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转录组分析揭示了根系对感染作出反应时的候选枢纽基因和潜在途径。

Transcriptomic Analysis Reveals Candidate Hub Genes and Putative Pathways in Roots Responding to Infection.

作者信息

Zheng Qiwei, Zhou Yangpujia, Ni Sui

机构信息

School of Marine Sciences, Ningbo University, Ningbo 315211, China.

出版信息

Curr Issues Mol Biol. 2025 Jul 10;47(7):536. doi: 10.3390/cimb47070536.

Abstract

, a soil-borne fungus responsible for Verticillium wilt, primarily colonizes members of the Brassicaceae family. Using roots as an experimental host, we systematically identify -responsive genes and pathways through comprehensive transcriptomic analysis, alongside screening of potential hub genes and evaluation of infection-associated regulatory mechanisms. The GSE62537 dataset was retrieved from the Gene Expression Omnibus database. After performing GEO2R analysis and filtering out low-quality data, 222 differentially expressed genes (DEGs) were identified, of which 184 were upregulated. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed on these DEGs. A protein-protein interaction network was constructed using the STRING database. CytoHubba and CytoNCA plugins in Cytoscape v3.10.3 were used to analyze and evaluate this network; six hub genes and four functional gene modules were identified. The GeneMANIA database was used to construct a co-expression network for hub genes. Systematic screening of transcription factors within the 14 DEGs revealed the inclusion of the hub gene . Integrative bioinformatics analysis centered on enabled prediction of a pathogen-responsive regulatory network architecture. We report -responsive components in , providing insights for disease resistance studies in Brassicaceae crops.

摘要

一种导致黄萎病的土传真菌,主要侵染十字花科植物成员。以根系作为实验宿主,我们通过全面的转录组分析系统地鉴定响应基因和途径,同时筛选潜在的枢纽基因并评估感染相关的调控机制。从基因表达综合数据库中检索了GSE62537数据集。在进行GEO2R分析并过滤掉低质量数据后,鉴定出222个差异表达基因(DEG),其中184个上调。对这些DEG进行了基因本体论和京都基因与基因组百科全书富集分析。使用STRING数据库构建了蛋白质-蛋白质相互作用网络。使用Cytoscape v3.10.3中的CytoHubba和CytoNCA插件对该网络进行分析和评估;鉴定出六个枢纽基因和四个功能基因模块。使用GeneMANIA数据库为枢纽基因构建共表达网络。对14个DEG中的转录因子进行系统筛选,发现其中包含枢纽基因。以该枢纽基因为中心的综合生物信息学分析能够预测病原体响应调控网络架构。我们报告了十字花科植物中响应该病原体的成分,为十字花科作物的抗病性研究提供了见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/559c/12293646/40a3a47201b3/cimb-47-00536-g001.jpg

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