Next Article in Journal
Anti-Inflammatory Effects of Diospyrin on Lipopolysaccharide-Induced Inflammation Using RAW 264.7 Mouse Macrophages
Next Article in Special Issue
Comparative Evaluation of the Angiogenic Potential of Hypoxia Preconditioned Blood-Derived Secretomes and Platelet-Rich Plasma: An In Vitro Analysis
Previous Article in Journal
Emerging Concepts and Challenges in Rheumatoid Arthritis Gene Therapy
Open AccessArticle

Meta-Analysis of Hypoxic Transcriptomes from Public Databases

by 1,* and 2,*
Database Center for Life Science (DBCLS), Joint Support-Center for Data Science Research, Research Organization of Information and Systems, 1111 Yata, Mishima, Shizuoka 411-8540, Japan
Department of Human Stress Response Science, Institute of Biomedical Science, Kansai Medical University, Hirakata 573-1010, Japan
Authors to whom correspondence should be addressed.
Biomedicines 2020, 8(1), 10;
Received: 30 November 2019 / Revised: 26 December 2019 / Accepted: 8 January 2020 / Published: 9 January 2020
(This article belongs to the Special Issue Hypoxia-Inducible Factors: Regulation and Therapeutic Potential)
Hypoxia is the insufficiency of oxygen in the cell, and hypoxia-inducible factors (HIFs) are central regulators of oxygen homeostasis. In order to obtain functional insights into the hypoxic response in a data-driven way, we attempted a meta-analysis of the RNA-seq data from the hypoxic transcriptomes archived in public databases. In view of methodological variability of archived data in the databases, we first manually curated RNA-seq data from appropriate pairs of transcriptomes before and after hypoxic stress. These included 128 human and 52 murine transcriptome pairs. We classified the results of experiments for each gene into three categories: upregulated, downregulated, and unchanged. Hypoxic transcriptomes were then compared between humans and mice to identify common hypoxia-responsive genes. In addition, meta-analyzed hypoxic transcriptome data were integrated with public ChIP-seq data on the known human HIFs, HIF-1 and HIF-2, to provide insights into hypoxia-responsive pathways involving direct transcription factor binding. This study provides a useful resource for hypoxia research. It also demonstrates the potential of a meta-analysis approach to public gene expression databases for selecting candidate genes from gene expression profiles generated under various experimental conditions. View Full-Text
Keywords: hypoxia; transcriptome; RNA-seq; ChIP-seq; public database; meta-analysis hypoxia; transcriptome; RNA-seq; ChIP-seq; public database; meta-analysis
Show Figures

Figure 1

MDPI and ACS Style

Bono, H.; Hirota, K. Meta-Analysis of Hypoxic Transcriptomes from Public Databases. Biomedicines 2020, 8, 10.

AMA Style

Bono H, Hirota K. Meta-Analysis of Hypoxic Transcriptomes from Public Databases. Biomedicines. 2020; 8(1):10.

Chicago/Turabian Style

Bono, Hidemasa; Hirota, Kiichi. 2020. "Meta-Analysis of Hypoxic Transcriptomes from Public Databases" Biomedicines 8, no. 1: 10.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop