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Chinese Agricultural Science Bulletin ›› 2021, Vol. 37 ›› Issue (24): 102-109.doi: 10.11924/j.issn.1000-6850.casb2020-0622

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Response of Sugarcane Leaves to the Infection of Puccinia melanocephala: Transcriptomic Analysis

Gao Xiaoning(), Wu Zilin, Huang Yonghong, Liu Rui, Qi Yongwen()   

  1. Institute of Bioengineering, Guangdong Academy of Sciences, Guangdong Sugarcane Genetic Improvement Engineering Center, Guangzhou 510316
  • Received:2020-11-05 Revised:2021-03-17 Online:2021-08-25 Published:2021-08-27
  • Contact: Qi Yongwen E-mail:gxn336@126.com;yongwen2001@163.com

Abstract:

The aim is to analyze the gene expression patterns of sugarcane leaves in response to the infection of P. melanocephala, and to provide data for further research on the molecular mechanism of sugarcane resistance to brown rust. The healthy and infected sugarcane leaves by P. melanocephala were sequenced at transcriptomic level using high-throughput sequencing platform, Illumina Hiseq 2500. The functional annotation and analysis for the differentially expressed genes (DEGs) was carried out with bioinformatics methods. The relative expression levels of five DEGs were further verified by real-time fluorescence quantitative PCR (qRT-PCR). The transcriptome data showed that 4716 DEGs were obtained, including 2979 up-regulated and 1737 down-regulated DEGs. GO annotation results showed that DEGs mainly gathered in the physiological and biochemical processes of cell process, biological process, and catalytic activity, etc. KEGG enrichment analysis revealed that 1919 DEGs were annotated into 114 pathways. The relative genes in the metabolic pathways related to plants’ resistance to biotic stress were significantly up-regulated, and these metabolic pathways included phenylpropane biosynthesis, flavonoids biosynthesis, and glutathione metabolism and so on. In addition, the qRT-PCR results confirmed that the expression profiles of five up-regulated genes were consistent with that of transcriptome sequencing.

Key words: sugarcane, Puccinia melanocephala, compatible interaction, high-throughput sequencing, transcriptomics, differential expression genes

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