A bioinformatics workflow to decipher transcriptomic data from vitamin D studies. Issue 189 (May 2019)

• Record Type: Journal Article
• Authors: Muñoz García, Amadeo; Eijssen, Lars M.; Kutmon, Martina; Sarathy, Chaitra; Cengo, Ardi; Hewison, Martin; Evelo, Chris T.; Lenz, Michael; Coort, Susan L.
• Is Part Of: Journal of steroid biochemistry and molecular biology. Issue 189(2019)
• Page Start: 28
• Page End: 35
• Publication Date: 2019-05
• Subjects: Transcriptomic data -- Vitamin D -- Bioinformatics -- Biological pathways -- Network analysis; Steroid hormones -- Periodicals; Biochemistry -- Periodicals; Hormones -- Periodicals; Molecular Biology -- Periodicals; Hormones stéroïdes -- Périodiques; Steroid hormones; Periodicals; 572.579
• DOI: 10.1016/j.jsbmb.2019.01.003
• Languages: English
• ISSNs: 0960-0760

Abstract

Graphical abstract: Highlights: A straightforward and available bioinformatics workflow. Pathway and network analysis to decipher transcriptomic data. Application of dry-lab approaches using wet-lab experiments. Vitamin D gene expression studies explored with bioinformatics tools. Giving new insights into the role of vitamin D in immune system. Abstract: The link between the experimental laboratory studies and bioinformatic approaches aims to find procedures to connect tools from both branches producing workflows that bring together different techniques that are capable of exploiting data at many levels. Thanks to the open access sources and the numerous tools available, it is possible to create various pipelines capable of solving specific problems. Nevertheless the lack of connectivity between them that interconnect different approaches complicates the exploitation of these workflows. Here, we present a detailed description of a workflow composed of different bioinformatics tools that exploits data from large-scale gene expression experiments, contextualizing them at many biological levels. To illustrate the relevance of our workflow for the vitamin D community we applied it to data from myeloid cell models treated with the hormonally active form of vitamin. From raw files of functional genomic studies it is possible to utilize the whole information to obtain a biological insight. Different software and algorithms are included to analyse at pathway, metabolic, ontology and molecular biology level the effects on gene expression. The usage of different databases to analyse gene expression data allows to perform a complete interpretation of functional genomic studies and the implementation of analysis and visualization software tools gives a better understanding of the biological meaning of the results. This review is an example of how to select and bring together several software modules to create one pipeline that processes and analyses genomic data at many biological levels making it open, reproducible and user friendly. Finally, the application of our bioinformatic pipeline revealed that vitamin D modulates crucial metabolic pathways in different myeloid cells that may play an important role in their immune function.