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6. Primiparous sow behaviour on the day of farrowing as one of the primary contributors to the growth of piglets in early lactation.

Author

Girardie, Océane, Laloë, Denis, Bonneau, Mathieu, Billon, Yvon, Bailly, Jean, David, Ingrid, and Canario, Laurianne

Subjects
PIGLETS, LEAST squares, MULTIVARIATE analysis, SOWS, SWINE
Abstract

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

Published
2024
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7. Driving gut microbiota enterotypes through host genetics.

Author

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

Subjects
GENETICS, ENTEROTYPES, ANIMAL species, POLYSACCHARIDES, PEPTIDES, DATABASES
Abstract

Background: Population stratification based on interindividual variability in gut microbiota composition has revealed the existence of several ecotypes named enterotypes in humans and various animal species. Enterotypes are often associated with environmental factors including diet, but knowledge of the role of host genetics remains scarce. Moreover, enterotypes harbor functionalities likely associated with varying abilities and susceptibilities of their host. Previously, we showed that under controlled conditions, 60-day-old pig populations consistently split into two enterotypes with either Prevotella and Mitsuokella (PM enterotype) or Ruminococcus and Treponema (RT enterotype) as keystone taxa. Here, our aim was to rely on pig as a model to study the influence of host genetics to assemble enterotypes, and to provide clues on enterotype functional differences and their links with growth traits. Results: We established two pig lines contrasted for abundances of the genera pairs specifying each enterotype at 60 days of age and assessed them for fecal microbiota composition and growth throughout three consecutive generations. Response to selection across three generations revealed, per line, an increase in the prevalence of the selected enterotype and in the average relative abundances of directly and indirectly selected bacterial genera. The PM enterotype was found less diverse than the RT enterotype but more efficient for piglet growth during the post-weaning period. Shotgun metagenomics revealed differentially abundant bacterial species between the two enterotypes. By using the KEGG Orthology database, we show that functions related to starch degradation and polysaccharide metabolism are enriched in the PM enterotype, whereas functions related to general nucleoside transport and peptide/nickel transport are enriched in the RT enterotype. Our results also suggest that the PM and RT enterotypes might differ in the metabolism of valine, leucin, and isoleucine, favoring their biosynthesis and degradation, respectively. Conclusion: We experimentally demonstrated that enterotypes are functional ecosystems that can be selected as a whole by exerting pressure on the host genetics. We also highlight that holobionts should be considered as units of selection in breeding programs. These results pave the way for a holistic use of host genetics, microbiota diversity, and enterotype functionalities to understand holobiont shaping and adaptation. 4B2VhAArUR-Phf8Fa7EFRX Video Abstract [ABSTRACT FROM AUTHOR]

Published
2024
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8. Divergent selection for feed efficiency in pigs altered the duodenum transcriptomic response to feed intake and its DNA methylation profiles.

Author

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

Subjects
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]

Published
2024
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14. Sex and fetal genome influence gene expression in pig endometrium at the end of gestation.

Author

Bonnet, Agnes, Bluy, Lisa, Gress, Laure, Canario, Laurianne, Ravon, Laure, Sécula, Aurelie, Billon, Yvon, and Liaubet, Laurence

Abstract

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

Published
2024
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17. Driving gut microbiota enterotypes through host genetics

Author

Rogel-Gaillard, Claire, primary, Larzul, Catherine, additional, Estellé, Jordi, additional, Borey, Marion, additional, Blanc, Fany, additional, Lemonnier, Gaëtan, additional, Jardet, Deborah, additional, Lecardonnel, Jérôme, additional, Billon, Yvon, additional, Thiam, Mamadou-Gabou, additional, Oñate, Florian Plaza, additional, Quinquis, Benoit, additional, and Galleron, Nathalie, additional

Published
2023
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18. Driving gut microbiota enterotypes through host genetics

Author

Larzul, Catherine, primary, Estellé, Jordi, additional, Borey, Marion, additional, Blanc, Fany, additional, Lemonnier, Gaëtan, additional, Billon, Yvon, additional, Thiam, Mamadou-Gabou, additional, Quinquis, Benoit, additional, Galleron, Nathalie, additional, Jardet, Deborah, additional, Lecardonnel, Jérôme, additional, Oñate, Florian Plaza, additional, and Rogel-Gaillard, Claire, additional

Published
2023
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19. A methyl-seq tool to capture genomic imprinted loci

Author

Hubert Jean-Noël, Iannuccelli Nathalie, Cabau Cédric, Jacomet Eva, Billon Yvon, Serre Rémy-Felix, Vandecasteele Céline, Donnadieu Cécile, and Demars Julie

Abstract

Genomic imprinting represents an original model of epigenetic regulation resulting in a parent-of-origin expression. Despite the critical role of imprinted genes in mammalian growth, metabolism and neuronal function, there is no molecular tool specifically targeting them for a systematic evaluation. Here, we optimized and compared to bisulfite-based standard a novel methyl-seq system to capture 165 candidate regions for genomic imprinting and ultimately detect parent-of-origin methylation, the main hallmark of imprinting.

