Search

The objective of this study was to examine the genetic basis of homogeneity in piglets and the genetic correlations with litter size and growth during lactation. Genetic parameters for variation in piglet BW within litters at birth and at 3 wk of age, and in the BW of individual piglets at 3 wk (BW3) were estimated from the Norwegian Landrace nucleus population. Data on BW3 were collected from 146,572 piglets from 14,045 litters in 58 herds. Body weight at birth and at 3 wk of age was recorded for 13,318 piglets from 5 nucleus herds. Litter data were evaluated using multivariate trait models. The heritability estimates for the SD of BW at birth and at 3 wk (SDBW3) were in agreement with the literature (0.10 and 0.08. respectively). The genetic correlation for the number of piglets born alive and the mean BW at 3 wk was negative (-0.40 [+ or -] 0.07), and the correlation of number of piglets born alive with SDBW3 was close to zero (-0.03 [+ or -] 0.11). The genetic correlation between the SD of BW at birth and SDBW3 was moderate (0.51 [+ or -] 0.31). The mean BW at birth was genetically correlated with mean BW at 3 wk (0.59 [+ or -] 0.16) but was independent of SDBW3 (0.08 [+ or -] 0.27). The estimates of direct and maternal heritability for BW3 were 0.03 and 0.07, respectively, and the genetic correlation between the 2 components was negative (-0.43 [+ or -] 0.10). The genetic correlation of SDBW3 with the maternal effect on BW3 was positive and strong (0.66 [+ or -] 0.08), whereas a negative correlation was found with the direct effect on BW3 (-0.18 [+ or -] 0.14). These results suggest that it is possible to select for mean BW at birth without an increase in within-litter heterogeneity at 3 wk of age. A more efficient strategy would be to consider both the direct and the maternal effects on BW3 in the genetic evaluation, together with SDBW3. Thus, it is possible to avoid the increase in within-litter heterogeneity that would occur as a result of selection performed at 3 wk on a litter trait such as mean BW. Key words: genetic correlation, growth, heterogeneity, piglet body weight, sow, within-litter standard deviation doi: 10.2527/jas.2009-2056

Correlated effects of selection for components of litter size on growth and backfat thickness were estimated using data from 3 pig lines derived from the same base population of Large White. Two lines were selected for 6 generations on either high ovulation rate at puberty (OR) or high prenatal survival corrected for ovulation rate in the first 2 parities (PS). The third line was an unselected control (C). Genetic parameters for individual piglet BW at birth (IWB); at 3 wk of age (IW3W); and at weaning (IWW); ADG from birth to weaning (ADGBW), from weaning to 10 wk of age (ADGPW), and from 25 to 90 kg of BW (ADGT); and age (AGET) and average backfat thickness (ABT) at 90 kg of BW were estimated using REML methodology applied to a multivariate animal model. In addition to fixed effects, the model included the common environment of birth litter, as well as direct and maternal additive genetic effects as random effects. Genetic trends were estimated by computing differences between OR or PS and C lines at each generation using both least squares (LS) and mixed model (MM) methodology. Average genetic trends for direct and maternal effects were computed by regressing line differences on generation number. Estimates of direct and maternal heritabilities were, respectively, 0.10, 0.12, 0.20, 0.24, and 0.41, and 0.17, 0.33, 0.32, 0.41, and 0.21 (SE = 0.03 to 0.04) for IWB, IW3W, IWW, ADGBW, and ADGPW. Genetic correlations between direct and maternal effects were moderately negative for IWB (-0.21 [+ or -] 0.18), but larger for the 4 other traits (-0.59 to -0.74). Maternal effects were nonsignificant and were removed from the final analyses of ADGT, AGET, and ABT. Direct heritability estimates were 0.34, 0.46, and 0.21 (SE = 0.03 to 0.05) for ADGT, AGET, and ABT, respectively. Direct and maternal genetic correlations of OR with performance traits were nonsignificant, with the exception of maternal correlations with IWB (-0.28 [+ or -] 0.13) and ADGPW (0.23 [+ or -] 0.11) and direct correlation with AGET (-0.23 [+ or -] 0.09). Prenatal survival also had low direct but moderate to strong maternal genetic correlations (-0.34 to -0.65) with performance traits. The only significant genetic trends were a negative maternal trend for IBW in the OR line and favorable direct trends for postweaning growth (ADGT and AGET) in both lines. Selection for components of litter size has limited effects on growth and backfat thickness, although it slightly reduces birth weight and improves postweaning growth. Key words: genetic parameter, growth, ovulation rate, pig, prenatal survival, selection experiment

