US2TS presentation on Gene Ontology http://us2ts.org/

1. Chris Mungall
Lawrence Berkeley National
Laboratory
Life Sciences Session
US2TS 2018@chrismungall
Gene Ontology: Lessons Learned

2. 2001: we sequenced the human
genome…

3. ftp://ftp.ncbi.nlm.nih.gov/refseq/H_sapiens/annotation/GRCh38_latest/refseq_identifier
s/GRCh38_latest_genomic.fna.gz
ATTGGGTTGCACCCATCTGTGCTGCGGACTCTTCCCTCGGAATGAGAGAGGGAGATGGCTCCCAGTGTGGTTGG
AAGTCA
CCCCACCCCACAACAACACAGTGCAACAGGCCCCGGCTTCACGCCCATTCAGTTCAGGACAAGTTTTTTGGAGC
ATCTAC
TCTGGGCCAGGCCCGTAGGATACTAAGATGAAATAGAGACAGTTCCTGCCTTTGAAGGGTGGTGATTTACCGGT
GGGGAG
AAAGGAAGAGGCCCATGAAAAGTCGTGTCTGTAGAAGGTAAGAAGGGGCACAACCGCCATGGCAGGGGAGT
CACAAAGGA
GAAGCATTCAGCCTGCCGAGAGGTCCCAGGACTTTCCTGGAGGATCAGTCCCCAAACTGACTGTGACAGGGA
GCTAGACC
CAGATAACAGCAGAGGCCCAGAATAAGAAAGAGTCTGTGAGTGGGCAGAATTCCCTCCAGGGTCATGAGGGG
AGCTGACT
TCTGATTAGGGCATTTCATCCTTCTCTGAAATGCAGCTGAGAACTGGTCAGCCTCACTCCCTTGCTGAGACCAAT
AGCAA
TCCCTGATGATCTTGCCACAGGTCCAGCAGGTGCCCCATCCACACTTTGTCCCCAGCCCCTACCAGGAAGCTC
CAAACAC
CTACCTGAGGGGCCAACTCTGATTCCCAAGGAGGTGACACCTCCTGCCCCTTGTTGATAGAACATTGATAAGGA
AATAGG
ACTGAGTTTTAAGCTTCTTTCCATGTCAAATATTTAAAGGCAATATAATGTTCAAGTTTAAATAATATTTCATGTGTA
AT
TAAACAATCCCTTATTGTTAAATAGATGGGTTCCAATTTTGAACTGCTATAATCTGTGTATGTGTCCTTGATTAAAT
CCT
TAAGAGAAATCCCTAGAAACATTATCTTAGGGTCAAATGGCTTGGATATTCTGTAAACTGCTGATAATTATGGGAA
ATTG
CCTTCCAGGAAGGTTATAACAATTTGCCTGATCCCCAGCAGCAACAGACTTTACAAAGTACTCAGTATCTAATAT
TTAAC
TTTGATAAAGATAAGCTTCTCCCTTCTTTTTCACTTAAAATGCTCTGTCCCACCTCACTTTTCAGTGTCTCTTCACA
CTG
ACTAGACGGTTGGCTAATACTTCAGAGCTTGCAGAGCATCTTTATACACTTTTAATCCTCCTAACAACCGTGAGA
GATGG
AGCTTACTATTATCATCCGTGTTTGCAAATGAGGCCCTGAGAAGTTGAGTGATTTCTGTAAGGTCTCAGAGCCAA
TAGAC
ACTGGTAATGAAATAAAATGCAAGGCCCCTTATCTTTGGAGCCCAGTGTTCCTTCCACATAGGTGGTTCTCCACC
CAGGC

4. Gene Ontology: Annotating gene
function
 Systematically annotate all genes in key species using an
ontology
 What does the gene do?
 What process is it playing a part in?
 Where in the cell is it doing this?
I bind to
DNA
I bind to
molecules
outside the
cell
I regulate
genes that
program cells
to commit
suicide!
I transduce
signals to
the nucleus
of the cell
Cell Part
Biological Process
Molecular Function
AGGCACGCCCATTCAGTTCA….ACAATTGGGTTGCACCCATCTGTGCTGCGGACTCTTCCCTCGGAATGAGAGAGGGAGATGGCCATG..
I’m in the
membran
e
I’m in the
nucleus

