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1. Analysis of hybridization in French wild boar populations using genome-wide genotyping data

Author

Mary, Nicolas, Iannuccelli, Nathalie, Petit, Geoffrey, Bonnet, Nathalie, Pinton, Alain, Grosbois, Vladimir, Servin, Bertrand, Riquet, Juliette, and Ducos, Alain

Subjects
Quantitative Biology - Populations and Evolution
Abstract

The "genetic purity" of French wild boar populations has been monitored since the 1980s based on a cytogenetic difference between wild boars and domestic pigs (36 and 38 chromosomes, respectively). This difference makes it possible to identify any boar with 37 or 38 chromosomes as "hybrid", without however being able to determine the origin (recent or ancient) of the hybridization, nor guarantee the "purity" of an animal with 36 chromosomes. Analysis of results of more than 4,600 tests performed over the last 12 years reveals an average "hybrid" rate of 15.8%, with high variability between populations. To analyse hybridization in greater detail and overcome inherent limitations of the cytogenetic approach, 362 wild boars recently collected in different regions of France were genotyped on a 70K SNP (GeneSeek GGP Porcine HD) chip. This study showed that for 96.4% of the wild boars analysed, includingmost of those with 37 or 38 chromosomes, the percentage of the genome of "domestic pig" origin varied from 0 to 18%. This suggests that hybridization is a fairly common phenomenon but of moderate intensity, and often ancient. Nevertheless, higher rates of hybridization have been observed in some regions such as Ard{\`e}che, and several cases of recent hybridization with domestic pigs were found in 3.6% of the wild boars analysed, most of them with pigs of Asian origin., Comment: in French. Journ{\'e}es de la Recherche Porcine en France, 2021

Published
2021

7. 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

8. Genome‐wide analysis of hybridization in wild boar populations reveals adaptive introgression from domestic pig

Author

Mary, Nicolas, primary, Iannuccelli, Nathalie, additional, Petit, Geoffrey, additional, Bonnet, Nathalie, additional, Pinton, Alain, additional, Barasc, Harmonie, additional, Faure, Amélie, additional, Calgaro, Anne, additional, Grosbois, Vladimir, additional, Servin, Bertrand, additional, Ducos, Alain, additional, and Riquet, Juliette, additional

Published
2022
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10. 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

11. Detection of quantitative trait loci for reproduction and production traits in Large White and French Landrace pig populations (Open Access publication)

Author

Bidanel Jean-Pierre, Mercat Marie-José, Ronan Gueblez, Juliette Riquet, Gilbert Hélène, Druet Tom, Iannuccelli Nathalie, Tribout Thierry, Milan Denis, and Le Roy Pascale

Subjects
quantitative trait locus, pig, commercial population, production trait, reproduction trait, Animal culture, SF1-1100, Genetics, QH426-470
Abstract

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

Published
2008
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13. Detection of quantitative trait loci for carcass composition traits in pigs

Author

Renard Christine, Le Roy Pascale, Gruand Joseph, Amigues Yves, Riquet Juliette, Iannuccelli Nathalie, Bidanel Jean-Pierre, Milan Denis, and Chevalet Claude

Subjects
pig, gene mapping, quantitative trait locus, carcass composition, Animal culture, SF1-1100, Genetics, QH426-470
Abstract

Abstract A quantitative trait locus (QTL) analysis of carcass composition data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. A total of 488 F2 males issued from six F1 boars and 23 F1 sows, the progeny of six LW boars and six MS sows, were slaughtered at approximately 80 kg live weight and were submitted to a standardised cutting of the carcass. Fifteen traits, i.e. dressing percentage, loin, ham, shoulder, belly, backfat, leaf fat, feet and head weights, two backfat thickness and one muscle depth measurements, ham + loin and back + leaf fat percentages and estimated carcass lean content were analysed. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using a line-cross (LC) regression method where founder lines were assumed to be fixed for different QTL alleles and a half/full sib (HFS) maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Additional analyses were performed to search for multiple linked QTL and imprinting effects. Significant gene effects were evidenced for both leanness and fatness traits in the telomeric regions of SSC 1q and SSC 2p, on SSC 4, SSC 7 and SSC X. Additional significant QTL were identified for ham weight on SSC 5, for head weight on SSC 1 and SSC 7, for feet weight on SSC 7 and for dressing percentage on SSC X. LW alleles were associated with a higher lean content and a lower fat content of the carcass, except for the fatness trait on SSC 7. Suggestive evidence of linked QTL on SSC 7 and of imprinting effects on SSC 6, SSC 7, SSC 9 and SSC 17 were also obtained.

Published
2002
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14. Detection of quantitative trait loci for growth and fatness in pigs

Author

Gellin Joël, Renard Christine, Quintanilla Raquel, Lagant Hervé, Le Roy Pascale, Gruand Joseph, Caritez Jean-Claude, Boscher Marie-Yvonne, Bourgeois Florence, Amigues Yves, Iannuccelli Nathalie, Milan Denis, Bidanel Jean-Pierre, Ollivier Louis, and Chevalet Claude

Subjects
pig, gene mapping, quantitative trait locus, growth, fatness, Animal culture, SF1-1100, Genetics, QH426-470
Abstract

Abstract A quantitative trait locus (QTL) analysis of growth and fatness data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. Six boars and 23 F1 sows, the progeny of six LW boars and six MS sows, produced 530 F2 males and 573 F2 females. Nine growth traits, i.e. body weight at birth and at 3, 10, 13, 17 and 22 weeks of age, average daily gain from birth to 3 weeks, from 3 to 10 weeks and from 10 to 22 weeks of age, as well as backfat thickness at 13, 17 and 22 weeks of age and at 40 and 60 kg live weight were analysed. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using two interval mapping methods: a line-cross (LC) regression method where founder lines were assumed to be fixed for different QTL alleles and a half-/full-sib (HFS) maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Both methods revealed highly significant gene effects for growth on chromosomes 1, 4 and 7 and for backfat thickness on chromosomes 1, 4, 5, 7 and X, and significant gene effects on chromosome 6 for growth and backfat thickness. Suggestive QTLs were also revealed by both methods on chromosomes 2 and 3 for growth and 2 for backfat thickness. Significant gene effects were detected for growth on chromosomes 11, 13, 14, 16 and 18 and for backfat thickness on chromosome 8, 10, 13 and 14. LW alleles were associated with high growth rate and low backfat thickness, except for those of chromosome 7 and to a lesser extent early-growth alleles on chromosomes 1 and 2 and backfat thickness alleles on chromosome 6.

