Evidence map›Paper›PMID 39582626›Full record

ArticleFrontiers in plant science2024

Using single-sample networks and genetic algorithms to identify radiation-responsive genes in rice affected by heavy ions of the galactic cosmic radiation with different LET values.

Yan Zhang, Wei Wang, Meng Zhang, Binquan Zhang, Shuai Gao, Meng Hao, Dazhuang Zhou, Lei Zhao, Guenther Reitz, Yeqing Sun

Abstract read
In one paragraph

Article in Frontiers in plant science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yan ZhangInstitute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian, Liaoning, China.
Wei WangInstitute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian, Liaoning, China.
Meng ZhangInstitute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian, Liaoning, China.
Binquan ZhangNational Space Science Center, Chinese Academy of Sciences, Beijing, China.
Shuai GaoInstitute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian, Liaoning, China.
Meng HaoInstitute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian, Liaoning, China.
Dazhuang ZhouNational Space Science Center, Chinese Academy of Sciences, Beijing, China.
Lei ZhaoInstitute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian, Liaoning, China.
Guenther ReitzConsultant German Aerospace Center, Aerospace Medicine, Radiobiology Department, Köln, Germany.
Yeqing SunInstitute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Heavy ions of the galactic cosmic radiation dominate the radiation risks and biological effects for plants under spaceflight conditions. However, the biological effects and sensitive genes caused by heavy ions with different linear energy transfer (LET) values have not been thoroughly studied. Methods: To comprehensively analyze the biological effects of heavy ions with different LET values on rice under spaceflight conditions, we utilized the Shijian-10 recoverable satellite (SJ-10) to transport the dehydrated rice seeds on a 12.5-day mission in a 252 km low Earth orbit (LEO), and obtained rice plants hit by individual heavy ions with LET values ranging from 18 keV/μm to 213 keV/μm. The transcriptome and methylation sequencing were conducted on above plants, and a bioinformatics pipeline based on single-sample networks (SSNs) and genetic algorithms (GA) was developed to analyze the multi-omics expression profiles in this work. Note that SSNs can depict the gene interaction patterns within a single sample. The LET regression models were constructed from both gene expression and interaction pattern perspectives respectively, and the radiation response genes that played significant roles in the models were identified. We designed a gene selection algorithm based on GA to enhance the performance of LET regression models. Results: The experimental results demonstrate that all our models exhibit excellent regression performance (R2 values close to 1), which indicates that both gene expressions and interaction patterns can reflect the molecular changes caused by heavy ions with different LET values. LET-related genes (genes exhibiting strong correlation with LET values) and radiation-responsive genes were identified, primarily involved in DNA damage and repair, oxidative stress, photosynthesis, nucleic acid metabolism, energy metabolism, amino acid/protein metabolism, and lipid metabolism, etc. DNA methylation plays a crucial role in responding to heavy ions stressors and regulates the aforementioned processes. Discussion: To the best of our knowledge, this is the first study to report the multi-omics changes in plants after exposure to heavy ions with different LET values under spaceflight conditions.

Indexed as

gene interaction patternheavy ionsLET regression modellinear energy transferspaceflightspace radiation

Identifiers

PMID39582626
PMCPMC11581881

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.