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Large-scale identification of odorant-binding proteins and chemosensory proteins from expressed sequence tags in insects

机译:从昆虫中表达的序列标签大规模识别气味结合蛋白和化学感应蛋白

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Background Insect odorant binding proteins (OBPs) and chemosensory proteins (CSPs) play an important role in chemical communication of insects. Gene discovery of these proteins is a time-consuming task. In recent years, expressed sequence tags (ESTs) of many insect species have accumulated, thus providing a useful resource for gene discovery. Results We have developed a computational pipeline to identify OBP and CSP genes from insect ESTs. In total, 752,841 insect ESTs were examined from 54 species covering eight Orders of Insecta. From these ESTs, 142 OBPs and 177 CSPs were identified, of which 117 OBPs and 129 CSPs are new. The complete open reading frames (ORFs) of 88 OBPs and 123 CSPs were obtained by electronic elongation. We randomly chose 26 OBPs from eight species of insects, and 21 CSPs from four species for RT-PCR validation. Twenty two OBPs and 16 CSPs were confirmed by RT-PCR, proving the efficiency and reliability of the algorithm. Together with all family members obtained from the NCBI (OBPs) or the UniProtKB (CSPs), 850 OBPs and 237 CSPs were analyzed for their structural characteristics and evolutionary relationship. Conclusions A large number of new OBPs and CSPs were found, providing the basis for deeper understanding of these proteins. In addition, the conserved motif and evolutionary analysis provide some new insights into the evolution of insect OBPs and CSPs. Motif pattern fine-tune the functions of OBPs and CSPs, leading to the minor difference in binding sex pheromone or plant volatiles in different insect Orders.
机译:背景技术昆虫气味结合蛋白(OBP)和化学感应蛋白(CSP)在昆虫的化学交流中起重要作用。这些蛋白质的基因发现是一项耗时的任务。近年来,许多昆虫物种的表达序列标签(EST)已经积累,从而为基因发现提供了有用的资源。结果我们开发了一种计算流程,可从昆虫EST中鉴定OBP和CSP基因。总共检查了来自八个昆虫纲的54个物种的752,841个昆虫EST。从这些EST中,鉴定出142个OBP和177个CSP,其中117个OBP和129个CSP是新的。通过电子延伸获得了88个OBP和123个CSP的完整开放阅读框(ORF)。我们从八种昆虫中随机选择了26种OBP,并从四种昆虫中随机选择了21种CSP用于RT-PCR验证。 RT-PCR证实了22个OBP和16个CSP,证明了该算法的有效性和可靠性。连同从NCBI(OBP)或UniProtKB(CSP)获得的所有家族成员一起,分析了850个OBP和237个CSP的结构特征和进化关系。结论发现了大量新的OBP和CSP,为深入了解这些蛋白质提供了基础。另外,保守的基序和进化分析为昆虫OBP和CSP的进化提供了一些新见解。母题模式微调了OBP和CSP的功能,导致在不同昆虫纲中结合性信息素或植物挥发物的差异很小。

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