Acta Veterinaria et Zootechnica Sinica ›› 2021, Vol. 52 ›› Issue (11): 3118-3125.doi: 10.11843/j.issn.0366-6964.2021.011.013

• ANIMAL BIOTECHNOLOGY AND REPRODUCTION • Previous Articles     Next Articles

Screen of Candidate Biomarkers for Different Pregnancy Status of Cows Based on UHPLC-QTOF-MS Metabolomics

LUO Fang, TAO Jinzhong*   

  1. Department of Animal Science, School of Agriculture, Ningxia University, Yinchuan 750021, China
  • Received:2021-02-16 Online:2021-11-23 Published:2021-11-24

Abstract: This study aimed to select candidate biomarkers for different pregnancy status of cows on 17 days after artificial insemination. Healthy Holstein dairy cow with a weight of (550±50)kg and similar body condition scores in a dairy farm in Ningxia was used as the test object. After synchronization of estrus, blood was collected from tail vein before morning feeding on the 17th day after artificial insemination. Pregnancy status of cows was diagnosed by pedometer and B-ultrasound instrument at the later stage. According to the diagnosis results, cows were divided into pregnant group (group A, n=12) and non-pregnant return to estrus group (group B, n=24). Blood samples from the two groups were collected for analyzing metabolic profile and metabolites change. Principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) showed that the plasma metabolic profile of group A and B were significantly changed. A total of 8 differential metabolites with area under the ROC curve (AUC)> 0.8 were selected. Ala-Leu, Glycine, L-Proline, L-Norleucine, DL-Phenylalanine, Sarcosine, Pyrrole-2-carboxylic acid and Val-Met were expected to be the different metabolites for the identification of pregnancy cows (group A) and non-pregnant return to estrus cows (group B). In conclusion, the 8 metabolites in plasma could be used as potential biomarkers in the pregnancy recognition period, which could provide new ideas for early pregnancy diagnosis.

Key words: Holstein cows, pregnancy recognition, metabolomics, biomarkers

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