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

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 h...

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Autores principales: Ikeue, Daisuke, Schudoma, Christian, Zhang, Wenna, Ogata, Yoshiyuki, Sakamoto, Tomoaki, Kurata, Tetsuya, Furuhashi, Takeshi, Kragler, Friedrich, Aoki, Koh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4458054/
https://www.ncbi.nlm.nih.gov/pubmed/26052341
http://dx.doi.org/10.1186/s13007-015-0066-6
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author Ikeue, Daisuke
Schudoma, Christian
Zhang, Wenna
Ogata, Yoshiyuki
Sakamoto, Tomoaki
Kurata, Tetsuya
Furuhashi, Takeshi
Kragler, Friedrich
Aoki, Koh
author_facet Ikeue, Daisuke
Schudoma, Christian
Zhang, Wenna
Ogata, Yoshiyuki
Sakamoto, Tomoaki
Kurata, Tetsuya
Furuhashi, Takeshi
Kragler, Friedrich
Aoki, Koh
author_sort Ikeue, Daisuke
collection PubMed
description 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.
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spelling pubmed-44580542015-06-07 A bioinformatics approach to distinguish plant parasite and host transcriptomes in interface tissue by classifying RNA-Seq reads Ikeue, Daisuke Schudoma, Christian Zhang, Wenna Ogata, Yoshiyuki Sakamoto, Tomoaki Kurata, Tetsuya Furuhashi, Takeshi Kragler, Friedrich Aoki, Koh Plant Methods Methodology 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. BioMed Central 2015-05-03 /pmc/articles/PMC4458054/ /pubmed/26052341 http://dx.doi.org/10.1186/s13007-015-0066-6 Text en © Ikeue et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology
Ikeue, Daisuke
Schudoma, Christian
Zhang, Wenna
Ogata, Yoshiyuki
Sakamoto, Tomoaki
Kurata, Tetsuya
Furuhashi, Takeshi
Kragler, Friedrich
Aoki, Koh
A bioinformatics approach to distinguish plant parasite and host transcriptomes in interface tissue by classifying RNA-Seq reads
title A bioinformatics approach to distinguish plant parasite and host transcriptomes in interface tissue by classifying RNA-Seq reads
title_full A bioinformatics approach to distinguish plant parasite and host transcriptomes in interface tissue by classifying RNA-Seq reads
title_fullStr A bioinformatics approach to distinguish plant parasite and host transcriptomes in interface tissue by classifying RNA-Seq reads
title_full_unstemmed A bioinformatics approach to distinguish plant parasite and host transcriptomes in interface tissue by classifying RNA-Seq reads
title_short A bioinformatics approach to distinguish plant parasite and host transcriptomes in interface tissue by classifying RNA-Seq reads
title_sort bioinformatics approach to distinguish plant parasite and host transcriptomes in interface tissue by classifying rna-seq reads
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4458054/
https://www.ncbi.nlm.nih.gov/pubmed/26052341
http://dx.doi.org/10.1186/s13007-015-0066-6
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