Characterization of RNAi components

F. graminearum possesses two Dicers and two Argonautes, as previously reported [37]. Both Dicers (FgDicer1 and FgDicer2) contain domain architectures similar to those of other representative orthologs; however, FgDicer1 and Dcl1 of Schizosaccharomyces pombe do not carry the double-stranded RNA-binding (DSRM) domain (Fig 1A). Each Argonaute has a conserved catalytic triad (Asp-Asp-His/Asp, DDH/D); FgAgo2 contains the third histidine residue but is replaced by an aspartate in FgAgo1. FgAGO2 was also annotated as FgSMS2 in a previous study [9].

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Fig 1. Characterization of Dicers and Argonautes in F. graminearum.

(A) Domain architectures of F. graminearum Dicer and Argonaute proteins along with those of representative orthologs. Domains were predicted using SMART [38]. Conservation analysis of the Asp-Asp-His (DDH) motif that comprises the active sites of Argonautes. The DDH motif is conserved in FgAgo2, but the third histidine residue is replaced by an aspartate in FgAgo1. The amino acid sequences of orthologs: Homo sapiens Dicer1 (NP_803187), Arabidopsis thaliana Dcl2 (NP_566199), Schizosaccharomyces pombe Dcl1 (Q09884), F. graminearum FgDicer1 (Gene ID: FGSG_09025), FgDicer2 (Gene ID: FGSG_04408), H. sapiens Ago2 (NP_036286), A. thaliana Ago1 (NP_849784), S. pombe Ago1 (NP_587782), F. graminearum FgAgo1 (Gene ID: FGSG_16976), and F. graminearum FgAgo2 (Gene ID: FGSG_00348). (B) Expression profiles of FgDICER1, FgDICER2, FgAGO1, and FgAGO2 in the F. graminearum wild-type strain during vegetative and sexual development. Transcript levels were analyzed via qRT-PCR during the vegetative (V3 and V5, 3 and 5 days after inoculation, respectively) and sexual stages (S3, S5 and S7, 3, 5, and 7 days after sexual induction, respectively) on carrot agar. The transcript level of the gene at the 3-day vegetative stage (V3) was arbitrarily set to 1, and this value was used for comparison to other periods. (C) Forcible ascospore discharge. A semi-circular agar block covered with perithecia was placed on a coverslip. Images were collected 48 h after the assay was initiated. White cloudy material (indicated with an arrow) represents discharged ascospores. (D) Number of discharged ascospores. Discharged ascospores were corrected for one week from the 7-day-old sexually induced cultures. (E) Asci rosettes. Imaging was performed 8 days after sexual induction. Red arrows indicate asci with defective ascospore delimitation. Scale bar = 20 μm.

https://doi.org/10.1371/journal.pgen.1006595.g001

We measured the transcript levels of these genes during vegetative growth and sexual development (Fig 1B). The expression levels of FgDICER1 and FgAGO2 were significantly increased after sexual induction, suggesting that they have active roles during perithecia development in F. graminearum. The transcript levels of FgDICER2 were similarly maintained throughout the developmental stages, while FgAGO1 transcripts accumulated to high levels as mycelia aged (V5, 5 days after inoculation) and as perithecia matured (S3–7, 3–7 days after sexual induction).

To characterize the roles of these genes in fungal development, we generated each gene deletion mutant using the homologous recombination method (S1 Fig and S1 Table). Although all of the tested F. graminearum strains produced mature perithecia with similar numbers, the Fgdicer1 and Fgago2 mutants were severely defective in forcible ascospore discharge, while the Fgdicer2 and Fgago1 mutants showed indistinguishable phenotypes compared to those of the wild type (Fig 1C and 1D). Except for defective sexual development, we could not find any defect in vegetative growth, virulence, or stress responses in the mutants, in accordance with a previous report [37].

Double-deletion mutants were generated to verify the redundant roles of Dicers or Argonautes. Fgdicer2 and Fgago1 mutants were first outcrossed with the Δmat2 strain to produce the HK338 (Δmat2 ΔFgdicer2) and HK339 (Δmat2 ΔFgago1) strains, respectively (S1 Table). Then, the double-deletion mutants HK340 (ΔFgdicer1 ΔFgdicer2) and HK341 (ΔFgago1 ΔFgago2) were generated from the outcrosses HK338 × Fgdicer1 and HK339 × Fgago2, respectively. Deletion of both FgDICER1 and FgDICER2 almost completely abolished ascospore discharge, whereas Fgdicer1 mutants discharged reduced amounts of ascospores compared to those of the wild type, suggesting a synergistic effect of mutant phenotypes between single- and double-deletion mutants (Fig 1C and 1D). Double-deletion Fgago1 Fgago2 mutants showed similar phenotypes to those of Fgago2 mutants with respect to forcible ascospore discharge.