Effects of selection for reproductive traits were estimated using data from 3 pig lines derived from the same Large White population base. Two lines were selected for 6 generations on high ovulation rate at puberty (OR line) or high prenatal survival corrected for ovulation rate in the first 2 parities (PS line). The third line was an unselected control line. Genetic parameters for age and BW at puberty (AP and WP); number of piglets born alive, weaned, and nurtured (NBA, NW, and NN, respectively); proportions of still-birth (PSB) and survival from birth to weaning (PSW); litter and average piglet BW at birth (LWB and AWB), at 21 d (LW21 and AW21), and at weaning (LWW and AWW) were estimated using REML methodology. Heritability estimates were 0.38 [+ or -] 0.03, 0.46 [+ or -] 0.03, 0.16 [+ or -] 0.01, 0.08 [+ or -] 0.01, 0.09 [+ or -] 0.01, 0.04 [+ or -] 0.01, 0.04 [+ or -]0.02, 0.19 [+ or -] 0.02, 0.10 [+ or -] 0.02, 0.10 [+ or -] 0.02, 0.36 [+ or -]0.02, 0.27 [+ or -] 0.01, and 0.24 [+ or -] 0.01 for AP, WP, NBA, PSB, NW, NN, PSW, LWB, LW21, LWW, AWB, AW21, and AWW, respectively. The measures of litter size showed strong genetic correlations ([r.sub.a] [greater than or equal to] 0.95) and had antagonistic relations with PSB ([r.sub.a] = -0.59 to -0.75) and average piglet BW ([r.sub.a] = -0.19 to -0.46). They also had strong positive genetic correlations with prenatal survival ([r.sub.a] = 0.67 to 0.78) and moderate ones with ovulation rate ([r.sub.a] = 0.36 to 0.42). Correlations of litter size with PSW were negative at birth but positive at weaning. The OR and PS lines were negatively related to PSW and average piglet BW. Puberty traits had positive genetic correlations with OR and negative ones with PS. Genetic trends were estimated by computing differences between OR or PS and control lines at each generation using least squares and mixed model methodologies. Average genetic trends were computed by regressing line differences on generation number. Significant (P < 0.05) average genetic trends were obtained in OR and PS lines for AP (respectively, 2.1 [+ or -] 0.9 and 3.2 [+ or -] 1.0 d/generation) and WP (respectively, 2.0 [+ or -] 0.5 and 1.8 [+ or -] 0.5 d/generation) and in the PS line for NBA (0.22 [+ or -] 0.10 piglet/generation). Tendencies (P < 0.10) were also observed for LWB (0.21 [+ or -] 0.12 kg/generation) and AWW (-0.25 [+ or -] 0.14 kg/generation) in the PS line. Selection on components of litter size can be used to improve litter size at birth, but result in undesirable trends for preweaning survival. Key words: genetic parameter, litter size, ovulation rate, piglet survival, pig, prenatal survival

Litter characteristics at birth were recorded in 4 genetic types of sows with differing maternal abilities. Eighty-two litters from [F.sub.1] Duroc x Large White sows, 651 litters from Large White sows, 63 litters from Meishan sows, and 173 litters from Laconie sows were considered. Statistical models included random effects of sow, litter, or both; fixed effects of sow genetic type, parity, birth assistance, and piglet sex, as well as gestation length, farrowing duration, piglet birth weight, and litter size as linear covariates. The quadratic components of the last 2 factors were also considered. For statistical analyses, GLM were first considered, assuming a binomial distribution of still-birth. Hierarchical models were also fitted to the data to take into account correlations among piglets from the same litter. Model selection was performed based on deviance and deviance information criterion. Finally, standard and robust generalized estimating equations (GEE) procedures were applied to quantify the importance of each effect on a piglet's probability of stillbirth. The 5 most important factors involved were, in decreasing order (contribution of each effect to variance reduction): difference between piglet birth weight and the litter mean (2.36%), individual birth weight (2.25%), piglet sex (1.01%), farrowing duration (0.99%), and sow genetic type (0.94%). Probability of stillbirth was greater for lighter piglets, for male piglets, and for piglets from small or very large litters. Probability of still-birth increased with sow parity number and with farrowing duration. Piglets born from Meishan sows had a lower risk of stillbirth (P < 0.0001) and were little affected by the sources of variation mentioned above compared with the 3 other sow genetic types. Standard and robust GEE approaches gave similar results despite some disequilibrium in the data set structure highlighted with the robust GEE approach. Key words: Bayesian generalized linear model, birth weight, farrowing duration, robust generalized estimating equation, stillbirth

