Genes with expression levels correlating to drip loss prove association of their polymorphism with water holding capacity of pork

Six genes that were known to exhibit expression levels that are correlated to drip loss BVES, SLC3A2, ZDHHC5, CS, COQ9, and EGFR have been for candidate gene analysis. Based on in silico analysis SNPs were detected, confirmed by sequencing, and used for genotyping. The SNPs were genotyped in about 1,800 animals from six pig populations including commercial herds of Pietrain (PI) and German Landrace (DL), different commercial herds of Pietrain × (German Large White × German Landrace) (PIF1(a/b/c)), and one experimental F₂-population Duroc × Pietrain (DUPI). Comparative and genetic mapping established the location of BVES on SSC1, of SLC3A2 and ZDHHC5 on SSC2, of CS on SSC5, of COQ9 on SSC6 and of EGFR on SSC9, respectively, coinciding with QTL regions for carcass and meat quality traits. BVES, SLC3A2, and CS revealed association at least with drip loss and with several other measures of water holding capacity (WHC). Moreover, COQ9 and EGFR were associated with several meat quality traits such as meat color and/or thawing loss. This study reveals statistic evidence in addition to the functional relationship of these genes to WHC previously evidenced by expression analysis. This study reveals positional and genetic statistical evidence for a link of genetic variation at these loci or close to them and promotes those six candidate genes as functional and/or positional candidate genes for meat quality traits.     

A two‐step approach to map quantitative trait loci for meat quality in connected porcine F2 crosses considering main and epistatic effects

The aim of this study was to map QTL for meat quality traits in three connected porcine F₂ crosses comprising around 1000 individuals. The three crosses were derived from the founder breeds Chinese Meishan, European Wild Boar and Pietrain. The animals were genotyped genomewide for approximately 250 genetic markers, mostly microsatellites. They were phenotyped for seven meat quality traits (pH at 45 min and 24 h after slaughter, conductivity at 45 min and 24 h after slaughter, meat colour, drip loss and rigour). QTL mapping was conducted using a two‐step procedure. In the first step, the QTL were mapped using a multi‐QTL multi‐allele model that was tailored to analyse multiple connected F₂ crosses. It considered additive, dominance and imprinting effects. The major gene RYR1:g.1843C>T affecting the meat quality on SSC6 was included as a cofactor in the model. The mapped QTL were tested for pairwise epistatic effects in the second step. All possible epistatic effects between additive, dominant and imprinting effects were considered, leading to nine orthogonal forms of epistasis. Numerous QTL were found. The most interesting chromosome was SSC6. Not all genetic variance of meat quality was explained by RYR1:g.1843C>T. A small confidence interval was obtained, which facilitated the identification of candidate genes underlying the QTL. Epistasis was significant for the pairwise QTL on SSC12 and SSC14 for pH24 and for the QTL on SSC2 and SSC5 for rigour. Some evidence for additional pairwise epistatic effects was found, although not significant. Imprinting was involved in epistasis.     

Associations of functional candidate genes derived from gene-expression profiles of prenatal porcine muscle tissue with meat quality and muscle deposition

Ten genes (ANK1, bR10D1, CA3, EPOR, HMGA2, MYPN, NME1, PDGFRA, ERC1, TTN), whose candidacy for meat-quality and carcass traits arises from their differential expression in prenatal muscle development, were examined for association in 1700 performance-tested fattening pigs of commercial purebred and crossbred herds of Duroc, Pietrain, Pietrain x (Landrace x Large White), Duroc x (Landrace x Large White) as well as in an experimental F(2) population based on a reciprocal cross of Duroc and Pietrain. Comparative sequencing revealed polymorphic sites segregating across commercial breeds. Genetic mapping results corresponded to pre-existing assignments to porcine chromosomes or current human-porcine comparative maps. Nine of these genes showed association with meat-quality and carcass traits at a nominal P-value of < or = 0.05; PDGFRA revealed no association reaching the P < or = 0.05 threshold. In particular, HMGA2, CA3, EPOR, NME1 and TTN were associated with meat colour, pH and conductivity of loin 24 h postmortem; CA3 and MYPN exhibited association with ham weight and lean content (FOM) respectively at P-values of < 0.003 that correspond to false discovery rates of < 0.05. However, none of the genes showed significant associations for a particular trait across all populations. The study revealed statistical-genetic evidence for association of the functional candidate genes with traits related to meat quality and muscle deposition. The polymorphisms detected are not likely causal, but markers were identified that are in linkage disequilibrium with causal genetic variation within particular populations.     

