Novel phenotypes of feeding and social behaviour and their relationship with individual rabbit growth and feed efficiency.

Due to the lack of a recording system for individual consumption of group-housed rabbits, published studies about feeding behaviour are based on information recorded at the group- and not at the individual level and periods covering only a few days or, in some cases, only part of a day. Such information could be used to inform rabbit management systems but cannot be used for genetic selection. We aimed to generate and use information from a novel automated feeder for group-housed rabbits to identify new phenotypes for individual animals that could be incorporated into breeding programs to improve feed efficiency and social behaviour under different feeding regimens. At 39 d of age, rabbits from 15 batches were placed in cages and fed ad libitum to become used to the electronic feeder. From 42 to 58-59 d, one group of 1 086 rabbits was fed ad libitum (AL), while another group of 1 134 rabbits was fed on a restricted feeding schedule (R) by limiting the feeding time to the period between 1800 and 0600 h of the following day. We implemented a reliable multivariate method to remove anomalous feeding behaviour records. We then defined novel traits for feeding behaviour that apply to both types of feeding regimes, and for social behaviour that indicates an animal's rank within the cage hierarchy. We based these traits on feeder records and a biologically sound definition of a meal. Finally, we estimated the phenotypic correlations of those traits with growth and feed efficiency traits. Our findings demonstrate that variables about resource distribution among cage mates and an animal's priority for feed access were found to be good indicators of an animal's dominant or subordinate status within the cage. Based on results obtained in R animals (results were similar in AL animals), the most efficient animals were those that ate less frequently (phenotypic correlation with feed conversion ratio, rho = 0.6), and consumed smaller amounts per meal (rho = 0.7), spent less time at the feeder (rho = 0.4), and appeared to be subordinate, as they did not have priority access to the feeder (rho = -0.3), and had the smallest share of resources (range of rho = 0.2-0.6). We conclude that quantifying feeding and social behaviour traits can enhance the understanding of the mechanisms through which individuals exert their effects on the performance of their cage mates.

Dissecting total genetic variance into additive and dominance components of purebred and crossbred pig traits.

The partition of the total genetic variance into its additive and non-additive components can differ from trait to trait, and between purebred and crossbred populations. A quantification of these genetic variance components will determine the extent to which it would be of interest to account for dominance in genomic evaluations or to establish mate allocation strategies along different populations and traits. This study aims at assessing the contribution of the additive and dominance genomic variances to the phenotype expression of several purebred Piétrain and crossbred (Piétrain × Large White) pig performances. A total of 636 purebred and 720 crossbred male piglets were phenotyped for 22 traits that can be classified into six groups of traits: growth rate and feed efficiency, carcass composition, meat quality, behaviour, boar taint and puberty. Additive and dominance variances estimated in univariate genotypic models, including additive and dominance genotypic effects, and a genomic inbreeding covariate allowed to retrieve the additive and dominance single nucleotide polymorphism variances for purebred and crossbred performances. These estimated variances were used, together with the allelic frequencies of the parental populations, to obtain additive and dominance variances in terms of genetic breeding values and dominance deviations. Estimates of the Piétrain and Large White allelic contributions to the crossbred variance were of about the same magnitude in all the traits. Estimates of additive genetic variances were similar regardless of the inclusion of dominance. Some traits showed relevant amount of dominance genetic variance with respect to phenotypic variance in both populations (i.e. growth rate 8%, feed conversion ratio 9% to 12%, backfat thickness 14% to 12%, purebreds-crossbreds). Other traits showed higher amount in crossbreds (i.e. ham cut 8% to 13%, loin 7% to 16%, pH semimembranosus 13% to 18%, pH longissimus dorsi 9% to 14%, androstenone 5% to 13% and estradiol 6% to 11%, purebreds-crossbreds). It was not encountered a clear common pattern of dominance expression between groups of analysed traits and between populations. These estimates give initial hints regarding which traits could benefit from accounting for dominance for example to improve genomic estimated breeding value accuracy in genetic evaluations or to boost the total genetic value of progeny by means of assortative mating.

Prediction of complex traits: Conciliating genetics and statistics.

