Multi-tissue metabolic and transcriptomic responses to a short-term heat stress in swine.

BACKGROUND: Heat stress (HS) is an increasing threat for pig production with a wide range of impacts. When submitted to high temperatures, pigs will use a variety of strategies to alleviate the effect of HS. While systemic adaptations are well known, tissue-specific changes remain poorly understood. In this study, thirty-two pigs were submitted to a 5-day HS at 32 °C. RESULTS: Transcriptomic and metabolomic analyses were performed on several tissues. The results revealed differentially expressed genes and metabolites in different tissues. Specifically, 481, 1774, 71, 1572, 17, 164, and 169 genes were differentially expressed in muscle, adipose tissue, liver, blood, thyroid, pituitary, and adrenal glands, respectively. Regulatory glands (pituitary, thyroid, and adrenal) had a lower number of regulated genes, perhaps indicating an earlier sensitivity to HS. In addition, 7, 8, 2, and 8 metabolites were differentially produced in muscle, liver, plasma, and urine, respectively. The study also focused on the oxidative stress pathway in muscle and liver by performing a correlation analysis between genes and metabolites. CONCLUSIONS: This study has identified various adaptation mechanisms in swine that enable them to cope with heat stress (HS). These mechanisms include a global decrease in energetic metabolism, as well as changes in metabolic precursors that are linked with protein and lipid catabolism and anabolism. Notably, the adaptation mechanisms differ significantly between regulatory (pituitary, thyroid and adrenal glands) and effector tissues (muscle, adipose tissue, liver and blood). Our findings provide new insights into the comprehension of HS adaptation mechanisms in swine.

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

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

Asterics: a simple tool for the ExploRation and Integration of omiCS data.

BACKGROUND: The rapid development of omics acquisition techniques has induced the production of a large volume of heterogeneous and multi-level omics datasets, which require specific and sometimes complex analyses to obtain relevant biological information. Here, we present ASTERICS (version 2.5), a publicly available web interface for the analyses of omics datasets. RESULTS: ASTERICS is designed to make both standard and complex exploratory and integration analysis workflows easily available to biologists and to provide high quality interactive plots. Special care has been taken to provide a comprehensive documentation of the implemented analyses and to guide users toward sound analysis choices regarding some specific omics data. Data and analyses are organized in a comprehensive graphical workflow within ASTERICS workspace to facilitate the understanding of successive data editions and analyses leading to a given result. CONCLUSION: ASTERICS provides an easy to use platform for omics data exploration and integration. The modular organization of its open source code makes it easy to incorporate new workflows and analyses by external contributors. ASTERICS is available at https://asterics.miat.inrae.fr and can also be deployed using provided docker images.

Whole-genome sequencing of cryopreserved resources from French Large White pigs at two distinct sampling times reveals strong signatures of convergent and divergent selection between the dam and sire lines.

BACKGROUND: Numerous genomic scans for positive selection have been performed in livestock species within the last decade, but often a detailed characterization of the detected regions (gene or trait under selection, timing of selection events) is lacking. Cryopreserved resources stored in reproductive or DNA gene banks offer a great opportunity to improve this characterization by providing direct access to recent allele frequency dynamics, thereby differentiating between signatures from recent breeding objectives and those related to more ancient selection constraints. Improved characterization can also be achieved by using next-generation sequencing data, which helps narrowing the size of the detected regions while reducing the number of associated candidate genes. METHODS: We estimated genetic diversity and detected signatures of recent selection in French Large White pigs by sequencing the genomes of 36 animals from three distinct cryopreserved samples: two recent samples from dam (LWD) and sire (LWS) lines, which had diverged from 1995 and were selected under partly different objectives, and an older sample from 1977 prior to the divergence. RESULTS: French LWD and LWS lines have lost approximately 5% of the SNPs that segregated in the 1977 ancestral population. Thirty-eight genomic regions under recent selection were detected in these lines and the corresponding selection events were further classified as convergent between lines (18 regions), divergent between lines (10 regions), specific to the dam line (6 regions) or specific to the sire line (4 regions). Several biological functions were found to be significantly enriched among the genes included in these regions: body size, body weight and growth regardless of the category, early life survival and calcium metabolism more specifically in the signatures in the dam line and lipid and glycogen metabolism more specifically in the signatures in the sire line. Recent selection on IGF2 was confirmed and several other regions were linked to a single candidate gene (ARHGAP10, BMPR1B, GNA14, KATNA1, LPIN1, PKP1, PTH, SEMA3E or ZC3HAV1, among others). CONCLUSIONS: These results illustrate that sequencing the genome of animals at several recent time points generates considerable insight into the traits, genes and variants under recent selection in a population. This approach could be applied to other livestock populations, e.g. by exploiting the rich biological resources stored in cryobanks.

