Gibellulopsis nigrescens Vn-1 induced the defense response of sunflower
We previously identified the hypovirulent strain G. nigrescens Vn-1 as a promising candidate for conferral of cross-protection against sunflower Verticillium wilt [42]. To investigate the mechanism of induced resistance achieved with this hypovirulent strain in the present study, we measured defense enzyme activities in sunflower at different time points after inoculation. We found that the activities of four defense enzymes, namely, peroxidase (POD), superoxide dismutase (SOD), catalase (CAT), and phenylalanine ammonia lyase (PAL), were induced after inoculation. Three of these enzymes (POD, SOD, and CAT) had their highest levels of catalytic activity at 24 h post-inoculation (hpi). The highest PAL activity occurred at 12 hpi, with no significant difference observed between 12 hpi and 24 hpi (Fig. 1A). Defense enzyme activities after inoculation with G. nigrescens Vn-1 were higher than those following infection with V. dahliae V33, a virulent strain causing more serious symptoms of sunflower Verticillium wilt. A quantity Real Time Polymerase Chain Reaction (qRT-PCR) analysis revealed that the expressions of HaPOD, HaSOD, HaCAT, and HaPAL were upregulated at 24 hpi (Fig. 1B). Interestingly, sunflower seedlings inoculated with G. nigrescens Vn-1 or V. dahliae V33 exhibited reduced H2O2 accumulation compared with a control (CK) sample at 24 hpi (Fig. 2). These results indicate that hypovirulent strain G. nigrescens Vn-1 was able to induce the defense response of sunflower and that 24 hpi was the critical time point, as expressions of the resistance genes were upregulated. The hypovirulent and virulent strains were both able to clear H2O2 accumulated in sunflower seedlings during infection.
Overview of Illumina RNA-sequencing data
To investigate the mechanism of resistance induced by hypovirulent strain G. nigrescens Vn-1, we performed transcriptome sequencing of sunflower root samples inoculated with G. nigrescens Vn-1 or V. dahliae V33, as well as a control, at 24 hpi. The sequencing results were used for comparative transcriptome analysis. More than 45 million clean reads (> 6.5 Gb) were generated per root sample (Table 1). The transcriptome assemblies obtained for the three groups of sunflower roots were pooled and used to assemble complete transcripts based on the sunflower genome. After elimination of incomplete transcripts, 86.17% to 87.30% of clean reads were mapped to the reference genome; in total, 83.17% to 84.34 % of clean reads were uniquely mapped (Fig. 3A, Table S1). More than 95% of the reads were located within exons (Fig. 3B, Table S1). In this study, a gene was considered to be expressed in a sample if a transcript was detected in the cDNA library for three replicates. Relatively few genes were highly expressed (Fig. 3C). In each group of sunflower root samples, the data from three replicates were highly correlated (Pearsonās r > 0.95), thus indicating that the transcriptome profiles were highly reproducible (Fig. 3D).
Functional enrichment analysis of DEGs
To investigate sunflower genes potentially involved in resistance to Verticillium wilt, we compared the three transcriptomes. We identified a total of 1,790 DEGs between Vn-1 and WT groups, including 404 and 1,386 DEGs with up- and downregulated expressions, respectively. We also identified 3,469 DEGs between V33 and WT groups, including 1,204 and 2,445 DEGs with up- and downregulated expressions, respectively. Moreover, 744 DEGs were discovered between Vn-1 and V33 groups, of which 501 and 243 were up- and downregulated, respectively (Fig. 4A). Many more genes were differentially expressed between V33 and CK groups than between Vn-1 and CK groups. Venn diagram analysis of DEGs revealed that 1,167 DEGs were included in either Vn-1 vs. CK or V33 vs. CK comparisons, whereas only 58 DEGs were included in all three comparison groups (Vn-1 vs. CK, V33 vs. CK, and Vn-1 vs. V33) (Fig 4B).Ā
Validation of DEGs
To confirm the reliability of the DEGs identified in the comparative transcriptome analysis, we randomly selected 16 DEGs that were differentially expressed among the three comparison groups for qRT-PCR verification. The qRT-PCR results for most DEGs were highly correlated with the RNA-seq data (Pearsonās r ³ 0.80); the exception was HannXRQ_Chr01g0021411 (Pearsonās r = 0.79) (Fig. 5). This strong correlation indicates that the RNA-seq data were valid and reliable.
