Skip to main content
ARS Home » Research » Publications at this Location » Publication #303714

Title: Fertility prediction of frozen boar sperm using novel and conventional analyses

item DAIGNEAULT, BRADFORD - University Of Illinois
item MCNAMARA, KELLI - University Of Illinois
item Purdy, Phil
item RODRIGUEZ_ZAS, SANDRA - University Of Illinois
item KRISHER, REBECCA - University Of Illinois
item KNOX, ROBERT - University Of Illinois
item MILLER, DAVID - University Of Illinois

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 4/14/2014
Publication Date: 7/19/2014
Citation: Daigneault, B.W., Mcnamara, K.A., Purdy, P.H., Rodriguez_Zas, S.L., Krisher, R.L., Knox, R.V., Miller, D.J. 2014. Fertility prediction of frozen boar sperm using novel and conventional analyses. Meeting Abstract. Society for the Study of Reproduction, Grand Rapids, MI, July 19-23, 2014.

Interpretive Summary:

Technical Abstract: Frozen-thawed boar sperm is seldom used for artificial insemination (AI) because fertility is lower than fresh or cooled semen. Despite the many advantages of AI including reduced pathogen exposure and ease of semen transport, cryo-induced damage to sperm usually results in decreased litter sizes and pregnancy rates. Conventional laboratory evaluation of frozen-thawed sperm may not provide accurate estimates of fertility. Identifying sperm traits that predict fertility would help select those semen samples that would produce adequate litter sizes and pregnancy rates and propagate industry use of frozen boar sperm. Our objective was to identify traits of cryopreserved sperm that are related to boar fertility for AI through the use of novel and traditional laboratory analyses. Semen from 14 boars of several breeds was cooled to 15°C for overnight shipping prior to freezing. Semen was thawed and motility was estimated and confirmed using Computer Automated Sperm Assessment (CASA). Sperm viability and acrosome integrity were measured at 0, 30 and 60 min post-thaw. In addition to traditional analyses, each sperm sample was tested by IVF in two to three independent replicates and fertilization, cleavage and blastocyst development were recorded. As an assessment of sperm reservoir formation, a sperm-oviduct binding assay was used to compare the number of sperm bound to epithelial aggregates harvested from gilt isthmus. Additionally, a competitive zona binding assay using two distinct fluorophores for sperm identification was employed to measure the number of sperm from each boar bound to the zona. Frozen sperm from the same ejaculates subjected to laboratory analyses were used to determine boar fertility. Fertility was measured by AI of mature gilts using 4.0 x 106 total sperm from one boar at 24 h and a second boar at 36 h after the onset of estrus and calculated as the percentage of the litter sired by each boar. AI order was reversed in consecutive replicates so that order of insemination was evenly distributed among boar comparisons. Reproductive tracts were harvested at ~ 32 d after AI and the number of fetuses were recorded and sampled for paternity identification using microsatellite markers. The least-squared means (LSM) of each laboratory evaluation were modeled by boar using multiple regression analyses to test their collective values in predicting fertility. The model generated was highly predictive of fertility (P <0.001, r2 = 0.87) and included 5 traits; acrosome compromised sperm (0 and 30 min), percent live sperm (0 min), percent total motility (30 min) and the number of zona bound sperm. An additional model in which fertility was assessed by the number of piglets sired by boar also predicted fertility (P <0.05, r2 = 0.57) and shared many of the same traits including percent live sperm, motility and the number of sperm bound to zona. These models indicate that the fertility of cryopreserved boar sperm can be predicted using both traditional and novel laboratory assays that consider multiple functions of sperm and offer a