cacao biocurator training cacao fall 2011. cacao syllabus what is cacao & why is it important?...
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Mutualistic Relationship
• We want you to get experience with: 1. CRITICALLY reading scientific papers 2. Bioinformatics resources3. Collaborating with other biocurators4. Synthesizing functional annotations
• We want to get high quality functional annotations to contribute back to the GO Consortium and other biological databases
What is a functional annotation?
• Process of attaching information from the scientific literature to proteins
Growing need for functional annotations
• Advances in DNA sequencing mean lots of new genomes & metagenomes
Growing need for high quality functional annotations
• High quality annotations allow us to infer the function of genes
• Which allows us to understand the capabilities of genomes and understand the patterns of gene expression
Two problems meet
How can we get more curators
with finite budgets?
How can we incorporate more
critical analysis intoundergraduate
education?
What does a functional annotation have to do with this course?
• Process of attaching information from the scientific literature to proteins
• CACAO will teach you to become a biocurator– you will be adding functional annotations to the biological database GONUTS
(http://gowiki.tamu.edu)
CACAO
Community
Assessment- How well can
Community - you (with our coaching)
Annotation with- assign gene functions
Ontologies- using GO?
Can students become biocurators? YES!
Spring 2010 Fall 2010 Spring 2011
Institutions TAMU TAMU
UCL
TAMU
Miami (Ohio)
N. Texas
Penn State
Mich. State
Rounds 1 round 4 rounds 5 rounds
Annotations* / Submitted
118/153 496/753 726/1013
1340 GO annotations in 2 & 1/2 semesters!
Functional annotation with Gene Ontology
• Controlled vocabulary with – Term identifiers
• GO:0000075
– Name• cell cycle checkpoint
– Definitions• "A point in the eukaryotic cell cycle where
progress through the cycle can be halted until conditions are suitable for the cell to proceed to the next stage." [GOC:mah, ISBN:0815316194]
– Relationships• is_a GO:0000074 ! regulation of progression
through cell cycle
• Terms arranged in a Directed Acyclic Graph (DAG)
Why use Ontologies?
• Standardization• facilitate comparison across systems• facilitate computer based reasoning systems
– Good for data mining!
• leading functional annotation ontology = Gene Ontology (GO)
What is GO? Who is the GO Consortium (GOC)?
• GO = ~30,000 terms for gene product attributes
1. Molecular Function (enzyme activity)
2. Biological Process (pathways)
3. Cellular Component (parts of the cell)
• GO Consortium - set of biological databases that are involved in developing GO and contributing GO annotations
Molecular Function
• activities or “jobs” of a gene product
glucose-6-phosphate isomerase activity
figure from GO consortium presentations
Biological Process
• a commonly recognized series of events
cell divisionFigure from Nature Reviews Microbiology 6, 28-40 (January 2008)
Which subontology (MF, BP or CC) would the following terms fit in?
GO:0003909 DNA ligase activity
GO:0071705 Nitrogen compound transport
GO:0007124 Pseudohyphal growth
GO:0015123 Acetate transmembrane transporter activity
GO:0071514 Genetic imprinting
GO:0005773 Vacuole
GO:0000312 Plastid small ribosomal subunit
Questions?
1. You will be making functional (GO) annotations using GO terms.
2. You can search for GO terms on GONUTS.
What do we know so far?
Why are we using GONUTS?
• Students can add functional annotations to proteins.
• It has all the GO terms in it, too.• Some of the GO terms have usage notes. • It works a lot like Wikipedia, so it’s familiar.• It has the ability to keep track of each student’s
and team’s annotations.• We run it.
http://gowiki.tamu.edu
REQUIRED parts of a GO annotation
GO
http://gowiki.tamu.edu/wiki/index.php/ECOLI:LPOB
** I will cover this again!!
Questions?
1. You will be making functional (GO) annotations using GO terms.2. You can search for GO terms on GONUTS.
3. You will be adding your GO annotations to GONUTS.4. There are 4 required parts to a GO annotation.5. You have to base your annotation on an experiment
published in a scientific paper.
What do we know so far?
