Multi-Omic Meta-Analysis of Transcriptomes and the Bibliome Uncovers Novel Hypoxia-Inducible Genes

Abstract

Hypoxia is a condition in which cells, tissues, or organisms are deprived of sufficient oxygen supply. Aerobic organisms have a hypoxic response system, represented by hypoxia-inducible factor 1-α (HIF1A), to adapt to this condition. Due to publication bias, there has been little focus on genes other than well-known signature hypoxia-inducible genes. Therefore, in this study, we performed a meta-analysis to identify novel hypoxia-inducible genes. We searched publicly available transcriptome databases to obtain hypoxia-related experimental data, retrieved the metadata, and manually curated it. We selected the genes that are differentially expressed by hypoxic stimulation, and evaluated their relevance in hypoxia by performing enrichment analyses. Next, we performed a bibliometric analysis using gene2pubmed data to examine genes that have not been well studied in relation to hypoxia. Gene2pubmed data provides information about the relationship between genes and publications. We calculated and evaluated the number of reports and similarity coefficients of each gene to HIF1A, which is a representative gene in hypoxia studies. In this data-driven study, we report that several genes that were not known to be associated with hypoxia, including the G protein-coupled receptor 146 gene, are upregulated by hypoxic stimulation.

Comparison of Oxidative and Hypoxic Stress Responsive Genes from Meta-Analysis of Public Transcriptomes

“…We calculated the ratio of expression value of each gene in all pairs between Oxidative stress and Normal state (termed as ON_ratio) [10,11]. The ON_ratio was calculated using equation ( 1):…”

“…Hypoxia is characterized by reduced oxygen availability in tissues and is known to increase ROS levels through changes in signaling cascades and protein expression [9]. A previous study has successfully attained the collective intelligence of public hypoxic transcriptomes by analyzing 944 runs of RNA-seq data [10]. This approach, a statistical analysis of combined results from multiple studies, called meta-analysis has attracted attentions.…”

“…To discover novel areas by utilizing valuable open sources, we collected OS transcriptomes of human cultured cells from public databases and performed a meta-analysis. This study aimed to investigate the key genes and characteristics for not only specifically OS, but also comparison between OS and hypoxia, by analyzing the differentially expressed genes (DEGs) from the meta-analysis of both of OS and hypoxia, based on 1783 RNA-seq data (839 from this study and 944 from our previous study of meta-analysis in hypoxia [10]). These investigated genes, the OS curated dataset for OS, and the method described in this study to compare the results of multiple meta-analyses are expected to be valuable sources for promoting future studies.…”

Comparison of Oxidative and Hypoxic Stress Responsive Genes from Meta-Analysis of Public Transcriptomes

“…Hypoxia is characterized by reduced oxygen availability in tissues and is known to increase ROS levels through changes in signaling cascades and protein expression [ 9 ]. A previous study has successfully attained the collective intelligence of public hypoxic transcriptomes by analyzing 944 runs of RNA-seq data [ 10 ]. This approach, a statistical analysis of combined results from multiple studies, called meta-analysis, has attracted attention.…”

“…This study aimed to investigate the key genes and characteristics for both OS and the comparison between OS and hypoxia by analyzing the differentially expressed genes (DEGs) from the meta-analysis of both OS and hypoxia. The investigation was based on 1783 sets of RNA-seq data (839 from this study and 944 from our previous study of meta-analysis in hypoxia [ 10 ]). These investigated genes, the curated dataset for OS, and the method described in this study to compare the results of multiple meta-analyses are expected to be valuable sources for promoting future studies.…”