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Proteomic fertility markers in ram sperm
Mustafa Hitit1, Mehmet Özbek2, Serife Ayaz-Guner3
1Department of Genetics, Faculty of Veterinary Medicine, Kastamonu University, Kastamonu, Turkey.
Animal Reproduction Science
|November 25, 2021
Summary
Researchers identified distinct protein profiles in ram sperm to predict fertility. This proteomic analysis offers potential new markers for evaluating semen quality and improving sheep reproduction efficiency.
Area of Science:
- Animal Science
- Reproductive Biology
- Proteomics
Background:
- Accurate ram fertility estimation is crucial for sheep farming efficiency and profitability.
- Current methods for predicting ram fertility lack precision.
- Understanding sperm proteome differences can reveal fertility indicators.
Purpose of the Study:
- To identify proteomic profiles of ram sperm with contrasting fertility phenotypes.
- To explore potential protein markers for semen quality and fertilizing capacity.
Main Methods:
- Sperm samples were collected from mature rams categorized into greater-fertility (GF) and lesser-fertility (LF) groups based on pregnancy rates.
- Proteomics assessment was performed using Label-free Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (LC-MS/MS).
- Proteins were identified and quantified to compare abundance between GF and LF ram sperm.
Main Results:
- A total of 997 proteins were identified, with 57 unique to GF and 93 unique to LF sperm.
- 190 differentially abundant proteins were found, with 124 more abundant in GF and 66 in LF rams.
- Significant differences in Gene Ontology (GO) and pathway terms were observed between GF and LF sperm proteomes, suggesting functional implications for fertility.
Conclusions:
- Differential abundance of sperm proteins between greater-fertility and lesser-fertility rams indicates functional impacts on male fertility.
- The study highlights potential protein markers for evaluating semen quality and estimating ram sperm fertilizing capacity.
- Proteomic profiling offers a promising approach to enhance ram fertility prediction in sheep farming.
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