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Pseudomonas Genome Database - 2014 Gene Ontology Annotation Initiative

2014 Gene Ontology Annotation Initiative

We have launched a new initiative to apply a critical and conservative approach to mapping high quality, curated gene ontology (GO) terms to the P. aeruginosa PAO1 genome annotation. The database is recognized as an authoritative source for high quality genome annotations and we feel users can benefit from an ontology-rich data structure providing details of function and biological processes in a specific and hierarchical manner. By having data in this format, we can utilize a wide range of tools for the purpose of improving annotation transfer and enrichment analysis associated with omics studies being conducted in many labs.

Annotate some GO terms, get your name on a paper!

While there are ways to automate the process using computational predictions, this is not accurate or specific enough for the high quality annotation we wish to continue to provide. We therefore are putting out a call to the PseudoCAP Community to see if they are interested in participating in the annotation/curation process, in return for authorship on a paper.

The project is well underway and an initial pilot consisting of a select group of Pseudomonas aeruginosa researchers is already wrapping up. We hope you can assist us by annotating genes in your area of expertise with GO terms. We plan to publish the results of this approach in a leading biological database journal, whereby all significant contributors of annotations will be added as co-authors (as a consortium).

If you are interested in participating in this venture and want to hear how you can be of help, please contact us at pseudocap-mail@sfu.ca

Frequently Asked Questions

What is the Gene Onotology (GO)?

The Gene Ontology provides a controlled vocabulary (GO Terms) and associated definitions to describe genes and their products. All Gene Ontology terms fall into one of three namespaces (domains)

  1. Molecular Function
  2. Biological Process
  3. Cellular Component

The ontology terms are structured as a "directed acyclic graph" whereby each term has a number of defined relationships between other terms in the same namespace.

If you would like more details about the Gene Ontology, please visit the consortium website or read the most recent publication.

What are the benefits of mapping genes to GO terms?

  1. The use of GO terms by collaborating databases facilitates uniform queries across them.
  2. Controlled vocabularies are structured so that they can be queried at different levels. For example, you can use GO to find all the gene products in the Pseudomonas aeruginosa PAO1 genome that are involved in signal transduction (GO:0007165 ), or you can zoom in on all gene products with phosphorelay response regulator activity (GO:0000156).
  3. You can take advantage of a wide range of tools developed for querying gene ontology terms. For example, you can do GO term enrichment (over-representation analysis) on large data sets including RNA-Seq and microarray data.
  4. Depending on how much we know about a particular gene, we can assign annotations at different levels of specificity.

Which genes can I annotate?

We are very flexible. You are welcome to submit annotations for genes in your area of expertise or what you find interesting.

We are most interested in genes that have been experimentally studied in P. aeruginosa. If you find annotations for genes in other well-studied organisms (e.g. E. coli) and your expert knowledge indicates that the same annotation applies for P. aeruginosa,we will be happy to receive those too. Feel free to send us (pseudocap-mail@sfu.ca) a list of genes you would like to annotate so that we can make sure your efforts are not being duplicated.

Are the annotations submission subject to any review?

Our philosophy is that critical, conservative annotation is most important, and as part of the submission process, all annotations will undergo review. We encourage participants to provide GO terms that are clearly supported by scientific literature.

How much of a time commitment will it be?

With a large number of researchers participating, we don't anticipate it taking very long to put together a submission worthy of being included on the paper. As a rule of thumb, we would appreciate each participant to provide GO annotations for around 5 genes (with each one having multiple terms). We ask that you also summarize the role that each listed participant played in the annotation process.

Where can I find more instructions for how to assign GO terms for this project?

We have put together a help document detailing what we are looking for annotators to provide (download)