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.     

Effect of age and parity on litter size in pigs

Litter size increased (P less than 0.01) as the age of the dam at farrowing increased. However, previous reproductive experience (parity) had no direct effect on litter size of dams of the same age.     

Effect of average litter weight in pigs on growth performance,carcass characteristics and meat quality of the offspring as depending on birth weight

Offspring born from normal litter size (10 to 15 piglets) but classified as having lower than average birth weight (average of the sow herd used: 1.46 ± 0.2 kg; mean ± s.d.) carry at birth negative phenotypic traits normally associated with intrauterine growth restriction, such as brain-sparing and impaired myofiber hyperplasia. The objective of the study was to assess long-term effects of intrauterine crowding by comparing postnatal performance, carcass characteristics and pork quality of offspring born from litters with higher (>1.7 kg) or lower (<1.3 kg) than average litter birth weight. From a population of multiparous Swiss Large White sows (parity 2 to 6), 16 litters with high (H = 1.75 kg) or low (L = 1.26 kg) average litter birth weight were selected. At farrowing, two female pigs and two castrated pigs were chosen from each litter: from the H-litters those with the intermediate (H_I = 1.79 kg) and lowest (H_L = 1.40 kg) birth weight, and from L-litters those with the highest (L_H = 1.49 kg) and intermediate (L_I = 1.26 kg) birth weight. Average birth weight of the selected H_I and L_I piglets differed (P < 0.05), whereas birth weight of the H_L- and L_H-piglets were similar (P > 0.05). These pigs were fattened in group pen and slaughtered at 165 days of age. Pre-weaning performance of the litters and growth performance, carcass and meat quality traits of the selected pigs were assessed. Number of stillborn and pig mortality were greater (P < 0.05) in L- than in H-litters. Consequently, fewer (P < 0.05) piglets were weaned and average litter weaning weight decreased by 38% (P < 0.05). The selected pigs of the L-litters displayed catch-up growth during the starter and grower–finisher periods, leading to similar (P > 0.05) slaughter weight at 165 days of age. However, H_L-gilts were more feed efficient and had leaner carcasses than H_I-, L_H- and L_I-pigs (birth weight class × gender interaction P < 0.05). Meat quality traits were mostly similar between groups. The marked between-litter birth weight variation observed in normal size litters had therefore no evident negative impact on growth potential and quality of pigs from the lower birth weight group.     

Bayesian analysis of response to selection: a case study using litter size in Danish Yorkshire pigs

Implementation of a Bayesian analysis of a selection experiment is illustrated using litter size [total number of piglets born (TNB)] in Danish Yorkshire pigs. Other traits studied include average litter weight at birth (WTAB) and proportion of piglets born dead (PRBD). Response to selection for TNB was analyzed with a number of models, which differed in their level of hierarchy, in their prior distributions, and in the parametric form of the likelihoods. A model assessment study favored a particular form of an additive genetic model. With this model, the Monte Carlo estimate of the 95% probability interval of response to selection was (0.23; 0.60), with a posterior mean of 0.43 piglets. WTAB showed a correlated response of -7.2 g, with a 95% probability interval equal to (-33.1; 18.9). The posterior mean of the genetic correlation between TNB and WTAB was -0.23 with a 95% probability interval equal to (-0.46; -0.01). PRBD was studied informally; it increases with larger litters, when litter size is >7 piglets born. A number of methodological issues related to the Bayesian model assessment study are discussed, as well as the genetic consequences of inferring response to selection using additive genetic models.     

Genetic parameters for canalisation analysis of litter size and litter weight traits at birth in mice

The aim of this research was to explore the genetic parameters associated with environmental variability for litter size (LS), litter weight (LW) and mean individual birth weight (IW) in mice before canalisation. The analyses were conducted on an experimental mice population designed to reduce environmental variability for LS. The analysed database included 1976 records for LW and IW and 4129 records for LS. The total number of individuals included in the analysed pedigree was 3997. Heritabilities estimated for the traits under an initial exploratory approach varied from 0.099 to 0.101 for LS, from 0.112 to 0.148 for LW and from 0.028 to 0.033 for IW. The means of the posterior distribution of the heritability under a Bayesian approach were the following: 0.10 (LS), 0.13 (LW) and 0.03 (IW). In general, the heritabilities estimated under the initial exploratory approach for the environmental variability of the analysed traits were low. Genetic correlations estimated between the trait and its variability reached values of -0.929 (LS), -0.815 (LW) and 0.969 (IW). The results presented here for the first time in mice may suggest a genetic basis for variability of the evaluated traits, thus opening the possibility to be implemented in selection schemes.     