This review focuses on methods used to predict complex traits. Main characteristics of prediction approaches are given: the deterministic or stochastic nature of prediction, the objects of prediction, the sources of information and the main statistical methods. Sources of information discussed are the traditional genealogies and phenotypes, nucleotide sequences, expression data and epigenetics marks. Statistical methods are presented as successive degrees of generalization from the definition of the conditional expectation as the prediction rule, to best linear unbiased prediction, then Bayesian and, recently, machine learning methods, including meta-methods. We highlight the contributions of Daniel Gianola to this methodological evolution.

Daily exposure to summer temperatures affects the motile subpopulation structure of epididymal sperm cells but not male fertility in an in vivo rabbit model.

High temperatures have negative effects on sperm quality leading to temporary or permanent sterility. The aim of the study was to assess the effect of long exposure to summer circadian heat stress cycles on sperm parameters and the motile subpopulation structure of epididymal sperm cells from rabbit bucks. Twelve White New Zealand rabbit bucks were exposed to a daily constant temperature of the thermoneutral zone (from 18 °C to 22 °C; control group) or exposed to a summer circadian heat stress cycles (30 °C, 3 h/day; heat stress group). Spermatozoa were flushed from the epididymis and assessed for sperm quality parameters at recovery. Sperm total motility and progressivity were negatively affected by high temperatures (P < 0.05), as were also specific motility parameters (curvilinear velocity, linear velocity, mean velocity, straightness coefficient, linearity coefficient, wobble coefficient, and frequency of head displacement; P < 0.05, but not the mean amplitude of lateral head displacement). Heat stress significantly increased the percentage of less-motile sperm subpopulations, although the percentage of the high-motile subpopulation was maintained, which is consistent with the fact that no effect was detected on fertility rates. However, prolificacy was reduced in females submitted to heat stress when inseminated by control bucks. In conclusion, our results suggest that environmental high temperatures are linked to changes in the proportion of motile sperm subpopulations of the epididymis, although fertility is still preserved despite the detrimental effects of heat stress. On the other hand, prolificacy seems to be affected by the negative effects of high temperatures, especially by altering female reproduction.

Lactating performance, water and feed consumption of rabbit does reared under a Mediterranean summer circadian cycle of temperature v. comfort temperature conditions.

The general aim of this research was to study the effect of high ambient temperature on the performance of does during lactation, specifically the following factors: average daily feed (ADFI) and water (ADWI) intakes, daily milk yield (DMY); milk composition: dry matter (DM), CP and gross energy (GE); doe BW (DW); individual kit weaning weight (IWW) and litter survival rate during lactation (SR). The study was undertaken comparing the performance of two groups of contemporary does reared under the same management, feeding regime and environmental conditions, except the environmental temperature and humidity. A total of 80 females were randomly allocated, at 60 days of age, into two identical and continuous rooms. In one room, the temperature was maintained permanently within the thermo-neutral zone (between 18°C to 22°C); thus, environmental conditions in this room were considered as comfort conditions. In the second room, the environmental temperature pattern simulated the daily temperature cycles that were characteristic of the summer in Mediterranean countries (24°C at 0800 h, increasing up to 29°C until 1100 h; maintenance at 29°C to 31°C for 4 h and decreasing to about 24°C to 26°C around 1700 h until 0800 h of the following day), which were considered as thermal stress conditions. Females followed a semi-intensive reproductive rhythm, first artificial insemination at 4.5 months of age, with subsequent 42-day reproductive cycles. Traits were recorded from a total of 138 lactations. Does were controlled up to the 5th lactation. Data were analyzed using linear and linear mixed models. High ambient temperature led to a lower ADFI (-9.4%), DW (-6.2%) and IWW (-8%), but it did not affect ADWI. No significant difference was found either for DMY, milk composition (DM, CP and GE) and SR during the lactation period. Heat stress was moderate, and does were able to adapt to it behaviorally by decreasing feed intake (to reduce heat production), but also live weight, allowing them to preserve milk yield and composition for assuring litter survival. On the other hand, water consumption could not be the main animal mechanism to overcome heat stress.

Model averaging for genome-enabled prediction with reproducing kernel Hilbert spaces: a case study with pig litter size and wheat yield.

