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Honey bee subspecies originate from specific geographical areas in Africa, Europe and the Middle East, and beekeepers interested in specific phenotypes have imported genetic material to regions outside of the bees' original range for use either in pure lines or controlled crosses. Moreover, imported drones are present in the environ-ment and mate naturally with queens from the local subspecies. The resulting ad-mixture complicates population genetics analyses, and population stratification can be a major problem for association studies. To better understand Western European honey bee populations, we produced a whole genome sequence and single nucleotide polymorphism (SNP) genotype data set from 870 haploid drones and demonstrate its utility for the identification of nine genetic backgrounds and various degrees of admixture in a subset of 629 samples. Five backgrounds identified correspond to sub-species, two to isolated populations on islands and two to managed populations. We also highlight several large haplotype blocks, some of which coincide with the position of centromeres. The largest is 3.6 Mb long and represents 21% of chromosome 11, with two major haplotypes corresponding to the two dominant genetic backgrounds identified. This large naturally phased data set is available as a single vcf file that can now serve as a reference for subsequent populations genomics studies in the honey bee, such as (i) selecting individuals of verified homogeneous genetic backgrounds as references, (ii) imputing genotypes from a lower-density data set generated by an SNP- chip or by low- pass sequencing, or (iii) selecting SNPs compatible with the re-quirements of genotyping chips. This work was performed in collaboration with the GeT platform, Toulouse (France), a partner of the National Infrastructure France Génomique, thanks to support by the Commissariat aux Grands Invetissements (ANR-10- INBS-0009). Bioinformatics analyses were performed on the GenoToul Bioinfo computer cluster. This work was funded by a grant from the INRA Département de Génétique Animale (INRA Animal Genetics division) and by the SeqApiPop pro-gramme, funded by the FranceAgriMer grant 14-21- AT. We thank John Kefuss for helpful discussions. We thank Andrew Abrahams for providing honey bee samples from Colonsay (Scotland), the Association Conservatoire de l'Abeille Noire Bretonne (ACANB) for samples from Ouessant (France), CETA de Savoie for sample from Savoie, ADAPI for samples from Porquerolles and all beekeepers and bee breeders who kindly participated in this study by providing sam-ples from their colonies. info:eu-repo/semantics/publishedVersion

Honey bee subspecies originate from specific geographic areas in Africa, Europe and the Middle East. The interest of beekeepers in specific phenotypes has led them to import subspecies to regions outside of their original range. The resulting admixture complicates population genetics analyses and population stratification can be a major problem for association studies. As a typical example, the case of the French population is studied here. We sequenced 870 haploid drones for SNP detection and identified nine genetic backgrounds in 629 samples. Five correspond to subspecies, two to isolated populations and two to human-mediated population management. We also highlight several large haplotype blocks, some of which coincide with the position of centromeres. The largest is 3.6 Mb long on chromosome 11, representing 1.6 % of the genome and has two major haplotypes, corresponding to the two dominant genetic backgrounds identified.

International audience

International audience

The ambition of the foresight on livestock farming was to rethink the place, the roles of livestock and how it should be transformed to fully contribute to the development of more sustainable agri-food systems. It was also to identify cross-disciplinary research themes that explore promising fronts of science or methodologies to solve knowledge locks. The foresight was managed by a group of 15 researchers and mobilized a hundred researchers. Based on an analysis of the context and the drivers for the evolution of the systems, we propose a new conceptual framework to think about innovations. Livestock farming must be part of circular agri-food systems in which it must contribute, beyond an increased efficiency of production factors, to the preservation of the quality of the resources and to the production of a food at an affordable price. Systems need to be rethought to be climate-smart and to respond to the health and welfare challenges of animals and people, rethink the linkages between livestock, crop production and territories to maximize recycling and rethink livestock linkages, processing and consumption of livestock products. Innovations should be based on the principles of agro-ecology supplemented by those of the circular economy and mobilizing levers of (bio) technologies and organizational innovation. The text describes 4 major scientific priorities with their research issues and produces recommendations for an action plan., L’ambition de l’Atelier de Réflexion Prospective sur l’élevage a été de repenser la place, les rôles de l’élevage et en quoi il doit se transformer pour contribuer pleinement au développement de systèmes agri-alimentaires plus durables ainsi que d’identifier des thématiques de recherches interdisciplinaires permettant d’explorer des fronts de science ou méthodologiques porteurs d’avenir pour lever les verrous de connaissances. La réflexion a été animée par un groupe de 15 chercheurs et en a mobilisé une centaine. À partir d’une analyse du contexte et des drivers d’évolution des systèmes nous proposons un nouveau cadre conceptuel et des voies de progrès pour penser l’élevage de demain. L’élevage doit s’inscrire dans le cadre de systèmes agri-alimentaires circulaires dans lesquels il doit contribuer, au-delà d’une efficience accrue des moyens de production, à la préservation de la qualité des ressources et à la production d’une alimentation à un prix abordable. Il faut repenser les systèmes pour qu’ils soient climato-intelligents et répondent aux enjeux de santé et du bien-être des animaux et des Hommes ; repenser les liens entre élevage, production végétale et territoire pour maximiser les recyclages et repenser les liens entre élevage, transformation et consommation des produits de l’élevage. Les innovations doivent être basées sur les principes de l’agroécologie complétés par ceux de l’économie circulaire et par la mobilisation des leviers des (bio)technologies et de l’innovation organisationnelle. Le texte décrit quatre grandes priorités scientifiques avec leurs enjeux de recherche et produit des recommandations pour un plan d’action.

International audience

International audience

National audience; The impact of host genetic variation in shaping innate and adaptive immune responses is an emerging lever to consider in new vaccination strategies. This issue has been addressed by the H2020-funded SAPHIR project by studying the genetic control of responses to vaccines against Mycoplasma hyopneumoniae (M. hyo) or Influenza A Virus (IAV) in pigs. Large White pigs housed in a conventional facility (48 families produced in five batches) were vaccinated at weaning (around 28 days of age), which was followed with a booster vaccination three weeks later. Overall, 182 and 98 piglets were vaccinated against M. hyo or IAV, respectively, and 64 non-vaccinated piglets were included as shared controls for the two vaccine experiments. The humoral vaccine response was measured by following the dynamics of seric M. hyo- or IAV-specific IgG, prior vaccination on the vaccine day, every week during five weeks post-vaccination, and before slaughtering at 21 weeks-of-age. In addition, haemagglutination inihibition (HAI) assays were performed for IAV-vaccinated pigs. Our results showed a wide range of individual variability. One week after the booster vaccination, M. hyo IgG levels (relative to a positive control) ranged from 0.36 to 2.15 (mean=1.34, coefficient of variation=21.2%) and IAV-specific IgG levels ranged from 10.3 to 128.5 µg/mL (mean=33.41 µg/mL, coefficient of variation=69.6%). For IAV-vaccinated animals, HAI titers ranged from 40 to 2560 (geometric mean=343.7). Interestingly, females exhibited a significantly higher humoral immune response to vaccination compared to males for the two vaccines. Heritability of specific antibody response variation could be estimated for animals vaccinated against M. hyo (h2=0.34 one week after the booster vaccination), showing a moderate genetic control. Ongoing genome wide association studies (GWAS) have revealed few candidate genomic regions found associated with the individual variability of vaccine responses to M. hyo or IAV that need to be further investigated.

International audience; Cette synthèse fait le point sur les principales évolutions de l’amélioration génétique du porc en France depuis la loi sur l’élevage de 1966. Elle évoque rapidement les 20 premières années, qui ont fait l’objet d’une synthèse en 1986, puis décrit plus en détail les évolutions ultérieures. Les objectifs de sélection, initialement limités aux caractères de production, se sont complexifiés avec la prise en compte de la qualité de la viande, puis de la prolificité et enfin des aptitudes maternelles des truies. La mise en place d’une évaluation génétique utilisant la méthodologie du « BLUP - modèle animal » au milieu des années 1990 et le développement de l’insémination artificielle ont profondément changé le travail des sélectionneurs. Une nouvelle évolution majeure, la sélection génomique, a récemment été mise en place. La sélection a conduit à des améliorations importantes des performances pour les principaux caractères de l’objectif de sélection depuis 1970 : plus de 200 g de gain moyen quotidien, plus de 0,5 point d’indice de consommation, plus de 12 points de taux de viande maigre dans la carcasse, jusqu’à près de six porcelets nés vifs par portée supplémentaires. Ces évolutions favorables ont réduit l’empreinte environnementale de la production, mais ont également eu des effets défavorables : une augmentation la mortalité des porcelets avant sevrage et une plus grande hétérogénéité des performances. Les enjeux pour l’avenir en termes d’objectifs d’amélioration génétique (prise en compte de caractères liés au bien-être, à la robustesse et à l’adaptation…), de méthodes et d’outils sont ensuite discutés.

The aims of this study were to investigate variation in content of androstenone (AND), skatole (SKA), and indole (IND), quantified in adipose tissue of intact male pigs at 160 d of age (105 kg BW) and 220 d of age (155 kg BW), to estimate genetic parameters and to investigate the genetic relationships for AND, SKA, IND, and growth traits. A sample of adipose tissue was collected in vivo, using a biopsy device, from the neck of 500 intact males at the 2 ages and at slaughter from the ham of 100 of the investigated animals. Backfat depth was measured at 220 d of age, whereas BW was recorded at each sampling. Quantification of AND, SKA, and IND was performed by HPLC with fluorescence detection. Estimates of genetic parameters were obtained through Bayesian analyses after logarithmic transformations of original measures. Contents of boar taint compounds (BTC) measured at 220 d were higher than those at 160 d of age. Correlations between contents of BTC in backfat and ham fat ranged from 0.7 (IND) to 0.88 (SKA). Medium-high h were estimated for BTC at both ages, but estimates at 220 d (0.58, 0.60, and 0.69 for AND, SKA, and IND, respectively) were greater than those at 160 d. The genetic correlation between contents at 160 and 220 d of each BTC was positive, but the probability that such estimates were greater than 0.8 was very low, indicating that contents at 160 and 220 d were traits controlled by different genetic backgrounds. Different rankings were observed when breeding values for the content at 160 and 220 d of age were used to rank animals. As a consequence, performance testing programs for BTC should be based preferably on phenotypes measured at 220 d of age. Weak genetic correlations were observed between content of BT compounds and growth traits (BW, backfat depth, and daily gain from 160 to 220 d of age), indicating that selective breeding to reduce the risk of tainted pork is expected to exert trivial effects on growth performance and fat deposition. Results indicate that prevalence of BTC is high in mature and heavy pigs relative to young and light pigs. High heritability; positive genetic correlations between AND, SKA, and IND; and trivial effects on growth traits suggest that reduction of BTC through selective breeding is feasible and exploitable as an alternative to surgical castration also for pigs slaughtered at heavy BW.

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Genetic trends for male and female sexual development and components of litter size and weight at birth (LB) as well as traits related to sow lifetime productivity were estimated in a French Large White (LW) pig population using frozen semen. Two experimental groups (EXP = L77 and L98) were produced by inseminating LW sows with either stored frozen semen from 17 LW boars born in 1977 (EXP = L77) or with semen from 23 LW boars born in 1998 (EXP = L98). In each group, about 100 males were measured for testicular development and bulbo-urethral gland development, and 90 gilts were checked for puberty, among which about 50 gilts were measured for their first ovulation rate at puberty (ORP). The females were then mated to 15 randomly chosen males for each group for 6 successive parities and measured for total number born (TNB), number born alive (NBA), litter weight at birth (LWB), and interval from weaning to first estrus as well as ovulation rate at fertilization (ORF = ovulation rate of gestating sows) on a subset of litters. The data were analyzed using mixed linear models including the fixed effects of EXP, of finishing (sexual development traits) or farrowing group, and parity (LB traits); the random effects of birth litter (sexual development traits) or sow (LB traits); and, when relevant, age or BW as covariates. The homogeneity of residual variances across EXP was also tested. For each trait, the genetic trend was estimated as twice the difference between L98 and L77. Limited differences were observed for sexual development traits, except for ORF, which increased by 0.17 ± 0.06/yr. The residual SD of NBA (2.7 vs. 2.0; P = 0.004) and LWB (3.1 vs. 2.5; P = 0.03) were larger in L98 sows than in L77 sows. Positive trends were observed for all litter traits (0.22 ± 0.07 ova, 0.12 ± 0.04 piglet, 0.09 ± 0.04 piglet, and 0.23 ± 0.06 kg/yr for ORF, TNB, NBA, and LWB, respectively) but at the expense of a degradation of prenatal and farrowing survival. A negative trend was also observed for length of productive life (−8.9 ± 3.9 d/yr). These results suggest that gains in productivity were associated with a loss of robustness.

Four main evolutionary lineages of A. mellifera have been described including eastern Europe (C) and western and northern Europe (M). Many apiculturists prefer bees from the C lineage due to their docility and high productivity. In France, the routine importation of bees from the C lineage has resulted in the widespread admixture of bees from the M lineage. The haplodiploid nature of the honeybee Apis mellifera and its small genome size, permits affordable and extensive genomics studies. As a pilot study of a larger project to characterise French honeybee populations, we sequenced 60 drones sampled from two commercial populations managed for the production of honey and royal jelly. Results indicate a C lineage origin, whilst mitochondrial analysis suggests two drones originated from the O lineage. Analysis of heterozygous SNPs identified potential copy number variants near to genes encoding odorant binding proteins and several cytochrome P450 genes. Signatures of selection were detected using the hapFLK haplotype-based method, revealing several regions under putative selection for royal jelly production. The framework developed during this study will be applied to a broader sampling regime, allowing the genetic diversity of French honeybees to be characterised in detail.

Residual feed intake (RFI) has been explored as an alternative selection criterion to feed conversion ratio to capture the fraction of feed intake not explained by expected production and maintenance requirements. Selection experiments have found that low RFI in the growing pig is genetically correlated with reduced fatness and feed intake. Selection for feed conversion ratio also reduces sow appetite and fatness, which, together with increased prolificacy, has been seen as a hindrance for sow lifetime performance. The aims of our study were to derive equations for sow RFI during lactation (SRFI) and to evaluate the effect of selection for RFI during growth on sow traits during lactation. Data were obtained on 2 divergent lines selected for 7 generations for low and high RFI during growth in purebred Large Whites. The RFI was measured on candidates for selection (1,065 pigs), and sow performance data were available for 480 sows having from 1 to 3 parities (1,071 parities). Traits measured were sow daily feed intake (SDFI); sow BW and body composition before farrowing and at weaning (28.4 ± 1.7d); number of piglets born total, born alive, and surviving at weaning; and litter weight, average piglet BW, and within-litter SD of piglet BW at birth, 21 d of age (when creep feeding was available), and weaning. Sow RFI was defined as the difference between observed SDFI and SDFI predicted for sow maintenance and production. Daily production requirements were quantified by litter size and daily litter BW gain as well as daily changes in sow body reserves. The SRFI represented 24% of the phenotypic variability of SDFI. Heritability estimates for RFI and SRFI were both 0.14. The genetic correlation between RFI and SRFI was 0.29 ± 0.23. Genetic correlations of RFI with sow traits were low to moderate, consistent with responses to selection; selection for low RFI during growth reduced SDFI and increased number of piglets and litter growth, but also increased mobilization of body reserves. No effect on rebreeding performance was found. Metabolic changes previously observed during growth in response to selection might explain part of the better efficiency of the low-RFI sows, decreasing basal metabolism and favoring rapid allocation of resources to lactation. We propose to consider SRFI as an alternative to SDFI to select for efficient sows with reduced input demands during lactation.

A QTL analysis of female reproductive data from a 3-generation experimental cross between Meishan and Large White pig breeds is presented. Six F1 boars and 23 F1 sows, progeny of 6 Large White boars and 6 Meishan sows, produced 502 F2 gilts whose reproductive tract was collected after slaughter at 30 d of gestation. Five traits [i.e., the total weight of the reproductive tract, of the empty uterine horns, of the ovaries (WOV), and of the embryos], as well as the length of uterine horns (LUH), were measured and analyzed with and without adjustment for litter size. Animals were genotyped for a total of 137 markers covering the entire porcine genome. Analyses were carried out based on interval mapping methods, using a line-cross regression and a half-full sib maximum likelihood test. A total of 18 genome-wide significant (P < 0.05) QTL were detected on 9 different chromosomes (i.e., SSC 1, 5, 6, 7, 9, 12, 13, 18, and X). Five genome-wide significant QTL were detected for LUH, 4 for weight of the empty uterine horns and WOV, 2 for total weight of the reproductive tract, and 1 for weight of the embryos. Twenty-two additional suggestive QTL were also detected. The largest effects were obtained for LUH and WOV on SSC13 (9.2 and 7.0% of trait phenotypic variance, respectively). Meishan alleles had both positive (e.g., on SSC7) and negative effects (e.g., on SSC13) on the traits investigated. Moreover, the QTL were generally not fixed in founder breeds, and opposite effects were in some cases obtained in different families. Although reproductive tract characteristics had only a moderate correlation with reproductive performances, most of the major QTL detected in this study were previously reported as affecting female reproduction, generally with reduced significance levels. This study thus shows that focusing on traits with high heritability might help to detect loci involved in low heritability major traits for breeding.

A quantitative trait locus (QTL) affecting fatness in a way opposite to expectations based on breed means was mapped to swine chromosome 7 (SSC7) using crosses between Large White (LW) and Meishan (MS) founders. Defining the molecular fatness trait more explicitly would allow deducing positional candidate genes, for which expression differences must be analysed in experimental populations. First, mRNA levels of genes representing sequential steps in adipogenesis or involved in lipid metabolism were studied in backfat of pigs having homozygous LWQTL7/LWQTL7 or heterozygous LWQTL7/MSQTL7 alleles and considered at two ages. mRNA level of DLK1 expressed in preadipocytes was greater in MSQTL7/LWQTL7 pigs than in homozygous pigs at 28 days. Transcript abundances of CEBPA involved in differentiation, the prolipogenic FASN gene and the adipocyte-specific marker FABP4 were lower in MSQTL7/LWQTL7 pigs compared with LWQTL7/LWQTL7 pigs at 150 days. Because these results suggest a lag time in terminal differentiation associated with the MS allele, seven genes in the QTL interval were deduced as promising candidates for the QTL effect by bioinformatics analysis. Among them, PPARD and CDKN1A had lower expression levels in MSQTL7/LWQTL7 pigs at both ages. Genotype-related differences were observed in mRNA levels of PPARD target genes involved in cell differentiation (FZD7) or fatty acid oxidation (ACADL and ACOX1) at 150 days. These results re-evaluate the potential of PPARD to explain part of variation in pig adiposity.

A quantitative trait locus (QTL) for boar fat androstenone levels has been identified near the SSC7 centromere in a Large White × Meishan cross. Backcrosses were produced to isolate the Chinese haplotype in a European genetic background. The expression of 25 genes from the QTL region was studied in the testes and livers of 5-month-old backcross boars, with the aim of identifying the causal gene. Using Fluidigm, a new high-throughput technology, the expression of 25 genes was measured in a single real-time PCR experiment. This study found six significantly down-regulated genes (C6ORF106, C6ORF81, CLPS, SLC26A8, SRPK1 and MAPK14) in the testes of MS-LW backcross boars. However, according to current knowledge, none of the genes appear to be related to androstenone metabolism. In the livers, none of the genes were significantly up- or down-regulated, including TEAD3, which was previously designated as a possible candidate to explain this QTL.

Technological meat quality is a significant economic factor in pork production, and numerous publications have shown that it is strongly influenced both by genetic status and by rearing and slaughter conditions. The quality of meat is often described by meat pH at different times postmortem, as well as by color and drip loss, whereas carcass quality is often characterized by lean percentage. A meta-analysis of findings relating to 3,530 pigs reported in 23 publications was carried out to assess the effects of the halothane gene, sex, breed, and slaughter weight of animals on 7 selected variables: pH at 45 min postmortem, ultimate pH, reflectance (L*-value), redness (a*-value), yellowness (b*-value), drip loss, and lean percentage. Two statistical methods were used in the meta-analysis: the method of effect size and the better known random effects model. The method of effect size was associated with Markov chain Monte Carlo techniques for implementing Bayesian hierarchical models to avoid the problems of limited data and publication bias. The results of our meta-analysis showed that the halothane genotype had a significant effect on all analyzed pork quality variables. Between-study variance was evaluated with the Cochran (1954) Q-test of heterogeneity. Meta-regression was used to explain this variance, with covariates such as breed, sex, slaughter weight, and fasting duration being integrated into different regression models. The halothane gene effect was associated with the breed effect only for the following variables: L*-value, b*-value, and drip loss. Slaughter weight contributed significantly only to the explanation of differences in ultimate pH between homozygous genotypes. In response to inconsistencies reported in the literature regarding the difference between the genotypes NN and Nn, results of the meta-analysis showed that the difference between these 2 genotypes was significant for all the analyzed variables except the a*-value.

Genetic trends for growth, feed efficiency, composition, and morphometry of carcasses were estimated in a French Large White (LW) pig population using frozen semen. Two groups of pigs were produced by inseminating LW sows with either stored, frozen semen from 17 LW boars born in 1977 or with semen from 23 LW boars born in 1998. In each group, 15 males and 90 females were randomly chosen and mated to produce approximately 1,000 pigs/group. These pigs were performance tested with individual ADFI and serial BW and backfat thickness measurements, slaughtered at 105 kg of BW, and measured for carcass traits. The data were analyzed using mixed linear animal models, including the fixed effect of the experimental group (offspring of 1977 or 1998 boars), the random effect of the additive genetic value of each animal, and, when significant, the fixed effects of sex, fattening batch, and slaughterhouse, the linear regression on BW, and the random effect of the common environment of birth litter. For each trait, the genetic trend was estimated as twice the difference between the 2 experimental groups. Results showed moderately favorable trends for on-test ADG (3.7 +/- 1.3 g/d per year) and feed conversion ratio (-0.014 +/- 0.005 kg/kg per year) in spite of a tendency toward an increase in ADFI (7.6 +/- 4.7 g/yr). A strong reduction in carcass fatness (-0.35 +/- 0.07 mm/yr for carcass average backfat thickness) and a large improvement in carcass leanness (0.31 +/- 0.10 mm(2)/yr and 0.41 +/- 0.08%/yr for loin eye area and carcass muscle content, respectively) were observed. Carcass shape measurements (back and leg length, back width, muscle thickness of hind limbs) were not affected by selection. Serial measurements of BW and backfat thickness showed that the major part of the genetic gains occurred during late growth and that the reduction in the backfat layer was more pronounced in the rear than in the front part of the carcass. The use of frozen semen appears to be a powerful practice to thoroughly investigate changes attributable to selection.

Correlated effects of selection for components of litter size on carcass and meat quality traits were estimated using data from 3 lines of pigs derived from the same Large White base population. Two lines were selected for 6 generations on 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 (CON). The 3 lines were kept for a 7th generation, but without any selection. Carcass and meat quality traits were recorded on the 5th to 7th generation of the experiment. Carcass traits included dressing percentage, carcass length (LGTH), average backfat thickness (ABT), estimated lean meat content, and 8 carcass joint weight traits. Meat quality traits included pH recorded 24 h after slaughter (pH24) of LM, gluteus superficialis (GS), biceps femoris (BF), and adductor femoris (AD) muscles, as well as reflectance and water-holding capacity (WHC) of GS and BF muscles. Heritabilities of carcass and meat quality traits and their genetic correlations with OR and PS were estimated using REML methodology applied to a multiple trait animal model. Correlated responses to selection were then estimated by computing differences between OR or PS and CON lines at generations 5 to 7 using least squares and mixed model methodology. Heritability (h(2)) estimates were 0.08 +/- 0.04, 0.58 +/- 0.10, 0.70 +/- 0.10, and 0.74 +/- 0.10 for dressing percentage, LGTH, ABT, and lean meat content, respectively, ranged from 0.28 to 0.72 for carcass joint traits, from 0.28 to 0.45 for pH24 and reflectance measurements, and from 0.03 to 0.11 for WHC measurements. Both OR and PS had weak genetic correlations with carcass (r(G) = -0.09 to 0.17) and most meat quality traits. Selection for OR did not affect any carcass composition or meat quality trait. Correlated responses to selection for PS were also limited, with the exception of a decrease in pH24 of GS and BF muscles (-0.12 to -0.14 after 6 generations; P < 0.05), in WHC of GS muscle (-18.9 s after 6 generations; P < 0.05) and a tendency toward an increase in loin weight (0.44 kg after 6 generations; P < 0.10) .

