Analysis of functional candidate genes for meat quality and carcass traits in pigs

Twelve genes, BVES, SLC3A2, AHNAK, ZDHHC5, CS, LYZ, KERA, COQ9, UN (a nonannotated EST), EGFR, VTN and ZYX, whose candidacy for traits related to water-holding capacity of meat arises from their trait-dependent differential expression and/or trait correlated expression, were selected for analysis. Based on in silico analysis SNPs were detected, confirmed by sequencing and used for genotyping. For the first eleven genes, the SNPs were genotyped in ca. 1,800 animals from 6 pig populations including commercial herds of Pietrain (PI(a/b)), Pietrain x (German Large White x German Landrace) (PIF1(a/b/c)), and German Landrace (DL(a/b)) and one experimental F2-population Duroc x Pietrain (DUPI). For ZYX, the SNPs were genotyped in 870 animals from 4 pig populations including PI, DL, F1 and PIF1. Comparative and genetic mapping established the location of BVES on SSC1, of SLC3A2, AHNAK and ZDHHC5 on SSC2, of CS, LYZ and KERA on SSC5, of COQ9 on SSC6, of UN on SSC7, of EGFR on SSC9, of VTN on SSC12 and of ZYX on SSC18 respectively, coinciding with QTL regions for carcass and meat quality traits. BVES, SLC3A2, AHNAK, CS, LYZ, UN, VTN and ZYX revealed association with drip loss and also with several other measures of carcass and meat quality traits. KERA was associated with loin eye area and pH. Moreover, several carcass fatness traits and meat quality traits such as meat color and thawing loss were associated with COQ9 and EGFR. However, none of the candidate genes showed a significant association to a particular trait across all populations. This may be due to breed specific effects that are related to the differences in carcass and meat quality of these pig breeds. This study reveals statistic evidence for a link of genetic variation at these loci or close to them with phenotypic variation and promotes those twelve candidate genes as functional and/or positional candidate genes for carcass and meat quality traits.Analyse von funktionalen Kandidatengenen für Fleischqualität und Schlachtkörpermerkmale in Schweinen Zwölf Gene, BVES, SLC3A2, AHNAK, ZDHHC5, CS, LYZ, KERA, COQ9, UN (ein unannotiertes EST), EGFR, VTN und ZYX, deren Kandidatenstatus für Merkmale des Wasserbindungsvermögens von Fleisch auf ihrer merkmalsabhängigen differentiellen Expression und/oder merkmalskorrelierten Expression beruht, wurden für die Analyse ausgewählt. Basierend auf in silico-Analysen wurden SNPs detektiert, die durch Sequenzierung bestätigt und dann zur Genotypisierung verwendet wurden. Für die ersten elf Gene wurden die SNPs in ca. 1.800 Tieren aus sechs Schweinepopulationen genotypisiert; dazu gehörten kommerzielle Herden der Rassen Pietrain (PI(a/b)), Deutsche Landrasse (DL(a/b)) und eine Drei-Rassen-Kreuzung aus Pietrain x (Deutsches Edelschwein x Deutsche Landrasse) (PIF1(a/b/c)) sowie eine experimentelle F2-Population aus Duroc x Pietrain (DUPI). Für ZYX wurden die SNPs in 870 Tieren aus vier Schweinepopulationen genotypisiert; dazu gehörten PI, DL, F1 und PIF1. Genetische Kartierung etablierte die Lage von BVES auf SSC1, von SLC3A2, AHNAK und ZDHHC5 auf SSC2, von CS, LYZ und KERA auf SSC5, von COQ9 auf SSC6, von UN auf SSC7, von EGFR auf SSC9, von VTN auf SSC12 und von ZYX auf SSC18, jeweils in Regionen, die mit QTL-Regionen für Schlachtkörper- und Fleischqualitätsmerkmale zusammenfallen. BVES, SLC3A2, AHNAK, CS, LYZ, UN, VTN und ZYX ließen sowohl Assoziationen mit Tropfsaftverlust als auch mit verschiedenen anderen Messgrößen für Schlachtkörper- und Fleischqualitätsmerkmale erkennen. KERA war mit der Kotelettfläche und dem pH-Wert assoziiert. Außerdem waren verschiedene Schlachtkörper- Fettmerkmale und Fleischqualitätsmerkmale wie z.B. OPTO und Auftauverlust mit COQ9 und EGFR assoziiert. Allerdings zeigte keines der Kandidatengene eine signifikante Assoziation mit einem bestimmten Merkmal in allen Populationen. Dies könnte an den rassenspezifischen Effekten liegen, die die Unterschiede in der Schlachtkörper- und Fleischqualität dieser Schweinerassen bedingen. Diese Studie zeigt statistische Hinweise auf eine Verbindung von genetischer Variation an oder in der Nähe dieser Loci und phänotypischer Variation. Dies bestätigt die zwölf Kandidatengene als funktionale und/oder positionelle Kandidatengene für Schlachtkörper- und Fleischqualitätsmerkmale

Trait correlated expression combined with expression QTL analysis reveals biological pathways and candidate genes affecting water holding capacity of muscle

<p>Abstract</p> <p>Background</p> <p>Leakage of water and ions and soluble proteins from muscle cells occurs during prolonged exercise due to ischemia causing muscle damage. Also <it>post mortem </it>anoxia 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 as <it>ante </it>and <it>post </it>slaughter metabolic processes.</p> <p>Results</p> <p>Expression microarray analysis of M. <it>longissimus dorsi </it>RNAs 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 had <it>trans </it>acting and 8 had <it>cis </it>acting regulation.</p> <p>Conclusion</p> <p>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.</p

Histogram of the distribution of pair wise correlation coefficients of expression value and drip loss

<p><b>Copyright information:</b></p><p>Taken from "Trait correlated expression combined with expression QTL analysis reveals biological pathways and candidate genes affecting water holding capacity of muscle"</p><p>http://www.biomedcentral.com/1471-2164/9/367</p><p>BMC Genomics 2008;9():367-367.</p><p>Published online 31 Jul 2008</p><p>PMCID:PMC2529315.</p><p></p

Histogram of the distribution of drip loss phenotypes among a subset of 74 animals of the DuPi population selected for chip hybridization

<p><b>Copyright information:</b></p><p>Taken from "Trait correlated expression combined with expression QTL analysis reveals biological pathways and candidate genes affecting water holding capacity of muscle"</p><p>http://www.biomedcentral.com/1471-2164/9/367</p><p>BMC Genomics 2008;9():367-367.</p><p>Published online 31 Jul 2008</p><p>PMCID:PMC2529315.</p><p></p