Respective contributions of MIAME, GeneOntology and UMLS for

transcriptome analysis

Fouzia Moussouni, Anita Burgun, Franck Le Duff,

Emilie Guérin, Olivier Loréal

INSERM U522 and Medical Informatics Laboratory,

CHU Pontchaillou

Rennes, FRANCE

Transcriptome & DNA microarraystudy of transcriptionnal response of the cell

NormalNormal PathologicPathologic

Response to a growth factor

Response to a growth factor

Response to genetic

disturbances

Response to genetic

disturbances

Response to chemics or foods

treatment

Response to chemics or foods

treatment

Pathological situations studied at INSERM U522Pathological situations studied at INSERM U522

IRON IRON overloadoverload

DNA mutation(s)DNA mutation(s)Hemochromatosis…Hemochromatosis…

Chronic liver diseasesChronic liver diseases

FibrosisFibrosis

CirrhosisCirrhosis

HepatocarcinomaHepatocarcinoma

MechanismsMechanisms

One may deposit thousands of genes

1 gene but multiple

facets !

Intensive data generation1 measure1 Expression Level

1 Spot intensity

Available knowledge on the expressed genes, that need to be

capturized and organized.

Experimental Raw Data

Nucleic Sequence components - promoters, introns, exons, transcripts, regulators, …

Chromosomal localization,

Functional proteins and known genes products,

Tissue distribution,

Known gene interactions,

Expression level in physiologic and pathologic conditions,

Known gene variations,

Clinical Implications,

Literature and bibliographic data on a gene.

One gene but multiple descriptions

ExternalSources

AnalysisGene Expressionwarehouse

Micro-arrays Substractive banks

SAGE

ClinicalData

? ? ?

Need of an integrated gene expression environment (for the liver!)

Integration

Data cleaning !

experimental data

BIO KNOWLEDGE

Gene Expression Warehouse

Standardization and controlled specification

ONTOLOGY DESIGN

Knowledge extraction and data exchange

Standardization ONTOLOGY DESIGN

Respective contributions

MIAME

UMLS

GO

MIAME

MIAME will provide a standard framework to represent the minimum information that must be reported about microarray experiments :

• Experience• Array• Samples• Hybridization • Measures• Normalisation and control

Work in progress ...

Minimum information about a microarray experiment (MIAME) toward standards for microarray data', A. Brazma, at al., Nature Genetics, vol 29 (December 2001), pp 365 - 371.

GO is an ontology for molecular biology and Genomics,

GeneOntology (GO)

But GO is not populated with :

GOAGOA

gene sequences gene products, ...

The Unified Medical Language System (UMLS) is intended to help health

professionals and researchers to use biomedical information from different sources.

UMLS

Examples from iron metabolism are studied

How pathologic disease states related to iron metabolism alteration are described in GO and UMLS ?

BIOLOGICAL MODEL FOR IRON METABOLISM

Iron metabolism diseases

IRON METABOLISM

GENES

Iron overloadaceruloplasminemia

Iron deficiency

Other diseaseshyperferritinemiacataract

PATHOLOGICSTATES

alteration

Other diseaseshyperferritinemiacataract

Iron overload due to a gene alteration

Iron overload during Aceruloplasminemia

mutation

Feroxydase activity in plasmaFe2+ Fe3+

Iron binding with plasmatic transferrin

Ceruloplasmin

Gene

THE IRON STAYS INSIDE THE CELL !!

NO

NO

BIOLOGICAL MODEL FOR IRON METABOLISM

Other diseaseshyperferritinemiacataract

IRON METABOLISM

GENES

PATHOLOGICSTATES

alteration

Iron metabolism diseases

Iron overloadaceruloplasminemia

Iron deficiency

A second scenario related to iron metabolism genes alteration

Cataract and hyperferritinemia

mutation

IRP

IRE Translation in excess

L_Ferritin

gene

L_FerritinmRNA

L_Ferritin protein in excess

CATARACT and HYPERFERRITINEMIA !

UMLS view

Cataract and hyperferritinemia

AA, Peptide or ProreinBiologically Active Substance

AA, Peptide or Protein

Ferritin

Iron compound

L_FerritinH_Ferritin

Metalloprotein

RNAbindingProtein

IronSulfurProt

Cataract

Co-occursIn Medline(freq 26)

Co-occursIn Medline

IRP

IRE

GO/ GOAnnotations view

Cataract and hyperferritinemia

FerritinHeavyChain

Cell component

Ferritin

IRP

Ferritin Light Chain

IRE

Ligand binding Prot or carrier

Ferric iron binding

Iron homeostasis

Iron transport

Hydro-lyase

Metabolism

Cataract

Link in GO Annotations DB

Target representation

Cataract and hyperferritinemia

CataractIRP

Ligand binding Prot or carrier

Ferric iron binding

Iron homeostasis

Iron transportFerritin Light Chain

FerritinHeavyChain

Ferritin

IRE HyperferritinemiaGenes

Mutated genes Dynamic linksModeling of biological functions

DNA Chips

And more generally …

Recapitulative Information on disease states, clinical treatments and

followups.Normal vs. pathologic

Information on Roles of the genes in Biological and

metabolic states

?

We need precise and dynamic models to get

the whole picture

MIAME

Information on biological

samples, experiments and results

GOA

UMLS

Gene products for Iron metabolism, as they are actually described in GO and UMLS.