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The study was to focus on the relationship between wave motion (mass sperm motility, measured by a mass sperm motility score, manually assessed by artificial insemination (AI) center operators) and fertility in male sheep. A dataset of 711,562 artificial inseminations performed in seven breeds by five French AI centers during the 2001-2005 time period was used for the analysis. Factors influencing the outcome of the insemination, which is a binary response observed at lambing of either success (1) or failure (0), were studied using a joint model within each breed and AI center (eight separate analyses). The joint model is a multivariate model where all information related to the female, the male and the insemination process were included to improve the estimation of the factor effects. Results were consistent for all analyses. The male factors affecting AI results were the age of the ram and the mass motility. After correction for the other factors of variation, the lambing rate increased quasi linearly from three to more than ten points with the mass sperm motility score depending on the breed and the AI center. The consistency of the relationship for all breeds indicated that mass sperm motility is predictive of the fertility resulting when sperm are used from a specific ejaculate. Nonetheless, predictability could be improved if an objective measurement of mass sperm motility were available as a substitute for the subjective scoring currently in use in AI centers., (Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.)

A total of 416,670 lactations for 189,101 ewes from 3,603 sires and distributed across 1,978 herd-year groups were used to estimate genetic and environmental parameters of standardized milk yield (SMY(T)), fertility in ewe lambs (PR(1)), and fertility in adult ewes (PR(A)). Parameters were estimated with a multiple-trait sire linear model. Heritabilities for SMY(T), PR(1), and PR(A) were 0.27 (0.009), 0.04 (0.004), and 0.05 (0.004), respectively. These results were in accordance with the literature. The genetic correlation between PR(1) and PR(A) was 0.55, indicating that fertility is not the same trait in ewe lambs and adult ewes. The genetic correlation between milk yield and lamb fertility was not significantly different from zero. The genetic correlation between milk yield and fertility in adult ewe (-0.23) was in the range of antagonistic correlations reported in dairy cattle. Consequently, these results show that selection for milk yield can induce an indirect decrease in fertility. Nevertheless, no phenotypic decrease in fertility in artificial insemination matings has been observed in this population. This is the first time that correlation between milk yield and fertility is reported in sheep and further investigations are needed to confirm this result.

The outcome of an insemination depends on male and female fertility. Nevertheless, few studies have incorporated genetic evaluation of these 2 traits jointly. The aim of this work was to compare genetic parameter estimates of male and female fertility defined as success or failure to artificial insemination (AI), using 8 different models. The first 2 models were simple repeatability models studying fertility of one sex and ignoring any information of the other. Models 3 and 4 took into account the information of the other sex by the inclusion of its random permanent environmental effect, whereas models 5 and 6 included fixed effects of the other sex. Models 7 and 8 were joint genetic evaluation models of male and female fertility ignoring or considering genetic correlation. Data were composed of 147,018 AI of the Manech Tête Rousse breed recorded from 2000 to 2004 corresponding to 79,352 ewes and 963 rams. The pedigree file included 120,989 individuals. Variance component estimates from the different models were quite similar; heritabilities varied from 0.050 to 0.053 for female fertility and were near 0.003 for male fertility. Correlations among estimated breeding values in the same sex using different models were higher than 0.99. The genetic correlation between male and female fertility was not significantly different from 0. These results show that for French dairy sheep with extensive use of AI, estimation of breeding values for male and female fertility might be implemented with quite simple models.