FUT1基因多态性及其与产仔性状的关联性研究

采用PCR-RFLP技术6个中外品种共245头猪的FUT1基因进行了研究, 结果表明, Hin 6Ⅰ位点上, 大白猪、长白猪和杜洛克猪3个外来猪种均存在多态, 且以敏感型(GG型和AG型)居多; 山西黑猪、太原花猪和马身猪3个本地猪种的所有检测样品都表现为GG型。用方差分析方法分析FUT1基因型、品种和胎次与产仔性状之间的关系, 基因型和品种对猪的总产仔数的影响显著, 胎次对总产仔数影响不显著。而基因型、品种和胎次对产活仔数影响均不显著。     

Genetic determinism for within-litter birth weight variation and its relationship with litter weight and litter size in the Ripollesa ewe breed

Birth weight plays a central role in lamb survival and growth, and the knowledge of its genetic determinism has become essential in worldwide selection programmes. Within this context, within-litter birth weight variation (BWV) has been suggested as an attractive trait to homogenise litters in prolific species, although it has not been analysed in sheep. The objective of this study was to ascertain whether maternal additive genetic variance exists for BWV in Ripollesa ewes, and to study its genetic, permanent environmental and residual relationships with litter weight (LW) and litter size (LS) at birth. Data were recorded in the Ripollesa experimental flock of the Universitat Autònoma of Barcelona, between 1986 and 2005, and included 1 662 litters from 380 ewes, with 712 records of BWV and 1 530 records of LW. Traits were analysed with a multivariate animal model solved through Bayesian methodologies, and with a threshold characterisation of LS. Additionally, the effect of BWV on lamb survival was studied. Additive genetic variance was observed for BWV (h² = 0.061), as well as for LW (h² = 0.200) and LS (h² = 0.141). Nevertheless, genetic correlations among those traits were not substantial (BWV and LW = 0.151; BWV and LS = − 0.219; LW and LS = − 0.320) and suffered from a high degree of uncertainly, with the null correlation included within the highest posterior interval at 95%. Within-litter birth weight variation and LS showed a negative and large permanent environmental correlation ( − 0.872), and LW and LS were negatively correlated due to residual ( − 0.762) and permanent environmental ( − 0.449) random sources of variation. Within-litter birth weight variation influenced lamb mortality during the first 7 days of life (P < 0.05), increasing and decreasing survivability in heavier and lighter littermates, respectively. Nevertheless, stillbirths and lambs died after the 1st week of life were not affected by BWV (P>0.05). The low heritability found indicates that slow genetic progress may be expected from selecting for BWV. Close to zero genetic correlations suggest that this selection will probably not affect LS and LW, although some significant permanent and residual correlations must be taken into account. Further studies are needed to understand better the genetic architecture among these three reproductive traits.     

Response to selection for litter size in Danish Landrace pigs: a Bayesian analysis

A replicated selection experiment aimed at increasing litter size (total number of pigs born per litter) in Danish Landrace pigs was conducted from 1984 to 1991. The experiment included two selection and two control lines. In each generation, 30 and 14 first litters were produced in selection and control lines, respectively, and dams produced two litters. Each replicate, consisting of one selection and one control line, was founded from 60 families chosen randomly from the population at large. Family selection was practiced, and the criterion was the predicted breeding value for litter size computed using a repeatability animal model, and taking into account all available information. The data consisted of 947 records from 523 dams (424 dams had two litters) representing five cycles of selection of increased litter size. Data were analyzed from a Bayesian perspective, based on marginal posterior distributions of genetic parameters of interest. Marginalization was achieved using Gibbs sampling, with a single chain length of 1 205 000. After discarding the first 5 000 iterations, a sample was drawn every ten iterations, so 120 000 samples in total were saved. Densities were estimated and plotted, and summary statistics were computed from the estimated densities. The posterior means (± standard error) of heritability and repeatability were 0.22 ± 0.06 and 0.32 ± 0.05, respectively. These point estimates of genetic parameters were within the range of literature values, although on the high side. The posterior mean (± standard error) of genetic response to selection, defined as the difference between the mean breeding values of the selected lines and that of the base population, was 1.37 ± 0.43 pigs after five cycles of selection. The regression (through the origin) of breeding values in the selected lines on generation was 0.25 ± 0.08 pigs. Several informative priors constructed from information obtained with field data in this population were used to examine their influence on inferences. The priors were influential because of the relatively small scale of the experiment. An analysis excluding data from one of the control lines gave smaller genetic variance and heritability, and a smaller response to selection. However, it appears that selection for litter size is effective, but that the true rate of response is probably smaller than data from this experiment suggest.     