Gene Ontology (GO) enrichment analysis of DEGs
To functionally characterize DEGs, we performed a GO enrichment analysis. The number of significantly enriched GO terms in the V33 vs. CK comparison group was much higher than in Vn-1 vs. CK and Vn-1 vs. V33 comparison groups. The nine most significantly enriched GO terms in the Vn-1 vs. CK group were as follows: oxidationāreduction process, response to oxidative stress, single-organism metabolic process, lipid metabolic process, siroheme biosynthetic process, siroheme metabolic process, heme biosynthetic process, cellular glucan metabolic process, and glucan metabolic process (Fig. 6A, Table S2). Oxidationāreduction, lipid metabolic, carbohydrate metabolic, and signaling processes were the major subcategories of processes within the biological process category. These four subcategories were also enriched in the V33 vs. CK comparison group (Fig. 6B, Table S2). In both Vn-1 vs. CK and V33 vs. CK comparison groups, the most abundant GO term in the cellular component category was extracellular region. In the molecular function category, oxidoreductase activity was the most significantly enriched subcategory in all three comparison groups (Fig. 6, Table S2). According to this GO enrichment analysis of DEGs, enriched resistance-related GO terms in Vn-1 vs. CK and V33 vs. CK comparison groups were highly similar, which suggests that both hypovirulent and virulent strains could induce defense responses at early stage of infection.
To identify GO terms associated with Verticillium wilt resistance in sunflower, we compared the terms significantly enriched in Vn-1 vs. CK and V33 vs. CK groups. We found 34 enriched GO terms common to both groups. In addition, 23 and 57 significantly enriched terms were unique to Vn-1 vs. CK and V33 vs. CK groups, respectively (Fig. 7). We speculated that these GO terms were related to resistance and susceptibility to Verticillium wilt.Ā
KEGG pathway enrichment analysis of DEGs
DEG functions were also examined by KEGG pathway enrichment analysis. DEGs identified in the three comparison groups were found to be related to 17 KEGG pathway (Table S3). According to the results of the analysis, infection with either hypovirulent or virulent strains influenced the expressions of genes related to the following pathways: biosynthesis of secondary metabolites, biosynthesis of unsaturated fatty acids, fatty acid elongation, fatty acid metabolism, phenylalanine metabolism, phenylpropanoid biosynthesis, and plantāpathogen interaction. Majority of DEGs contributing to plantāpathogen interaction pathway, were down-regulated during the Verticillium species interacting with sunflower (Fig S1). Infection with hypovirulent strain Vn-1 additionally affected the expressions of genes in alanine, aspartate, and glutamate metabolism; cutin, suberin and wax biosynthesis; and ribosome pathways (Table S3, Fig. S2), whereas virulent strain V33 was also able to trigger gene expressions in carbon fixation in photosynthetic organisms, carbon metabolism, citrate cycle (TCA cycle), fatty acid degradation, glycolysis/gluconeogenesis, pentose phosphate, and proteasome pathways (Table S3, Fig. S3). Moreover, only three KEGG pathways were significantly enriched in DEGs in the Vn-1 vs. V33 comparison: biosynthesis of unsaturated acids, fatty acid metabolism, and plantāpathogen interaction (Table S3). These results suggest that genes in many KEGG pathways, including alanine, aspartate, and glutamate metabolism; cutin, suberin and wax biosynthesis; and ribosome pathways, were involved in the specific resistance induced by the hypovirulent strain.Ā
Prediction of genes related to Verticillium wilt resistance in sunflower
To detect Verticillium wilt resistance genes in sunflower, we analyzed the DEGs uncovered by comparative transcriptome methods. DEGs upregulated in Vn-1 vs. CK and Vn-1 vs. V33 comparison groups but downregulated or not significantly changed in V33 vs. CK were predicted to be resistance genes. As a result, 33 genes were predicted to participate in resistance against V. dahliae (Fig. 8). As detailed in Table S4, these predicted resistance genes encode seven transcription factors, two phytohormone response factors, two E3 ubiquitin-protein ligases, and two CCR4-associated factor 1 proteins. In addition, two proteins (with conserved leucine-rich repeat (LRR) domains) encoded by HannXRQ_Chr01g0025331 and HannXRQ_Chr14g0444761 were predicted as resistance-related receptors (Fig. S4).
In contrast to resistance genes, genes related to susceptibility were expected to be upregulated in V33 vs. CK and V33 vs. Vn-1 comparison groups and downregulated or unchanged in the Vn-1 vs. CK group. As a result, 160 genes were predicted to be related to susceptibility to Verticillium wilt in sunflower (Fig. 8, Table S5). Further research to verify these potential resistance and susceptibility genes is required.