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ProMetIS, deep phenotyping of mouse models by combined proteomics and metabolomics analysis

Abstract : Genes are pleiotropic and getting a better knowledge of their function requires a comprehensive characterization of their mutants. Here, we generated multi-level data combining phenomic, proteomic and metabolomic acquisitions from plasma and liver tissues of two C57BL/6N mouse models lacking the Lat (linker for activation of T cells) and the Mx2 (MX dynamin-like GTPase 2) genes, respectively. Our dataset consists of 9 assays (1 preclinical, 2 proteomics and 6 metabolomics) generated with a fully non-targeted and standardized approach. The data and processing code are publicly available in the ProMetIS R package to ensure accessibility, interoperability, and reusability. The dataset thus provides unique molecular information about the physiological role of the Lat and Mx2 genes. Furthermore, the protocols described herein can be easily extended to a larger number of individuals and tissues. Finally, this resource will be of great interest todevelop new bioinformatic and biostatistic methods for multi-omics data integration
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https://hal-pasteur.archives-ouvertes.fr/pasteur-03453736
Contributor : Claudine Medigue Connect in order to contact the contributor
Submitted on : Sunday, November 28, 2021 - 6:15:38 PM
Last modification on : Tuesday, May 17, 2022 - 7:40:07 AM

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Alyssa Imbert, Magali Rompais, Mohammed Selloum, Florence Castelli, Emmanuelle Mouton-Barbosa, et al.. ProMetIS, deep phenotyping of mouse models by combined proteomics and metabolomics analysis. In press. ⟨pasteur-03453736⟩

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