Published
2001
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15. Analyse de l'hybridation dans les populations françaises de sangliers à l'aide de données de génotypage pangénomique

Author

Mary, Nicolas, Iannuccelli, Nathalie, Petit, Geoffrey, Bonnet, Nathalie, Pinton, Alain, Grosbois, Vladimir, Servin, Bertrand, Riquet, Juliette, Ducos, Alain, Montpellier Cirad, Institut National de la Recherche Agronomique (INRA), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées

Subjects
[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics, FOS: Biological sciences, [SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE], Populations and Evolution (q-bio.PE), [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Quantitative Biology - Populations and Evolution
Abstract

The "genetic purity" of French wild boar populations has been monitored since the 1980s based on a cytogenetic difference between wild boars and domestic pigs (36 and 38 chromosomes, respectively). This difference makes it possible to identify any boar with 37 or 38 chromosomes as "hybrid", without however being able to determine the origin (recent or ancient) of the hybridization, nor guarantee the "purity" of an animal with 36 chromosomes. Analysis of results of more than 4,600 tests performed over the last 12 years reveals an average "hybrid" rate of 15.8%, with high variability between populations. To analyse hybridization in greater detail and overcome inherent limitations of the cytogenetic approach, 362 wild boars recently collected in different regions of France were genotyped on a 70K SNP (GeneSeek GGP Porcine HD) chip. This study showed that for 96.4% of the wild boars analysed, includingmost of those with 37 or 38 chromosomes, the percentage of the genome of "domestic pig" origin varied from 0 to 18%. This suggests that hybridization is a fairly common phenomenon but of moderate intensity, and often ancient. Nevertheless, higher rates of hybridization have been observed in some regions such as Ard{\`e}che, and several cases of recent hybridization with domestic pigs were found in 3.6% of the wild boars analysed, most of them with pigs of Asian origin., Comment: in French. Journ{\'e}es de la Recherche Porcine en France, 2021

Published
2021

16. Genetic diversity of eleven European pig breeds

Author

Foulley Jean-Louis, Geldermann Hermann, Beeckmann Petra, Jørgensen Claus B, Nissen Peter H, Andersson Leif, Giuffra Elisabetta, Groenen Martien AM, Milan Denis, Legault Christian, Iannuccelli Nathalie, Laval Guillaume, Chevalet Claude, and Ollivier Louis

Subjects
genetic diversity, molecular marker, conservation, pig, European breed, Animal culture, SF1-1100, Genetics, QH426-470
Abstract

Abstract A set of eleven pig breeds originating from six European countries, and including a small sample of wild pigs, was chosen for this study of genetic diversity. Diversity was evaluated on the basis of 18 microsatellite markers typed over a total of 483 DNA samples collected. Average breed heterozygosity varied from 0.35 to 0.60. Genotypic frequencies generally agreed with Hardy-Weinberg expectations, apart from the German Landrace and Schwäbisch-Hällisches breeds, which showed significantly reduced heterozygosity. Breed differentiation was significant as shown by the high among-breed fixation index (overall FST = 0.27), and confirmed by the clustering based on the genetic distances between individuals, which grouped essentially all individuals in 11 clusters corresponding to the 11 breeds. The genetic distances between breeds were first used to construct phylogenetic trees. The trees indicated that a genetic drift model might explain the divergence of the two German breeds, but no reliable phylogeny could be inferred among the remaining breeds. The same distances were also used to measure the global diversity of the set of breeds considered, and to evaluate the marginal loss of diversity attached to each breed. In that respect, the French Basque breed appeared to be the most "unique" in the set considered. This study, which remains to be extended to a larger set of European breeds, indicates that using genetic distances between breeds of farm animals in a classical taxonomic approach may not give clear resolution, but points to their usefulness in a prospective evaluation of diversity.

Published
2000
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17. 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

18. A Long Read project to find optimal technologic combinations for genome assembly and variability, epigenetic marks detection and metagenomic analysis

Author

Iampietro, Carole, Eché, Camille, Castinel, Adrien, Serre, Rémy-Félix, Klopp, Christophe, Denis, Erwan, Bouchez, Olivier, Kuchly, Claire, Vandecasteele, Céline, BROHA, Amandine, THERVILLE, Romain, Di Franco, Arnaud, Djebali Quelen, Sarah, DREAU, Andreea, Hoede, Claire, KOROVINA, Oleksandra, BIRBES, CLEMENT, Laborie, Didier, Mainguy, Jean, Noirot, Céline, Salin, Gerald, Terzian, Paul, Trotard, Marie-Stéphane, Boichard, Didier, Boussaha, Mekki, Grohs, Cécile, Charcosset, Alain, Belcram, Harry, Joets, Johann, Combes, Sylvie, Pascal, Géraldine, Pitel, Frederique, Leroux, Sophie, Riquet, Juliette, Demars, Julie, Tosser-Klopp, Gwenola, Vitte, Clémentine, Iannuccelli, Nathalie, Lluch, Jérôme, Lopez-Roques, Celine, Faraut, Thomas, Zytnicki, Matthias, Gaspin, Christine, Milan, Denis, Donnadieu, Cécile, 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), Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), 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), 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), Génétique Animale et Biologie Intégrative (GABI), Université Paris-Saclay-AgroParisTech-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Génétique Quantitative et Evolution - Le Moulon (Génétique Végétale) (GQE-Le Moulon), AgroParisTech-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), FEDER-Région Occitanie, 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), and AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
[SDV.GEN]Life Sciences [q-bio]/Genetics, [SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics, [SDV]Life Sciences [q-bio], [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [INFO]Computer Science [cs], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2020

