Genetic parameter estimates for semen production traits and growth rate of a paternal rabbit line

Association of GH gene polymorphism with growth and semen traits in rabbits

<p>Although growth hormone (<em>GH</em>) gene mutations are described in several species, the studies concerning their variabilities and associations with economic traits in rabbits are scarce, particularly associations with semen traits. A total of 149 rabbit bucks from five populations (V-line=36, Moshtohor line=28, APRI line=42, cross ½A½M=23, and Gabali=20) were used in the present study to identify polymorphism of c.-78 C&gt;T single nucleotide polymorphism (SNP) of <em>GH</em> gene among these populations and to investigate the association of <em>GH</em> gene polymorphism with body weight (BW), daily weight gain (DG) and semen traits. DNA was extracted from blood samples for genotyping of c.-78 C&gt;T SNP of <em>GH</em> gene based on polymerase chain reaction with the restriction fragment length polymorphism (PCR-RFLP) technique. The genetic diversity of SNP C&gt;T of <em>GH</em> gene was assessed in terms of genotypic and allelic frequencies, effective number of alleles (Ne), observed (Ho) and expected (He) heterozygosity, Hardy-Weinberg equilibrium (HWE), reduction in heterozygosity due to inbreeding (F_IS) and polymorphism information content (PIC). Three genotypes of TT, CC and TC of PCR product of 231 bp of <em>GH</em> gene were detected and all the populations were in HWE in terms of <em>GH</em> gene. The highest Ne was obtained for the Moshtohor line (1.978), while the lowest allelic numbers were obtained for V-line (1.715) and Gabali breed (1.800). The highest genotype frequency of <em>GH</em> gene was 0.48 in TT genotype of V-line, 0.21 in CC genotype of Moshtohor line, 0.67 and 0.56 in TC genotype of ½A½M and Gabali rabbits (<em>P</em>&lt;0.05). The highest frequency for C allele was recorded by Moshtohor line (0.45) and the lowest frequency by Gabali (0.32). The genetic diversity scores for <em>GH</em> gene were intermediate (Ho=0.551, He=0.471, PIC=0.358). The values of Ho ranged from 0.444 in V-line to 0.667 in ½A½M cross, while the values of He were 0.425 in V-line and 0.508 in Moshtohor line. The values of PIC were moderate and ranged from 0.332 in V-line to 0.375 in M-line. The highest F_IS was observed in Moshtohor line (0.042) and the lowest value was observed in ½A½M cross (–0.413). The CT genotype of <em>GH</em> gene showed the highest and significant values for body weights at 4, 8, 10 and 12 wk (542, 1131, 1465 and 1861 g) and daily gains at intervals of 4-6 and 8-10 wk (23.1 and 26.5 g). Additionally, the CT genotype recorded the highest and significant values for volume of ejaculate (1.1 mL), sperm motility (57.6%), live sperm (85.6%), normal sperm (93.1%) and sperm concentration in semen (611×106/mL), along with the lowest and significant values for dead sperms (14.4%) and abnormal sperms (6.9%).</p>

Effect of early development on semen parameters and lifespan of rabbit males selected by high growth rate

Life history theory suggests that different body development dynamics may influence survival and future reproductive performance of organisms. The present work studied how these dynamics could influence seminal traits and lifespan of rabbit males selected for growth rate and intended for AI. To achieve this goal, a total of 550 rabbit males were controlled from birth, evaluated both during the testing phase (four consecutive weeks after reaching 147 days of life) and the productive phase (377 of them from the end of the testing phase until 2 years of life). In order to obtain individuals with different body development dynamics, we pre-selected males based on their live weight (LW) at 0, 28, 63 and 147 days and on their average daily gain (ADG) between each period (0-28, 28-63 and 63-147 days). Libido and main seminal traits (semen volume, motility, concentration, and production, as well as normal apical ridge and abnormalities of spermatozoa) were controlled during the testing phase. Semen volume, motility and concentration were subsequently controlled during the productive phase, as well as the length of the male life, calculated as the number of days a rabbit was present at the farm between age 147 and day of death, culling or censoring; set to 2 years of life). The birth weight, the ADG between 0 and 28 days and between 28 and 63 days were positively related to some seminal parameters measured during the testing phase (semen volume, concentration, production and motility; P < 0.05), while the ADG between 63 and 147 days was negatively related to the seminal productivity throughout the productive life of the males (an increment of 10 g per day on ADG reduced the number of profitable ejaculates by 4.9%; P < 0.05). In addition, a higher growth between 0 and 28 and between 63 and 147 days increased the risk of death or culling of males during the productive phase (P < 0.05). In conclusion, an adequate body development early in life seems to have a positive effect on the degree of sexual maturity with which male rabbits begin their reproductive life, but reaching the reproduction onset with excessive weight can reduce their reproductive performance and lifespan.

