CASSIOPE: an expert system for conserved regions searches.
BACKGROUND
Understanding genome evolution provides insight into biological mechanisms. For many years comparative genomics and analysis of conserved chromosomal regions have helped to unravel the mechanisms involved in genome evolution and their implications for the study of biological systems. Detection of conserved regions (descending from a common ancestor) not only helps clarify genome evolution but also makes it possible to identify quantitative trait loci (QTLs) and investigate gene function.The identification and comparison of conserved regions on a genome scale is computationally intensive, making process automation essential. Three key requirements are necessary: consideration of phylogeny to identify orthologs between multiple species, frequent updating of the annotation and panel of compared genomes and computation of statistical tests to assess the significance of identified conserved gene clusters.


RESULTS
We developed a modular system superimposed on a multi-agent framework, called CASSIOPE (Clever Agent System for Synteny Inheritance and Other Phenomena in Evolution). CASSIOPE automatically identifies statistically significant conserved regions between multiple genomes based on automated phylogenies and statistical testing. Conserved regions were searched for in 19 species and 1,561 hits were found. To our knowledge, CASSIOPE is the first system to date that integrates evolutionary biology-based concepts and fulfills all three key requirements stated above. All results are available at http://194.57.197.245/cassiopeWeb/displayCluster?clusterId=1


CONCLUSIONS
CASSIOPE makes it possible to study conserved regions from a chosen query genetic region and to infer conserved gene clusters based on phylogenies and statistical tests assessing the significance of these conserved regions.Source code is freely available, please contact: Pierre.pontarotti@univ-provence.fr.
Rascol
Virginie Lopez
VL
EBM UMR 6632 LATP, 3 place V Hugo - 13 331 Marseille cedex 03 France. virginie.lopez-rascol@univ-provence.fr
Levasseur
Anthony
A
Chabrol
Olivier
O
Grusea
Simona
S
Gouret
Philippe
P
Danchin
Etienne G J
EG
Pontarotti
Pierre
P
D019295:Computational Biology / Q000379:methods*; D017124:Conserved Sequence; D016678:Genome; D023281:Genomics / Q000379:methods; D010802:Phylogeny; D040641:Quantitative Trait Loci; D012984:Software