Published
2023

22. Stronger transcriptomic response to feed intake in the duodenum of pig with high feed efficiency from a divergent selection experiment

Author

Devailly, Guillaume, primary, Feve, Katia, additional, Saci, Safia, additional, Sarry, Julien, additional, Valiere, Sophie, additional, Lluch, Jerome, additional, Bouchez, Olivier, additional, Ravon, Laure, additional, Billon, Yvon, additional, Gilbert, Helene, additional, Beaumont, Martin, additional, and Demars, Julie, additional

Published
2022
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23. Plasma 1H-NMR metabolic and amino acid profiles of newborn piglets from two lines divergently selected for residual feed intake.

Author

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

Subjects
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]

Published
2023
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24. Transcriptomic and DNA methylation response to feed intake in the duodenum in high- and low- feed efficiency pig lines

Author

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

Subjects
[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.

Published
2022

27. Additional file 1 of Microbiability and microbiome-wide association analyses of feed efficiency and performance traits in pigs

Author

Aliakbari, Amir, Zemb, Olivier, Cauquil, Laurent, Barilly, Céline, Billon, Yvon, and Gilbert, Hélène

Abstract

Additional file 1: Figure S1. Average correlations between $${\widehat{\mathbf{m}}}_{\mathbf{p}}$$ m ^ p ( $$\widehat{\mathbf{m}}$$ m ^ using a partial dataset) and $${\widehat{\mathbf{m}}}_{\mathbf{w}}$$ m ^ w ( $$\widehat{\mathbf{m}}$$ m ^ using the whole dataset) for the CG design, and their SD as error bars. Figure S2. Average correlations between $${(\widehat{\mathbf{a}+\mathbf{m}})}_{\mathbf{p}}$$ ( a + m ^ ) p and $${(\widehat{\mathbf{a}+\mathbf{m}})}_{\mathbf{w}}$$ ( a + m ^ ) w for CG designs, and their SD as error bars. Figure S3. Results of microbiome wide association analyses using back solving of BLUP solutions between operational taxonomic units and residual feed intake (RFI), feed conversion ratio (FCR), daily feed intake (DFI), average daily gain (ADG) and back fat thickness (BFT).

Published
2022
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28. Heterologous hybridization using the human exome - a molecular tool to target and identify major genes

Author

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)

Subjects
[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.

Published
2021

29. Mise au point et validation d’un système embarqué pour mesurer l’activité posturale des truies

Author

Canario, Laurianne, Labrune, Yann, Bompa, Jean-François, Billon, Yvon, Ravon, Laure, Reignier, Sébastien, Bailly, Jean, RICARD, Edmond, 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)

Subjects
[SDV.BA.MVSA]Life Sciences [q-bio]/Animal biology/Veterinary medicine and animal Health, [SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

International audience

Published
2021

30. Response to selection on fecal microbiota composition in Large White piglets

Author

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

Subjects
[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

Published
2021

32. Genetic relationships between feed efficiency and gut microbiome in pig lines selected for residual feed intake

Author

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)

Subjects
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.

Published
2021

33. Additional file 6 of Identification of genomic regions affecting production traits in pigs divergently selected for feed efficiency

Author

Delpuech, Emilie, Aliakbari, Amir, Labrune, Yann, Fève, Katia, Billon, Yvon, Gilbert, Hélène, and Riquet, Juliette

Abstract

Additional file 6: Figure S3. Manhattan plots for GWAS of RFI trait in global, HRFI line or LRFI line populations. The plot shows the − log10(p-values) for all SNPs in the analysis against their genomic position. Changes in color represent different chromosomes. The dashed line represents the threshold for genome wide significance (threshold of -log10(p-value) = 4.5).

