A genome-wide association analysis for porcine serum lipid traits reveals the existence of age-specific genetic determinants

Arianna Manunza, Joaquim Casellas, Raquel Quintanilla, Rayner González-Prendes, Ramona N. Pena, Joan Tibau, Anna Mercadé, Anna Castelló, Nitdia Aznárez, Jules Hernández-Sánchez, Marcel Amills

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18 Citations (Scopus)


© 2014 Manunza et al.; licensee BioMed Central Ltd. Background: The genetic determinism of blood lipid concentrations, the main risk factor for atherosclerosis, is practically unknown in species other than human and mouse. Even in model organisms, little is known about how the genetic determinants of lipid traits are modulated by age-specific factors. To gain new insights into this issue, we have carried out a genome-wide association study (GWAS) for cholesterol (CHOL), triglyceride (TRIG) and low (LDL) and high (HDL) density lipoprotein concentrations measured in Duroc pigs at two time points (45 and 190 days).Results: Analysis of data with mixed-model methods (EMMAX, GEMMA, GenABEL) and PLINK showed a low positional concordance between trait-associated regions (TARs) for serum lipids at 45 and 190 days. Besides, the proportion of phenotypic variance explained by SNPs at these two time points was also substantially different. The four analyses consistently detected two regions on SSC3 (124 Mb, CHOL and LDL at 190 days) and SSC6 (135 Mb, CHOL and TRIG at 190 days) with highly significant effects on the porcine blood lipid profile. Moreover, we have found that SNP variation within SSC3, SSC6, SSC10, SSC13 and SSC16 TARs is associated with the expression of several genes mapping to other chromosomes and related to lipid metabolism.Conclusions: Our data demonstrate that the effects of genomic determinants influencing lipid concentrations in pigs, as well as the amount of phenotypic variance they explain, are influenced by age-related factors.
Original languageEnglish
Article number758
JournalBMC Genomics
Publication statusPublished - 4 Sep 2014


  • Animal model
  • Gene expression
  • Genome-wide analysis
  • Lipids and lipoproteins


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