155 results on '"Billon, Yvon"'
Search Results
2. Driving gut microbiota enterotypes through host genetics
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Larzul, Catherine, Estellé, Jordi, Borey, Marion, Blanc, Fany, Lemonnier, Gaëtan, Billon, Yvon, Thiam, Mamadou Gabou, Quinquis, Benoît, Galleron, Nathalie, Jardet, Deborah, Lecardonnel, Jérôme, Plaza Oñate, Florian, and Rogel-Gaillard, Claire
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- 2024
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3. Sex and fetal genome influence gene expression in pig endometrium at the end of gestation
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Bonnet, Agnes, Bluy, Lisa, Gress, Laure, Canario, Laurianne, Ravon, Laure, Sécula, Aurelie, Billon, Yvon, and Liaubet, Laurence
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- 2024
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4. Detection of DNA methylation signatures through the lens of genomic imprinting
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Hubert, Jean-Noël, Iannuccelli, Nathalie, Cabau, Cédric, Jacomet, Eva, Billon, Yvon, Serre, Rémy-Félix, Vandecasteele, Céline, Donnadieu, Cécile, and Demars, Julie
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- 2024
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5. Plasma 1H-NMR metabolic and amino acid profiles of newborn piglets from two lines divergently selected for residual feed intake
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Liaubet, Laurence, Guilmineau, Camille, Lefort, Gaëlle, Billon, Yvon, Reigner, Sébastien, Bailly, Jean, Marty-Gasset, Nathalie, Gress, Laure, Servien, Rémi, Bonnet, Agnès, Gilbert, Hélène, Vialaneix, Nathalie, and Quesnel, Hélène
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- 2023
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6. Rabbit targeted genomic sequences after heterologous hybridization using human exome
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Iannuccelli, Nathalie, Sarry, Julien, Billon, Yvon, Aymard, Patrick, Helies, Virginie, Cabau, Cédric, Donnadieu, Cécile, and Demars, Julie
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- 2022
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7. Microbiability and microbiome-wide association analyses of feed efficiency and performance traits in pigs
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Aliakbari, Amir, Zemb, Olivier, Cauquil, Laurent, Barilly, Céline, Billon, Yvon, and Gilbert, Hélène
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- 2022
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8. Plasticity of feeding behaviour traits in response to production environment (temperate vs. tropical) in group-housed growing pigs
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Poullet, Nausicaa, Rauw, Wendy M., Renaudeau, David, Riquet, Juliette, Giorgi, Mario, Billon, Yvon, Gilbert, Hélène, and Gourdine, Jean-Luc
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- 2022
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9. Divergent selection for feed efficiency in pigs altered the duodenum transcriptomic response to feed intake and its DNA methylation profiles.
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Devailly, Guillaume, Fève, Katia, Saci, Safia, Sarry, Julien, Valière, Sophie, Lluch, Jérôme, Bouchez, Olivier, Ravon, Laure, Billon, Yvon, Gilbert, Hélène, Riquet, Juliette, Beaumont, Martin, and Demars, Julie
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DNA methylation ,DUODENUM ,SWINE farms ,TRANSCRIPTOMES ,SWINE ,TIGHT junctions - Abstract
Feed efficiency is a trait of interest in pigs as it contributes to lowering the ecological and economical costs of pig production. A divergent genetic selection experiment from a Large White pig population was performed for 10 generations, leading to pig lines with relatively low-(LRFI) and high- (HRFI) residual feed intake (RFI). Feeding behavior and metabolic differences have been previously reported between the two lines. We hypothesized that part of these differences could be related to differential sensing and absorption of nutrients in the proximal intestine. We investigated the duodenum transcriptome and DNA methylation profiles comparing overnight fasting with ad libitum feeding in LRFI and HRFI pigs (n = 24). We identified 1,106 differentially expressed genes between the two lines, notably affecting pathways of the transmembrane transport activity and related to mitosis or chromosome separation. The LRFI line showed a greater transcriptomic response to feed intake than the HRFI line. Feed intake affected genes from both anabolic and catabolic pathways in the pig duodenum, such as rRNA production and autophagy. Several nutrient transporter and tight junction genes were differentially expressed between lines and/or by short-term feed intake. We also identified 409 differentially methylated regions in the duodenum mucosa between the two lines, while this epigenetic mark was less affected by feeding. Our findings highlighted that the genetic selection for feed efficiency in pigs changed the transcriptome profiles of the duodenum, and notably its response to feed intake, suggesting key roles for this proximal gut segment in mechanisms underlying feed efficiency. [ABSTRACT FROM AUTHOR]
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- 2024
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10. Influence of genetics and the pre-vaccination blood transcriptome on the variability of antibody levels after vaccination against Mycoplasma hyopneumoniae in pigs
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Blanc, Fany, Maroilley, Tatiana, Revilla, Manuel, Lemonnier, Gaëtan, Leplat, Jean-Jacques, Billon, Yvon, Ravon, Laure, Bouchez, Olivier, Bidanel, Jean-Pierre, Bed’Hom, Bertrand, Pinard-van der Laan, Marie-Hélène, Estellé, Jordi, and Rogel-Gaillard, Claire
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- 2021
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11. Links between fecal microbiota and the response to vaccination against influenza A virus in pigs
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Borey, Marion, Blanc, Fany, Lemonnier, Gaëtan, Leplat, Jean-Jacques, Jardet, Deborah, Rossignol, Marie-Noëlle, Ravon, Laure, Billon, Yvon, Bernard, Maria, Estellé, Jordi, and Rogel-Gaillard, Claire
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- 2021
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12. Identification of genomic regions affecting production traits in pigs divergently selected for feed efficiency
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Delpuech, Emilie, Aliakbari, Amir, Labrune, Yann, Fève, Katia, Billon, Yvon, Gilbert, Hélène, and Riquet, Juliette
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- 2021
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13. The maturity in fetal pigs using a multi-fluid metabolomic approach
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Lefort, Gaëlle, Servien, Rémi, Quesnel, Hélène, Billon, Yvon, Canario, Laurianne, Iannuccelli, Nathalie, Canlet, Cécile, Paris, Alain, Vialaneix, Nathalie, and Liaubet, Laurence
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- 2020
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14. Effects of divergent selection upon adrenocortical activity on immune traits in pig
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Hervé, Julie, Terenina, Elena, Haurogné, Karine, Bacou, Elodie, Kulikova, Elizaveta, Allard, Marie, Billon, Yvon, Bach, Jean-Marie, Mormède, Pierre, and Lieubeau, Blandine
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- 2019
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15. Plasma 1H-NMR metabolic and amino acid profiles of newborn piglets from two lines divergently selected for residual feed intake.
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Liaubet, Laurence, Guilmineau, Camille, Lefort, Gaëlle, Billon, Yvon, Reigner, Sébastien, Bailly, Jean, Marty-Gasset, Nathalie, Gress, Laure, Servien, Rémi, Bonnet, Agnès, Gilbert, Hélène, Vialaneix, Nathalie, and Quesnel, Hélène
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PIGLETS ,AMINO acids ,UREA ,SWINE breeding ,NEWBORN infants ,ENERGY metabolism - Abstract
Together with environmental factors, physiological maturity at birth is a major determinant for neonatal survival and postnatal development in mammalian species. Maturity at birth is the outcome of complex mechanisms of intra-uterine development and maturation during the end of gestation. In pig production, piglet preweaning mortality averages 20% of the litter and thus, maturity is a major welfare and economic concern. Here, we used both targeted and untargeted metabolomic approaches to provide a deeper understanding of the maturity in a model of lines of pigs divergently selected on residual feed intake (RFI), previously shown to have contrasted signs of maturity at birth. Analyses were conducted on plasma metabolome of piglets at birth and integrated with other phenotypic characteristics associated to maturity. We confirmed proline and myo-inositol, previously described for their association with delayed growth, as potential markers of maturity. Urea cycle and energy metabolism were found more regulated in piglets from high and low RFI lines, respectively, suggesting a better thermoregulation ability for the low RFI (with higher feed efficiency) piglets. [ABSTRACT FROM AUTHOR]
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- 2023
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16. Transcriptomic and DNA methylation response to feed intake in the duodenum in high- and low- feed efficiency pig lines
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Devailly, Guillaume, Fêve, Katia, Saci, Safia, Sarry, Julien, Valière, Sophie, Bouchez, Olivier, Ravon, Laure, Billon, Yvon, Beaumont, Martin, Gilbert, Hélène, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Génome et Transcriptome - Plateforme Génomique ( GeT-PlaGe), Plateforme Génome & Transcriptome (GET), Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité Expérimentale Elevages Porcins Innovants (GenESI), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), French Minister of Higher Education, Research and Innovation (APAFIS#21107-2018120415595562 v10), and Devailly, Guillaume
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[SDV.MHEP.PHY] Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO] ,[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,[SDV.MHEP.PHY]Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO] ,[SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] - Abstract
International audience; Feed efficiency is a complex trait of interest in animal breeding to reduce environmental impact of livestock herding and the cost of animal feed. A divergent selection on feed efficiency was carried out in pigs for more than 10 generations at an INRAE experimental unit, establishing lines of relative high- and low-feed efficiency in large white pigs. The objective of this study was to identify the molecular mechanisms underlying the divergence in feed efficiency between the two pig lines in the duodenum. We focused on the duodenum because of its sensory role in the hunger satiety pathways.Duodenum mucosal samples were collected in post-weaning pigs from the two divergent lines either after a 12 h period of feed restriction, or with a 10 h period of feed restriction followed by a 2 h period of ad libitum feed access (n = 6 per group and per line). Transcritomes and methylomes were analysed by poly-A RNA sequencing (RNA-seq) and by methylated DNA precipitation followed by sequencing (MeDP-seq), respectively. Transcriptomic reads were analysed with nf-core/rnaseq and limma-voom. MeDP-seq reads were analysed with nf-core/chipseq and the BayMeth method.A total of 962 genes were differentially expressed in the duodenum mucosa between the conditions (fasted vs fed), in contrast with 318 differentially expressed genes when comparing the divergent lines. The DNA methylome of the duodenum mucosa was unaffected by short term feed intake, but was distinct between the lines. More transcripts were affected by short term feed intake in the feed-efficient line than in the other line, including genes of the incretine secretion pathways involved in the production of GIP and GLP-1.Thus the duodenum transcriptomic response to short term feed intake was distinct in feed efficient and less efficient pig lines. These differences might in part be due to differences in DNA methylation profiles.
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- 2022
17. Heterologous hybridization using the human exome - a molecular tool to target and identify major genes
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Iannuccelli, Nathalie, Cabau, Cédric, Sarry, Julien, Bouchez, Olivier, Billon, Yvon, Riquet, Juliette, Allain, Daniel, Demars, Julie, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
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[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics ,human+exome+capture+sequencing+variants - Abstract
International audience; Identifying causal mutations responsible of phenotypes in a time and cost-effective manner remains a challenge still for all species. Although the portfolio of next-generation sequencing methodologies offers a broad range of opportunities nowadays, having the right and suitable molecular genetic tools in non-model organisms is often an issue. For the European rabbit (Oryctolagus cuniculus), considered as an animal model for experimental research, the OryCun2.0 reference genome was released in 2009 and the Affymetrix AxiomOrcun SNP Array was made available in 2016. This novel beadchip gives the possibility to develop conveniently genome-wide association studies (GWAS) in rabbits without however freeing itself from the subsequent steps of causal mutation characterization. Whole exome sequencing (WES) appears as a direct and suitable strategy to target and sequence variants all at once. Unfortunately, no exome enrichment tool exist for rabbits. Here, we proposed to capture the rabbit exome using the marketed human panel since human and rabbit genomes are closely related on the phylogenetic tree of species. We performed heterologous hybridization for 48 rabbits from 7 different populations and generated 2 billion sequencing reads for the whole dataset. The quality of the heterologous hybridization allowed the capture of the rabbit exome and enabled a dataset of 40,000 confident variants that specifically target both protein-coding and extended exons. This method also presents a unique opportunity to investigate both (i) the genetic diversity of different rabbits’ breeds and (ii) the mendelian determinism of specific phenotypes in rabbits without resorting to costly customized tools.
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- 2021
18. Response to selection on fecal microbiota composition in Large White piglets
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Larzul, Catherine, Borey, Marion, Billon, Yvon, Rossignol, Marie-Noelle, Lemonnier, Gaëtan, Estelle, Jordi, Rogel Gaillard, Claire, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), LARZUL, Catherine, and Rogel-Gaillard, Claire
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[SDV] Life Sciences [q-bio] ,[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics ,[SDV.GEN.GA] Life Sciences [q-bio]/Genetics/Animal genetics - Abstract
International audience; Pig gut microbiota displays high inter-individual variability and it remains an open question to determine to what extent its taxonomic composition relies on host genetic determinism and not only on environmental conditions. We carried out a study to demonstrate coevolution of the host and its gut microbiota established one month post-weaning, by directional selection over two generations. The gut microbiota was characterized by sequencing the V3-V4 variable region of the 16S rRNA gene from fecal samples collected on 60-day-old Large White piglets. Amplicon sequence variants were inferred from amplicon data and the microbial community was further studied at the genus level. Based on the stratification of the initial population (generation G0) according to the two major pig enterotypes, characterized by relative overabundance of either Prevotella and Mitsuokella or Ruminococcus and Treponema, we used the relative abundance of these four genera as selection criteria. From the G0 population of 317 piglets, we selected 6 males and 30 females per line and produced two successive generations (G1 and G2) of approximately 130 pigs per line. We consistently confirmed a moderate heritability for each of the selected genera (h²=0.3 to 0.4). We also estimated the heritability values of the relative abundances for 64 additional bacterial genera, which ranged from 0.1 to 0.5. We showed significant differences between the two lines in the relative abundance of the four bacterial genera at G1 (P
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- 2021
19. Early-life establishment of the swine gut microbiome and impact on host phenotypes
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Mach, Núria, Berri, Mustapha, Estellé, Jordi, Levenez, Florence, Lemonnier, Gaëtan, Denis, Catherine, Leplat, Jean-Jacques, Chevaleyre, Claire, Billon, Yvon, Doré, Joël, Rogel-Gaillard, Claire, and Lepage, Patricia
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- 2015
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20. Genetic relationships between feed efficiency and gut microbiome in pig lines selected for residual feed intake
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Aliakbari, Amir, Zemb, Olivier, Billon, Yvon, Barilly, Céline, Ahn, Ingrid, Riquet, Juliette, Gilbert, Hélène, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité Expérimentale Elevages Porcins Innovants (GenESI), and Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
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Swine ,gut microbiome ,pigs ,Original Articles ,heritability ,Animal Feed ,Gastrointestinal Microbiome ,Eating ,Feces ,[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics ,Phenotype ,feed efficiency ,Animals ,Original Article ,genetic - Abstract
International audience; This study aimed to evaluate the genetic relationship between faecal microbial composition and five feed efficiency (FE) and production traits, residual feed intake (RFI), feed conversion ratio (FCR), daily feed intake (DFI), average daily gain (ADG) and backfat thickness (BFT). A total of 588 samples from two experimental pig lines developed by divergent selection for RFI were sequenced for the 16 rRNA hypervariable V3-V4 region. The 75 genera with less than 20% zero values (97% of the counts) and two alpha-diversity indexes were analysed. Line comparison of the microbiota traits and estimations of heritability (h(2)) and genetic correlations (r(g)) were analysed. A non-metric multidimensional scaling showed line differences between genera. The alpha-diversity indexes were higher in the LRFI line than in the HRFI line (p < .01), with h(2) estimates of 0.19 +/- 0.08 (Shannon) and 0.12 +/- 0.06 (Simpson). Forty-eight genera had a significant h(2) (>0.125). The r(g) of the alpha-diversities indexes with production traits were negative. Some r(g) of genera belonging to the Lachnospiraceae, Ruminococcaceae, Prevotellaceae, Lactobacillaceae, Streptococcaceae, Rikenellaceae and Desulfovibrionaceae families significantly differed from zero (p < .05) with FE traits, RFI (3), DFI (7) and BFT (11). These results suggest that a sizable part of the variability of the gut microbial community is under genetic control and has genetic relationships with FE, including diversity indicators. It offers promising perspectives for selection for feed efficiency using gut microbiome composition in pigs.
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- 2021
21. Radars à ondes millimétriques pour l'enregistrement automatique de l'activité posturale des truies
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Dore, Alexandre, Lihoreau, Mathieu, Billon, Yvon, Ravon, Laure, Bailly, Jean, Bompa, Jean-François, Ricard, Edmond, Aubert, Hervé, Henry, Dominique, Canario, Laurianne, Équipe MIcro et Nanosystèmes pour les Communications sans fil (LAAS-MINC), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Centre de Recherches sur la Cognition Animale (CRCA), Centre de Biologie Intégrative (CBI), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut des sciences du cerveau de Toulouse. (ISCT), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J)-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Unité Expérimentale Elevages Porcins Innovants (GenESI), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), European Association for Animal Production, Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Centre de Recherches sur la Cognition Animale - UMR5169 (CRCA), Institut des sciences du cerveau de Toulouse. (ISCT), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre de Biologie Intégrative (CBI), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-École nationale supérieure agronomique de Toulouse (ENSAT), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
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[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing ,Sow ,Truie ,[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE] ,[INFO.INFO-NA]Computer Science [cs]/Numerical Analysis [cs.NA] ,ComputingMilieux_MISCELLANEOUS ,[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] - Abstract
Visio-conférence; International audience
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- 2020
22. Studies of male and female meiosis in inv(4)(p1.4;q2.3) pig carriers
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Massip, Katia, Yerle, Martine, Billon, Yvon, Ferchaud, Stéphane, Bonnet, Nathalie, Calgaro, Anne, Mary, Nicolas, Dudez, Anne-Marie, Sentenac, Céline, Plard, Christophe, Ducos, Alain, and Pinton, Alain
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- 2010
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23. Development and validation of an embedded tool to measure postural activity of lactating sows
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Canario, Laurianne, Labrune, Yann, Bompa, Jean-François, Billon, Yvon, Ravon, Laure, Reignier, Sébastien, Bailly, Jean, bonneau, Mathieu, Ricard, Edmond, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Génétique, Expérimentation et Système Innovants (GenESI), Institut National de la Recherche Agronomique (INRA), and Unité de Recherches Zootechniques (URZ)
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[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT] ,activité ,accélérateur ,truie - Abstract
International audience; The objective was to develop a tool to measure sow postural activity during lactation while kept between fences in the farrowing crate. Several trials were carried out to select sensors and test their ability to detect 5 different positions of the sow. First, several sensors, placed in a single metal box, were attached to the upper part of the back of sows with a custom-built belt that passes underneath the belly, just behind the front legs. For validation of the positions predicted from sensor data, sow behaviour was recorded with use of a digital camera and video records were analysed by a single observer. Prediction ability was tested with machine learning applied to random forests for the three-axis data provided by the sensors in the X, Y and Z dimensions. When comparing information provided by three sensors, i.e. two accelerometers (sensors A and B) and an application developed for a smartphone (sensor C), one sensor detected five positions more accurately than the other two. The error rate of prediction from 30% of the data was 2.1% with sensor A, 3.1% with sensor B, and 4.8% with sensor C. Additional trials focused on the ability of sensor A to distinguish among the five positions, using five sows. Statistical sensitivity was 0.94 and 0.95 for the right and left lateral positions, respectively; 0.79 for the ventral position; 0.75 for the standing position; but only 0.33 for the sitting position (because it represented only 4% of sows’ time budget). One single axis was sufficient to detect the two lateral positions. Next, we concentrated our interest on the advantages and drawbacks of 2 accelerometers: we ran new trials to compare outputs from sensor A with those obtained with a sensor D. We used acquisition speeds varying from 1 to 16 obs/sec to optimize the sampling rate to detect positions accurately and to test if postural changes at risk for the piglets can be detected. Analyses are in progress. The use of accelerometers to measure finely the postural activity of lactating sows is promising.
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- 2019
24. Searching for markers of immunocompetence in blood: application to vaccination against Influenza A virus in pigs
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Blanc, Fany, Estellé, Jordi, Lemonnier, Gaëtan, Leplat, Jean Jacques, Bouguyon, Edwige, Billon, Yvon, Bouchez, Olivier, Pinard - Van Der Laan, Marie-Hélène, Rogel Gaillard, Claire, Génétique Animale et Biologie Intégrative (GABI), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Université Paris Saclay (COMUE), Unité de recherche Virologie et Immunologie Moléculaires (VIM), Institut National de la Recherche Agronomique (INRA), UE 1372 Génétique, Expérimentation et Système Innovants, Institut National de la Recherche Agronomique (INRA)-Génétique animale (G.A.)-Physiologie Animale et Systèmes d'Elevage (PHASE), Institut National de la Recherche Agronomique (INRA)-Génétique, Expérimentation et Système Innovants (GenESI), GeT PlaGe, Genotoul, Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Unité de recherche Virologie et Immunologie Moléculaires (VIM (UR 0892)), Génétique, Expérimentation et Système Innovants (GenESI), Génome et Transcriptome - Plateforme Génomique (GeT-PlaGe), Institut National de la Recherche Agronomique (INRA)-Plateforme Génome & Transcriptome (GET), Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), European Project: 633184,H2020,H2020-SFS-2014-2,SAPHIR(2015), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3)
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[SDV]Life Sciences [q-bio] ,education ,reproductive and urinary physiology ,humanities ,health care economics and organizations - Abstract
Searching for markers of immunocompetence in blood: application to vaccination against Influenza A virus in pigs . International Veterinary Immunology Symposium (IVIS)
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- 2019
25. Towards the quantitative characterisation of piglets’ robustness to weaning: a modelling approach
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Revilla, Manuel, Friggens, Nicolas, Broudiscou, Laurent, Lemonnier, Gaetan, Blanc, Fany, Ravon, Laure, Mercat, M. J., Billon, Yvon, Rogel Gaillard, Claire, Le Floc'h, Nathalie, Estellé, Jordi, Muñoz-Tamayo, Rafael, Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Modélisation Systémique Appliquée aux Ruminants (MoSAR), UE 1372 Génétique, Expérimentation et Système Innovants, Institut National de la Recherche Agronomique (INRA)-Génétique animale (G.A.)-Physiologie Animale et Systèmes d'Elevage (PHASE), Institut National de la Recherche Agronomique (INRA)-Génétique, Expérimentation et Système Innovants (GenESI), Institut du porc and Alliance R&D, Institut du Porc, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Génétique, Expérimentation et Système Innovants (GenESI), Institut National de la Recherche Agronomique (INRA), Institut du Porc (IFIP), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA), AgroParisTech-Institut National de la Recherche Agronomique (INRA), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
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Diarrhea ,perturbation ,sevrage ,[SDV]Life Sciences [q-bio] ,Weight Gain ,Models, Biological ,SF1-1100 ,dynamic modelling ,modelling ,body weight ,modèle mathématique ,robustesse des animaux ,Animals ,resilience ,modélisation ,Swine Diseases ,weaning ,pigs ,swine ,sucking pig ,Animal culture ,Female ,Physiology and Functional Biology ,porcelet ,mathematical model ,Research Article ,porc - Abstract
Lien vers la version preprint déposée sur Biorxiv.org https://prodinra.inra.fr/record/447811; Weaning is a critical transition phase in swine production in which piglets must cope with different stressors that may affect their health. During this period, the prophylactic use of antibiotics is still frequent to limit piglet morbidity, which raises both economic and public health concerns such as the appearance of antimicrobial-resistant microbes. With the interest of developing tools for assisting health and management decisions around weaning, it is key to provide robustness indexes that inform on the animals’ capacity to endure the challenges associated with weaning. This work aimed at developing a modelling approach for facilitating the quantification of piglet resilience to weaning. A total of 325 Large White pigs weaned at 28 days of age were monitored and further housed and fed conventionally during the post-weaning period without antibiotic administration. Body weight and diarrhoea scores were recorded before and after weaning, and blood was sampled at weaning and 1 week later for collecting haematological data. A dynamic model was constructed based on the Gompertz–Makeham law to describe live weight trajectories during the first 75 days after weaning, following the rationale that the animal response is partitioned in two time windows (a perturbation and a recovery window). Model calibration was performed for each animal. Our results show that the transition time between the two time windows, as well as the weight trajectories are characteristic for each individual. The model captured the weight dynamics of animals at different degrees of perturbation, with an average coefficient of determination of 0.99, and a concordance correlation coefficient of 0.99. The utility of the model is that it provides biologically meaningful parameters that inform on the amplitude and length of perturbation, and the rate of animal recovery. Our rationale is that the dynamics of weight inform on the capability of the animal to cope with the weaning disturbance. Indeed, there were significant correlations between model parameters and individual diarrhoea scores and haematological traits. Overall, the parameters of our model can be useful for constructing weaning robustness indexes by using exclusively the growth curves. We foresee that this modelling approach will provide a step forward in the quantitative characterisation of robustness.
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- 2019
26. Effect of chronic and acute heat challenges on fecal microbiota composition, production, and thermoregulation traits in growing pigs
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Le Sciellour, Mathilde, Zemb, Olivier, Hochu, Isabelle, Riquet, Juliette, Gilbert, Hélène, Giorgi, Mario, Billon, Yvon, Gourdine, Jean-Luc, Renaudeau, David, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Plateforme Tropicale d'Expérimentation sur l'Animal (PTEA), Institut National de la Recherche Agronomique (INRA), Génétique, Expérimentation et Système Innovants (GenESI), Unité de Recherches Zootechniques (URZ), ANR-12-ADAP-0015, European Project: 633531,H2020,H2020-SFS-2014-2,Feed-a-Gene(2015), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT], UE 1372 Génétique, Expérimentation et Système Innovants, Institut National de la Recherche Agronomique (INRA)-Génétique animale (G.A.)-Physiologie Animale et Systèmes d'Elevage (PHASE), Institut National de la Recherche Agronomique (INRA)-Génétique, Expérimentation et Système Innovants (GenESI), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-École nationale supérieure agronomique de Toulouse (ENSAT), and Université de Toulouse (UT)-Université de Toulouse (UT)
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Animal biology ,stress thermique ,Pig ,climat ,Microbiota ,Climate ,Performance ,[SDV.BA]Life Sciences [q-bio]/Animal biology ,swine ,performance animale ,Enterotype ,Heat stress ,population bactérienne ,heat stress ,microbiote ,composition ,Biologie animale ,porc - Abstract
The present study aimed at investigating the impact of heat challenges on gut microbiota composition in growing pigs and its relationship with pigs’ performance and thermoregulation responses. From a total of 10 F1 sire families, 558 and 564 backcross Large White × Créole pigs were raised and phenotyped from 11 to 23 wk of age in temperate (TEMP) and in tropical (TROP) climates, respectively. In TEMP, all pigs were subjected to an acute heat challenge (3 wk at 29 °C) from 23 to 26 wk of age. Feces samples were collected at 23 wk of age both in TEMP and TROP climate (TEMP23 and TROP23 samples, respectively) and at 26 wk of age in TEMP climate (TEMP26 samples) for 16S rRNA analyses of fecal microbiota composition. The fecal microbiota composition significantly differed between the 3 environments. Using a generalized linear model on microbiota composition, 182 operational taxonomic units (OTU) and 2 pathways were differentially abundant between TEMP23 and TEMP26, and 1,296 OTU and 20 pathways between TEMP23 and TROP23. Using fecal samples collected at 23 wk of age, pigs raised under the 2 climates were discriminated with 36 OTU using a sparse partial least square discriminant analysis that had a mean classification error-rate of 1.7%. In contrast, pigs in TEMP before the acute heat challenge could be discriminated from the pigs in TEMP after the heat challenge with 32 OTU and 9.3% error rate. The microbiota can be used as biomarker of heat stress exposition. Microbiota composition revealed that pigs were separated into 2 enterotypes. The enterotypes were represented in both climates. Whatever the climate, animals belonging to the Turicibacter–Sarcina–Clostridium sensu stricto dominated enterotype were 3.3 kg heavier (P < 0.05) at 11 wk of age than those belonging to the Lactobacillus-dominated enterotype. This latter enterotype was related to a 0.3 °C lower skin temperature (P < 0.05) at 23 wk of age. Following the acute heat challenge in TEMP, this enterotype had a less-stable rectal temperature (0.34 vs. 0.25 °C variation between weeks 23 and 24, P < 0.05) without affecting growth performance (P > 0.05). Instability of the enterotypes was observed in 34% of the pigs, switching from an enterotype to another between 23 and 26 wk of age after heat stress. Despite a lower microbial diversity, the Turicibacter–Sarcina–Clostridium sensu stricto dominated enterotype was better adapted to heat stress conditions with lower thermoregulation variations.