Large White and Meishan sows differ in maternal ability and early piglet growth. We investigated the relationships between 100 maternal traits, grouped into 11 blocks according to the biological function they describe and litter growth over three successive periods after birth (D0-D1, D1-D3 and D3-D7; D0 starting at the onset of farrowing), as a measure of sow investment in early piglet production. Within- and between-breed variation was exploited to cover a maximum of the variability existing in pig maternal populations. The objective was to quantify the contribution of maternal traits, including functional traits and behavioural traits, to early litter growth. Multivariate analyses were used to depict correlations among traits. A partial least square multiblock analysis allowed quantifying the effect of maternal traits on early growth traits. Partial triadic analyses highlighted how sow behaviour changed with days, and whether it resulted in changes in litter growth. Several behavioural traits (standing activity, reactivity to different stimuli, postural activity) and functional traits (body reserves, udder quality) at farrowing contributed substantially to litter growth from D0 to D7. Sow aggression towards piglets and time spent standing at D0 were unfavourably correlated to D1-D3 litter growth. Time spent lying with udder exposed at D0 was favourably correlated to D1-D3 litter growth. The farrowing duration was negatively correlated to D0-D1 and D1-D3 litter growth. Furthermore, D3-D7 litter growth was positively correlated to feed intake in the same period. Several behavioural traits and some functional traits influence early litter growth. The contribution of sow behaviour was greater in the critical period around farrowing than in later days., (© 2024. The Author(s).)

Background: A fine balance of feto-maternal resource allocation is required to support pregnancy, which depends on interactions between maternal and fetal genetic potential, maternal nutrition and environment, endometrial and placental functions. In particular, some imprinted genes have a role in regulating maternal-fetal nutrient exchange, but few have been documented in the endometrium. The aim of this study is to describe the expression of 42 genes, with parental expression, in the endometrium comparing two extreme breeds: Large White (LW); Meishan (MS) with contrasting neonatal mortality and maturity at two days of gestation (D90-D110). We investigated their potential contribution to fetal maturation exploring genes-fetal phenotypes relationships. Last, we hypothesized that the fetal genome and sex influence their endometrial expression. For this purpose, pure and reciprocally crossbred fetuses were produced using LW and MS breeds. Thus, in the same uterus, endometrial samples were associated with its purebred or crossbred fetuses., Results: Among the 22 differentially expressed genes (DEGs), 14 DEGs were differentially regulated between the two days of gestation. More gestational changes were described in LW (11 DEGs) than in MS (2 DEGs). Nine DEGs were differentially regulated between the two extreme breeds, highlighting differences in the regulation of endometrial angiogenesis, nutrient transport and energy metabolism. We identified DEGs that showed high correlations with indicators of fetal maturation, such as ponderal index at D90 and fetal blood fructose level and placental weight at D110. We pointed out for the first time the influence of fetal sex and genome on endometrial expression at D90, highlighting AMPD3, CITED1 and H19 genes. We demonstrated that fetal sex affects the expression of five imprinted genes in LW endometrium. Fetal genome influenced the expression of four genes in LW endometrium but not in MS endometrium. Interestingly, both fetal sex and fetal genome interact to influence endometrial gene expression., Conclusions: These data provide evidence for some sexual dimorphism in the pregnant endometrium and for the contribution of the fetal genome to feto-maternal interactions at the end of gestation. They suggest that the paternal genome may contribute significantly to piglet survival, especially in crossbreeding production systems., (© 2024. The Author(s).)

