Motility Assessment of Ram Spermatozoa.
BIOLOGY 2022;
11:biology11121715. [PMID:
36552225 PMCID:
PMC9774426 DOI:
10.3390/biology11121715]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 11/11/2022] [Accepted: 11/22/2022] [Indexed: 11/29/2022]
Abstract
For successful fertilisation to occur, spermatozoa need to successfully migrate through the female reproductive tract and penetrate the oocyte. Predictably, poor sperm motility has been associated with low rates of fertilisation in many mammalian species, including the ram. As such, motility is one of the most important parameters used for in vitro evaluation of ram sperm quality and function. This review aims to outline the mechanical and energetic processes which underpin sperm motility, describe changes in motility which occur as a result of differences in sperm structure and the surrounding microenvironment, and assess the effectiveness of the various methods used to assess sperm motility in rams. Methods of subjective motility estimation are convenient, inexpensive methods widely used in the livestock industries, however, the subjective nature of these methods can make them unreliable. Computer-assisted sperm analysis (CASA) technology accurately and objectively measures sperm motility via two-dimensional tracing of sperm head motion, making it a popular method for sperm quality assurance in domesticated animal production laboratories. Newly developed methods of motility assessment including flagellar tracing, three-dimensional sperm tracing, in vivo motility assessment, and molecular assays which quantify motility-associated biomarkers, enable analysis of a new range of sperm motion parameters with the potential to reveal new mechanistic insights and improve ram semen assessment. Experimental application of these technologies is required to fully understand their potential to improve semen quality assessment and prediction of reproductive success in ovine artificial breeding programs.
Collapse