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.

Type traits and mammary health traits are important to dairy ruminant breeding because they influence animal health, milking ability, and longevity, as well as the economic sustainability of farms. The availability of the genomic sequence and a single nucleotide polymorphism chip in goats has opened up new fields of investigation to better understand the genes and mechanisms that underlie such complex traits and to be able to select them. Our objective was to perform a genome-wide association study in dairy goats for 11 type traits and somatic cell count (SCC) as proxies for mastitis resistance. A genome-wide association study was implemented using a daughter design composed of 1,941 Alpine and Saanen goats sired by 20 artificial insemination bucks, genotyped with the Illumina GoatSNP50 BeadChip (Illumina Inc., San Diego, CA). This association study was based on both linkage analyses and linkage disequilibrium using QTLmap software (http://dga7.jouy.inra.fr/qtlmap/) interval mapping was performed with the likelihood ratio test using linear regressions. Breeds were analyzed together and separately. The study highlighted 37 chromosome-wide significant quantitative trait loci (QTL) with linkage analyses and 222 genome-wide significant QTL for linkage disequilibrium, for type and SCC traits in dairy goats. Genomic control of those traits was mostly polygenic and breed-specific, suggesting that within-breed selection would be favored for those traits. Of note, Capra hircus autosome (CHI) 19 appeared to be highly enriched in single nucleotide polymorphisms associated with type and SCC, with 2 highly significant regions in the Saanen breed. One region (33-42 Mb) was significantly associated with SCC and includes candidate genes associated with response to intramammary infections (RARA, STAT3, STAT5A, and STAT5B). Another region of the CHI 19 (24.5-27 Mb) exhibited an adverse pleiotropic effect on milk production (milk, fat yield, and protein yield) and udder traits (udder floor position and rear udder attachment) that agreed with the negative genetic correlations that exist between those 2 groups of traits. These QTL were not found in the Alpine breed. In Alpine, the 2 most significant regions were associated with chest depth on CHI 6 (45.8-46.0 Mb) and CHI 8 (80.7-81.1 Mb). These results will be helpful for goat selection in the future and could lead to identification of causal mutations.

BackgroundMost rabbit production farms apply feed restriction at fattening because of its protective effect against digestive diseases that affect growing rabbits. However, it leads to competitive behaviour between cage mates, which is not observed when animals are fed ad libitum. Our aim was to estimate the contribution of direct () and social () genetic effects (also known as indirect genetic effects) to total heritable variance of average daily gain () in rabbits on different feeding regimens (FR), and the magnitude of the interaction between genotype and FR (G × FR).MethodsA total of 6264 contemporary kits were housed in cages of eight individuals and raised on full () or restricted () feeding to 75% of the ad libitum intake. A Bayesian analysis of weekly records of (from 32 to 60 days of age) in rabbits on and was performed with a two-trait model including and .ResultsThe ratio between total heritable variance and phenotypic variance () was low (<0.10) and did not differ significantly between FR. However, the ratio between (i.e. variance of relative to phenotypic variance) and was ~0.52 and 0.86 for animals on and , respectively, thus contributed more to the heritable variance of animals on than on . Feeding regimen also affected the sign and magnitude of the correlation between and , i.e. −0.5 and ~0 for animals on and , respectively. The posterior mean (posterior sd) of the correlation between estimated total breeding values (ETBV) of animals on and was 0.26 (0.20), indicating very strong G × FR interactions. The correlations between and in rabbits on and ranged from −0.47 ( on and on ) to 0.64.ConclusionsOur results suggest that selection of rabbits for under may completely fail to improve in rabbits on . Social genetic effects contribute substantially to ETBV of rabbits on but not on . Selection for should be performed under production conditions regarding the FR, by accounting for if the amount of food is limited.

Obtaining unbiased estimates of the direct-maternal genetic correlation proves far from straightforward for several reasons. Consequently, the use of such over- or underestimated correlations may introduce errors in genetic evaluation models. The objective of our study was to evaluate how the value of the direct-maternal genetic correlation affects EBV. Direct, maternal, and total breeding values were predicted for the ADG or weight at weaning for 3 different species (sheep, rabbits, and pigs) using models that differ depending on the fixed value of the direct-maternal genetic correlation (ranging from -0.9 to 0.9) as well as a model in which the correlation was estimated. The results were consistent between species. The direct-maternal genetic correlation had a greater impact on the estimated maternal genetic effects than on direct effects. The lowest correlations between maternal breeding values obtained with different models were -0.20, -0.01, and -0.72 in pigs, sheep, and rabbits, respectively, whereas for the direct breeding value, the lowest correlations were 0.45, 0.90, and 0.95 in pigs, sheep, and rabbits, respectively. The total EBV, calculated as the unweighted sum of direct and maternal genetic effects, did not differ greatly between the models, the lowest correlations between total breeding values being 0.93, 0.98, and 0.97 for pigs, sheep, and rabbits, respectively. Given the uncertainty associated with estimating the direct-maternal genetic correlation, setting its value to 0 in genetic evaluation models appears to be a good compromise.

