دورية أكاديمية
أعرض في EDS

Utility of Extrapolating Human S1500+ Genes to the Whole Transcriptome: Tunicamycin Case Study.

التفاصيل البيبلوغرافية
العنوان: Utility of Extrapolating Human S1500+ Genes to the Whole Transcriptome: Tunicamycin Case Study.
المؤلفون: Mav D; Sciome LLC, Research Triangle Park, NC, USA., Phadke DP; Sciome LLC, Research Triangle Park, NC, USA., Balik-Meisner MR; Sciome LLC, Research Triangle Park, NC, USA., Merrick BA; Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA., Auerbach S; Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA., Niemeijer M; Division of Toxicology, Leiden Academic Centre for Drug Research (LACDR), Leiden University, Leiden, The Netherlands., Huppelschoten S; Division of Toxicology, Leiden Academic Centre for Drug Research (LACDR), Leiden University, Leiden, The Netherlands., Baze A; KaLy-Cell, Plobsheim, France., Parmentier C; KaLy-Cell, Plobsheim, France., Richert L; KaLy-Cell, Plobsheim, France., van de Water B; Division of Toxicology, Leiden Academic Centre for Drug Research (LACDR), Leiden University, Leiden, The Netherlands., Shah RR; Sciome LLC, Research Triangle Park, NC, USA., Paules RS; Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA.
المصدر: Bioinformatics and biology insights [Bioinform Biol Insights] 2020 Sep 29; Vol. 14, pp. 1177932220952742. Date of Electronic Publication: 2020 Sep 29 (Print Publication: 2020).
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: SAGE Publications Country of Publication: United States NLM ID: 101467187 Publication Model: eCollection Cited Medium: Print ISSN: 1177-9322 (Print) Linking ISSN: 11779322 NLM ISO Abbreviation: Bioinform Biol Insights Subsets: PubMed not MEDLINE
أسماء مطبوعة: Publication: <2016- > : Thousand Oaks, CA : SAGE Publications
Original Publication: Auckland, New Zealand : Libertas Academica
مستخلص: The TempO-Seq S1500+ platform(s), now available for human, mouse, rat, and zebrafish, measures a discrete number of genes that are representative of biological and pathway co-regulation across the entire genome in a given species. While measurement of these genes alone provides a direct assessment of gene expression activity, extrapolating expression values to the whole transcriptome (~26 000 genes in humans) can estimate measurements of non-measured genes of interest and increases the power of pathway analysis algorithms by using a larger background gene expression space. Here, we use data from primary hepatocytes of 54 donors that were treated with the endoplasmic reticulum (ER) stress inducer tunicamycin and then measured on the human S1500+ platform containing ~3000 representative genes. Measurements for the S1500+ genes were then used to extrapolate expression values for the remaining human transcriptome. As a case study of the improved downstream analysis achieved by extrapolation, the "measured only" and "whole transcriptome" (measured + extrapolated) gene sets were compared. Extrapolation increased the number of significant genes by 49%, bringing to the forefront many that are known to be associated with tunicamycin exposure. The extrapolation procedure also correctly identified established tunicamycin-related functional pathways reflected by coordinated changes in interrelated genes while maintaining the sample variability observed from the "measured only" genes. Extrapolation improved the gene- and pathway-level biological interpretations for a variety of downstream applications, including differential expression analysis, gene set enrichment pathway analysis, DAVID keyword analysis, Ingenuity Pathway Analysis, and NextBio correlated compound analysis. The extrapolated data highlight the role of metabolism/metabolic pathways, the ER, immune response, and the unfolded protein response, each of which are key activities associated with tunicamycin exposure that were unrepresented or underrepresented in one or more of the analyses of the original "measured only" dataset. Furthermore, the inclusion of the extrapolated genes raised "tunicamycin" from third to first upstream regulator in Ingenuity Pathway Analysis and from sixth to second most correlated compound in NextBio analysis. Therefore, our case study suggests an approach to extend and enhance data from the S1500+ platform for improved insight into biological mechanisms and functional outcomes of diseases, drugs, and other perturbations.
Competing Interests: Declaration of conflicting interests:The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
(© The Author(s) 2020.)
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معلومات مُعتمدة: HHSN273201700001C United States ES NIEHS NIH HHS
فهرسة مساهمة: Keywords: GeniE; S1500+; Transcriptomics; extrapolation; gene inference
تواريخ الأحداث: Date Created: 20201022 Latest Revision: 20201024
رمز التحديث: 20240628
مُعرف محوري في PubMed: PMC7545517
DOI: 10.1177/1177932220952742
PMID: 33088175
قاعدة البيانات: MEDLINE
الوصف
تدمد:1177-9322
DOI:10.1177/1177932220952742