in the database. We are interested in ABI3, and there happens
to be an ABI3 knockout experiment: scroll down to “abi3-6
16 DAF Seed.” Notice how the correlation is negative. Click
the leftmost “More info” link under the “Correlation from. . .”
columns. You will see a scatter plot showing the expression of
differentially expressed genes in the two experiments. It is
pretty amazing to see how anti-correlated this data set is.
We hope you can appreciate how powerful this tool would be if
you had a mutant whose mode-of-action was unknown. Simply by
analyzing your own expression data from that mutant with AtCAST
you would quickly be able to identify similar experiments in the
database, which could lead you quite rapidly to a functional
hypothesis as to the role for the mutant gene.
3.6 Promoter
Analysis
Gene expression is dependent on the cis-regulatory elements present in the promoter regions of genes. These elements act as binding
sites for one or more transcription factors. Many tools have been
developed to better understand how these transcription factorbinding sites might regulate such expression. In this section we
will introduce tools that will help us to analyze and visualize promoter regions of Arabidopsis genes.
3.6.1 Cistome
Imagine a set of genes that are coexpressed in response to a certain
stimulus. It will be of interest to determine common upstream
regulatory motifs between these genes that could explain this particular behavior and identify putative upstream regulators. Cistome
[36] is a tool that searches for enriched motifs in the promoter
regions of these genes.
1. Go to http://www.bar.utoronto.ca/cistome/cgi-bin/BAR_
Cistome.cgi. Enter the AGI ID list in the “Enter a list of
genes” box and click “Add to List.” You will use the top
50 coexpressed genes for ABI3 across a “Developmental
Map” as identified with the Expression Angler tool (see Supplementary Table S1).
2. Choose “TSS/TrSS (TAIR upstream)” as the start position and
1000 bp as the sequence length.
3. Choose a motif set. In this section, we are interested in studying whether a particular motif is overrepresented in the promoter regions of our gene set. Under the “Enter Motifs” tab,
select “Paste in your own PSSMs or consensus sequences”
(PSSMs are Position Specific Scoring Matrices, a more flexible
way to represent transcription factor binding sites and describes
the probability of how often a given nucleotide can be present
at each position of the motif). Select the blank option for the
“Data set” dropdown menu.
4. Enter the search sequence in the format required. Here, we will
use the G-box motif (CACGTG), which is a binding site for the
PIF transcription factor family.
Arabidopsis Bioinformatics
47
to be an ABI3 knockout experiment: scroll down to “abi3-6
16 DAF Seed.” Notice how the correlation is negative. Click
the leftmost “More info” link under the “Correlation from. . .”
columns. You will see a scatter plot showing the expression of
differentially expressed genes in the two experiments. It is
pretty amazing to see how anti-correlated this data set is.
We hope you can appreciate how powerful this tool would be if
you had a mutant whose mode-of-action was unknown. Simply by
analyzing your own expression data from that mutant with AtCAST
you would quickly be able to identify similar experiments in the
database, which could lead you quite rapidly to a functional
hypothesis as to the role for the mutant gene.
3.6 Promoter
Analysis
Gene expression is dependent on the cis-regulatory elements present in the promoter regions of genes. These elements act as binding
sites for one or more transcription factors. Many tools have been
developed to better understand how these transcription factorbinding sites might regulate such expression. In this section we
will introduce tools that will help us to analyze and visualize promoter regions of Arabidopsis genes.
3.6.1 Cistome
Imagine a set of genes that are coexpressed in response to a certain
stimulus. It will be of interest to determine common upstream
regulatory motifs between these genes that could explain this particular behavior and identify putative upstream regulators. Cistome
[36] is a tool that searches for enriched motifs in the promoter
regions of these genes.
1. Go to http://www.bar.utoronto.ca/cistome/cgi-bin/BAR_
Cistome.cgi. Enter the AGI ID list in the “Enter a list of
genes” box and click “Add to List.” You will use the top
50 coexpressed genes for ABI3 across a “Developmental
Map” as identified with the Expression Angler tool (see Supplementary Table S1).
2. Choose “TSS/TrSS (TAIR upstream)” as the start position and
1000 bp as the sequence length.
3. Choose a motif set. In this section, we are interested in studying whether a particular motif is overrepresented in the promoter regions of our gene set. Under the “Enter Motifs” tab,
select “Paste in your own PSSMs or consensus sequences”
(PSSMs are Position Specific Scoring Matrices, a more flexible
way to represent transcription factor binding sites and describes
the probability of how often a given nucleotide can be present
at each position of the motif). Select the blank option for the
“Data set” dropdown menu.
4. Enter the search sequence in the format required. Here, we will
use the G-box motif (CACGTG), which is a binding site for the
PIF transcription factor family.
Arabidopsis Bioinformatics
47