A genetical genomics approach reveals new candidates and confirms known candidate genes for drip loss in a porcine resource population


Heidt H., Cinar M. U. , Uddin M. J. , Looft C., Juengst H., Tesfaye D., ...More

MAMMALIAN GENOME, vol.24, pp.416-426, 2013 (Journal Indexed in SCI) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 24
  • Publication Date: 2013
  • Doi Number: 10.1007/s00335-013-9473-z
  • Title of Journal : MAMMALIAN GENOME
  • Page Numbers: pp.416-426

Abstract

In this study lean meat water-holding capacity (WHC) of a Duroc × Pietrain (DuPi) resource population with corresponding genotypes and transcriptomes was investigated using genetical genomics. WHC was characterized by drip loss measured in M. longissimus dorsi. The 60K Illumina SNP chips identified genotypes of 169 F2 DuPi animals. Whole-genome transcriptomes of muscle samples were available for 132 F2 animals using the Affymetrix 24K GeneChip® Porcine Genome Array. Performing genome-wide association studies of transcriptional profiles, which are correlated with phenotypes, allows elucidation of cis- and trans-regulation. Expression levels of 1,228 genes were significantly correlated with drip loss and were further analyzed for enrichment of functional annotation groups as defined by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. A hypergeometric gene set enrichment test was performed and revealed glycolysis/glyconeogenesis, pentose phosphate pathway, and pyruvate metabolism as the most promising pathways. For 267 selected transcripts, expression quantitative trait loci (eQTL) analysis was performed and revealed a total of 1,541 significant associations. Because of positional accordance of the gene underlying transcript and the eQTL location, it was possible to identify eight eQTL that can be assumed to be cis-regulated. Comparing the results of gene set enrichment and the eQTL detection tests, molecular networks and potential candidate genes, which seemed to play key roles in the expression of WHC, were detected. The α-1-microglobulin/bikunin precursor (AMBP) gene was assumed to be cis-regulated and was part of the glycolysis pathway. This approach supports the identification of trait-associated SNPs and the further biological understanding of complex traits.

 

In this study lean meat water-holding capacity (WHC) of a Duroc x Pietrain (DuPi) resource population with corresponding genotypes and transcriptomes was investigated using genetical genomics. WHC was characterized by drip loss measured in M. longissimus dorsi. The 60K Illumina SNP chips identified genotypes of 169 F-2 DuPi animals. Whole-genome transcriptomes of muscle samples were available for 132 F-2 animals using the Affymetrix 24K GeneChipA (R) Porcine Genome Array. Performing genome-wide association studies of transcriptional profiles, which are correlated with phenotypes, allows elucidation of cis- and trans-regulation. Expression levels of 1,228 genes were significantly correlated with drip loss and were further analyzed for enrichment of functional annotation groups as defined by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. A hypergeometric gene set enrichment test was performed and revealed glycolysis/glyconeogenesis, pentose phosphate pathway, and pyruvate metabolism as the most promising pathways. For 267 selected transcripts, expression quantitative trait loci (eQTL) analysis was performed and revealed a total of 1,541 significant associations. Because of positional accordance of the gene underlying transcript and the eQTL location, it was possible to identify eight eQTL that can be assumed to be cis-regulated. Comparing the results of gene set enrichment and the eQTL detection tests, molecular networks and potential candidate genes, which seemed to play key roles in the expression of WHC, were detected. The alpha-1-microglobulin/bikunin precursor (AMBP) gene was assumed to be cis-regulated and was part of the glycolysis pathway. This approach supports the identification of trait-associated SNPs and the further biological understanding of complex traits.