Genome-wide characterization and transcriptomic analyses of neuropeptides and their receptors in an endoparasitoid wasp, Pteromalus puparum.
Gang XuZi-Wen TengGui-Xiang GuYi-Xiang QiLei GuoShan XiaoFei WangQi FangFang WangQi-Sheng SongDavid StanleyGong-Yin YePublished in: Archives of insect biochemistry and physiology (2019)
In insects, neuropeptides constitute a group of signaling molecules that act in regulation of multiple physiological and behavioral processes by binding to their corresponding receptors. On the basis of the bioinformatic approaches, we screened the genomic and transcriptomic data of the parasitoid wasp, Pteromalus puparum, and annotated 36 neuropeptide precursor genes and 33 neuropeptide receptor genes. Compared to the number of precursor genes in Bombyx mori (Lepidoptera), Chilo suppressalis (Lepidoptera), Drosophila melanogaster (Diptera), Nilaparvata lugens (Hemiptera), Apis mellifera (Hymenoptera), and Tribolium castaneum (Coleoptera), P. puparum (Hymenoptera) has the lowest number of neuropeptide precursor genes. This lower number may relate to its parasitic life cycle. Transcriptomic data of embryos, larvae, pupae, adults, venom glands, salivary glands, ovaries, and the remaining carcass revealed stage-, sex-, and tissue-specific expression patterns of the neuropeptides, and their receptors. These data provided basic information about the identity and expression profiles of neuropeptides and their receptors that are required to functionally address their biological significance in an endoparasitoid wasp.
Keyphrases
- genome wide
- drosophila melanogaster
- single cell
- dna methylation
- electronic health record
- bioinformatics analysis
- genome wide identification
- copy number
- rna seq
- big data
- life cycle
- poor prognosis
- healthcare
- genome wide analysis
- machine learning
- data analysis
- transcription factor
- health information
- deep learning
- long non coding rna