Individual efficiency for the use of feed resources in rabbits

A Bayesian procedure, which allows consideration of the individual variation in the feed resource allocation pattern, is described and implemented in 2 sire lines of rabbit (Caldes and R). The procedure is based on a hierarchical Bayesian scheme, where the first stage of the model consists of a multiple regression model of feed intake on metabolic BW and BW gain. In a second stage, an animal model was assumed including batch, parity order, litter size, and common environmental litter effects. Animals were reared during the fattening period (from weaning at 32 d of age to 60 d of age) in individual cages on an experimental farm, and were fed ad libitum with a commercial diet. Body weight (g) and cumulative feed intake (g) were recorded weekly. Individual BW gain (g) and average BW (ABW, g) were calculated from these data for each 7-d period. Metabolic BW (g(0.75)) was estimated as ABW(0.75). The number of animals actually measured was 444 and 445 in the Caldes and R lines, respectively. Marginal posterior distributions of the genetic parameters were obtained by Gibbs sampling. Posterior means (posterior SD) for heritabilities for partial coefficients of regression of feed intake on metabolic BW and feed intake on BW gain were estimated to be 0.35 (0.17) and 0.40 (0.17), respectively, in the Caldes line and 0.26 (0.19) and 0.27 (0.14), respectively, in line R. The estimated posterior means (posterior SD) for the proportion of the phenotypic variance due to common litter environmental effects of the same coefficients of regression were respectively, 0.39 (0.14) and 0.28 (0.13) in the Caldes line and 0.44 (0.22) and 0.49 (0.14) in line R. These results suggest that efficiency of use of feed resources could be improved by including these coefficients in an index of selection.     

Reproductive performance of crossbred and purebred male rabbits

The effect of buck genetic type and crossbreeding parameters on fertility and prolificacy were estimated using two rabbit sire lines and their reciprocal crosses. The relationship between the reproductive performance of inseminated multiparous does and several semen quality traits was also investigated. The semen characteristics evaluated were: pH (pH), mass and individual motility (MM, IM), percentage of viable spermatozoa (Vi), spermatozoa with normal apical ridge (NAR), normal spermatozoa (NSP), spermatozoa with morphological abnormalities of head (HAP), neck-midpiece (NAP), and tail (TAP), spermatozoa with the presence of proximal (PD) and distal (DD) cytoplasmic droplets.

Fertility was analysed as a continuous trait (kindling rate) or as a binary trait (success or failure of kindling). In the first case, the analysis was performed using GLM procedures of SAS v.8 according to a model that included the fixed factors of buck genetic type, number of ejaculates per pool and week of insemination. In the second case, fertility was analysed using GENMOD procedures of SAS v.8 according to a mixed model including the same fixed factors as before plus the physiological status of the does and the permanent random effect of female. Number of kits born alive and number of stillborn were analysed with MIXED procedures of SAS v.8 with the same model used for the analysis of fertility as a binary trait. Estimates of the estimable functions of crossbreeding genetic parameters of the lines were obtained from the solutions of the corresponding models by generalized least squares using GLM, GENMOD and MIXED procedures. Crossbreeding parameters were estimated according to the model of Dickerson. A linear regression was used to determine the relationship between fertility and litter size and the semen characteristics evaluated.

Significant differences in fertility were observed among buck genetic types, which were favourable to type R. Differences between lines in maternal genetic effects were relevant and favourable to type R for fertility. Individual heterosis was important but unfavourable for fertility.

A slight correlation was obtained between all semen quality traits and fertility and prolificacy. Two multiple models were found for fertility, including NAP, IM, NSP, buck genetic type and Vi in one model or NAR in other model. Individual motility had an important positive effect, while NAP had a small negative effect. When MM, TAP and buck genetic type were included in a multiple model for the number of kits born alive, both MM and TAP had significant small effects. Individual motility and DD appeared to be related to number of kits stillborn, but only DD had a significant although negligible effect.     

