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, Shu-Sheng Liu
Author Information
  1. Xiao-Wei Wang: Ministry of Agriculture Key Laboratory of Molecular Biology of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou 310029, China. xwwang@zju.edu.cn

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.

References

  1. Pest Manag Sci. 2002 Sep;58(9):868-75 [PMID: 12233176]
  2. Nature. 2006 Oct 26;443(7114):898-900 [PMID: 17066003]
  3. Bioinformatics. 2003 Mar 22;19(5):651-2 [PMID: 12651724]
  4. Insect Biochem Mol Biol. 2008 Oct;38(10):940-9 [PMID: 18721883]
  5. Biol Reprod. 2005 Jul;73(1):72-9 [PMID: 15744019]
  6. J Insect Physiol. 2007 Mar;53(3):216-29 [PMID: 17074360]
  7. Nucleic Acids Res. 2008 Dec;36(21):e141 [PMID: 18927111]
  8. Genome Res. 1997 Oct;7(10):986-95 [PMID: 9331369]
  9. Genome Res. 2008 Sep;18(9):1538-43 [PMID: 18550804]
  10. Mol Phylogenet Evol. 2007 Sep;44(3):1306-19 [PMID: 17627853]
  11. Nucleic Acids Res. 2004 Jan 1;32(Database issue):D277-80 [PMID: 14681412]
  12. Arch Insect Biochem Physiol. 2005 Apr;58(4):216-25 [PMID: 15756703]
  13. Mol Immunol. 2009 Sep;46(15):2918-30 [PMID: 19631987]
  14. BMC Genomics. 2007 Sep 15;8:324 [PMID: 17868469]
  15. BMC Genomics. 2008 Jul 18;9:342 [PMID: 18638407]
  16. Science. 1993 Jan 1;259(5091):74-7 [PMID: 8418497]
  17. Nat Genet. 2008 Dec;40(12):1413-5 [PMID: 18978789]
  18. BMC Genomics. 2006 Apr 11;7:79 [PMID: 16608516]
  19. Genomics. 2008 Oct;92(4):187-94 [PMID: 18602984]
  20. N Biotechnol. 2009 Apr;25(4):195-203 [PMID: 19429539]
  21. Science. 2007 Dec 14;318(5857):1769-72 [PMID: 17991828]
  22. Bull Entomol Res. 2010 Jun;100(3):359-66 [PMID: 20178675]
  23. Genome Res. 2010 Feb;20(2):265-72 [PMID: 20019144]
  24. Pest Manag Sci. 2007 Aug;63(8):776-83 [PMID: 17569108]
  25. Nat Methods. 2008 Jan;5(1):16-8 [PMID: 18165802]
  26. Nature. 2009 Mar 12;458(7235):239-42 [PMID: 19279641]

MeSH Term

Animals
Cluster Analysis
Databases, Genetic
Female
Gene Expression Profiling
Gene Expression Regulation, Developmental
Hemiptera
Insect Proteins
Insecticides
Sequence Analysis, DNA

Chemicals

Insect Proteins
Insecticides