Mutant phenotypes and synergisms were confirmed using several complementation assays (S2 Fig). First, reintroduction of the intact FgDICER1 and FgAGO2 genes into each corresponding single deletion mutant restored defective sexual development (Fig 1C and 1D). Next, the roles of FgDICER2 and FgAGO2 were further verified by introducing each gene into the double-deletion mutants using the outcrosses Δmat2 × HK340 (ΔFgdicer1 ΔFgdicer2) and Δmat2 × HK341 (ΔFgago1 ΔFgago2). The resulting strains (ΔFgdicer1 FgDICER2 and ΔFgago1 FgAGO2 in Fig 1C and 1D) showed similar phenotypes to those of the Fgdicer1 and Fgago1 mutants.

To determine the mechanism underlying defective ascospore discharge, we dissected mature perithecia to observe rosette asci (Fig 1E). The F. graminearum wild-type strain produced eight normal spindle-shaped ascospores per ascus. However, some asci of the mutants that were defective in ascospore discharge (ΔFgdicer1, ΔFgago2, ΔFgdicer1 ΔFgdicer2, and ΔFgago1 ΔFgago2) contained abnormally shaped ascospores and fewer than eight per ascus. The morphologies of abnormal-shaped ascospores vary, including larger ones, smaller ones, and broken ones. Moreover, small, ghost-like ascospores with incomplete spore delimitation were observed in these mutants (Fig 1E). Thus, we concluded that defective forcible ascospore discharge of Dicer or Argonaute mutants was due to abnormal ascospore production.

Transcriptome analysis of RNAi component mutants

To investigate the molecular mechanisms underlying defective ascosporogenesis of the RNAi component mutants, we analyzed the transcriptomes of the F. graminearum strains using RNA-seq. Based on a threshold of reads per kilobase of exon per hundred million mapped reads (RPKHM) values (≥ 10) under all tested conditions, 11,908 of 13,820 genes were selected for further analyses (S2 Table). Differentially expressed genes (DEGs) were identified as genes displaying a greater than 3-fold change in transcript levels compared to those of the wild type.

Deletion of both FgDICER1 and FgDICER2 induced the differential expression of 380 genes; 241 genes were upregulated, and 139 genes were downregulated (Fig 2A and 2B). While most of the upregulated genes in the Fgdicer2 mutant overlapped with those of the Fgdicer1 Fgdicer2 mutant (15/18), 70% of the genes (58/84) were specifically upregulated in the Fgdicer1 mutant (Fig 2A). Similarly, 80% (297/378) and 61% of the genes (73/119) were increased or decreased, respectively, in their expression only in the Fgago2 mutant but not in the Fgago1 Fgago2 mutant (Fig 2A and 2B). In contrast, most of the downregulated genes in each Dicer single mutant were also reduced in transcript levels in the Fgdicer1 Fgdicer2 mutant (Fig 2B).

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Fig 2. Transcriptome analysis of RNAi component mutants.

Venn diagrams illustrating the overlap between upregulated (A) and downregulated (B) genes in the RNAi component mutants compared to those of the wild type. DEGs were identified as genes showing a greater than 3-fold change in transcript levels compared to those of the wild type. (C) Correlation analyses of transcriptomes of Fgdicer1 Fgdicer2 and Fgago1 Fgago2. (D) Venn diagrams illustrating the overlap between DEGs of the Fgdicer1 Fgdicer2 and Fgago1 Fgago2 mutants. (E) Correlation analyses of transcriptomes of Fgdicer1 Fgdicer2 and Fgdicer1, Fgdicer1 Fgdicer2 and Fgdicer2, Fgago1 Fgago2 and Fgago1, and Fgago1 Fgago2 and Fgago2.

https://doi.org/10.1371/journal.pgen.1006595.g002

Transcriptomes between the double-deletion mutants, Fgdicer1 Fgdicer2 and Fgago1 Fgago2, were highly positively correlated (R² = 0.91; Fig 2C), and most DEGs overlapped in these mutants (Fig 2D), suggesting that these two mutants were impaired in the same regulatory pathway. However, each transcriptome of Fgdicer1 and Fgdicer2 showed a mild positive correlation with that of Fgdicer1 Fgdicer2, supporting the functional synergism of FgDicer1- and FgDicer2-mediated transcriptional regulation during ascospore formation in F. graminearum (Fig 2E). While the transcriptome of the Fgago1 mutant showed a relatively lower positive correlation with that of the Fgago1 Fgago2 mutant, transcriptomes between the Fgago2 and Fgago1 Fgago2 mutants had a much higher correlation (slope = 0.72 and R² = 0.36). Taken together, these results showed that the two Dicers and two Argonautes have redundant roles in the same biological pathway affecting ascospore formation in F. graminearum.

