Research in the Evolutionary Bioinformatics (EB) group is mainly focused on linking the evolution of animal development to genome evolution. The group develops Bgee, a database for gene expression evolution, Selectome, a database of positive selection, and studies the consequences of whole gene and genome duplication in fishes. The group is also involved in targeted projects in the field of comparative functional genomics.
The aim of evolutionary developmental biology (Evo-Devo) is to develop an understanding of the basis of animal diversity. This diversity must be encoded in the genomes, but linking the evolution of genomes to development requires new bioinformatics tools able to provide genomic studies with a fine level of detail, whilst Evo-Devobioinformatics usually studies a broad genomic view. Comparison of expression patterns is the basic tool of Evo-Devo, providing the molecular basis for differences between close species (e.g., butterfly wing spots), and for conservation between distant lineages (e.g., antero-posterior axis in vertebrates and insects). Evolutionary novelty has also been shown to stem from key mutations in proteins. Duplication, whether local or global, plays a major role in such structural change. For example, steroid receptors in vertebrates diversified by whole genome duplication. The EB group seeks to scale up both expression and protein evolution studies so that they can be conducted genome-wide.
Projects and Services
Bgee, a database for gene expression evolution
Bgee is a database to compare expression patterns between animal species. Bgee addresses difficulties such as complex anatomies, and diverse sources of data, by the use of ontologies and the explicit representation of homology. Homology relationships are defined both between genes and between anatomical features. The main efforts are the annotation of anatomical and developmental terms and their homology relationships, and the annotation and statistical treatment of transcriptome data. Such efforts provide an answer to the question “Where is this gene expressed?” from the analysis of data as diverse as ESTs, microarrays, and in situ hybridization. The EB group has the aim of producing a database useful to disciplines such as comparative genomics, Evo-Devo, or transcriptome studies, whilst providing an improved integration of homology and related concepts into bioinformatics through ontologies and ontology tools.
Whole genome duplication in fishes and protein evolution
Gene and genome duplication are considered major mechanisms in the creation of new functions in genomes, or in the refinement of networks by the division of function among more genes.
The EB group is especially interested in the genome duplications which occurred in the Paleozoic, in the ancestor of vertebrates and in the ancestor of teleost fishes.
More generally, the EB group is interested in all factors which affect the evolution of proteins and protein-coding genes. These notably include positive (Darwinian) selection, which can be statistically difficult and computationally expensive to characterize. For this we develop the database Selectome: http://selectome.unil.ch/
Gene and genome duplication are considered major mechanisms in the creation of new functions in genomes, or in the refinement of networks by the division of function among more genes. In animals, the best demonstrated whole genome duplication occurred in the origin of teleost fishes. This makes fishes an ideal model to study the consequences of genome duplication, particularly since we have a good sampling of genome sequences, abundant functional information, and a very well studied outgroup: the tetrapodes (including human).
More specifically, the EB group studies the consequences of duplication on proteins using models of selection, phylogeny, and structure. A software pipeline has been set up to perform specific and sensitive tests on a large scale.
Comparative functional genomics: case studies
The EB group collaborates with experimental biology laboratories, bringing expertise in comparative functional genomics. The two main focuses are nuclear hormone receptors and muscle. It is increasingly important to integrate diverse types of data (transcriptome, proteome, ChIP-on-chip, interactome) into one picture, while taking into account the diversity of species in which the data might be generated. Thus in the Crescendo Integrated Project on nuclear receptors in ageing and development (FP6), data are generated for mouse, human cell lines, Xenopus, zebrafish and amphioxus. Managing all of this data, and integrating it to understand the nuclear receptor regulatory network, are tasks of the Evolutionary Bioinformatics group.
Websites for Further Information
Evolutionary Bioinformatics Group: http://www.unil.ch/dee/page22707_en.htmlBgee database: http://bgee.unil.ch/
Selectome database: http://selectome.unil.ch/