19. 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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20. Study of fetal pig maturity in relation with neonatal survival using a multi-fluids metabolomic approach

Author

Lefort, Gaëlle, Vialaneix, Nathalie, Quesnel, Hélène, Pere, Marie-Christine, 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), 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, Analyse de Xénobiotiques, Identification, Métabolisme (E20 Metatoul-AXIOM), 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)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-MetaToul-MetaboHUB, 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-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), Innovations Thérapeutiques et Résistances (InTheRes), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), ANR-16-CONV-0004,DIGITAG,Institut Convergences en Agriculture Numérique(2016), ANR-09-GENM-0005,PORCINET,Approche intégrée de la maturité des porcelets(2009), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), 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-MetaToul-MetaboHUB, 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), 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)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
[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], [MATH]Mathematics [math]
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 strongly relies on the process of maturation during the last month of gestation. The objective of the current study was to compare progeny from Large White and Meishan pigs, which differ for piglet survival and vitality, to describe the metabolic status of the piglets. Thirty-nine sows were anesthetized at 90 or 110 days after conception (average gestation term: 114 days). Their fetuses (on average 15.7 per sow) were quickly obtained by caesarean section and this study focuses on the plasmatic, the urinary and the amniotic liquid metabolomes (1H-NMR) of 507 to 604 fetuses. Raw 1D Bruker spectral data files were treated with ASICS, an R package available on Bioconductor. ASICS allowed the direct identification and quantification of about 90 metabolites from a library of 190 metabolites, with about 60 metabolites per fluid, among which 39 were in common in the three fluids. A multivariate analysis and a mixed model were applied to the quantification results to explain the differences between the gestational stages and the breeds. The results provide new insights in the biological pathways involved in piglet maturation. Grants: ANR ANR-09-GENM005 (PORCINET) and ANR-16-CONV-0004 (#DigitAg), INRA (divisions GA, SA, MIA).

Published
2019

22. Corticosteroid Binding Globulin: A New Target for Cortisol-Driven Obesity

Author

Ousova, Olga, Guyonnet-Duperat, Véronique, Iannuccelli, Nathalie, Bidanel, Jean-Pierre, Milan, Denis, Genêt, Carine, Llamas, Bastien, Yerle, Martine, Gellin, Joël, Chardon, Patrick, Emptoz-Bonneton, Agnès, Pugeat, Michel, Mormède, Pierre, and Moisan, Marie-Pierre

Published
2004

23. High-resolution autosomal radiation hybrid maps of the pig genome and their contribution to the genome sequence assembly

Author

Servin Bertrand, Faraut Thomas, Iannuccelli Nathalie, Zelenika Diana, and Milan Denis

Subjects
Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background The release of the porcine genome sequence offers great perspectives for Pig genetics and genomics, and more generally will contribute to the understanding of mammalian genome biology and evolution. The process of producing a complete genome sequence of high quality, while facilitated by high-throughput sequencing technologies, remains a difficult task. The porcine genome was sequenced using a combination of a hierarchical shotgun strategy and data generated with whole genome shotgun. In addition to the BAC contig map used for the clone-by-clone approach, genomic mapping resources for the pig include two radiation hybrid (RH) panels at two different resolutions. These two panels have been used extensively for the physical mapping of pig genes and markers prior to the availability of the pig genome sequence. Results In order to contribute to the assembly of the pig genome, we genotyped the two radiation hybrid (RH) panels with a SNP array (the Illumina porcineSNP60 array) and produced high density physical RH maps for each pig autosome. We first present the methods developed to obtain high density RH maps with 38,379 SNPs from the SNP array genotyping. We then show how they were useful to identify problems in a draft of the pig genome assembly, and how the RH maps enabled the problems to be corrected in the porcine genome sequence. Finally, we used the RH maps to predict the position of 2,703 SNPs and 1,328 scaffolds currently unplaced on the porcine genome assembly. Conclusions A complete process, from genotyping of a high density SNP array on RH panels, to the construction of genome-wide high density RH maps, and finally their exploitation for validating and improving a genome assembly is presented here. The study includes the cross-validation of RH based findings with independent information from genetic data and comparative mapping with the Human genome. Several additional resources are also provided, in particular the predicted genomic location of currently unplaced SNPs and associated scaffolds summing up to a total of 72 megabases, that can be useful for the exploitation of the pig genome assembly.

Published
2012
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24. ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra

Author

Lefort, Gaëlle, primary, Liaubet, Laurence, additional, Canlet, Cécile, additional, Tardivel, Patrick, additional, Père, Marie-Christine, additional, Quesnel, Hélène, additional, Paris, Alain, additional, Iannuccelli, Nathalie, additional, Vialaneix, Nathalie, additional, and Servien, Rémi, additional

Published
2019
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25. Genetic variability of transcript abundance in pig peri-mortem skeletal muscle: eQTL localized genes involved in stress response, cell death, muscle disorders and metabolism

Author

Liaubet Laurence, Lobjois Valérie, Faraut Thomas, Tircazes Aurélie, Benne Francis, Iannuccelli Nathalie, Pires José, Glénisson Jérome, Robic Annie, Le Roy Pascale, SanCristobal Magali, and Cherel Pierre

