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Bridging neuropeptidomics and genomics with bioinformatics: Prediction of mammalian neuropeptide prohormone processing.

ABSTRACT: Neuropeptides are an important class of cell to cell signaling molecules that are difficult to predict from genetic information because of their large number of post-translational modifications. The transition from prohormone genetic sequence information to the determination of the biologically active neuropeptides requires the identification of the cleaved basic sites, among the many possible cleavage sites, that exist in the prohormone. We report a binary logistic regression model trained on mammalian prohormones that is more sensitive than existing methods in predicting these processing sites, and demonstrate the application of this method to mammalian neuropeptidomic studies. By comparing the predictive abilities of a binary logistic model trained on molluscan prohormone cleavages with the reported model, we establish the need for phyla-specific models.

SUBMITTER: Amare A

PROVIDER: S-EPMC2548284 | biostudies-literature | 2006 May

REPOSITORIES: biostudies-literature

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Bridging neuropeptidomics and genomics with bioinformatics: Prediction of mammalian neuropeptide prohormone processing.

Amare Andinet A Hummon Amanda B AB Southey Bruce R BR Zimmerman Tyler A TA Rodriguez-Zas Sandra L SL Sweedler Jonathan V JV

Journal of proteome research 20060501 5

Neuropeptides are an important class of cell to cell signaling molecules that are difficult to predict from genetic information because of their large number of post-translational modifications. The transition from prohormone genetic sequence information to the determination of the biologically active neuropeptides requires the identification of the cleaved basic sites, among the many possible cleavage sites, that exist in the prohormone. We report a binary logistic regression model trained on m ...[more]

PMID: 16674105

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Project description:Neuropeptides regulate cell-cell signaling and influence many biological processes in vertebrates, including development, growth, and reproduction. The complex processing of neuropeptides from prohormone proteins by prohormone convertases, combined with the evolutionary distance between the chicken and mammalian species that have experienced extensive neuropeptide research, has led to the empirical confirmation of only 18 chicken prohormone proteins. To expand our knowledge of the neuropeptide and prohormone convertase gene complement, we performed an exhaustive survey of the chicken genomic, EST, and proteomic databases using a list of 95 neuropeptide and 7 prohormone convertase genes known in other species. Analysis of the EST resources and 22 microarray studies offered a comprehensive portrait of gene expression across multiple conditions. Five neuropeptide genes (apelin, cocaine-and amphetamine-regulated transcript protein, insulin-like 5, neuropeptide S, and neuropeptide B) previously unknown in chicken were identified and 62 genes were confirmed. Although most neuropeptide gene families known in human are present in chicken, there are several gene not present in the chicken. Conversely, several chicken neuropeptide genes are absent from mammalian species, including C-RF amide, c-type natriuretic peptide 1 precursor, and renal natriuretic peptide. The prohormone convertases, with one exception, were found in the chicken genome. Bioinformatic models used to predict prohormone cleavages confirm that the processing of prohormone proteins into neuropeptides is similar between species. Neuropeptide genes are most frequently expressed in the brain and head, followed by the ovary and small intestine. Microarray analyses revealed that the expression of adrenomedullin, chromogranin-A, augurin, neuromedin-U, platelet-derived growth factor A and D, proenkephalin, relaxin-3, prepronociceptin, and insulin-like growth factor I was most susceptible (P-value<0.005) to changes in developmental stage, gender, and genetic line among other conditions studied. Our complete survey and characterization facilitates understanding of neuropeptides genes in the chicken, an animal of importance to biomedical and agricultural research.

Dataset Information

Bridging neuropeptidomics and genomics with bioinformatics: Prediction of mammalian neuropeptide prohormone processing.

Publications

Bridging neuropeptidomics and genomics with bioinformatics: Prediction of mammalian neuropeptide prohormone processing.

Similar Datasets

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