Constructing mRNA-meth-miRNA single-sample networks to reveal the molecular interaction patterns induced by lunar orbital stressors in rice (Oryzasativa)
- PMID: 39724765
- DOI: 10.1016/j.plaphy.2024.109430
Constructing mRNA-meth-miRNA single-sample networks to reveal the molecular interaction patterns induced by lunar orbital stressors in rice (Oryzasativa)
Abstract
To explore the bio-effects during Moon exploration missions, we utilized the Chang'E 5 probe to carry the seeds of Oryza. Sativa L., which were later returned to Earth after 23 days in lunar orbit and planted in an artificial climate chamber. Compared to the control group, rice seeds that underwent spaceflight showed inhibited growth and development when planted on the ground. Then we collected samples and employed RNA sequencing (RNA-Seq) and whole-genome bisulfite sequencing (WGBS) in the tillering and heading stages of rice. To gain a comprehensive understanding of the dysregulation in molecular interaction patterns during Moon exploration, a bioinformatics pipeline based on mRNA-meth-miRNA Single-Sample Networks (SSNs) was developed. Specifically, we constructed four SSNs for each sample at the mRNA, DNA methylation (promoter and gene bodies), and miRNA levels. By combining with the Protein-Protein Interaction (PPI) network, SSNs can character individual-specific gene interaction patterns. Under spaceflight conditions, distinct interaction patterns emerge across various omics levels. However, the molecules driving changes at each omics level predominantly regulate consistent biological functions, such as metabolic processes, DNA damage and repair, cell cycle, developmental processes, etc. In the tillering stage, pathways such as ubiquitin mediated proteolysis, nucleotide excision repair, and nucleotide metabolism are significantly enriched. Moreover, we identified 18 genes that played key/hub roles in the dysregulation of multi-omics molecular interaction patterns, and observed their involvement in regulating the above biological processes. As aforementioned, our multi-omics SSNs method can reveal the molecular interaction patterns under deep space exploration.
Keywords: Deep space exploration; Gene interaction pattern; Multi-omics; Oryza sativa; Single-sample network; Spaceflight.
Copyright © 2024 Elsevier Masson SAS. All rights reserved.
Conflict of interest statement
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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