WormPaths: Caenorhabditis elegans metabolic pathway annotation and visualization [preprint]
Authors
Walker, Melissa D.Giese, Gabrielle E.
Holdorf, Amy D.
Bhattacharya, Sushila
Diot, Cedric
Garcia-Gonzalez, Aurian
Horowitz, Brent
Lee, Yong-Uk
Leland, Thomas
Li, Xuhang
Mirza, Zeynep
Na, Huimin
Nanda, Shivani
Ponomarova, Olga
Zhang, Hefei
Zhang, Jingyan
Yilmaz, L. Safak
Walhout, Albertha J. M.
UMass Chan Affiliations
Graduate School of Biomedical SciencesProgram in Molecular Medicine
Program in Systems Biology
Document Type
PreprintPublication Date
2020-12-23Keywords
Geneticsmetabolism
metabolic pathways
Caenorhabditis elegans
WormPaths
Biochemical Phenomena, Metabolism, and Nutrition
Cellular and Molecular Physiology
Genetics and Genomics
Physiological Processes
Systems and Integrative Physiology
Metadata
Show full item recordAbstract
In our group, we aim to understand metabolism in the nematode Caenorhabditis elegans and its relationships with gene expression, physiology and the response to therapeutic drugs. On March 15, 2020, a stay-at-home order was put into effect in the state of Massachusetts, USA, to flatten the curve of the spread of the novel SARS-CoV2 virus that causes COVID-19. For biomedical researchers in our state, this meant putting a hold on experiments for nine weeks until May 18, 2020. To keep the lab engaged and productive, and to enhance communication and collaboration, we embarked on an in-lab project that we all found important but that we never had the time for: the detailed annotation and drawing of C. elegans metabolic pathways. As a result, we present WormPaths, which is composed of two parts: 1) the careful manual annotation of metabolic genes into pathways, categories and levels, and 2) 66 pathway maps that include metabolites, metabolite structures, genes, reactions, and pathway connections between maps. These maps are available on our WormFlux website. We show that WormPaths provides easy-to-navigate maps and that the different levels in WormPaths can be used for metabolic pathway enrichment analysis of transcriptomic data. In the unfortunate event of additional lockdowns, we envision further developing these maps to be more interactive, with an analogy of road maps that are available on mobile devices.Source
bioRxiv 2020.12.22.424026; doi: https://doi.org/10.1101/2020.12.22.424026. Link to preprint on bioRxiv.
DOI
10.1101/2020.12.22.424026Permanent Link to this Item
http://hdl.handle.net/20.500.14038/29653Notes
This article is a preprint. Preprints are preliminary reports of work that have not been certified by peer review.
Related Resources
Now published in Genetics doi: 10.1093/genetics/iyab089
Rights
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.Distribution License
http://creativecommons.org/licenses/by-nc/4.0/ae974a485f413a2113503eed53cd6c53
10.1101/2020.12.22.424026
Scopus Count
Except where otherwise noted, this item's license is described as The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.