Association of corticotropin-releasing hormone gene variation with performance and meat quality traits in commercial pig lines

The porcine corticotropin-releasing hormone(CRH) gene is a functional-positional candidate for quantitative tract loci on porcine chromosome 4 with major effects on growth and carcass composition. In addition, the central role of CRH in the neuroendocrine response to stress implicates the CRH gene as a functional candidate for meat quality. Association of a single nucleotide polymorphism (SNP) in the promoter region of the porcine CRH gene (g.233C > T) with several growth, carcass and meat quality traits was examined using more than 2000 individuals from four commercial lines: German Landrace (LR), Pietrain (Pi), German Large White x German Landrace (F1) and the German commercial fattening pig cross of Pietrain x F1 (PiF1). Significant association of the CRH SNP was found with feed conversion ratio in the PiF1 line, with carcass length in the LR line and with lean content in the F1, LR and Pi lines. Moreover, significant association with meat colour was found in the Pi and LR lines; however, the effects were in opposite directions. The presented results indicate that sequence variation in the porcine CRH gene has no major effect on growth and carcass composition in commercial pig lines, although it may significantly contribute to variation in meat quality. The g.233C>T SNP may be in incomplete linkage disequilibrium with causal mutations and/or exhibit effects in the context of DNA variation at other interacting loci.     

Different Statistical Approaches to Investigate Porcine Muscle Metabolome Profiles to Highlight New Biomarkers for Pork Quality Assessment

The aim of this study was to elucidate the underlying biochemical processes to identify potential key molecules of meat quality traits drip loss, pH of meat 1 h post-mortem (pH1), pH in meat 24 h post-mortem (pH24) and meat color. An untargeted metabolomics approach detected the profiles of 393 annotated and 1,600 unknown metabolites in 97 Duroc × Pietrain pigs. Despite obvious differences regarding the statistical approaches, the four applied methods, namely correlation analysis, principal component analysis, weighted network analysis (WNA) and random forest regression (RFR), revealed mainly concordant results. Our findings lead to the conclusion that meat quality traits pH1, pH24 and color are strongly influenced by processes of post-mortem energy metabolism like glycolysis and pentose phosphate pathway, whereas drip loss is significantly associated with metabolites of lipid metabolism. In case of drip loss, RFR was the most suitable method to identify reliable biomarkers and to predict the phenotype based on metabolites. On the other hand, WNA provides the best parameters to investigate the metabolite interactions and to clarify the complex molecular background of meat quality traits. In summary, it was possible to attain findings on the interaction of meat quality traits and their underlying biochemical processes. The detected key metabolites might be better indicators of meat quality especially of drip loss than the measured phenotype itself and potentially might be used as bio indicators.     

RNA‐seq analysis reveals new candidate genes for drip loss in a Pietrain × Duroc × Landrace × Yorkshire population

Drip loss, one of the most important meat quality traits, is characterized by low heritability. To date, the genetic factors affecting the drip loss trait have not been clearly elucidated. The objective of this study was to identify critical candidate genes affecting drip loss. First, we generated a Pietrain × Duroc × Landrace × Yorkshire commercial pig population and obtained phenotypic values for the drip loss trait. Furthermore, we constructed two RNA libraries from pooled samples of longissimus dorsi muscles with the highest (H group) and lowest (L group) drip loss and identified the differentially expressed genes (DEGs) between these extreme phenotypes using RNA‐seq technology. In total, 25 883 genes were detected in the H and L group libraries, and none was specifically expressed in only one library. Comparative analysis of gene expression levels found that 150 genes were differentially expressed, of which 127 were upregulated and 23 were downregulated in the H group relative to the L group. In addition, 68 drip loss quantitative trait loci (QTL) overlapping with 63 DEGs were identified, and these QTL were distributed mainly on chromosomes 1, 2, 5 and 6. Interestingly, the triadin (TRDN) gene, which is involved in muscle contraction and fat deposition, and the myostatin (MSTN) gene, which has a role in muscle growth, were localized to more than two drip loss QTL, suggesting that both are critical candidate genes responsible for drip loss.     