Joint Automatic Metabolite Identification and Quantification of a Set of 1H NMR Spectra.

Metabolomics is a promising approach to characterize phenotypes or to identify biomarkers. It is also easily accessible through NMR, which can provide a comprehensive understanding of the metabolome of any living organisms. However, the analysis of 1H NMR spectrum remains difficult, mainly due to the different problems encountered to perform automatic identification and quantification of metabolites in a reproducible way. In addition, methods that perform automatic identification and quantification of metabolites are often designed to process one given complex mixture spectrum at a time. Hence, when a set of complex mixture spectra coming from the same experiment has to be processed, the approach is simply repeated independently for every spectrum, despite their resemblance. Here, we present new methods that are the first to either align spectra or to identify and quantify metabolites by integrating information coming from several complex spectra of the same experiment. The performances of these new methods are then evaluated on both simulated and real datasets. The results show an improvement in the metabolite identification and in the accuracy of metabolite quantifications, especially when the concentration is low. This joint procedure is available in version 2.0 of ASICS package.

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

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.

Integrated Analysis of Proteomic and Transcriptomic Data Highlights Late Fetal Muscle Maturation Process.

In pigs, the perinatal period is the most critical time for survival. Piglet maturation, which occurs at the end of gestation, is an important determinant of early survival. Skeletal muscle plays a key role in adaptation to extra-uterine life, e.g. motor function and thermoregulation. Progeny from two breeds with extreme neonatal mortality rates were analyzed at 90 and 110 days of gestation (dg). The Large White breed is a highly selected breed for lean growth and exhibits a high rate of neonatal mortality, whereas the Meishan breed is fatter and more robust and has a low neonatal mortality. Our aim was to identify molecular signatures underlying late fetal longissimus muscle development. First, integrated analysis was used to explore relationships between co-expression network models built from a proteomic data set (bi-dimensional electrophoresis) and biological phenotypes. Second, correlations with a transcriptomic data set (microarrays) were investigated to combine different layers of expression with a focus on transcriptional regulation. Muscle glycogen content and myosin heavy chain polymorphism were good descriptors of muscle maturity and were used for further data integration analysis. Using 89 identified unique proteins, network inference, correlation with biological phenotypes and functional enrichment revealed that mitochondrial oxidative metabolism was a key determinant of neonatal muscle maturity. Some proteins, including ATP5A1 and CKMT2, were important nodes in the network related to muscle metabolism. Transcriptomic data suggest that overexpression of mitochondrial PCK2 was involved in the greater glycogen content of Meishan fetuses at 110 dg. GPD1, an enzyme involved in the mitochondrial oxidation of cytosolic NADH, was overexpressed in Meishan. Thirty-one proteins exhibited a positive correlation between mRNA and protein levels in both extreme fetal genotypes, suggesting transcriptional regulation. Gene ontology enrichment and Ingenuity analyses identified PPARGC1A and ESR1 as possible transcriptional factors positively involved in late fetal muscle maturation.

Time course study of the response to LPS targeting the pig immune gene networks.

