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Updated: Nov 15, 2025

Evaluation of Intracellular Location of Reactive Oxygen Species in Solea Senegalensis Spermatozoa
Published on: March 11, 2018
Spermatozoal transcripts associated with oxidative stress and mitochondrial membrane potential differ between high-
Kaustubh Kishor Saraf1, Arumugam Kumaresan1, Manish Kumar Sinha1
1Theriogenology Laboratory, Veterinary Gynaecology and Obstetrics, Southern Regional Station of ICAR- National Dairy Research Institute, Bengaluru, Karnataka, India.
Abstract:
The presence of various forms of RNAs having roles in fertilisation and early embryonic development is well documented in mammalian spermatozoa. In the present study, using Agilent microarray platform, we compared sperm mRNA expression profiles between high- and low-fertile crossbred bulls with normal semen parameters. Microarray data acquisition and analysis were performed using GeneSpring GX version software, wherein spermatozoa from high-fertile bulls were kept as control while spermatozoa from low-fertile bulls were considered as treatment group. A total of 6,238 transcripts were detected in crossbred bull spermatozoa; 559 transcripts (>1.5-fold) were differentially regulated between high- and low-fertile bulls. Functional annotation has categorised these transcripts into biological process, cellular, and molecular functions. It was observed that transcripts associated with oxidation reduction process (p = .003), mitochondrial membrane potential (p = .03), were significantly down-regulated while transcripts associated with apoptosis (p = .04) were up-regulated in low-fertile spermatozoa. The dysregulated genes were involved in important cellular pathways including oxidative phosphorylation (p = .002), oestrogen signalling (p = .002), Wnt signalling (p = .035), cGMP-PKG signalling (p = .007) and MAPK signalling (p = .032) pathways. Collectively, the present study discovered profound discrepancies in sperm mRNA expression between high- and low-fertile crossbred bulls, with potential possibilities for their use in fertility prediction.
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