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. 2010 Jun 24:11:400.
doi: 10.1186/1471-2164-11-400.

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

Xiao-Wei Wang  1 , Jun-Bo Luan, Jun-Min Li, Yan-Yuan Bao, Chuan-Xi Zhang, Shu-Sheng Liu
Affiliations

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

Xiao-Wei Wang et al. BMC Genomics. .

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.

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Figures

Figure 1
Figure 1
Effect of query sequence length on the percentage of sequences for which significant matches were found. The proportion of sequences with matches (with a cut-off E-value of 1.0E-5) in NCBI nr databases is greater among the longer assembled sequences.
Figure 2
Figure 2
Characteristics of homology search of Illumina sequences against the nr database. (A) E-value distribution of BLAST hits for each unique sequence with a cut-off E-value of 1.0E-5. (B) Similarity distribution of the top BLAST hits for each sequence. (C) Species distribution is shown as a percentage of the total homologous sequences with an E-value of at least 1.0E-5. We used the first hit of each sequence for analysis. Homo: Homo sapiens; Mus: Mus musculus; Rat: Rattus norvegicus.
Figure 3
Figure 3
Histogram presentation of Gene Ontology classification. The results are summarized in three main categories: biological process, cellular component and molecular function. The right y-axis indicates the number of genes in a category. The left y-axis indicates the percentage of a specific category of genes in that main category.
Figure 4
Figure 4
Histogram presentation of clusters of orthologous groups (COG) classification. Out of 27,290 nr hits, 7790 sequences have a COG classification among the 25 categories.
Figure 5
Figure 5
Distribution of total tags and distinct tags over different tag abundance categories. (A) Distribution of total tags. Numbers in the square brackets indicate the range of copy numbers for a specific category of tags. For example, [2,5] means all the tags in this category has 2 to 5 copies. Numbers in the parentheses show the total tag copy number for all the tags in that category. (B) Distribution of distinct tags. Numbers in the square brackets indicate the range of copy numbers for a specific category of tags. Numbers in the parentheses show the total types of tags in that category.
Figure 6
Figure 6
The level of gene expression for each gene. Gene expression level was determined by calculating the number of unambiguous tags for each gene and then normalizing to TPM (transcript copies per million tags).
Figure 7
Figure 7
Changes in gene expression profile among the different developmental stages. The number of up-regulated and down-regulated genes between pupa and egg & nymph; adult and pupa are summarized.
Figure 8
Figure 8
Analyses of differentially expressed genes during whitefly development. The gene expression levels of vitellogenin 1 (A); vitellogenin 2 (B); ecdysone receptor (C); ecdysone-inducible protein E75 (D) and translation elongation factor 2 (E) were determined by calculating the number of unambiguous tags for each gene and then normalizing to TPM (transcript copies per million tags).
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