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Christophe Andreoli

Publications and source records attributed to Christophe Andreoli.

4 recordsLinked to original sources

Integrative analysis of the mitochondrial proteome in yeast.

In this study yeast mitochondria were used as a model system to apply, evaluate, and integrate different genomic approaches to define the proteins of an organelle. Liquid chromatography mass spectrometry applied to purified mitochondria identified 546 proteins. By expression analysis and comparison to other proteome studies, we demonstrate that the proteomic approach identifies primarily highly abundant proteins. By expanding our evaluation to other types of genomic approaches, including systematic deletion phenotype screening, expression profiling, subcellular localization studies, protein interaction analyses, and computational predictions, we show that an integration of approaches moves beyond the limitations of any single approach. We report the success of each approach by benchmarking it against a reference set of known mitochondrial proteins, and predict approximately 700 proteins associated with the mitochondrial organelle from the integration of 22 datasets. We show that a combination of complementary approaches like deletion phenotype screening and mass spectrometry can identify over 75% of the known mitochondrial proteome. These findings have implications for choosing optimal genome-wide approaches for the study of other cellular systems, including organelles and pathways in various species. Furthermore, our systematic identification of genes involved in mitochondrial function and biogenesis in yeast expands the candidate genes available for mapping Mendelian and complex mitochondrial disorders in humans.

Chemical Fractionation↗

Plotting haplotype-specific linkage disequilibrium patterns by extended haplotype homozygosity.

UNLABELLED: Association studies may request more details of a specific haplotype. Haplotype-specific decay of linkage disequilibrium is such a crucial and versatile characteristic. It may be used, e.g. to search for signals of natural selection in a risk haplotype. Here, we present a web-based tool to explore the relationship between population frequency and extended linkage disequilibrium measured as haplotype homozygosity of observed haplotypes within a specified candidate region. AVAILABILITY: The web-tool is available at http://ihg.gsf.de/cgi-bin/mueller/webehh.pl

Algorithms↗

Mechanisms for multiple intracellular localization of human mitochondrial proteins.

There is an increasing number of reports that some single gene products function in more than one cellular compartment. This review lists and categorizes the targeting mechanisms of 31 human mitochondrial proteins that have multiple localizations. Further, genetic disorders based on mislocalization are described, and prediction algorithms for multi-localized proteins are proposed. A high diversity of experimentally verified targeting mechanisms ranging from single protein to multi-protein mechanisms exists, with a combination of multiple transcription starting points and alternative splicing being the most frequent. This observation stresses the individuality of the evolutionary histories of such mechanisms. We did not find specific localization strategies to cluster with certain protein functions. There was also no bias with respect to the evolutionary origin of the multi-compartmentalized mitochondrial proteins. Both, genes of bacterial and eukaryotic origin show multiple localization, which does not corroborate the hypothesis that the development of multiple targeting is coupled predominantly with the recruitment of nuclear eukaryotic genes for novel mitochondrial functions.

Journal Article↗

Gene mapping and marker clustering using Shannon's mutual information.

Finding the causal genetic regions underlying complex traits is one of the main aims in human genetics. In the context of complex diseases, which are believed to be controlled by multiple contributing loci of largely unknown effect and position, it is especially important to develop general yet sensitive methods for gene mapping. We discuss the use of Shannon's information theory for population-based gene mapping of discrete and quantitative traits and for marker clustering. Various measures of mutual information were employed in order to develop a comprehensive framework for gene mapping analyses. An algorithm aimed at finding so-called relevance chains of causal markers is proposed. Moreover, entropy measures are used in conjunction with multidimensional scaling to visualize clusters of genetic markers. The relevance chain algorithm successfully detected the two causal regions in a simulated scenario. The approach has also been applied to a published clinical study on autoimmune (Graves') disease. Results were consistent with those of standard statistical methods, but identified an additional locus of interest in the promotor region of the associated gene CTLA4. The developed software is freely available at http://www.Int.ei.tum.de/download/InfoGeneMap/.

Algorithms↗