Subjects
eQTL, muscle, transcriptome, genetical genomics, systems biology, pig, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background The genetics of transcript-level variation is an exciting field that has recently given rise to many studies. Genetical genomics studies have mainly focused on cell lines, blood cells or adipose tissues, from human clinical samples or mice inbred lines. Few eQTL studies have focused on animal tissues sampled from outbred populations to reflect natural genetic variation of gene expression levels in animals. In this work, we analyzed gene expression in a whole tissue, pig skeletal muscle sampled from individuals from a half sib F2 family shortly after slaughtering. Results QTL detection on transcriptome measurements was performed on a family structured population. The analysis identified 335 eQTLs affecting the expression of 272 transcripts. The ontologic annotation of these eQTLs revealed an over-representation of genes encoding proteins involved in processes that are expected to be induced during muscle development and metabolism, cell morphology, assembly and organization and also in stress response and apoptosis. A gene functional network approach was used to evidence existing biological relationships between all the genes whose expression levels are influenced by eQTLs. eQTLs localization revealed a significant clustered organization of about half the genes located on segments of chromosome 1, 2, 10, 13, 16, and 18. Finally, the combined expression and genetic approaches pointed to putative cis-drivers of gene expression programs in skeletal muscle as COQ4 (SSC1), LOC100513192 (SSC18) where both the gene transcription unit and the eQTL affecting its expression level were shown to be localized in the same genomic region. This suggests cis-causing genetic polymorphims affecting gene expression levels, with (e.g. COQ4) or without (e.g. LOC100513192) potential pleiotropic effects that affect the expression of other genes (cluster of trans-eQTLs). Conclusion Genetic analysis of transcription levels revealed dependence among molecular phenotypes as being affected by variation at the same loci. We observed the genetic variation of molecular phenotypes in a specific situation of cellular stress thus contributing to a better description of muscle physiologic response. In turn, this suggests that large amounts of genetic variation, mediated through transcriptional networks, can drive transient cell response phenotypes and contribute to organismal adaptative potential.

Published
2011
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26. Progeny-testing of full-sibs IBD in a SSC2 QTL region highlights epistatic interactions for fatness traits in pigs

Author

Iannuccelli Nathalie, Gilbert Hélène, Fève Katia, Sanchez Marie-Pierre, Tortereau Flavie, Billon Yvon, Milan Denis, Bidanel Jean-Pierre, and Riquet Juliette

Subjects
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.

Published
2011
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27. Joint analysis of quantitative trait loci and major-effect causative mutations affecting meat quality and carcass composition traits in pigs

Author

Iannuccelli Nathalie, Milan Denis, Glénisson Jérôme, Pires José, Cherel Pierre, Hérault Frédéric, Damon Marie, and Le Roy Pascale

Subjects
Genetics, QH426-470
Abstract

Abstract Background Detection of quantitative trait loci (QTLs) affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effects. We report on a microsatellite-based QTL detection scan including all autosomes for pig meat quality and carcass composition traits in an F2 population of 1,000 females and barrows resulting from an intercross between a Pietrain and a Large White-Hampshire-Duroc synthetic sire line. Our QTL detection design allowed side-by-side comparison of the RYR1 and PRKAG3 mutation effects seen as QTLs when segregating at low frequencies (0.03-0.08), with independent QTL effects detected from most of the same population, excluding any carrier of these mutations. Results Large QTL effects were detected in the absence of the RYR1 and PRKGA3 mutations, accounting for 12.7% of phenotypic variation in loin colour redness CIE-a* on SSC6 and 15% of phenotypic variation in glycolytic potential on SSC1. We detected 8 significant QTLs with effects on meat quality traits and 20 significant QTLs for carcass composition and growth traits under these conditions. In control analyses including mutation carriers, RYR1 and PRKAG3 mutations were detected as QTLs, from highly significant to suggestive, and explained 53% to 5% of the phenotypic variance according to the trait. Conclusions Our results suggest that part of muscle development and backfat thickness effects commonly attributed to the RYR1 mutation may be a consequence of linkage with independent QTLs affecting those traits. The proportion of variation explained by the most significant QTLs detected in this work is close to the influence of major-effect mutations on the least affected traits, but is one order of magnitude lower than effect on variance of traits primarily affected by these causative mutations. This suggests that uncovering physiological traits directly affected by genetic polymorphisms would be an appropriate approach for further characterization of QTLs.

Published
2011
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28. A locally congenic backcross design in pig: a new regional fine QTL mapping approach miming congenic strains used in mouse

Author

Billon Yvon, Iannuccelli Nathalie, Sanchez Marie-Pierre, Servin Bertrand, Gilbert Hélène, Riquet Juliette, Bidanel Jean-Pierre, and Milan Denis

Subjects
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.

Published
2011
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29. ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra

Author

Lefort, Gaëlle, primary, Liaubet, Laurence, additional, Canlet, Cécile, additional, Tardivel, Patrick, additional, Pére, Marie-Christine, additional, Quesnel, Hélène, additional, Paris, Alain, additional, Iannuccelli, Nathalie, additional, Vialaneix, Nathalie, additional, and Servien, Rémi, additional

Published
2018
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30. Recombinational landscape of porcine X chromosome and individual variation in female meiotic recombination associated with haplotypes of Chinese pigs

Author

Riquet Juliette, Guo Beili, Huang Weibing, Duan Yanyu, Iannuccelli Nathalie, Ma Junwu, Huang Lusheng, and Milan Denis