BACKGROUND: Stress is a generic term used to describe non-specific responses of the body to all kinds of challenges. A very large variability in the response can be observed across individuals, depending on numerous conditioning factors like genetics, early influences and life history. As a result, there is a wide range of individual vulnerability and resilience to stress, also called robustness. The importance of robustness-related traits in breeding strategies is increasing progressively towards the production of animals with a high level of production under a wide range of climatic conditions and management systems, together with a lower environmental impact and a high level of animal welfare. The present study aims at describing blood transcriptomic, hormonal, and metabolic responses of pigs to a systemic challenge using lipopolysaccharide (LPS). The objective is to analyze the individual variation of the biological responses in relation to the activity of the HPA axis measured by the levels of plasma cortisol after LPS and ACTH in 120 juvenile Large White (LW) pigs. The kinetics of the response was measured with biological variables and whole blood gene expression at 4 time points. A multilevel statistical analysis was used to take into account the longitudinal aspect of the data. RESULTS: Cortisol level reaches its peak 4 h after LPS injection. The characteristic changes of white blood cell count to LPS were observed, with a decrease of total count, maximal at t=+4 h, and the mirror changes in the respective proportions of lymphocytes and granulocytes. The lymphocytes / granulocytes ratio was maximal at t=+1 h. An integrative statistical approach was used and provided a set of candidate genes for kinetic studies and ongoing complementary studies focused on the LPS-stimulated inflammatory response. CONCLUSIONS: The present study demonstrates the specific biomarkers indicative of an inflammation in swine. Furthermore, these stress responses persist for prolonged periods of time and at significant expression levels, making them good candidate markers for evaluating the efficacy of anti-inflammatory drugs.

Comparing the intestinal transcriptome of Meishan and Large White piglets during late fetal development reveals genes involved in glucose and lipid metabolism and immunity as valuable clues of intestinal maturity.

BACKGROUND: Maturity of intestinal functions is critical for neonatal health and survival, but comprehensive description of mechanisms underlying intestinal maturation that occur during late gestation still remain poorly characterized. The aim of this study was to investigate biological processes specifically involved in intestinal maturation by comparing fetal jejunal transcriptomes of two representative porcine breeds (Large White, LW; Meishan, MS) with contrasting neonatal vitality and maturity, at two key time points during late gestation (gestational days 90 and 110). MS and LW sows inseminated with mixed semen (from breed LW and MS) gave birth to both purebred and crossbred fetuses. We hypothesized that part of the differences in neonatal maturity between the two breeds results from distinct developmental profiles of the fetal intestine during late gestation. Reciprocal crossed fetuses were used to analyze the effect of parental genome. Transcriptomic data and 23 phenotypic variables known to be associated with maturity trait were integrated using multivariate analysis with expectation of identifying relevant genes-phenotypic variable relationships involved in intestinal maturation. RESULTS: A moderate maternal genotype effect, but no paternal genotype effect, was observed on offspring intestinal maturation. Four hundred and four differentially expressed probes, corresponding to 274 differentially expressed genes (DEGs), more specifically involved in the maturation process were further studied. In day 110-MS fetuses, Ingenuity® functional enrichment analysis revealed that 46% of DEGs were involved in glucose and lipid metabolism, cell proliferation, vasculogenesis and hormone synthesis compared to day 90-MS fetuses. Expression of genes involved in immune pathways including phagocytosis, inflammation and defense processes was changed in day 110-LW compared to day 90-LW fetuses (corresponding to 13% of DEGs). The transcriptional regulator PPARGC1A was predicted to be an important regulator of differentially expressed genes in MS. Fetal blood fructose level, intestinal lactase activity and villous height were the best predicted phenotypic variables with probes mostly involved in lipid metabolism, carbohydrate metabolism and cellular movement biological pathways. CONCLUSIONS: Collectively, our findings indicate that the neonatal maturity of pig intestine may rely on functional development of glucose and lipid metabolisms, immune phagocyte differentiation and inflammatory pathways. This process may partially be governed by PPARGC1A.

Deciphering mechanisms underlying the genetic variation of general production and liver quality traits in the overfed mule duck by pQTL analyses.