The imprinted gene DIO3 is a candidate gene for litter size in pigs

Genomic imprinting is an important epigenetic phenomenon, which on the phenotypic level can be detected by the difference between the two heterozygote classes of a gene. Imprinted genes are important in both the development of the placenta and the embryo, and we hypothesized that imprinted genes might be involved in female fertility traits. We therefore performed an association study for imprinted genes related to female fertility traits in two commercial pig populations. For this purpose, 309 SNPs in fifteen evolutionary conserved imprinted regions were genotyped on 689 and 1050 pigs from the two pig populations. A single SNP association study was used to detect additive, dominant and imprinting effects related to four reproduction traits; total number of piglets born, the number of piglets born alive, the total weight of the piglets born and the total weight of the piglets born alive. Several SNPs showed significant (q-value < 0.10) additive and dominant effects and one SNP showed a significant imprinting effect. The SNP with a significant imprinting effect is closely linked to DIO3, a gene involved in thyroid metabolism. The imprinting effect of this SNP explained approximately 1.6% of the phenotypic variance, which corresponded to approximately 15.5% of the additive genetic variance. In the other population, the imprinting effect of this QTL was not significant (q-value > 0.10), but had a similar effect as in the first population. The results of this study indicate a possible association between the imprinted gene DIO3 and female fertility traits in pigs.     

Influence of SLA haplotype on ovulation rate and litter size in miniature pigs

Systemic blood was collected from and surgery performed on sows of 3 strains of miniature swine bred for specific SLA (swine MHC) haplotypes (a, c and d) from Day 2 to Day 6 after mating (first day of mating = Day 0). Ovulation rate was determined by counting corpora lutea and embryos were flushed from the uterus. Progesterone, oestradiol-17 beta and oestrone were quantitated in blood plasma and uterine flushings by RIA. SLAd/d females had a higher ovulation rate than SLAa/a or SLAc/c females (11.50 +/- 0.87 vs 9.11 +/- 0.68 and 8.17 +/- 0.83, respectively; P less than 0.01). Oestrone was higher than oestradiol-17 beta in systemic plasma (56.5 +/- 6.4 vs 33.0 +/- 4.7 pg/ml, P less than 0.01) while oestradiol-17 beta was higher than oestrone in uterine flushings (19.8 +/- 1.4 vs 14.9 +/- 1.5 pg/horn, P less than 0.10). Systemic progesterone concentration was correlated with day after mating (r = 0.93, P less than 0.01). There was no effect of haplotype on any of the hormone concentrations measured. Litter size was analysed from 99 matings amongst SLAa/a, SLAa/c, SLAa/d, SLAd/c and SLAd/d sires and dams. Litter size from -/d and d/d sows or from d/d boars were larger (P less than 0.05) than for all other matings. Although ovulation rate was higher in SLAd/d sows, the significant effect of sire SLA genotype on litter size suggests an additional effect of the d haplotype on embryonic survival.     

A SNP in the miR-27a gene is associated with litter size in pigs

MicroRNAs (miRNAs) are 20–25 nt, endogenous non-coding RNA molecules that act by binding to the complementary sequence of target messenger RNAs. Many evidences showed that miRNAs were involved in the process of germ proliferation and differentiation. In the present study, miR-27a gene was selected as a candidate gene for litter size due to its biological function, its location near a mummified pigs QTL, and its differentially expressed profile in Large White and Chinese Erhualian PMSG-hCG stimulated preovulatory ovaries. By comparative sequencing of miR-27a gene in Large White and Chinese Meishan pigs, one SNP (T/C) which created an additional HpaII site was detected. Then associations of this SNP with litter size traits were assessed in Large White (n = 142) and DIV (n = 140) pig populations. The statistical analysis demonstrated that AA differed from AB (P < 0.01) and BB (P < 0.05) for total number of piglets born in the first parities, and also differed from AB (P < 0.01) for the number of piglets born alive in all parities (P < 0.05) in DIV pigs. No significant difference was observed between different genotypes in Large White pigs.     

