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. 2022 Oct 12:13:1008665.
doi: 10.3389/fpls.2022.1008665. eCollection 2022.

Alternative splicing reprogramming in fungal pathogen Sclerotinia sclerotiorum at different infection stages on Brassica napus

Affiliations

Alternative splicing reprogramming in fungal pathogen Sclerotinia sclerotiorum at different infection stages on Brassica napus

Xiaohui Cheng et al. Front Plant Sci. .

Abstract

Alternative splicing (AS) is an important post-transcriptional mechanism promoting the diversity of transcripts and proteins to regulate various life processes in eukaryotes. Sclerotinia stem rot is a major disease of Brassica napus caused by Sclerotinia sclerotiorum, which causes severe yield loss in B. napus production worldwide. Although many transcriptome studies have been carried out on the growth, development, and infection of S. sclerotiorum, the genome-wide AS events of S. sclerotiorum remain poorly understood, particularly at the infection stage. In this study, transcriptome sequencing was performed to systematically explore the genome-scale AS events of S. sclerotiorum at five important infection stages on a susceptible oilseed rape cultivar. A total of 130 genes were predicted to be involved in AS from the S. sclerotiorum genome, among which 98 genes were differentially expressed and may be responsible for AS reprogramming for its successful infection. In addition, 641 differential alternative splicing genes (DASGs) were identified during S. sclerotiorum infection, accounting for 5.76% of all annotated S. sclerotiorum genes, and 71 DASGs were commonly found at all the five infection stages. The most dominant AS type of S. sclerotiorum was found to be retained introns or alternative 3' splice sites. Furthermore, the resultant AS isoforms of 21 DASGs became pseudogenes, and 60 DASGs encoded different putative proteins with different domains. More importantly, 16 DASGs of S. sclerotiorum were found to have signal peptides and possibly encode putative effectors to facilitate the infection of S. sclerotiorum. Finally, about 69.27% of DASGs were found to be non-differentially expressed genes, indicating that AS serves as another important way to regulate the infection of S. sclerotiorum on plants besides the gene expression level. Taken together, this study provides a genome-wide landscape for the AS of S. sclerotiorum during infection as well as an important resource for further elucidating the pathogenic mechanisms of S. sclerotiorum.

Keywords: Sclerotinia sclerotiorum; alternative splicing; reprogramming; secreted proteins; transcriptome sequencing.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
RNA-seq data validation by quantitative real-time PCR (qRT-PCR). The qRT-PCR results are presented as relative expression using actin as a reference gene. The expression levels are presented as the mean of three biological replicates, and the error bars show the standard deviation.
Figure 2
Figure 2
Expression patterns of splicing‐related genes during S. sclerotiorum infection on Brassica napus. The gene ID of splicing factors is listed in the heat map. Blue to red indicate gene expression values from low to high. Z score normalization was applied for the transcription levels of genes at all stages. Cluster analysis was performed using the R package pheatmap.
Figure 3
Figure 3
Differential alternative splicing genes (DASGs) and differentially expressed genes (DEGs) in S. sclerotiorum at different infection stages. (A) Number of different types of differentially expressing events and corresponding genes identified in different infected samples. A3SS, alternative 3′ splice site; A5SS, alternative 5′ splice site; ES, exon skipping; RI, retained intron; MXE, mutually exclusive exon. (B) Venn diagram of the overlap of DEGs and DASGs.
Figure 4
Figure 4
Differential alternative splicing genes (DASGs) with modified functions in S. sclerotiorum. (A) Fifteen most frequently modified domains in DASGs. (B) The network was constructed using STRING (https://string-db.org/). There are 41 protein nodes and 73 protein–protein association edges in the network. Seven differently colored lines represent the types of evidence used in predicting associations. Light blue line, database evidence; purple line, experimental evidence; green line, neighborhood evidence; blue line, co-occurrence evidence; yellow line, text mining evidence; black line, co-expression evidence; and dark blue lines, protein homology evidence.
Figure 5
Figure 5
Modified functions of secreted protein-coding genes by alternative splicing (AS) in S. sclerotiorum. (A) The expression patterns of the secreted protein-coding genes undergo AS. (B) Schematic representation of Sscle_04g035680 produced by AS. The blue boxes and polylines indicate the exons and introns, respectively. The red boxes, green boxes, and yellow box indicates the signal peptides, WSC domains, and transmembrane domain, respectively.

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