lecture four: go: the gene ontology ---- infrastructure for systems biology

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Lecture Four: GO: The Gene Ontology ----Infrastructure for Systems Biology

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Lecture Four: GO: The Gene Ontology ---- Infrastructure for Systems Biology. S. cerevisiae. D. melanogaster. Cells that normally survive. CED-3 CED-4 OFF. CED-9 ON. Cells that normally die. CED-3 CED-4 ON. CED-9 OFF. C elegans. M. musculus. - PowerPoint PPT Presentation

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Page 1: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Lecture Four:

GO: The Gene Ontology----Infrastructure for Systems Biology

Page 2: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

S. cerevisiae

Page 3: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

D. melanogaster

Page 4: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Cells that normally surviveCED-9

ON

CED-3CED-4OFF

CED-9OFF

CED-3CED-4

ON

Cells that normally die

C elegans

Page 5: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

M. musculus

Page 6: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

MCM3

MCM2

CDC46/MCM5

CDC47/MCM7

CDC54/MCM4

MCM6

These proteins form a hexamer in the species that have been examined

Comparison of sequences from 4 organisms

Page 7: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

A Common Language for Annotation of Genes from

Yeast, Flies and Mice

The Gene Ontologies

…and Plants and Worms

…and Humans

…and anything else!

Page 8: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Gene Ontology - 1998

FlyBase Drosophila Cambridge, EBI, HarvardBerkeley & Bloomington.

SGD Saccharomyces Stanford.

MGI Mus Jackson Labs., Bar Harbor.

Page 9: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Gene Ontology -now

• Fruitfly - FlyBase• Budding yeast - Saccharomyces Genome Database (SGD)• Mouse - Mouse Genome Database (MGD & GXD)• Rat - Rat Genome Database (RGD)• Weed - The Arabidopsis Information Resource (TAIR)• Worm - WormBase• Dictyostelium discoidem - Dictybase• InterPro/UniProt at EBI - InterPro• Fission yeast - Pombase• Human - UniProt, Ensembl, NCBI, Incyte, Celera, Compugen• Parasites - Plasmodium, Trypanosoma, Leishmania - GeneDB - Sa

nger• Microbes - Vibrio, Shewanella, B. anthracus, … - TIGR• Grasses - rice & maize - Gramene database• zebra fish – Zfin.........

Page 10: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

To provide

structured controlled vocabularies

for the

representation of biological knowledge

in

biological databases.

Page 11: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

• Be open source

• Use open standards

• Make data & code available without constraint

• Involve your community

Page 12: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Gene Ontology Objectives• GO represents concepts used to classify

specific parts of our biological knowledge:– Biological Process– Molecular Function– Cellular Component

• GO develops a common language applicable to any organism

• GO terms can be used to annotate gene products from any species, allowing comparison of information across species

Page 13: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

GO: Three ontologies

Where does it act?

What processes is it involved in?

What does it do? Molecular Function

Cellular Component

Biological Process

gene product

Page 14: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Molecular Function 7,309 terms Biological Process 10,041 terms Cellular Component 1,629 terms

Total 18, 975 terms

Definitions: 94.9 %Obsolete terms: 992

Content of GO

Page 15: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

term: gluconeogenesis

id: GO:0006094

definition: The formation of glucose from noncarbohydrate precursors, such as pyruvate, amino acids and glycerol.

What’s in a GO term?

Page 16: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Mitochondrial P450

Annotation of gene products with GO terms

Page 17: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Cellular component: mitochondrial inner membrane GO:0005743

Biological process:Electron transportGO:0006118

Molecular function: monooxygenase activity GO:0004497substrate + O2 = CO2 +H20 product

Page 18: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Other gene products annotated to monooxygenase activity (GO:0004497)

- monooxygenase, DBH-like 1 (mouse)

- prostaglandin I2 (prostacyclin) synthase (mouse)

- flavin-containing monooxygenase (yeast)   

- ferulate-5-hydrolase 1 (arabidopsis)

Page 19: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology
Page 20: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology
Page 21: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

What’s in a name?