Cet article retrace les principales étapes et la contribution de l’INRA au développement de la génomique, qui révolutionne depuis deux décennies les connaissances sur la structure et le fonctionnement du génome des animaux d’élevage. L’élaboration, dans les années 90, des premières cartes de marqueurs microsatellites a rapidement permis de mettre en évidence de nombreux locus à effets quantitatifs et de localiser les premiers gènes majeurs. En parallèle, les travaux de cytogénétique et de génomique comparative permettaient de tirer parti de l’avancée des connaissances sur le génome de l’homme et de la souris. A la fin des années 90, la construction d’outils de cartographie à haute densité, cartes d’hybrides d’irradiation et banques de grands fragments, a permis l’essor des travaux de cartographie fine et l’identification des premières mutations causales. Le début des années 2000 a été marqué par le développement des outils d’étude systématique de l’expression des gènes, micro-réseaux et puces à ADN, le démarrage du séquençage des premiers génomes d’animaux d’élevage, et l’essor des bases de données génomiques et de la bioinformatique. La connaissance des séquences permet ensuite de détecter in silico leurs variations, en particulier les très nombreuses variations ponctuelles (SNP) et de caractériser finement la structure des génomes des populations animales. La génomique a également renouvelé les méthodes d’amélioration génétique des populations, avec la mise en place de programmes de sélection assistée par marqueurs, de caractérisation et de gestion de la variabilité génétique et le développement d’applications en matière de contrôle de généalogie ou de traçabilité., This article outlines the main steps and the contribution of INRA to the development of genomics, which has revolutionised over the last two decades the knowledge of livestock genome structure and function. The development in the 1990’s of the first microsatellite marker maps quickly allowed the first major genes to be localised and numerous quantitative trait loci to be detected. Meanwhile, cytogenetics and comparative genomics studies allowed livestock genomics to benefit from advances in the knowledge of human and mouse genomes. At the end of the 1990’s, the construction of high-density mapping tools such as radiation hybrid maps and large insert libraries made it possible to develop fine mapping programmes and to identify the first causative mutations. The early 2000’s have been marked by the development of systematic gene expression tools, i.e. micro-arrays and DNA chips, the start of the first animal genome sequencing projects, and the rise of genomic databases and bioinformatics. Available sequence data then made it possible to detect in silico their variations, in particular the numerous single point polymorphisms (SNP) and to finely characterise the structure of livestock population genomes. Genomics has also renewed breeding programmes, with the development of programmes for marker-assisted selection, for the characterisation and the management of genetic variability and of parentage control or traceability applications.

A genome-wide scan was performed in Large White and French Landrace pig populations in order to identify QTL affecting reproduction and production traits. The experiment was based on a granddaughter design, including five Large White and three French Landrace half-sib families identified in the French porcine national database. A total of 239 animals (166 sons and 73 daughters of the eight male founders) distributed in eight families were genotyped for 144 microsatellite markers. The design included 51 262 animals recorded for production traits, and 53 205 litter size records were considered. Three production and three reproduction traits were analysed: average backfat thickness (US_M) and live weight (LWGT) at the end of the on-farm test, age of candidates adjusted at 100 kg live weight, total number of piglets born per litter, and numbers of stillborn (STILLp) and born alive (LIVp) piglets per litter. Ten QTL with medium to large effects were detected at a chromosome-wide significance level of 5% affecting traits US_M (on SSC2, SSC3 and SSC17), LWGT (on SSC4), STILLp (on SSC6, SSC11 and SSC14) and LIVp (on SSC7, SSC16 and SSC18). The number of heterozygous male founders varied from 1 to 3 depending on the QTL.

Correlated effects of selection for com- ponents 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 environ- ment of birth litter, as well as direct and maternal additive genetic effects as random effects. Genetic trends were estimated by computing differences be- tween OR or PS and C lines at each generation using both least squares (LS) and mixed model (MM) method- ology. 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 ef- fects were moderately negative for IWB (−0.21 ± 0.18), but larger for the 4 other traits (−0.59 to −0.74). Mater- nal 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 excep- tion of maternal correlations with IWB (−0.28 ± 0.13) and ADGPW (0.23 ± 0.11) and direct correlation with AGET (−0.23 ± 0.09). Prenatal survival also had low direct but moderate to strong maternal genetic correla- tions (−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 postwean- ing growth.

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 stillbirth (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 +/- 0.03, 0.46 +/- 0.03, 0.16 +/- 0.01, 0.08 +/- 0.01, 0.09 +/- 0.01, 0.04 +/- 0.01, 0.04 +/- 0.02, 0.19 +/- 0.02, 0.10 +/- 0.02, 0.10 +/- 0.02, 0.36 +/- 0.02, 0.27 +/- 0.01, and 0.24 +/- 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(a) >/= 0.95) and had antagonistic relations with PSB (r(a) = -0.59 to -0.75) and average piglet BW (r(a) = -0.19 to -0.46). They also had strong positive genetic correlations with prenatal survival (r(a) = 0.67 to 0.78) and moderate ones with ovulation rate (r(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 +/- 0.9 and 3.2 +/- 1.0 d/generation) and WP (respectively, 2.0 +/- 0.5 and 1.8 +/- 0.5 d/generation) and in the PS line for NBA (0.22 +/- 0.10 piglet/generation). Tendencies (P < 0.10) were also observed for LWB (0.21 +/- 0.12 kg/generation) and AWW (-0.25 +/- 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.

The effects of season (hot vs. warm) in a tropical humid climate, parity (primiparous vs. multiparous) and breed (Creole: CR, Large White: LW) on rectal temperature (RT) were studied for a total of 222 lactations obtained in 85 sows (43 CR and 42 LW; 56 primiparous and 166 multiparous) over a 28-d lactation, between June 2002 and April 2005. Mean daily ambient temperature was higher during the hot season than during the warm season (26.0 vs. 24.1°C) and relative humidity was high and similar in both seasons (89% on average). At farrowing, BW was lower (172 vs. 233 kg) and backfat thickness was higher (37 vs. 21 mm) in CR than in LW sows (p

SummaryA multivariate QTL detection was carried out on fatness and carcass composition traits on porcine chromosome 7 (SSC7). Single-trait QTLs have already been detected in the SLA region, and multivariate approaches have been used to exploit the correlations between the traits to obtain more information on their pattern: almost 500 measurements were recorded for backfat thickness (BFT1, BFT2), backfat weight (BFW) and leaf fat weight (LFW) but only about half that number for intramuscular fat content (IMF), affecting the detection. First, groups of traits were selected using a backward selection procedure: traits were selected based on their contribution to the linear combination of traits discriminating the putative QTL haplotypes. Three groups of traits could be distinguished based on successive discriminant analyses: external fat (BFT1, BFT2), internal fat (LFW, IMF) and BFW. At least four regions were distinguished, preferentially affecting one or the other group, with the SLA region always influencing all the traits. Meishan alleles decreased all trait values except IMF, confirming an opportunity for marker-assisted selection to improve meat quality with maintenance of carcass composition based on Meishan alleles.

