Resistance genes are an effective means for disease control in plants. They predominantly function by inducing a hypersensitive reaction, which results in localized cell death restricting pathogen spread. Some resistance genes elicit an atypical response, termed extreme resistance, where resistance is not associated with a hypersensitive reaction and its standard defense responses. Unlike hypersensitive reaction, the molecular regulatory mechanism(s) underlying extreme resistance is largely unexplored. One of the few known, naturally occurring, instances of extreme resistance is resistance derived from the soybean Rsv3 gene, which confers resistance against the most virulent Soybean mosaic virus strains. To discern the regulatory mechanism underlying Rsv3-mediated extreme resistance, we generated a gene regulatory network using transcriptomic data from time course comparisons of Soybean mosaic virus-G7-inoculated resistant (L29, Rsv3-genotype) and susceptible (Williams82, rsv3-genotype) soybean cultivars. Our results show Rsv3 begins mounting a defense by 6 hpi via a complex phytohormone network, where abscisic acid, cytokinin, jasmonic acid, and salicylic acid pathways are suppressed. We identified putative regulatory interactions between transcription factors and genes in phytohormone regulatory pathways, which is consistent with the demonstrated involvement of these pathways in Rsv3-mediated resistance. One such transcription factor identified as a putative transcriptional regulator was MYC2 encoded by Glyma.07G051500. Known as a master regulator of abscisic acid and jasmonic acid signaling, MYC2 specifically recognizes the G-box motif (“CACGTG”), which was significantly enriched in our data among differentially expressed genes implicated in abscisic acid- and jasmonic acid-related activities. This suggests an important role for Glyma.07G051500 in abscisic acid- and jasmonic acid-derived defense signaling in Rsv3. Resultantly, the findings from our network offer insights into genes and biological pathways underlying the molecular defense mechanism of Rsv3-mediated extreme resistance against Soybean mosaic virus. The computational pipeline used to reconstruct the gene regulatory network in this study is freely available at https://github.com/LiLabAtVT/rsv3-network.
Digital Object Identifier (DOI)
This project was funded in part by the Virginia Soybean Board. Additional funding was provided by the Agricultural Experiment Station Hatch Program and Open Access Subvention Fund – both at Virginia Tech. LD was funded in part by the John Lee Pratt Fellowship Program at Virginia Tech.
The sequencing data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE137263.
The computational pipeline used to reconstruct the gene regulatory network in this study is freely available at https://github.com/LiLabAtVT/rsv3-network.
DeMers, Lindsay C.; Redekar, Neelam R.; Kachroo, Aardra; Tolin, Sue A.; Li, Song; and Saghai Maroof, M. A., "A Transcriptional Regulatory Network of Rsv3-Mediated Extreme Resistance against Soybean Mosaic Virus" (2020). Plant Pathology Faculty Publications. 92.
S1 Table. Log2 fold change for differentially expressed genes for time pair comparisons. https://doi.org/10.1371/journal.pone.0231658.s001
pone.0231658.s002.xlsx (15 kB)
S2 Table. Gene ontology enrichment analysis (GO terms with padj < .05 only). https://doi.org/10.1371/journal.pone.0231658.s002
pone.0231658.s003.xlsx (55 kB)
S3 Table. Interactions predicted by four out of five network inference methods. https://doi.org/10.1371/journal.pone.0231658.s003
pone.0231658.s004.xlsx (102 kB)
S4 Table. Putative TF-gene interactions supported by orthologous interactions found in A. thaliana. https://doi.org/10.1371/journal.pone.0231658.s004
pone.0231658.s005.xlsx (47 kB)
S5 Table. Putative TF-module interactions supported by orthologous interactions found in A. thaliana. https://doi.org/10.1371/journal.pone.0231658.s005
pone.0231658.s006.xlsx (51 kB)
S6 Table. Motif enrichment analysis of co-expression modules and transcription factors recognizing motif sequences. https://doi.org/10.1371/journal.pone.0231658.s006