BACKGROUND: The aim of this study was to analyse the mechanisms that underlie phenotypic quantitative trait loci (QTL) in overfed mule ducks by identifying co-localized proteomic QTL (pQTL). The QTL design consisted of three families of common ducks that were progeny-tested by using 294 male mule ducks. This population of common ducks was genotyped using a genetic map that included 334 genetic markers located across 28 APL chromosomes (APL for Anas platyrhynchos). Mule ducks were phenotyped for 49 traits related to growth, metabolism, overfeeding ability and meat and fatty liver quality, and 326 soluble fatty liver proteins were quantified. RESULTS: One hundred and seventy-six pQTL and 80 phenotypic QTL were detected at the 5% chromosome-wide significance threshold. The great majority of the identified pQTL were trans-acting and localized on a chromosome other than that carrying the coding gene. The most significant pQTL (1% genome-wide significance) were found for alpha-enolase on APL18 and fatty acid synthase on APL24. Some proteins were associated with numerous pQTL (for example, 17 and 14 pQTL were detected for alpha-enolase and apolipoprotein A1, respectively) and pQTL hotspots were observed on some chromosomes (APL18, 24, 25 and 29). We detected 66 co-localized phenotypic QTL and pQTL for which the significance of the two-trait QTL (2t-QTL) analysis was higher than that of the strongest QTL using a single-trait approach. Among these, 16 2t-QTL were pleiotropic. For example, on APL15, melting rate and abundance of two alpha-enolase spots appeared to be impacted by a single locus that is involved in the glycolytic process. On APLZ, we identified a pleiotropic QTL that modified both the blood level of glucose at the beginning of the force-feeding period and the concentration of glutamate dehydrogenase, which, in humans, is involved in increased glucose absorption by the liver when the glutamate dehydrogenase 1 gene is mutated. CONCLUSIONS: We identified pleiotropic loci that affect metabolic pathways linked to glycolysis or lipogenesis, and in the end to fatty liver quality. Further investigation, via transcriptomics and metabolomics approaches, is required to confirm the biomarkers that were found to impact the genetic variability of these phenotypic traits.

Handling missing rows in multi-omics data integration: multiple imputation in multiple factor analysis framework.

BACKGROUND: In omics data integration studies, it is common, for a variety of reasons, for some individuals to not be present in all data tables. Missing row values are challenging to deal with because most statistical methods cannot be directly applied to incomplete datasets. To overcome this issue, we propose a multiple imputation (MI) approach in a multivariate framework. In this study, we focus on multiple factor analysis (MFA) as a tool to compare and integrate multiple layers of information. MI involves filling the missing rows with plausible values, resulting in M completed datasets. MFA is then applied to each completed dataset to produce M different configurations (the matrices of coordinates of individuals). Finally, the M configurations are combined to yield a single consensus solution. RESULTS: We assessed the performance of our method, named MI-MFA, on two real omics datasets. Incomplete artificial datasets with different patterns of missingness were created from these data. The MI-MFA results were compared with two other approaches i.e., regularized iterative MFA (RI-MFA) and mean variable imputation (MVI-MFA). For each configuration resulting from these three strategies, the suitability of the solution was determined against the true MFA configuration obtained from the original data and a comprehensive graphical comparison showing how the MI-, RI- or MVI-MFA configurations diverge from the true configuration was produced. Two approaches i.e., confidence ellipses and convex hulls, to visualize and assess the uncertainty due to missing values were also described. We showed how the areas of ellipses and convex hulls increased with the number of missing individuals. A free and easy-to-use code was proposed to implement the MI-MFA method in the R statistical environment. CONCLUSIONS: We believe that MI-MFA provides a useful and attractive method for estimating the coordinates of individuals on the first MFA components despite missing rows. MI-MFA configurations were close to the true configuration even when many individuals were missing in several data tables. This method takes into account the uncertainty of MI-MFA configurations induced by the missing rows, thereby allowing the reliability of the results to be evaluated.

Intestinal toxicity of the masked mycotoxin deoxynivalenol-3-ß-D-glucoside.

