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Open Access Highly Accessed Research article

Rapid transcriptome characterization and parsing of sequences in a non-model host-pathogen interaction; pea-Sclerotinia sclerotiorum

Xiaofeng Zhuang1, Kevin E McPhee2, Tristan E Coram3, Tobin L Peever4 and Martin I Chilvers1*

Author affiliations

1 Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, East Lansing, MI, USA

2 Department of Plant Sciences, North Dakota State University, 370G Loftsgard Hall, Fargo, ND, USA

3 Dow AgroSciences LLC, 9330 Zionsville Road, Indianapolis, IN, USA

4 Department of Plant Pathology, Washington State University, Pullman, WA, USA

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Citation and License

BMC Genomics 2012, 13:668  doi:10.1186/1471-2164-13-668

Published: 26 November 2012

Abstract

Background

White mold, caused by Sclerotinia sclerotiorum, is one of the most important diseases of pea (Pisum sativum L.), however, little is known about the genetics and biochemistry of this interaction. Identification of genes underlying resistance in the host or pathogenicity and virulence factors in the pathogen will increase our knowledge of the pea-S. sclerotiorum interaction and facilitate the introgression of new resistance genes into commercial pea varieties. Although the S. sclerotiorum genome sequence is available, no pea genome is available, due in part to its large genome size (~3500 Mb) and extensive repeated motifs. Here we present an EST data set specific to the interaction between S. sclerotiorum and pea, and a method to distinguish pathogen and host sequences without a species-specific reference genome.

Results

10,158 contigs were obtained by de novo assembly of 128,720 high-quality reads generated by 454 pyrosequencing of the pea-S. sclerotiorum interactome. A method based on the tBLASTx program was modified to distinguish pea and S. sclerotiorum ESTs. To test this strategy, a mixture of known ESTs (18,490 pea and 17,198 S. sclerotiorum ESTs) from public databases were pooled and parsed; the tBLASTx method successfully separated 90.1% of the artificial EST mix with 99.9% accuracy. The tBLASTx method successfully parsed 89.4% of the 454-derived EST contigs, as validated by PCR, into pea (6,299 contigs) and S. sclerotiorum (2,780 contigs) categories. Two thousand eight hundred and forty pea ESTs and 996 S. sclerotiorum ESTs were predicted to be expressed specifically during the pea-S. sclerotiorum interaction as determined by homology search against 81,449 pea ESTs (from flowers, leaves, cotyledons, epi- and hypocotyl, and etiolated and light treated etiolated seedlings) and 57,751 S. sclerotiorum ESTs (from mycelia at neutral pH, developing apothecia and developing sclerotia). Among those ESTs specifically expressed, 277 (9.8%) pea ESTs were predicted to be involved in plant defense and response to biotic or abiotic stress, and 93 (9.3%) S. sclerotiorum ESTs were predicted to be involved in pathogenicity/virulence. Additionally, 142 S. sclerotiorum ESTs were identified as secretory/signal peptides of which only 21 were previously reported.

Conclusions

We present and characterize an EST resource specific to the pea-S. sclerotiorum interaction. Additionally, the tBLASTx method used to parse S. sclerotiorum and pea ESTs was demonstrated to be a reliable and accurate method to distinguish ESTs without a reference genome.

Keywords:
Pisum sativum; Sclerotinia sclerotiorum; Transcriptome; Parsing of host-pathogen sequences; Non-model organism