CACAO Biocurator Training CACAO Fall 2011. CACAO Syllabus What is CACAO & why is it important? Training Examples.

CACAO Biocurator Training

CACAO Fall 2011

CACAO

• Syllabus

• What is CACAO & why is it important?

• Training

• Examples

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 an annotation?

Hint: try looking for a definition on Wikipedia.

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

Classic MODel

Literature

Datasets

Curators(rate limiting)

Database

Classic MODel is Expensive

YIKES!

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

Cellular Component

• where a gene product acts

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)

Where can we find GO terms?

http://gowiki.tamu.edu

GONUTS

http://gowiki.tamu.edu/

Search for GO terms on GONUTS


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?

Where are we adding GO annotations?


GONUTS


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.



REQUIRED parts of a GO annotation

GO

http://gowiki.tamu.edu/wiki/index.php/ECOLI:LPOB

** I will cover this again!!

Parts of a GO annotation (cont)

Evidence code

Parts of a GO annotation (cont)

Reference Notes (about evidence)

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.


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

Part 1: Synthesizing GO annotations

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

http://uniprot.org/

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

Search for GO terms on GONUTS


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?


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

http://www.uniprot.org/

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.


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 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


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


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

What you might also have to fill in


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.


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)

Where do annotations show up?

Refinements & Challenges

What can you challenge?

Scoreboard

Schedule

Spring 2011 - Results by organism

0

50

100

150

200

250

Bacillus

Burkholderia

E. coli

PseudomonasSalmonella

StaphylococcusStreptococcus

Vibrio

S. cerevisiaeChlamydomonas

ArabidopsisC. elegansDrosophilahumanmouse

Olive baboon

# wrong

# change

# perfect

CACAO Biocurator Training CACAO Fall 2011. CACAO Syllabus What is CACAO & why is it important? Training Examples.

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