Weighted gene co-expression network analysis reveals potential candidate genes affecting drip loss in pork

Drip loss is an essential evaluation indicator for pork quality. It is closely related to other meat quality indicators, including water-holding capacity, water loss rate and pH value at 45 min (pH₁) and 24 h post-mortem (pH₂), and is influenced by environmental and genetic factors and their interactions. We previously conducted differentially expressed gene analysis to identify candidate genes affecting drip loss using eight individuals with extremely high- and low-drip loss selected from 28 purebred Duroc pigs. Using 28 identical samples, in the present study, we performed weighted gene co-expression network analysis with drip loss and drip loss-related traits, including water-holding capacity, water loss rate, pH₁ and pH₂. A total of 25 modules were identified, and five of them correlated with at least two drip loss or drip loss-related traits. After functional enrichment analysis of genes in the five modules, three modules were found to be critical, as their genes were significantly involved in amino acid metabolism, immune response and apoptosis, which have potential relationships with drip loss. Furthermore, we identified five candidate genes affecting drip loss in one critical module, AASS, BCKDHB, ALDH6A1, MUT and MCCC1, as they overlapped with differentially expressed genes detected in our previous study, exhibited protein–protein interactions and had potential biological functions in affecting drip loss according to the literature. The outcomes of the present study enhance our understanding of the molecular mechanisms underlying drip loss and will aid in improving the pork quality.     

Genetic parameters of meat quality traits in two pig breeds measured by rapid methods

To study genetic variation in meat quality traits measured by rapid methods, data were recorded between 2005 and 2008 on samples of M. longissimus dorsi (LD) in Landrace (n = 3838) and Duroc (n = 2250) pigs included in the Norwegian pig breeding scheme. In addition, ultimate pH levels in the glycolytic LD (loin muscle) and M. gluteus medius (GM, ham muscle), and in the oxidative m. gluteus profundus (GP, ham muscle) were recorded as an extended data set (n = 16 732 and n = 7456 for Landrace and Duroc, respectively) from 1998 to 2008. Data were analysed with a multi-trait animal model using AI-REML methodology. Meat from Duroc had considerably more intramuscular fat (IMF), less moisture and protein, appeared darker with higher colour intensity and had lower drip loss than meat from Landrace. The heritability estimates (s.e. 0.01 to 0.07) for pH in LD (0.19 and 0.27 for Landrace and Duroc, respectively), GM (0.12 and 0.22) and GP (0.19 and 0.38), drip loss (0.23 and 0.33), colour values: L* (lightness) (0.41 and 0.28), a* (redness) (0.46 and 0.43), b* (yellowness) (0.31 and 0.33), IMF (0.50 and 0.62), muscle moisture (0.31 and 0.50) and muscle protein content (0.40 and 0.54) in LD all demonstrated moderate-to-high genetic variation for these traits in both breeds. Near infrared spectroscopy and EZ-DripLoss are modern technologies used in this study for the determination of chemical components and drip loss in meat. These methods gave higher heritabilities than more traditional methods used to measure these traits. The estimated genetic correlations between moisture and IMF in Duroc, and pH and drip loss in Duroc were both -0.89. Interesting differences between the two breeds in numerical value of some genetic correlations were observed, probably reflecting the differences in physiology and selection history between Landrace and Duroc. The estimated genetic correlation between drip loss and pH was much stronger in Duroc than in Landrace (-0.89 and -0.63, respectively). This might be due to the high pH in Duroc, whereas Landrace had a lower pH closer to the iso-electric point for muscle proteins. The positive genetic correlation between the L* value in meat and IMF in Duroc (0.50) was an effect of differences in visible marbling, rather than meat colour. For Landrace, this correlation was negative (-0.20). IMF content showed favourable genetic correlations to drip loss (-0.36 and -0.35 for Landrace and Duroc, respectively).     