To dissect the characteristics of DEGs via disruption of the RNAi pathway, we examined the expression profiles of the upregulated (200) and downregulated (112) genes in both the Fgdicer1 Fgdicer2 and Fgago1 Fgago2 mutants compared to those of the wild type. Raw RNA-seq data from F. graminearum sexual developmental stages were obtained from a previous study [8], and the time-course expression patterns during sexual development were clustered into 10 groups using the R package Mfuzz [39] with the default setting, which performs fuzzy c-means clustering (S3 Fig and S3 Table). Mating-type genes (MATs) are important sex-specific upstream regulators that orchestrate sexual reproduction processes in F. graminearum, and the RNAi pathway was proposed to be a downstream regulatory mechanism of MATs [9]. MAT1-1-2 and MAT1-1-3 were included in group 2, and MAT1-1-1 and MAT1-2-1 were members of group 9 (Fig 3A and S3 Table). More than half of the upregulated genes were included in groups 2 or 9, in which the transcript levels were decreased at 4 days after sexual induction (Fig 3A and S4 Table). Group 5 possessed approximately 40% of the downregulated genes, and the transcript levels of group 5 genes were generally increased 4 days after sexual induction (Fig 3A). In short, the RNAi pathway affects the transcript abundance of genes closely related to the MAT-mediated regulatory mechanism during the late stages of sexual development in F. graminearum.

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Fig 3. Characterization of DEGs in RNAi-deficient mutants.

(A) Expression profiles of clustered groups including the mating-type genes. Fuzzy clustering categorized total genes into 10 groups depending on their expression profiles during sexual development (0–5 day after sexual induction). The genes included in groups 2 and 9 showed similar expression patterns as those of the mating-type genes (MAT1-1-1, MAT1-1-2, MAT1-1-3, and MAT1-2-1) during sexual reproduction. Transcriptome data during sexual development were obtained from a previous study [8] and re-analyzed for this study. (B) Gene Ontology (GO) enrichment network of the upregulated genes in the RNAi-deficient mutants. (C) GO enrichment network of the downregulated genes in the RNAi-deficient mutants. GO terms were statistically analyzed using GOstats [40] and visualized using REVIGO [41].

https://doi.org/10.1371/journal.pgen.1006595.g003

Our transcriptome analysis revealed that the RNAi pathway affects several important sexual reproduction-related molecular processes in F. graminearum (S2 Table). Pheromone precursor gene PPG1 (Gene ID: FGSG_05061), two putative transcription factors (Gene ID: FGSG_01366 and FGSG_16753), and transaldolase (Gene ID: FGSG_13162), which are known to be important for sexual development, were significantly downregulated in RNAi-deficient mutants [9,10,42]. Moreover, three of these genes (FGSG_01366, FGSG_13162, and FGSG_16753) are under the control of MAT genes in F. graminearum [9]. In addition, 11 fungal-specific transcription factors with a Zn(II)₂Cys₆ fungal-type DNA-binding domain (FGSG_01760, FGSG_03892, FGSG_03912, FGSG_04782, FGSG_04786, FGSG_09111, FGSG_11186, FGSG_11358, FGSG_11672, FGSG_12597, and FGSG_16075) were downregulated in RNAi component mutants; null mutants of these factors did not show any mutant phenotype [10].

Gene Ontology (GO) enrichment analysis was additionally applied to classify the functions of the predicted DEGs, and the GO terms were statistically analyzed using GOstats [40] and subsequently visualized using REVIGO [41]. REVIGO provides a network structure of non-redundant GO terms (Fig 3B and 3C). Although we did not find any functionally characterized genes from the upregulated DEGs, they were assigned to 62 categories; 27 were included in biological processes, 26 in molecular functions, and 9 in cellular components. Accordingly, the most significant GO terms were related to the transport of organic compounds such as “amino acid transport” and “carbohydrate transport” of biological processes and "transmembrane transporter activity" of molecular functions (Fig 3B). Downregulated genes were assigned to 76 categories (36 in biological processes, 36 in molecular functions, and 4 in cellular components). Most GO terms corresponding to negatively regulated genes were involved in carbohydrate catabolism, such as “carbohydrate catabolism” and “polysaccharide catabolism” (Fig 3C).

Based on our GO enrichment analysis, we demonstrated that one of the important molecular processes regulated by the RNAi pathway is carbon metabolism. Production of triacylglycerol is important for perithecia development, and therefore, dynamic changes in carbon metabolism should occur during sexual reproduction processes in F. graminearum [43]. Accordingly, acetyl coenzyme A production and translocation between cellular organelles are closely involved in various steps of sexual development in F. graminearum [44–47]. In our transcriptome data, transaldolase (Gene ID: FGSG_13162) is involved in the pentose-phosphate pathway, and ascospore formation [9] was markedly downregulated in RNAi-deficient mutants (S2 Table).

Characterization of sRNAs

To determine the relationship between sRNA production and transcriptome alteration, we isolated total low-molecular-weight RNAs from the wild-type and RNAi component mutant strains 5 days after sexual induction and used them for sRNA sequencing (S5 Table). After the adaptor sequences were trimmed, raw reads were normalized using DESeq to adjust for differences in library sizes [48]. Total reads with 18–32 nt perfect matches were used for alignment to the genome of F. graminearum [4,49].