Predictive ability of yet-to-be observed litter size (pig) grain yield (wheat) records of several reproducing kernel Hilbert spaces (RKHS) regression models combining different number of Gaussian or t kernels was evaluated. Predictive performance was assessed as the average (over 50 replicates) predictive correlation in the testing set. Predictions from these models were combined using three different types of model averaging: (i) mean of predicted phenotypes obtained in each model, (ii) weighted average using mean squared error as weight or (iii) using the marginal likelihood as weight. (ii) and (iii) were obtained in a validation set with 5% of the data. Phenotypes consisted of 2598, 1604 and 1879 average litter size records from three commercial pig lines and wheat grain yield of 599 lines evaluated in four macro-environments. SNPs from the PorcineSNP60 BeadChip and 1447 DArT markers were used as predictors for the pig and wheat data analyses, respectively. Gaussian and univariate t kernels led to same predictive performance. Multikernel RKHS regression models overcame shortcomings of single kernel models (increasing the predictive correlation of RKHS models by 0.05 where 3 Gaussian or t kernels were fitted in the RKHS models simultaneously). None of the proposed averaging strategies improved the predictive correlations attained with single models using multiple kernel fitting.

Genome-enabled methods for predicting litter size in pigs: a comparison.

Predictive ability of models for litter size in swine on the basis of different sources of genetic information was investigated. Data represented average litter size on 2598, 1604 and 1897 60K genotyped sows from two purebred and one crossbred line, respectively. The average correlation (r) between observed and predicted phenotypes in a 10-fold cross-validation was used to assess predictive ability. Models were: pedigree-based mixed-effects model (PED), Bayesian ridge regression (BRR), Bayesian LASSO (BL), genomic BLUP (GBLUP), reproducing kernel Hilbert spaces regression (RKHS), Bayesian regularized neural networks (BRNN) and radial basis function neural networks (RBFNN). BRR and BL used the marker matrix or its principal component scores matrix (UD) as covariates; RKHS employed a Gaussian kernel with additive codes for markers whereas neural networks employed the additive genomic relationship matrix (G) or UD as inputs. The non-parametric models (RKHS, BRNN, RNFNN) gave similar predictions to the parametric counterparts (average r ranged from 0.15 to 0.23); most of the genome-based models outperformed PED (r = 0.16). Predictive abilities of linear models and RKHS were similar over lines, but BRNN varied markedly, giving the best prediction (r = 0.31) when G was used in crossbreds, but the worst (r = 0.02) when the G matrix was used in one of the purebred lines. The r values for RBFNN ranged from 0.16 to 0.23. Predictive ability was better in crossbreds (0.26) than in purebreds (0.15 to 0.22). This may be related to family structure in the purebred lines.

Prediction of clinical mastitis outcomes within and between environments using whole-genome markers.

The objective of this study was to evaluate genome-enabled predictions of daughter yield deviations for clinical mastitis in Norwegian Red cows within and between environments according to mastitis pathogen status. Genome-based predictions of daughter yield deviations for clinical mastitis for 1,126 bulls within and between 5 environments were performed using Bayesian ridge regression. The environments were defined as herd-5-yr classes with the following prevalence of bacteriological milk samples found positive for contagious mastitis pathogens: <50% (L50), ≥ 50% (H50), ≤ 25% (L75), >25% and <75% (M75), and ≥ 75% (H75). In addition, predictions based on all data across environment groups (the full data set, FD) were calculated to provide a benchmark for comparison. Predictive ability was evaluated using a 10-fold cross validation. A bootstrap procedure was used to obtain 95% confidence intervals for the cross-validation distribution of predictive ability for each data set. Predictive ability ranged from 0.04 for L75 to 0.19 for FD. Similar predictions within and between environments showed no evidence of genotype by environment interaction. The 95% confidence interval for all 5 environmental data sets included zero and ranged from 0.02 to 0.35 for FD. The bootstrap distribution showed large variation within each data set and small variation between data sets. Although we found no evidence of genotype by environment interaction, rank correlations of the single nucleotide polymorphism effects between different environments ranged from 0.15 (L75 - H75) to 0.92 (M75 - FD), indicating that single nucleotide polymorphisms may have a differential contribution to predictive ability in environments with distinct pathogen loads.

Effect of heat intensity and persistency on prolificacy and preweaning kit growth at different stages of the rabbit production cycle.

