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Meta-Analysis of Oxidative Transcriptomes in Insects

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Program of Biomedical Science, Graduate School of Integrated Sciences for Life, Hiroshima University, 3-10-23 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-0046, Japan
Database Center for Life Science (DBCLS), Joint Support-Center for Data Science Research, Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa, Chiba 277-0871, Japan
Academic Editor: Maria Cristina Albertini
Antioxidants 2021, 10(3), 345;
Received: 1 February 2021 / Revised: 17 February 2021 / Accepted: 22 February 2021 / Published: 25 February 2021
(This article belongs to the Special Issue Oxidative Stress Response in a Wide Variety of Insect Species)
Data accumulation in public databases has resulted in extensive use of meta-analysis, a statistical analysis that combines the results of multiple studies. Oxidative stress occurs when there is an imbalance between free radical activity and antioxidant activity, which can be studied in insects by transcriptome analysis. This study aimed to apply a meta-analysis approach to evaluate insect oxidative transcriptomes using publicly available data. We collected oxidative stress response-related RNA sequencing (RNA-seq) data for a wide variety of insect species, mainly from public gene expression databases, by manual curation. Only RNA-seq data of Drosophila melanogaster were found and were systematically analyzed using a newly developed RNA-seq analysis workflow for species without a reference genome sequence. The results were evaluated by two metric methods to construct a reference dataset for oxidative stress response studies. Many genes were found to be downregulated under oxidative stress and related to organ system process (GO:0003008) and adherens junction organization (GO:0034332) by gene enrichment analysis. A cross-species analysis was also performed. RNA-seq data of Caenorhabditis elegans were curated, since no RNA-seq data of insect species are currently available in public databases. This method, including the workflow developed, represents a powerful tool for deciphering conserved networks in oxidative stress response. View Full-Text
Keywords: insect; meta-analysis; oxidative stress; public database; RNA-seq; transcriptome insect; meta-analysis; oxidative stress; public database; RNA-seq; transcriptome
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MDPI and ACS Style

Bono, H. Meta-Analysis of Oxidative Transcriptomes in Insects. Antioxidants 2021, 10, 345.

AMA Style

Bono H. Meta-Analysis of Oxidative Transcriptomes in Insects. Antioxidants. 2021; 10(3):345.

Chicago/Turabian Style

Bono, Hidemasa. 2021. "Meta-Analysis of Oxidative Transcriptomes in Insects" Antioxidants 10, no. 3: 345.

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