Saint-Jean-de-Braye, France
Saint-Jean-de-Braye, France

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Cherel P.,Hendrix Genetics RTC | Herault F.,French National Institute for Agricultural Research | Vincent A.,French National Institute for Agricultural Research | Vincent A.,Agrocampus Ouest | And 3 more authors.
Journal of Animal Science | Year: 2012

A family structured population of 325 pigs (females and barrows) was produced as an intercross between 2 commercial sire lines and was subjected to a systematic transcriptome analysis of LM samples obtained shortly after slaughter. Additionally, measurements of meat quality traits of fresh and cooked loin were gathered from the same animals. The transcriptome analysis was achieved by microarray hybridization, using a custom repertoire of 15,000 6mer DNA probes targeting transcripts expressed in growing pig skeletal muscle. These data allowed us to estimate the heritability of expression abundance for each of the quantified RNA species. The abundance of 9,765 RNA was estimated as heritable with a false discovery rate of 5%, from which 1,174 were deemed as highly heritable (h2 > 0.50). We also observed a large number of transcripts whose LM expression abundance is genetically correlated with 4 meat quality traits: the loin pH measured at 45 min postmortem (pH45), 253 transcripts; the loin cooking loss (CL), 134 transcripts; the cooked loin shear force (SFc), 184 transcripts; and the loin color redness (a*) value, 190 transcripts. Heritable and meat quality genetically correlated transcripts showed an over-representation of biological processes involved in the induction of apoptosis (genetically correlated with CL), complement activation (genetically correlated with SFc), glucose metabolism (genetically correlated with a*), and cation channel activity (genetically correlated with pH45). Overall, the biological functions highlighted in the highly heritable transcripts and the lack of transcript that would be genetically correlated with LM glycolytic potential suggest that the genetic variability of the LM postmortem transcriptome is focused on muscle tissue response to postmortem ischemia and reflects more distantly the antemortem muscle physiology. Because of the contrasting distributions of the genetic correlations between LM RNA concentrations and the different meat quality traits studied, indirect selection strategies of meat quality traits based on measurements of selected LM RNA species could be only proposed for a subset of the analyzed meat characteristics (pH45, SFc, a*, CL). A substantial improvement in the efficiency of selection for these meat quality traits could result from measuring muscle RNA concentrations on selection candidates, if the same genetic parameters can be verified using in vivo-sampled muscles. © 2012 American Society of Animal Science. All rights reserved.


Liaubet L.,French National Institute for Agricultural Research | Lobjois V.,French National Institute for Agricultural Research | Faraut T.,French National Institute for Agricultural Research | Tircazes A.,French National Institute for Agricultural Research | And 8 more authors.
BMC Genomics | Year: 2011

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. © 2011 Liaubet et al; licensee BioMed Central Ltd.


Cherel P.,Hendrix Genetics RTC | Pires J.,Hendrix Genetics RTC | Glenisson J.,Hendrix Genetics RTC | Milan D.,French National Institute for Agricultural Research | And 7 more authors.
BMC Genetics | Year: 2011

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. © 2011 Cherel et al; licensee BioMed Central Ltd.


Villa-Vialaneix N.,French National Institute for Agricultural Research | Liaubet L.,French National Institute for Agricultural Research | Laurent T.,Toulouse 1 University Capitole | Cherel P.,Hendrix Genetics RTC | And 2 more authors.
PLoS ONE | Year: 2013

What are the commonalities between genes, whose expression level is partially controlled by eQTL, especially with regard to biological functions? Moreover, how are these genes related to a phenotype of interest? These issues are particularly difficult to address when the genome annotation is incomplete, as is the case for mammalian species. Moreover, the direct link between gene expression and a phenotype of interest may be weak, and thus difficult to handle. In this framework, the use of a co-expression network has proven useful: it is a robust approach for modeling a complex system of genetic regulations, and to infer knowledge for yet unknown genes. In this article, a case study was conducted with a mammalian species. It showed that the use of a co-expression network based on partial correlation, combined with a relevant clustering of nodes, leads to an enrichment of biological functions of around 83%. Moreover, the use of a spatial statistics approach allowed us to superimpose additional information related to a phenotype; this lead to highlighting specific genes or gene clusters that are related to the network structure and the phenotype. Three main results are worth noting: first, key genes were highlighted as a potential focus for forthcoming biological experiments; second, a set of biological functions, which support a list of genes under partial eQTL control, was set up by an overview of the global structure of the gene expression network; third, pH was found correlated with gene clusters, and then with related biological functions, as a result of a spatial analysis of the network topology. © 2013 Villa-Vialaneix et al.


PubMed | Hendrix Genetics RTC
Type: Journal Article | Journal: Journal of animal science | Year: 2012

A family structured population of 325 pigs (females and barrows) was produced as an intercross between 2 commercial sire lines and was subjected to a systematic transcriptome analysis of LM samples obtained shortly after slaughter. Additionally, measurements of meat quality traits of fresh and cooked loin were gathered from the same animals. The transcriptome analysis was achieved by microarray hybridization, using a custom repertoire of 15,000 6mer DNA probes targeting transcripts expressed in growing pig skeletal muscle. These data allowed us to estimate the heritability of expression abundance for each of the quantified RNA species. The abundance of 9,765 RNA was estimated as heritable with a false discovery rate of 5%, from which 1,174 were deemed as highly heritable (h(2) > 0.50). We also observed a large number of transcripts whose LM expression abundance is genetically correlated with 4 meat quality traits: the loin pH measured at 45 min postmortem (pH45), 253 transcripts; the loin cooking loss (CL), 134 transcripts; the cooked loin shear force (SFc), 184 transcripts; and the loin color redness (a*) value, 190 transcripts. Heritable and meat quality genetically correlated transcripts showed an over-representation of biological processes involved in the induction of apoptosis (genetically correlated with CL), complement activation (genetically correlated with SFc), glucose metabolism (genetically correlated with a*), and cation channel activity (genetically correlated with pH45). Overall, the biological functions highlighted in the highly heritable transcripts and the lack of transcript that would be genetically correlated with LM glycolytic potential suggest that the genetic variability of the LM postmortem transcriptome is focused on muscle tissue response to postmortem ischemia and reflects more distantly the antemortem muscle physiology. Because of the contrasting distributions of the genetic correlations between LM RNA concentrations and the different meat quality traits studied, indirect selection strategies of meat quality traits based on measurements of selected LM RNA species could be only proposed for a subset of the analyzed meat characteristics (pH45, SFc, a*, CL). A substantial improvement in the efficiency of selection for these meat quality traits could result from measuring muscle RNA concentrations on selection candidates, if the same genetic parameters can be verified using in vivo-sampled muscles.

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