期刊
PLOS ONE
卷 6, 期 12, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0029127
关键词
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资金
- National Basic Research Program of China [2009CB125903, 2009CB119200]
- Natural Science Foundation of Chongqing (CSTC) [2009BA1042]
- Program for Innovative Research Team in University [IRT0976]
- earmarked fund for Modern Agro-industry (Citrus) Technology Research System, China [CARS-27-06B]
Background: The oriental fruit fly, Bactrocera dorsalis (Hendel), is one of the most economically important pests in the world, causing serious damage to fruit production. However, lack of genetic information on this organism is an obstacle to understanding the mechanisms behind its development and its ability to resist insecticides. Analysis of the B. dorsalis transcriptome and its expression profile data is essential to extending the genetic information resources on this species, providing a shortcut that will support studies on B. dorsalis. Methodology/Principal Findings: We performed de novo assembly of a transcriptome using short read sequencing technology (Illumina). The results generated 484,628 contigs, 70,640 scaffolds, and 49,804 unigenes. Of those unigenes, 27,455 (55.13%) matched known proteins in the NCBI database, as determined by BLAST search. Clusters of orthologous groups (COG), gene orthology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations were performed to better understand the functions of these unigenes. Genes related to insecticide resistance were analyzed in additional detail. Digital gene expression (DGE) libraries showed differences in gene expression profiles at different developmental stages (eggs, third-instar larvae, pupae, and adults). To confirm the DGE results, the expression profiles of six randomly selected genes were analyzed. Conclusion/Significance: This transcriptome greatly improves our genetic understanding of B. dorsalis and makes a huge number of gene sequences available for further study, including both genes of known importance and genes of unknown function. The DGE data provide comprehensive insight into gene expression profiles at different developmental stages. This facilitates the study of the role of each gene in the developmental process and in insecticide resistance.
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