Supplementary Materials for Combinatorial interaction network of transcriptomic and phenotypic responses to nitrogen and hormones in the Arabidopsis thaliana root Daniela Ristova, Clément Carré, Marjorie Pervent, Anna Medici, Grace Jaeyoon Kim, Domenica Scalia, Sandrine Ruffel, Kenneth D. Birnbaum, Benoît Lacombe, Wolfgang Busch, Gloria M. Coruzzi, Gabriel Krouk* *Corresponding author. Email: [email protected]Published 25 October 2016, Sci. Signal. 9, rs13 (2016) DOI: 10.1126/scisignal.aaf2768 The PDF file includes: Fig. S1. Hormones and nitrogen interact to shape root system architecture (absolute quantification). Fig. S2. Revealing genome-wide features of nitrogen-hormone interactions, the top 100 models. Fig. S3. Study of the NO3*CK-only responsive genes. Fig. S4. qRT-PCR validation of sentinel genes. Fig. S5. Sungear figures (generalized Venn diagram) measuring the convergence of nutritional and hormonal signaling pathways. Fig. S6. Identification of marker genes of simple signals. Fig. S7. Multivariate model with signal-to-trait connections. Fig. S8. Clustering analysis of genes correlated with root traits. Fig. S9. Clustering of all the genes controlled by NO3 − . Fig. S10. Clustering of all the genes controlled by NH4 + . Fig. S11. Clustering of all the genes controlled by IAA. Fig. S12. Clustering of all the genes controlled by CK. Fig. S13. Clustering of all the genes controlled by ABA. Fig. S14. Characterization of mutants at the transcriptional level. Fig. S15. Mutation in a K + channel affects root development and ABA responsiveness on nitrate-containing media. Fig. S16. Venn diagram illustrating the influence of signal combinations on the whole root transcriptome. Table S1. Matrix of treatments applied in this study. www.sciencesignaling.org/cgi/content/full/9/451/rs13/DC1
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Supplementary Materials for
Combinatorial interaction network of transcriptomic and phenotypic
responses to nitrogen and hormones in the Arabidopsis thaliana root
Daniela Ristova, Clément Carré, Marjorie Pervent, Anna Medici, Grace Jaeyoon Kim,
Domenica Scalia, Sandrine Ruffel, Kenneth D. Birnbaum, Benoît Lacombe,
before treatment; P2: primary root growth after treatment; LR: lateral root; LR.nb: total number
of visible (>0.5 mm) lateral roots; LR.nb.P1: number of visible lateral roots in P1; LR.length:
Mean of lateral roots; LR.dens: number of lateral roots per cm of primary root; LR.P.ratio: ratio
between LR length and P length; T.LR.L: Total LR length; T.R.L: Total root length (P plus LR
length).
Number'of'probes'
3499'
Mod
el'#'
Figure S2. Revealing genome-wide features of nitrogen-hormone interactions, the top 100 models.Dominant models of gene regulation classified by the number of probes affected by a given modelof regulation.
Figure S3. Study of the NO3*CK-only responsive genes. (A) Heat map of the 328 genes having NO3*CK as the only significant term controlling them (see Fig. 2A). (B) GeneCloud results highlighting the most highly represented semantic terms in this gene list controlled by the NO3*CK composite signal alone. (C) GeneCloud table of the most highly represented semantic term sorted by p-value.
Figure S4. qRT-PCR validation of sentinel genes. qRT-PCR validation of sentinel genes reporting hormone [retrieved from ref Nemhauser et al, 2006] and nitrogen treatments. Data are means ± SEM, n = 6 from 3 independent experiments performed on different days.
NO3-
NH4+
IAA
CK
ABA
mR
NA
leve
l
NAC4
ARR8
IAA19
NIR1
NRT2.1
Figure S5. Sungear figures (generalized Venn diagram) measuring the convergence of
nutritional and hormonal signaling pathways. Each vessel represents a set of genes genes that
are similarly regulated pointing to vertices (the simple or composite signals indicated). The size
of the vessel is proportional to the size of the corresponding gene set (64, 65).
Figure S6. Identification of marker genes of simple signals. Pattern matching was used to
uncover genes that were mainly regulated by a simple signal. Pattern matching consisted of
correlating (Pearson) gene expression to an idealized model of regulation corresponding to each
signal. Because each signal has a different strength (Fig. 2), the threshold used has been
incrementally modified (by 0.5 steps) in order to retrieve more than 5 genes and have an overall
correlation with the idealized model >0.6. The thresholds used here are: Nitrogen (>0.65), NO3-
(>0.7), NH4+ (>0.6), CK (>0.75), IAA (>0.8), ABA (>0.9).
NO3-
NH4+
IAA
CK
ABA
NO3-
NH4+
IAA
CK
ABA
Nitrogen
Figure S7. Multivariate model with signal-to-trait connections. This is a modified version of
the multivariate network model presented Fig. 2B, where signals are connected to traits according
to ANOVA results. The network was then displayed using the Cytoscape layout function named
‘force directed,’ which displays nodes according to their connectivity (Force of the edges are un-
weighted, all even). This displays clusters of nodes (including genes) that are related to the
signals and to the traits. These clusters are subjected to GeneSect in order to identify biological
functions that are over-represented in each cluster.
Figure S8. Clustering analysis of genes correlated with root traits. (A) Clustering analysis of
genes correlated with root traits in our data set in the Vanneste et al. (2005) dataset. Genes
correlated with lateral root initiation (LRI) are marked by a red spot in the LRI column. This
overlap is larger than expected by chance based on a randomization test (Genesect). (B)
Clustering analysis of genes correlated with root traits in our data set in the data set from Lavenus
et al. (2015), who analyzed gene expression dynamics upon gravistimulation, leading to root
initiation and development. The influence of the simple (single) signals (current study) are
represented by color coding in the columns to the right of the image (ABA in green, IAA in red,
NO3- in Cyan, CK in blue, NH4
+ in purple).