Heterosis, direct and maternal genetic effects on semen quality traits of rabbits

A complete diallel cross involving two rabbit sire lines (C and R) was carried out to estimate the crossbreeding genetic parameters of seminal traits. 2140 ejaculates from 153 males were analyzed. The traits studied were: presence of gel plugs (G), urine (U), and calcium carbonate deposits (CC), number of useful ejaculates (UE), pH, volume (V), mass and individual motility (Mm, Mi), useful Mi (UM), concentration (Cn), number of spermatozoa per ejaculate (TSE), percentage of viable spermatozoa (Vi), spermatozoa with normal apical ridge (NAR), normal spermatozoa (Nr), spermatozoa with morphological abnormalities of head (H), neck-midpiece (Nm), and tail (T), presence of proximal and distal cytoplasmic droplet (Dp, Dd).

Estimates of heterosis, direct and maternal genetic effects were obtained from the solutions of the mixed model. There were major differences in direct genetic effects between lines, which were favourable to line C for Cn and TSE, and unfavourable for CC, Nm and Dp. Smaller differences were also observed in Vi and NAR favourable to line R. Differences between lines with respect to the maternal genetic effects were relevant and favourable to line C for V and to line R for U, UM, Cn, TSE, Nm, Mi, and Mm. Individual heterosis was high for Dp and Dd.     

Dimethylsulfoniopropionate uptake by marine phytoplankton

Dimethylsulfoniopropionate (DMSP) accounts for most of the organic sulfur fluxes from primary to secondary producers in marine microbial food webs. Incubations of natural communities and axenic cultures with radio-labeled DMSP showed that dominant phytoplankton groups of the ocean, the unicellular cyanobacteria Prochlorococcus and Synechococcus and diatoms, as well as heterotrophic bacteria take up and assimilate DMSP sulfur, thus diverting a proportion of plankton-produced organic sulfur from emission into the atmosphere.     

Different ways to model biological relationships between fertility and pH of the semen in rabbits

This work aimed to study the relationship between pH of the semen and fertility (Fert, defined as the success or failure of conception), which is of special interest because pH of the semen can be considered a global marker of the expression of some seminal quality traits. Different methods used to model the relationship between Fert and pH are presented here: 1) ignoring genetic and environmental correlations and including pH either as a covariate or as a cross-classified effect on fertility, 2) a bivariate mixed model, and 3) recursive bivariate mixed models. A total of 653 pH records and 6,365 Fert records after AI were used. Crossbreed does from 2 maternal lines were artificially inseminated with buck semen from a paternal line in a commercial environment. A negative, and almost linear, effect of pH on Fert was detected. The posterior median of pH and Fert heritabilities, and the highest posterior density interval at 95% (in parentheses) were approximately 0.18 (0.05, 0.29) and approximately 0.10 (0.02, 0.20) across all the models, respectively. Genetic correlations between traits were negative, but the highest posterior density interval at 95% included zero [i.e., -0.31 (-0.91, 0.33) in the bivariate mixed model and -0.17 (-0.99, 0.48) and -0.44 (-0.99, 0.10) in the recursive bivariate mixed models including pH as a covariate or as a cross-classified effect, respectively]. All models predicted Fert data reasonably well (i.e., 76 and 62% correct predictions for success and failure, respectively). No differences in the prediction of the EBV for male fertility were encountered between models, showing a good concordance in the animals ranked by their EBV (the correlation between EBV in all models was close to 1). Thus, no differences in results were obtained considering, or not considering, genetic and environmental correlations between pH and Fert and assuming, or not assuming, recursiveness between each trait. This is because the magnitude of the effect of pH on Fert was not large enough; therefore, the same results were obtained even though the models were of different complexity.     