Effects of aminoglutethimide phosphate on litter size and birth weight in superovulated rats

In this study, litter sizes, birth weights and survival rates of neonates in superovulated rats treated with aminoglutethimide phosphate (AGP) were studied. Young (8- to 9-week old) and adult (14- to 16-week old) rats were treated with 20 or 40 IU PMSG between 1100 and 1300 hours on the day of early diestrus, followed by identical doses of hCG 52 to 54 hours later. These rats received 10 mg AGP on Days 0 to 2 of pregnancy (AGP rats). The duration of pregnancy in the AGP-treated and control rats was about the same. Mean live litter sizes in young and in adult AGP rats treated with 20 IU PMSG and 20 IU hCG were significantly higher (15.5 and 15.4; P<0.01) than in the control rats (11.5 and 12.6). When AGP was given to young and adult rats pretreated with 40 IU PMSG and 40 IU hCG, they produced means of 17.7 and 17.3 live neonates, respectively. The birth weights for young (5.55 to 5.88 g) and adult (5.89 to 5.96 g) AGP rats were smaller than those of respective control rats (6.44 and 6.40 g; P < 0.05-0.01). When the number of neonates was adjusted to 8 per dam for nursing and rearing, all of them were alive at 5 weeks after birth and showed normal growth. However, body weight gains of the progeny of AGP dams were lower than those of controls. These results indicate that rats treated with large doses of gonadotropins and AGP produce larger litter sizes than nontreated controls.     

Selection response for litter size at birth and litter weight at weaning in the first parity in mice

Summary Five 60-pair lines of mice were selected for seven generations for the following criteria: number born alive (LSO), random selection of litters (LC), number born alive divided by the weight of the dam at 9 weeks (LSO/DWT), total litter weight weaned divided by the weight of the dam at 9 weeks (LWT/DWT), and weight of litter weaned (LWT). All traits were measured in the first parity only and litters were not standardized. Realized heritabilities for LSO, LWT, LSO/DWT, and LWT/ DWT were 0.10± 0.06, 0.11±0.07, 0.22 ± 0.04, and 0.22 ± 0.08, respectively. Selection response for the two ratio lines was due to correlated responses in the respective numerators, LSO and LWT, as DWT did not decrease. In terms of improving LWT, selection for LWT/ DWT was three times as effective as selection for LSO/ DWT.     

Single-trait and antagonistic index selection for litter size and body weight in mice

Individual selection based on female performance only was conducted in four lines of mice: L⁺ for increased litter size, W⁺ for increased 6-week body weight, L^-W⁺ for a selection index aimed at decreasing litter size and increasing 6-week body weight and L⁺W^- for a selection index aimed at increasing litter size and decreasing 6-week body weight. A fifth line (K) served as an unselected control. All litters were standardized to eight mice at one day of age. Expected heritability was based on twice the regression of offspring on dam (h²_d), which contains additive genetic variance due to direct (σ²_Ao) and maternal (σ²_Am) effects and their covariance (σ_AoAm). Responses and correlated responses were measured either deviated (method 1) or not deviated (method 2) from the control line. Realized heritabilities (h²_R) for litter size were 0.19 ± 0.04 (1) and 0.16 ± 0.03 (2), which were similar to h ²_d of 0.17 ± 0.04. The h² _R for 6-week body weight of 0.55 ± 0.07 (1) and 0.44 ± 0.07 (2) agreed with h²_d of 0.42 ± 0.02. Realized genetic correlations (r*_GR) between litter size and 6-week body weight calculated from the double-selection experiment were 0.52 ± 0.10 (1) and 0.52 ± 0.13 (2), which were not significantly different from the base population estimate of r* _Gd = 0.63 ± 0.14. Divergence (L^-W ⁺ minus L⁺W^-) in the antagonistic index selection lines was 0.21 ± 0.01 index units (I = 0.305 P_W - 0.436 P_L, where P _W and P_L are the phenotypic values for 6-week body weight and litter size, respectively.). The h² _R of index units of 0.14 ± 0.02 calculated from divergence agreed with h²_d of 0.14 ± 0.04. Divergences in litter size (-0.19 ± 0.07) and 6-week body weight (0.46 ± 0.10) were in the expected direction. Antagonistic index selection yielded about one-half the expected divergence in litter size, while divergence in 6-week body weight was only slightly less than expected. Realized genetic correlations indicated that litter size, 6-week body weight and index units each showed positive pleiotropy with 3-week body weight, postweaning gain and weight at vaginal introitus and negative pleiotropy with age at vaginal introitus. Sex ratio and several components of fitness (days from joining to parturition, percent fertile matings and percent perinatal survival) did not change significantly in the selected lines.     

