A bioinformatics approach to distinguish plant parasite and host transcriptomes in interface tissue by classifying RNA-Seq reads

Daisuke Ikeue, Christian Schudoma, Wenna Zhang, Yoshiyuki Ogata, Tomoaki Sakamoto, Tetsuya Kurata, Takeshi Furuhashi, Friedrich Kragler, Koh Aoki

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    7 Citations (Scopus)

    Abstract

    Background: The genus Cuscuta is a group of parasitic plants that are distributed world-wide. The process of parasitization starts with a Cuscuta plant coiling around the host stem. The parasite's haustorial organs then establish a vascular connection allowing for access to the phloem content. The host and the parasite form new cellular connections, suggesting coordination of developmental and biochemical processes. Simultaneous monitoring of gene expression in the parasite's and host's tissues may shed light on the complex events occurring between the parasitic and host cells and may help to overcome experimental limitations (i.e. how to separate host tissue from Cuscuta tissue at the haustorial connection). A novel approach is to use bioinformatic analysis to classify sequencing reads as either belonging to the host or to the parasite and to characterize the expression patterns. Owing to the lack of a comprehensive genomic dataset from Cuscuta spp., such a classification has not been performed previously. Results: We first classified RNA-Seq reads from an interface region between the non-model parasitic plant Cuscuta japonica and the non-model host plant Impatiens balsamina. Without established reference sequences, we classified reads as originating from either of the plants by stepwise similarity search against de novo assembled transcript sets of C. japonica and I. balsamina, unigene sets of the same genus, and cDNA sequences of the same family. We then assembled de novo transcriptomes from the classified read sets. We assessed the quality of the classification by mapping reads to contigs of both plants, achieving a misclassification rate low enough (0.22-0.39%) to be used reliably for differential gene expression analysis. Finally, we applied our read classification method to RNA-Seq data from the interface between the non-model parasitic plant C. japonica and the model host plant Glycine max. Analysis of gene expression profiles at 5 parasitizing stages revealed differentially expressed genes from both C. japonica and G. max, and uncovered the coordination of cellular processes between the two plants. Conclusions: We demonstrated that reliable identification of differentially expressed transcripts in undissected interface region of the parasite-host association is feasible and informative with respect to differential-expression patterns.

    Original languageEnglish
    Article number34
    JournalPlant Methods
    Volume11
    Issue number1
    DOIs
    Publication statusPublished - 2015 Jul 1

    Keywords

    • Classification
    • Cuscuta japonica
    • Cuscuta reflexa
    • Parasite-host interaction
    • Parasitic plant
    • Transcriptome

    ASJC Scopus subject areas

    • Biotechnology
    • Genetics
    • Plant Science

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  • Cite this

    Ikeue, D., Schudoma, C., Zhang, W., Ogata, Y., Sakamoto, T., Kurata, T., Furuhashi, T., Kragler, F., & Aoki, K. (2015). A bioinformatics approach to distinguish plant parasite and host transcriptomes in interface tissue by classifying RNA-Seq reads. Plant Methods, 11(1), [34]. https://doi.org/10.1186/s13007-015-0066-6