An activity pattern describes variations in activities over time. The objectives of this study are to automatically predict sow activity from computer vision over 11 days peripartum and estimate how sow behavior influences piglet's performance during early lactation. The analysis of video images used the convolutional neural network (CNN) YOLO for sow detection and posture classification of 21 Large White and 22 Meishan primiparous sows housed in individual farrowing pens. A longitudinal analysis and a clustering method were combined to identify groups of sows with a similar activity pattern. Traits under study are as follows: (i) the distribution of time spent daily in different postures and (ii) different activities while standing. Six postures were included along with three classes of standing activities, i.e., eating, drinking, and other, which can be in motion or not and root-pawing or not. They correspond to a postural budget and a standing-activity budget. Groups of sows with similar changes in their budget over the period (D-3 to D-1; D0 and D1-D7) were identified with the k-means clustering method. Next, behavioral traits (time spent daily in each posture, frequency of postural changes) were used as explanatory variables in the Cox proportional hazards model for survival and in the linear model for growth. Piglet survival was influenced by sow behavior on D-1 and during the period D1-D7. Piglets born from sows that were standing and doing an activity other than drinking and eating on D-1 had a 26% lower risk of dying than other piglets. Those born from sows that changed posture more frequently on D1-D7 had a 44% lower risk of dying. The number of postural changes, which illustrate sow restlessness, influenced piglet growth in the three periods. The average daily gain of piglets born from sows that were more restless on D1-D7 and that changed posture more frequently to hide their udder on D0 decreased by 22 and 45 g/d, respectively. Conversely, those born from sows that changed posture more frequently to hide their udder during the period of D1-D7 grew faster (+71 g/d) than the other piglets. Sow restlessness at different time periods influenced piglet performance., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Girardie, Bonneau, Billon, Bailly, David and Canario.)

Innovations in the breeding and management of pigs are needed to improve the performance and welfare of animals raised in social groups, and in particular to minimise biting and damage to group mates. Depending on the context, social interactions between pigs can be frequent or infrequent, aggressive, or non-aggressive. Injuries or emotional distress may follow. The behaviours leading to damage to conspecifics include progeny savaging, tail, ear or vulva biting, and excessive aggression. In combination with changes in husbandry practices designed to improve living conditions, refined methods of genetic selection may be a solution reducing these behaviours. Knowledge gaps relating to lack of data and limits in statistical analyses have been identified. The originality of this paper lies in its proposal of several statistical methods for common use in analysing and predicting unwanted behaviours, and for genetic use in the breeding context. We focus on models of interaction reflecting the identity and behaviour of group mates which can be applied directly to damaging traits, social network analysis to define new and more integrative traits, and capture-recapture analysis to replace missing data by estimating the probability of behaviours. We provide the rationale for each method and suggest they should be combined for a more accurate estimation of the variation underlying damaging behaviours., Competing Interests: LF-G was employed by the company AXIOM. LZ was employed by the company Topigs Norsvin. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Canario, Bijma, David, Camerlink, Martin, Rauw, Flatres-Grall, Zande, Turner, Larzul and Rydhmer.)

In mammalian species, the first days after birth are an important period for survival and the mortality rate is high before weaning. In pigs, perinatal deaths average 20% of the litter, with important economic and societal consequences. Maturity is one of the most important factors that influence piglet survival at birth. Maturity can be defined as the outcome of complex mechanisms of intra-uterine development and maturation during the last month of gestation. Here, we provide new insights into maturity obtained by studying the end of gestation at two different stages (3 weeks before term and close to term) in two breeds of pigs that strongly differ in terms of neonatal survival. We used metabolomics to characterize the phenotype, to identify biomarkers, and provide a comprehensive understanding of the metabolome of the fetuses in late gestation in three fluids (plasma, urine, and amniotic fluid). Our results show that the biological processes related to amino acid and carbohydrate metabolisms are critical for piglet maturity. We confirm the involvement of some previously described metabolites associated with delayed growth (e.g., proline and myo-inositol). Altogether, our study proposes new routes for improved characterization of piglet maturity at birth.

