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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.    Electronic supplementary material  The online version of this article (doi:10.1186/s13007-015-0066-6) contains supplementary material, which is available to authorized users.

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