mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dynamics and mutations Annie Yim, Prasanna Koti, Adrien Bonnard, Fabio Marchiano, Milena Dürrbaum, Cecilia Garcia-Perez, José Villaveces, Salma Gamal, Giovanni Cardone, Fabiana Perocchi, et al.
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Annie Yim, Prasanna Koti, Adrien Bonnard, Fabio Marchiano, Milena Dürrbaum, et al.. mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dy- namics and mutations. Nucleic Acids Research, Oxford University Press, 2020, 10.1093/nar/gkz1128. hal-02394433
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Distributed under a Creative Commons Attribution| 4.0 International License Nucleic Acids Research, 2019 1 doi: 10.1093/nar/gkz1128 Downloaded from https://academic.oup.com/nar/advance-article-abstract/doi/10.1093/nar/gkz1128/5651332 by Bibliothèque de l'université la Méditerranée user on 04 December 2019 mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dynamics and mutations Annie Yim1,†, Prasanna Koti1,†, Adrien Bonnard2, Fabio Marchiano3, Milena Durrbaum¨ 1, Cecilia Garcia-Perez4, Jose Villaveces1, Salma Gamal1, Giovanni Cardone1, Fabiana Perocchi4, Zuzana Storchova1,5 and Bianca H. Habermann 1,3,*
1Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany, 2Aix-Marseille University, INSERM, TAGC U1090, 13009 Marseille, France, 3Aix-Marseille University, CNRS, IBDM UMR 7288, 13009 Marseille, France, 4Functional Genomics of Mitochondrial Signaling, Gene Center, Ludwig Maximilian University (LMU), Munich, Germany and 5Department of Molecular Genetics, TU Kaiserslautern, Paul Ehrlich Strasse 24, 67663 Kaiserslautern, Germany
Received May 30, 2019; Revised October 30, 2019; Editorial Decision November 13, 2019; Accepted November 18, 2019
ABSTRACT aiding experimental scientists to quantify mitochon- drial expression dynamics. Mitochondria participate in metabolism and signal- ing. They adapt to the requirements of various cell types. Publicly available expression data permit to study expression dynamics of genes with mitochon- INTRODUCTION drial function (mito-genes) in various cell types, con- Enormous amounts of transcriptomic data are publicly ditions and organisms. Yet, we lack an easy way of available for exploration. This richness of data gives us the extracting these data for mito-genes. Here, we intro- unique opportunity to explore the behavior of individual duce the visual data mining platform mitoXplorer, genes or groups of genes within a vast variety of different which integrates expression and mutation data of cell types, developmental or disease conditions or in differ- mito-genes with a manually curated mitochondrial ent species. By integrating these data in a sophisticated way, interactome containing ∼1200 genes grouped in 38 we may be capable to discover new dependencies between mitochondrial processes. User-friendly analysis and genesorprocesses. Specific databases are available for mining and exploring visualization tools allow to mine mitochondrial ex- disease-associated data, such as The Cancer Genome Atlas pression dynamics and mutations across various (TCGA, https://portal.gdc.cancer.gov/)(1), or the Interna- datasets from four model species including human. tional Cancer Consortium Data Portal (ICGC, https://dcc. To test the predictive power of mitoXplorer, we quan- icgc.org/)(2). Especially cancer data portals allow users to tify mito-gene expression dynamics in trisomy 21 perform deeper exploration of expression changes of indi- cells, as mitochondrial defects are frequent in tri- vidual genes or gene groups in different tumor types ((1– somy 21. We uncover remarkable differences in the 3); for a review on available cancer data portals, see (4)). regulation of the mitochondrial transcriptome and Expression Atlas (https://www.ebi.ac.uk/gxa/home)onthe proteome in one of the trisomy 21 cell lines, caused other hand provides pre-processed data from a large variety by dysregulation of the mitochondrial ribosome and of different studies in numerous species (5). Indeed, the ma- resulting in severe defects in oxidative phosphory- jority of transcriptomic datasets are not related to cancer and are stored in public repositories such as Gene Expres- lation. With the newly developed Fiji plugin mito- sion Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) Morph, we identify mild changes in mitochondrial (6), DDBJ Omics Archive (https://www.ddbj.nig.ac.jp/gea/ morphology in trisomy 21. Taken together, mitoX- index-e.html)(7), or ArrayExpress (https://www.ebi.ac.uk/ plorer (http://mitoxplorer.ibdm.univ-mrs.fr)isauser- arrayexpress/)(8). Currently, it is not straightforward to in- friendly, web-based and freely accessible software, tegrate data from these repositories without at least basic programming knowledge.
*To whom correspondence should be addressed. Tel: +33 4 91 26 92 36; Email: [email protected] †The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.