Subjects
Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background Variations in recombination fraction (θ) among chromosomal regions, individuals and families have been observed and have an important impact on quantitative trait loci (QTL) mapping studies. Such variations on porcine chromosome X (SSC-X) and on other mammalian chromosome X are rarely explored. The emerging assembly of pig sequence provides exact physical location of many markers, facilitating the study of a fine-scale recombination landscape of the pig genome by comparing a clone-based physical map to a genetic map. Using large offspring of F1 females from two large-scale resource populations (Large White ♂ × Chinese Meishan ♀, and White Duroc ♂ × Chinese Erhualian ♀), we were able to evaluate the heterogeneity in θ for a specific interval among individual F1 females. Results Alignments between the cytogenetic map, radiation hybrid (RH) map, genetic maps and clone map of SSC-X with the physical map of human chromosome X (HSA-X) are presented. The most likely order of 60 markers on SSC-X is inferred. The average recombination rate across SSC-X is of ~1.27 cM/Mb. However, almost no recombination occurred in a large region of ~31 Mb extending from the centromere to Xq21, whereas in the surrounding regions and in the Xq telomeric region a recombination rate of 2.8-3.3 cM/Mb was observed, more than twice the chromosome-wide average rate. Significant differences in θ among F1 females within each population were observed for several chromosomal intervals. The largest variation was observed in both populations in the interval UMNP71-SW1943, or more precisely in the subinterval UMNP891-UMNP93. The individual variation in θ over this subinterval was found associated with F1 females' maternal haplotypes (Chinese pig haplotypes) and independent of paternal haplotype (European pig haplotypes). The θ between UMNP891 and UMNP93 for haplotype 1122 and 4311 differed by more than fourteen-fold (10.3% vs. 0.7%). Conclusions This study reveals marked regional, individual and haplotype-specific differences in recombination rate on SSC-X. Lack of recombination in such a large region makes it impossible to narrow QTL interval using traditional fine-mapping approaches. The relationship between recombination variation and haplotype polymorphism is shown for the first time in pigs.

Published
2010
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33. Identification of QTL with effects on intramuscular fat content and fatty acid composition in a Duroc × Large White cross

Author

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

Subjects
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.

Published
2007
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34. Genetic diversity of eleven European pig breeds

Author

Laval, Guillaume, Iannuccelli, Nathalie, Legault, Christian, Milan, Denis, Groenen, Martien AM, Giuffra, Elisabetta, Andersson, Leif, Nissen, Peter H, Jørgensen, Claus B, Beeckmann, Petra, Geldermann, Hermann, Foulley, Jean-Louis, Chevalet, Claude, and Ollivier, Louis

Published
2000
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35. Late Fetal Blood Transcriptomic Approach To Get Insight Into Biology Related To Birth Survival

Author

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

Subjects
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).

Published
2017

36. 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

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)

Published
2017

37. ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra.

Author

Lefort, Gaëlle, Liaubet, Laurence, Canlet, Cécile, Tardivel, Patrick, Père, Marie-Christine, Quesnel, Hélène, Paris, Alain, Iannuccelli, Nathalie, Vialaneix, Nathalie, and Servien, Rémi

Subjects
NUCLEAR magnetic resonance spectroscopy, WORKFLOW, NUCLEAR magnetic resonance, METABOLITE analysis, AUTOMATIC identification, WORKFLOW management, STATISTICS
Abstract

Motivation In metabolomics, the detection of new biomarkers from Nuclear Magnetic Resonance (NMR) spectra is a promising approach. However, this analysis remains difficult due to the lack of a whole workflow that handles spectra pre-processing, automatic identification and quantification of metabolites and statistical analyses, in a reproducible way. Results We present ASICS, an R package that contains a complete workflow to analyse spectra from NMR experiments. It contains an automatic approach to identify and quantify metabolites in a complex mixture spectrum and uses the results of the quantification in untargeted and targeted statistical analyses. ASICS was shown to improve the precision of quantification in comparison to existing methods on two independent datasets. In addition, ASICS successfully recovered most metabolites that were found important to explain a two level condition describing the samples by a manual and expert analysis based on bucketing. It also found new relevant metabolites involved in metabolic pathways related to risk factors associated with the condition. Availability and implementation ASICS is distributed as an R package, available on Bioconductor. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Published
2019
Full Text
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39. Transcriptome profiling to predict piglet early development and vitality from umbilical cord blood

Author

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)

Subjects
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

Published
2016

40. Des approches multi-omiques pour caractériser la fin du développement foetal et mieux comprendre le déterminisme de la maturité à la naissance en lien avec la survie néonatale

Author

Liaubet , Laurence, Voillet , Valentin, Paris , Alain, Luron , Isabelle, Louveau , Isabelle, Gondret , Florence, Lefaucheur , Louis, Jégou , Maëva, Mormede , Elena, Yammine , Sami, Lippi , Yannick, Canlet , Cecile, Martin , Pascal, Lascor , Christine, Iannuccelli , Nathalie, Billon , Yvon, Canario , Laurianne, San Cristobal , Magali, 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), Nutrition, Métabolismes et Cancer (NuMeCan), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Toxicologie Alimentaire (UTA), Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB), Génétique, Expérimentation et Système Innovants (GenESI), Institut National de la Recherche Agronomique (INRA), ANR‐09‐GENM005 PORCINET, INRA, Région Midi‐Pyrénées., 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 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), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, 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 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), 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), ProdInra, Archive Ouverte, GenPhySE - UMR 1388 ( Génétique Physiologie et Systèmes d'Elevage ), Institut National de la Recherche Agronomique ( INRA ) -École nationale supérieure agronomique de Toulouse [ENSAT]-ENVT, UR 1341 Alimentation et adaptations digestives, nerveuses et comportementales, Institut National de la Recherche Agronomique ( INRA ) -Alimentation Humaine ( ALIM.H ) -Alimentation et adaptations digestives, nerveuses et comportementales ( ADNC ), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] ( PEGASE ), Institut National de la Recherche Agronomique ( INRA ) -AGROCAMPUS OUEST, Toxicologie Alimentaire ( UTA ), Institut National de la Recherche Agronomique ( INRA ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, and Institut National de la Recherche Agronomique ( INRA ) -Génétique animale ( G.A. ) -Physiologie Animale et Systèmes d'Elevage ( PHASE ) -Génétique, Expérimentation et Système Innovants ( GenESI )

