium (Al)
Technique(s) used
QTL (Col-0 × Ler)
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Selenate
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