Natural food contaminants such as mycotoxins are an important problem for human health. Deoxynivalenol (DON) is one of the most common mycotoxins detected in cereals and grains. Its toxicological effects mainly concern the immune system and the gastrointestinal tract. This toxin is a potent ribotoxic stressor leading to MAP kinase activation and inflammatory response. DON frequently co-occurs with its glucosylated form, the masked mycotoxin deoxynivalenol-3-ß-D-glucoside (D3G). The toxicity of this later compound remains unknown in mammals. This study aimed to assess the ability of D3G to elicit a ribotoxic stress and to induce intestinal toxicity. The toxicity of D3G and DON (0-10 µM) was studied in vitro, on the human intestinal Caco-2 cell line, and ex vivo, on porcine jejunal explants. First, an in silico analysis revealed that D3G, contrary to DON, was unable to bind to the A-site of the ribosome peptidyl transferase center, the main targets for DON toxicity. Accordingly, D3G did not activate JNK and P38 MAPKs in treated Caco-2 cells and did not alter viability and barrier function on cells, as measured by the trans-epithelial electrical resistance. Treatment of intestinal explants for 4 h with 10 µM DON induced morphological lesions and up-regulated the expression of pro-inflammatory cytokines as measured by qPCR and pan-genomic microarray analysis. By contrast, expression profile of D3G-treated explants was similar to that of controls, and these explants did not show histomorphology alteration. In conclusion, our data demonstrated that glucosylation of DON suppresses its ability to bind to the ribosome and decreases its intestinal toxicity.

Time course of the response to ACTH in pig: biological and transcriptomic study.

BACKGROUND: HPA axis plays a major role in physiological homeostasis. It is also involved in stress and adaptive response to the environment. In farm animals in general and specifically in pigs, breeding strategies have highly favored production traits such as lean growth rate, feed efficiency and prolificacy at the cost of robustness. On the hypothesis that the HPA axis could contribute to the trade-off between robustness and production traits, we have designed this experiment to explore individual variation in the biological response to the main stress hormone, cortisol, in pigs. We used ACTH injections to trigger production of cortisol in 120 juvenile Large White (LW) pigs from 28 litters and the kinetics of the response was measured with biological variables and whole blood gene expression at 4 time points. A multilevel statistical analysis was used to take into account the longitudinal aspect of the data. RESULTS: Cortisol level reached its peak 1 h after ACTH injection. White blood cell composition was modified with a decrease of lymphocytes and monocytes and an increase of granulocytes (F D R<0.05). Basal level of cortisol was correlated with birth and weaning weights. Microarray analysis identified 65 unique genes of which expression responded to the injection of ACTH (adjusted P<0.05). These genes were classified into 4 clusters with distinctive kinetics in response to ACTH injection. The first cluster identified genes strongly correlated to cortisol and previously reported as being regulated by glucocorticoids. In particular, DDIT4, DUSP1, FKBP5, IL7R, NFKBIA, PER1, RGS2 and RHOB were shown to be connected to each other by the glucocorticoid receptor NR3C1. Most of the differentially expressed genes that encode transcription factors have not been described yet as being important in transcription networks involved in stress response. Their co-expression may mean co-regulation and they could thus provide new patterns of biomarkers of the individual sensitivity to cortisol. CONCLUSIONS: We identified 65 genes as biological markers of HPA axis activation at the gene expression level. These genes might be candidates for a better understanding of the molecular mechanisms of the stress response.

Exploring transcriptomic diversity in muscle revealed that cellular signaling pathways mainly differentiate five Western porcine breeds.

BACKGROUND: Among transcriptomic studies, those comparing species or populations can increase our understanding of the impact of the evolutionary forces on the differentiation of populations. A particular situation is the one of short evolution time with breeds of a domesticated species that underwent strong selective pressures. In this study, the gene expression diversity across five pig breeds has been explored in muscle. Samples came from: 24 Duroc, 33 Landrace, 41 Large White dam line, 10 Large White sire line and 39 Piétrain. From these animals, 147 muscle samples obtained at slaughter were analyzed using the porcine Agilent 44 K v1 microarray. RESULTS: A total of 12,358 genes were identified as expressed in muscle after normalization and 1,703 genes were declared differential for at least one breed (FDR < 0.001). The functional analysis highlighted that gene expression diversity is mainly linked to cellular signaling pathways such as the PI3K (phosphoinositide 3-kinase) pathway. The PI3K pathway is known to be involved in the control of development of the skeletal muscle mass by affecting extracellular matrix - receptor interactions, regulation of actin cytoskeleton pathways and some metabolic functions. This study also highlighted 228 spots (171 unique genes) that differentiate the breeds from each other. A common subgroup of 15 genes selected by three statistical methods was able to differentiate Duroc, Large White and Piétrain breeds. CONCLUSIONS: This study on transcriptomic differentiation across Western pig breeds highlighted a global picture: mainly signaling pathways were affected. This result is consistent with the selection objective of increasing muscle mass. These transcriptional changes may indicate selection pressure or simply breed differences which may be driven by human selection. Further work aiming at comparing genetic and transcriptomic diversities would further increase our understanding of the consequences of human impact on livestock species.