Background Radiotherapy (RT) is currently considered the treatment of choice for presumed canine intracranial gliomas. However, variable therapeutic responses are described, due to heterogeneous populations and different radiation methods or protocols. Only one study dedicated to intracranial suspected glioma highlighted prognostic criteria. Determination or confirmation of specific clinical and imaging prognostic factors may guide the therapeutic management of these tumours. The objectives were to provide data on long-term clinical outcome (including quality of life, QoL) and to determine specific prognostic factors associated with survival time. We report a single-institution retrospective study, including all dogs with suspected symptomatic primary solitary intracranial glioma, treated with a complete uniform fractionated megavoltage radiation protocol of 15x3Gy over 5 weeks, between January 2013 and February 2019. Thirty-eight client-owned dogs were included. Medical records were retrospectively evaluated for median overall survival time (MST), clinical and imaging responses. Prognostic factors on survival were researched in terms of signalment, clinical presentation, tumour imaging characteristics and response following RT. Finally, the RT’s impact on the dogs’ clinical signs and Qol were evaluated by the owners. Results The disease-specific MST was 698 days (95% CI: 598–1135). Survival at 1 and 2 years were respectively 74.2 ± 7.4% and 49.0 ± 9.8%. Initial clinical signs were related to survival, as well as tumour characteristics such as cystic-pattern, mass effect and Tumour/Brain volume ratio. No significant adverse effect or radiotoxicity was observed. Conclusions RT appears as a safe and effective treatment for canine intracranial gliomas, allowing long-term tumour control, improvement of life’s quality and management of associated clinical signs. The initial clinical signs and MRI characteristics (Tumour/Brain volume ratio, cyst-like lesion and mass effect) may help predict the prognosis.

Selection for disease resistance is a powerful way to improve the health status of herds and to reduce the use of antibiotics. The objectives of this study were to estimate 1) the genetic parameters for simple visually assessed disease syndromes and for a composite trait of resistance to infectious disease including all syndromes and 2) their genetic correlations with production traits in a rabbit population. Disease symptoms were recorded in the selection herds of 2 commercial paternal rabbit lines during weighing at the end of the test (63 and 70 d of age, respectively). Causes of mortality occurring before these dates were also recorded. Seven disease traits were analyzed: 3 elementary traits visually assessed by technicians on farm (diarrhea, various digestive syndromes, and respiratory syndromes), 2 composite traits (all digestive syndromes and all infectious syndromes), and 2 mortality traits (digestive mortality and infectious mortality). Each animal was assigned only 1 disease trait, corresponding to the main syndrome ( = 153,400). Four production traits were also recorded: live weight the day before the end of test on most animals ( = 137,860) and cold carcass weight, carcass yield, and perirenal fat percentage of the carcass on a subset of slaughtered animals ( = 13,765). Records on both lines were analyzed simultaneously using bivariate linear animal models after validation of consistency with threshold models applied to logit-transformed traits. The heritabilities were low for disease traits, from 0.01 ± 0.002 for various digestive syndromes to 0.04 ± 0.004 for infectious mortality, and moderate to high for production traits. The genetic correlations between digestive syndromes were high and positive, whereas digestive and respiratory syndromes were slightly negatively correlated. The genetic correlations between the composite infectious disease trait and digestive or respiratory syndromes were moderate. Genetic correlations between disease and production traits were favorable. Our results indicate that it is possible to select rabbits using visually assessed disease syndromes without the need for a trade-off between health and production traits. Using a composite criterion that includes all infectious syndromes is easy to implement and heritable and is, therefore, a promising way to improve the general disease resistance in livestock species.

Artificial inseminations (n 5 678 168) recorded during 5 years in five French artificial insemination (AI) centres (2 'Lacaune', 1 'Manech tê te rousse', 1 'Manech tê te noire' and 1 'Basco bé arnaise') 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.

For years, animal selection in livestock species has been performed by selecting animals based on genetic inheritance. However, evolutionary studies have reported that nongenetic information that drives natural selection can also be inherited across generations (epigenetic, microbiota, environmental inheritance). In response to this finding, the concept of inclusive heritability, which combines all sources of information inherited across generations, was developed. To better predict the transmissible potential of each animal by taking into account these diverse sources of inheritance and improve selection in livestock species, we propose the “transmissibility model.” Similarly to the animal model, this model uses pedigree and phenotypic information to estimate variance components and predict the transmissible potential of an individual, but differs by estimating the path coefficients of inherited information from parent to offspring instead of using a set value of 0.5 for both the sire and the dam (additive genetic relationship matrix). We demonstrated the structural identifiability of the transmissibility model, and performed a practical identifiability and power study of the model. We also performed simulations to compare the performances of the animal and transmissibility models for estimating the covariances between relatives and predicting the transmissible potential under different combinations of sources of inheritance. The transmissibility model provided similar results to the animal model when inheritance was of genetic origin only, but outperformed the animal model for estimating the covariances between relatives and predicting the transmissible potential when the proportion of inheritance of nongenetic origin was high or when the sire and dam path coefficients were very different.