Longitudinal analysis of direct and indirect effects on average daily gain in rabbits using a structured antedependence model

BACKGROUND

Indirect genetic effects (IGE) are important components of various traits in several species. Although the intensity of social interactions between partners likely vary over time, very few genetic studies have investigated how IGE vary over time for traits under selection in livestock species. To overcome this issue, our aim was: (1) to analyze longitudinal records of average daily gain (ADG) in rabbits subjected to a 5-week period of feed restriction using a structured antedependence (SAD) model that includes IGE and (2) to evaluate, by simulation, the response to selection when IGE are present and genetic evaluation is based on a SAD model that includes IGE or not.

RESULTS

The direct genetic variance for ADG (g/d) increased from week 1 to 3 [from 8.03 to 13.47 (g/d)²] and then decreased [6.20 (g/d)² at week 5], while the indirect genetic variance decreased from week 1 to 4 [from 0.43 to 0.22 (g/d)²]. The correlation between the direct genetic effects of different weeks was moderate to high (ranging from 0.46 to 0.86) and tended to decrease with time interval between measurements. The same trend was observed for IGE for weeks 2 to 5 (correlations ranging from 0.62 to 0.91). Estimates of the correlation between IGE of week 1 and IGE of the other weeks did not follow the same pattern and correlations were lower. Estimates of correlations between direct and indirect effects were negative at all times. After seven generations of simulated selection, the increase in ADG from selection on EBV from a SAD model that included IGE was higher (~ 30%) than when those effects were omitted.

CONCLUSIONS

Indirect genetic effects are larger just after mixing animals at weaning than later in the fattening period, probably because of the establishment of social hierarchy that is generally observed at that time. Accounting for IGE in the selection criterion maximizes genetic progress.

Freezability genetics in rabbit semen

The aim of this study was to estimate the heritability of semen freezability and to estimate the genetic correlation between frozen-thawed sperm traits and the growth rate in a paternal rabbit line. Estimated heritabilities showed that frozen-thawed semen traits are heritable (ranged between 0.08 and 0.15). In the case of Live-FT (percentage of viable sperm after freezing), the estimated heritability is the highest one, and suggests the possibility of effective selection. After the study of genetic correlations it seems that daily weight gain (DG) was negatively correlated with sperm freezability, but no further conclusions could be drawn due to the high HPD95%. More data should be included in order to obtain better accuracy for the estimates of these genetic correlations. If the results obtained at present study were confirmed, it would imply that selection for DG could alter sperm cell membranes or seminal plasma composition, both components related to sperm cryoresistance.

Interaction of direct and social genetic effects with feeding regime in growing rabbits

Background

Most 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 (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d$$\end{document}d) and social (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$s$$\end{document}s) genetic effects (also known as indirect genetic effects) to total heritable variance of average daily gain (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{ADG}}$$\end{document}ADG) in rabbits on different feeding regimens (FR), and the magnitude of the interaction between genotype and FR (G × FR).

Methods

A total of 6264 contemporary kits were housed in cages of eight individuals and raised on full (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F$$\end{document}F) or restricted (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R$$\end{document}R) feeding to 75% of the ad libitum intake. A Bayesian analysis of weekly records of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{ADG}}$$\end{document}ADG (from 32 to 60 days of age) in rabbits on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F$$\end{document}F and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R$$\end{document}R was performed with a two-trait model including \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d$$\end{document}d and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$s$$\end{document}s.

Results

The ratio between total heritable variance and phenotypic variance (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T^{2}$$\end{document}T2) was low (<0.10) and did not differ significantly between FR. However, the ratio between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$h^{2}$$\end{document}h2 (i.e. variance of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d$$\end{document}d relative to phenotypic variance) and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T^{2}$$\end{document}T2 was ~0.52 and 0.86 for animals on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R$$\end{document}R and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F$$\end{document}F, respectively, thus \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$s$$\end{document}s contributed more to the heritable variance of animals on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R$$\end{document}R than on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F$$\end{document}F. Feeding regimen also affected the sign and magnitude of the correlation between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d$$\end{document}d and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$s$$\end{document}s, i.e. −0.5 and ~0 for animals on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R$$\end{document}R and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F$$\end{document}F, respectively. The posterior mean (posterior sd) of the correlation between estimated total breeding values (ETBV) of animals on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R$$\end{document}R and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F$$\end{document}F was 0.26 (0.20), indicating very strong G × FR interactions. The correlations between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d$$\end{document}d and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$s$$\end{document}s in rabbits on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F$$\end{document}F and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R$$\end{document}R ranged from −0.47 (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d$$\end{document}d on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F$$\end{document}F and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$s$$\end{document}s on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R$$\end{document}R) to 0.64.

Conclusions

Our results suggest that selection of rabbits for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{ADG}}$$\end{document}ADG under \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F$$\end{document}F may completely fail to improve \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{ADG}}$$\end{document}ADG in rabbits on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R$$\end{document}R. Social genetic effects contribute substantially to ETBV of rabbits on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R$$\end{document}R but not on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F$$\end{document}F. Selection for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{ADG}}$$\end{document}ADG should be performed under production conditions regarding the FR, by accounting for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$s$$\end{document}s if the amount of food is limited.

