Abstracts (first author)


Bgee, a database for the study of gene expression evolution


Author(s): Robinson-Rechavi M, Team B, Bastian FB


Gene expression patterns (where and when genes are expressed) are a key feature in understanding gene function and evolution. To apply compare results between different model organisms and human, or to study gene expression evolution, a comparative approach must be used, but no tools allow to easily compare gene expression across species. We have thus developed Bgee (Base for Gene Expression Evolution), a database designed to automatically compare expression patterns between animals. This is achieved by i) the aggregation and curation of expression data from different types and sources, to map them to formal representations of anatomies and developments of different species; Bgee release 12 contains curated and quality controlled data for Affymetrix chips EST libraries, and RNA-seq libraries annotated by our curators, as well as in situ hybridizations. ii) the analysis of these data by dedicated statistical tests to define high confidence gene expression patterns. iii) the definition of comparison criteria between anatomies of different species; Bgee curators have designed relationships between more than 5000 species-specific terms, which map to more than 1000 homologous organ groups; the latter are organized in multi-species ontologies (the HOG and vHOG ontologies). Bgee is available at: http://bgee.unil.ch/

Abstracts (coauthor)


The aim is to understand how the complex anatomy and developmental processes of animal influence the evolution of protein-coding genes.

The influence of different parameters, from gene size to expression levels, on the evolution of proteins has been previously studied in yeast, Drosophila and mammals. Here we investigate these relations further, especially taking in account gene expression and chromatin organization in different organs and different developmental stages. For expression we used a microarray experiment over zebrafish development as well as the RNA-seq data from ENCODE for 22 different tissues of mouse. We also used chromatin accessibility in mouse tissues, and we use ENCODE data to define which transcript is used as reference to compute gene length, intron number, etc. We find strong differences between tissues or developmental stages in impact of expression on evolutionary rate. Over all tissues, an interesting result is that evolutionary rate is better correlated with maximal expression in one tissue then with average expression value over all tissues.


Chairman: Octávio S. Paulo
Tel: 00 351 217500614 direct
Tel: 00 351 217500000 ext22359
Fax: 00 351 217500028
email: mail@eseb2013.com


XIV Congress of the European Society for Evolutionary Biology

Organization Team
Department of Animal Biology (DBA)
Faculty of Sciences of the University of Lisbon
P-1749-016 Lisbon


Computational Biology & Population Genomics Group