After that, peak intensities were normalized to the total spectral intensity by first QC. Then, based on the set 10ppm mass deviation and adduct ion , compare it with the high-quality secondary spectrum database for metabolite identification to obtain the accurate qualitative and relative quantitative results. Statistical analyses were performed using the statistical software R (R version R-3.4.3), Python (Python 2.7.6 version) and CentOS (CentOS release 6.6), When data were not normally distributed, standardize according to the formula: sample raw quantitation value / (The sum of sample metabolite quantitation value /The sum of QC1 sample metabolite quantitation value) to obtain relative peak areas; And compounds whose CVs of relative peak areas in QC samples were greater than 30% were removed, and finally the metabolites' identification and relative quantification results were obtained.
"],"technology_type":["mass spectrometry assay"],"disease":[""],"extraction_protocol":["The ground samples were mixed with 500 μL of 80% methanol aqueous solution, followed by an ice bath and high-speed centrifugation. The supernatant was then diluted to a methanol concentration of 53%. After a second centrifugation, the supernatant was subjected to LC-MS analysis.
"],"organism":["Cervus nippon"],"data_transformation_protocol":["The data files generated by UHPLC-MS/MS were processed using the XCMS to peak alignment, peak picking, and quantitation for each metabolite.
"],"study_factor":["Stage"],"metabolights_link":["https://www.ebi.ac.uk/metabolights/MTBLS12622"],"submitter_email":["lihepinghrb2002@nefu.edu.cn"],"sample_collection_protocol":["Six 5-year-old healthy adult male sika deer were used in this study. At the early, middle, and late growth stages (EG, MG, and LG), the mesenchyme tissues from the antler tip were collected. The tissues were excised into small pieces and immediately transferred into sterile, RNase-free cryovials, followed by storage in liquid nitrogen.
"],"repository":["MetaboLights"],"study_status":["Public"],"ptm_modification":[""],"omics_type":["Metabolomics"],"instrument_platform":["Liquid Chromatography MS - negative - reverse phase","Liquid Chromatography MS - positive - reverse phase"],"study_design":["Thermo Scientific Vanquish UHPLC System","untargeted analysis","Thermo Scientific Q Exactive HF-X","Transcriptome","antler","Lipid Metabolism","Q Exactive™ HF-X","Thermo Scientific Surveyor HPLC system","metabolome","Cervus nippon","proteome"],"chromatography_protocol":["UHPLC-MS/MS analyses were performed using a Vanquish UHPLC system (ThermoFisher, Germany) coupled with an Orbitrap Q Exactive™ HF-X mass spectrometer (Thermo Fisher, Germany). Samples were injected onto a Hypersil Gold column (100×2.1 mm, 1.9μm) using a 12-min linear gradient at a flow rate of 0.2 mL/min. The eluents for the positive and negative polarity modes were eluent A (0.1% FA in Water) and eluent B (Methanol). The solvent gradient was set as follows: 2% B, 1.5 min; 2-85% B, 3 min; 85-100% B, 10 min; 100-2% B, 10.1 min; 2% B, 12 min.
"],"publication":["Multi-omics integration analysis reveals metabolic changes during sika deer antler growth."],"curator_keywords":["Thermo Scientific Vanquish UHPLC System","untargeted analysis","Thermo Scientific Q Exactive HF-X","Transcriptome","antler","Lipid Metabolism","Q Exactive™ HF-X","Thermo Scientific Surveyor HPLC system","metabolome","proteome","Cervus nippon"],"submitter_affiliation":["Northeast Forestry University"],"submitter_name":["Heping Li"],"mass_spectrometry_protocol":["Q Exactive™ HF-X mass spectrometer was operated in positive/negative polarity mode with spray voltage of 3.5 kV, capillary temperature of 320°C, sheath gas flow rate of 35 psi and aux gas flow rate of 10 L/min, S-lens RF level of 60, Aux gas heater temperature of 350°C.
"],"additional_accession":[]},"is_claimable":false,"name":"Multi-omics integration analysis reveals metabolic changes during sika deer antler growth","description":"Background: Antler is an important economic trait of sika deer (Cervus nippon), capable of rapid growth without signs of tumorigenesis. However, the molecular mechanisms underlying its unique growth pattern remain poorly understood. This study conducted a combined transcriptomic, proteomic, metabolomic and single-cell transcriptomic analysis of tip mesenchyme of antler at three key growth stages, early, middle, and late growth (EG, MG, LG), to explore the molecular characteristics during antler growth.
Results: Active post-transcriptional and post-translational regulation likely occurred during antler growth, as characterized by significant alternative splicing (AS) events and significant enrichment of post-transcriptional and post-translational regulatory functions at the protein level. The multi-level regulatory network constructed based on differentially expressed genes, proteins, and metabolites (DEGs, DEPs, DEMs) indicated continuous and extensive metabolic reprogramming in the glycerophospholipid metabolism pathway. PLA2G3, MBOAT2, LPCAT3, DGKI, and EPT1 were positioned at core nodes within this pathway. The qRT-PCR confirmed that these genes were predominantly expressed in MG, suggesting their role as crucial candidate genes involved in regulating the metabolic reprogramming. Analysis of single-cell transcriptomic data revealed that the MBOAT2, LPCAT3, DGKI, and EPT1 genes were expressed in key cell types such as chondroblasts, chondrocytes, osteoblasts, and mesenchymal cells.
Conclusions: Integrated multi-omics analyses indicated that the rapid growth of antlers is closely associated with continuous metabolic reprogramming, involving multi-layered regulation of glycerophospholipid metabolism. This study established a foundational multi-omics resource, providing new perspectives for elucidating the molecular mechanisms of antler growth and for subsequent functional studies, while also offering novel insights for research on organ and tissue growth in animals.
","dates":{"publication":"2026-04-01","submission":"2025-06-20"},"accession":"MTBLS12622","cross_references":{}}