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Embracing the dark side: computational approaches to unveil the functionality of genes lacking biological annotation in drug-induced liver injury

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dc.contributor.author Souza, Terezinha
dc.contributor.author Panuwat, Trairatphisan
dc.contributor.author Piñero González, Janet, 1977-
dc.contributor.author Furlong, Laura I., 1971-
dc.contributor.author Saez-Rodriguez, Julio
dc.contributor.author Kleinjans, Jos C.
dc.contributor.author Jennen, Danyel
dc.date.accessioned 2019-04-26T07:34:01Z
dc.date.available 2019-04-26T07:34:01Z
dc.date.issued 2018
dc.identifier.citation Souza T, Trairatphisan P, Piñero J, Furlong LI, Saez-Rodriguez J, Kleinjans J et al. Embracing the dark side: computational approaches to unveil the functionality of genes lacking biological annotation in drug-induced liver injury. Front Genet. 2018 Nov 20;9:527. DOI: 10.3389/fgene.2018.00527
dc.identifier.issn 1664-8021
dc.identifier.uri http://hdl.handle.net/10230/37137
dc.description.abstract In toxicogenomics, functional annotation is an important step to gain additional insights into genes with aberrant expression that drive pathophysiological mechanisms. Nevertheless, there exists a gap on annotation of these genes which often hampers the interpretation of results and limits their applicability in translational medicine. In this study, we evaluated the coverage of functional annotations of differentially expressed genes (DEGs) induced by 10 selected compounds from the TG-GATEs database identified as high- or no-risk in causing drug-induced liver injury (most-DILI or no-DILI, respectively) using in vitro human data. Functional roles of DEGs not present in the most common biological annotation databases - termed "dark genes" - were unveiled via literature mining and via the identification of shared regulatory transcription factors or signaling pathways. Our results demonstrated that there were approximately 13% of dark genes induced by these compounds in vitro and we were able to obtain additional relevant information for up to 76% of those. Using interactome data from several sources, we have uncovered genes such as LRBA, and WDR26 as highly connected in the protein network that play roles in drug response. Genes such as MALAT1, H19, and MIR29C - whose links to hepatotoxicity have been confirmed - were identified as markers for the most-DILI group and appeared as top hits across all literature-based mining methods. Furthermore, we investigated the potential impact of dark genes on liver toxicity by identifying their rat orthologs in combination with their correlation to drug-induced liver pathologies observed in vivo following chemical exposure. We identified a set of important regulatory transcription factors of dark genes for all most-DILI compounds including E2F1 and JUND with supporting evidences in literature and we found Magee1 correlated with chemically induced bile duct hyperplasia and adverse responses at 29 days in rats in vivo. In conclusion, in this study we show the potential role of these poorly annotated genes in mechanisms underlying hepatotoxicity and offer a number of computational approaches that may help to minimize current gaps in gene annotation and highlight their values as potential biomarkers in toxicological studies.
dc.description.sponsorship This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement no. 116030 (TransQST). This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Frontiers
dc.relation.ispartof Frontiers in Genetics. 2018 Nov 20;9:527
dc.rights Copyright © 2018 Souza, Trairatphisan, Piñero, Furlong, Saez-Rodriguez, Kleinjans and Jennen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) https://creativecommons.org/licenses/by/4.0/. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject.other Bioinformàtica
dc.title Embracing the dark side: computational approaches to unveil the functionality of genes lacking biological annotation in drug-induced liver injury
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.3389/fgene.2018.00527
dc.subject.keyword DILI
dc.subject.keyword Annotation
dc.subject.keyword Gene ontology
dc.subject.keyword Network biology
dc.subject.keyword Text mining
dc.subject.keyword Translational bioinformatics
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/116030
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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