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Transcriptome analysis reveals molecular mechanisms of sclerotial development in the rice sheath blight pathogen Rhizoctonia solani AG1-IA

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Abstract

Rhizoctonia solani AG1-IA is a soil-borne necrotrophic pathogen that causes devastating rice sheath blight disease in rice-growing regions worldwide. Sclerotia play an important role in the life cycle of R. solani AG1-IA. In this study, RNA sequencing was used to investigate the transcriptomic dynamics of sclerotial development (SD) of R. solani AG1-IA. Gene ontology and pathway enrichment analyses using the Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to investigate the functions and pathways of differentially expressed genes (DEGs). Six cDNA libraries were generated, and more than 300 million clean reads were obtained and assembled into 15,100 unigenes. In total, 12,575 differentially expressed genes were identified and 34.62% (4353) were significantly differentially expressed with a FDR ≤ 0.01 and |log2Ratio| ≥ 1, which were enriched into eight profiles using Short Time-series Expression Miner. Furthermore, KEGG and gene ontology analyses suggest the DEGs were significantly enriched in several biological processes and pathways, including binding and catalytic functions, biosynthesis of ribosomes, and other biological functions. Further annotation of the DEGs using the Clusters of Orthologous Groups (COG) database found most DEGs were involved in amino acid transport and metabolism, as well as energy production and conversion. Furthermore, DEGs relevant to SD of R. solani AG1-IA were involved in secondary metabolite biosynthesis, melanin biosynthesis, ubiquitin processes, autophagy, and reactive oxygen species metabolism. The gene expression profiles of 10 randomly selected DEGs were validated by quantitative real-time reverse transcription PCR and were consistent with the dynamics in transcript abundance identified by RNA sequencing. The data provide a high-resolution map of gene expression during SD, a key process contributing to the pathogenicity of this devastating pathogen. In addition, this study provides a useful resource for further studies on the genomics of R. solani AG1-IA and other Rhizoctonia species.

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Acknowledgments

This work was supported by a grant from a National Natural Science Foundation of China (Grant No. 31801677) awarded to Canwei Shu, and a Natural Science Foundation of Guangdong Province for Doctoral program (Grant No. 2016A030310454) awarded to Canwei Shu and the National Natural Science Foundation of China (Grant Nos. 31271994 and 31470247) awarded to Erxun Zhou.

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Authors and Affiliations

  1. Integrative Microbiology Research Centre, Guangdong Province Key Laboratory of Microbial Signals and Disease Control, College of Agriculture, South China Agricultural University, Guangzhou, 510642, Guangdong, China

    Canwei Shu, Mei Zhao, Wenbo Zheng, Chenjiaozi Wang, Mei Yang & Erxun Zhou

  2. CSIRO Agriculture and Food, Centre for Environment and Life Sciences, Floreat, WA, Australia

    Jonathan P. Anderson, Gagan Garg & Karam B. Singh

  3. The UWA Institute of Agriculture, University of Western Australia, Crawley, WA, Australia

    Jonathan P. Anderson & Karam B. Singh

  4. Centre for Crop and Disease Management, School of Molecular and Life Sciences, Curtin University, Bentley, WA, Australia

    Karam B. Singh

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  1. Canwei Shu
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Fig. S1

Length distribution of assembled unigenes. (PNG 47 kb)

High Resolution Image (TIF 122 kb)

Fig. S2

Length distribution of coding sequences (CDS) produced by searching unigenes against Nr database using BLAST2GO (E-value <10−5) and size distribution of the proteins predicted from the CDS sequences. (PNG 79 kb)

High Resolution Image (TIF 5570 kb)

Fig. S3

Short time-series expression miner (STEM) clustering of DEGs. Eight profiles ordered based on significance (p value) of the number of genes assigned versus expected. Profile 4 (0.0, 0.0, 1.0): 1218 genes assigned, 1069.8 genes expected, p = 1.2E−06 (significant). Profile 1 (0.0,-1.0,-1.0): 1210 genes assigned, 1069.8 genes expected, p = 4.1E−06 (significant). Profile 0 (0.0,-1.0,-2.0): 877 genes assigned, 761.0 genes expected, p = 9.5E−06 (significant). Profile 2 (0.0,-1.0, 0.0): 1828 genes assigned, 1710.7 genes expected, p = 0.00097 (significant). Profile 7 (0.0, 1.0, 2.0): 836 genes assigned, 761.0 genes expected, p = 0.0027 (significant). Profile 3 (0.0, 0.0,-1.0): 1217 genes assigned, 1308.5 genes expected, p = 1 (not significant). Profile 5 (0.0, 1.0, 0.0): 1048 genes assigned, 1428.7 genes expected, p = 1 (not significant). Profile 6 (0.0, 1.0, 1.0): 1184 genes assigned, 1308.5 genes expected, p = 1 (not significant). (PNG 93 kb)

High Resolution Image (TIF 33688 kb)

Fig. S4

Venn diagram illustrating number of DEGs co-existed in different Rhizoctonia solani AGs (i.e., R. solani AG1-IB, R. solani AG3 and R. solani AG8). (PNG 30 kb)

High Resolution Image (TIF 178 kb)

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Shu, C., Zhao, M., Anderson, J.P. et al. Transcriptome analysis reveals molecular mechanisms of sclerotial development in the rice sheath blight pathogen Rhizoctonia solani AG1-IA. Funct Integr Genomics 19, 743–758 (2019). https://doi.org/10.1007/s10142-019-00677-0

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