henhao
Sign in
Systems BiologyPLoS Computational Biology
Peer-reviewed journal article

Network architecture of transcriptomic stress responses in zebrafish embryos

Kaylee BeineiD, Lauric FeugereiD, Alexander P. TurneriD, Katharina C. Wollenberg ValeroiD

PDFDOIPreprint

Abstract

Protein-protein interaction (PPI) network topology can contribute to explain fundamental properties of genes, from expression levels to evolutionary constraints. Genes central to a network are more likely to be both conserved and highly expressed, whereas genes that are able to evolve in response to selective pressures but expressed at lower levels are located on the periphery of the network. The stress response is likewise thought to be conserved, however, experimental evidence for these patterns is limited. We examined whether the transcriptomic response to two environmental stressors (heat, UV, and their combination) is related to PPI architecture in zebrafish (Danio rerio) embryos. We show that stress response genes are situated more centrally in the PPI network. The transcriptomic response to heat was located in both central and peripheral positions, whereas UV response occupied central to intermediate positions. Across treatments, differentially expressed genes in different parts of the network affected identical phenotypes. Our results indicate that the zebrafish stress response has mostly conserved but also some stressor-specific aspects. These properties can aid in better understanding the organismal response to diverse and co-occurring stressors. Network position was further linked to the magnitude of fold changes of genes and types and number of linked phenotype components. Given the speed of contemporary changes in aquatic ecosystems, our approach can aid in identifying novel key regulators of the systemic response to specific stressors.

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.