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- 2019
27. Genotype by environment interactions for performance and thermoregulation responses in growing pigs
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Gourdine, Jean-Luc, Riquet, Juliette, Rose, Roseline, Poullet, Nausicaa, Giorgi, Mario, Billon, Yvon, Renaudeau, David, Gilbert, Hélène, Unité de Recherches Zootechniques (URZ), Institut National de la Recherche Agronomique (INRA), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Plateforme Tropicale d'Expérimentation sur l'Animal (PTEA), Génétique, Expérimentation et Système Innovants (GenESI), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), ANR PigHeat, ANR-12-ADAP-0015, La Région Guadeloupe, and Europe : FEDER, FES, FEADER : Projet AgroEcodiv
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Male ,thermoregulation ,[SDV.GEN]Life Sciences [q-bio]/Genetics ,Genotype ,Swine ,[SDV]Life Sciences [q-bio] ,Body Weight ,Animal Genetics and Genomics ,Temperature ,Bayes Theorem ,Breeding ,heat stress ,[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics ,Phenotype ,Animals ,Female ,Gene-Environment Interaction ,[INFO]Computer Science [cs] ,Heat-Shock Response ,Body Temperature Regulation ,temperate - Abstract
International audience; Heat stress affects pig health, welfare, and production, and thus the economic viability of the pig sector in many countries. Breeding for heat tolerance is a complex issue, increasingly important due to climate change and the development of pig production in tropical areas. Characterizing genetic determinism of heat tolerance would help building selection schemes dedicated to high performance in tropical areas. The main objective of our study was to estimate the genetic parameters for production and thermoregulation traits in two highly related growing pig populations reared in temperate (TEMP) or tropical humid (TROP) environment. Pigs came from a backcross population between Large White (LW, heat sensitive) and Creole (CR, heat tolerant) pigs. Phenotypic data were obtained on a total of 1,297 pigs using the same procedures in both environments, for body weight (BW, at weeks 11 and 23), daily feed intake (ADFI), backfat thickness (BFT, at weeks 19 and 23), cutaneous temperature (CT, at weeks 19 and 23), and rectal temperature (RT, at weeks 19, 21, and 23). Feed conversion ratio (FCR) and residual feed intake (RFI) were computed for the whole test period (11 to 23 wk). Criteria comparing the fits to the data revealed genotype × environment (G × E) interactions for most traits but not for FCR. The variance components were obtained using two different methods, a restricted maximum likelihood method and a Bayesian Markov chain Monte Carlo method, considering that traits are either similar or different in each environment. Regardless of the method, heritability estimates for production traits were moderate to high, except for FCR (lower than 0.18). Heritability estimates for RT were low to moderate, ranging from 0.04 to 0.34. The genetic correlations of each trait between environments generally differed from 1, except for FCR and ADG. For most thermoregulation traits, they also did not differ significantly from zero, suggesting that the main genetic bases of heat tolerance may vary in different environment. Within environments, the unfavorable genetic correlations between production traits and RT suggest an antagonism between the ability to maintain inner temperature and the ability to increase ADFI and ADG. However, greater RT were also associated to leaner pigs and better feed efficiency. Nevertheless, due to large inaccuracies of these estimations, larger cohorts would be needed to decide about the best breeding schemes to choose for tropical pig production.
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- 2019
28. Immunome differences between porcine ileal and jejunal Peyer’s patches revealed by global transcriptome sequencing of gut-associated lymphoid tissues
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Maroilley, Tatiana, Berri, Mustapha, Lemonnier, Gaetan, Esquerré, D., Chevaleyre, Claire, Melo, Sandrine, MEURENS, François, Coville, Jean-Luc, Leplat, Jean Jacques, Rau, Andrea, Bed'Hom, Bertrand, Vincent-Naulleau, Silvia, Mercat, Marie-José, Billon, Yvon, Lepage, Patricia, Rogel-Gaillard, Claire, Estellé, Jordi, Canadian Space Agency (CSA), Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Institut de radiobiologie cellulaire et moléculaire (iRCM), Service de radiobiologie expérimentale et innovation technologiques (SREIT), Laboratoire de Radiologie et d'Etude du génome, Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Institut Sophia Agrobiotech [Sophia Antipolis] (ISA), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (... - 2019) (UNS), Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), MICrobiologie de l'ALImentation au Service de la Santé (MICALIS), Infectiologie et Santé Publique (UMR ISP), Institut National de la Recherche Agronomique (INRA)-Université de Tours (UT), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-École nationale supérieure agronomique de Toulouse (ENSAT), Université de Toulouse (UT)-Université de Toulouse (UT), DRF/IRCM/SREIT/LREG, Institut du Porc (IFIP), Génétique, Expérimentation et Système Innovants (GenESI), Institut National de la Recherche Agronomique (INRA), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Institut Sophia Agrobiotech (ISA), Centre National de la Recherche Scientifique (CNRS)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Recherche Agronomique (INRA), SUS-FLORA project (ANR-10-GENM-016) of the French National Agency and internal funds of INRA’s Animal Genetics Division, Biologie, Epidémiologie et analyse de risque en Santé Animale (BIOEPAR), Institut National de la Recherche Agronomique (INRA)-École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS), Laboratoire de radiobiologie et d'étude du génome (LREG), Institut National de la Recherche Agronomique (INRA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS), INRA, ANR-10-GENM-0016,SUS_FLORA,Contribution du microbiote intestinal à l'homéostasie du système immunitaire chez le porc: approches génétiques et génomiques(2010), AgroParisTech-Institut National de la Recherche Agronomique (INRA), and Institut National de la Recherche Agronomique (INRA)-Université de Tours
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Male ,[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT] ,Lymphoid Tissue ,Swine ,T-Lymphocytes ,education ,lcsh:Medicine ,[SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy ,Peyer's Patches ,Ileum ,Exome Sequencing ,Animals ,Mesentery ,lcsh:Science ,ComputingMilieux_MISCELLANEOUS ,B-Lymphocytes ,[SDV.GEN]Life Sciences [q-bio]/Genetics ,[SDV.BA]Life Sciences [q-bio]/Animal biology ,[SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE] ,lcsh:R ,Cell Differentiation ,Jejunum ,[SDV.IMM]Life Sciences [q-bio]/Immunology ,lcsh:Q ,Female ,Lymph Nodes ,Transcriptome - Abstract
International audience; The epithelium of the intestinal mucosa and the gut-associated lymphoid tissues (GALT) constitute an essential physical and immunological barrier against pathogens. In order to study the specificities of the GALT transcriptome in pigs, we compared the transcriptome profiles of jejunal and ileal Peyer's patches (PPs), mesenteric lymph nodes (MLNs) and peripheral blood (PB) of four male piglets by RNA-Seq. We identified 1,103 differentially expressed (DE) genes between ileal PPs (IPPs) and jejunal PPs (JPPs), and six times more DE genes between PPs and MLNs. The master regulator genes FOXP3, GATA3, STAT4, TBX21 and RORC were less expressed in IPPs compared to JPPs, whereas the transcription factor BCL6 was found more expressed in IPPs. In comparison between IPPs and JPPs, our analyses revealed predominant differential expression related to the differentiation of T cells into Th1, Th2, Th17 and iTreg in JPPs. Our results were consistent with previous reports regarding a higher T/B cells ratio in JPPs compared to IPPs. We found antisense transcription for respectively 24%, 22% and 14% of the transcripts detected in MLNs, PPs and PB, and significant positive correlations between PB and GALT transcriptomes. Allele-specific expression analyses revealed both shared and tissue-specific cis-genetic control of gene expression.