The aim of this research was to assess the effect of temperature intensity and variation both throughout the day and between days within different periods of the reproductive cycle and the lactation of the rabbit. This information would help in establishing optimal patterns of environmental temperature control in rabbitries. The traits analyzed were total number of kits born (TB), number of kits alive at weaning (NW), and average individual weight at weaning (AvgWW). For each trait, several mixed models were fitted to the data, differing only in the number and type of temperature descriptors included in the vector of fixed effects. Those descriptors were the average daily mean, maximum, and range of temperatures (AvgTmean, AvgTmax, and AvgRg, respectively) and the CV of daily mean temperature (CVTmean). All were calculated for periods in which important physiological processes related to the studied traits occur. High environmental temperature was found to have a detrimental effect on prolificacy and preweaning growth of the kits. When the average daily mean reached 20°C, it produced a linear decay of TB of around 0.1 kit/°C. The most sensitive period for TB could cover from spermatogenesis to embryo implantation. However, the high correlation between descriptors calculated for different periods makes it difficult to assign an effect to each specific period and therefore to the specific physiological process occurring in that period. The effect on NW was smaller and quadratic, with an optimum value between 18°C and 21°C. Weaning weight was the most strongly affected trait similar to NW. It also showed a quadratic response to AvgTmean, with an optimum value in the same temperature interval as NW and a strong decline in weaning weight with temperatures higher than 21°C (-14 g/°C). There were no differences on the effect of heat at different stages of lactation on NW and AvgWW. The impact of high environmental temperatures on prolificacy is alleviated if a drop in temperature is produced during the day. Thus, the effect of AvgRg was relevant and positive for TB and NW. However, it had a quadratic negative effect for AvgWW at late lactation. The temperature variation between days within a period has a positive effect on TB and AvgWW but a negative effect on NW when it is produced at middle lactation, whereas there is no effect at other stages of lactation.

Genetic correlation between growth and female and male contributions to fertility in rabbit.

A Bayesian bivariate Linear-Threshold Animal Model was implemented to determine the genetic correlation between fertility (F), defined as success or failure to conceive, and average daily gain (ADG) in a rabbit line selected for ADG. A total of 27 234 records of F from 7895 females and 1293 males, and 114 135 records of ADG were used for the analysis. The pedigree included 114 485 animals. The model used for ADG included the systematic effects of year-season, parity order and number of kids born alive, the animal additive effect, the maternal and paternal permanent environmental effects, the common litter permanent environmental effect and the residual. The model for the liability of F included the systematic effects of year-season and physiological status of the female, the female and male additive genetic effects, the female and male permanent environmental effects and the residual, which was divided into a permanent environmental effect related to the common litter effect for ADG, and an independent term. The estimated heritabilities were 0.15 for ADG and 0.07 and 0.04 for the female and male contributions to F, respectively. Male and female contributions to F had a positive genetic correlation (0.34). The genetic correlation between ADG and the female component of F was low to moderate and negative (-0.31), whereas it was null for the male contribution to F. Thus, it is expected that only the female contribution to reproductive performance may be impaired by selection for ADG in rabbit lines.

ATM and DNA-PKcs make a complementary couple in DNA double strand break repair.

The interplay between ATM and DNA-PKcs kinases during double strand breaks (DSBs) resolution is still a matter of debate. ATM and DNA-PKcs participate differently in the DNA damage response pathway (DDR), but important common aspects are indeed found: both of them are activated when faced with DSBs, they share common targets in the DDR and the absence of either kinase results in faulty DSB repair. Absence of ATM translates into timely repair that, nevertheless, is incomplete. On the other hand, DNA-PKcs absence translates into slower repair, which in turn gives rise to the accumulation of simple and complex reorganizations. These outcomes confirm that the function of both protein kinases is essential to guarantee genome integrity. Interestingly, V(D)J and CSR recombination events provide a powerful tool to study the interplay between both kinases in DSB repair. Although the physiological DSBs generated during V(D)J and CSR recombination are resolved by the non-homologous end-joining (NHEJ) repair pathway, ATM absence during these events translates into chromosome translocations. These results suggest that NHEJ accuracy is threatened in the absence of ATM, which may play a role in avoiding illegitimate repair by favouring the joining of the correct DNA ends. Indeed, simultaneous DNA-PKcs and ATM deficiency during V(D)J and CSR recombination translates into a synergistic increase in potentially dangerous chromosomal translocations and deletions. Although the exact nature of their interaction remains elusive, the evidence indicates that ATM and DNA-PKcs play complementary roles that allow complete and legitimate DSB repair to be reached. Faithful repair can only be achieved by the presence and correct functioning of both kinases: while DNA-PKcs ensures fast rejoining, ATM guarantees complete repair.

Genetic basis of semen traits and their relationship with growth rate in rabbits.