Evolutionary biologists studying wild species have demonstrated that genetic and non-genetic sources of information are inherited across generations and are therefore responsible for phenotypic resemblance between relatives. Although it has been postulated that non-genetic sources of inheritance are important in natural selection, they are not taken into account for livestock selection that is based on genetic inheritance only. According to the natural selection theory, the contribution of non-genetic inheritance may be significant for the transmission of characters. If this theory is confirmed in livestock, not considering non-genetic means of transmission in selection schemes might prevent achieving maximum progress in the livestock populations being selected. The present discussion paper reviews the different mechanisms of genetic and non-genetic inheritance reported in the literature as occurring in livestock species. Non-genetic sources of inheritance comprise information transmitted via physical means, such as epigenetic and microbiota inheritance, and those transmitted via learning mechanisms: behavioral, cultural and ecological inheritance. In the first part of this paper we review the evidence that suggests that both genetic and non-genetic information contribute to inheritance in livestock (i.e. transmitted from one generation to the next and causing phenotypic differences between individuals) and discuss how the environment may influence non-genetic inherited factors. Then, in a second step, we consider methods for favoring the transmission of non-genetic inherited factors by estimating and selecting animals on their extended transmissible value and/or introducing favorable non-genetic factors via the animals' environment., (Copyright © 2019 David, Canario, Combes and Demars.)

In pigs, the perinatal period is the most critical time for survival. Piglet maturation, which occurs at the end of gestation, is an important determinant of early survival. Skeletal muscle plays a key role in adaptation to extra-uterine life, e.g. motor function and thermoregulation. Progeny from two breeds with extreme neonatal mortality rates were analyzed at 90 and 110 days of gestation (dg). The Large White breed is a highly selected breed for lean growth and exhibits a high rate of neonatal mortality, whereas the Meishan breed is fatter and more robust and has a low neonatal mortality. Our aim was to identify molecular signatures underlying late fetal longissimus muscle development. First, integrated analysis was used to explore relationships between co-expression network models built from a proteomic data set (bi-dimensional electrophoresis) and biological phenotypes. Second, correlations with a transcriptomic data set (microarrays) were investigated to combine different layers of expression with a focus on transcriptional regulation. Muscle glycogen content and myosin heavy chain polymorphism were good descriptors of muscle maturity and were used for further data integration analysis. Using 89 identified unique proteins, network inference, correlation with biological phenotypes and functional enrichment revealed that mitochondrial oxidative metabolism was a key determinant of neonatal muscle maturity. Some proteins, including ATP5A1 and CKMT2, were important nodes in the network related to muscle metabolism. Transcriptomic data suggest that overexpression of mitochondrial PCK2 was involved in the greater glycogen content of Meishan fetuses at 110 dg. GPD1, an enzyme involved in the mitochondrial oxidation of cytosolic NADH, was overexpressed in Meishan. Thirty-one proteins exhibited a positive correlation between mRNA and protein levels in both extreme fetal genotypes, suggesting transcriptional regulation. Gene ontology enrichment and Ingenuity analyses identified PPARGC1A and ESR1 as possible transcriptional factors positively involved in late fetal muscle maturation., (© 2018 by The American Society for Biochemistry and Molecular Biology, Inc.)

Background: Maturity of intestinal functions is critical for neonatal health and survival, but comprehensive description of mechanisms underlying intestinal maturation that occur during late gestation still remain poorly characterized. The aim of this study was to investigate biological processes specifically involved in intestinal maturation by comparing fetal jejunal transcriptomes of two representative porcine breeds (Large White, LW; Meishan, MS) with contrasting neonatal vitality and maturity, at two key time points during late gestation (gestational days 90 and 110). MS and LW sows inseminated with mixed semen (from breed LW and MS) gave birth to both purebred and crossbred fetuses. We hypothesized that part of the differences in neonatal maturity between the two breeds results from distinct developmental profiles of the fetal intestine during late gestation. Reciprocal crossed fetuses were used to analyze the effect of parental genome. Transcriptomic data and 23 phenotypic variables known to be associated with maturity trait were integrated using multivariate analysis with expectation of identifying relevant genes-phenotypic variable relationships involved in intestinal maturation., Results: A moderate maternal genotype effect, but no paternal genotype effect, was observed on offspring intestinal maturation. Four hundred and four differentially expressed probes, corresponding to 274 differentially expressed genes (DEGs), more specifically involved in the maturation process were further studied. In day 110-MS fetuses, Ingenuity® functional enrichment analysis revealed that 46% of DEGs were involved in glucose and lipid metabolism, cell proliferation, vasculogenesis and hormone synthesis compared to day 90-MS fetuses. Expression of genes involved in immune pathways including phagocytosis, inflammation and defense processes was changed in day 110-LW compared to day 90-LW fetuses (corresponding to 13% of DEGs). The transcriptional regulator PPARGC1A was predicted to be an important regulator of differentially expressed genes in MS. Fetal blood fructose level, intestinal lactase activity and villous height were the best predicted phenotypic variables with probes mostly involved in lipid metabolism, carbohydrate metabolism and cellular movement biological pathways., Conclusions: Collectively, our findings indicate that the neonatal maturity of pig intestine may rely on functional development of glucose and lipid metabolisms, immune phagocyte differentiation and inflammatory pathways. This process may partially be governed by PPARGC1A.