Effect of different freezing velocities on the quality and fertilising ability of cryopreserved rabbit spermatozoa

The freezing step of the cryopreservation protocol negatively influences the quality and fertilising ability of rabbit spermatozoa. This study determines the effect of different rates of freezing on the quality and fertilising ability of rabbit spermatozoa cryopreserved with dimethylsulfoxide (DMSO) (1.75M) and sucrose (0.05M). Ejaculates from meat rabbit line males (n=12) were pooled and each pool (n=7) was split into four aliquots. One group of straws (control, C) was frozen in static liquid nitrogen vapour (5cm above the liquid nitrogen, 10min) and the other groups were frozen at different freezing rates (°Cmin(-1)) from -6°C to -100°C using a programmable freezer: slow (-15°Cmin(-1), S), medium (-40°Cmin(-1), M) or fast (-60°Cmin(-1), F). After thawing (50°C, 12s), the quality was highest (P<0.05) in C and M samples and lowest in S and F samples. F samples presented the lowest litter sizes (P≤0.05) and fertility whilst M samples exhibited the highest values. In conclusion, the freezing rate affects both the quality and the fertilising ability of frozen-thawed rabbit spermatozoa, with both slow (-15°Cmin(-1)) and fast (-60°Cmin(-1)) freezing rates being detrimental for the quality and fertilising ability.

Genetic parameters of rabbit semen traits and male fertilising ability

This study aimed to estimate genetic parameters for rabbit semen production, semen characteristics and fertilising ability following artificial insemination. It involved five successive batches of 30-36 bucks each, 22 weeks of semen collection, and 11 weeks of semen recording per batch. Semen analyses were based on 2312 ejaculates. A total of 2019 inseminations were performed on 674 females with semen from 236 ejaculates from 128 bucks. Heritability estimates of semen traits ranged from 0.05 to 0.18. At approximately 0.05-0.06 for pH, volume and mass motility, they were higher for concentration (0.10) and the total number of sperms per ejaculate (0.12), and even higher for motility traits based on computer-assisted semen analysis. The percentage of motile sperms had the highest heritability (0.18) and appeared to be a good candidate criterion to select for both sperm number and motility. The heritability estimates were close to zero for all three criteria of fertilising ability: fertility (F), prolificacy (live births, LB) and their product (LB per insemination). A permanent environmental effect of the male seemed to be higher for LB (0.04) than for F (0.01). The rabbit does accounted for approximately 10% of the variance of the three criteria. With respect to the female, the male contribution was negligible for fertility and in a ratio of 4-10 for the number of live births. In our experimental conditions, prolificacy would thus be more highly influenced by the buck than fertility.

Semen characteristics of purebred and crossbred male rabbits

The aim of this investigation was to evaluate the semen quality traits of purebred male rabbits and their crosses under subtropical Egyptian conditions. A full 3 x 3 diallel crossing was performed for producing the first generation progeny of New Zealand White (N), Flander (F) and Rex (R) breeds. The highest ejaculate volume (p< 0.05) and percentage of live sperms (p<0.01) with the lowest percentage of sperm cell morphological abnormalities (p<0.05) had been recorded in the NF bucks. Moreover, they possessed positive estimates of direct heterosis for ejaculate volume, mass motility (Mm), individual motility (Im) and sperm cell concentration (SCC). On the contrary, pH had negative estimates of direct heterosis in all crosses and their reciprocal. Semen pH was negatively correlated with SCC (r = -0.18), Mm (r = -0.13) and Im (r = -0.23). In conclusion, the superiority of crossbreeding was particularly obvious in the New Zealand White x Flander males, which cumulated heterosis and favorable maternal effects of the Flander dams.

mRNA expression in rabbit blastocyst and endometrial tissue of candidate gene involved in gestational losses

Gestation is a complex process that involves different growth factors, cytokines and adhesion proteins related with embryo development, cellular differentiation and proliferation, embryo-endometrium interaction, angiogenesis, maternal-embryonic recognition and growth development of placenta and embryos. In this study, we examine pre-implantational (at 6 days of gestation) and gestational (at 12 days and total from ovulation to birth) losses in two rabbit lines selected by different criteria (post-weaning daily gain and litter size) and the pattern of a set of candidate transcripts, at 6 days of gestation, related with embryo development and implantation process, such as Oct-4, epidermal growth factor receptor 3 (erbB3), Transforming Growth Factor β2, Vascular Endothelial Growth Factor and Interferon γ and related with insulin-like growth factors signalling as insulin growth factors I and II and their receptors in rabbit blastocysts and endometrial tissue. Similar pre-implantational losses were obtained in both lines. However, the gestational losses of the line selected by post-weaning daily gain clearly mirrored an increase in losses by 50% at 12 days and at birth (22.4 vs 9.5 and 50.2 vs 25.4, respectively, between line selected by post-weaning daily gain and line selected by litter size). In blastocysts and endometrial tissue at 6 days of gestation qRT-PCR assays indicated that the mean insulin-like growth factor (IGF)-IIR mRNA expression was down-regulated in line selected by post-weaning daily gain. Dysregulation of the IGF-IIR could be potential reasons for induced gestational losses. We conclude that IGF-IIR gene expression in blastocyst and endometrial tissue at 6th day of gestation tends to decline in line selected by post-weaning daily gain. The functional significance related with gestational losses is uncertain.