猪CAST基因的单核苷酸多态性及其对肉质性状的效应

CAST基因作为肉质性状的主要候选基因.以80头外来猪和190头地方猪为材料,在CAST基因内含子24上检测到两个多态性位点(A916G 和C1633G ).在916位点上,长白猪和大白猪以A基因为优势基因,其频率分别为0.88和1.00;莱芜猪,大薄莲猪,沂蒙黑猪和里岔黑猪以B基因为优势基因,其频率分别为0.93, 0.97, 0.78和0.68.在1633位点上,长白猪和大白猪以C基因为优势基因,其频率分别为0.82和0.79:莱芜猪,大薄莲猪,沂蒙黑猪和里岔黑猪以D基因为优势基因,其频率分别为1.00, 1.00, 0.88, 0.78.在试验猪种中,共检测到6种单倍型(AACC,AACD,AADD,ABCC,BBCC,BBDD).单倍型分布的多重比较结果表明,外来猪种(长白猪和大白猪)与地方猪种(莱芜猪,大薄莲猪,沂蒙黑猪和里岔黑猪)比较差异极显著(P < 0.01).固定效应模型分析结果表明,嫩度,屠宰45 min后pH值和滴水损失单倍型间差异显著(P < 0.05).最小二乘分析结果表明,外来猪种与地方猪种在嫩度,屠宰45 min后pH值和滴水损失间差异显著(P < 0.05).BBDD单倍型个体与其它单倍型个体比较,嫩度及滴水损失差异显著(P < 0.05);AADD,BBCC,BBDD单倍型个体与其它单倍型个体比较,屠宰45 min后pH值差异显著(P < 0.05).因此,在育种过程中将CAST基因应用于标记辅助选择,将有利于改善猪肉品质,加快育种进程.     

Polymorphisms on SSC15q21-q26 Containing QTL for reproduction in Swine and its association with litter size

Several quantitative trait loci (QTL) for important reproductive traits (ovulation rate) have been identified on the porcine chromosome 15 (SSC15). To assist in the selection of positional candidate swine genes for these QTL on SSC15, twenty-one genes had already been assigned to SSC15 in a previous study in our lab, by using the radiation hybrid panel IMpRH. Further polymorphism studies were carried out on these positional candidate genes with four breeds of pigs (Duroc, Erhualian, Dahuabai and Landrace) harboring significant differences in reproduction traits. A total of nineteen polymorphisms were found in 21 genes. Among these, seven in six genes were used for association studies, whereby NRP2 polymorphism was found to be significantly (p < 0.05) associated with litter-size traits. NRP2 might be a candidate gene for pig-litter size based on its chromosome location (Du et al., 2006), significant association with litter-size traits and relationships with Sema and the VEGF super families.     

Associations between single nucleotide polymorphisms in 33 candidate genes and meat quality traits in commercial pigs

This study aimed to evaluate the effects of single nucleotide polymorphisms (SNPs) in candidate genes for meat quality using a custom 96‐SNP panel (Illumina Vera Code GoldenGate Assay) on 15 traits collected from 400 commercial pigs. Meat quality measurements included muscle pH, color (L*, a* and b*), drip loss, cooking loss, peak shear force and six sensory traits including appearance (outside and inside), tenderness, juiciness, flavor and overall liking as well as carcass weight and probe yield. Thirty‐five SNPs with minor allele frequencies > 0.10 remained for the multimarker association using the GLM procedure of sas 9.2. Results showed that 20 SNPs were significantly associated with at least one of the traits with either additive or dominance or both effects (P < 0.05). Among these significant SNPs, five of them in ADIPOQ, FTO, TNF, LEPR and AMPD1 had an effect on more than three traits simultaneously; those in MC4R, CAST, DGAT1 and MYF6 had an effect on two traits, while the others were associated with one trait. The results suggest that these markers could be incorporated into commercial pigs for marker‐assisted selection and breeding programs for carcass and meat quality trait improvement.     