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- 2018
29. Testicular development, sex hormones and boar taint in pig lines divergent for residual feed intake
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Prunier, Armelle, Billon, Yvon, Ruesche, Julien, Ferchaud, Stéphane, Gilbert, Hélène, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), UE 1372 Génétique, Expérimentation et Système Innovants, Institut National de la Recherche Agronomique (INRA)-Génétique animale (G.A.)-Physiologie Animale et Systèmes d'Elevage (PHASE), Institut National de la Recherche Agronomique (INRA)-Génétique, Expérimentation et Système Innovants (GenESI), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT], École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Génétique, Expérimentation et Système Innovants (GenESI), and Institut National de la Recherche Agronomique (INRA)
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boar taint ,puberty ,consommation alimentaire résiduelle ,stéroïde ,puberte ,[SDV]Life Sciences [q-bio] ,feed efficiency ,steroid ,efficience alimentaire ,porc mâle entier ,lignée divergente - Abstract
Improving feed efficiency and rearing entire male pigs are relevant strategies to reduce feed cost and environmental waste in pig production. The major constraint for rearing entire male pigs being boar taint, an experiment was performed to determine the consequences of a divergent selection on residual feed intake (RFI: low RFI = LRFI; high RFI = HRFI) on pubertal development and boar taint. Purebred French Large White male pigs from two divergent lines for RFI (9th generation of selection, n = 45 or 43 pigs/line from 33 litters) were reared in two batches (n = 19 to 24 pigs/line/batch). Blood samples were drawn at 15 and 166±1 days of age (mean±SD) and pigs were weighed. After slaughter at 167±1 days of age, a backfat sample was collected in the neck and the genital tract was removed for testis and epididymis weighing after tissue trimming. Percentages of testis and epididymis weight relatively to liveweight were calculated for statistical analyses. All data were analyzed by ANOVA using R, including line and batch as fixed effects and litter as a random effect. When necessary, a log transformation was applied before analysis and adjusted means were backcalculated. Before slaughter, LRFI pigs were lighter than HRFI pigs (100±2 vs 106±2 kg liveweight, P0.1). However, plasma oestradiol-17 before slaughter (9.0 vs 17.5 pg/ml), fat androstenone (0.22 vs 0.34 µg/g pure fat), testis (3.5 vs 4.4‰) and epidydimis (1.18 vs 1.62‰) relative weights were lower in HRFI than LRFI pigs (P
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- 2018
30. On the influence of host genetics on gut microbiota composition in pigs
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Estellé, Jordi, Mach Casellas, Nuria, RAMAYO CALDAS, Yuliaxis, Levenez, Florence, Lemonnier, Gaetan, Denis, Catherine, Berri, El Mostafa, Mercat, Marie-José, Billon, Yvon, Dore, Joel, Larzul, Catherine, Lepage, Patricia, Rogel Gaillard, Claire, Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Université Paris Saclay (COmUE), MetaGenoPolis, Institut National de la Recherche Agronomique (INRA), Département Santé Animale (DEPT SA), Institut du Porc (IFIP), Génétique, Expérimentation et Système Innovants (GenESI), MICrobiologie de l'ALImentation au Service de la Santé (MICALIS), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées
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[SDV.GEN]Life Sciences [q-bio]/Genetics ,[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics ,[SDV]Life Sciences [q-bio] ,[INFO]Computer Science [cs] ,ComputingMilieux_MISCELLANEOUS - Abstract
International audience
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- 2018
31. Thermoregulation of piglets from two genetic lines divergent for residual feed intake
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SCHMITT, O., Billon, Yvon, Gilbert, Hélène, Bonnet, Agnes, Liaubet, Laurence, Scotland's Rural College (SRUC), University of Edinburgh, Teagasc Agriculture and Food Development Authority (Teagasc), Génétique, Expérimentation et Système Innovants (GenESI), Institut National de la Recherche Agronomique (INRA), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, and GISA SubPig
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pig ,genetic lines ,thermoregulation ,[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT] ,residual feed intake ,animal diseases ,feed efficiency ,piglet maturity - Abstract
International audience; Hypothermia is a factor of piglet neonatal mortality. This study used Infra-Red Thermography (IRT) to assess thermoregulation abilities of piglets from two lines divergent for residual feed intake (RFI). At birth, body weight and rectal temperature were recorded from piglets of the 11th generation of the low RFI (LRFI, more efficient; n=34) and the high RFI (HRFI, less efficient; n=28). IRT images were taken at 8, 15, 30 and 60 min post-partum. Temperatures of the ear base and tip, and minimum, maximum and average temperatures of the back (i.e. shoulders to rumps) were extracted with Thermacam Researcher Pro 2.0, and analysed with linear mixed models (SAS 9.4). All temperatures increased overtime. The rectal temperature of piglets at birth was correlated with the initial temperature of the ear base and the maximum back temperature (0.36 and 0.35, respectively, P
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- 2018
32. Divergent selection on adrenocortical activity modulates immune traits in pig
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Lieubeau, Blandine, Hervé, Julie, Haurogné, Karine, Bacou, Elodie, Allard, Marie, Billon, Yvon, Terenina, Elena, Bach, Jean-Marie, Mormède, Pierre, Immuno-Endocrinologie Cellulaire et Moléculaire (IECM), and Ecole Nationale Vétérinaire de Nantes-Université de Nantes (UN)-Institut National de la Recherche Agronomique (INRA)
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[SDV]Life Sciences [q-bio] ,ComputingMilieux_MISCELLANEOUS - Abstract
International audience
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- 2018
33. The effect of divergent selection on adrenocortical activity in Large White pigs on gene expression after ACTH, LPS and social stress challenges
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Terenina, Elena, Dugué, Claire, Kulikova, E., Bazovkina, Darya, Gress, Laure, Lefort, Gaëlle, Billon, Yvon, Larzul, Catherine, Mormède, Pierre, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Russian Academy of Sciences [Moscow] (RAS), Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), Institut National de la Recherche Agronomique (INRA), and Génétique, Expérimentation et Système Innovants (GenESI)
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pig ,[SDV.GEN]Life Sciences [q-bio]/Genetics ,[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics ,behavior ,[SDV]Life Sciences [q-bio] ,selection ,genetic ,[INFO]Computer Science [cs] ,[MATH]Mathematics [math] - Abstract
International audience; The effect of divergent selection on adrenocortical activity in Large White pigs on gene expression after ACTH, LPS and social stress challenges. E. Terenina1, C. Dugué1, E. Kulikova2, D. Bazovkina2, L. Gress1, G. Lefort1, Y. Billon3, C. Larzul1 & P. Mormede1 1 GenPhySE, INRA, INPT, ENSAT, Université de Toulouse, 31326 Castanet-Tolosan, France elena.mormede@inra.fr (Corresponding Author) 2 Department of Behavioral Neurogenomics, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia 3 GenESI, INRA, Le Magneraud, 17700 Surgères, France The objective of the present experiment is to analyze the expression of candidate genes related to HPA axis and stress in the third generation of selection of two lines of pigs divergently selected on the basis of plasma cortisol levels measured one hour after injection of ACTH. This test allows to objectify the activity level of the hypothalamic-pituitary-adrenal (HPA) axis, a major neuroendocrine system of the stress response. The kinetics of the blood transcriptomic responses to adrenocorticotropic hormone (ACTH), lipopolysaccharide (LPS) and social stress were measured at 4 time points (0, 1h, 4h, and 24h after the challenge). Our results suggest that the responses to these different challenges are not affected in the same way by HPA axis activity. We found 22 differentially expressed genes for the inflammatory stress, 2 genes specific to the response to ACTH injection and 12 genes for the social stress. The expression of studied candidate genes did not differ according to the line. Four genes (MEGF9, S100A9, CERS4 and PSAP) were found to be differentially expressed in the three tests and could therefore be used for the overall study of stress response. With the financial support of the Agence Nationale de la Recherche, program ANR BIOADAPT, project SUSoSTRESS (ANR-12-ADAP-0008).
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- 2018
34. Divergent selection on adrenocortical activity in Large White pigs: study of responses to breeding challenges
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Mormède, Pierre, Terenina, Elena, Billon, Yvon, Ferchaud, Stéphane, Gress, Laure, Rémignon, Hervé, Manse, Hélène, Larzul, Catherine, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Génétique, Expérimentation et Système Innovants (GenESI), and Institut National de la Recherche Agronomique (INRA)
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pig ,stress ,[SDV.GEN]Life Sciences [q-bio]/Genetics ,[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics ,[SDV]Life Sciences [q-bio] ,selection ,[INFO]Computer Science [cs] ,genetic - Abstract
International audience; This experiment had the objective to analyze responses to various breeding challenges in the third generation of selection of two lines of pigs genetically selected on the basis of plasma cortisol levels measured one hour after injection of ACTH. This test allows to objectify the activity level of the hypothalamic-pituitary-adrenal (HPA) axis, a major neuroendocrine system of the stress response. The results presented here show that the post-weaning growth rate was significantly lower in the high line, although the two lines had the same overall growth rate throughout their productive lives. The effects of a prolonged exposure to high temperature (30°C) and of group mixing stress prior to slaughter did not differ between the lines. These results show that the responses to different challenges are not affected in the same way by the HPA axis activity. These results, together with production data, will allow to evaluate the relevance of this criterion of selection to increase the robustness of animals. With the financial support of the Agence Nationale de la Recherche, program ANR BIOADAPT, project SUSoSTRESS (ANR-12-ADAP-0008). Keywords: genetic selection, cortisol, stress, robustness, heat stress, weaning stress, mixing stress, pig.
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- 2018
35. Effect of heat stress on faecal microbiota composition in swine: preliminary results
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Le Sciellour, Mathilde, Hochu, Isabelle, Zemb, Olivier, Riquet, Juliette, Gilbert, Hélène, Giorgi, Mario, Billon, Yvon, Gourdine, Jean-Luc, Renaudeau, David, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-École nationale supérieure agronomique de Toulouse (ENSAT), Université de Toulouse (UT)-Université de Toulouse (UT), Plateforme Tropicale d'Expérimentation sur l'Animal (PTEA), Institut National de la Recherche Agronomique (INRA), Génétique, Expérimentation et Système Innovants (GenESI), Unité de Recherches Zootechniques (URZ), ANR PIG_HEAT, European Project: 633531,H2020,H2020-SFS-2014-2,Feed-a-Gene(2015), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées
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pig ,heat stress ,[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT] ,fecal microbiota ,Autre (Sciences du Vivant) - Abstract
International audience; Gut microbiota plays a central role in health and nutrient digestion and would help the host for better coping with environmental perturbations. In tropical conditions or in temperate countries during Summer, elevated ambient temperatures can cause economic losses to the pig industry. During heat stress (HS), the reduction in voluntary feed intake is the main adaptation response for reducing heat production. This lower feed intake has subsequent negative effects on pig performance. The main purpose of this study was to investigate the relationships between HS and gut microbiota composition. A better understanding of the microbiota response to HS could allow the selection for animals well adapted to HS. Genetically related pigs were raised under temperate or tropical farm conditions with mean thermal humidity indexes respectively 23 and 25.5 from 11 to 23 weeks of age. In temperate conditions, pigs were submitted to a 3-week HS challenge at 30 °C. Faecal samples were collected in all pigs at 23 weeks of age in both environments (n=1,200 samples) and at 26 weeks of age in the temperate environment (n=600). Therefore, it was possible to compare microbiota from pigs raised in a temperate environment, a tropical climate, and exposed to HS. Microbiota extracted from pigs under temperate and tropical climate had different compositions whereas pigs exposed to heat challenge or raised in tropical conditions tended to share a common microbiota. HS challenge drastically modified gut microbiota and the groups before and after the challenge could be predicted in a multilevel sparse partial least square discriminant analysis with 30 OTUs and a mean classification error rate of 14%. Our experiment suggests that microbiota can be used as biomarkers of HS exposition.