Muscle transcriptomic investigation of late fetal development identifies candidate genes for piglet maturity.

BACKGROUND: In pigs, the perinatal period is the most critical time for survival. Piglet maturation, which occurs at the end of gestation, leads to a state of full development after birth. Therefore, maturity is an important determinant of early survival. Skeletal muscle plays a key role in adaptation to extra-uterine life, e.g. glycogen storage and thermoregulation. In this study, we performed microarray analysis to identify the genes and biological processes involved in piglet muscle maturity. Progeny from two breeds with extreme muscle maturity phenotypes were analyzed at two time points during gestation (gestational days 90 and 110). The Large White (LW) breed is a selected breed with an increased rate of mortality at birth, whereas the Meishan (MS) breed produces piglets with extremely low mortality at birth. The impact of the parental genome was analyzed with reciprocal crossed fetuses. RESULTS: Microarray analysis identified 12,326 differentially expressed probes for gestational age and genotype. Such a high number reflects an important transcriptomic change that occurs between 90 and 110 days of gestation. 2,000 probes, corresponding to 1,120 unique annotated genes, involved more particularly in the maturation process were further studied. Functional enrichment and graph inference studies underlined genes involved in muscular development around 90 days of gestation, and genes involved in metabolic functions, such as gluconeogenesis, around 110 days of gestation. Moreover, a difference in the expression of key genes, e.g. PCK2, LDHA or PGK1, was detected between MS and LW just before birth. Reciprocal crossing analysis resulted in the identification of 472 genes with an expression preferentially regulated by one parental genome. Most of these genes (366) were regulated by the paternal genome. Among these paternally regulated genes, some known imprinted genes, such as MAGEL2 or IGF2, were identified and could have a key role in the maturation process. CONCLUSION: These results reveal the biological mechanisms that regulate muscle maturity in piglets. Maturity is also under the conflicting regulation of the parental genomes. Crucial genes, which could explain the biological differences in maturity observed between LW and MS breeds, were identified. These genes could be excellent candidates for a key role in the maturity.

Sperm DNA methylation analysis in swine reveals conserved and species-specific methylation patterns and highlights an altered methylation at the GNAS locus in infertile boars.

Male infertility is an increasing health issue in today's society for both human and livestock populations. In livestock, male infertility slows the improvement of animal selection programs and agricultural productivity. There is increasing evidence that epigenetic marks play an important role in the production of good-quality sperm. We therefore screened for specific or common epigenetic signatures of livestock infertility. To do so, we compared DNA methylation level in sperm DNA from fertile and infertile boars. We evaluated first the global level of sperm DNA methylation and found no difference between the two groups of boars. We then selected 42 loci of interest, most of them known to be imprinted in human or mice, and assessed the imprinting status of five of them not previously described in swine tissues: WT1, CNTN3, IMPACT, QPCT, and GRB10. DNA methylation level was then quantified in fertile and infertile boars at these 42 loci. Results from fertile boars indicated that the methylation level of the selected loci is highly conserved between pig, human, and mice, with a few exceptions, including the POU5F1 (OCT4) promoter and RTL1. Comparison between fertile and infertile boars revealed that one imprinted region, the GNAS locus, shows an increase in sperm DNA methylation in three out of eight infertile boars with low semen quality. This increase in DNA methylation is associated with an altered expression of the genes belonging to the GNAS locus, suggesting a new role for GNAS in the proper formation of functional gametes.

