ArticleBMC genomics2019
RNA-Seq analysis reveals transcript diversity and active genes after common cutworm (Spodoptera litura Fabricius) attack in resistant and susceptible wild soybean lines.
Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- GmIQD63 functions as a novel GmCDPK38-interacting protein in soybean defense against the common cutworm.Planta · 2025Article
- Physiological responses and transcriptome analysis ofFrontiers in plant science · 2024Article
- SoybeanInternational journal of molecular sciences · 2022Article
- CALCIUM-DEPENDENT PROTEIN KINASE38 regulates flowering time and common cutworm resistance in soybean.Plant physiology · 2022Article
- Exploring the genetic potential of Pakistani soybean cultivars through RNA-seq based transcriptome analysis.Molecular biology reports · 2022Article
- Plant Soft Rot Development and Regulation from the Viewpoint of Transcriptomic Profiling.Plants (Basel, Switzerland) · 2020Article
- Article
- Knockdown of GmVQ58 encoding a VQ motif-containing protein enhances soybean resistance to the common cutworm (Spodoptera litura Fabricius).Journal of experimental botany · 2020Article
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10 authors.
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Abstract
backgroundCommon cutworm (CCW) is highly responsible for destabilizing soybean productivity. Wild soybean is a resource used by breeders to discover elite defensive genes.
resultsThe transcriptomes of two wild accessions (W11 and W99) with different resistance to CCW were analyzed at early- and late-induction time points. After induction, the susceptible accession W11 differentially expressed 1268 and 508 genes at the early and late time points, respectively. Compared with W11, the resistant accession W99 differentially expressed 1270 genes at the early time point and many more genes (2308) at the late time point. In total, 3836 non-redundant genes were identified in both lines. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the differentially expressed genes (DEGs) in W99 at the late time point were mostly associated with specific processes and pathways. Among the non-redundant genes, 146 genes were commonly up-regulated in the treatment condition compared with the control condition at the early- and late-induction time points in both accessions used in this experiment. Approximately 40% of the common DEGs were related to secondary metabolism, disease resistance, and signal transduction based on their putative function. Excluding the common DEGs, W99 expressed more unique DEGs than W11. Further analysis of the 3836 DEGs revealed that the induction of CCW not only up-regulated defense-related genes, including 37 jasmonic acid (JA)-related genes, 171 plant-pathogen-related genes, and 17 genes encoding protease inhibitors, but also down-regulated growth-related genes, including 35 photosynthesis-related genes, 48 nutrition metabolism genes, and 28 auxin metabolism genes. Therefore, representative defense-related and growth-related genes were chosen for binding site prediction via co-expression of transcription factors (TFs) and spatial expression pattern analyses. In total, 53 binding sites of 28 TFs were identified based on 3 defense-related genes and 3 growth-related genes. Phosphate transporter PT1, which is a representative growth-related gene, was transformed into soybean, and the transgenic soybean plants were susceptible to CCW.
conclusionsIn summary, we described transcriptome reprograming after herbivore induction in wild soybean, identified the susceptibility of growth-related genes, and provided new resources for the breeding of herbivore-resistant cultivated soybeans.
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