Related Experiment Video
Updated: Aug 29, 2025
A Contrast of Three Inoculation Techniques used to Determine the Race of Unknown Fusarium oxysporum f.sp. niveum Isolates
Published on: October 28, 2021
Meta-analysis of fungal plant pathogen Fusarium oxysporum infection-related gene profiles using transcriptome
Hongsheng Cai1, Na Yu1, Yingying Liu1
1Key Laboratory of Molecular and Cytogenetics, Heilongjiang Province, College of Life Science and Technology, Harbin Normal University, Harbin, China.
Abstract:
Fusarium oxysporum is a serious soil-borne fungal pathogen that affects the production of many economically important crops worldwide. Recent reports suggest that this fungus is becoming the dominant species in soil and could become the main infectious fungus in the future. However, the infection mechanisms employed by F. oxysporum are poorly understood. In the present study, using a network meta-analysis technique and public transcriptome datasets for different F. oxysporum and plant interactions, we aimed to explore the common molecular infection strategy used by this fungus and to identify vital genes involved in this process. Principle component analysis showed that all the fungal culture samples from different datasets were clustered together, and were clearly separated from the infection samples, suggesting the feasibility of an integrated analysis of heterogeneous datasets. A total of 335 common differentially expressed genes (DEGs) were identified among these samples, of which 262 were upregulated and 73 were downregulated significantly across the datasets. The most enriched functional categories of the common DEGs were carbohydrate metabolism, amino acid metabolism, and lipid metabolism. Nine co-expression modules were identified, and two modules, the turquoise module and the blue module, correlated positively and negatively with all the infection processes, respectively. Co-expression networks were constructed for these two modules and hub genes were identified and validated. Our results comprise a cross fungal-host interaction resource, highlighting the use of a network biology approach to gain molecular insights.
Insights
Fusarium oxysporum infection mechanisms were explored using network meta-analysis. This study identified common molecular strategies and vital genes, revealing key metabolic pathways involved in fungal pathogenesis.
Area of Science:
- Plant Pathology
- Mycology
- Genomics
Background:
- Fusarium oxysporum is a significant soil-borne fungal pathogen impacting global crop production.
- This fungus is increasingly dominant, posing a future threat, yet its infection mechanisms remain poorly understood.
Purpose of the Study:
- To explore the common molecular infection strategy of Fusarium oxysporum.
- To identify vital genes involved in the fungal infection process using network biology.
Main Methods:
- Network meta-analysis of public transcriptome datasets from F. oxysporum and plant interactions.
- Principle component analysis for dataset integration.
- Identification and validation of differentially expressed genes (DEGs) and co-expression network modules.
Main Results:
- 335 common DEGs identified across datasets (262 upregulated, 73 downregulated).
- Enriched functional categories include carbohydrate, amino acid, and lipid metabolism.
- Two key co-expression modules (turquoise and blue) were identified, correlating with infection processes, and hub genes were validated.
Conclusions:
- This study provides a valuable resource for understanding cross-fungal-host interactions.
- Network biology offers molecular insights into Fusarium oxysporum pathogenesis.
- Identified genes and pathways are crucial for fungal infection and potential targets for crop protection.