Strong relationship between DMS and the solar radiation dose over the global surface ocean

Marine biogenic dimethylsulfide (DMS) is the main natural source of tropospheric sulfur, which may play a key role in cloud formation and albedo over the remote ocean. Through a global data analysis, we found that DMS concentrations are highly positively correlated with the solar radiation dose in the upper mixed layer of the open ocean, irrespective of latitude, plankton biomass, or temperature. This is a necessary condition for the feasibility of a negative feedback in which light-attenuating DMS emissions are in turn driven by the light dose received by the pelagic ecosystem.     

Predicting fertility from seminal traits: Performance of several parametric and non-parametric procedures

This research aimed at assessing the efficacy of non-parametric procedures to improve the classification of the ejaculates in the artificial insemination (AI) centers according to their fertility rank predicted from characteristics of the AI doses. A total of 753 ejaculates from 193 bucks were evaluated at three different times from 5 to 9 months of age for 21 seminal variables (related to ejaculate pH and volume, sperm concentration, viability, morphology and acrosome reaction traits, and dose characteristic) and their corresponding fertility score after AI over crossbred females. Fertility rate was categorized into five classes of equal length. Linear Regression (LR), Ordinal Logistic Regression (OLR), Support Vector Regression (SVR), Support Vector Ordinal Regression (SVOR), and Non-deterministic Ordinal Regression (NDOR) were compared in terms of their predictive ability with two base line algorithms: MEAN and MODE which always predict the mean and mode value of the classes observed in the data set, respectively. Predicting ability was measured in terms of rate of erroneous classifications, linear loss (average of the distance between the predicted and the observed classes), the number of predicted classes and the F₁ statistic (which allows comparing procedures taking into account that they can predict different number of classes). The seminal traits with a bigger influence on fertility were established using stepwise regression and a nondeterministic classifier. MEAN, LR and SVR produced a higher percentage of wrong classified cases than MODE (taken as reference for this statistic), whereas it was 6%, 13% and 39% smaller for SVOR, OLR and NDOR, respectively. However, NDOR predicted an average of 2.04 classes instead of one class predicted by the other procedures. All the procedures except MODE showed a similar smaller linear loss than the reference one (MEAN) SVOR being the one with the best performance. The NDOR showed the highest value of the F₁ statistic. Values of linear loss and F₁ statistics were far from their best value indicating that possibly, the variation in fertility explained by this group of semen characteristics is very low. From the total amount of traits included in the full model, 11, 16, 15, 18 and 3 features were kept after performing variable selection with the LR, OLR, SVR, SVOR and NDOR methods, respectively. For all methods, the reduced models showed almost an irrelevant decrease in their predictive abilities compared to the corresponding values obtained with the full models.     

Genetics of litter size in three maternal lines of rabbits: repeatability versus multiple-trait models

Variance components were estimated in 3 lines of rabbits selected for litter size at weaning (A, Prat, and V) to test one of the assumptions of the models used for selection: that litter size data at different parities are repeated measurements of the same trait. Multiple-trait analyses were performed for the total number of kits born (TB), the number of kits born alive (BA), and the number of kits weaned (NW) per litter. Estimates were obtained by REML in multivariate analyses, including all of the information of the selection criteria, under a repeatability model or a multiple-trait model, considering litter size at the first, second, and subsequent parities as different traits. Models included the fixed effects of the physiological status of the female and the year-season of mating day, buck and doe random permanent environmental effects, and doe additive genetic effects. Results indicated that prolificacy was determined mainly by doe components and that the service sire had a very small effect. Heritabilities for the first and second parities were greater than the estimates obtained under the repeatability model (0.04 to 0.14 for the repeatability model). In the A and V lines, similar values of heritability were found at the first and second parities, but in the Prat line heritability at the second parity was always greater than at the first and greater parities (values of 0.21, 0.17, and 0.15 for TB, BA, and NW, respectively, in second parities of the Prat line). Genetic correlations between the same traits at different parities were approximately 0.8 for all traits in line A, but much lower in the other 2 lines. On average, the values were 0.64 for TB, 0.48 for BA, and 0.39 for NW between the first and second parities, and 0.65 for TB, 0.56 for BA, and 0.45 for NW between the first and third and greater parities. Genetic correlations between the second and greater parities showed the greatest values (approximately 0.8) in lines A and Prat for all traits, but they were lower in line V (0.63 for BA and 0.37 for NW). The heterogeneity of heritabilities and genetic correlations between parities lower than 0.9 suggests that litter size at different parities could be considered as different traits when genetic evaluations are performed. However, when the accuracies of predicted breeding values under a multiple-trait and a repeatability model were calculated, assuming the first to be the true model, the values obtained were nearly the same for all traits in all lines.     