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 ([Formula: see text]) and social ([Formula: see text]) genetic effects (also known as indirect genetic effects) to total heritable variance of average daily gain ([Formula: see text]) 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 ([Formula: see text]) or restricted ([Formula: see text]) feeding to 75% of the ad libitum intake. A Bayesian analysis of weekly records of [Formula: see text] (from 32 to 60 days of age) in rabbits on [Formula: see text] and [Formula: see text] was performed with a two-trait model including [Formula: see text] and [Formula: see text]., Results: The ratio between total heritable variance and phenotypic variance ([Formula: see text]) was low (<0.10) and did not differ significantly between FR. However, the ratio between [Formula: see text] (i.e. variance of [Formula: see text] relative to phenotypic variance) and [Formula: see text] was ~0.52 and 0.86 for animals on [Formula: see text] and [Formula: see text], respectively, thus [Formula: see text] contributed more to the heritable variance of animals on [Formula: see text] than on [Formula: see text]. Feeding regimen also affected the sign and magnitude of the correlation between [Formula: see text] and [Formula: see text], i.e. -0.5 and ~0 for animals on [Formula: see text] and [Formula: see text], respectively. The posterior mean (posterior sd) of the correlation between estimated total breeding values (ETBV) of animals on [Formula: see text] and [Formula: see text] was 0.26 (0.20), indicating very strong G × FR interactions. The correlations between [Formula: see text] and [Formula: see text] in rabbits on [Formula: see text] and [Formula: see text] ranged from -0.47 ([Formula: see text] on [Formula: see text] and [Formula: see text] on [Formula: see text]) to 0.64., Conclusions: Our results suggest that selection of rabbits for [Formula: see text] under [Formula: see text] may completely fail to improve [Formula: see text] in rabbits on [Formula: see text]. Social genetic effects contribute substantially to ETBV of rabbits on [Formula: see text] but not on [Formula: see text]. Selection for [Formula: see text] should be performed under production conditions regarding the FR, by accounting for [Formula: see text] if the amount of food is limited.

Background: Some genetic studies need to take into account correlations between traits that are repeatedly measured over time. Multiple-trait random regression models are commonly used to analyze repeated traits but suffer from several major drawbacks. In the present study, we developed a multiple-trait extension of the structured antedependence model (SAD) to overcome this issue and validated its usefulness by modeling the association between litter size (LS) and average birth weight (ABW) over parities in pigs and rabbits., Methods: The single-trait SAD model assumes that a random effect at time [Formula: see text] can be explained by the previous values of the random effect (i.e. at previous times). The proposed multiple-trait extension of the SAD model consists in adding a cross-antedependence parameter to the single-trait SAD model. This model can be easily fitted using ASReml and the OWN Fortran program that we have developed. In comparison with the random regression model, we used our multiple-trait SAD model to analyze the LS and ABW of 4345 litters from 1817 Large White sows and 8706 litters from 2286 L-1777 does over a maximum of five successive parities., Results: For both species, the multiple-trait SAD fitted the data better than the random regression model. The difference between AIC of the two models (AIC&#95;random regression-AIC&#95;SAD) were equal to 7 and 227 for pigs and rabbits, respectively. A similar pattern of heritability and correlation estimates was obtained for both species. Heritabilities were lower for LS (ranging from 0.09 to 0.29) than for ABW (ranging from 0.23 to 0.39). The general trend was a decrease of the genetic correlation for a given trait between more distant parities. Estimates of genetic correlations between LS and ABW were negative and ranged from -0.03 to -0.52 across parities. No correlation was observed between the permanent environmental effects, except between the permanent environmental effects of LS and ABW of the same parity, for which the estimate of the correlation was strongly negative (ranging from -0.57 to -0.67)., Conclusions: We demonstrated that application of our multiple-trait SAD model is feasible for studying several traits with repeated measurements and showed that it provided a better fit to the data than the random regression model.

