CEA, LIST, Laboratoire Sciences des Données et de la Décision, IFB, MetaboHUB, Gif-sur-Yvette, France.
IFB-core, UMS3601, Genoscope, Evry, France.
Sci Data. 2021 Dec 3;8(1):311. doi: 10.1038/s41597-021-01095-3.
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/6 N 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 to develop new bioinformatic and biostatistic methods for multi-omics data integration.
基因具有多效性,要更好地了解它们的功能,需要全面描述它们的突变体。在这里,我们生成了多层次的数据,结合了来自缺乏 Lat(T 细胞激活连接蛋白)和 Mx2(MX 动力蛋白样 GTPase 2)基因的两个 C57BL/6N 小鼠模型的表型、蛋白质组学和代谢组学的采集。我们的数据集由 9 项检测(1 项临床前、2 项蛋白质组学和 6 项代谢组学)组成,采用完全非靶向和标准化的方法生成。数据和处理代码在 ProMetIS R 包中公开,以确保可访问性、互操作性和可重用性。该数据集因此提供了关于 Lat 和 Mx2 基因生理作用的独特分子信息。此外,本文描述的方案可以很容易地扩展到更多的个体和组织。最后,这个资源对于开发新的生物信息学和生物统计学方法来整合多组学数据将非常有兴趣。