Elliptical selection experiment for the estimation of genetic parameters of the growth rate and feed conversion ratio in rabbits

Two elliptical selection experiments were performed in two contemporary sire lines of rabbits (C and R) in order to optimize the experimental design for estimating the genetic parameters of the growth rate (GR) and feed conversion ratio (FCR). Twelve males and 19 females from line C, and 13 males and 23 females from line R, were selected from an ellipse defined by a quadratic index based on these traits. Data from 160 rabbits of each of the parental generations of lines C and R and their offspring (275 and 266 animals, respectively) were used for the analysis. A Bayesian framework was adopted for inference. Marginal posterior distributions of the genetic parameters were obtained by Gibbs sampling. An animal model including batch, parity order, litter size, and common environmental litter effects was assumed. Posterior means (posterior standard deviations) for heritabilities of GR and FCR were estimated to be 0.31 (0.10) and 0.31 (0.10), respectively, in line C and 0.21 (0.08) and 0.25 (0.12) in line R. Posterior means of the proportion of the variance due to common litter environmental effects were 0.14 (0.06) and 0.21 (0.06) for GR and FCR, respectively, in line C and 0.17 (0.06) and 0.22 (0.06) in line R. Posterior means of genetic correlation between both traits were -0.49 (0.25) in line C and -0.47 (0.32) in line R, indicating that selection for GR was expected to result in a similar correlated response in FCR in both lines.     

Genetic parameters of fertility in two lines of rabbits with different reproductive potential

A Bayesian analysis with a threshold model was performed for fertility defined as a binary trait (1 = successful mating, 0 = unsuccessful mating) in two populations of rabbits of different reproductive potential and different genetic origin: Line P selected for litter size and Line C selected for growth rate. There were 20,793 records of natural mating (86.2% successful) in Line C between 1983 and 2003, and 17,548 records (80.5% successful) in Line P, between 1992 and 2003. Data related to 5,388 and 3,848 females and 1,021 and 685 males in Lines C and P, respectively. The pedigree included 6,409 and 4,533 individuals in Lines C and P, respectively. The binary response was modeled under a probit approach. The model for the latent variable included male and female additive genetic effects, male and female permanent environmental effects, and the year-season and physiological status of the female (nulliparous, multiparous lactating, or multiparous nonlactating) as systematic effects. Means (standard deviation in parentheses) of the estimated marginal posterior distribution (EMPD) of male heritability were 0.013 (0.006) and 0.010 (0.008) in Lines C and P, respectively, and those of EMPD of female heritability were 0.056 (0.013) and 0.062 (0.018) in Lines C and P, respectively. Means of the EMPD of the proportion of the phenotypic variance due to environmental male and female effects were, respectively, 0.031 (0.007) and 0.128 (0.018) in Line C and 0.053 (0.010) and 0.231 (0.024) in Line P. Means (standard deviations in parentheses) of the EMPD of genetic correlation between male and female fertility were 0.733 (0.197) in Line C and 0.434 (0.381) in Line P. The posterior distribution of genetic correlations presents a huge dispersion, and the estimates should be taken with caution because of the almost negligible estimate of the male genetic component. Results indicate that little genetic variation exists for female fertility, and practically none for male fertility. It would, therefore, be possible to improve reproductive performance by including female fertility in a breeding program, but response to selection would be very small.