Author
CROSS, A - South Dakota State University | |
King, David - Andy | |
Shackelford, Steven | |
Wheeler, Tommy | |
CASSADY, J - South Dakota State University | |
Nonneman, Danny - Dan | |
Rohrer, Gary |
Submitted to: Meeting Abstract
Publication Type: Abstract Only Publication Acceptance Date: 7/10/2017 Publication Date: 10/11/2017 Citation: Cross, A.J., King, D.A., Shackelford, S.D., Wheeler, T.L., Cassady, J.P., Nonneman, D.J., Rohrer, G.A. 2017. Genome-wide association of myoglobin concentrations in pork loins. [abstract] In proceedings: South Dakota State University Swine Day Proceedings. Brookings, SD. Oct. 11, 2017. pg. 12. Interpretive Summary: Technical Abstract: Introduction: Pork is a widely consumed protein source. In order to remain competitive, pork quality must improve. Pork quality is a focus not only for producers and packers, but also for consumers. Consumer purchasing decisions are largely based on lean meat color, indicating freshness. Myoglobin content in pork is the main factor that determines color. In order to increase myoglobin content and change lean pork color, it is important to understand genetic variation and parameters affecting myoglobin concentration. The objective of this study was to identify genetic markers associated with myoglobin concentration and lean meat color. Materials and Methods: Data were collected on pigs (n=559) from two different commercial swine facilities. Each farm sent an equal number of pigs to three different processing facilities. All pigs were from the same genetic line. After processing, ultimate pH was measured in the longissimus muscle, a sample was then frozen and myoglobin concentration was measured from the frozen tissue using an AMSA suggested protocol. DNA was extracted and genotyping conducted using the NeoGen GGP-Porcine chip. After quality checks, a total of 7755 single nucleotide polymorphisms (SNP) were used for the analysis. A Bayes-C model implemented in GenSel software was applied with pi=0.9996. The model included a fixed effect of slaughter group, which consisted of farm and plant, and ultimate pH as a covariate. Myoglobin concentration was then analyzed using a general linear model. Slaughter group was included as a fixed effect. Ultimate pH and the most significant SNP from the detected regions were included as covariates. Results and Discussion: Greater than 60% of the genetic variance was explained by regions within five chromosomes, where each position accounted for >1% of genetic variance. Chromosome 7 accounted for 36.0% of the genetic variance. Chromosome 14 had three significant regions, accounting for 23.2% of the genetic variance in myoglobin concentration. Candidate genes were identified on chromosome 7 that affect iron homeostasis and muscle development. Top three SNP from the general linear model exceeded a Bonferroni correction factor (6.4 x 10-6) and three other SNP had nominal significance levels of P<0.0001. An increase in ultimate pH resulted in an increase in myoglobin concentration. Implications: Genes associated with myoglobin concentrations were identified enabling selection for higher myoglobin concentrations in pork. Increasing myoglobin concentrations will improve lean meat color, therefore increasing consumer acceptance and consumption of pork. USDA is an equal opportunity provider and employer. |