Selection for litter size and litter birthweight in Large White pigs: Maximum,mean and variability of reproduction traits

Gradually increasing trend of litter size poses a challenge to pig farmers in terms of managing larger litters. Therefore, it seems that a balanced approach that optimises litter size, litter birthweight, and uniformity of those traits is needed in order to address animal welfare and farm management concerns. This study aimed to investigate this issue by defining several traits for total number born (TNB), number born alive (NBA) and litter birthweight (LW). First, the highest value from at least five records per sow was selected as maximum (max) value for each reproduction trait. Second, a mean (mean) for each reproduction trait was calculated per sow. Last, the variability of reproduction traits between parities of the sow was calculated as log-transformed variance of residuals of all observations per sow for each reproduction trait (LnVar). In total, 23 193 Large White sows from Topigs Norsvin with 152 282 litter records were used for analysis in ASReml 4.1. Also, a simulation of breeding schemes was performed with the use of SelAction 2.1 and estimates from genetic analysis. Maximum value of reproductive traits had a much higher heritability than repeated observations or mean of reproduction traits, e.g., 0.31 for maxTNB vs. 0.12 for TNB and 0.07 for meanTNB, which allows for a faster response under selection. The maximum value traits, however, were found to carry more risks, i.e. higher ratio of stillborn (not for maxNBA) and increased variability of traits. Thus, using them in breeding programme should be carefully considered. The genetic coefficient of variation on SD level estimated to indicate the genetic magnitude for variability phenotypes indicated a maximum change of 6–9% in genetic SD of TNB, NBA and LW. The genetic correlations between mean and corresponding variability traits varied from 0.66 to 0.74, whereas the correlation between other mean and variability traits ranged from 0.33 to 0.99. The simulation indicated that even with selection targeted against the variability of reproduction traits, a very limited change should be expected due to a complex genetic and phenotypic relationship between the traits. In the scenarios with selection against LnVarTNB and LnVarLW, this was a decrease of 0.1–0.6% per year, whereas in scenario with selection against LnVarNBA, the range was 0.6–1.1% per year. It is still possible to increase litter size and birthweight further, however, a balance between mean and variability of reproduction traits is required, which can be obtained only by a very well designed breeding programme.     

Bayesian inference of genetic parameters and selection response for litter size components in pigs.

Three contemporary lines were formed from the progeny of 50 French Large White sows. In the first line, gilts were selected for ovulation rate at puberty. In the second line, they were selected for prenatal survival of the first two parities, corrected for ovulation rate. The control constituted the third line. Ovulation rate at puberty was analyzed using an animal model with a batch effect. Prenatal survival was analyzed with a repeatability animal model that included batch and parity effects. Flat priors were used to represent vague previous knowledge about parity and batch effects. Additive and residual effects were represented assuming that they were a priori normally distributed. Variance components were assumed to follow either uniform or inverted chi-square distributions, a priori. The use of different priors did not affect the results substantially. Heritabilities for ovulation rate ranged from 0.32 to 0.39, and from 0.11 to 0.16 for prenatal survival, depending on the prior used. The mean of the marginal posterior distribution of response to four generations of selection ranged from 0.38 to 0.40 ova per generation, and from 1.1 to 1.3% of the mean survival rate for average survival per generation.     

Chiasma frequency in strains of mice selected for litter size and for high body weight

Summary Chiasma frequency was measured in male mice of three outbred lines: FZt:DU (control); DU:6, selected for increased body weight; and DU:C, selected for high fertility. Chiasma frequency was seen to increase in the high body weight line, but decrease in the high fertility line. In both selected lines the intragroup variance in chiasma frequency increased while in DU:C the intracell variance was lower than in the control.     

LH receptor induction and ovulation rate in mice selected for litter size and body weight

Female mice from lines which had undergone long-term single trait and antagonistic index selection for litter size and body weight were analysed for ovulation rate and LH receptor induction. Compared to randomly selected controls, selection for large litter size increased ovulation rate (60%; P less than 0.001) and decreased LH receptor induction per microgram ovarian DNA (87%; P less than 0.01). Selection for large body weight increased ovulation rate (18%; P less than 0.001), but did not lead to a significant correlated response in LH receptor induction. Index selection for large litter size and small body weight increased ovulation rate (14%; P less than 0.01) and decreased LH receptor induction (72%; P less than 0.01), while index selection for small litter size and large body weight did not significantly alter either ovulation rate or LH receptor induction. LH receptor quantities in testes of males from the 5 lines did not exhibit the among-line profile which was observed in ovaries of females. These results confirm the role of ovulation rate in mediation of the positive genetic correlation between litter size and body weight in mice. Increased ovulation rate in mice selected for large litter size may be due to mechanisms associated with LH receptors as well as factors related to growth. In contrast, increased ovulation rate in mice selected for large body weight may be due exclusively to factors related to growth.