This work aims to estimate the genetic parameters of seminal and production traits in a paternal line of rabbits selected for ADG during the fattening period. The considered traits were male libido (Lib) defined as successful mounting of an artificial vagina; presence of urine (Ur) and calcium carbonate deposits (Ca) in the ejaculate; semen pH; individual sperm motility (IM); the suitability for AI of the ejaculate (Sui), which involves the subjective combination of several quality traits; the average ejaculate volume (Vol); sperm concentration (Conc); and the average sperm production per ejaculate (Prod = Vol × Conc). The genetic relationship between all of these traits with ADG is also provided. Male libido and seminal data came either from routine evaluations of the ejaculates in an AI center or from 2 experiments in which bucks from the same population were used. Two consecutive ejaculates per male and per week were collected, leaving 7 d within weekly collections. A linear tri-trait model was used to analyze Conc, Vol, and ADG, whereas linear and threshold-linear 2-trait models were used to analyze male libido and the remaining seminal traits with ADG. A Bayesian approach was adopted for inference. Approximately 38% of ejaculates were rejected for AI primarily due to low IM scores. Variables related to the quality of the ejaculate (Ur, Ca, pH, IM, Sui) and Lib were found to be lowly heritable (h(2) ranged from 0.04 to 0.11), but repeatable. This indicates performance of bucks for seminal quality traits and libido in AI centers would be more strongly affected by management practices rather than genetic selection. Semen production traits exhibited moderate values of h(2) (0.22, 0.27, and 0.23 for Conc, Vol, and Prod, respectively), suggesting the possibility of effective selection for these traits. A moderate to high negative genetic correlation (r(g); posterior mean; highest posterior density at 95%, HPD(95%)) was estimated between Conc and Vol (-0.53, HPD(95%) = -0.76, -0.27). The ADG was estimated to have an h(2) of 0.16, to have a low, positive r(g) with Conc (0.21, HPD(95%) = -0.03, 0.48), to have a low, negative r(g) with Vol (-0.19, HPD(95%) = -0.47, 0.08), and to be genetically uncorrelated with all remaining traits analyzed. Therefore, selection for increasing ADG in paternal lines is expected to have no detrimental effects on Ur, Ca, pH, IM, Sui, and Lib and little to no effect on Conc, Vol, and Prod.

Using the product threshold model for estimating separately the effect of temperature on male and female fertility.

Animals under environmental thermal stress conditions have reduced fertility due to impairment of some mechanisms involved in their reproductive performance that are different in males and females. As a consequence, the most sensitive periods of time and the magnitude of effect of temperature on fertility can differ between sexes. The objective of this study was to estimate separately the effect of temperature in different periods around the insemination time on male and on female fertility by using the product threshold model. This model assumes that an observed reproduction outcome is the result of the product of 2 unobserved variables corresponding to the unobserved fertilities of the 2 individuals involved in the mating. A total of 7,625 AI records from rabbits belonging to a line selected for growth rate and indoor daily temperature records were used. The average maximum daily temperature and the proportion of days in which the maximum temperature was greater than 25°C were used as temperature descriptors. These descriptors were calculated for several periods around the day of AI. In the case of males, 4 periods of time covered different stages of the spermatogenesis, the transit through the epididymus of the sperm, and the day of AI. For females, 5 periods of time covered the phases of preovulatory follicular maturation including day of AI and ovulation, fertilization and peri-implantational stage of the embryos, embryonic and early fetal periods of gestation, and finally, late gestation until birth. The effect of the different temperature descriptors was estimated in the corresponding male and female liabilities in a set of threshold product models. The temperature of the day of AI seems to be the most relevant temperature descriptor affecting male fertility because greater temperature records on the day of AI caused a decrease in male fertility (-6% in male fertility rate with respect to thermoneutrality). Departures from the thermal zone in temperature descriptors covering several periods before AI until early gestation had a negative effect on female fertility, with the pre- and peri-implantational period of the embryos being especially sensitive (from -5 to -6% in female fertility rate with respect to thermoneutrality). The latest period of gestation was unaffected by the temperature. Overall, magnitude and persistency of the temperatures reached in the conditions of this study do not seem to be great enough to have a large effect on male and female rabbit fertility.

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.

Product versus additive model for studying artificial insemination results in several livestock populations.