Subjects
métabolome, [ SDV ] Life Sciences [q-bio], prédicteur, [SDV]Life Sciences [q-bio], haut débit, identification de gènes, [SDV] Life Sciences [q-bio], développement foetal, fœtus, porcelet, mécanisme biologique, protéome, transcriptome, porc
Abstract

Session : Génétique et qualitéSession : Génétique et qualité; National audience; Selection for high prolificacy and lean growth rate in swine has been associated with a substantial increase in piglet mortality. The first 24‐48 hours after birth represent a critical period for survival. A major determinant for early survival is piglet maturity at birth which relies greatly on the process of tissue maturation during the last month of gestation. The objective of this study was to compare the progenies from Large White (LW) and Meishan (MS) breeds which differ for piglet survival and neonatal mortality.This project proposes multi‐disciplinary and multi‐omic approaches to identify the molecular and genetic basis related to maturity and perinatal survival. The metabolome was analyzed on plasma, urine, and amniotic liquid on 612 fetuses: it displayed higher heterogeneity at the end of gestation. The transcriptome of adrenal glands, muscle, liver, subcutaneous adipose tissue, and small intestine and the proteome of muscle and adipose subcutaneous tissue were analyzed on 64 fetuses. The first analyses identified the biological processes involved in development and maturity, and key genes that may explain the differences observed between LW and MS.

Published
2014

41. A multi-tissue analysis in fetal pigs to identify genes involved in the determinism of maturity and survival at birth

Author

Liaubet, Laurence, Jégou, Maëva, Le Huërou-Luron, Isabelle, Lippi, Yannick, Yammine, Sami, Terenina, Elena, Louveau, Isabelle, Iannuccelli, Nathalie, Lascor, Christine, Billon, Yvon, Martin, Pascal, Quesnel, Helene, Canario, Laurianne, San Cristobal, Magali, Laboratoire de Génétique Cellulaire (LGC), 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, Alimentation Adaptations Digestives, Nerveuse et Comportementales (ADNC), Institut National de la Recherche Agronomique (INRA), 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), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Génétique, Expérimentation et Système Innovants (GenESI), PORCINET ANR09GENM005, 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), 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), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)

Subjects
[SDV]Life Sciences [q-bio], tissu adipeux, période neonatale, maturité, effet génétique, survie neonatale, meishan, porcelet, mortalité, large white, biomarqueur, ComputingMilieux_MISCELLANEOUS, expression des gènes, porc
Abstract

International audience

Published
2013

42. Mise en évidence de régions QTL sélectionnées dans une lignée synthétique sino-européenne

Author

Labrune, Yann, Gilbert, Hélène, Iannuccelli, Nathalie, Schwob, Sandrine, Delaunay, Isabelle, Bidanel, Jean Pierre, Bellec, Thierry, Riquet, Juliette, Laboratoire de Génétique Cellulaire (LGC), 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, Pôle génétique, Institut du Porc (IFIP), Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, ADN (ADN), Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), Institut du Porc, and AgroParisTech-Institut National de la Recherche Agronomique (INRA)

Subjects
[SDV]Life Sciences [q-bio]
Abstract

The French pig breeding organisation ADN has been developing since 2001 the Chinese European composite line Duochan (25% Meishan, 25% French Landrace, 50% Large White). In order to set up marker assisted selection in the Duochan line, molecular screening was conducted (1) to confirm the effects of QTL identified in the INRA PorQTL (MS x LW) experimental design and (2) to seek for additional chromosomal regions influencing production and reproduction traits included in the breeding goal. Firstly, two groups of 30 individuals, representing the line at its foundation and after two generations of selection, were genotyped using the pig 60K SNP chip to identify regions of the genome that have been affected by selection or drift. In a second step, a set of 384 SNPs tagging these candidate regions was established to test associations between markers and performances of 480 animals born between 2003 and 2006. Each selected animal had a CD (coefficient of determination) greater than 0.25 for a global breeding value combining growth, carcass and reproduction traits). QTLs (Quantitative Trait Loci) were detected in 16 different chromosomal regions. Some of these regions simultaneously affected production and reproduction traits. These results indicated that a marker assisted selection scheme can be proposed for the Duochan selection.

Published
2013

43. Positional cloning of genes involved in major congenital diseases in pig

Author

Rousseau, Sarah, Servin, Bertrand, Iannuccelli, Nathalie, Pailhoux, Eric, Riquet, Juliette, 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, Biologie du développement et reproduction (BDR), Centre National de la Recherche Scientifique (CNRS)-École nationale vétérinaire d'Alfort (ENVA)-Institut National de la Recherche Agronomique (INRA), Plant & Animal Genome. USA., and ProdInra, Migration

Subjects
[SDV.BDD] Life Sciences [q-bio]/Development Biology, [SDV.BDLR]Life Sciences [q-bio]/Reproductive Biology, [SDV.BDD]Life Sciences [q-bio]/Development Biology, [SDV.BDLR] Life Sciences [q-bio]/Reproductive Biology, pig, association study, intersexuality, scrotal hernia
Abstract

International audience; Congenital diseases are defined as a physical defect or a health problem that is present at birth. Despite a quite low incidence of these diseases (1-3%), these defects are a significant problem in the pig industry and lead to severe economic loss and poor animal welfare. The most important congenital defects that occur in piglets are urogenital, including testicular migration defects (scrotal or inguinal hernias, cryptorchidism) and gonadal differentiation anomalies (intersexuality). Beside sanitary and environmental factors, frequencies of disorders are known to be influenced by genetic components. The aim of this work, developed in the frame of the SwAn project, is the identification of genes underlining congenital hereditary disorders in pigs for further marker assisted selection against genetic defects. SwAn is a collaborative project with the French private pig breeding companies, the French pig institute (IFIP), and INRA (National Institute of Agronomic Research). A collection of 1800 samples of affected piglets, and their two non-affected parents was established with the French pig breeders. A genome-wide association study (GWAS) with a SNP panel comprising 60 000 markers (Illumina©) and covering the entire genome was performed. Results obtained for intersexuality, scroto-inguinal hernia and cryptorchidism will be presented. The overall expected impact of SwAn is to improve the sustainability of pork production as well as pig health and welfare. Moreover, identification of causative genes in pigs would be relevant for similar diseases in humans and other mammalian species.

