PXD080427

PXD080427 is an original dataset announced via ProteomeXchange.

Title	Integrated Serum Metabolomics and Proteomics with Machine Learning Identifies Candidate Biomarkers for Lactation Performance in Dairy Mares
Description	Background: Mare milk is characterized by high nutritional value, good digestibility, and bioactive components with potential functional properties. However, dairy mares show marked individual variation in milk yield, and stable molecular indicators for identifying high-yielding individuals remain limited. Therefore, this study aimed to characterize molecular signatures associated with lactation-performance differences between high- and low-yielding dairy mares. Results: A total of 193 mid-lactation mares were enrolled, and 102 differential metabolites and 37 differentially expressed proteins were identified between high- and low-yielding mares. The differential molecules were mainly enriched in ABC transporters, glycine, serine and threonine metabolism, linoleic acid metabolism, focal adhesion, regulation of the actin cytoskeleton, redox homeostasis, and immune defense. Increased levels of Gly, 12,13-DiHOME, and 5-ALA in high-yielding mares suggested enhanced amino acid supply, lipid utilization, and mitochondrial-related energy metabolism, whereas changes in ARPC3, LAMP2, SEPTIN6, ST6GAL1, and MYL6 indicated potential involvement of cytoskeletal remodeling, lysosomal homeostasis, epithelial polarity, glycoprotein processing, and cell contraction. In cross-platform validation, Gly, 12,13-DiHOME, 5-ALA, ARPC3, PRDX2, LYZ, and LAMP2 exhibited relatively consistent differences and may serve as priority candidate molecules for further research. Conclusions: This study revealed serum multi-omics signatures associated with lactation-performance differences in dairy mares and highlighted candidate molecules related to nutrient metabolism, cytoskeletal remodeling, antioxidant defense, and immune regulation. These findings provide candidate biomarkers for early screening of high-yielding mares and offer insights into the molecular mechanisms underlying lactation performance in dairy horses
HostingRepository	PRIDE
AnnounceDate	2026-07-21
AnnouncementXML	Submission_2026-07-21_02:59:24.958.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	liangyi jin
SpeciesList	scientific name: Equus caballus (Horse); NCBI TaxID: NEWT:9796;
ModificationList	No PTMs are included in the dataset
Instrument	Orbitrap Astral Zoom

Revision	Datetime	Status	ChangeLog Entry
0	2026-07-01 05:57:16	ID requested
⏵ 1	2026-07-21 02:59:25	announced

Dataset with its publication pending

submitter keyword: dairy mares

lactation performance

serum metabolomics

DIA proteomics

machine learning

candidate biomarkers

Bei Li
contact affiliation	Inner Mongolia Key Laboratory of Equus Science Research and Technology Innovation, Inner Mongolia Agricultural University
contact email	mulanlb@163.com
lab head
liangyi jin
contact affiliation	Equus Research Center, College of Animal Science, Inner Mongolia Agricultural University
contact email	15575532582@163.com
dataset submitter

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PRIDE project URI

• PRIDE
  1. PXD080427
     1. Label: PRIDE project
     2. Name: Integrated Serum Metabolomics and Proteomics with Machine Learning Identifies Candidate Biomarkers for Lactation Performance in Dairy Mares