-The aim of this study was to assess the application of a cryopreservation program to preserve two selected rabbit lines. One of them was selected by litter size at weaning, line V (Synthetic breed). The second, line R (synthetic breed), was selected by growth rate. In this study, embryos were collected, from donor does belonging to the 7th and 15th generations of lines R and V, respectively, were vitrified and were stored from 1992-1993. Those embryos from donor does belonging to the 17th and 21st generations of lines R and V respectively, were vitrified and sotred from 1998-1999. Embryo transfers were carried out in 1999. Morphologically normal embryos at the morulae stage were cryopreserved by vitrification in a 2.8 M dimethyl-sulfoxide + 3.5 M ethyleneglycol + 0.3 g·L -1 bovine serum albumine in Dulbecco phosphate buffered saline solution. The main problem in the cryopreservation program was the low embryo production efficiency: significant differences were obtained in recovery efficiency between lines and line R showed the lowest proportion of donor does with 55% (at least 4 normal embryos) vs. 72% in line V. However, after transfer in recipient does of line V, the fertility rate at birth (81%), the rate of alive born by pregnant recipients (43%) and the number of males and does with offspring (9 to 18 different males, 12 to 32 females) enabled the different generations from each line to be re-established and studies on the selection process genetic gain to be developed. cryopreservation / embryo / line / rabbit

Aim: The objective of this work was to study the growth performance, slaughter traits, meat quality, and metabolic profile in rabbits of local Algerian population and a synthetic line. Materials and Methods: In total, 120 weaned rabbits were used (60 per group). Growth traits were recorded from weaning (35 days) to slaughter (91 days). At slaughter, carcass traits, meat quality, and metabolic profiles were measured. Results: The synthetic line showed heavier total weight and faster daily weight gain than the local population (+15% and +19%, respectively), better feed conversion (3.92 vs. 4.81 g/g), and heavier weight of cold carcass, and perirenal fat (+15%). No differences were found between the two groups in dressing out percentage, muscular pH, weight of liver, or scapular fat. Wider intestinal villi were found in the synthetic line (+20%, p<0.0001) allowing better absorption surface in this line. The synthetic line also showed higher fat content (3.41% vs. 2.22%, p<0.0001) in the meat and lower protein content (22.02% vs. 18.98%, p=0.0002). Glucose level was 19% higher in the local population than in the synthetic line. Conclusion: The synthetic line is well adapted to the local conditions of Algeria. This line has shown better growth, daily gain, and feed conversion, due to its better intestinal absorption surface.

The objective of this study was to obtain heritability estimates for reproductive (litter size at birth, number born alive, litter size at weaning) and growth traits (individual weaning weight, individual weight at the end of the fattening period), then determine the genetic correlation between them in a synthetic rabbit line. A total of 805 females, 3242 parities, and 18 472 growth records were measured from 2006 to 2017. A pentavariate animal model was used with reproductive and growth traits. Heritability ranged from 0.025 to 0.126 for reproductive traits and from 0.033 to 0.059 for growth traits. These traits showed a large coefficient of variation (from 32% to 56% for reproductive traits and from 21% to 28% for growth traits). The repeatability of reproductive traits was low and the common litter effect for growth traits was the most important component of total variance. The genetic and phenotypic correlations between reproductive and growth traits were high and negative, especially with weight at weaning (−0.848, −0.922, and −0.854 for litter size at birth, number born alive, and litter size at weaning, respectively). In conclusion, because of the high negative correlation between reproductive and growth traits, both reproductive and growth traits should be selected in independent lines and the response to selection should be due mainly to the high coefficient of variation of the traits.

A divergent selection experiment for environmental variance of litter size variance was carried out in rabbits over thirteen generations. The aim of this study was to evaluate the inflammatory response in the two lines of the experiment, in order to analyse the effect of selection on susceptibility to diseases after challenging to stressful situations, such as 24 h after the first delivery. A total of 78 females were used in this study, 39 from each line. The line selected for litter size heterogeneity (the high line) showed lower white blood leukocyte count (WBC; −0.87 × 103/µL), lower percentage of basophils (−0.11%), higher concentration of TNF-α (+13.8 pg/mL), and greater concentration of CRP (+38.1 µg/mL) than the line selected for litter size homogeneity (the low line). The high line had also higher concentrations of bilirubin, cholesterol, gamma-glutamyl transferase (GGT) and alkaline phosphatase (ALP) compared to the low line (difference between lines were +0.08 µmol/L, +0.14 µmol/L, +0.35 U/L and +2.4 U/L, respectively). The high line showed higher inflammatory response than the low line, in accordance with a larger susceptibility to infectious disorders. In conclusion, the line selected to increase litter size environmental variability seems to have poor capacity coping with environmental stressors. Therefore, selection for litter size environmental variability can be a useful way to improve animal welfare.

This note provides a description of software that allows to fit Bayesian genetically structured variance models using Markov chain Monte Carlo (MCMC). The gsevm v.2 program was written in Fortran 90. The DOS and Unix executable programs, the user's guide, and some example files are freely available for research purposes at http://www.bdporc.irta.es/estudis.jsp. The main feature of the program is to compute Monte Carlo estimates of marginal posterior distributions of parameters of interest. The program is quite flexible, allowing the user to fit a variety of linear models at the level of the mean and the logvariance.