La
tera
l R
oo
t in
itia
tio
n g
en
es
ov
erl
ap
(40
) is
H
igh
er
tha
n e
xp
ecte
d (
Zs
co
re=
9)
A B
Time after gravistimulation
Figure S9. Clustering of all the genes controlled by NO3
−.
NO3- responsive probes (720)
Figure S10. Clustering of all the genes controlled by NH4+.
NH4+ responsive probes (767)
Figure S11. Clustering of all the genes controlled by IAA.
IAA responsive probes (1301)
Figure S12. Clustering of all the genes controlled by CK.
CK responsive probes (995)
Figure S13. Clustering of all the genes controlled by ABA.
ABA responsive probes (5799)
Figure S14. Characterization of mutants at the transcriptional level.standard MS/2 media, and transcript accumulation SEM, n = 3.
Characterization of mutants at the transcriptional level. Plants weand transcript accumulation was measured by qRT-PCR. Data are means ±
were grown on PCR. Data are means ±
Figure S15. Mutation in a K+ channel affects root development and ABA responsiveness on nitrate-containing media. Plants (WT and gork mutants) were grown on 0.5 mM NH4NO3 media for 10 days and then transferred to fresh media containing 0.5 mM NH4NO3, with or without 1µM ABA. The plates were photographed each day thereafter for 5 days. (A) Analysis of variance (ANOVA) results for total root length across time points (day 1 to day 5). (B) Two independent mutant gork lines (salk_082258 in the Col-0 background and gork-1 in WS background) display phenotypes in root development and in the root response to ABA treatment. Data are presented as mean +/- SEM, n=8–9. Asterisks represent the time points at which the interaction between the genotype and the ABA response are significant (p<0.05). (C) At day 5 plants were harvested and meristem size (from quiescent center to the first elongating epidermal cell) measured. Left: Lateral root meristem measurements on plants treated for 5 days with ABA as described above. Data are presented as mean +/- SEM, n=19–33. Right: Swellings of epidermal cells observed in both the primary root (Prim) and lateral root (LR) in salk_082258 after 10 days of growth in the presence of ABA. These are representative pictures taken from a high number (>20) of observations performed in different experiments in different labs.
Figure S16. Venn diagram illustrating the influence of signal combinations on the whole root transcriptome. Probes regulated by simple signals (ABA, IAA, CK, NO3, or NH4) or by composite signals (IAA*CK or IAA*CK*ABA... for example) have been retrieved. A Venn diagram has been generated to compare the different probes regulated by simple or composite signals.
=Controlled by at least a composite signal
e.g: CK*IAA, NO3*NH4, CK*NO3 …
Controlled by at least a simple signal =
e.g: CK, IAA, NO3, NH4 …
Treat #
KN
O3
(1
mM
)
NH
4C
l
(1
mM
)
Au
xin
(5
00
nM
)
Cyto
kin
in
(5
00
nM
)
AB
A
(1
µM
)
KC
l
(1
mM
)
DM
SO
1 0 0 0 0 0 2 3
2 0 0 0 0 1 2 2
3 0 0 0 1 0 2 2
4 0 0 0 1 1 2 1
5 0 0 1 0 0 2 2
6 0 0 1 0 1 2 1
7 0 0 1 1 0 2 1
8 0 0 1 1 1 2 0
9 0 1 0 0 0 1 3
10 0 1 0 0 1 1 2
11 0 1 0 1 0 1 2
12 0 1 0 1 1 1 1
13 0 1 1 0 0 1 2
14 0 1 1 0 1 1 1
15 0 1 1 1 0 1 1
16 0 1 1 1 1 1 0
17 1 0 0 0 0 1 3
18 1 0 0 0 1 1 2
19 1 0 0 1 0 1 2
20 1 0 0 1 1 1 1
21 1 0 1 0 0 1 2
22 1 0 1 0 1 1 1
23 1 0 1 1 0 1 1
24 1 0 1 1 1 1 0
25 0.5 0.5 0 0 0 1 3
26 0.5 0.5 0 0 1 1 2
27 0.5 0.5 0 1 0 1 2
28 0.5 0.5 0 1 1 1 1
29 0.5 0.5 1 0 0 1 2
30 0.5 0.5 1 0 1 1 1
31 0.5 0.5 1 1 0 1 1
32 0.5 0.5 1 1 1 1 0
Table S1. Matrix of treatments applied in this study. All combinations of the 5 signaling
were performed, including the mock treatments (KCl and DMSO).
Table S2. Genome-wide ANOVA results. The table, provided in a separate Excel file
(ANOVA_Results.xlsx), contains p-values for each probe for their response to simple and
composite signals.
Table S3. GeneCloud analysis of the 10 dominant modes of regulation and gene clusters. This table is provided in a separate Excel file (GeneCloud_Results.xlsx). 14 sets of genes
controlled by simple signals or combinations of signals were subjected to GeneCloud analysis
(https://m2sb.org/?page=AtGeneCloudG).
Table S4. Best marker genes for the simple signals. Pattern matching has been used to uncover
genes mainly regulated by a simple signal as depicted in Fig S6 for the 5 signaling molecules
tested as well as for overall nitrogen content of the media.
Table S4
These genes have been retrieved by Pattern Matching as described in the manuscript.
They represent the best marker genes for the simple signals.