To find novel neuropeptide and/or peptide hormone precursors in the avian brain, we performed a cDNA subtractive screen of the chicken hypothalamic infundibulum, which contains one of the feeding and neuroendocrine centers. After sequencing 596 clones, we identified a novel cDNA encoding a previously unknown protein. The deduced precursor protein consisted of 182 amino acid residues, including one putative small secretory protein of 80 amino acid residues. This small protein was flanked at the N-terminus by a signal peptide and at the C-terminus by a glycine amidation signal and a dibasic amino acid cleavage site. Because the predicted C-terminal amino acids of the small protein were Gly-Leu-NH2, the small protein was named neurosecretory protein GL (NPGL). Quantitative RT-PCR analysis demonstrated specific expression of the NPGL precursor mRNA in the hypothalamic infundibulum. Furthermore, the mRNA levels in the hypothalamic infundibulum increased during post-hatching development. In situ hybridization analysis showed that the cells containing the NPGL precursor mRNA were localized in the medial mammillary nucleus and infundibular nucleus within the hypothalamic infundibulum of 8- and 15-day-old chicks. Subcutaneous infusion of NPGL in chicks increased body weight gain without affecting food intake. To our knowledge, this is the first report to describe the identification and localization of the NPGL precursor mRNA and the function of its translated product in animals. Our findings indicate that NPGL may participate in the growth process in chicks.
Pubmed ID: 24582750 RIS Download
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Collection of genome databases for vertebrates and other eukaryotic species with DNA and protein sequence search capabilities. Used to automatically annotate genome, integrate this annotation with other available biological data and make data publicly available via web. Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species.
View all literature mentionsWeb application for prediction of the presence and location of signal peptide cleavage sites in amino acid sequences from different organisms. The method incorporates a prediction of cleavage sites and a signal peptide/non-signal peptide prediction based on a combination of several artificial neural networks.
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