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Título: | GAIT-GM integrative cross-omics analyses reveal cholinergic defects in a C. elegans model of Parkinson’s disease |
Autor: | McIntyre, Lauren M.; Huertas, Francisco; Morse, Alison M.; Kaletsky, Rachel; Murphy, Coleen T.; Kalia, Vrinda; Miller, Gary W.; Moskalenko, Olexander; Conesa, Ana CSIC ORCID; Mor, Danielle E. | Fecha de publicación: | 2022 | Editor: | Springer Nature | Citación: | Scientific Reports 12: 3268 (2022) | Resumen: | Parkinson’s disease (PD) is a disabling neurodegenerative disorder in which multiple cell types, including dopaminergic and cholinergic neurons, are affected. The mechanisms of neurodegeneration in PD are not fully understood, limiting the development of therapies directed at disease-relevant molecular targets. C. elegans is a genetically tractable model system that can be used to disentangle disease mechanisms in complex diseases such as PD. Such mechanisms can be studied combining high-throughput molecular profiling technologies such as transcriptomics and metabolomics. However, the integrative analysis of multi-omics data in order to unravel disease mechanisms is a challenging task without advanced bioinformatics training. Galaxy, a widely-used resource for enabling bioinformatics analysis by the broad scientific community, has poor representation of multi-omics integration pipelines. We present the integrative analysis of gene expression and metabolite levels of a C. elegans PD model using GAIT-GM, a new Galaxy tool for multi-omics data analysis. Using GAIT-GM, we discovered an association between branched-chain amino acid metabolism and cholinergic neurons in the C. elegans PD model. An independent follow-up experiment uncovered cholinergic neurodegeneration in the C. elegans model that is consistent with cholinergic cell loss observed in PD. GAIT-GM is an easy to use Galaxy-based tool for generating novel testable hypotheses of disease mechanisms involving gene-metabolite relationships. | Descripción: | GAIT-GM scripts, test data, Galaxy xmls are available at https://github.com/secimTools/gait-gm, as a PyPi repository (https://pypi.org/project/gait-gm/ ), and as a bioconda package (https://anaconda.org/bioconda/gait-gm ). A detailed Galaxy User Guide providing step-by-step instructions for running each tool in Galaxy is included as Supplementary Material. All tools are deposited in the Galaxy ToolShed for download and installation (https://toolshed.g2.bx.psu.edu/view/malex/gait_gm/ec9ee8edb84d ). r-mixomincs version 6.3.228, python version 3.7 and R version 4.1.1 and SECOMTools version 21.6.3. Raw RNAseq reads are available at National Center for Biotechnology Information BioProject PRJNA599166 and raw metabolomics data are available at Dryad (https://doi.org/10.5061/dryad.5mkkwh72q). | Versión del editor: | https://doi.org/10.1038/s41598-022-07238-9 | URI: | http://hdl.handle.net/10261/285832 | DOI: | 10.1038/s41598-022-07238-9 | E-ISSN: | 2045-2322 |
Aparece en las colecciones: | (I2SysBio) Artículos |
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