Background: Leakage of water and ions and soluble proteins from muscle cells occurs during prolonged exercise due to ischemia causing muscle damage. Alsopost mortemanoxia during conversion of muscle to meat is marked by loss of water and soluble components from the muscle cell. There is considerable variation in the water holding capacity of meat affecting economy of meat production. Water holding capacity depends on numerous genetic and environmental factors relevant to structural and biochemical muscle fibre properties a well asanteandpostslaughter metabolic processes.Results: Expression microarray analysis of M.longissimus dorsiRNAs of 74 F2 animals of a resource population showed 1,279 transcripts with trait correlated expression to water holding capacity. Negatively correlated transcripts were enriched in functional categories and pathways like extracellular matrix receptor interaction and calcium signalling. Transcripts with positive correlation dominantly represented biochemical processes including oxidative phosphorylation, mitochondrial pathways, as well as transporter activity. A linkage analysis of abundance of trait correlated transcripts revealed 897 expression QTL (eQTL) with 104 eQTL coinciding with QTL regions for water holding capacity; 96 transcripts hadtransacting and 8 hadcisacting regulation.Conclusion: The complex relationships between biological processes taking place in live skeletal muscle and meat quality are driven on the one hand by the energy reserves and their utilisation in the muscle and on the other hand by the muscle structure itself and calcium signalling. Holistic expression profiling was integrated with QTL analysis for the trait of interest and for gene expression levels for creation of a priority list of genes out of the orchestra of genes of biological networks relevant to the liability to develop elevated drip loss.

Background: Stress, elicited for example by aggressive interactions, has negative effects on various biological functions including immune defence, reproduction, growth, and, in livestock, on product quality. Stress response and aggressiveness are mutually interrelated and show large interindividual variation, partly attributable to genetic factors. In the pig little is known about the molecular-genetic background of the variation in stress responsiveness and aggressiveness. To identify candidate genes we analyzed association of DNA markers in each of ten genes (CRH g.233C>T, CRHR1 c.*866_867insA, CRHBP c.51G>A, POMC c.293_298del, MC2R c.306T>G, NR3C1 c.*2122A>G, AVP c.207A>G, AVPR1B c.1084A>G, UCN g.1329T>C, CRHR2 c.*13T>C) related to the hypothalamic-pituitary-adrenocortical (HPA) axis, one of the main stress-response systems, with various stress- and aggression-related parameters at slaughter. These parameters were: physiological measures of the stress response (plasma concentrations of cortisol, creatine kinase, glucose, and lactate), adrenal weight (which is a parameter reflecting activity of the central branch of the HPA axis over time) and aggressive behaviour (measured by means of lesion scoring) in the context of psychosocial stress of mixing individuals with different aggressive temperament. Results: The SNP NR3C1 c.*2122A>G showed association with cortisol concentration (p = 0.024), adrenal weight (p = 0.003) and aggressive behaviour (front lesion score, p = 0.012; total lesion score p = 0.045). The SNP AVPR1B c.1084A>G showed a highly significant association with aggressive behaviour (middle lesion score, p = 0.007; total lesion score p = 0.003). The SNP UCN g.1329T>C showed association with adrenal weight (p = 0.019) and aggressive behaviour (front lesion score, p = 0.029). The SNP CRH g.233C>T showed a significant association with glucose concentration (p = 0.002), and the polymorphisms POMC c.293_298del and MC2R c.306T>G with adrenal weight (p = 0.027 and p < 0.0001 respectively). Conclusions: The multiple and consistent associations shown by SNP in NR3C1 and AVPR1B provide convincing evidence for genuine effects of their DNA sequence variation on stress responsiveness and aggressive behaviour. Identification of the causal functional molecular polymorphisms would not only provide markers useful for pig breeding but also insight into the molecular bases of the stress response and aggressive behaviour in general.

Background: Physiological processes aiding the conversion of muscle to meat involve many genes associated with muscle structure and metabolic processes. MicroRNAs regulate networks of genes to orchestrate cellular functions, in turn regulating phenotypes.Results: We applied weighted gene co-expression network analysis to identify co-expression modules that correlated to meat quality phenotypes and were highly enriched for genes involved in glucose metabolism, response to wounding, mitochondrial ribosome, mitochondrion, and extracellular matrix. Negative correlation of miRNA with mRNA and target prediction were used to select transcripts out of the modules of trait-associated mRNAs to further identify those genes that are correlated with post mortem traits.Conclusions: Porcine muscle co-expression transcript networks that correlated topost mortemtraits were identified. The integration of miRNA and mRNA expression analyses, as well as network analysis, enabled us to interpret the differentially-regulated genes from a systems perspective. Linking co-expression networks of transcripts and hierarchically organized pairs of miRNAs and mRNAs to meat properties yields new insight into several biological pathways underlying phenotype differences. These pathways may also be diagnostic for many myopathies, which are accompanied by deficient nutrient and oxygen supply of muscle fibers.

