AtREA
- Arabidopsis thaliana regulatory
element analyzer
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is a collection of programs
for analysis of distribution,
features
and combination of known and novel CREs
(Cis-Regulatory
Elements ) in
Arabidopsis
functional classes, metabolic pathways, genome
wide microarray and user defined datasets.
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Doc
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Distribution
of CRE: The CRE distribution
analysis module in ATREA has been designed to study CRE
distribution in arabidopsis functional classes and coexpressed gene
sets. The functional classes that can be analyzed using this module
includes all three Gene Ontology(GO) categories -biological process(GOBP), molecular function(GOMF) and cellular component(GOCC) and
MIPS FUNCAT subgroups. This module can be also used to metabolic
pathways and expression classes (derived from microarray data). Many
known Arabidopsis CREs require the presence of a second
CRE in nearby region to be functional (ABRE, for example,requires the
presence of a coupling element(CE) ) and therefore occur as
structured cis-regulatory pairs or modules. The CRE pairs subsection can be used to study the distribution of such CRE pairs where both the component
CREs as well as maximum and minimum distance within them can be
specified in the input menu. The CRE-combination subsection can receive
a set of up to four different CREs (separated by hash sign) as input and analyze
their distribution in functional and expression classes.
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Help
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| CRE
feature analysis module |
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Evaluation
of CRE features: CRE feature analysis module of AtREA can be
used to evaluate strand and positional trends in a CREs distribution
in upstream sequences in Arabidopsis genome. Moreover by selecting an
expression slide and expression type from slide and expression type
menu, this analysis can be applied to a specific expression
dataset/user deifned list fo genes,
which in addition of detecting strand and positional preference also
evaluates the impact of position and strand in expression. For many
CREs like ACGT core consensus it has been shown that the frequency of
occurrence of this CRE in promoter can have direct impact on
expression. The "frequency" option from the CRE feature menu can be
used to analyze the impact of multiple occurrences of a CRE in
expression of genes. The “variant” analysis option
generates all possible single nucleotide variants of the supplied CRE
and compares the distribution of these variants with the original
user defined CRE both in genome and the selected expression dataset.
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Help
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| Promoter
state analysis module |
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Promoter state analysis
tool: The promoter
state module of AtREA has been designed to study the role of
CREs/CRE combinations in regulation of gene expression. This module
takes as input a set of induced/repressed genes(from expression
dataset/or user defined list) and a set of CREs that may be involved
in expression regulation under the given condition, which can be
derived from literature/experimental data and/or computational
analysis. The module first segregates the upstream sequence set into
CRE states based on presence/frequency of occurrence of each of the
user defined CREs.
The
module then compares the expected frequency of occurrence of each of
the states (assumed from their respective genomic occurrences) to
their actual frequency of occurrence in the selected gene set and
identify overrepresented states in the selected gene set. The CRE
state module can therefore be applied for identification of CRE/CRE
combinations that show significant over representation in
induced/repressed genes in a experimental condition and also to
recognize CRE combination which show significant difference in
expression compared to expression of the component CREs.
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Help
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| Future Improvements |
In the next version of AtREA we plan to include:
A module for CRE conservation analysis among different plant species.
Increase the upstream sequence length and inlcude UTRs in the sequence dataset
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To cite AtREA please refer to:
Choudhury A and Lahiri A (2008) Arabidopsis thaliana regulatory element analyzer Bioinformatics, 24: 2263 - 2264.
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ananyo.c@gmail.com
Department of
Biophysics, Molecular Biology and Genetics,
University
of Calcutta, India
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