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- 2018
36. Towards the quantitative characterisation of piglets’ robustness to weaning: a modelling approach
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Revilla Sanchez, Manuel, Friggens, Nicolas Charles, Broudiscou, Laurent, Lemonnier, Gaetan, Blanc, Fany, Ravon, Laure, Mercat, Marie-Jose, Billon, Yvon, Rogel-Gaillard, Claire, Le Floc'h, Nathalie, Estelle Fabrellas, Jordi, and Muñoz-Tamayo, Rafael
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robustesse des animaux ,sevrage ,modelling ,piglet ,precision farming ,resilience ,robustness ,weaning ,porcelet ,modélisation - Abstract
Weaning is a critical transition phase in swine production in which piglets must cope with different stressors that may affect their health. During this period, the prophylactic use of antibiotics is still frequent to limit piglet morbidity, which raises both economic and public health concerns such as the appearance of antimicrobial-resistant microbes. With the interest of developing tools for assisting health and management decisions around weaning, it is key to provide robustness indexes that inform on the animals capacity to endure the challenges associated to weaning. This work aimed at developing a modelling approach for facilitating the quantification of piglet resilience to weaning. We monitored 325 Large White pigs weaned at 28 days of age and further housed and fed conventionally during the post-weaning period without antibiotic administration. Body weight and diarrhoea scores were recorded before and after weaning, and blood was sampled at weaning and one week later for collecting haematological data. We constructed a dynamic model based on the Gompertz-Makeham law to describe live weight trajectories during the first 75 days after weaning following the rationale that the animal response is partitioned in two time windows (a perturbation and a recovery window). Model calibration was performed for each animal. Our results show that the transition time between the two time windows, as well as the weight trajectories are characteristic for each individual. The model captured the weight dynamics of animals at different degrees of perturbation, with an average coefficient of determination of 0.99, and a concordance correlation coefficient of 0.99. The utility of the model is that it provides biological parameters that inform on the amplitude and length of perturbation, and the rate of animal recovery. Our rationale is that the dynamics of weight inform on the capability of the animal to cope with the weaning disturbance. Indeed, there were significant correlations between model parameters and individual diarrhoea scores and haematological traits. Overall, the parameters of our model can be useful for constructing weaning robustness indexes by using exclusively the growth curves. We foresee that this modelling approach will provide a step forward in the quantitative characterization of robustness.
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- 2018
37. Integrated analysis of proteomic and transcriptomic data highlights late fetal muscle maturation process
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Voillet, Valentin, San Cristobal, Magali, Pere, Marie-Christine, Billon, Yvon, Canario, Laurianne, Liaubet, Laurence, Lefaucheur, Louis, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT], Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), UE 1372 Génétique, Expérimentation et Système Innovants, Institut National de la Recherche Agronomique (INRA)-Génétique animale (G.A.)-Physiologie Animale et Systèmes d'Elevage (PHASE), Institut National de la Recherche Agronomique (INRA)-Génétique, Expérimentation et Système Innovants (GenESI), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA), Génétique, Expérimentation et Système Innovants (GenESI), Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
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Animal biology ,muscle ,maturation ,Research ,Gene Expression Profiling ,transcriptomique ,[SDV.BA]Life Sciences [q-bio]/Animal biology ,Muscle Proteins ,swine ,Muscle Development ,caractérisation moléculaire ,Fetal Development ,Fetus ,proteomics ,Biologie animale ,fœtus amnion fetus yolk sac ,Animals ,fœtus ,protéomique ,porc ,métabolisme musculaire - Abstract
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.
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- 2018
38. Progeny-testing of full-sibs IBD in a SSC2 QTL region highlights epistatic interactions for fatness traits in pigs
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Iannuccelli Nathalie, Gilbert Hélène, Fève Katia, Sanchez Marie-Pierre, Tortereau Flavie, Billon Yvon, Milan Denis, Bidanel Jean-Pierre, and Riquet Juliette
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Genetics ,QH426-470 - Abstract
Abstract Background Many QTL have been detected in pigs, but very few of them have been fine-mapped up to the causal mutation. On SSC2, the IGF2-intron3-G3072A mutation has been described as the causative polymorphism for a QTL underlying muscle mass and backfat deposition, but further studies have demonstrated that at least one additional QTL should segregate downstream of this mutation. A marker-assisted backcrossing design was set up in order to confirm the segregation of this second locus, reduce its confidence interval and better understand its mode of segregation. Results Five recombinant full-sibs, with genotype G/G at the IGF2 mutation, were progeny-tested. Only two of them displayed significant QTL for fatness traits although four inherited the same paternal and maternal chromosomes, thus exhibiting the same haplotypic contrast in the QTL region. The hypothesis of an interaction with another region in the genome was proposed to explain these discrepancies and after a genome scan, four different regions were retained as potential interacting regions with the SSC2 QTL. A candidate interacting region on SSC13 was confirmed by the analysis of an F2 pedigree, and in the backcross pedigree one haplotype in this region was found to mask the SSC2 QTL effect. Conclusions Assuming the hypothesis of interactions with other chromosomal regions, the QTL could be unambiguously mapped to a 30 cM region delimited by recombination points. The marker-assisted backcrossing design was successfully used to confirm the segregation of a QTL on SSC2 and, because full-sibs that inherited the same alleles from their two parents were analysed, the detection of epistatic interactions could be performed between alleles and not between breeds as usually done with the traditional Line-Cross model. Additional analyses of other recombinant sires should provide more information to further improve the fine-mapping of this locus, and confirm or deny the interaction identified between chromosomes 2 and 13.
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- 2011
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39. A locally congenic backcross design in pig: a new regional fine QTL mapping approach miming congenic strains used in mouse
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Billon Yvon, Iannuccelli Nathalie, Sanchez Marie-Pierre, Servin Bertrand, Gilbert Hélène, Riquet Juliette, Bidanel Jean-Pierre, and Milan Denis
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Genetics ,QH426-470 - Abstract
Abstract Background In previous studies, a major QTL affecting fatness and growth has been mapped to pig chromosome 1q (SSC1q) using Large White - Meishan intercrosses. A higher fat depth and a larger growth rate have been reported for the allele of MS origin. Additionally the LW allele showed partial dominance effects over the MS allele for both traits. In order to refine the QTL mapping interval, advanced backcross generations were produced. Recombinant heterozygous sires were mated to LW sows in order to progeny test the sire segregation of the QTL and refine the QTL localisation. However due to the partial dominance of the LW allele, BC scheme using LW as the receiving population was not optimal. Results To overcome the difficulties related to the dominance of the LW QTL allele, a population of dams locally homozygous for the MS haplotype in the QTL region, but with an overall 29/32 LW genetic background, has been set up. Progeny testing results, using these receiver dams, were much more significant than those previously obtained with LW dams, and the SSC1 QTL interval was refined to 8 cM. Considering the results obtained, a powerful experimental design for farm animals is proposed, mimicking locally genetically identical strains used in mouse for QTL fine mapping. Conclusions We have further characterized the fatness QTL on pig chromosome 1 and refined its map position from a 30 cM interval to a 8 cM interval, using a locally congenic BC design. We have obtained highly significant results and overcome difficulties due to the dominance of the LW allele. This design will be used to produce additional, advanced BC families to further refine this QTL localization.
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- 2011
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40. Identification of QTL with effects on intramuscular fat content and fatty acid composition in a Duroc × Large White cross
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Legault Christian, Larzul Catherine, Gilbert Hélène, Gandemer Gilles, Billon Yvon, Bidanel Jean-Pierre, Basso Benjamin, Iannuccelli Nathalie, Sanchez Marie-Pierre, Riquet Juliette, Milan Denis, and Le Roy Pascale
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Genetics ,QH426-470 - Abstract
Abstract Background Improving pork quality can be done by increasing intramuscular fat (IMF) content. This trait is influenced by quantitative trait loci (QTL) sought out in different pig populations. Considering the high IMF content observed in the Duroc pig, it was appealing to determine whether favourable alleles at a major gene or QTL could be found. The detection was performed in an experimental F2 Duroc × Large White population first by segregation analysis, then by QTL mapping using additional molecular information. Results Segregation analysis provided evidence for a major gene, with a recessive Duroc allele increasing IMF by 1.8% in Duroc homozygous pigs. However, results depended on whether data were normalised or not. After Box-Cox transformation, likelihood ratio was indeed 12 times lower and no longer significant. The QTL detection results were partly consistent with the segregation analysis. Three QTL significant at the chromosome wide level were evidenced. Two QTL, located on chromosomes 13 and 15, showed a high IMF Duroc recessive allele with an overall effect slightly lower than that expected from segregation analysis (+0.4 g/100 g muscle). The third QTL was located on chromosome 1, with a dominant Large White allele inducing high IMF content (+0.5 g/100 g muscle). Additional QTL were detected for muscular fatty acid composition. Conclusion The study presented results from two complementary approaches, a segregation analysis and a QTL detection, to seek out genes involved in the higher IMF content observed in the Duroc population. Discrepancies between both methods might be partially explained by the existence of at least two QTL with similar characteristics located on two different chromosomes for which different boars were heterozygous. The favourable and dominant allele detected in the Large White population was unexpected. Obviously, in both populations, the favourable alleles inducing high IMF content were not fixed and improving IMF by fixing favourable alleles using markers can then be applied both in Duroc and LW populations. With QTL affecting fatty acid composition, combining an increase of IMF content enhancing monounsaturated fatty acid percentage would be of great interest.