The size distributions and 5′ end frequencies of sRNAs were analyzed. Identified sRNAs were 18–32 nt long, with a clear peak at approximately 24 nt in the F. graminearum wild-type strain (Fig 4A). The sRNAs with a 5′ end with U (5′-U) accounted for 70% of the total sRNAs in the wild-type strain and were mostly 21–26 nt long (Fig 4A and 4B). Deletion of either FgDICER1, FgDICER2, or FgAGO2 attenuated the biases of sRNAs toward specific sizes (21–26 nt) and 5′-U; these changes were milder in Fgdicer1 than those in Fgdicer2 and Fgago2. Deletion of FgAGO1 did not result in distinct changes in sRNA characteristics, but results for the Fgago2 mutant were similar to those of Fgdicer2 (Fig 4B). Fgdicer1 Fgdicer2 and Fgago1 Fgago2 mutants typically abolished these biases. Taken together, these findings showed that F. graminearum has distinct FgDicer1-, FgDicer2-, or FgAgo2-dependent sRNA production/accumulation mechanisms and that these sRNAs have strong tendencies toward being 24 nt long and 5′-U. Moreover, both members of Dicers and Argonautes have functional redundancies.

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Fig 4. Characterization of sRNAs.

(A) Nucleotide preference of 5′ end and size distribution of sRNAs produced by F. graminearum strains. (B) Analysis of 5′ end nucleotide preference of sRNAs produced by F. graminearum strains. (C) Relative abundance of sRNAs mapped to various genomic features produced by F. graminearum strains. (D) Absolute abundance of sRNAs mapped to various genomic features produced by F. graminearum strains. -, sRNAs with antisense direction; +, sRNAs with sense direction; 5′-U, sRNAs with 5′ uracil (22–25 nt).

https://doi.org/10.1371/journal.pgen.1006595.g004

To investigate the origin of sRNAs, we mapped sRNA sequences to the F. graminearum genome [4] with a recent annotation [49] to identify their various genomic features, such as coding sequences of rRNA, tRNA, and predicted proteins as well as intergenic regions (S6 Table). In the wild-type strain, sRNAs were in the rRNA region composed of approximately 40% of the total sRNAs (Fig 4C). Approximately 30% and 27% of the sRNAs mapped to protein-coding genes and intergenic regions, respectively. sRNA-producing loci frequently covered both protein-coding sequences and adjacent regions. Because there is little information about the untranslated region (UTR) in a recent annotation of F. graminearum [49], 500 bp upstream and downstream regions were arbitrarily denoted as 5′-UTR and 3′-UTR, respectively. Thereafter, 27% of the intergenic sequences were again separated into 16% of the UTRs and 11% of the intergenic sequences; predicted sRNAs corresponding to putative transcript sequences (protein-coding regions and UTRs) accounted for 46% (Fig 4C). Henceforth, we will call these sRNAs exonic siRNAs (ex-siRNAs), as previously reported [50].

When Dicer or Argonaute genes were deleted, the ratios of most genomic features aligned with sRNAs, except that the rRNA, protein-coding gene (sense strand), and UTR (sense strand), were decreased with analogous tendencies shown for size distributions and 5′-U in the corresponding deletion mutants (Fig 4C). In particular, sRNAs mapped to antisense sequences of putative transcripts were markedly reduced in the Fgdicer1 Fgdicer2 and Fgago1 Fgago2 mutants.

Various genomic features of sRNA-producing sequences were further assessed in detail with total normalized reads. The sRNAs produced from protein-coding genes converged on exons rather than introns (Fig 4D). The total amounts of sRNAs were decreased in the Fgdicer1, Fgdicer2, Fgdicer1 Fgdicer2, Fgago2, and Fgago1 Fgago2 mutants, principally because of the reduced number of introns, exons, and UTRs with an antisense direction. Dicer- and Argonaute-dependent sRNAs with 5′-U (22–25 nt) were particularly enriched in antisense sequences of putative transcripts (Fig 4D and S6 Table). Moreover, the results confirmed that Dicers and Argonautes have redundant roles. Interestingly, total counts of sRNAs with antisense sequences of tRNA and rRNA were also markedly reduced in the Fgdicer1 Fgdicer2 and Fgago1 Fgago2 mutants, primarily because of a decreased number of sRNAs with 5′-U. The results suggest that Dicer- and Argonaute-dependent biogenesis/accumulation of sRNAs occurs at a genome-wide level.

Characterization of sRNA-producing genes and regulatory functions of sRNAs

As most sRNAs were produced from gene regions, except for rRNA-mediated sRNAs, we focused on the characteristics of sRNA-producing genes (S7 Table). The F. graminearum wild-type strain produces sRNAs from 5180 genes, and 80% (4155/5180) of the genes produced only sense-specific sRNAs, suggesting that sense sRNAs were byproducts of mRNA degradation (Fig 5A and S8 Table). Accordingly, the number of genes producing only sense sRNAs was similar among the wild-type and RNAi component mutant strains.

