In silico analysis of gene expression patterns during early development of Xenopus laevis.

The information as to where and when a mRNA is present in a given cell is essential to bridge the gap between the DNA sequence of a gene and its physiological function. Therefore, a major component of functional genomics is to characterize the levels and the spatio-temporal domains of gene expression. Currently, there is just a few specialised public databases available storing the data on gene expression while they are needed as a resource for the field. Moreover, there is a need to develop and assess computational tools to compare and analyse expression profiles in a suitable way for biological interpretation. Here we describe our recent work on developing a database on gene expression for the frog Xenopus laevis, and on setting up and using new tools for the analysis and comparison of gene expression patterns. We used histogram clustering to compare expression profiles at both gene and tissue levels using a set of data coming from the characterization of the expression of genes during early development of Xenopus. This enabled us to draw a tree of tissue relatedness and to identify coexpressed genes by in silico analysis.