Biomedical subjects

Stéphane Vialette

Publications and source records attributed to Stéphane Vialette.

5 recordsLinked to original sources

PubMed2006

Comparing gene expression networks in a multi-dimensional space to extract similarities and differences between organisms.

MOTIVATION: Molecular evolution, which is classically assessed by comparison of individual proteins or genes between species, can now be studied by comparing co-expressed functional groups of genes. This approach, which better reflects the functional constraints on the evolution of organisms, can exploit the large amount of data generated by genome-wide expression analyses. However, it requires new methodologies to represent the data in a more accessible way for cross-species comparisons. RESULTS: In this work, we present an approach based on Multi-dimensional Scaling techniques, to compare the conformation of two gene expression networks, represented in a multi-dimensional space. The expression networks are optimally superimposed, taking into account two criteria: (1) inter-organism orthologous gene pairs have to be nearby points in the final multi-dimensional space and (2) the distortion of the gene expression networks, the organization of which reflects the similarities between the gene expression measurements, has to be circumscribed. Using this approach, we compared the transcriptional programs that drive sporulation in budding and fission yeasts, extracting some common properties and differences between the two species.

Computational Biology↗

PubMed2004

MiCoViTo: a tool for gene-centric comparison and visualization of yeast transcriptome states.

BACKGROUND: Information obtained by DNA microarray technology gives a rough snapshot of the transcriptome state, i.e., the expression level of all the genes expressed in a cell population at any given time. One of the challenging questions raised by the tremendous amount of microarray data is to identify groups of co-regulated genes and to understand their role in cell functions. RESULTS: MiCoViTo (Microarray Comparison Visualization Tool) is a set of biologists' tools for exploring, comparing and visualizing changes in the yeast transcriptome by a gene-centric approach. A relational database includes data linked to genome expression and graphical output makes it easy to visualize clusters of co-expressed genes in the context of available biological information. To this aim, upload of personal data is possible and microarray data from fifty publications dedicated to S. cerevisiae are provided on-line. A web interface guides the biologist during the usage of this tool and is freely accessible at http://www.transcriptome.ens.fr/micovito/. CONCLUSIONS: MiCoViTo offers an easy-to-read picture of local transcriptional changes connected to current biological knowledge. This should help biologists to mine yeast microarray data and better understand the underlying biology. We plan to add functional annotations from other organisms. That would allow inter-species comparison of transcriptomes via orthology tables.

Cluster Analysis↗

PubMed2004

yMGV: a cross-species expression data mining tool.

The yeast Microarray Global Viewer (yMGV @ http://transcriptome.ens.fr/ymgv) was created 3 years ago as a database that houses a collection of Saccharomyces cerevisiae and Schizosaccharo myces pombe microarray data sets published in 82 different articles. yMGV couples data mining tools with a user-friendly web interface so that, with a few mouse clicks, one can identify the conditions that affect the expression of a gene or list of genes regulated in a set of experiments. One of the major new features we present here is a set of tools that allows for inter-organism comparisons. This should enable the fission yeast community to take advantage of the large amount of available information on budding yeast transcriptome. New tools and ongoing developments are also presented here.

Computational Biology↗

PubMed2003

Long mRNAs coding for yeast mitochondrial proteins of prokaryotic origin preferentially localize to the vicinity of mitochondria.

BACKGROUND: Subcellular messenger RNA localization is important in most eukaryotic cells, even in unicellular organisms like yeast for which this process has been underestimated. Microarrays are rarely used to study subcellular mRNA localization at whole-genome level, but can be adapted to that purpose. This work focuses on studying the repartition of yeast nuclear transcripts encoding mitochondrial proteins between free cytosolic polysomes and polysomes bound to the mitochondrial outer membrane. RESULTS: Combining biochemical fractionations with oligonucleotide array analyses permits clustering of genes on the basis of the subcellular sites of their mRNA translation. A large fraction of yeast nuclear transcripts known to encode mitochondrial proteins is found in mitochondrial outer-membrane-bound fractions. These results confirm and extend a previous analysis conducted with partial genomic microarrays. Interesting statistical relations among mRNA localization, gene origin and mRNA lengths were found: longer and older mRNAs are more prone to be localized to the vicinity of mitochondria. These observations are included in a refined model of mitochondrial protein import. CONCLUSIONS: Mitochondrial biogenesis requires concerted expression of the many genes whose products make up the organelle. In the absence of any clear transcriptional program, coordinated mRNA localization could be an important element of the time-course of organelle construction. We have built a 'MitoChip' localization database from our results which allows us to identify interesting genes whose mRNA localization might be essential for mitochondrial biogenesis in most eukaryotic cells. Moreover, many components of the experimental and data-analysis strategy implemented here are of general relevance in global transcription studies.

Biological Transport↗

PubMed2002

In Saccharomyces cerevisiae, ATP2 mRNA sorting to the vicinity of mitochondria is essential for respiratory function.

We recently demonstrated that polysome-associated mRNAs that co-isolate with mitochondria encode a subset of mitochondrial proteins, and that the 3' UTRs of these transcripts are essential for their localization to the vicinity of the organelle. To address the question of the involvement of the mRNA targeting process in mitochondrial biogenesis, we studied the role of ATP2 3' UTR. An altered ATP2 allele in which the 3' UTR was replaced by the ADH1 3' UTR exhibits properties supporting the importance of mRNA localization to the vicinity of mitochondria: (i) the mutated strain presents a respiratory dysfunction; (ii) mitochondrial import of the protein translated from the altered gene is strongly reduced, even though the precursor is addressed to the organelle surface; (iii) systematic deletions of ATP2 3' UTR revealed a 100 nucleotide element presenting RNA targeting properties. Additionally, when the ATM1 3' UTR was replaced by the ADH1 3' UTR, we obtained cells in which ATM1 mRNA is also delocalized, and presenting a respiratory dysfunction. This demonstrates that mRNA localization to the vicinity of mitochondria plays a critical role in organelle biogenesis.

3' Untranslated Regions↗