there are quite a few SNPs in the upstream region of ABI3 that
also overlap a transposable element. Most interestingly, this
region is also highly sensitive to DNaseI cleavage as evidenced
by the union peak track indicating likely active transcriptional
regulation. For the CHH-methylation data, we can see that the
upstream transposons are depleted for this methyl-cytosine
context in the ago4 mutant. There also appears to be a region
that is highly enriched in H3K27me2 within the gene body of
ABI3. You may even predict that some of the SNPs located in
this putative regulatory region may have functional consequences for ABI3 expression, a hypothesis which could be
easily tested.
Two other useful sites that we call your attention to here are the
Ecker Laboratory’s 1001 Epigenomes Browser at http://
neomorph.salk.edu/1001.aj.php [23] and the Jacobsen Lab Epigenomics Browser at https://www.mcdb.ucla.edu/Research/
Jacobsen/LabWebSite/P_EpigenomicsData.php, where several
publications’ worth of data are available for browsing. However,
EPIC-CoGe appears to be the most comprehensive resource
to date.
3.4 Expression
Analysis
Online expression analyses can be useful in place of performing
Northern analyses, quantitative RT-PCR or constructing promoter:reporter fusions to determine patterns of expression. For
instance, imagine we had identified an abi3 mutation by positional
cloning and wanted to know more about its biological function,
and perhaps to guide us where to look elsewhere for a phenotype.
One of the first steps would be to examine its expression pattern.
Online tools such as the eFP Browser or Genevestigator make this
very easy, provided the platform used for measuring the transcriptome is able to detect the transcript for one’s gene of interest (see
Note 4).
3.4.1 eFP Browser
The eFP (“electronic fluorescent pictograph”) Browser at the
Bio-Analytic Resource for Plant Biology at http://bar.utoronto.
ca/efp/cgi-bin/efpWeb.cgi [24] provides easy access to 150 million expression measurements from A. thaliana, soybean (Glycine
max), barrel medic (Medicago truncatula), poplar (Populus trichocarpa), maize (Zea mays), barley (Hordeum vulgare), rice (Oryza
sativa), and others. Four-fifths of the measurements were made
using Arabidopsis samples. Small pictographs are used to represent
the experimental samples and contexts from which the expression
data were generated, while differing expression levels within these
samples are denoted by a color scale.
1. Go to http://bar.utoronto.ca and select “Arabidopsis eFP
Browser” from the BAR’s homepage.
36
G. Alex Mason et al.
also overlap a transposable element. Most interestingly, this
region is also highly sensitive to DNaseI cleavage as evidenced
by the union peak track indicating likely active transcriptional
regulation. For the CHH-methylation data, we can see that the
upstream transposons are depleted for this methyl-cytosine
context in the ago4 mutant. There also appears to be a region
that is highly enriched in H3K27me2 within the gene body of
ABI3. You may even predict that some of the SNPs located in
this putative regulatory region may have functional consequences for ABI3 expression, a hypothesis which could be
easily tested.
Two other useful sites that we call your attention to here are the
Ecker Laboratory’s 1001 Epigenomes Browser at http://
neomorph.salk.edu/1001.aj.php [23] and the Jacobsen Lab Epigenomics Browser at https://www.mcdb.ucla.edu/Research/
Jacobsen/LabWebSite/P_EpigenomicsData.php, where several
publications’ worth of data are available for browsing. However,
EPIC-CoGe appears to be the most comprehensive resource
to date.
3.4 Expression
Analysis
Online expression analyses can be useful in place of performing
Northern analyses, quantitative RT-PCR or constructing promoter:reporter fusions to determine patterns of expression. For
instance, imagine we had identified an abi3 mutation by positional
cloning and wanted to know more about its biological function,
and perhaps to guide us where to look elsewhere for a phenotype.
One of the first steps would be to examine its expression pattern.
Online tools such as the eFP Browser or Genevestigator make this
very easy, provided the platform used for measuring the transcriptome is able to detect the transcript for one’s gene of interest (see
Note 4).
3.4.1 eFP Browser
The eFP (“electronic fluorescent pictograph”) Browser at the
Bio-Analytic Resource for Plant Biology at http://bar.utoronto.
ca/efp/cgi-bin/efpWeb.cgi [24] provides easy access to 150 million expression measurements from A. thaliana, soybean (Glycine
max), barrel medic (Medicago truncatula), poplar (Populus trichocarpa), maize (Zea mays), barley (Hordeum vulgare), rice (Oryza
sativa), and others. Four-fifths of the measurements were made
using Arabidopsis samples. Small pictographs are used to represent
the experimental samples and contexts from which the expression
data were generated, while differing expression levels within these
samples are denoted by a color scale.
1. Go to http://bar.utoronto.ca and select “Arabidopsis eFP
Browser” from the BAR’s homepage.
36
G. Alex Mason et al.