Genetic trends in maternal abilities were studied in French Large White sows. Two lines representing old-type and modern-type pigs were obtained by inseminating modern sows with semen from boars born in 1977 or 1998. Successive generations were produced by inter-se mating. The maternal performance of sows from the second generation was compared in farrowing crates. Video analysis was performed for the 1st h after the onset of 43 and 36 farrowing events, and for the 6 first hours for 23 and 21 events, in old-type and modern-type sows, respectively. Genetic trends were estimated as twice the difference in estimates between the 2 lines. The contribution of behavior to the probability of stillbirth and piglet death in the first 2 days was estimated as the percentage of deviance reduction (DR) due to the addition of behavior traits as factors in the mortality model. Sow activity decreased strongly from the 1st to the 2nd h in both lines (P < 0.001). In the first 6 h, old-type sows sat (1st parity), stood (2nd parity) and rooted (both parities) for longer than modern-type sows, which were less active, especially in 2nd parity. In modern-type sows, stillbirth was associated positively with lying laterally in the first 6 h (4.6% DR) and negatively in the 1st h (9.1% DR). First-parity old-type sows were more attentive to piglets (P = 0.003) than modern-type sows which responded more to nose contacts at 2nd parity (P = 0.01). Maternal reactivity of modern-type sows was associated with a higher risk of piglet death (4.6% DR). Respiratory distress at birth tended to be higher in modern-type piglets than in old-type piglets (P < 0.10) and was associated with a higher risk of piglet death in both lines (2.7-3.1% DR). Mobility at birth was lower in modern-type than old-type piglets (P < 0.0001). Genetic trends show that sow and piglet behaviors at farrowing have changed. Our results indicate reduced welfare in parturient modern-type sows and their newborn piglets.

Background: In pigs, the perinatal period is the most critical time for survival. Piglet maturation, which occurs at the end of gestation, leads to a state of full development after birth. Therefore, maturity is an important determinant of early survival. Skeletal muscle plays a key role in adaptation to extra-uterine life, e.g. glycogen storage and thermoregulation. In this study, we performed microarray analysis to identify the genes and biological processes involved in piglet muscle maturity. Progeny from two breeds with extreme muscle maturity phenotypes were analyzed at two time points during gestation (gestational days 90 and 110). The Large White (LW) breed is a selected breed with an increased rate of mortality at birth, whereas the Meishan (MS) breed produces piglets with extremely low mortality at birth. The impact of the parental genome was analyzed with reciprocal crossed fetuses., Results: Microarray analysis identified 12,326 differentially expressed probes for gestational age and genotype. Such a high number reflects an important transcriptomic change that occurs between 90 and 110 days of gestation. 2,000 probes, corresponding to 1,120 unique annotated genes, involved more particularly in the maturation process were further studied. Functional enrichment and graph inference studies underlined genes involved in muscular development around 90 days of gestation, and genes involved in metabolic functions, such as gluconeogenesis, around 110 days of gestation. Moreover, a difference in the expression of key genes, e.g. PCK2, LDHA or PGK1, was detected between MS and LW just before birth. Reciprocal crossing analysis resulted in the identification of 472 genes with an expression preferentially regulated by one parental genome. Most of these genes (366) were regulated by the paternal genome. Among these paternally regulated genes, some known imprinted genes, such as MAGEL2 or IGF2, were identified and could have a key role in the maturation process., Conclusion: These results reveal the biological mechanisms that regulate muscle maturity in piglets. Maturity is also under the conflicting regulation of the parental genomes. Crucial genes, which could explain the biological differences in maturity observed between LW and MS breeds, were identified. These genes could be excellent candidates for a key role in the maturity.