Two models can be used for studying binary results of AI. The additive threshold model proposes an underlying variable as summing the environmental and genetic effects from the 2 individuals involved in the mating, and the product threshold model assumes that the conditional probability of AI success is the product of the probabilities of success of 2 unobserved binary phenotypes (one is the male fertility; the other is the female fertility). The purpose of this paper is to compare the predictive ability of the product and the additive threshold models for studying AI results and to compare results obtained with the 2 models in 3 different species: cattle, sheep, and rabbits. Results showed that the predictive ability of the product model is similar to the additive model in sheep and rabbits but worst in cattle (percentage of wrong prediction = 42, 27, and 35% in the additive model; 43, 28, and 47% in the product model in sheep, rabbits, and cattle, respectively). Even when the 2 models have similar performance, they differed in their EBV (for instance, Pearson correlation between EBV predicted with the 2 models = 0.46 in sheep for male fertility). The product model can determine which sex is responsible for an AI failure. In sheep, the female was the responsible in 94% of the cases and male in 2% of them; in rabbits, the female was the responsible in 54% of the cases and the male in 39% of them. Different estimates of probabilities for male and female fertility success obtained with the product model in the 3 species suggest that male and female fertilities behave differently depending on the species and the uniqueness of the data sets. Although product model seems to provide additional information in the fertility process, further research is needed to understand the worst performance of the product model in cattle.

Interaction of genotype × artificial insemination conditions for male effect on fertility and prolificacy.

Failures in fertilization or embryogenesis have been shown to be partly the result of poor semen quality. When AI is practiced, fertilization rate depends on the number and quality of spermatozoa in the insemination dose around the time of application. Individual variation in the male effect on fertility (success or failure to conceive; Fert) and prolificacy (total number of kids born per litter; TB) could also depend on these factors, and it could be better observed under limited conditions of AI, such as decreased sperm concentration, small or null preselection of ejaculates for any semen quality trait, or a long storage period of the AI doses. The aim of this research was to determine if an interaction existed between male genotype and the AI conditions for male effects on Fert and TB after AI was performed under different conditions. Fertility and TB were assumed to be different traits and were analyzed in 2 sets of independent analyses. In the first step, the different conditions were determined uniquely by the sperm dosage. Artificial insemination was performed at 10 and 40 × 10(6) spermatozoa/mL. In the second step, the different conditions were determined by all the factors involved in the AI process as a whole (conditions and duration of the storage period of the dose, genetic type of the female, and environmental conditions on the farm). Data from AI from the former experiment were analyzed with data from AI performed under different conditions. Threshold and linear 2-trait models were assumed for Fert and TB, respectively. The sperm dosage had a clear effect on Fert and TB, which favored the greater dosage (+0.13% and +1.25 kids born, respectively). Prolificacy was more sensitive to sperm reduction than was fertility. Male heritabilities for Fert were 0.09 for both sperm dosages, and were 0.08 and 0.06 for male TB with a smaller and larger sperm dosage, respectively. No genotype × sperm dosage interaction was found. Therefore, the same response to selection to improve male Fert and TB could be achieved at any sperm concentration. However, an interaction between male genotype and the AI conditions as a whole seemed to exist, indicating that the AI conditions for selection for Fert and TB could be modified to maximize genetic progress. Consequently, the optimization of a breeding program for male Fert and TB under a given set of semen utilization conditions is achievable.

Telomere dysfunction and chromosome structure modulate the contribution of individual chromosomes in abnormal nuclear morphologies.

The cytokinesis-block micronucleus assay has emerged as a biomarker of chromosome damage relevant to cancer. Although it was initially developed to measure micronuclei, it is also useful for measuring nucleoplasmic bridges and nuclear buds. Abnormal nuclear morphologies are frequently observed in malignant tissues and short-term tumour cell cultures. Changes in chromosome structure and number resulting from chromosome instability are important factors in oncogenesis. Telomeres have become key players in the initiation of chromosome instability related to carcinogenesis by means of breakage-fusion-bridge cycles. To better understand the connection between telomere dysfunction and the appearance of abnormal nuclear morphologies, we have characterised the presence of micronuclei, nucleoplasmic bridges and nuclear buds in human mammary primary epithelial cells. These cells can proliferate beyond the Hayflick limit by spontaneously losing expression of the p16(INK4a) protein. Progressive telomere shortening leads to the loss of the capping function, and the appearance of end-to-end chromosome fusions that can enter into breakage-fusion-bridge cycles generating massive chromosomal instability. In human mammary epithelial cells, different types of abnormal nuclear morphologies were observed, however only nucleoplasmatic bridges and buds increased significantly with population doublings. Fluorescent in situ hybridisation using centromeric and painting specific probes for chromosomes with eroded telomeres has revealed that these chromosomes are preferentially included in the different types of abnormal nuclear morphologies observed, thus reflecting their common origin. Accordingly, real-time imaging of cell divisions enabled us to determine that anaphase bridge resolution was mainly through chromatin breakage and the formation of symmetric buds in daughter nuclei. Few micronuclei emerged in this cell system thus validating the scoring of nucleoplasmic bridges and nuclear buds for measuring chromosome instability in telomere-dysfunction cell environments.