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- 2007
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41. Responses of pigs divergently selected for cortisol response or feed efficiency to an ACTH challenge
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Gilbert, Hélène, Mormede, Elena, Louveau, Isabelle, Ruesche, Julien, Gress, Laure, Billon, Yvon, Mormède, Pierre, Larzul, Catherine, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT], Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), UE 1372 Génétique, Expérimentation et Système Innovants, Institut National de la Recherche Agronomique (INRA)-Génétique animale (G.A.)-Physiologie Animale et Systèmes d'Elevage (PHASE), Institut National de la Recherche Agronomique (INRA)-Génétique, Expérimentation et Système Innovants (GenESI), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Génétique, Expérimentation et Système Innovants (GenESI), and Institut National de la Recherche Agronomique (INRA)
- Subjects
endocrine system ,genetique ,[SDV]Life Sciences [q-bio] ,efficacité alimentaire ,Cortisol ,swine ,robustness ,robustesse ,hormones, hormone substitutes, and hormone antagonists ,porc - Abstract
Selection for feed efficiency can impair the animal’s ability to respond to stress. A key driver of this response is the hypothalamo-pituitary-adrenal (HPA) axis, which releases cortisol in response to stressors. Injection of a normalized dose of adrenocorticotropic hormone (ACTH) to stimulate cortisol release by the adrenal cortex is a standardized method to evaluate the activity of the HPA axis independently of the animal’s perception of stress. It has been used to select during three generations a highCortisol line and a lowCortisol line, that had divergent cortisol levels 1 h after ACTH injection (H1, peak of the response). A trial was set up to compare the responses to ACTH of these two lines and those of two other lines divergently selected for residual feed intake (RFI, measure of net feed efficiency) during nine generations. At 6 weeks of age, 48 pigs per line were tested. Blood samples were collected before and 1 (H1) and 4 h after injection (H4) when cortisol is expected to return to basal level. In the Cortisol lines, plasma cortisol was multiplied by 2 (P
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- 2017
42. Late Fetal Blood Transcriptomic Approach To Get Insight Into Biology Related To Birth Survival
- Author
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Liaubet, Laurence, Voillet, Valentin, Lippi, Yannick, Iannuccelli, Nathalie, Lascor, Christine, Billon, Yvon, San Cristobal, Magali, Canario, Laurianne, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Transcriptomic impact of Xenobiotics (E23 TRiX), ToxAlim (ToxAlim), Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Plateforme Génome & Transcriptome (GET), Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Génétique, Expérimentation et Système Innovants (GenESI), Institut National de la Recherche Agronomique (INRA), Dynamiques Forestières dans l'Espace Rural (DYNAFOR), Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National Polytechnique (Toulouse) (Toulouse INP), ANR-09-GENM-0005,PORCINET,Approche intégrée de la maturité des porcelets(2009), Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-Plateforme Génome & Transcriptome (GET), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ecole Nationale Vétérinaire de Toulouse - ENVT (FRANCE), Ecole d'Ingénieurs de Purpan - EIP (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Institut National de la Recherche Agronomique - INRA (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Institut National Polytechnique de Toulouse - INPT (FRANCE), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT], Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), UE 1372 Génétique, Expérimentation et Système Innovants, Institut National de la Recherche Agronomique (INRA)-Génétique animale (G.A.)-Physiologie Animale et Systèmes d'Elevage (PHASE), Institut National de la Recherche Agronomique (INRA)-Génétique, Expérimentation et Système Innovants (GenESI), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure Agronomique de Toulouse-Institut National Polytechnique (Toulouse) (Toulouse INP), and ANR-09-GENM-005 PORCINET
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pig ,Pig ,[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT] ,Blood ,Autre ,blood ,Fetal maturity ,microarray ,fetal maturity ,Microarray ,Génétique animale ,Autre (Sciences du Vivant) - Abstract
In recent decades, improvement of prolificacy and body composition has been accompanied by a substantial increase in the mortality of piglets before weaning. The most critical period is the perinatal period, mostly during the first 24-48 hours following birth. The maturity of piglets, defined as the state of full development for survival at birth, is an important determinant of early mortality. The objective of our project is to take advantage of current knowledge about two pig breeds, Large White (LW) pigs selected for prolificacy and body composition and Meishan (MS) pigs being more robust. Maturity of several tissues and metabolite profiles of various fluids are analyzed on the fetuses (LW, MS and reciprocal F1) at day 90 or 110 of gestation (birth at day 114). Here we presented the transcriptomic analysis done on total blood samples (N=63). We did two different statistical analyses, a supervised one to reveal differential pathways for the interaction between gestational stages and genotypes and an unsupervised analysis (hclust and differential analyses) to identify potential predictors of a lesser maturity at birth. All p-values were adjusted with a Bonferroni correction < 1%. The 265 genes differential for the interaction (Bonferroni 1%) in blood samples revealed many genes for mitochondrial ATP synthesis, transcriptional regulation, and response to hypoxia (overexpressed in LW at day 110 of gestation).
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- 2017
43. Genetic dissection of mechanisms underlying heat adaptation in pigs
- Author
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Riquet, Juliette, Gilbert, Hélène, Feve, Katia, Labrune, Yann, Rose, Roseline, Billon, Yvon, Giorgi, Mario, Loyau, Thomas, Gourdine, Jean-Luc, Renaudeau, David, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Unité de Recherches Zootechniques (URZ), Institut National de la Recherche Agronomique (INRA), Génétique, Expérimentation et Système Innovants (GenESI), Plateforme Tropicale d'Expérimentation sur l'Animal (PTEA), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), and ANR
- Subjects
[SDV.GEN]Life Sciences [q-bio]/Genetics ,[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics ,genotyping ,pigs and related specie ,[SDV]Life Sciences [q-bio] ,genome-wide asociation ,[INFO]Computer Science [cs] ,adaptation ,environment ,ComputingMilieux_MISCELLANEOUS - Abstract
International audience
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- 2017
44. Tropical heat stress in pigs : dissecting GxE
- Author
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Gilbert, Hélène, Renaudeau, David, Labrune, Yann, Feve, Katia, Rose, Roseline, Billon, Yvon, Giordi, Mario, Loyau, Thomas, Riquet, Juliette, Gourdine, Jean-Luc, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Unité de Recherches Zootechniques (URZ), Institut National de la Recherche Agronomique (INRA), Génétique, Expérimentation et Système Innovants (GenESI), Plateforme Tropicale d'Expérimentation sur l'Animal (PTEA), and ANR PIG_HEAT
- Subjects
pig ,heat stress ,[SDV.GEN]Life Sciences [q-bio]/Genetics ,[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics ,QTL ,[SDV]Life Sciences [q-bio] ,genetic parameters ,genetics ,[INFO]Computer Science [cs] ,ComputingMilieux_MISCELLANEOUS - Abstract
International audience
- Published
- 2017
45. An intestinal transcriptome analysis in fetal pigs reveals genes involved in glucose and lipid metabolism and immunity as valuable clues of maturity at birth
- Author
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Yao, Ying, Voillet, Valentin, Jégou, Maëva, San Cristobal, Magali, Dou, Samir, Rome, Véronique, Lippi, Yannick, Billon, Yvon, Pere, Marie-Christine, Boudry, Gaëlle, Gress, Laure, Iannuccelli, Nathalie, Mormède, Pierre, Quesnel, Helene, Canario, Laurianne, Liaubet, Laurence, Le Huërou-Luron, Isabelle, Nutrition, Métabolismes et Cancer (NuMeCan), Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Sichuan Agricultural University, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-École nationale supérieure agronomique de Toulouse (ENSAT), Université de Toulouse (UT)-Université de Toulouse (UT), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Transcriptomic impact of Xenobiotics (E23 TRiX), ToxAlim (ToxAlim), Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Ecole d'Ingénieurs de Purpan (INP - PURPAN), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Plateforme Génome & Transcriptome (GET), Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Génétique, Expérimentation et Système Innovants (GenESI), Institut National de la Recherche Agronomique (INRA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT], Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), UE 1372 Génétique, Expérimentation et Système Innovants, Institut National de la Recherche Agronomique (INRA)-Génétique animale (G.A.)-Physiologie Animale et Systèmes d'Elevage (PHASE), Institut National de la Recherche Agronomique (INRA)-Génétique, Expérimentation et Système Innovants (GenESI), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Plateforme Génome & Transcriptome (GET), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-Plateforme Génome & Transcriptome (GET), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)
- Subjects
Animal biology ,[SDV.BA]Life Sciences [q-bio]/Animal biology ,Biologie animale - Abstract
International audience; An intestinal transcriptome analysis in fetal pigs reveals genes involved in glucose and lipid metabolism and immunity as valuable clues of maturity at birth. 50. Annual Meeting of the European Society for Pediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN)
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- 2017
46. Dissecting G x E interactions for responses to tropical heat stress in pig breeding
- Author
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Gilbert, Hélène, Renaudeau, David, Labrune, Yann, Feve, Katia, Rose, Roseline, Billon, Yvon, Giorgi, Mario, Loyau, Thomas, Riquet, Juliette, Gourdine, Jean-Luc, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Unité de Recherches Zootechniques (URZ), Institut National de la Recherche Agronomique (INRA), Génétique, Expérimentation et Système Innovants (GenESI), Plateforme Tropicale d'Expérimentation sur l'Animal (PTEA), and ANR PIG_HEAT
- Subjects