Next week
• Review of GO & GO annotations
• More biocurator training– lots of examples– lots of practice
BICH 485 & 689 students - please stick around to talk about these courses!
Plan for training
1. Synthesizing GO annotations
2. Refinements
3. Judging & Assessment
4. Individual & Team tracking
What can you annotate?
• Proteins. – Any protein with a record in UniProt (Universal Protein Resource -
http://uniprot.org)
• How can you find proteins to annotate?– Think of ways to identify a protein or paper to annotate
Choosing a protein to annotate
1. randomly2. topics of interest (ie efflux pump proteins, biofilms, marine biology)3. papers you have come across while doing other stuff4. methods you know or want to learn5. phenotypes and mutants you are interested in6. by author7. by pathway or regulon 8. suggested by another
- high ratio of IEA:manual annotations in GONUTS- mentioned in another class
9. current paper mentions another gene product10. review papers (ie Annual Reviews are excellent sources)11. Uniprot, GONUTS, WikiPathways, PubMed searches12. protein annotated by other teams13. ask a coach
Practice
1. What is the GO term for GO:0004713?
2. What is the GO identifier for mitosis?
3. How many results (ballpark) do you get when you search for cell division using the Go, Search or G buttons?
4. How many child terms are there for plasma membrane? How many grandchildren?
5. What term is the parent of GO:006825?
http://gowiki.tamu.edu
Finding a scientific paper on a certain protein
• Has to be a scientific paper with experimental data in it.– Anything else is a valid reason to challenge!
• PubMed, PubMed Central, GoogleScholar…• No review articles• no books, textbooks, wikipedia articles, class
notes…• You will need the PMID number
Practice - searching PubMed
1. How many papers do you get when you search for “coli”?2. How many of those papers are reviews?3. What is the title of the oldest paper when you search for “coli AND
RNA polymerase”?4. How many results are there when you search for “GTPase activity
and Gene Ontology”?5. What is the PMID of the paper when you search for “Hu JC AND
coli AND lysR AND 2010”?
http://pubmed.org
Why do we annotate on GONUTS?
• UniProt (Universal Protein Resource) will not let us annotate protein records on their site.
• They are a professionally-curated & closed database.
• GONUTS will.• GONUTS pulls the info from the UniProt record when it
makes a page for you to edit.
• UniProt - http://www.uniprot.org
• UniProt is not community edited, so we can’t add annotations directly to their database
Making a protein page on GONUTS requires a UniProt accession
Practice - Searching UniProt
Find the UniProt accessions for:a) Mouse Lsr proteinb) Diptheria toxin from Corynebacteriumc) mutS from E. coli K-12
http://uniprot.org
How do you make a new gene page in GONUTS?
1 2
• Use a UniProt accession to make a page on GONUTS that you can add your own annotations to.
• GoPageMaker will:- Check if the page exists in GONUTS & take you there if it does.- Make a page & pull all of the annotations from UniProt into a table that you can edit.
Practice
1. How many annotations are on the page for the p53 protein from humans?
2. How many different evidence codes are there on the page for the Bub1a protein from mice?
3. Give one of the paper identifiers for an annotation for the LpxK protein from E. coli.
http://gowiki.tamu.edu
Questions?
1. You will be making functional (GO) annotations using GO terms.2. You can search for GO terms on GONUTS.3. You will be adding your GO annotations to GONUTS.4. There are 4 required parts to a GO annotation.5. You have to base your annotation on an experiment published in a
scientific paper.
6. You can annotate any protein with a record in UniProt.
7. You have to make a page in GONUTS for your protein using the UniProt accession.
What do we know so far?
What are evidence codes?
• Describe the type of work or analysis done by the authors
• 5 general categories of evidence codes:1. Experimental2. Computational3. Author Statement4. Curator Assigned5. Automatically assigned by GO
• Describe the type of work or analysis done by the authors• 5 general categories of evidence codes:
1. Experimental2. Computational3. Author Statement4. Curator Assigned5. Automatically assigned by GO
• CACAO biocurators may only use certain experimental and computational evidence codes
What are the evidence codes?