Background: Postnatal muscle growth is largely depending on the number and size of muscle fibers. The number of myofibers and to a large extent their metabolic and contractile properties, which also influence their size, are determined prenatally during the process of myogenesis. Hence identification of genes and their networks governing prenatal development of skeletal muscles will provide insight into the control of muscle growth and facilitate finding the source of its variation. So far most of the genes involved in myogenesis were identified by in vitro studies using gene targeting and transgenesis. Profiling of transcriptome changes during the myogenesis in vivo promises to obtain a more complete picture. In order to address this, we performed transcriptome profiling of prenatal skeletal muscle using differential display RT-PCR as on open system with the potential to detect novel transcripts. Seven key stages of myogenesis (days 14, 21, 35, 49, 63, 77 and 91 post conception) were studied in two breeds, Pietrain and Duroc, differing markedly in muscularity and muscle structure. Results: Eighty prominent cDNA fragments were sequenced, 43 showing stage-associated and 37 showing breed-associated differences in the expression, respectively. Out of the resulting 85 unique expressed sequence tags, EST, 52 could be assigned to known genes. The most frequent functional categories represented genes encoding myofibrillar proteins (8), genes involved in cell adhesion, cell-cell signaling and extracellular matrix synthesis/remodeling (8), genes regulating gene expression (8), and metabolism genes (8). Some of the EST that showed no identity to any known transcripts in the databases are located in introns of known genes and most likely represent novel exons (e.g. HMGA2). Expression of thirteen transcripts along with five reference genes was further analyzed by means of real-time quantitative PCR. Nine of the target transcripts showed higher than twofold differences in the expression between the two breeds (GATA3, HMGA2, NRAP, SMC6L1, SPP1, RAB6IP2, TJP1 and two EST). Conclusion: The present study revealed several genes and novel transcripts not previously associated with myogenesis and expands our knowledge of genetic factors operating during myogenesis. Genes that exhibited differences between the divergent breeds represent candidate genes for muscle growth and structure.

Background The proportion of muscle fibre types and their size affect muscularity as well as functional properties of the musculature and meat quality. We aimed to identify QTL for microstructural muscle properties including muscle fibre size, their numbers and fibre type proportions as well as biophysical parameters of meat quality and traits related to body composition, i.e. pH, conductivity, area of M. longissimus dorsi and lean meat content. A QTL scan was conducted in a porcine experimental population that is based on Duroc and Berlin Miniature Pig. Results Least square regression interval mapping revealed five significant and 42 suggestive QTL for traits related to muscle fibre composition under the line-cross model as well as eight significant and 40 suggestive QTL under the half-sib model. For traits related to body composition and biophysical parameters of meat quality five and twelve significant plus nine and 22 suggestive QTL were found under the line-cross and half-sib model, respectively. Regions with either significant QTL for muscle fibre traits or significant QTL for meat quality and muscularity or both were detected on SSC1, 2, 3, 4, 5, 13, 14, 15, and 16. QTL for microstructural properties explained a larger proportion of variance than did QTL for meat quality and body composition. Conclusion Microstructural properties of pig muscle and meat quality are governed by genetic variation at many loci distributed throughout the genome. QTL analysis under both, the line-cross and half-sib model, allows detecting QTL in case of fixation or segregation of the QTL alleles among the founder populations and thus provide comprehensive insight into the genetic variation of the traits under investigation. Genomic regions affecting complex traits of muscularity and meat quality as well as microstructural properties might point to QTL that in first instance affect muscle fibre traits and by this in second instance meat quality. Disentangling complex traits in their constituent phenotypes might facilitate the identification of QTL and the elucidation of the pleiotropic nature of QTL effects.

Recent evidence indicates that maternal nutrition during pregnancy influences gene expression in offspring through epigenetic alterations. In the present study we evaluated the effect of protein excess and deficiency during porcine pregnancy on offspring hepatic and skeletal muscular expression patterns of key genes of methionine metabolism (DNMT1, DNMT3a, DNMT3b, BHMT, MAT2B and AHCYL1), condensin I subunit genes (NCAPD2, NCAPG and NCAPH), important for chromosome condensation and segregation, global DNA methylation and gene-specific DNA methylation. German Landrace sows were randomly assigned to control (CO), high protein (HP) and low protein (LP) diet groups. Tissue samples of offspring were collected from fetal (dpc95), newborn (dpn1), weanling (dpn28) and finisher pigs (dpn188). Gene expression of DNMT1, DNMT3a and DNMT3b was influenced by both HP and LP diets, indicating an involvement of DNA methylation in fetal programming by maternal protein supply. Moreover, hepatic global methylation was significantly affected by protein restriction at dpc95 (p = 0.004) and by protein excess at dpn188 (p = 0.034). Gene expression in fetal liver was significantly different between CO and LP for NCAPD2 (p = 0.0005), NCAPG (p = 0.0009) and NCAPH (p < 0.0001). In skeletal muscle, LP fetuses had significantly altered gene expression of NCAPD2 (p = 0.020) and NCAPH (p = 0.001), compared with CO. Furthermore, NCAPG was differentially methylated among LP, HP and CO; indeed, a significant positive correlation was detected with transcript amount in fetal pigs (r = 0.47, p = 0.002). These data demonstrate that both restriction and excess dietary protein during pregnancy alters the offspring’s epigenetic marks and influences gene expression.