Effects of selection for ovulation rate or prenatal survival were examined using data from 3 pigs lines derived from the same base Large White population. 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 ovulation rate on the left, right, and both ovaries at puberty (ORPL, ORPR, and ORP, respectively) and at fertilization (ORFL, ORFR, and ORF, respectively), total number of piglets born (TNB) per litter, prenatal survival (PS = TNB/ORF), and PS corrected for ovulation rate (CPS = PS + 0.018ORF) were estimated using REML methodology. Responses to selection were estimated by computing differences between OR or PS and control lines at each generation using least squares and mixed models methodology. Average genetic trends were computed by regressing line differences on generation number. Realized heritabilities were estimated using standard procedures. Heritability estimates were 0.17, 0.11, 0.34, 0.13, 0.09, 0.33, 0.14, 0.11, and 0.17 (SE = 0.01 to 0.03) for ORPL, ORPR, ORP, ORFL, ORFR, ORF, PS, CPS, and TNB, respectively. Realized heritabilities were 0.37 +/- 0.08 and 0.10 +/- 0.09 for ORP and CPS, respectively. The different measures of ovulation rate had strong genetic correlations (r(g) > 0.7). The ORF had midrange negative genetic correlations with PS and CPS (-0.45 +/- 0.07 and -0.42 +/- 0.08, respectively). The ORP also had an antagonistic genetic relationship with PS (-0.26 +/- 0.07) but was almost independent from CPS (-0.02 +/- 0.11). The TNB was moderately correlated with ORP and ORF (r(g) = 0.41 +/- 0.09 for both traits). Average genetic trends in OR and PS lines were, respectively, 0.49 +/- 0.10 and 0.11 +/- 0.10 for ORP, and 0.43 +/- 0.11 and 0.11 +/- 0.11 for ORF. Responses to selection were slightly superior in the left than in the right ovary. No significant difference was found for PS or CPS in any of the lines. The TNB did not change in the OR line but significantly improved in the PS line (0.24 +/- 0.11 piglets/generation).

Population genomics and signatures of selection in resequenced honey bee drones. 66. Annual Meeting of the European Federation of Animal Science (EAAP)

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Sequencing haploid drones from royal jelly and honey bee populations for detection of differentiation and selective sweeps. The Biology of Genomes

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Records of length of productive life, from first farrowing to culling, of 16,464 Large White purebred sows from SUISAG were studied using survival analysis. The major aims of the study were to model the risk of culling within parity and to assess the influence of exterior traits, such as the number of teats or feet and leg scores, on culling. Culling was concentrated at the first day after each farrowing or at the first day after weaning. Weaning itself was mostly between 21 and 49 d after farrowing, with an average weaning age of 35 d. Because of the definition of culling date used, there was practically no risk of culling from these periods. The culling rates at different periods suggested a modeling of the baseline hazard function within parity instead of over the entire productive life of the animals. A piecewise Weibull function and a simple graphical method to validate its adequacy were proposed for sow longevity analysis. The risk of culling increased with older parities (P < 0.001) and with decreasing litter size at weaning (P < 0.001). The exterior traits analyzed (number of teats, and feet and leg scores, on a scale from 1 to 7) had a moderate effect on the risk of culling compared with other factors but were still influential on survival, productive life expectancy, and annual replacement rate. Sows with less than 13 good teats had 1.35 times greater risk of being culled than sows with more good teats (P < 0.05). Sows with an X-O rear leg score of 2 had 1.4 times greater risk of being culled than sows with an intermediate score of 4 (P < 0.05). Sows at the optimum score of 4 for the size of inner claws of the rear leg had 0.83 times less risk of being culled (P < 0.01) than sows with scores of 2 and 3. Furthermore, when a phenotypic index for feet and legs was used to group these variables, the effect was highly significant (P < 0.001). Therefore, a means to improve longevity is through phenotypic selection of replacement gilts based on exterior traits: gilts with 13 or less good teats or with extreme feet and leg scores should be culled. From a genetic point of view, sows with the best value in the current index for exterior traits had a lower risk of culling (P < 0.01), and therefore, it is possible to obtain a response for sow longevity via indirect selection for exterior traits. From 1999 to 2003, the trend has been to eliminate extreme animals on exterior traits. This may partly explain the improvement of sow length of productive life longevity from 560 d in 2000 to nearly 710 d in 2003 observed in the data set.

A total of 179 lactations obtained on 71 multiparous sows [30 Creole (CR) and 41 Large White (LW)] between June 2001 and July 2004 were used to determine effects of breed (CR vs. LW) and season (hot vs. warm) in a tropical humid climate on performance during a 28-d lactation period. Mean daily ambient temperature was greater during the hot season than during the warm season (26.0 vs. 23.8 degrees C), and relative humidity was similar in both seasons (85% on average). For both breeds, ADFI was reduced (-700 g/d, P < 0.01), sow BW loss was greater (17 vs. 12 kg, P < 0.01), and piglet growth was reduced (197 vs. 210 g/d, P < 0.05) during the hot vs. the warm season. At farrowing, LW sows were heavier (255 vs. 186 kg, P < 0.01) and had less backfat (21 vs. 40 mm, P < 0.01) than CR sows. The growth rate of CR piglets was lower than that of LW piglets (192 vs. 215 g/d, P < 0.01). A breed x season interaction was observed (P < 0.05) for ADFI and sow BW loss. During the hot season, the reduction of ADFI was more pronounced in LW than in CR sows (-910 vs. -470 g/d). Regardless of the season, BW loss of CR sows remained constant (14.2 kg), whereas it increased during the hot season for LW sows (10 kg). The weaning-to-estrus and the weaning-to-conception intervals were not affected by breed or season and averaged 4.8 and 6.1 d, respectively. The rectal temperature was greater (0.3 degrees C) during the hot season than during the warm season and greater in LW than in CR sows (39.1 vs. 38.8 degrees C, P < 0.10). This study confirms the negative effect of hot season in a tropical humid climate on performance of lactating sows and that breed can have a significant effect on lactation performance. The results also suggest that CR sows are more heat tolerant than LW sows.