The number of dysfunctional telomeres in a cell: one amplifies; more than one translocate.

Chromosomal instability is increasingly appreciated as a key component of tumorigenesis in humans. A combination of abnormal telomere shortening and cell-cycle checkpoint deficiency has been proposed as the initial lesions causing destabilizing chromatin bridges in proliferative cells. We examined the participation of the different types of end-to-end fusions in generating instable karyotypes in non-transformed human breast epithelial cells. We concluded that short dysfunctional telomeres represent an initiating substrate for post-replicative rejoining of sister chromatids and are likely to make an important contribution to the formation of chromosomal rearrangements and the amplification of chromosome arm segments in breast epithelial cells. We propose that there is a chronological order in the participation of the different types of end-to-end fusions in the generation of chromosomal instability. Thus, intrachromosomal post-replicative joining would proceed mainly in the early stages after overcoming growth arrest, when telomere dysfunction is limited and affects only one chromosome end in a cell. The absence of a second substrate for end joining will conduct the cell with the uncapped chromosome to replicate its DNA and fuse the uncapped sister chromatids after replication. Later, since telomeres shorten progressively with each DNA replication round, the uncapping will affect many more chromosome ends, and fusions between the uncapped ends from different chromosomes will be produced. While the fusion of sister chromatids will produce chromosome segment amplification and terminal deletions in the daughter cells, interchromosomal fusion will produce unbalanced rearrangements other than chromosome segment amplifications.

Radiation-induced chromosome breaks in ataxia-telangiectasia cells remain open.

PURPOSE: To determine if broken chromosome-end healing mechanisms through the addition of new telomeric sequences exist in cells having difficulties in rejoining the ends of broken chromosomes. MATERIALS AND METHODS: A full-colour painting protocol of all human chromosomes by FISH was combined with a telomeric and centromeric labelling using PNA probes to characterize the rejoining pattern and telomere status of radiation-induced chromosome breaks in ataxia-telangiectasia (A-T) and normal lymphoblastoid cell lines. RESULTS: It was first established that the cell lines used for chromosome healing analysis were chromosomally stable. FISH analysis provided evidence that the frequency of deleted chromosomes, apparently unrejoined, was much higher in A-T than in normal cells, as expected by the role of ATM in cell-cycle control, as well as in DNA repair. In spite of their high frequency, broken chromosome ends in A-T cells do not seem to act as substrates for telomerase since additional terminal telomere sequences (more than the 92 expected pairs) indicative of chromosome healing were never observed. Broken chromosome ends in A-T cells remained open. CONCLUSION: The disability of cells to rejoin broken chromosome ends does not lead to the healing of DSBs by the acquisition of new telomeric sequences.

Absence of chromosomal instability in spermatozoa of men affected by testicular cancer.

Testicular germ cell cancer affects mainly young men. It is the most frequent type of cancer in 20-35 year old men. Since cancer treatment using antineoplasic drugs and ionizing radiation has a negative effect on the function of the gonads, testicular cancer patients are offered the opportunity to cryopreserve their semen samples before the beginning of therapy. For this reason it would be of interest to know whether there is chromosome instability in their spermatozoa prior to any treatment. Using the interspecific human-hamster fertilization system, we have analysed a total of 340 chromosome complements from spermatozoa of control donors and 320 chromosome complements from testicular cancer patients. There were no significant differences in the frequencies of chromosomal aberrations between controls and cancer patients (9.7 and 10.3% respectively; P = 0.4921). Our results indicate that spermatozoa from untreated testicular cancer patients do not show an increased chromosomal instability as compared to control donors.