Published
2013

44. Cartographie fine de régions QTL à l’aide de la puce Porcine SNP60 pour l’ingestion, la croissance, la composition de la carcasse et la qualité de la viande en race Large White

Author

Sanchez, Marie Pierre, Tribout, Thierry, Iannuccelli, Nathalie, Bouffaud, Marcel, Servin, Bertrand, Dehais, Patrice, Muller, Nelly, Mercat , Marie‐José, Estelle Fabrellas, Jordi, Bidanel, Jean Pierre, Gaillard, Claire, Milan, Denis, Gilbert, Hélène, Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Laboratoire de Génétique Cellulaire (LGC), 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-Institut National de la Recherche Agronomique (INRA), UE 0450 Unité Expérimentale de Testage de Porcs, Institut National de la Recherche Agronomique (INRA)-Génétique animale (G.A.)-Unité Expérimentale de Testage de Porcs (UETP), Pôle génétique, Institut du Porc, ANR Delisus, ANR Immopig, AgroParisTech-Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Unité expérimentale de testage de porcs, Institut National de la Recherche Agronomique (INRA), and Institut du Porc (IFIP)

Subjects
cartographie fine, qtl, composition de la carcasse, [SDV]Life Sciences [q-bio], race porcine large white, croissance animale, qualité de la viande, ingestion alimentaire
Abstract

Près de 500 porcs Large White (106 familles de pères) ont été génotypés pour la puce PorcineSNP60 et contrôlés pour 21 caractères d’ingestion, de croissance, de composition de carcasse et de qualité de la viande. Sur les 64432 marqueurs SNP (Single Nucleotide Polymorphism) de la puce, 44412 ont passé le contrôle qualité et ont donc été utilisés pour des analyses d’association avec la méthode FASTA (estimation conjointe des effets individuels des SNP et de l’effet polygénique). Au total, 45 régions avec des effets significatifs (P, About 500 Large White pigs (106 sire families) were genotyped using the PorcineSNP60 Beadchip and controlled for feed intake, growth, carcass composition and meat quality. Of the 64,432 SNP (Single Nucleotide Polymorphism) of the chip, 44,412 passed the quality control and were thus used for genome‐wide association analyses (GWAS) with the FASTA method (individual effects of SNP and polygenic effect are estimated jointly). A total of 45 regions with significant effects (P < 10‐4) have been identified for SNP distributed on all chromosomes (SSC) except on SSC5 and SSC12. In 18 of these regions (from 7 to 1,251kb), several SNP had significant effects on growth and feed intake (3 regions), on carcass composition traits (10 regions) and meat quality traits (5 regions). Eight of these regions had never been described before. The region which had the greatest number of significant effects (a region of 183kb on SSC1 for meat quality) was submitted to haplotype analyses. Three haplotypes of 6 SNP were found in the studied Large White population, they had significant effects on all meat quality traits included in the analyses. These results show that GWAS analyses with the PorcineSNP60 Beadchip allow QTL to be mapped with a good accuracy. Therefore considering the selection of the favorable alleles (or haplotypes) and also analysing the genetic architecture of complex traits can now be envisaged in commercial pig populations.

Published
2012

45. Microsatellite mapping of quantitative trait loci affecting female reproductive tract characteristics in Meishan x Large White F2 pigs

Author

Rosendo, Adalberto, Iannuccelli, Nathalie, Gilbert, Hélène, Riquet, Juliette, Billon, Yvon, AMIGUES, YVES, Milan, Denis, Bidanel, Jean Pierre, Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Laboratoire de Génétique Cellulaire (LGC), 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-Institut National de la Recherche Agronomique (INRA), Génétique Expérimentale en Productions Animales (GEPA), Institut National de la Recherche Agronomique (INRA), Laboratoire d'Analyse Génétique pour les Espèces Animales (LABOGENA), The experimental program was funded by the European Union (Bridge and Biotech+ programs), INRA (Department of Animal Genetics and AIP 'Structure des génomes animaux'), and the 'Groupement de recherches et études sur les génomes'., Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, and AgroParisTech-Institut National de la Recherche Agronomique (INRA)

Subjects
pig, gene mapping, quantitative trait loci, reproductive tract, [SDV.SA.SPA]Life Sciences [q-bio]/Agricultural sciences/Animal production studies, Science des productions animales, Animal production studies
Abstract

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

Published
2012

46. A fine genetic analysis of congenital diseases in pig

Author

Rousseau, Sarah, Iannuccelli, Nathalie, Pailhoux, Eric, Servin, Bertrand, Riquet, Juliette, Laboratoire de Génétique Cellulaire (LGC), 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, Biologie du développement et reproduction (BDR), and Centre National de la Recherche Scientifique (CNRS)-École nationale vétérinaire d'Alfort (ENVA)-Institut National de la Recherche Agronomique (INRA)

Subjects
[SDV]Life Sciences [q-bio], trouble génétique, [INFO]Computer Science [cs], porcin, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2012

47. Molecular characterization of the porcine TEAD3 (TEF-5) gene: examination of a promoter mutation as the causal mutation of a quantitative trait loci affecting the androstenone level in boar fat

Author

Robic, Annie, Larzul, Catherine, Grindflek, E., Chevillon, P., Hofer, A., Feve, Katia, Iannuccelli, Nathalie, Milan, Denis, Prunier, Armelle, Riquet, Juliette, Laboratoire de Génétique Cellulaire (LGC), 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 Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Systèmes d'Elevage, Nutrition Animale et Humaine (SENAH), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure Agronomique de Rennes, Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), and Ecole Nationale Supérieure Agronomique de Rennes-Institut National de la Recherche Agronomique (INRA)