5. GO knowledge graph
Gene
A
ter
m
ter
m
ter
m
ter
m
ter
m
ter
m
ter
m
ter
m
Gene
B
ter
m
ter
m
ter
m
ter
m
ter
m
ter
m
ter
m
ter
m
subClassOf
subClassOf
part-of some
ter
m
ter
m
ter
m
EquivalentTo
And
Use of OWL within the Gene Ontology
2014. http://doi.org/10.1101/010090

6. Modular approach: Using
reasoning to leverage other
ontologies
glucan biosynthesis
(GO:0009250)
polysaccharide
biosynthesis
(GO:0000271)
⊑
≡
⊓
⊓
∃.has_output
≡
∃.has_output
⊑
Inferred by
OWL reasoner
biosynthesis
(GO:0009058)
glucan
(CHEBI:37163)
biosynthesis
(GO:0009058)
polysaccharide
(CHEBI:18154)

8. Beyond simple annotation /
‘tagging’
 Bags of terms are not enough to represent
biology accurately
Gene
A
ter
m
ter
m
ter
m
ter
m
ter
m
ter
m
ter
m
ter
m
Gene
B
ter
m
ter
m
ter
m
ter
m
ter
m
ter
m
ter
m

9. BFA1
mitotic
spindle
Classes
Instances
exit from
mitosis
GTPase
activity
TEM1
enabledBy
enabledBy
regulates
partOf partOf
occursIn
gene
product
...
...
... ...
GTPase
inhibitor
...
GO Causal Activity Model (GO-CAM) RDF Graphs

10. BFA1
mitotic
spindle
Classes
Instances
exit from
mitosis
GTPase
activity
TEM1
enabledBy
enabledBy
regulates
partOf partOf
occursIn
gene
product
...
...
... ...
GTPase
inhibitor
...

11. http://noctua.berkeleybop.org https://f1000research.com/posters/7-257

12. Collaborative
Editing!
http://noctua.berkeleybop.org https://f1000research.com/posters/7-257
https://github.com/balhoff/arachne
Scalable OWL-RL Abox
inferences

13. OBO Foundry and Library
http://obofoundry.org
OBO Principles each ontology
adheres to
• Open (CC BY or 0)
• Standard syntax and semantics
(OWL)
• Standard PURLs for classes
• Versioning
• Well-defined scope
• Classes should be defined
• Use of standard relations (RO/BFO)
• Documentation
• Documented Plurality of Users
• Commitment To Collaboration
• Locus of Authority
• Naming Conventions
• Maintenance
Suite of integrated ontologies
that are:
• Logically well formed
• Scientifically accurate
• Interoperable and interconnected
• Non-overlapping
A collective of ontology developers
committed to:
• Collaboration
• Shared standards
OBO Working groups:
• Technical
• Editorial
• Outreach
Examples
• GO: for describing function of genes
• Uberon: Anatomy
• ENVO: environment and habitat

14. ROBOT: Bridging Software and
Ontology Engineering
 ROBOT is an OBO Tool
 Command line tool for OWL ontologies
 Automates common ontology workflow tasks
 Automated classification
 Templated Ontology Population
 Ontology Unit Tests
 SPARQL-based QC checks
 Modular Ontology Construction (MIREOT/SLME)
 Conversion
http://robot.obolibrary.org

15. Take homes
 OWL axiomatization highly useful
 Not everyone needs to see it
 Simple graphs fine for most users
 Even advanced users use a subset
 Tools for working with OWL are getting better
 You aren’t limited to Protégé
 Design Pattern tools
 RDF is useful as base layer
 But we need abstractions on top
 Bundled triples
 Consumers like a variety of formats
 Users like TSV data dumps, JSON APIs
 We’d like to be better linked data citizens