Expressed sequence tags from larval gut of the European corn borer (Ostrinia nubilalis): exploring candidate genes potentially involved in Bacillus thuringiensis toxicity and resistance
Lepidoptera represents more than 160,000 insect species which include some of the most devastating pests of crops, forests, and stored products. However, the genomic information on lepidopteran insects is very limited. Only a few studies have focused on developing expressed sequence tag (EST) librar...
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Veröffentlicht in: | BMC genomics 2009-06, Vol.10 (1), p.286-286, Article 286 |
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Zusammenfassung: | Lepidoptera represents more than 160,000 insect species which include some of the most devastating pests of crops, forests, and stored products. However, the genomic information on lepidopteran insects is very limited. Only a few studies have focused on developing expressed sequence tag (EST) libraries from the guts of lepidopteran larvae. Knowledge of the genes that are expressed in the insect gut are crucial for understanding basic physiology of food digestion, their interactions with Bacillus thuringiensis (Bt) toxins, and for discovering new targets for novel toxins for use in pest management. This study analyzed the ESTs generated from the larval gut of the European corn borer (ECB, Ostrinia nubilalis), one of the most destructive pests of corn in North America and the western world. Our goals were to establish an ECB larval gut-specific EST database as a genomic resource for future research and to explore candidate genes potentially involved in insect-Bt interactions and Bt resistance in ECB.
We constructed two cDNA libraries from the guts of the fifth-instar larvae of ECB and sequenced a total of 15,000 ESTs from these libraries. A total of 12,519 ESTs (83.4%) appeared to be high quality with an average length of 656 bp. These ESTs represented 2,895 unique sequences, including 1,738 singletons and 1,157 contigs. Among the unique sequences, 62.7% encoded putative proteins that shared significant sequence similarities (E-value |
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ISSN: | 1471-2164 1471-2164 |
DOI: | 10.1186/1471-2164-10-286 |