Similarities and differences in genome-wide expression data of six organisms.
Détails
Télécharger: BIB_228BF88426DE.P001.pdf (3327.48 [Ko])
Etat: Public
Version: de l'auteur⸱e
Etat: Public
Version: de l'auteur⸱e
ID Serval
serval:BIB_228BF88426DE
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Similarities and differences in genome-wide expression data of six organisms.
Périodique
PLoS Biology
ISSN
1545-7885
Statut éditorial
Publié
Date de publication
2004
Peer-reviewed
Oui
Volume
2
Numéro
1
Pages
E9
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S.
Résumé
Comparing genomic properties of different organisms is of fundamental importance in the study of biological and evolutionary principles. Although differences among organisms are often attributed to differential gene expression, genome-wide comparative analysis thus far has been based primarily on genomic sequence information. We present a comparative study of large datasets of expression profiles from six evolutionarily distant organisms: S. cerevisiae, C. elegans, E. coli, A. thaliana, D. melanogaster, and H. sapiens. We use genomic sequence information to connect these data and compare global and modular properties of the transcription programs. Linking genes whose expression profiles are similar, we find that for all organisms the connectivity distribution follows a power-law, highly connected genes tend to be essential and conserved, and the expression program is highly modular. We reveal the modular structure by decomposing each set of expression data into coexpressed modules. Functionally related sets of genes are frequently coexpressed in multiple organisms. Yet their relative importance to the transcription program and their regulatory relationships vary among organisms. Our results demonstrate the potential of combining sequence and expression data for improving functional gene annotation and expanding our understanding of how gene expression and diversity evolved.
Mots-clé
Animals, Arabidopsis, Caenorhabditis elegans, Cluster Analysis, Databases, Genetic, Drosophila melanogaster, Escherichia coli, Evolution, Molecular, Gene Deletion, Gene Expression Profiling, Genes, Plant, Genome, Genome, Bacterial, Genome, Fungal, Genome, Human, Genomics, Humans, Internet, Models, Statistical, Oligonucleotide Array Sequence Analysis, Open Reading Frames, RNA Interference, Saccharomyces cerevisiae, Sequence Analysis, DNA, Species Specificity, Transcription, Genetic
Pubmed
Web of science
Open Access
Oui
Création de la notice
24/01/2008 14:10
Dernière modification de la notice
20/08/2019 13:00