Cytogenetic mapping of<Emphasis Type="Italic">DGAT1, PPARA,ADIPOR1</Emphasis> and<Emphasis Type="Italic">CREB</Emphasis> genes in the pig

In the present study we show FISH localization of 4 porcine BAC clones harbouring potential candidate genes for fatness traits: DGAT1 (SSC4p15), PPARA (SSC5p15), ADIPOR1 (SSC10p13) and CREB (SSC15q24). Until now the CREB and ADIPOR1 genes are considered to be monomorphic, DGAT1 is highly polymorphic, while for the PPARA gene only 1 SNP was identified. Assignment of the studied genes in relation to QTL chromosome regions for meat quality in pig chromosomes SSC4, SSC5, SSC10 and SSC15 is discussed.     

Study of candidate genes for glycolytic potential of porcine skeletal muscle: identification and analysis of mutations, linkage and physical mapping and association with meat quality traits in pigs

Several genes (PRKAA2, PRKAB1, PRKAB2, PRKAG3, GAA, GYS1, PYGM, ALDOA, GPI, LDHA, PGAM2 and PKM2), chosen according to their role in the regulation of the energy balance and in the glycogen metabolism and glycolysis of the skeletal muscle, were studied. Eleven single nucleotide polymorphisms (SNPs) were identified in six of these genes (PRKAB1, GAA, PYGM, LDHA, PGAM2 and PKM2). Allele frequencies were analyzed in seven different pig breeds for these loci and for a polymorphism already described for GPI and for three polymorphic sites already reported at the PRKAG3 locus (T30N, G52S and I199V). Linkage mapping assigned PYGM and LDHA to porcine chromosome (SSC) 2, PKM2 to SSC7, GAA to SSC12, PRKAB1 to SSC14 and PGAM2 to SSC18. Physical mapping, obtained by somatic cell hybrid panel analysis, confirmed the linkage assignments of PRKAB1 and GAA and localized ALDOA, PRKAB2 and GYS1 to SSC3, SSC4 and SSC6, respectively. Pigs selected for the association study, for which several meat quality traits were measured, were first genotyped at the PRKAG3 R200Q polymorphic site (RN locus), in order to exclude carriers of the 200Q allele, and then were genotyped for all the mutations considered in this work. Significant associations (P < or = 0.001) were observed for the PRKAG3 T30N and G52S polymorphic sites with meat colour (L* at 24 h post mortem). PGAM2 and PKM2 were significantly associated (P = 0.01) with drip loss percentage and glycogen content at one hour post mortem, respectively.     

QTL analysis of white blood cell, platelet and red blood cell-related traits in an F2 intercross between Landrace and Korean native pigs

Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F₂ intercross between Landrace and Korean native pigs. Eight blood‐related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F₂ progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome‐wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood‐related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker‐assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans.     

A genome-wide association study identifies genomic loci associated with backfat thickness,carcass weight,and body weight in two commercial pig populations

Growth and fatness traits are economically important in the pig industry. To dissect the genetic architecture of these traits in commercial pigs, we conducted a genome-wide association study (GWAS) for carcass weight, backfat thickness, and body weight in two commercial populations: Duroc × (Landrace × Yorkshire) (DLY) and Duroc populations. To enhance the detection power, three GWAS approaches including single-trait GWAS, multi-trait GWAS and meta-analysis were used in this study. A total of 13 suggestive loci were identified on nine chromosomes. The most significant locus was detected at 272.05 Mb on SSC1, and it was associated with backfat thickness at the first rib in the DLY population. Three genes at the identified loci (TBC1D1, BAAT and PHLPP1) were highlighted as functionally plausible candidate genes for pig growth and fatness traits. Genome-wide significant locus was not evidenced in this study, indicating that large populations are required to identify QTL with minor effects on growth and fatness traits in commercial pig populations, in which intensively artificial selections have been imposed on these traits and small genetical variances usually retain in these traits.