Subjects
pig, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, boar taint, qtl, mutation
Abstract

Chantier qualité GA; A quantitative trait loci (QTL) for accumulation of androstenone in fat has been identified in an Large White × Meishan cross in a region of SSC7-containing TEAD3. In humans, TEAD3 is a transcription activator, known to be able to regulate the transcription of HSD3B. This enzyme is involved in the degradation of androstenone in the liver. In this study, porcine transcripts of TEAD3 were characterized and compared with mammalian transcripts. The complete structure of porcine TEAD3 gene was characterized including two 5′ non-coding exons and one exon 5 not used in porcine transcripts. Variations were screened in sequences related to TEAD3: in exons, in flanking sequences of exons and in the promoter region. A SNP characterized at 726 bp at 5′ of the first exon was tested on several pig populations without coherent and convincing results concerning its association with androstenone levels. We showed that in the liver of adult boars, the transcripts levels of TEAD3 and HSD3B were correlated. As in humans, it is possible that HSD3B is a target gene of TEAD3 in porcine liver. Nevertheless, no expression variation was observed for TEAD3 or HSD3B in liver between animals with different genotypes at the SNP. We concluded that this SNP was not the causal mutation of this QTL.

Published
2012

48. Microsatellite mapping of quantitative trait loci affecting meat quality, stress hormones and production traits in Duroc3Large White F2 pigs

Author

Sanchez, Marie Pierre, Iannuccelli, Nathalie, Basso, Benjamin, Foury, Aline, Billon, Yvon, Gandemer, Gilles, Gilbert, Hélène, Mormède, Pierre, Bidanel, Jean Pierre, Larzul, Catherine, Riquet, Juliette, Milan, Denis, Le Roy, Pascale, Génétique Animale et Biologie Intégrative (GABI), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Laboratoire de Génétique Cellulaire (LGC), 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-Institut National de la Recherche Agronomique (INRA), Unité de Psychoneuroimmunologie, Nutrition et Génétique (PsyNuGen), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA)-Université Bordeaux Segalen - Bordeaux 2, Génétique Expérimentale en Productions Animales (GEPA), Institut National de la Recherche Agronomique (INRA), Services généraux de centre, Génétique Animale (GARen), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST-Ecole Nationale Supérieure Agronomique de Rennes-IFR140, Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS), Services déconcentrés d'appui à la recherche Nouvelle-Aquitaine-Bordeaux (SDAR Nouvelle-Aquitaine-Bordeaux), 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)-Ecole Nationale Supérieure Agronomique de Rennes, and IFR140-Ecole Nationale Supérieure Agronomique de Rennes-AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA)

Subjects
pig, qtl, meat quality, production, stress hormone, [SDV.SA.SPA]Life Sciences [q-bio]/Agricultural sciences/Animal production studies, food and beverages, Science des productions animales, Animal production studies
Abstract

An F2 cross between Duroc and Large White pigs was carried out in order to detect quantitative trait loci (QTL) for 11 meat quality traits (L*, a* and b* Minolta coordinates and water-holding capacity (WHC) of two ham muscles, ultimate pH of two ham and one loin muscles), 13 production traits (birth weight, average daily gain during post-weaning and fattening periods, carcass fat depths at three locations, estimated lean meat content, carcass length and weights of five carcass cuts) and three stress hormone-level traits (cortisol, adrenaline and noradrenaline). Animals from the three generations of the experimental design (including 456 F2 pigs) were genotyped for 91 microsatellite markers covering all the autosomes. A total of 56 QTL were detected: 49 reached the chromosome-wide level (suggestive QTL with a maximal probability of 0.05) and seven were significant at the genome-wide level (with a probability varying from 631024 to 331023). Twenty suggestive QTL were identified for ultimate pH, colour measurements and WHC on chromosome (SSC) 5, 6, 7, 8, 9, 11, 13, 14, 15 and 17. For production traits, 33 QTL were detected on all autosomes except SSC6, 8 and 9. Seven of these QTL, located on SSC2, 3, 10, 13, 16 and 17, exceeded the genome-wide significance threshold. Finally, three QTL were identified for levels of stress hormones: a QTL for cortisol level on SSC7 in the cortisol-binding globulin gene region, a QTL for adrenaline level on SSC10 and a QTL for noradrenaline level on SSC13. Among all the detected QTL, seven are described for the first time: a QTL for ultimate pH measurement on SSC5, two QTL affecting birth weight on SSC2 and 10, two QTL for growth rate on SSC15 (during fattening) and 17 (during post-weaning) and two QTL affecting the adrenaline and noradrenaline levels. For each QTL, only one to five of the six F1 sires were found to be heterozygous. It means that all QTL are segregating in at least one of the founder populations used in this study. These results suggest that both meat quality and production traits can be improved in purebred Duroc and Large White pigs through markerassisted selection. It is of particular interest for meat quality traits, which are difficult to include in classical selection programmes.

Published
2011

49. SwAn, anomalies congénitales chez le porc : cartographie génétique fine des gènes sous-jacents

Author

Riquet, Juliette, Mercat, Marie-José, Iannuccelli, Nathalie, Servin, Bertrand, Pailhoux, Eric, Larzul, Catherine, Pôle génétique, Institut du Porc, Laboratoire de Génétique Cellulaire (LGC), 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-Institut National de la Recherche Agronomique (INRA), Biologie du Développement et Reproduction (BDR), Institut National de la Recherche Agronomique (INRA), Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, ANR, Institut du Porc (IFIP), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Biologie du développement et reproduction (BDR), and Centre National de la Recherche Scientifique (CNRS)-École nationale vétérinaire d'Alfort (ENVA)-Institut National de la Recherche Agronomique (INRA)

Subjects
[SDV]Life Sciences [q-bio]
Abstract

absent

Published
2010

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