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Fig 5. Characterization of sRNA-producing genes.

(A) Number of genes that produce sRNAs depending on F. graminearum strains. (B) Number of genes that produce sRNAs with 5′-U depending on F. graminearum strains. (C) Correlation analyses of transcriptomes of Fgdicer1 Fgdicer2 and Fgago1 Fgago2 compared to that of the wild type depending on sRNA counts. The log₂ ratio of transcript abundance in Fgdicer1 Fgdicer2 versus wild-type (x axis) and Fgago1 Fgago2 versus wild-type (y axis) is plotted. Colors indicate the sRNA density (reads per kilobase). (D) Correlation analyses of sRNA counts and transcript abundance. Gene numbers with corresponding log₂ ratio of transcript abundance in Fgdicer1 Fgdicer2 or Fgago1 Fgago2 versus the wild-type strain Z-3639 were counted. Most genes producing antisense sRNAs more than 1000 counts per kilobase (red graphs) were positively regulated in Fgdicer1 Fgdicer2 and Fgago1 Fgago2 compared to those in the wild type. Colors indicate the sRNA density denoted in Fig 5C.

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We investigated 5′-U sRNA-producing genes from F. graminearum strains (Fig 5B and S8 Table). The genes were selected when the amount of 5′-U sRNA was more than 70% of the total sRNAs (S7 and S8 Tables). Approximately 1000 genes preferentially produced 5′-U sRNAs in the F. graminearum wild-type strain. Among them, more than half of the genes generated sRNAs with both orientations, and 10% of the genes produced only sense-specific sRNAs. A markedly reduced number of genes produced 5′-U sRNAs in Fgdicer2 and Fgago2 compared to those of the wild type, whereas the Fgdicer1 mutant showed a slight reduction in the number of 5′-U sRNA-producing genes. Double deletion of FgDICER1 and FgDICER2 largely abolished 5′-U sRNA production. Genes producing antisense-specific or sense-specific sRNAs were counted in the Fgago1 Fgago2 mutant. Taken together, these findings show that most sRNAs originating from the gene region with a 5′-U or antisense direction were distinctly produced in a Dicer-dependent manner.

We investigated whether sRNAs affected the transcript levels of corresponding genes in F. graminearum. First, all genes were categorized depending on the levels of sense or antisense sRNA counts, and they were applied in correlation analyses of transcript abundance between Fgdicer1 Fgdicer2 and Fgago1 Fgago2 versus the wild-type strain (Fig 5C). As the genes produced more sense or antisense sRNAs, a greater number of genes tended to accumulate more transcripts in Fgdicer1 Fgdicer2 and Fgago1 Fgago2 than those in the wild type. In particular, most genes producing either sense or antisense sRNAs at more than 1000 counts per kilobase (red dots in Fig 5C) were upregulated in the RNAi-deficient mutants. To analyze the negative correlation between sRNA production and transcript amounts of genes in detail, we assessed the gene numbers depending on transcript abundance in Fgdicer1 Fgdicer2 or Fgago1 Fgago2 versus the wild-type strain (Fig 5D). Whereas both sense and antisense sRNAs produced below 100 counts per kilobase did not show substantial changes in transcript levels of the corresponding genes, most genes producing antisense sRNAs at more than 1000 counts per kilobase (red graphs) were positively regulated in Fgdicer1 Fgdicer2 and Fgago1 Fgago2 compared to those in the wild type (Fig 5D). Both sense and antisense 5′-U sRNA (22–25 nt)-producing genes showed similar results to those obtained from antisense sRNAs (S4 Fig). Taken together, these findings show that a sRNA-mediated gene regulatory mechanism is not a critical factor that determines final transcript levels of most genes, but highly expressed sRNAs with antisense orientations participate in the negative transcriptional gene regulation of corresponding genes at a genome-wide level.

Although we found that F. graminearum possesses a global negative transcriptional regulatory mechanism involving antisense sRNAs during sexual development, only 57 genes produced antisense sRNAs among 200 upregulated DEGs (S2 and S7 Tables). Instead, a defective phenotype in ascospore production of RNAi-deficient mutants appears to be derived by the downregulation of sexual reproduction-related genes, such as PPG1 (Gene ID: FGSG_05061), transcription factors (Gene ID: FGSG_01366 and FGSG_16753), and transaldolase (Gene ID: FGSG_13162), as noted above [9,10,42]. Thus, genes with substantial changes in transcript levels were not directly affected by RNAi-mediated gene regulation. Thirty-two transcription factor genes are possibly modulated by antisense sRNAs, and three of them (FGSG_01022, FGSG_09654, and MAT1-2-1) are closely related to perithecia development in F. graminearum [10]. In particular, RNAi participates in the regulation of one of the MATs, MAT1-2-1, during sexual development. In the case of kinases, another important mediator for signal transduction pathways, four genes (FGSG_00469, FGSG_16383, FGSG_05418, and FGSG_16493) produced antisense sRNAs, and one of them (FGSG_05418) was shown to be important for ascospore formation in F. graminearum [11]. Although most of the mentioned genes involved in sexual development are known to be related to the perithecium development or the early stages of sexual development, our additional transcript analysis during sexual development demonstrated that they also have important functions during the late stages of sexual development (S5 Fig). In particular, most of tested genes were dynamically changed in expression approximately 5 days after sexual induction, and these patterns of several genes were altered in RNAi-deficient mutants compared to those of the wild type. Thus, the RNAi mechanism fine-tunes the transcriptome to modulate various molecular processes, including signal transduction networks, during ascospore production in F. graminearum.

