bioRxivPhysiology
Transcriptome analysis of FOXO-dependent hypoxia gene expression identifies Hipk as a regulator of low oxygen tolerance in Drosophila
K. Ding, E. C. Barretto, M. Johnston, B. Lee, M. Gallo, S. S. Grewal
Abstract
When exposed to low oxygen or hypoxia, animals must alter their metabolism and physiology to ensure proper cell-, tissue- and whole-body level adaptations to their hypoxic environment. These alterations often involve changes in gene expression. While extensive work has emphasized the importance of the HIF-1 alpha transcription factor on controlling hypoxia gene expression, less is known about other transcriptional mechanisms. We previously identified the transcription factor FOXO as a regulator of hypoxia tolerance in Drosophila larvae and adults. Here we use an RNA-sequencing approach to identify FOXO-dependent changes in gene expression that are associated with these tolerance effects. We found that hypoxia altered the expression of over 2000 genes and that approximately 40% of these gene expression changes required FOXO. We discovered that hypoxia exposure led to a FOXO-dependent increase in genes involved in cell signaling, such as kinases, GTPase regulators, and regulators of the Hippo/Yorkie pathway. Among these, we identified homeodomain-interacting protein kinase (Hipk) as being required for hypoxia survival. We also found that hypoxia suppresses the expression of genes involved in ribosome synthesis and egg production, and we showed that hypoxia suppresses tRNA synthesis and mRNA translation and reduces female fecundity. Among the downregulated genes, we discovered that FOXO was required for suppression of many ribosomal protein genes and genes involved in oxidative phosphorylation, pointing to a role for FOXO in limiting energetically costly processes such as protein synthesis and mitochondrial activity upon hypoxic stress. This work uncovers a widespread role for FOXO in mediating hypoxia changes in gene expression.
- organism: Drosophila
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
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