• Glucose synthesis• Glucose biosynthesis• Glucose formation• Glucose anabolism• Gluconeogenesis

• All refer to the process of making glucose from simpler components

Page 22: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

tree directed acyclic graph

Page 23: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Nucleus

Nucleoplasm Nuclearenvelope

ChromosomePerinuclear spaceNucleolus

A child is a subset ofa parent’s elements

The cell component term Nucleus has 5 children

Parent-Child Relationships

Page 24: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Ontology RelationshipsDirected Acyclic Graph

Page 25: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology
Page 26: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Evidence Codes for GO Evidence Codes for GO AnnotationsAnnotations

http://www.geneontology.org/doc/GO.evidence.html

Page 27: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

IEA Inferred from Electronic Annotation

ISS Inferred from Sequence Similarity

IEP Inferred from Expression Pattern

IMP Inferred from Mutant Phenotype

IGI Inferred from Genetic Interaction

IPI Inferred from Physical Interaction

IDA Inferred from Direct Assay

RCA Inferred from Reviewed Computational Analysis

TAS Traceable Author Statement

NAS Non-traceable Author Statement

IC Inferred by Curator

ND No biological Data available

Page 28: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Meloidogyne incognita: McCarter et al. 2003

Annotation summaries

Page 29: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology
Page 30: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Two types of GO Annotations:

Electronic Annotation

Manual Annotation

All annotations must:

• be attributed to a source

• indicate what evidence was found to support the GO term-gene/protein association

Page 31: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Manual Annotations

• High–quality, specific gene/gene product associations made, using:

• Peer-reviewed papers

• Evidence codes to grade evidence

BUT – is very time consuming and requires trained biologists

Page 32: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

1. Extract information from published literature

2. Curators performs manual sequence similarity analyses to transfer annotations between highly similar gene products (BLAST, protein domain analysis)

Manual Annotations: Methods

Page 33: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Finding GO termsIn this study, we report the isolation and molecular characterization of the B. napus PERK1 cDNA, that is predicted to encode a novel receptor-like kinase. We have shown that like other plant RLKs, the kinase domain of PERK1 has serine/threonine kinase activity, In addition, the location of a PERK1-GFP fusion protein to the plasma membrane supports the prediction that PERK1 is an integral membrane protein…these kinases have been implicated in early stages of wound response…

Process: response to wounding GO:0009611

serine/threonine kinase activity,

Function: protein serine/threonine kinase activity GO:0004674

integral membrane protein

Component: integral to plasma membrane GO:0005887

PubMed ID: 12374299wound response

Page 34: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Electronic Annotations

• Provides large-coverage

• High-quality

BUT – annotations tend to use high-level GO terms and provide little detail.

Page 35: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

1. Database entries

• Manual mapping of GO terms to concepts external to GO (‘translation tables’)

• Proteins then electronically annotated with the relevant GO term(s)

2. Automatic sequence similarity analyses to transfer annotations between highly similar gene products

Electronic Annotations: Methods

Page 36: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Fatty acid biosynthesis (Swiss-Prot Keyword)

EC:6.4.1.2 (EC number)

IPR000438: Acetyl-CoA carboxylase carboxyl transferase beta subunit (InterPro entry)

GO:Fatty acid biosynthesis

(GO:0006633)

GO:acetyl-CoA carboxylase activity

(GO:0003989)

GO:acetyl-CoA carboxylaseactivity

(GO:0003989)

Electronic Annotations

Page 37: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Mappings of external concepts to GO

EC:1.1.1.1 > GO:alcohol dehydrogenase activity ; GO:0004022EC:1.1.1.10 > GO:L-xylulose reductase activity ; GO:0050038EC:1.1.1.104 > GO:4-oxoproline reductase activity ; GO:0016617EC:1.1.1.105 > GO:retinol dehydrogenase activity ; GO:0004745

Page 38: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

• A gene product can have several functions, cellular locations and be involved in many processes

• Annotation of a gene product to one ontology is independent from its annotation to other ontologies

• Annotations are only to terms reflecting a normal activity or location

• Usage of ‘unknown’ GO terms

Additional points

Page 39: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Unknown v.s. Unannotated

• “Unknown” is used when the curator has determined that there is no existing literature to support an annotation.– Biological process unknown GO:0000004– Molecular function unknown GO:0005554– Cellular component unknown GO:0008372

• NOT the same as having no annotation at all – No annotation means that no one has looked yet

Page 40: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

Annotation of a genome

• GO annotations are always work in progress

• Part of normal curation process

– More specific information

– Better evidence code

• Replace obsolete terms

• “Last reviewed” date

Page 41: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

How to access the Gene ontology and its annotations

1. Downloads • Ontologies

• Annotations : Gene association files

• Ontologies and Annotations

2. Web-based access • AmiGO (http://www.godatabase.org)

• QuickGO

(http://www.ebi.ac.uk/ego)

among others…

Page 42: Lecture Four:  GO: The Gene Ontology ---- Infrastructure for Systems Biology

组别 第四讲:讨论论文(课堂讨论时间 5 分左右)

A

C

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