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

Together with environmental factors, physiological maturity at birth is a major determinant for neonatal survival and postnatal development in mammalian species. Maturity at birth is the outcome of complex mechanisms of intra-uterine development and maturation during the end of gestation. In pig production, piglet preweaning mortality averages 20% of the litter and thus, maturity is a major welfare and economic concern. Here, we used both targeted and untargeted metabolomic approaches to provide a deeper understanding of the maturity in a model of lines of pigs divergently selected on residual feed intake (RFI), previously shown to have contrasted signs of maturity at birth. Analyses were conducted on plasma metabolome of piglets at birth and integrated with other phenotypic characteristics associated to maturity. We confirmed proline and myo-inositol, previously described for their association with delayed growth, as potential markers of maturity. Urea cycle and energy metabolism were found more regulated in piglets from high and low RFI lines, respectively, suggesting a better thermoregulation ability for the low RFI (with higher feed efficiency) piglets.

Transcriptome profiling of sheep granulosa cells and oocytes during early follicular development obtained by laser capture microdissection.

BACKGROUND: Successful achievement of early folliculogenesis is crucial for female reproductive function. The process is finely regulated by cell-cell interactions and by the coordinated expression of genes in both the oocyte and in granulosa cells. Despite many studies, little is known about the cell-specific gene expression driving early folliculogenesis. The very small size of these follicles and the mixture of types of follicles within the developing ovary make the experimental study of isolated follicular components very difficult.The recently developed laser capture microdissection (LCM) technique coupled with microarray experiments is a promising way to address the molecular profile of pure cell populations. However, one main challenge was to preserve the RNA quality during the isolation of single cells or groups of cells and also to obtain sufficient amounts of RNA.Using a new LCM method, we describe here the separate expression profiles of oocytes and follicular cells during the first stages of sheep folliculogenesis. RESULTS: We developed a new tissue fixation protocol ensuring efficient single cell capture and RNA integrity during the microdissection procedure. Enrichment in specific cell types was controlled by qRT-PCR analysis of known genes: six oocyte-specific genes (SOHLH2, MAEL, MATER, VASA, GDF9, BMP15) and three granulosa cell-specific genes (KL, GATA4, AMH).A global gene expression profile for each follicular compartment during early developmental stages was identified here for the first time, using a bovine Affymetrix chip. Most notably, the granulosa cell dataset is unique to date. The comparison of oocyte vs. follicular cell transcriptomes revealed 1050 transcripts specific to the granulosa cell and 759 specific to the oocyte.Functional analyses allowed the characterization of the three main cellular events involved in early folliculogenesis and confirmed the relevance and potential of LCM-derived RNA. CONCLUSIONS: The ovary is a complex mixture of different cell types. Distinct cell populations need therefore to be analyzed for a better understanding of their potential interactions. LCM and microarray analysis allowed us to identify novel gene expression patterns in follicular cells at different stages and in oocyte populations.

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

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.

Correlation Networks Provide New Insights into the Architecture of Testicular Steroid Pathways in Pigs.

Steroid metabolism is a fundamental process in the porcine testis to provide testosterone but also estrogens and androstenone, which are essential for the physiology of the boar. This study concerns boars at an early stage of puberty. Using a RT-qPCR approach, we showed that the transcriptional activities of several genes providing key enzymes involved in this metabolism (such as CYP11A1) are correlated. Surprisingly, HSD17B3, a key gene for testosterone production, was absent from this group. An additional weighted gene co-expression network analysis was performed on two large sets of mRNA-seq to identify co-expression modules. Of these modules, two containing either CYP11A1 or HSD17B3 were further analyzed. This comprehensive correlation meta-analysis identified a group of 85 genes with CYP11A1 as hub gene, but did not allow the characterization of a robust correlation network around HSD17B3. As the CYP11A1-group includes most of the genes involved in steroid synthesis pathways (including LHCGR encoding for the LH receptor), it may control the synthesis of most of the testicular steroids. The independent expression of HSD17B3 probably allows part of the production of testosterone to escape this control. This CYP11A1-group contained also INSL3 and AGT genes encoding a peptide hormone and an angiotensin peptide precursor, respectively.