Validation of sRNA-seq and mRNA-seq

We visualized patterns of sequence alignments at the ex-siRNA-producing genes using Integrative Genomics Viewer (IGV) [51]. The IGV image of the gene (FGSG_11711) showed that ex-siRNAs are produced over the entire ranges of the gene (S6 Fig), demonstrating that total amount of siRNAs of the gene does not always reflect abundances of specific ex-siRNAs. Therefore, we identified ex-siRNAs with over 500 raw counts (S9 Table). Since repeated trials of the standard Northern blot analysis of six highly expressed ex-siRNAs (S7 Fig) were unsuccessful in detecting signals, we quantified the absolute amount of the ex-siRNA with the highest expression (siRNA of FGSG_09213) using stem-loop RT-PCR (S8 Fig). Whereas Northern blot analysis of our system could detect 1–10 fmoles synthetic siRNA of FGSG_09213, approximately 0.05 fmoles of siRNAs were detected in 100 ng of small RNA-enriched RNA samples from the F. graminearum wild type. Thereafter, we analyzed siRNAs using stem-loop RT-PCR (Fig 6). Abundances of siRNAs in the wild-type and the other mutant strains determined by RT-PCR were mostly consistent with our sRNA-seq results (S7 Fig and Fig 7A). We also verified that transcript levels of FGSG_10502 and FGSG_03222 were negatively correlated with corresponding ex-siRNA production (Fig 7B).

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Fig 6. Detection of ex-siRNAs.

Quantification of ex-siRNA candidates was performed using stem-loop RT-PCR assays. Each 100 ng of small RNA-enriched RNA samples was used for reverse transcription reactions, and the images were obtained from 25–30 cycles of PCR using 10% acrylamide gel.

https://doi.org/10.1371/journal.pgen.1006595.g006

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Fig 7. Representative IGV images of genes possibly regulated by ex-siRNA.

(A) Aligned sRNA-seq and mRNA-seq results of F. graminearum strains were visualized using IGV. Red stars indicate selected ex-siRNA for RT-PCR. (B) Relative transcript abundances of genes in the F. graminearum strains during sexual development. Transcript levels were analyzed via qRT-PCR 5 days after sexual induction. The transcript level of the wild type was arbitrarily set to 1.

https://doi.org/10.1371/journal.pgen.1006595.g007

Degradome analysis

We analyzed the degradome of the F. graminearum wild-type strain to elucidate the mechanism for genome-wide sRNA-mediated gene silencing. Total RNAs were isolated from the wild-type strain 5 days after sexual induction, and RNA fragments with a 5′ monophosphate and polyA tail, which were cleaved products of transcripts, were subjected to the degradome library construction and deep sequencing. In our degradome sequencing method, we expected 16 nt reads after trimming the adapter sequences, and enriched reads of 16 nt and 17 nt were further used for alignment (S10 Table). Approximately 95% of the trimmed sequences from two independent degradome libraries perfectly matched one or more positions in the F. graminearum genome (S11 Table). To monitor transcript degradation, we used degradome tags with a sense direction for further analyses. The libraries of degradome tags were markedly biased toward the 3′ ends of protein coding sequences (CDS) and 3′-UTR regions (Fig 8A). Specifically, most degradome tags were enriched in the exon and 3′-UTR regions (Fig 8B and S11 Table).

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Fig 8. Degradome analyses.

(A) Histogram displaying the 5′ positions of degradome tags from two wild-type libraries relative to normalized transcript positions. The protein-coding sequence of the transcript is exhibited from 0 to 100. (B) Frequency of degradome tags mapped to various genomic features produced by the wild-type strain. (C) Correlation analyses between wild-type degradome counts and transcript abundances of wild-type or Fgdicer1 Fgdicer2 strains. (D) Correlation analyses of transcriptomes of Fgdicer1 Fgdicer2 and Fgago1 Fgago2 compared to that of the wild type. Colors indicate the degradome tag density (reads per kilobase). (E) Average degradome counts depending on percentile ranks of antisense sRNA counts. Percentile ranks of genes were assigned based on their antisense sRNA counts. (F) Average transcript abundance of Fgdicer1 Fgdicer2 compared to the wild type depending on the percentile ranks of the degradome tags/transcript counts ratio. (G) Number of sRNA-producing genes corresponding to the percentile ranks of the degradome tags/transcript counts ratio. Numbers of sRNA-producing genes were divided into four groups depending on the transcript abundance of Fgdicer1 Fgdicer2 compared to the wild type.