The effects of breed and season on performance and feeding behavior were studied during 76 lactations in multiparous Large White (LW; n = 17) and Creole (CR; n = 23) sows reared in a humid tropical climate. The experiment was conducted in Guadeloupe (French West Indies, latitude 16 degrees N, longitude 61 degrees W) between May 2002 and July 2004. Average daily ambient temperature was greater during the hot season than during the warm season (26.0 vs. 23.8 degrees C), but relative humidity was similar in both seasons (85% on average). The daily fluctuations of ambient temperature and relative humidity were similar for both seasons. At farrowing, BW was lower (187 vs. 265 kg) and backfat thickness was greater (40 vs. 22 mm) in CR than in LW sows (P < 0.01). Sows were offered feed ad libitum between the fifth and the 26th day of lactation. There was a breed x season interaction (P < 0.05) for ADFI. During the hot season the reduction of ADFI was more pronounced in LW than in CR sows (-1,100 vs. -300 g/d). Irrespective of breed and season, the daily number of meals was 9.0. The meal size and the rate of feed intake were greater in LW than in CR sows, respectively (555 g and 153 g/min vs. 390 g and 83 g/min; P < 0.01). The diurnal proportion of ADFI was greater in CR than in LW sows (0.60 vs. 0.41; P < 0.01). The reduction in ADFI in LW sows during the hot season was mainly related to a reduction in feed intake during the day rather than during the night (-1.3 vs. -0.2 kg; P < 0.01). Duration of standing was not affected by breed or season, and it averaged 120 min/day. This study confirms the negative effect of the hot season on feeding behavior of lactating sows. It also suggests a better acclimation to daily high temperatures and a greater heat tolerance in CR compared with LW sows, at least for eating behavior.

A QTL analysis of multibreed experiments (i.e., crossed populations involving more than two founder breeds) offers clear advantages over classical two-breed crosses, among them increased power and a more comprehensive coverage of the total genetic variability in the species. An alternative to designed multibreed crosses is to reanalyze jointly several experiments involving different breeds. We report a multibreed, multitrait QTL analysis of SSCX that involves five different crosses, six breeds, and almost 3,000 genotyped individuals using a truly multibreed strategy to allow for any number of founder breed origins. Traits analyzed were growth, fat thickness, carcass length, and shoulder and ham weights. Generally, the joint analysis resulted in more significant QTL than the single-experiment analyses. We show that the QTL for fatness, which is highly significant (nominal P < 10 -43 ), is of Asiatic origin (Meishan). The next most significant QTL (nominal P < 10 -15 ) affected ham weight and seems to be segregating only between Large White and the rest of the breeds. A multitrait, multi-QTL analysis suggests that these are two distinct loci. Additionally, a locus segregating only between Iberian and Landrace affects live weight. The advantages of joint, multibreed analyses clearly outweigh their potential risks.

Pig chromosome 7 (SSC 7) has been shown to be rich in QTL affecting performance and quality traits. Most studies mapped the QTL close to the swine leukocyte antigens (SLA), which has a large effect on adaptability and natural selection. Previous comparative mapping studies suggested that the 15-cM region limited by markers LRA1 (mapped at 55 cM) and S0102 (mapped at 70 cM) contains hundreds of genes. To decrease the number of candidate genes, we improved the mapping resolution with a genetic chromosome dissection through a backcross recombinant progeny test program between Meishan (MS) and European (EU; i.e., Large White or Landrace) breeds. Three first-generation backcross--(EU x MS) x EU--and two second-generation backcross--([EU x MS] x EU) x EU--sires carrying a recombination in the QTL mapping interval were progeny-tested (i.e., measured for a total of 44 growth, fatness, carcass and meat quality traits). Progeny family size varied from 29 to 119 pigs. Animals were genotyped for markers covering the region of interest. Progeny-test results allowed the QTL interval to be decreased from 15 to 20 cM down to 10 cM, and even less than 6 cM if we assumed that the EU pigs used in this study share only one QTL allele. Except for a putative QTL affecting some carcass composition traits, the SLA is excluded as a candidate region, suggesting that it might be possible to apply a marker-assisted selection strategy for this QTL, while controlling SLA allele diversity. The strong QTL effects remaining in animals with only 12.5% (issued from first-generation backcross boars) and 6.25% (issued from second-generation back-cross boars) Meishan genetic background shows that epistatic interactions are likely to be limited. Finally, the QTL does not have strong effects on meat quality traits.

The effects of season in a tropical climate and parity on lactation performance of 106 Large White sows over several reproductive cycles (301 lactations in total) were studied in Guadeloupe (French West Indies, 16°N latitude, 61°W longitude) between January 1999 and March 2003. Two seasons were determined a posteriori from climatic parameters recorded continuously in a station close to the experimental unit. During the warm season, ambient temperature and relative humidity averaged 23-5°C and 0-831, respectively. In the hot season, the corresponding values were 26-0°C and 0-834, respectively. Over the 28-day lactation period, average daily food intake (ADFI) was lower (P < 0-001) and live-weight (LW) loss was higher (P < 0-05) during the hot season than during the warm season (3-9 v. 4-7 kg/day and 17 v. 12 kg, respectively). Growth rate and mean LW of piglets at weaning were lower (P < 0-05) during the hot season (203 v. 220 g/day and 7-0 v. 7-5 kg, respectively). However, the weaning-to-oestrus interval was not affected by season (5-4 days on average). The effect of season on ad libitum ADFI was less accentuated for primiparous than for multiparous sows (warm-hot 360 v. 2002 g/day). Irrespective of the season, ADFI was lower (P < 0-01) and piglet growth rate tended to be lower (P < 0-2) in primiparous than in multiparous sows (4-0 v. 4-4 kg/day and 205 v. 215 g/day, respectively). Moreover, the percentage of sows that returned to oestrus later than 5 days after weaning was higher in primiparous than in multiparous sows (25 v. 2%, P < 0-001). This study confirmed the negative effects of the hot season on performance of lactating sows raised in a humid tropical climate; the effects of season are dependent on parity number.

