[Show abstract][Hide abstract] ABSTRACT: 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.
[Show abstract][Hide abstract] ABSTRACT: PhénoFinlait gathers together the actors of dairy industries including cattle, sheep and goats; around a common goal: monitoring milk Fatty Acid (FA) and protein composition. Quantifying FA and proteins by a reliable and cheap large-scale method is necessary before identifying the ways to adapt this composition to consumers’ and dairy processors’ demand. The objectives of the project were i) to characterize precisely the milk composition, ii) to phenotype and genotype a large population of females all over France, and iii)
to identify the genetic and feeding levers to control this composition. Mid infrared (MIR) spectrometry has been chosen to quantify milk FA and proteins. With this method, the four caseins, the two main whey proteins, and 15 to 27 FA can be quantified routinely and precisely. A large-scale data collection has been carried out in more than 1,500 commercial dairy cattle, goat and sheep farms. Dairy production, MIR spectra, female physiological stages, and composition of the diet were collected. More than 12,000 cows, goats and ewes were also genotyped. Finally, more than 800,000 representative data are stored in a database for the study of the genetic determinism of milk FA and protein composition, and the impact of husbandry.
[Show abstract][Hide abstract] ABSTRACT: Abstract Text: French dairy sheep breeding schemes require a significant number of alive AI rams due to the fresh semen constraints. This number may be reduced significantly (by 25% to 45%) in the case of genomic selection (GS). For the AI rams, in a GS design, a genomic selection rate (r1) at 3-month-old, completed by a progeny selection rate (r2) at 2.5-year-old, is replacing the only progeny selection rate (r) at 2.5-year-old performed in a classical scheme. Compared to actual optimum (r) of 0.5, r1 and r2values of respectively 0.3 and 0.8 allow an annual genetic gain increased by 15%, at same breeding cost of the AI rams. Genomic selection will be implemented in 2015 in Lacaune and in a near future in Manech breed.
Dairy sheep Lacaune, Manech
Genomic breeding scheme
10th World Congress on Genetics Applied to Livestock Production; 08/2014
[Show abstract][Hide abstract] ABSTRACT: Abstract Text: Genomic selection opens new perspectives for breeding programs of dairy ruminants. In France, several projects have enabled the creation of reference populations in dairy sheep and goats. Early studies have shown that the reliability of genomic evaluations using a GBLUP method in these species is lower than in Holstein dairy cattle breed. The single-step approach gives best predictions for candidates at birth (genomic evaluation accuracy obtained by cross validation for milk yield of 0.47 in Lacaune dairy sheep and 0.43 in goats’ breeds). The multi-breed approach is effective in goats by blending Alpine and Saanen breeds, but not in sheep. Finally, switching to genomic selection is planned in Lacaune dairy sheep and is under consideration for other sheep breeds. In goats, inclusion of major genes in genomic evaluations should be explored before switching to genomic breeding programs.
10th World Congress on Genetics Applied to Livestock Production; 08/2014
[Show abstract][Hide abstract] ABSTRACT: Genomic selection opens new perspectives for breeding programs of dairy ruminants. In France, several projects have enabled the creation of reference popula-tions in dairy sheep and goats. Early studies have shown that the reliability of genomic evaluations using a GBLUP method in these species is lower than in Holstein dairy cattle breed. The single-step approach gives best predictions for candidates at birth (genomic evaluation accuracy ob-tained by cross validation for milk yield of 0.47 in Lacaune dairy sheep and 0.43 in goats' breeds). The multi-breed approach is effective in goats by blending Alpine and Saanen breeds, but not in sheep. Finally, switching to ge-nomic selection is planned in Lacaune dairy sheep and is under consideration for other sheep breeds. In goats, inclu-sion of major genes in genomic evaluations should be ex-plored before switching to genomic breeding programs.
10 th World Congress of Genetics Applied to Livestock Production, Vancouver, Canada; 08/2014
[Show abstract][Hide abstract] ABSTRACT: The expected increase of global demand for milk and meat opens opportunities for the development of ruminant production sectors but at the same time the french farming systems are characterized by very diverse systems and lower productivity and competititveness comparared to other production area in Europe. The ruminant sectors faces strong criticims owing to their impact on the environment and human health and the attractivity for livestock production is decreasing. What are the ways to improve the competitiveness of french farms? How can we reconcile economic, environmental and social performances? What are the conditons to meet for developping high-performance ruminant production systems? These questions were addressed to INRA by the General Commission on Strategy and Foresight (CSPF) to determine the potential for development of a high performing French agriculture. We report here the main results in concern with ruminant livestock farming
[Show abstract][Hide abstract] ABSTRACT: This international symposium included a lot of presentation by different specialists of main countries involved in dairy sheep management and breeding. This presentation is the french one.
[Show abstract][Hide abstract] ABSTRACT: 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.
[Show abstract][Hide abstract] ABSTRACT: Artificial inseminations (n = 678 168) recorded during 5 years in five French artificial insemination (AI) centres (2 'Lacaune', 1 'Manech tête rousse', 1 'Manech tête noire' and 1 'Basco béarnaise') were analysed to determine environmental and genetic factors affecting the insemination results. Analyses within centre-breed were performed using a linear model, which jointly estimates male and female fertility. This model combined four categories of data: the environmental effects related to the female, those related to the male, the non-sex-specific effects and finally the pedigree data of these males and females. After selection, the environmental female effects considered were age, synchronisation (0/1) on the previous year, total number of synchronisations during the female reproductive life, time interval between previous lambing and insemination, already dry or still lactating (0/1) when inseminated, and milk quantity produced during the previous year expressed as quartiles intra herd * year. The environmental male effects were motility and concentration of the semen. The non-sex-specific effects were the inseminator, the interaction herd * year nested within the inseminator, considered as random effects and the interaction year * season considered as a fixed effect. The main variation factors of AI success were relative to non-sex-specific effects and to female effects. Heritability estimates varied from 0.001 to 0.005 for male fertility and from 0.040 to 0.078 for female fertility. Repeatability estimates varied from 0.007 to 0.015 for male fertility and from 0.104 to 0.136 for female fertility. These parameters indicate that genetic improvement of AI results through a classical polygenic selection would be difficult. Moreover, in spite of the large quantity of variation factors fitted by the joint model, a very large residual variance remained unexplained.
[Show abstract][Hide abstract] ABSTRACT: 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.