Published
2021
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34. Radars à ondes millimétriques pour l'enregistrement automatique de l'activité posturale des truies

Author

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)

Subjects
[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

Published
2020

35. Étude de la maturité des porcelets en fin de gestation par une approche métabolomique multifluide

Author

Lefort, Gaëlle, Vialaneix, Nathalie, Quesnel, Hélène, Pere, Marie-Christine, Billon, Yvon, Canario, Laurianne, Iannuccelli, Nathalie, Canlet, Cécile, Paris, Alain, Servien, Rémi, Liaubet, Laurence, Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), 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, 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), 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), MCAM, Muséum National d’Histoire Naturelle (MNHN), Centre National de la Recherche Scientifique (CNRS), Innovations Thérapeutiques et Résistances (InTheRes), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), ANR-16-CONV-0004, ANR-09-GENM005, Ecole Nationale Vétérinaire de Toulouse (ENVT), 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), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-INSTITUT AGRO 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 Expérimentale Elevages Porcins Innovants (GenESI), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Analyse de Xénobiotiques, Identification, Métabolisme (E20 Metatoul-AXIOM), 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-MetaToul-MetaboHUB, 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), Molécules de Communication et Adaptation des Micro-organismes (MCAM), Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS), 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 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)-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), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]

Subjects
nuclear magnetic resonance, gestation, métabolite, [SDV]Life Sciences [q-bio], metabolite, résonance magnétique nucléaire, sucking pig, génotype, porcelet, mortality, mortalité
Abstract

International audience; Selection for prolificacy and lean growth in swine has been associated with a substantial increase in piglet mortality. The first 24-48 hours after birth represent the most critical period. A major determinant for early survival is piglet maturity at birth, which relies strongly on maturation during the last month of gestation. The objective of the current study was to compare progeny from Large White and Meishan sows to describe the metabolic status of their fetuses. These two breeds differ in piglet survival. Thirty-nine sows were inseminated with mixed semen and anesthetized at 90 or 110 days after conception (mean gestation: 114 days). Their fetuses (mean = 15.7 per sow) were quickly removed by caesarean section, and this study focused on plasmatic, urinary and amniotic liquid metabolomes (1H-NMR) of 507-604 fetuses. Raw 1D Bruker spectral data files were treated with ASICS, an R package available on Bioconductor. ASICS allowed for direct identification and quantification of ca. 90 metabolites from a library of 190 metabolites, with 63-68 metabolites per fluid, of which 39 were common to the three fluids. Mixed models were applied to the quantification results to explain differences between gestational stages and fetal genotypes. A total of 55 metabolites for plasma, 37 for urine and 46 for amniotic liquid were found to be differential (FDR < 0.05). The results provide new insights into biological pathways involved in piglet maturation. In particular, we found large differences in metabolite concentrations between the two stages of gestation and betweenthe fetal genotypes for certain amino acids and sugars in plasma.; La sélection pour la prolificité chez le porc a été associée à une augmentation importante de la mortalité périnatale. Les premières 24-48 heures après la naissance représentent la période la plus critique. Un facteur déterminant pour la survie est la maturité à la naissance, très dépendante du développement foetal en fin de gestation.Notre objectif est ici de comparer le statut métabolique de porcelets descendant de Large White et Meishan qui sont deux races qui diffèrent en terme de survie et de vitalité néonatales. Trente-neuf truies ont été anesthésiées à 90 et 110 jours de gestation. Leurs foetus ont été extraits par césarienne et cette étude s'est concentrée sur les métabolomes plasmatique, urinaire et du liquide amniotique de 610 foetus. Les spectres de RMN 1H ont été analysés avec le package R ASICS qui permet d'identifier et de quantifier les métabolites présents dans un spectre. Environ 60 métabolites par fluide ont été identifiés et 39 sont communs aux trois métabolomes. Une analyse statistique multivariée et des modèles mixtes ont été réalisés pour identifier les différences significatives entre les stades gestationnels et les races. Les résultats permettent de mettre en évidence les voies métaboliques impliquées dans la maturité des porcelets : à 90 jours de gestation les métabolites nécessaires à la prolifération cellulaire sont plus abondants qu'à 110 jours où ce sont les métabolites impliqués dans le métabolisme énergétique qui sont les plus abondants. De plus, des métabolites associés à ces voies comme le myo-inositol ou le glucose, ont des concentrations significativement différentes entre les deux races ce qui tendrait à expliquer des différences de maturité.

Published
2020

36. Late fetal late development at thefeto-maternal interface: contribution of the fetal genome

Author

Bonnet, Agnès, Gress, Laure, Bluy, Lisa, Canario, Laurianne, Ravon, Laure, Billon, Yvon, Liaubet, Laurence, 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)

Subjects
[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], embryonic structures, genomique, endomètre, génétique, porc
Abstract

National audience; Piglet perinatal mortality is partly due to delayed maturation at the end of gestation. A fine balance of feto-maternal allocation of resources is necessary to support this process. Regulations result from interactions between maternal and fetal genes, maternal nutrition and the environment, as well as endometrial and placental functions. An experiment based on the use of mixed semen of two breeds with contrasting piglet maturity (i.e., Large White (LW) and Meishan (MS)) was performed. We investigated fetal genomeand sex influences on the expression of 41 imprinted genes from days 90-110 of gestation (D90-D110) at the level of the dam endometrium. Standardized relative expression data were quantified by qPCR and analyzed using linear mixed models (FDR

