AUTHOR=Su Xiaohu , Zhu Yijing , Guo Zirong , Qiu Shuang , Liu Quan , Bian Chao , Chen Liqiang , Yamashiro Hideaki , Liu Guangnan , Zhang Zhanwen , Zhang Liguo , Tong Bin 

TITLE=Identification of embryonic yield-related serum biomarkers using proteomic analysis in ovine superovulation

JOURNAL=Frontiers in Veterinary Science

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/veterinary-science/articles/10.3389/fvets.2025.1675287

DOI=10.3389/fvets.2025.1675287

ISSN=2297-1769

ABSTRACT=Superovulation is an efficient technology for the propagation of excellent livestock. Blood proteins other than reproductive hormones might be related to the outcome of superovulation. In this study, to identify potential protein biomarkers, the serum proteome of superovulation donor ewes was analyzed. The ewes were classified into spontaneous estrus (SE) and induced estrus (IE) groups, and their blood samples were collected before the first follicle-stimulating hormone (FSH) injection. Then, high (HEY) and low embryonic yield (LEY) populations of each group were identified based on the total embryonic number. Five donors from each population were selected for serum proteomic analysis. Finally, partially differentially expressed proteins (DEPs) were verified using the enzyme-linked immunosorbent assay (ELISA). Averages of 18.6 ± 12.4 and 14.4 ± 8.7 total embryos were collected from the SE and IE groups, respectively. We identified 13 and 12 DEPs in the SE and IE groups, respectively, after the comparison of the HEY and LEY populations of both groups. Furthermore, the ELISA revealed that three DEPs—ACAA1, B2MG, and ADAMTS13—in the SE group and two DEPs—B2MG and APO-F—in the IE group exhibited a significant linear correlation with the total number of embryos. This study showed that ACAA1, B2MG, ADAMTS13, and APO-F could be used as potential biomarkers for donor selection in ovine superovulation. Our results provide novel insights into the relationship between blood proteins and ovarian function and offer a theoretical basis for the prediction of superovulation outcomes.