The Role of Plant Transcription Factors in the Fight against Plant Viruses

Kotapati, Kasi Viswanath; Kuo, Song-Yi; Tu, Chin-Wei; Hsu, Yau-Heiu; Huang, Ying; Hu, Chung-Chi

doi:10.3390/ijms24098433

Cited by 30 publications

(12 citation statements)

References 181 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, we identified the functional known gene CUC2 ( AT5G53950 ) which is an elite polyphenotype gene ( Figure 4A ). In A. thaliana , AT5G39610 is associated with salt resistance ( Zhao et al., 2022 ), AT3G49530 is associated with drought resistance ( Kim et al., 2012 ), and AT5G08790 is associated with disease resistance ( Viswanath et al., 2023 ). In rice, LOC_OS04G38720 influences plant height and grain weight ( Chen et al., 2015 ; Jiang et al., 2018 ).…”

Section: Resultsmentioning

confidence: 99%

A new model construction based on the knowledge graph for mining elite polyphenotype genes in crops

Zhang,

Zhao,

Xian

et al. 2024

Front. Plant Sci.

View full text Add to dashboard Cite

Identifying polyphenotype genes that simultaneously regulate important agronomic traits (e.g., plant height, yield, and disease resistance) is critical for developing novel high-quality crop varieties. Predicting the associations between genes and traits requires the organization and analysis of multi-dimensional scientific data. The existing methods for establishing the relationships between genomic data and phenotypic data can only elucidate the associations between genes and individual traits. However, there are relatively few methods for detecting elite polyphenotype genes. In this study, a knowledge graph for traits regulating-genes was constructed by collecting data from the PubMed database and eight other databases related to the staple food crops rice, maize, and wheat as well as the model plant Arabidopsis thaliana. On the basis of the knowledge graph, a model for predicting traits regulating-genes was constructed by combining the data attributes of the gene nodes and the topological relationship attributes of the gene nodes. Additionally, a scoring method for predicting the genes regulating specific traits was developed to screen for elite polyphenotype genes. A total of 125,591 nodes and 547,224 semantic relationships were included in the knowledge graph. The accuracy of the knowledge graph-based model for predicting traits regulating-genes was 0.89, the precision rate was 0.91, the recall rate was 0.96, and the F1 value was 0.94. Moreover, 4,447 polyphenotype genes for 31 trait combinations were identified, among which the rice polyphenotype gene IPA1 and the A. thaliana polyphenotype gene CUC2 were verified via a literature search. Furthermore, the wheat gene TraesCS5A02G275900 was revealed as a potential polyphenotype gene that will need to be further characterized. Meanwhile, the result of venn diagram analysis between the polyphenotype gene datasets (consists of genes that are predicted by our model) and the transcriptome gene datasets (consists of genes that were differential expression in response to disease, drought or salt) showed approximately 70% and 54% polyphenotype genes were identified in the transcriptome datasets of Arabidopsis and rice, respectively. The application of the model driven by knowledge graph for predicting traits regulating-genes represents a novel method for detecting elite polyphenotype genes.

show abstract

Section: Resultsmentioning

confidence: 99%

A new model construction based on the knowledge graph for mining elite polyphenotype genes in crops

Zhang,

Zhao,

Xian

et al. 2024

Front. Plant Sci.

View full text Add to dashboard Cite

show abstract

“…Numerous studies have reported that plant TFs participate in viral infection by interacting with viral proteins (Viswanath et al., 2023 ). The changes in transcription levels of these TFs during RSV infection have been validated, but it is still unknown whether these TFs can directly interact with RSV proteins.…”

Section: Resultsmentioning

confidence: 99%

Integrated ATAC‐seq and RNA‐seq data analysis identifies transcription factors related to rice stripe virus infection in Oryza sativa

Li,

Zhang

et al. 2024

Molecular Plant Pathology

View full text Add to dashboard Cite

Animal studies have shown that virus infection causes changes in host chromatin accessibility, but little is known about changes in chromatin accessibility of plants infected by viruses and its potential impact. Here, rice infected by rice stripe virus (RSV) was used to investigate virus‐induced changes in chromatin accessibility. Our analysis identified a total of 6462 open‐ and 3587 closed‐differentially accessible chromatin regions (DACRs) in rice under RSV infection by ATAC‐seq. Additionally, by integrating ATAC‐seq and RNA‐seq, 349 up‐regulated genes in open‐DACRs and 126 down‐regulated genes in closed‐DACRs were identified, of which 34 transcription factors (TFs) were further identified by search of upstream motifs. Transcription levels of eight of these TFs were validated by reverse transcription‐PCR. Importantly, four of these TFs (OsWRKY77, OsWRKY28, OsZFP12 and OsERF91) interacted with RSV proteins and are therefore predicted to play important roles in RSV infection. This is the first application of ATAC‐seq and RNA‐seq techniques to analyse changes in rice chromatin accessibility caused by RSV infection. Integrating ATAC‐seq and RNA‐seq provides a new approach to select candidate TFs in response to virus infection.

show abstract

“…Transcription factors (TFs) play crucial roles in plant defense mechanisms and innate immunity through interactions with cofactors and cisacting elements. The transcriptional regulation of certain TFs can enhance plant defenses against viral infections ( Viswanath et al, 2023 ). Therefore, it is plausible that miRNAs may regulate the viral infection process by targeting TFs.…”

Section: Resultsmentioning

confidence: 99%

Unraveling the regulatory network of miRNA expression in Potato Y virus-infected of Nicotiana benthamiana using integrated small RNA and transcriptome sequencing

Song,

Gao,

Song

et al. 2024

Front. Genet.

View full text Add to dashboard Cite

Potato virus Y (PVY) disease is a global problem that causes significant damage to crop quality and yield. As traditional chemical control methods are ineffective against PVY, it is crucial to explore new control strategies. MicroRNAs (miRNAs) play a crucial role in plant and animal defense responses to biotic and abiotic stresses. These endogenous miRNAs act as a link between antiviral gene pathways and host immunity. Several miRNAs target plant immune genes and are involved in the virus infection process. In this study, we conducted small RNA sequencing and transcriptome sequencing on healthy and PVY-infected N. benthamiana tissues (roots, stems, and leaves). Through bioinformatics analysis, we predicted potential targets of differentially expressed miRNAs using the N. benthamiana reference genome and the PVY genome. We then compared the identified differentially expressed mRNAs with the predicted target genes to uncover the complex relationships between miRNAs and their targets. This study successfully constructed a miRNA-mRNA network through the joint analysis of Small RNA sequencing and transcriptome sequencing, which unveiled potential miRNA targets and identified potential binding sites of miRNAs on the PVY genome. This miRNA-mRNA regulatory network suggests the involvement of miRNAs in the virus infection process.

show abstract

The Role of Plant Transcription Factors in the Fight against Plant Viruses

Cited by 30 publications

References 181 publications

A new model construction based on the knowledge graph for mining elite polyphenotype genes in crops

A new model construction based on the knowledge graph for mining elite polyphenotype genes in crops

Integrated ATAC‐seq and RNA‐seq data analysis identifies transcription factors related to rice stripe virus infection in Oryza sativa

Unraveling the regulatory network of miRNA expression in Potato Y virus-infected of Nicotiana benthamiana using integrated small RNA and transcriptome sequencing

Contact Info

Product

Resources

About