[Gramene] GO analysis of RNA-Seq data

[Loraine, Ann]

Hello,

I am using GOSeq (Bioconductor package) to analyze some RNA-Seq data from rice.

I'm writing to ask your advice on how to best use the rice GO annotations Gramene has provided on the geneontology.org Web site.

I have differential expression information for genes annotated as part of the (latest) MSU7 gene annotations release.

(I made it by aligning my reads against the assembly. I then counted reads that overlapped the MSU7-annotated gene models.)

However, it is not entirely clear how to map rice genome locus ids (such as LOC_Os06g31210) onto the Gene Ontology category annotations listed in the gene association file (gene_association.gramene_oryza.gz) available from geneontology.org.

I see that some of the lines contain ids such as LOC_Os06g31210, which look like gene ids from the MSU annotations.

My question is: can you explain how I should map MSU7 locus ids onto the GO ids listed in the file?

It looks like you were using the Uniprot id as the primary key. If I could get a mapping between Uniprot id and MSU7 locus identifiers, that would probably be enough.

Could you let me know what the best way to do this would be?

I can easily run blast, blat, or write a simple program to match fields across files. For example, I could extract the genomic sequence for each gene model and then use blastx to identify the best hit protein id from SwissProt/UniProt. If the GO file is using the Uniprot id as the primary key, then I could link locus ids to GO terms using the best hit from Uniprot.

Does this sound like it would work or would you recommend a more straightforward path?

Thank you so much for the Gramene resource and for providing the GO annotations!

Best wishes,

Ann Loraine

-------------------------------
Ann Loraine, Ph.D.
Associate Professor
Department of Bioinformatics and Genomics
University of North Carolina at Charlotte
North Carolina Research Campus
600 Laureate Way
Kannapolis, NC 28081
704-250-5750
aloraine at uncc.edu
http://www.transvar.org
http://www.bioviz.org
http://www.uncc.edu

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