Published
2020

40. Discovery of Predictors of Mycoplasma hyopneumoniae Vaccine Response Efficiency in Pigs: 16S rRNA Gene Fecal Microbiota Analysis

Author

Munyaka, Peris M., primary, Blanc, Fany, additional, Estellé, Jordi, additional, Lemonnier, Gaëtan, additional, Leplat, Jean-Jacques, additional, Rossignol, Marie-Noëlle, additional, Jardet, Déborah, additional, Plastow, Graham, additional, Billon, Yvon, additional, Willing, Benjamin P., additional, and Rogel-Gaillard, Claire, additional

Published
2020
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41. The maturity in fetal pigs using a multi-fluid metabolomic approach

Author

Lefort, Gaëlle, primary, Servien, Rémi, additional, Quesnel, Hélène, additional, Billon, Yvon, additional, Canario, Laurianne, additional, Iannuccelli, Nathalie, additional, Canlet, Cécile, additional, Paris, Alain, additional, Vialaneix, Nathalie, additional, and Liaubet, Laurence, additional

Published
2020
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42. Development and validation of an embedded tool to measure postural activity of lactating sows

Author

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)

Subjects
[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.

Published
2019

43. Searching for markers of immunocompetence in blood: application to vaccination against Influenza A virus in pigs

Author

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)

Subjects
[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)

Published
2019

44. Thermoregulation of piglets from two genetic lines divergent for residual feed intake

Author

Schmitt , Océane, Reigner, Sébastien, Bailly, Jean, Ravon, Laure, Billon, Yvon, Gress, Laure, Bluy, Lisa, Gilbert, Hélène, Bonnet, Agnes, Liaubet, Laurence, 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 metaprogramme GISA SubPig

Subjects
[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], animal diseases, maturité, porcelet, thermorégulation, efficacité alimentaire, Autre (Sciences du Vivant)
Abstract

National 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). Birth phenotypes (e.g. body weight, rectal temperature, physical measures, vitality test) were recorded from piglets selected for low RFI (more efficient; LRFI; n=34) or high RFI (less efficient; HRFI; n=28). The 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. No difference in phenotypic data was detected between the two lines. All temperatures increased over time. 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 < 0.05). Overall, LRFI piglets, compared to HRFI piglets, had higher minimum (28.0 ± 0.2 °C vs 26.8 ± 0.2 °C, respectively, P < 0.001) and average (35.5 ± 0.2 °C vs 34.5 ± 0.1 °C, respectively, P < 0.001) back temperatures. Ear tip temperature decreased in HRFI piglets from 8 to 15 min post-partum, while it increased in LRFI piglets (-1.1 ± 0.4 °C vs 0.5 ± 0.5 °C, respectively, P < 0.05). In conclusion, IRT allowed non-invasive assessment of piglets’ thermoregulation abilities. Piglets selected for low RFI seemed to have better thermoregulation abilities at birth.

Published
2019

45. Additional file 2: of Effects of divergent selection upon adrenocortical activity on immune traits in pig

Author

HervÊ, Julie, Terenina, Elena, HaurognÊ, Karine, Bacou, Elodie, Kulikova, Elizaveta, Allard, Marie, Billon, Yvon, Bach, Jean-Marie, MormèDe, Pierre, and Lieubeau, Blandine

Abstract

Table S1. Variableâ s contributions to the first two dimensions of the PCA. Variables that contributed to more than 10% to one axis are underlined. (PDF 35 kb)

Published
2019
Full Text
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46. Towards the quantitative characterisation of piglets’ robustness to weaning: a modelling approach

Author

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)

Subjects
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.

Published
2019

47. Effect of chronic and acute heat challenges on fecal microbiota composition, production, and thermoregulation traits in growing pigs

Author

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)

Subjects
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.

Published
2019

48. Additional file 1: of Effects of divergent selection upon adrenocortical activity on immune traits in pig

Author

Hervé, Julie, Terenina, Elena, Haurogné, Karine, Bacou, Elodie, Kulikova, Elizaveta, Allard, Marie, Billon, Yvon, Bach, Jean-Marie, Mormède, Pierre, and Lieubeau, Blandine

Abstract

Figure S1. PCA variables’ correlogram. Correlations of each variable to the first two dimensions of the PCA are shown. CTL, CD8αhi cytotoxic T lymphocytes. (PDF 129 kb)

Published
2019
Full Text
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49. Genotype by environment interactions for performance and thermoregulation responses in growing pigs

Author

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

Subjects
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.

Published
2019

50. Immunome differences between porcine ileal and jejunal Peyer’s patches revealed by global transcriptome sequencing of gut-associated lymphoid tissues

Author

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

Subjects
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.

Published
2018

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