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Simultaneous transcriptome analysis of sorghum and Bipolaris sorghicola by using RNA-seq in combination with de novo transcriptome assembly

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NIAID Data Ecosystem2026-03-10 收录
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https://www.ncbi.nlm.nih.gov/sra/DRP000986
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The recent development of RNA sequencing (RNA-seq) technology has enabled us to analyze the transcriptomes of plants and their pathogens simultaneously. However, RNA-seq often relies on aligning reads to a reference genome and is thus unsuitable for analyzing most plant pathogens, as their genomes have not been fully sequenced. Here, we analyzed the transcriptomes of Sorghum bicolor (L.) Moench and its pathogen Bipolaris sorghicola simultaneously by using RNA-seq in combination with de novo transcriptome assembly. We sequenced the mixed transcriptome of the disease-resistant sorghum cultivar SIL-05 and B. sorghicola in infected leaves in the early stages of infection (12 and 24 h post-inoculation) by using Illumina mRNA-Seq technology. Sorghum gene expression was quantified by aligning reads to the sorghum reference genome. For B. sorghicola, reads that could not be aligned to the sorghum reference genome were subjected to de novo transcriptome assembly. We identified genes of B. sorghicola for growth of this fungus in sorghum, as well as genes in sorghum for the defense response. The genes of B. sorghicola included those encoding Woronin body major protein, LysM domain-containing intracellular hyphae protein, transcriptional factors CpcA and HacA, and plant cell-wall degrading enzymes. The sorghum genes included those encoding two receptors of the simple eLRR domain protein family, transcription factors that are putative orthologs of OsWRKY45 and OsWRKY28 in rice, and a class III peroxidase that is a homolog involved in disease resistance in the Poaceae. These defense-related genes were particularly strongly induced among paralogs annotated in the sorghum genome. Thus, in the absence of genome sequences for the pathogen, simultaneous transcriptome analysis of plant and pathogen by using de novo assembly was useful for identifying putative key genes in the plant–pathogen interaction.
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2017-09-17
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