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Comparative proteomics analysis reveals the difference during antler regeneration stage between red deer and sika deer. | LitMetric

AI Article Synopsis

  • Deer antler serves as a unique model for studying regenerative medicine due to its capacity to regenerate, with red and sika deer being the primary subjects in research.
  • A previous study utilizing proteomic technology uncovered specific signaling pathways involved in antler stem cell activity from red deer, while genomic analysis of sika deer revealed key genes governing antler development.
  • The current study conducted a comparative proteomic analysis, identifying 36 proteins prevalent in red deer antlers and 144 in sika deer, highlighting distinct biological pathways related to regeneration.

Article Abstract

Deer antler, as the only mammalian regenerative appendage, provides an optimal model to study regenerative medicine. Antler harvested from red deer or sika deer were mainly study objects used to disclose the mechanism underlying antler regeneration over past decades. A previous study used proteomic technology to reveal the signaling pathways of antler stem cell derived from red deer. Moreover, transcriptome of antler tip from sika deer provide us with the essential genes, which regulated antler development and regeneration. However, antler comparison between red deer and sika deer has not been well studied. In our current study, proteomics were employed to analyze the biological difference of antler regeneration between sika deer and red deer. The proteomics profile was completed by searching the UniProt database, and differentially expressed proteins were identified by bioinformatic software. Thirty-six proteins were highly expressed in red deer antler, while 144 proteins were abundant in sika deer. GO and KEGG analysis revealed that differentially expressed proteins participated in the regulation of several pathways including oxidative phosphorylation, ribosome, extracellular matrix interaction, and PI3K-Akt pathway.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6642628PMC
http://dx.doi.org/10.7717/peerj.7299DOI Listing

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