Systems Genomic and Transcriptomic approaches for simultaneous improvement of feed efficiency and production in Danish Pigs

Victor Adriano Okstoft Carmelo

Research output: Book/ReportPh.D. thesisResearch

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Feed efficiency (FE) is the most important phenotype in commercial pig production. It is of high economic value, but also important for sustainable production. The goal in this thesis, was to further our biological understanding of FE in pigs, using metabolomic, transcriptomic and genomic data. Beyond biological understanding, we aimed to develop potential biomarkers that could be applied in pig production for FE in all omics data types. Metabolomics is one of the key links in the connections between genetics, environment and phenotypes. Metabolomics analysis can predict underlying phenotypes with noninvasive techniques. We performed metabolomics analysis of blood plasma on 109 performance tested young boars, of the DanBred Duroc (Duroc) and DanBred Landrace (Landrace) breeds, with 59 and 50 boars of each breed, respectively. This was the first study applying metabolomics analyses of FE phenotypes in pigs. As an addition, we also analyzed daily gain (DG) at different growth stages. The results showed significant overall relation between both FE phenotypes and the DG phenotypes, based on mixed and linear modelling. This identified 67 metabolites significantly associated with DG phenotypes and 1 with FE at a false discovery rate (FDR) < 0.05. Based on metabolites network analysis, we identified several modules, which were correlated both with DG and FE phenotypes, respectively. Pathway enrichment analysis and gene-metabolite networks identified several putative key hub metabolites. If we view the metabolites as the most external link to our phenotypes, the next link in the chain are the proteins. An effective way of doing genome wide analysis of protein activity is by doing analysis of the expression of the genes associated with the proteins through transcriptomics. In pig production, and for FE, muscle is a key organ. Thus, we performed muscle transcriptomics on a sub-population of 41 pigs from the metabolomics study, mainly focusing in feed conversion ratio (FCR). Similarly to the metabolomics results, we were able to demonstrate an overall relation between gene expression and FCR. We identified 14 differentially expressed (DE) genes (FDR < 0.1). Pathway analysis revealed enrichment of mitochondrial genes in the top FCR genes. Gene-gene interaction analysis identified top interactive genes among potential FCR genes. Network analysis revealed two modules correlated to FCR, which contained enrichment of mitochondrial and nucleic acid metabolism genes, respectively. Finally, a novel possible link between the effect of exercise on human muscle, and the muscle of efficient pigs was established. The deepest layer underlying all the causal mechanism in organisms, is genetics. We thus aimed to establish a link between genes whose expression might affect FCR, and the genetic control mechanisms behind them. This was done through expressed quantitative trait loci (eQTL) analysis. We identified 15 potential individual eQTLs (FDR < 0.1), and in agreement with previous studies, we observed that the overall distribution of p-values in our analysis were significantly left-skewed towards lower values. We applied targeted pathway enrichment to trans-eQTLs, demonstrating significant enrichment of genomic context-based gene ontologies. Overall, based on the work in this thesis we identified many potential FE biomarkers, and found strategies for analyzing the complex and statistically challenging phenotype of FE. This has given us new insights in the biological background of FE, and acts as a stepping-stone for future work in the subject
Original languageEnglish
PublisherTechnical University of Denmark
Number of pages120
Publication statusPublished - 2020


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