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Marx, H.* ; Hahne, H.* ; Ulbrich, S.E.* ; Schnieke, A.* ; Rottmann, O.* ; Frishman, D. ; Kuster, B.*

Annotation of the domestic pig genome by quantitative proteogenomics.

J. Proteome Res. 16, 2887-2898 (2017)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
The pig is one of the earliest domesticated animals in the history of human civilization and represents one of the most important livestock animals. The recent sequencing of the Sus scrofa genome was a major step toward the comprehensive understanding of porcine biology, evolution, and its utility as a promising large animal model for biomedical and xenotransplantation research. However, the functional and structural annotation of the Sus scrofa genome is far from complete. Here, we present mass spectrometry-based quantitative proteomics data of nine juvenile organs and six embryonic stages between 18 and 39 days after gestation. We found that the data provide evidence for and improve the annotation of 8176 protein-coding genes including 588 novel and 321 refined gene models. The analysis of tissue-specific proteins and the temporal expression profiles of embryonic proteins provides an initial functional characterization of expressed protein interaction networks and modules including as yet uncharacterized proteins. Comparative transcript and protein expression analysis to human organs reveal a moderate conservation of protein translation across species. We anticipate that this resource will facilitate basic and applied research on Sus scrofa as well as its porcine relatives.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Mammal Development ; Mass Spectrometry ; Pig ; Proteogenomics ; Quantitative Proteomics
ISSN (print) / ISBN 1535-3893
e-ISSN 1535-3907
Zeitschrift Journal of Proteome Research
Quellenangaben Band: 16, Heft: 8, Seiten: 2887-2898 Artikelnummer: , Supplement: ,
Verlag American Chemical Society (ACS)
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Bioinformatics and Systems Biology (IBIS)