Opportunities and limits of commercial farm data to study the genetic determinism of feed efficiency throughout lactation in dairy sheep.

The collective economic and environmental interest of the whole dairy sheep sector is to reduce feed costs and the negative impact of milk production on the environment. Thus, this study focused on the characterisation and genetic selection potential of feed efficiency in the Lacaune breed. Estimates for feed efficiency in dairy ewes are limited, mainly due to a lack of individual feed intake measurements in the sheepfold or in the pasture. We estimated the genetic parameters for two approximated (not entirely based on individual data) feed efficiency traits (lactation feed conversion ratio (LFCR) and residual energy intake (REI)) and daily milk yield (DMY) at different stages of lactation and throughout lactation. The accuracy of the efficiency traits was first evaluated on samples from Lacaune dairy ewes that were monitored individually, especially for their feed intake. Then, feed efficiency estimation methods were applied on eight commercial farms corresponding to 4 680 Lacaune dairy ewes over two milk lactations (30 854 records). Animals were collectively (for a large part of feed intake) or individually (for milk performance and dynamics of body fat reserves) monitored at different lactation stages. The heritabilities of LFCR and REI were estimated over lactations at 0.10 ± 0.01 and 0.11 ± 0.01, respectively. High genetic correlations were observed between the two efficiency traits and milk production traits, with a genetic correlation between LFCR and DMY of 0.74 ± 0.04 and between REI and DMY of -0.79 ± 0.04. A strong influence of environmental factors such as farm, year of milk production and lactation stage affected the genetic link between REI and milk production traits. Efficiency values observed in early lactation when animals were bred in the sheepfold were less genetically correlated with values obtained later in lactation when animals were grass-fed. However, individual characterisation of feed efficiency remains difficult due to the collective feeding context in dairy ewe farms.

Genetic correlation between female fertility and milk yield in Lacaune sheep.

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.

Environmental and genetic variation factors of artificial insemination success in French dairy sheep.

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.

Genetic analysis of male and female fertility after artificial insemination in sheep: comparison of single-trait and joint models.

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.

Genetic parameters for milk somatic cell scores and relationships with production traits in French Lacaune dairy sheep.

Records from 94,445 and 45,499 French Lacaune dairy ewes in first and second lactations, respectively, were used to estimate genetic parameters for somatic cell scores. Somatic cell count data came from an extensive recording scheme and sample testing that began in 1999 using the flocks enrolled in the official milk recording system. Somatic cell count data were from 2 to 4 test days per lactation. Lactation average and single test-day somatic cell scores were considered in multitrait sire models. The heritability estimate of lactation somatic cell score was close to 0.13 and similar for first and second parity. Heritabilities of somatic cell scores increased from first to fourth test day (from 0.07 to 0.11 in first lactation and from 0.05 to 0.13 in second lactation). Genetic correlations between somatic cell scores were high, usually more than 0.91, but lower between first test day and later test days in first lactation (0.64 to 0.88). The genetic correlations between lactation somatic cell score and milk yield, between lactation somatic cell score and fat content, and between lactation somatic cell score and protein content were 0.18, 0.04, and 0.03 in first lactation, respectively. The genetic antagonism between test day somatic cell score and milk yield measured in first lactation increased from beginning to the end of the lactation (0.05 to 0.23). This antagonism was slightly lower for somatic cell score in second lactation (from 0.09 to 0.14, and 0.08 for lactation mean). Environmental correlations in first lactation between lactation somatic cell score and milk yield, between lactation somatic cell score and fat content, and between lactation somatic cell score and protein content were -0.18, 0.13, and 0.30, respectively.