pig ,heat stress ,[SDV.GEN]Life Sciences [q-bio]/Genetics ,[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics ,QTL ,[SDV]Life Sciences [q-bio] ,genetic parameters ,genetics ,[INFO]Computer Science [cs] ,ComputingMilieux_MISCELLANEOUS - Abstract
International audience
- Published
- 2017
47. Interactions between sire family and production environment (temperate vs. tropical) on performance and thermoregulation responses in growing pigs
- Author
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Rose, Roseline, Gilbert, Hélène, Loyau, Thomas, Giorgi, Mario, Billon, Yvon, Riquet, Juliette, Renaudeau, David, Gourdine, Jean-Luc, Unité de Recherches Zootechniques (URZ), Institut National de la Recherche Agronomique (INRA), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Plateforme Tropicale d'Expérimentation sur l'Animal (PTEA), Génétique, Expérimentation et Système Innovants (GenESI), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), and French National Agency of Research ANR-12-ADAP-0015 / Department of Animal Genetics of INRA AO2012
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Male ,thermoregulation ,[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT] ,Hot Temperature ,Swine ,Temperature ,Animal Genetics and Genomics ,tropical ,Humidity ,Environment ,Animal Feed ,heat stress ,growing pig ,Phenotype ,Animals ,environment interaction ,Female ,genetic ,Body Temperature Regulation ,temperate - Abstract
International audience; The aim of this study was to evaluate the effect of 2 climatic environments (temperate [TEMP] vs. tropical humid [TROP]) on production and thermoregulation traits in growing pigs. A backcross design involving Large White (LW; heat sensitive) and Creole (CR; heat tolerant) pigs was studied. The same 10 F-1 LW x CR boars were mated with related LW sows in each environment. A total of 1,298 backcross pigs (n = 634 pigs from 11 batches for the TEMP environment and n = 664 pigs from 12 batches for the TROP environment) were phenotyped on BW (every 15 d from wk 11 to 23 of age), voluntary feed intake (ADFI, from wk 11 to 23), backfat thickness (BFT; at wk 19 and 23), skin temperature (ST; at wk 19 and 23), and rectal temperature (RT; at wk 19, 21, and 23). The feed conversion ratio was computed for the whole test period (11 to 23 wk). The calculation of the temperature-humidity index showed an average difference of 2.4 degrees C between the TEMP and TROP environments. The ADG and ADFI were higher in the TEMP environment than in the TROP environment (834 vs. 754 g/d and 2.20 vs. 1.80 kg/d, respectively; P < 0.001). Body temperatures were higher in the TROP environment than in the TEMP environment (35.9 vs. 34.8 degrees C for ST and 39.5 vs. 39.3 degrees C for RT, respectively; P < 0.001). Most of the studied traits (i.e., BW, BFT, ADG, ADFI, and RT) were affected by sire family x environment interactions (P < 0.05), resulting in "robust" and "sensitive" families. Our results show a family dependency in the relationships between heat resistance and robustness, suggesting the possibility of finding genotypes with high production and low heat sensitivity. Further research is needed to confirm the genetic x environment interaction and to detect QTL related to heat tolerance.
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- 2017
48. Estimation of the effects of selection on French Large White sow and piglet performance during the suckling period
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Silalahi, Parsaoran, Tribout, Thierry, Billon, Yvon, Gogué, Jean-Marcel, Bidanel, Jean Pierre, Bogor Agricultural University - IPB (INDONESIA), Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Université Paris-Saclay, UE 1372 Génétique, Expérimentation et Système Innovants, Institut National de la Recherche Agronomique (INRA)-Génétique animale (G.A.)-Physiologie Animale et Systèmes d'Elevage (PHASE), Institut National de la Recherche Agronomique (INRA)-Génétique, Expérimentation et Système Innovants (GenESI), Domaine expérimental Bourges-La Sapinière (BOURGES), Institut National de la Recherche Agronomique (INRA), Action innovante du Ministère de l'Agriculture, and Génétique, Expérimentation et Système Innovants (GenESI)
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Male ,Swine ,Colostrum ,animal diseases ,[SDV]Life Sciences [q-bio] ,Stillbirth ,Animals, Suckling ,Eating ,Random Allocation ,Milk ,fluids and secretions ,Pregnancy ,Animals ,Birth Weight ,Female ,Semen Preservation - Abstract
Autre unité expérimentale impliquée : INRA, UE332 Domaine Expérimental de Bourges; The effects of 21 yr of selection were estimated for sow and piglet performance during the suckling period 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 fresh semen from 23 LW boars born in 1998 (EXP = L98). Seventy-four L77 and 89 L98 randomly chosen females were mated to 15 L77 and 15 L98, respectively, randomly chosen boars for 6 successive parities. They produced 2,796 L77 progeny (G77) and 3,529 L98 progeny (G98) piglets including stillbirths. To disentangle direct and maternal effects on piglet growth, a 2 × 2 factorial design was set by cross-fostering half-litters across genetic groups the day after farrowing, resulting in mixed G77/G98 litters nursed by either L77 or L98 sows. Piglet traits investigated included individual weight at birth (IWB), at 21 d of age (IW21d), and at weaning at 4 wk of age (IWW) and ADG from birth to 21 d of age (ADG21d) and from birth to weaning (ADGBW) as well as probability of stillbirth, probability of mortality on the first day after farrowing and from d 2 to weaning. Sow traits analyzed included weight before farrowing and at weaning, feed intake, milk production, colostrum, and milk composition. The variability of performance across genetic groups and litters was also investigated. The data were analyzed using generalized (piglet mortality) or linear mixed models (other traits). Results showed an increase in IWB (+240 ± 72 g in 21 yr for IWB adjusted for total number born), and a negative maternal genetic trend was observed on piglet growth during the suckling period (e.g., +33 ± 13 g/d in 21 yr for ADG21d, that is, 14% of the mean), whereas direct genetic effects remained unchanged. Piglets from L98 litters also had a 40% larger probability of being stillborn and a 28% larger probability of dying on d 1 and had a more heterogeneous IWB (358 vs. 336 g; P < 0.001) and growth during the suckling period (60 vs. 56 g/d; P < 0.001). Sows from L77 and L98 experimental groups did not differ in weight, feed intake, colostrum, and milk composition. These results give evidence of negative correlated effects of selection for piglet traits related to robustness. These adverse effects are at least partly of maternal origin.
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- 2017
49. Transcriptome profiling to predict piglet early development and vitality from umbilical cord blood
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Canario, Laurianne, Voillet, Valentin, Iannuccelli, Nathalie, Lippi, Yannick, Billon, Yvon, San Cristobal, Magali, Liaubet, Laurence, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT], ToxAlim (ToxAlim), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), UE 1372 Génétique, Expérimentation et Système Innovants, Institut National de la Recherche Agronomique (INRA)-Génétique animale (G.A.)-Physiologie Animale et Systèmes d'Elevage (PHASE), Institut National de la Recherche Agronomique (INRA)-Génétique, Expérimentation et Système Innovants (GenESI), ANR PORCINET - DGA PENELOPE, École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Transcriptomic impact of Xenobiotics (E23 TRiX), Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Plateforme Génome & Transcriptome (GET), Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Génétique, Expérimentation et Système Innovants (GenESI), Institut National de la Recherche Agronomique (INRA), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-Plateforme Génome & Transcriptome (GET), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
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animal diseases ,[SDV.BDD.MOR]Life Sciences [q-bio]/Development Biology/Morphogenesis - Abstract
The objective was to identify molecular predictors of piglet level of vitality and development at birth. The parental genetic influences on early-life traits were analyzed with comparison of purebred and crossbred piglets born in the same litter, from Meishan (MS) or Large White (LW) sows. We used mixed semen from the 2 breeds to inseminate first parity sows. Phenotypes included growth, body mass indexes and indicators of vitality, i.e., reactivity scores, with repeated measurements. The study included litters from 8 LW sows and 9 MS sows producing a total of 245 piglets. Blood samples were collected at birth from the umbilical cord in PAXgene Blood RNA Tube. Transcriptome analyses were carried out with the Agilent 60K microarray on 3 to 8 newborn piglets from each litter, resulting in a total of 21 LWLW, 19 MSLW, 22 LWMS and 19 MSMS samples. Statistical analyses were carried out with restricted maximum likelihood methodology, differential and discriminant analyses. Crossbred piglets from LW sows had a higher early growth than their purebred counterparts (P
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- 2016
50. Responses to weaning in two pig lines divergently selected on residual feed intake depending on diet
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Gilbert, Hélène, Ruesche, Julien, Muller, Nathalie, Billon, Yvon, Robert, F., ROGER, L., Montagne, Lucile, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT], Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), UE 1372 Génétique, Expérimentation et Système Innovants, Institut National de la Recherche Agronomique (INRA)-Génétique animale (G.A.)-Physiologie Animale et Systèmes d'Elevage (PHASE), Institut National de la Recherche Agronomique (INRA)-Génétique, Expérimentation et Système Innovants (GenESI), CCPA,Centrale Coopérative de Productions Animales (CCPA), European Project: 613574, Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-École nationale supérieure agronomique de Toulouse (ENSAT), Université de Toulouse (UT)-Université de Toulouse (UT), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Génétique, Expérimentation et Système Innovants (GenESI), Institut National de la Recherche Agronomique (INRA), Groupe CCPA, École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
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pig ,stress ,weaning ,[SDV]Life Sciences [q-bio] ,feed efficiency ,genetics - Abstract
Responses to weaning in two pig lines divergently selected on residual feed intake depending on diet. 67. Annual Meeting of the European Federation of Animal Science (EAAP)
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- 2016
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