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Open Access Highly Accessed Research article

De novo characterization of a whitefly transcriptome and analysis of its gene expression during development

Xiao-Wei Wang*, Jun-Bo Luan, Jun-Min Li, Yan-Yuan Bao, Chuan-Xi Zhang and Shu-Sheng Liu*

Author Affiliations

Ministry of Agriculture Key Laboratory of Molecular Biology of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou 310029, China

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BMC Genomics 2010, 11:400  doi:10.1186/1471-2164-11-400

Published: 24 June 2010

Abstract

Background

Whitefly (Bemisia tabaci) causes extensive crop damage throughout the world by feeding directly on plants and by vectoring hundreds of species of begomoviruses. Yet little is understood about its genes involved in development, insecticide resistance, host range plasticity and virus transmission.

Results

To facilitate research on whitefly, we present a method for de novo assembly of whitefly transcriptome using short read sequencing technology (Illumina). In a single run, we produced more than 43 million sequencing reads. These reads were assembled into 168,900 unique sequences (mean size = 266 bp) which represent more than 10-fold of all the whitefly sequences deposited in the GenBank (as of March 2010). Based on similarity search with known proteins, these analyses identified 27,290 sequences with a cut-off E-value above 10-5. Assembled sequences were annotated with gene descriptions, gene ontology and clusters of orthologous group terms. In addition, we investigated the transcriptome changes during whitefly development using a tag-based digital gene expression (DGE) system. We obtained a sequencing depth of over 2.5 million tags per sample and identified a large number of genes associated with specific developmental stages and insecticide resistance.

Conclusion

Our data provides the most comprehensive sequence resource available for whitefly study and demonstrates that the Illumina sequencing allows de novo transcriptome assembly and gene expression analysis in a species lacking genome information. We anticipate that next generation sequencing technologies hold great potential for the study of the transcriptome in other non-model organisms.