Experimental Evidence Codes
• IDA: Inferred from Direct Assay• IMP: Inferred from Mutant Phenotype• IGI: Inferred from Genetic Interaction• IEP: Inferred from Expression Pattern• IPI: Inferred from Physical Interaction• EXP: Inferred from Experiment
Experimental Evidence Codes
• IDA: Inferred from Direct Assay• IMP: Inferred from Mutant Phenotype• IGI: Inferred from Genetic Interaction• IEP: Inferred from Expression Pattern• IPI: Inferred from Physical Interaction• EXP: Inferred from Experiment
http://geneontology.org/GO.evidence.shtml
Computational Evidence Codes
• ISS: Inferred from Sequence or Structural Similarity• ISO: Inferred from Sequence Orthology• ISA: Inferred from Sequence Alignment• ISM: Inferred from Sequence Model• IGC: Inferred from Genomic Context• IBA: Inferred from Biological Aspect of Ancestor• IBD: Inferred from Biological Aspect of Descendant• IKR: Inferred from Key Residues• IRD: Inferred from Rapid Divergence• RCA: Inferred from Reviewed Computational Analysis
http://geneontology.org/GO.evidence.shtml
Computational Evidence Codes
• ISS: Inferred from Sequence or Structural Similarity• ISO: Inferred from Sequence Orthology• ISA: Inferred from Sequence Alignment• ISM: Inferred from Sequence Model• IGC: Inferred from Genomic Context• IBA: Inferred from Biological Aspect of Ancestor• IBD: Inferred from Biological Aspect of Descendant• IKR: Inferred from Key Residues• IRD: Inferred from Rapid Divergence• RCA: Inferred from Reviewed Computational Analysis
http://geneontology.org/GO.evidence.shtml
Summary of Evidence Codes for CACAO
• IDA: Inferred from Direct Assay• IMP: Inferred from Mutant Phenotype• IGI: Inferred from Genetic Interaction• IEP: Inferred from Expression Pattern• ISO: Inferred from Sequence Orthology• ISA: Inferred from Sequence Alignment• ISM: Inferred from Sequence Model• IGC: Inferred from Genomic Context
• If it’s not one of these 8, your annotation is incorrect!!!
Required parts (for every annotation)
GO:0004713
PMID:1111
IDA: Inferred from direct assay
Figure 2a
Questions?
1. You will be making functional (GO) annotations using GO terms.2. You can search for GO terms on GONUTS.3. You will be adding your GO annotations to GONUTS.4. There are 4 required parts to a GO annotation.5. You have to base your annotation on an experiment published in a
scientific paper.
6. You can annotate any protein with a record in UniProt.
7. You have to make a page in GONUTS for your protein using the UniProt accession.
What do we know so far?
Practice - Identify the problem annotation(s) & why
1. GO:0003674 PMID:20372022 IDA: Inferred from Direct Assay Table 2. 2. GO:0016985 PMID:20372022 IMP: Inferred from Mutant Phenotype Table 2. 3. GO:0016985 PMID:20372022 IDA: Inferred from Direct Assay 4. GO:0016985 PMID:20372022 IDA: Inferred from Direct Assay Table 2. 5. GO:0003674 PMID:20372022 IDA: Inferred from Direct Assay Table 2.6. GO:0016985 PMID:20372002 IGI: Inferred from Genetic Interaction Table 2.7. GO:0016985 20372022 IDA: Inferred from Direct Assay Table 2.8. GO:0016985 PMID:20372002 EXP: Inferred from Experiment Table 2.
9. What is the UniProt accession of the protein described/annotated?
GO ID Reference Evidence Code Notes
How is CACAO scored?
• Points for a complete annotation• GO term (right level of specificity)• Reference (paper)• Evidence code• Identify where in the paper the evidence is
• Refinements used to steal points for incorrect &/or incomplete annotations
• Identify a problem • Suggest correct alternative
• Refinements can be entered by any team (including the original team)
How can you get the annotations required by Rubric #2?
1. Synthesize complete & correct annotations.
2. Correctly refine (challenge & correct) someone else’s annotation.
3. If your annotation gets challenged, offer the best correction.
Summary
• You will be searching literature for experimental evidence for a protein’s function (MF), processes (BP) and location (CC)