https://doi.org/10.1371/journal.pgen.1006595.g008

The average of the total abundances of degradome tags for the CDS and 3′-UTR regions was calculated as reads per kilobase of sequence per two billion mapped sequence reads with a cutoff value of 10 (S12 Table). Comparison of the degradome abundance of the wild-type strain to the transcript values of the wild-type and RNAi component mutant strains similarly showed a distinct positive correlation (Fig 8C). Accordingly, genes with higher degradome counts tended to accumulate more transcripts in Fgdicer1 Fgdicer2 and Fgago1 Fgago2 than those in the wild type (Fig 8D). Taken together, these findings revealed that degradome tag abundance is primarily determined by the level of the corresponding gene transcript in F. graminearum.

The only known mechanism for siRNA-mediated gene silencing in filamentous fungi is siRNA-guided mRNA degradation [34]. As siRNA-guided endonucleolytic cleavage events should lead to the rapid decay of transcripts [52], we investigated the correlation between the abundance of degradome tags and antisense sRNA-mediated gene regulation. As genes produced more sRNAs with an antisense direction, the absolute number of degraded transcripts increased in the F. graminearum wild-type strain (Fig 8E). As the degradome generally reflects transcript levels, the abundances of degradome tags were normalized with transcript counts, and total genes were listed in the order of their given degradome tags:transcript counts ratios. When a higher portion of transcripts was degraded in the wild-type strain (higher percentile rank classes), corresponding genes tended to be upregulated in Fgdicer1 Fgdicer2 mutants (Fig 8F), suggesting that Dicer-dependent gene regulation globally triggers transcript degradation in this fungus.

When sRNA-producing genes were evenly distributed among the percentile rank classes, markedly reduced and increased portions of genes produced sRNAs in the down- (Fgdicer1 Fgdicer2/Z-3639 < 1) and upregulated (Fgdicer1 Fgdicer2/Z-3639 > 1) gene groups, respectively (Fig 8G). More than 70% of the genes were concentrated in the top 20% of the percentile rank class in the genes that were upregulated more than 2-fold in Fgdicer1 Fgdicer2 compared to that of the wild type (Fgdicer1 Fgdicer2/Z-3639 > 2; Fig 8G). Taken together, these results show that RNAi-mediated negative gene regulation occurs post-transcriptionally by degrading corresponding gene transcripts during sexual reproduction in F. graminearum.

Fungal strains and media

The wild-type strain Z-3639 and transgenic strains derived from this strain were used in this study (S1 Table). Fungal strains were stored as conidia and mycelia in 30% glycerol solution at -80°C. All of the media used in this study were prepared as described in the Fusarium laboratory manual [1].

Nucleic acid manipulation and quantitative real-time (qRT)-PCR

Genomic DNA was extracted from lyophilized mycelia according to the Fusarium laboratory manual [1]. Restriction endonuclease digestion, agarose gel electrophoresis, Southern and Northern blotting, and hybridization with ³²P-labeled probes were performed following standard protocols [69]. PCR and qRT-PCR primers used in this study were synthesized by an oligonucleotide synthesis facility (Bionics, Seoul, Korea) (S13 Table). Stem-loop RT-PCR analyses of siRNAs were performed as previously described [70,71].

For detection of small RNAs, RNAs that are highly enriched for small RNA species (less than 200 nt) were isolated using a mirVana^TM miRNA isolation kit (Invitrogen), separated in a 15% urea-polyacrylamide gel, and transferred to Immobilon-Ny + membranes (Millipore, Billerica, MA, USA). The membranes were probed with ³²P-labeled oligonucleotides in PerfectHyb^TM Plus Hybridization Buffer (Sigma-Aldrich, St. Louis, MO, USA) at 37°C. Hybridization and washing steps were performed as previously described [72].

Total RNA was isolated from mycelia that were ground in liquid nitrogen using an Easy-Spin total RNA extraction kit (iNtRON Biotech, Seongnam, Korea), and each first-strand cDNA was synthesized using SuperScript III reverse transcriptase (Invitrogen, Carlsbad, CA, USA). qRT-PCR was performed with SYBR Green Supermix (Bio-Rad, Hercules, CA, USA) and a 7500 real-time PCR system (Applied Biosystems, Foster City, CA, USA) with corresponding primer pairs (S13 Table). The ubiquitin C-terminal hydrolase gene UBH (Gene ID: FGSG_01231) was used as a reference gene. We compared the cycle threshold (2^-ΔΔCT) to measure the transcript levels of target genes in different conditions. PCR was performed three times with three replicates per run.

