[Arabidopsis] BAR News, November 2010: combining interaction and expression data, a rice interactome, next generation mapping and more!

Nicholas Provart via arab-gen%40net.bio.net (by nicholas.provart from utoronto.ca)
Thu Nov 4 14:31:43 EST 2010


Hello Arabidopsis Researchers,

Several students and research associates have been busily at work in my lab
these past 6 months, and have developed some more bioinformatic tools and
analyses we hope you'll find useful. You can find these at the Bio-Array
Resource at http://bar.utoronto.ca. Thanks to Robert Breit [1,2,7], Joe Wu
[3], Rohan Patel [4,5], Ryan Austin [1,7], Garon La [8], Kante Easley [8],
and Hardeep Nahal [1-8] for their efforts!

1. Cistome and Cistern for mapping and analysing promoter sequences for
over-represented motifs have been merged into one easier-to-use web
application, Cistome. It is now possible to discover and map PSSMs onto one
of several promoter data sets (up to 3 kb) or onto your own promoter data
set, and to view SeqLogos and positional distribution graphs for the
resultant matches.

2. Our Arabidopsis Interactions Viewer containing 70,944 predicted (see
Geisler-Lee et al. 2007) and 4,300 confirmed protein-protein interactions in
Arabidopsis now has an improved output generated with Cytoscape Web,
developed by the Bader and Morris labs at the University of Toronto.
Additionally, it is now possible to overlay gene expression data from more
than 2,500 expression data sets archived in the BAR onto the AIV nodes
generated by an AIV query or from an uploaded PPI network, to get an idea of
which subnetworks might be active in certain tissues or under certain
conditions. 

3. In collaboration with Matt Geisler at Southern Illinois University we
have developed a Rice Interactions Viewer for exploring 37,112 predicted and
68 documented rice interactions. In addition, the subcellular localizations
for these rice proteins, predicted by Shanghai Jiao Tong University
researcher Hong-Bin Shen's Plant-mPLoc algorithm (Chou et al. 2010, PLoS
ONE), may be viewed within the RIV. Additionally, rice expression data may
be overlaid onto the nodes, as described above.

4. Two new eFP Browsers make their debut: a Maize eFP Browser based on
mRNA-seq expression data from the Brutnell lab at Cornell, just published in
Li et al. in Nature Genetics (http://dx.doi.org/10.1038/ng.703), and a
Soybean eFP Browser based on data from Libault et al.'s (2010) Plant
Physiol. and Plant Journal papers.

5. BAR Expressologs: we have computed the most likely "expressolog"
(expression homolog) for most genes across 6 plant species: Arabidopsis,
poplar, rice, barley, soybean, and barrel medic, based on inferred tissue
equivalencies and expression profile similarity in the gene expression
developmental atlases available for these species. Links that appear at the
top of the eFP Browser pages will guide you to the homolog with the most
similar expression profile in another species, insofar as this is possible.

6. Our collaborator Quaid Morris has made the AraNet functional prediction
network described by Sue Rhee and colleagues (Lee et al., 2010) available in
his GeneMANIA interface for easy exploration at http://genemania.org, under
the Predicted option for Arabidopsis.

7. A Next Generation Mapping application is available
(http://bar.utoronto.ca/ngm) for using Next Generation Sequencing data from
pooled F2 populations to rapidly map causal SNPs from EMS mutants identified
in e.g. forward genetic screens.

8. Our ePlant (Fucile et al., PLoS ONE, accepted) now contains a sequence
polymorphism viewer for viewing synonymous and non-synonymous SNPs (from
Jander et al. 2002 and Nordborg et al. 2005, with more to come from the 1001
Arabidopsis Genomes project) along with sequence homologs from other
species. Clicking on a residue that has a non-synonymous change will take
you to its location in the corresponding protein's predicted or determined
tertiary structure. It is also possible to browse additional cell-type and
tissue-level gene expression data sets in ePlant's 3D framework.

As always, we welcome your feedback.

Best,

Nick

.........................................
Nicholas Provart, PhD
Associate Professor, Plant Cyberinfrastructure & Systems Biology
Director, Graduate Program in Genome Biology and Bioinformatics
Chair, Bioinformatics SC, Multinational Arabidopsis Steering Committee
Member, Centre for the Analysis of Genome Evolution and Function
Rm 3051, Dept. of Cell and Systems Biology, Uni. Toronto
25 Willcocks St., Toronto, ON. M5S 3B2. CANADA

Tel. (+1) (416) 978-7141, Fax. (+1) (416) 978-5878
URL. http://www.csb.utoronto.ca/faculty/provart-nicholas
The Bio-Array Resource. http://www.BAR.utoronto.ca   
email. nicholas.provart from utoronto.ca
TTC. Spadina LRT, Willcocks St.





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