visualization options. You can also map Pfam domains and
CDD Feature hits onto the 3D structure by selecting the
appropriate button (if available for your protein of interest),
or identify any non-synonymous (amino acid-changing) polymorphisms from the 1001 Genomes database, which are visualized as pins, sized and colored according to the frequency of
the polymorphism.
3.11.4 TF2Network
We saw with ePlant and AIV2 that it is possible to start to think
about networks of genes controlling the expression of other genes,
perhaps combinatorially. With TF2Network [74] we can start with
a list of coexpressed genes and then see if there are potentially
common regulators of those genes. TF2Network uses position
weight matrices and scores the occurrence of each PWM in the
coexpressed gene promoters using hypergeometric tests. It assigns
p-values, corrected by the Benjamini-Hochberg method. The top
50 TFs, according to p-value, are visually reported as predicted
regulators. Experimentally determined PPIs and PDIs are also
incorporated into the output.
1. Go
to:
http://bioinformatics.psb.ugent.be/webtools/
TF2Network/.
2. Let’s use the top 50 coexpressed genes for ABI3 across a
“Developmental Map” as identified with the Expression Angler
tool (see Supplemental Table S1). We will copy the AGI IDs and
paste them into the input box. Then click “submit.”
3. Select the ABI3 TF by clicking on its row in the left panel of the
output to view its interactions in the Cytoscape panel on the
right. Manipulate the edges to explore its different interactions
by using the smaller sliders in the “Edge Manipulation panel.”
Use the mouse wheel to zoom into the network. Click on node
for this gene and examine the information in the gene info
panel.
4. Select an additional TF in the regulator panel (e.g., ABF4/
At3g19290) to see interactions between the two genes and the
input gene set. It is possible to sort by CO (coexpression
column indicating what percent of the input genes are coexpressed—in a TF2Network internal coexpression database—
with the inferred regulator), PD (experimentally determined
protein-DNA data column showing percent of input genes
having PDI data) or the PWM column (the number of PWM
matches to input set promoters is shown in the Hits column)
(see Fig. 28). With TF2Network, we see that ABI5
(At2g36270) has experimentally determined protein-DNA
interactions with 41% of the input set promoters. It is also
coexpressed (based on TF2Network’s own database of coexpression analyses) with 90% of the input gene set, and has PWM
Arabidopsis Bioinformatics
77
CDD Feature hits onto the 3D structure by selecting the
appropriate button (if available for your protein of interest),
or identify any non-synonymous (amino acid-changing) polymorphisms from the 1001 Genomes database, which are visualized as pins, sized and colored according to the frequency of
the polymorphism.
3.11.4 TF2Network
We saw with ePlant and AIV2 that it is possible to start to think
about networks of genes controlling the expression of other genes,
perhaps combinatorially. With TF2Network [74] we can start with
a list of coexpressed genes and then see if there are potentially
common regulators of those genes. TF2Network uses position
weight matrices and scores the occurrence of each PWM in the
coexpressed gene promoters using hypergeometric tests. It assigns
p-values, corrected by the Benjamini-Hochberg method. The top
50 TFs, according to p-value, are visually reported as predicted
regulators. Experimentally determined PPIs and PDIs are also
incorporated into the output.
1. Go
to:
http://bioinformatics.psb.ugent.be/webtools/
TF2Network/.
2. Let’s use the top 50 coexpressed genes for ABI3 across a
“Developmental Map” as identified with the Expression Angler
tool (see Supplemental Table S1). We will copy the AGI IDs and
paste them into the input box. Then click “submit.”
3. Select the ABI3 TF by clicking on its row in the left panel of the
output to view its interactions in the Cytoscape panel on the
right. Manipulate the edges to explore its different interactions
by using the smaller sliders in the “Edge Manipulation panel.”
Use the mouse wheel to zoom into the network. Click on node
for this gene and examine the information in the gene info
panel.
4. Select an additional TF in the regulator panel (e.g., ABF4/
At3g19290) to see interactions between the two genes and the
input gene set. It is possible to sort by CO (coexpression
column indicating what percent of the input genes are coexpressed—in a TF2Network internal coexpression database—
with the inferred regulator), PD (experimentally determined
protein-DNA data column showing percent of input genes
having PDI data) or the PWM column (the number of PWM
matches to input set promoters is shown in the Hits column)
(see Fig. 28). With TF2Network, we see that ABI5
(At2g36270) has experimentally determined protein-DNA
interactions with 41% of the input set promoters. It is also
coexpressed (based on TF2Network’s own database of coexpression analyses) with 90% of the input gene set, and has PWM
Arabidopsis Bioinformatics
77