We present data suggesting that corticosteroid-binding globulin (CBG) may be the causal gene of a previously identified quantitative trait locus (QTL) associated with cortisol levels, fat, and muscle content in a pig intercross. Because Cbg in human and mouse maps in the region orthologous to the pig region containing this QTL, we considered Cbg as an interesting positional candidate gene because CBG plays a major role in cortisol bioavailability. Firstly, we cloned pig Cbg from a bacterial artificial chromosome library and showed by fluorescent in situ hybridization and radiation hybrid mapping that it maps on 7q26 at the peak of the QTL interval. Secondly, we detected in a subset of the pig intercross progeny a highly significant genetic linkage between CBG plasma binding capacity values and the chromosome 7 markers flanking the cortisol-associated QTL. In this population, CBG capacity is correlated positively to fat and negatively to muscle content. Thirdly, CBG capacity was three times higher in Meishan compared with Large White parental breeds and a 7-fold difference was found in Cbg mRNA expression between the two breeds. Overall, the data accumulated in this study point to Cbg gene as a key regulator of cortisol levels and obesity susceptibility.

Segregation analyses were performed using both maximum likelihood – via a Quasi Newton algorithm – (ML-QN) and Bayesian – via Gibbs sampling – (Bayesian-GS) approaches in the Chinese European Tiameslan pig line. Major genes were searched for average ultrasonic backfat thickness (ABT), carcass fat (X2 and X4) and lean (X5) depths, days from 20 to 100 kg (D20100), Napole technological yield (NTY), number of false (FTN) and good (GTN) teats, as well as total teat number (TTN). The discrete nature of FTN was additionally considered using a threshold model under ML methodology. The results obtained with both methods consistently suggested the presence of major genes affecting ABT, X2, NTY, GTN and FTN. Major genes were also suggested for X4 and X5 using ML-QN, but not the Bayesian-GS, approach. The major gene affecting FTN was confirmed using the threshold model. Genetic correlations as well as gene effect and genotype frequency estimates suggested the presence of four different major genes. The first gene would affect fatness traits (ABT, X2 and X4), the second one a leanness trait (X5), the third one NTY and the last one GTN and FTN. Genotype frequencies of breeding animals and their evolution over time were consistent with the selection performed in the Tiameslan line.

A QTL analysis of fat androstenone levels from a three-generation experimental cross between Large White and Meishan pig breeds was carried out. A total of 485 F 2 males grouped in 24 full-sib families, their 29 parents and 12 grandparents were typed for 137 markers distributed over the entire porcine genome. The F 2 male population was measured for fat androstenone levels at 100, 120, 140, and 160 d of age and at slaughter around 80 kg liveweight. Statistical analyses were performed using two interval mapping methods: a line-cross (LC) regression method, which assumes alternative alleles are fixed in founder lines, and a half- full-sib (HFS) maximum likelihood method, where allele substitution effects were estimated within each half- and full-sib family. Both methods revealed genomewide significant gene effects on chromosomes 3, 7, and 14. The QTL explained, respectively, 7 to 11%, 11 to 15%, and 6 to 8% of phenotypic variance. Three additional significant QTL explaining 4 to 7% of variance were detected on chromosomes 4 and 9 using LC method and on chromosome 6 using HFS method. Suggestive QTL were also obtained on chromosomes 2, 10, 11, 13, and 18. Meishan alleles were associated with higher androstenone levels, except on chromosomes 7, 10, and 13, although 10 and 13 additive effects were near zero. The QTL had essentially additive effects, except on chromosomes 4, 10, and 13. No evidence of linked QTL or imprinting effects on androstenone concentration could be found across the entire porcine genome. The steroid chromosome P450 21-hydroxylase (CYP21) and cytochrome P450 cholesterol side chain cleavage subfamily XIA (CYP11A) loci were investigated as possible candidate genes for the chromosome 7 QTL. No mutation of coding sequence has been found for CYP21. Involvement of a candidate regulatory mutation of CYP11A gene proposed by others can be excluded in our animals.

L'implication relativement récente de l'INRA et de l'ITSAP-Institut de l'abeille sur la thématique"génétique de l'abeille" semble mériter quelques précisions sur les perspectives des travaux en cours. Ce texte rappelle quelques notions importantes pour aborder sereinement ce sujet et replace la démarche proposée par les instituts techniques et scientifiques dans ce contexte.

A Reprendre pas de CLé UT; International audience; 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: Numerous quantitative trait loci (QTL) have been detected in pigs over the past 20 years using microsatellite markers. However, due to the low density of these markers, the accuracy of QTL location has generally been poor. Since 2009, the dense genome coverage provided by the Illumina PorcineSNP60 BeadChip has made it possible to more accurately map QTL using genome-wide association studies (GWAS). Our objective was to perform high-density GWAS in order to identify genomic regions and corresponding haplotypes associated with production traits in a French Large White population of pigs. Methods: Animals (385 Large White pigs from 106 sires) were genotyped using the PorcineSNP60 BeadChip and evaluated for 19 traits related to feed intake, growth, carcass composition and meat quality. Of the 64 432 SNPs on the chip, 44 412 were used for GWAS with an animal mixed model that included a regression coefficient for the tested SNPs and a genomic kinship matrix. SNP haplotype effects in QTL regions were then tested for association with phenotypes following phase reconstruction based on the Sscrofa10.2 pig genome assembly. Results: Twenty-three QTL regions were identified on autosomes and their effects ranged from 0.25 to 0.75 phenotypic standard deviation units for feed intake and feed efficiency (four QTL), carcass (12 QTL) and meat quality traits (seven QTL). The 10 most significant QTL regions had effects on carcass (chromosomes 7, 10, 16, 17 and 18) and meat quality traits (two regions on chromosome 1 and one region on chromosomes 8, 9 and 13). Thirteen of the 23 QTL regions had not been previously described. A haplotype block of 183 kb on chromosome 1 (six SNPs) was identified and displayed three distinct haplotypes with significant (0.0001 < P < 0.03) associations with all evaluated meat quality traits. Conclusions: GWAS analyses with the PorcineSNP60 BeadChip enabled the detection of 23 QTL regions that affect feed consumption, carcass and meat quality traits in a LW population, of which 13 were novel QTL. The proportionally larger number of QTL found for meat quality traits suggests a specific opportunity for improving these traits in the pig by genomic selection.

National audience; L’implication relativement récente de l’INRA et de l’ITSAP-Institut de l’abeille sur la thématique « génétique de l’abeille » semble mériter quelques précisions sur les perspectives des travaux en cours. Ce texte rappelle quelques notions importantes pour aborder sereinement ce sujet et replace la démarche proposée par les instituts techniques et scientifiques dans ce contexte.