Targeted gene deletion and genetic complementation

The double-joint (DJ) PCR strategy was applied to construct fusion PCR products for targeted gene deletion and complementation [73]. For FgDICER1 deletion, the 5′ and 3′ flanking regions of FgDICER1 were amplified from the genomic DNA of the F. graminearum wild-type strain (S1 Fig). A geneticin resistance gene cassette (GEN) was amplified from pII99. Three amplicons (5′ flanking region, GEN, and 3′ flanking region) were mixed at a 1:3:1 molar ratio and fused by a second round of DJ PCR. Finally, the fusion constructs were amplified with the nested primers using the second-round PCR product as a template.

For complementation, the 5′ flanking region that included the FgDICER1 open-reading frame with its own promoter and 3′ flanking region were amplified from genomic DNA of the wild-type strain. The HYG construct was amplified from pBCATPH. Three amplicons were then fused in a second round of DJ PCR. Finally, the fusion constructs for transformation were amplified with the nested primers using the second-round PCR product as a template. Fungal transformation was performed as previously described [44]. The same strategy was used for deletion and complementation of other RNAi component genes (S2 Fig).

Sexual crosses

For self-crosses, mycelia were grown on carrot agar for 5 days and then removed with the back of a surgical blade (surgical blade #11; Feather Safety Razor, Osaka, Japan) while applying 2.5% sterilized Tween 60 solution [1]. For outcrosses, the heterothallic Δmat2 strain was fertilized with 1 ml of a conidial suspension (10⁵ conidia/ml) from fertilizing parents. All of the sexually induced cultures were incubated under near-UV light (wavelength: 365 nm; HKiv Import & Export Co., Ltd., Xiamen, China) at 25°C.

Deep sequencing of transcriptome, sRNAs, and degradome

Transcriptome analysis in F. graminearum was performed as previously described [74]. Total RNA was isolated from each fungal culture at 5 days after sexual induction on carrot agar using an Easy-Spin total RNA extraction kit (iNtRON Biotech). More than five biological replicates of each strain were pooled for RNA-seq library construction. RNA-seq libraries were constructed using the Illumina TruSeq^TM RNA sample prep kit with no modifications to the standard low-throughput protocol. Samples were run on an Illumina HiSeq2000 instrument using the reagents provided in the Illumina TruSeq paired-end (PE) cluster kit V3-cBot-HS and the TruSeq SBS kit v3-HS (200 cycles). Similarly, a small RNA library was prepared using a TruSeq small RNA library prep kit following the manufacturer’s instruction. Then, each library was subjected to single-end 100 bp sequencing using a HiSeq2000 instrument.

Degradome-seq was performed as previously described with some modifications [75,76]. Poly (A)⁺ RNA was isolated using the NucleoTraP^® mRNA purification kits (Machery-Nagel, Düren, Germany) according to the manufacturer’s instructions. A 5′ RNA adapter (5′-GUUCAGAGUUCUACAGUCCGACGAUC-3′) was ligated to the cleavage products, which contain a 5′ monophosphate. The ligated products were reverse-transcribed into cDNA using an oligo (dT) primer (5′-CGAGCACAGAATTAATACGACTTTTTTTTTTTTTTTTTT-3′) by SuperScript III reverse transcriptase (Invitrogen) and amplified by PCR with a pair of cDNA primers (5´-GTTCAGAGTTCTACAGTCCGA-3′ and 5´-CGAGCACAGAATTAATACGACT-3′). The resulting product was digested with a MmeI (NEB, MA, USA) to obtain short fragments from the 5´ end of double-stranded cDNA. The digested products were ligated with an annealed duplex DNA adapter (top, 5´-p- TGGAATTCTCGGGTGCCAAGG- 3′ and bottom, 5´-CCTTGGCACCCGAGAATTCCANN-3′) using T4 DNA ligase (NEB). The ligated DNA products (~62 bp) were isolated using a 12% polyacrylamide gel (PAGE), and the purified products were amplified by PCR with a set of indexed TruSeq. The final PCR products were purified by running a 6% PAGE gel based on size (~128 bp). Most enzymes and primer sequences used in this study were obtained from a TruSeq small RNA library prep kit. Libraries were used for throughput sequencing on a HiSeq2000 platform.

Alignments were performed with BWA [77] using the F. graminearum genome [49], and the htseq-count script of the HTSeq package was used to compute the counts per gene [78]. Genome-wide transcript levels were quantified in reads per kilobase of exon per hundred million mapped sequence reads (RPKHM) [79]. Genes with maximum RPKHM values below 10 were deleted from the analysis. DEGs were identified based on fold-change values.

High-quality small RNA reads were obtained from raw reads by filtering out poor quality reads and removing adaptor sequences using the FASTX toolkit [80]. Adaptor-trimmed unique sequences were aligned to the F. graminearum genome using bowtie [49,81], and structural RNAs, such as tRNA, rRNA, snRNA, and snoRNA, were identified. The perfectly matched reads between 18–32 nt (for sRNAs) in length were selected.

Data access

The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus [82] and are accessible through the accession numbers GSE87724 for mRNA-seq and GSE87835 for sRNA-seq. Raw data of degradome-seq have been deposited in NCBI's Sequence Read Archive (BioProject PRJNA348145).